diff --git a/_build/.doctrees/environment.pickle b/_build/.doctrees/environment.pickle index a4f36ab..4bba059 100644 Binary files a/_build/.doctrees/environment.pickle and b/_build/.doctrees/environment.pickle differ diff --git a/_build/.doctrees/titlepage.doctree b/_build/.doctrees/titlepage.doctree index 4486f8a..bf280d9 100644 Binary files a/_build/.doctrees/titlepage.doctree and b/_build/.doctrees/titlepage.doctree differ diff --git a/_build/html/.buildinfo b/_build/html/.buildinfo deleted file mode 100644 index 71daa62..0000000 --- a/_build/html/.buildinfo +++ /dev/null @@ -1,4 +0,0 @@ -# Sphinx build info version 1 -# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 041481c9bbd721076049b1dc858ca2f1 -tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/_build/html/_images/hammerdirt.png b/_build/html/_images/hammerdirt.png deleted file mode 100644 index b6ce0f8..0000000 Binary files a/_build/html/_images/hammerdirt.png and /dev/null differ diff --git a/_build/html/_sources/extracting_topo_data.ipynb b/_build/html/_sources/extracting_topo_data.ipynb deleted file mode 100644 index 15d1cc8..0000000 --- a/_build/html/_sources/extracting_topo_data.ipynb +++ /dev/null @@ -1,884 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "99471458-7fe0-401a-967a-1483c9f641b4", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [], - "source": [ - "%load_ext watermark\n", - "import pandas as pd\n", - "import session_config\n", - "import reports\n", - "import roughdraft\n", - "import geospatial\n", - "from session_config import lat_lon\n", - "from gridforecast import SampleSelector\n", - "\n", - "import geopandas as gpd\n", - "import matplotlib.lines as mlines\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib.patches as mpatches\n", - "\n", - "from shapely import Point\n", - "from shapely import unary_union" - ] - }, - { - "cell_type": "markdown", - "id": "7243c6a6-9d9a-4e27-a183-f2fb2a5ec059", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "# Land cover and land use \n", - "\n", - "_The land cover and land use are used to determine the similarity of one survey location to another. In this way we can evaluate the probable minimum amount of trash at a given location based on the physical environment._\n", - "\n", - "Land cover and land use provide information about the physical characteristics of a survey location. The land use and cover is measured by considering the proportion of land dedicated to specific purposes within a radius of 1'500 m of the survey location of interest. The specific puroposes are defined by the following map layers available at [swissTLMRegio](https://www.swisstopo.admin.ch/en/landscape-model-swisstlmregio):\n", - "\n", - "1. Landcover (TLM_BODENBEDECKUNG)\n", - "2. Streets (TLM_STRASSEN)\n", - "3. Hydrology (TLM_GEWAESSER)\n", - "4. Sports and recreation (TLM_FREIZEITAREAL)\n", - "5. Public services (TLM_NUTZUNGSAREAL)\n", - "\n", - "## Defining similar locations\n", - "\n", - "When comparing feature vectors in three-dimensional space, various distance metrics can be applied, each depending on the nature of the data and the type of comparison needed. **Euclidean distance** measures the straight-line distance between two points, making it suitable when the magnitude of differences in the same-scale features matters. **Manhattan distance** measures the sum of absolute differences across each dimension, which is useful when you prefer a more \"axis-aligned\" measure of difference, particularly when feature importance might vary along each axis. **Cosine similarity**, however, compares the orientation of the vectors in space, measuring how aligned they are regardless of magnitude. This is particularly relevant when the proportions between feature values are more important than their absolute values. In our analysis, cosine similarity was chosen because we are more interested in the relative proportions of the feature variables rather than their magnitudes.\n", - "\n", - "Cosine similarity measures the cosine of the angle between two vectors in multi-dimensional space, focusing on the direction of the vectors rather than their length. The similarity ranges from -1 (perfectly opposite directions) to 1 (identical directions), with 0 indicating orthogonal or no similarity. The formula normalizes the vectors to unit length, comparing only the relative proportions between the dimensions. Cosine similarity is especially useful when the magnitude of the vectors varies significantly, but the pattern or trend of the features is important.\n", - "\n", - "For example, imagine comparing two feature vectors:\n", - "\n", - "- $ x = [0.4, 0.5, 0.6] $ \n", - "- $y = [0.2, 0.25, 0.3] $\n", - "\n", - "Even though the absolute values of \\(y\\) are smaller than those of \\(x\\), the proportions between dimensions remain the same (i.e., $ 0.4/0.5 \\approx 0.2/0.25$)). Cosine similarity will show that these two vectors are highly similar because their pattern or direction is nearly identical. By contrast, Euclidean distance would highlight the magnitude differences between the vectors, leading to a different measure of similarity.\n", - "\n", - "## Example: defining the land use for one location\n", - "\n", - "For each location the land use and land cover is calculated by first extracting the relevant features from the appropriate map layers within a radius of 1 500 m." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "7c242e95-6a6d-47e5-8c55-ce456aaa4b89", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [], - "source": [ - "\n", - "\n", - "gpd.options.io_engine = \"pyogrio\"\n", - "\n", - "\n", - "land_covers = [\n", - " \"Wald\",\n", - " \"See\",\n", - " \"Stausee\",\n", - " \"Siedl\",\n", - " \"Stadtzentr.\",\n", - " \"Sumpf\",\n", - " \"Obstanlage\",\n", - " \"Reben\",\n", - " \"recreation\",\n", - " 'public-services',\n", - " 'undefined'\n", - " ]\n", - "\n", - "def a_point_buffer(this_location, buffer_radius: int = 1500, coordinate_crs: str = 'epsg:4326', to_crs: str = \"epsg:2056\"):\n", - " \n", - " if isinstance(this_location, dict):\n", - " this_location = pd.DataFrame([this_location])\n", - " this_geometry = [Point(this_location['longitude'], this_location['latitude'])]\n", - "\n", - " if isinstance(this_location, pd.Series):\n", - " this_geometry = [Point(this_location.longitude, this_location.latitude)]\n", - " \n", - " this_shape = gpd.GeoDataFrame(this_location, geometry=this_geometry, crs=coordinate_crs)\n", - " this_shape = this_shape.to_crs(to_crs)\n", - "\n", - " this_buffer = gpd.GeoDataFrame(geometry=this_shape.buffer(1500), crs=to_crs)\n", - " location_buffer = this_buffer.dissolve()\n", - " return this_shape, location_buffer, location_buffer.total_bounds\n", - "\n", - "\n", - "def location_geo_attributes(bounds, buffer, shape_file, objcolumn: str = 'OBJVAL', objval: str ='land-cover', buffer_name: str = None):\n", - " minx, miny, maxx, maxy = bounds\n", - " landcover = gpd.read_file(shape_file, bbox=(minx, miny, maxx, maxy))\n", - " landcover = landcover.drop_duplicates()\n", - " landcover = gpd.overlay(landcover, buffer, how='intersection', keep_geom_type=True)\n", - " landcover.rename(columns={objcolumn:objval}, inplace=True)\n", - " \n", - " landcover['buffer-name'] = buffer_name\n", - " return landcover[['buffer-name', objval, 'geometry']], landcover['land-cover'].unique()\n", - "\n", - "def assign_colors_to_polygons(buffer_contents: gpd.GeoDataFrame, colors: dict = None, objval: str = None):\n", - " buffer_contents['color'] = buffer_contents[objval].map(colors)\n", - " return buffer_contents\n", - " \n", - "def compute_landuse_percent_of_buffer(buffer_contents, buffer_area):\n", - "\n", - " land_covers = buffer_contents['land-cover'].unique()\n", - "\n", - " if 'Stausee' in land_covers:\n", - " \n", - " if 'See' in land_covers:\n", - " see_stausee_gdf = buffer_contents[buffer_contents['land-cover'].isin(['See', 'Stausee'])]\n", - " combined_geometry = unary_union(see_stausee_gdf['geometry'])\n", - " new_row = {\n", - " 'buffer-name': buffer_contents['buffer-name'].unique()[0],\n", - " 'land-cover': 'See',\n", - " 'geometry': combined_geometry\n", - " }\n", - " buffer_contents = buffer_contents[~buffer_contents['land-cover'].isin(['See', 'Stausee'])]\n", - " \n", - " new_gdf = gpd.GeoDataFrame([new_row], columns=buffer_contents.columns, crs=buffer_contents.crs)\n", - "\n", - " # Concatenate the original GeoDataFrame with the new GeoDataFrame\n", - " buffer_contents = pd.concat([buffer_contents, new_gdf], ignore_index=True)\n", - " \n", - " else:\n", - " see_stausee_gdf = buffer_contents[buffer_contents['land-cover'].isin(['Stausee'])]\n", - " a_geometry = unary_union(see_stausee_gdf['geometry'])\n", - " new_row = {\n", - " 'buffer-name': buffer_contents['buffer-name'].unique()[0],\n", - " 'land-cover': 'See',\n", - " 'geometry': a_geometry\n", - " }\n", - " buffer_contents = buffer_contents[~buffer_contents['land-cover'].isin(['See', 'Stausee'])]\n", - " \n", - " new_gdf = gpd.GeoDataFrame([new_row], columns=buffer_contents.columns, crs=buffer_contents.crs)\n", - "\n", - " buffer_contents = pd.concat([buffer_contents, new_gdf], ignore_index=True)\n", - " \n", - "\n", - " elif 'See' in buffer_contents['land-cover'].unique():\n", - " water_surface = buffer_contents.loc[buffer_contents['land-cover'] == 'See', 'geometry'].geometry.area.values[0]\n", - " buffer_contents['buffer-area-dry'] = buffer_area - water_surface\n", - " buffer_contents['area_m2'] = buffer_contents.geometry.area\n", - " buffer_contents['buffer-area-dry'] = buffer_area - water_surface\n", - " buffer_contents['rate'] = buffer_contents.area_m2/buffer_contents['buffer-area-dry']\n", - "\n", - " else:\n", - " buffer_contents['area_m2'] = buffer_contents.geometry.area\n", - " buffer_contents['buffer-area-dry'] = buffer_area\n", - " buffer_contents['rate'] = buffer_contents.area_m2/buffer_contents['buffer-area-dry'] \n", - " \n", - " return buffer_contents\n", - "\n", - "def compute_undefined_sections_of_buffer(buffer, buffer_contents, objval: str = 'land-cover', buffer_name: str = 'None'):\n", - " undefined = buffer.geometry.iloc[0]\n", - " \n", - " for aval in buffer_contents.geometry:\n", - " undefined = undefined.difference(aval)\n", - " args = {\n", - " 'geometry':[undefined],\n", - " objval : ['undefined'],\n", - " 'buffer-name':[ buffer_name]\n", - " }\n", - " undef = gpd.GeoDataFrame(args, crs=buffer.crs)\n", - "\n", - " return undef\n", - "\n", - "\n", - "landuse_trans = {\n", - " 'Wald': 'forest',\n", - " 'Fels': 'ravines',\n", - " 'Geroell': 'boulders',\n", - " 'Gletscher': 'glacier',\n", - " 'Stausee': 'reservoir',\n", - " 'See': 'lake',\n", - " 'Reben': 'vineyards',\n", - " 'Obstanlage': 'orchards',\n", - " 'Siedl': 'buildings',\n", - " 'Sumpf': 'wetlands',\n", - " 'undefined': 'undefined',\n", - " 'streets': 'streets',\n", - " 'recreation': 'recreation',\n", - " 'public-services': 'public-services',\n", - " 'location' : 'location'\n", - " \n", - "}\n", - "\n", - "landuse_color = {\n", - " 'forest': 'olivedrab',\n", - " 'ravines': 'gray',\n", - " 'boulders': 'gray',\n", - " 'glacier': 'gray',\n", - " 'reservoir': 'dodgerblue',\n", - " 'lake': 'dodgerblue',\n", - " 'vineyards': 'seagreen',\n", - " 'orchards': 'yellowgreen',\n", - " 'buildings': 'slategray',\n", - " 'wetlands': 'yellow',\n", - " 'undefined': 'khaki',\n", - " 'recreation': 'red',\n", - " 'public-services': 'magenta',\n", - " 'rivers': 'dodgerblue',\n", - " 'streets': 'black'\n", - "}\n", - "\n", - "\n", - "class RandomPointLanduse:\n", - "\n", - " def __init__(self, name, latitude, longitude, feature_type):\n", - " self.lat = latitude\n", - " self.lon = longitude\n", - " self.feature_type = feature_type\n", - " self.name = name\n", - " self.point = None\n", - " self.buffer = None\n", - " self.bounds = None\n", - " self.buffer_content = None\n", - "\n", - " def point_buffer_bounds(self, **kwargs):\n", - " lat_lon = {'latitude':self.lat, 'longitude': self.lon}\n", - " this_point, abuffer, bufferbounds = a_point_buffer(lat_lon)\n", - " self.point = this_point\n", - " self.buffer = abuffer\n", - " self.bounds = bufferbounds\n", - "\n", - " def land_cover(self, **kwargs):\n", - " buffer_content, _ = location_geo_attributes(self.bounds, self.buffer, 'data/ignorethis/shapes/landcover.shp', buffer_name=self.name, **kwargs)\n", - " self.buffer_content = buffer_content\n", - "\n", - " def public_services(self, **kwargs):\n", - " # public services\n", - " args = dict(objcolumn='OBJEKTART', objval='land-cover', buffer_name=self.name)\n", - " nz, _ = location_geo_attributes(self.bounds, self.buffer, 'data/ignorethis/shapes/nutuzungsareal.shp', **args, **kwargs)\n", - " nz_comb = unary_union(nz.geometry)\n", - " nz_comb = gpd.GeoDataFrame([{'geometry': nz_comb, 'buffer-name':self.name, 'land-cover': 'public-services' }], crs=self.buffer_content.crs)\n", - " buffer_content = pd.concat([self.buffer_content, nz_comb])\n", - " self.buffer_content\n", - "\n", - " def recreation(self, **kwargs):\n", - " args = dict(objcolumn='OBJEKTART', objval='land-cover', buffer_name=self.name)\n", - " fz,_ = location_geo_attributes(self.bounds, self.buffer,'data/ignorethis/shapes/freizeit.shp', **args, **kwargs)\n", - " fz_comb = unary_union(fz.geometry)\n", - " fz_comb = gpd.GeoDataFrame([{'geometry': fz_comb, 'buffer-name':self.name, 'land-cover': 'recreation' }], crs=self.buffer_content.crs)\n", - " buffer_content = pd.concat([self.buffer_content, fz_comb])\n", - " self.buffer_content = buffer_content \n", - " \n", - " def undefined_areas(self, **kwargs): \n", - " combined_polygon = unary_union(self.buffer_content.geometry)\n", - " combined_Pn = gpd.GeoDataFrame({'geometry': [combined_polygon]}, crs=self.buffer_content.crs)\n", - " undefined = compute_undefined_sections_of_buffer(self.buffer, combined_Pn, buffer_name=self.name)\n", - " # combine the known land cover with the undefined\n", - " buffer_content = pd.concat([self.buffer_content, undefined])\n", - " self.buffer_content = buffer_content\n", - "\n", - " def streets(self, **kwargs): \n", - "\n", - " minx, miny, maxx, maxy = self.bounds\n", - " streets = gpd.read_file('data/ignorethis/shapes/strasse.shp',bbox=(minx, miny, maxx, maxy))\n", - " \n", - " streets = gpd.overlay(streets, self.buffer, how='intersection', keep_geom_type=True)\n", - " streets = streets.drop_duplicates()\n", - " # print(streets)\n", - " streets = streets.dissolve()\n", - " st_comb = gpd.GeoDataFrame([{'geometry': streets.geometry.values[0], 'buffer-name':self.name, 'land-cover': 'streets' }], crs=self.buffer_content.crs)\n", - " st_result = pd.DataFrame([{'land-cover': 'streets', 'rate': 0, 'meters': st_comb.geometry.length, 'buffer-name':self.name}])\n", - " buffer_content = pd.concat([self.buffer_content, st_comb])\n", - " self.buffer_content = buffer_content\n", - " return st_result\n", - "\n", - " def buffer_composition_proportions(self):\n", - "\n", - " self.point_buffer_bounds()\n", - " self.land_cover()\n", - " self.public_services()\n", - " self.recreation()\n", - " \n", - " t = compute_landuse_percent_of_buffer(self.buffer_content.copy(), self.buffer.geometry.area[0])\n", - " surface_columns = [x for x in t['land-cover'].unique() if x in land_covers]\n", - " t = t[t['land-cover'].isin(surface_columns)].groupby('land-cover').agg({'rate':'sum', 'area_m2': 'sum'}) \n", - " t = pd.DataFrame(t['rate']).T\n", - " t['location'] = self.name\n", - " t.reset_index(inplace=True, drop=True)\n", - " st_result = self.streets()\n", - " t['streets'] = st_result.loc[0, 'meters'][0]\n", - "\n", - " t.columns = [landuse_trans[x] for x in t.columns]\n", - " new_column_order =['location', *[x for x in t.columns if x != 'location']]\n", - " bcx = self.buffer_content\n", - " bcx['land-cover'] = bcx['land-cover'].apply(lambda x: landuse_trans[x])\n", - " self.buffer_content = bcx\n", - " # t.rename(columns={'Siedl':'buildings', 'Wald':'forest'}, inplace=True)\n", - "\n", - " return t[new_column_order]\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "41824624-42ae-4426-8382-70f6e70b5744", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [ - { - "data": { - "image/png": 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C29vbPUuuzQcffCAA8dJLL7m3vfHGGyI5OVno9XoxfPhw8dxzz4n/+7//O2O2V2xsrLjyyivPiAkQv/71r9tta5uV98ILL7i33XbbbcJoNIr9+/eLiy66SBgMBmEymcQvf/lL0djY2O7402dZCiFEY2Oj+MMf/iCSk5OFTqcT/v7+Ii0tTfz2t78VpaWlZ33cOppl+dlnn4mxY8cKLy8vERUVJR566CH3LLlTZ+zNnTtXpKamdumchw4dEpdeeqnw8vISJpNJ3HnnneK///1vl2YBth1/4403iqCgIKHT6URMTIxYtGiRsFgs7n0yMzPF1VdfLfz9/YVOpxNjx44VK1eu7PB8dXV1wmAwtHtunK6iokLce++9Ij4+Xmi1WmEymcTEiRPFY4895v67dPT3PJf+9vh2NIOx7Xy+vr4iMDBQ3HjjjSI/P/+MGZFtsywrKirOec7a2lpxxx13iICAAOHt7S0uvfRScfjw4S7NshRCiKNHj4oFCxYIPz8/ERISIn7zm9+IL774ot19PHz4sLjllltEQkKCMBgMwt/fX0yZMkWsWrXqjPO98cYbYurUqcJoNAqDwSASEhLErbfeKtLT088ZiyRJA5sixGkVRSWJlpmAH374IY2NjZ4ORZIkSZIGPTmGTJIkSZIkycNkQiZJkiRJkuRhsstSkiRJkiTJw2QLmSRJkiRJkofJhEySJEmSJMnDZEImSZIkSZLkYTIhkyRJkiRJ8jCZkEmSJEmSJHmYTMgkSZIkSZI8TCZkkiRJkiRJHiYTMkmSJEmSJA+TCZkkSZIkSZKHyYRMkiRJkiTJwzSeDkCSJEmSPMHlcmGz2TwdhjSIabVa1Gp1l/aVCZkkSZI05NhsNnJzc3G5XJ4ORRrkAgICCA8PR1GUs+4nEzJJkiRpSBFCUFJSglqtJjo6GpVKjt6Rep4QArPZTHl5OQARERFn3V8mZJIkSdKQ4nA4MJvNREZG4u3t7elwpEHMYDAAUF5eTmho6Fm7L+XHAkmSJGlIcTqdAOh0Og9HIg0FbUm/3W4/634yIZMkSZKGpHON6ZGkntDV55lMyCRJkiTpfJm3Qt60lu+SdAFkQiZJkiRJ56vmb2DZATWvejqSAeWiiy7i/vvv93QYLFq0iOuuu87TYQAyIZMkSZKk8+OohIYPW35u+KDld6lfysvLQ1EUMjIy2m1/5ZVXWLVqlUdiOp1MyCRJkiTpfNS9CbTVMXNB/VuejKbbZFFc8Pf3JyAgwNNhADIhkyRJkqRzsxeBZU/7r9rXANG6g4Cav5+5j72ox0L48MMPSUtLw2AwEBQUxPz582lqagI67gK87rrrWLRokfv3uLg4nnnmGRYtWoS/vz+LFy9m+vTpPPLII+2Oq6ioQKvVsn79eqAlcVuyZAlRUVEYjUamTp3Khg0bAGhqasLPz48PP/yw3Tk+++wzjEYjDQ0NXbpvNTU13HrrrQQGBuLt7c0VV1zBsWPH2u2zZcsW5s6di7e3N4GBgVx22WXU1NQA8NVXXzFr1iwCAgIICgriqquuIicnx31sfHw8AOPHj0dRFC666CLgzC5Lq9XKvffeS2hoKF5eXsyaNYtdu3a5b9+wYQOKorB27VomTZqEt7c3M2bM4MiRI126n2cjEzJJkiRJOpfiWyBvYvsvey7tEjL78TP3Kf5Jj1y+pKSEW265hTvuuIOsrCw2bNjA9ddfjxDi3Aef4oUXXmD06NHs3r2bxx9/nIULF/Kf//yn3Xnee+89wsLCmDt3LgC33347W7ZsYfXq1ezfv58bb7yRyy+/nGPHjmE0Grn55ptZuXJlu+usXLmSG264AV9f3y7FtWjRItLT0/n000/Ztm0bQgh+8IMfuEtFZGRkMG/ePFJTU9m2bRubN2/m6quvdpcwaWpq4oEHHmDXrl2sXbsWlUrFD3/4Q/dKDDt37gTgu+++o6SkhI8//rjDOJYsWcJHH33Em2++yZ49e0hMTOSyyy6jurq63X6PPfYYy5YtIz09HY1Gwx133NGl+3lWQpIkSZKGkObmZnHo0CHR3Nzc9YNq3xTisJcQWYoQWXThS2nZv/bNHol59+7dAhB5eXkd3j537lxx3333tdt27bXXittuu839e2xsrLjuuuva7VNeXi40Go3YuHGje9v06dPFQw89JIQQIjs7WyiKIoqKitodN2/ePPHoo48KIYTYsWOHUKvV7n0qKiqEVqsVGzZs6PT+nBrv0aNHBSC2bNnivr2yslIYDAbx/vvvCyGEuOWWW8TMmTM7Pd/pysvLBSAyMzOFEELk5uYKQOzdu7fdfrfddpu49tprhRBCNDY2Cq1WK9555x337TabTURGRornn39eCCHE+vXrBSC+++479z5ffPGFADp9PnX1+SYr9UvSeRJC4HA6sVptWGx2bDYbFqsdm82OxWZr+W5t+26lydxMY5OZ5mYLZovFfZsQAp1Wi5eXDoOXHm8vL4xGb3yM3nh7G/DS6dDrdeh12pYv9886vA16dFqtrKckSb3N/1bwmgRFPwRbNifHjnVEBboREPUx6Ef1yOXHjh3LvHnzSEtL47LLLmPBggXccMMNBAYGdus8kyZNavd7SEgIl156Ke+88w6zZ88mNzeXbdu28Y9//AOAPXv2IIQgKSmp3XFWq5WgoCAApkyZQmpqKm+99RaPPPIIb7/9NjExMcyZM6dLMWVlZaHRaJg6dap7W1BQEMnJyWRlZQEtLWQ33nhjp+fIycnh8ccfZ/v27VRWVrpbxvLz8xk9enSX4sjJycFutzNz5kz3Nq1Wy5QpU9xxtBkzZoz757YlkcrLy4mJienStToiEzJJ6oTL5aKmroGKqlrKq2ooq6jmRGExldW12BzO1ib+sydCQgiEy4Vwd2soqFQKitJ+tIDZ6oDGZlwuV+t5W/ZXlJZ9O0q4hMvFgYztlNmLiYyPJGJYJEEBJkYOS2Ra6nhGxSXJNfokqSfpR0HcHii5Exre63w/3x9DxP+BqueWZVKr1Xz77bds3bqVb775hr/97W889thj7Nixg/j4eFQq1Rndlx1VhjcajWdsW7hwIffddx9/+9vfePfdd0lNTWXs2LFAy+ugWq1m9+7dZyz74+Pj4/75rrvu4tVXX+WRRx5h5cqV3H777V3+oHh63KdubztH2xJEnbn66quJjo5mxYoVREZG4nK5GD16dLcmLrTFcXrcp8bRRqvVun9uu+1CF6qXCZk0pAkhaGgyU1FVS0VVDeWVNeQXlVBaXkWTxdZuP5fLiUqlPuU/5rlfbBRFQTnL2mWn604CVVtdSVlRATbFRnp1OuxR0JmMeIX747XdH7VRj9rsxNelJ8JoIjE0hnHxI5mRNpnosMguX0eSpFOojOA9Fxre5+T4sVMpLbf3YDLmPrOiMHPmTGbOnMkTTzxBbGwsa9as4YEHHiAkJISSkhL3vk6nkwMHDnDxxRef87zXXXcdd999N1999RXvvvsuP/vZz9y3jR8/HqfTSXl5ObNnz+70HD/96U9ZsmQJy5cv5+DBg9x2221dvl+jRo3C4XCwY8cOZsyYAUBVVRVHjx5l5MiRQEuL1Nq1a3nqqafOOL6qqoqsrCxef/11d4ybN29ut0/bMlltY846kpiYiE6nY/PmzfzkJy1j/+x2O+np6X1SM00mZNKQYLHaKK+qoaKqhoqqWk4UFJGTe4L6RjMGY8ug05aky4WiKGckRoqioFb3r/8ugcGhTJ41n7LiAppq9tLc0ICtqhFbVSP1B4tQ6bV4hfthDvWj3FrL/to8Pj66Eb5+HZfVjsYi8FO8CPcJIjY4gjCDiZiQSH628KeevmuS1L9ZdgNqwNHBjerW23vWjh07WLt2LQsWLCA0NJQdO3ZQUVHhTlguueQSHnjgAb744gsSEhJ46aWXqK2t7dK5jUYj1157LY8//jhZWVnuZAQgKSmJhQsXcuutt7Js2TLGjx9PZWUl69atIy0tjR/84AcABAYGcv311/PQQw+xYMEChg0b1uX7NmLECK699loWL17M66+/jq+vL4888ghRUVFce+21ADz66KOkpaXxq1/9il/84hfodDrWr1/PjTfeiMlkIigoiP/3//4fERER5OfnnzFzNDQ0FIPBwFdffcWwYcPw8vLC39//jMfhl7/8JQ899BAmk4mYmBief/55zGYzd955Z5fvz/nqX+8wktRDmi1WjucXk51XyP5DR6mua3Tf5nI6qa2uZM/2DXgbfZlxScsLSkvS1fXWrP7APzAI/8AgDNowsuxHsJTVYS2tx1Jej8tqx3yiCvOJqk6PLxeQDWx2N/op/OXIh3jZ1YTq/JgSl8bNF19NStyIPrk/kjQgNG+nJRnTgKKBgF9C7T9A2Fu2N2/r8Uv6+fmxceNGXn75Zerr64mNjWXZsmVcccUVANxxxx3s27ePW2+9FY1Gw29/+9sutY61WbhwIVdeeSVz5sw5YxzUypUreeaZZ3jwwQcpKioiKCiI6dOnu5OxNnfeeSfvvvvuec04XLlyJffddx9XXXUVNpuNOXPm8OWXX7q7BpOSkvjmm2/4/e9/z5QpUzAYDEydOpVbbrkFlUrF6tWruffeexk9ejTJycksX77cXdoCQKPRsHz5cv74xz/yxBNPMHv2bHfpjlP9+c9/xuVy8bOf/YyGhgYmTZrE119/3e2xeudDEZ113krSAGKxWsk5cWYC5nI6UXWQZDXU1bJj49fo9V7MXnBtX4fb4+w42OKdjktp+e8snC5s1U1YSuuwVjQgnOcY26CAxqhHG2jEJyEUlUaFcAkUdUtLoaizEoEfMxLGcfPF15Acm9Dbd0mSeo3FYiE3N5f4+Hi8vLy6d7DLAkd9ACfokk8O3Lceah3wfxRQQ1IjqLp57gHunXfe4b777qO4uNjdRSh1/fkmW8ikAclibW0Byy1kf9Yxqmpbig+enoB1lIxBy6clAEcHg14HIi0aQpwmyjQtrWGKWoU+xBd9SNdqAHVEUZ8cI6f46ylxNvNx5Q4+/mAHos5KpOLH9OEyQZOGGNEM+tHgNQHCXj05VqxtwH/pPWDNAGEBhkZCZjabyc3N5bnnnuPuu++Wydh5kgmZNCBYrDZy84s5lldI5qGjVLYlYK0D7dt0loCdTtPaDO50OTttRRtoouzh7oSsN7S1lkFLglZ8RoLmz4yEcdxyyTWMiB7ea3FIkkepA1sSL6WDCTgqI0SuBOHq+PZB6vnnn+fZZ59lzpw5PProo54OZ8CSXZZSv+QSgtz8Yg4dzWX/WRKw8z6/y8W6Lz4AYO5l16HV6S/4nP3BdsNezCqLR64tnK52XZyRij+zEsdz08VXywRN6lcuqMtSkrpJdllKA1JpRRXp+w6zNX0/zVbbmS1gPZCMtZxHhVqtwel04LDbB01CNswezlF9nkeufWYLmpkPyrfxwXvbUGqsTA5K4rc/vJNR8UlnOYskSdLQJBMyyePqGhrZk3mULbsyqKptwOVyuctO9FQC1hGNpjUhcwyOcWQA4Y4QsnUn3IP7PenUBE0E6NjhyOPmDx5HX+NgXvwkfvujuwgLCvFghJIkSf2HTMgkj7BYrezPymFr+n5OFJW1q5DcV9XlNRotVqtl0AzsB9CgIcQZRJmm0tOhtKcotNXTtZk0/K9+H1+s+BUB9Wp+OPYSfnntzzB4nb0StyRJ0mAmEzKpzzicTg5nn+Dd9z/iqy+/QKPRotHp0On0aHV6tFodWp2u3c8a7cnfNT28ZqO6dWC/w9FRcceBa5g9vP8lZKdq/RuqNGrqAgRvFqxj5YtfE2Xz5bbZ13HTvGvkkk+SJA05MiGTepUQgrzCEnZlZLFr3yEcThd5x3Kw223Y7TZoburyuRRFaUnUtDp3IqfR6tB7GYiKGY7B6HPuk5xCo2lLyLq+1tlA4O/yxdtlwKxq9nQo56SoWpMzLy3FOjN/3reaP21+k1H6SH51xU+ZO366hyOUJEnqGzIhk3pFWWU1u/cfZsuu/Zgt1naD84fFJRISHtWSlNls2G3W1p+tONq2tf7e9rPT6UAIgc1mxWazwml5XH7OESJjhhM3YiRehq6tIedOyAZRl2WbYfYwjw3uP19K27hBXz1Zrgp+9d+/0PR0MXH6EF7/8yskxyZ6OEJJkqTeIxMyqccIIcjKzuN/67ZSWFqJcLlOvsmeMjhfo9W664B1ldPp7Dhhs9uoriijurKMwhPZlBTkMiwukdjEkej0Z5856a5FNsi6LAHCHaFk6/JxKeeo0N/PCJfAUlpLU04FlrI6AI5qzTz95lsEuQLx99Pyq5/dQnhIkIcjlQajWgs09WGDuVEHAd2ounHRRRcxbtw4Xn755XPuu2HDBi6++GJqamoICAg47xilviMTMumCuVwuMg4d48t1W6mqqXfPklR6cByQWq1GbfCGDlq/4hJHUlNZTs7hTGprKjlx/AhFJ3KISUghfsTITuM42WU5+FrINKi5yDyVRsXc6T5lmkpO6Ir6MKrOOa12mnIraTpegdNsBUCLjpjgeJKi0zC5AlEpKurq7Pz572/jb9Cw6JYfEh8T5eHIpcGi1gJLN0B1H/b0mwyw9KLuJWXS4CUTMum8ORwOdu7L4qv122hoanYnYp4YkB0YHMrEmZdQXVFKzuED1NdVc/zoARwOO0mp4zo8Rj2IE7I2PqLz7lsfewx2xU6xtrwPI2rPZXPQcLSMxuwyhMMJgJfWwIhhqaREj0FvNKLi5ESOtudWbZON5Ss/RK8W/PSGqxidIrszpQvTZGtJxvQaMPTBO2Ozo+V6TTaZkEktZEImdZvFamPb7gN8/f12LNaW9v2+LFfRGUVRCAqNwBQSTklBLof27SL/+BH8A0yERcWcsb+7y3IQjiHrqmTbcJpVFmrU9X16XZfDSVN2OQ1HS3HZWrqMffwCSI0bT2L4KBS1ql0idrq2pa6abS7+770vUAsHN1w9n6kTxvToTFxp6DFoWroS+4L1AkZL/Pvf/+bll1/myJEjGI1GLrnkEl5++WVCQ0M73L+5uZkbbriBqqoqvvzyS0wmEytXruT5558nNzeXuLg47r33Xn71q1+df1DSBZEJmdRlTeZmNu7IYN2WdOwOJ4qi9Ms3P0VRiIwZjrmpkbzsLLL27cLo64+Pn3+7/dwLjA/iFrJzUYA0Swrphv19suSScLpoyq2g/nAJLkvL4+7j409a0lQSQ5MRikBF1xP7tsTMLlS89/kG3vvvN1w5bxYXz56KWpbOkAYxm83G008/TXJyMuXl5fz2t79l0aJFfPnll2fsW1dXx1VXXYWXlxdr167FaDSyYsUKnnzySV599VXGjx/P3r17Wbx4MUajkdtuu80D90iSCZl0TrX1DazfuofNO/fhdLn6bSJ2uoTk0dTXVlNdWUZm+hYmz56PRnvyo+/JMWSDb1B/1ymoUTHWMpJdhkwcSu89Fpbyemr3nMDR2JL4Gb19GZ04maSIUQiVQtu/89HWOutSNHyxYSeffbeZi6aP56oFF6HVyJc5afC544473D8PHz6c5cuXM2XKFBobG/HxOVkCqKysjJtuuomEhAT+85//oNO1vAY+/fTTLFu2jOuvvx6A+Ph4Dh06xOuvvy4TMg+Rr1RSp8qravh2007S9x12z5gcCIlYG0WlYvSEaezc+C1NTQ0czNjJmEkz3fehrctyMJa96A4FBS+hZ4wlmb1ehxA9vOySy+agdn8B5ryWYrXeeiOpiZNIjhoNatUFpGFnakvMFLWW73ceYP22vUwZk8wN11yOl76P+qEkqQ/s3buXpUuXkpGRQXV1NS5Xy4zq/Px8Ro0a5d5v/vz5TJ48mffffx91a4tyRUUFBQUF3HnnnSxevNi9r8PhwN+/fU+C1HdkQiadoaCknK83bOfg0dxemTHZl3R6L9ImzWD31vVUlBaRl51F/IiWF6vBPMuyuxQU/F2+JFvjOaw/Tk9kSEIImguqqd1XgMtqR4+OEdGjGZM8BZVWe9YxYheqLelWa3SkH8xh5/7ljEqIZuGNV+Nr7FqdOknqr5qamliwYAELFizg3//+NyEhIeTn53PZZZdhs7Wv23HllVfy0UcfcejQIdLS0gDcyduKFSuYOnVqu/3bkjap78mETHIrq6zmoy/Wcyyv0F3I1dMD9XuCf2AQyaMnkLV/F8cPH8A/wIQpJPzkLEv74KrUf74UFCKdYTQ5minQllzQuRxNVmr3nsBSWodO6Ag3xjIubSb+pqAebA/rGkVRodaoyMot5g9/+SfxUUH8YtEtssVMGrAOHz5MZWUlf/7zn4mOjgYgPT29w33//Oc/4+Pjw7x589iwYQOjRo0iLCyMqKgojh8/zsKFC/sydOksZEImYbXZ+Pr7HazfuueU0hWD61NSVOxw6moqKS7IJXP3NqbMWdCuMKwQYkB1x/amRFssZqWZKk1tt48VLkHjsTLqDxVhsOsJVYJJThxHTEISarVnX27aPlzkFVfzuz++xA8unsYV8+bIv7s04MTExKDT6fjb3/7GL37xCw4cOMDTTz/d6f4vvvgiTqeTSy65hA0bNpCSksLSpUu599578fPz44orrsBqtZKenk5NTQ0PPPBAH94bqY1MyIYwIQT7DmXz/uffYW629ovSFecihMBht2FuaqTZ3ERzUyPN5kaamxoxmxvRanUEh0USGjEMX//Adm+2yWkTaayvo76umsz0rYydMhsAl3DhcrlkU30rBYXR1iTSVQdoUnVeWPZ09vpmanblolTbCXIFEGaKInnMRHx8/Hox2u5TVCo0Wh3fbsngu407uPeuhcTJArNSq+Y+muNzIdcJCQlh1apV/P73v2f58uVMmDCBF198kWuuuabTY1566aV2Sdldd92Ft7c3L7zwAkuWLMFoNJKWlsb9999//oFJF0QRQvTsCF5pQCirrOa9T78jt6Ck3RJH/YEQAmuzGbO5keamJnfC1WxuxNzU2OUxX15e3oSERxESEUWgKQRFpaLZ3MTOjd9gt9uIjI6npCAPgWD2pdei95LVGdsIBDbFzk7DfuzK2R9vIQSNx8qxHijHx+6Nt9qbxNSxREUP7/etTy6nExSF6BA/7ln8U7zOsdyWNDhYLBZyc3OJj4/Hq/X/vazUL/WWjp5vHZEJ2RDTUfekJ7iczpYWrlNat9zJl7kJl8t51uP1Xga8vX0wGH0wuL8baW5qpLy0kOryUhzOkx9BT205U4B9u7YgEFjMZry8vZlx8Q/w9vHt5Xs9sAgEDaom9ngdwNXJzEtHoxXLrhI05U50QospJIxRY6d0eYH3/sLlcuF02Ljioqn8YP7cfp9IShemszfI/r6WpTQwyYRMasfpdLJz70E+/W4zzRZbj73hCCFwOhzY7bZ2C3+f7WebzYrNYkHQ+VNPUZSWRMvbiMHo0z758jaiPkdtKafTSXVFGRWlhVSUFmE/ZeC+Wq1padVpqKW+pgpTSDiz5l+NX4CpRx6TwUQgKFdXcVB/rN3MS+ESqHObsWZUoLYrqNRqkkaNJyq2/7eKdaZtHKHitPKbO39CfOwwT4ck9ZKuvkFKUk/o6vNNjiEbAsoqq1nx9ge8986baNQaDEYfvAxGDN5GvLxbvxuM6PR6HHZ7pwmVw97yu91uw2E7+fP55vRtsRhOSba8jUYM3j54GbwvqBtVrVYTEh5JSHgkwuWitrqS8tJCKkqKsFjMIMBibqKpoR5LczMnco4QP2IkRl//AZtQ9AYFhTBnME12M3m6IhDga/bCsauSptJq1CgEBAYzavxUvI0+5z5hP9b2d3ei4eU3PmBYiC+/Wfwz2Y0pSVKfkC1kg5jVZuPrDTtYv20PleUlZOzY2GvXUqnUaHU6tNqWL41Wh1bX+l2rQ6PVotXp0Wq1aLQ6DN5GtDp9nyc/Qgga6mqoKC2itOgEeccOE2AKRqvToVKr0eu9MIWEYwoJIygkAp18M3Y7ri3Ald9I0b7D2O02VCo1CcmjiRme1K/GIPYU2Y05eMkWMqkvyS7LIUwIQcahY3zw2VrMFuvJT/4OB5bmJprN5tbvTVjMTTQ3N2Exm7HbrC2J0ykJVUfJVUeJ1kCdodjUWE9VWQnVlWXUVJbjPGXsmkqlJjI6jpjhyUN+fJndZuVI5h5Ki/MB8PMPZNS4qWesDzrYuMuhOCzce9dC2Y05SMiETOpLMiEbosoqqnnvs2/JLShFCBeK0vWWi6Fei8vldFJbXUl1RSlVFaU01NcCLd12oRHDiE1MGZLjzCrLSsjatwurtRlFUYgfMYq4EaP6fYmUnmKzWtm7bQMxiSmMTxvJfXffKrsxBziZkEl9SSZkQ4xLCNZu3sWX67a5q+xL508IQW11JSeys6gsP1m13hQcRlxiCoHBYYM+eXXY7Rw7tI+i/BwAjD5+jBo3Bf/AIA9H1neEEOzftYWKsiJ8fP2ZPHs+LqeDG39wEXNnTj33CaR+SSZkUl+Sg/qHkIbGJlZ98CU5J4pai7vKZOxCKYpCYFAIgUEhNNbXciL7MKXF+VRXllFdWYavXyCxCcmERkYPypaimqoKMnZspKG+BoPBh9jEFBJS0gZs1/T5KjqRQ0VZESqVmtTxU1GrNagUFWu+3cbOPft58Nd3Dsq/vyRJfU++kgxwR4/n8+zf3iQ7r3DQt9h4io9fAKkTpjHjkiuJjh+BWq2hob6GA3u3s3XtF5zIPjxo1sN0Op0cPZjBnq3raairoaG2BqfTgd1qobaqHNG6KPFQ0Fhfx7GDGQAkpqTh6x8ItFT6VxSFoqom7nvsOUrLKzwYpSRJg4XsshygnC4XX63fznebd3m0wOtQZLdZKczLoTDvGFarBQCNRktkzHBi4kfg5W30cITnp762moN7d9DUWA+Al5cBIcBqPVm6XK/3IiwqlvCoWHz9AwbthwCn08muTd/S2FBHUEg446Z2vOaly+XEYbdzzfzpXHbJHA9EKp2PzrqQ6pobMdstfRaHt9YLf0PPlItZunQpn3zyCRkZGT1yPk9QFIU1a9Zw3XXXeTqUHiXHkA1itfUNvPHe5+QXlQ3aN8SBwOl0UlZ0ghM5R9xJjKIohEVEE5OQPGAmALhcLvKOHSL32CGEEOj1XowcO5ngsEiEENTXVFFSdIKyovx2BXaNPn6ED2tJzgwDNAk9nd1mo7ToBEUncmhsqEOn82Lq3MvOuqyWEC5AwddLzZMP/QrNEOvWHYg6eoOsa27kL+tWUdNc32dxBBr8ePiSRT2SlDU2NmK1WgkKGrhjPId6QibHkA0wB4/m8uYHX2C12WWrmIep1WoiY4YTER1PVXkp+cePUF1ZRmlxPqXF+QSaQohJSCY4LLLfJs6N9XUcythBfV0NAGGRMaSkTUCra5lFqCgK/qZg/E3BJKWOp6q8lNKiE1SWFtHUWE/O4UxyDmcSaAohfFgsoRHRaHU6T96lbmubwFGcf5zy4gJ36RO1Ss3oCVPPucZp20zmRquL+x97jkfuvZNhkRG9HrfUs8x2CzXN9eg1Orw0vT+L1uKwUtNcj9lu6ZGEzMfHBx+f/l+c2W63o9VqPR1GvyTf0QcIh9PJf7/ZyL/+8yk2mYz1K4qiEBwWwYTpFzF1zgIihsWhKAo11RXs27WZTd98yqGMnZSXFOKwd21h9N4mXC5OZB9m56Zvqa+rQavVkTZhOmkTp7uTsdOpVCpCwiNJmzid2QuuYdTYKZiCQlFoua9Z+9PZ9O2nFOfn9vG9OT9Wi4UT2YfZvv5/7N66jpLCPJwuJz6+/iSljmfWpVdjCgnv1jnVem/+/Pe3+fR/3/ZS1FJv89Lo8dZ59fpXd5O+119/naioKFynjeO85ppruO2221i6dCnjxo1zb1+0aBHXXXcdL774IhEREQQFBfHrX/8a+ymvQTabjSVLlhAVFYXRaGTq1Kls2LABgKamJvz8/Pjwww/bXe+zzz7DaDTS0NAAwMMPP0xSUhLe3t4MHz6cxx9/vN012uJ64403GD58OHq9HiEEx44dY86cOXh5eTFq1Ci+/bb9/xmbzcY999xDREQEXl5exMXF8dxzz3XrMRtoZAvZAFBdW8+//vMpxWWVLWvtyWSs3/L1DyR1/FQSUtIozD1GUf5xbDYLxQW5FBfkolJUBASFEBIeRXBoBAYPLDfU3NTIwYyd1Fa3DEYPDo1g5NjJ6L0MXT6HRqsjMiaeyJh4LM1mSotOUFp4gsaGOo4e3EtwWGS/XOVAuFxUV5ZRlH+citIi97JfGrWGsKgYImOG4xdgOu8WTZVKjaJVsX7nIfbsP8RjD/4a7TnWXZWkrrjxxhu59957Wb9+PfPmzQOgpqaGr7/+ms8++4ytW7eeccz69euJiIhg/fr1ZGdnc9NNNzFu3DgWL14MwO23305eXh6rV68mMjKSNWvWcPnll5OZmcmIESO4+eabWblyJTfccIP7nG2/+/q2FMv29fVl1apVREZGkpmZyeLFi/H19WXJkiXuY7Kzs3n//ff56KOPUKvVuFwurr/+eoKDg9m+fTv19fXcf//97WJfvnw5n376Ke+//z4xMTEUFBRQUFDQ0w9rvyJfKfq5/VnZvP3R/7DZHbJVbADxMniTOGosw5NHU1tdSWV5CZVlxZibGtylM47QMg4rODQSv4BAjL7+ePv49urfubykkEN7d+BwOtCoNYxIHU9kTPwFdal6GbyJSxxJbEIKOzd+S0N9DXnHDpE0enwPRn5hms1NlBTkUpyf27KWaSv/gCCiYocTGhGNpoe6Udoey9pmF/c99md+98tbGR4X0yPnloYuk8nE5ZdfzrvvvutOyD744ANMJhPz5s3rMCELDAzk1VdfRa1Wk5KSwpVXXsnatWtZvHgxOTk5/Oc//6GwsJDIyEgAfve73/HVV1+xcuVK/vSnP3HXXXcxY8YMiouLiYyMpLKyks8//7xda9Yf/vAH989xcXE8+OCDvPfee+0SMpvNxttvv01ISAgA33zzDVlZWeTl5TFsWMvqF3/605+44oor3Mfk5+czYsQIZs2ahaIoxMbG9uCj2T/JhKyfsjscfPL1RramZyKEkMnYAKVSqzGFhGEKCWPEqLGYmxqpLCumsqyY2uoKmhrrW7oPjx9u2V9R4e3ji4+vP0Zff4y+fvj4+mPwNl5Qy6hwuTh+9CC5xw4BEGAKIXXclB5toVMUhRGjxrBn+/cU5mUTHT/CIy2Ap2qsryPn8H4qy0oQtLSGabU6IobFERkTj49fQK9dW0EhsbKCIz+7g5zrrubSB+/rtWtJQ8PChQv5+c9/zmuvvYZer+edd97h5ptv7rQ+YGpqarvbIiIiyMzMBGDPnj0IIUhKSmp3zKkTA6ZMmUJqaipvvfUWjzzyCG+//TYxMTHMmXNyRvGHH37Iyy+/THZ2No2NjTgcDvz8/NqdMzY21p2MAWRlZRETE+NOxgCmT5/e7phFixZx6aWXkpyczOWXX85VV13FggULuvNwDTgyIeuHyqtq+Ne7/6W8qrali7KfDgiXukdRFIw+vhh9kolNSMZus1FVUUpjfS01VeU0NdTjcNhpbKijsaGu3bFqlbpdgubj15Kw6b0M53x+2G02Du7d7l5xICY+icRRY3slyTeFhGMKDqO6sozjRw6QOmFaj1+jK2xWK8ePHqAoL8ediJmCw4iMGU5IeFSvF7jVWa1M2reLtCOZGMxmmv75Ou9t38l1q/4feuPgmJEq9b2rr74al8vFF198weTJk9m0aRN//etfO93/9MHziqK4x6C5XC7UajW7d+8+4//DqZMD7rrrLl599VUeeeQRVq5cye233+5+zdm+fTs333wzTz31FJdddhn+/v6sXr2aZcuWtTuf8bTnfEfFHU5/HZswYQK5ubn873//47vvvuPHP/4x8+fPP2NM22AiE7J+Zu/Bo7zz8VfYHU7ZKjbIaXU6wqNiIKqlO0sIgdXSTGN9HU2tSVlTQx1NDfU4XU7q66qpr6tudw6NRutuTWtJ0loSNp2+ZWZgY30d+3dtxmxuRK1SkzJ2EhHD4nr1fiWOHMPOTd9SWpRPTEKyu6BqX3A5nRTmZXP86EEcjpaBxaHhw0gYOQZjHy0QH15Wwqydm4gsK6be15dq/0D8GhuYtGMba+dfScorLzJ8yqQ+iUUaXAwGA9dffz3vvPMO2dnZJCUlMXHixPM61/jx43E6nZSXlzN79uxO9/vpT3/KkiVLWL58OQcPHuS2225z37ZlyxZiY2N57LHH3NtOnDhxzmuPGjWK/Px8d1cowLZt287Yz8/Pj5tuuombbrqJG264gcsvv5zq6mpMpoFRUqi7ZELWj2zYtof/frNJdlEOUYqi4GXwxsvgTXDYybIJwuWi2dzkTtAaG+pbErXGlha12ppKamsq251Lp/NCCBeWZjNqjQaDwciYyTP7JDnyCzARHhlDaXE+2Vn7GT9tbq9fUwhBZVkJ2YcyaGpqmf3l6xdAUup4AoNDe/36ACqnkzFZ+5i0Px0vi4Xy4BCc6paX2HpfPyx6PSmFeRTe/WvK//AI0370wz6JSxpcFi5cyNVXX83Bgwf56U9/et7nSUpKYuHChdx6660sW7aM8ePHU1lZybp160hLS+MHP/gB0DIO7frrr+ehhx5iwYIF7boZExMTyc/PZ/Xq1UyePJkvvviCNWvWnPPa8+fPJzk52X3t+vr6dkkdwEsvvURERATjxo1DpVLxwQcfEB4eTkBAwHnf5/5OJmT9gEsIPvt2Mxu27QHObLqVhjZF1TKuzNvHFyJOvhi6nE7MTY0nE7XWljVzUyMVZUU01NUSHT+CwKCQs5az6A3DU9IoKymgqqKU6ooyTCFh3TrebrNSW11FXXWFezWEs7GYm6hpnTWq03mRkJJGZHRcn81I9muoY+bOzSScyKFZ70VZcCic9v/YptNTHhzGsMpyKp56hm/LK7n0l4v7JD6p6ywOa7++ziWXXILJZOLIkSP85Cc/uaAYVq5cyTPPPMODDz5IUVERQUFBTJ8+3Z2Mtbnzzjt59913ueOOO9ptv/baa/ntb3/LPffcg9Vq5corr+Txxx9n6dKlZ72uSqVizZo13HnnnUyZMoW4uDiWL1/O5Zdf7t7Hx8eHv/zlLxw7dgy1Ws3kyZP58ssvB3VjhazU72FOp5N3//stezKPeDoUaRCwWizsT99MZWkxdruNlLGTGJEyxiOlUo5k7qEg7xh+/iYmz57f6QcNIQSWZjO11RXUVVdSW115xhi6rlCp1MTEjyBuxKgemzHZFZElhVy0bQPB1ZVUBZqwnSPxVVwuokqLOBaXQO4v7uauW2/po0ilNoOxUn9veuedd7jvvvsoLi5GN8AKP/cHslL/AGC12fm//3zK0dwC2SomXbC66kr2796K1dKMwejDxHFTCD2lRa2vxSeNoqQgl/q6asqLCwiLOrP0Q0NdLYcydtBQX3vGbUajLwFBIXgbzz32S1GpCAmL7NtZnUIw8lgWM9K34GVtpjQkDNGFxNdgbabZy5tDSaPJOV7GC8tf56F77+6DgKWz8Tf48PAliwbsWpa9wWw2k5uby3PPPcfdd98tk7FeJhMyD2kyN/P3Nz9yF3uVpPMlhKDoRA5HD+zFJVwYffwYM2kmRl+/cx/ci3R6L2ISUjh+9AA5hzMJiRjm7m5wx3wwA5fLiaIo+PoHEmgKwd8UTIAp2D0xoV8SggmZu5mydyculUJ50JldlB1ROZ3419eTkTqO43GJKIpCcY2Fx55+kacfe2BQd8cMBP4Gn36dIPW1559/nmeffZY5c+bw6KOPejqcQU92WXpATV09y9/4gOraevkCLF0Qp9PJ4f3plBTmARAaMYxRY6f0aZfd2Tjsdrau+xKbzULy6AlEx4/AbrORtX8X5SWFQMtKAaPGTenfCdgpFJeLyRk7mbQ/HYteT4NPFxNfIQitLKciOJT/LrgO62ldF8LawAt/fERW9u8DXe1CkqSe0NXnm8wG+lhJeSUv/PMdmYxJF6y5qZH0zWspKcxDQWHEyLGkTZzRb5IxAI1WS3zSKAByjx6iuryUnRu/obykEJWiImnUOMZOmT1gkjGAsQczmLRvF2YvQ9eTMcC3qQGbTs+WybPOSMYA0Plw76PP0NRkPvM2SZIGPZkR9KHj+UX89f+tpslskcmYdEGqykvYuallmSKdzovx0+cSm5jSL7u/o2KGY/D2obqylO+/+YTm5iYM3j5MnHkJMQnJ/TLmzow4fpSpGTuw6r1o6sZ4NY3DjtFsJiN1HEWdjOtTFAWdtz8PPPEXyisqO9xHkqTBS2YFfWTLzr28+I+3abbIZEw6f0IIco8eJGPHJux2G34BJqbMuRRTcPfKSvQlh8OO02HHbrXh5eVNWGQMU+dcin9gkKdD65aokkJm79gIQlDfnfF5QhBcXUVBZDR7R084664qlQovnwAe/8tr5BzPu7CAJUkaUORghT6wfc8BHv/jn6goKQIFNGoNWp2+9UuHTu918mf3dv0pP+sGVCuC1DvsNhuHMnZQUVYMwLDYBJJSx6Pq5WWALoQQgj3bNmC1WggKDWfk2EmED4sbcM9nn8YG5m7bgMFibhnA3w0B9bU0eRvZPGU2ji50J6tUKryMvrz4+jvcdcvVTBw35nzDliRpAJEJWS8SQvDd5l18uW4bCFBUCkIIHE4HjmYHzc1NXTqPgoJWpzstSTslgdOfvl2PWq0ecG96Uuca6mrJTN+C2dyISqUmJW0ikTHxng7rnCzNZhob6lCr1EyZswAfP39Ph9RtaoeDOdu/J7i6ktKQsC7Npmyjs1nR2exsnDadyqCQcx/QSqVSofPy5o33/0dNTR3zL+58aRtJkgYHmZD1EpcQrPnfBjbv2g/A2CmzEELgdNixWa3YbVZsNht2W9vP1tN+br3NbkMgsLVu71oK17IYtbulTX9qAufVmtjp2t+u1XmkeKh0bqWFJ8jatwuny4nBYCRt0gz8AgbGWm6NrfXFjL5+AzIZA5iQuZuEEzlUBgZ1qc4YtJS38DE3YTQ3cnR4MgeTR3f7uiqVCq1Ox3/X7aCquoabfnRNt88hSdLAIROyXuByuXjrw/+RcehYu1YqRVHQaHVotDqgawsdu1yu1uTM4k7UbFbLyYTtlGSu7XaXy4nT5cRpMWOxdH3Gllar66QFzqtdd2rbd7VGI1vhepHL5eLYoQwKco8BYAoO6/MlkC5UW0Lm4xfg0TjOV1x+LuMP7KXJ24i9q0UxhSCkqgKr3os6vwC2Tp6J6zy7lRVFhVqtsHV/DjW1b/OLO392XueRuqap2YLNZuuz6+l0OoyGrs8wvuiiixg3bhwvv/zyeV0vLy+P+Ph49u7dy7hx49iwYQMXX3wxNTU1na4RuWrVKu6//35qa2sBWLp0KZ988gkZGRnnFYPUOZmQ9TAhBO9/vu6MZOx8qVQq9F5e6LtYK6elFc5xRktbuxY462mtcfaWFyC73dbyc+vizOeOTX3WcW+601votLp+Pd6pP7FamsncvY3a1vUZ40eMYnhS6oBrxWwYwAmZX30ds3ZtQuN0UBPQ9UXZ/RrrsRgMbJk0i0pTMPW+F9Yy2PY6kpVfyYpV/2bxovNfUFrqXFOzhTX/20CjubnPrunjbeCHV1zUraTsQkRHR1NSUkJwcPB5n+N3v/sdv/nNb3owKqmNTMh62P/Wb2PH3oMeazlqaYXTotFqu7yMjHC5WpKxtm5Uq6Vdd+oZrXBWK06XE5fLidXSjNXS9RcwjUZ7ZqLWLoHzatedqtFqh1wrXG11JZnpW7BaLWg0WlLHTyUkPMrTYZ0Xm7VlAWUhXB6OpHtaxo1twFRT3TJurIu0dhvezc1snjKLrNb6az2h7f/A/pxSPv70C66/5soeO7fUwmaz0WhuRqvRoNP2/lujze6g0dyMzWbrs4RMrVYTHh5+Qefw8fHBx0euZtAbZELWgzbv2se3m3Z5OoxuU1QqdHovdHovjF08pn0r3Gmtcae3wLVuFwgcDjsOhx3MjV2LTVE6bIHT6b3wDzThbwpBM4gqm5cU5HFo306EEPj4+pM2aSZGn651b/dH4VGx1FZXkHcsi8jo+IFRAFYIJmfsJL4gj0pT18eNIQRBNdWcGBbL/pFjezwsRVFQq9V8ty2TIFMgc2fN6PFrSKDTatD30ZqNdoej28c4HA7uuece/v3vf6NWq/nlL3/J008/jaIoKIrCmjVruO6669z7BwQE8PLLL7No0aIzuiw7smrVKp544gkqKyu57LLLmDVrVrvbT++yXLRoEbW1tcyaNYtly5Zhs9m4+eabefnll9G2ziouKSnhrrvuYt26dYSHh/Pss8/y+9//nvvvv5/777/ffd433niDsrIygoKCuOGGG1i+fHm3H5+BbPC8k3lYxqFjfPTlBk+H0WfUGg1qjQYv766lcMLlwuGwn9IC1zoeztbBeLjWhM7hdCCEwGq1YLV2vOCvSlHhHxhEYHAYpuBQ/AKDBmydt+L8XLL27UIgCIuMYeTYyQM+2YyKiac4P4f6uhqys/YzatwUT4d0Tgl52Yw7lEGD0Qe7tutvzAH1dTR5G9kyeRbOXvq7KYoKrU7Pu5+uwxQYQFpqz7XCSQPDm2++yZ133smOHTtIT0/n5z//ObGxsSxevPiCz71jxw7uuOMO/vSnP3H99dfz1Vdf8eSTT57zuPXr1xMREcH69evJzs7mpptuYty4ce6Ybr31ViorK9mwYQNarZYHHniA8vJy9/EffvghL730EqtXryY1NZXS0lL27dt3wfdnoBnYr/b9xLHcAt764EuEEEOue62rFJXK3cpFF1t8nE7nad2mJ1vgLM1N1FSVY2k2U1NdQU11BcePttR4CwgKcSdoPn4BA+JvcmoyNiwukeTREwZE3OeiqFQkj57Ari1rKS7IJSo2oV8XhA2sqWLmrs0gRLcq8WttNvQ2KxunzqHKdP7jc7pCpVLhZTDyyv+9x+O/XUxsdMeV/6XBKTo6mpdeeglFUUhOTiYzM5OXXnqpRxKyV155hcsuu4xHHnkEgKSkJLZu3cpXX3111uMCAwN59dVXUavVpKSkcOWVV7J27VoWL17M4cOH+e6779i1axeTJk0C4F//+hcjRoxwH5+fn094eDjz589Hq9USExPDlCn9/8NbTxuYTQn9SGFJOf98ew1Ol2tQvIH2J2q1Gi+DN77+gZhCwgmPiiE6fgQJKaNJHT+VmfOuYsbFPyAlbRJhkTHodHocTgeV5SUcO5TBjo3fsOmb/5KZvpXCvBzMjQ0IITx9t84wWJOxNv6mYCKjW2qmHcnc0y//BtCSVM3d/j3+DXVUdSdpFILg2ipyo+M4kJLWewGeQqVSYfQN4I8v/pPq6po+uabUP0ybNq3d68P06dM5duwYTqfzgs+dlZXF9OnT2207/feOpKamoj5lwlZERIS7BezIkSNoNBomTDi5SkViYiKBgScnytx44400NzczfPhwFi9ezJo1a3CcR3fuQCdbyC7Qi6/+ix1bN5I2cSbG7iynIl0wRVHw9vHF28eXYXEJCCForK+jprKM6soyaqsqsNmslJUUUFZSAICXlzemkDACg0MJDArFy+Dt0fsw2JOxNgkpYygvKaS+rpotaz9vGbOo8zpjNq5Gq0Oj0aLWaNBoNKg12pbvak3vzjAVgikZO4guLqDSFNyt4q+BdTXU+/ixdfKs8y5vcT5cTgelJUX87sm/8PcXlmLo4kxsafBSFOWMDzx2u73Lx5/vhyXtaStQKIqCy+U66zlP3R4dHc2RI0f49ttv+e677/jVr37FCy+8wPfff3/GuQczmZBdgMLCQr5c8x56g5HD+9OZMOPiQflmOlAoioKvfwC+/gHEJCTjcrmor61uTdDKqaupwmIxU1yQS3FBLgD+gUEMT0rFFBLe53+7oZKMAei9vEhISePIgT1Yms1YmrteH6+NWqVGo9USGBRK3IhRPVpoNiEvm7TDmdT7+OLQdP0NQG+1oHU42DxlDjV9WKzXYm4iY+cmGhvqcNht3P/o07z24h/btVJIg9P27dvP+H3EiBGo1WpCQkIoKSlx33bs2DHM5q7/Xxs1alSH578QKSkpOBwO9u7dy8SJEwHIzs521zVrYzAYuOaaa7jmmmv49a9/TUpKCpmZme1a1gY7mZCdp+rqai677DKaGxsICQ2ltrqS4vxcomKHezo0qZVKpSLAFEyAKZj4pFScDge11ZXuBK2hroa6mir27thIoCmE4SlpBHZjeZsLMZSSsTbR8SMIDovEamnucBauzWrFbrfidDhaFyRv+d72SdrpcuK0OiktzqesuIDQyGjieyAxC6irYUb6VhACcxcnqQAowoWptoYjCclkjRh5QTF0R0NdDRk7NmG1NqPXGxgWNwLvgEAefOxpXnruyUH/PBrqCgoKeOCBB7j77rvZs2cPf/vb31i2bBkAl1xyCa+++irTpk3D5XLx8MMPd6uF6d5772XGjBk8//zzXHfddXzzzTfnHD92LikpKcyfP5+f//zn/OMf/0Cr1fLggw9iMBjcz9VVq1bhdDqZOnUq3t7evP322xgMBmJjYy/o2gONTMjOg9ls5pprrqGsrIzNmzfz+dfrePPtf5OdtY/gsMguF3GV+pZaoyEoNJyg0JY6PFaLhRM5hynMy6amuoLdW9cRFBLO8OTRvTrwvLSogKzMdOprqxk5dtKQSMbaGLyNGLqR9AghWmfoOnA67FgtzeTnHqW8pJCy4nzKWxOzhOTReJ9HeRC1w8HsHRsJrKuhNLTr9cYATDXV1PgHsm3SjK6XxrhAlWUlHNi9FYfTgY+vP+OmzHbPdFYMgTz5p2X88bHf9Uksg5XN3jdjl873OrfeeivNzc1MmTIFtVrNb37zG37+858DsGzZMm6//XbmzJlDZGQkr7zyCrt37+7yuadNm8a//vUvnnzySZYuXcr8+fP5wx/+wNNPP31esbZ56623uPPOO5kzZw7h4eE899xzHDx4EK/W98qAgAD+/Oc/88ADD+B0OklLS+Ozzz4jKKj/TgDqDYroryNs+ymHw8EPf/hD1q1bx6eff8mRgiqO5pxg1+a11NdVExYZQ9rEcw+ClPoPS7OZvGOHKMo/7m6NCQmPIiE5rcfXX6yuKGXvjk1UlhWhVmuIT0olbeL0gVGfqx9pqKsl99hByksKgZZlvyZMvxhf/4BunWfKnu1M3buDqkBTt0pcGJrNGM1NrJ19KUcTkrt1zfNVdCKHw5m7EUJgCg5jzKQZrcuwnSSEIDbYm9/e8/M+iWmgslgs5ObmEh8f704KhkKl/v6isLCQ6OhovvvuO+bNm+fpcHpdR8+3jsiErBuEENx55528++5/ePHVFeSV1CAQuFyChroadm76FiEEYyfPJiQ80tPhSt3U3NTI8aMHKS08gUCgoBAWGc3w82x9OV19bQ17tq7D4XTg7e2D1dKM0+XEy8ubtEkz+nU5iP6qoa6WrH27qK+rRqfTM2H6xV1OomMK87h8/VfYNRoau/H3VTschFRXsG/UODZOm9utCQDnQwhBzuFM8rKzAIgYFsfIMZM6XIasrUVxQnIUty28qVfjGsg6e4Ps72tZDlTr1q2jsbGRtLQ0SkpKWLJkCUVFRRw9enRIDNqXCVkv+P3vf8+7H6zhpkW/wu5wcfoDd+zQPk7kHMbLy5tpF18x4It6DlVNDXXkHDngbn1RFIWIYXEkjhxz3i1ZzU2NpG9Zi9VqwRQUyripczA3NZKZvoWmpgZUKjXJo8cTFZvQk3dlSLDbbOzd/n1rUubFhOkXnTMpMzY1cs03/8VUW015cGjXLyYEYRVlFIdH8fn8q7Hpe3ehd5fTyaGMnZQW5wMwPCmV+KTUs3ZxC9GyIsYVs8Zx5eWX9mp8A1VX3yClnvH111/z4IMPcvz4cXx9fZkxYwYvv/zykBkjJhOyHrbspVfYsGMfiSPHdji1GFq6M3d8/zXN5kZi4pNIGj3eA5FKPaWhroacwweoLC8GQK83MHri9G4P/LdZLaRvWYe5qQFfvwAmzrjY3dXksNs4mLGTitIiACKj40lOmyhny3VTS1K2gfq6GnQ6LybOuAhjJ4t6q5xO5m/6lpTsw5SGhHVr/FdAXQ1OtYbPLr2Giu4kcufBbrOyf9cWaqorUBSFkWMmExkT36VjhcuF1Wrh1h/OZ/rUyb0a50AkEzKpL3X1+SYLw56D0+nk1RVvk1dlIzFlDNB5XRWNRkNKWsu03oLcY9RUlne4nzQw+PoHMm7qbCbNnIfRxw+rtZk929ZzIvtwl+v1OBwOMnZuwtzUgMFgZOyU2e3G/Wi0OsZMmklCShoKCsUFuezesg6Luam37tagpNXpGD9tLr5+gdhsFvZs20BTY0OH+6YeOUDS8aNUBwR2KxnTW63obTZ2jZ3c68lYc1Mj6ZvXUlNdgUajZfzUOV1OxuDk+rQr3v2UkpLSXoxUkqSeIhOys2i2WHnu1bfILqpqeRPtwliRoNBwIobFIRDs27WZhjpZRXugCzAFM3n2pYRHxiCE4FjWPvanb8FhP/tYE5fLxYHdW6mvrUar1TFu2twOC9EqikL8iFGMnzYHrVZHfV01OzZ+Q3WFfCPtDq1Oz4Tpc/Hx9cdqtXCidczVqUIqy5mSsROLXo+1G93PisuFqbaaY/EjOJg8uifDPkNdTRW7Nq+lqakBLy9vJs28BFNIeLfPo1Kp8As08ejTL7iLdEqS1H/JhKwTQgj+899vqKyp7XZJgpQxkwg0heBw2Nm7fWOnn9SlgUOj0ZA6YRopaRNRqdRUlBaxc+O3nSbcQggO70+nsrwEtUrNuCmzMZ5j4LgpJJwpcxbg52/Cbrexd/tG8o5l9dulhvojrU6P3ssAgNHnzJUzxmTtw9jcRF0n3ZmdCa6potIUxJZersZfUVrEnq3rsdks+PoFMmnWPHz8As77fIqiIjAshmeff6nngpQkqVfIhKwT2/YcIPPwcRSl+w+RWq1m7JRZ+Pm3dJ/s3baBZtkFNeApisKwuEQmzrgYg8GI2dzSrVScf/yMfY8fOUBxQS4KCqMnTse/iwtOG7yNTJx5CZHR8QgE2Yf3k5m+FUc3lj8Zyuw2GzVVFQAEh50509mm1aG4XGgdXX88fZoacarVbJk8q1uzMburIPcY+3dtwelyEhQSzsQZF/fM0l5CUNbg5Lt1Gy78XJIk9RqZkHWguKyCD79Yd0Hn0Gh1jJs6B6PRF6vFzI7vv6Y4/zhCdh1cGCFavjzIPzCIKXMuJTg0EqfLyaF9uziUsRNn62K4hXnZ5B47BEDKmImEhEd16/xqtZpR46a0lDZQqSkvLWTXpm9paqjr8fsy2OQfP4LL5cTH17/DUiX7Ro3jeGwCpppq/Brqzvlc0jjs+DQ1sG/kWE4Mi+uVmIUQHD2YwZEDexAIomISGDdlNpqeKgegKGg0Wv695hsqKyt75pySJPU4OcvyNFabjT///W2qa+tQqS68a8LSbHa3lgD4+PozYtRYgkIjLvjcQ9GCDV8RWVaMU6XGqVbhVGtafz755VBrWr40Ld9dbbep1FQFBnFiWGyPVFYXQpCXncXxwwcQCHz9AogYFsexQ/sQCIYnjWZ4cuoFXaOuporM9K1YLGY0ag0jx00hLDL6gmMfjGxWC1vXfoHD6WDMpJmERgzrcD+1w8GYrH1MzNyNV3MzlaZgnB2VqBGCiIpSTkTF8uW8K7tVOLarnE4nB/dud5dYSUhJIy5xZK+s3CCEoKGykH/97YUhszJEZ+QsS6kvybIX5+nfH39F+v7D3X7B8m2oZ+629ZSFhJOROh677uSLt8vpdLea2FsHggeFhDNi1NgLGh8y5AjBTz96G/+GWix6LxQh2n/Bmdtan95CUVCEwK7VsnnyLA6MHNNjYVVXlHFgz3YaGmqorawgNDKaYbGJpIyZ2CNvfDarhQN7tlNdWQZAbEIKiSlpKH20XM9AcfRgBvnHj+Dnb2Ly7PnnfOzDy0uYuXMzkWVFNBh9aTL6tLs9qKaKZr2BzxZcQ3UvFO21WS3s27WZupoqVCo1o8ZOJnxY79dlivBTseS3v+n16/Rnnb5BVldDY2PfBeLjA6a+W5S+P1AUhTVr1nDdddd5OpQ+09WETFYuPcX+rGy2HjiB7jzeRI3NTcQV5pGYl0N4eSnrZs1zv8Cr1GpiEpKJiI4j91gWhbnHqKoopfr7MgJMwfj6B+LjH4CvXyBGXz9U8o22QxqHA63DhtlgpPG0N8+uCqquZPyBvWTHJWLpifE5gCkkjNQJU1n72fsEhUYQFjGMlLSeW59Sp/di/NQ5LdXacw5zIucw9bXVcsmlU1iazRTmZQOQkDK6S499aWgEny24hkkZu0g7nImxuZxKUxAulRpvcxOKEGybNKNXkjFzYwMZOzZiNjei1eoYM3lWnyxsL4Qgr7yJzVu3M2vGtF6/3oBSXQ333QcVFX13zZAQeOWVQZmULV26lE8++YSMjIx220tKSggMDPRMUP2cTMhOseVAAXv1cwhylTPclokaZ5ePLQsO49CIVMZk7Sf5+BG0DjvfzL2s3SBgrU5PUuo4hsUlkp21j/KSQmqqK6ipPvkCoFKp8fH1x8fPH41Wh0qlQqVSo1K3flepW7ap1Sdv68Lviko14LspvKwW1E4XVt15dh0JgZfVQl0Pt0pams1k7duFKTgMf1MQqeOn9XjrlaJSkThqLH4BJg5l7KSmqpwdG79hzMQZXZ4wMJjlHTuEy+UkwBTSrRIRNp2erZNnUhQxjBnpWwirLKfB6INPUxN7Rk/g6PCkHo/V0mwmfcs6bDYLBoORcVNnd1rEtqcpioJWp2fFu58wOnUkAf59c90BobGxJRkzGMC7Zz6snZXZ3HK9xsbzTshsNhu683097ITdbu/V5YzCw7tfwmWokAlZq9yiCp79/AQ+CZHYfJKwq7xItO5BJ7q2rplQqdg4bS7ezU2MyMtmWEkhF29Zx1eXXHHG2BNvow9jJs2kqbGB+poqGupqWr7qa3E47NTXVVNfV92j909B6TRxU1Qq1KrW76f93rK/Go1Gg1anR6vTo9Pp0Ghbv+v0Lcf0QbKncThQhEBvs2JpLW3QLYqCXavDp6mR2Ts3sX7GJTgu8IXHYbexb+cmLM1mjD6+jJ08G3UvLpkVGhmN0deP/elbaWqsZ/fW9SSNnkBU7PABn3Cfr+amRopaZ7ompKR1/3FQFE5Ex1ERFML03VsZkXuM/KgYdo6f2uPrVAohOJSxE5vNgo+vP+OnXYS+j8cwqVQqAoPDeejxZ/l/r/xlyD5vOuXt3dKV2Beau7eQ+UUXXcTo0aPR6XS89dZbpKam8o9//IPf/e53bNy4EaPRyIIFC3jppZcIDm75oOZyuXjhhRdYsWIFBQUFhIWFcffdd/PYY4+Rl5dHfHw87733Hq+99hrbt2/nH//4B7fffjsrV67k+eefJzc3l7i4OO69915+9atfuWN5+OGHWbNmDYWFhYSHh7Nw4UKeeOIJtFotq1at4qmnngJwP79WrlzJokWLzuiyzMzM5L777mPbtm14e3vzox/9iL/+9a/4tP4NFi1aRG1tLbNmzWLZsmXYbDZuvvlmXn755UG3DqZMyACn08WPn/4YQsZzydhhOBUNe3JVHFb0jLDswiDMXTqPQ6tl5/hpRJSXoghBXGEeo7My2TtmYof7G318Mfr4EhEdB7S8WDebm2ioq6GpoR6X04HL5cLlcrZ8dzq78PspP4uTMzoFAqfLidPV9Va/rlKr1Gh0OnStCZtWp0er1bX+rEN76m2t29UaTbffCGr9A8hIHcfkfbvwaWqg0dj9EgTlQSEE1VQxIvcYxeFRF1Tk0+V0sn/XFhrqa9HrvRg3dQ66Xl7bEMDo68/kWfM5tG8n5SWFHM5Mp762asguuXT8yAGEEASFhF9Qt5/Z28jaWfM5kpBCrV9Au3GgPeVEzmGqK8tQqzWkTZrZ58lYG0VRMJoiWf7a/+O+X9/tkRik8/Pmm2/yy1/+ki1btlBdXc3cuXNZvHgxf/3rX2lububhhx/mxz/+MevWtVQKePTRR1mxYgUvvfQSs2bNoqSkhMOHD7c758MPP8yyZctYuXIler2eFStW8OSTT/Lqq68yfvx49u7dy+LFizEajdx2220A+Pr6smrVKiIjI8nMzGTx4sX4+vqyZMkSbrrpJg4cOMBXX33Fd999B4B/B62xZrOZyy+/nGnTprFr1y7Ky8u56667uOeee1i1apV7v/Xr1xMREcH69evJzs7mpptuYty4cSxevLiXHmXPkAkZcO9fP+SEegSzRkXj72MEYPoIEztzVBxCS7I1HR9XbZfOVR4SxsGkVCbt34UiIPXYQTJGj+/SrD5FUfA2+uB9nuOjTieEOGfiJlxOnM7W7y4nwuXC6Wz9fsrvTocdm82K3WbDfsp3l2jZz2lpxmrp+qc9laI6JWHTu5M2jVaHXu+Fl7cP3kYjXt4+J5MMRWHXuCloHA4m799Fo7dP91swFAWztxFvsxm75vw/XbW1dFRXlaNRaxg3dQ6GHvq7dYVGqyVt4gxO5BwmJyuT4oJcGutrSZs0E4O3sc/i8LTa6kpKik4AMLwnKugrCoW9NIu1vraa44cPAJCUOv6chYL7wuGCKnbt3sPkiRM8HYrURYmJiTz//PMAPPHEE0yYMIE//elP7tvfeOMNoqOjOXr0KBEREbzyyiu8+uqr7kQqISGBWbNmtTvn/fffz/XXX+/+/emnn2bZsmXubfHx8Rw6dIjXX3/dfZ4//OEP7v3j4uJ48MEHee+991iyZAkGgwEfHx80Gs1ZuyjfeecdmpubeeuttzAaW163Xn31Va6++mr+8pe/EBYWBkBgYCCvvvoqarWalJQUrrzyStauXSsTssFmzbrdvH9Yw/DkYSTHnixFYdRrmZFkYkeOioPKdJKsuwl0dm1tyqwRI0nJOYza6aDC1PsDdTujKApqtbrXWk2EEDgdjpYEzd6SoNlsVhw2GzabDbv91ATu5M9OV0vrndXajNV69iROQUHvZcBg9MHgbcRg9MHm7U0wCjqrBdV5dF0GVVdRERRCdlzi+d51srP2U1qcj6IojJk8E1//vh+kqigKcYkj8fM3cWDPNurrati58RtGT5g2JMqqCJeLI5m7AYiKGY5/Lwy+7ykOh4ODe7bjEi5Cw4d1a13K3qIoCjq9gVffeI+/Jye5u4ik/m3SpEnun3fv3s369es7/Nvl5ORQW1uL1Wpl3rx5XT5nRUUFBQUF3Hnnne0SHofD0a6V68MPP+Tll18mOzubxsZGHA4Hfn5nro5xNllZWYwdO9adjAHMnDkTl8vFkSNH3AlZampqu/exiIgIMjMzu3WtgWBIJ2RFZdXc/+Y+AmImMXfcmW/Oeo2amSNM7DquIqt+Kgm2fYQ68jlXm0xNgIkN0y+m1j+A6gBTj49D6S8URUGj1aLRaulOWnRmEte+1c1qbaa5qYlmcyMOhx2LxYzFYqamquX440JQ0tSApq4GxctAgEZDoEZLgFZLgEZDgEZLgEaLbydj2+xaLc4LSFLzjx/lRE5Lk/+osVPOa53BnmQKCWPKnAXsT99CfW01GTs2MTx5NHEjeqeeVX9ReCKHhvpatFodCSk9V8akNxw7mEFTUwN6LwMjx07qN38XlUpFYEgESx5/ltdees7T4UhdcGry4nK53K1Jp4uIiOD48TNXEenKOQFWrFjB1KlT2+3XlhRt376dm2++maeeeorLLrsMf39/Vq9ezbJly7p1X4QQnf5fOHX76WPFFEUZlOuzDtmEzOUS/PiPH+IIHsvl44ejVnfcpahWKUxJCCAzX8Wx6gnYFD3D7MfOnpQpCsfjEnol7sFArdGg1mjw4uxda0II7DYrzU2NmM2N7iStuakRUVWBurKcZpeTMpuTMpv1zOsoijs5C9BoCNBqCdRoqff2Ia62mriCvG7/ncqK8jl6cC8AiSPHuMf/eZqXwZtJMy7hyIG9FOXnkHMkk/raalLHT0HTCwVNPc1qsZBzuOUTckLKmD4Zu3e+6mqqKMrPQUEhddxUtLr+FauiKOj8Q/nnv1bxi7sWeTocqRsmTJjARx99RFxcHJoOJhONGDECg8HA2rVrueuuu7p0zrCwMKKiojh+/DgLFy7scJ8tW7YQGxvLY4895t524sSJdvvodDqczrOPWR41ahRvvvkmTU1N7qRwy5YtqFQqkpJ6foZzfzdkE7KHX13DMTGc6SnRmPzP3lSvUhTGxvpzVKcit2wMFpUPcdYDaJHrC/amli4VL3R6rzNKO4wMjWD2xm84GmCixumg1mGn1mGnxt7yc73DgVMIquw2quztZ8qqXC78LM1ovv+KUvMs/AOD8A8Mci9K3ZmaynIOZuwEIDpuBLEJKT17hy+QSq1m5NhJ+AeaOJy5h4qyInZu+o4xk2bi4ze4yhtkZ+3D4bDj528iqh90/3VGCEH2oX0ARETHYQoJ83BEnVHYe6SQQ4eyGDVqpKeDkbro17/+NStWrOCWW27hoYceIjg4mOzsbFavXs2KFSvw8vLi4YcfZsmSJeh0OmbOnElFRQUHDx7kzjvv7PS8S5cu5d5778XPz48rrrgCq9VKeno6NTU1PPDAAyQmJpKfn8/q1auZPHkyX3zxBWvWrGl3jri4OHJzc8nIyGDYsGH4+vqiP+2D08KFC3nyySe57bbbWLp0KRUVFfzmN7/hZz/7mbu7cigZkgnZgexC3tpjIzp5GKOGn7kAcWeSInzx1qvJKdVTrQ4j3JFPsKMAo6uhF6OVOlIUHoXL4E2itbnDumJOIah3nEzUGpubsTY20GhtpkStodLXn3JvI805J2cbGQxGd3LmFxiEr18AqtYm+sb6Wvbt2ozL5SQ0YhhJqeP6TbfT6SJjhuPjF8D+9C2YmxrYtfk7Ro6dTHhUjKdD6xG11ZWUFOYBkJw2oV+vWFBZVkxNdQVqlbpnJh30EkVRMBiN/Omvr/H2iuX99rndJ8xdm1XfH64TGRnJli1bePjhh7nsssuwWq3ExsZy+eWXuwuMP/7442g0Gp544gmKi4uJiIjgF7/4xVnPe9ddd+Ht7c0LL7zAkiVLMBqNpKWlcf/99wNw7bXX8tvf/pZ77rkHq9XKlVdeyeOPP87SpUvd5/jRj37Exx9/zMUXX0xtba277MWpvL29+frrr7nvvvuYPHlyu7IXQ9GQXDppzj3/j1zDeH500VgMXt3vzrE7obDWSnFNM9bGWgLspYQ58gl0lqFi8PVr91djD+xl1q7NNBh9aD696r4QGM1N+DU24FKpcKlUVAeYEIpC+ugJZIaEU1tbTV1NFXU1lTQ11CNo/19Bo9YQERNPeFQs+9O3YLU0E2gKYdy0uQOivITNauXAnm3uJZdi4pNIHDV2QK8EIVwudm76lob6WqJihjNy7GRPh9Qp4XKxfcNXNDU1EJc4ksQeXK6rt7hcLiaMCOO2n/7E06H0qg6XspGV+qVeIpdO6sSqz7Zw2BbFxNSw80rGALRqiA/SE2fSU232JbcymKMNseisVUQ4TxBkL0IvulfwT+q+/aPG4t9Qx9hDGTg0GncBXp3Niqm2Bovei1q/AJxqNdsmziA3Jt5dfsQb8Pbzd892c9jt1NdWtSZoLV92u42C3GPs27EZRa0iNHwYYybPGhDJGIBOr29ZcunIAfKys8jPPUpDXQ2jJ87wWP2rC5V79BANdTXUVFUwbe7lng7nrIryc2lqakCn0xOX2L+6tzujKPDNpt1cf+3V+Pp6vixHnzKZWpIjuZal5CFDqoWsqdlK2i/fRhM9hR/OTUPVg83yzQ7BiUoLFXXNOMw1hDiKCLHn4+eqOuesTOn8ae02Fmz4moQTOVQEBeNQa4goL+V47HB2jpuKVa/HbPA+Y7WEcxFCUFNZRt6xLBrrayktLsA/MIjwqBhiE0cSMMCWKyovKeRQxk4cDjt6LwNpE2cMuPtQWVZCxo6NlJcU4Odvwj8ouN8uHeWw29m2/kusVgvJoycQHT/C0yF1i8Zawwt/WurpMHpNV1ssJKknyBayDjz0t08w+47gstToHk3GAAwahZRwAyNCDZQ1+FFQFUJ5QzxGewXhznyC7MVo5CSAHmfX6lg/8xK0DjsxRfnYtFqavL3ZMX4aFcGh531eRVEwhYRjCgmnrrqKgJzDVJQWUVFWTEVZMQGBwcQmjiQ4LGJAjLcJjRiG0def/bs209RYz56t6xnRuq7qQIjf3NjAgT3bQIHU8VMxNzX266Wj8o8fwWq14G30JSpmuKfD6SZBnV1NZuYB0tL677g3SRpsBu5gkm46mFPIR4cE0VHhRIb0XhFPtQoi/TVMifdjUkoUhvAU8nxnstt7Hid0o2hSDbFugD5g9jbyzdzLODEsFrtWy6apcy8oGTudvymIMZNnMu3iK4iKSUClUlNbU8m+XZvITN+K1WLpsWv1JqOPL5NnX0pYRDQu4eLIgT0cytiJ0+HwdGhn5bDb2bdrMw6HnYDAYNImzmDyrPmERgzDJVwczkwna9+uc06x7ytWSzMnco4AkJiS5p4YMnC0rBjyl1deZwh1oEiSxw2ZLss5v1lBrte48x7IfyHckwCqm7E11eLtqEGDDZVwosaJSjhR4UKFC6X1ZwUXKuFCpbhQIVDhQn3KdgUniNb9Ret2WrarhMt9jv7TZtD7vCzNBNTXUtrLVeqtlmbyjx8l//gRhBBotTqS0yYSFhndr1ppOiOEIP/4UbKz9iGEwNcvgDGTZvbp0k9dJYQgc/dWyksK0XsZmDL7Und5EiGEe+kogcDP38SYSTPw8vDSUVn70inKz8E/MIhJM+cNiOdER1xOJxOTI7h14S2eDqXHyS5LqS919fk2JBKyNz/fykOf1jBhfBrjkzw39V8IqLG4qG0WuITA6RI4XeASApdLtMzyEwIhBELQ+r3lyyVa9kMIFOFq3dfVclLhQggXwuU6+bMQ4HKBcKK4nCjCgdKWALqTQCdq4WhNBp0oCHdyeDIhFC37tyaFbcmfIpwnv7cmgCpO/tySDIpBnRA21NVyKGMnDfU1KIqKAFMwoydMHzAD5msqy8ncvQ2bzYJWqyN1/DSCw/rXkku5xw6RczgTlaJi4oyLOxwvVl1RSububdjtNnQ6PaMnTPdYva+mhjq2b/gagWDSjEsIuIDFzj1NCBflxQW8vuypQTfAXyZkUl+SCVkrs8XG6F+81SsD+fuaECAAV0te1pqktf7Oab8LcJ2yr7M16XO6ROvPtCaEAqfglESw9YvW7y5wIRCnJIwIF5ySEApXSxJIWyLYmhwK4ULlcoBwtCR6rclfSxLoRN2aFKo4tZXP6U78WpLBky2DSuv+uJwYXI1o8HxXm8vl4uiBvezbuQmbzUJ0fBIpYyYNmNYyS7OZzN1bqaupQkEhPimV+KRR/SL2yrIS9u3chEAwcswkomI7X1Wh2dxEZvoW6utqUFBIHDmGmITkPr8f+3ZuoqKsmJDwKMZOnnXuAwYAra2G559d6ukwepRMyKS+JAf1t+rNgfx9TVFAAVTndTeU1q/zJ86SAJ6aBJ6eLLa17jmdLpyipVXQeUpy6BS0turR2hrYcjLXKQmhuzUQF83NFoy2cpItO9ELz47fUqlUJKdNoCg/h7LiAhrrazmwZxvlxQWMGjcFzWlrsPU3XgZvJk6/mKMHMyg8kc3xowdal1yailbnuSWX2gbxCwTDYhPOmowBGLyNTJw5j8P70ykpzONY1j7q62oYOXZyh0vK9IaaynIqyopRFIXEkWP75Jq9T1BrU3Pg4EFGp6Z6OhhJGtQGdUJ2MKeQDw86iUnp3YH8Q4WigFqB8xuirHC+R4rTksAmi4304xoOiymkWD2flCmKQnR8Ei6XC41Gi8vlpLy0ENtOK+OmzumzhOB8qdRqUsZMxC/QxJH9u6ksL2bXpm9JmzQTX/+APo/n9EH8Sanju3ScWq1m1Lgp+AWYOHpwL2XF+TQ11DFm0ky8fXq3y00IwbHWJZKiYhIw9vL1+k7LAP8/v/xP3v5/Q7yCvyT1skE9y/JXL/8PXUgiM9P671p30rkpSsvsVY0KdGoINOqYHO9PnTacI15TsCqe73I4tYty3NS5aDRaaqsryNixEUc/n8XYJjI6nkmz5mEwGDGbG0nf/J17iaK+IoTgUMZOmhrrW+qlTZrRrVmKLcnxCCbOuAS93kBjQx07N31LRWlxL0YNZcUF1NdVo1FriE8aXC1JiqIiKCKef//nPU+HIkmD2qBNyN76YitZ1khS48+/Ir/UfwX4eDE9KYh6XWS/SMr8AkwYvH1wOh04bFbGTxuYSZmvfyBT5lxKUEg4TpeTg3t3cCRzD64+KimRl51FeWkhKkXFmIkzzrnge2cCTMFMmXMpAYHBOBx29u3axPEjB3qljIPL6STncCYAsYkpA2ZSR3coKoWvNuyksS+r2EvdsmjRIq677rpBe72hYFAmZGaLjaUfHCIgLJqxSdGeDkfqJb4GHVMTA/tFUqYoCmGRLc+10uJ8/AODBmxSptXpGTdlNvEjWlp6CvKOsWfbBqyW3l0OrLKshOOHDwAti4ZfaAV+vZeBCdMvIjqupUr+8aMH2bdzE3ab7YJjPVVhXjbN5kb0egPRw5N79Nz9haKoCI2K5ek/L/N0KNIFsttlgfL+alAmZEv+9glm30SmD4KB/NLZtSVlddoIjuon4fLgUzo8qqWkSlV5KQ67bUAnZYpKRULKaMZOnt0Sf00lOzd+Q21V7yy83N1B/F2lUqtJTptA6ripqFVqKstL2LXpWxrra3vk/HabjdxjhwAYnjy6348XvDCCGouKAwcPejqQIe3DDz8kLS0Ng8FAUFAQ8+fP56GHHuLNN9/kv//9L4qioCgKGzZsIC8vD0VReP/997nooovw8vLi3//+NwArV65k5MiReHl5kZKSwmuvvdbuOkVFRdx0000EBgYSFBTEtddeS15eHgBLly7t8Ho2m4177rmHiIgIvLy8iIuL47nnnuvrh2jAGnSvHoeOF/HBQSfRKRFyIP8Q4WvQMTrKm/35YZRo4ohyHPdIHEZff4w+fjQ11lNeWkRkdLw7Kdu7/Xt3UjYQBvq3CQmPZMrsS9mfvoXGhjp2b1tP0qhxDIsf0WMDvM93EH93RETH4ePnz/5dWzCbG9m1eS1jJ8/EFBJ+Qec9kZ2F3W7Dx9efyOi4ngm231Lw9vHlLy//k7cG2QB/IQS2Hm457SqdTtflx7KkpIRbbrmF559/nh/+8Ic0NDSwadMmbr31VvLz86mvr2flypUAmEwmiotbxk4+/PDDLFu2jJUrV6LX61mxYgVPPvkkr776KuPHj2fv3r0sXrwYo9HIbbfdhtls5uKLL2b27Nls3LgRjUbDM888w+WXX87+/fv53e9+R1ZW1hnXW758OZ9++invv/8+MTExFBQUUFBQ0DsP3CA0MN4VuuH+V/+HLmQss9LiPB2K1IcigvzIr2ymkBRMzjIMoqnPY1AUhfCoGHKOHKCsKJ/I6JbJJAM9KfP28WXSrPkc3reL0uJ8jhzcS11tNSljJl3wfbjQQfzd0TY+btv6r7DZLBQX5F1QQmYxN5GfewyAxJFjUFSDssOhHUVRCAiL5ZP/fsYPr7vG0+H0GJvNxr333uuRay9fvhy9Xt+lfUtKSnA4HFx//fXExsYCkJaWBoDBYMBqtRIefuZz+v777+f66693//7000+zbNky97b4+HgOHTrE66+/zm233cbq1atRqVT861//cieLK1euJCAggA0bNrBgwYIOr5efn8+IESOYNWsWiqK4Y5S6ZlC9guw7ms/e2kAShgVh8OraE1waPMbEBWJR+XBCNxJPVTsOjWzptqyuLMNmtbq3D+TuSwCNRkPqhGkkpY5HURRKi06Qvvk7zI0NF3TevGM9M4i/qypKi7DZLKgUFbEJFzbeKy/7MC6Xk8CgUIJ6ebmu/kStUfOfjz+X61x6wNixY5k3bx5paWnceOONrFixgpqamnMeN2nSJPfPFRUVFBQUcOedd+Lj4+P+euaZZ8jJyQFg9+7dZGdn4+vr677dZDJhsVjc+3Rk0aJFZGRkkJyczL333ss333xz4Xd6CBkYH9G76Mk31qI3pTJeDuQfkgx6HYkheo6XRRPsKCbY2bulDjpi9PHFzz+Q+roayksKGRZ3cizUQG8pUxSFmOFJ+PoHcmD3VndJidTx0wgJj+z2+SrLSjh+pOcG8Z+LuamRowf2AjA8ZTS+/uc/pMHSbKa4ILflXEmpg6r77lwURUVwVALr1m9g3iUXezqcHqHT6Vi+fLnHrt1VarWab7/9lq1bt/LNN9/wt7/9jccee4wdO3ac9Tij8eT6ri6XC4AVK1YwderUM87fts/EiRN55513zjhXSEjny4FNmDCB3Nxc/ve///Hdd9/x4x//mPnz5/Phhx92+T4OZQPjnaALcgrL2VbmTWJqIF66/l0dXeo9wyMCKayxke8ahX9zJVr6flxIWGQM9XU1lBXnt0vIYOAnZQCBQSFMnn0pB3Zvo7amkn27NhE/IpXhSaO63G3XW4P4OyNcLg7u3Y7D6SDQFELsBc6GzM85gsvlJMAUMqDXqzxfOr2eN/79/qBJyBRF6XK3oacpisLMmTOZOXMmTzzxBLGxsaxZswadToezC+VpwsLCiIqK4vjx4yxcuLDDfSZMmMB7771HaGgofn5+He7T2fX8/Py46aabuOmmm7jhhhu4/PLLqa6uxmQyde+ODkGDpsty6f99jTogmokpnls8XPI8RVEYG+tHvTqQQl2iR2JoK39RW1WBpdl8xu0DvfsSWpZcOrWkRO6xg2Ts3ITdZj3HkeBwONifvqVXB/GfLi/7MHU1VWg0WkaNn3pB472sFgtFJ1q6beJH9I91P/uaoij4BEeRnr7b06EMKTt27OBPf/oT6enp5Ofn8/HHH1NRUcHIkSOJi4tj//79HDlyhMrKyrOWt1i6dCnPPfccr7zyCkePHiUzM5OVK1fy17/+FYCFCxcSHBzMtddey6ZNm8jNzeX777/nvvvuo7CwEKDD67300kusXr2aw4cPc/ToUT744APCw8MJCAjoi4dnwBsUCVlZVR3f5qqJCgvGaBgYn3Kk3hPg402kv5YSbSL1qr6faevlbSQgMBiBoLyksMN9BkNS5i4pMb6lpERVRSk7N31HQ13nY1qEEBzZn05jQx16fe8O4m9TV1PF8aOtXaOjJ2DwNp7jiLPLP34Ep8uJX4AJU0hYT4Q4IBm8ffj7ijc9HcaQ4ufnx8aNG/nBD35AUlISf/jDH1i2bBlXXHEFixcvJjk5mUmTJhESEsKWLVs6Pc9dd93Fv/71L1atWkVaWhpz585l1apVxMe3TETy9vZm48aNxMTEcP311zNy5EjuuOMOmpub3S1mHV3Px8eHv/zlL0yaNInJkyeTl5fHl19+iWoITHjpCYoYBCMzf/X8e6wpiuS6iycQ4HthL7bS4OBwOFl/qAJ/WzGjLVtQ4erT6xfkHuPIgT34BwQxefb8Tverq6li7/bvW1qLTCEDrvuyTUNdLfvTt9BsbkStUpMyZhIRHZSBKDqRQ9b+dBRFYcL0iwns5e4+h8PBro3f0NTUQFhkDKMnTLugFi2b1crWtZ/jcDoYO3n2eY2dG0zqa6tZ8oufkJw8sAriWiwWcnNziY+Px2sQrqwg9S9dfb4N+LS1vqmZ/x60EBYWIpMxyU2jUTM6ypsadSglmrg+v35oRDQKCnW1VTQ3db7czGBoKQPw9Q9gyuxLCQ6NaFlyKWMHhzN3t1tyqaGuhiOtg+oTUtJ6PRkDyD6UQVNTA3ovAylpEy64e7Eg9ygOpwNfv0CCw4bOzMrO+AWYePnvKzwdhiQNCgM+IfvTyq9x+MUxKWlof1KVzhQR5EeAt5ZCfQrNSt8m63ovLwKDQ4GWhafPZrAkZVqdjrFTZjM8aTQKCoV52ezeth5LsxmH3UZm+lZcLichYZHEJqT0ejwVpcUUto71Sh03Fa3uwoYz2G02ClrrjsUnDc2xY2cSNDm17nFFkiSdvwGdkFmsdv6zq5qQ0BBCAjueCSINbZ6sTRbWWpOsrDj/nPsOlqRMURSGJ6cydspstFoddTVV7Nz4LftaK+QbDEZGjZvS68mMzWoha98uAGKGJ/fIWK/CvGM4HHZ8fP0JCY+64PMNDgpBoeEsW/7auXeVJOmsBnRC9td3v6PZJ5YJI2TXgdSxttpkFZpoqtR924oaGhGFoig01NfS1FB3zv0HS1IGEBwWweTZl+LrF4DNZqGmqhyVSs3oidMvuKXqXIQQZO3bhc1mwcfXn4SUtAs+p8NuJ//4UQDihujMyk4JQVmtlaqqKk9HIkkD2oBNyJxOF298X0hQSBhRcs1K6SyGRwSi0+nI143CTteLMF4orU5PUEjLh4VzdVu2GUxJmbfRh0kz5xExLA6VSk3y6PH4Bwb1+nWL849TUVaMSqUmdfw0d7HLC1FSkIvdbsNo9CUsYlgPRDmIKAphUTG89LeB10o2COa0SQNAV59nAzYhe/3j76k3xDJm+NCddi51TfvaZCP69NphUS01ycqK8rv8n3IwJWVqjYbU8VO56PIf9nrxV2gpOHv0YAYACcmj8fUP6JHzVpaXABAVmzAk1qzsLiEER0+U09jY+QSW/qQtSffUguLS0GI2t9Sj1GrPXrR+4M2vB1wuwd+/OkpA5HSGRw29KtlS97XUJmuipDaBIEcJfq7qPrluSFgUapWapqYGGutru7xcz2Co6H+q3q41Bi3LvRzYux2n04EpKJSYC1yr0n1ep5PaqgqAIV137GwURSEqLpFX//H/eOShBzwdzjlpNBq8vb2pqKhAq9XKOllSrxBCYDabKS8vJyAg4Jyt9QPy1X311zuo0EQzM04mY1LXjYo2sb7BSZ4utc9qk2m0WoLCIigvKaSsKL9b6ycOtqSst+UdO0R9bfXJavw9NM6rrqYKp8uJTueF0de/R845GAkh2JV5FKvV2u+XIVIUhYiICHJzczlx4oSnw5EGuYCAAMLDw8+534AsDDvp7tepCZrKDZeMRSUH10rdUFJVz/78ehJte4myH++Ta5YXF7B/91a8DN7MnHdVtxOFwVI8tjfVVVeSvnUdQghGT5hOeFTPLaGWc/gAuccOEh4Zw+iJ03vsvIOREC5GhBv59S9+7ulQusTlcsluS6lXabXaLo9jHXCv6v/bkskJEcnkmGCZjEndFhHkR35lM4UiBZOjDINo6vVrBoVFolFrsDSbqa+pwt8U3K3jZUvZ2TkcDg7u3YEQgvCo2B5NxgBqqsoB2V3ZNQrrNqfzi8V39shkit6mUqlkpX6p3xhwHed/Xr0db1MkaQmyEKx0fsbEBWJR911tMrVa7a5bVdqFmmQdGUwD/XvasYMZmM2NeHl5kzx6Qo+fv61kia+/qcfPPdgoikLU8GQ++PAjT4ciSQPOgErICsuqyGoMID4iUA7ClM6bJ2qThbW22pQXFyBc5zd2TSZlZ6ooLaIoPwcFhVHjp6DV9WxZE7vNit3e0qVlMPr06LkHK5VKzX+//M7TYUjSgDOgsprXPtqMyjeM1PhzD46TpLMZHhGIVqslXzcSJ73ftWIKDkOr1WG1WqhpnbF3PmRSdpLVcko1/oRkTME936Vobl2HVK83yC7iLlIUBafaQHl5uadDkaQBZUAlZJ/tKSUg0ISf0dvToUgDnKIopER406AKoELT+4U+VWo1oa0FRbtaJLYzMilrq8a/E5vNiq9fAAnJo3vlOvbWAd8yGeueyJh43nl3tafDkKQBZcAkZHsPn6CUMOLC5ZqVUs8IC/JDr1VTpE3sk1aytrUty0sKcDmdF3SuoZ6UFZ3IobK8xF2Nv7fqnPkHmlBQaGpqoNnc+xNABpNNO/Z6OgRJGlAGTEL2z0+2ofUNYWScXLdS6hkKLa1kjX3UShYYFIJe74XdbqO68sK7c4ZqUtbU2MCx1mr8iSPH4OPXe7XBtDo9Aa2zYgtyj8mldrpIURR8gsI5duyYp0ORpAFjQCRkLpfgu8ONBJkC8dKdfekBSeqOvmwlU1QqQiNal1I6z9mWpxtqSZnL5eLgnu04XU5MwWFEx/f+UlgRMfEA5B8/wuH9u897UsZQExQSztuy21KSumxAJGTfbj9Agy6CxEi5iLjUs/q6laxttmVFaRHOC+y2bDOUkrLcowepr6tGq9UxatyUHqvGfzaR0fEkp45HQaEoP4dtG76i6MTxC+52HuyEEOw9KFsVJamrBkRC9n9f7kHnF8yIaFmYUep5fdlK5h8YhJfBG4fDTlXrgtU9dd7BnpTVVleSdywLgJQxk/Ay9N3knujhSaRNmoFWq8Pc1EDW/l1sWfcFJ3KO4LDb+yyOgURRFCJiRrBjxw5PhyJJA0K/T8jsDidbCyA8KAC1ut+HKw1AfdlKpiiKe3B/WVHPdFu2GcxJmcNub6nGjyBiWBxhkdF9HkNoxDBmzr+apFHj0HsZsFqaOXYogy1rPyfn8AFsVkufx9TfGX39ePf9jz0dhiQNCP0+w3n3qx3YvCNIjgnydCjSINaXrWRtCVllWXGPt64M1qTs6MG9NJsbMRiMJI8e77E4NBoNMQnJzLzkSkaNnYzR6IvdbiP32EG2fPc5Rw7swSJnY54kBLlFFdhlK6IknVO/T8jeWXsIb/9ghoXJhEzqPX3ZSubrH4C30Reny0lFWVGPn3+wJWXlJYUUF+S2VuOfikbbs9X4z4dKrSYyZjjTLrqcMRNn4OdvwulyUpB7jC3rvuDg3h3uJZeGNEUhJmEkX339tacjkaR+r18nZLUNZvbXGIkM9pMLiUu9rq9ayU7ttiy/wCKxnRksSZnV0uyuxh+bmEJgUIiHI2pPUakIjYxm8uz5TJg2F1NwGEIISgrz2LbhK/bt2kxdTZWnw/QonV7Pms++8nQYktTv9euEbMUnm3EZwxgZF+rpUKQhoC9bycKjWsZAVZWXYrdZe+UaAz0pE0JwKGMndrsNX79AhielejqkTimKgikknAnTL2LyrPmEhrc8fypKi9i1+Tv2bF1PVXnpEJ1xKKhpstPY2OjpQCSpX+vXCdnH23LxCwwiNFBW55f6Rl+1khl9/fHx9cclXFSU9ny3ZZuBnJQV5mVTVVGKWqVm9ISpvVaNv6f5BwYxZvJMpl90OZHR8SiKQnVVOXt3fM+uTd9d0ALzA5NC9PBkPvxIDu6XpLPptwlZXnEl2ZYgYkJkMib1nb5sJWurSVbaw7MtTzcQk7KmhjqyD+0DIHHUWIy+vVeNv7cYff0ZNW4KM+ddRUx8Emq1hvq6avbv3jrkapmpVCq+WrvJ02FIUr/WbxOyf3y0CbVPKCOHh3s6FGmI6atWsrZxZDWV5VgtvVsyYSAlZS6nkwN7duB0OQkKCWdYXKKnQ7ogXgZvkkaPZ+a8qxielDoka5kpioLQGiktLfV0KJLUb/XbhOyLfeUEmkz4eRs8HYo0xPRVK5m30Qe/ABMCQXlJ7wzuP9VAScqOHz1IQ30NWq2OkWMn90k1/r6g0+sZnjz6HLXMemc8YX8QGRPPO/95z9NhSFK/1S8Tsr1ZeZQRTlzYwOumkAaHkEAfFKBa3buL2Ye3FYntpdmWp+vvSVlNVQUnsg8DMHLs5D6txt9Xzl7L7LNBW8tMCMHGbbs9HYYk9Vv9MiF7f10GaqOJlFjZXSl5hlqlxlvrokEdgIvea6EJjYxGQaG2uqLP3oT7a1LmsNs41FqNPzI6ntCI3l9b1JO6Ususpqpi0MzMVBQFtF5UVlZ6OhRJ6pf6ZUK27XA5Pr5+eOm1ng5FGsICvDU4FD0WxafXruFl8CbAFAz0XSsZ9M+k7MiBvTQ3N2Hw9iEp1XPV+Pva2WqZ7d66jq3rviT36MFB0Wo2LDaR77//3tNhSFK/1O8SMpdLcKzBiyA/OXZM8qxAow4HWswq3169Tttsy75MyKB/JWVlxQWUFOahoJA6fioa7dD7MHZ6LbOomOFoNFqazY3kHDnAlrVfsGfbBkoK83D2gxbN86HT69mwaZunw5CkfqnfJWRb9x3DpjMxLFiWu5A8y8/Y8qGgtxOy0IhhKIpCfV015saGXr3W6TpMyvp4xp+l2czh/ekAxI0Y6W4xHMr8A4MYOXYysy69htRxU1tazRBUV5ZxcO8ONn37KVn70qmrrhxQXZpCCI7nF3s6DEnql/pdQvb5lkOoDQHERMi1KyXP8vb2QsFFoyqgV6+j03thCg4D+r6VDM5Myvbu+B67zdYn1xYul7sav5+/ifh+XI3fEzQaDRHRcUyYflFr2YzRGAxGHA47Rfk57Nqylu0bviIv+/+3d9/Rcd3nnf/f997pg8EMeu8EQBLsTSJFSlSzZMndVuIW2/H6ZNdJ1utkd51qO042m91kN5tkz0l2f7/dTZxfNsVOHCcukixZIiWRFHsFiN77AFMBTL/39wdIWoUVHOAOgOd1Dg8tYObeB2b74Pt97vO9Sjy2YHa5d6QoClZnHn6/3+xShMg5ORfITnRN4/F4cNjW35aFyC2Ljf0GUa1gWRv74SczyabGl3dI7K14C4rYtf8wVquNcHCWcyeOLPsIhsV5Y28SmJlCUzXadj2IqubcX0k5w+ly09jaxoHHn2X3/kepqK5H0yzMz0XovXqJYy9/nwsnX2NqfCTnBs6mkgkGuts5efRF3B6v9JEJcRM59befrhv0RhwUSv+YyBEr0dgPUFJehaqozEXDzEXCy3qvW8n3FbJr/6PYbA6ikSBnj79CIh5blntlMhkunTnG1MQIqqqxZfd+3HnLuzW8ViiKQkFxKW07H+DQkx9g8/a9+ApLMDCYmZ7g8tnjvP7SP9N5+SyRUMDULc14bIHu9gsce/n79HVdIRoJsTAX5egbb5pWkxC5ymJ2AW91/GIPKbv0j4ncUeC2MRY2WFA9uDLL199ltdkoKq3APzXG1Pgweflbl+1et+Px+tj90GOcO/Eq83MRzh5/lV0PPoLD5c7aPdKpFJdOv0FgdhpN1di29yBFpTLiZiksViuVtY1U1jayMBdlYnSQiZFB4vEFRgd7GR3sJc/jpbKmgfLqOmx2x4rUlUzE6eu8wsTIALqxeG6nJ99HbWMrhSVl9HdfWpE6hFhNciqQff9YB6qzWPrHRM5YbOxPLDb2L/MuUFlV7WIgGxumsXWLaRPq3Xke9hx4jHNvHmVhPsqZ46+w68HDuLKwgpVKJrlw8jXCoVksFivb9x2ioKgkC1ULV56Hpo1baWxpIzAzzcTIANOTY8xFw3R3XKDn6kWKSyupqKmnuKxyWbaHDcNgbKifvs5LpFKLfYgFhSXUN2+isKT8xu9pq8OD3++npER+7YW4LqcC2YmuaTzeBukfEzljpRr7AYrLKtE0CwsLc0RCAbwF5n1j4nTnsfvAo5w/cYT5+ejiStn+R+7rkO9kIs75N48SjYSwWm3sfPAR8n2FWaxawOJcs6LScopKy0klk0yNjzA+0k8kFMA/NYZ/agybzUF5VS0VNQ14vL6s3Hdhfo72828SDs4C4MkvoHXLTnw3CdxV9U0cOXKE5557Liv3FmItyJkesuv9Y0X5a++oFLF6rWRjv8ViobisEjDnact3cjhd7DrwGHkeL4lEjLPHXyUaDi7pWvHYAmePvUI0EsJud7D7wGMSxlaA1Wajur6JfYeeZP/hp6lr2ojd7iCZjDM80M3J117k1Gs/YmSgh1Ry6Q9xpNNpLp56nXBwceWztW0n+w49cdMwBmCz2XntmPSRCfFWORPIrvePVZVIY6/ILd4VauwHKKusARaftsyF+VJ2h4PdBx4l31tIMpng7PFXCQfu7eibhfk5zh57hfn5KA6Hi90HHiMvX86pXWluj5fmzds5+MT72bHvEKUV1aiKSiQcpOvKOV5/6XtcOnOMmalxDF2/p2t3XT7L/FwEu8PJg4efpqaxBeU2W6Iyj0yId8uZLcvvvdG+2D9WLv1jIrc4NNAVC0nFjstY3sGtRaUVWCxWEvEYocBMTvRXWW12du1/hAsnXycUnOH8m0cXe7+KS+/43vlomHMnjpJIxHC5PVl/QEDcO0VVKS6rpLiskmQiwdT4MOPDA0QjQaYnRpmeGMVud1BeXU9lTf0dt6nHhwdunLKwZdf+uzoQfnEeWT7T09OUlt7595EQ60HOrJCd6PbjyfdK/5hY1zRNo6S8CjBvJtnNWKw2dlw7ZzGdSXPh5GvMTk/c9j2RUJCzx18lkYiR5/Gy+8BjEsZyjM1up6ahmQceeQ8PPPwUtQ0t2Gx2Eok4Q32dnDjyAqdff5nRwb6bDgs2dJ2ejgsANLZuuadvIKrr5VxLId4qJwKZrhv0Rp0UeWT+mBDl1862nB4fveeto+VksVjYvu8QJWWVZPQMF0+9wfTE6E1fGwrMcO7EqySTCfK9hew+8Ch2x8qMXBBL4/H6aNmyk4NPvJ9tex6ipKwSRVEIh2bpvHyGN176Z66cPUHAP3nj92U0EiaVSmKxWKnfsPGe7me12Tj6hpxrKcR1ObFl+caFbtI26R8TAqCguAyr1UYyGScwM51TM7o0TWPr7gO0nz/J1MQIl88ep23HA5RX1914TcA/xcXTb5DJpCkoLGH7vkPr8rDw1UrVNEorqimtqCYRjzM5NsTEyABz0TCT48NMjg/jcLioqKknc+1EAF9hyW17xm7GMAwGRm6/yirEepITK2Q/ONaB6vRSJ/PHhEBV1RvN/ZNjQyZX826qprFl14NUVNdjGAbt508yPtwPgH9ynAunXieTSVNUUs6OBx6WMLaK2R0O6ppaeeCRp9h36Emq6zdgtdqIxxcY6Ong/JtHWZiLLqnXUVEUbK7FPjIhRI4EshPdfjweD3b5i1sIAMqrFlec/BOjZNJpk6t5N0VV2bxjH9V1TRgYdFw8zaXTx7h05g10PUNpeTXb9x5Es+TEIry4T4qikO8rZOPW3Rx88gNs3bWfopJyLBYrDpcLq822pOtW1W3gyJEj2S1WiFUqJwJZf1TOrxTirbyFxTidbtKZNP6p3BwPoCgKrVt3U9fYimHoXDl3gmgoREVVHVt370fVNLNLFMtA0zTKqmrZ+eAjNLa2oaoa6SV+02C12Th24lSWKxRidTI9kE3MhEhoHglkQryFoig3+rImR3Nv2/I6RVHYsHk7ja1bKauqQ9fTOFx5YNKxT2JlebwFwP2t5I5OTGWzJCFWLdMD2bmrQyhWp0zoF+Idrm9bzvonSCbiJldza4qi0NS6habWLeQXFDHQ005f5+WcGGwrlldZZS2aqhEM+Dn/5tGbjsa4LcMgHJ1fnuKEWGVMD2SX+yZQrE5KfPKEpRBv5fbkk+8txDCMnDhK6U7qmzfR0rYTgMHeq/S0X5BQtsZ5vD527j+M1WojFFwcdZKIx+7+AooCqpV4PHe/4RBipZgeyLpHZ7HZHTjsS2sKFWItu75tOTE6aG4hd6m2sYWNW3cDMDzQzZVzb5JOpUyuSiwnX2Exu/Y/it3uIBoJcfqNlwnO3P2TkwXFpfT19S1jhUKsDqYHsoHpeZxO6R8T4mbKKmtRFIVIKMD83PIe25Qt1fUb2Lx9H4qiMDU+zMnXfkQ4OGt2WWIZebw+9jz0OC63h3hsgXMnjtDTcRH92pyy2yksLqO7u3sFqhQit5keyCbmFFwOWR0T4mbsDgdFJYuDYadycCbZrVTWNrDnwGM4nW5iC3OcOfZjhvq60HPo5AGRXU53HvsOPUllTQMGBkN9nZx6/SWi4dBt3+fK89DZJYFMCFMDma4bhPQ88p0yf0yIW7ne3D8xOrSqerK8hcXse/g9lFZUE1uYp6/zEuffPEo8tmB2aWKZWKxWNu/Yx/a9B7HZHMxFw5x+/SUGe6/e9hiw/sHcObdVCLOYGsj6RqbIWFwUeOSMOyFupbi8CotmIbYwt+q2/qw2G207HkBVVMaG+pkcHeLNIy8wMTq4qsKluDcl5VU8ePgpSsqq0A2d3quXOHfiCLH5uZu+fsofWOEKhcg9pgays53DiyMvvG4zyxAip1ksFkoqqoHcnkl2KzNT49gcDqpqGykuqySdTtF+/iRXzp4glUyYXZ5YJja7g217H2Lz9r1YNAvBgJ+TR19kfHjgHWHcYC4mvw+EMDWQtQ9MoVqdFMrICyFu6/q25dT48F01SueS0cFeYHEsxr5DT9DUumWx4X9ihDePvMBMjp5EIO6foihU1jbywCNP4SssIZ1J03HxFJdOH3vLbD0Fq8NFKBQys1QhTGdqIOsdD2J3OLDKEStC3FZhcSl2h5NUKsnYtYO8V4NoOEQw4L/xD7OiqjS0tLH34BO43B7moxFee/GfZTzGGud057F7/2E2bNqGqqj4p8Z488iL+CcXw3hRSRk9PT0mVymEuUwNZEMzMRl5IVavm/VAGQaKrqOl0yhZfKJQUVUamjcDMNjTseSzA1fa9dWx0vJqHM6fnMaR7ytk38PvQdd1opEAfZ2XOfnaj5iZGpfesjVKUVXqN2xi76EnyPN4SSbjXDz9OlcvnsbjLaCrq8vsEoUwlcXMm0/FLBQ45AlLsfoous4HX/hHbOkUQ1V1zLvzKAgFqB8ZRMtkUDAIegv47tMfztq5jpU1DQz1dRFbmGN0sIf6DZuyct3lkkommbw2qqO6fsO7Pm+xWNiy60EunztBbH6O2MIcF069TmFxGS1tO8nL9650yWIFeLwF7D30JP2dlxnu72ZsuJ+5aJhi+z0euyTEGmPaClkylSaKh3yXzCATq49iGBREQtSNDrHv4ikOH3+VHe0XsCfjqIaOe2GewlAA272e7XcbqqbR2NIGwFBv572fG7jCJkYHyWTS5Hm8+IpKbvqasqo6HE4X+QVFlFfWoqoagZkpTh59kc5LZ3L6DE+xdJqm0dy2g13Xjl1KxGP09K2erXghloNpgexyzwiG1UWBR7Ysxeo1U1jEZEk5UyVlTJaWE873Ec3zEHM4SFmspKzZXQEur6rFnZdPKpVkuD93t3gMw7ixXVld34xyi1VCu8NBcWkFqqricLrYf/hpSiuqMTAYHerj+Cs/ZLD3KplV9iCDuDsFxaXs2HeIfYeeZG4ht7/BEGK5mRbIznePolgdFPlk5IVYfbRMBsUwMG4WNAwDV2yBsfIqDDW7f8QUVaVp41YAhvq6bjRF55qAf4qF+SgWi/XGeZy3UlHTAMDE2BAOp4ttex5i94HHyPcWkk6n6L16iTePvMDU+Ij0l61B3sJibHY7sURafn3FumZaILs65EezOinw5JlVghBLZk8mUHWdjPruJ4TzoxFiThcdrW3Lcu+S8ipKK6rR9QyXzrzB1PjIstznfowOLj4xV1FTj8Vy+1bV4tKKG9tWgZkpAAqKSth76AnadjyA3eEktjDH5bPHOXv8VSIhGSK69ii4831MTk6aXYgQpjEtkPVPhHE6HKhqdhqehVhJ9mQCLZO+eSCbj5Kw2Ql5lqcpXVEUtuzaT3llLYZhcOXsCSZGBpflXksRW5hnZmoCWNyuvBNV026soo2/5etQFIWKmnr2P/oMjS1taKpGKODn1Osv0X7+pBzBtMYUlZTL6AuxrpkWyMZCCRwy8kKsUs54DEsmQ+YmM/QC3gJ84RCf+Ke/5pmXv0/1MqxgqapK284Hbhzk3HHhFGNDfVm/z1KMDfZiYFBYXIY77+6GPlde27b0T46962EFi8VCY+sW9j/2DBXV9cDiAwMnXvkh/V1XVs0IEHF7rjwPvb29ZpchhGlMC2TzaRWrRVbHxOrkXphD1XX0mwSyBZcbf2Exqq6zuaeDDQPL812/oqps2r6XmvpmDAyuXjrDcH/3stzrbmUymRuDa2sa7rw6dp3HW4An34euZ5gav/lB0w6ni7adD7Dv0JP4CkvI6Bn6u9s58eoPmRiRszFXO6vVRiQSMbsMIUxj3tgLXcOS5YZnIVZK3vz8bT+fsVhwJBKMl1VyZvveZatDURRatuykrmkjAN3t5xnsubps97uTqfFhUqkkDqeL4tKKe3rv9eb+8ZGB274u31fI7gOPsm33AZyuPBLxGO0XTnL69ZcJzvqXXLswz8zUBMlEnEgkanYpQpjG3ECmyQqZWJ2sqSRa5tZbZXlzUVIWK2/sO8jcXW7bLZWiKGzYtI3Gli0A9HZeovvKeVPOvBwduDbqom4Dyj1+w1VeVYuiKERCAeaj4du+VlEUSitrePDw02zYtA2LxUokHODs8Ve4dOYYsfm5JX8NYmXpus6Vcyc49soPGBvPzaeGhVgJpgWylGKVMyzFqpWw29FV7e3HIxkGjniMwuAsheEA/XWNDF/reVpuiqLQ2NrGhk3bABge6Ob0Gy8zF7l9sMmmcHCWSDiAqmpU1jbc8/ttdgfFpZXA25v7b0fTNOo3bOLAY89QXdeEgsL0xCgnjrxAT8dF0imZbZXrZqbGSadT2GwOVM3Uw2OEMJVpgSxtaFgtsmUpVod39id1N7YS9njxRcK4FuYpmZmm3D+FMx4nUFDE0QcPc2bb8m1V3kr9hk1s33sQm81ONBLi1OsvMdzXtSL9VdcHwZZV1mCzO5Z0jYqaegAmRwcx7uEsUJvdwcZte3jgkfdQWFyGrmcY6uvk+CvPMzrYd0/XEitHz2TovXoJgMraBmIxOZlBrF+mfDuyEE+iq1ZsEsjEKlBa5KU/FGXC1oQzMYfdiDPvzuPS5m3sP3sCPa0yUlXLQG0jY2WVhLwFWR8Iey9KyqvI9xVx9eJpZqbH6e64wMz0BJt37HvbAd/ZlEzEb8xDu9m5lXeruKwSm81BIhFn1j9Fcdm99aHl5fvY+eAjzE5P0tNxgfm5CJ2XzzA62EPz5h0UlZYvuTaRfaNDfSzMR7HZHNRv2MR0/yWzSxLCNKYEsmB4DkXVsFpky1LkPm+em70brFwY1LiseNiQvIgv4+fKxq1E8/KZLi4lskwzx5bK7nCwfd9Bxob66em4cON8yNatuymvqs36/caHB9D1DPneQrwFRUu+jqqqlFfVMjzQzcTIwD0HMljcvi0uq6CwpIyxoT76u64wFw1z/uRRiksraN68HXeO/XqtR6lkgoHudgCaNm7BYrUSTyRMrkoI85jybfxsZB4UDZtVAplYHQrdNg5uLMLqq6LDsZ8RazMJq53ehuacC2PXKYpCdX0T+x5+D/m+QlKpJFfOneDKuTezejC5oeuMDl0/t3Lpq2PXXX/a0j81Tiq59H+gVVWlpqGZA489S21jK4qiMDM9wZtHX6Tz8lmS8o+/qfq720mlkuR5vDfm0CVTMlNOrF+mBLJQdAFF1bBZpYFTrB42TWVfo4+ailIGHTvoduwjqdjMLuuO3Hke9jz0OI0tbSiKwuTYECePvkjAP5WV689MTxCPLWC12ijLwuqbx+vDk1+ArmeYHLv5TLJ7YbXZaGnbwf7D76WkrOrGwecnXv0hw31dpjyNut7Nz0Vv9By2tO248USuBDKxnpkSyIKRBVA17BLIxCqjKLCh3IXHkmJaqyasld7X9RzWGB/b/S0c1liWKrw5VVVpbN3Cnocex+X2EI8vcO7NI3S3XyBzn4Fk5Nrg26raRrQsPTldea25P5tHQrnyPGzfd5Bd+w/jyfeRSiXp7rjAm0dfZHpiVAbLrpB0Kkn7uRMYhkFJWSWFJdf6+gyDTEYevhDrlymBLDwfu7ZlKYFMrD7BUIRoUsGlhylI399hyDtrzvPQhuPsqLmQneLuwFtQxL6H30NVbRMAw/1dnH79JaLh0JKuNz8XJTAzhYJCVRa2K68rq6pDVVQi4QCRUDBr1wUoLC5j36En2bx9L3a7g4X5KJfOHOPciSNEw9m9l3i7dDrNhZOvEwkHsdkcNLft/MknFcjI07BiHTMnkM3FUVQNh00CmVh9AuE5dEWjKtWHhfvbYtl+LYjtqDmfhcrujsViYdP2PWzfewibzcFcNMzpN15mqLfznleJRgcXV8eKyypwutxZq9Fmt1NaUQ1AT/v5rK9eKapKZW0j+x99hobmzWiqRnB2mlOvvUTHhVMk4su7YrkeZTIZLp1+g1BwBqvVxs4HH8blznvLKxQMZFi4WL9MCWSR+fjilqUt9/tvhHinkqICDEMhdZ/9Y07rAs2li4GmubQHp3UhG+XdtZLySh48/BQlZZXoeoaeqxc5d+II8YXbHwt1XTqdvrGlmI1m/nfasGkbmmYhGPAzOTaU9esDWKxWmjZuZf+j76W8shYDg/GRAU688kMGujvueztXLNJ1nStnjxOYmcKiWdix7xAeb8HbXqMAqmYhIQ9biHXKlEAWXUiiqBqaJnPIxOrjzXPhc6lMWJtIKEsbgAqwpeoKirK48qOqBm1VV7JV4l2z2R1s23uQTdv2YNEsBGenefPoi0yM3vmw7snRIdLpFC635yd9QFnkcLmpb94EQO8yT913uNxs2b2fvQ89jregiHQmTV/XZU688kMmR4ekv+w+GLpO+/mT+KfG0VSN7fsO4S0svulrbXY7c3Ny7JVYn8wJZLEkmqqiKrI8LVanzTVe4loeg7YtZFhaI/uOmvPoxuKfgYyurFgf2TspikJV3eJ4DK+viHQ6Rfv5k9fGY9x8tWLxScXF1b3q+g0oy/Rnua6xFbfbQyIRp7+rfVnu8VbewmL2PPQ4W3btx+FwEY8vcOX8m5x548eEAzPLfv+1Jr4wz6Uzx5kaH0ZVVLbueYiC4ps/CGMAVpudaFQOGBfrkylNXHPxlKyOiVUt3+Vke63BxeHF+UkbEufRePf2VoFrlp996M+xW94dbIrzZlDVxZUXTTXYVH6VX3vv777rdYm0nT8/9rMEF5Y+cPVuuPI87HnoMQZ6rjLQ087U+DChgJ+2HfvetQIWCswwFw2jaRYqlvG8TlXTaNmyi/MnjzIy2ENlbQN5+b5lux8sBtTyqlpKyqsY7u9iqOcq4dAsp4/9mPLKWpo2bctqv9xalE6lGOy9ynB/N7qeQVEUtux68I6Dfm02h6yQiXXLlEA2H09l7fF4IcxSXrB4DNHtQtlC0o2BQmm+/47XU1Xjpq8bnq1hIbkyAUBRVRpb2ygqLaf9/EkW5qOce/MotQ0tNG3aduPP7ei1URflVXVYl7kXtKi0nNLyaqYnR+m6fI5dBx5dthW5t9I0jYbmzVTWNNLXeYmJkUEmx4fxT45R09hC/YZNWKzWZa9jNTF0nbHhAfq7rpBMLp5LWVBUSvPm7eT7Cu/4frvDIStkYt0yKZCl0RwSyMTqd6dQlkg7+OOXv8zTW17giU0vYRjKjVWx29F1BUUxePnqk7xw5Wl0Y2X/vFwfj9HbcYHRoT6GB7qZ9U+yZdeDWG12pidHgeVp5r+ZlrYdzE5P3GjwX85VuXeyOxxs3rGPmoZmetovEJidZrD3KhMjAzS2bqWypv7GYNP1bHZ6gu72xfNDAdxuDxs2b6e4rPKuA7TNLoFMrF+mBLJ4Skd1y8gLsTbcKZTphsYPLz9Lz1QzP7P/L3HZFtDUW89byugqC0kXf3niM/ROtyxv8bdhsVjYuG0PxWWVdFw4zfxchNOvv4wrz4Ou6xQWleLx+lakFofLTX3LZvo6L9PbcZGSskos1pV9StvjLWDn/sPMTI3T03GRhfkoVy+dZmSge90eXJ5Opwn4Jxkb6mPWvziTz2q10di6haq6JtR7DKqqqslTlmLdMiUVWTUVQwYAijXkeii7NNxISrFRlerBl/G/bapSz3QL//mFX+VzB/6cppI+brZoYBgwMNPAXxz7WeaTee9+gQmKyxbHY1y9eAb/5Bj93e14vAUrtjp2XV1jKxMjgyzMR+nvaqdly847vynLFEWhpLyKopJyRq8dXD4+3E88voCvoITmth248zwrXtdKSsTjzEyNMTM1TsA/RUZf/OZDVTVq6jdQ37x5ydvYyURc2lnEumVKIHPbNTIZObNMrC3lBS7cTjtXJ/K4GinHm5qk8h3BbD6RRySWj26oaMq7vynRDZVwzJszYey6xfEYDzExMkCZv4bisipKyqtWtAZV02jdspPzJ19jZLCHipqGFVuhu1kttY0t6HqGWf8kowO9pJNJZv0T1Da00NCyecVX8LLFMAwy6RSJeIxEPE4iESMRj5GMxwkHZwmHZt/2eqcrj5KySmoamnG67+/3bSIRw+NZ24FWiFsxJZC5HBYyCzJwUaw9HofGvgYP4ZiLrknfu4KZRU2zperK27YsdV15y9OW+rXPp8noubWtrygKlbWNVNY2mlZDUWnFjQb/S6ffYM/BJ7A7lj4L7n5k0mlG+nvwFhSxbc9DzEcjzEyPM9TfxcToEE0bt1BZ03Cjv8wwjMUfuo5h6Oi6ga5n3vUxw9AxdB3dMDD0zE0+dv21b/+Yfu3jd3rdjY9df9/19+g6mUyGZDx2Y9XrVvJ9hZSUV1FSVoXbk5+1hyySiTh5ebn1zYgQK8WUv/HzHFYyUQlkYu3yOm8ezN5b/HfYLCkAdANUBUaD1dQWjdz4b7slSWtZFx0TbSZ/Fblp47bdzEVCLCzMceHka+w+8KgpTzuODPaQSMRwOt00tW5B1TRmpiboaT/P/HyUq5fOcOLV53F7vNjtDnRjdbVpWCxW7A7n4g+7A7vDiSvPQ1FpBXaHM+v3U4BUMikrZGLdMiWQeZw2OURWrAvvDGbNdcMYxuLWZCpj4W9PfZKLozvYUXOej+/9GyxaGlXR2VZ9UQLZLdjsDnY8+Ahn3vgx0UiQS2eOsWPfIdQV7D1KJZMM9XYC0HgtjMHimZ6FJWWMDvYyOtDD+HA/83MRnE43+QVF7wqOiqKgKiqKqi7+b1VFufbfqqIs/vzWj93mdYpy7fPv+JiiLt7j+udufEzV3vFeBVWzYLM7sNsdaJYV/udBkRUysb6Zs0LmtKFndDIZXQbEinXB69R4sMHB4+UvoChwNbSN/3T6G7jCM7iJcmFkJ0OztXz2wDepKxpmW/UlvnXmp1d83MVq4XLnseOBQ5w7/iqBmSmuXjzN5p0PrMh8MoChvk5SqSR5Hi/lVbVv+5yqqtQ2tlBWVUtevo+J0UEAFFWhsqaBxpY2bHbHjRAmrjEglUzICplYt0xJQ163HYwM8VTKjNsLYQq36kdTMrwS+U3+dOYEg5aDXHYcYsLSgAEEF4r4kx//G37U/h40NUOeXSaW306+r5Ctew6gKAoTY0P0Xb20IvdNxOOMXBuM29i65ZYzyOzXHoQ4+MT7KK+qRVU1xkcGOPnajxgd7JUnzd/BYHHl0eVymV2KEKYwZ8vS7cDQkySTKdwOuxklCLHionolvzURwUDD64IDLXY6J2z0+l2EkyU0JC9jN2I8f+UZXmh/GsOQ1eM7KSqtYNO2vXRcPMVgXyd2p4uahuZlvedATzuZTBqvr+iunjR1e7xs33eIgH+Sno6LRCMhujsuMDrYy4bN2ykpr5KVMgAMFAX5/0KsW6b8je/Lc4KeIZ6S0RdifTHechC5pii0Veaxq6mEoLuZS45DzGiVGCBh7B5U1jbQtHErAN1XzjM1PrJs94rNzzE+1A9A06at9xQeCkvK2XfoSTZv34vd7mBhYY5LZ45x7virREKB5Sp5FVHQVAljYv0y5W/9Ao8LjAzJpAQyIYrybBxqLcJdXEWnYx/99u2kkDMS70X9hk1U12/AwODK2RP0d11Zli3B/u52dEOnsLiMwuKye36/oqpU1jay/9FnaGjejKZqBAN+Tr3+Eu3nTxKPLWS95tXEapGeSbF+mbJl6fM4MfQMybSMvhACwKIp7KrLZzzfxtUxJxG1kMbEJbz67J3fLFAUhda2neiZDOMjA/R3tzPrn6Rt54O47nNY6XVzkTCTo0MAbNi07b6uZbFaadq4laq6Jvo6LzMxOsjE6CDT4yPUNm2kbsNGLCv9lGMOsFrX39csxHWmrJAVevNAlxUyId6pssDBwdZiFF8t7c6HGLZtJIOsGtwNRVXZvGMfW3btx2KxEg7Ocuroi4yPDGAYdz7Q/U76Oi9jYFBaUU2+rzALFYPD6aJt5wPsO/QkBYUlZPQMAz3tnHjlB4wP96+7xn+7CfPkhMgV5mxZ5rsXA1lGVsiEeCe7VeWBRh/1VWUMObbT4djPvCqjAO5WeVUtDzzyFAWFJaQzaTounOLKuTdJJZNLvmY4MIN/agwFhabWLVmsdlG+r5BdBx5l256HcLrySCTidFw8zanXXyLgn8r6/XKVw7E6j5sSIhtMCWT5bicYGVKp9fXdnxB3S1GgsdTFgy3FxD0NbxuPIe7M6XKza/9hmjYuNt5PjQ9z8uiLBGem7/lahmHQ23kZgIqaetweb7bLBRa3XUsrqtl/+GlaNu/AYrESjYQ49+YRLp56nfloZFnum0ucJh2DJUQuMCWQqaqCxUiRkh4yIW7L47BwoKWAkvIKep276XLsY05dnkCw1iiqSkPzZvY89Dgut4d4fIFzJ47Q23ER/R5W5wP+KYKz06iqRmPL8p+eoGoatU2tHHjsWWrqm1EUBf/UOG8efYGuy+dIJhLLXoNZXK7sH8kkxGph2rP1FlKkMrJCJsSd/GQ8Rinzvk1ccj5Cj32XBLO75C0oYt/D76GypgEDg8G+Ts4c+/FdrTgZhkHftdWx6romHC73cpd7g81up3XrLh585GlKyioxDIORwR6Ov/IDhvq67ilUrhZuCWRiHTMtkNmUDGkJZELctaI8KweafGxuqiZSsFWC2T2wWCxs3rGPbXsewmq1EQkHOfnaj+jvukLmNsHGPzFKJBzAolmob960ghX/hNuTz/Z9h9j14GE8+T7S6RQ9HRc4ceQFpsdHsvLAQi7QdV2OTRLrmmnPGNvUDKnM2viLRIiVoihQnm+lzONjKuqmb7oAf7SakvQoFak+8vSw2SXmtOtPSF69eJpZ/yT93e1Mjg7RunUXRaUVb3utoes3Vsdqm1qx2c3tbyosKWPfoSeZGB2ir/MysYU5Lp09jq+gmOa2HXgLikyt736lUyk8BXKwuFi/TAtkDk0ntc4e6RYiWySYLZ3D6WLHAw8zPTFKd/t5FhbmOH/yNUorqmlp24nDuXiW4sToIPPzUaxWG7WNrSZXvWhxsGwDpZU1DPd1MtTbSSg4w+k3Xqaiqo6mjVtXdFs1mxLxBTyecrPLEMI0pgWyErdGf2Lpj6ELISSYLZWiKJRV1lBUUk5/dzsjA91MT4wSmJ6kvmUzVXVN9He1A1DfvBlLjs3HslgsNLZuobK28SeDZceGmJ4YpbaplbqmjTlX850E/FPUPL7X7DKEMI1pgayhLI8Of8ys2wuxpkgwWxqL1UpL2w4qquvpunyWUHCG3quXuHrxDOlUEl9hCdX1G8wu85auD5ataWimp/0CwYCfgZ4Oxof7FwNbTQOKmvvnoioKBGanaWlpMbsUIUxj2p/UjTVFpBIJ5hbiZpUgxJpzPZhJ8/+98Xh97H7oMdp2PIDd7iCdShINB5mLhOnvusJcJGR2ibf11sGyrmuDZa9eOsPJ135EwD9pdnl3ZBgQCc5SX19vdilCmEYxTHpE58cnO/jE/xnk8UP7qK8oNqMEIdY8w4CpaIq+6XkS0aCsmAEYBg0jA8TsTmYLinDFFphz55G5dnZkOpViYnSAvs4rpFPJxZQLePILqKiuo6yqDnsODzDVMxlGh/oY6G4nlVpsCykuraB58/ZlG2qbDade+R7Hjr5sdhlCmMa0QBaMzNPy5RfZtXsPuzbWmlGCEOuGBLOfKAzO8uHnv4MtlSR+7clJXVUZqGlgvLyK8bJKFlxu9EyGmekJJkeHmJkaRzcWH0JSUCgsKaOipoGSskq0HD0EPJVMMNDdwchgD4ZhoCgKVXVNNLa0mf7E6M0MXnqDf/yHb5tdhhCmMS2QAdR+7ptUbj7Ao7ubzSpBiHVFghm09HXx1JEXmC0oxJGIY08kSFmtOOJxUGDB6WaksoY39h0idu2Jy1QywdT4CBOjg4SDszeuZbFYKa2opry6joKiUpRrq2m5ZH4uSm/HRfxTY8BizS1tO6msbTC5sp/QMxm0+TH+8L/+V7NLEcI0pn5rV2yLMxdPmVmCEOuKNP9DyezieZYpq42U1Ub02uircD4ouk5BOEj9yCCnd+y7EcisNjvV9Ruort/AwlyUidEhJkcHicXmGR8ZYHxkAIfDRXl1HRXVdTm1NejO87B930ECM1P0tF8kGgnScfEUqqZRXpUbuxPh0Cz726ShX6xvpgay6gIrV+LS1C/ESrtZMJuZq8Vu3PrJZ13XceshvEYQVzpEnh7CQnoFq84Cw6BqYoyEzXbzT6sqmq4zWVpBKN9309e48jw0bdxCY2sbocAMk6NDTI0PE48vMNh7lcHeq3jyfRQUl1FQVEpBUTEW683vt5IKi8vYd+gJutsvMDLYQ8f5k9hsdgpLyswujdnpSVo+/ITZZQhhKlMDWVO5l9PDcXTdQFVzb6lfiLXurcEsFPcRv83xiJlMhuB8Cn88STIRIxOfw50J4tNnceth3JkgNiNOLv9JtqZSeOaj17Yq4yRtNgzlLQ+bGwZaJkNfXdONZv5bURSFgqISCopKaNmyk5mpcSZHB5mZniAaCRGNhBju70JBweMroLColILiUryFJVhM6jtTVJWWLTtJJhNMjQ9z6cwxHjz89I1huKbUpEBQRl4IYW4g21RXQqY3RnhunoJ8OTJDCLMoChTc8VxnjWqvhmE4SGbyiSRKmJmrJriQYiqZIBOPYkuH8Wb85OthXJkQTmMupwJa2mKhs2kjDaMDuGILFIRDNz4et9nR9Awxh5ORynvbytM0jbLKGsoqa0gm4gRmpgnOTBOcnWZhPkokFCASCjDY14miKOT7Cim8toLmLSxG07Rl+GpvTlEU2nbsIzY/RyQcYHSwlw2btq3Y/d/JMAwWomEqKytNq0GIXGBqU/+pK/08+ycdPHJgL8015i+bCyGWJq1DJGkQmEsRnk8RTybJxOdQk9HFgEYYdzqIS4+gYv6RaYqu442EKQrOUBScpdw/SVFwFnsywVBVHc8/9swdV8juVjy2cCOcBWemicXm3/Z5VdXw+gopKC5dDGgFRagrENCmJ0a5dOYYVquNg0+839SnRc+/9kOO/PhF0+4vRC4wdYVsW3MNpM4SjMjEfiFWM4sKhQ6FQocNim3ohpu5ZAHBhTSBuXrGE0nSiQWMRBRPZhbftT40t0l9aIaqEvIVEPIV0New+JS3LZnAGwkv9o5l8WlJh9NFRU09FTX1AMTm526Es8DsNIl4jGDATzDgB9rRVA1vYfFi/1lxKfm+QtRlmLZfUlaJ3eEkEY8RCQUoKC7N+j3uVkVZiWn3FiJXmBrIHHYrHqJEFhJmliGEyDJVgXw75Nst1BVYMAwXCykf4XiGmbk6puJJUtf60PIyAbx6gDw9hCsTwm6Y86BP0mbHvwKhxOnOw+nOo7K2EcMwbgS069ucyWScwMwUgZkp6AKLZlkMaNdW0PK9BVk5DklRVVxuD4l4jHh8IQtf2dIYuk5TU+6M4BDCLKZPNCxzpAjFV9mTWkKIe6Io4LaB26ZRmb/Yh5a41oc2O1f1tj40eyqCV/fjMRa3OR3GfE71oWWToii48jy48jxU1TUt9lPNRRbD2bVVtFQqyax/ktlrRyBZLFZ8hSUUFi+uoOXl+5Y8/8zhWGwcTJr4tHskHGT3bmnoF8L0QFZb5GAiZt53Z0KIlaco4LCAw6JS6nYADlIZD9FkEbPzKcLzGwgkEot9aKnFPjSvEcaVud6HZlrr67JSFAW3x4vb46WmoRnDMJiLhG+Es+DsNOl0ipnpcWamxwGwWm34ikpuPMXp9njvOqDZrwWyRNy8tpHxkQFaPvGsafcXIleYHsiaKn0c7UqQzmSwrOCTRkKI3GLVoNCpUOhc7EPL6G7mU4UE5lME5xsYSyRJXetD82ZmbsxDc+vh1TcP7S4pioLH68Pj9VHb2IKh60QjoRvhLDTrJ5VK4p8cwz+5OInfZrPf6D8rKCrFlee5ZUC7HsjM3LIMzfppbpbTWoQwPZC11ZehX4kSCM9RWpg7062FEObS1Ot9aFbqC603+tBC8Qyz0TqmEot9aHo8ijsTwKcHcOsh3JkQNmNt9qUqqkq+r5B8XyF1GzZi6DqRcJDAzBTBmWnCgZnFGWMTI0xNjABgtzsX56VdC2hOd96NgGa/Nn8sbuIuRToRo7Cw0LT7C5ErTA9kOzfWYPzjWWbC8xLIhBC39NY+tKq39qHFS5iZqyEQSzKZTJCORXGkQ3j1mRvz0NZqH5qiqngLivAWFNHQvBk9kyESCtzY4gwFZ0kkYkyODzM5PgyAw+G6Ec4s104sSJgYyHxemUEpBORAIGutq0BNLcjoCyHEPbnRh5anUppnB+ykMh4iySICc0nCCykCiSTp+ByWVARvZob8Nd6HpmoavqISfEUlNLS0kclkCAdnCM74Cc5OEwnOEo8vMDE6yMToIHomg39yjMKSMjKZzIoOqIXFobDVFTKDUgjIgUCmaSoV1jAzUTnTUghxf6waFDkVipyLAS2jw1yqkOB8isB842IfWnweklG8mVnyjRDudAC3HkbjNudGrVKaplFYXEZh8WLoSafTRIIzN57iDAdnURSFPI+PRGweV17+itY3MzXOgb17VvSeQuQq0wMZwK56Dy8GonKmpRAiqzQVvHbwvrMPLfaTeWjJRAwjHqYq3U9ZcgArKbPLXjYWi4XCknIKS8oBSKdSHH3xH0kkYiSTSVbyREtFgaG+Tn79X39uBe8qRO7KiUD2nj1NfP+7YSZmQ1SVFJhdjhBijXpbH5rXiWE4SWS8jAS8jMwUMhGrpzrdR0lqaM0+uflWFquVfG8h4dAsycTK7lIYBkSDfjZt2rSi9xUiV2X/PI4lePbgdoiHGJ4Kml2KEGIdud6H1lzq5ODGYoor6xhw7+Wi8xGmrHUkFbvZJS47m33xa0wlV/bJVMMwaG2qX/JQWyHWmpxYIfO4HVRagkyHpLFfCGEOq6qwqcJFY6mT7ok8hufKGYhHcaZD+HQ/Hj1EXiaw5kZqWG2LgSyZWNmvyz85xiMPH1rRewqRy3IikIH0kQkhcoNdU9ha7Satu4nEi5iZSxFeSOJPxEnH1l5Ac7oXx05EQoEVu6eiwHB/F7/xpZ9dsXsKketyJpDd6CObCVFVKn1kQghzWVQodCkUumyAjbSeRzhexOwaC2hFJeX0dV4mODuNruuoWTi4/E6kf0yId8uZQPbswe186W//ieHpoAQyIUTOsahQ5FIoWmMBzeMtwGazk0wmCAdnKSgqWfZ7GobBxg0N0j8mxFvkTCBb7CMLSR+ZEGJVWCsBTVEUCovLmBwfZnZ6YkUCmfSPCfFuORPIAHbXe3hB+siEEKvQag5ohaXlTI4P458co2nj1mVduVIUGO7r4vC/+fyy3UOI1SinAtmTezbwve+GpI9MCLHqraaAVlJWhcViZX4ugn9ilNLKmmW7l2FANORn48aNy3YPIVajnApkzx7ctthHNiV9ZEKItSWXA5rVZqO2sYX+7nb6u9spqahetlWyxf4xmT8mxDvlVCDzuB1UWkNMh6WPTAixtuVaQKtpaGG4v5u5aHhZV8n8E6McfuSRZbm2EKtZTgUygN11Hl4IRKSPTAixrpgd0FZilUxRYKi/i6/+0heyel0h1oKcC2SLfWRBxmeCVJcWml2OEEKY4m4Dmjs9S1Wql4LMFPcbn966SjY5NkRFdX0WvpKfMAyYD83S2tqa1esKsRbkxFmWb/XswW0QDzEyFTK7FCGEyBnXA1pLqY299Xk82FzMluZalOJWrroO0u44QFArxbiPe1htNuqaFpvtu6+cJxHP7oHjhmGwsVn6x4S4mZwLZB63gyrpIxNCiNuyqFDs1thT72FvawVGUSsdroN0OPYTVouWfN26plY8+T5SqSRdl89iGPcT8d7OPzHKIw8/nLXrCbGW5FwgA9hdn084sthHJoQQ4vbyHRp7G/LZ3VJJ3NtMh2M/IbV4SddSNY3NO/ahKArTk6NMj49kpUYFGOrr4vDhw1m5nhBrTU4Gsqf3NZOaDzM4MWN2KUIIsWr4nBoPNnlR7B567TtIKI4lXcfjLaCheTMAnZfPZmXr0gCigSnpHxPiFnIykH340V04YhP0jM6aXYoQQqwqmqqyuyGfOa2APtt29CW2+tdv2JTVrcuFuQiPHT4o/WNC3EJOBjJNUzlYrzE9GyKVyZhdjhBCrCoel4Ot1Xn4LTWMW5uWdI1sb11ePvcmP/PpT9/XNYRYy3IykAF84dm9JKIz9AxNmV2KEEKsOlXF+ZR67QzbNhFRlzZCKJtbl8m5ADt37lzy+4VY63I2kD22bxMFqQn6JkJmlyKEEKtSW42XpGJn1Nq85GtkY+tydnqCD3/gfbJdKcRt5GwgA3jPZi+zgSCxeNLsUoQQYtVRFQXNyKAr2tKvkYWtyyvnT/LJT35yyTUIsR7kdCD74kcOkI5Oc3VwwuxShBBi3bqfrUvDMPA6NRoaGparPCHWhJwOZG1N1VRp0wxOR8wuRQgh1rWlbF0qisLoYC8//dzHVqBCIVa3nA5kAB/YXUkoECAUnTe7FCGEWLeWsnVpGAZdl8/y3HPPrUCFQqxuOR/IvvjRQxhzk3QMyNOWQghhpsWtyzbg7rYu9UyGptoKioqWfpSTEOtFzgeyimIfG91hRv2ybSmEEGar37DxrrYuFUWh5+olPvXJT6xwhUKsTjkfyACeO7SBaGiGiZmQ2aUIIcTqsQxjJu5269IwDIZ6rvC+970v6zUIsRatikD2+Q88hLYwydWhabNLEUKIVUPTVDRVIY0tq9e9m63LVDLBA7u24XQ6s3pvIdaqVRHI3E47u0oSTM5E0PX7O09NCCHWCwUFn0tjQfMs+aDxW7nd1qWiQMeFU3zqU5/K6j2FWMtWRSAD+OyTW4lFZhic8JtdihBCrBrlXjsp7ESXeHzSrdxu69IwYGZ8iMOHD2f1nkKsZasmkH308T04Y+N0jwbMLkUIIVaNQm8ehgIRLbuBDG69dTkfDfOeJw6jaUs/IUCI9WbVBDJNUznUYGV6NkQqkzG7HCGEWBUcdjtOzSColbMcDR8327q8fO5NPi3blULck1UTyAB+7gP7SEb9dA9Oml2KEEKsGsV5FuJqHguqJ+vXvtnWZWYhzPbt27N+LyHWslUVyB7e1UpRepLusaDZpQghxKpR5nWSVixZ7yO77vrWpd3hJBTw85EPvR9lGUZuCLGWrapABvC5h2sIzEwxOi29ZEIIcTe8+W4wIKwVL9s96jds5MFHnqa/6wo/93M/t2z3EWKtWnWB7Jc/9QTOuUHO98i2pRBC3A2rxYLHbhDSSsmwPI32mkUjGgny7FOPUVi4PCtxQqxlqy6Q2awWPrmvCL9/mumgHKckhBB3o9RjI6U4mFe9y3J9w4Azr7/Mv/3lX16W6wux1q26QAbw6597GktkkLNd42aXIoQQq0Kx10Va0ZZl/AXAXCTEQ/t2UFlZuSzXF2KtW5WBzON28KEtLqam/YSi82aXI4QQOS8/z4WGQUgrWZbrnzz6Il/5yleW5dpCrAerMpAB/Na/eBojPMSZzlGzSxFCiJynqio+p0JUKyKV5bMt47EFNjfXsWHDhqxeV4j1ZNUGspLCfN7TAGNTs8zH3n2wrRBCiLcry792jJJWkNXrnnztR/zqr/xKVq8pxHqzagMZwDe+8BSZ0IiskgkhxF0o8rnRUbLaR5ZKJqkozGPHjh1Zu6YQ69GqDmQNVSUcKF9geHKWeDJldjlCCJHTXE4HNlUnqJVl7Rils8df4Vd/RXrHhLhfqzqQAXzj80+QDIxyvmvE7FKEECKnKSgU5VmIqfnEFdd9X0/PpLGR4NChQ1moToj1bdUHsm3NNezwBekfn5VDx4UQ4g7KvA5S2IhmYdvywqk3+JV//++yUJUQYtUHMoCvfeYRYoExLnZLL5kQQtxOQb4bQ4GIWnRf1zEMnXhoive+971ZqkyI9W1NBLKDO5pptU/TMzqLrutmlyOEEDnLbrPhshjX+siWdgC4okD7+VP80pe/JIeIC5ElayKQAfzaxx9gPjDOlf4xs0sRQoicVuqxklRdzKv5S3q/rhtMD/fwsY99LMuVCbF+rZlA9uyh7dQoY3QOzaIb2Xp+SAgh1p6SfCcpxUpUvfc+MkVR6O24yC988eewWCzLUJ0Q69OaCWQAv/zBbUQDE3QPT5pdihBC5CxfvhvFMAhpxff8XsMw6L96ns9+9rPLUJkQ69eaCmSffPpBipPDXBnwyyqZEELcgqZpeB0Q1krIoN31+xRFYaivk89/9tPY7fZlrFCI9WdNBTJVVfj1j20jPDXCxW6ZSyaEELdS6rGSUhxE1bs/RknXM3SeP84Xv/jFZaxMiPVpTQUygE8/s5/N9jHaB6aIxRNmlyOEEDmp2Ocmo2j3NI/szBuv8Du/9TXcbvcyVibE+rTmAhnAn/7SsyT9vbxxedDsUoQQIid53E40dIJa6V29Pr4wh9uS5iMf+cgyVybE+rQmA9nmxio+1qYxOjbBuD9odjlCCJFzFEWl0KUyrxWQVO7cD3bk+e/wJ3/8RzJ3TIhlsiYDGcAf/OsP4Yr2cqJ9RBr8hRDiJsq8NpLYbjv+QlEURgd7+eCz76G1tXUFqxNifVmzgczlsPFbz20mNDXCxR5p8BdCiHcq8uZhoBC5TR+ZrmdoP/MaX/3N31zByoRYf9ZsIAP4zLMH2GQfo71/ilg8aXY5QgiRUxwOOw5VJ6iVc6t9hDNvvMJvf/2r0sgvxDJb04EM4E+//AxJfx/HLg+YXYoQQuQUBYUij4W4mkdMyXvX5+ML87gtaT760Y+aUJ0Q68uaD2RtTdV8rE1lZGxSGvyFEOIdSr2OxWOUbrJteeT5f5BGfiFWyJoPZHC9wb9HGvyFEOIdCr2LK2NhrejGxxRFYWxIGvmFWEnrIpC5HDa+/jFp8BdCiHeyWqy4rQYhrRT92j8Jup7hyilp5BdiJa2LQAbw2fcdYKN9XBr8hRDiHUo8VpKKk3nVC8CZY6/w278ljfxCrKR1E8gA/uzL75UGfyGEeIdSr4s0ViJa4WIjv5qSRn4hVti6CmRtTdV8dLMiDf5CCPEW+R4XqqITUks48vx3+GNp5Bdixa2rQAbwX770YWnwF0KIt9BUjXy7wVTCxjPPvJeNGzeaXZIQ6866C2Quh42vfXQToWlp8BdCCADdMJiajRAcuMhXf/1XzC5HiHVp3QUygM+9/yE228e53DvObDhqdjlCCGGqc53DzIwP8e+ersGX/+4BsUKI5bcuAxnAX3/1Y1hm2nnlXD/pTMbscoQQwhTj/iBX+kbZmz/Blz7+uNnlCLFurdtAVllSwJ/87C4i470cPd9ndjlCCLHi4skUr10cJC/Uwf/92ifMLkeIdW3dBjKADx7eycfbdAaHR+gcnDC7HCGEWFGvnu1lYaKLP//SI/g8LrPLEWJdW9eBDOC/ffmjNOi9nL46TCgyb3Y5QgixIs53DTM+OsQvHPRwcGeL2eUIse6t+0CmaSrf/tpHUfwd/PhcH7qum12SEEIsq+lAmEs9o2xzjPKbn3/G7HKEEEggA6C2opg/+GQboYk+Xrso/WRCiLUrlU7z6vkBHMEO/vbrP42qygBYIXKBBLJrPv7UPj7YFKd/cJSekSmzyxFCiGXxytle5ie6+Z//aj/FBR6zyxFCXCOB7C3+9N//FFXJbk62DxOZj5ldjhBCZNXl3lFGR4b5/B4bTz7YZnY5Qoi3kED2FlaLxt/9xgfRpzv48ZledF2OVhJCrA0zoSjnu0bZaBnid7/4QbPLEUK8gwSyd2iuK+c/PtfM7Hg/xy9LP5kQYvVLZTK8eq4fy2w7f/f156RvTIgcJIHsJj77vgM8XROlZ2CMgXG/2eUIIcR9OXqul8hED3/6hT1UFPvMLkcIcRMSyG7hf//6xymNdXL88hDzsbjZ5QghxJJ0DIwzNDLCp7YqPHtou9nlCCFuQQLZLdisFv7m154lPXWVl8/0ohvSTyaEWF2CkTnOdI7QZPTxX//NR8wuRwhxGxLIbqOtqZqvvb8G//gAJ9sHzC5HCCHuWiaj8+Oz/Wj+Dr799Y9J35gQOU4C2R38q48d5nBpgM6+UbqHJ80uRwgh7kg3DF4+201oopc//JmtVJcVmV2SEOIOJJDdhf/vq5+kLnmVE5cHGJ6aNbscIYS4rTcu9DE60Me/3GPhY0/sMbscIcRdkEB2Fxx2Ky/8/qcpCF/i6Lk+pgMRs0sSQoibOn11kJ7+AT7QEOE/fPEDZpcjhLhLEsjuUkG+m+f/w0exzVzi5TM9hOcWzC5JCCHepr1vjMtdg+zPH+H/+ZWPm12OEOIeSCC7B7UVxXz3N55Cn7zECye7icUTZpckhBAA9I1Oc7pjgFZ6+Pv/8Flp4hdilZFAdo+2NdfwV1/aT2zsMj882UUqnTa7JCHEOjfuD3LsUj/lC+08//ufwWrRzC5JCHGPJJAtwSO7N/Inn95IeOQqL5zsRtd1s0sSQqxTs6Eor5ztIy9wiRd+7+O4nXazSxJCLIEEsiV67sm9fP2ZUqaHunjpdLcMjhVCrLi5hRg/Ot2DOn2RH/z2Bykr8ppdkhBiiSSQ3Yeff+5R/tU+CyODvbxxodfscoQQ60g8keL5N7tJTlzm77/yGBtqyswuSQhxHySQ3aff/pfv5yONc/T0DXCqY9DscoQQ60A6k+H5k13MjbXzv39uF3vbGswuSQhxnySQZcGffeWnecg3xpWuQa70jpldjhBiDdN1gxdPdhEY6eT3n6vnvQ9tNbskIUQWSCDLAlVV+NbvfIZNSjdnrg7QNzpldklCiDXqlbPdTAz18JXH8vnMswfMLkcIkSUSyLLEatH4we9/loqFdo5dGmBsOmh2SUKINebYxT6GBvr43LYM/+7T7zG7HCFEFkkgyyK3086L/+kTeIKXePVcLzOhqNklCSHWiHOdw3T2DfBUZYA/+NJHzC5HCJFlEsiyrKQwnx/89ofQpi/yo9M9EsqEEPftYs8oFzsH2O0Y4ptf/ZTZ5QghloEEsmXQVF3KP/7akygT53jhZJdsXwohluzNKwOcvdJNm9bNP/0nORJJiLVKMQyZaLpc+kanefZr3yVasI2HtjXQVC1zgoQQd0c3DI6e66W/v49HS6b569/6NJom30MLsVZJIFtm/kCEp37tb5hwtrFnUwNbNlSZXZIQIsdlMjo/OtXF2FAvn9gY50/+7XNmlySEWGYSyFbAfCzBs1/5JleNFra01rNvc73ZJQkhclQyleb5NzvxD3fx5YNOfuPzz5hdkhBiBUggWyGZjM7HfvObHAtVsaGpkUM7mlAV6QURQvzEfCzB8292ERnt4Hc/VMUXPnTI7JKEECtEAtkK0nWDn/+Dv+M7fXlU12/gyb0tqKr0hAghIBSZ58VT3cTHL/NnP7uVDx7eaXZJQogVJIHMBF/7n9/jf5xKU1LXwnsfaMVqsZhdkhDCRFOzIX58tg9j8hJ/+8sHObC92eyShBArTAKZSf7020f4xg+n8NZs4pkHWnE67GaXJIQwwdCEn9cu9OOcucg/fe1ZNjfKgz9CrEcSyEz07ZdO86W/6sRZtZWnH2jBm+cyuyQhxArqHJzgzSv9lESv8MLv/RSVJQVmlySEMIkEMpMdPdvJp//4BGrFNp7Y20xpQb7ZJQkhVsC5rmEudg7SmL7KC3/wGfLdTrNLEkKYSAJZDrjUM8KHfvdFksXbeGRXE7VlRWaXJIRYRscv9XG1d4DdzmH+6fc+g80qfaRCrHcSyHLE8MQM7/3NfyCYv5X92xppqS03uyQhRJbpusErZ3sYGujl6aoAf/Gbn5KjkIQQgASynBKMzPP0V/6KIdsmNjZW88CWBplVJsQaMR9L8PLZXvwjPXxum84ffOkjZpckhMghEshyTDyR4md+5685MlVISVUDT+zZgNvpMLssIcR9GByf4fiVIZKTHXz1fTX8/HOHzS5JCJFjJJDlqP/x90f47e+NYCnbxP4tdTRWlZhdkhDiHum6wfHL/fQMjFIS6+RvfvVZtmyoNrssIUQOkkCWw9r7RvnE7/2AaedGmhuqOLC1SfpNhFglIgsxfnymj9mxfp6qCfO/fvXjOOxWs8sSQuQoCWQ5LplK84Xf+1ueH/ZQVNnI43uayHfLvDIhclnvyBQn24dJT3fwux9t4mc/cNDskoQQOU4C2Srxze8f59e/3YNaupkH2mpprikzuyQhxDvous7rF/vpGxyhMtnNt37jgzTXyRPTQog7k0C2ivSOTPFTv/NdxmwtNNZV8/COJjmcXIgcEYrO8+Nz/YTG+/hAY4w/+8pPYbVoZpclhFglJJCtMql0hl/4g2/x3T4HvoomHt/VhC/fbXZZQqxrnUMTnO4YAX87/+WTm/n4Uw+YXZIQYpWRQLZKfetHp/i3f9WOUbqZvZtq2VhfYXZJQqw76UyG1y70MTA0Qn2ml2997aPUVxabXZYQYhWSQLaKDY7P8NO/8w8MqBuoq63h8M4mLJpskQixEgLhKD8+N0Bkopef3pThj37po2iatBAIIZZGAtkql8no/PIff4e/uaKQX7mBx3Y2UuTzmF2WEGtae98YZ7tGsMx08Mef28GHHt1ldklCiFVOAtka8b2jF/jF/3OWdHEbW5sq2d5SI8cuCZFlsXiS1y71MzoyQrMywLd/6zkqSwrMLksIsQZIIFtDxv1BPvk7f09HvBJfWQ3722rkHwshskA3DC72jNDeP0XS38dndtn4z7/4YRnULITIGglka9A3v3+cb/x9BwueZmqqynloawNOh83ssoRYlcb9QU60jxCaGmGjfZw/+/J7aWuS44+EENklgWyNmo8l+Pf//bv8Q4eBraSJtsYytjfLNqYQdysWT/DG5UFGxyZwRXv5+sc289n3HTC7LCHEGiWBbI1r7xvli3/0PJ0J2cYU4m7ohsHF7hHaB6ZI+nt5rk3j9//1h3DJKrMQYhlJIFsnfrKNuYHqqgoObq3H6bCbXZYQOeUn25PDbLaP86e/9CybG6vMLksIsQ5IIFtHFuJJvvLfv8u32zPYSjbQ1lAmT2MKwdu3J93RHr7+XBufeVa2J4UQK0cC2TrU0T/Gz/+3H9CRqMRXVsuDbTVUyTamWId0w+BC9wgdsj0phDCZBLJ17C9/cJxvfLudeU8z1ZUVHNwm25hi/RjzBzlxZYTwtGxPCiHMJ4FsnXvnNubmhjJ2yDamWMNi8QRvXBpkdHxxe/IbP7WFTz+z3+yyhBDrnAQyAbx9G9NbWsOWxlJaasslmIk1I55Mcb5rhL6xGZL+Xn5qi5X//IsflO1JIUROkEAm3uavfniC//gPl5mx1uAprGBjXRFbGqtQVTk0WaxO87E4ZzpHGZ6cJRkYZYcvyB/94ntle1IIkVMkkIl30XWDv3nhJH/4TxcZNqpwF1bSXF3E9pZqrJpmdnlC3JVQdJ4znaOMTc2SCY1woHyBb3z+CbY115hdmhBCvIsEMnFbP3j9Ir/3tyfpSpTiLKymobKQXS01OOxWs0sT4qamgxHOdo0zNe2H8DBPNhh84wtP0VBVYnZpQghxSxLIxF1540IPv/2XR7kQKsBaWE1deRF7NlbjdjrMLk0IAEanA5zvmcTv92OJDPKhLU6+9vmnKCvyml2aEELckQQycU+u9I7ytf/zMscmnGi+GqrKitjTWo0v3212aWKd6hub5lLfNIGZKZxzQ3xyXyG/9rmnyHc7zS5NCCHumgQysSSD4zN8/X+9wIv9oHjrKCstYXdLJaWF+WaXJtYB3TDoGpygfWiG8Mwk3vgQ/+KRGn75U09gs1rMLk8IIe6ZBDJxX/yBCN/43y/wj1cWSOfXU1JSys7mcqpLC80uTaxBmYzO5f4xuoZnmJudoCQ9wi883cq//MjDaJo8CSyEWL0kkImsiM7H+Y9/8QJ/fWqWWF49hcVltFQV0FJXjtUiT2aK+xOZX6B9YJKB8SALgXHq1XH+7Ud28FNP7kNVZVaeEGL1k0AmsiqZSvOH//dl/uK1YWa1Cmz5JZQU+WipLqShokT+8RR3LZ5IcXVwgsGpCKHgLHp0mk15QX714/t570NbzS5PCCGySgKZWDavnevi//3eKV7rTxFzVuLML6a8OJ9NdaVUFPvMLk/koExGp2dkit7xIDOBIOmonwqmeP/uCn7+IwepKpOtcCHE2iSBTCy7TEbnO6+c5ZsvXebstI2MqxyPr4jqknw2N5Tj88gTmuuZbhiMTM7QNRJgajZEMjKDJznOk5s8fPHDB9jeUmt2iUIIsewkkIkVNR9L8OffO863Xuuhc96HkleKr6CIurJ8NtdX4JRzBdeN6WCEq4PTjM2EiYVnsC1M8FCNwr94djdPPNAm29tCiHVFApkwzcRMiP/xndf55zPjjGZKsHhKKSospKnCR3NdmRzTtAZFFmJ09E8yMh0mEgqgzk+yvXCBTz2+mU889YA8ACKEWLckkImc0NE/xp995zgvtgcJWiuxeYopK/LRXF1EfUWRHG6+isUTKTqHJhicjBAMBsjMTbPBMctHDzTwhQ8exOdxmV2iEEKYTgKZyDmvnrnK//r+GV4fSBN3VmB1efHm51Pic1Jb6qOyxCcBLYfFEymGJmcYm4kyG1lgLholMx+gjEnet6OMn//oQWoris0uUwghcooEMpGzMhmdfzpynh+e7ObsYISxlA8cPqyufLz5+ZR6ndSU+agsLpB+IxPdNIDFwtgSAZq9CQ5sLOW5R7ezc1O92aUKIUTOkkAmVo3ofJznj13iR2f6JKCZKJ5MMTwxy+hMhNlI7FoACy0GsPw4+zeW8v6DbTy4dYP8OgghxF2SQCZWresB7cXTvZwdijKe8oGj4FpA81Dqc1JbWkBFsU+CwX14awALRGJErwewZIBmz2IAe/ahNg5skwAmhBBLJYFMrBnR+Tg/eOMSL525eUAr9jgoyHdS7HVT6M3DIk9xvkssnsQfjhIILxCIxm4EMD0WwpoIsCE/zv7WUt53UAKYEEJkkwQysWa9M6BNJL3oFheKzYlqdWK323G5XLgdFrwuGwUeF0VeNz6Pe00HjVQ6w0woSiA8T2guTiSWZCGeIhaLkUzEMVIxjFQMeyZKk+daAHtoMwe2N6/p/1+EEMJMEsjEuqHrBt1DE5zrHKZ9cJresSDDs3Gm4laieMDqRLE60WwOnA4HTqeTPIcFn9tOYb6bYl8eeS6H2V/GXdF1nWBknpnwHMFonMhCkvl4ilhsgUQ8gX4tdGnpeXzaPJV5BvWlebRWF7G1qYLdm+ooK/Ka/WUIIcS6IYFMCBafFLzcO8qF7hGuDvnpmwgzEkoxk3CwoOahWp0oVhcWmx2n04nDYcOiKlg0Fev1HxYVq0XDZtGwWS3YrIs/260W7DYrDpsVTbu7cR26YZDJZIglUyQTaRLpNIlkmmQ6TSqVIZnOkErriz8yGdIZnXTGIJXRicfixOJxMtdCl5JawMMc5c40tcVOmqsK2NJQxq5NdTRWlcqqlxBC5AAJZELcQSi6wLmrQ1zqHaNzZIaBqTn8cxniGZWErpEyNFJYSSsWUCygqqBaUJTFn1FVlGsfV1UNTVPRNO3GD0XV0DMZMpk0mXSGjJ4hkzEwjAzoGQw9A3oaDB3jLT+rRhqLkcZKGpuawa5mcFl0qgvsNFV42Vxfyo6WGrZsqJYJ+EIIkeMkkAmRJbpuMBeLEwjPEwzPEYzGCEUXCM3FiMzHCc8nmIsliMaSzMVSLCTSzCcWV7ocNg233YLbYSHPYcXjsuFx2cl3O/DlOfC6nRTku/B5XBR63RTm5+GwW83+koUQQmSJBDIhhBBCCJPJ+TNCCCGEECaTQCaEEEIIYTIJZEIIIYQQJpNAJoQQQghhMglkQgghhBAmk0AmhBBCCGEyCWRCCCGEECaTQCaEEEIIYTIJZEIIIYQQJpNAJoQQQghhMglkQgghhBAmk0AmhBBCCGEyCWRCCCGEECaTQCaEEEIIYTIJZEIIIYQQJpNAJoQQQghhMglkQgghhBAmk0AmhBBCCGEyCWRCCCGEECaTQCaEEEIIYTIJZEIIIYQQJpNAJoQQQghhMglkQgghhBAmk0AmhBBCCGEyCWRCCCGEECaTQCaEEEIIYTIJZEIIIYQQJvv/AcNLwowO1gs8AAAAAElFTkSuQmCC", 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" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "def plot_buffer_content(random_point_object, title: str = 'Example land cover and land use'):\n", - "\n", - " bc = random_point_object.buffer_content\n", - " to_plot = bc['land-cover'].unique()\n", - " legend = []\n", - "\n", - " fig, ax = plt.subplots()\n", - "\n", - " random_point_object.buffer.plot(ax=ax, facecolor='white', edgecolor='black', zorder=0)\n", - " random_point_object.point.plot(ax=ax, marker='*', facecolor='gold', markersize=150, edgecolor='gold', zorder=6)\n", - " legendentry = mlines.Line2D([], [], color='gold', marker='*', linestyle='None', markersize=10, label='survey location')\n", - " legend = [legendentry]\n", - " \n", - " for ashape in to_plot:\n", - " \n", - " if ashape in ['forest', 'buildings', 'vineyards', 'orchards', 'wetlands', 'ravines', 'boulders', 'glacier', 'undefined']:\n", - " bc[bc['land-cover'] == ashape].plot(ax=ax, facecolor=landuse_color[ashape], edgecolor=landuse_color[ashape], alpha=1, zorder=1)\n", - " legendentry = mpatches.Patch(facecolor=landuse_color[ashape], edgecolor=landuse_color[ashape], label=ashape, alpha=.6)\n", - " legend.append(legendentry)\n", - " \n", - " if ashape in ['recreation', 'public-services']:\n", - " bc[bc['land-cover'] == ashape].plot(ax=ax, facecolor=landuse_color[ashape], edgecolor=landuse_color[ashape], alpha=.6, zorder=2)\n", - " legendentry = mpatches.Patch(facecolor=landuse_color[ashape], edgecolor=landuse_color[ashape], label=ashape, alpha=.6)\n", - " legend.append(legendentry)\n", - "\n", - " if ashape in ['rivers']:\n", - " bc[bc['land-cover'] == ashape].plot(ax=ax, facecolor=landuse_color[ashape], edgecolor=landuse_color[ashape], alpha=.6, zorder=3)\n", - " legendentry = mlines.Line2D([], [], color=landuse_color[ashape], label=ashape, alpha=.6)\n", - " legend.append(legendentry)\n", - " \n", - " if ashape in ['streets']:\n", - " bc[bc['land-cover'] == ashape].plot(ax=ax, edgecolor=landuse_color[ashape], alpha=.6, zorder=4)\n", - " legendentry = mlines.Line2D([], [], color=landuse_color[ashape], label=ashape, alpha=.6)\n", - " legend.append(legendentry)\n", - " if ashape in ['lake']:\n", - " bc[bc['land-cover'] == ashape].plot(ax=ax, facecolor=landuse_color[ashape], edgecolor=landuse_color[ashape], alpha=.6, zorder=5)\n", - " legendentry = mpatches.Patch(facecolor=landuse_color[ashape], edgecolor=landuse_color[ashape], label=ashape, alpha=.6)\n", - " legend.append(legendentry)\n", - "\n", - " \n", - " ax.axis('off')\n", - " ax.set_title(title)\n", - " ax.legend(handles=legend, bbox_to_anchor=(1, 1), loc='upper left')\n", - " plt.tight_layout()\n", - "\n", - " plt.close()\n", - " return fig\n", - " \n", - "\n", - "\n", - "\n", - "random_loc = 'quai-maria-belgia'\n", - "lat, lon = lat_lon.loc[random_loc,['latitude', 'longitude']]\n", - "arandompoint = RandomPointLanduse(random_loc, lat, lon, 'l')\n", - "t = arandompoint.buffer_composition_proportions()\n", - "\n", - "\n", - "plot_buffer_content(arandompoint) " - ] - }, - { - "cell_type": "markdown", - "id": "b272b600-6fda-448a-9b9e-a971c08c1939", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Land use profile\n", - "\n", - "The land use profile is the array of values between 0 and 1 that contains the proportion of the buffer zone occupied by the different land use and land cover attributes within the buffer zone of a survey location." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "7000f83c-e59e-4715-8195-20d6ba30b222", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
locationvineyardslakebuildingsrecreationstreets
0quai-maria-belgia0.0159071.2842480.9836560.01542813894.013291
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" - ], - "text/plain": [ - " location vineyards lake buildings recreation streets\n", - "0 quai-maria-belgia 0.015907 1.284248 0.983656 0.015428 13894.013291" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "t" - ] - }, - { - "cell_type": "markdown", - "id": "d907e381-96fb-4187-9c2f-8559a358ea93", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "### Finding similar locations\n", - "\n", - "The similarity of a location to other locations is determined by the cosine similarity, the manhattan distance or the euclidean distance between the land use profile of the location of interest and the land use profile of previously surveyed locations. The default method is cosine similarity, the default similarity threshold is 0.9. \n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "eab9954a-9316-4560-a92b-4e7c061e0cfd", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [], - "source": [ - "feature_variables = ['buildings', 'public-services', 'streets', 'undefined', 'recreation', 'forest']\n", - "survey_data = session_config.collect_survey_data()\n", - "new_lu = pd.read_csv('data/end_process/new_lu.csv')\n", - "prior_data = survey_data[survey_data.location != random_loc].copy()\n", - "prior_data = prior_data[prior_data.feature_type == 'l'].copy()\n", - "prior_data = prior_data[prior_data.code == 'G27'].copy()\n", - "\n", - "\n", - "\n", - "selector = SampleSelector(new_lu.copy(), prior_data, feature_variables, t, threshold=.99)\n", - "sampled_data, weights_df = selector.sample_data()\n", - "\n", - "similar = new_lu[new_lu.location.isin(sampled_data.location.unique())]" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "2a966cac-f2f8-4dcd-a70a-4a157734a26a", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [ - { - "data": { - "image/png": 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" - ], - "text/plain": [ - " location vineyards lake buildings recreation streets\n", - "0 arabie 0.069983 1.061684 0.914234 0.014763 17114.587103" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "t[t.location == random_loc]" - ] - }, - { - "cell_type": "markdown", - "id": "604a8e56-93fd-418a-9cc1-c9c05ae5b466", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "## Minimum Expected values\n", - "\n", - "_The expected values are the minimum pcs/m we expect to find based on the survey results from similar locations._\n", - "\n", - "> In the case of locations that were previously sampled the minimum expected value is the conditional probability given the results from the location of interest and the results from similar locations.\n", - "\n", - "### For locations that have never been sampled\n", - "\n", - "The expected values or forecasts for a location that has never been sampled is the distribution of previous survey results from locations that meet the similarity threshold. " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "358a7430-3de1-47dd-af70-81d17f87862e", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " pcs/m\n", - "count 50.000000\n", - "mean 1.161000\n", - "std 1.877075\n", - "min 0.000000\n", - "25% 0.162500\n", - "50% 0.450000\n", - "75% 1.150000\n", - "max 8.180000" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "sampled_data[['pcs/m']].describe()" - ] - }, - { - "cell_type": "markdown", - "id": "7bca0862-a1e5-4fd3-ae17-65ac2fd7cd0a", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "source": [ - "(usingqgis)=\n", - "## Using QGIS\n", - "\n", - "For this method we are using the land-cover layer from swissTLM regio\n", - "\n", - "finished columns = slug, attribute , attribute_type, area, dry,\tscale\n", - "\n", - "In QGIS:\n", - "\n", - "1. create a buffer around each survey point\n", - " * make sure that the survey location and feature_type is in the attributes of the new buffer layer\n", - " * the survey locations are loaded as points from .csv file\n", - " * reproject the points layer to the project CRS \n", - "\n", - "2. use the new buffer layer as an overlay to the land-cover layer\n", - " * use the overlay intersection tool\n", - " * select the fields to keep from the buffer (slug and feature type)\n", - " * select the fields to keep from the land-cover layer\n", - " * run the function\n", - " * this creates a temporary layer called _intersection_\n", - "\n", - "3. get the surface area of all the land-cover and land-use features in each buffer of the temporary layer\n", - " * use the field calculator for the attribute table of the layer\n", - " * in the field calculator, make a new field and enter the formula `\\$area`\n", - " * for this example the method is elipsoid _bessel 1841 (epsg 7001)_\n", - " * this is set in the properties of the QGIS project\n", - " * Export the layer as .csv\n", - "\n", - "4. verify the land-use features per location\n", - " * drop duplicate values: use location, feature and area to define duplicates\n", - " * attention! different names for lake and reservoir\n", - " * change Stausee to See\n", - "\n", - "5. make a dry land feature\n", - " * this is the surface area of the buffer that is not covered by water\n", - " * substract the area of See from the area of the buffer\n", - " * identify survey locations that have siginifcant water features but are not listed as lakes\n", - " \n", - "6. Scale the land-use attributes of interest to the available dry-land\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "54fba949-faaf-45c5-a4b7-f0111a5c8872", - "metadata": { - "editable": true, - "slideshow": { - "slide_type": "" - }, - "tags": [ - "remove-input" - ] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Author: hammerdirt-analyst\n", - "\n", - "conda environment: cantonal_report\n", - "\n", - "pandas : 2.2.2\n", - "geopandas : 0.14.4\n", - "matplotlib: 3.8.4\n", - "\n" - ] - } - ], - "source": [ - "%watermark -a hammerdirt-analyst -co --iversions" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.19" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/_build/html/_sources/project.md b/_build/html/_sources/project.md deleted file mode 100644 index cf2d51c..0000000 --- a/_build/html/_sources/project.md +++ /dev/null @@ -1,112 +0,0 @@ -# Proposal - -The challenge in front of us is to transform the observations into accurate and actionable information for two different purposes. There is the -administration of the territory and identification of priorities with regard to plastics in the environment. Then, once the priorities have been established these -new indicators must be reported on. This project concerns the infrastructure and processes necessary to identify priorities and develop indicators to reduce plastics -in the environment from litter density counts. - -Therefore, we propose a harmonised reporting system that is administered by regional or national NGOS in collaboration with an academic partner with -the stated goal of producing reliable reports for the public administration and others who communicate on such matters. This allows administrations to -identify priorities and set baseline values according to agreed upon and observed indicators. - -The first report proved that a relatively small team could cover a large territory with the correct technology. This remains the case. -That is why we see this project, in its current iteration, specifically attractive to stakeholders with an internal data-science team. -Stakeholders with experience in python or R will feel right at home in the development environment and will be the source of many improvements. -For those interested in learning the basics, we are here to coach them and help them in their projects. - -The proposal is thus to establish a hub that is dedicated to the collection, cleaning, aggregating and distribution of litter density data. -The distribution of the data has the primary goal of producing decision support products to local administrations and other organizations charged with -reducing plastics in the environment. The _hub_ is staffed by three people and who conduct surveys, produce value added research, teach other -NGOs to collect samples, and respond to requests from local administrations. Activities or changes in protocol are considered in consultation with academic advising team. - -## Goals - -> * Develop a reporting and research tool for stakeholders in the waste management, life cycle assessment and environmental monitoring sectors. -> * Increase capacity of stakeholders to monitor and report observations according to the current standard in the federal report using open source tools. -> * Assist in the reduction and prevention of plastics in the environment - -:::{dropdown} Deliverables: four year contract -1. 800 samples -2. Revised updated federal report -3. New cantonal and municipal reports -4. Cloud service for cantonal and municipal reporting -5. Chat service for endusers to develop indi -::: - -:::{dropdown} Objectives -1. Collect 400 - 500 samples in a 12 month period - * reduce the number of items reported as _fragmented_ or _Gfrags_ - 1. This value can range from 20% - 30% of the total items collected - * include polymer identification for a subset of samples - 1. Subset should support an academic publication - 2. Subset should support a regional assessment of polymer types - * Increase knowledge sharing between surveyors - * Capacity building for surveyors - -2. Increase the number of associations competent to collect and report data - * Develop one association on Lac de Constance or Zurichsee - * Develop training materials and protocols with ASL - -3. Structure report specifically for cantonal and municipal reporting - * Revise and improve the current report - * Consider the format of the report given cantonal requirements (attached) - -4. Build upon previous research and reports - * Continue to develop modeling and parameter estimation for litter density - * Focus on topographical features and densities - * Consider polymer types and densities - -5. Define groups of objects of interest with stakeholders - * single use plastics - * agricultural plastics - * construction plastics - * industrial plastics - -6. Develop a cloud first infrastructure and chat agent - * Move all data and software assets to Infrastructure as a Service (IaaS) - * Develop machine learning and artificial intelligence pipelines for data analysis - * Develop Automated programming interfaces (APIs) for data collection and reporting - * Develop a user interface for data collection and reporting - * Deploy chat agent -::: - -:::{dropdown} Benchmarks -1. Year one: Proposed updates and revisions to the federal report. Proposed model for cantonal and municipal reporting. - * Formal research proposal for polymer identification - * Formal research proposal for topographical features - * Functioning prototype of cloud service - * 100 samples collected - * stakeholder meeting -2. Year two: - * Assessment of software and data collection - * Revised report with current data - * Update on capacity building - * End of year two: - 1. Presentation of revised report with current data - 2. Summary of capacity building - 3. 400 samples - 3. stakeholder meeting -3. Year three: - * Presentation of feedback - * stakeholder meeting - * Proposed changes to app and report - * Final report: - 1. implementation of feedback - 2. 200 samples - 3. cloud service for cantonal and municipal reporting -4. Year four: - * Testing and implementation - * 100 samples - -::: - -:::{dropdown} Cost - -> Less than 1% of the estimated cost to prevent and remove litter annualy in Switzerland. [BAFU/OFEV - litter costs](https://www.bafu.admin.ch/bafu/en/home/topics/waste/publications-studies/publications/litter-dropping-costs-money.html) - -::: - - -## Interested ? - -Interested administrations or other potential financial partners should contact roger at hammerdirt. \ No newline at end of file diff --git a/_build/html/_sources/titlepage.md b/_build/html/_sources/titlepage.md deleted file mode 100644 index 2fb2170..0000000 --- a/_build/html/_sources/titlepage.md +++ /dev/null @@ -1,70 +0,0 @@ -# Reporting volunteer observations - -This is the proof of concept for a distributed reporting system of marine litter density using data from volunteers. - -:::{dropdown} Recent changes - -__September 25:__ Added llm assisted reporting - -__June 24:__ Added responses to use cases - -__June 22:__ Added methods to calculate landuse profile using Geopandas. - - -::: - -::::{grid} - -:::{grid-item} - -This is an application of large language models (llms) and machine learning to provide summary reports of volunteer observations -of marine litter using the OSPAR, JRC or NOAA methods for counting beach litter. - -The application provides summary reports of exising data and provides forecasts for a region, city or body of water. The llm -acts first as a transcriber of test results and then as an assistant to provide a written report and resource package that can -be either used directly or integrated into other documents. - -::: - -:::{grid-item-card} - -```{image} resources/hammerdirt.png -:alt: bob -:class: bg-primary mb-1 -:width: 400px -:align: center -``` -::: -:::: -::::{grid} - -:::{grid-item} - - -This application minimizes the cost of reporting and evaluating beach litter density and uses geospatial analysis to leverage -the use of data from other disparate locations. Most importantly, decision makers and stakeholders have access to reliable, -readable reports that allow them to communicate effectively and make informed decisions. - -The data in these reports is a combination of observations from variety of groups in Switerland since 2015. The observations were recorded using an interpretation of the _Guide for Monitoring Marine Litter on European Seas_ [The guide](https://mcc.jrc.ec.europa.eu/main/dev.py?N=41&O=439&titre_chap=TG%20Litter&titre_page=Guidance%20for%20the%20Monitoring%20of%20Marine%20Litter). The guide and the monitoring of beach litter are part of decades of research, here is the brief history [A Brief History of Marine Litter Research](https://link.springer.com/chapter/10.1007/978-3-319-16510-3_1). - -::: -:::{grid-item} -__Associated projects__ - -* https://hammerdirt-analyst.github.io/IQAASL-End-0f-Sampling-2021/ -* https://hammerdirt-analyst.github.io/solid-waste-team/titlepage.html -* https://hammerdirt-analyst.github.io/landuse/titlepage.html -* https://associationsauvegardeleman.github.io/plastock/ -* https://hammerdirt-analyst.github.io/finding-one-object/titlepage.html - - -::: - -:::{grid-item} -:columns: 12 - -__THE TEAM__ - -Shannon Erismann, Montserrat Filella, Téo Gursoy, Christian Ludwig, Roger Erismann, Bettina Siegenthaler -::: -:::: diff --git a/_build/html/_sphinx_design_static/design-tabs.js b/_build/html/_sphinx_design_static/design-tabs.js deleted file mode 100644 index b25bd6a..0000000 --- a/_build/html/_sphinx_design_static/design-tabs.js +++ 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margin-top: 0; - margin-bottom: 0; - margin-left: 1.5em; -} - -.guilabel, .menuselection { - font-family: sans-serif; -} - -.accelerator { - text-decoration: underline; -} - -.classifier { - font-style: oblique; -} - -.classifier:before { - font-style: normal; - margin: 0 0.5em; - content: ":"; - display: inline-block; -} - -abbr, acronym { - border-bottom: dotted 1px; - cursor: help; -} - -.translated { - background-color: rgba(207, 255, 207, 0.2) -} - -.untranslated { - background-color: rgba(255, 207, 207, 0.2) -} - -/* -- code displays --------------------------------------------------------- */ - -pre { - overflow: auto; - overflow-y: hidden; /* fixes display issues on Chrome browsers */ -} - -pre, div[class*="highlight-"] { - clear: both; -} - -span.pre { - -moz-hyphens: none; - -ms-hyphens: none; - -webkit-hyphens: none; - hyphens: none; - white-space: nowrap; -} - -div[class*="highlight-"] { - margin: 1em 0; -} - -td.linenos pre { - border: 0; - background-color: transparent; - color: #aaa; -} - -table.highlighttable { - display: block; -} - -table.highlighttable tbody { - display: block; -} - -table.highlighttable tr { - display: flex; -} - -table.highlighttable td { - margin: 0; - padding: 0; -} - -table.highlighttable td.linenos { - padding-right: 0.5em; -} - -table.highlighttable td.code { - flex: 1; - overflow: hidden; -} - -.highlight .hll { - display: block; -} - -div.highlight pre, -table.highlighttable pre { - margin: 0; -} - -div.code-block-caption + div { - margin-top: 0; -} - -div.code-block-caption { - margin-top: 1em; - padding: 2px 5px; - font-size: small; -} - -div.code-block-caption code { - background-color: transparent; -} - -table.highlighttable td.linenos, -span.linenos, -div.highlight span.gp { /* gp: Generic.Prompt */ - user-select: none; - -webkit-user-select: text; /* Safari fallback only */ - -webkit-user-select: none; /* Chrome/Safari */ - -moz-user-select: none; /* Firefox */ - -ms-user-select: none; /* IE10+ */ -} - -div.code-block-caption span.caption-number { - padding: 0.1em 0.3em; - font-style: italic; -} - -div.code-block-caption span.caption-text { -} - -div.literal-block-wrapper { - margin: 1em 0; -} - -code.xref, a code { - background-color: transparent; - font-weight: bold; -} - -h1 code, h2 code, h3 code, h4 code, h5 code, h6 code { - background-color: transparent; -} - -.viewcode-link { - float: right; -} - -.viewcode-back { - float: right; - font-family: sans-serif; -} - -div.viewcode-block:target { - margin: -1px -10px; - padding: 0 10px; -} - -/* -- math display ---------------------------------------------------------- */ - -img.math { - vertical-align: middle; -} - -div.body div.math p { - text-align: center; -} - -span.eqno { - float: right; -} - -span.eqno a.headerlink { - position: absolute; - z-index: 1; -} - -div.math:hover a.headerlink { - visibility: visible; -} - -/* -- printout stylesheet --------------------------------------------------- */ - -@media print { - div.document, - div.documentwrapper, - div.bodywrapper { - margin: 0 !important; - width: 100%; - } - - div.sphinxsidebar, - div.related, - div.footer, - #top-link { - display: none; - } -} \ No newline at end of file diff --git a/_build/html/_static/check-solid.svg b/_build/html/_static/check-solid.svg deleted file mode 100644 index 92fad4b..0000000 --- a/_build/html/_static/check-solid.svg +++ /dev/null @@ -1,4 +0,0 @@ - - - - diff --git a/_build/html/_static/clipboard.min.js b/_build/html/_static/clipboard.min.js deleted file mode 100644 index 54b3c46..0000000 --- a/_build/html/_static/clipboard.min.js +++ /dev/null @@ -1,7 +0,0 @@ -/*! - * clipboard.js v2.0.8 - * https://clipboardjs.com/ - * - * Licensed MIT © Zeno Rocha - */ -!function(t,e){"object"==typeof exports&&"object"==typeof module?module.exports=e():"function"==typeof define&&define.amd?define([],e):"object"==typeof exports?exports.ClipboardJS=e():t.ClipboardJS=e()}(this,function(){return n={686:function(t,e,n){"use strict";n.d(e,{default:function(){return o}});var e=n(279),i=n.n(e),e=n(370),u=n.n(e),e=n(817),c=n.n(e);function a(t){try{return document.execCommand(t)}catch(t){return}}var f=function(t){t=c()(t);return a("cut"),t};var l=function(t){var e,n,o,r=1 - - - - diff --git a/_build/html/_static/copybutton.css b/_build/html/_static/copybutton.css deleted file mode 100644 index f1916ec..0000000 --- a/_build/html/_static/copybutton.css +++ /dev/null @@ -1,94 +0,0 @@ -/* Copy buttons */ -button.copybtn { - position: absolute; - display: flex; - top: .3em; - right: .3em; - width: 1.7em; - height: 1.7em; - opacity: 0; - transition: opacity 0.3s, border .3s, background-color .3s; - user-select: none; - padding: 0; - border: none; - outline: none; - border-radius: 0.4em; - /* The colors that GitHub uses */ - border: #1b1f2426 1px solid; - background-color: #f6f8fa; - color: #57606a; -} - -button.copybtn.success { - border-color: #22863a; - color: #22863a; -} - -button.copybtn svg { - stroke: currentColor; - width: 1.5em; - height: 1.5em; - padding: 0.1em; -} - -div.highlight { - position: relative; -} - -/* Show the copybutton */ -.highlight:hover button.copybtn, button.copybtn.success { - opacity: 1; -} - -.highlight button.copybtn:hover { - background-color: rgb(235, 235, 235); -} - -.highlight button.copybtn:active { - background-color: rgb(187, 187, 187); -} - -/** - * A minimal CSS-only tooltip copied from: - * https://codepen.io/mildrenben/pen/rVBrpK - * - * To use, write HTML like the following: - * - *

Short

- */ - .o-tooltip--left { - position: relative; - } - - .o-tooltip--left:after { - opacity: 0; - visibility: hidden; - position: absolute; - content: attr(data-tooltip); - padding: .2em; - font-size: .8em; - left: -.2em; - background: grey; - color: white; - white-space: nowrap; - z-index: 2; - border-radius: 2px; - transform: translateX(-102%) translateY(0); - transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); -} - -.o-tooltip--left:hover:after { - display: block; - opacity: 1; - visibility: visible; - transform: translateX(-100%) translateY(0); - transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1); - transition-delay: .5s; -} - -/* By default the copy button shouldn't show up when printing a page */ -@media print { - button.copybtn { - display: none; - } -} diff --git a/_build/html/_static/copybutton.js b/_build/html/_static/copybutton.js deleted file mode 100644 index 2ea7ff3..0000000 --- a/_build/html/_static/copybutton.js +++ /dev/null @@ -1,248 +0,0 @@ -// Localization support -const messages = { - 'en': { - 'copy': 'Copy', - 'copy_to_clipboard': 'Copy to clipboard', - 'copy_success': 'Copied!', - 'copy_failure': 'Failed to copy', - }, - 'es' : { - 'copy': 'Copiar', - 'copy_to_clipboard': 'Copiar al portapapeles', - 'copy_success': '¡Copiado!', - 'copy_failure': 'Error al copiar', - }, - 'de' : { - 'copy': 'Kopieren', - 'copy_to_clipboard': 'In die Zwischenablage kopieren', - 'copy_success': 'Kopiert!', - 'copy_failure': 'Fehler beim Kopieren', - }, - 'fr' : { - 'copy': 'Copier', - 'copy_to_clipboard': 'Copier dans le presse-papier', - 'copy_success': 'Copié !', - 'copy_failure': 'Échec de la copie', - }, - 'ru': { - 'copy': 'Скопировать', - 'copy_to_clipboard': 'Скопировать в буфер', - 'copy_success': 'Скопировано!', - 'copy_failure': 'Не удалось скопировать', - }, - 'zh-CN': { - 'copy': '复制', - 'copy_to_clipboard': '复制到剪贴板', - 'copy_success': '复制成功!', - 'copy_failure': '复制失败', - }, - 'it' : { - 'copy': 'Copiare', - 'copy_to_clipboard': 'Copiato negli appunti', - 'copy_success': 'Copiato!', - 'copy_failure': 'Errore durante la copia', - } -} - -let locale = 'en' -if( document.documentElement.lang !== undefined - && messages[document.documentElement.lang] !== undefined ) { - locale = document.documentElement.lang -} - -let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT; -if (doc_url_root == '#') { - doc_url_root = ''; -} - -/** - * SVG files for our copy buttons - */ -let iconCheck = ` - ${messages[locale]['copy_success']} - - -` - -// If the user specified their own SVG use that, otherwise use the default -let iconCopy = ``; -if (!iconCopy) { - iconCopy = ` - ${messages[locale]['copy_to_clipboard']} - - - -` -} - -/** - * Set up copy/paste for code blocks - */ - -const runWhenDOMLoaded = cb => { - if (document.readyState != 'loading') { - cb() - } else if (document.addEventListener) { - document.addEventListener('DOMContentLoaded', cb) - } else { - document.attachEvent('onreadystatechange', function() { - if (document.readyState == 'complete') cb() - }) - } -} - -const codeCellId = index => `codecell${index}` - -// Clears selected text since ClipboardJS will select the text when copying -const clearSelection = () => { - if (window.getSelection) { - window.getSelection().removeAllRanges() - } else if (document.selection) { - document.selection.empty() - } -} - -// Changes tooltip text for a moment, then changes it back -// We want the timeout of our `success` class to be a bit shorter than the -// tooltip and icon change, so that we can hide the icon before changing back. -var timeoutIcon = 2000; -var timeoutSuccessClass = 1500; - -const temporarilyChangeTooltip = (el, oldText, newText) => { - el.setAttribute('data-tooltip', newText) - el.classList.add('success') - // Remove success a little bit sooner than we change the tooltip - // So that we can use CSS to hide the copybutton first - setTimeout(() => el.classList.remove('success'), timeoutSuccessClass) - setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon) -} - -// Changes the copy button icon for two seconds, then changes it back -const temporarilyChangeIcon = (el) => { - el.innerHTML = iconCheck; - setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon) -} - -const addCopyButtonToCodeCells = () => { - // If ClipboardJS hasn't loaded, wait a bit and try again. This - // happens because we load ClipboardJS asynchronously. - if (window.ClipboardJS === undefined) { - setTimeout(addCopyButtonToCodeCells, 250) - return - } - - // Add copybuttons to all of our code cells - const COPYBUTTON_SELECTOR = 'div.highlight pre'; - const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR) - codeCells.forEach((codeCell, index) => { - const id = codeCellId(index) - codeCell.setAttribute('id', id) - - const clipboardButton = id => - `` - codeCell.insertAdjacentHTML('afterend', clipboardButton(id)) - }) - -function escapeRegExp(string) { - return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string -} - -/** - * Removes excluded text from a Node. - * - * @param {Node} target Node to filter. - * @param {string} exclude CSS selector of nodes to exclude. - * @returns {DOMString} Text from `target` with text removed. - */ -function filterText(target, exclude) { - const clone = target.cloneNode(true); // clone as to not modify the live DOM - if (exclude) { - // remove excluded nodes - clone.querySelectorAll(exclude).forEach(node => node.remove()); - } - return clone.innerText; -} - -// Callback when a copy button is clicked. Will be passed the node that was clicked -// should then grab the text and replace pieces of text that shouldn't be used in output -function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { - var regexp; - var match; - - // Do we check for line continuation characters and "HERE-documents"? - var useLineCont = !!lineContinuationChar - var useHereDoc = !!hereDocDelim - - // create regexp to capture prompt and remaining line - if (isRegexp) { - regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') - } else { - regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') - } - - const outputLines = []; - var promptFound = false; - var gotLineCont = false; - var gotHereDoc = false; - const lineGotPrompt = []; - for (const line of textContent.split('\n')) { - match = line.match(regexp) - if (match || gotLineCont || gotHereDoc) { - promptFound = regexp.test(line) - lineGotPrompt.push(promptFound) - if (removePrompts && promptFound) { - outputLines.push(match[2]) - } else { - outputLines.push(line) - } - gotLineCont = line.endsWith(lineContinuationChar) & useLineCont - if (line.includes(hereDocDelim) & useHereDoc) - gotHereDoc = !gotHereDoc - } else if (!onlyCopyPromptLines) { - outputLines.push(line) - } else if (copyEmptyLines && line.trim() === '') { - outputLines.push(line) - } - } - - // If no lines with the prompt were found then just use original lines - if (lineGotPrompt.some(v => v === true)) { - textContent = outputLines.join('\n'); - } - - // Remove a trailing newline to avoid auto-running when pasting - if (textContent.endsWith("\n")) { - textContent = textContent.slice(0, -1) - } - return textContent -} - - -var copyTargetText = (trigger) => { - var target = document.querySelector(trigger.attributes['data-clipboard-target'].value); - - // get filtered text - let exclude = '.linenos'; - - let text = filterText(target, exclude); - return formatCopyText(text, '', false, true, true, true, '', '') -} - - // Initialize with a callback so we can modify the text before copy - const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText}) - - // Update UI with error/success messages - clipboard.on('success', event => { - clearSelection() - temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success']) - temporarilyChangeIcon(event.trigger) - }) - - clipboard.on('error', event => { - temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure']) - }) -} - -runWhenDOMLoaded(addCopyButtonToCodeCells) \ No newline at end of file diff --git a/_build/html/_static/copybutton_funcs.js b/_build/html/_static/copybutton_funcs.js deleted file mode 100644 index dbe1aaa..0000000 --- a/_build/html/_static/copybutton_funcs.js +++ /dev/null @@ -1,73 +0,0 @@ -function escapeRegExp(string) { - return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string -} - -/** - * Removes excluded text from a Node. - * - * @param {Node} target Node to filter. - * @param {string} exclude CSS selector of nodes to exclude. - * @returns {DOMString} Text from `target` with text removed. - */ -export function filterText(target, exclude) { - const clone = target.cloneNode(true); // clone as to not modify the live DOM - if (exclude) { - // remove excluded nodes - clone.querySelectorAll(exclude).forEach(node => node.remove()); - } - return clone.innerText; -} - -// Callback when a copy button is clicked. Will be passed the node that was clicked -// should then grab the text and replace pieces of text that shouldn't be used in output -export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") { - var regexp; - var match; - - // Do we check for line continuation characters and "HERE-documents"? - var useLineCont = !!lineContinuationChar - var useHereDoc = !!hereDocDelim - - // create regexp to capture prompt and remaining line - if (isRegexp) { - regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)') - } else { - regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)') - } - - const outputLines = []; - var promptFound = false; - var gotLineCont = false; - var gotHereDoc = false; - const lineGotPrompt = []; - for (const line of textContent.split('\n')) { - match = line.match(regexp) - if (match || gotLineCont || gotHereDoc) { - promptFound = regexp.test(line) - lineGotPrompt.push(promptFound) - if (removePrompts && promptFound) { - outputLines.push(match[2]) - } else { - outputLines.push(line) - } - gotLineCont = line.endsWith(lineContinuationChar) & useLineCont - if (line.includes(hereDocDelim) & useHereDoc) - gotHereDoc = !gotHereDoc - } else if (!onlyCopyPromptLines) { - outputLines.push(line) - } else if (copyEmptyLines && line.trim() === '') { - outputLines.push(line) - } - } - - // If no lines with the prompt were found then just use original lines - if (lineGotPrompt.some(v => v === true)) { - textContent = outputLines.join('\n'); - } - - // Remove a trailing newline to avoid auto-running when pasting - if (textContent.endsWith("\n")) { - textContent = textContent.slice(0, -1) - } - return textContent -} diff --git a/_build/html/_static/design-tabs.js b/_build/html/_static/design-tabs.js deleted file mode 100644 index b25bd6a..0000000 --- a/_build/html/_static/design-tabs.js +++ /dev/null @@ -1,101 +0,0 @@ -// @ts-check - -// Extra JS capability for selected tabs to be synced -// The selection is stored in local storage so that it persists across page loads. - -/** - * @type {Record} - */ -let sd_id_to_elements = {}; -const storageKeyPrefix = "sphinx-design-tab-id-"; - -/** - * Create a key for a tab element. - * @param {HTMLElement} el - The tab element. - * @returns {[string, string, string] | null} - The key. - * - */ -function create_key(el) { - let syncId = el.getAttribute("data-sync-id"); - let syncGroup = el.getAttribute("data-sync-group"); - if (!syncId || !syncGroup) return null; - return [syncGroup, syncId, syncGroup + "--" + syncId]; -} - -/** - * Initialize the tab selection. - * - */ -function ready() { - // Find all tabs with sync data - - /** @type {string[]} */ - let groups = []; - - document.querySelectorAll(".sd-tab-label").forEach((label) => { - if (label instanceof HTMLElement) { - let data = create_key(label); - if (data) { - let [group, id, key] = data; - - // add click event listener - // @ts-ignore - label.onclick = onSDLabelClick; - - // store map of key to elements - if (!sd_id_to_elements[key]) { - sd_id_to_elements[key] = []; - } - sd_id_to_elements[key].push(label); - - if (groups.indexOf(group) === -1) { - groups.push(group); - // Check if a specific tab has been selected via URL parameter - const tabParam = new URLSearchParams(window.location.search).get( - group - ); - if (tabParam) { - console.log( - "sphinx-design: Selecting tab id for group '" + - group + - "' from URL parameter: " + - tabParam - ); - window.sessionStorage.setItem(storageKeyPrefix + group, tabParam); - } - } - - // Check is a specific tab has been selected previously - let previousId = window.sessionStorage.getItem( - storageKeyPrefix + group - ); - if (previousId === id) { - // console.log( - // "sphinx-design: Selecting tab from session storage: " + id - // ); - // @ts-ignore - label.previousElementSibling.checked = true; - } - } - } - }); -} - -/** - * Activate other tabs with the same sync id. - * - * @this {HTMLElement} - The element that was clicked. - */ -function onSDLabelClick() { - let data = create_key(this); - if (!data) return; - let [group, id, key] = data; - for (const label of sd_id_to_elements[key]) { - if (label === this) continue; - // @ts-ignore - label.previousElementSibling.checked = true; - } - window.sessionStorage.setItem(storageKeyPrefix + group, id); -} - -document.addEventListener("DOMContentLoaded", ready, false); diff --git a/_build/html/_static/doctools.js b/_build/html/_static/doctools.js deleted file mode 100644 index 4d67807..0000000 --- a/_build/html/_static/doctools.js +++ /dev/null @@ -1,156 +0,0 @@ -/* - * doctools.js - * ~~~~~~~~~~~ - * - * Base JavaScript utilities for all Sphinx HTML documentation. - * - * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ -"use strict"; - -const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([ - "TEXTAREA", - "INPUT", - "SELECT", - "BUTTON", -]); - -const _ready = (callback) => { - if (document.readyState !== "loading") { - callback(); - } else { - document.addEventListener("DOMContentLoaded", callback); - } -}; - -/** - * Small JavaScript module for the documentation. - */ -const Documentation = { - init: () => { - Documentation.initDomainIndexTable(); - Documentation.initOnKeyListeners(); - }, - - /** - * i18n support - */ - TRANSLATIONS: {}, - PLURAL_EXPR: (n) => (n === 1 ? 0 : 1), - LOCALE: "unknown", - - // gettext and ngettext don't access this so that the functions - // can safely bound to a different name (_ = Documentation.gettext) - gettext: (string) => { - const translated = Documentation.TRANSLATIONS[string]; - switch (typeof translated) { - case "undefined": - return string; // no translation - case "string": - return translated; // translation exists - default: - return translated[0]; // (singular, plural) translation tuple exists - } - }, - - ngettext: (singular, plural, n) => { - const translated = Documentation.TRANSLATIONS[singular]; - if (typeof translated !== "undefined") - return translated[Documentation.PLURAL_EXPR(n)]; - return n === 1 ? singular : plural; - }, - - addTranslations: (catalog) => { - Object.assign(Documentation.TRANSLATIONS, catalog.messages); - Documentation.PLURAL_EXPR = new Function( - "n", - `return (${catalog.plural_expr})` - ); - Documentation.LOCALE = catalog.locale; - }, - - /** - * helper function to focus on search bar - */ - focusSearchBar: () => { - document.querySelectorAll("input[name=q]")[0]?.focus(); - }, - - /** - * Initialise the domain index toggle buttons - */ - initDomainIndexTable: () => { - const toggler = (el) => { - const idNumber = el.id.substr(7); - const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`); - if (el.src.substr(-9) === "minus.png") { - el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`; - toggledRows.forEach((el) => (el.style.display = "none")); - } else { - el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`; - toggledRows.forEach((el) => (el.style.display = "")); - } - }; - - const togglerElements = document.querySelectorAll("img.toggler"); - togglerElements.forEach((el) => - el.addEventListener("click", (event) => toggler(event.currentTarget)) - ); - togglerElements.forEach((el) => (el.style.display = "")); - if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler); - }, - - initOnKeyListeners: () => { - // only install a listener if it is really needed - if ( - !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS && - !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS - ) - return; - - document.addEventListener("keydown", (event) => { - // bail for input elements - if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; - // bail with special keys - if (event.altKey || event.ctrlKey || event.metaKey) return; - - if (!event.shiftKey) { - switch (event.key) { - case "ArrowLeft": - if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; - - const prevLink = document.querySelector('link[rel="prev"]'); - if (prevLink && prevLink.href) { - window.location.href = prevLink.href; - event.preventDefault(); - } - break; - case "ArrowRight": - if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; - - const nextLink = document.querySelector('link[rel="next"]'); - if (nextLink && nextLink.href) { - window.location.href = nextLink.href; - event.preventDefault(); - } - break; - } - } - - // some keyboard layouts may need Shift to get / - switch (event.key) { - case "/": - if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; - Documentation.focusSearchBar(); - event.preventDefault(); - } - }); - }, -}; - -// quick alias for translations -const _ = Documentation.gettext; - -_ready(Documentation.init); diff --git a/_build/html/_static/documentation_options.js b/_build/html/_static/documentation_options.js deleted file mode 100644 index dab586c..0000000 --- a/_build/html/_static/documentation_options.js +++ /dev/null @@ -1,13 +0,0 @@ -const DOCUMENTATION_OPTIONS = { - VERSION: '', - LANGUAGE: 'en', - COLLAPSE_INDEX: false, - BUILDER: 'html', - FILE_SUFFIX: '.html', - LINK_SUFFIX: '.html', - HAS_SOURCE: true, - SOURCELINK_SUFFIX: '', - NAVIGATION_WITH_KEYS: false, - SHOW_SEARCH_SUMMARY: true, - ENABLE_SEARCH_SHORTCUTS: true, -}; \ No newline at end of file diff --git a/_build/html/_static/file.png b/_build/html/_static/file.png deleted file mode 100644 index a858a41..0000000 Binary files a/_build/html/_static/file.png and /dev/null differ diff --git a/_build/html/_static/images/logo_binder.svg b/_build/html/_static/images/logo_binder.svg deleted file mode 100644 index 45fecf7..0000000 --- a/_build/html/_static/images/logo_binder.svg +++ /dev/null @@ -1,19 +0,0 @@ - - - - -logo - - - - - - - - diff --git a/_build/html/_static/images/logo_colab.png b/_build/html/_static/images/logo_colab.png deleted file mode 100644 index b7560ec..0000000 Binary files a/_build/html/_static/images/logo_colab.png and /dev/null differ diff --git a/_build/html/_static/images/logo_deepnote.svg b/_build/html/_static/images/logo_deepnote.svg deleted file mode 100644 index fa77ebf..0000000 --- a/_build/html/_static/images/logo_deepnote.svg +++ /dev/null @@ -1 +0,0 @@ - diff --git a/_build/html/_static/images/logo_jupyterhub.svg b/_build/html/_static/images/logo_jupyterhub.svg deleted file mode 100644 index 60cfe9f..0000000 --- a/_build/html/_static/images/logo_jupyterhub.svg +++ /dev/null @@ -1 +0,0 @@ -logo_jupyterhubHub diff --git a/_build/html/_static/language_data.js b/_build/html/_static/language_data.js deleted file mode 100644 index 367b8ed..0000000 --- a/_build/html/_static/language_data.js +++ /dev/null @@ -1,199 +0,0 @@ -/* - * language_data.js - * ~~~~~~~~~~~~~~~~ - * - * This script contains the language-specific data used by searchtools.js, - * namely the list of stopwords, stemmer, scorer and splitter. - * - * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ - -var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; - - -/* Non-minified version is copied as a separate JS file, if available */ - -/** - * Porter Stemmer - */ -var Stemmer = function() { - - var step2list = { - ational: 'ate', - tional: 'tion', - enci: 'ence', - anci: 'ance', - izer: 'ize', - bli: 'ble', - alli: 'al', - entli: 'ent', - eli: 'e', - ousli: 'ous', - ization: 'ize', - ation: 'ate', - ator: 'ate', - alism: 'al', - iveness: 'ive', - fulness: 'ful', - ousness: 'ous', - aliti: 'al', - iviti: 'ive', - biliti: 'ble', - logi: 'log' - }; - - var step3list = { - icate: 'ic', - ative: '', - alize: 'al', - iciti: 'ic', - ical: 'ic', - ful: '', - ness: '' - }; - - var c = "[^aeiou]"; // consonant - var v = "[aeiouy]"; // vowel - var C = c + "[^aeiouy]*"; // consonant sequence - var V = v + "[aeiou]*"; // vowel sequence - - var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 - var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 - var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 - var s_v = "^(" + C + ")?" + v; // vowel in stem - - this.stemWord = function (w) { - var stem; - var suffix; - var firstch; - var origword = w; - - if (w.length < 3) - return w; - - var re; - var re2; - var re3; - var re4; - - firstch = w.substr(0,1); - if (firstch == "y") - w = firstch.toUpperCase() + w.substr(1); - - // Step 1a - re = /^(.+?)(ss|i)es$/; - re2 = /^(.+?)([^s])s$/; - - if (re.test(w)) - w = w.replace(re,"$1$2"); - else if (re2.test(w)) - w = w.replace(re2,"$1$2"); - - // Step 1b - re = /^(.+?)eed$/; - re2 = /^(.+?)(ed|ing)$/; - if (re.test(w)) { - var fp = re.exec(w); - re = new RegExp(mgr0); - if (re.test(fp[1])) { - re = /.$/; - w = w.replace(re,""); - } - } - else if (re2.test(w)) { - var fp = re2.exec(w); - stem = fp[1]; - re2 = new RegExp(s_v); - if (re2.test(stem)) { - w = stem; - re2 = /(at|bl|iz)$/; - re3 = new RegExp("([^aeiouylsz])\\1$"); - re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); - if (re2.test(w)) - w = w + "e"; - else if (re3.test(w)) { - re = /.$/; - w = w.replace(re,""); - } - else if (re4.test(w)) - w = w + "e"; - } - } - - // Step 1c - re = /^(.+?)y$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(s_v); - if (re.test(stem)) - w = stem + "i"; - } - - // Step 2 - re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step2list[suffix]; - } - - // Step 3 - re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step3list[suffix]; - } - - // Step 4 - re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; - re2 = /^(.+?)(s|t)(ion)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(mgr1); - if (re.test(stem)) - w = stem; - } - else if (re2.test(w)) { - var fp = re2.exec(w); - stem = fp[1] + fp[2]; - re2 = new RegExp(mgr1); - if (re2.test(stem)) - w = stem; - } - - // Step 5 - re = /^(.+?)e$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(mgr1); - re2 = new RegExp(meq1); - re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); - if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) - w = stem; - } - re = /ll$/; - re2 = new RegExp(mgr1); - if (re.test(w) && re2.test(w)) { - re = /.$/; - w = w.replace(re,""); - } - - // and turn initial Y back to y - if (firstch == "y") - w = firstch.toLowerCase() + w.substr(1); - return w; - } -} - diff --git a/_build/html/_static/locales/ar/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ar/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 15541a6..0000000 Binary files a/_build/html/_static/locales/ar/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ar/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ar/LC_MESSAGES/booktheme.po deleted file mode 100644 index 34d404c..0000000 --- a/_build/html/_static/locales/ar/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ar\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "طباعة إلى PDF" - -msgid "Theme by the" -msgstr "موضوع بواسطة" - -msgid "Download source file" -msgstr "تنزيل ملف المصدر" - -msgid "open issue" -msgstr "قضية مفتوحة" - -msgid "Contents" -msgstr "محتويات" - -msgid "previous page" -msgstr "الصفحة السابقة" - -msgid "Download notebook file" -msgstr "تنزيل ملف دفتر الملاحظات" - -msgid "Copyright" -msgstr "حقوق النشر" - -msgid "Download this page" -msgstr "قم بتنزيل هذه الصفحة" - -msgid "Source repository" -msgstr "مستودع المصدر" - -msgid "By" -msgstr "بواسطة" - -msgid "repository" -msgstr "مخزن" - -msgid "Last updated on" -msgstr "آخر تحديث في" - -msgid "Toggle navigation" -msgstr "تبديل التنقل" - -msgid "Sphinx Book Theme" -msgstr "موضوع كتاب أبو الهول" - -msgid "suggest edit" -msgstr "أقترح تحرير" - -msgid "Open an issue" -msgstr "افتح قضية" - -msgid "Launch" -msgstr "إطلاق" - -msgid "Fullscreen mode" -msgstr "وضع ملء الشاشة" - -msgid "Edit this page" -msgstr "قم بتحرير هذه الصفحة" - -msgid "By the" -msgstr "بواسطة" - -msgid "next page" -msgstr "الصفحة التالية" diff --git a/_build/html/_static/locales/bg/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/bg/LC_MESSAGES/booktheme.mo deleted file mode 100644 index da95120..0000000 Binary files a/_build/html/_static/locales/bg/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/bg/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/bg/LC_MESSAGES/booktheme.po deleted file mode 100644 index 7420c19..0000000 --- a/_build/html/_static/locales/bg/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: bg\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Печат в PDF" - -msgid "Theme by the" -msgstr "Тема от" - -msgid "Download source file" -msgstr "Изтеглете изходния файл" - -msgid "open issue" -msgstr "отворен брой" - -msgid "Contents" -msgstr "Съдържание" - -msgid "previous page" -msgstr "предишна страница" - -msgid "Download notebook file" -msgstr "Изтеглете файла на бележника" - -msgid "Copyright" -msgstr "Авторско право" - -msgid "Download this page" -msgstr "Изтеглете тази страница" - -msgid "Source repository" -msgstr "Хранилище на източника" - -msgid "By" -msgstr "От" - -msgid "repository" -msgstr "хранилище" - -msgid "Last updated on" -msgstr "Последна актуализация на" - -msgid "Toggle navigation" -msgstr "Превключване на навигацията" - -msgid "Sphinx Book Theme" -msgstr "Тема на книгата Sphinx" - -msgid "suggest edit" -msgstr "предложи редактиране" - -msgid "Open an issue" -msgstr "Отворете проблем" - -msgid "Launch" -msgstr "Стартиране" - -msgid "Fullscreen mode" -msgstr "Режим на цял екран" - -msgid "Edit this page" -msgstr "Редактирайте тази страница" - -msgid "By the" -msgstr "По" - -msgid "next page" -msgstr "Следваща страница" diff --git a/_build/html/_static/locales/bn/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/bn/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 6b96639..0000000 Binary files a/_build/html/_static/locales/bn/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/bn/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/bn/LC_MESSAGES/booktheme.po deleted file mode 100644 index 63a07c3..0000000 --- a/_build/html/_static/locales/bn/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,63 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: bn\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "পিডিএফ প্রিন্ট করুন" - -msgid "Theme by the" -msgstr "থিম দ্বারা" - -msgid "Download source file" -msgstr "উত্স ফাইল ডাউনলোড করুন" - -msgid "open issue" -msgstr "খোলা সমস্যা" - -msgid "previous page" -msgstr "আগের পৃষ্ঠা" - -msgid "Download notebook file" -msgstr "নোটবুক ফাইল ডাউনলোড করুন" - -msgid "Copyright" -msgstr "কপিরাইট" - -msgid "Download this page" -msgstr "এই পৃষ্ঠাটি ডাউনলোড করুন" - -msgid "Source repository" -msgstr "উত্স সংগ্রহস্থল" - -msgid "By" -msgstr "দ্বারা" - -msgid "Last updated on" -msgstr "সর্বশেষ আপডেট" - -msgid "Toggle navigation" -msgstr "নেভিগেশন টগল করুন" - -msgid "Sphinx Book Theme" -msgstr "স্পিনিক্স বুক থিম" - -msgid "Open an issue" -msgstr "একটি সমস্যা খুলুন" - -msgid "Launch" -msgstr "শুরু করা" - -msgid "Edit this page" -msgstr "এই পৃষ্ঠাটি সম্পাদনা করুন" - -msgid "By the" -msgstr "দ্বারা" - -msgid "next page" -msgstr "পরবর্তী পৃষ্ঠা" diff --git a/_build/html/_static/locales/ca/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ca/LC_MESSAGES/booktheme.mo deleted file mode 100644 index a4dd30e..0000000 Binary files a/_build/html/_static/locales/ca/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ca/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ca/LC_MESSAGES/booktheme.po deleted file mode 100644 index 8fb358b..0000000 --- a/_build/html/_static/locales/ca/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ca\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Imprimeix a PDF" - -msgid "Theme by the" -msgstr "Tema del" - -msgid "Download source file" -msgstr "Baixeu el fitxer font" - -msgid "open issue" -msgstr "número obert" - -msgid "previous page" -msgstr "Pàgina anterior" - -msgid "Download notebook file" -msgstr "Descarregar fitxer de quadern" - -msgid "Copyright" -msgstr "Copyright" - -msgid "Download this page" -msgstr "Descarregueu aquesta pàgina" - -msgid "Source repository" -msgstr "Dipòsit de fonts" - -msgid "By" -msgstr "Per" - -msgid "Last updated on" -msgstr "Darrera actualització el" - -msgid "Toggle navigation" -msgstr "Commuta la navegació" - -msgid "Sphinx Book Theme" -msgstr "Tema del llibre Esfinx" - -msgid "suggest edit" -msgstr "suggerir edició" - -msgid "Open an issue" -msgstr "Obriu un número" - -msgid "Launch" -msgstr "Llançament" - -msgid "Edit this page" -msgstr "Editeu aquesta pàgina" - -msgid "By the" -msgstr "Per la" - -msgid "next page" -msgstr "pàgina següent" diff --git a/_build/html/_static/locales/cs/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/cs/LC_MESSAGES/booktheme.mo deleted file mode 100644 index c39e01a..0000000 Binary files a/_build/html/_static/locales/cs/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/cs/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/cs/LC_MESSAGES/booktheme.po deleted file mode 100644 index c6ef469..0000000 --- a/_build/html/_static/locales/cs/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: cs\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Tisk do PDF" - -msgid "Theme by the" -msgstr "Téma od" - -msgid "Download source file" -msgstr "Stáhněte si zdrojový soubor" - -msgid "open issue" -msgstr "otevřené číslo" - -msgid "Contents" -msgstr "Obsah" - -msgid "previous page" -msgstr "předchozí stránka" - -msgid "Download notebook file" -msgstr "Stáhnout soubor poznámkového bloku" - -msgid "Copyright" -msgstr "autorská práva" - -msgid "Download this page" -msgstr "Stáhněte si tuto stránku" - -msgid "Source repository" -msgstr "Zdrojové úložiště" - -msgid "By" -msgstr "Podle" - -msgid "repository" -msgstr "úložiště" - -msgid "Last updated on" -msgstr "Naposledy aktualizováno" - -msgid "Toggle navigation" -msgstr "Přepnout navigaci" - -msgid "Sphinx Book Theme" -msgstr "Téma knihy Sfinga" - -msgid "suggest edit" -msgstr "navrhnout úpravy" - -msgid "Open an issue" -msgstr "Otevřete problém" - -msgid "Launch" -msgstr "Zahájení" - -msgid "Fullscreen mode" -msgstr "Režim celé obrazovky" - -msgid "Edit this page" -msgstr "Upravit tuto stránku" - -msgid "By the" -msgstr "Podle" - -msgid "next page" -msgstr "další strana" diff --git a/_build/html/_static/locales/da/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/da/LC_MESSAGES/booktheme.mo deleted file mode 100644 index f43157d..0000000 Binary files a/_build/html/_static/locales/da/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/da/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/da/LC_MESSAGES/booktheme.po deleted file mode 100644 index 306a38e..0000000 --- a/_build/html/_static/locales/da/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: da\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Udskriv til PDF" - -msgid "Theme by the" -msgstr "Tema af" - -msgid "Download source file" -msgstr "Download kildefil" - -msgid "open issue" -msgstr "åbent nummer" - -msgid "Contents" -msgstr "Indhold" - -msgid "previous page" -msgstr "forrige side" - -msgid "Download notebook file" -msgstr "Download notesbog-fil" - -msgid "Copyright" -msgstr "ophavsret" - -msgid "Download this page" -msgstr "Download denne side" - -msgid "Source repository" -msgstr "Kildelager" - -msgid "By" -msgstr "Ved" - -msgid "repository" -msgstr "lager" - -msgid "Last updated on" -msgstr "Sidst opdateret den" - -msgid "Toggle navigation" -msgstr "Skift navigation" - -msgid "Sphinx Book Theme" -msgstr "Sphinx bogtema" - -msgid "suggest edit" -msgstr "foreslå redigering" - -msgid "Open an issue" -msgstr "Åbn et problem" - -msgid "Launch" -msgstr "Start" - -msgid "Fullscreen mode" -msgstr "Fuldskærmstilstand" - -msgid "Edit this page" -msgstr "Rediger denne side" - -msgid "By the" -msgstr "Ved" - -msgid "next page" -msgstr "Næste side" diff --git a/_build/html/_static/locales/de/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/de/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 648b565..0000000 Binary files a/_build/html/_static/locales/de/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/de/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/de/LC_MESSAGES/booktheme.po deleted file mode 100644 index 4925360..0000000 --- a/_build/html/_static/locales/de/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: de\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "In PDF drucken" - -msgid "Theme by the" -msgstr "Thema von der" - -msgid "Download source file" -msgstr "Quelldatei herunterladen" - -msgid "open issue" -msgstr "offenes Thema" - -msgid "Contents" -msgstr "Inhalt" - -msgid "previous page" -msgstr "vorherige Seite" - -msgid "Download notebook file" -msgstr "Notebook-Datei herunterladen" - -msgid "Copyright" -msgstr "Urheberrechte ©" - -msgid "Download this page" -msgstr "Laden Sie diese Seite herunter" - -msgid "Source repository" -msgstr "Quell-Repository" - -msgid "By" -msgstr "Durch" - -msgid "repository" -msgstr "Repository" - -msgid "Last updated on" -msgstr "Zuletzt aktualisiert am" - -msgid "Toggle navigation" -msgstr "Navigation umschalten" - -msgid "Sphinx Book Theme" -msgstr "Sphinx-Buch-Thema" - -msgid "suggest edit" -msgstr "vorschlagen zu bearbeiten" - -msgid "Open an issue" -msgstr "Öffnen Sie ein Problem" - -msgid "Launch" -msgstr "Starten" - -msgid "Fullscreen mode" -msgstr "Vollbildmodus" - -msgid "Edit this page" -msgstr "Bearbeite diese Seite" - -msgid "By the" -msgstr "Bis zum" - -msgid "next page" -msgstr "Nächste Seite" diff --git a/_build/html/_static/locales/el/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/el/LC_MESSAGES/booktheme.mo deleted file mode 100644 index fca6e93..0000000 Binary files a/_build/html/_static/locales/el/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/el/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/el/LC_MESSAGES/booktheme.po deleted file mode 100644 index 3e01acb..0000000 --- a/_build/html/_static/locales/el/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: el\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Εκτύπωση σε PDF" - -msgid "Theme by the" -msgstr "Θέμα από το" - -msgid "Download source file" -msgstr "Λήψη αρχείου προέλευσης" - -msgid "open issue" -msgstr "ανοιχτό ζήτημα" - -msgid "Contents" -msgstr "Περιεχόμενα" - -msgid "previous page" -msgstr "προηγούμενη σελίδα" - -msgid "Download notebook file" -msgstr "Λήψη αρχείου σημειωματάριου" - -msgid "Copyright" -msgstr "Πνευματική ιδιοκτησία" - -msgid "Download this page" -msgstr "Λήψη αυτής της σελίδας" - -msgid "Source repository" -msgstr "Αποθήκη πηγής" - -msgid "By" -msgstr "Με" - -msgid "repository" -msgstr "αποθήκη" - -msgid "Last updated on" -msgstr "Τελευταία ενημέρωση στις" - -msgid "Toggle navigation" -msgstr "Εναλλαγή πλοήγησης" - -msgid "Sphinx Book Theme" -msgstr "Θέμα βιβλίου Sphinx" - -msgid "suggest edit" -msgstr "προτείνω επεξεργασία" - -msgid "Open an issue" -msgstr "Ανοίξτε ένα ζήτημα" - -msgid "Launch" -msgstr "Εκτόξευση" - -msgid "Fullscreen mode" -msgstr "ΛΕΙΤΟΥΡΓΙΑ ΠΛΗΡΟΥΣ ΟΘΟΝΗΣ" - -msgid "Edit this page" -msgstr "Επεξεργαστείτε αυτήν τη σελίδα" - -msgid "By the" -msgstr "Από το" - -msgid "next page" -msgstr "επόμενη σελίδα" diff --git a/_build/html/_static/locales/eo/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/eo/LC_MESSAGES/booktheme.mo deleted file mode 100644 index d1072bb..0000000 Binary files a/_build/html/_static/locales/eo/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/eo/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/eo/LC_MESSAGES/booktheme.po deleted file mode 100644 index f7ed226..0000000 --- a/_build/html/_static/locales/eo/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: eo\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Presi al PDF" - -msgid "Theme by the" -msgstr "Temo de la" - -msgid "Download source file" -msgstr "Elŝutu fontodosieron" - -msgid "open issue" -msgstr "malferma numero" - -msgid "Contents" -msgstr "Enhavo" - -msgid "previous page" -msgstr "antaŭa paĝo" - -msgid "Download notebook file" -msgstr "Elŝutu kajeran dosieron" - -msgid "Copyright" -msgstr "Kopirajto" - -msgid "Download this page" -msgstr "Elŝutu ĉi tiun paĝon" - -msgid "Source repository" -msgstr "Fonto-deponejo" - -msgid "By" -msgstr "De" - -msgid "repository" -msgstr "deponejo" - -msgid "Last updated on" -msgstr "Laste ĝisdatigita la" - -msgid "Toggle navigation" -msgstr "Ŝalti navigadon" - -msgid "Sphinx Book Theme" -msgstr "Sfinksa Libro-Temo" - -msgid "suggest edit" -msgstr "sugesti redaktadon" - -msgid "Open an issue" -msgstr "Malfermu numeron" - -msgid "Launch" -msgstr "Lanĉo" - -msgid "Fullscreen mode" -msgstr "Plenekrana reĝimo" - -msgid "Edit this page" -msgstr "Redaktu ĉi tiun paĝon" - -msgid "By the" -msgstr "Per la" - -msgid "next page" -msgstr "sekva paĝo" diff --git a/_build/html/_static/locales/es/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/es/LC_MESSAGES/booktheme.mo deleted file mode 100644 index ba2ee4d..0000000 Binary files a/_build/html/_static/locales/es/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/es/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/es/LC_MESSAGES/booktheme.po deleted file mode 100644 index 5e0029e..0000000 --- a/_build/html/_static/locales/es/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: es\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Imprimir en PDF" - -msgid "Theme by the" -msgstr "Tema por el" - -msgid "Download source file" -msgstr "Descargar archivo fuente" - -msgid "open issue" -msgstr "Tema abierto" - -msgid "Contents" -msgstr "Contenido" - -msgid "previous page" -msgstr "pagina anterior" - -msgid "Download notebook file" -msgstr "Descargar archivo de cuaderno" - -msgid "Copyright" -msgstr "Derechos de autor" - -msgid "Download this page" -msgstr "Descarga esta pagina" - -msgid "Source repository" -msgstr "Repositorio de origen" - -msgid "By" -msgstr "Por" - -msgid "repository" -msgstr "repositorio" - -msgid "Last updated on" -msgstr "Ultima actualización en" - -msgid "Toggle navigation" -msgstr "Navegación de palanca" - -msgid "Sphinx Book Theme" -msgstr "Tema del libro de la esfinge" - -msgid "suggest edit" -msgstr "sugerir editar" - -msgid "Open an issue" -msgstr "Abrir un problema" - -msgid "Launch" -msgstr "Lanzamiento" - -msgid "Fullscreen mode" -msgstr "Modo de pantalla completa" - -msgid "Edit this page" -msgstr "Edita esta página" - -msgid "By the" -msgstr "Por el" - -msgid "next page" -msgstr "siguiente página" diff --git a/_build/html/_static/locales/et/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/et/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 983b823..0000000 Binary files a/_build/html/_static/locales/et/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/et/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/et/LC_MESSAGES/booktheme.po deleted file mode 100644 index 8680982..0000000 --- a/_build/html/_static/locales/et/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: et\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Prindi PDF-i" - -msgid "Theme by the" -msgstr "Teema" - -msgid "Download source file" -msgstr "Laadige alla lähtefail" - -msgid "open issue" -msgstr "avatud küsimus" - -msgid "Contents" -msgstr "Sisu" - -msgid "previous page" -msgstr "eelmine leht" - -msgid "Download notebook file" -msgstr "Laadige sülearvuti fail alla" - -msgid "Copyright" -msgstr "Autoriõigus" - -msgid "Download this page" -msgstr "Laadige see leht alla" - -msgid "Source repository" -msgstr "Allikahoidla" - -msgid "By" -msgstr "Kõrval" - -msgid "repository" -msgstr "hoidla" - -msgid "Last updated on" -msgstr "Viimati uuendatud" - -msgid "Toggle navigation" -msgstr "Lülita navigeerimine sisse" - -msgid "Sphinx Book Theme" -msgstr "Sfinksiraamatu teema" - -msgid "suggest edit" -msgstr "soovita muuta" - -msgid "Open an issue" -msgstr "Avage probleem" - -msgid "Launch" -msgstr "Käivitage" - -msgid "Fullscreen mode" -msgstr "Täisekraanirežiim" - -msgid "Edit this page" -msgstr "Muutke seda lehte" - -msgid "By the" -msgstr "Autor" - -msgid "next page" -msgstr "järgmine leht" diff --git a/_build/html/_static/locales/fi/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/fi/LC_MESSAGES/booktheme.mo deleted file mode 100644 index d8ac054..0000000 Binary files a/_build/html/_static/locales/fi/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/fi/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/fi/LC_MESSAGES/booktheme.po deleted file mode 100644 index 34dac21..0000000 --- a/_build/html/_static/locales/fi/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: fi\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Tulosta PDF-tiedostoon" - -msgid "Theme by the" -msgstr "Teeman tekijä" - -msgid "Download source file" -msgstr "Lataa lähdetiedosto" - -msgid "open issue" -msgstr "avoin ongelma" - -msgid "Contents" -msgstr "Sisällys" - -msgid "previous page" -msgstr "Edellinen sivu" - -msgid "Download notebook file" -msgstr "Lataa muistikirjatiedosto" - -msgid "Copyright" -msgstr "Tekijänoikeus" - -msgid "Download this page" -msgstr "Lataa tämä sivu" - -msgid "Source repository" -msgstr "Lähteen arkisto" - -msgid "By" -msgstr "Tekijä" - -msgid "repository" -msgstr "arkisto" - -msgid "Last updated on" -msgstr "Viimeksi päivitetty" - -msgid "Toggle navigation" -msgstr "Vaihda navigointia" - -msgid "Sphinx Book Theme" -msgstr "Sphinx-kirjan teema" - -msgid "suggest edit" -msgstr "ehdottaa muokkausta" - -msgid "Open an issue" -msgstr "Avaa ongelma" - -msgid "Launch" -msgstr "Tuoda markkinoille" - -msgid "Fullscreen mode" -msgstr "Koko näytön tila" - -msgid "Edit this page" -msgstr "Muokkaa tätä sivua" - -msgid "By the" -msgstr "Mukaan" - -msgid "next page" -msgstr "seuraava sivu" diff --git a/_build/html/_static/locales/fr/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/fr/LC_MESSAGES/booktheme.mo deleted file mode 100644 index f663d39..0000000 Binary files a/_build/html/_static/locales/fr/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/fr/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/fr/LC_MESSAGES/booktheme.po deleted file mode 100644 index 8991a1b..0000000 --- a/_build/html/_static/locales/fr/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: fr\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Imprimer au format PDF" - -msgid "Theme by the" -msgstr "Thème par le" - -msgid "Download source file" -msgstr "Télécharger le fichier source" - -msgid "open issue" -msgstr "signaler un problème" - -msgid "Contents" -msgstr "Contenu" - -msgid "previous page" -msgstr "page précédente" - -msgid "Download notebook file" -msgstr "Télécharger le fichier notebook" - -msgid "Copyright" -msgstr "droits d'auteur" - -msgid "Download this page" -msgstr "Téléchargez cette page" - -msgid "Source repository" -msgstr "Dépôt source" - -msgid "By" -msgstr "Par" - -msgid "repository" -msgstr "dépôt" - -msgid "Last updated on" -msgstr "Dernière mise à jour le" - -msgid "Toggle navigation" -msgstr "Basculer la navigation" - -msgid "Sphinx Book Theme" -msgstr "Thème du livre Sphinx" - -msgid "suggest edit" -msgstr "suggestion de modification" - -msgid "Open an issue" -msgstr "Ouvrez un problème" - -msgid "Launch" -msgstr "lancement" - -msgid "Fullscreen mode" -msgstr "Mode plein écran" - -msgid "Edit this page" -msgstr "Modifier cette page" - -msgid "By the" -msgstr "Par le" - -msgid "next page" -msgstr "page suivante" diff --git a/_build/html/_static/locales/hr/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/hr/LC_MESSAGES/booktheme.mo deleted file mode 100644 index eca4a1a..0000000 Binary files a/_build/html/_static/locales/hr/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/hr/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/hr/LC_MESSAGES/booktheme.po deleted file mode 100644 index 42c4233..0000000 --- a/_build/html/_static/locales/hr/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: hr\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Ispis u PDF" - -msgid "Theme by the" -msgstr "Tema autora" - -msgid "Download source file" -msgstr "Preuzmi izvornu datoteku" - -msgid "open issue" -msgstr "otvoreno izdanje" - -msgid "Contents" -msgstr "Sadržaj" - -msgid "previous page" -msgstr "Prethodna stranica" - -msgid "Download notebook file" -msgstr "Preuzmi datoteku bilježnice" - -msgid "Copyright" -msgstr "Autorska prava" - -msgid "Download this page" -msgstr "Preuzmite ovu stranicu" - -msgid "Source repository" -msgstr "Izvorno spremište" - -msgid "By" -msgstr "Po" - -msgid "repository" -msgstr "spremište" - -msgid "Last updated on" -msgstr "Posljednje ažuriranje:" - -msgid "Toggle navigation" -msgstr "Uključi / isključi navigaciju" - -msgid "Sphinx Book Theme" -msgstr "Tema knjige Sphinx" - -msgid "suggest edit" -msgstr "predloži uređivanje" - -msgid "Open an issue" -msgstr "Otvorite izdanje" - -msgid "Launch" -msgstr "Pokrenite" - -msgid "Fullscreen mode" -msgstr "Način preko cijelog zaslona" - -msgid "Edit this page" -msgstr "Uredite ovu stranicu" - -msgid "By the" -msgstr "Od strane" - -msgid "next page" -msgstr "sljedeća stranica" diff --git a/_build/html/_static/locales/id/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/id/LC_MESSAGES/booktheme.mo deleted file mode 100644 index d07a06a..0000000 Binary files a/_build/html/_static/locales/id/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/id/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/id/LC_MESSAGES/booktheme.po deleted file mode 100644 index b8d8d89..0000000 --- a/_build/html/_static/locales/id/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: id\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Cetak ke PDF" - -msgid "Theme by the" -msgstr "Tema oleh" - -msgid "Download source file" -msgstr "Unduh file sumber" - -msgid "open issue" -msgstr "masalah terbuka" - -msgid "Contents" -msgstr "Isi" - -msgid "previous page" -msgstr "halaman sebelumnya" - -msgid "Download notebook file" -msgstr "Unduh file notebook" - -msgid "Copyright" -msgstr "hak cipta" - -msgid "Download this page" -msgstr "Unduh halaman ini" - -msgid "Source repository" -msgstr "Repositori sumber" - -msgid "By" -msgstr "Oleh" - -msgid "repository" -msgstr "gudang" - -msgid "Last updated on" -msgstr "Terakhir diperbarui saat" - -msgid "Toggle navigation" -msgstr "Alihkan navigasi" - -msgid "Sphinx Book Theme" -msgstr "Tema Buku Sphinx" - -msgid "suggest edit" -msgstr "menyarankan edit" - -msgid "Open an issue" -msgstr "Buka masalah" - -msgid "Launch" -msgstr "Meluncurkan" - -msgid "Fullscreen mode" -msgstr "Mode layar penuh" - -msgid "Edit this page" -msgstr "Edit halaman ini" - -msgid "By the" -msgstr "Oleh" - -msgid "next page" -msgstr "halaman selanjutnya" diff --git a/_build/html/_static/locales/it/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/it/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 53ba476..0000000 Binary files a/_build/html/_static/locales/it/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/it/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/it/LC_MESSAGES/booktheme.po deleted file mode 100644 index 36fca59..0000000 --- a/_build/html/_static/locales/it/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: it\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Stampa in PDF" - -msgid "Theme by the" -msgstr "Tema di" - -msgid "Download source file" -msgstr "Scarica il file sorgente" - -msgid "open issue" -msgstr "questione aperta" - -msgid "Contents" -msgstr "Contenuti" - -msgid "previous page" -msgstr "pagina precedente" - -msgid "Download notebook file" -msgstr "Scarica il file del taccuino" - -msgid "Copyright" -msgstr "Diritto d'autore" - -msgid "Download this page" -msgstr "Scarica questa pagina" - -msgid "Source repository" -msgstr "Repository di origine" - -msgid "By" -msgstr "Di" - -msgid "repository" -msgstr "repository" - -msgid "Last updated on" -msgstr "Ultimo aggiornamento il" - -msgid "Toggle navigation" -msgstr "Attiva / disattiva la navigazione" - -msgid "Sphinx Book Theme" -msgstr "Tema del libro della Sfinge" - -msgid "suggest edit" -msgstr "suggerisci modifica" - -msgid "Open an issue" -msgstr "Apri un problema" - -msgid "Launch" -msgstr "Lanciare" - -msgid "Fullscreen mode" -msgstr "Modalità schermo intero" - -msgid "Edit this page" -msgstr "Modifica questa pagina" - -msgid "By the" -msgstr "Dal" - -msgid "next page" -msgstr "pagina successiva" diff --git a/_build/html/_static/locales/iw/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/iw/LC_MESSAGES/booktheme.mo deleted file mode 100644 index a45c657..0000000 Binary files a/_build/html/_static/locales/iw/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/iw/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/iw/LC_MESSAGES/booktheme.po deleted file mode 100644 index dede9cb..0000000 --- a/_build/html/_static/locales/iw/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: iw\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "הדפס לקובץ PDF" - -msgid "Theme by the" -msgstr "נושא מאת" - -msgid "Download source file" -msgstr "הורד את קובץ המקור" - -msgid "open issue" -msgstr "בעיה פתוחה" - -msgid "Contents" -msgstr "תוכן" - -msgid "previous page" -msgstr "עמוד קודם" - -msgid "Download notebook file" -msgstr "הורד קובץ מחברת" - -msgid "Copyright" -msgstr "זכויות יוצרים" - -msgid "Download this page" -msgstr "הורד דף זה" - -msgid "Source repository" -msgstr "מאגר המקורות" - -msgid "By" -msgstr "על ידי" - -msgid "repository" -msgstr "מאגר" - -msgid "Last updated on" -msgstr "עודכן לאחרונה ב" - -msgid "Toggle navigation" -msgstr "החלף ניווט" - -msgid "Sphinx Book Theme" -msgstr "נושא ספר ספינקס" - -msgid "suggest edit" -msgstr "מציע לערוך" - -msgid "Open an issue" -msgstr "פתח גיליון" - -msgid "Launch" -msgstr "לְהַשִׁיק" - -msgid "Fullscreen mode" -msgstr "מצב מסך מלא" - -msgid "Edit this page" -msgstr "ערוך דף זה" - -msgid "By the" -msgstr "דרך" - -msgid "next page" -msgstr "עמוד הבא" diff --git a/_build/html/_static/locales/ja/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ja/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 1cefd29..0000000 Binary files a/_build/html/_static/locales/ja/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ja/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ja/LC_MESSAGES/booktheme.po deleted file mode 100644 index 2615f0d..0000000 --- a/_build/html/_static/locales/ja/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ja\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "PDFに印刷" - -msgid "Theme by the" -msgstr "のテーマ" - -msgid "Download source file" -msgstr "ソースファイルをダウンロード" - -msgid "open issue" -msgstr "未解決の問題" - -msgid "Contents" -msgstr "目次" - -msgid "previous page" -msgstr "前のページ" - -msgid "Download notebook file" -msgstr "ノートブックファイルをダウンロード" - -msgid "Copyright" -msgstr "Copyright" - -msgid "Download this page" -msgstr "このページをダウンロード" - -msgid "Source repository" -msgstr "ソースリポジトリ" - -msgid "By" -msgstr "著者" - -msgid "repository" -msgstr "リポジトリ" - -msgid "Last updated on" -msgstr "最終更新日" - -msgid "Toggle navigation" -msgstr "ナビゲーションを切り替え" - -msgid "Sphinx Book Theme" -msgstr "スフィンクスの本のテーマ" - -msgid "suggest edit" -msgstr "編集を提案する" - -msgid "Open an issue" -msgstr "問題を報告" - -msgid "Launch" -msgstr "起動" - -msgid "Fullscreen mode" -msgstr "全画面モード" - -msgid "Edit this page" -msgstr "このページを編集" - -msgid "By the" -msgstr "によって" - -msgid "next page" -msgstr "次のページ" diff --git a/_build/html/_static/locales/ko/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ko/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 06c7ec9..0000000 Binary files a/_build/html/_static/locales/ko/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ko/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ko/LC_MESSAGES/booktheme.po deleted file mode 100644 index c9e13a4..0000000 --- a/_build/html/_static/locales/ko/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ko\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "PDF로 인쇄" - -msgid "Theme by the" -msgstr "테마별" - -msgid "Download source file" -msgstr "소스 파일 다운로드" - -msgid "open issue" -msgstr "열린 문제" - -msgid "Contents" -msgstr "내용" - -msgid "previous page" -msgstr "이전 페이지" - -msgid "Download notebook file" -msgstr "노트북 파일 다운로드" - -msgid "Copyright" -msgstr "저작권" - -msgid "Download this page" -msgstr "이 페이지 다운로드" - -msgid "Source repository" -msgstr "소스 저장소" - -msgid "By" -msgstr "으로" - -msgid "repository" -msgstr "저장소" - -msgid "Last updated on" -msgstr "마지막 업데이트" - -msgid "Toggle navigation" -msgstr "탐색 전환" - -msgid "Sphinx Book Theme" -msgstr "스핑크스 도서 테마" - -msgid "suggest edit" -msgstr "편집 제안" - -msgid "Open an issue" -msgstr "이슈 열기" - -msgid "Launch" -msgstr "시작하다" - -msgid "Fullscreen mode" -msgstr "전체 화면으로보기" - -msgid "Edit this page" -msgstr "이 페이지 편집" - -msgid "By the" -msgstr "에 의해" - -msgid "next page" -msgstr "다음 페이지" diff --git a/_build/html/_static/locales/lt/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/lt/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 4468ba0..0000000 Binary files a/_build/html/_static/locales/lt/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/lt/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/lt/LC_MESSAGES/booktheme.po deleted file mode 100644 index 35eabd9..0000000 --- a/_build/html/_static/locales/lt/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: lt\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Spausdinti į PDF" - -msgid "Theme by the" -msgstr "Tema" - -msgid "Download source file" -msgstr "Atsisiųsti šaltinio failą" - -msgid "open issue" -msgstr "atviras klausimas" - -msgid "Contents" -msgstr "Turinys" - -msgid "previous page" -msgstr "Ankstesnis puslapis" - -msgid "Download notebook file" -msgstr "Atsisiųsti nešiojamojo kompiuterio failą" - -msgid "Copyright" -msgstr "Autorių teisės" - -msgid "Download this page" -msgstr "Atsisiųskite šį puslapį" - -msgid "Source repository" -msgstr "Šaltinio saugykla" - -msgid "By" -msgstr "Iki" - -msgid "repository" -msgstr "saugykla" - -msgid "Last updated on" -msgstr "Paskutinį kartą atnaujinta" - -msgid "Toggle navigation" -msgstr "Perjungti naršymą" - -msgid "Sphinx Book Theme" -msgstr "Sfinkso knygos tema" - -msgid "suggest edit" -msgstr "pasiūlyti redaguoti" - -msgid "Open an issue" -msgstr "Atidarykite problemą" - -msgid "Launch" -msgstr "Paleiskite" - -msgid "Fullscreen mode" -msgstr "Pilno ekrano režimas" - -msgid "Edit this page" -msgstr "Redaguoti šį puslapį" - -msgid "By the" -msgstr "Prie" - -msgid "next page" -msgstr "Kitas puslapis" diff --git a/_build/html/_static/locales/lv/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/lv/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 74aa4d8..0000000 Binary files a/_build/html/_static/locales/lv/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/lv/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/lv/LC_MESSAGES/booktheme.po deleted file mode 100644 index ee1bd08..0000000 --- a/_build/html/_static/locales/lv/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: lv\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Drukāt PDF formātā" - -msgid "Theme by the" -msgstr "Autora tēma" - -msgid "Download source file" -msgstr "Lejupielādēt avota failu" - -msgid "open issue" -msgstr "atklāts jautājums" - -msgid "Contents" -msgstr "Saturs" - -msgid "previous page" -msgstr "iepriekšējā lapa" - -msgid "Download notebook file" -msgstr "Lejupielādēt piezīmju grāmatiņu" - -msgid "Copyright" -msgstr "Autortiesības" - -msgid "Download this page" -msgstr "Lejupielādējiet šo lapu" - -msgid "Source repository" -msgstr "Avota krātuve" - -msgid "By" -msgstr "Autors" - -msgid "repository" -msgstr "krātuve" - -msgid "Last updated on" -msgstr "Pēdējoreiz atjaunināts" - -msgid "Toggle navigation" -msgstr "Pārslēgt navigāciju" - -msgid "Sphinx Book Theme" -msgstr "Sfinksa grāmatas tēma" - -msgid "suggest edit" -msgstr "ieteikt rediģēt" - -msgid "Open an issue" -msgstr "Atveriet problēmu" - -msgid "Launch" -msgstr "Uzsākt" - -msgid "Fullscreen mode" -msgstr "Pilnekrāna režīms" - -msgid "Edit this page" -msgstr "Rediģēt šo lapu" - -msgid "By the" -msgstr "Ar" - -msgid "next page" -msgstr "nākamā lapaspuse" diff --git a/_build/html/_static/locales/ml/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ml/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 2736e8f..0000000 Binary files a/_build/html/_static/locales/ml/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ml/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ml/LC_MESSAGES/booktheme.po deleted file mode 100644 index d471277..0000000 --- a/_build/html/_static/locales/ml/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ml\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "PDF- ലേക്ക് പ്രിന്റുചെയ്യുക" - -msgid "Theme by the" -msgstr "പ്രമേയം" - -msgid "Download source file" -msgstr "ഉറവിട ഫയൽ ഡൗൺലോഡുചെയ്യുക" - -msgid "open issue" -msgstr "തുറന്ന പ്രശ്നം" - -msgid "previous page" -msgstr "മുൻപത്തെ താൾ" - -msgid "Download notebook file" -msgstr "നോട്ട്ബുക്ക് ഫയൽ ഡൺലോഡ് ചെയ്യുക" - -msgid "Copyright" -msgstr "പകർപ്പവകാശം" - -msgid "Download this page" -msgstr "ഈ പേജ് ഡൗൺലോഡുചെയ്യുക" - -msgid "Source repository" -msgstr "ഉറവിട ശേഖരം" - -msgid "By" -msgstr "എഴുതിയത്" - -msgid "Last updated on" -msgstr "അവസാനം അപ്‌ഡേറ്റുചെയ്‌തത്" - -msgid "Toggle navigation" -msgstr "നാവിഗേഷൻ ടോഗിൾ ചെയ്യുക" - -msgid "Sphinx Book Theme" -msgstr "സ്ഫിങ്ക്സ് പുസ്തക തീം" - -msgid "suggest edit" -msgstr "എഡിറ്റുചെയ്യാൻ നിർദ്ദേശിക്കുക" - -msgid "Open an issue" -msgstr "ഒരു പ്രശ്നം തുറക്കുക" - -msgid "Launch" -msgstr "സമാരംഭിക്കുക" - -msgid "Edit this page" -msgstr "ഈ പേജ് എഡിറ്റുചെയ്യുക" - -msgid "By the" -msgstr "എഴുതിയത്" - -msgid "next page" -msgstr "അടുത്ത പേജ്" diff --git a/_build/html/_static/locales/mr/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/mr/LC_MESSAGES/booktheme.mo deleted file mode 100644 index fe53010..0000000 Binary files a/_build/html/_static/locales/mr/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/mr/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/mr/LC_MESSAGES/booktheme.po deleted file mode 100644 index f3694ac..0000000 --- a/_build/html/_static/locales/mr/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: mr\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "पीडीएफवर मुद्रित करा" - -msgid "Theme by the" -msgstr "द्वारा थीम" - -msgid "Download source file" -msgstr "स्त्रोत फाइल डाउनलोड करा" - -msgid "open issue" -msgstr "खुला मुद्दा" - -msgid "previous page" -msgstr "मागील पान" - -msgid "Download notebook file" -msgstr "नोटबुक फाईल डाउनलोड करा" - -msgid "Copyright" -msgstr "कॉपीराइट" - -msgid "Download this page" -msgstr "हे पृष्ठ डाउनलोड करा" - -msgid "Source repository" -msgstr "स्त्रोत भांडार" - -msgid "By" -msgstr "द्वारा" - -msgid "Last updated on" -msgstr "अखेरचे अद्यतनित" - -msgid "Toggle navigation" -msgstr "नेव्हिगेशन टॉगल करा" - -msgid "Sphinx Book Theme" -msgstr "स्फिंक्स बुक थीम" - -msgid "suggest edit" -msgstr "संपादन सुचवा" - -msgid "Open an issue" -msgstr "एक मुद्दा उघडा" - -msgid "Launch" -msgstr "लाँच करा" - -msgid "Edit this page" -msgstr "हे पृष्ठ संपादित करा" - -msgid "By the" -msgstr "द्वारा" - -msgid "next page" -msgstr "पुढील पृष्ठ" diff --git a/_build/html/_static/locales/ms/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ms/LC_MESSAGES/booktheme.mo deleted file mode 100644 index f02603f..0000000 Binary files a/_build/html/_static/locales/ms/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ms/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ms/LC_MESSAGES/booktheme.po deleted file mode 100644 index 65b7c60..0000000 --- a/_build/html/_static/locales/ms/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ms\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Cetak ke PDF" - -msgid "Theme by the" -msgstr "Tema oleh" - -msgid "Download source file" -msgstr "Muat turun fail sumber" - -msgid "open issue" -msgstr "isu terbuka" - -msgid "previous page" -msgstr "halaman sebelumnya" - -msgid "Download notebook file" -msgstr "Muat turun fail buku nota" - -msgid "Copyright" -msgstr "hak cipta" - -msgid "Download this page" -msgstr "Muat turun halaman ini" - -msgid "Source repository" -msgstr "Repositori sumber" - -msgid "By" -msgstr "Oleh" - -msgid "Last updated on" -msgstr "Terakhir dikemas kini pada" - -msgid "Toggle navigation" -msgstr "Togol navigasi" - -msgid "Sphinx Book Theme" -msgstr "Tema Buku Sphinx" - -msgid "suggest edit" -msgstr "cadangkan edit" - -msgid "Open an issue" -msgstr "Buka masalah" - -msgid "Launch" -msgstr "Lancarkan" - -msgid "Edit this page" -msgstr "Edit halaman ini" - -msgid "By the" -msgstr "Oleh" - -msgid "next page" -msgstr "muka surat seterusnya" diff --git a/_build/html/_static/locales/nl/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/nl/LC_MESSAGES/booktheme.mo deleted file mode 100644 index e59e7ec..0000000 Binary files a/_build/html/_static/locales/nl/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/nl/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/nl/LC_MESSAGES/booktheme.po deleted file mode 100644 index 71bd1cd..0000000 --- a/_build/html/_static/locales/nl/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: nl\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Afdrukken naar pdf" - -msgid "Theme by the" -msgstr "Thema door de" - -msgid "Download source file" -msgstr "Download het bronbestand" - -msgid "open issue" -msgstr "open probleem" - -msgid "Contents" -msgstr "Inhoud" - -msgid "previous page" -msgstr "vorige pagina" - -msgid "Download notebook file" -msgstr "Download notebookbestand" - -msgid "Copyright" -msgstr "auteursrechten" - -msgid "Download this page" -msgstr "Download deze pagina" - -msgid "Source repository" -msgstr "Bronopslagplaats" - -msgid "By" -msgstr "Door" - -msgid "repository" -msgstr "repository" - -msgid "Last updated on" -msgstr "Laatst geupdate op" - -msgid "Toggle navigation" -msgstr "Schakel navigatie" - -msgid "Sphinx Book Theme" -msgstr "Sphinx-boekthema" - -msgid "suggest edit" -msgstr "suggereren bewerken" - -msgid "Open an issue" -msgstr "Open een probleem" - -msgid "Launch" -msgstr "Lancering" - -msgid "Fullscreen mode" -msgstr "Volledig scherm" - -msgid "Edit this page" -msgstr "bewerk deze pagina" - -msgid "By the" -msgstr "Door de" - -msgid "next page" -msgstr "volgende bladzijde" diff --git a/_build/html/_static/locales/no/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/no/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 6cd15c8..0000000 Binary files a/_build/html/_static/locales/no/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/no/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/no/LC_MESSAGES/booktheme.po deleted file mode 100644 index b21346a..0000000 --- a/_build/html/_static/locales/no/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: no\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Skriv ut til PDF" - -msgid "Theme by the" -msgstr "Tema av" - -msgid "Download source file" -msgstr "Last ned kildefilen" - -msgid "open issue" -msgstr "åpent nummer" - -msgid "Contents" -msgstr "Innhold" - -msgid "previous page" -msgstr "forrige side" - -msgid "Download notebook file" -msgstr "Last ned notatbokfilen" - -msgid "Copyright" -msgstr "opphavsrett" - -msgid "Download this page" -msgstr "Last ned denne siden" - -msgid "Source repository" -msgstr "Kildedepot" - -msgid "By" -msgstr "Av" - -msgid "repository" -msgstr "oppbevaringssted" - -msgid "Last updated on" -msgstr "Sist oppdatert den" - -msgid "Toggle navigation" -msgstr "Bytt navigasjon" - -msgid "Sphinx Book Theme" -msgstr "Sphinx boktema" - -msgid "suggest edit" -msgstr "foreslå redigering" - -msgid "Open an issue" -msgstr "Åpne et problem" - -msgid "Launch" -msgstr "Start" - -msgid "Fullscreen mode" -msgstr "Fullskjerm-modus" - -msgid "Edit this page" -msgstr "Rediger denne siden" - -msgid "By the" -msgstr "Ved" - -msgid "next page" -msgstr "neste side" diff --git a/_build/html/_static/locales/pl/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/pl/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 9ebb584..0000000 Binary files a/_build/html/_static/locales/pl/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/pl/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/pl/LC_MESSAGES/booktheme.po deleted file mode 100644 index 1b7233f..0000000 --- a/_build/html/_static/locales/pl/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: pl\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Drukuj do PDF" - -msgid "Theme by the" -msgstr "Motyw autorstwa" - -msgid "Download source file" -msgstr "Pobierz plik źródłowy" - -msgid "open issue" -msgstr "otwarty problem" - -msgid "Contents" -msgstr "Zawartość" - -msgid "previous page" -msgstr "Poprzednia strona" - -msgid "Download notebook file" -msgstr "Pobierz plik notatnika" - -msgid "Copyright" -msgstr "prawa autorskie" - -msgid "Download this page" -msgstr "Pobierz tę stronę" - -msgid "Source repository" -msgstr "Repozytorium źródłowe" - -msgid "By" -msgstr "Przez" - -msgid "repository" -msgstr "magazyn" - -msgid "Last updated on" -msgstr "Ostatnia aktualizacja" - -msgid "Toggle navigation" -msgstr "Przełącz nawigację" - -msgid "Sphinx Book Theme" -msgstr "Motyw książki Sphinx" - -msgid "suggest edit" -msgstr "zaproponuj edycję" - -msgid "Open an issue" -msgstr "Otwórz problem" - -msgid "Launch" -msgstr "Uruchomić" - -msgid "Fullscreen mode" -msgstr "Pełny ekran" - -msgid "Edit this page" -msgstr "Edytuj tę strone" - -msgid "By the" -msgstr "Przez" - -msgid "next page" -msgstr "Następna strona" diff --git a/_build/html/_static/locales/pt/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/pt/LC_MESSAGES/booktheme.mo deleted file mode 100644 index d0ddb87..0000000 Binary files a/_build/html/_static/locales/pt/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/pt/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/pt/LC_MESSAGES/booktheme.po deleted file mode 100644 index 1b27314..0000000 --- a/_build/html/_static/locales/pt/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: pt\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Imprimir em PDF" - -msgid "Theme by the" -msgstr "Tema por" - -msgid "Download source file" -msgstr "Baixar arquivo fonte" - -msgid "open issue" -msgstr "questão aberta" - -msgid "Contents" -msgstr "Conteúdo" - -msgid "previous page" -msgstr "página anterior" - -msgid "Download notebook file" -msgstr "Baixar arquivo de notebook" - -msgid "Copyright" -msgstr "direito autoral" - -msgid "Download this page" -msgstr "Baixe esta página" - -msgid "Source repository" -msgstr "Repositório fonte" - -msgid "By" -msgstr "De" - -msgid "repository" -msgstr "repositório" - -msgid "Last updated on" -msgstr "Última atualização em" - -msgid "Toggle navigation" -msgstr "Alternar de navegação" - -msgid "Sphinx Book Theme" -msgstr "Tema do livro Sphinx" - -msgid "suggest edit" -msgstr "sugerir edição" - -msgid "Open an issue" -msgstr "Abra um problema" - -msgid "Launch" -msgstr "Lançamento" - -msgid "Fullscreen mode" -msgstr "Modo tela cheia" - -msgid "Edit this page" -msgstr "Edite essa página" - -msgid "By the" -msgstr "Pelo" - -msgid "next page" -msgstr "próxima página" diff --git a/_build/html/_static/locales/ro/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ro/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 3c36ab1..0000000 Binary files a/_build/html/_static/locales/ro/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ro/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ro/LC_MESSAGES/booktheme.po deleted file mode 100644 index 1783ad2..0000000 --- a/_build/html/_static/locales/ro/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ro\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Imprimați în PDF" - -msgid "Theme by the" -msgstr "Tema de" - -msgid "Download source file" -msgstr "Descărcați fișierul sursă" - -msgid "open issue" -msgstr "problema deschisă" - -msgid "Contents" -msgstr "Cuprins" - -msgid "previous page" -msgstr "pagina anterioară" - -msgid "Download notebook file" -msgstr "Descărcați fișierul notebook" - -msgid "Copyright" -msgstr "Drepturi de autor" - -msgid "Download this page" -msgstr "Descarcă această pagină" - -msgid "Source repository" -msgstr "Depozit sursă" - -msgid "By" -msgstr "De" - -msgid "repository" -msgstr "repertoriu" - -msgid "Last updated on" -msgstr "Ultima actualizare la" - -msgid "Toggle navigation" -msgstr "Comutare navigare" - -msgid "Sphinx Book Theme" -msgstr "Tema Sphinx Book" - -msgid "suggest edit" -msgstr "sugerează editare" - -msgid "Open an issue" -msgstr "Deschideți o problemă" - -msgid "Launch" -msgstr "Lansa" - -msgid "Fullscreen mode" -msgstr "Modul ecran întreg" - -msgid "Edit this page" -msgstr "Editați această pagină" - -msgid "By the" -msgstr "Langa" - -msgid "next page" -msgstr "pagina următoare" diff --git a/_build/html/_static/locales/ru/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ru/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 6b8ca41..0000000 Binary files a/_build/html/_static/locales/ru/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ru/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ru/LC_MESSAGES/booktheme.po deleted file mode 100644 index b1176b7..0000000 --- a/_build/html/_static/locales/ru/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ru\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Распечатать в PDF" - -msgid "Theme by the" -msgstr "Тема от" - -msgid "Download source file" -msgstr "Скачать исходный файл" - -msgid "open issue" -msgstr "открытый вопрос" - -msgid "Contents" -msgstr "Содержание" - -msgid "previous page" -msgstr "Предыдущая страница" - -msgid "Download notebook file" -msgstr "Скачать файл записной книжки" - -msgid "Copyright" -msgstr "авторское право" - -msgid "Download this page" -msgstr "Загрузите эту страницу" - -msgid "Source repository" -msgstr "Исходный репозиторий" - -msgid "By" -msgstr "По" - -msgid "repository" -msgstr "хранилище" - -msgid "Last updated on" -msgstr "Последнее обновление" - -msgid "Toggle navigation" -msgstr "Переключить навигацию" - -msgid "Sphinx Book Theme" -msgstr "Тема книги Сфинкс" - -msgid "suggest edit" -msgstr "предложить редактировать" - -msgid "Open an issue" -msgstr "Открыть вопрос" - -msgid "Launch" -msgstr "Запуск" - -msgid "Fullscreen mode" -msgstr "Полноэкранный режим" - -msgid "Edit this page" -msgstr "Редактировать эту страницу" - -msgid "By the" -msgstr "Посредством" - -msgid "next page" -msgstr "Следующая страница" diff --git a/_build/html/_static/locales/sk/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/sk/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 59bd0dd..0000000 Binary files a/_build/html/_static/locales/sk/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/sk/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/sk/LC_MESSAGES/booktheme.po deleted file mode 100644 index 6501288..0000000 --- a/_build/html/_static/locales/sk/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: sk\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Tlač do PDF" - -msgid "Theme by the" -msgstr "Téma od" - -msgid "Download source file" -msgstr "Stiahnite si zdrojový súbor" - -msgid "open issue" -msgstr "otvorené vydanie" - -msgid "Contents" -msgstr "Obsah" - -msgid "previous page" -msgstr "predchádzajúca strana" - -msgid "Download notebook file" -msgstr "Stiahnite si zošit" - -msgid "Copyright" -msgstr "Autorské práva" - -msgid "Download this page" -msgstr "Stiahnite si túto stránku" - -msgid "Source repository" -msgstr "Zdrojové úložisko" - -msgid "By" -msgstr "Autor:" - -msgid "repository" -msgstr "Úložisko" - -msgid "Last updated on" -msgstr "Posledná aktualizácia dňa" - -msgid "Toggle navigation" -msgstr "Prepnúť navigáciu" - -msgid "Sphinx Book Theme" -msgstr "Téma knihy Sfinga" - -msgid "suggest edit" -msgstr "navrhnúť úpravu" - -msgid "Open an issue" -msgstr "Otvorte problém" - -msgid "Launch" -msgstr "Spustiť" - -msgid "Fullscreen mode" -msgstr "Režim celej obrazovky" - -msgid "Edit this page" -msgstr "Upraviť túto stránku" - -msgid "By the" -msgstr "Podľa" - -msgid "next page" -msgstr "ďalšia strana" diff --git a/_build/html/_static/locales/sl/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/sl/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 87bf26d..0000000 Binary files a/_build/html/_static/locales/sl/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/sl/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/sl/LC_MESSAGES/booktheme.po deleted file mode 100644 index 3c7e3a8..0000000 --- a/_build/html/_static/locales/sl/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: sl\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Natisni v PDF" - -msgid "Theme by the" -msgstr "Tema avtorja" - -msgid "Download source file" -msgstr "Prenesite izvorno datoteko" - -msgid "open issue" -msgstr "odprto vprašanje" - -msgid "Contents" -msgstr "Vsebina" - -msgid "previous page" -msgstr "Prejšnja stran" - -msgid "Download notebook file" -msgstr "Prenesite datoteko zvezka" - -msgid "Copyright" -msgstr "avtorske pravice" - -msgid "Download this page" -msgstr "Prenesite to stran" - -msgid "Source repository" -msgstr "Izvorno skladišče" - -msgid "By" -msgstr "Avtor" - -msgid "repository" -msgstr "odlagališče" - -msgid "Last updated on" -msgstr "Nazadnje posodobljeno dne" - -msgid "Toggle navigation" -msgstr "Preklopi navigacijo" - -msgid "Sphinx Book Theme" -msgstr "Tema knjige Sphinx" - -msgid "suggest edit" -msgstr "predlagajte urejanje" - -msgid "Open an issue" -msgstr "Odprite številko" - -msgid "Launch" -msgstr "Kosilo" - -msgid "Fullscreen mode" -msgstr "Celozaslonski način" - -msgid "Edit this page" -msgstr "Uredite to stran" - -msgid "By the" -msgstr "Avtor" - -msgid "next page" -msgstr "Naslednja stran" diff --git a/_build/html/_static/locales/sr/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/sr/LC_MESSAGES/booktheme.mo deleted file mode 100644 index ec740f4..0000000 Binary files a/_build/html/_static/locales/sr/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/sr/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/sr/LC_MESSAGES/booktheme.po deleted file mode 100644 index 773b8ad..0000000 --- a/_build/html/_static/locales/sr/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: sr\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Испис у ПДФ" - -msgid "Theme by the" -msgstr "Тхеме би" - -msgid "Download source file" -msgstr "Преузми изворну датотеку" - -msgid "open issue" -msgstr "отворено издање" - -msgid "Contents" -msgstr "Садржај" - -msgid "previous page" -msgstr "Претходна страница" - -msgid "Download notebook file" -msgstr "Преузмите датотеку бележнице" - -msgid "Copyright" -msgstr "Ауторско право" - -msgid "Download this page" -msgstr "Преузмите ову страницу" - -msgid "Source repository" -msgstr "Изворно спремиште" - -msgid "By" -msgstr "Од стране" - -msgid "repository" -msgstr "спремиште" - -msgid "Last updated on" -msgstr "Последње ажурирање" - -msgid "Toggle navigation" -msgstr "Укључи / искључи навигацију" - -msgid "Sphinx Book Theme" -msgstr "Тема књиге Спхинк" - -msgid "suggest edit" -msgstr "предложи уређивање" - -msgid "Open an issue" -msgstr "Отворите издање" - -msgid "Launch" -msgstr "Лансирање" - -msgid "Fullscreen mode" -msgstr "Режим целог екрана" - -msgid "Edit this page" -msgstr "Уредите ову страницу" - -msgid "By the" -msgstr "Од" - -msgid "next page" -msgstr "Следећа страна" diff --git a/_build/html/_static/locales/sv/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/sv/LC_MESSAGES/booktheme.mo deleted file mode 100644 index b07dc76..0000000 Binary files a/_build/html/_static/locales/sv/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/sv/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/sv/LC_MESSAGES/booktheme.po deleted file mode 100644 index bcac54c..0000000 --- a/_build/html/_static/locales/sv/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: sv\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Skriv ut till PDF" - -msgid "Theme by the" -msgstr "Tema av" - -msgid "Download source file" -msgstr "Ladda ner källfil" - -msgid "open issue" -msgstr "öppna problemrapport" - -msgid "Contents" -msgstr "Innehåll" - -msgid "previous page" -msgstr "föregående sida" - -msgid "Download notebook file" -msgstr "Ladda ner notebook-fil" - -msgid "Copyright" -msgstr "Upphovsrätt" - -msgid "Download this page" -msgstr "Ladda ner den här sidan" - -msgid "Source repository" -msgstr "Källkodsrepositorium" - -msgid "By" -msgstr "Av" - -msgid "repository" -msgstr "repositorium" - -msgid "Last updated on" -msgstr "Senast uppdaterad den" - -msgid "Toggle navigation" -msgstr "Växla navigering" - -msgid "Sphinx Book Theme" -msgstr "Sphinx Boktema" - -msgid "suggest edit" -msgstr "föreslå ändring" - -msgid "Open an issue" -msgstr "Öppna en problemrapport" - -msgid "Launch" -msgstr "Öppna" - -msgid "Fullscreen mode" -msgstr "Fullskärmsläge" - -msgid "Edit this page" -msgstr "Redigera den här sidan" - -msgid "By the" -msgstr "Av den" - -msgid "next page" -msgstr "nästa sida" diff --git a/_build/html/_static/locales/ta/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ta/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 29f52e1..0000000 Binary files a/_build/html/_static/locales/ta/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ta/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ta/LC_MESSAGES/booktheme.po deleted file mode 100644 index b48bdfa..0000000 --- a/_build/html/_static/locales/ta/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ta\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "PDF இல் அச்சிடுக" - -msgid "Theme by the" -msgstr "வழங்கிய தீம்" - -msgid "Download source file" -msgstr "மூல கோப்பைப் பதிவிறக்குக" - -msgid "open issue" -msgstr "திறந்த பிரச்சினை" - -msgid "previous page" -msgstr "முந்தைய பக்கம்" - -msgid "Download notebook file" -msgstr "நோட்புக் கோப்பைப் பதிவிறக்கவும்" - -msgid "Copyright" -msgstr "பதிப்புரிமை" - -msgid "Download this page" -msgstr "இந்தப் பக்கத்தைப் பதிவிறக்கவும்" - -msgid "Source repository" -msgstr "மூல களஞ்சியம்" - -msgid "By" -msgstr "வழங்கியவர்" - -msgid "Last updated on" -msgstr "கடைசியாக புதுப்பிக்கப்பட்டது" - -msgid "Toggle navigation" -msgstr "வழிசெலுத்தலை நிலைமாற்று" - -msgid "Sphinx Book Theme" -msgstr "ஸ்பிங்க்ஸ் புத்தக தீம்" - -msgid "suggest edit" -msgstr "திருத்த பரிந்துரைக்கவும்" - -msgid "Open an issue" -msgstr "சிக்கலைத் திறக்கவும்" - -msgid "Launch" -msgstr "தொடங்க" - -msgid "Edit this page" -msgstr "இந்தப் பக்கத்தைத் திருத்தவும்" - -msgid "By the" -msgstr "மூலம்" - -msgid "next page" -msgstr "அடுத்த பக்கம்" diff --git a/_build/html/_static/locales/te/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/te/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 0a5f4b4..0000000 Binary files a/_build/html/_static/locales/te/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/te/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/te/LC_MESSAGES/booktheme.po deleted file mode 100644 index 952278f..0000000 --- a/_build/html/_static/locales/te/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: te\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "PDF కి ముద్రించండి" - -msgid "Theme by the" -msgstr "ద్వారా థీమ్" - -msgid "Download source file" -msgstr "మూల ఫైల్‌ను డౌన్‌లోడ్ చేయండి" - -msgid "open issue" -msgstr "ఓపెన్ ఇష్యూ" - -msgid "previous page" -msgstr "ముందు పేజి" - -msgid "Download notebook file" -msgstr "నోట్బుక్ ఫైల్ను డౌన్లోడ్ చేయండి" - -msgid "Copyright" -msgstr "కాపీరైట్" - -msgid "Download this page" -msgstr "ఈ పేజీని డౌన్‌లోడ్ చేయండి" - -msgid "Source repository" -msgstr "మూల రిపోజిటరీ" - -msgid "By" -msgstr "ద్వారా" - -msgid "Last updated on" -msgstr "చివరిగా నవీకరించబడింది" - -msgid "Toggle navigation" -msgstr "నావిగేషన్‌ను టోగుల్ చేయండి" - -msgid "Sphinx Book Theme" -msgstr "సింహిక పుస్తక థీమ్" - -msgid "suggest edit" -msgstr "సవరించమని సూచించండి" - -msgid "Open an issue" -msgstr "సమస్యను తెరవండి" - -msgid "Launch" -msgstr "ప్రారంభించండి" - -msgid "Edit this page" -msgstr "ఈ పేజీని సవరించండి" - -msgid "By the" -msgstr "ద్వారా" - -msgid "next page" -msgstr "తరువాతి పేజీ" diff --git a/_build/html/_static/locales/tg/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/tg/LC_MESSAGES/booktheme.mo deleted file mode 100644 index b21c6c6..0000000 Binary files a/_build/html/_static/locales/tg/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/tg/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/tg/LC_MESSAGES/booktheme.po deleted file mode 100644 index c33dc42..0000000 --- a/_build/html/_static/locales/tg/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: tg\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Чоп ба PDF" - -msgid "Theme by the" -msgstr "Мавзӯъи аз" - -msgid "Download source file" -msgstr "Файли манбаъро зеркашӣ кунед" - -msgid "open issue" -msgstr "барориши кушод" - -msgid "Contents" -msgstr "Мундариҷа" - -msgid "previous page" -msgstr "саҳифаи қаблӣ" - -msgid "Download notebook file" -msgstr "Файли дафтарро зеркашӣ кунед" - -msgid "Copyright" -msgstr "Ҳуқуқи муаллиф" - -msgid "Download this page" -msgstr "Ин саҳифаро зеркашӣ кунед" - -msgid "Source repository" -msgstr "Анбори манбаъ" - -msgid "By" -msgstr "Бо" - -msgid "repository" -msgstr "анбор" - -msgid "Last updated on" -msgstr "Last навсозӣ дар" - -msgid "Toggle navigation" -msgstr "Гузаришро иваз кунед" - -msgid "Sphinx Book Theme" -msgstr "Сфинкс Мавзӯи китоб" - -msgid "suggest edit" -msgstr "пешниҳод вироиш" - -msgid "Open an issue" -msgstr "Масъаларо кушоед" - -msgid "Launch" -msgstr "Оғоз" - -msgid "Fullscreen mode" -msgstr "Ҳолати экрани пурра" - -msgid "Edit this page" -msgstr "Ин саҳифаро таҳрир кунед" - -msgid "By the" -msgstr "Бо" - -msgid "next page" -msgstr "саҳифаи оянда" diff --git a/_build/html/_static/locales/th/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/th/LC_MESSAGES/booktheme.mo deleted file mode 100644 index abede98..0000000 Binary files a/_build/html/_static/locales/th/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/th/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/th/LC_MESSAGES/booktheme.po deleted file mode 100644 index 9d24294..0000000 --- a/_build/html/_static/locales/th/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: th\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "พิมพ์เป็น PDF" - -msgid "Theme by the" -msgstr "ธีมโดย" - -msgid "Download source file" -msgstr "ดาวน์โหลดไฟล์ต้นฉบับ" - -msgid "open issue" -msgstr "เปิดปัญหา" - -msgid "Contents" -msgstr "สารบัญ" - -msgid "previous page" -msgstr "หน้าที่แล้ว" - -msgid "Download notebook file" -msgstr "ดาวน์โหลดไฟล์สมุดบันทึก" - -msgid "Copyright" -msgstr "ลิขสิทธิ์" - -msgid "Download this page" -msgstr "ดาวน์โหลดหน้านี้" - -msgid "Source repository" -msgstr "ที่เก็บซอร์ส" - -msgid "By" -msgstr "โดย" - -msgid "repository" -msgstr "ที่เก็บ" - -msgid "Last updated on" -msgstr "ปรับปรุงล่าสุดเมื่อ" - -msgid "Toggle navigation" -msgstr "ไม่ต้องสลับช่องทาง" - -msgid "Sphinx Book Theme" -msgstr "ธีมหนังสือสฟิงซ์" - -msgid "suggest edit" -msgstr "แนะนำแก้ไข" - -msgid "Open an issue" -msgstr "เปิดปัญหา" - -msgid "Launch" -msgstr "เปิด" - -msgid "Fullscreen mode" -msgstr "โหมดเต็มหน้าจอ" - -msgid "Edit this page" -msgstr "แก้ไขหน้านี้" - -msgid "By the" -msgstr "โดย" - -msgid "next page" -msgstr "หน้าต่อไป" diff --git a/_build/html/_static/locales/tl/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/tl/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 8df1b73..0000000 Binary files a/_build/html/_static/locales/tl/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/tl/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/tl/LC_MESSAGES/booktheme.po deleted file mode 100644 index 20e0d07..0000000 --- a/_build/html/_static/locales/tl/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: tl\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "I-print sa PDF" - -msgid "Theme by the" -msgstr "Tema ng" - -msgid "Download source file" -msgstr "Mag-download ng file ng pinagmulan" - -msgid "open issue" -msgstr "bukas na isyu" - -msgid "previous page" -msgstr "Nakaraang pahina" - -msgid "Download notebook file" -msgstr "Mag-download ng file ng notebook" - -msgid "Copyright" -msgstr "Copyright" - -msgid "Download this page" -msgstr "I-download ang pahinang ito" - -msgid "Source repository" -msgstr "Pinagmulan ng imbakan" - -msgid "By" -msgstr "Ni" - -msgid "Last updated on" -msgstr "Huling na-update noong" - -msgid "Toggle navigation" -msgstr "I-toggle ang pag-navigate" - -msgid "Sphinx Book Theme" -msgstr "Tema ng Sphinx Book" - -msgid "suggest edit" -msgstr "iminumungkahi i-edit" - -msgid "Open an issue" -msgstr "Magbukas ng isyu" - -msgid "Launch" -msgstr "Ilunsad" - -msgid "Edit this page" -msgstr "I-edit ang pahinang ito" - -msgid "By the" -msgstr "Sa pamamagitan ng" - -msgid "next page" -msgstr "Susunod na pahina" diff --git a/_build/html/_static/locales/tr/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/tr/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 029ae18..0000000 Binary files a/_build/html/_static/locales/tr/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/tr/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/tr/LC_MESSAGES/booktheme.po deleted file mode 100644 index a77eb02..0000000 --- a/_build/html/_static/locales/tr/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: tr\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "PDF olarak yazdır" - -msgid "Theme by the" -msgstr "Tarafından tema" - -msgid "Download source file" -msgstr "Kaynak dosyayı indirin" - -msgid "open issue" -msgstr "Açık konu" - -msgid "Contents" -msgstr "İçindekiler" - -msgid "previous page" -msgstr "önceki sayfa" - -msgid "Download notebook file" -msgstr "Defter dosyasını indirin" - -msgid "Copyright" -msgstr "Telif hakkı" - -msgid "Download this page" -msgstr "Bu sayfayı indirin" - -msgid "Source repository" -msgstr "Kaynak kod deposu" - -msgid "By" -msgstr "Tarafından" - -msgid "repository" -msgstr "depo" - -msgid "Last updated on" -msgstr "Son güncelleme tarihi" - -msgid "Toggle navigation" -msgstr "Gezinmeyi değiştir" - -msgid "Sphinx Book Theme" -msgstr "Sfenks Kitap Teması" - -msgid "suggest edit" -msgstr "düzenleme öner" - -msgid "Open an issue" -msgstr "Bir sorunu açın" - -msgid "Launch" -msgstr "Başlatmak" - -msgid "Fullscreen mode" -msgstr "Tam ekran modu" - -msgid "Edit this page" -msgstr "Bu sayfayı düzenle" - -msgid "By the" -msgstr "Tarafından" - -msgid "next page" -msgstr "sonraki Sayfa" diff --git a/_build/html/_static/locales/uk/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/uk/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 16ab789..0000000 Binary files a/_build/html/_static/locales/uk/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/uk/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/uk/LC_MESSAGES/booktheme.po deleted file mode 100644 index 993dd07..0000000 --- a/_build/html/_static/locales/uk/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: uk\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "Друк у форматі PDF" - -msgid "Theme by the" -msgstr "Тема від" - -msgid "Download source file" -msgstr "Завантажити вихідний файл" - -msgid "open issue" -msgstr "відкритий випуск" - -msgid "Contents" -msgstr "Зміст" - -msgid "previous page" -msgstr "Попередня сторінка" - -msgid "Download notebook file" -msgstr "Завантажте файл блокнота" - -msgid "Copyright" -msgstr "Авторське право" - -msgid "Download this page" -msgstr "Завантажте цю сторінку" - -msgid "Source repository" -msgstr "Джерело сховища" - -msgid "By" -msgstr "Автор" - -msgid "repository" -msgstr "сховище" - -msgid "Last updated on" -msgstr "Останнє оновлення:" - -msgid "Toggle navigation" -msgstr "Переключити навігацію" - -msgid "Sphinx Book Theme" -msgstr "Тема книги \"Сфінкс\"" - -msgid "suggest edit" -msgstr "запропонувати редагувати" - -msgid "Open an issue" -msgstr "Відкрийте випуск" - -msgid "Launch" -msgstr "Запуск" - -msgid "Fullscreen mode" -msgstr "Повноекранний режим" - -msgid "Edit this page" -msgstr "Редагувати цю сторінку" - -msgid "By the" -msgstr "По" - -msgid "next page" -msgstr "Наступна сторінка" diff --git a/_build/html/_static/locales/ur/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/ur/LC_MESSAGES/booktheme.mo deleted file mode 100644 index de8c84b..0000000 Binary files a/_build/html/_static/locales/ur/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/ur/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/ur/LC_MESSAGES/booktheme.po deleted file mode 100644 index 2f77426..0000000 --- a/_build/html/_static/locales/ur/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,66 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: ur\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "پی ڈی ایف پرنٹ کریں" - -msgid "Theme by the" -msgstr "کے ذریعہ تھیم" - -msgid "Download source file" -msgstr "سورس فائل ڈاؤن لوڈ کریں" - -msgid "open issue" -msgstr "کھلا مسئلہ" - -msgid "previous page" -msgstr "سابقہ ​​صفحہ" - -msgid "Download notebook file" -msgstr "نوٹ بک فائل ڈاؤن لوڈ کریں" - -msgid "Copyright" -msgstr "کاپی رائٹ" - -msgid "Download this page" -msgstr "اس صفحے کو ڈاؤن لوڈ کریں" - -msgid "Source repository" -msgstr "ماخذ ذخیرہ" - -msgid "By" -msgstr "بذریعہ" - -msgid "Last updated on" -msgstr "آخری بار تازہ کاری ہوئی" - -msgid "Toggle navigation" -msgstr "نیویگیشن ٹوگل کریں" - -msgid "Sphinx Book Theme" -msgstr "سپنکس بک تھیم" - -msgid "suggest edit" -msgstr "ترمیم کی تجویز کریں" - -msgid "Open an issue" -msgstr "ایک مسئلہ کھولیں" - -msgid "Launch" -msgstr "لانچ کریں" - -msgid "Edit this page" -msgstr "اس صفحے میں ترمیم کریں" - -msgid "By the" -msgstr "کی طرف" - -msgid "next page" -msgstr "اگلا صفحہ" diff --git a/_build/html/_static/locales/vi/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/vi/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 2bb3255..0000000 Binary files a/_build/html/_static/locales/vi/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/vi/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/vi/LC_MESSAGES/booktheme.po deleted file mode 100644 index 33159f3..0000000 --- a/_build/html/_static/locales/vi/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: vi\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "In sang PDF" - -msgid "Theme by the" -msgstr "Chủ đề của" - -msgid "Download source file" -msgstr "Tải xuống tệp nguồn" - -msgid "open issue" -msgstr "vấn đề mở" - -msgid "Contents" -msgstr "Nội dung" - -msgid "previous page" -msgstr "trang trước" - -msgid "Download notebook file" -msgstr "Tải xuống tệp sổ tay" - -msgid "Copyright" -msgstr "Bản quyền" - -msgid "Download this page" -msgstr "Tải xuống trang này" - -msgid "Source repository" -msgstr "Kho nguồn" - -msgid "By" -msgstr "Bởi" - -msgid "repository" -msgstr "kho" - -msgid "Last updated on" -msgstr "Cập nhật lần cuối vào" - -msgid "Toggle navigation" -msgstr "Chuyển đổi điều hướng thành" - -msgid "Sphinx Book Theme" -msgstr "Chủ đề sách nhân sư" - -msgid "suggest edit" -msgstr "đề nghị chỉnh sửa" - -msgid "Open an issue" -msgstr "Mở một vấn đề" - -msgid "Launch" -msgstr "Phóng" - -msgid "Fullscreen mode" -msgstr "Chế độ toàn màn hình" - -msgid "Edit this page" -msgstr "chỉnh sửa trang này" - -msgid "By the" -msgstr "Bằng" - -msgid "next page" -msgstr "Trang tiếp theo" diff --git a/_build/html/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 0e3235d..0000000 Binary files a/_build/html/_static/locales/zh_CN/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/zh_CN/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/zh_CN/LC_MESSAGES/booktheme.po deleted file mode 100644 index 2e519ef..0000000 --- a/_build/html/_static/locales/zh_CN/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: zh_CN\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "列印成 PDF" - -msgid "Theme by the" -msgstr "主题作者：" - -msgid "Download source file" -msgstr "下载源文件" - -msgid "open issue" -msgstr "创建议题" - -msgid "Contents" -msgstr "目录" - -msgid "previous page" -msgstr "上一页" - -msgid "Download notebook file" -msgstr "下载笔记本文件" - -msgid "Copyright" -msgstr "版权" - -msgid "Download this page" -msgstr "下载此页面" - -msgid "Source repository" -msgstr "源码库" - -msgid "By" -msgstr "作者：" - -msgid "repository" -msgstr "仓库" - -msgid "Last updated on" -msgstr "上次更新时间：" - -msgid "Toggle navigation" -msgstr "显示或隐藏导航栏" - -msgid "Sphinx Book Theme" -msgstr "Sphinx Book 主题" - -msgid "suggest edit" -msgstr "提出修改建议" - -msgid "Open an issue" -msgstr "创建议题" - -msgid "Launch" -msgstr "启动" - -msgid "Fullscreen mode" -msgstr "全屏模式" - -msgid "Edit this page" -msgstr "编辑此页面" - -msgid "By the" -msgstr "作者：" - -msgid "next page" -msgstr "下一页" diff --git a/_build/html/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo b/_build/html/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo deleted file mode 100644 index 9116fa9..0000000 Binary files a/_build/html/_static/locales/zh_TW/LC_MESSAGES/booktheme.mo and /dev/null differ diff --git a/_build/html/_static/locales/zh_TW/LC_MESSAGES/booktheme.po b/_build/html/_static/locales/zh_TW/LC_MESSAGES/booktheme.po deleted file mode 100644 index beecb07..0000000 --- a/_build/html/_static/locales/zh_TW/LC_MESSAGES/booktheme.po +++ /dev/null @@ -1,75 +0,0 @@ - -msgid "" -msgstr "" -"Project-Id-Version: Sphinx-Book-Theme\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=UTF-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Language: zh_TW\n" -"Plural-Forms: nplurals=2; plural=(n != 1);\n" - -msgid "Print to PDF" -msgstr "列印成 PDF" - -msgid "Theme by the" -msgstr "佈景主題作者：" - -msgid "Download source file" -msgstr "下載原始檔" - -msgid "open issue" -msgstr "公開的問題" - -msgid "Contents" -msgstr "目錄" - -msgid "previous page" -msgstr "上一頁" - -msgid "Download notebook file" -msgstr "下載 Notebook 檔案" - -msgid "Copyright" -msgstr "Copyright" - -msgid "Download this page" -msgstr "下載此頁面" - -msgid "Source repository" -msgstr "來源儲存庫" - -msgid "By" -msgstr "作者：" - -msgid "repository" -msgstr "儲存庫" - -msgid "Last updated on" -msgstr "最後更新時間：" - -msgid "Toggle navigation" -msgstr "顯示或隱藏導覽列" - -msgid "Sphinx Book Theme" -msgstr "Sphinx Book 佈景主題" - -msgid "suggest edit" -msgstr "提出修改建議" - -msgid "Open an issue" -msgstr "開啟議題" - -msgid "Launch" -msgstr "啟動" - -msgid "Fullscreen mode" -msgstr "全螢幕模式" - -msgid "Edit this page" -msgstr "編輯此頁面" - -msgid "By the" -msgstr "作者：" - -msgid "next page" -msgstr "下一頁" diff --git a/_build/html/_static/minus.png b/_build/html/_static/minus.png deleted file mode 100644 index d96755f..0000000 Binary files a/_build/html/_static/minus.png and /dev/null differ diff --git a/_build/html/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css b/_build/html/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css deleted file mode 100644 index 3356631..0000000 --- a/_build/html/_static/mystnb.4510f1fc1dee50b3e5859aac5469c37c29e427902b24a333a5f9fcb2f0b3ac41.css +++ /dev/null @@ -1,2342 +0,0 @@ -/* Variables */ -:root { - --mystnb-source-bg-color: #f7f7f7; 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-div.highlight .-Color[class*=-C26] { - color: #005FD7 -} - -div.highlight .-Color[class*=-BGC26] { - background-color: #005FD7 -} - -div.highlight .-Color[class*=-C27] { - color: #005FFF -} - -div.highlight .-Color[class*=-BGC27] { - background-color: #005FFF -} - -div.highlight .-Color[class*=-C28] { - color: #008700 -} - -div.highlight .-Color[class*=-BGC28] { - background-color: #008700 -} - -div.highlight .-Color[class*=-C29] { - color: #00875F -} - -div.highlight .-Color[class*=-BGC29] { - background-color: #00875F -} - -div.highlight .-Color[class*=-C30] { - color: #008787 -} - -div.highlight .-Color[class*=-BGC30] { - background-color: #008787 -} - -div.highlight .-Color[class*=-C31] { - color: #0087AF -} - -div.highlight .-Color[class*=-BGC31] { - background-color: #0087AF -} - -div.highlight .-Color[class*=-C32] { - color: #0087D7 -} - -div.highlight .-Color[class*=-BGC32] { - background-color: #0087D7 -} - -div.highlight .-Color[class*=-C33] { - color: #0087FF -} - -div.highlight .-Color[class*=-BGC33] { - background-color: #0087FF -} - -div.highlight .-Color[class*=-C34] { - color: #00AF00 -} - -div.highlight .-Color[class*=-BGC34] { - background-color: #00AF00 -} - -div.highlight .-Color[class*=-C35] { - color: #00AF5F -} - -div.highlight .-Color[class*=-BGC35] { - background-color: #00AF5F -} - -div.highlight .-Color[class*=-C36] { - color: #00AF87 -} - -div.highlight .-Color[class*=-BGC36] { - background-color: #00AF87 -} - -div.highlight .-Color[class*=-C37] { - color: #00AFAF -} - -div.highlight .-Color[class*=-BGC37] { - background-color: #00AFAF -} - -div.highlight .-Color[class*=-C38] { - color: #00AFD7 -} - -div.highlight .-Color[class*=-BGC38] { - background-color: #00AFD7 -} - -div.highlight .-Color[class*=-C39] { - color: #00AFFF -} - -div.highlight .-Color[class*=-BGC39] { - background-color: #00AFFF -} - -div.highlight .-Color[class*=-C40] { - color: #00D700 -} - -div.highlight .-Color[class*=-BGC40] { - background-color: #00D700 -} - -div.highlight .-Color[class*=-C41] { - color: #00D75F -} - -div.highlight .-Color[class*=-BGC41] { - background-color: #00D75F -} - -div.highlight .-Color[class*=-C42] { - color: #00D787 -} - -div.highlight .-Color[class*=-BGC42] { - background-color: #00D787 -} - -div.highlight .-Color[class*=-C43] { - color: #00D7AF -} - -div.highlight .-Color[class*=-BGC43] { - background-color: #00D7AF -} - -div.highlight .-Color[class*=-C44] { - color: #00D7D7 -} - -div.highlight .-Color[class*=-BGC44] { - background-color: #00D7D7 -} - -div.highlight .-Color[class*=-C45] { - color: #00D7FF -} - -div.highlight .-Color[class*=-BGC45] { - background-color: #00D7FF -} - -div.highlight .-Color[class*=-C46] { - color: #00FF00 -} - -div.highlight .-Color[class*=-BGC46] { - background-color: #00FF00 -} - -div.highlight .-Color[class*=-C47] { - color: #00FF5F -} - -div.highlight .-Color[class*=-BGC47] { - background-color: #00FF5F -} - -div.highlight .-Color[class*=-C48] { - color: #00FF87 -} - -div.highlight .-Color[class*=-BGC48] { - background-color: #00FF87 -} - -div.highlight .-Color[class*=-C49] { - color: #00FFAF -} - -div.highlight .-Color[class*=-BGC49] { - background-color: #00FFAF -} - -div.highlight .-Color[class*=-C50] { - color: #00FFD7 -} - -div.highlight .-Color[class*=-BGC50] { - background-color: #00FFD7 -} - -div.highlight .-Color[class*=-C51] { - color: #00FFFF -} - -div.highlight .-Color[class*=-BGC51] { - background-color: #00FFFF -} - -div.highlight .-Color[class*=-C52] { - color: #5F0000 -} - -div.highlight .-Color[class*=-BGC52] { - background-color: #5F0000 -} - -div.highlight .-Color[class*=-C53] { - color: #5F005F -} - -div.highlight .-Color[class*=-BGC53] { - background-color: #5F005F -} - -div.highlight .-Color[class*=-C54] { - color: #5F0087 -} - -div.highlight .-Color[class*=-BGC54] { - background-color: #5F0087 -} - -div.highlight .-Color[class*=-C55] { - color: #5F00AF -} - -div.highlight .-Color[class*=-BGC55] { - background-color: #5F00AF -} - -div.highlight .-Color[class*=-C56] { - color: #5F00D7 -} - -div.highlight .-Color[class*=-BGC56] { - background-color: #5F00D7 -} - -div.highlight .-Color[class*=-C57] { - color: #5F00FF -} - -div.highlight .-Color[class*=-BGC57] { - background-color: #5F00FF -} - -div.highlight .-Color[class*=-C58] { - color: #5F5F00 -} - -div.highlight .-Color[class*=-BGC58] { - background-color: #5F5F00 -} - -div.highlight .-Color[class*=-C59] { - color: #5F5F5F -} - -div.highlight .-Color[class*=-BGC59] { - background-color: #5F5F5F -} - -div.highlight .-Color[class*=-C60] { - color: #5F5F87 -} - -div.highlight .-Color[class*=-BGC60] { - background-color: #5F5F87 -} - -div.highlight .-Color[class*=-C61] { - color: #5F5FAF -} - -div.highlight .-Color[class*=-BGC61] { - background-color: #5F5FAF -} - -div.highlight .-Color[class*=-C62] { - color: #5F5FD7 -} - -div.highlight .-Color[class*=-BGC62] { - background-color: #5F5FD7 -} - -div.highlight .-Color[class*=-C63] { - color: #5F5FFF -} - -div.highlight .-Color[class*=-BGC63] { - background-color: #5F5FFF -} - -div.highlight .-Color[class*=-C64] { - color: #5F8700 -} - -div.highlight .-Color[class*=-BGC64] { - background-color: #5F8700 -} - -div.highlight .-Color[class*=-C65] { - color: #5F875F -} - -div.highlight .-Color[class*=-BGC65] { - background-color: #5F875F -} - -div.highlight .-Color[class*=-C66] { - color: #5F8787 -} - -div.highlight .-Color[class*=-BGC66] { - background-color: #5F8787 -} - -div.highlight .-Color[class*=-C67] { - color: #5F87AF -} - -div.highlight .-Color[class*=-BGC67] { - background-color: #5F87AF -} - -div.highlight .-Color[class*=-C68] { - color: #5F87D7 -} - -div.highlight .-Color[class*=-BGC68] { - background-color: #5F87D7 -} - -div.highlight .-Color[class*=-C69] { - color: #5F87FF -} - -div.highlight .-Color[class*=-BGC69] { - background-color: #5F87FF -} - -div.highlight .-Color[class*=-C70] { - color: #5FAF00 -} - -div.highlight .-Color[class*=-BGC70] { - background-color: #5FAF00 -} - -div.highlight .-Color[class*=-C71] { - color: #5FAF5F -} - -div.highlight .-Color[class*=-BGC71] { - background-color: #5FAF5F -} - -div.highlight .-Color[class*=-C72] { - color: #5FAF87 -} - -div.highlight .-Color[class*=-BGC72] { - background-color: #5FAF87 -} - -div.highlight .-Color[class*=-C73] { - color: #5FAFAF -} - -div.highlight .-Color[class*=-BGC73] { - background-color: #5FAFAF -} - -div.highlight .-Color[class*=-C74] { - color: #5FAFD7 -} - -div.highlight .-Color[class*=-BGC74] { - background-color: #5FAFD7 -} - -div.highlight .-Color[class*=-C75] { - color: #5FAFFF -} - -div.highlight .-Color[class*=-BGC75] { - background-color: #5FAFFF -} - -div.highlight .-Color[class*=-C76] { - color: #5FD700 -} - -div.highlight .-Color[class*=-BGC76] { - background-color: #5FD700 -} - -div.highlight .-Color[class*=-C77] { - color: #5FD75F -} - -div.highlight .-Color[class*=-BGC77] { - background-color: #5FD75F -} - -div.highlight .-Color[class*=-C78] { - color: #5FD787 -} - -div.highlight .-Color[class*=-BGC78] { - background-color: #5FD787 -} - -div.highlight .-Color[class*=-C79] { - color: #5FD7AF -} - -div.highlight .-Color[class*=-BGC79] { - background-color: #5FD7AF -} - -div.highlight .-Color[class*=-C80] { - color: #5FD7D7 -} - -div.highlight .-Color[class*=-BGC80] { - background-color: #5FD7D7 -} - -div.highlight .-Color[class*=-C81] { - color: #5FD7FF -} - -div.highlight .-Color[class*=-BGC81] { - background-color: #5FD7FF -} - -div.highlight .-Color[class*=-C82] { - color: #5FFF00 -} - -div.highlight .-Color[class*=-BGC82] { - background-color: #5FFF00 -} - -div.highlight .-Color[class*=-C83] { - color: #5FFF5F -} - -div.highlight .-Color[class*=-BGC83] { - background-color: #5FFF5F -} - -div.highlight .-Color[class*=-C84] { - color: #5FFF87 -} - -div.highlight .-Color[class*=-BGC84] { - background-color: #5FFF87 -} - -div.highlight .-Color[class*=-C85] { - color: #5FFFAF -} - -div.highlight .-Color[class*=-BGC85] { - background-color: #5FFFAF -} - -div.highlight .-Color[class*=-C86] { - color: #5FFFD7 -} - -div.highlight .-Color[class*=-BGC86] { - background-color: #5FFFD7 -} - -div.highlight .-Color[class*=-C87] { - color: #5FFFFF -} - -div.highlight .-Color[class*=-BGC87] { - background-color: #5FFFFF -} - -div.highlight .-Color[class*=-C88] { - color: #870000 -} - -div.highlight .-Color[class*=-BGC88] { - background-color: #870000 -} - -div.highlight .-Color[class*=-C89] { - color: #87005F -} - -div.highlight .-Color[class*=-BGC89] { - background-color: #87005F -} - -div.highlight .-Color[class*=-C90] { - color: #870087 -} - -div.highlight .-Color[class*=-BGC90] { - background-color: #870087 -} - -div.highlight .-Color[class*=-C91] { - color: #8700AF -} - -div.highlight .-Color[class*=-BGC91] { - background-color: #8700AF -} - -div.highlight .-Color[class*=-C92] { - color: #8700D7 -} - -div.highlight .-Color[class*=-BGC92] { - background-color: #8700D7 -} - -div.highlight .-Color[class*=-C93] { - color: #8700FF -} - -div.highlight .-Color[class*=-BGC93] { - background-color: #8700FF -} - -div.highlight .-Color[class*=-C94] { - color: #875F00 -} - -div.highlight .-Color[class*=-BGC94] { - background-color: #875F00 -} - -div.highlight .-Color[class*=-C95] { - color: #875F5F -} - -div.highlight .-Color[class*=-BGC95] { - background-color: #875F5F -} - -div.highlight .-Color[class*=-C96] { - color: #875F87 -} - -div.highlight .-Color[class*=-BGC96] { - background-color: #875F87 -} - -div.highlight .-Color[class*=-C97] { - color: #875FAF -} - -div.highlight .-Color[class*=-BGC97] { - background-color: #875FAF -} - -div.highlight .-Color[class*=-C98] { - color: #875FD7 -} - -div.highlight .-Color[class*=-BGC98] { - background-color: #875FD7 -} - -div.highlight .-Color[class*=-C99] { - color: #875FFF -} - -div.highlight .-Color[class*=-BGC99] { - background-color: #875FFF -} - -div.highlight .-Color[class*=-C100] { - color: #878700 -} - -div.highlight .-Color[class*=-BGC100] { - background-color: #878700 -} - -div.highlight .-Color[class*=-C101] { - color: #87875F -} - -div.highlight .-Color[class*=-BGC101] { - background-color: #87875F -} - -div.highlight .-Color[class*=-C102] { - color: #878787 -} - -div.highlight .-Color[class*=-BGC102] { - background-color: #878787 -} - -div.highlight .-Color[class*=-C103] { - color: #8787AF -} - -div.highlight .-Color[class*=-BGC103] { - background-color: #8787AF -} - -div.highlight .-Color[class*=-C104] { - color: #8787D7 -} - -div.highlight .-Color[class*=-BGC104] { - background-color: #8787D7 -} - -div.highlight .-Color[class*=-C105] { - color: #8787FF -} - -div.highlight .-Color[class*=-BGC105] { - background-color: #8787FF -} - -div.highlight .-Color[class*=-C106] { - color: #87AF00 -} - -div.highlight .-Color[class*=-BGC106] { - background-color: #87AF00 -} - -div.highlight .-Color[class*=-C107] { - color: #87AF5F -} - -div.highlight .-Color[class*=-BGC107] { - background-color: #87AF5F -} - -div.highlight .-Color[class*=-C108] { - color: #87AF87 -} - -div.highlight .-Color[class*=-BGC108] { - background-color: #87AF87 -} - -div.highlight .-Color[class*=-C109] { - color: #87AFAF -} - -div.highlight .-Color[class*=-BGC109] { - background-color: #87AFAF -} - -div.highlight .-Color[class*=-C110] { - color: #87AFD7 -} - -div.highlight .-Color[class*=-BGC110] { - background-color: #87AFD7 -} - -div.highlight .-Color[class*=-C111] { - color: #87AFFF -} - -div.highlight .-Color[class*=-BGC111] { - background-color: #87AFFF -} - -div.highlight .-Color[class*=-C112] { - color: #87D700 -} - -div.highlight .-Color[class*=-BGC112] { - background-color: #87D700 -} - -div.highlight .-Color[class*=-C113] { - color: #87D75F -} - -div.highlight .-Color[class*=-BGC113] { - background-color: #87D75F -} - -div.highlight .-Color[class*=-C114] { - color: #87D787 -} - -div.highlight .-Color[class*=-BGC114] { - background-color: #87D787 -} - -div.highlight .-Color[class*=-C115] { - color: #87D7AF -} - -div.highlight .-Color[class*=-BGC115] { - background-color: #87D7AF -} - -div.highlight .-Color[class*=-C116] { - color: #87D7D7 -} - -div.highlight .-Color[class*=-BGC116] { - background-color: #87D7D7 -} - -div.highlight .-Color[class*=-C117] { - color: #87D7FF -} - -div.highlight .-Color[class*=-BGC117] { - background-color: #87D7FF -} - -div.highlight .-Color[class*=-C118] { - color: #87FF00 -} - -div.highlight .-Color[class*=-BGC118] { - background-color: #87FF00 -} - -div.highlight .-Color[class*=-C119] { - color: #87FF5F -} - -div.highlight .-Color[class*=-BGC119] { - background-color: #87FF5F -} - -div.highlight .-Color[class*=-C120] { - color: #87FF87 -} - -div.highlight .-Color[class*=-BGC120] { - background-color: #87FF87 -} - -div.highlight .-Color[class*=-C121] { - color: #87FFAF -} - -div.highlight .-Color[class*=-BGC121] { - background-color: #87FFAF -} - -div.highlight .-Color[class*=-C122] { - color: #87FFD7 -} - -div.highlight .-Color[class*=-BGC122] { - background-color: #87FFD7 -} - -div.highlight .-Color[class*=-C123] { - color: #87FFFF -} - -div.highlight .-Color[class*=-BGC123] { - background-color: #87FFFF -} - -div.highlight .-Color[class*=-C124] { - color: #AF0000 -} - -div.highlight .-Color[class*=-BGC124] { - background-color: #AF0000 -} - -div.highlight .-Color[class*=-C125] { - color: #AF005F -} - -div.highlight .-Color[class*=-BGC125] { - background-color: #AF005F -} - -div.highlight .-Color[class*=-C126] { - color: #AF0087 -} - -div.highlight .-Color[class*=-BGC126] { - background-color: #AF0087 -} - -div.highlight .-Color[class*=-C127] { - color: #AF00AF -} - -div.highlight .-Color[class*=-BGC127] { - background-color: #AF00AF -} - -div.highlight .-Color[class*=-C128] { - color: #AF00D7 -} - -div.highlight .-Color[class*=-BGC128] { - background-color: #AF00D7 -} - -div.highlight .-Color[class*=-C129] { - color: #AF00FF -} - -div.highlight .-Color[class*=-BGC129] { - background-color: #AF00FF -} - -div.highlight .-Color[class*=-C130] { - color: #AF5F00 -} - -div.highlight .-Color[class*=-BGC130] { - background-color: #AF5F00 -} - -div.highlight .-Color[class*=-C131] { - color: #AF5F5F -} - -div.highlight .-Color[class*=-BGC131] { - background-color: #AF5F5F -} - -div.highlight .-Color[class*=-C132] { - color: #AF5F87 -} - -div.highlight .-Color[class*=-BGC132] { - background-color: #AF5F87 -} - -div.highlight .-Color[class*=-C133] { - color: #AF5FAF -} - -div.highlight .-Color[class*=-BGC133] { - background-color: #AF5FAF -} - -div.highlight .-Color[class*=-C134] { - color: #AF5FD7 -} - -div.highlight .-Color[class*=-BGC134] { - background-color: #AF5FD7 -} - -div.highlight .-Color[class*=-C135] { - color: #AF5FFF -} - -div.highlight .-Color[class*=-BGC135] { - background-color: #AF5FFF -} - -div.highlight .-Color[class*=-C136] { - color: #AF8700 -} - -div.highlight .-Color[class*=-BGC136] { - background-color: #AF8700 -} - -div.highlight .-Color[class*=-C137] { - color: #AF875F -} - -div.highlight .-Color[class*=-BGC137] { - background-color: #AF875F -} - -div.highlight .-Color[class*=-C138] { - color: #AF8787 -} - -div.highlight .-Color[class*=-BGC138] { - background-color: #AF8787 -} - -div.highlight .-Color[class*=-C139] { - color: #AF87AF -} - -div.highlight .-Color[class*=-BGC139] { - background-color: #AF87AF -} - -div.highlight .-Color[class*=-C140] { - color: #AF87D7 -} - -div.highlight .-Color[class*=-BGC140] { - background-color: #AF87D7 -} - -div.highlight .-Color[class*=-C141] { - color: #AF87FF -} - -div.highlight .-Color[class*=-BGC141] { - background-color: #AF87FF -} - -div.highlight .-Color[class*=-C142] { - color: #AFAF00 -} - -div.highlight .-Color[class*=-BGC142] { - background-color: #AFAF00 -} - -div.highlight .-Color[class*=-C143] { - color: #AFAF5F -} - -div.highlight .-Color[class*=-BGC143] { - background-color: #AFAF5F -} - -div.highlight .-Color[class*=-C144] { - color: #AFAF87 -} - -div.highlight .-Color[class*=-BGC144] { - background-color: #AFAF87 -} - -div.highlight .-Color[class*=-C145] { - color: #AFAFAF -} - -div.highlight .-Color[class*=-BGC145] { - background-color: #AFAFAF -} - -div.highlight .-Color[class*=-C146] { - color: #AFAFD7 -} - -div.highlight .-Color[class*=-BGC146] { - background-color: #AFAFD7 -} - -div.highlight .-Color[class*=-C147] { - color: #AFAFFF -} - -div.highlight .-Color[class*=-BGC147] { - background-color: #AFAFFF -} - -div.highlight .-Color[class*=-C148] { - color: #AFD700 -} - -div.highlight .-Color[class*=-BGC148] { - background-color: #AFD700 -} - -div.highlight .-Color[class*=-C149] { - color: #AFD75F -} - -div.highlight .-Color[class*=-BGC149] { - background-color: #AFD75F -} - -div.highlight .-Color[class*=-C150] { - color: #AFD787 -} - -div.highlight .-Color[class*=-BGC150] { - background-color: #AFD787 -} - -div.highlight .-Color[class*=-C151] { - color: #AFD7AF -} - -div.highlight .-Color[class*=-BGC151] { - background-color: #AFD7AF -} - -div.highlight .-Color[class*=-C152] { - color: #AFD7D7 -} - 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Object.getOwnPropertyNames(this))this[t]=null}_queueCallback(t,e,i=!0){Ut(t,e,i)}_getConfig(t){return t=this._mergeConfigObj(t,this._element),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}static getInstance(t){return Nt.get(Ht(t),this.DATA_KEY)}static getOrCreateInstance(t,e={}){return this.getInstance(t)||new this(t,"object"==typeof e?e:null)}static get VERSION(){return"5.3.3"}static get DATA_KEY(){return`bs.${this.NAME}`}static get EVENT_KEY(){return`.${this.DATA_KEY}`}static eventName(t){return`${t}${this.EVENT_KEY}`}}const ye=t=>{let e=t.getAttribute("data-bs-target");if(!e||"#"===e){let i=t.getAttribute("href");if(!i||!i.includes("#")&&!i.startsWith("."))return null;i.includes("#")&&!i.startsWith("#")&&(i=`#${i.split("#")[1]}`),e=i&&"#"!==i?i.trim():null}return e?e.split(",").map((t=>Mt(t))).join(","):null},we={find:(t,e=document.documentElement)=>[].concat(...Element.prototype.querySelectorAll.call(e,t)),findOne:(t,e=document.documentElement)=>Element.prototype.querySelector.call(e,t),children:(t,e)=>[].concat(...t.children).filter((t=>t.matches(e))),parents(t,e){const i=[];let n=t.parentNode.closest(e);for(;n;)i.push(n),n=n.parentNode.closest(e);return i},prev(t,e){let i=t.previousElementSibling;for(;i;){if(i.matches(e))return[i];i=i.previousElementSibling}return[]},next(t,e){let i=t.nextElementSibling;for(;i;){if(i.matches(e))return[i];i=i.nextElementSibling}return[]},focusableChildren(t){const e=["a","button","input","textarea","select","details","[tabindex]",'[contenteditable="true"]'].map((t=>`${t}:not([tabindex^="-"])`)).join(",");return this.find(e,t).filter((t=>!Wt(t)&&Bt(t)))},getSelectorFromElement(t){const e=ye(t);return e&&we.findOne(e)?e:null},getElementFromSelector(t){const e=ye(t);return e?we.findOne(e):null},getMultipleElementsFromSelector(t){const e=ye(t);return e?we.find(e):[]}},Ee=(t,e="hide")=>{const i=`click.dismiss${t.EVENT_KEY}`,n=t.NAME;fe.on(document,i,`[data-bs-dismiss="${n}"]`,(function(i){if(["A","AREA"].includes(this.tagName)&&i.preventDefault(),Wt(this))return;const s=we.getElementFromSelector(this)||this.closest(`.${n}`);t.getOrCreateInstance(s)[e]()}))},Ae=".bs.alert",Te=`close${Ae}`,Ce=`closed${Ae}`;class Oe extends ve{static get NAME(){return"alert"}close(){if(fe.trigger(this._element,Te).defaultPrevented)return;this._element.classList.remove("show");const t=this._element.classList.contains("fade");this._queueCallback((()=>this._destroyElement()),this._element,t)}_destroyElement(){this._element.remove(),fe.trigger(this._element,Ce),this.dispose()}static jQueryInterface(t){return this.each((function(){const e=Oe.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named 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Default(){return Pe}static get DefaultType(){return Me}static get NAME(){return"swipe"}dispose(){fe.off(this._element,Le)}_start(t){this._supportPointerEvents?this._eventIsPointerPenTouch(t)&&(this._deltaX=t.clientX):this._deltaX=t.touches[0].clientX}_end(t){this._eventIsPointerPenTouch(t)&&(this._deltaX=t.clientX-this._deltaX),this._handleSwipe(),Xt(this._config.endCallback)}_move(t){this._deltaX=t.touches&&t.touches.length>1?0:t.touches[0].clientX-this._deltaX}_handleSwipe(){const t=Math.abs(this._deltaX);if(t<=40)return;const e=t/this._deltaX;this._deltaX=0,e&&Xt(e>0?this._config.rightCallback:this._config.leftCallback)}_initEvents(){this._supportPointerEvents?(fe.on(this._element,Ie,(t=>this._start(t))),fe.on(this._element,Ne,(t=>this._end(t))),this._element.classList.add("pointer-event")):(fe.on(this._element,Se,(t=>this._start(t))),fe.on(this._element,De,(t=>this._move(t))),fe.on(this._element,$e,(t=>this._end(t))))}_eventIsPointerPenTouch(t){return this._supportPointerEvents&&("pen"===t.pointerType||"touch"===t.pointerType)}static isSupported(){return"ontouchstart"in document.documentElement||navigator.maxTouchPoints>0}}const Fe=".bs.carousel",He=".data-api",Be="ArrowLeft",We="ArrowRight",ze="next",Re="prev",qe="left",Ve="right",Ye=`slide${Fe}`,Ke=`slid${Fe}`,Qe=`keydown${Fe}`,Xe=`mouseenter${Fe}`,Ue=`mouseleave${Fe}`,Ge=`dragstart${Fe}`,Je=`load${Fe}${He}`,Ze=`click${Fe}${He}`,ti="carousel",ei="active",ii=".active",ni=".carousel-item",si=ii+ni,oi={[Be]:Ve,[We]:qe},ri={interval:5e3,keyboard:!0,pause:"hover",ride:!1,touch:!0,wrap:!0},ai={interval:"(number|boolean)",keyboard:"boolean",pause:"(string|boolean)",ride:"(boolean|string)",touch:"boolean",wrap:"boolean"};class li extends ve{constructor(t,e){super(t,e),this._interval=null,this._activeElement=null,this._isSliding=!1,this.touchTimeout=null,this._swipeHelper=null,this._indicatorsElement=we.findOne(".carousel-indicators",this._element),this._addEventListeners(),this._config.ride===ti&&this.cycle()}static get Default(){return ri}static get DefaultType(){return ai}static get NAME(){return"carousel"}next(){this._slide(ze)}nextWhenVisible(){!document.hidden&&Bt(this._element)&&this.next()}prev(){this._slide(Re)}pause(){this._isSliding&&jt(this._element),this._clearInterval()}cycle(){this._clearInterval(),this._updateInterval(),this._interval=setInterval((()=>this.nextWhenVisible()),this._config.interval)}_maybeEnableCycle(){this._config.ride&&(this._isSliding?fe.one(this._element,Ke,(()=>this.cycle())):this.cycle())}to(t){const e=this._getItems();if(t>e.length-1||t<0)return;if(this._isSliding)return void fe.one(this._element,Ke,(()=>this.to(t)));const i=this._getItemIndex(this._getActive());if(i===t)return;const n=t>i?ze:Re;this._slide(n,e[t])}dispose(){this._swipeHelper&&this._swipeHelper.dispose(),super.dispose()}_configAfterMerge(t){return t.defaultInterval=t.interval,t}_addEventListeners(){this._config.keyboard&&fe.on(this._element,Qe,(t=>this._keydown(t))),"hover"===this._config.pause&&(fe.on(this._element,Xe,(()=>this.pause())),fe.on(this._element,Ue,(()=>this._maybeEnableCycle()))),this._config.touch&&je.isSupported()&&this._addTouchEventListeners()}_addTouchEventListeners(){for(const t of we.find(".carousel-item img",this._element))fe.on(t,Ge,(t=>t.preventDefault()));const t={leftCallback:()=>this._slide(this._directionToOrder(qe)),rightCallback:()=>this._slide(this._directionToOrder(Ve)),endCallback:()=>{"hover"===this._config.pause&&(this.pause(),this.touchTimeout&&clearTimeout(this.touchTimeout),this.touchTimeout=setTimeout((()=>this._maybeEnableCycle()),500+this._config.interval))}};this._swipeHelper=new je(this._element,t)}_keydown(t){if(/input|textarea/i.test(t.target.tagName))return;const e=oi[t.key];e&&(t.preventDefault(),this._slide(this._directionToOrder(e)))}_getItemIndex(t){return this._getItems().indexOf(t)}_setActiveIndicatorElement(t){if(!this._indicatorsElement)return;const e=we.findOne(ii,this._indicatorsElement);e.classList.remove(ei),e.removeAttribute("aria-current");const i=we.findOne(`[data-bs-slide-to="${t}"]`,this._indicatorsElement);i&&(i.classList.add(ei),i.setAttribute("aria-current","true"))}_updateInterval(){const t=this._activeElement||this._getActive();if(!t)return;const e=Number.parseInt(t.getAttribute("data-bs-interval"),10);this._config.interval=e||this._config.defaultInterval}_slide(t,e=null){if(this._isSliding)return;const i=this._getActive(),n=t===ze,s=e||Gt(this._getItems(),i,n,this._config.wrap);if(s===i)return;const o=this._getItemIndex(s),r=e=>fe.trigger(this._element,e,{relatedTarget:s,direction:this._orderToDirection(t),from:this._getItemIndex(i),to:o});if(r(Ye).defaultPrevented)return;if(!i||!s)return;const a=Boolean(this._interval);this.pause(),this._isSliding=!0,this._setActiveIndicatorElement(o),this._activeElement=s;const l=n?"carousel-item-start":"carousel-item-end",c=n?"carousel-item-next":"carousel-item-prev";s.classList.add(c),qt(s),i.classList.add(l),s.classList.add(l),this._queueCallback((()=>{s.classList.remove(l,c),s.classList.add(ei),i.classList.remove(ei,c,l),this._isSliding=!1,r(Ke)}),i,this._isAnimated()),a&&this.cycle()}_isAnimated(){return this._element.classList.contains("slide")}_getActive(){return we.findOne(si,this._element)}_getItems(){return we.find(ni,this._element)}_clearInterval(){this._interval&&(clearInterval(this._interval),this._interval=null)}_directionToOrder(t){return Kt()?t===qe?Re:ze:t===qe?ze:Re}_orderToDirection(t){return 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.${gi}`,vi='[data-bs-toggle="collapse"]',yi={parent:null,toggle:!0},wi={parent:"(null|element)",toggle:"boolean"};class Ei extends ve{constructor(t,e){super(t,e),this._isTransitioning=!1,this._triggerArray=[];const i=we.find(vi);for(const t of i){const e=we.getSelectorFromElement(t),i=we.find(e).filter((t=>t===this._element));null!==e&&i.length&&this._triggerArray.push(t)}this._initializeChildren(),this._config.parent||this._addAriaAndCollapsedClass(this._triggerArray,this._isShown()),this._config.toggle&&this.toggle()}static get Default(){return yi}static get DefaultType(){return wi}static get NAME(){return"collapse"}toggle(){this._isShown()?this.hide():this.show()}show(){if(this._isTransitioning||this._isShown())return;let t=[];if(this._config.parent&&(t=this._getFirstLevelChildren(".collapse.show, .collapse.collapsing").filter((t=>t!==this._element)).map((t=>Ei.getOrCreateInstance(t,{toggle:!1})))),t.length&&t[0]._isTransitioning)return;if(fe.trigger(this._element,hi).defaultPrevented)return;for(const e of t)e.hide();const e=this._getDimension();this._element.classList.remove(gi),this._element.classList.add(_i),this._element.style[e]=0,this._addAriaAndCollapsedClass(this._triggerArray,!0),this._isTransitioning=!0;const i=`scroll${e[0].toUpperCase()+e.slice(1)}`;this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(_i),this._element.classList.add(gi,mi),this._element.style[e]="",fe.trigger(this._element,di)}),this._element,!0),this._element.style[e]=`${this._element[i]}px`}hide(){if(this._isTransitioning||!this._isShown())return;if(fe.trigger(this._element,ui).defaultPrevented)return;const t=this._getDimension();this._element.style[t]=`${this._element.getBoundingClientRect()[t]}px`,qt(this._element),this._element.classList.add(_i),this._element.classList.remove(gi,mi);for(const t of this._triggerArray){const e=we.getElementFromSelector(t);e&&!this._isShown(e)&&this._addAriaAndCollapsedClass([t],!1)}this._isTransitioning=!0,this._element.style[t]="",this._queueCallback((()=>{this._isTransitioning=!1,this._element.classList.remove(_i),this._element.classList.add(gi),fe.trigger(this._element,fi)}),this._element,!0)}_isShown(t=this._element){return t.classList.contains(mi)}_configAfterMerge(t){return t.toggle=Boolean(t.toggle),t.parent=Ht(t.parent),t}_getDimension(){return this._element.classList.contains("collapse-horizontal")?"width":"height"}_initializeChildren(){if(!this._config.parent)return;const t=this._getFirstLevelChildren(vi);for(const e of t){const t=we.getElementFromSelector(e);t&&this._addAriaAndCollapsedClass([e],this._isShown(t))}}_getFirstLevelChildren(t){const e=we.find(bi,this._config.parent);return we.find(t,this._config.parent).filter((t=>!e.includes(t)))}_addAriaAndCollapsedClass(t,e){if(t.length)for(const i of t)i.classList.toggle("collapsed",!e),i.setAttribute("aria-expanded",e)}static jQueryInterface(t){const e={};return"string"==typeof t&&/show|hide/.test(t)&&(e.toggle=!1),this.each((function(){const i=Ei.getOrCreateInstance(this,e);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t]()}}))}}fe.on(document,pi,vi,(function(t){("A"===t.target.tagName||t.delegateTarget&&"A"===t.delegateTarget.tagName)&&t.preventDefault();for(const t of we.getMultipleElementsFromSelector(this))Ei.getOrCreateInstance(t,{toggle:!1}).toggle()})),Qt(Ei);const Ai="dropdown",Ti=".bs.dropdown",Ci=".data-api",Oi="ArrowUp",xi="ArrowDown",ki=`hide${Ti}`,Li=`hidden${Ti}`,Si=`show${Ti}`,Di=`shown${Ti}`,$i=`click${Ti}${Ci}`,Ii=`keydown${Ti}${Ci}`,Ni=`keyup${Ti}${Ci}`,Pi="show",Mi='[data-bs-toggle="dropdown"]:not(.disabled):not(:disabled)',ji=`${Mi}.${Pi}`,Fi=".dropdown-menu",Hi=Kt()?"top-end":"top-start",Bi=Kt()?"top-start":"top-end",Wi=Kt()?"bottom-end":"bottom-start",zi=Kt()?"bottom-start":"bottom-end",Ri=Kt()?"left-start":"right-start",qi=Kt()?"right-start":"left-start",Vi={autoClose:!0,boundary:"clippingParents",display:"dynamic",offset:[0,2],popperConfig:null,reference:"toggle"},Yi={autoClose:"(boolean|string)",boundary:"(string|element)",display:"string",offset:"(array|string|function)",popperConfig:"(null|object|function)",reference:"(string|element|object)"};class Ki extends ve{constructor(t,e){super(t,e),this._popper=null,this._parent=this._element.parentNode,this._menu=we.next(this._element,Fi)[0]||we.prev(this._element,Fi)[0]||we.findOne(Fi,this._parent),this._inNavbar=this._detectNavbar()}static get Default(){return Vi}static get DefaultType(){return Yi}static get NAME(){return Ai}toggle(){return this._isShown()?this.hide():this.show()}show(){if(Wt(this._element)||this._isShown())return;const t={relatedTarget:this._element};if(!fe.trigger(this._element,Si,t).defaultPrevented){if(this._createPopper(),"ontouchstart"in document.documentElement&&!this._parent.closest(".navbar-nav"))for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._element.focus(),this._element.setAttribute("aria-expanded",!0),this._menu.classList.add(Pi),this._element.classList.add(Pi),fe.trigger(this._element,Di,t)}}hide(){if(Wt(this._element)||!this._isShown())return;const t={relatedTarget:this._element};this._completeHide(t)}dispose(){this._popper&&this._popper.destroy(),super.dispose()}update(){this._inNavbar=this._detectNavbar(),this._popper&&this._popper.update()}_completeHide(t){if(!fe.trigger(this._element,ki,t).defaultPrevented){if("ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._popper&&this._popper.destroy(),this._menu.classList.remove(Pi),this._element.classList.remove(Pi),this._element.setAttribute("aria-expanded","false"),_e.removeDataAttribute(this._menu,"popper"),fe.trigger(this._element,Li,t)}}_getConfig(t){if("object"==typeof(t=super._getConfig(t)).reference&&!Ft(t.reference)&&"function"!=typeof t.reference.getBoundingClientRect)throw new TypeError(`${Ai.toUpperCase()}: Option "reference" provided type "object" without a required "getBoundingClientRect" method.`);return t}_createPopper(){if(void 0===e)throw new TypeError("Bootstrap's dropdowns require Popper (https://popper.js.org)");let t=this._element;"parent"===this._config.reference?t=this._parent:Ft(this._config.reference)?t=Ht(this._config.reference):"object"==typeof this._config.reference&&(t=this._config.reference);const i=this._getPopperConfig();this._popper=Dt(t,this._menu,i)}_isShown(){return this._menu.classList.contains(Pi)}_getPlacement(){const t=this._parent;if(t.classList.contains("dropend"))return Ri;if(t.classList.contains("dropstart"))return qi;if(t.classList.contains("dropup-center"))return"top";if(t.classList.contains("dropdown-center"))return"bottom";const e="end"===getComputedStyle(this._menu).getPropertyValue("--bs-position").trim();return t.classList.contains("dropup")?e?Bi:Hi:e?zi:Wi}_detectNavbar(){return null!==this._element.closest(".navbar")}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_getPopperConfig(){const t={placement:this._getPlacement(),modifiers:[{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"offset",options:{offset:this._getOffset()}}]};return(this._inNavbar||"static"===this._config.display)&&(_e.setDataAttribute(this._menu,"popper","static"),t.modifiers=[{name:"applyStyles",enabled:!1}]),{...t,...Xt(this._config.popperConfig,[t])}}_selectMenuItem({key:t,target:e}){const i=we.find(".dropdown-menu .dropdown-item:not(.disabled):not(:disabled)",this._menu).filter((t=>Bt(t)));i.length&&Gt(i,e,t===xi,!i.includes(e)).focus()}static jQueryInterface(t){return this.each((function(){const e=Ki.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}static clearMenus(t){if(2===t.button||"keyup"===t.type&&"Tab"!==t.key)return;const e=we.find(ji);for(const i of e){const e=Ki.getInstance(i);if(!e||!1===e._config.autoClose)continue;const n=t.composedPath(),s=n.includes(e._menu);if(n.includes(e._element)||"inside"===e._config.autoClose&&!s||"outside"===e._config.autoClose&&s)continue;if(e._menu.contains(t.target)&&("keyup"===t.type&&"Tab"===t.key||/input|select|option|textarea|form/i.test(t.target.tagName)))continue;const o={relatedTarget:e._element};"click"===t.type&&(o.clickEvent=t),e._completeHide(o)}}static dataApiKeydownHandler(t){const e=/input|textarea/i.test(t.target.tagName),i="Escape"===t.key,n=[Oi,xi].includes(t.key);if(!n&&!i)return;if(e&&!i)return;t.preventDefault();const s=this.matches(Mi)?this:we.prev(this,Mi)[0]||we.next(this,Mi)[0]||we.findOne(Mi,t.delegateTarget.parentNode),o=Ki.getOrCreateInstance(s);if(n)return t.stopPropagation(),o.show(),void o._selectMenuItem(t);o._isShown()&&(t.stopPropagation(),o.hide(),s.focus())}}fe.on(document,Ii,Mi,Ki.dataApiKeydownHandler),fe.on(document,Ii,Fi,Ki.dataApiKeydownHandler),fe.on(document,$i,Ki.clearMenus),fe.on(document,Ni,Ki.clearMenus),fe.on(document,$i,Mi,(function(t){t.preventDefault(),Ki.getOrCreateInstance(this).toggle()})),Qt(Ki);const Qi="backdrop",Xi="show",Ui=`mousedown.bs.${Qi}`,Gi={className:"modal-backdrop",clickCallback:null,isAnimated:!1,isVisible:!0,rootElement:"body"},Ji={className:"string",clickCallback:"(function|null)",isAnimated:"boolean",isVisible:"boolean",rootElement:"(element|string)"};class Zi extends be{constructor(t){super(),this._config=this._getConfig(t),this._isAppended=!1,this._element=null}static get Default(){return Gi}static get DefaultType(){return Ji}static get NAME(){return Qi}show(t){if(!this._config.isVisible)return void Xt(t);this._append();const e=this._getElement();this._config.isAnimated&&qt(e),e.classList.add(Xi),this._emulateAnimation((()=>{Xt(t)}))}hide(t){this._config.isVisible?(this._getElement().classList.remove(Xi),this._emulateAnimation((()=>{this.dispose(),Xt(t)}))):Xt(t)}dispose(){this._isAppended&&(fe.off(this._element,Ui),this._element.remove(),this._isAppended=!1)}_getElement(){if(!this._element){const t=document.createElement("div");t.className=this._config.className,this._config.isAnimated&&t.classList.add("fade"),this._element=t}return this._element}_configAfterMerge(t){return t.rootElement=Ht(t.rootElement),t}_append(){if(this._isAppended)return;const t=this._getElement();this._config.rootElement.append(t),fe.on(t,Ui,(()=>{Xt(this._config.clickCallback)})),this._isAppended=!0}_emulateAnimation(t){Ut(t,this._getElement(),this._config.isAnimated)}}const tn=".bs.focustrap",en=`focusin${tn}`,nn=`keydown.tab${tn}`,sn="backward",on={autofocus:!0,trapElement:null},rn={autofocus:"boolean",trapElement:"element"};class an extends be{constructor(t){super(),this._config=this._getConfig(t),this._isActive=!1,this._lastTabNavDirection=null}static get Default(){return on}static get DefaultType(){return rn}static get NAME(){return"focustrap"}activate(){this._isActive||(this._config.autofocus&&this._config.trapElement.focus(),fe.off(document,tn),fe.on(document,en,(t=>this._handleFocusin(t))),fe.on(document,nn,(t=>this._handleKeydown(t))),this._isActive=!0)}deactivate(){this._isActive&&(this._isActive=!1,fe.off(document,tn))}_handleFocusin(t){const{trapElement:e}=this._config;if(t.target===document||t.target===e||e.contains(t.target))return;const i=we.focusableChildren(e);0===i.length?e.focus():this._lastTabNavDirection===sn?i[i.length-1].focus():i[0].focus()}_handleKeydown(t){"Tab"===t.key&&(this._lastTabNavDirection=t.shiftKey?sn:"forward")}}const ln=".fixed-top, .fixed-bottom, .is-fixed, .sticky-top",cn=".sticky-top",hn="padding-right",dn="margin-right";class un{constructor(){this._element=document.body}getWidth(){const t=document.documentElement.clientWidth;return Math.abs(window.innerWidth-t)}hide(){const t=this.getWidth();this._disableOverFlow(),this._setElementAttributes(this._element,hn,(e=>e+t)),this._setElementAttributes(ln,hn,(e=>e+t)),this._setElementAttributes(cn,dn,(e=>e-t))}reset(){this._resetElementAttributes(this._element,"overflow"),this._resetElementAttributes(this._element,hn),this._resetElementAttributes(ln,hn),this._resetElementAttributes(cn,dn)}isOverflowing(){return this.getWidth()>0}_disableOverFlow(){this._saveInitialAttribute(this._element,"overflow"),this._element.style.overflow="hidden"}_setElementAttributes(t,e,i){const n=this.getWidth();this._applyManipulationCallback(t,(t=>{if(t!==this._element&&window.innerWidth>t.clientWidth+n)return;this._saveInitialAttribute(t,e);const s=window.getComputedStyle(t).getPropertyValue(e);t.style.setProperty(e,`${i(Number.parseFloat(s))}px`)}))}_saveInitialAttribute(t,e){const i=t.style.getPropertyValue(e);i&&_e.setDataAttribute(t,e,i)}_resetElementAttributes(t,e){this._applyManipulationCallback(t,(t=>{const i=_e.getDataAttribute(t,e);null!==i?(_e.removeDataAttribute(t,e),t.style.setProperty(e,i)):t.style.removeProperty(e)}))}_applyManipulationCallback(t,e){if(Ft(t))e(t);else for(const i of we.find(t,this._element))e(i)}}const fn=".bs.modal",pn=`hide${fn}`,mn=`hidePrevented${fn}`,gn=`hidden${fn}`,_n=`show${fn}`,bn=`shown${fn}`,vn=`resize${fn}`,yn=`click.dismiss${fn}`,wn=`mousedown.dismiss${fn}`,En=`keydown.dismiss${fn}`,An=`click${fn}.data-api`,Tn="modal-open",Cn="show",On="modal-static",xn={backdrop:!0,focus:!0,keyboard:!0},kn={backdrop:"(boolean|string)",focus:"boolean",keyboard:"boolean"};class Ln extends ve{constructor(t,e){super(t,e),this._dialog=we.findOne(".modal-dialog",this._element),this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._isShown=!1,this._isTransitioning=!1,this._scrollBar=new un,this._addEventListeners()}static get Default(){return xn}static get DefaultType(){return kn}static get NAME(){return"modal"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||this._isTransitioning||fe.trigger(this._element,_n,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._isTransitioning=!0,this._scrollBar.hide(),document.body.classList.add(Tn),this._adjustDialog(),this._backdrop.show((()=>this._showElement(t))))}hide(){this._isShown&&!this._isTransitioning&&(fe.trigger(this._element,pn).defaultPrevented||(this._isShown=!1,this._isTransitioning=!0,this._focustrap.deactivate(),this._element.classList.remove(Cn),this._queueCallback((()=>this._hideModal()),this._element,this._isAnimated())))}dispose(){fe.off(window,fn),fe.off(this._dialog,fn),this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}handleUpdate(){this._adjustDialog()}_initializeBackDrop(){return new Zi({isVisible:Boolean(this._config.backdrop),isAnimated:this._isAnimated()})}_initializeFocusTrap(){return new an({trapElement:this._element})}_showElement(t){document.body.contains(this._element)||document.body.append(this._element),this._element.style.display="block",this._element.removeAttribute("aria-hidden"),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.scrollTop=0;const e=we.findOne(".modal-body",this._dialog);e&&(e.scrollTop=0),qt(this._element),this._element.classList.add(Cn),this._queueCallback((()=>{this._config.focus&&this._focustrap.activate(),this._isTransitioning=!1,fe.trigger(this._element,bn,{relatedTarget:t})}),this._dialog,this._isAnimated())}_addEventListeners(){fe.on(this._element,En,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():this._triggerBackdropTransition())})),fe.on(window,vn,(()=>{this._isShown&&!this._isTransitioning&&this._adjustDialog()})),fe.on(this._element,wn,(t=>{fe.one(this._element,yn,(e=>{this._element===t.target&&this._element===e.target&&("static"!==this._config.backdrop?this._config.backdrop&&this.hide():this._triggerBackdropTransition())}))}))}_hideModal(){this._element.style.display="none",this._element.setAttribute("aria-hidden",!0),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._isTransitioning=!1,this._backdrop.hide((()=>{document.body.classList.remove(Tn),this._resetAdjustments(),this._scrollBar.reset(),fe.trigger(this._element,gn)}))}_isAnimated(){return this._element.classList.contains("fade")}_triggerBackdropTransition(){if(fe.trigger(this._element,mn).defaultPrevented)return;const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._element.style.overflowY;"hidden"===e||this._element.classList.contains(On)||(t||(this._element.style.overflowY="hidden"),this._element.classList.add(On),this._queueCallback((()=>{this._element.classList.remove(On),this._queueCallback((()=>{this._element.style.overflowY=e}),this._dialog)}),this._dialog),this._element.focus())}_adjustDialog(){const t=this._element.scrollHeight>document.documentElement.clientHeight,e=this._scrollBar.getWidth(),i=e>0;if(i&&!t){const t=Kt()?"paddingLeft":"paddingRight";this._element.style[t]=`${e}px`}if(!i&&t){const t=Kt()?"paddingRight":"paddingLeft";this._element.style[t]=`${e}px`}}_resetAdjustments(){this._element.style.paddingLeft="",this._element.style.paddingRight=""}static jQueryInterface(t,e){return this.each((function(){const i=Ln.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===i[t])throw new TypeError(`No method named "${t}"`);i[t](e)}}))}}fe.on(document,An,'[data-bs-toggle="modal"]',(function(t){const e=we.getElementFromSelector(this);["A","AREA"].includes(this.tagName)&&t.preventDefault(),fe.one(e,_n,(t=>{t.defaultPrevented||fe.one(e,gn,(()=>{Bt(this)&&this.focus()}))}));const i=we.findOne(".modal.show");i&&Ln.getInstance(i).hide(),Ln.getOrCreateInstance(e).toggle(this)})),Ee(Ln),Qt(Ln);const Sn=".bs.offcanvas",Dn=".data-api",$n=`load${Sn}${Dn}`,In="show",Nn="showing",Pn="hiding",Mn=".offcanvas.show",jn=`show${Sn}`,Fn=`shown${Sn}`,Hn=`hide${Sn}`,Bn=`hidePrevented${Sn}`,Wn=`hidden${Sn}`,zn=`resize${Sn}`,Rn=`click${Sn}${Dn}`,qn=`keydown.dismiss${Sn}`,Vn={backdrop:!0,keyboard:!0,scroll:!1},Yn={backdrop:"(boolean|string)",keyboard:"boolean",scroll:"boolean"};class Kn extends ve{constructor(t,e){super(t,e),this._isShown=!1,this._backdrop=this._initializeBackDrop(),this._focustrap=this._initializeFocusTrap(),this._addEventListeners()}static get Default(){return Vn}static get DefaultType(){return Yn}static get NAME(){return"offcanvas"}toggle(t){return this._isShown?this.hide():this.show(t)}show(t){this._isShown||fe.trigger(this._element,jn,{relatedTarget:t}).defaultPrevented||(this._isShown=!0,this._backdrop.show(),this._config.scroll||(new un).hide(),this._element.setAttribute("aria-modal",!0),this._element.setAttribute("role","dialog"),this._element.classList.add(Nn),this._queueCallback((()=>{this._config.scroll&&!this._config.backdrop||this._focustrap.activate(),this._element.classList.add(In),this._element.classList.remove(Nn),fe.trigger(this._element,Fn,{relatedTarget:t})}),this._element,!0))}hide(){this._isShown&&(fe.trigger(this._element,Hn).defaultPrevented||(this._focustrap.deactivate(),this._element.blur(),this._isShown=!1,this._element.classList.add(Pn),this._backdrop.hide(),this._queueCallback((()=>{this._element.classList.remove(In,Pn),this._element.removeAttribute("aria-modal"),this._element.removeAttribute("role"),this._config.scroll||(new un).reset(),fe.trigger(this._element,Wn)}),this._element,!0)))}dispose(){this._backdrop.dispose(),this._focustrap.deactivate(),super.dispose()}_initializeBackDrop(){const t=Boolean(this._config.backdrop);return new Zi({className:"offcanvas-backdrop",isVisible:t,isAnimated:!0,rootElement:this._element.parentNode,clickCallback:t?()=>{"static"!==this._config.backdrop?this.hide():fe.trigger(this._element,Bn)}:null})}_initializeFocusTrap(){return new an({trapElement:this._element})}_addEventListeners(){fe.on(this._element,qn,(t=>{"Escape"===t.key&&(this._config.keyboard?this.hide():fe.trigger(this._element,Bn))}))}static jQueryInterface(t){return this.each((function(){const e=Kn.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t](this)}}))}}fe.on(document,Rn,'[data-bs-toggle="offcanvas"]',(function(t){const e=we.getElementFromSelector(this);if(["A","AREA"].includes(this.tagName)&&t.preventDefault(),Wt(this))return;fe.one(e,Wn,(()=>{Bt(this)&&this.focus()}));const i=we.findOne(Mn);i&&i!==e&&Kn.getInstance(i).hide(),Kn.getOrCreateInstance(e).toggle(this)})),fe.on(window,$n,(()=>{for(const t of we.find(Mn))Kn.getOrCreateInstance(t).show()})),fe.on(window,zn,(()=>{for(const t of we.find("[aria-modal][class*=show][class*=offcanvas-]"))"fixed"!==getComputedStyle(t).position&&Kn.getOrCreateInstance(t).hide()})),Ee(Kn),Qt(Kn);const Qn={"*":["class","dir","id","lang","role",/^aria-[\w-]*$/i],a:["target","href","title","rel"],area:[],b:[],br:[],col:[],code:[],dd:[],div:[],dl:[],dt:[],em:[],hr:[],h1:[],h2:[],h3:[],h4:[],h5:[],h6:[],i:[],img:["src","srcset","alt","title","width","height"],li:[],ol:[],p:[],pre:[],s:[],small:[],span:[],sub:[],sup:[],strong:[],u:[],ul:[]},Xn=new Set(["background","cite","href","itemtype","longdesc","poster","src","xlink:href"]),Un=/^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i,Gn=(t,e)=>{const i=t.nodeName.toLowerCase();return e.includes(i)?!Xn.has(i)||Boolean(Un.test(t.nodeValue)):e.filter((t=>t instanceof RegExp)).some((t=>t.test(i)))},Jn={allowList:Qn,content:{},extraClass:"",html:!1,sanitize:!0,sanitizeFn:null,template:"
"},Zn={allowList:"object",content:"object",extraClass:"(string|function)",html:"boolean",sanitize:"boolean",sanitizeFn:"(null|function)",template:"string"},ts={entry:"(string|element|function|null)",selector:"(string|element)"};class es extends be{constructor(t){super(),this._config=this._getConfig(t)}static get Default(){return Jn}static get DefaultType(){return Zn}static get NAME(){return"TemplateFactory"}getContent(){return Object.values(this._config.content).map((t=>this._resolvePossibleFunction(t))).filter(Boolean)}hasContent(){return this.getContent().length>0}changeContent(t){return this._checkContent(t),this._config.content={...this._config.content,...t},this}toHtml(){const t=document.createElement("div");t.innerHTML=this._maybeSanitize(this._config.template);for(const[e,i]of Object.entries(this._config.content))this._setContent(t,i,e);const e=t.children[0],i=this._resolvePossibleFunction(this._config.extraClass);return i&&e.classList.add(...i.split(" ")),e}_typeCheckConfig(t){super._typeCheckConfig(t),this._checkContent(t.content)}_checkContent(t){for(const[e,i]of Object.entries(t))super._typeCheckConfig({selector:e,entry:i},ts)}_setContent(t,e,i){const n=we.findOne(i,t);n&&((e=this._resolvePossibleFunction(e))?Ft(e)?this._putElementInTemplate(Ht(e),n):this._config.html?n.innerHTML=this._maybeSanitize(e):n.textContent=e:n.remove())}_maybeSanitize(t){return this._config.sanitize?function(t,e,i){if(!t.length)return t;if(i&&"function"==typeof i)return i(t);const n=(new window.DOMParser).parseFromString(t,"text/html"),s=[].concat(...n.body.querySelectorAll("*"));for(const t of s){const i=t.nodeName.toLowerCase();if(!Object.keys(e).includes(i)){t.remove();continue}const n=[].concat(...t.attributes),s=[].concat(e["*"]||[],e[i]||[]);for(const e of n)Gn(e,s)||t.removeAttribute(e.nodeName)}return n.body.innerHTML}(t,this._config.allowList,this._config.sanitizeFn):t}_resolvePossibleFunction(t){return Xt(t,[this])}_putElementInTemplate(t,e){if(this._config.html)return e.innerHTML="",void e.append(t);e.textContent=t.textContent}}const is=new Set(["sanitize","allowList","sanitizeFn"]),ns="fade",ss="show",os=".tooltip-inner",rs=".modal",as="hide.bs.modal",ls="hover",cs="focus",hs={AUTO:"auto",TOP:"top",RIGHT:Kt()?"left":"right",BOTTOM:"bottom",LEFT:Kt()?"right":"left"},ds={allowList:Qn,animation:!0,boundary:"clippingParents",container:!1,customClass:"",delay:0,fallbackPlacements:["top","right","bottom","left"],html:!1,offset:[0,6],placement:"top",popperConfig:null,sanitize:!0,sanitizeFn:null,selector:!1,template:'',title:"",trigger:"hover focus"},us={allowList:"object",animation:"boolean",boundary:"(string|element)",container:"(string|element|boolean)",customClass:"(string|function)",delay:"(number|object)",fallbackPlacements:"array",html:"boolean",offset:"(array|string|function)",placement:"(string|function)",popperConfig:"(null|object|function)",sanitize:"boolean",sanitizeFn:"(null|function)",selector:"(string|boolean)",template:"string",title:"(string|element|function)",trigger:"string"};class fs extends ve{constructor(t,i){if(void 0===e)throw new TypeError("Bootstrap's tooltips require Popper (https://popper.js.org)");super(t,i),this._isEnabled=!0,this._timeout=0,this._isHovered=null,this._activeTrigger={},this._popper=null,this._templateFactory=null,this._newContent=null,this.tip=null,this._setListeners(),this._config.selector||this._fixTitle()}static get Default(){return ds}static get DefaultType(){return us}static get NAME(){return"tooltip"}enable(){this._isEnabled=!0}disable(){this._isEnabled=!1}toggleEnabled(){this._isEnabled=!this._isEnabled}toggle(){this._isEnabled&&(this._activeTrigger.click=!this._activeTrigger.click,this._isShown()?this._leave():this._enter())}dispose(){clearTimeout(this._timeout),fe.off(this._element.closest(rs),as,this._hideModalHandler),this._element.getAttribute("data-bs-original-title")&&this._element.setAttribute("title",this._element.getAttribute("data-bs-original-title")),this._disposePopper(),super.dispose()}show(){if("none"===this._element.style.display)throw new Error("Please use show on visible elements");if(!this._isWithContent()||!this._isEnabled)return;const t=fe.trigger(this._element,this.constructor.eventName("show")),e=(zt(this._element)||this._element.ownerDocument.documentElement).contains(this._element);if(t.defaultPrevented||!e)return;this._disposePopper();const i=this._getTipElement();this._element.setAttribute("aria-describedby",i.getAttribute("id"));const{container:n}=this._config;if(this._element.ownerDocument.documentElement.contains(this.tip)||(n.append(i),fe.trigger(this._element,this.constructor.eventName("inserted"))),this._popper=this._createPopper(i),i.classList.add(ss),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.on(t,"mouseover",Rt);this._queueCallback((()=>{fe.trigger(this._element,this.constructor.eventName("shown")),!1===this._isHovered&&this._leave(),this._isHovered=!1}),this.tip,this._isAnimated())}hide(){if(this._isShown()&&!fe.trigger(this._element,this.constructor.eventName("hide")).defaultPrevented){if(this._getTipElement().classList.remove(ss),"ontouchstart"in document.documentElement)for(const t of[].concat(...document.body.children))fe.off(t,"mouseover",Rt);this._activeTrigger.click=!1,this._activeTrigger[cs]=!1,this._activeTrigger[ls]=!1,this._isHovered=null,this._queueCallback((()=>{this._isWithActiveTrigger()||(this._isHovered||this._disposePopper(),this._element.removeAttribute("aria-describedby"),fe.trigger(this._element,this.constructor.eventName("hidden")))}),this.tip,this._isAnimated())}}update(){this._popper&&this._popper.update()}_isWithContent(){return Boolean(this._getTitle())}_getTipElement(){return this.tip||(this.tip=this._createTipElement(this._newContent||this._getContentForTemplate())),this.tip}_createTipElement(t){const e=this._getTemplateFactory(t).toHtml();if(!e)return null;e.classList.remove(ns,ss),e.classList.add(`bs-${this.constructor.NAME}-auto`);const i=(t=>{do{t+=Math.floor(1e6*Math.random())}while(document.getElementById(t));return t})(this.constructor.NAME).toString();return e.setAttribute("id",i),this._isAnimated()&&e.classList.add(ns),e}setContent(t){this._newContent=t,this._isShown()&&(this._disposePopper(),this.show())}_getTemplateFactory(t){return this._templateFactory?this._templateFactory.changeContent(t):this._templateFactory=new es({...this._config,content:t,extraClass:this._resolvePossibleFunction(this._config.customClass)}),this._templateFactory}_getContentForTemplate(){return{[os]:this._getTitle()}}_getTitle(){return this._resolvePossibleFunction(this._config.title)||this._element.getAttribute("data-bs-original-title")}_initializeOnDelegatedTarget(t){return this.constructor.getOrCreateInstance(t.delegateTarget,this._getDelegateConfig())}_isAnimated(){return this._config.animation||this.tip&&this.tip.classList.contains(ns)}_isShown(){return this.tip&&this.tip.classList.contains(ss)}_createPopper(t){const e=Xt(this._config.placement,[this,t,this._element]),i=hs[e.toUpperCase()];return Dt(this._element,t,this._getPopperConfig(i))}_getOffset(){const{offset:t}=this._config;return"string"==typeof t?t.split(",").map((t=>Number.parseInt(t,10))):"function"==typeof t?e=>t(e,this._element):t}_resolvePossibleFunction(t){return Xt(t,[this._element])}_getPopperConfig(t){const e={placement:t,modifiers:[{name:"flip",options:{fallbackPlacements:this._config.fallbackPlacements}},{name:"offset",options:{offset:this._getOffset()}},{name:"preventOverflow",options:{boundary:this._config.boundary}},{name:"arrow",options:{element:`.${this.constructor.NAME}-arrow`}},{name:"preSetPlacement",enabled:!0,phase:"beforeMain",fn:t=>{this._getTipElement().setAttribute("data-popper-placement",t.state.placement)}}]};return{...e,...Xt(this._config.popperConfig,[e])}}_setListeners(){const t=this._config.trigger.split(" ");for(const e of t)if("click"===e)fe.on(this._element,this.constructor.eventName("click"),this._config.selector,(t=>{this._initializeOnDelegatedTarget(t).toggle()}));else if("manual"!==e){const t=e===ls?this.constructor.eventName("mouseenter"):this.constructor.eventName("focusin"),i=e===ls?this.constructor.eventName("mouseleave"):this.constructor.eventName("focusout");fe.on(this._element,t,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusin"===t.type?cs:ls]=!0,e._enter()})),fe.on(this._element,i,this._config.selector,(t=>{const e=this._initializeOnDelegatedTarget(t);e._activeTrigger["focusout"===t.type?cs:ls]=e._element.contains(t.relatedTarget),e._leave()}))}this._hideModalHandler=()=>{this._element&&this.hide()},fe.on(this._element.closest(rs),as,this._hideModalHandler)}_fixTitle(){const t=this._element.getAttribute("title");t&&(this._element.getAttribute("aria-label")||this._element.textContent.trim()||this._element.setAttribute("aria-label",t),this._element.setAttribute("data-bs-original-title",t),this._element.removeAttribute("title"))}_enter(){this._isShown()||this._isHovered?this._isHovered=!0:(this._isHovered=!0,this._setTimeout((()=>{this._isHovered&&this.show()}),this._config.delay.show))}_leave(){this._isWithActiveTrigger()||(this._isHovered=!1,this._setTimeout((()=>{this._isHovered||this.hide()}),this._config.delay.hide))}_setTimeout(t,e){clearTimeout(this._timeout),this._timeout=setTimeout(t,e)}_isWithActiveTrigger(){return Object.values(this._activeTrigger).includes(!0)}_getConfig(t){const e=_e.getDataAttributes(this._element);for(const t of Object.keys(e))is.has(t)&&delete e[t];return t={...e,..."object"==typeof t&&t?t:{}},t=this._mergeConfigObj(t),t=this._configAfterMerge(t),this._typeCheckConfig(t),t}_configAfterMerge(t){return t.container=!1===t.container?document.body:Ht(t.container),"number"==typeof t.delay&&(t.delay={show:t.delay,hide:t.delay}),"number"==typeof t.title&&(t.title=t.title.toString()),"number"==typeof t.content&&(t.content=t.content.toString()),t}_getDelegateConfig(){const t={};for(const[e,i]of Object.entries(this._config))this.constructor.Default[e]!==i&&(t[e]=i);return t.selector=!1,t.trigger="manual",t}_disposePopper(){this._popper&&(this._popper.destroy(),this._popper=null),this.tip&&(this.tip.remove(),this.tip=null)}static jQueryInterface(t){return this.each((function(){const e=fs.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named "${t}"`);e[t]()}}))}}Qt(fs);const ps=".popover-header",ms=".popover-body",gs={...fs.Default,content:"",offset:[0,8],placement:"right",template:'',trigger:"click"},_s={...fs.DefaultType,content:"(null|string|element|function)"};class bs extends fs{static get Default(){return gs}static get 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Map,this._rootElement="visible"===getComputedStyle(this._element).overflowY?null:this._element,this._activeTarget=null,this._observer=null,this._previousScrollData={visibleEntryTop:0,parentScrollTop:0},this.refresh()}static get Default(){return xs}static get DefaultType(){return ks}static get NAME(){return"scrollspy"}refresh(){this._initializeTargetsAndObservables(),this._maybeEnableSmoothScroll(),this._observer?this._observer.disconnect():this._observer=this._getNewObserver();for(const t of this._observableSections.values())this._observer.observe(t)}dispose(){this._observer.disconnect(),super.dispose()}_configAfterMerge(t){return t.target=Ht(t.target)||document.body,t.rootMargin=t.offset?`${t.offset}px 0px -30%`:t.rootMargin,"string"==typeof t.threshold&&(t.threshold=t.threshold.split(",").map((t=>Number.parseFloat(t)))),t}_maybeEnableSmoothScroll(){this._config.smoothScroll&&(fe.off(this._config.target,ws),fe.on(this._config.target,ws,Ts,(t=>{const e=this._observableSections.get(t.target.hash);if(e){t.preventDefault();const i=this._rootElement||window,n=e.offsetTop-this._element.offsetTop;if(i.scrollTo)return void i.scrollTo({top:n,behavior:"smooth"});i.scrollTop=n}})))}_getNewObserver(){const t={root:this._rootElement,threshold:this._config.threshold,rootMargin:this._config.rootMargin};return new IntersectionObserver((t=>this._observerCallback(t)),t)}_observerCallback(t){const e=t=>this._targetLinks.get(`#${t.target.id}`),i=t=>{this._previousScrollData.visibleEntryTop=t.target.offsetTop,this._process(e(t))},n=(this._rootElement||document.documentElement).scrollTop,s=n>=this._previousScrollData.parentScrollTop;this._previousScrollData.parentScrollTop=n;for(const o of t){if(!o.isIntersecting){this._activeTarget=null,this._clearActiveClass(e(o));continue}const t=o.target.offsetTop>=this._previousScrollData.visibleEntryTop;if(s&&t){if(i(o),!n)return}else s||t||i(o)}}_initializeTargetsAndObservables(){this._targetLinks=new Map,this._observableSections=new Map;const t=we.find(Ts,this._config.target);for(const e of t){if(!e.hash||Wt(e))continue;const t=we.findOne(decodeURI(e.hash),this._element);Bt(t)&&(this._targetLinks.set(decodeURI(e.hash),e),this._observableSections.set(e.hash,t))}}_process(t){this._activeTarget!==t&&(this._clearActiveClass(this._config.target),this._activeTarget=t,t.classList.add(As),this._activateParents(t),fe.trigger(this._element,ys,{relatedTarget:t}))}_activateParents(t){if(t.classList.contains("dropdown-item"))we.findOne(".dropdown-toggle",t.closest(".dropdown")).classList.add(As);else for(const e of we.parents(t,".nav, .list-group"))for(const t of we.prev(e,Os))t.classList.add(As)}_clearActiveClass(t){t.classList.remove(As);const e=we.find(`${Ts}.${As}`,t);for(const t of e)t.classList.remove(As)}static jQueryInterface(t){return this.each((function(){const e=Ls.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}fe.on(window,Es,(()=>{for(const t of we.find('[data-bs-spy="scroll"]'))Ls.getOrCreateInstance(t)})),Qt(Ls);const Ss=".bs.tab",Ds=`hide${Ss}`,$s=`hidden${Ss}`,Is=`show${Ss}`,Ns=`shown${Ss}`,Ps=`click${Ss}`,Ms=`keydown${Ss}`,js=`load${Ss}`,Fs="ArrowLeft",Hs="ArrowRight",Bs="ArrowUp",Ws="ArrowDown",zs="Home",Rs="End",qs="active",Vs="fade",Ys="show",Ks=".dropdown-toggle",Qs=`:not(${Ks})`,Xs='[data-bs-toggle="tab"], [data-bs-toggle="pill"], [data-bs-toggle="list"]',Us=`.nav-link${Qs}, .list-group-item${Qs}, [role="tab"]${Qs}, ${Xs}`,Gs=`.${qs}[data-bs-toggle="tab"], .${qs}[data-bs-toggle="pill"], .${qs}[data-bs-toggle="list"]`;class Js extends ve{constructor(t){super(t),this._parent=this._element.closest('.list-group, .nav, [role="tablist"]'),this._parent&&(this._setInitialAttributes(this._parent,this._getChildren()),fe.on(this._element,Ms,(t=>this._keydown(t))))}static get NAME(){return"tab"}show(){const t=this._element;if(this._elemIsActive(t))return;const e=this._getActiveElem(),i=e?fe.trigger(e,Ds,{relatedTarget:t}):null;fe.trigger(t,Is,{relatedTarget:e}).defaultPrevented||i&&i.defaultPrevented||(this._deactivate(e,t),this._activate(t,e))}_activate(t,e){t&&(t.classList.add(qs),this._activate(we.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.removeAttribute("tabindex"),t.setAttribute("aria-selected",!0),this._toggleDropDown(t,!0),fe.trigger(t,Ns,{relatedTarget:e})):t.classList.add(Ys)}),t,t.classList.contains(Vs)))}_deactivate(t,e){t&&(t.classList.remove(qs),t.blur(),this._deactivate(we.getElementFromSelector(t)),this._queueCallback((()=>{"tab"===t.getAttribute("role")?(t.setAttribute("aria-selected",!1),t.setAttribute("tabindex","-1"),this._toggleDropDown(t,!1),fe.trigger(t,$s,{relatedTarget:e})):t.classList.remove(Ys)}),t,t.classList.contains(Vs)))}_keydown(t){if(![Fs,Hs,Bs,Ws,zs,Rs].includes(t.key))return;t.stopPropagation(),t.preventDefault();const e=this._getChildren().filter((t=>!Wt(t)));let i;if([zs,Rs].includes(t.key))i=e[t.key===zs?0:e.length-1];else{const n=[Hs,Ws].includes(t.key);i=Gt(e,t.target,n,!0)}i&&(i.focus({preventScroll:!0}),Js.getOrCreateInstance(i).show())}_getChildren(){return we.find(Us,this._parent)}_getActiveElem(){return this._getChildren().find((t=>this._elemIsActive(t)))||null}_setInitialAttributes(t,e){this._setAttributeIfNotExists(t,"role","tablist");for(const t of e)this._setInitialAttributesOnChild(t)}_setInitialAttributesOnChild(t){t=this._getInnerElement(t);const e=this._elemIsActive(t),i=this._getOuterElement(t);t.setAttribute("aria-selected",e),i!==t&&this._setAttributeIfNotExists(i,"role","presentation"),e||t.setAttribute("tabindex","-1"),this._setAttributeIfNotExists(t,"role","tab"),this._setInitialAttributesOnTargetPanel(t)}_setInitialAttributesOnTargetPanel(t){const e=we.getElementFromSelector(t);e&&(this._setAttributeIfNotExists(e,"role","tabpanel"),t.id&&this._setAttributeIfNotExists(e,"aria-labelledby",`${t.id}`))}_toggleDropDown(t,e){const i=this._getOuterElement(t);if(!i.classList.contains("dropdown"))return;const n=(t,n)=>{const s=we.findOne(t,i);s&&s.classList.toggle(n,e)};n(Ks,qs),n(".dropdown-menu",Ys),i.setAttribute("aria-expanded",e)}_setAttributeIfNotExists(t,e,i){t.hasAttribute(e)||t.setAttribute(e,i)}_elemIsActive(t){return t.classList.contains(qs)}_getInnerElement(t){return t.matches(Us)?t:we.findOne(Us,t)}_getOuterElement(t){return t.closest(".nav-item, .list-group-item")||t}static jQueryInterface(t){return this.each((function(){const e=Js.getOrCreateInstance(this);if("string"==typeof t){if(void 0===e[t]||t.startsWith("_")||"constructor"===t)throw new TypeError(`No method named "${t}"`);e[t]()}}))}}fe.on(document,Ps,Xs,(function(t){["A","AREA"].includes(this.tagName)&&t.preventDefault(),Wt(this)||Js.getOrCreateInstance(this).show()})),fe.on(window,js,(()=>{for(const t of we.find(Gs))Js.getOrCreateInstance(t)})),Qt(Js);const Zs=".bs.toast",to=`mouseover${Zs}`,eo=`mouseout${Zs}`,io=`focusin${Zs}`,no=`focusout${Zs}`,so=`hide${Zs}`,oo=`hidden${Zs}`,ro=`show${Zs}`,ao=`shown${Zs}`,lo="hide",co="show",ho="showing",uo={animation:"boolean",autohide:"boolean",delay:"number"},fo={animation:!0,autohide:!0,delay:5e3};class po extends ve{constructor(t,e){super(t,e),this._timeout=null,this._hasMouseInteraction=!1,this._hasKeyboardInteraction=!1,this._setListeners()}static get Default(){return fo}static get DefaultType(){return uo}static get NAME(){return"toast"}show(){fe.trigger(this._element,ro).defaultPrevented||(this._clearTimeout(),this._config.animation&&this._element.classList.add("fade"),this._element.classList.remove(lo),qt(this._element),this._element.classList.add(co,ho),this._queueCallback((()=>{this._element.classList.remove(ho),fe.trigger(this._element,ao),this._maybeScheduleHide()}),this._element,this._config.animation))}hide(){this.isShown()&&(fe.trigger(this._element,so).defaultPrevented||(this._element.classList.add(ho),this._queueCallback((()=>{this._element.classList.add(lo),this._element.classList.remove(ho,co),fe.trigger(this._element,oo)}),this._element,this._config.animation)))}dispose(){this._clearTimeout(),this.isShown()&&this._element.classList.remove(co),super.dispose()}isShown(){return this._element.classList.contains(co)}_maybeScheduleHide(){this._config.autohide&&(this._hasMouseInteraction||this._hasKeyboardInteraction||(this._timeout=setTimeout((()=>{this.hide()}),this._config.delay)))}_onInteraction(t,e){switch(t.type){case"mouseover":case"mouseout":this._hasMouseInteraction=e;break;case"focusin":case"focusout":this._hasKeyboardInteraction=e}if(e)return void this._clearTimeout();const i=t.relatedTarget;this._element===i||this._element.contains(i)||this._maybeScheduleHide()}_setListeners(){fe.on(this._element,to,(t=>this._onInteraction(t,!0))),fe.on(this._element,eo,(t=>this._onInteraction(t,!1))),fe.on(this._element,io,(t=>this._onInteraction(t,!0))),fe.on(this._element,no,(t=>this._onInteraction(t,!1)))}_clearTimeout(){clearTimeout(this._timeout),this._timeout=null}static jQueryInterface(t){return this.each((function(){const e=po.getOrCreateInstance(this,t);if("string"==typeof t){if(void 0===e[t])throw new TypeError(`No method named 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100644 index 28755c2..0000000 --- a/_build/html/_static/scripts/bootstrap.js.LICENSE.txt +++ /dev/null @@ -1,5 +0,0 @@ -/*! - * Bootstrap v5.3.3 (https://getbootstrap.com/) - * Copyright 2011-2024 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors) - * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE) - */ diff --git a/_build/html/_static/scripts/bootstrap.js.map b/_build/html/_static/scripts/bootstrap.js.map deleted file mode 100644 index e9e8158..0000000 --- a/_build/html/_static/scripts/bootstrap.js.map +++ /dev/null @@ -1 +0,0 @@ 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(element.nodeName || '').toLowerCase() : null;\n}","export default function getWindow(node) {\n if (node == null) {\n return window;\n }\n\n if (node.toString() !== '[object Window]') {\n var ownerDocument = node.ownerDocument;\n return ownerDocument ? ownerDocument.defaultView || window : window;\n }\n\n return node;\n}","import getWindow from \"./getWindow.js\";\n\nfunction isElement(node) {\n var OwnElement = getWindow(node).Element;\n return node instanceof OwnElement || node instanceof Element;\n}\n\nfunction isHTMLElement(node) {\n var OwnElement = getWindow(node).HTMLElement;\n return node instanceof OwnElement || node instanceof HTMLElement;\n}\n\nfunction isShadowRoot(node) {\n // IE 11 has no ShadowRoot\n if (typeof ShadowRoot === 'undefined') {\n return false;\n }\n\n var OwnElement = getWindow(node).ShadowRoot;\n return node instanceof OwnElement || node instanceof ShadowRoot;\n}\n\nexport { isElement, isHTMLElement, isShadowRoot };","import getNodeName from \"../dom-utils/getNodeName.js\";\nimport { isHTMLElement } from \"../dom-utils/instanceOf.js\"; // This modifier takes the styles prepared by the `computeStyles` modifier\n// and applies them to the HTMLElements such as popper and arrow\n\nfunction applyStyles(_ref) {\n var state = _ref.state;\n Object.keys(state.elements).forEach(function (name) {\n var style = state.styles[name] || {};\n var attributes = state.attributes[name] || {};\n var element = state.elements[name]; // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n } // Flow doesn't support to extend this property, but it's the most\n // effective way to apply styles to an HTMLElement\n // $FlowFixMe[cannot-write]\n\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (name) {\n var value = attributes[name];\n\n if (value === false) {\n element.removeAttribute(name);\n } else {\n element.setAttribute(name, value === true ? '' : value);\n }\n });\n });\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state;\n var initialStyles = {\n popper: {\n position: state.options.strategy,\n left: '0',\n top: '0',\n margin: '0'\n },\n arrow: {\n position: 'absolute'\n },\n reference: {}\n };\n Object.assign(state.elements.popper.style, initialStyles.popper);\n state.styles = initialStyles;\n\n if (state.elements.arrow) {\n Object.assign(state.elements.arrow.style, initialStyles.arrow);\n }\n\n return function () {\n Object.keys(state.elements).forEach(function (name) {\n var element = state.elements[name];\n var attributes = state.attributes[name] || {};\n var styleProperties = Object.keys(state.styles.hasOwnProperty(name) ? state.styles[name] : initialStyles[name]); // Set all values to an empty string to unset them\n\n var style = styleProperties.reduce(function (style, property) {\n style[property] = '';\n return style;\n }, {}); // arrow is optional + virtual elements\n\n if (!isHTMLElement(element) || !getNodeName(element)) {\n return;\n }\n\n Object.assign(element.style, style);\n Object.keys(attributes).forEach(function (attribute) {\n element.removeAttribute(attribute);\n });\n });\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'applyStyles',\n enabled: true,\n phase: 'write',\n fn: applyStyles,\n effect: effect,\n requires: ['computeStyles']\n};","import { auto } from \"../enums.js\";\nexport default function getBasePlacement(placement) {\n return placement.split('-')[0];\n}","export var max = Math.max;\nexport var min = Math.min;\nexport var round = Math.round;","export default function getUAString() {\n var uaData = navigator.userAgentData;\n\n if (uaData != null && uaData.brands && Array.isArray(uaData.brands)) {\n return uaData.brands.map(function (item) {\n return item.brand + \"/\" + item.version;\n }).join(' ');\n }\n\n return navigator.userAgent;\n}","import getUAString from \"../utils/userAgent.js\";\nexport default function isLayoutViewport() {\n return !/^((?!chrome|android).)*safari/i.test(getUAString());\n}","import { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport { round } from \"../utils/math.js\";\nimport getWindow from \"./getWindow.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getBoundingClientRect(element, includeScale, isFixedStrategy) {\n if (includeScale === void 0) {\n includeScale = false;\n }\n\n if (isFixedStrategy === void 0) {\n isFixedStrategy = false;\n }\n\n var clientRect = element.getBoundingClientRect();\n var scaleX = 1;\n var scaleY = 1;\n\n if (includeScale && isHTMLElement(element)) {\n scaleX = element.offsetWidth > 0 ? round(clientRect.width) / element.offsetWidth || 1 : 1;\n scaleY = element.offsetHeight > 0 ? round(clientRect.height) / element.offsetHeight || 1 : 1;\n }\n\n var _ref = isElement(element) ? getWindow(element) : window,\n visualViewport = _ref.visualViewport;\n\n var addVisualOffsets = !isLayoutViewport() && isFixedStrategy;\n var x = (clientRect.left + (addVisualOffsets && visualViewport ? visualViewport.offsetLeft : 0)) / scaleX;\n var y = (clientRect.top + (addVisualOffsets && visualViewport ? visualViewport.offsetTop : 0)) / scaleY;\n var width = clientRect.width / scaleX;\n var height = clientRect.height / scaleY;\n return {\n width: width,\n height: height,\n top: y,\n right: x + width,\n bottom: y + height,\n left: x,\n x: x,\n y: y\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\"; // Returns the layout rect of an element relative to its offsetParent. Layout\n// means it doesn't take into account transforms.\n\nexport default function getLayoutRect(element) {\n var clientRect = getBoundingClientRect(element); // Use the clientRect sizes if it's not been transformed.\n // Fixes https://github.com/popperjs/popper-core/issues/1223\n\n var width = element.offsetWidth;\n var height = element.offsetHeight;\n\n if (Math.abs(clientRect.width - width) <= 1) {\n width = clientRect.width;\n }\n\n if (Math.abs(clientRect.height - height) <= 1) {\n height = clientRect.height;\n }\n\n return {\n x: element.offsetLeft,\n y: element.offsetTop,\n width: width,\n height: height\n };\n}","import { isShadowRoot } from \"./instanceOf.js\";\nexport default function contains(parent, child) {\n var rootNode = child.getRootNode && child.getRootNode(); // First, attempt with faster native method\n\n if (parent.contains(child)) {\n return true;\n } // then fallback to custom implementation with Shadow DOM support\n else if (rootNode && isShadowRoot(rootNode)) {\n var next = child;\n\n do {\n if (next && parent.isSameNode(next)) {\n return true;\n } // $FlowFixMe[prop-missing]: need a better way to handle this...\n\n\n next = next.parentNode || next.host;\n } while (next);\n } // Give up, the result is false\n\n\n return false;\n}","import getWindow from \"./getWindow.js\";\nexport default function getComputedStyle(element) {\n return getWindow(element).getComputedStyle(element);\n}","import getNodeName from \"./getNodeName.js\";\nexport default function isTableElement(element) {\n return ['table', 'td', 'th'].indexOf(getNodeName(element)) >= 0;\n}","import { isElement } from \"./instanceOf.js\";\nexport default function getDocumentElement(element) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return ((isElement(element) ? element.ownerDocument : // $FlowFixMe[prop-missing]\n element.document) || window.document).documentElement;\n}","import getNodeName from \"./getNodeName.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport { isShadowRoot } from \"./instanceOf.js\";\nexport default function getParentNode(element) {\n if (getNodeName(element) === 'html') {\n return element;\n }\n\n return (// this is a quicker (but less type safe) way to save quite some bytes from the bundle\n // $FlowFixMe[incompatible-return]\n // $FlowFixMe[prop-missing]\n element.assignedSlot || // step into the shadow DOM of the parent of a slotted node\n element.parentNode || ( // DOM Element detected\n isShadowRoot(element) ? element.host : null) || // ShadowRoot detected\n // $FlowFixMe[incompatible-call]: HTMLElement is a Node\n getDocumentElement(element) // fallback\n\n );\n}","import getWindow from \"./getWindow.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isHTMLElement, isShadowRoot } from \"./instanceOf.js\";\nimport isTableElement from \"./isTableElement.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getUAString from \"../utils/userAgent.js\";\n\nfunction getTrueOffsetParent(element) {\n if (!isHTMLElement(element) || // https://github.com/popperjs/popper-core/issues/837\n getComputedStyle(element).position === 'fixed') {\n return null;\n }\n\n return element.offsetParent;\n} // `.offsetParent` reports `null` for fixed elements, while absolute elements\n// return the containing block\n\n\nfunction getContainingBlock(element) {\n var isFirefox = /firefox/i.test(getUAString());\n var isIE = /Trident/i.test(getUAString());\n\n if (isIE && isHTMLElement(element)) {\n // In IE 9, 10 and 11 fixed elements containing block is always established by the viewport\n var elementCss = getComputedStyle(element);\n\n if (elementCss.position === 'fixed') {\n return null;\n }\n }\n\n var currentNode = getParentNode(element);\n\n if (isShadowRoot(currentNode)) {\n currentNode = currentNode.host;\n }\n\n while (isHTMLElement(currentNode) && ['html', 'body'].indexOf(getNodeName(currentNode)) < 0) {\n var css = getComputedStyle(currentNode); // This is non-exhaustive but covers the most common CSS properties that\n // create a containing block.\n // https://developer.mozilla.org/en-US/docs/Web/CSS/Containing_block#identifying_the_containing_block\n\n if (css.transform !== 'none' || css.perspective !== 'none' || css.contain === 'paint' || ['transform', 'perspective'].indexOf(css.willChange) !== -1 || isFirefox && css.willChange === 'filter' || isFirefox && css.filter && css.filter !== 'none') {\n return currentNode;\n } else {\n currentNode = currentNode.parentNode;\n }\n }\n\n return null;\n} // Gets the closest ancestor positioned element. Handles some edge cases,\n// such as table ancestors and cross browser bugs.\n\n\nexport default function getOffsetParent(element) {\n var window = getWindow(element);\n var offsetParent = getTrueOffsetParent(element);\n\n while (offsetParent && isTableElement(offsetParent) && getComputedStyle(offsetParent).position === 'static') {\n offsetParent = getTrueOffsetParent(offsetParent);\n }\n\n if (offsetParent && (getNodeName(offsetParent) === 'html' || getNodeName(offsetParent) === 'body' && getComputedStyle(offsetParent).position === 'static')) {\n return window;\n }\n\n return offsetParent || getContainingBlock(element) || window;\n}","export default function getMainAxisFromPlacement(placement) {\n return ['top', 'bottom'].indexOf(placement) >= 0 ? 'x' : 'y';\n}","import { max as mathMax, min as mathMin } from \"./math.js\";\nexport function within(min, value, max) {\n return mathMax(min, mathMin(value, max));\n}\nexport function withinMaxClamp(min, value, max) {\n var v = within(min, value, max);\n return v > max ? max : v;\n}","import getFreshSideObject from \"./getFreshSideObject.js\";\nexport default function mergePaddingObject(paddingObject) {\n return Object.assign({}, getFreshSideObject(), paddingObject);\n}","export default function getFreshSideObject() {\n return {\n top: 0,\n right: 0,\n bottom: 0,\n left: 0\n };\n}","export default function expandToHashMap(value, keys) {\n return keys.reduce(function (hashMap, key) {\n hashMap[key] = value;\n return hashMap;\n }, {});\n}","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport contains from \"../dom-utils/contains.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport { within } from \"../utils/within.js\";\nimport mergePaddingObject from \"../utils/mergePaddingObject.js\";\nimport expandToHashMap from \"../utils/expandToHashMap.js\";\nimport { left, right, basePlacements, top, bottom } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar toPaddingObject = function toPaddingObject(padding, state) {\n padding = typeof padding === 'function' ? padding(Object.assign({}, state.rects, {\n placement: state.placement\n })) : padding;\n return mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n};\n\nfunction arrow(_ref) {\n var _state$modifiersData$;\n\n var state = _ref.state,\n name = _ref.name,\n options = _ref.options;\n var arrowElement = state.elements.arrow;\n var popperOffsets = state.modifiersData.popperOffsets;\n var basePlacement = getBasePlacement(state.placement);\n var axis = getMainAxisFromPlacement(basePlacement);\n var isVertical = [left, right].indexOf(basePlacement) >= 0;\n var len = isVertical ? 'height' : 'width';\n\n if (!arrowElement || !popperOffsets) {\n return;\n }\n\n var paddingObject = toPaddingObject(options.padding, state);\n var arrowRect = getLayoutRect(arrowElement);\n var minProp = axis === 'y' ? top : left;\n var maxProp = axis === 'y' ? bottom : right;\n var endDiff = state.rects.reference[len] + state.rects.reference[axis] - popperOffsets[axis] - state.rects.popper[len];\n var startDiff = popperOffsets[axis] - state.rects.reference[axis];\n var arrowOffsetParent = getOffsetParent(arrowElement);\n var clientSize = arrowOffsetParent ? axis === 'y' ? arrowOffsetParent.clientHeight || 0 : arrowOffsetParent.clientWidth || 0 : 0;\n var centerToReference = endDiff / 2 - startDiff / 2; // Make sure the arrow doesn't overflow the popper if the center point is\n // outside of the popper bounds\n\n var min = paddingObject[minProp];\n var max = clientSize - arrowRect[len] - paddingObject[maxProp];\n var center = clientSize / 2 - arrowRect[len] / 2 + centerToReference;\n var offset = within(min, center, max); // Prevents breaking syntax highlighting...\n\n var axisProp = axis;\n state.modifiersData[name] = (_state$modifiersData$ = {}, _state$modifiersData$[axisProp] = offset, _state$modifiersData$.centerOffset = offset - center, _state$modifiersData$);\n}\n\nfunction effect(_ref2) {\n var state = _ref2.state,\n options = _ref2.options;\n var _options$element = options.element,\n arrowElement = _options$element === void 0 ? '[data-popper-arrow]' : _options$element;\n\n if (arrowElement == null) {\n return;\n } // CSS selector\n\n\n if (typeof arrowElement === 'string') {\n arrowElement = state.elements.popper.querySelector(arrowElement);\n\n if (!arrowElement) {\n return;\n }\n }\n\n if (!contains(state.elements.popper, arrowElement)) {\n return;\n }\n\n state.elements.arrow = arrowElement;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'arrow',\n enabled: true,\n phase: 'main',\n fn: arrow,\n effect: effect,\n requires: ['popperOffsets'],\n requiresIfExists: ['preventOverflow']\n};","export default function getVariation(placement) {\n return placement.split('-')[1];\n}","import { top, left, right, bottom, end } from \"../enums.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport getWindow from \"../dom-utils/getWindow.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getComputedStyle from \"../dom-utils/getComputedStyle.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport { round } from \"../utils/math.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar unsetSides = {\n top: 'auto',\n right: 'auto',\n bottom: 'auto',\n left: 'auto'\n}; // Round the offsets to the nearest suitable subpixel based on the DPR.\n// Zooming can change the DPR, but it seems to report a value that will\n// cleanly divide the values into the appropriate subpixels.\n\nfunction roundOffsetsByDPR(_ref, win) {\n var x = _ref.x,\n y = _ref.y;\n var dpr = win.devicePixelRatio || 1;\n return {\n x: round(x * dpr) / dpr || 0,\n y: round(y * dpr) / dpr || 0\n };\n}\n\nexport function mapToStyles(_ref2) {\n var _Object$assign2;\n\n var popper = _ref2.popper,\n popperRect = _ref2.popperRect,\n placement = _ref2.placement,\n variation = _ref2.variation,\n offsets = _ref2.offsets,\n position = _ref2.position,\n gpuAcceleration = _ref2.gpuAcceleration,\n adaptive = _ref2.adaptive,\n roundOffsets = _ref2.roundOffsets,\n isFixed = _ref2.isFixed;\n var _offsets$x = offsets.x,\n x = _offsets$x === void 0 ? 0 : _offsets$x,\n _offsets$y = offsets.y,\n y = _offsets$y === void 0 ? 0 : _offsets$y;\n\n var _ref3 = typeof roundOffsets === 'function' ? roundOffsets({\n x: x,\n y: y\n }) : {\n x: x,\n y: y\n };\n\n x = _ref3.x;\n y = _ref3.y;\n var hasX = offsets.hasOwnProperty('x');\n var hasY = offsets.hasOwnProperty('y');\n var sideX = left;\n var sideY = top;\n var win = window;\n\n if (adaptive) {\n var offsetParent = getOffsetParent(popper);\n var heightProp = 'clientHeight';\n var widthProp = 'clientWidth';\n\n if (offsetParent === getWindow(popper)) {\n offsetParent = getDocumentElement(popper);\n\n if (getComputedStyle(offsetParent).position !== 'static' && position === 'absolute') {\n heightProp = 'scrollHeight';\n widthProp = 'scrollWidth';\n }\n } // $FlowFixMe[incompatible-cast]: force type refinement, we compare offsetParent with window above, but Flow doesn't detect it\n\n\n offsetParent = offsetParent;\n\n if (placement === top || (placement === left || placement === right) && variation === end) {\n sideY = bottom;\n var offsetY = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.height : // $FlowFixMe[prop-missing]\n offsetParent[heightProp];\n y -= offsetY - popperRect.height;\n y *= gpuAcceleration ? 1 : -1;\n }\n\n if (placement === left || (placement === top || placement === bottom) && variation === end) {\n sideX = right;\n var offsetX = isFixed && offsetParent === win && win.visualViewport ? win.visualViewport.width : // $FlowFixMe[prop-missing]\n offsetParent[widthProp];\n x -= offsetX - popperRect.width;\n x *= gpuAcceleration ? 1 : -1;\n }\n }\n\n var commonStyles = Object.assign({\n position: position\n }, adaptive && unsetSides);\n\n var _ref4 = roundOffsets === true ? roundOffsetsByDPR({\n x: x,\n y: y\n }, getWindow(popper)) : {\n x: x,\n y: y\n };\n\n x = _ref4.x;\n y = _ref4.y;\n\n if (gpuAcceleration) {\n var _Object$assign;\n\n return Object.assign({}, commonStyles, (_Object$assign = {}, _Object$assign[sideY] = hasY ? '0' : '', _Object$assign[sideX] = hasX ? '0' : '', _Object$assign.transform = (win.devicePixelRatio || 1) <= 1 ? \"translate(\" + x + \"px, \" + y + \"px)\" : \"translate3d(\" + x + \"px, \" + y + \"px, 0)\", _Object$assign));\n }\n\n return Object.assign({}, commonStyles, (_Object$assign2 = {}, _Object$assign2[sideY] = hasY ? y + \"px\" : '', _Object$assign2[sideX] = hasX ? x + \"px\" : '', _Object$assign2.transform = '', _Object$assign2));\n}\n\nfunction computeStyles(_ref5) {\n var state = _ref5.state,\n options = _ref5.options;\n var _options$gpuAccelerat = options.gpuAcceleration,\n gpuAcceleration = _options$gpuAccelerat === void 0 ? true : _options$gpuAccelerat,\n _options$adaptive = options.adaptive,\n adaptive = _options$adaptive === void 0 ? true : _options$adaptive,\n _options$roundOffsets = options.roundOffsets,\n roundOffsets = _options$roundOffsets === void 0 ? true : _options$roundOffsets;\n var commonStyles = {\n placement: getBasePlacement(state.placement),\n variation: getVariation(state.placement),\n popper: state.elements.popper,\n popperRect: state.rects.popper,\n gpuAcceleration: gpuAcceleration,\n isFixed: state.options.strategy === 'fixed'\n };\n\n if (state.modifiersData.popperOffsets != null) {\n state.styles.popper = Object.assign({}, state.styles.popper, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.popperOffsets,\n position: state.options.strategy,\n adaptive: adaptive,\n roundOffsets: roundOffsets\n })));\n }\n\n if (state.modifiersData.arrow != null) {\n state.styles.arrow = Object.assign({}, state.styles.arrow, mapToStyles(Object.assign({}, commonStyles, {\n offsets: state.modifiersData.arrow,\n position: 'absolute',\n adaptive: false,\n roundOffsets: roundOffsets\n })));\n }\n\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-placement': state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'computeStyles',\n enabled: true,\n phase: 'beforeWrite',\n fn: computeStyles,\n data: {}\n};","import getWindow from \"../dom-utils/getWindow.js\"; // eslint-disable-next-line import/no-unused-modules\n\nvar passive = {\n passive: true\n};\n\nfunction effect(_ref) {\n var state = _ref.state,\n instance = _ref.instance,\n options = _ref.options;\n var _options$scroll = options.scroll,\n scroll = _options$scroll === void 0 ? true : _options$scroll,\n _options$resize = options.resize,\n resize = _options$resize === void 0 ? true : _options$resize;\n var window = getWindow(state.elements.popper);\n var scrollParents = [].concat(state.scrollParents.reference, state.scrollParents.popper);\n\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.addEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.addEventListener('resize', instance.update, passive);\n }\n\n return function () {\n if (scroll) {\n scrollParents.forEach(function (scrollParent) {\n scrollParent.removeEventListener('scroll', instance.update, passive);\n });\n }\n\n if (resize) {\n window.removeEventListener('resize', instance.update, passive);\n }\n };\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'eventListeners',\n enabled: true,\n phase: 'write',\n fn: function fn() {},\n effect: effect,\n data: {}\n};","var hash = {\n left: 'right',\n right: 'left',\n bottom: 'top',\n top: 'bottom'\n};\nexport default function getOppositePlacement(placement) {\n return placement.replace(/left|right|bottom|top/g, function (matched) {\n return hash[matched];\n });\n}","var hash = {\n start: 'end',\n end: 'start'\n};\nexport default function getOppositeVariationPlacement(placement) {\n return placement.replace(/start|end/g, function (matched) {\n return hash[matched];\n });\n}","import getWindow from \"./getWindow.js\";\nexport default function getWindowScroll(node) {\n var win = getWindow(node);\n var scrollLeft = win.pageXOffset;\n var scrollTop = win.pageYOffset;\n return {\n scrollLeft: scrollLeft,\n scrollTop: scrollTop\n };\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nexport default function getWindowScrollBarX(element) {\n // If has a CSS width greater than the viewport, then this will be\n // incorrect for RTL.\n // Popper 1 is broken in this case and never had a bug report so let's assume\n // it's not an issue. I don't think anyone ever specifies width on \n // anyway.\n // Browsers where the left scrollbar doesn't cause an issue report `0` for\n // this (e.g. Edge 2019, IE11, Safari)\n return getBoundingClientRect(getDocumentElement(element)).left + getWindowScroll(element).scrollLeft;\n}","import getComputedStyle from \"./getComputedStyle.js\";\nexport default function isScrollParent(element) {\n // Firefox wants us to check `-x` and `-y` variations as well\n var _getComputedStyle = getComputedStyle(element),\n overflow = _getComputedStyle.overflow,\n overflowX = _getComputedStyle.overflowX,\n overflowY = _getComputedStyle.overflowY;\n\n return /auto|scroll|overlay|hidden/.test(overflow + overflowY + overflowX);\n}","import getParentNode from \"./getParentNode.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nexport default function getScrollParent(node) {\n if (['html', 'body', '#document'].indexOf(getNodeName(node)) >= 0) {\n // $FlowFixMe[incompatible-return]: assume body is always available\n return node.ownerDocument.body;\n }\n\n if (isHTMLElement(node) && isScrollParent(node)) {\n return node;\n }\n\n return getScrollParent(getParentNode(node));\n}","import getScrollParent from \"./getScrollParent.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport getWindow from \"./getWindow.js\";\nimport isScrollParent from \"./isScrollParent.js\";\n/*\ngiven a DOM element, return the list of all scroll parents, up the list of ancesors\nuntil we get to the top window object. This list is what we attach scroll listeners\nto, because if any of these parent elements scroll, we'll need to re-calculate the\nreference element's position.\n*/\n\nexport default function listScrollParents(element, list) {\n var _element$ownerDocumen;\n\n if (list === void 0) {\n list = [];\n }\n\n var scrollParent = getScrollParent(element);\n var isBody = scrollParent === ((_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body);\n var win = getWindow(scrollParent);\n var target = isBody ? [win].concat(win.visualViewport || [], isScrollParent(scrollParent) ? scrollParent : []) : scrollParent;\n var updatedList = list.concat(target);\n return isBody ? updatedList : // $FlowFixMe[incompatible-call]: isBody tells us target will be an HTMLElement here\n updatedList.concat(listScrollParents(getParentNode(target)));\n}","export default function rectToClientRect(rect) {\n return Object.assign({}, rect, {\n left: rect.x,\n top: rect.y,\n right: rect.x + rect.width,\n bottom: rect.y + rect.height\n });\n}","import { viewport } from \"../enums.js\";\nimport getViewportRect from \"./getViewportRect.js\";\nimport getDocumentRect from \"./getDocumentRect.js\";\nimport listScrollParents from \"./listScrollParents.js\";\nimport getOffsetParent from \"./getOffsetParent.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport { isElement, isHTMLElement } from \"./instanceOf.js\";\nimport getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getParentNode from \"./getParentNode.js\";\nimport contains from \"./contains.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport rectToClientRect from \"../utils/rectToClientRect.js\";\nimport { max, min } from \"../utils/math.js\";\n\nfunction getInnerBoundingClientRect(element, strategy) {\n var rect = getBoundingClientRect(element, false, strategy === 'fixed');\n rect.top = rect.top + element.clientTop;\n rect.left = rect.left + element.clientLeft;\n rect.bottom = rect.top + element.clientHeight;\n rect.right = rect.left + element.clientWidth;\n rect.width = element.clientWidth;\n rect.height = element.clientHeight;\n rect.x = rect.left;\n rect.y = rect.top;\n return rect;\n}\n\nfunction getClientRectFromMixedType(element, clippingParent, strategy) {\n return clippingParent === viewport ? rectToClientRect(getViewportRect(element, strategy)) : isElement(clippingParent) ? getInnerBoundingClientRect(clippingParent, strategy) : rectToClientRect(getDocumentRect(getDocumentElement(element)));\n} // A \"clipping parent\" is an overflowable container with the characteristic of\n// clipping (or hiding) overflowing elements with a position different from\n// `initial`\n\n\nfunction getClippingParents(element) {\n var clippingParents = listScrollParents(getParentNode(element));\n var canEscapeClipping = ['absolute', 'fixed'].indexOf(getComputedStyle(element).position) >= 0;\n var clipperElement = canEscapeClipping && isHTMLElement(element) ? getOffsetParent(element) : element;\n\n if (!isElement(clipperElement)) {\n return [];\n } // $FlowFixMe[incompatible-return]: https://github.com/facebook/flow/issues/1414\n\n\n return clippingParents.filter(function (clippingParent) {\n return isElement(clippingParent) && contains(clippingParent, clipperElement) && getNodeName(clippingParent) !== 'body';\n });\n} // Gets the maximum area that the element is visible in due to any number of\n// clipping parents\n\n\nexport default function getClippingRect(element, boundary, rootBoundary, strategy) {\n var mainClippingParents = boundary === 'clippingParents' ? getClippingParents(element) : [].concat(boundary);\n var clippingParents = [].concat(mainClippingParents, [rootBoundary]);\n var firstClippingParent = clippingParents[0];\n var clippingRect = clippingParents.reduce(function (accRect, clippingParent) {\n var rect = getClientRectFromMixedType(element, clippingParent, strategy);\n accRect.top = max(rect.top, accRect.top);\n accRect.right = min(rect.right, accRect.right);\n accRect.bottom = min(rect.bottom, accRect.bottom);\n accRect.left = max(rect.left, accRect.left);\n return accRect;\n }, getClientRectFromMixedType(element, firstClippingParent, strategy));\n clippingRect.width = clippingRect.right - clippingRect.left;\n clippingRect.height = clippingRect.bottom - clippingRect.top;\n clippingRect.x = clippingRect.left;\n clippingRect.y = clippingRect.top;\n return clippingRect;\n}","import getWindow from \"./getWindow.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport isLayoutViewport from \"./isLayoutViewport.js\";\nexport default function getViewportRect(element, strategy) {\n var win = getWindow(element);\n var html = getDocumentElement(element);\n var visualViewport = win.visualViewport;\n var width = html.clientWidth;\n var height = html.clientHeight;\n var x = 0;\n var y = 0;\n\n if (visualViewport) {\n width = visualViewport.width;\n height = visualViewport.height;\n var layoutViewport = isLayoutViewport();\n\n if (layoutViewport || !layoutViewport && strategy === 'fixed') {\n x = visualViewport.offsetLeft;\n y = visualViewport.offsetTop;\n }\n }\n\n return {\n width: width,\n height: height,\n x: x + getWindowScrollBarX(element),\n y: y\n };\n}","import getDocumentElement from \"./getDocumentElement.js\";\nimport getComputedStyle from \"./getComputedStyle.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getWindowScroll from \"./getWindowScroll.js\";\nimport { max } from \"../utils/math.js\"; // Gets the entire size of the scrollable document area, even extending outside\n// of the `` and `` rect bounds if horizontally scrollable\n\nexport default function getDocumentRect(element) {\n var _element$ownerDocumen;\n\n var html = getDocumentElement(element);\n var winScroll = getWindowScroll(element);\n var body = (_element$ownerDocumen = element.ownerDocument) == null ? void 0 : _element$ownerDocumen.body;\n var width = max(html.scrollWidth, html.clientWidth, body ? body.scrollWidth : 0, body ? body.clientWidth : 0);\n var height = max(html.scrollHeight, html.clientHeight, body ? body.scrollHeight : 0, body ? body.clientHeight : 0);\n var x = -winScroll.scrollLeft + getWindowScrollBarX(element);\n var y = -winScroll.scrollTop;\n\n if (getComputedStyle(body || html).direction === 'rtl') {\n x += max(html.clientWidth, body ? body.clientWidth : 0) - width;\n }\n\n return {\n width: width,\n height: height,\n x: x,\n y: y\n };\n}","import getBasePlacement from \"./getBasePlacement.js\";\nimport getVariation from \"./getVariation.js\";\nimport getMainAxisFromPlacement from \"./getMainAxisFromPlacement.js\";\nimport { top, right, bottom, left, start, end } from \"../enums.js\";\nexport default function computeOffsets(_ref) {\n var reference = _ref.reference,\n element = _ref.element,\n placement = _ref.placement;\n var basePlacement = placement ? getBasePlacement(placement) : null;\n var variation = placement ? getVariation(placement) : null;\n var commonX = reference.x + reference.width / 2 - element.width / 2;\n var commonY = reference.y + reference.height / 2 - element.height / 2;\n var offsets;\n\n switch (basePlacement) {\n case top:\n offsets = {\n x: commonX,\n y: reference.y - element.height\n };\n break;\n\n case bottom:\n offsets = {\n x: commonX,\n y: reference.y + reference.height\n };\n break;\n\n case right:\n offsets = {\n x: reference.x + reference.width,\n y: commonY\n };\n break;\n\n case left:\n offsets = {\n x: reference.x - element.width,\n y: commonY\n };\n break;\n\n default:\n offsets = {\n x: reference.x,\n y: reference.y\n };\n }\n\n var mainAxis = basePlacement ? getMainAxisFromPlacement(basePlacement) : null;\n\n if (mainAxis != null) {\n var len = mainAxis === 'y' ? 'height' : 'width';\n\n switch (variation) {\n case start:\n offsets[mainAxis] = offsets[mainAxis] - (reference[len] / 2 - element[len] / 2);\n break;\n\n case end:\n offsets[mainAxis] = offsets[mainAxis] + (reference[len] / 2 - element[len] / 2);\n break;\n\n default:\n }\n }\n\n return offsets;\n}","import getClippingRect from \"../dom-utils/getClippingRect.js\";\nimport getDocumentElement from \"../dom-utils/getDocumentElement.js\";\nimport getBoundingClientRect from \"../dom-utils/getBoundingClientRect.js\";\nimport computeOffsets from \"./computeOffsets.js\";\nimport rectToClientRect from \"./rectToClientRect.js\";\nimport { clippingParents, reference, popper, bottom, top, right, basePlacements, viewport } from \"../enums.js\";\nimport { isElement } from \"../dom-utils/instanceOf.js\";\nimport mergePaddingObject from \"./mergePaddingObject.js\";\nimport expandToHashMap from \"./expandToHashMap.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport default function detectOverflow(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n _options$placement = _options.placement,\n placement = _options$placement === void 0 ? state.placement : _options$placement,\n _options$strategy = _options.strategy,\n strategy = _options$strategy === void 0 ? state.strategy : _options$strategy,\n _options$boundary = _options.boundary,\n boundary = _options$boundary === void 0 ? clippingParents : _options$boundary,\n _options$rootBoundary = _options.rootBoundary,\n rootBoundary = _options$rootBoundary === void 0 ? viewport : _options$rootBoundary,\n _options$elementConte = _options.elementContext,\n elementContext = _options$elementConte === void 0 ? popper : _options$elementConte,\n _options$altBoundary = _options.altBoundary,\n altBoundary = _options$altBoundary === void 0 ? false : _options$altBoundary,\n _options$padding = _options.padding,\n padding = _options$padding === void 0 ? 0 : _options$padding;\n var paddingObject = mergePaddingObject(typeof padding !== 'number' ? padding : expandToHashMap(padding, basePlacements));\n var altContext = elementContext === popper ? reference : popper;\n var popperRect = state.rects.popper;\n var element = state.elements[altBoundary ? altContext : elementContext];\n var clippingClientRect = getClippingRect(isElement(element) ? element : element.contextElement || getDocumentElement(state.elements.popper), boundary, rootBoundary, strategy);\n var referenceClientRect = getBoundingClientRect(state.elements.reference);\n var popperOffsets = computeOffsets({\n reference: referenceClientRect,\n element: popperRect,\n strategy: 'absolute',\n placement: placement\n });\n var popperClientRect = rectToClientRect(Object.assign({}, popperRect, popperOffsets));\n var elementClientRect = elementContext === popper ? popperClientRect : referenceClientRect; // positive = overflowing the clipping rect\n // 0 or negative = within the clipping rect\n\n var overflowOffsets = {\n top: clippingClientRect.top - elementClientRect.top + paddingObject.top,\n bottom: elementClientRect.bottom - clippingClientRect.bottom + paddingObject.bottom,\n left: clippingClientRect.left - elementClientRect.left + paddingObject.left,\n right: elementClientRect.right - clippingClientRect.right + paddingObject.right\n };\n var offsetData = state.modifiersData.offset; // Offsets can be applied only to the popper element\n\n if (elementContext === popper && offsetData) {\n var offset = offsetData[placement];\n Object.keys(overflowOffsets).forEach(function (key) {\n var multiply = [right, bottom].indexOf(key) >= 0 ? 1 : -1;\n var axis = [top, bottom].indexOf(key) >= 0 ? 'y' : 'x';\n overflowOffsets[key] += offset[axis] * multiply;\n });\n }\n\n return overflowOffsets;\n}","import getOppositePlacement from \"../utils/getOppositePlacement.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getOppositeVariationPlacement from \"../utils/getOppositeVariationPlacement.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport computeAutoPlacement from \"../utils/computeAutoPlacement.js\";\nimport { bottom, top, start, right, left, auto } from \"../enums.js\";\nimport getVariation from \"../utils/getVariation.js\"; // eslint-disable-next-line import/no-unused-modules\n\nfunction getExpandedFallbackPlacements(placement) {\n if (getBasePlacement(placement) === auto) {\n return [];\n }\n\n var oppositePlacement = getOppositePlacement(placement);\n return [getOppositeVariationPlacement(placement), oppositePlacement, getOppositeVariationPlacement(oppositePlacement)];\n}\n\nfunction flip(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n\n if (state.modifiersData[name]._skip) {\n return;\n }\n\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? true : _options$altAxis,\n specifiedFallbackPlacements = options.fallbackPlacements,\n padding = options.padding,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n _options$flipVariatio = options.flipVariations,\n flipVariations = _options$flipVariatio === void 0 ? true : _options$flipVariatio,\n allowedAutoPlacements = options.allowedAutoPlacements;\n var preferredPlacement = state.options.placement;\n var basePlacement = getBasePlacement(preferredPlacement);\n var isBasePlacement = basePlacement === preferredPlacement;\n var fallbackPlacements = specifiedFallbackPlacements || (isBasePlacement || !flipVariations ? [getOppositePlacement(preferredPlacement)] : getExpandedFallbackPlacements(preferredPlacement));\n var placements = [preferredPlacement].concat(fallbackPlacements).reduce(function (acc, placement) {\n return acc.concat(getBasePlacement(placement) === auto ? computeAutoPlacement(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n flipVariations: flipVariations,\n allowedAutoPlacements: allowedAutoPlacements\n }) : placement);\n }, []);\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var checksMap = new Map();\n var makeFallbackChecks = true;\n var firstFittingPlacement = placements[0];\n\n for (var i = 0; i < placements.length; i++) {\n var placement = placements[i];\n\n var _basePlacement = getBasePlacement(placement);\n\n var isStartVariation = getVariation(placement) === start;\n var isVertical = [top, bottom].indexOf(_basePlacement) >= 0;\n var len = isVertical ? 'width' : 'height';\n var overflow = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n altBoundary: altBoundary,\n padding: padding\n });\n var mainVariationSide = isVertical ? isStartVariation ? right : left : isStartVariation ? bottom : top;\n\n if (referenceRect[len] > popperRect[len]) {\n mainVariationSide = getOppositePlacement(mainVariationSide);\n }\n\n var altVariationSide = getOppositePlacement(mainVariationSide);\n var checks = [];\n\n if (checkMainAxis) {\n checks.push(overflow[_basePlacement] <= 0);\n }\n\n if (checkAltAxis) {\n checks.push(overflow[mainVariationSide] <= 0, overflow[altVariationSide] <= 0);\n }\n\n if (checks.every(function (check) {\n return check;\n })) {\n firstFittingPlacement = placement;\n makeFallbackChecks = false;\n break;\n }\n\n checksMap.set(placement, checks);\n }\n\n if (makeFallbackChecks) {\n // `2` may be desired in some cases – research later\n var numberOfChecks = flipVariations ? 3 : 1;\n\n var _loop = function _loop(_i) {\n var fittingPlacement = placements.find(function (placement) {\n var checks = checksMap.get(placement);\n\n if (checks) {\n return checks.slice(0, _i).every(function (check) {\n return check;\n });\n }\n });\n\n if (fittingPlacement) {\n firstFittingPlacement = fittingPlacement;\n return \"break\";\n }\n };\n\n for (var _i = numberOfChecks; _i > 0; _i--) {\n var _ret = _loop(_i);\n\n if (_ret === \"break\") break;\n }\n }\n\n if (state.placement !== firstFittingPlacement) {\n state.modifiersData[name]._skip = true;\n state.placement = firstFittingPlacement;\n state.reset = true;\n }\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'flip',\n enabled: true,\n phase: 'main',\n fn: flip,\n requiresIfExists: ['offset'],\n data: {\n _skip: false\n }\n};","import getVariation from \"./getVariation.js\";\nimport { variationPlacements, basePlacements, placements as allPlacements } from \"../enums.js\";\nimport detectOverflow from \"./detectOverflow.js\";\nimport getBasePlacement from \"./getBasePlacement.js\";\nexport default function computeAutoPlacement(state, options) {\n if (options === void 0) {\n options = {};\n }\n\n var _options = options,\n placement = _options.placement,\n boundary = _options.boundary,\n rootBoundary = _options.rootBoundary,\n padding = _options.padding,\n flipVariations = _options.flipVariations,\n _options$allowedAutoP = _options.allowedAutoPlacements,\n allowedAutoPlacements = _options$allowedAutoP === void 0 ? allPlacements : _options$allowedAutoP;\n var variation = getVariation(placement);\n var placements = variation ? flipVariations ? variationPlacements : variationPlacements.filter(function (placement) {\n return getVariation(placement) === variation;\n }) : basePlacements;\n var allowedPlacements = placements.filter(function (placement) {\n return allowedAutoPlacements.indexOf(placement) >= 0;\n });\n\n if (allowedPlacements.length === 0) {\n allowedPlacements = placements;\n } // $FlowFixMe[incompatible-type]: Flow seems to have problems with two array unions...\n\n\n var overflows = allowedPlacements.reduce(function (acc, placement) {\n acc[placement] = detectOverflow(state, {\n placement: placement,\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding\n })[getBasePlacement(placement)];\n return acc;\n }, {});\n return Object.keys(overflows).sort(function (a, b) {\n return overflows[a] - overflows[b];\n });\n}","import { top, bottom, left, right } from \"../enums.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\n\nfunction getSideOffsets(overflow, rect, preventedOffsets) {\n if (preventedOffsets === void 0) {\n preventedOffsets = {\n x: 0,\n y: 0\n };\n }\n\n return {\n top: overflow.top - rect.height - preventedOffsets.y,\n right: overflow.right - rect.width + preventedOffsets.x,\n bottom: overflow.bottom - rect.height + preventedOffsets.y,\n left: overflow.left - rect.width - preventedOffsets.x\n };\n}\n\nfunction isAnySideFullyClipped(overflow) {\n return [top, right, bottom, left].some(function (side) {\n return overflow[side] >= 0;\n });\n}\n\nfunction hide(_ref) {\n var state = _ref.state,\n name = _ref.name;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var preventedOffsets = state.modifiersData.preventOverflow;\n var referenceOverflow = detectOverflow(state, {\n elementContext: 'reference'\n });\n var popperAltOverflow = detectOverflow(state, {\n altBoundary: true\n });\n var referenceClippingOffsets = getSideOffsets(referenceOverflow, referenceRect);\n var popperEscapeOffsets = getSideOffsets(popperAltOverflow, popperRect, preventedOffsets);\n var isReferenceHidden = isAnySideFullyClipped(referenceClippingOffsets);\n var hasPopperEscaped = isAnySideFullyClipped(popperEscapeOffsets);\n state.modifiersData[name] = {\n referenceClippingOffsets: referenceClippingOffsets,\n popperEscapeOffsets: popperEscapeOffsets,\n isReferenceHidden: isReferenceHidden,\n hasPopperEscaped: hasPopperEscaped\n };\n state.attributes.popper = Object.assign({}, state.attributes.popper, {\n 'data-popper-reference-hidden': isReferenceHidden,\n 'data-popper-escaped': hasPopperEscaped\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'hide',\n enabled: true,\n phase: 'main',\n requiresIfExists: ['preventOverflow'],\n fn: hide\n};","import getBasePlacement from \"../utils/getBasePlacement.js\";\nimport { top, left, right, placements } from \"../enums.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport function distanceAndSkiddingToXY(placement, rects, offset) {\n var basePlacement = getBasePlacement(placement);\n var invertDistance = [left, top].indexOf(basePlacement) >= 0 ? -1 : 1;\n\n var _ref = typeof offset === 'function' ? offset(Object.assign({}, rects, {\n placement: placement\n })) : offset,\n skidding = _ref[0],\n distance = _ref[1];\n\n skidding = skidding || 0;\n distance = (distance || 0) * invertDistance;\n return [left, right].indexOf(basePlacement) >= 0 ? {\n x: distance,\n y: skidding\n } : {\n x: skidding,\n y: distance\n };\n}\n\nfunction offset(_ref2) {\n var state = _ref2.state,\n options = _ref2.options,\n name = _ref2.name;\n var _options$offset = options.offset,\n offset = _options$offset === void 0 ? [0, 0] : _options$offset;\n var data = placements.reduce(function (acc, placement) {\n acc[placement] = distanceAndSkiddingToXY(placement, state.rects, offset);\n return acc;\n }, {});\n var _data$state$placement = data[state.placement],\n x = _data$state$placement.x,\n y = _data$state$placement.y;\n\n if (state.modifiersData.popperOffsets != null) {\n state.modifiersData.popperOffsets.x += x;\n state.modifiersData.popperOffsets.y += y;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'offset',\n enabled: true,\n phase: 'main',\n requires: ['popperOffsets'],\n fn: offset\n};","import computeOffsets from \"../utils/computeOffsets.js\";\n\nfunction popperOffsets(_ref) {\n var state = _ref.state,\n name = _ref.name;\n // Offsets are the actual position the popper needs to have to be\n // properly positioned near its reference element\n // This is the most basic placement, and will be adjusted by\n // the modifiers in the next step\n state.modifiersData[name] = computeOffsets({\n reference: state.rects.reference,\n element: state.rects.popper,\n strategy: 'absolute',\n placement: state.placement\n });\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'popperOffsets',\n enabled: true,\n phase: 'read',\n fn: popperOffsets,\n data: {}\n};","import { top, left, right, bottom, start } from \"../enums.js\";\nimport getBasePlacement from \"../utils/getBasePlacement.js\";\nimport getMainAxisFromPlacement from \"../utils/getMainAxisFromPlacement.js\";\nimport getAltAxis from \"../utils/getAltAxis.js\";\nimport { within, withinMaxClamp } from \"../utils/within.js\";\nimport getLayoutRect from \"../dom-utils/getLayoutRect.js\";\nimport getOffsetParent from \"../dom-utils/getOffsetParent.js\";\nimport detectOverflow from \"../utils/detectOverflow.js\";\nimport getVariation from \"../utils/getVariation.js\";\nimport getFreshSideObject from \"../utils/getFreshSideObject.js\";\nimport { min as mathMin, max as mathMax } from \"../utils/math.js\";\n\nfunction preventOverflow(_ref) {\n var state = _ref.state,\n options = _ref.options,\n name = _ref.name;\n var _options$mainAxis = options.mainAxis,\n checkMainAxis = _options$mainAxis === void 0 ? true : _options$mainAxis,\n _options$altAxis = options.altAxis,\n checkAltAxis = _options$altAxis === void 0 ? false : _options$altAxis,\n boundary = options.boundary,\n rootBoundary = options.rootBoundary,\n altBoundary = options.altBoundary,\n padding = options.padding,\n _options$tether = options.tether,\n tether = _options$tether === void 0 ? true : _options$tether,\n _options$tetherOffset = options.tetherOffset,\n tetherOffset = _options$tetherOffset === void 0 ? 0 : _options$tetherOffset;\n var overflow = detectOverflow(state, {\n boundary: boundary,\n rootBoundary: rootBoundary,\n padding: padding,\n altBoundary: altBoundary\n });\n var basePlacement = getBasePlacement(state.placement);\n var variation = getVariation(state.placement);\n var isBasePlacement = !variation;\n var mainAxis = getMainAxisFromPlacement(basePlacement);\n var altAxis = getAltAxis(mainAxis);\n var popperOffsets = state.modifiersData.popperOffsets;\n var referenceRect = state.rects.reference;\n var popperRect = state.rects.popper;\n var tetherOffsetValue = typeof tetherOffset === 'function' ? tetherOffset(Object.assign({}, state.rects, {\n placement: state.placement\n })) : tetherOffset;\n var normalizedTetherOffsetValue = typeof tetherOffsetValue === 'number' ? {\n mainAxis: tetherOffsetValue,\n altAxis: tetherOffsetValue\n } : Object.assign({\n mainAxis: 0,\n altAxis: 0\n }, tetherOffsetValue);\n var offsetModifierState = state.modifiersData.offset ? state.modifiersData.offset[state.placement] : null;\n var data = {\n x: 0,\n y: 0\n };\n\n if (!popperOffsets) {\n return;\n }\n\n if (checkMainAxis) {\n var _offsetModifierState$;\n\n var mainSide = mainAxis === 'y' ? top : left;\n var altSide = mainAxis === 'y' ? bottom : right;\n var len = mainAxis === 'y' ? 'height' : 'width';\n var offset = popperOffsets[mainAxis];\n var min = offset + overflow[mainSide];\n var max = offset - overflow[altSide];\n var additive = tether ? -popperRect[len] / 2 : 0;\n var minLen = variation === start ? referenceRect[len] : popperRect[len];\n var maxLen = variation === start ? -popperRect[len] : -referenceRect[len]; // We need to include the arrow in the calculation so the arrow doesn't go\n // outside the reference bounds\n\n var arrowElement = state.elements.arrow;\n var arrowRect = tether && arrowElement ? getLayoutRect(arrowElement) : {\n width: 0,\n height: 0\n };\n var arrowPaddingObject = state.modifiersData['arrow#persistent'] ? state.modifiersData['arrow#persistent'].padding : getFreshSideObject();\n var arrowPaddingMin = arrowPaddingObject[mainSide];\n var arrowPaddingMax = arrowPaddingObject[altSide]; // If the reference length is smaller than the arrow length, we don't want\n // to include its full size in the calculation. If the reference is small\n // and near the edge of a boundary, the popper can overflow even if the\n // reference is not overflowing as well (e.g. virtual elements with no\n // width or height)\n\n var arrowLen = within(0, referenceRect[len], arrowRect[len]);\n var minOffset = isBasePlacement ? referenceRect[len] / 2 - additive - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis : minLen - arrowLen - arrowPaddingMin - normalizedTetherOffsetValue.mainAxis;\n var maxOffset = isBasePlacement ? -referenceRect[len] / 2 + additive + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis : maxLen + arrowLen + arrowPaddingMax + normalizedTetherOffsetValue.mainAxis;\n var arrowOffsetParent = state.elements.arrow && getOffsetParent(state.elements.arrow);\n var clientOffset = arrowOffsetParent ? mainAxis === 'y' ? arrowOffsetParent.clientTop || 0 : arrowOffsetParent.clientLeft || 0 : 0;\n var offsetModifierValue = (_offsetModifierState$ = offsetModifierState == null ? void 0 : offsetModifierState[mainAxis]) != null ? _offsetModifierState$ : 0;\n var tetherMin = offset + minOffset - offsetModifierValue - clientOffset;\n var tetherMax = offset + maxOffset - offsetModifierValue;\n var preventedOffset = within(tether ? mathMin(min, tetherMin) : min, offset, tether ? mathMax(max, tetherMax) : max);\n popperOffsets[mainAxis] = preventedOffset;\n data[mainAxis] = preventedOffset - offset;\n }\n\n if (checkAltAxis) {\n var _offsetModifierState$2;\n\n var _mainSide = mainAxis === 'x' ? top : left;\n\n var _altSide = mainAxis === 'x' ? bottom : right;\n\n var _offset = popperOffsets[altAxis];\n\n var _len = altAxis === 'y' ? 'height' : 'width';\n\n var _min = _offset + overflow[_mainSide];\n\n var _max = _offset - overflow[_altSide];\n\n var isOriginSide = [top, left].indexOf(basePlacement) !== -1;\n\n var _offsetModifierValue = (_offsetModifierState$2 = offsetModifierState == null ? void 0 : offsetModifierState[altAxis]) != null ? _offsetModifierState$2 : 0;\n\n var _tetherMin = isOriginSide ? _min : _offset - referenceRect[_len] - popperRect[_len] - _offsetModifierValue + normalizedTetherOffsetValue.altAxis;\n\n var _tetherMax = isOriginSide ? _offset + referenceRect[_len] + popperRect[_len] - _offsetModifierValue - normalizedTetherOffsetValue.altAxis : _max;\n\n var _preventedOffset = tether && isOriginSide ? withinMaxClamp(_tetherMin, _offset, _tetherMax) : within(tether ? _tetherMin : _min, _offset, tether ? _tetherMax : _max);\n\n popperOffsets[altAxis] = _preventedOffset;\n data[altAxis] = _preventedOffset - _offset;\n }\n\n state.modifiersData[name] = data;\n} // eslint-disable-next-line import/no-unused-modules\n\n\nexport default {\n name: 'preventOverflow',\n enabled: true,\n phase: 'main',\n fn: preventOverflow,\n requiresIfExists: ['offset']\n};","export default function getAltAxis(axis) {\n return axis === 'x' ? 'y' : 'x';\n}","import getBoundingClientRect from \"./getBoundingClientRect.js\";\nimport getNodeScroll from \"./getNodeScroll.js\";\nimport getNodeName from \"./getNodeName.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getWindowScrollBarX from \"./getWindowScrollBarX.js\";\nimport getDocumentElement from \"./getDocumentElement.js\";\nimport isScrollParent from \"./isScrollParent.js\";\nimport { round } from \"../utils/math.js\";\n\nfunction isElementScaled(element) {\n var rect = element.getBoundingClientRect();\n var scaleX = round(rect.width) / element.offsetWidth || 1;\n var scaleY = round(rect.height) / element.offsetHeight || 1;\n return scaleX !== 1 || scaleY !== 1;\n} // Returns the composite rect of an element relative to its offsetParent.\n// Composite means it takes into account transforms as well as layout.\n\n\nexport default function getCompositeRect(elementOrVirtualElement, offsetParent, isFixed) {\n if (isFixed === void 0) {\n isFixed = false;\n }\n\n var isOffsetParentAnElement = isHTMLElement(offsetParent);\n var offsetParentIsScaled = isHTMLElement(offsetParent) && isElementScaled(offsetParent);\n var documentElement = getDocumentElement(offsetParent);\n var rect = getBoundingClientRect(elementOrVirtualElement, offsetParentIsScaled, isFixed);\n var scroll = {\n scrollLeft: 0,\n scrollTop: 0\n };\n var offsets = {\n x: 0,\n y: 0\n };\n\n if (isOffsetParentAnElement || !isOffsetParentAnElement && !isFixed) {\n if (getNodeName(offsetParent) !== 'body' || // https://github.com/popperjs/popper-core/issues/1078\n isScrollParent(documentElement)) {\n scroll = getNodeScroll(offsetParent);\n }\n\n if (isHTMLElement(offsetParent)) {\n offsets = getBoundingClientRect(offsetParent, true);\n offsets.x += offsetParent.clientLeft;\n offsets.y += offsetParent.clientTop;\n } else if (documentElement) {\n offsets.x = getWindowScrollBarX(documentElement);\n }\n }\n\n return {\n x: rect.left + scroll.scrollLeft - offsets.x,\n y: rect.top + scroll.scrollTop - offsets.y,\n width: rect.width,\n height: rect.height\n };\n}","import getWindowScroll from \"./getWindowScroll.js\";\nimport getWindow from \"./getWindow.js\";\nimport { isHTMLElement } from \"./instanceOf.js\";\nimport getHTMLElementScroll from \"./getHTMLElementScroll.js\";\nexport default function getNodeScroll(node) {\n if (node === getWindow(node) || !isHTMLElement(node)) {\n return getWindowScroll(node);\n } else {\n return getHTMLElementScroll(node);\n }\n}","export default function getHTMLElementScroll(element) {\n return {\n scrollLeft: element.scrollLeft,\n scrollTop: element.scrollTop\n };\n}","import { modifierPhases } from \"../enums.js\"; // source: https://stackoverflow.com/questions/49875255\n\nfunction order(modifiers) {\n var map = new Map();\n var visited = new Set();\n var result = [];\n modifiers.forEach(function (modifier) {\n map.set(modifier.name, modifier);\n }); // On visiting object, check for its dependencies and visit them recursively\n\n function sort(modifier) {\n visited.add(modifier.name);\n var requires = [].concat(modifier.requires || [], modifier.requiresIfExists || []);\n requires.forEach(function (dep) {\n if (!visited.has(dep)) {\n var depModifier = map.get(dep);\n\n if (depModifier) {\n sort(depModifier);\n }\n }\n });\n result.push(modifier);\n }\n\n modifiers.forEach(function (modifier) {\n if (!visited.has(modifier.name)) {\n // check for visited object\n sort(modifier);\n }\n });\n return result;\n}\n\nexport default function orderModifiers(modifiers) {\n // order based on dependencies\n var orderedModifiers = order(modifiers); // order based on phase\n\n return modifierPhases.reduce(function (acc, phase) {\n return acc.concat(orderedModifiers.filter(function (modifier) {\n return modifier.phase === phase;\n }));\n }, []);\n}","import getCompositeRect from \"./dom-utils/getCompositeRect.js\";\nimport getLayoutRect from \"./dom-utils/getLayoutRect.js\";\nimport listScrollParents from \"./dom-utils/listScrollParents.js\";\nimport getOffsetParent from \"./dom-utils/getOffsetParent.js\";\nimport orderModifiers from \"./utils/orderModifiers.js\";\nimport debounce from \"./utils/debounce.js\";\nimport mergeByName from \"./utils/mergeByName.js\";\nimport detectOverflow from \"./utils/detectOverflow.js\";\nimport { isElement } from \"./dom-utils/instanceOf.js\";\nvar DEFAULT_OPTIONS = {\n placement: 'bottom',\n modifiers: [],\n strategy: 'absolute'\n};\n\nfunction areValidElements() {\n for (var _len = arguments.length, args = new Array(_len), _key = 0; _key < _len; _key++) {\n args[_key] = arguments[_key];\n }\n\n return !args.some(function (element) {\n return !(element && typeof element.getBoundingClientRect === 'function');\n });\n}\n\nexport function popperGenerator(generatorOptions) {\n if (generatorOptions === void 0) {\n generatorOptions = {};\n }\n\n var _generatorOptions = generatorOptions,\n _generatorOptions$def = _generatorOptions.defaultModifiers,\n defaultModifiers = _generatorOptions$def === void 0 ? [] : _generatorOptions$def,\n _generatorOptions$def2 = _generatorOptions.defaultOptions,\n defaultOptions = _generatorOptions$def2 === void 0 ? DEFAULT_OPTIONS : _generatorOptions$def2;\n return function createPopper(reference, popper, options) {\n if (options === void 0) {\n options = defaultOptions;\n }\n\n var state = {\n placement: 'bottom',\n orderedModifiers: [],\n options: Object.assign({}, DEFAULT_OPTIONS, defaultOptions),\n modifiersData: {},\n elements: {\n reference: reference,\n popper: popper\n },\n attributes: {},\n styles: {}\n };\n var effectCleanupFns = [];\n var isDestroyed = false;\n var instance = {\n state: state,\n setOptions: function setOptions(setOptionsAction) {\n var options = typeof setOptionsAction === 'function' ? setOptionsAction(state.options) : setOptionsAction;\n cleanupModifierEffects();\n state.options = Object.assign({}, defaultOptions, state.options, options);\n state.scrollParents = {\n reference: isElement(reference) ? listScrollParents(reference) : reference.contextElement ? listScrollParents(reference.contextElement) : [],\n popper: listScrollParents(popper)\n }; // Orders the modifiers based on their dependencies and `phase`\n // properties\n\n var orderedModifiers = orderModifiers(mergeByName([].concat(defaultModifiers, state.options.modifiers))); // Strip out disabled modifiers\n\n state.orderedModifiers = orderedModifiers.filter(function (m) {\n return m.enabled;\n });\n runModifierEffects();\n return instance.update();\n },\n // Sync update – it will always be executed, even if not necessary. This\n // is useful for low frequency updates where sync behavior simplifies the\n // logic.\n // For high frequency updates (e.g. `resize` and `scroll` events), always\n // prefer the async Popper#update method\n forceUpdate: function forceUpdate() {\n if (isDestroyed) {\n return;\n }\n\n var _state$elements = state.elements,\n reference = _state$elements.reference,\n popper = _state$elements.popper; // Don't proceed if `reference` or `popper` are not valid elements\n // anymore\n\n if (!areValidElements(reference, popper)) {\n return;\n } // Store the reference and popper rects to be read by modifiers\n\n\n state.rects = {\n reference: getCompositeRect(reference, getOffsetParent(popper), state.options.strategy === 'fixed'),\n popper: getLayoutRect(popper)\n }; // Modifiers have the ability to reset the current update cycle. The\n // most common use case for this is the `flip` modifier changing the\n // placement, which then needs to re-run all the modifiers, because the\n // logic was previously ran for the previous placement and is therefore\n // stale/incorrect\n\n state.reset = false;\n state.placement = state.options.placement; // On each update cycle, the `modifiersData` property for each modifier\n // is filled with the initial data specified by the modifier. This means\n // it doesn't persist and is fresh on each update.\n // To ensure persistent data, use `${name}#persistent`\n\n state.orderedModifiers.forEach(function (modifier) {\n return state.modifiersData[modifier.name] = Object.assign({}, modifier.data);\n });\n\n for (var index = 0; index < state.orderedModifiers.length; index++) {\n if (state.reset === true) {\n state.reset = false;\n index = -1;\n continue;\n }\n\n var _state$orderedModifie = state.orderedModifiers[index],\n fn = _state$orderedModifie.fn,\n _state$orderedModifie2 = _state$orderedModifie.options,\n _options = _state$orderedModifie2 === void 0 ? {} : _state$orderedModifie2,\n name = _state$orderedModifie.name;\n\n if (typeof fn === 'function') {\n state = fn({\n state: state,\n options: _options,\n name: name,\n instance: instance\n }) || state;\n }\n }\n },\n // Async and optimistically optimized update – it will not be executed if\n // not necessary (debounced to run at most once-per-tick)\n update: debounce(function () {\n return new Promise(function (resolve) {\n instance.forceUpdate();\n resolve(state);\n });\n }),\n destroy: function destroy() {\n cleanupModifierEffects();\n isDestroyed = true;\n }\n };\n\n if (!areValidElements(reference, popper)) {\n return instance;\n }\n\n instance.setOptions(options).then(function (state) {\n if (!isDestroyed && options.onFirstUpdate) {\n options.onFirstUpdate(state);\n }\n }); // Modifiers have the ability to execute arbitrary code before the first\n // update cycle runs. They will be executed in the same order as the update\n // cycle. This is useful when a modifier adds some persistent data that\n // other modifiers need to use, but the modifier is run after the dependent\n // one.\n\n function runModifierEffects() {\n state.orderedModifiers.forEach(function (_ref) {\n var name = _ref.name,\n _ref$options = _ref.options,\n options = _ref$options === void 0 ? {} : _ref$options,\n effect = _ref.effect;\n\n if (typeof effect === 'function') {\n var cleanupFn = effect({\n state: state,\n name: name,\n instance: instance,\n options: options\n });\n\n var noopFn = function noopFn() {};\n\n effectCleanupFns.push(cleanupFn || noopFn);\n }\n });\n }\n\n function cleanupModifierEffects() {\n effectCleanupFns.forEach(function (fn) {\n return fn();\n });\n effectCleanupFns = [];\n }\n\n return instance;\n };\n}\nexport var createPopper = /*#__PURE__*/popperGenerator(); // eslint-disable-next-line import/no-unused-modules\n\nexport { detectOverflow };","export default function debounce(fn) {\n var pending;\n return function () {\n if (!pending) {\n pending = new Promise(function (resolve) {\n Promise.resolve().then(function () {\n pending = undefined;\n resolve(fn());\n });\n });\n }\n\n return pending;\n };\n}","export default function mergeByName(modifiers) {\n var merged = modifiers.reduce(function (merged, current) {\n var existing = merged[current.name];\n merged[current.name] = existing ? Object.assign({}, existing, current, {\n options: Object.assign({}, existing.options, current.options),\n data: Object.assign({}, existing.data, current.data)\n }) : current;\n return merged;\n }, {}); // IE11 does not support Object.values\n\n return Object.keys(merged).map(function (key) {\n return merged[key];\n });\n}","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nimport offset from \"./modifiers/offset.js\";\nimport flip from \"./modifiers/flip.js\";\nimport preventOverflow from \"./modifiers/preventOverflow.js\";\nimport arrow from \"./modifiers/arrow.js\";\nimport hide from \"./modifiers/hide.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles, offset, flip, preventOverflow, arrow, hide];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow }; // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper as createPopperLite } from \"./popper-lite.js\"; // eslint-disable-next-line import/no-unused-modules\n\nexport * from \"./modifiers/index.js\";","import { popperGenerator, detectOverflow } from \"./createPopper.js\";\nimport eventListeners from \"./modifiers/eventListeners.js\";\nimport popperOffsets from \"./modifiers/popperOffsets.js\";\nimport computeStyles from \"./modifiers/computeStyles.js\";\nimport applyStyles from \"./modifiers/applyStyles.js\";\nvar defaultModifiers = [eventListeners, popperOffsets, computeStyles, applyStyles];\nvar createPopper = /*#__PURE__*/popperGenerator({\n defaultModifiers: defaultModifiers\n}); // eslint-disable-next-line import/no-unused-modules\n\nexport { createPopper, popperGenerator, defaultModifiers, detectOverflow };","/*!\n * Bootstrap v5.3.3 (https://getbootstrap.com/)\n * Copyright 2011-2024 The Bootstrap Authors (https://github.com/twbs/bootstrap/graphs/contributors)\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n */\nimport * as Popper from '@popperjs/core';\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/data.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n/**\n * Constants\n */\n\nconst elementMap = new Map();\nconst Data = {\n set(element, key, instance) {\n if (!elementMap.has(element)) {\n elementMap.set(element, new Map());\n }\n const instanceMap = elementMap.get(element);\n\n // make it clear we only want one instance per element\n // can be removed later when multiple key/instances are fine to be used\n if (!instanceMap.has(key) && instanceMap.size !== 0) {\n // eslint-disable-next-line no-console\n console.error(`Bootstrap doesn't allow more than one instance per element. Bound instance: ${Array.from(instanceMap.keys())[0]}.`);\n return;\n }\n instanceMap.set(key, instance);\n },\n get(element, key) {\n if (elementMap.has(element)) {\n return elementMap.get(element).get(key) || null;\n }\n return null;\n },\n remove(element, key) {\n if (!elementMap.has(element)) {\n return;\n }\n const instanceMap = elementMap.get(element);\n instanceMap.delete(key);\n\n // free up element references if there are no instances left for an element\n if (instanceMap.size === 0) {\n elementMap.delete(element);\n }\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/index.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst MAX_UID = 1000000;\nconst MILLISECONDS_MULTIPLIER = 1000;\nconst TRANSITION_END = 'transitionend';\n\n/**\n * Properly escape IDs selectors to handle weird IDs\n * @param {string} selector\n * @returns {string}\n */\nconst parseSelector = selector => {\n if (selector && window.CSS && window.CSS.escape) {\n // document.querySelector needs escaping to handle IDs (html5+) containing for instance /\n selector = selector.replace(/#([^\\s\"#']+)/g, (match, id) => `#${CSS.escape(id)}`);\n }\n return selector;\n};\n\n// Shout-out Angus Croll (https://goo.gl/pxwQGp)\nconst toType = object => {\n if (object === null || object === undefined) {\n return `${object}`;\n }\n return Object.prototype.toString.call(object).match(/\\s([a-z]+)/i)[1].toLowerCase();\n};\n\n/**\n * Public Util API\n */\n\nconst getUID = prefix => {\n do {\n prefix += Math.floor(Math.random() * MAX_UID);\n } while (document.getElementById(prefix));\n return prefix;\n};\nconst getTransitionDurationFromElement = element => {\n if (!element) {\n return 0;\n }\n\n // Get transition-duration of the element\n let {\n transitionDuration,\n transitionDelay\n } = window.getComputedStyle(element);\n const floatTransitionDuration = Number.parseFloat(transitionDuration);\n const floatTransitionDelay = Number.parseFloat(transitionDelay);\n\n // Return 0 if element or transition duration is not found\n if (!floatTransitionDuration && !floatTransitionDelay) {\n return 0;\n }\n\n // If multiple durations are defined, take the first\n transitionDuration = transitionDuration.split(',')[0];\n transitionDelay = transitionDelay.split(',')[0];\n return (Number.parseFloat(transitionDuration) + Number.parseFloat(transitionDelay)) * MILLISECONDS_MULTIPLIER;\n};\nconst triggerTransitionEnd = element => {\n element.dispatchEvent(new Event(TRANSITION_END));\n};\nconst isElement = object => {\n if (!object || typeof object !== 'object') {\n return false;\n }\n if (typeof object.jquery !== 'undefined') {\n object = object[0];\n }\n return typeof object.nodeType !== 'undefined';\n};\nconst getElement = object => {\n // it's a jQuery object or a node element\n if (isElement(object)) {\n return object.jquery ? object[0] : object;\n }\n if (typeof object === 'string' && object.length > 0) {\n return document.querySelector(parseSelector(object));\n }\n return null;\n};\nconst isVisible = element => {\n if (!isElement(element) || element.getClientRects().length === 0) {\n return false;\n }\n const elementIsVisible = getComputedStyle(element).getPropertyValue('visibility') === 'visible';\n // Handle `details` element as its content may falsie appear visible when it is closed\n const closedDetails = element.closest('details:not([open])');\n if (!closedDetails) {\n return elementIsVisible;\n }\n if (closedDetails !== element) {\n const summary = element.closest('summary');\n if (summary && summary.parentNode !== closedDetails) {\n return false;\n }\n if (summary === null) {\n return false;\n }\n }\n return elementIsVisible;\n};\nconst isDisabled = element => {\n if (!element || element.nodeType !== Node.ELEMENT_NODE) {\n return true;\n }\n if (element.classList.contains('disabled')) {\n return true;\n }\n if (typeof element.disabled !== 'undefined') {\n return element.disabled;\n }\n return element.hasAttribute('disabled') && element.getAttribute('disabled') !== 'false';\n};\nconst findShadowRoot = element => {\n if (!document.documentElement.attachShadow) {\n return null;\n }\n\n // Can find the shadow root otherwise it'll return the document\n if (typeof element.getRootNode === 'function') {\n const root = element.getRootNode();\n return root instanceof ShadowRoot ? root : null;\n }\n if (element instanceof ShadowRoot) {\n return element;\n }\n\n // when we don't find a shadow root\n if (!element.parentNode) {\n return null;\n }\n return findShadowRoot(element.parentNode);\n};\nconst noop = () => {};\n\n/**\n * Trick to restart an element's animation\n *\n * @param {HTMLElement} element\n * @return void\n *\n * @see https://www.charistheo.io/blog/2021/02/restart-a-css-animation-with-javascript/#restarting-a-css-animation\n */\nconst reflow = element => {\n element.offsetHeight; // eslint-disable-line no-unused-expressions\n};\nconst getjQuery = () => {\n if (window.jQuery && !document.body.hasAttribute('data-bs-no-jquery')) {\n return window.jQuery;\n }\n return null;\n};\nconst DOMContentLoadedCallbacks = [];\nconst onDOMContentLoaded = callback => {\n if (document.readyState === 'loading') {\n // add listener on the first call when the document is in loading state\n if (!DOMContentLoadedCallbacks.length) {\n document.addEventListener('DOMContentLoaded', () => {\n for (const callback of DOMContentLoadedCallbacks) {\n callback();\n }\n });\n }\n DOMContentLoadedCallbacks.push(callback);\n } else {\n callback();\n }\n};\nconst isRTL = () => document.documentElement.dir === 'rtl';\nconst defineJQueryPlugin = plugin => {\n onDOMContentLoaded(() => {\n const $ = getjQuery();\n /* istanbul ignore if */\n if ($) {\n const name = plugin.NAME;\n const JQUERY_NO_CONFLICT = $.fn[name];\n $.fn[name] = plugin.jQueryInterface;\n $.fn[name].Constructor = plugin;\n $.fn[name].noConflict = () => {\n $.fn[name] = JQUERY_NO_CONFLICT;\n return plugin.jQueryInterface;\n };\n }\n });\n};\nconst execute = (possibleCallback, args = [], defaultValue = possibleCallback) => {\n return typeof possibleCallback === 'function' ? possibleCallback(...args) : defaultValue;\n};\nconst executeAfterTransition = (callback, transitionElement, waitForTransition = true) => {\n if (!waitForTransition) {\n execute(callback);\n return;\n }\n const durationPadding = 5;\n const emulatedDuration = getTransitionDurationFromElement(transitionElement) + durationPadding;\n let called = false;\n const handler = ({\n target\n }) => {\n if (target !== transitionElement) {\n return;\n }\n called = true;\n transitionElement.removeEventListener(TRANSITION_END, handler);\n execute(callback);\n };\n transitionElement.addEventListener(TRANSITION_END, handler);\n setTimeout(() => {\n if (!called) {\n triggerTransitionEnd(transitionElement);\n }\n }, emulatedDuration);\n};\n\n/**\n * Return the previous/next element of a list.\n *\n * @param {array} list The list of elements\n * @param activeElement The active element\n * @param shouldGetNext Choose to get next or previous element\n * @param isCycleAllowed\n * @return {Element|elem} The proper element\n */\nconst getNextActiveElement = (list, activeElement, shouldGetNext, isCycleAllowed) => {\n const listLength = list.length;\n let index = list.indexOf(activeElement);\n\n // if the element does not exist in the list return an element\n // depending on the direction and if cycle is allowed\n if (index === -1) {\n return !shouldGetNext && isCycleAllowed ? list[listLength - 1] : list[0];\n }\n index += shouldGetNext ? 1 : -1;\n if (isCycleAllowed) {\n index = (index + listLength) % listLength;\n }\n return list[Math.max(0, Math.min(index, listLength - 1))];\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/event-handler.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst namespaceRegex = /[^.]*(?=\\..*)\\.|.*/;\nconst stripNameRegex = /\\..*/;\nconst stripUidRegex = /::\\d+$/;\nconst eventRegistry = {}; // Events storage\nlet uidEvent = 1;\nconst customEvents = {\n mouseenter: 'mouseover',\n mouseleave: 'mouseout'\n};\nconst nativeEvents = new Set(['click', 'dblclick', 'mouseup', 'mousedown', 'contextmenu', 'mousewheel', 'DOMMouseScroll', 'mouseover', 'mouseout', 'mousemove', 'selectstart', 'selectend', 'keydown', 'keypress', 'keyup', 'orientationchange', 'touchstart', 'touchmove', 'touchend', 'touchcancel', 'pointerdown', 'pointermove', 'pointerup', 'pointerleave', 'pointercancel', 'gesturestart', 'gesturechange', 'gestureend', 'focus', 'blur', 'change', 'reset', 'select', 'submit', 'focusin', 'focusout', 'load', 'unload', 'beforeunload', 'resize', 'move', 'DOMContentLoaded', 'readystatechange', 'error', 'abort', 'scroll']);\n\n/**\n * Private methods\n */\n\nfunction makeEventUid(element, uid) {\n return uid && `${uid}::${uidEvent++}` || element.uidEvent || uidEvent++;\n}\nfunction getElementEvents(element) {\n const uid = makeEventUid(element);\n element.uidEvent = uid;\n eventRegistry[uid] = eventRegistry[uid] || {};\n return eventRegistry[uid];\n}\nfunction bootstrapHandler(element, fn) {\n return function handler(event) {\n hydrateObj(event, {\n delegateTarget: element\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, fn);\n }\n return fn.apply(element, [event]);\n };\n}\nfunction bootstrapDelegationHandler(element, selector, fn) {\n return function handler(event) {\n const domElements = element.querySelectorAll(selector);\n for (let {\n target\n } = event; target && target !== this; target = target.parentNode) {\n for (const domElement of domElements) {\n if (domElement !== target) {\n continue;\n }\n hydrateObj(event, {\n delegateTarget: target\n });\n if (handler.oneOff) {\n EventHandler.off(element, event.type, selector, fn);\n }\n return fn.apply(target, [event]);\n }\n }\n };\n}\nfunction findHandler(events, callable, delegationSelector = null) {\n return Object.values(events).find(event => event.callable === callable && event.delegationSelector === delegationSelector);\n}\nfunction normalizeParameters(originalTypeEvent, handler, delegationFunction) {\n const isDelegated = typeof handler === 'string';\n // TODO: tooltip passes `false` instead of selector, so we need to check\n const callable = isDelegated ? delegationFunction : handler || delegationFunction;\n let typeEvent = getTypeEvent(originalTypeEvent);\n if (!nativeEvents.has(typeEvent)) {\n typeEvent = originalTypeEvent;\n }\n return [isDelegated, callable, typeEvent];\n}\nfunction addHandler(element, originalTypeEvent, handler, delegationFunction, oneOff) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n let [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n\n // in case of mouseenter or mouseleave wrap the handler within a function that checks for its DOM position\n // this prevents the handler from being dispatched the same way as mouseover or mouseout does\n if (originalTypeEvent in customEvents) {\n const wrapFunction = fn => {\n return function (event) {\n if (!event.relatedTarget || event.relatedTarget !== event.delegateTarget && !event.delegateTarget.contains(event.relatedTarget)) {\n return fn.call(this, event);\n }\n };\n };\n callable = wrapFunction(callable);\n }\n const events = getElementEvents(element);\n const handlers = events[typeEvent] || (events[typeEvent] = {});\n const previousFunction = findHandler(handlers, callable, isDelegated ? handler : null);\n if (previousFunction) {\n previousFunction.oneOff = previousFunction.oneOff && oneOff;\n return;\n }\n const uid = makeEventUid(callable, originalTypeEvent.replace(namespaceRegex, ''));\n const fn = isDelegated ? bootstrapDelegationHandler(element, handler, callable) : bootstrapHandler(element, callable);\n fn.delegationSelector = isDelegated ? handler : null;\n fn.callable = callable;\n fn.oneOff = oneOff;\n fn.uidEvent = uid;\n handlers[uid] = fn;\n element.addEventListener(typeEvent, fn, isDelegated);\n}\nfunction removeHandler(element, events, typeEvent, handler, delegationSelector) {\n const fn = findHandler(events[typeEvent], handler, delegationSelector);\n if (!fn) {\n return;\n }\n element.removeEventListener(typeEvent, fn, Boolean(delegationSelector));\n delete events[typeEvent][fn.uidEvent];\n}\nfunction removeNamespacedHandlers(element, events, typeEvent, namespace) {\n const storeElementEvent = events[typeEvent] || {};\n for (const [handlerKey, event] of Object.entries(storeElementEvent)) {\n if (handlerKey.includes(namespace)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n}\nfunction getTypeEvent(event) {\n // allow to get the native events from namespaced events ('click.bs.button' --> 'click')\n event = event.replace(stripNameRegex, '');\n return customEvents[event] || event;\n}\nconst EventHandler = {\n on(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, false);\n },\n one(element, event, handler, delegationFunction) {\n addHandler(element, event, handler, delegationFunction, true);\n },\n off(element, originalTypeEvent, handler, delegationFunction) {\n if (typeof originalTypeEvent !== 'string' || !element) {\n return;\n }\n const [isDelegated, callable, typeEvent] = normalizeParameters(originalTypeEvent, handler, delegationFunction);\n const inNamespace = typeEvent !== originalTypeEvent;\n const events = getElementEvents(element);\n const storeElementEvent = events[typeEvent] || {};\n const isNamespace = originalTypeEvent.startsWith('.');\n if (typeof callable !== 'undefined') {\n // Simplest case: handler is passed, remove that listener ONLY.\n if (!Object.keys(storeElementEvent).length) {\n return;\n }\n removeHandler(element, events, typeEvent, callable, isDelegated ? handler : null);\n return;\n }\n if (isNamespace) {\n for (const elementEvent of Object.keys(events)) {\n removeNamespacedHandlers(element, events, elementEvent, originalTypeEvent.slice(1));\n }\n }\n for (const [keyHandlers, event] of Object.entries(storeElementEvent)) {\n const handlerKey = keyHandlers.replace(stripUidRegex, '');\n if (!inNamespace || originalTypeEvent.includes(handlerKey)) {\n removeHandler(element, events, typeEvent, event.callable, event.delegationSelector);\n }\n }\n },\n trigger(element, event, args) {\n if (typeof event !== 'string' || !element) {\n return null;\n }\n const $ = getjQuery();\n const typeEvent = getTypeEvent(event);\n const inNamespace = event !== typeEvent;\n let jQueryEvent = null;\n let bubbles = true;\n let nativeDispatch = true;\n let defaultPrevented = false;\n if (inNamespace && $) {\n jQueryEvent = $.Event(event, args);\n $(element).trigger(jQueryEvent);\n bubbles = !jQueryEvent.isPropagationStopped();\n nativeDispatch = !jQueryEvent.isImmediatePropagationStopped();\n defaultPrevented = jQueryEvent.isDefaultPrevented();\n }\n const evt = hydrateObj(new Event(event, {\n bubbles,\n cancelable: true\n }), args);\n if (defaultPrevented) {\n evt.preventDefault();\n }\n if (nativeDispatch) {\n element.dispatchEvent(evt);\n }\n if (evt.defaultPrevented && jQueryEvent) {\n jQueryEvent.preventDefault();\n }\n return evt;\n }\n};\nfunction hydrateObj(obj, meta = {}) {\n for (const [key, value] of Object.entries(meta)) {\n try {\n obj[key] = value;\n } catch (_unused) {\n Object.defineProperty(obj, key, {\n configurable: true,\n get() {\n return value;\n }\n });\n }\n }\n return obj;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/manipulator.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nfunction normalizeData(value) {\n if (value === 'true') {\n return true;\n }\n if (value === 'false') {\n return false;\n }\n if (value === Number(value).toString()) {\n return Number(value);\n }\n if (value === '' || value === 'null') {\n return null;\n }\n if (typeof value !== 'string') {\n return value;\n }\n try {\n return JSON.parse(decodeURIComponent(value));\n } catch (_unused) {\n return value;\n }\n}\nfunction normalizeDataKey(key) {\n return key.replace(/[A-Z]/g, chr => `-${chr.toLowerCase()}`);\n}\nconst Manipulator = {\n setDataAttribute(element, key, value) {\n element.setAttribute(`data-bs-${normalizeDataKey(key)}`, value);\n },\n removeDataAttribute(element, key) {\n element.removeAttribute(`data-bs-${normalizeDataKey(key)}`);\n },\n getDataAttributes(element) {\n if (!element) {\n return {};\n }\n const attributes = {};\n const bsKeys = Object.keys(element.dataset).filter(key => key.startsWith('bs') && !key.startsWith('bsConfig'));\n for (const key of bsKeys) {\n let pureKey = key.replace(/^bs/, '');\n pureKey = pureKey.charAt(0).toLowerCase() + pureKey.slice(1, pureKey.length);\n attributes[pureKey] = normalizeData(element.dataset[key]);\n }\n return attributes;\n },\n getDataAttribute(element, key) {\n return normalizeData(element.getAttribute(`data-bs-${normalizeDataKey(key)}`));\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/config.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Class definition\n */\n\nclass Config {\n // Getters\n static get Default() {\n return {};\n }\n static get DefaultType() {\n return {};\n }\n static get NAME() {\n throw new Error('You have to implement the static method \"NAME\", for each component!');\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n return config;\n }\n _mergeConfigObj(config, element) {\n const jsonConfig = isElement(element) ? Manipulator.getDataAttribute(element, 'config') : {}; // try to parse\n\n return {\n ...this.constructor.Default,\n ...(typeof jsonConfig === 'object' ? jsonConfig : {}),\n ...(isElement(element) ? Manipulator.getDataAttributes(element) : {}),\n ...(typeof config === 'object' ? config : {})\n };\n }\n _typeCheckConfig(config, configTypes = this.constructor.DefaultType) {\n for (const [property, expectedTypes] of Object.entries(configTypes)) {\n const value = config[property];\n const valueType = isElement(value) ? 'element' : toType(value);\n if (!new RegExp(expectedTypes).test(valueType)) {\n throw new TypeError(`${this.constructor.NAME.toUpperCase()}: Option \"${property}\" provided type \"${valueType}\" but expected type \"${expectedTypes}\".`);\n }\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap base-component.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst VERSION = '5.3.3';\n\n/**\n * Class definition\n */\n\nclass BaseComponent extends Config {\n constructor(element, config) {\n super();\n element = getElement(element);\n if (!element) {\n return;\n }\n this._element = element;\n this._config = this._getConfig(config);\n Data.set(this._element, this.constructor.DATA_KEY, this);\n }\n\n // Public\n dispose() {\n Data.remove(this._element, this.constructor.DATA_KEY);\n EventHandler.off(this._element, this.constructor.EVENT_KEY);\n for (const propertyName of Object.getOwnPropertyNames(this)) {\n this[propertyName] = null;\n }\n }\n _queueCallback(callback, element, isAnimated = true) {\n executeAfterTransition(callback, element, isAnimated);\n }\n _getConfig(config) {\n config = this._mergeConfigObj(config, this._element);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n\n // Static\n static getInstance(element) {\n return Data.get(getElement(element), this.DATA_KEY);\n }\n static getOrCreateInstance(element, config = {}) {\n return this.getInstance(element) || new this(element, typeof config === 'object' ? config : null);\n }\n static get VERSION() {\n return VERSION;\n }\n static get DATA_KEY() {\n return `bs.${this.NAME}`;\n }\n static get EVENT_KEY() {\n return `.${this.DATA_KEY}`;\n }\n static eventName(name) {\n return `${name}${this.EVENT_KEY}`;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dom/selector-engine.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst getSelector = element => {\n let selector = element.getAttribute('data-bs-target');\n if (!selector || selector === '#') {\n let hrefAttribute = element.getAttribute('href');\n\n // The only valid content that could double as a selector are IDs or classes,\n // so everything starting with `#` or `.`. If a \"real\" URL is used as the selector,\n // `document.querySelector` will rightfully complain it is invalid.\n // See https://github.com/twbs/bootstrap/issues/32273\n if (!hrefAttribute || !hrefAttribute.includes('#') && !hrefAttribute.startsWith('.')) {\n return null;\n }\n\n // Just in case some CMS puts out a full URL with the anchor appended\n if (hrefAttribute.includes('#') && !hrefAttribute.startsWith('#')) {\n hrefAttribute = `#${hrefAttribute.split('#')[1]}`;\n }\n selector = hrefAttribute && hrefAttribute !== '#' ? hrefAttribute.trim() : null;\n }\n return selector ? selector.split(',').map(sel => parseSelector(sel)).join(',') : null;\n};\nconst SelectorEngine = {\n find(selector, element = document.documentElement) {\n return [].concat(...Element.prototype.querySelectorAll.call(element, selector));\n },\n findOne(selector, element = document.documentElement) {\n return Element.prototype.querySelector.call(element, selector);\n },\n children(element, selector) {\n return [].concat(...element.children).filter(child => child.matches(selector));\n },\n parents(element, selector) {\n const parents = [];\n let ancestor = element.parentNode.closest(selector);\n while (ancestor) {\n parents.push(ancestor);\n ancestor = ancestor.parentNode.closest(selector);\n }\n return parents;\n },\n prev(element, selector) {\n let previous = element.previousElementSibling;\n while (previous) {\n if (previous.matches(selector)) {\n return [previous];\n }\n previous = previous.previousElementSibling;\n }\n return [];\n },\n // TODO: this is now unused; remove later along with prev()\n next(element, selector) {\n let next = element.nextElementSibling;\n while (next) {\n if (next.matches(selector)) {\n return [next];\n }\n next = next.nextElementSibling;\n }\n return [];\n },\n focusableChildren(element) {\n const focusables = ['a', 'button', 'input', 'textarea', 'select', 'details', '[tabindex]', '[contenteditable=\"true\"]'].map(selector => `${selector}:not([tabindex^=\"-\"])`).join(',');\n return this.find(focusables, element).filter(el => !isDisabled(el) && isVisible(el));\n },\n getSelectorFromElement(element) {\n const selector = getSelector(element);\n if (selector) {\n return SelectorEngine.findOne(selector) ? selector : null;\n }\n return null;\n },\n getElementFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.findOne(selector) : null;\n },\n getMultipleElementsFromSelector(element) {\n const selector = getSelector(element);\n return selector ? SelectorEngine.find(selector) : [];\n }\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/component-functions.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\nconst enableDismissTrigger = (component, method = 'hide') => {\n const clickEvent = `click.dismiss${component.EVENT_KEY}`;\n const name = component.NAME;\n EventHandler.on(document, clickEvent, `[data-bs-dismiss=\"${name}\"]`, function (event) {\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n const target = SelectorEngine.getElementFromSelector(this) || this.closest(`.${name}`);\n const instance = component.getOrCreateInstance(target);\n\n // Method argument is left, for Alert and only, as it doesn't implement the 'hide' method\n instance[method]();\n });\n};\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap alert.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$f = 'alert';\nconst DATA_KEY$a = 'bs.alert';\nconst EVENT_KEY$b = `.${DATA_KEY$a}`;\nconst EVENT_CLOSE = `close${EVENT_KEY$b}`;\nconst EVENT_CLOSED = `closed${EVENT_KEY$b}`;\nconst CLASS_NAME_FADE$5 = 'fade';\nconst CLASS_NAME_SHOW$8 = 'show';\n\n/**\n * Class definition\n */\n\nclass Alert extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$f;\n }\n\n // Public\n close() {\n const closeEvent = EventHandler.trigger(this._element, EVENT_CLOSE);\n if (closeEvent.defaultPrevented) {\n return;\n }\n this._element.classList.remove(CLASS_NAME_SHOW$8);\n const isAnimated = this._element.classList.contains(CLASS_NAME_FADE$5);\n this._queueCallback(() => this._destroyElement(), this._element, isAnimated);\n }\n\n // Private\n _destroyElement() {\n this._element.remove();\n EventHandler.trigger(this._element, EVENT_CLOSED);\n this.dispose();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Alert.getOrCreateInstance(this);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nenableDismissTrigger(Alert, 'close');\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Alert);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap button.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$e = 'button';\nconst DATA_KEY$9 = 'bs.button';\nconst EVENT_KEY$a = `.${DATA_KEY$9}`;\nconst DATA_API_KEY$6 = '.data-api';\nconst CLASS_NAME_ACTIVE$3 = 'active';\nconst SELECTOR_DATA_TOGGLE$5 = '[data-bs-toggle=\"button\"]';\nconst EVENT_CLICK_DATA_API$6 = `click${EVENT_KEY$a}${DATA_API_KEY$6}`;\n\n/**\n * Class definition\n */\n\nclass Button extends BaseComponent {\n // Getters\n static get NAME() {\n return NAME$e;\n }\n\n // Public\n toggle() {\n // Toggle class and sync the `aria-pressed` attribute with the return value of the `.toggle()` method\n this._element.setAttribute('aria-pressed', this._element.classList.toggle(CLASS_NAME_ACTIVE$3));\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Button.getOrCreateInstance(this);\n if (config === 'toggle') {\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$6, SELECTOR_DATA_TOGGLE$5, event => {\n event.preventDefault();\n const button = event.target.closest(SELECTOR_DATA_TOGGLE$5);\n const data = Button.getOrCreateInstance(button);\n data.toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Button);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/swipe.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$d = 'swipe';\nconst EVENT_KEY$9 = '.bs.swipe';\nconst EVENT_TOUCHSTART = `touchstart${EVENT_KEY$9}`;\nconst EVENT_TOUCHMOVE = `touchmove${EVENT_KEY$9}`;\nconst EVENT_TOUCHEND = `touchend${EVENT_KEY$9}`;\nconst EVENT_POINTERDOWN = `pointerdown${EVENT_KEY$9}`;\nconst EVENT_POINTERUP = `pointerup${EVENT_KEY$9}`;\nconst POINTER_TYPE_TOUCH = 'touch';\nconst POINTER_TYPE_PEN = 'pen';\nconst CLASS_NAME_POINTER_EVENT = 'pointer-event';\nconst SWIPE_THRESHOLD = 40;\nconst Default$c = {\n endCallback: null,\n leftCallback: null,\n rightCallback: null\n};\nconst DefaultType$c = {\n endCallback: '(function|null)',\n leftCallback: '(function|null)',\n rightCallback: '(function|null)'\n};\n\n/**\n * Class definition\n */\n\nclass Swipe extends Config {\n constructor(element, config) {\n super();\n this._element = element;\n if (!element || !Swipe.isSupported()) {\n return;\n }\n this._config = this._getConfig(config);\n this._deltaX = 0;\n this._supportPointerEvents = Boolean(window.PointerEvent);\n this._initEvents();\n }\n\n // Getters\n static get Default() {\n return Default$c;\n }\n static get DefaultType() {\n return DefaultType$c;\n }\n static get NAME() {\n return NAME$d;\n }\n\n // Public\n dispose() {\n EventHandler.off(this._element, EVENT_KEY$9);\n }\n\n // Private\n _start(event) {\n if (!this._supportPointerEvents) {\n this._deltaX = event.touches[0].clientX;\n return;\n }\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX;\n }\n }\n _end(event) {\n if (this._eventIsPointerPenTouch(event)) {\n this._deltaX = event.clientX - this._deltaX;\n }\n this._handleSwipe();\n execute(this._config.endCallback);\n }\n _move(event) {\n this._deltaX = event.touches && event.touches.length > 1 ? 0 : event.touches[0].clientX - this._deltaX;\n }\n _handleSwipe() {\n const absDeltaX = Math.abs(this._deltaX);\n if (absDeltaX <= SWIPE_THRESHOLD) {\n return;\n }\n const direction = absDeltaX / this._deltaX;\n this._deltaX = 0;\n if (!direction) {\n return;\n }\n execute(direction > 0 ? this._config.rightCallback : this._config.leftCallback);\n }\n _initEvents() {\n if (this._supportPointerEvents) {\n EventHandler.on(this._element, EVENT_POINTERDOWN, event => this._start(event));\n EventHandler.on(this._element, EVENT_POINTERUP, event => this._end(event));\n this._element.classList.add(CLASS_NAME_POINTER_EVENT);\n } else {\n EventHandler.on(this._element, EVENT_TOUCHSTART, event => this._start(event));\n EventHandler.on(this._element, EVENT_TOUCHMOVE, event => this._move(event));\n EventHandler.on(this._element, EVENT_TOUCHEND, event => this._end(event));\n }\n }\n _eventIsPointerPenTouch(event) {\n return this._supportPointerEvents && (event.pointerType === POINTER_TYPE_PEN || event.pointerType === POINTER_TYPE_TOUCH);\n }\n\n // Static\n static isSupported() {\n return 'ontouchstart' in document.documentElement || navigator.maxTouchPoints > 0;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap carousel.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$c = 'carousel';\nconst DATA_KEY$8 = 'bs.carousel';\nconst EVENT_KEY$8 = `.${DATA_KEY$8}`;\nconst DATA_API_KEY$5 = '.data-api';\nconst ARROW_LEFT_KEY$1 = 'ArrowLeft';\nconst ARROW_RIGHT_KEY$1 = 'ArrowRight';\nconst TOUCHEVENT_COMPAT_WAIT = 500; // Time for mouse compat events to fire after touch\n\nconst ORDER_NEXT = 'next';\nconst ORDER_PREV = 'prev';\nconst DIRECTION_LEFT = 'left';\nconst DIRECTION_RIGHT = 'right';\nconst EVENT_SLIDE = `slide${EVENT_KEY$8}`;\nconst EVENT_SLID = `slid${EVENT_KEY$8}`;\nconst EVENT_KEYDOWN$1 = `keydown${EVENT_KEY$8}`;\nconst EVENT_MOUSEENTER$1 = `mouseenter${EVENT_KEY$8}`;\nconst EVENT_MOUSELEAVE$1 = `mouseleave${EVENT_KEY$8}`;\nconst EVENT_DRAG_START = `dragstart${EVENT_KEY$8}`;\nconst EVENT_LOAD_DATA_API$3 = `load${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst EVENT_CLICK_DATA_API$5 = `click${EVENT_KEY$8}${DATA_API_KEY$5}`;\nconst CLASS_NAME_CAROUSEL = 'carousel';\nconst CLASS_NAME_ACTIVE$2 = 'active';\nconst CLASS_NAME_SLIDE = 'slide';\nconst CLASS_NAME_END = 'carousel-item-end';\nconst CLASS_NAME_START = 'carousel-item-start';\nconst CLASS_NAME_NEXT = 'carousel-item-next';\nconst CLASS_NAME_PREV = 'carousel-item-prev';\nconst SELECTOR_ACTIVE = '.active';\nconst SELECTOR_ITEM = '.carousel-item';\nconst SELECTOR_ACTIVE_ITEM = SELECTOR_ACTIVE + SELECTOR_ITEM;\nconst SELECTOR_ITEM_IMG = '.carousel-item img';\nconst SELECTOR_INDICATORS = '.carousel-indicators';\nconst SELECTOR_DATA_SLIDE = '[data-bs-slide], [data-bs-slide-to]';\nconst SELECTOR_DATA_RIDE = '[data-bs-ride=\"carousel\"]';\nconst KEY_TO_DIRECTION = {\n [ARROW_LEFT_KEY$1]: DIRECTION_RIGHT,\n [ARROW_RIGHT_KEY$1]: DIRECTION_LEFT\n};\nconst Default$b = {\n interval: 5000,\n keyboard: true,\n pause: 'hover',\n ride: false,\n touch: true,\n wrap: true\n};\nconst DefaultType$b = {\n interval: '(number|boolean)',\n // TODO:v6 remove boolean support\n keyboard: 'boolean',\n pause: '(string|boolean)',\n ride: '(boolean|string)',\n touch: 'boolean',\n wrap: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Carousel extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._interval = null;\n this._activeElement = null;\n this._isSliding = false;\n this.touchTimeout = null;\n this._swipeHelper = null;\n this._indicatorsElement = SelectorEngine.findOne(SELECTOR_INDICATORS, this._element);\n this._addEventListeners();\n if (this._config.ride === CLASS_NAME_CAROUSEL) {\n this.cycle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$b;\n }\n static get DefaultType() {\n return DefaultType$b;\n }\n static get NAME() {\n return NAME$c;\n }\n\n // Public\n next() {\n this._slide(ORDER_NEXT);\n }\n nextWhenVisible() {\n // FIXME TODO use `document.visibilityState`\n // Don't call next when the page isn't visible\n // or the carousel or its parent isn't visible\n if (!document.hidden && isVisible(this._element)) {\n this.next();\n }\n }\n prev() {\n this._slide(ORDER_PREV);\n }\n pause() {\n if (this._isSliding) {\n triggerTransitionEnd(this._element);\n }\n this._clearInterval();\n }\n cycle() {\n this._clearInterval();\n this._updateInterval();\n this._interval = setInterval(() => this.nextWhenVisible(), this._config.interval);\n }\n _maybeEnableCycle() {\n if (!this._config.ride) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.cycle());\n return;\n }\n this.cycle();\n }\n to(index) {\n const items = this._getItems();\n if (index > items.length - 1 || index < 0) {\n return;\n }\n if (this._isSliding) {\n EventHandler.one(this._element, EVENT_SLID, () => this.to(index));\n return;\n }\n const activeIndex = this._getItemIndex(this._getActive());\n if (activeIndex === index) {\n return;\n }\n const order = index > activeIndex ? ORDER_NEXT : ORDER_PREV;\n this._slide(order, items[index]);\n }\n dispose() {\n if (this._swipeHelper) {\n this._swipeHelper.dispose();\n }\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n config.defaultInterval = config.interval;\n return config;\n }\n _addEventListeners() {\n if (this._config.keyboard) {\n EventHandler.on(this._element, EVENT_KEYDOWN$1, event => this._keydown(event));\n }\n if (this._config.pause === 'hover') {\n EventHandler.on(this._element, EVENT_MOUSEENTER$1, () => this.pause());\n EventHandler.on(this._element, EVENT_MOUSELEAVE$1, () => this._maybeEnableCycle());\n }\n if (this._config.touch && Swipe.isSupported()) {\n this._addTouchEventListeners();\n }\n }\n _addTouchEventListeners() {\n for (const img of SelectorEngine.find(SELECTOR_ITEM_IMG, this._element)) {\n EventHandler.on(img, EVENT_DRAG_START, event => event.preventDefault());\n }\n const endCallBack = () => {\n if (this._config.pause !== 'hover') {\n return;\n }\n\n // If it's a touch-enabled device, mouseenter/leave are fired as\n // part of the mouse compatibility events on first tap - the carousel\n // would stop cycling until user tapped out of it;\n // here, we listen for touchend, explicitly pause the carousel\n // (as if it's the second time we tap on it, mouseenter compat event\n // is NOT fired) and after a timeout (to allow for mouse compatibility\n // events to fire) we explicitly restart cycling\n\n this.pause();\n if (this.touchTimeout) {\n clearTimeout(this.touchTimeout);\n }\n this.touchTimeout = setTimeout(() => this._maybeEnableCycle(), TOUCHEVENT_COMPAT_WAIT + this._config.interval);\n };\n const swipeConfig = {\n leftCallback: () => this._slide(this._directionToOrder(DIRECTION_LEFT)),\n rightCallback: () => this._slide(this._directionToOrder(DIRECTION_RIGHT)),\n endCallback: endCallBack\n };\n this._swipeHelper = new Swipe(this._element, swipeConfig);\n }\n _keydown(event) {\n if (/input|textarea/i.test(event.target.tagName)) {\n return;\n }\n const direction = KEY_TO_DIRECTION[event.key];\n if (direction) {\n event.preventDefault();\n this._slide(this._directionToOrder(direction));\n }\n }\n _getItemIndex(element) {\n return this._getItems().indexOf(element);\n }\n _setActiveIndicatorElement(index) {\n if (!this._indicatorsElement) {\n return;\n }\n const activeIndicator = SelectorEngine.findOne(SELECTOR_ACTIVE, this._indicatorsElement);\n activeIndicator.classList.remove(CLASS_NAME_ACTIVE$2);\n activeIndicator.removeAttribute('aria-current');\n const newActiveIndicator = SelectorEngine.findOne(`[data-bs-slide-to=\"${index}\"]`, this._indicatorsElement);\n if (newActiveIndicator) {\n newActiveIndicator.classList.add(CLASS_NAME_ACTIVE$2);\n newActiveIndicator.setAttribute('aria-current', 'true');\n }\n }\n _updateInterval() {\n const element = this._activeElement || this._getActive();\n if (!element) {\n return;\n }\n const elementInterval = Number.parseInt(element.getAttribute('data-bs-interval'), 10);\n this._config.interval = elementInterval || this._config.defaultInterval;\n }\n _slide(order, element = null) {\n if (this._isSliding) {\n return;\n }\n const activeElement = this._getActive();\n const isNext = order === ORDER_NEXT;\n const nextElement = element || getNextActiveElement(this._getItems(), activeElement, isNext, this._config.wrap);\n if (nextElement === activeElement) {\n return;\n }\n const nextElementIndex = this._getItemIndex(nextElement);\n const triggerEvent = eventName => {\n return EventHandler.trigger(this._element, eventName, {\n relatedTarget: nextElement,\n direction: this._orderToDirection(order),\n from: this._getItemIndex(activeElement),\n to: nextElementIndex\n });\n };\n const slideEvent = triggerEvent(EVENT_SLIDE);\n if (slideEvent.defaultPrevented) {\n return;\n }\n if (!activeElement || !nextElement) {\n // Some weirdness is happening, so we bail\n // TODO: change tests that use empty divs to avoid this check\n return;\n }\n const isCycling = Boolean(this._interval);\n this.pause();\n this._isSliding = true;\n this._setActiveIndicatorElement(nextElementIndex);\n this._activeElement = nextElement;\n const directionalClassName = isNext ? CLASS_NAME_START : CLASS_NAME_END;\n const orderClassName = isNext ? CLASS_NAME_NEXT : CLASS_NAME_PREV;\n nextElement.classList.add(orderClassName);\n reflow(nextElement);\n activeElement.classList.add(directionalClassName);\n nextElement.classList.add(directionalClassName);\n const completeCallBack = () => {\n nextElement.classList.remove(directionalClassName, orderClassName);\n nextElement.classList.add(CLASS_NAME_ACTIVE$2);\n activeElement.classList.remove(CLASS_NAME_ACTIVE$2, orderClassName, directionalClassName);\n this._isSliding = false;\n triggerEvent(EVENT_SLID);\n };\n this._queueCallback(completeCallBack, activeElement, this._isAnimated());\n if (isCycling) {\n this.cycle();\n }\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_SLIDE);\n }\n _getActive() {\n return SelectorEngine.findOne(SELECTOR_ACTIVE_ITEM, this._element);\n }\n _getItems() {\n return SelectorEngine.find(SELECTOR_ITEM, this._element);\n }\n _clearInterval() {\n if (this._interval) {\n clearInterval(this._interval);\n this._interval = null;\n }\n }\n _directionToOrder(direction) {\n if (isRTL()) {\n return direction === DIRECTION_LEFT ? ORDER_PREV : ORDER_NEXT;\n }\n return direction === DIRECTION_LEFT ? ORDER_NEXT : ORDER_PREV;\n }\n _orderToDirection(order) {\n if (isRTL()) {\n return order === ORDER_PREV ? DIRECTION_LEFT : DIRECTION_RIGHT;\n }\n return order === ORDER_PREV ? DIRECTION_RIGHT : DIRECTION_LEFT;\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Carousel.getOrCreateInstance(this, config);\n if (typeof config === 'number') {\n data.to(config);\n return;\n }\n if (typeof config === 'string') {\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$5, SELECTOR_DATA_SLIDE, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (!target || !target.classList.contains(CLASS_NAME_CAROUSEL)) {\n return;\n }\n event.preventDefault();\n const carousel = Carousel.getOrCreateInstance(target);\n const slideIndex = this.getAttribute('data-bs-slide-to');\n if (slideIndex) {\n carousel.to(slideIndex);\n carousel._maybeEnableCycle();\n return;\n }\n if (Manipulator.getDataAttribute(this, 'slide') === 'next') {\n carousel.next();\n carousel._maybeEnableCycle();\n return;\n }\n carousel.prev();\n carousel._maybeEnableCycle();\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$3, () => {\n const carousels = SelectorEngine.find(SELECTOR_DATA_RIDE);\n for (const carousel of carousels) {\n Carousel.getOrCreateInstance(carousel);\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Carousel);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap collapse.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$b = 'collapse';\nconst DATA_KEY$7 = 'bs.collapse';\nconst EVENT_KEY$7 = `.${DATA_KEY$7}`;\nconst DATA_API_KEY$4 = '.data-api';\nconst EVENT_SHOW$6 = `show${EVENT_KEY$7}`;\nconst EVENT_SHOWN$6 = `shown${EVENT_KEY$7}`;\nconst EVENT_HIDE$6 = `hide${EVENT_KEY$7}`;\nconst EVENT_HIDDEN$6 = `hidden${EVENT_KEY$7}`;\nconst EVENT_CLICK_DATA_API$4 = `click${EVENT_KEY$7}${DATA_API_KEY$4}`;\nconst CLASS_NAME_SHOW$7 = 'show';\nconst CLASS_NAME_COLLAPSE = 'collapse';\nconst CLASS_NAME_COLLAPSING = 'collapsing';\nconst CLASS_NAME_COLLAPSED = 'collapsed';\nconst CLASS_NAME_DEEPER_CHILDREN = `:scope .${CLASS_NAME_COLLAPSE} .${CLASS_NAME_COLLAPSE}`;\nconst CLASS_NAME_HORIZONTAL = 'collapse-horizontal';\nconst WIDTH = 'width';\nconst HEIGHT = 'height';\nconst SELECTOR_ACTIVES = '.collapse.show, .collapse.collapsing';\nconst SELECTOR_DATA_TOGGLE$4 = '[data-bs-toggle=\"collapse\"]';\nconst Default$a = {\n parent: null,\n toggle: true\n};\nconst DefaultType$a = {\n parent: '(null|element)',\n toggle: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Collapse extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isTransitioning = false;\n this._triggerArray = [];\n const toggleList = SelectorEngine.find(SELECTOR_DATA_TOGGLE$4);\n for (const elem of toggleList) {\n const selector = SelectorEngine.getSelectorFromElement(elem);\n const filterElement = SelectorEngine.find(selector).filter(foundElement => foundElement === this._element);\n if (selector !== null && filterElement.length) {\n this._triggerArray.push(elem);\n }\n }\n this._initializeChildren();\n if (!this._config.parent) {\n this._addAriaAndCollapsedClass(this._triggerArray, this._isShown());\n }\n if (this._config.toggle) {\n this.toggle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$a;\n }\n static get DefaultType() {\n return DefaultType$a;\n }\n static get NAME() {\n return NAME$b;\n }\n\n // Public\n toggle() {\n if (this._isShown()) {\n this.hide();\n } else {\n this.show();\n }\n }\n show() {\n if (this._isTransitioning || this._isShown()) {\n return;\n }\n let activeChildren = [];\n\n // find active children\n if (this._config.parent) {\n activeChildren = this._getFirstLevelChildren(SELECTOR_ACTIVES).filter(element => element !== this._element).map(element => Collapse.getOrCreateInstance(element, {\n toggle: false\n }));\n }\n if (activeChildren.length && activeChildren[0]._isTransitioning) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_SHOW$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n for (const activeInstance of activeChildren) {\n activeInstance.hide();\n }\n const dimension = this._getDimension();\n this._element.classList.remove(CLASS_NAME_COLLAPSE);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.style[dimension] = 0;\n this._addAriaAndCollapsedClass(this._triggerArray, true);\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n this._element.style[dimension] = '';\n EventHandler.trigger(this._element, EVENT_SHOWN$6);\n };\n const capitalizedDimension = dimension[0].toUpperCase() + dimension.slice(1);\n const scrollSize = `scroll${capitalizedDimension}`;\n this._queueCallback(complete, this._element, true);\n this._element.style[dimension] = `${this._element[scrollSize]}px`;\n }\n hide() {\n if (this._isTransitioning || !this._isShown()) {\n return;\n }\n const startEvent = EventHandler.trigger(this._element, EVENT_HIDE$6);\n if (startEvent.defaultPrevented) {\n return;\n }\n const dimension = this._getDimension();\n this._element.style[dimension] = `${this._element.getBoundingClientRect()[dimension]}px`;\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_COLLAPSING);\n this._element.classList.remove(CLASS_NAME_COLLAPSE, CLASS_NAME_SHOW$7);\n for (const trigger of this._triggerArray) {\n const element = SelectorEngine.getElementFromSelector(trigger);\n if (element && !this._isShown(element)) {\n this._addAriaAndCollapsedClass([trigger], false);\n }\n }\n this._isTransitioning = true;\n const complete = () => {\n this._isTransitioning = false;\n this._element.classList.remove(CLASS_NAME_COLLAPSING);\n this._element.classList.add(CLASS_NAME_COLLAPSE);\n EventHandler.trigger(this._element, EVENT_HIDDEN$6);\n };\n this._element.style[dimension] = '';\n this._queueCallback(complete, this._element, true);\n }\n _isShown(element = this._element) {\n return element.classList.contains(CLASS_NAME_SHOW$7);\n }\n\n // Private\n _configAfterMerge(config) {\n config.toggle = Boolean(config.toggle); // Coerce string values\n config.parent = getElement(config.parent);\n return config;\n }\n _getDimension() {\n return this._element.classList.contains(CLASS_NAME_HORIZONTAL) ? WIDTH : HEIGHT;\n }\n _initializeChildren() {\n if (!this._config.parent) {\n return;\n }\n const children = this._getFirstLevelChildren(SELECTOR_DATA_TOGGLE$4);\n for (const element of children) {\n const selected = SelectorEngine.getElementFromSelector(element);\n if (selected) {\n this._addAriaAndCollapsedClass([element], this._isShown(selected));\n }\n }\n }\n _getFirstLevelChildren(selector) {\n const children = SelectorEngine.find(CLASS_NAME_DEEPER_CHILDREN, this._config.parent);\n // remove children if greater depth\n return SelectorEngine.find(selector, this._config.parent).filter(element => !children.includes(element));\n }\n _addAriaAndCollapsedClass(triggerArray, isOpen) {\n if (!triggerArray.length) {\n return;\n }\n for (const element of triggerArray) {\n element.classList.toggle(CLASS_NAME_COLLAPSED, !isOpen);\n element.setAttribute('aria-expanded', isOpen);\n }\n }\n\n // Static\n static jQueryInterface(config) {\n const _config = {};\n if (typeof config === 'string' && /show|hide/.test(config)) {\n _config.toggle = false;\n }\n return this.each(function () {\n const data = Collapse.getOrCreateInstance(this, _config);\n if (typeof config === 'string') {\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n }\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$4, SELECTOR_DATA_TOGGLE$4, function (event) {\n // preventDefault only for elements (which change the URL) not inside the collapsible element\n if (event.target.tagName === 'A' || event.delegateTarget && event.delegateTarget.tagName === 'A') {\n event.preventDefault();\n }\n for (const element of SelectorEngine.getMultipleElementsFromSelector(this)) {\n Collapse.getOrCreateInstance(element, {\n toggle: false\n }).toggle();\n }\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Collapse);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap dropdown.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$a = 'dropdown';\nconst DATA_KEY$6 = 'bs.dropdown';\nconst EVENT_KEY$6 = `.${DATA_KEY$6}`;\nconst DATA_API_KEY$3 = '.data-api';\nconst ESCAPE_KEY$2 = 'Escape';\nconst TAB_KEY$1 = 'Tab';\nconst ARROW_UP_KEY$1 = 'ArrowUp';\nconst ARROW_DOWN_KEY$1 = 'ArrowDown';\nconst RIGHT_MOUSE_BUTTON = 2; // MouseEvent.button value for the secondary button, usually the right button\n\nconst EVENT_HIDE$5 = `hide${EVENT_KEY$6}`;\nconst EVENT_HIDDEN$5 = `hidden${EVENT_KEY$6}`;\nconst EVENT_SHOW$5 = `show${EVENT_KEY$6}`;\nconst EVENT_SHOWN$5 = `shown${EVENT_KEY$6}`;\nconst EVENT_CLICK_DATA_API$3 = `click${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYDOWN_DATA_API = `keydown${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst EVENT_KEYUP_DATA_API = `keyup${EVENT_KEY$6}${DATA_API_KEY$3}`;\nconst CLASS_NAME_SHOW$6 = 'show';\nconst CLASS_NAME_DROPUP = 'dropup';\nconst CLASS_NAME_DROPEND = 'dropend';\nconst CLASS_NAME_DROPSTART = 'dropstart';\nconst CLASS_NAME_DROPUP_CENTER = 'dropup-center';\nconst CLASS_NAME_DROPDOWN_CENTER = 'dropdown-center';\nconst SELECTOR_DATA_TOGGLE$3 = '[data-bs-toggle=\"dropdown\"]:not(.disabled):not(:disabled)';\nconst SELECTOR_DATA_TOGGLE_SHOWN = `${SELECTOR_DATA_TOGGLE$3}.${CLASS_NAME_SHOW$6}`;\nconst SELECTOR_MENU = '.dropdown-menu';\nconst SELECTOR_NAVBAR = '.navbar';\nconst SELECTOR_NAVBAR_NAV = '.navbar-nav';\nconst SELECTOR_VISIBLE_ITEMS = '.dropdown-menu .dropdown-item:not(.disabled):not(:disabled)';\nconst PLACEMENT_TOP = isRTL() ? 'top-end' : 'top-start';\nconst PLACEMENT_TOPEND = isRTL() ? 'top-start' : 'top-end';\nconst PLACEMENT_BOTTOM = isRTL() ? 'bottom-end' : 'bottom-start';\nconst PLACEMENT_BOTTOMEND = isRTL() ? 'bottom-start' : 'bottom-end';\nconst PLACEMENT_RIGHT = isRTL() ? 'left-start' : 'right-start';\nconst PLACEMENT_LEFT = isRTL() ? 'right-start' : 'left-start';\nconst PLACEMENT_TOPCENTER = 'top';\nconst PLACEMENT_BOTTOMCENTER = 'bottom';\nconst Default$9 = {\n autoClose: true,\n boundary: 'clippingParents',\n display: 'dynamic',\n offset: [0, 2],\n popperConfig: null,\n reference: 'toggle'\n};\nconst DefaultType$9 = {\n autoClose: '(boolean|string)',\n boundary: '(string|element)',\n display: 'string',\n offset: '(array|string|function)',\n popperConfig: '(null|object|function)',\n reference: '(string|element|object)'\n};\n\n/**\n * Class definition\n */\n\nclass Dropdown extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._popper = null;\n this._parent = this._element.parentNode; // dropdown wrapper\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n this._menu = SelectorEngine.next(this._element, SELECTOR_MENU)[0] || SelectorEngine.prev(this._element, SELECTOR_MENU)[0] || SelectorEngine.findOne(SELECTOR_MENU, this._parent);\n this._inNavbar = this._detectNavbar();\n }\n\n // Getters\n static get Default() {\n return Default$9;\n }\n static get DefaultType() {\n return DefaultType$9;\n }\n static get NAME() {\n return NAME$a;\n }\n\n // Public\n toggle() {\n return this._isShown() ? this.hide() : this.show();\n }\n show() {\n if (isDisabled(this._element) || this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$5, relatedTarget);\n if (showEvent.defaultPrevented) {\n return;\n }\n this._createPopper();\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement && !this._parent.closest(SELECTOR_NAVBAR_NAV)) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n this._element.focus();\n this._element.setAttribute('aria-expanded', true);\n this._menu.classList.add(CLASS_NAME_SHOW$6);\n this._element.classList.add(CLASS_NAME_SHOW$6);\n EventHandler.trigger(this._element, EVENT_SHOWN$5, relatedTarget);\n }\n hide() {\n if (isDisabled(this._element) || !this._isShown()) {\n return;\n }\n const relatedTarget = {\n relatedTarget: this._element\n };\n this._completeHide(relatedTarget);\n }\n dispose() {\n if (this._popper) {\n this._popper.destroy();\n }\n super.dispose();\n }\n update() {\n this._inNavbar = this._detectNavbar();\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Private\n _completeHide(relatedTarget) {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$5, relatedTarget);\n if (hideEvent.defaultPrevented) {\n return;\n }\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n if (this._popper) {\n this._popper.destroy();\n }\n this._menu.classList.remove(CLASS_NAME_SHOW$6);\n this._element.classList.remove(CLASS_NAME_SHOW$6);\n this._element.setAttribute('aria-expanded', 'false');\n Manipulator.removeDataAttribute(this._menu, 'popper');\n EventHandler.trigger(this._element, EVENT_HIDDEN$5, relatedTarget);\n }\n _getConfig(config) {\n config = super._getConfig(config);\n if (typeof config.reference === 'object' && !isElement(config.reference) && typeof config.reference.getBoundingClientRect !== 'function') {\n // Popper virtual elements require a getBoundingClientRect method\n throw new TypeError(`${NAME$a.toUpperCase()}: Option \"reference\" provided type \"object\" without a required \"getBoundingClientRect\" method.`);\n }\n return config;\n }\n _createPopper() {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s dropdowns require Popper (https://popper.js.org)');\n }\n let referenceElement = this._element;\n if (this._config.reference === 'parent') {\n referenceElement = this._parent;\n } else if (isElement(this._config.reference)) {\n referenceElement = getElement(this._config.reference);\n } else if (typeof this._config.reference === 'object') {\n referenceElement = this._config.reference;\n }\n const popperConfig = this._getPopperConfig();\n this._popper = Popper.createPopper(referenceElement, this._menu, popperConfig);\n }\n _isShown() {\n return this._menu.classList.contains(CLASS_NAME_SHOW$6);\n }\n _getPlacement() {\n const parentDropdown = this._parent;\n if (parentDropdown.classList.contains(CLASS_NAME_DROPEND)) {\n return PLACEMENT_RIGHT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPSTART)) {\n return PLACEMENT_LEFT;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP_CENTER)) {\n return PLACEMENT_TOPCENTER;\n }\n if (parentDropdown.classList.contains(CLASS_NAME_DROPDOWN_CENTER)) {\n return PLACEMENT_BOTTOMCENTER;\n }\n\n // We need to trim the value because custom properties can also include spaces\n const isEnd = getComputedStyle(this._menu).getPropertyValue('--bs-position').trim() === 'end';\n if (parentDropdown.classList.contains(CLASS_NAME_DROPUP)) {\n return isEnd ? PLACEMENT_TOPEND : PLACEMENT_TOP;\n }\n return isEnd ? PLACEMENT_BOTTOMEND : PLACEMENT_BOTTOM;\n }\n _detectNavbar() {\n return this._element.closest(SELECTOR_NAVBAR) !== null;\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _getPopperConfig() {\n const defaultBsPopperConfig = {\n placement: this._getPlacement(),\n modifiers: [{\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }]\n };\n\n // Disable Popper if we have a static display or Dropdown is in Navbar\n if (this._inNavbar || this._config.display === 'static') {\n Manipulator.setDataAttribute(this._menu, 'popper', 'static'); // TODO: v6 remove\n defaultBsPopperConfig.modifiers = [{\n name: 'applyStyles',\n enabled: false\n }];\n }\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _selectMenuItem({\n key,\n target\n }) {\n const items = SelectorEngine.find(SELECTOR_VISIBLE_ITEMS, this._menu).filter(element => isVisible(element));\n if (!items.length) {\n return;\n }\n\n // if target isn't included in items (e.g. when expanding the dropdown)\n // allow cycling to get the last item in case key equals ARROW_UP_KEY\n getNextActiveElement(items, target, key === ARROW_DOWN_KEY$1, !items.includes(target)).focus();\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Dropdown.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n static clearMenus(event) {\n if (event.button === RIGHT_MOUSE_BUTTON || event.type === 'keyup' && event.key !== TAB_KEY$1) {\n return;\n }\n const openToggles = SelectorEngine.find(SELECTOR_DATA_TOGGLE_SHOWN);\n for (const toggle of openToggles) {\n const context = Dropdown.getInstance(toggle);\n if (!context || context._config.autoClose === false) {\n continue;\n }\n const composedPath = event.composedPath();\n const isMenuTarget = composedPath.includes(context._menu);\n if (composedPath.includes(context._element) || context._config.autoClose === 'inside' && !isMenuTarget || context._config.autoClose === 'outside' && isMenuTarget) {\n continue;\n }\n\n // Tab navigation through the dropdown menu or events from contained inputs shouldn't close the menu\n if (context._menu.contains(event.target) && (event.type === 'keyup' && event.key === TAB_KEY$1 || /input|select|option|textarea|form/i.test(event.target.tagName))) {\n continue;\n }\n const relatedTarget = {\n relatedTarget: context._element\n };\n if (event.type === 'click') {\n relatedTarget.clickEvent = event;\n }\n context._completeHide(relatedTarget);\n }\n }\n static dataApiKeydownHandler(event) {\n // If not an UP | DOWN | ESCAPE key => not a dropdown command\n // If input/textarea && if key is other than ESCAPE => not a dropdown command\n\n const isInput = /input|textarea/i.test(event.target.tagName);\n const isEscapeEvent = event.key === ESCAPE_KEY$2;\n const isUpOrDownEvent = [ARROW_UP_KEY$1, ARROW_DOWN_KEY$1].includes(event.key);\n if (!isUpOrDownEvent && !isEscapeEvent) {\n return;\n }\n if (isInput && !isEscapeEvent) {\n return;\n }\n event.preventDefault();\n\n // TODO: v6 revert #37011 & change markup https://getbootstrap.com/docs/5.3/forms/input-group/\n const getToggleButton = this.matches(SELECTOR_DATA_TOGGLE$3) ? this : SelectorEngine.prev(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.next(this, SELECTOR_DATA_TOGGLE$3)[0] || SelectorEngine.findOne(SELECTOR_DATA_TOGGLE$3, event.delegateTarget.parentNode);\n const instance = Dropdown.getOrCreateInstance(getToggleButton);\n if (isUpOrDownEvent) {\n event.stopPropagation();\n instance.show();\n instance._selectMenuItem(event);\n return;\n }\n if (instance._isShown()) {\n // else is escape and we check if it is shown\n event.stopPropagation();\n instance.hide();\n getToggleButton.focus();\n }\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_DATA_TOGGLE$3, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_KEYDOWN_DATA_API, SELECTOR_MENU, Dropdown.dataApiKeydownHandler);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_KEYUP_DATA_API, Dropdown.clearMenus);\nEventHandler.on(document, EVENT_CLICK_DATA_API$3, SELECTOR_DATA_TOGGLE$3, function (event) {\n event.preventDefault();\n Dropdown.getOrCreateInstance(this).toggle();\n});\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Dropdown);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/backdrop.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$9 = 'backdrop';\nconst CLASS_NAME_FADE$4 = 'fade';\nconst CLASS_NAME_SHOW$5 = 'show';\nconst EVENT_MOUSEDOWN = `mousedown.bs.${NAME$9}`;\nconst Default$8 = {\n className: 'modal-backdrop',\n clickCallback: null,\n isAnimated: false,\n isVisible: true,\n // if false, we use the backdrop helper without adding any element to the dom\n rootElement: 'body' // give the choice to place backdrop under different elements\n};\nconst DefaultType$8 = {\n className: 'string',\n clickCallback: '(function|null)',\n isAnimated: 'boolean',\n isVisible: 'boolean',\n rootElement: '(element|string)'\n};\n\n/**\n * Class definition\n */\n\nclass Backdrop extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isAppended = false;\n this._element = null;\n }\n\n // Getters\n static get Default() {\n return Default$8;\n }\n static get DefaultType() {\n return DefaultType$8;\n }\n static get NAME() {\n return NAME$9;\n }\n\n // Public\n show(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._append();\n const element = this._getElement();\n if (this._config.isAnimated) {\n reflow(element);\n }\n element.classList.add(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n execute(callback);\n });\n }\n hide(callback) {\n if (!this._config.isVisible) {\n execute(callback);\n return;\n }\n this._getElement().classList.remove(CLASS_NAME_SHOW$5);\n this._emulateAnimation(() => {\n this.dispose();\n execute(callback);\n });\n }\n dispose() {\n if (!this._isAppended) {\n return;\n }\n EventHandler.off(this._element, EVENT_MOUSEDOWN);\n this._element.remove();\n this._isAppended = false;\n }\n\n // Private\n _getElement() {\n if (!this._element) {\n const backdrop = document.createElement('div');\n backdrop.className = this._config.className;\n if (this._config.isAnimated) {\n backdrop.classList.add(CLASS_NAME_FADE$4);\n }\n this._element = backdrop;\n }\n return this._element;\n }\n _configAfterMerge(config) {\n // use getElement() with the default \"body\" to get a fresh Element on each instantiation\n config.rootElement = getElement(config.rootElement);\n return config;\n }\n _append() {\n if (this._isAppended) {\n return;\n }\n const element = this._getElement();\n this._config.rootElement.append(element);\n EventHandler.on(element, EVENT_MOUSEDOWN, () => {\n execute(this._config.clickCallback);\n });\n this._isAppended = true;\n }\n _emulateAnimation(callback) {\n executeAfterTransition(callback, this._getElement(), this._config.isAnimated);\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/focustrap.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$8 = 'focustrap';\nconst DATA_KEY$5 = 'bs.focustrap';\nconst EVENT_KEY$5 = `.${DATA_KEY$5}`;\nconst EVENT_FOCUSIN$2 = `focusin${EVENT_KEY$5}`;\nconst EVENT_KEYDOWN_TAB = `keydown.tab${EVENT_KEY$5}`;\nconst TAB_KEY = 'Tab';\nconst TAB_NAV_FORWARD = 'forward';\nconst TAB_NAV_BACKWARD = 'backward';\nconst Default$7 = {\n autofocus: true,\n trapElement: null // The element to trap focus inside of\n};\nconst DefaultType$7 = {\n autofocus: 'boolean',\n trapElement: 'element'\n};\n\n/**\n * Class definition\n */\n\nclass FocusTrap extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n this._isActive = false;\n this._lastTabNavDirection = null;\n }\n\n // Getters\n static get Default() {\n return Default$7;\n }\n static get DefaultType() {\n return DefaultType$7;\n }\n static get NAME() {\n return NAME$8;\n }\n\n // Public\n activate() {\n if (this._isActive) {\n return;\n }\n if (this._config.autofocus) {\n this._config.trapElement.focus();\n }\n EventHandler.off(document, EVENT_KEY$5); // guard against infinite focus loop\n EventHandler.on(document, EVENT_FOCUSIN$2, event => this._handleFocusin(event));\n EventHandler.on(document, EVENT_KEYDOWN_TAB, event => this._handleKeydown(event));\n this._isActive = true;\n }\n deactivate() {\n if (!this._isActive) {\n return;\n }\n this._isActive = false;\n EventHandler.off(document, EVENT_KEY$5);\n }\n\n // Private\n _handleFocusin(event) {\n const {\n trapElement\n } = this._config;\n if (event.target === document || event.target === trapElement || trapElement.contains(event.target)) {\n return;\n }\n const elements = SelectorEngine.focusableChildren(trapElement);\n if (elements.length === 0) {\n trapElement.focus();\n } else if (this._lastTabNavDirection === TAB_NAV_BACKWARD) {\n elements[elements.length - 1].focus();\n } else {\n elements[0].focus();\n }\n }\n _handleKeydown(event) {\n if (event.key !== TAB_KEY) {\n return;\n }\n this._lastTabNavDirection = event.shiftKey ? TAB_NAV_BACKWARD : TAB_NAV_FORWARD;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/scrollBar.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst SELECTOR_FIXED_CONTENT = '.fixed-top, .fixed-bottom, .is-fixed, .sticky-top';\nconst SELECTOR_STICKY_CONTENT = '.sticky-top';\nconst PROPERTY_PADDING = 'padding-right';\nconst PROPERTY_MARGIN = 'margin-right';\n\n/**\n * Class definition\n */\n\nclass ScrollBarHelper {\n constructor() {\n this._element = document.body;\n }\n\n // Public\n getWidth() {\n // https://developer.mozilla.org/en-US/docs/Web/API/Window/innerWidth#usage_notes\n const documentWidth = document.documentElement.clientWidth;\n return Math.abs(window.innerWidth - documentWidth);\n }\n hide() {\n const width = this.getWidth();\n this._disableOverFlow();\n // give padding to element to balance the hidden scrollbar width\n this._setElementAttributes(this._element, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n // trick: We adjust positive paddingRight and negative marginRight to sticky-top elements to keep showing fullwidth\n this._setElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING, calculatedValue => calculatedValue + width);\n this._setElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN, calculatedValue => calculatedValue - width);\n }\n reset() {\n this._resetElementAttributes(this._element, 'overflow');\n this._resetElementAttributes(this._element, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_FIXED_CONTENT, PROPERTY_PADDING);\n this._resetElementAttributes(SELECTOR_STICKY_CONTENT, PROPERTY_MARGIN);\n }\n isOverflowing() {\n return this.getWidth() > 0;\n }\n\n // Private\n _disableOverFlow() {\n this._saveInitialAttribute(this._element, 'overflow');\n this._element.style.overflow = 'hidden';\n }\n _setElementAttributes(selector, styleProperty, callback) {\n const scrollbarWidth = this.getWidth();\n const manipulationCallBack = element => {\n if (element !== this._element && window.innerWidth > element.clientWidth + scrollbarWidth) {\n return;\n }\n this._saveInitialAttribute(element, styleProperty);\n const calculatedValue = window.getComputedStyle(element).getPropertyValue(styleProperty);\n element.style.setProperty(styleProperty, `${callback(Number.parseFloat(calculatedValue))}px`);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _saveInitialAttribute(element, styleProperty) {\n const actualValue = element.style.getPropertyValue(styleProperty);\n if (actualValue) {\n Manipulator.setDataAttribute(element, styleProperty, actualValue);\n }\n }\n _resetElementAttributes(selector, styleProperty) {\n const manipulationCallBack = element => {\n const value = Manipulator.getDataAttribute(element, styleProperty);\n // We only want to remove the property if the value is `null`; the value can also be zero\n if (value === null) {\n element.style.removeProperty(styleProperty);\n return;\n }\n Manipulator.removeDataAttribute(element, styleProperty);\n element.style.setProperty(styleProperty, value);\n };\n this._applyManipulationCallback(selector, manipulationCallBack);\n }\n _applyManipulationCallback(selector, callBack) {\n if (isElement(selector)) {\n callBack(selector);\n return;\n }\n for (const sel of SelectorEngine.find(selector, this._element)) {\n callBack(sel);\n }\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap modal.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$7 = 'modal';\nconst DATA_KEY$4 = 'bs.modal';\nconst EVENT_KEY$4 = `.${DATA_KEY$4}`;\nconst DATA_API_KEY$2 = '.data-api';\nconst ESCAPE_KEY$1 = 'Escape';\nconst EVENT_HIDE$4 = `hide${EVENT_KEY$4}`;\nconst EVENT_HIDE_PREVENTED$1 = `hidePrevented${EVENT_KEY$4}`;\nconst EVENT_HIDDEN$4 = `hidden${EVENT_KEY$4}`;\nconst EVENT_SHOW$4 = `show${EVENT_KEY$4}`;\nconst EVENT_SHOWN$4 = `shown${EVENT_KEY$4}`;\nconst EVENT_RESIZE$1 = `resize${EVENT_KEY$4}`;\nconst EVENT_CLICK_DISMISS = `click.dismiss${EVENT_KEY$4}`;\nconst EVENT_MOUSEDOWN_DISMISS = `mousedown.dismiss${EVENT_KEY$4}`;\nconst EVENT_KEYDOWN_DISMISS$1 = `keydown.dismiss${EVENT_KEY$4}`;\nconst EVENT_CLICK_DATA_API$2 = `click${EVENT_KEY$4}${DATA_API_KEY$2}`;\nconst CLASS_NAME_OPEN = 'modal-open';\nconst CLASS_NAME_FADE$3 = 'fade';\nconst CLASS_NAME_SHOW$4 = 'show';\nconst CLASS_NAME_STATIC = 'modal-static';\nconst OPEN_SELECTOR$1 = '.modal.show';\nconst SELECTOR_DIALOG = '.modal-dialog';\nconst SELECTOR_MODAL_BODY = '.modal-body';\nconst SELECTOR_DATA_TOGGLE$2 = '[data-bs-toggle=\"modal\"]';\nconst Default$6 = {\n backdrop: true,\n focus: true,\n keyboard: true\n};\nconst DefaultType$6 = {\n backdrop: '(boolean|string)',\n focus: 'boolean',\n keyboard: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Modal extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._dialog = SelectorEngine.findOne(SELECTOR_DIALOG, this._element);\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._isShown = false;\n this._isTransitioning = false;\n this._scrollBar = new ScrollBarHelper();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$6;\n }\n static get DefaultType() {\n return DefaultType$6;\n }\n static get NAME() {\n return NAME$7;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown || this._isTransitioning) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$4, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._isTransitioning = true;\n this._scrollBar.hide();\n document.body.classList.add(CLASS_NAME_OPEN);\n this._adjustDialog();\n this._backdrop.show(() => this._showElement(relatedTarget));\n }\n hide() {\n if (!this._isShown || this._isTransitioning) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$4);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._isShown = false;\n this._isTransitioning = true;\n this._focustrap.deactivate();\n this._element.classList.remove(CLASS_NAME_SHOW$4);\n this._queueCallback(() => this._hideModal(), this._element, this._isAnimated());\n }\n dispose() {\n EventHandler.off(window, EVENT_KEY$4);\n EventHandler.off(this._dialog, EVENT_KEY$4);\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n handleUpdate() {\n this._adjustDialog();\n }\n\n // Private\n _initializeBackDrop() {\n return new Backdrop({\n isVisible: Boolean(this._config.backdrop),\n // 'static' option will be translated to true, and booleans will keep their value,\n isAnimated: this._isAnimated()\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _showElement(relatedTarget) {\n // try to append dynamic modal\n if (!document.body.contains(this._element)) {\n document.body.append(this._element);\n }\n this._element.style.display = 'block';\n this._element.removeAttribute('aria-hidden');\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.scrollTop = 0;\n const modalBody = SelectorEngine.findOne(SELECTOR_MODAL_BODY, this._dialog);\n if (modalBody) {\n modalBody.scrollTop = 0;\n }\n reflow(this._element);\n this._element.classList.add(CLASS_NAME_SHOW$4);\n const transitionComplete = () => {\n if (this._config.focus) {\n this._focustrap.activate();\n }\n this._isTransitioning = false;\n EventHandler.trigger(this._element, EVENT_SHOWN$4, {\n relatedTarget\n });\n };\n this._queueCallback(transitionComplete, this._dialog, this._isAnimated());\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS$1, event => {\n if (event.key !== ESCAPE_KEY$1) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n this._triggerBackdropTransition();\n });\n EventHandler.on(window, EVENT_RESIZE$1, () => {\n if (this._isShown && !this._isTransitioning) {\n this._adjustDialog();\n }\n });\n EventHandler.on(this._element, EVENT_MOUSEDOWN_DISMISS, event => {\n // a bad trick to segregate clicks that may start inside dialog but end outside, and avoid listen to scrollbar clicks\n EventHandler.one(this._element, EVENT_CLICK_DISMISS, event2 => {\n if (this._element !== event.target || this._element !== event2.target) {\n return;\n }\n if (this._config.backdrop === 'static') {\n this._triggerBackdropTransition();\n return;\n }\n if (this._config.backdrop) {\n this.hide();\n }\n });\n });\n }\n _hideModal() {\n this._element.style.display = 'none';\n this._element.setAttribute('aria-hidden', true);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n this._isTransitioning = false;\n this._backdrop.hide(() => {\n document.body.classList.remove(CLASS_NAME_OPEN);\n this._resetAdjustments();\n this._scrollBar.reset();\n EventHandler.trigger(this._element, EVENT_HIDDEN$4);\n });\n }\n _isAnimated() {\n return this._element.classList.contains(CLASS_NAME_FADE$3);\n }\n _triggerBackdropTransition() {\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED$1);\n if (hideEvent.defaultPrevented) {\n return;\n }\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const initialOverflowY = this._element.style.overflowY;\n // return if the following background transition hasn't yet completed\n if (initialOverflowY === 'hidden' || this._element.classList.contains(CLASS_NAME_STATIC)) {\n return;\n }\n if (!isModalOverflowing) {\n this._element.style.overflowY = 'hidden';\n }\n this._element.classList.add(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.classList.remove(CLASS_NAME_STATIC);\n this._queueCallback(() => {\n this._element.style.overflowY = initialOverflowY;\n }, this._dialog);\n }, this._dialog);\n this._element.focus();\n }\n\n /**\n * The following methods are used to handle overflowing modals\n */\n\n _adjustDialog() {\n const isModalOverflowing = this._element.scrollHeight > document.documentElement.clientHeight;\n const scrollbarWidth = this._scrollBar.getWidth();\n const isBodyOverflowing = scrollbarWidth > 0;\n if (isBodyOverflowing && !isModalOverflowing) {\n const property = isRTL() ? 'paddingLeft' : 'paddingRight';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n if (!isBodyOverflowing && isModalOverflowing) {\n const property = isRTL() ? 'paddingRight' : 'paddingLeft';\n this._element.style[property] = `${scrollbarWidth}px`;\n }\n }\n _resetAdjustments() {\n this._element.style.paddingLeft = '';\n this._element.style.paddingRight = '';\n }\n\n // Static\n static jQueryInterface(config, relatedTarget) {\n return this.each(function () {\n const data = Modal.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](relatedTarget);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$2, SELECTOR_DATA_TOGGLE$2, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n EventHandler.one(target, EVENT_SHOW$4, showEvent => {\n if (showEvent.defaultPrevented) {\n // only register focus restorer if modal will actually get shown\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$4, () => {\n if (isVisible(this)) {\n this.focus();\n }\n });\n });\n\n // avoid conflict when clicking modal toggler while another one is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR$1);\n if (alreadyOpen) {\n Modal.getInstance(alreadyOpen).hide();\n }\n const data = Modal.getOrCreateInstance(target);\n data.toggle(this);\n});\nenableDismissTrigger(Modal);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Modal);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap offcanvas.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$6 = 'offcanvas';\nconst DATA_KEY$3 = 'bs.offcanvas';\nconst EVENT_KEY$3 = `.${DATA_KEY$3}`;\nconst DATA_API_KEY$1 = '.data-api';\nconst EVENT_LOAD_DATA_API$2 = `load${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst ESCAPE_KEY = 'Escape';\nconst CLASS_NAME_SHOW$3 = 'show';\nconst CLASS_NAME_SHOWING$1 = 'showing';\nconst CLASS_NAME_HIDING = 'hiding';\nconst CLASS_NAME_BACKDROP = 'offcanvas-backdrop';\nconst OPEN_SELECTOR = '.offcanvas.show';\nconst EVENT_SHOW$3 = `show${EVENT_KEY$3}`;\nconst EVENT_SHOWN$3 = `shown${EVENT_KEY$3}`;\nconst EVENT_HIDE$3 = `hide${EVENT_KEY$3}`;\nconst EVENT_HIDE_PREVENTED = `hidePrevented${EVENT_KEY$3}`;\nconst EVENT_HIDDEN$3 = `hidden${EVENT_KEY$3}`;\nconst EVENT_RESIZE = `resize${EVENT_KEY$3}`;\nconst EVENT_CLICK_DATA_API$1 = `click${EVENT_KEY$3}${DATA_API_KEY$1}`;\nconst EVENT_KEYDOWN_DISMISS = `keydown.dismiss${EVENT_KEY$3}`;\nconst SELECTOR_DATA_TOGGLE$1 = '[data-bs-toggle=\"offcanvas\"]';\nconst Default$5 = {\n backdrop: true,\n keyboard: true,\n scroll: false\n};\nconst DefaultType$5 = {\n backdrop: '(boolean|string)',\n keyboard: 'boolean',\n scroll: 'boolean'\n};\n\n/**\n * Class definition\n */\n\nclass Offcanvas extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n this._isShown = false;\n this._backdrop = this._initializeBackDrop();\n this._focustrap = this._initializeFocusTrap();\n this._addEventListeners();\n }\n\n // Getters\n static get Default() {\n return Default$5;\n }\n static get DefaultType() {\n return DefaultType$5;\n }\n static get NAME() {\n return NAME$6;\n }\n\n // Public\n toggle(relatedTarget) {\n return this._isShown ? this.hide() : this.show(relatedTarget);\n }\n show(relatedTarget) {\n if (this._isShown) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, EVENT_SHOW$3, {\n relatedTarget\n });\n if (showEvent.defaultPrevented) {\n return;\n }\n this._isShown = true;\n this._backdrop.show();\n if (!this._config.scroll) {\n new ScrollBarHelper().hide();\n }\n this._element.setAttribute('aria-modal', true);\n this._element.setAttribute('role', 'dialog');\n this._element.classList.add(CLASS_NAME_SHOWING$1);\n const completeCallBack = () => {\n if (!this._config.scroll || this._config.backdrop) {\n this._focustrap.activate();\n }\n this._element.classList.add(CLASS_NAME_SHOW$3);\n this._element.classList.remove(CLASS_NAME_SHOWING$1);\n EventHandler.trigger(this._element, EVENT_SHOWN$3, {\n relatedTarget\n });\n };\n this._queueCallback(completeCallBack, this._element, true);\n }\n hide() {\n if (!this._isShown) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, EVENT_HIDE$3);\n if (hideEvent.defaultPrevented) {\n return;\n }\n this._focustrap.deactivate();\n this._element.blur();\n this._isShown = false;\n this._element.classList.add(CLASS_NAME_HIDING);\n this._backdrop.hide();\n const completeCallback = () => {\n this._element.classList.remove(CLASS_NAME_SHOW$3, CLASS_NAME_HIDING);\n this._element.removeAttribute('aria-modal');\n this._element.removeAttribute('role');\n if (!this._config.scroll) {\n new ScrollBarHelper().reset();\n }\n EventHandler.trigger(this._element, EVENT_HIDDEN$3);\n };\n this._queueCallback(completeCallback, this._element, true);\n }\n dispose() {\n this._backdrop.dispose();\n this._focustrap.deactivate();\n super.dispose();\n }\n\n // Private\n _initializeBackDrop() {\n const clickCallback = () => {\n if (this._config.backdrop === 'static') {\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n return;\n }\n this.hide();\n };\n\n // 'static' option will be translated to true, and booleans will keep their value\n const isVisible = Boolean(this._config.backdrop);\n return new Backdrop({\n className: CLASS_NAME_BACKDROP,\n isVisible,\n isAnimated: true,\n rootElement: this._element.parentNode,\n clickCallback: isVisible ? clickCallback : null\n });\n }\n _initializeFocusTrap() {\n return new FocusTrap({\n trapElement: this._element\n });\n }\n _addEventListeners() {\n EventHandler.on(this._element, EVENT_KEYDOWN_DISMISS, event => {\n if (event.key !== ESCAPE_KEY) {\n return;\n }\n if (this._config.keyboard) {\n this.hide();\n return;\n }\n EventHandler.trigger(this._element, EVENT_HIDE_PREVENTED);\n });\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Offcanvas.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (data[config] === undefined || config.startsWith('_') || config === 'constructor') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config](this);\n });\n }\n}\n\n/**\n * Data API implementation\n */\n\nEventHandler.on(document, EVENT_CLICK_DATA_API$1, SELECTOR_DATA_TOGGLE$1, function (event) {\n const target = SelectorEngine.getElementFromSelector(this);\n if (['A', 'AREA'].includes(this.tagName)) {\n event.preventDefault();\n }\n if (isDisabled(this)) {\n return;\n }\n EventHandler.one(target, EVENT_HIDDEN$3, () => {\n // focus on trigger when it is closed\n if (isVisible(this)) {\n this.focus();\n }\n });\n\n // avoid conflict when clicking a toggler of an offcanvas, while another is open\n const alreadyOpen = SelectorEngine.findOne(OPEN_SELECTOR);\n if (alreadyOpen && alreadyOpen !== target) {\n Offcanvas.getInstance(alreadyOpen).hide();\n }\n const data = Offcanvas.getOrCreateInstance(target);\n data.toggle(this);\n});\nEventHandler.on(window, EVENT_LOAD_DATA_API$2, () => {\n for (const selector of SelectorEngine.find(OPEN_SELECTOR)) {\n Offcanvas.getOrCreateInstance(selector).show();\n }\n});\nEventHandler.on(window, EVENT_RESIZE, () => {\n for (const element of SelectorEngine.find('[aria-modal][class*=show][class*=offcanvas-]')) {\n if (getComputedStyle(element).position !== 'fixed') {\n Offcanvas.getOrCreateInstance(element).hide();\n }\n }\n});\nenableDismissTrigger(Offcanvas);\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Offcanvas);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/sanitizer.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n// js-docs-start allow-list\nconst ARIA_ATTRIBUTE_PATTERN = /^aria-[\\w-]*$/i;\nconst DefaultAllowlist = {\n // Global attributes allowed on any supplied element below.\n '*': ['class', 'dir', 'id', 'lang', 'role', ARIA_ATTRIBUTE_PATTERN],\n a: ['target', 'href', 'title', 'rel'],\n area: [],\n b: [],\n br: [],\n col: [],\n code: [],\n dd: [],\n div: [],\n dl: [],\n dt: [],\n em: [],\n hr: [],\n h1: [],\n h2: [],\n h3: [],\n h4: [],\n h5: [],\n h6: [],\n i: [],\n img: ['src', 'srcset', 'alt', 'title', 'width', 'height'],\n li: [],\n ol: [],\n p: [],\n pre: [],\n s: [],\n small: [],\n span: [],\n sub: [],\n sup: [],\n strong: [],\n u: [],\n ul: []\n};\n// js-docs-end allow-list\n\nconst uriAttributes = new Set(['background', 'cite', 'href', 'itemtype', 'longdesc', 'poster', 'src', 'xlink:href']);\n\n/**\n * A pattern that recognizes URLs that are safe wrt. XSS in URL navigation\n * contexts.\n *\n * Shout-out to Angular https://github.com/angular/angular/blob/15.2.8/packages/core/src/sanitization/url_sanitizer.ts#L38\n */\n// eslint-disable-next-line unicorn/better-regex\nconst SAFE_URL_PATTERN = /^(?!javascript:)(?:[a-z0-9+.-]+:|[^&:/?#]*(?:[/?#]|$))/i;\nconst allowedAttribute = (attribute, allowedAttributeList) => {\n const attributeName = attribute.nodeName.toLowerCase();\n if (allowedAttributeList.includes(attributeName)) {\n if (uriAttributes.has(attributeName)) {\n return Boolean(SAFE_URL_PATTERN.test(attribute.nodeValue));\n }\n return true;\n }\n\n // Check if a regular expression validates the attribute.\n return allowedAttributeList.filter(attributeRegex => attributeRegex instanceof RegExp).some(regex => regex.test(attributeName));\n};\nfunction sanitizeHtml(unsafeHtml, allowList, sanitizeFunction) {\n if (!unsafeHtml.length) {\n return unsafeHtml;\n }\n if (sanitizeFunction && typeof sanitizeFunction === 'function') {\n return sanitizeFunction(unsafeHtml);\n }\n const domParser = new window.DOMParser();\n const createdDocument = domParser.parseFromString(unsafeHtml, 'text/html');\n const elements = [].concat(...createdDocument.body.querySelectorAll('*'));\n for (const element of elements) {\n const elementName = element.nodeName.toLowerCase();\n if (!Object.keys(allowList).includes(elementName)) {\n element.remove();\n continue;\n }\n const attributeList = [].concat(...element.attributes);\n const allowedAttributes = [].concat(allowList['*'] || [], allowList[elementName] || []);\n for (const attribute of attributeList) {\n if (!allowedAttribute(attribute, allowedAttributes)) {\n element.removeAttribute(attribute.nodeName);\n }\n }\n }\n return createdDocument.body.innerHTML;\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap util/template-factory.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$5 = 'TemplateFactory';\nconst Default$4 = {\n allowList: DefaultAllowlist,\n content: {},\n // { selector : text , selector2 : text2 , }\n extraClass: '',\n html: false,\n sanitize: true,\n sanitizeFn: null,\n template: '
'\n};\nconst DefaultType$4 = {\n allowList: 'object',\n content: 'object',\n extraClass: '(string|function)',\n html: 'boolean',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n template: 'string'\n};\nconst DefaultContentType = {\n entry: '(string|element|function|null)',\n selector: '(string|element)'\n};\n\n/**\n * Class definition\n */\n\nclass TemplateFactory extends Config {\n constructor(config) {\n super();\n this._config = this._getConfig(config);\n }\n\n // Getters\n static get Default() {\n return Default$4;\n }\n static get DefaultType() {\n return DefaultType$4;\n }\n static get NAME() {\n return NAME$5;\n }\n\n // Public\n getContent() {\n return Object.values(this._config.content).map(config => this._resolvePossibleFunction(config)).filter(Boolean);\n }\n hasContent() {\n return this.getContent().length > 0;\n }\n changeContent(content) {\n this._checkContent(content);\n this._config.content = {\n ...this._config.content,\n ...content\n };\n return this;\n }\n toHtml() {\n const templateWrapper = document.createElement('div');\n templateWrapper.innerHTML = this._maybeSanitize(this._config.template);\n for (const [selector, text] of Object.entries(this._config.content)) {\n this._setContent(templateWrapper, text, selector);\n }\n const template = templateWrapper.children[0];\n const extraClass = this._resolvePossibleFunction(this._config.extraClass);\n if (extraClass) {\n template.classList.add(...extraClass.split(' '));\n }\n return template;\n }\n\n // Private\n _typeCheckConfig(config) {\n super._typeCheckConfig(config);\n this._checkContent(config.content);\n }\n _checkContent(arg) {\n for (const [selector, content] of Object.entries(arg)) {\n super._typeCheckConfig({\n selector,\n entry: content\n }, DefaultContentType);\n }\n }\n _setContent(template, content, selector) {\n const templateElement = SelectorEngine.findOne(selector, template);\n if (!templateElement) {\n return;\n }\n content = this._resolvePossibleFunction(content);\n if (!content) {\n templateElement.remove();\n return;\n }\n if (isElement(content)) {\n this._putElementInTemplate(getElement(content), templateElement);\n return;\n }\n if (this._config.html) {\n templateElement.innerHTML = this._maybeSanitize(content);\n return;\n }\n templateElement.textContent = content;\n }\n _maybeSanitize(arg) {\n return this._config.sanitize ? sanitizeHtml(arg, this._config.allowList, this._config.sanitizeFn) : arg;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this]);\n }\n _putElementInTemplate(element, templateElement) {\n if (this._config.html) {\n templateElement.innerHTML = '';\n templateElement.append(element);\n return;\n }\n templateElement.textContent = element.textContent;\n }\n}\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap tooltip.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$4 = 'tooltip';\nconst DISALLOWED_ATTRIBUTES = new Set(['sanitize', 'allowList', 'sanitizeFn']);\nconst CLASS_NAME_FADE$2 = 'fade';\nconst CLASS_NAME_MODAL = 'modal';\nconst CLASS_NAME_SHOW$2 = 'show';\nconst SELECTOR_TOOLTIP_INNER = '.tooltip-inner';\nconst SELECTOR_MODAL = `.${CLASS_NAME_MODAL}`;\nconst EVENT_MODAL_HIDE = 'hide.bs.modal';\nconst TRIGGER_HOVER = 'hover';\nconst TRIGGER_FOCUS = 'focus';\nconst TRIGGER_CLICK = 'click';\nconst TRIGGER_MANUAL = 'manual';\nconst EVENT_HIDE$2 = 'hide';\nconst EVENT_HIDDEN$2 = 'hidden';\nconst EVENT_SHOW$2 = 'show';\nconst EVENT_SHOWN$2 = 'shown';\nconst EVENT_INSERTED = 'inserted';\nconst EVENT_CLICK$1 = 'click';\nconst EVENT_FOCUSIN$1 = 'focusin';\nconst EVENT_FOCUSOUT$1 = 'focusout';\nconst EVENT_MOUSEENTER = 'mouseenter';\nconst EVENT_MOUSELEAVE = 'mouseleave';\nconst AttachmentMap = {\n AUTO: 'auto',\n TOP: 'top',\n RIGHT: isRTL() ? 'left' : 'right',\n BOTTOM: 'bottom',\n LEFT: isRTL() ? 'right' : 'left'\n};\nconst Default$3 = {\n allowList: DefaultAllowlist,\n animation: true,\n boundary: 'clippingParents',\n container: false,\n customClass: '',\n delay: 0,\n fallbackPlacements: ['top', 'right', 'bottom', 'left'],\n html: false,\n offset: [0, 6],\n placement: 'top',\n popperConfig: null,\n sanitize: true,\n sanitizeFn: null,\n selector: false,\n template: '
' + '
' + '
' + '
',\n title: '',\n trigger: 'hover focus'\n};\nconst DefaultType$3 = {\n allowList: 'object',\n animation: 'boolean',\n boundary: '(string|element)',\n container: '(string|element|boolean)',\n customClass: '(string|function)',\n delay: '(number|object)',\n fallbackPlacements: 'array',\n html: 'boolean',\n offset: '(array|string|function)',\n placement: '(string|function)',\n popperConfig: '(null|object|function)',\n sanitize: 'boolean',\n sanitizeFn: '(null|function)',\n selector: '(string|boolean)',\n template: 'string',\n title: '(string|element|function)',\n trigger: 'string'\n};\n\n/**\n * Class definition\n */\n\nclass Tooltip extends BaseComponent {\n constructor(element, config) {\n if (typeof Popper === 'undefined') {\n throw new TypeError('Bootstrap\\'s tooltips require Popper (https://popper.js.org)');\n }\n super(element, config);\n\n // Private\n this._isEnabled = true;\n this._timeout = 0;\n this._isHovered = null;\n this._activeTrigger = {};\n this._popper = null;\n this._templateFactory = null;\n this._newContent = null;\n\n // Protected\n this.tip = null;\n this._setListeners();\n if (!this._config.selector) {\n this._fixTitle();\n }\n }\n\n // Getters\n static get Default() {\n return Default$3;\n }\n static get DefaultType() {\n return DefaultType$3;\n }\n static get NAME() {\n return NAME$4;\n }\n\n // Public\n enable() {\n this._isEnabled = true;\n }\n disable() {\n this._isEnabled = false;\n }\n toggleEnabled() {\n this._isEnabled = !this._isEnabled;\n }\n toggle() {\n if (!this._isEnabled) {\n return;\n }\n this._activeTrigger.click = !this._activeTrigger.click;\n if (this._isShown()) {\n this._leave();\n return;\n }\n this._enter();\n }\n dispose() {\n clearTimeout(this._timeout);\n EventHandler.off(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n if (this._element.getAttribute('data-bs-original-title')) {\n this._element.setAttribute('title', this._element.getAttribute('data-bs-original-title'));\n }\n this._disposePopper();\n super.dispose();\n }\n show() {\n if (this._element.style.display === 'none') {\n throw new Error('Please use show on visible elements');\n }\n if (!(this._isWithContent() && this._isEnabled)) {\n return;\n }\n const showEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOW$2));\n const shadowRoot = findShadowRoot(this._element);\n const isInTheDom = (shadowRoot || this._element.ownerDocument.documentElement).contains(this._element);\n if (showEvent.defaultPrevented || !isInTheDom) {\n return;\n }\n\n // TODO: v6 remove this or make it optional\n this._disposePopper();\n const tip = this._getTipElement();\n this._element.setAttribute('aria-describedby', tip.getAttribute('id'));\n const {\n container\n } = this._config;\n if (!this._element.ownerDocument.documentElement.contains(this.tip)) {\n container.append(tip);\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_INSERTED));\n }\n this._popper = this._createPopper(tip);\n tip.classList.add(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we add extra\n // empty mouseover listeners to the body's immediate children;\n // only needed because of broken event delegation on iOS\n // https://www.quirksmode.org/blog/archives/2014/02/mouse_event_bub.html\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.on(element, 'mouseover', noop);\n }\n }\n const complete = () => {\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_SHOWN$2));\n if (this._isHovered === false) {\n this._leave();\n }\n this._isHovered = false;\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n hide() {\n if (!this._isShown()) {\n return;\n }\n const hideEvent = EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDE$2));\n if (hideEvent.defaultPrevented) {\n return;\n }\n const tip = this._getTipElement();\n tip.classList.remove(CLASS_NAME_SHOW$2);\n\n // If this is a touch-enabled device we remove the extra\n // empty mouseover listeners we added for iOS support\n if ('ontouchstart' in document.documentElement) {\n for (const element of [].concat(...document.body.children)) {\n EventHandler.off(element, 'mouseover', noop);\n }\n }\n this._activeTrigger[TRIGGER_CLICK] = false;\n this._activeTrigger[TRIGGER_FOCUS] = false;\n this._activeTrigger[TRIGGER_HOVER] = false;\n this._isHovered = null; // it is a trick to support manual triggering\n\n const complete = () => {\n if (this._isWithActiveTrigger()) {\n return;\n }\n if (!this._isHovered) {\n this._disposePopper();\n }\n this._element.removeAttribute('aria-describedby');\n EventHandler.trigger(this._element, this.constructor.eventName(EVENT_HIDDEN$2));\n };\n this._queueCallback(complete, this.tip, this._isAnimated());\n }\n update() {\n if (this._popper) {\n this._popper.update();\n }\n }\n\n // Protected\n _isWithContent() {\n return Boolean(this._getTitle());\n }\n _getTipElement() {\n if (!this.tip) {\n this.tip = this._createTipElement(this._newContent || this._getContentForTemplate());\n }\n return this.tip;\n }\n _createTipElement(content) {\n const tip = this._getTemplateFactory(content).toHtml();\n\n // TODO: remove this check in v6\n if (!tip) {\n return null;\n }\n tip.classList.remove(CLASS_NAME_FADE$2, CLASS_NAME_SHOW$2);\n // TODO: v6 the following can be achieved with CSS only\n tip.classList.add(`bs-${this.constructor.NAME}-auto`);\n const tipId = getUID(this.constructor.NAME).toString();\n tip.setAttribute('id', tipId);\n if (this._isAnimated()) {\n tip.classList.add(CLASS_NAME_FADE$2);\n }\n return tip;\n }\n setContent(content) {\n this._newContent = content;\n if (this._isShown()) {\n this._disposePopper();\n this.show();\n }\n }\n _getTemplateFactory(content) {\n if (this._templateFactory) {\n this._templateFactory.changeContent(content);\n } else {\n this._templateFactory = new TemplateFactory({\n ...this._config,\n // the `content` var has to be after `this._config`\n // to override config.content in case of popover\n content,\n extraClass: this._resolvePossibleFunction(this._config.customClass)\n });\n }\n return this._templateFactory;\n }\n _getContentForTemplate() {\n return {\n [SELECTOR_TOOLTIP_INNER]: this._getTitle()\n };\n }\n _getTitle() {\n return this._resolvePossibleFunction(this._config.title) || this._element.getAttribute('data-bs-original-title');\n }\n\n // Private\n _initializeOnDelegatedTarget(event) {\n return this.constructor.getOrCreateInstance(event.delegateTarget, this._getDelegateConfig());\n }\n _isAnimated() {\n return this._config.animation || this.tip && this.tip.classList.contains(CLASS_NAME_FADE$2);\n }\n _isShown() {\n return this.tip && this.tip.classList.contains(CLASS_NAME_SHOW$2);\n }\n _createPopper(tip) {\n const placement = execute(this._config.placement, [this, tip, this._element]);\n const attachment = AttachmentMap[placement.toUpperCase()];\n return Popper.createPopper(this._element, tip, this._getPopperConfig(attachment));\n }\n _getOffset() {\n const {\n offset\n } = this._config;\n if (typeof offset === 'string') {\n return offset.split(',').map(value => Number.parseInt(value, 10));\n }\n if (typeof offset === 'function') {\n return popperData => offset(popperData, this._element);\n }\n return offset;\n }\n _resolvePossibleFunction(arg) {\n return execute(arg, [this._element]);\n }\n _getPopperConfig(attachment) {\n const defaultBsPopperConfig = {\n placement: attachment,\n modifiers: [{\n name: 'flip',\n options: {\n fallbackPlacements: this._config.fallbackPlacements\n }\n }, {\n name: 'offset',\n options: {\n offset: this._getOffset()\n }\n }, {\n name: 'preventOverflow',\n options: {\n boundary: this._config.boundary\n }\n }, {\n name: 'arrow',\n options: {\n element: `.${this.constructor.NAME}-arrow`\n }\n }, {\n name: 'preSetPlacement',\n enabled: true,\n phase: 'beforeMain',\n fn: data => {\n // Pre-set Popper's placement attribute in order to read the arrow sizes properly.\n // Otherwise, Popper mixes up the width and height dimensions since the initial arrow style is for top placement\n this._getTipElement().setAttribute('data-popper-placement', data.state.placement);\n }\n }]\n };\n return {\n ...defaultBsPopperConfig,\n ...execute(this._config.popperConfig, [defaultBsPopperConfig])\n };\n }\n _setListeners() {\n const triggers = this._config.trigger.split(' ');\n for (const trigger of triggers) {\n if (trigger === 'click') {\n EventHandler.on(this._element, this.constructor.eventName(EVENT_CLICK$1), this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context.toggle();\n });\n } else if (trigger !== TRIGGER_MANUAL) {\n const eventIn = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSEENTER) : this.constructor.eventName(EVENT_FOCUSIN$1);\n const eventOut = trigger === TRIGGER_HOVER ? this.constructor.eventName(EVENT_MOUSELEAVE) : this.constructor.eventName(EVENT_FOCUSOUT$1);\n EventHandler.on(this._element, eventIn, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusin' ? TRIGGER_FOCUS : TRIGGER_HOVER] = true;\n context._enter();\n });\n EventHandler.on(this._element, eventOut, this._config.selector, event => {\n const context = this._initializeOnDelegatedTarget(event);\n context._activeTrigger[event.type === 'focusout' ? TRIGGER_FOCUS : TRIGGER_HOVER] = context._element.contains(event.relatedTarget);\n context._leave();\n });\n }\n }\n this._hideModalHandler = () => {\n if (this._element) {\n this.hide();\n }\n };\n EventHandler.on(this._element.closest(SELECTOR_MODAL), EVENT_MODAL_HIDE, this._hideModalHandler);\n }\n _fixTitle() {\n const title = this._element.getAttribute('title');\n if (!title) {\n return;\n }\n if (!this._element.getAttribute('aria-label') && !this._element.textContent.trim()) {\n this._element.setAttribute('aria-label', title);\n }\n this._element.setAttribute('data-bs-original-title', title); // DO NOT USE IT. Is only for backwards compatibility\n this._element.removeAttribute('title');\n }\n _enter() {\n if (this._isShown() || this._isHovered) {\n this._isHovered = true;\n return;\n }\n this._isHovered = true;\n this._setTimeout(() => {\n if (this._isHovered) {\n this.show();\n }\n }, this._config.delay.show);\n }\n _leave() {\n if (this._isWithActiveTrigger()) {\n return;\n }\n this._isHovered = false;\n this._setTimeout(() => {\n if (!this._isHovered) {\n this.hide();\n }\n }, this._config.delay.hide);\n }\n _setTimeout(handler, timeout) {\n clearTimeout(this._timeout);\n this._timeout = setTimeout(handler, timeout);\n }\n _isWithActiveTrigger() {\n return Object.values(this._activeTrigger).includes(true);\n }\n _getConfig(config) {\n const dataAttributes = Manipulator.getDataAttributes(this._element);\n for (const dataAttribute of Object.keys(dataAttributes)) {\n if (DISALLOWED_ATTRIBUTES.has(dataAttribute)) {\n delete dataAttributes[dataAttribute];\n }\n }\n config = {\n ...dataAttributes,\n ...(typeof config === 'object' && config ? config : {})\n };\n config = this._mergeConfigObj(config);\n config = this._configAfterMerge(config);\n this._typeCheckConfig(config);\n return config;\n }\n _configAfterMerge(config) {\n config.container = config.container === false ? document.body : getElement(config.container);\n if (typeof config.delay === 'number') {\n config.delay = {\n show: config.delay,\n hide: config.delay\n };\n }\n if (typeof config.title === 'number') {\n config.title = config.title.toString();\n }\n if (typeof config.content === 'number') {\n config.content = config.content.toString();\n }\n return config;\n }\n _getDelegateConfig() {\n const config = {};\n for (const [key, value] of Object.entries(this._config)) {\n if (this.constructor.Default[key] !== value) {\n config[key] = value;\n }\n }\n config.selector = false;\n config.trigger = 'manual';\n\n // In the future can be replaced with:\n // const keysWithDifferentValues = Object.entries(this._config).filter(entry => this.constructor.Default[entry[0]] !== this._config[entry[0]])\n // `Object.fromEntries(keysWithDifferentValues)`\n return config;\n }\n _disposePopper() {\n if (this._popper) {\n this._popper.destroy();\n this._popper = null;\n }\n if (this.tip) {\n this.tip.remove();\n this.tip = null;\n }\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Tooltip.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Tooltip);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap popover.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$3 = 'popover';\nconst SELECTOR_TITLE = '.popover-header';\nconst SELECTOR_CONTENT = '.popover-body';\nconst Default$2 = {\n ...Tooltip.Default,\n content: '',\n offset: [0, 8],\n placement: 'right',\n template: '
' + '
' + '

' + '
' + '
',\n trigger: 'click'\n};\nconst DefaultType$2 = {\n ...Tooltip.DefaultType,\n content: '(null|string|element|function)'\n};\n\n/**\n * Class definition\n */\n\nclass Popover extends Tooltip {\n // Getters\n static get Default() {\n return Default$2;\n }\n static get DefaultType() {\n return DefaultType$2;\n }\n static get NAME() {\n return NAME$3;\n }\n\n // Overrides\n _isWithContent() {\n return this._getTitle() || this._getContent();\n }\n\n // Private\n _getContentForTemplate() {\n return {\n [SELECTOR_TITLE]: this._getTitle(),\n [SELECTOR_CONTENT]: this._getContent()\n };\n }\n _getContent() {\n return this._resolvePossibleFunction(this._config.content);\n }\n\n // Static\n static jQueryInterface(config) {\n return this.each(function () {\n const data = Popover.getOrCreateInstance(this, config);\n if (typeof config !== 'string') {\n return;\n }\n if (typeof data[config] === 'undefined') {\n throw new TypeError(`No method named \"${config}\"`);\n }\n data[config]();\n });\n }\n}\n\n/**\n * jQuery\n */\n\ndefineJQueryPlugin(Popover);\n\n/**\n * --------------------------------------------------------------------------\n * Bootstrap scrollspy.js\n * Licensed under MIT (https://github.com/twbs/bootstrap/blob/main/LICENSE)\n * --------------------------------------------------------------------------\n */\n\n\n/**\n * Constants\n */\n\nconst NAME$2 = 'scrollspy';\nconst DATA_KEY$2 = 'bs.scrollspy';\nconst EVENT_KEY$2 = `.${DATA_KEY$2}`;\nconst DATA_API_KEY = '.data-api';\nconst EVENT_ACTIVATE = `activate${EVENT_KEY$2}`;\nconst EVENT_CLICK = `click${EVENT_KEY$2}`;\nconst EVENT_LOAD_DATA_API$1 = `load${EVENT_KEY$2}${DATA_API_KEY}`;\nconst CLASS_NAME_DROPDOWN_ITEM = 'dropdown-item';\nconst CLASS_NAME_ACTIVE$1 = 'active';\nconst SELECTOR_DATA_SPY = '[data-bs-spy=\"scroll\"]';\nconst SELECTOR_TARGET_LINKS = '[href]';\nconst SELECTOR_NAV_LIST_GROUP = '.nav, .list-group';\nconst SELECTOR_NAV_LINKS = '.nav-link';\nconst SELECTOR_NAV_ITEMS = '.nav-item';\nconst SELECTOR_LIST_ITEMS = '.list-group-item';\nconst SELECTOR_LINK_ITEMS = `${SELECTOR_NAV_LINKS}, ${SELECTOR_NAV_ITEMS} > ${SELECTOR_NAV_LINKS}, ${SELECTOR_LIST_ITEMS}`;\nconst SELECTOR_DROPDOWN = '.dropdown';\nconst SELECTOR_DROPDOWN_TOGGLE$1 = '.dropdown-toggle';\nconst Default$1 = {\n offset: null,\n // TODO: v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: '0px 0px -25%',\n smoothScroll: false,\n target: null,\n threshold: [0.1, 0.5, 1]\n};\nconst DefaultType$1 = {\n offset: '(number|null)',\n // TODO v6 @deprecated, keep it for backwards compatibility reasons\n rootMargin: 'string',\n smoothScroll: 'boolean',\n target: 'element',\n threshold: 'array'\n};\n\n/**\n * Class definition\n */\n\nclass ScrollSpy extends BaseComponent {\n constructor(element, config) {\n super(element, config);\n\n // this._element is the observablesContainer and config.target the menu links wrapper\n this._targetLinks = new Map();\n this._observableSections = new Map();\n this._rootElement = getComputedStyle(this._element).overflowY === 'visible' ? null : this._element;\n this._activeTarget = null;\n this._observer = null;\n this._previousScrollData = {\n visibleEntryTop: 0,\n parentScrollTop: 0\n };\n this.refresh(); // initialize\n }\n\n // Getters\n static get Default() {\n return Default$1;\n }\n static get DefaultType() {\n return DefaultType$1;\n }\n static get NAME() {\n return NAME$2;\n }\n\n // Public\n refresh() {\n this._initializeTargetsAndObservables();\n this._maybeEnableSmoothScroll();\n if (this._observer) {\n this._observer.disconnect();\n } else {\n this._observer = this._getNewObserver();\n }\n for (const section of this._observableSections.values()) {\n this._observer.observe(section);\n }\n }\n dispose() {\n this._observer.disconnect();\n super.dispose();\n }\n\n // Private\n _configAfterMerge(config) {\n // TODO: on v6 target should be given explicitly & remove the {target: 'ss-target'} case\n config.target = getElement(config.target) || document.body;\n\n // TODO: v6 Only for backwards compatibility reasons. Use rootMargin only\n config.rootMargin = config.offset ? `${config.offset}px 0px -30%` : config.rootMargin;\n if (typeof config.threshold === 'string') {\n config.threshold = config.threshold.split(',').map(value => Number.parseFloat(value));\n }\n return config;\n }\n _maybeEnableSmoothScroll() {\n if (!this._config.smoothScroll) {\n return;\n }\n\n // unregister any previous listeners\n EventHandler.off(this._config.target, EVENT_CLICK);\n EventHandler.on(this._config.target, EVENT_CLICK, SELECTOR_TARGET_LINKS, event => {\n const observableSection = this._observableSections.get(event.target.hash);\n if (observableSection) {\n event.preventDefault();\n const root = this._rootElement || window;\n const height = observableSection.offsetTop - this._element.offsetTop;\n if (root.scrollTo) {\n root.scrollTo({\n top: height,\n behavior: 'smooth'\n });\n return;\n }\n\n // Chrome 60 doesn't support `scrollTo`\n root.scrollTop = height;\n }\n });\n }\n _getNewObserver() {\n const options = {\n root: this._rootElement,\n threshold: this._config.threshold,\n rootMargin: this._config.rootMargin\n };\n return new IntersectionObserver(entries => this._observerCallback(entries), options);\n }\n\n // The logic of selection\n _observerCallback(entries) {\n const targetElement = entry => this._targetLinks.get(`#${entry.target.id}`);\n const activate = entry => {\n this._previousScrollData.visibleEntryTop = entry.target.offsetTop;\n this._process(targetElement(entry));\n };\n const parentScrollTop = (this._rootElement || document.documentElement).scrollTop;\n const userScrollsDown = parentScrollTop >= this._previousScrollData.parentScrollTop;\n this._previousScrollData.parentScrollTop = parentScrollTop;\n for (const entry of entries) {\n if (!entry.isIntersecting) {\n this._activeTarget = null;\n this._clearActiveClass(targetElement(entry));\n continue;\n }\n const entryIsLowerThanPrevious = entry.target.offsetTop >= this._previousScrollData.visibleEntryTop;\n // if we are scrolling down, pick the bigger offsetTop\n if (userScrollsDown && entryIsLowerThanPrevious) {\n activate(entry);\n // if parent isn't scrolled, let's keep the first visible item, breaking the iteration\n if (!parentScrollTop) {\n return;\n }\n continue;\n }\n\n // if we are scrolling up, pick the smallest offsetTop\n if (!userScrollsDown && !entryIsLowerThanPrevious) {\n activate(entry);\n }\n }\n }\n _initializeTargetsAndObservables() {\n this._targetLinks = new Map();\n this._observableSections = new Map();\n const targetLinks = SelectorEngine.find(SELECTOR_TARGET_LINKS, this._config.target);\n for (const anchor of targetLinks) {\n // ensure that the anchor has an id and is not disabled\n if (!anchor.hash || isDisabled(anchor)) {\n continue;\n }\n const observableSection = SelectorEngine.findOne(decodeURI(anchor.hash), this._element);\n\n // ensure that the observableSection exists & is visible\n if (isVisible(observableSection)) {\n this._targetLinks.set(decodeURI(anchor.hash), anchor);\n this._observableSections.set(anchor.hash, observableSection);\n }\n }\n }\n _process(target) {\n if (this._activeTarget === target) {\n return;\n }\n this._clearActiveClass(this._config.target);\n this._activeTarget = target;\n target.classList.add(CLASS_NAME_ACTIVE$1);\n this._activateParents(target);\n EventHandler.trigger(this._element, EVENT_ACTIVATE, {\n relatedTarget: target\n });\n }\n _activateParents(target) {\n // Activate dropdown parents\n if (target.classList.contains(CLASS_NAME_DROPDOWN_ITEM)) {\n SelectorEngine.findOne(SELECTOR_DROPDOWN_TOGGLE$1, target.closest(SELECTOR_DROPDOWN)).classList.add(CLASS_NAME_ACTIVE$1);\n return;\n }\n for (const listGroup of SelectorEngine.parents(target, SELECTOR_NAV_LIST_GROUP)) {\n // Set triggered links parents as active\n // With both -

Problem and objectives

+

Situation and solutions

  • The role of the llm assistant
  • Proposal
    • diff --git a/_build/html/bern_example.html b/docs/bern_example.html similarity index 99% rename from _build/html/bern_example.html rename to docs/bern_example.html index f68fd5d..c3d500e 100644 --- a/_build/html/bern_example.html +++ b/docs/bern_example.html @@ -171,7 +171,7 @@
-

Problem and objectives

+

Situation and solutions

  • The role of the llm assistant
  • Proposal
    • diff --git a/_build/html/bern_lakes_example.html b/docs/bern_lakes_example.html similarity index 99% rename from _build/html/bern_lakes_example.html rename to docs/bern_lakes_example.html index b8e232b..b9068af 100644 --- a/_build/html/bern_lakes_example.html +++ b/docs/bern_lakes_example.html @@ -171,7 +171,7 @@
-

Problem and objectives

+

Situation and solutions

  • The role of the llm assistant
  • Proposal
    • diff --git a/_build/html/biel_city_example.html b/docs/biel_city_example.html similarity index 99% rename from _build/html/biel_city_example.html rename to docs/biel_city_example.html index 92870c7..203bcd7 100644 --- a/_build/html/biel_city_example.html +++ b/docs/biel_city_example.html @@ -171,7 +171,7 @@
-

Problem and objectives

+

Situation and solutions

  • The role of the llm assistant
  • Proposal
    • diff --git a/_build/html/bielersee_example.html b/docs/bielersee_example.html similarity index 99% rename from _build/html/bielersee_example.html rename to docs/bielersee_example.html index f052f4c..c3a7052 100644 --- a/_build/html/bielersee_example.html +++ b/docs/bielersee_example.html @@ -171,7 +171,7 @@
-

Problem and objectives

+

Situation and solutions

  • The role of the llm assistant
  • Proposal
    • diff --git a/docs/extracting_topo_data.html b/docs/extracting_topo_data.html index d417525..7512943 100644 --- a/docs/extracting_topo_data.html +++ b/docs/extracting_topo_data.html @@ -8,7 +8,7 @@ - Extracting land use values — Project 2025 + Land cover and land use — Project 2025 @@ -57,11 +57,12 @@ + + - - + @@ -167,35 +168,27 @@ -

    Data and reporting

    +

    Situation and solutions

    -

    Methods and classes

    +

    Example reports

    Annex

    @@ -334,7 +327,7 @@
    -

    Extracting land use values

    +

    Land cover and land use

    @@ -344,28 +337,17 @@

    Contents

    @@ -379,182 +361,42 @@

    Contents

    +
    +

    Land cover and land use#

    +

    The land cover and land use are used to determine the similarity of one survey location to another. In this way we can evaluate the probable minimum amount of trash at a given location based on the physical environment.

    +

    Land cover and land use provide information about the physical characteristics of a survey location. The land use and cover is measured by considering the proportion of land dedicated to specific purposes within a radius of 1’500 m of the survey location of interest. The specific puroposes are defined by the following map layers available at swissTLMRegio:

    +
      +

    1. Landcover (TLM_BODENBEDECKUNG)

      2. +

    2. Streets (TLM_STRASSEN)

      3. +

    3. Hydrology (TLM_GEWAESSER)

      4. +

    4. Sports and recreation (TLM_FREIZEITAREAL)

      5. +

    5. Public services (TLM_NUTZUNGSAREAL)

      6. +
    +
    +

    Defining similar locations#

    +

    When comparing feature vectors in three-dimensional space, various distance metrics can be applied, each depending on the nature of the data and the type of comparison needed. Euclidean distance measures the straight-line distance between two points, making it suitable when the magnitude of differences in the same-scale features matters. Manhattan distance measures the sum of absolute differences across each dimension, which is useful when you prefer a more “axis-aligned” measure of difference, particularly when feature importance might vary along each axis. Cosine similarity, however, compares the orientation of the vectors in space, measuring how aligned they are regardless of magnitude. This is particularly relevant when the proportions between feature values are more important than their absolute values. In our analysis, cosine similarity was chosen because we are more interested in the relative proportions of the feature variables rather than their magnitudes.

    +

    Cosine similarity measures the cosine of the angle between two vectors in multi-dimensional space, focusing on the direction of the vectors rather than their length. The similarity ranges from -1 (perfectly opposite directions) to 1 (identical directions), with 0 indicating orthogonal or no similarity. The formula normalizes the vectors to unit length, comparing only the relative proportions between the dimensions. Cosine similarity is especially useful when the magnitude of the vectors varies significantly, but the pattern or trend of the features is important.

    +

    For example, imagine comparing two feature vectors:

    +
      +

    • \( x = [0.4, 0.5, 0.6] \)

      • +

    • \(y = [0.2, 0.25, 0.3] \)

      • +
    +

    Even though the absolute values of (y) are smaller than those of (x), the proportions between dimensions remain the same (i.e., \( 0.4/0.5 \approx 0.2/0.25\))). Cosine similarity will show that these two vectors are highly similar because their pattern or direction is nearly identical. By contrast, Euclidean distance would highlight the magnitude differences between the vectors, leading to a different measure of similarity.

    +
    +
    +

    Example: defining the land use for one location#

    +

    For each location the land use and land cover is calculated by first extracting the relevant features from the appropriate map layers within a radius of 1 500 m.

    -
    -
    -
    -
    land_uses_l = []
-for a_location in lake_locations:
-    this_location = locations_and_coordinates.loc[[a_location]].copy()
-    this_point, abuffer, bufferbounds = a_point_buffer(this_location)
-    buffer_content_i, names = location_geo_attributes(bufferbounds, abuffer, 'data/ignorethis/shapes/landcover.shp', buffer_name=a_location)
-    
-    # identify the undefined areas
-    combined_polygon = unary_union(buffer_content_i.geometry)
-    combined_Pn = gpd.GeoDataFrame({'geometry': [combined_polygon]}, crs=buffer_content_i.crs)
-    undefined = compute_undefined_sections_of_buffer(abuffer,combined_Pn, buffer_name=a_location)
-    
-    # combine the known land cover with the undefined
-    buffer_content_i = pd.concat([buffer_content_i, undefined])
-    
-    args = dict(objcolumn='OBJEKTART', objval='land-cover', buffer_name=a_location)
-    nz, _ = location_geo_attributes(bufferbounds, abuffer, 'data/ignorethis/shapes/nutuzungsareal.shp', **args)
-    nz_comb = unary_union(nz.geometry)
-    nz_comb = gpd.GeoDataFrame([{'geometry': nz_comb, 'buffer-name':a_location, 'land-cover': 'public-services' }], crs=buffer_content_i.crs)
-    
-    
-    fz,_ = location_geo_attributes(bufferbounds, abuffer,'data/ignorethis/shapes/freizeit.shp', **args)
-    fz_comb = unary_union(fz.geometry)
-    fz_comb = gpd.GeoDataFrame([{'geometry': fz_comb, 'buffer-name':a_location, 'land-cover': 'recreation' }], crs=buffer_content_i.crs)
-    q = pd.concat([buffer_content_i, nz_comb, fz_comb])
-    
-    
-    # indentify the contents of the buffer
-    minx, miny, maxx, maxy = bufferbounds
-    streets = gpd.read_file('data/ignorethis/shapes/strasse.shp',bbox=(minx, miny, maxx, maxy))
-    streets = streets.drop_duplicates()
-    streets = streets.dissolve()
-    streets = gpd.overlay(streets, abuffer, how='intersection', keep_geom_type=True)
-    
-    t = compute_landuse_percent_of_buffer(q, abuffer.geometry.area[0])
-    t = t.groupby('land-cover').rate.sum()
-    t['streets'] = streets.geometry.length[0]
-    t.drop('See', inplace=True)
-    t['location'] = a_location
-    land_uses_l.append(t)
-
    -
    -
    -
    -
    -
    -
    f = pd.DataFrame(land_uses_l).round(3)
-f.fillna(0, inplace=True)
-f.info()
-
    -
    -
    -
    <class 'pandas.core.frame.DataFrame'>
-Index: 128 entries, rate to rate
-Data columns (total 13 columns):
- #   Column           Non-Null Count  Dtype  
----  ------           --------------  -----  
- 0   Siedl            128 non-null    float64
- 1   Sumpf            128 non-null    float64
- 2   Wald             128 non-null    float64
- 3   public-services  128 non-null    float64
- 4   recreation       128 non-null    float64
- 5   undefined        128 non-null    float64
- 6   streets          128 non-null    float64
- 7   location         128 non-null    object 
- 8   Reben            128 non-null    float64
- 9   Fels             128 non-null    float64
- 10  Stadtzentr       128 non-null    float64
- 11  Obstanlage       128 non-null    float64
- 12  Geroell          128 non-null    float64
-dtypes: float64(12), object(1)
-memory usage: 14.0+ KB
-
    -
    -
    -
    -
    -
    -
    land_uses_r = []
-for a_location in river_locations:
-    this_location = locations_and_coordinates.loc[[a_location]].copy()
-    this_point, abuffer, bufferbounds = a_point_buffer(this_location)
-    buffer_content_i, names = location_geo_attributes(bufferbounds, abuffer, 'data/ignorethis/shapes/landcover.shp', buffer_name=a_location)
-    
-    # identify the undefined areas
-    combined_polygon = unary_union(buffer_content_i.geometry)
-    combined_Pn = gpd.GeoDataFrame({'geometry': [combined_polygon]}, crs=buffer_content_i.crs)
-    undefined = compute_undefined_sections_of_buffer(abuffer,combined_Pn, buffer_name=a_location)
-    
-    # combine the known land cover with the undefined
-    buffer_content_i = pd.concat([buffer_content_i, undefined])
-    
-    args = dict(objcolumn='OBJEKTART', objval='land-cover', buffer_name=a_location)
-    nz, _ = location_geo_attributes(bufferbounds, abuffer, 'data/ignorethis/shapes/nutuzungsareal.shp', **args)
-    nz_comb = unary_union(nz.geometry)
-    nz_comb = gpd.GeoDataFrame([{'geometry': nz_comb, 'buffer-name':a_location, 'land-cover': 'public-services' }], crs=buffer_content_i.crs)
-    
-    
-    fz,_ = location_geo_attributes(bufferbounds, abuffer,'data/ignorethis/shapes/freizeit.shp', **args)
-    fz_comb = unary_union(fz.geometry)
-    fz_comb = gpd.GeoDataFrame([{'geometry': fz_comb, 'buffer-name':a_location, 'land-cover': 'recreation' }], crs=buffer_content_i.crs)
-    q = pd.concat([buffer_content_i, nz_comb, fz_comb])
-    
-    
-    # indentify the contents of the buffer
-    minx, miny, maxx, maxy = bufferbounds
-    streets = gpd.read_file('data/ignorethis/shapes/strasse.shp',bbox=(minx, miny, maxx, maxy))
-    streets = streets.drop_duplicates()
-    streets = streets.dissolve()
-    streets = gpd.overlay(streets, abuffer, how='intersection', keep_geom_type=True)
-    t = compute_landuse_percent_of_buffer(q, abuffer.geometry.area[0])
-    t = t.groupby('land-cover').rate.sum()
-    t['streets'] = streets.geometry.length[0]
-    t['location'] = a_location
-    land_uses_r.append(t)
-
    -
    -
    -
    -
    -
    -
    rv = pd.DataFrame(land_uses_r).round(3)
-rv.fillna(0, inplace=True)
-rv.drop('See', axis=1, inplace=True)
-
    -
    -
    -
    -
    -
    -
    newlu = pd.concat([f,rv])
-newlu.set_index('location', inplace=True, drop=True)
-rename = {
-    'Siedl':'buildings', 
-    'Sumpf':'wetlands',
-    'Wald': 'forest',
-    'Reben': 'vineyards',
-    'Fels': 'cliffs',
-    'Stadtzentr': 'city-center',
-    'Obstanlage':'orchards',
-    'Geroell' : 'boulders'
-}
-
-newlu.rename(columns=rename, inplace=True)
-newlu.columns
-
    -
    -
    -
    -
    Index(['buildings', 'wetlands', 'forest', 'public-services', 'recreation',
-       'undefined', 'streets', 'vineyards', 'cliffs', 'city-center',
-       'orchards', 'boulders'],
-      dtype='object', name='land-cover')
-
    -
    -
    -
    -
    -
    -
    newlu.to_csv('data/in_process/new_lu.csv', index=True)
-
    -
    -
    -
    -
    -
    -
    pd.read_csv('data/in_process/new_lu.csv')
-
    +_images/35654890b0bbed1713742527927f50bbf0e6dcb77d969096b6f558f7da73db5f.png
    +
    +

    Land use profile#

    +

    The land use profile is the array of values between 0 and 1 that contains the proportion of the buffer zone occupied by the different land use and land cover attributes within the buffer zone of a survey location.

    +
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + - - - - + + - - - - + +
    buffer-nameland-coverarea_m2% of buffer
    anarchy-beachSee4'522'2831,78
    anarchy-beachSiedl2'262'1840,89
    anarchy-beachSiedl248'8550,10
    anarchy-beachSiedl23'9100,0150%0.450000
    anarchy-beachundefined00,0075%1.150000
    anarchy-beachpublic-services251'1880,04max8.180000
    -
    -
    -
    -
    -
    -
    -
    -
    -
    streets.geometry.length
-
    -
    -
    -
    -
    0    5526.40911
-dtype: float64
-
    -
    -
    -
    -
    -
    -_images/e9d5ab06c253a65f0c8a6bc52ad9f867b7eec9d24fbc4ba5d6ee5de224d0513f.png -
    -
    -
    -
    -_images/2a9deb60f3b91a4df7ffbbb5e6c20aeafcf462e0571dec3dced61eaea4dd992c.png -
    -
    -
    -
    -
    /tmp/ipykernel_250334/2395655611.py:8: UserWarning: The GeoDataFrame you are attempting to plot is empty. Nothing has been displayed.
-  wald.plot(ax=ax, facecolor='yellowgreen', edgecolor='darkgreen', alpha=1, hatch='oo',zorder=1)
-
    -
    -_images/795c5203fdd1548d51eb6dc21c668ca4188da0f1c84652a33dcd2b38db9a8985.png -
    -
    -
    -
    -_images/31ff44fba319361ac646f6e3120caea1195fc07597898ae541cf6ca3582999f1.png -
    -
    -
    -
    -_images/6eeb49561a4fc243279d1e5b4e7bdc63bda42f9ee394fe152537b06a4226e586.png -
    -
    -
    -
    -_images/3cb8da5a74d88b631ef83c8df79a210f0593100492f40bb79007573796bb4a56.png -
    -
    -
    -
    -
    /tmp/ipykernel_250334/2500445883.py:12: UserWarning: The GeoDataFrame you are attempting to plot is empty. Nothing has been displayed.
-  wald.plot(ax=ax, facecolor='yellowgreen', edgecolor='darkgreen', alpha=1, hatch='oo',zorder=1)
-
    -
    -_images/75faebd3764affa0782c04a3c7fe579b72ce51a967c27d0004911855b40b6e68.png -
    -
    -
    -

    Extracting land use values#

    -

    This is a summary of the methods used to extract topographical features from vector and points layers. The source for the vector layer is swissTLMRegio.

    -

    QGIS is not the optimal tool for this operation if the intention is to automate the aquisition of the data. However for a limited number of users and relatively few sample locations added each year QGIS is adequate to the task. A summary of the methods for using QGIS is below.

    -

    Note: 1’500 meter buffer (circular)

    -

    The land-use chapter in the federal report generated alot of interest Land use profile - german. It inspired an academic article and collaboration with Wagenigen Research and University.

    -

    Why don’t the percentages add up to 100 ?

    -

    This is because some features listed on the map are superimposed on to others. For example a wooded area may contain a public park, this would mean that the park is considered a feature and has a definite surface area but this is in addition to the surface area of the forested area where the park is located. In general we can define the difference in this way:

    -

    Land-cover: Are elements such as buildings, forest, orchard or undefined. There is at least one land-cover element for each survey location. If so then it takes 100% of the available dry land.

    -

    Land-use: Are elements that may or may not be in the buffer. These are items like schools, hospitals, water-treatment plants. Individually they are only a small portion of the available dry land.

    -
    -

    Technical requirements#

    -

    In addition to pandas, python and numpy, the following python packages are required:

    -
      -

    1. Geopandas

      2. -

    2. Shapely

      3. -
    -
    -

    A point and a buffer#

    -

    The first step is to create a buffer of the appropriate radius with the point (survey locatio) at the center. The point is constructed by using gps coordinates for the location as arguments to shapely.geometry.Point. This is then converted to Geopandas.GeodataFrame (gdf) using the coordinate reference system (crs) of the point data. From the gdf, use the buffer method and collect the bounds.

    -

    Making a buffer from a point

    -
    
-# method to make the buffer, the point and the bufferbounds
-def a_point_buffer(this_location: pd.Series, buffer_radius: int = 1500, coordinate_crs: str = 'epsg:4326', to_crs: str = "epsg:2056"):
-    # create a point, a buffer and buffer bounds for one location
-    this_geometry = [Point(this_location.longitude, this_location.latitude)]
-    this_shape = gpd.GeoDataFrame(this_location, geometry=this_geometry, crs=coordinate_crs)
-    this_shape = this_shape.to_crs(to_crs)
-
-    this_buffer = gpd.GeoDataFrame(geometry=this_shape.buffer(buffer_radius), crs=to_crs)
-    location_buffer = this_buffer.dissolve()
-    
-    return this_shape, location_buffer, location_buffer.total_bounds
-
-# select a location
-a_location = river_locations[5]
-# retrieve the grid coordinates
-this_location = locations_and_coordinates.loc[[a_location]].copy()
-# make the point, the buffer and the bounds
-this_point, abuffer, bufferbounds = a_point_buffer(this_location)
-
    -
    -
    -
    -

    Retrieve location attributes: land-cover#

    -

    The bounds and the buffer from the previous operation are used to construct an overlay for the .SHP file that holds the souce data. The name of the location is used to identify the buffer.

    -
    def location_geo_attributes(bounds, buffer, shape_file, objcolumn: str = 'OBJVAL', objval: str ='land-cover', buffer_name: str = None):
-    minx, miny, maxx, maxy = bounds
-    landcover = gpd.read_file(shape_file, bbox=(minx, miny, maxx, maxy))
-    landcover = landcover.drop_duplicates()
-    landcover = gpd.overlay(landcover, buffer, how='intersection', keep_geom_type=True)
-    landcover.rename(columns={objcolumn:objval}, inplace=True)
-    landcover['buffer-name'] = buffer_name
-    
-    return landcover[['buffer-name', objval, 'geometry']]
-
-# indentify the contents of the buffer    
-buffer_content = location_geo_attributes(bufferbounds, abuffer, 'data/ignorethis/shapes/landcover.shp', buffer_name=a_location)
-
    -
    -
    -
    -

    Undefined areas#

    -

    Not all areas of the buffer will have a defined land-cover. To identify those areas, all of the buffer_content is joined. For this we use the shapely.unary_union method and provide the buffer_content as an argument. This will produce a separate gdf that is the negative of the buffer_content.

    -
    # identify the undefined areas
-combined_polygon = unary_union(buffer_content_i.geometry)
-combined_Pn = gpd.GeoDataFrame({'geometry': [combined_polygon]}, crs=buffer_content_i.crs)
-undefined = compute_undefined_sections_of_buffer(abuffer,combined_Pn, buffer_name=a_location)
-
-# combine the known land cover with the undefined
-buffer_content_i = pd.concat([buffer_content_i, undefined])
-
-# assign 
-buffer_content = assign_colors_to_polygons(buffer_content_i, colors=land_use_colors, objval='land-cover')
-buffer_content = compute_landuse_percent_of_buffer(buffer_content, abuffer.geometry.area[0])
-buffer_content['area_m2'] = buffer_content['area_m2'].astype(int)
-
    -
    -

    To complete the process (for land-cover) the undefined areas are merged with the buffer_content and the surface area for each polygon is calculated.

    -
    -
    -

    Public services: land-use#

    -

    As noted earlier, some topographical features are overlayed on to other features. Here we are talking about two specific vector layers in the swissTLMRegio collection:

    -
      -

    1. Nutuzungsareal : infrastructure or other usage

      2. -

    2. Freizeitareal : recreation area

      3. -
    -

    We are interested in these layers because they give us information about the activities that may occur in proximity to the survey location. The same method is used to extract the polygons as was done with land use. However, we are using the shapely.unary_union method on the entire layer. Which means that we are not differentiating between the subcategories in each layer.

    -

    Once the buffer overlay has been applied to both layers the contents are combined and added to the buffer_content data:

    -
    # infrastructure
-args = dict(objcolumn='OBJEKTART', objval='land-use', buffer_name=a_location)
-nz = location_geo_attributes(bufferbounds, abuffer, 'data/ignorethis/shapes/nutuzungsareal.shp', **args)
-nz_comb = unary_union(nz.geometry)
-nz_comb = gpd.GeoDataFrame({'geometry': [nz_comb]}, crs=buffer_content_i.crs)
-
-# recreational areas
-args = dict(objcolumn='OBJEKTART', objval='land-use', buffer_name=a_location)
-fz = location_geo_attributes(bufferbounds, abuffer,'data/ignorethis/shapes/freizeit.shp', **args)
-fz_comb = unary_union(fz.geometry)
-fz_comb = gpd.GeoDataFrame({'geometry': [fz_comb]}, crs=buffer_content_i.crs)
-
-# combine them all into one category called public services
-public_service = pd.concat([nz, fz])
-ps_comb = unary_union(public_service.geometry)
-
-args = {
-    'geometry': [ps_comb],
-    'land-cover':['public-services'],
-    'buffer-name':[a_location],
-    'color':'red'
-}
-ps_comb = gpd.GeoDataFrame(args, crs=buffer_content_i.crs)
-ps_comb = compute_landuse_percent_of_buffer(ps_comb, abuffer.geometry.area[0])
-
-# combine the public services and the land-cover
-land_use_profile = pd.concat([buffer_content, ps_comb])
-land_use_profile['area_m2'] = land_use_profile['area_m2'].astype(int)
-land_use_profile['rate'] = land_use_profile['rate'].round(2)
-land_use_profile.rename(columns={'rate': '% of buffer'}, inplace=True)
-
    -
    -

    Which results in the land-use profile for the location in question, (not including streets).

    -
    -
    -

    Land use and cover for a location.

    -
    -
    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    buffer-nameland-coverarea_m2% of buffer
    anarchy-beachSee4'522'2831,78
    anarchy-beachSiedl2'262'1840,89
    anarchy-beachSiedl248'8550,10
    anarchy-beachSiedl23'9100,01
    anarchy-beachundefined00,00
    anarchy-beachpublic-services251'1880,04
    -
    -
    -
    -
    -

    Building a map of land cover#

    -
    -
    -
    -
    -
    -_images/e9d5ab06c253a65f0c8a6bc52ad9f867b7eec9d24fbc4ba5d6ee5de224d0513f.png -
    -
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    -
    -
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    -
    -_images/2a9deb60f3b91a4df7ffbbb5e6c20aeafcf462e0571dec3dced61eaea4dd992c.png -
    -
    -

    Surface area: 4’145’791 m², % of buffer: 59%

    -
    -
    -
    -
    -
    -
    -_images/795c5203fdd1548d51eb6dc21c668ca4188da0f1c84652a33dcd2b38db9a8985.png -
    -
    -

    Surface area: 1’528’977 m², % of buffer: 22%

    -
    -
    -
    -
    -
    -
    -_images/31ff44fba319361ac646f6e3120caea1195fc07597898ae541cf6ca3582999f1.png -
    -
    -

    Surface area: 1’484’991 m², % of buffer: 21%

    -
    -
    -
    -
    -
    -
    -_images/6eeb49561a4fc243279d1e5b4e7bdc63bda42f9ee394fe152537b06a4226e586.png -
    -
    -

    Surface area: 1’382’463 m², % of buffer: 20%

    -
    -
    -
    -
    -
    -
    -_images/3cb8da5a74d88b631ef83c8df79a210f0593100492f40bb79007573796bb4a56.png -
    -
    -

    Total length of streets : 17km

    -
    -
    -
    -
    -
    -
    -_images/75faebd3764affa0782c04a3c7fe579b72ce51a967c27d0004911855b40b6e68.png -
    -
    -
    -
    -
    -
    +
    @@ -1467,559 +614,20 @@

    Building a map of land cover
    # separate locations that are lakes
-# recall that feature type has a designator for lakes
-lakes = lg[(lg.feature_ty == 'l') | lg.slug.isin(snl)].copy()
-
-# from this subset of data separate the surface area covered by water
-# set the slug to the index and substract the surface area of the water
-# from the surface area of the buffer
-lake_only = lakes[lakes.feature == "See"]
-lo = lake_only[["slug", "area"]].set_index("slug")
-
-# substract the lake value from the area of the buffer
-lo["dry"] = 7065000 - lo.area
-lodry = lo["dry"]
-
-# merge the original land-use data from lakes with the
-# the dry land results
-lgi = lakes.merge(lo["dry"], left_on="slug", right_index=True)
-# remove the lake feature from the features columns
-lgi = lgi[lgi.feature != "See"].copy()
-
-# scale the landuse feature to the available dry land
-lgi["scale"] = (lgi.area/lgi.dry).round(3)
-
-# repeat the process for locations that do not have a lake feature
-# these locations are accounted for above
-eliminate = [*snl, *lo.index]
-# recuperate all other locations
-rivers_parcs = lg[~lg.slug.isin(eliminate)].copy()
-# define the dry land as the area of the buffer
-rivers_parcs["dry"] = 7065000
-# scale the features with the dry land value
-rivers_parcs["scale"] = rivers_parcs.area/rivers_parcs.dry
-
-# combine the two results
-land_cover = pd.concat([rivers_parcs, lgi])
-
    - -

    Once the dry land value is calculated for each buffer of the land-cover buffer use the dry-land value to scale the components of the land-use buffer

    -
    -

    Extracting street lengths#

    -

    The tlmREgio streets or strasse layer is applicable.

    -

    Note: the street lenghts are not scaled

    -

    finished columns = slug, attribute, attribute_type, length

    -

    Attention:

    -
      -

    1. The streets layer can have many copies of the same street in a buffer

      2. -

    2. The cumulative sum of a street in a layer can exceed the radius of the buffer (windy roads)

      3. -

    3. Dissolving the polylines of each buffer in the layer is essential

      4. -

    4. Drop duplicate values on slug, attribute, length

      5. -

    5. Using the same 1’500 m buffer that was used for land-cover and land-use. Intersect the buffer with the street layer

      6. -

    6. Dissolve the polylines in each buffer

      -
        -

      • select the fields from the streets layer to keep (OBJVAL)

        • -

      • select the fields from the buffer layer to kepp (slug, feature_ty)

        • -

      • check the box keep disjoint features separate

        • -

      • run the function

        • -

      • export to .csv

        • -
      -
      7. -
    -
    -
    -
    -

    Land-cover#

    -

    Land-cover attributes

    -
    -
    -
    array(['undefined', 'Siedl', 'Wald', 'Reben', 'Obstanlage'], dtype=object)
-
    -
    -
    -
    -

    land-cover attribute translations

    -
    land_cover_fr = {
-    'undefined': 'Non défini',
-    'Siedl': 'Siedl',
-    'Wald': 'Forêt',
-    'Reben': 'Vignes',
-    'Obstanlage': 'Verger'
-}
-
-land_cover_en = {
-    'undefined': 'Undefined',
-    'Siedl': 'Settlement',
-    'Wald': 'Forest',
-    'Reben': 'Vines',
-    'Obstanlage': 'Orchard'
-}
-
    -
    -

    Land-cover results for one location

    -
    -
    -
    -
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    slugattributeattribute_typeareadryscale
    141parc-des-pierrettesundefinedland-cover6828538325590.018
    623parc-des-pierrettesSiedlland-cover360688538325590.941
    624parc-des-pierrettesWaldland-cover15738938325590.041
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    Land-use#

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    Land-use attributes:

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    array(['Baumschule', 'Friedhof', 'Schul- und Hochschulareal',
-       'Wald nicht bestockt', 'Abwasserreinigungsareal',
-       'Historisches Areal', 'Kraftwerkareal', 'Schrebergartenareal',
-       'Truppenuebungsplatz', 'Unterwerkareal',
-       'Kehrichtverbrennungsareal', 'Spitalareal',
-       'Oeffentliches Parkareal', 'Messeareal',
-       'Massnahmenvollzugsanstaltsareal', 'Kiesabbauareal',
-       'Steinbruchareal', 'Klosterareal', 'Deponieareal', 'Antennenareal',
-       'Lehmabbauareal'], dtype=object)
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    Land-use translations and groups

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-land_use_fr = {
-    'Baumschule': 'Pépinière',
-    'Friedhof': 'Cimetière',
-    'Schul- und Hochschulareal': 'Zone scolaire et universitaire',
-    'Wald nicht bestockt': 'Forêt non peuplée',
-    'Abwasserreinigungsareal': 'Zone de traitement des eaux usées',
-    'Historisches Areal': 'Zone historique',
-    'Kraftwerkareal': 'Zone de centrale électrique',
-    'Schrebergartenareal': 'Zone de jardins familiaux',
-    'Truppenübungsplatz': 'Terrain d\'entraînement militaire',
-    'Unterwerkareal': 'Zone de sous-station',
-    'Kehrichtverbrennungsareal': 'Zone d\'incinération des déchets',
-    'Spitalareal': 'Zone d\'hôpital',
-    'Öffentliches Parkareal': 'Zone de parc public',
-    'Messeareal': 'Zone d\'exposition',
-    'Massnahmenvollzugsanstaltsareal': 'Zone d\'établissement de traitement',
-    'Kiesabbauareal': 'Zone d\'extraction de gravier',
-    'Steinbruchareal': 'Zone de carrière',
-    'Klosterareal': 'Zone de monastère',
-    'Deponieareal': 'Zone de décharge',
-    'Antennenareal': 'Zone d\'antennes',
-    'Lehmabbauareal': 'Zone d\'extraction d\'argile'
-}
-
-land_use_en = {
-    'Baumschule': 'Nursery',
-    'Friedhof': 'Cemetery',
-    'Schul- und Hochschulareal': 'School and University Area',
-    'Wald nicht bestockt': 'Non-stocked Forest',
-    'Abwasserreinigungsareal': 'Wastewater Treatment Area',
-    'Historisches Areal': 'Historical Area',
-    'Kraftwerkareal': 'Power Plant Area',
-    'Schrebergartenareal': 'Allotment Garden Area',
-    'Truppenübungsplatz': 'Military Training Ground',
-    'Unterwerkareal': 'Substation Area',
-    'Kehrichtverbrennungsareal': 'Waste Incineration Area',
-    'Spitalareal': 'Hospital Area',
-    'Öffentliches Parkareal': 'Public Park Area',
-    'Messeareal': 'Exhibition Area',
-    'Massnahmenvollzugsanstaltsareal': 'Correctional Facility Area',
-    'Kiesabbauareal': 'Gravel Extraction Area',
-    'Steinbruchareal': 'Quarry Area',
-    'Klosterareal': 'Monastery Area',
-    'Deponieareal': 'Landfill Area',
-    'Antennenareal': 'Antenna Area',
-    'Lehmabbauareal': 'Clay Extraction Area'
-}
-
-# land_uses_grouped:
-# outdoor non technical use:
-lu_non_tech = ['Friedhof', 'Hitorisches Areal', 'Schrebergartenareal', 'Öffentliches Parkareal', 'Messeareal', 'Klosterareal',  'Wald nicht bestockt']
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-# technical-extraction-incineration
-lu_extraction = ['Kiesabbauareal', 'Steinbruchareal',  'Lehmabbauareal',]
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-# waste-water-treatment-powere
-lu_technical = ['Kehrichtverbrennungsareal', 'Deponieareal', 'Deponieareal', 'Abwasserreinigungsareal','Unterwerkareal', 'Antennenareal']
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-# services:
-lu_serives = ['Massnahmenvollzugsanstaltsareal', 'Schul- und Hochschulareal', 'Spitalareal']
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    Land-use for one location:

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    slugattributeattribute_typeareadryscale
    685parc-des-pierrettesAbwasserreinigungsarealland-use4948838325590.012913
    686parc-des-pierrettesFriedhofland-use1132538325590.002955
    687parc-des-pierrettesOeffentliches Parkarealland-use17559138325590.045816
    688parc-des-pierrettesSchrebergartenarealland-use1730638325590.004516
    689parc-des-pierrettesSchul- und Hochschularealland-use118916138325590.310279
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    Streets#

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    Streets attributes:

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    array(['Autostr', 'Fahrstraes', 'Fussweg', 'HauptStrAB6', 'VerbindStr4',
-       'NebenStr3', 'VerbindStr6', 'Autobahn', 'HauptStrAB4', 'NebenStr6',
-       'Autob_Ri'], dtype=object)
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    Streets: translations and groups

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    streets_fr = {
-    'Autostr': 'autoroute',
-    'NebenStr3': 'route secondaire 3',
-    'NebenStr6': 'route secondaire 6',
-    'HauptStrAB6': 'route principale 6',
-    'HauptStrAB4': 'route principale 4',
-    'Fahrstraes': 'chemin carrossable',
-    'Fussweg': 'chemin pédestre',
-    'Autobahn': 'autoroute',
-    'Autob_Ri': 'autoroute',
-    'VerbindStr4': 'route de liason 4',
-    'VerbindStr6': 'route de liason 6',   
-}
-
-streets_en = {
-    'Autostr': 'freeway',
-    'NebenStr3': 'surface streets 3',
-    'NebenStr6': 'surface streets 3 6',
-    'HauptStrAB6': 'inter regional 6',
-    'HauptStrAB4': 'inter regional 4',
-    'Fahrstraes': 'bridle path',
-    'Fussweg': 'pedestrian trail',
-    'Autobahn': 'freeway',
-    'Autob_Ri': 'freeway',
-    'VerbindStr4': 'intra regional 4',
-    'VerbindStr6': 'intra regional 6',   
-}
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    The streets at one survey location:

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    slugattribute_typeattributelength
    638parc-des-pierrettesstreetsAutobahn1685
    639parc-des-pierrettesstreetsFahrstraes1046
    640parc-des-pierrettesstreetsFussweg3257
    641parc-des-pierrettesstreetsHauptStrAB62918
    642parc-des-pierrettesstreetsNebenStr32850
    643parc-des-pierrettesstreetsVerbindStr467
    644parc-des-pierrettesstreetsVerbindStr62864
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    Rivers: intersection, size and class#

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    This requires the 1’500 m buffer created at the begininng and the rivers layer and the lakes layer.

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    intersection, size and class#

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    1. Create a points layer of the intersection of rivers to lakes

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      • Keep only points that are labeled as river (fluss, fluss_u)

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      • Use the attribute table to select the points

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    2. Overlay the 1 500 m buffer on the new layer and collect all the intersections within each buffer

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      • export to .csv

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    3. Check for intersections that do not have lake name

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      • not all lakes and rivers have names in the layer

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      • find the correct name for the lake and add it to the record

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      • replace river names with nan value with “no name”

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    distance to intersection#

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    Note: the intersection points layer needs to be available

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    1. Using the hub lines tool in QGIS draw lines from survey location to intersect location

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      • Limit the distance to the radius of the buffer

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      • join on the slug field in both layers

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      • eliminate duplicates

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      • calculate the length of the line with $length in field calculator of the attribute table

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      • export to .csv

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    2. Identify locations (slugs) that are missing either the river_name or lake

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      • use the previous results (intersection, size and class) to fill in the missing values

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      • check that slugs not in the distance matrix are truly without intersections

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    sluglakeriver_namesizeclassdistanceattribute_type
    72parc-des-pierrettesLe LémanLa Mèbre88333river intersection
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    Author: hammerdirt-analyst
 
 conda environment: cantonal_report
 
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    ---------------------------------------------------------------------------
-ModuleNotFoundError                       Traceback (most recent call last)
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-      3 from langchain_core.runnables import RunnablePassthrough
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    Canton Bern Lakes#

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    Vital Statistics#

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    Political boundaries

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    The data analysis focuses on survey locations within the administrative boundaries of the canton of Bern. Specifically, the surveys span from November 15, 2015, to December 31, 2021. The study includes 19 survey locations distributed across 13 cities, all within Bern. The cities surveyed are Unterseen, Biel/Bienne, Vinelz, Thun, Brienz (BE), Spiez, Lüscherz, Nidau, Beatenberg, Ligerz, Bönigen, Gals, and Erlach. Additionally, there is a single survey area identified as Aare. The surveyed regions are confined to the canton of Bern, with no other cantons included in the study.

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    Features of interest

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    The survey data under analysis for the period from November 15, 2015, to December 31, 2021, covers three lakes in the canton of Bern. These lakes are Thunersee, Bielersee, and Brienzersee. No rivers or parks are included in this study. The analysis encompasses 19 survey locations across 13 cities within the canton of Bern, specifically focusing on Unterseen, Biel/Bienne, Vinelz, Thun, Brienz (BE), Spiez, Lüscherz, Nidau, Beatenberg, Ligerz, Bönigen, Gals, and Erlach. Additionally, there is a single survey area identified as Aare.

    -_images/622af51781c6949bc323c13320bb41b0b1cb414c19463d829a972f90ad257585.png -
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    Summary of survey results

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    The beach-litter survey conducted in Bern between November 15, 2015, and December 31, 2021, revealed an average of approximately 0.71 objects per meter. The data, collected from 74 samples, indicated significant variability in litter density. The 90% interval, which spans from the 5th to the 95th percentile, ranges from 0.02 objects per meter to 2.598 objects per meter. This interval reflects a broad distribution of litter densities across the surveyed areas. The standard deviation of 0.912 further underscores the variability in the litter data, with a maximum recorded density of 4.04 objects per meter.

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    Inventory and Most Common

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    The beach-litter survey conducted in Bern from January 26, 2020, to April 8, 2021, identified a total of 2,180 objects across 74 samples. The two most common categories of litter found were cigarette filters (code G27) and food wrappers for candy and snacks (code G30). Cigarette filters were the predominant type of debris, with a total quantity of 1,563 items, which accounts for approximately 71.7% of the total debris. The average density for cigarette filters was 0.475676 objects per meter, with a fail rate of 83.78%. The second most common category was food wrappers, with 565 items making up about 25.9% of the overall count. The average density for food wrappers was 0.21527 objects per meter, and the fail rate was 82.43%. These two categories alone comprised over 97% of the total debris collected during the survey.

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    code

    quantity

    pcs/m

    % of total

    sample_id

    fails

    rate

    object

    G27

    1,563

    0.475676

    71.7%

    74

    62

    83.78%

    Cigarette filters

    G30

    565

    0.21527

    25.9%

    74

    61

    82.43%

    Food wrappers; candy, snacks

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     Markdown(sampling_stratification['answer'])
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    Sampling stratification

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    The sampling stratification quantifies the proportion of samples collected based on the proportion of the buffer zone dedicated to specific land use features. Each survey location is surrounded by a buffer zone with a radius of 1,500 meters, and this zone includes various land-use features, each occupying a certain proportion (0-100%) of the buffer zone. The stratification helps understand how the distribution of land-use features within the buffer zone influences the sampling process.

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    Buffer Zone Proportions and Sampling Distribution:

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    • 0-20% Buffer Zone:

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      • Buildings: 31% of samples were collected where 0-20% of the buffer zone is dedicated to buildings.

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      • Wetlands: All samples (100%) were collected from locations with wetlands within this buffer zone.

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      • Forest: 24% of samples were from locations where 0-20% of the buffer had forest presence.

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      • Public Services, Recreation, Undefined Features: All samples noted these features at this level.

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      • Streets: 45% of the samples were associated with streets.

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      • Vineyards and Orchards: All samples (100%) were located within this buffer zone.

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    • 20-40% Buffer Zone:

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      • Buildings: 38% of samples were collected from locations with buildings.

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      • Wetlands: No samples were taken from wetlands.

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      • Forest: 66% of the samples represented forested areas.

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      • Public Services and Recreation: No samples were collected.

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      • Undefined Features: 8% of samples were associated with undefined features.

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      • Streets: 8% of samples were related to streets.

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    • 40-60% Buffer Zone:

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      • Buildings: 22% of samples were dedicated to buildings.

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      • Wetlands: No samples were taken from wetlands.

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      • Forest: Only 9% of samples represented forest.

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      • Public Services: No samples were recorded.

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      • Undefined Features: 57% of samples fell into this category.

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      • Streets: 19% of samples indicated the presence of streets.

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    • 60-80% Buffer Zone:

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      • Buildings: 7% of samples were linked to buildings.

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      • Wetlands: No samples were taken from wetlands.

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      • Forest: No samples were noted.

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      • Undefined Features: 0% of samples were associated with undefined features.

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      • Streets: 20% of samples were related to streets.

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    • 80-100% Buffer Zone:

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      • Buildings: Only 3% of samples were attributed to buildings.

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      • Wetlands and Forest: No samples were taken.

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      • Public Services, Recreation, Undefined Features, Streets, Vineyards, and Orchards: No contributions in this buffer zone.

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    This stratification allows for grouping locations according to the topographical features present within the buffer zone and helps in understanding how the observed litter density changes based on these land use features.

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    Sampling stratification

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    The sampling stratification quantifies the proportion of samples collected based on the proportion of the buffer zone dedicated to specific land use features. Each survey location is surrounded by a buffer zone with a radius of 1,500 meters, and this zone includes various land-use features, each occupying a certain proportion (0-100%) of the buffer zone. The stratification helps understand how the distribution of land-use features within the buffer zone influences the sampling process.

    -

    Buffer Zone Proportions and Sampling Distribution:

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    • 0-20% Buffer Zone:

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      • Buildings: 31% of samples were collected where 0-20% of the buffer zone is dedicated to buildings.

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      • Wetlands: All samples (100%) were collected from locations with wetlands within this buffer zone.

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      • Forest: 24% of samples were from locations where 0-20% of the buffer had forest presence.

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      • Public Services, Recreation, Undefined Features: All samples noted these features at this level.

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      • Streets: 45% of the samples were associated with streets.

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      • Vineyards and Orchards: All samples (100%) were located within this buffer zone.

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    • 20-40% Buffer Zone:

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      • Buildings: 38% of samples were collected from locations with buildings.

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      • Wetlands: No samples were taken from wetlands.

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      • Forest: 66% of the samples represented forested areas.

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      • Public Services and Recreation: No samples were collected.

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      • Undefined Features: 8% of samples were associated with undefined features.

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      • Streets: 8% of samples were related to streets.

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    • 40-60% Buffer Zone:

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      • Buildings: 22% of samples were dedicated to buildings.

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      • Wetlands: No samples were taken from wetlands.

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      • Forest: Only 9% of samples represented forest.

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      • Public Services: No samples were recorded.

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      • Undefined Features: 57% of samples fell into this category.

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      • Streets: 19% of samples indicated the presence of streets.

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    • 60-80% Buffer Zone:

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      • Buildings: 7% of samples were linked to buildings.

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      • Wetlands: No samples were taken from wetlands.

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      • Forest: No samples were noted.

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      • Undefined Features: 0% of samples were associated with undefined features.

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      • Streets: 20% of samples were related to streets.

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    • 80-100% Buffer Zone:

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      • Buildings: Only 3% of samples were attributed to buildings.

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      • Wetlands and Forest: No samples were taken.

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      • Public Services, Recreation, Undefined Features, Streets, Vineyards, and Orchards: No contributions in this buffer zone.

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    This stratification allows for grouping locations according to the topographical features present within the buffer zone and helps in understanding how the observed litter density changes based on these land use features.

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    requesting = 'Please summarize the following sections:'
-sections_to_summarize = 'Topography and trash density Bern 2015-11-15 2021-12-31: The changes in the observed litter density and the changes in land use'
-instructions = "Provide a narrative paragraph, and the table of values. note where the pcs/m is highest and lowest. Please label your response '### Topography and trash density'"
-instructions = "".join(instructions)
-sampling_stratification = data_chait.invoke({'input': f'{requesting} {sections_to_summarize}\n\nInstructions\n\n{instructions}'})
-glue('stratification-pcs-m', Markdown(sampling_stratification['answer']), display=False)
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    Topography and trash density

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    From the beach-litter survey data, we observe how litter density varies based on different topographical features and land-use categories. The data is categorized into five indices, each reflecting different average pieces of trash per meter (pcs/m) for various land-use types. In the first index, the highest litter density is observed in undefined areas with 1.14731 pcs/m, while the lowest is in streets with 0.350606 pcs/m. In the second index, undefined areas again show the highest density at 1.175 pcs/m, whereas wetlands, public services, recreation, vineyards, and orchards report no litter (0 pcs/m). The third index reveals buildings with the highest density at 1.83188 pcs/m and wetlands, public services, recreation, vineyards, and orchards again showing no litter. For the fourth index, streets exhibit the highest litter density at 1.942 pcs/m, with several categories including wetlands, forest, public services, recreation, vineyards, and orchards showing no litter. Lastly, in the fifth index, streets have the highest density at 0.5 pcs/m, with no litter observed in wetlands, forest, public services, recreation, vineyards, and orchards. This data highlights significant variability in litter density across different land-use types, with undefined areas and streets often showing higher litter densities.

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    buildings

    wetlands

    forest

    public-services

    recreation

    undefined

    streets

    vineyards

    orchards

    1

    0.608261

    0.710946

    0.359444

    0.710946

    0.710946

    1.14731

    0.350606

    0.710946

    0.710946

    2

    0.235714

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    0.907959

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    1.175

    0.681667

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    1.83188

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    0.235714

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    0

    0.374524

    0.344286

    0

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    0.414

    0

    0

    0

    0

    0

    1.942

    0

    0

    5

    0.32

    0

    0

    0

    0

    0

    0.5

    0

    0

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    Cluster Analysis

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    The cluster analysis of beach-litter survey data in Bern, spanning from November 15, 2015, to December 31, 2021, reveals notable differences in both cluster composition and average litter density per cluster. The survey locations were grouped using K-Means clustering, with the optimal number of clusters determined using the elbow method. Each cluster represents a unique mix of land use proportions and average litter density.

    -

    Cluster 0 is characterized by a high proportion of buildings (59.1%) and streets (36.4%), with a moderate amount of forest (22%) and undefined areas (18.9%). This cluster also has the highest average density of personal use litter, with 1.23192 objects per meter of beach.

    -

    Cluster 1, on the other hand, has a significant proportion of forest (53.7%) and undefined areas (24.5%), with fewer buildings (15.9%) and streets (8.5%). This cluster has the lowest average density of personal use litter, at 0.147857 objects per meter of beach.

    -

    Cluster 2 is dominated by undefined areas (54.1%) and streets (49.7%), with moderate proportions of buildings (30.9%) and a small amount of forest (10.7%). The average density of personal use litter here is 0.492941 objects per meter of beach.

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    Cluster 3 has a high proportion of undefined areas (55%) and a notable amount of forest (27.1%), with minimal buildings (4.7%) and no streets. This cluster shows an average personal use litter density of 0.695833 objects per meter of beach.

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    Finally, Cluster 4 is predominantly composed of buildings (68.2%) and streets (25.2%), with some forest (15.3%) and undefined areas (14.9%). The average density of personal use litter in this cluster is 0.356 objects per meter of beach.

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    These differences highlight the varying impact of land use on litter density, with urbanized areas (high buildings and streets) generally showing higher litter densities compared to more natural or undefined areas.

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    Public Services

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    Personal Use Litter Density (objects/meter)

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    0.356

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    Cluster analysis and land-use#

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    1. Does the average density per cluster, support any conclusions that could be drawn given the land-use profile?

      2. -

    2. Is their any possible correlations?

      3. -
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    Certainly!

    -

    The average density per cluster does indeed support some conclusions related to the land-use profiles in the region of Bern. For example, Cluster 0, which exhibits a high proportion of buildings (59.1%) and streets (36.39%), has the highest average density of personal use litter at 1.23192 objects per meter of beach. This suggests a correlation between high building density and litter presence, likely due to increased human activity. Conversely, Cluster 1, with a significant proportion of forest (53.7%) and lower building density (15.9%), has a much lower average litter density of 0.147857 objects per meter of beach, indicating that areas with more natural land cover such as forests tend to have less litter. Cluster 2 also supports this observation; with relatively high street presence (49.71%) and a lower forest proportion (10.7%), the average litter density is moderate at 0.492941 objects per meter. This suggests that street areas, which facilitate human transport and activity, may contribute to higher litter densities. Clusters that have high proportions of undefined land use and low building presence, such as Cluster 3, also show a moderate average litter density of 0.695833 objects per meter. Finally, Cluster 4, which features the highest building proportion (68.2%) and moderate street presence (25.18%), has a relatively lower average litter density of 0.356 objects per meter, possibly indicating areas where urban management strategies might mitigate litter despite high human activity. Overall, these correlations imply that higher land use for buildings and streets is associated with increased beach litter, while natural land covers like forests tend to correlate with lower litter densities.

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    Regression Analysis#

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    Summary of Regression Methods

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    The regression analysis conducted between November 15, 2015, and December 31, 2021, evaluated various linear and ensemble regression models using land-use features identified in the land-use profile. The models tested included Linear Regression, Random Forest Regression, Gradient Boosting Regression, and Theil-Sen Regression, with subsequent application of Bagging and Voting schemes on the model exhibiting the lowest R² value. The results indicated that the Gradient Boosting Regression model achieved the highest R² value of 0.440842 and the lowest mean squared error (MSE) of 0.347197, making it the most effective model in the analysis. The performance of other models was as follows: Linear Regression (R² = 0.322546, MSE = 0.420651), Random Forest Regression (R² = 0.260129, MSE = 0.459407), Theil-Sen Regressor (R² = 0.373587, MSE = 0.388957), Bagging with Gradient Boosting Regression (R² = 0.39959, MSE = 0.372812), and the Voting model (R² = 0.381679, MSE = 0.383933). The overall results underscore the superior predictive power of the Gradient Boosting Regression model, yet the R² values suggest moderate accuracy. Consequently, while the Gradient Boosting Regression model demonstrates the most promise among the tested models, the moderate R² values suggest that predictions should be treated with cautious optimism, recognizing that the models may not capture the full complexity of the data.

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    Forecasts for 2025

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    Grid Forecast Overview

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    A grid forecast is a technique used in Bayesian inference to estimate the posterior distribution of parameters. This method involves discretizing the parameter space into a grid and evaluating the posterior probability at each point. It is particularly useful when the posterior distribution lacks a closed-form solution and when the parameter space is relatively low-dimensional, making a grid search feasible.

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    Forecast Methods

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    1. Weighted Prior Forecast:

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      • This method uses a weighted combination of survey results from locations similar to the likelihood.

        • -

      • The expected average sample total is 2.0732.

        • -

      • The 90% Highest Density Interval (HDI) ranges from 0 to 12.42.

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      • Percentile rankings are as follows: 5th percentile is 0.06, 25th percentile is 0.25, 50th percentile (median) is 0.70, 75th percentile is 2.195, and 95th percentile is 12.42.

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      • The maximum value predicted by the model is 13.66.

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      2. -

    2. Observed 99th Percentile Forecast:

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      • This method utilizes samples taken from the same location but prior to the specified date range.

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      • The expected survey results indicate an average value of 0.7114.

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      • The 90% HDI ranges from 0 to 2.46.

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      • Percentile rankings are as follows: 5th percentile is 0, 25th percentile is 0.1375, median is 0.285, 75th percentile is 0.855, and 95th percentile is 2.1845.

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      • The maximum value predicted by the model is 3.78.

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      3. -
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    Estimation of Probable Range of Values

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    Given the results from the two forecast methods, we can estimate the probable range of values for 2025:

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      -

    • Based on the Weighted Prior Forecast, the sample total might fall between 0 (minimum) and 12.42 (90% HDI max), with a predicted maximum possible value of 13.66.

      • -

    • Based on the Observed 99th Percentile Forecast, the sample total might fall between 0 (minimum) and 2.46 (90% HDI max), with a predicted maximum possible value of 3.78.

      • -
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    Therefore, a conservative probable range of values for the sample total in 2025 would be between 0 and 12.42, considering the upper limits of the 90% HDIs from both forecast methods.

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    Grid forecast class

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    Grid forecast class#

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    The grid forecaster refers to the methods defined in gridforecast.py. The main purpose of the grid forecaster is to implement estimate the probability that a survey result y from a collection of survey results Y will exceed a value x on the grid X from 0 - max(X) for every x spaced 0.1, where max(X) is defined by Y. This is called a grid approximation, in this case we use a Bayesien framework and implement multinomila-Dirichlet conjugate to estimate the probabilities on each point of the grid. The complete method is a defined in grid approximation.

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    The grid forecast for any two arrays can be initiated by calling gridforecast.MulitnomialDirichlet and providing two pd.series of float values. However, for reporting we use the grid forecast to supplement the SurveyReport and the LandUseReport.

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    Note

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    The grid forecast allows us to estimate the probability of a set of survey results given another set of survey results. Therefore, to interpret the results of a grid forecast the relationship between the two arrays must be well understood. Our focus has been on the structural and geographic similarities of the survey locations.

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    Example creating reports and forecasts

    -
    # collecting the default data
-data = session_config.collect_survey_data()
-
-# the likelihood: the dates of the most recent samples
-recent_dates = {'start':'2020-01-01', 'end':'2021-12-31'}
-# the prior: the dates prior to the most recent samples
-prior_dates = {'start':'2015-11-15', 'end':'2019-12-31'}
-# the region of interest
-canton = 'Vaud'
-
-# the search parameters for the prior and likelihood
-likelihood_params = {'canton':canton, 'date_range':recent_dates}
-prior_params = {'canton':canton, 'date_range':prior_dates}
-
-# verify the parameters exist in the data
-# checking the parameters will verify that the requested data
-# exists. If the query is possible it is executed and the value of
-# comments='ok', if not empty arrays are returned with the message
-# 'no survey results found'. The method returns the query data, a list
-# of the sample locations and the comment.
-likelihood_data, likelihood_locations, likelihood_comments = check_params(likelihood_params, data, logger)
-prior_data, prior_locations, prior_comments = check_params(prior_params, data, logger)
-
-# if there is data for both the likelihood and the prior
-# make a survey report and a land use report for both sets of data
-likelihood_report, likelihood_land_use = make_report_objects(likelihood_data)
-prior_report, prior_land_use = make_report_objects(likelihood_data)
-
-# make forecast from all the available liklihood data
-forecast_object = MulitnomialDirichlet('comb', prior_report.sample_results['pcs/m'], likelihood_report.sample_results['pcs/m'], logger)
-
-# make forecast limiting the likelihood to the 99the percentile
-posterior_counts, comments = posterior_dirichlet_counts(lkl, prr, max_range=0.99)
-
-# forecasts from all the data
-forecasted_samples = forecast_object.sample_posterior()
-forecasted_summary = forecast_object.get_descriptive_statistics()
-
-# forecasts limited to the 99th percentile
-sample_values_99, posterior_99, summary_99 = gfcast.dirichlet_posterior(posterior_counts)
-
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    Using a weighted prior

    -

    To predict density given similar locations use the land-use report from a set survey results that does not contain any of the survey locations from the likelihood. The default method is to also only select values that have the same use case ie. parks, lakes or rivers.

    -
    # determine the proportion of each land-use feature in the likelihood
-weights = land_use_weights(likelihood_land_use, session_config.feature_variables)
-
-# from the pool of available data select records that are not included in the likelihood
-# in this case we eliminate the canton of interest, limit the date to the end date of the prior
-# and create a survey report and land use report for *the other prior data*
-other_data = data[(data.canton != canton)&(data['date'] <= prior_dates['end'])].copy()
-other_prior_report, other_prior_land_use = gfcast.make_report_objects(other_prior_data)
-
-# using the weights from the likelihood and the other_prior_land_use
-other_prior_data, prior_weights = select_prior_data_by_feature_weight(other_prior_land_use, weights, session_config.feature_variables)
-posterior_by_weight, weighted_comments = posterior_dirichlet_counts(likelihood_data, g['pcs/m'].values)
-posterior_sample_values, weighted_dist, weighted_summary = dirichlet_posterior(posterior_by_weight)
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    Grid forecaster methods#

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    The gridforecast.MulitnomialDirichlet is a class in gridforecast.py the built in methods are designed to generate forecasts under a variety of scenarios and provide the basic elements to evaluate those forecasts. In the examples below consider the forecast_object created in the previous example.

    -

    list of methods

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    1. MultinomialDirichlet

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      • compute_grid

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      • compute_counts

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      • compute_posterior_params

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      • sample_posterior

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      • compute_percentiles

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      • compute_hdi

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      • compute_expected_average

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      • probability_of_x

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      • get_descriptive_statistics

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    2. select_prior_data_by_feature_weight

      3. -

    3. posterior_dirichlet_counts

      4. -

    4. dirichlet_posterior

      5. -
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    -

    The grid size#

    -

    The grid size for each combination is based on the maximum value of either the likelihood or the prior.

    -
    def compute_grid(self):
-    max_value = round(max(self.prior_data.max(), self.likelihood_data.max()), 1)
-    return np.arange(0, max_value, 0.01)
-
-forecast_object.compute_grid()
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    array([0.000e+00, 1.000e-02, 2.000e-02, ..., 7.707e+01, 7.708e+01,
-       7.709e+01])
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    The counts#

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    The number of times that a survey result was either equal to zero or any other place on the grid can be accessed with forecastobject.prior or forecastobject.likelihood. This returns the value of np.histogram

    -
    def compute_counts(self, data):
-    counts, _ = np.histogram(data, bins=np.append(self.grid, self.grid[-1] + 0.1))
-    return counts
-
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-forecastobject.compute_counts(forecast_object.prior_data)
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    -
    array([0, 0, 0, ..., 0, 0, 1])
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    The posterior parameters#

    -

    The parameters for the Dirichlet posterior. This is the sum of forecastobject.prior and forecastobject.likelihood. Zero values of the sum are replaced with 0.01.

    -
    def compute_posterior_params(self):
-    post_counts = self.likelihood + self.prior
-    post_counts = np.where(post_counts > 0, post_counts, 0.01)
-    return post_counts
-    
-forecastobject.compute_posterior_params()
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    array([0.01, 0.01, 0.01, ..., 0.01, 0.01, 1.  ])
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    Sample the posterior distribution#

    -

    Sample the posterior distribution. Returns a set of expected survey values given the likelihood and the prior.

    -
    def sample_posterior(self, num_samples=100):
-    adist_samples = self.posterior_dist.rvs(1)[0]
-    posterior_samples = multinomial.rvs(num_samples, adist_samples)
-    sample_values = np.repeat(self.grid, posterior_samples)
-    return sample_values
-    
-forecast_object.sample_posterior()
-
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    array([ 0.35,  0.47,  0.47,  0.47,  0.55,  0.75,  0.92,  0.99,  1.  ,
-        1.  ,  1.06,  1.89,  1.89,  1.99,  2.21,  2.23,  2.29,  2.32,
-        2.4 ,  2.56,  2.6 ,  2.61,  2.61,  2.64,  2.64,  2.68,  2.7 ,
-        2.74,  2.86,  3.19,  3.42,  3.46,  3.46,  4.17,  4.2 ,  4.55,
-        4.67,  4.67,  4.67,  4.74,  4.74,  4.76,  4.93,  5.43,  5.75,
-        5.87,  6.04,  6.04,  6.59,  6.83,  6.83,  7.04,  7.04,  7.85,
-        7.85,  8.19,  8.55,  8.55,  8.55,  8.55,  8.92,  9.05, 10.08,
-       10.08, 11.21, 13.6 , 14.61, 15.37, 16.36, 17.05, 17.4 , 17.54,
-       21.16, 23.18, 26.11, 26.41, 26.82, 27.33, 31.6 , 33.63, 38.  ,
-       39.84, 41.37, 47.28, 47.28, 47.28, 47.28, 49.68, 50.06, 50.6 ,
-       51.46, 51.46, 55.83, 57.71, 57.71, 65.91, 67.34, 69.75, 73.5 ,
-       73.5 ])
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    The 90% interval of the predictions#

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    The 90% interval of the predictions is set to the following percentiles: [5, 25, 50, 75, 95]

    -
    def compute_percentiles(self, percentiles=[5, 25, 50, 75, 95]):
-    samples = self.sample_posterior(1000)
-    return np.percentile(samples, percentiles)
-
-forecast_object.compute_percentiles()
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    array([ 0.75  ,  2.7   ,  5.36  , 13.85  , 62.3315])
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    The 90% HDI#

    -

    The 90% highest density interval

    -
    def compute_hdi(self, credibility_mass=0.95):
-    samples = self.sample_posterior(1000)
-    sorted_samples = np.sort(samples)
-    ci_idx_inc = int(np.floor(credibility_mass * len(sorted_samples)))
-    n_cis = len(sorted_samples) - ci_idx_inc
-    ci_width = sorted_samples[ci_idx_inc:] - sorted_samples[:n_cis]
-    min_ci_width_idx = np.argmin(ci_width)
-    hdi_min = sorted_samples[min_ci_width_idx]
-    hdi_max = sorted_samples[min_ci_width_idx + ci_idx_inc]
-    
-    return hdi_min, hdi_max
-    
-forecast_object.compute_hdi()
-
    -
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    -
    -
    (np.float64(0.1), np.float64(63.58))
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    The expected mean#

    -

    The 90% highest density interval

    -
    forecast_object.compute_hdi()
-
    -
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    -
    -
    array([3.26850793e-05, 3.26850793e-05, 3.26850793e-05, ...,
-       3.26850793e-05, 3.26850793e-05, 3.26850793e-03])
-
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    The probability of x#

    -

    The chance that a result will exceed a given value

    -
    def probability_of_x(self, x):
-    if x < 0 or x > self.grid.max():
-        raise ValueError("x must be within the range of the grid.")
-
-    posterior_samples = self.posterior_dist.rvs(1000)
-    mp = np.mean(posterior_samples, axis=0)
-    bin_index = np.digitize([x], self.grid)
-    
-    return mp, bin_index, posterior_samples
-
-# in this case we are asking what is the chance of finding
-# at least one piece per meter
-a, b, c = forecast_object.probability_of_x(1)
-sum(a[b[0]:])
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    np.float64(0.9290825128991368)
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    The descriptive statistices#

    -

    The average, hdi and the 90% range of the expected distribution

    -
    forecast_object.get_descriptive_statistics()
-
    -
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    -
    {'code': 'comb',
- 'average': np.float64(11.853500000000002),
- 'hdi': (np.float64(0.1), np.float64(58.730000000000004)),
- 'range': array([ 0.9895,  2.57  ,  5.59  , 18.42  , 61.5595]),
- 'max_observed': np.float64(77.1)}
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    Select prior data by feature weight#

    -

    The average, hdi and the 90% range of the expected distribution

    -
    # get the land use weights from the observations of interest
-weights = land_use_weights(likelihood_land_use, feature_variables)
-
-# prior data does not include locations in canton
-# the surveys are limited to the prior date as defined
-other_data = data[(data.canton != canton)&(data['date'] <= prior_dates['end'])].copy()
-other_report, landuse_from_other = gfcast.make_report_objects(other_data)
-
-# use the land use object from the other data
-# and the weights from the likelihood to draw random
-# samples from the other data
-the_random_samples, w = select_prior_data_by_feature_weight(landuse_from_other, weights, feature_variables)
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    sample_idlocationdatequantitypcs/mpublic servicesstreetsorchardsvineyardsbuildingsforestundefinedbuildings_public services
    0('sihl_zuerich_eichenbergerd', '2018-03-30')sihl_zuerich_eichenbergerd2018-03-30170.3512112221
    1('emme_biberist_jennim', '2017-08-07')emme_biberist_jennim2017-08-07291.9511113221
    2('zuerichsee_staefa_hennm', '2017-05-22')zuerichsee_staefa_hennm2017-05-22655.9011112131
    3('langete_langenthal_geiserm', '2018-03-30')langete_langenthal_geiserm2018-03-30221.5512113121
    4('chriesbach_duebendorf_schneidera', '2018-02-...chriesbach_duebendorf_schneidera2018-02-05991.9412114111
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    Posterior Dirichlet counts#

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    The posterior distribution from the likelihood and the weighted prior.

    -
    # get the land use weights from the observations of interest
-likelihood = likelihood_report.sample_results['pcs/m'].values
-prior = the_random_samples['pcs/m'].values
-posterior_by_weight, comments = posterior_dirichlet_counts(likelihood, prior)
-sample_values, adist, summary = dirichlet_posterior(posterior_by_weight)
-
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    {'range': array([0.3 , 0.9 , 1.85, 4.7 , 9.18]),
- 'nsamples': 100,
- 'average': np.float64(3.5840000000000005),
- 'hdi': (np.float64(0.1), np.float64(10.700000000000001))}
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    Data and reporting

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    Situation and solutions

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    Methods and classes

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    Example reports

    Annex

    diff --git a/docs/haystackagents.html b/docs/haystackagents.html deleted file mode 100644 index 1b5c376..0000000 --- a/docs/haystackagents.html +++ /dev/null @@ -1,1385 +0,0 @@ - - - - - - - - - - - Haystack agents — Project 2025 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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    Haystack agents

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    Haystack agents#

    -
    -
    -
    from dotenv import load_dotenv
-from IPython.display import Markdown, display
-import os
-
-           
-
    -
    -
    -
    -
    -
    -
    import os
-from haystack import Pipeline, Document
-from haystack.utils import Secret
-from haystack.document_stores.in_memory import InMemoryDocumentStore
-from haystack.components.retrievers.in_memory import InMemoryBM25Retriever
-from haystack.components.generators import OpenAIGenerator
-from haystack.components.builders.answer_builder import AnswerBuilder
-from haystack.components.builders.prompt_builder import PromptBuilder
-
-from haystack.components.converters import MarkdownToDocument
-from haystack.components.preprocessors import DocumentCleaner
-from haystack.components.preprocessors import DocumentSplitter
-from haystack.components.writers import DocumentWriter
-from haystack.components.retrievers.filter_retriever import FilterRetriever
-
-from haystack.components.converters.pypdf import PyPDFToDocument
-from haystack_integrations.document_stores.chroma import ChromaDocumentStore
-from haystack_integrations.components.retrievers.chroma import ChromaQueryTextRetriever
-from haystack import component
-
-load_dotenv()
-api_key = os.getenv('OPENAI_API_KEY')
-model = 'gpt-4o-mini'
-
-def print_results(results, reply_object='llm'):
-    return Markdown(result[reply_object]['replies'][0])   
-
-document_store = InMemoryDocumentStore()
-
    -
    -
    -
    -
    /home/roger/anaconda3/envs/haystack2/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
-  from .autonotebook import tqdm as notebook_tqdm
-
    -
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    -
    -
    -

    In memory vector store : Report results#

    -

    Retrieving report results from an in memory vector store, using the FilterRetriever on the metadata

    -
    -

    Markdown documents#

    -
    -
    -
    help(InMemoryDocumentStore)
-
    -
    -
    -
    -
    Help on class InMemoryDocumentStore in module haystack.document_stores.in_memory.document_store:
-
-class InMemoryDocumentStore(builtins.object)
- |  InMemoryDocumentStore(bm25_tokenization_regex: str = '(?u)\\b\\w\\w+\\b', bm25_algorithm: Literal['BM25Okapi', 'BM25L', 'BM25Plus'] = 'BM25L', bm25_parameters: Optional[Dict] = None, embedding_similarity_function: Literal['dot_product', 'cosine'] = 'dot_product', index: Optional[str] = None)
- |
- |  Stores data in-memory. It's ephemeral and cannot be saved to disk.
- |
- |  Methods defined here:
- |
- |  __init__(self, bm25_tokenization_regex: str = '(?u)\\b\\w\\w+\\b', bm25_algorithm: Literal['BM25Okapi', 'BM25L', 'BM25Plus'] = 'BM25L', bm25_parameters: Optional[Dict] = None, embedding_similarity_function: Literal['dot_product', 'cosine'] = 'dot_product', index: Optional[str] = None)
- |      Initializes the DocumentStore.
- |
- |      :param bm25_tokenization_regex: The regular expression used to tokenize the text for BM25 retrieval.
- |      :param bm25_algorithm: The BM25 algorithm to use. One of "BM25Okapi", "BM25L", or "BM25Plus".
- |      :param bm25_parameters: Parameters for BM25 implementation in a dictionary format.
- |          For example: {'k1':1.5, 'b':0.75, 'epsilon':0.25}
- |          You can learn more about these parameters by visiting https://github.com/dorianbrown/rank_bm25.
- |      :param embedding_similarity_function: The similarity function used to compare Documents embeddings.
- |          One of "dot_product" (default) or "cosine". To choose the most appropriate function, look for information
- |          about your embedding model.
- |      :param index: A specific index to store the documents. If not specified, a random UUID is used.
- |          Using the same index allows you to store documents across multiple InMemoryDocumentStore instances.
- |
- |  bm25_retrieval(self, query: str, filters: Optional[Dict[str, Any]] = None, top_k: int = 10, scale_score: bool = False) -> List[haystack.dataclasses.document.Document]
- |      Retrieves documents that are most relevant to the query using BM25 algorithm.
- |
- |      :param query: The query string.
- |      :param filters: A dictionary with filters to narrow down the search space.
- |      :param top_k: The number of top documents to retrieve. Default is 10.
- |      :param scale_score: Whether to scale the scores of the retrieved documents. Default is False.
- |      :returns: A list of the top_k documents most relevant to the query.
- |
- |  count_documents(self) -> int
- |      Returns the number of how many documents are present in the DocumentStore.
- |
- |  delete_documents(self, document_ids: List[str]) -> None
- |      Deletes all documents with matching document_ids from the DocumentStore.
- |
- |      :param document_ids: The object_ids to delete.
- |
- |  embedding_retrieval(self, query_embedding: List[float], filters: Optional[Dict[str, Any]] = None, top_k: int = 10, scale_score: bool = False, return_embedding: bool = False) -> List[haystack.dataclasses.document.Document]
- |      Retrieves documents that are most similar to the query embedding using a vector similarity metric.
- |
- |      :param query_embedding: Embedding of the query.
- |      :param filters: A dictionary with filters to narrow down the search space.
- |      :param top_k: The number of top documents to retrieve. Default is 10.
- |      :param scale_score: Whether to scale the scores of the retrieved Documents. Default is False.
- |      :param return_embedding: Whether to return the embedding of the retrieved Documents. Default is False.
- |      :returns: A list of the top_k documents most relevant to the query.
- |
- |  filter_documents(self, filters: Optional[Dict[str, Any]] = None) -> List[haystack.dataclasses.document.Document]
- |      Returns the documents that match the filters provided.
- |
- |      For a detailed specification of the filters, refer to the DocumentStore.filter_documents() protocol
- |      documentation.
- |
- |      :param filters: The filters to apply to the document list.
- |      :returns: A list of Documents that match the given filters.
- |
- |  save_to_disk(self, path: str) -> None
- |      Write the database and its' data to disk as a JSON file.
- |
- |      :param path: The path to the JSON file.
- |
- |  to_dict(self) -> Dict[str, Any]
- |      Serializes the component to a dictionary.
- |
- |      :returns:
- |          Dictionary with serialized data.
- |
- |  write_documents(self, documents: List[haystack.dataclasses.document.Document], policy: haystack.document_stores.types.policy.DuplicatePolicy = <DuplicatePolicy.NONE: 'none'>) -> int
- |      Refer to the DocumentStore.write_documents() protocol documentation.
- |
- |      If `policy` is set to `DuplicatePolicy.NONE` defaults to `DuplicatePolicy.FAIL`.
- |
- |  ----------------------------------------------------------------------
- |  Class methods defined here:
- |
- |  from_dict(data: Dict[str, Any]) -> 'InMemoryDocumentStore'
- |      Deserializes the component from a dictionary.
- |
- |      :param data:
- |          The dictionary to deserialize from.
- |      :returns:
- |          The deserialized component.
- |
- |  load_from_disk(path: str) -> 'InMemoryDocumentStore'
- |      Load the database and its' data from disk as a JSON file.
- |
- |      :param path: The path to the JSON file.
- |      :returns: The loaded InMemoryDocumentStore.
- |
- |  ----------------------------------------------------------------------
- |  Readonly properties defined here:
- |
- |  storage
- |      Utility property that returns the storage used by this instance of InMemoryDocumentStore.
- |
- |  ----------------------------------------------------------------------
- |  Data descriptors defined here:
- |
- |  __dict__
- |      dictionary for instance variables
- |
- |  __weakref__
- |      list of weak references to the object
-
    -
    -
    -
    -
    -
    -
    # from haystack import Pipeline
-# from haystack.document_stores.in_memory import InMemoryDocumentStore
-
-model = 'gpt-4o-mini'
-report_document_store = InMemoryDocumentStore()
-
-document_pipeline = Pipeline()
-document_pipeline.add_component("converter", MarkdownToDocument())
-document_pipeline.add_component("cleaner", DocumentCleaner())
-document_pipeline.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=10))
-document_pipeline.add_component("writer", DocumentWriter(document_store=report_document_store))
-document_pipeline.connect("converter", "cleaner")
-document_pipeline.connect("cleaner", "splitter")
-document_pipeline.connect("splitter", "writer")
-
-document_pipeline.run({"converter": {"sources": ["vaud_report_results.md", "report_results.md"], 'meta':[{'doc-id': 'Vaud 2015-11-15 2021-12-31', 'topic':'reports'}, {'doc-id': 'Bern 2015-11-15 2021-12-31', 'topic':'reports'}]}})
-
-prompt_template = """
-    Given these documents, answer the question. Please provide the name of the reference(s) where the information came from\nDocuments:
-    {% for doc in documents %}
-        {{ doc.content }}
-    {% endfor %}
-
-    \nQuestion: {{question}}
-    \nAnswer:
-    """
-
-report_pipeline = Pipeline()
-report_pipeline.add_component(name="retriever", instance=FilterRetriever(document_store=report_document_store))
-report_pipeline.add_component(instance=PromptBuilder(template=prompt_template), name="prompt_builder")
-report_pipeline.add_component(instance=OpenAIGenerator(model=model), name="llm")
-report_pipeline.connect("retriever", "prompt_builder.documents")
-report_pipeline.connect("prompt_builder", "llm")
-
    -
    -
    -
    -
    Converting markdown files to Documents: 100%|█████| 2/2 [00:00<00:00, 22.29it/s]
-
    -
    -
    <haystack.core.pipeline.pipeline.Pipeline object at 0x7fedfe0d6c00>
-🚅 Components
-  - retriever: FilterRetriever
-  - prompt_builder: PromptBuilder
-  - llm: OpenAIGenerator
-🛤️ Connections
-  - retriever.documents -> prompt_builder.documents (List[Document])
-  - prompt_builder.prompt -> llm.prompt (str)
-
    -
    -
    -
    -
    -
    -
    # some_pdfs = [
-    
-#     {'topic': 'history of research, methods of research', 'source': 'resources/brief_history_marine_litter.pdf'},
-#     {'topic': 'threshold values, methods of calculation', 'source': 'resources/coastline_litter_threshold_value_report_14_9_2020_final.pdf'},
-#     {'topic': 'geospatial analysis, land use, feature evaluation', 'source': 'resources/revealing_the_role_of_landuse.pdf'}
-# ]
-
-# converter = PyPDFToDocument()
-
-# dox = []
-# for element in some_pdfs:
-#     results = converter.run(sources=[element['source']], meta={"topic":element['topic']})
-#     dox.append(results)
-
    -
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    -
    help(ChromaDocumentStore)
-
    -
    -
    -
    -
    Help on class ChromaDocumentStore in module haystack_integrations.document_stores.chroma.document_store:
-
-class ChromaDocumentStore(builtins.object)
- |  ChromaDocumentStore(collection_name: str = 'documents', embedding_function: str = 'default', persist_path: Optional[str] = None, distance_function: Literal['l2', 'cosine', 'ip'] = 'l2', metadata: Optional[dict] = None, **embedding_function_params)
- |
- |  A document store using [Chroma](https://docs.trychroma.com/) as the backend.
- |
- |  We use the `collection.get` API to implement the document store protocol,
- |  the `collection.search` API will be used in the retriever instead.
- |
- |  Methods defined here:
- |
- |  __init__(self, collection_name: str = 'documents', embedding_function: str = 'default', persist_path: Optional[str] = None, distance_function: Literal['l2', 'cosine', 'ip'] = 'l2', metadata: Optional[dict] = None, **embedding_function_params)
- |      Initializes the store. The __init__ constructor is not part of the Store Protocol
- |      and the signature can be customized to your needs. For example, parameters needed
- |      to set up a database client would be passed to this method.
- |
- |      Note: for the component to be part of a serializable pipeline, the __init__
- |      parameters must be serializable, reason why we use a registry to configure the
- |      embedding function passing a string.
- |
- |      :param collection_name: the name of the collection to use in the database.
- |      :param embedding_function: the name of the embedding function to use to embed the query
- |      :param persist_path: where to store the database. If None, the database will be `in-memory`.
- |      :param distance_function: The distance metric for the embedding space.
- |          - `"l2"` computes the Euclidean (straight-line) distance between vectors,
- |          where smaller scores indicate more similarity.
- |          - `"cosine"` computes the cosine similarity between vectors,
- |          with higher scores indicating greater similarity.
- |          - `"ip"` stands for inner product, where higher scores indicate greater similarity between vectors.
- |          **Note**: `distance_function` can only be set during the creation of a collection.
- |          To change the distance metric of an existing collection, consider cloning the collection.
- |      :param metadata: a dictionary of chromadb collection parameters passed directly to chromadb's client
- |          method `create_collection`. If it contains the key `"hnsw:space"`, the value will take precedence over the
- |          `distance_function` parameter above.
- |
- |      :param embedding_function_params: additional parameters to pass to the embedding function.
- |
- |  count_documents(self) -> int
- |      Returns how many documents are present in the document store.
- |
- |      :returns: how many documents are present in the document store.
- |
- |  delete_documents(self, document_ids: List[str]) -> None
- |      Deletes all documents with a matching document_ids from the document store.
- |
- |      :param document_ids: the object_ids to delete
- |
- |  filter_documents(self, filters: Optional[Dict[str, Any]] = None) -> List[haystack.dataclasses.document.Document]
- |      Returns the documents that match the filters provided.
- |
- |      Filters are defined as nested dictionaries. The keys of the dictionaries can be a logical operator (`"$and"`,
- |      `"$or"`, `"$not"`), a comparison operator (`"$eq"`, `$ne`, `"$in"`, `$nin`, `"$gt"`, `"$gte"`, `"$lt"`,
- |      `"$lte"`) or a metadata field name.
- |
- |      Logical operator keys take a dictionary of metadata field names and/or logical operators as value. Metadata
- |      field names take a dictionary of comparison operators as value. Comparison operator keys take a single value or
- |      (in case of `"$in"`) a list of values as value. If no logical operator is provided, `"$and"` is used as default
- |      operation. If no comparison operator is provided, `"$eq"` (or `"$in"` if the comparison value is a list) is used
- |      as default operation.
- |
- |      Example:
- |
- |      ```python
- |      filters = {
- |          "$and": {
- |              "type": {"$eq": "article"},
- |              "date": {"$gte": "2015-01-01", "$lt": "2021-01-01"},
- |              "rating": {"$gte": 3},
- |              "$or": {
- |                  "genre": {"$in": ["economy", "politics"]},
- |                  "publisher": {"$eq": "nytimes"}
- |              }
- |          }
- |      }
- |      # or simpler using default operators
- |      filters = {
- |          "type": "article",
- |          "date": {"$gte": "2015-01-01", "$lt": "2021-01-01"},
- |          "rating": {"$gte": 3},
- |          "$or": {
- |              "genre": ["economy", "politics"],
- |              "publisher": "nytimes"
- |          }
- |      }
- |      ```
- |
- |      To use the same logical operator multiple times on the same level, logical operators can take a list of
- |      dictionaries as value.
- |
- |      Example:
- |
- |      ```python
- |      filters = {
- |          "$or": [
- |              {
- |                  "$and": {
- |                      "Type": "News Paper",
- |                      "Date": {
- |                          "$lt": "2019-01-01"
- |                      }
- |                  }
- |              },
- |              {
- |                  "$and": {
- |                      "Type": "Blog Post",
- |                      "Date": {
- |                          "$gte": "2019-01-01"
- |                      }
- |                  }
- |              }
- |          ]
- |      }
- |      ```
- |
- |      :param filters: the filters to apply to the document list.
- |      :returns: a list of Documents that match the given filters.
- |
- |  search(self, queries: List[str], top_k: int, filters: Optional[Dict[str, Any]] = None) -> List[List[haystack.dataclasses.document.Document]]
- |      Search the documents in the store using the provided text queries.
- |
- |      :param queries: the list of queries to search for.
- |      :param top_k: top_k documents to return for each query.
- |      :param filters: a dictionary of filters to apply to the search. Accepts filters in haystack format.
- |      :returns: matching documents for each query.
- |
- |  search_embeddings(self, query_embeddings: List[List[float]], top_k: int, filters: Optional[Dict[str, Any]] = None) -> List[List[haystack.dataclasses.document.Document]]
- |      Perform vector search on the stored document, pass the embeddings of the queries instead of their text.
- |
- |      :param query_embeddings: a list of embeddings to use as queries.
- |      :param top_k: the maximum number of documents to retrieve.
- |      :param filters: a dictionary of filters to apply to the search. Accepts filters in haystack format.
- |
- |      :returns: a list of lists of documents that match the given filters.
- |
- |  to_dict(self) -> Dict[str, Any]
- |      Serializes the component to a dictionary.
- |
- |      :returns:
- |          Dictionary with serialized data.
- |
- |  write_documents(self, documents: List[haystack.dataclasses.document.Document], policy: haystack.document_stores.types.policy.DuplicatePolicy = <DuplicatePolicy.FAIL: 'fail'>) -> int
- |      Writes (or overwrites) documents into the store.
- |
- |      :param documents:
- |          A list of documents to write into the document store.
- |      :param policy:
- |          Not supported at the moment.
- |
- |      :raises ValueError:
- |          When input is not valid.
- |
- |      :returns:
- |          The number of documents written
- |
- |  ----------------------------------------------------------------------
- |  Class methods defined here:
- |
- |  from_dict(data: Dict[str, Any]) -> 'ChromaDocumentStore'
- |      Deserializes the component from a dictionary.
- |
- |      :param data:
- |          Dictionary to deserialize from.
- |      :returns:
- |          Deserialized component.
- |
- |  ----------------------------------------------------------------------
- |  Data descriptors defined here:
- |
- |  __dict__
- |      dictionary for instance variables
- |
- |  __weakref__
- |      list of weak references to the object
-
    -
    -
    -
    -
    -
    -
    file_names = ['resources/brief_history_marine_litter.pdf', 'resources/coastline_litter_threshold_value_report_14_9_2020_final.pdf', 'resources/revealing_the_role_of_landuse.pdf']
-metas = [{'topic': 'history of research, methods of research'},  {'topic': 'threshold values, methods of calculation'}, {'topic': 'geospatial analysis, land use, feature evaluation'}]
-
-
-context_document_store = ChromaDocumentStore(collection_name='context_docs')
-
-pipeline = Pipeline()
-pipeline.add_component("converter", PyPDFToDocument())
-pipeline.add_component("cleaner", DocumentCleaner())
-pipeline.add_component("splitter", DocumentSplitter(split_by="page", split_length=1))
-pipeline.add_component("writer", DocumentWriter(document_store=context_document_store))
-pipeline.connect("converter", "cleaner")
-pipeline.connect("cleaner", "splitter")
-pipeline.connect("splitter", "writer")
-
-pipeline.run({"converter": {"sources": file_names, "meta": metas}})
-# retriever = ChromaQueryTextRetriever(document_store=context_document_store)
-# retriever2 = FilterRetriever(document_store)
-
    -
    -
    -
    -
    {'writer': {'documents_written': 347}}
-
    -
    -
    -
    -
    -
    -
    g  = context_document_store.search(['land use and buffer zones'], top_k=5)
-print(len(g), len(g[0]))
-
    -
    -
    -
    -
    1 5
-
    -
    -
    -
    -
    -
    -
    g[0][0].meta['topic']
-
    -
    -
    -
    -
    'geospatial analysis, land use, feature evaluation'
-
    -
    -
    -
    -
    -
    -
    # from haystack.components.readers import ExtractiveReader
-
-# reader = ExtractiveReader()
-# reader.warm_up()
-
-
-# extractive_qa_pipeline = Pipeline()
-
-# context_pipeline = Pipeline()
-# context_pipeline.add_component(name="context_retriever", instance=FilterRetriever(document_store=context_document_store))
-# extractive_qa_pipeline.add_component(instance=reader, name="reader")
-
-# extractive_qa_pipeline.connect("embedder.embedding", "context_retriever.query_embedding")
-# extractive_qa_pipeline.connect("retriever.documents", "reader.documents")
-
    -
    -
    -
    -
    -
    -
    prompt_template = """
-    Given these documents, answer the question. Please provide the name of the reference(s) in your response\nDocuments:
-    {% for doc in documents %}
-        {{ doc.content }}
-    {% endfor %}
-
-    \nQuestion: {{question}}
-    \nAnswer:
-    """
-
-context_pipeline = Pipeline()
-context_pipeline.add_component(name="context_retriever", instance=FilterRetriever(document_store=context_document_store))
-context_pipeline.add_component(instance=PromptBuilder(template=prompt_template), name="prompt_builder_context")
-context_pipeline.add_component(instance=OpenAIGenerator( model=model), name="llm")
-context_pipeline.connect("context_retriever", "prompt_builder_context.documents")
-context_pipeline.connect("prompt_builder_context", "llm")
-
    -
    -
    -
    -
    <haystack.core.pipeline.pipeline.Pipeline object at 0x7fed9bf69010>
-🚅 Components
-  - context_retriever: FilterRetriever
-  - prompt_builder_context: PromptBuilder
-  - llm: OpenAIGenerator
-🛤️ Connections
-  - context_retriever.documents -> prompt_builder_context.documents (List[Document])
-  - prompt_builder_context.prompt -> llm.prompt (str)
-
    -
    -
    -
    -
    -
    -
    def context_pipeline_func(query: str):
-    print("context called")
-    if 'context_filter' in query:
-        result = context_pipeline.run({"retriever": {"filters": context_filters}, "prompt_builder": {"question": query}})
-
-        return {"reply": result["llm"]["replies"][0].content}
-    else:
-        return "There is no relevant background in my library"
-
-def report_pipeline_func(query: str, filters: dict):
-    print("report called")
-    if 'report_filters' in query:
-        result = context_pipeline.run({"retriever": {"filters": filters}, "prompt_builder": {"question": query}})
-        return {"reply": result["llm"]["replies"][0].content}
-    else:
-        return "There is no survey data for that date range and location, would you like a list of available cantons?"
-
-def call_tools(query, a_report_filter, a_context_filter):
-
-    report = report_pipeline_func(qeury, a_report_filter)
-    context = context_pipeline_func(query, a_context_filter)
-
-    return (f'the requested survey results:\n\n {report}\n\nSome relevant background info {context}')
-
-
-# result[reply_object]['replies'][0]
-
-@component
-class AssembleResources:
-    def __init__(self, query: str, report_filters: dict, context_filters: dict, context_pipeline: Pipeline, report_pipeline: Pipeline, reply_object: str = 'llm'):
-        self.report_filter = report_filters
-        self.context_filter = context_filters
-        self.query = query
-        self.cont_pipeline = context_pipeline
-        self.rep_pipeline = report_pipeline
-        self.reply_object = reply_object
-        
-
-    @component.output_types(report_results=str, context_results=str)
-    def run(self):
-        r = self.rep_pipeline.run({'retriever': {'filters': self.report_filter}, "prompt_builder":{"question":self.query}})
-        c = self.cont_pipeline.run({'context_retriever': {'filters': self.context_filter}, "prompt_builder_context":{"question":self.query}})
-        return {'report_results': r[self.reply_object]['replies'][0], 'context_results':c[self.reply_object]['replies'][0]}
-
    -
    -
    -
    -
    -
    -
    context_filters = {
-    'topic': {"$in":['threshold values, methods of calculation']},
-}
-
-v = ['Vaud 2015-11-15 2021-12-31']
-b = ['Bern 2015-11-15 2021-12-31']
-combined = [*v,*b]
-
-
-
-report_filters = {
-    'doc-id': {"$in":combined},
-}
-
    -
    -
    -
    -
    -
    -
    f = AssembleResources('What was the average pcs/m in Bern? How is beach litter measured or calculated? What other metrics are used?', report_filters, context_filters, context_pipeline, report_pipeline).run()
-Markdown(f['report_results'])
-
    -
    -
    -
    -

    The average pcs/m (objects per meter) in Bern is approximately 0.71, as stated in the summary statistics of the survey results.

    -

    Beach litter is measured or calculated by collecting samples from designated survey locations. The specific metrics used in the analysis typically include the average number of litter objects identified per meter, the standard deviation of litter density, the number of samples collected, and the percentile distribution (5th, 25th, 50th, 75th, 95th percentiles), as well as maximum observed litter density.

    -

    Other metrics utilized in the analysis might include:

    -
      -

    • Material composition of the litter identified (e.g., percentage of plastic).

      • -

    • Inventory items that categorize the type of litter.

      • -

    • Stratification based on land-use profiles around the surveyed locations, examining how litter density may vary in relation to different environmental features (e.g., buildings, wetlands, forests, public services).

      • -

    • Results from cluster analysis to identify similarities in land use among sampled locations.

      • -

    • Regression analysis outcomes that assess the relationship between land use features and litter density.

      • -
    -

    This information was derived from the “Survey report Canton Bern 2015-11-15 2021-12-31” document.

    -
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    -
    -
    -
    # f = AssembleResources('Which had the highest average pieces per meter Vaud or Bern?', report_filters, context_filters, context_pipeline, report_pipeline).run()
-Markdown(f['context_results'])
-
    -
    -
    -
    -

    The documents provided do not specifically mention the average number of litter pieces per meter (pcs/m) in Bern. They present information regarding a European threshold value for macro litter on coastlines but do not provide city-specific data.

    -

    Beach litter is typically measured or calculated using the following methodologies:

    -
      -

    1. Survey Length: Litter is surveyed along a set length of beach, commonly 100 meters. This standardization helps in achieving comparability across different monitoring sites.

      2. -

    2. Data Collection: Surveys are conducted multiple times a year, ideally in each season, to account for seasonal variations in litter accumulation.

      3. -

    3. Data Clean-Up: The collected data undergo cleaning to exclude fragments of litter that are not comparable (like smaller pieces) and to focus on macro-sized materials typically larger than 2.5 cm.

      4. -

    4. Abundance Calculation: The total abundance of litter per survey is calculated by summing up the remaining litter types and normalizing to 100 m of beach.

      5. -

    5. Statistical Methods: Various statistical methods are employed to calculate threshold values based on percentiles (e.g., the 10th percentile, 15th percentile), which allows for robust assessment values while accounting for uncertainties.

      6. -
    -

    Other metrics that are commonly used in beach litter assessments include:

    -
      -

    • Median Values: The median number of litter pieces is considered a robust indicator to assess beach litter levels as it is less influenced by extreme values compared to mean values.

      • -

    • Mean Values: While mean values can provide an overview, they are more susceptible to distortion from outliers.

      • -

    • Confidence Intervals: Calculated to assess the uncertainty around the median assessment values, ensuring statistical reliability.

      • -
    -

    In summary, beach litter assessments utilize a combination of systematic survey methodologies, statistical calculations for threshold values, and the use of metrics like mean and median to evaluate the litter’s impact on coastal environments.

    -
    -
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    -
    -
    from haystack import component
-
-@component
-class CombinedAnswer:
-  """
-  A component generating personal welcome message and making it upper case
-  """
-  @component.output_types(welcome_text=str, note=str)
-  def run(self, name:str):
-    return {"welcome_text": ('Hello {name}, welcome to Haystack!'.format(name=name)).upper(), "note": "welcome message is ready"}
-
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    -
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    -
    prompt_template = """
-    Given the results from the report and the results of the litterature review  documents, answer the question. Please provide the name of the reference(s) in your response\nDocuments:
-    \nReport results: {{report_results}}
-    \n
-    \nLitterature review: {{context_results}}
-    {% endfor %}
-
-    \nQuestion: {{question}}
-    \nAnswer:
-    """
-
-context_pipeline = Pipeline()
-# context_pipeline.add_component(name="context_retriever", instance=FilterRetriever(document_store=context_document_store))
-# context_pipeline.add_component(instance=PromptBuilder(template=prompt_template), name="prompt_builder_context")
-# context_pipeline.add_component(instance=OpenAIGenerator( model=model), name="llm")
-# context_pipeline.connect("context_retriever", "prompt_builder_context.documents")
-# context_pipeline.connect("prompt_builder_context", "llm")
-
    -
    -
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    -
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    break
-
    -
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      Cell In[13], line 1
-    break
-    ^
-SyntaxError: 'break' outside loop
-
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    Chroma vector store#

    -
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    break
-
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    # tools = [
-#     {
-#         "type": "function",
-#         "function": {
-#             "name": "context_pipeline_func",
-#             "description": "Retrieves background information about the query from matching meta-data",
-#             "parameters": {
-#                 "type": "object",
-#                 "properties": {
-#                     "query": {
-#                         "type": "string",
-#                         "description": "The query to use in the search. Infer this from the user's message. It should be a question or a statement",
-#                     },
-#                 },
-#                 "required": ["query"],
-#             },
-#         },
-#     },
-#     {
-#         "type": "function",
-#         "function": {
-#             "name": "report_pipeline_func",
-#             "description": "Retrieves the results from survey report documents based on the matching meta-data",
-#             "parameters": {
-#                 "type": "object",
-#                 "properties": {
-#                     "query": {
-#                         "type": "string",
-#                         "description": "The query to use in the search. Infer this from the user's message. It should be a question or a statement",
-#                     },
-#                 },
-#                 "required": ["query"],
-#             },
-#         },
-#     },
-# ]
-
    -
    -
    -
    -
    -
    -
    from haystack.components.retrievers.in_memory import InMemoryEmbeddingRetriever
-from haystack.components.readers import ExtractiveReader
-from haystack.components.embedders import SentenceTransformersTextEmbedder
-
-
-retriever = InMemoryEmbeddingRetriever(document_store=document_store)
-reader = ExtractiveReader()
-reader.warm_up()
-
-extractive_qa_pipeline = Pipeline()
-
-extractive_qa_pipeline.add_component(instance=SentenceTransformersTextEmbedder(model=model), name="embedder")
-extractive_qa_pipeline.add_component(instance=retriever, name="retriever")
-extractive_qa_pipeline.add_component(instance=reader, name="reader")
-
-extractive_qa_pipeline.connect("embedder.embedding", "retriever.query_embedding")
-extractive_qa_pipeline.connect("retriever.documents", "reader.documents")
-
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    Markdown(f['context_results'])
-
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    from haystack.dataclasses import ChatMessage
-from haystack.components.generators.chat import OpenAIChatGenerator
-from haystack.components.generators.utils import print_streaming_chunk
-import gradio as gr
-import json
-messages = [
-    ChatMessage.from_system(
-        "reply with at least a helpfull message"
-    ),
-    ChatMessage.from_user("What were the regression results for Vaud ? What were the regression results for Bern ? Whats the difference?.? context_filter, report_filters")
-]
-
-chat_generator = OpenAIChatGenerator(model=model, streaming_callback=print_streaming_chunk)
-response = chat_generator.run(messages=messages generation_kwargs={"tools": tools})
-
    -
    -
    -
    -
    -
    -
    from haystack.dataclasses import ChatMessage
-from haystack.components.generators.chat import OpenAIChatGenerator
-from haystack.components.generators.utils import print_streaming_chunk
-
-chat_generator = OpenAIChatGenerator(model="gpt-3.5-turbo", streaming_callback=print_streaming_chunk)
-response = chat_generator.run(messages=messages)
-
    -
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    response["replies"][0].meta["finish_reason"] == "tool_calls"
-
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    response["replies"]
-
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    -
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    from haystack.dataclasses import ChatMessage
-from haystack.components.generators.chat import OpenAIChatGenerator
-
-chat_generator = OpenAIChatGenerator(model="gpt-3.5-turbo")
-response = None
-messages = [
-    ChatMessage.from_system(
-        "Don't make assumptions about what values to plug into functions. Ask for clarification if a user request is ambiguous."
-    )
-]
-
    -
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    -
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    response["replies"][0].content
-
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    import json
-
-## Parse function calling information
-function_call = json.loads(response["replies"][0].content)[0]
-function_name = function_call["function"]["name"]
-function_args = json.loads(function_call["function"]["arguments"])
-print("Function Name:", function_name)
-print("Function Arguments:", function_args)
-
-## Find the correspoding function and call it with the given arguments
-available_functions = {"rag_pipeline_func": rag_pipeline_func, "get_current_weather": get_current_weather}
-function_to_call = available_functions[function_name]
-function_response = function_to_call(**function_args)
-print("Function Response:", function_response)
-
    -
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    -By the-team@ -

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    - - © Copyright 2023. -
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    - - \ No newline at end of file diff --git a/docs/landuse_class.html b/docs/landuse_class.html deleted file mode 100644 index 7c4cb7d..0000000 --- a/docs/landuse_class.html +++ /dev/null @@ -1,1248 +0,0 @@ - - - - - - - - - - - Land use class — Project 2025 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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    Land use class

    - -
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    - -
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    - - -Hide code cell source - -
    -
    %load_ext watermark
-import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
-import matplotlib as mpl
-import matplotlib.colors
-from matplotlib.colors import LinearSegmentedColormap, ListedColormap
-import seaborn as sns
-
    -
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    -
    -

    Land use class#

    -

    The landuse class groups the survey results according to the rate of landuse at each survey location. Provides the correlation matrix of the feature variables and the number of samples and the average result for each landuse type and magnitude.

    -
    -

    Why is this important?#

    -

    Because it is another way to get proxies for usage and population.

    -

    We assume there is a relationship between how the land is used and what it is we find on the ground. Archeaologists and Anthropologists make this basic assumption every time they undertake an excavation and interpret the results in the context of other findings. This interpretation of beach litter data does exactly the same. As discussed in Near or far and the federal report IQAASL at the national level there is strong evidence to support a correlation between the density of objects found and specific topographic features that can be isolated on a standard topographical map.

    -
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    What is important?#

    -

    The relationship between the topograhpical features and the density of the objects found.

    -

    However, the measured features are not independent of each other. For example if their are buildings in an area we expect to also find a road that leads to those buildings. This multicolinearity can lead to unstable coefficient estimates and make it challenging to interpret the individual effects of the correlated variables on the target variable.

    -

    The topographical data from the confederation provides continuity to what could be interpreted as unrelated observations. Furthermore, the labels provided for the various topographical features are indicators of use and have a real meaning to georaphers and engineers in planning and development. Local associations that are involved in preventing and reducing litter may also be interested.

    -
    -
    -
    -

    Make a land use object#

    -

    After the topographical features are extracted the results are applied to the data. The land use clas is available by calling geospatial.LandUseReport(df_target, features). The df_target and features variables are generated in the SurveyReport.

    -

    Instantiate a LandUseReport

    -
    # start a survey report
-import session_config
-import reports
-import geospatial
-
-# available data
-surveys = session_config.collect_survey_data()
-
-# boundaries / search parameters
-feature_type = 'canton'
-feature_name = 'Vaud'
-
-df = surveys[surveys[feature_type] == feature_name].copy()
-vaud_report = reports.SurveyReport(dfc=df)
-
-# the parameters for the land use report
-target_df = vaud_report.sample_results
-features = vaud_report.sampling_conditions()
-land_use_report = geospatial.LandUseReport(target_df, features)
-
    -
    -
    -

    Report contents#

    -
      -

    1. Number of samples per feature and magnitude

      2. -

    2. The total number of objects collected per feature and magnitude

      3. -

    3. The number of locations per feature and magnitude

      4. -

    4. The average pieces per meter for each feature and magnitude

      5. -

    5. The correlation matrix of the feature variables

      6. -

    6. The correlated pairs

      7. -

    7. The landuse on a conintuous scale

      8. -

    8. The landuse on a categorical scale

      9. -
    -
    -
    -
    -
    -

    Number of samples per feature#

    -
    -
    -
    samples_per_feature = land_use_report.n_samples_per_feature()
-samples_per_feature[session_config.feature_variables]
-
    -
    -
    -
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    orchardsvineyardsbuildingsforestundefinedpublic servicesstreets
    12512482521620820046
    20117221851160
    30211325045
    400500000
    5001580000
    -
    -
    -
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    Quantity per feature#

    -
    -
    -
    q_pf = land_use_report.n_pieces_per_feature()
-q_pf[session_config.feature_variables]
-
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    orchardsvineyardsbuildingsforestundefinedpublic servicesstreets
    18001679749211569630682026227914442
    201469513148496991773750897
    3012118689022115014677
    400133150000
    500548870000
    -
    -
    -
    -
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    Locations per feature#

    -
    -
    -
    l_pf = land_use_report.locations_per_feature()
-l_pf[session_config.feature_variables]
-
    -
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    orchardsvineyardsbuildingsforestundefinedpublic servicesstreets
    1383633531297
    201324922
    30111309
    40050000
    500260000
    -
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    density per feature#

    -
    -
    -
    r_pf = land_use_report.rate_per_feature().T
-r_pf[session_config.feature_variables]
-
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    orchardsvineyardsbuildingsforestundefinedpublic servicesstreets
    18.9217538.9499194.61288.5075938.6323087.845811.502174
    209.7519.014.25636418.25111113.1411767.273375
    305.0155.3523.6984624.6128012.144889
    4005.56040000
    5009.604430000
    -
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    Corelation matrix#

    -
    -
    -
    land_use_report.correlation_matrix()
-
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    orchardsvineyardsbuildingsforestundefinedpublic servicesstreets
    orchards1.0000000.215632-0.232329-0.0443110.205992-0.195685-0.087427
    vineyards0.2156321.000000-0.100630-0.190298-0.057757-0.215319-0.155203
    buildings-0.232329-0.1006301.000000-0.872981-0.9461090.4809620.532584
    forest-0.044311-0.190298-0.8729811.0000000.767505-0.367753-0.538793
    undefined0.205992-0.057757-0.9461090.7675051.000000-0.425264-0.412409
    public services-0.195685-0.2153190.480962-0.367753-0.4252641.0000000.542128
    streets-0.087427-0.1552030.532584-0.538793-0.4124090.5421281.000000
    -
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    Corelated pairs#

    -

    The correlated pairs method identifies the land-use features that are correlated with each other. The method returns a tuple with the two features that are correlated and the method that could be used to combine them.

    -
    -
    -
    print(f'Correlated pairs:\n{correlated_pairs}')
-
    -
    -
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    -
    Correlated pairs:
-[('buildings', 'public services', 'rate'), ('forest', 'undefined', 'sum')]
-
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    Continuous land use#

    -
    -
    -
    continuous = land_use_report.df_cont.copy()
-examps = continuous[continuous.location.isin(['veveyse', 'la-pecherie'])].drop_duplicates('location')
-examps[['location', *session_config.feature_variables]].fillna(0).set_index('location')
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    location
    la-pecherie0.1710.1620.1060.0960.4640.0104490.166033
    veveyse0.0000.0270.9580.0000.0150.0473930.344649
    -
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    Categorical land use#

    -
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    cat = land_use_report.df_cat.copy()
-examps = cat[cat.location.isin(['veveyse', 'la-pecherie'])].drop_duplicates('location')
-examps[['location', *session_config.feature_variables]].set_index('location')
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    location
    la-pecherie1111311
    veveyse1151112
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    Author: hammerdirt-analyst
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-conda environment: cantonal_report
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-pandas    : 2.0.3
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-matplotlib: 3.7.1
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    Langchain agents#

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    machine learning

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    import pandas as pd
-import numpy as np
-import geopandas as gpd
-import matplotlib.pyplot as plt
-from matplotlib.lines import Line2D
-from shapely.geometry import Point
-from shapely.geometry import box
-
-# import matplotlib.patches as mpatches
-import session_config
-from session_config import  collect_survey_data, feature_variables, agg_groups, feature_variables
-from session_config import lat_lon, beaches, model_rough_draft, model_corrections
-from session_config import tobo_snacks, report_meta_data, report_args
-from reports import make_report_objects
-from reports import histograms_standard
-from reports import ecdf_plots_standard, scatter_plot_standard
-import gridforecast as gfcast
-from linearmethods import LinearMethods
-from roughdraft import ReportTexts, messages_for_chat_completion, use_chat_completion
-from IPython.display import Markdown
-from geospatial import layer_selection_criteria, map_markers
-
-from dotenv import load_dotenv
-import os
-from myst_nb import glue
-
-from langchain_openai import ChatOpenAI
-import openai
-
-# beaches = pd.read_csv('data/end_process/beaches.csv')
-# lat_lon = beaches[['slug', 'latitude', 'longitude']].set_index('slug')
-
-load_dotenv()
-api_key = os.getenv('OPENAI_API_KEY')
-
-datax = collect_survey_data()
-
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    -
    -
    -
    -
    canton_layer = gpd.read_file('data/ignorethis/shapes/kantons.shp').to_crs(epsg=4326)
-dbckey = canton_layer[['NAME', 'KANTONSNUM']]
-dbckey = dbckey.drop_duplicates()
-dbckey.to_csv('data/end_process/kantonsnum.csv', index=False)
-
    -
    -
    -
    -
    -
    -
    this_report = report_args(**{'data': datax, 'start': '2020-01-01', 'end':'2021-12-01', 'name': 'Bern', 'boundary':'canton', 'boundary_name':'Bern', 'feature_type':'l', 'codes': tobo_snacks, 'columns_of_interest': feature_variables})
-report_data, report_meta = report_meta_data(**this_report)
-all_report, all_land_use = make_report_objects(report_data, info_columns = ['canton', 'city', 'feature_name'])
-
-
-client = ChatOpenAI(model=model_rough_draft)
-args = {
-    'report_meta': report_meta,
-   
-    'survey_report': all_report,
-    'landuse_report': all_land_use,
-    
-    
-   
-}
-
-firstdraft = ReportTexts(**args)
-asum, sampstrat, grid_f, lin_f, inv_f  = firstdraft.string_rep('rough_draft.md', datax)
-
    -
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    -

    machine learning#

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    -
    -
    # likelihood scatter
-s_like = firstdraft.survey_report.sample_results(info_columns=firstdraft.info_cols)
-
-# grid predictions and priors
-grid_forecast = firstdraft.grid_approximation(datax)
-
-# regression predictions
-regress_pred = firstdraft.linear_methods()
-
-# sampling stratification
-sampstrat = firstdraft.landuse_profile()
-
-# pcs/m stratified
-ratestrat = firstdraft.landuse_rates()
-
-# inventory
-inventory = firstdraft.inventory
-
-# markers layers
-markers, bounds = map_markers(firstdraft.survey_report.sample_results(info_columns=firstdraft.info_cols), lat_lon)
-res = layer_selection_criteria(report_meta, bounds)
-
-
-def situation_map_one(points, layers, title, legenditems, bounds):
-
-    fig, ax = plt.subplots(figsize=(9, 9))
-    
-    for element in layers:
-        if element == 'canton':
-            layers[element].plot(ax=ax, edgecolor='dodgerblue',  alpha=1, linewidth=.1)
-        if element == 'city':
-            layers[element].plot(ax=ax, edgecolor='black', facecolor='white', alpha=1, linewidth=.2)
-        
-        if element == 'river':
-            layers[element].plot(ax=ax, edgecolor='dodgerblue',  alpha=.4, linewidth=1)
-        
-        if element == 'lake': 
-            layers[element].plot(ax=ax, edgecolor='dodgerblue', facecolor='dodgerblue', alpha=.8, linewidth=.1)
-        
-
-    for c in points:
-        c['points'].plot(ax=ax, color= session_config.palette['prior'], marker='x', markersize=80, zorder=5, label = c['label'])
-    
-    
-    ax.set_title(f'{title}')
-    ax.set_xlim(bounds['min_lon']-.1, bounds['max_lon']+.1)
-    ax.set_ylim(bounds['min_lat'] - .1, bounds['max_lat'] + .1)
-    plt.xlabel('')
-    plt.ylabel('')
-    
-    plt.axis('off')
-    
-    plt.close()
-    return fig
-title='title'
-legenditems = ['hello']
-points = [{'points': markers, 'label':'label'}]
-situation_map_one(points, res[0], title, legenditems, bounds)
-
    -
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    -_images/85099e44487668046b7bdbca0f73ffcaf91c4d0b81ff2a5b0648cd1dba5207b7.png -
    -
    -
    -
    -
    def map_markers(df, lat_lon: pd.DataFrame = lat_lon):
-    """Map the markers"""
-
-    # collect information for popup display at each location
-    nsamples = df.groupby('location', observed=True)['sample_id'].nunique()
-    qty_location = df.groupby('location', observed=True)['quantity'].sum()
-    rate_location = df.groupby('location', observed=True)['pcs/m'].mean().round(2)
-    last_sample = df.groupby('location', observed=True)['date'].max()
-
-    # merge the pop-up information with the gps coordinates
-    df = pd.concat([nsamples, qty_location, rate_location, last_sample], axis=1)
-    df = df.merge(lat_lon, left_index=True, right_index=True)
-    df['location'] = df.index
-
-    # get the bounds of these points in a dict
-    max_lat, min_lat = df['latitude'].max(), df['latitude'].min()
-    max_lon, min_lon = df['longitude'].max(), df['longitude'].min()
-    td = df.to_dict(orient='records')
-
-    # make the points and geo dataframe
-    geometry = [Point(loc['longitude'], loc['latitude']) for loc in td]
-    geo_frame = gpd.GeoDataFrame(td, geometry=geometry, crs="EPSG:4326")
-
-    return geo_frame, {'max_lat': max_lat, 'min_lat': min_lat, 'max_lon': max_lon, 'min_lon': min_lon}
-
    -
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    markers
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    sample_idquantitypcs/mdatelatitudelongitudelocationgeometry
    0120.222020-10-0946.6866407.689760augustmutzenbergstrandwegPOINT (7.68976 46.68664)
    112590.332021-03-2547.0383987.108311bielersee_vinelz_fankhausersPOINT (7.10831 47.03840)
    2180.322020-11-0646.7271407.629620camping-gwatt-strandPOINT (7.62962 46.72714)
    3160.182020-11-1946.7200787.635304delta-parkPOINT (7.63530 46.72008)
    41280.492021-03-2547.0471597.097854erlach-camping-strandPOINT (7.09785 47.04716)
    5280.212020-08-2847.0462727.085007gals-reservePOINT (7.08501 47.04627)
    621061.252020-09-0746.6902837.898592hafeliPOINT (7.89859 46.69028)
    72241.542020-09-0947.0839797.135894ligerz-strandPOINT (7.13589 47.08398)
    84170.082020-12-2647.0479557.151242luscherz-plagePOINT (7.15124 47.04796)
    9100.002020-06-1047.0475197.152829luscherz-twoPOINT (7.15283 47.04752)
    10139672.002021-03-3147.1333397.227907mullermattePOINT (7.22791 47.13334)
    111150.602020-11-3047.1271967.232613nidau-strandPOINT (7.23261 47.12720)
    121430.672021-02-0546.7444518.049921oben-am-seePOINT (8.04992 46.74445)
    132340.422020-12-2547.1325107.233142strandboden-bielPOINT (7.23314 47.13251)
    142290.662020-11-0746.6843867.794768sundbach-strandPOINT (7.79477 46.68439)
    152570.312021-02-1446.7399397.633520thun-strandbadPOINT (7.63352 46.73994)
    1612420.062021-02-0546.7044377.657882thunersee_spiez_meierd_1POINT (7.65788 46.70444)
    17126580.682021-04-0846.6765837.817528weissenau-neuhausPOINT (7.81753 46.67658)
    182250.362020-11-0746.7403708.048640wycheleyPOINT (8.04864 46.74037)
    -
    -
    -
    -
    -
    from ipyleaflet import Map, GeoJSON, GeoData
-import geopandas, pandas as pd, numpy as np
-
-m = Map(center=(46.91, 7.43), zoom=15)
-
-numpoints = 10
-center = (7.43, 46.91)
-
-df = pd.DataFrame(
-    {'Conc': 1 * np.random.randn(numpoints) + 17,
-     'Longitude': 0.0004 * np.random.randn(numpoints) + center[0],
-     'Latitude': 0.0004 * np.random.randn(numpoints) + center[1]})
-
-gdf = geopandas.GeoDataFrame(
-    df, geometry=geopandas.points_from_xy(df.Longitude, df.Latitude))
-
-geo_data = GeoData(geo_dataframe = gdf,
-    style={'color': 'black', 'radius':8, 'fillColor': '#3366cc', 'opacity':0.5, 'weight':1.9, 'dashArray':'2', 'fillOpacity':0.6},
-    hover_style={'fillColor': 'red' , 'fillOpacity': 0.2},
-    point_style={'radius': 5, 'color': 'red', 'fillOpacity': 0.8, 'fillColor': 'blue', 'weight': 3},
-    name = 'Release')
-
-m.add(geo_data)
-m
-
    -
    -
    -
    -
    -
    -
    -
    -
    bounds
-
    -
    -
    -
    -
    {'max_lat': 47.133339,
- 'min_lat': 46.676583,
- 'max_lon': 8.0499211,
- 'min_lon': 7.0850075}
-
    -
    -
    -
    -
    -
    -
    import folium
-
-# m = folium.Map(
-#     [46.923579, 7.473319], zoom_start=3,tiles='https://wmts.geo.admin.ch/1.0.0/ch.swisstopo.swissimage/default/current/3857/{z}/{x}/{y}.jpeg', attr='My Data Attribution')
-
-
-
-min_lon, max_lon = 6.9, 8.14
-min_lat, max_lat = 46.57, 47.24
-
-m = folium.Map(
-    max_bounds=True,
-    zoom_start=15,
-    min_lat=min_lat,
-    max_lat=max_lat,
-    min_lon=min_lon,
-    max_lon=max_lon,
-    width=600,  # Set the width in pixels
-    height=400,
-    tiles='https://wmts.geo.admin.ch/1.0.0/ch.swisstopo.pixelkarte-farbe/default/current/3857/{z}/{x}/{y}.jpeg',
-    attr='My Data Attribution'
-)
-
-for _, row in markers.iterrows():
-    folium.Marker(
-        location=[row['latitude'], row['longitude']],
-        popup=row['location'],  # Set the location as the popup text
-        icon=folium.Icon(icon='info-sign', color='red')  # You can customize the icon as needed
-    ).add_to(m)
-m.fit_bounds([(7.0,46.67), (8.04, 47.14)])
-glue('map', m, display=False)
-
    -
    -
    -
    -

    hello

    -
    Make this Notebook Trusted to load map: File -> Trust Notebook
    -
    -
    from ipyleaflet import Map, basemaps
-
-center = [38.128, 2.588]
-zoom = 5
-
-Map(basemap=basemaps.OpenStreetMap.Mapnik, center=center, zoom=zoom)
-
    -
    -
    -
    -
    -
    -
    -
    -
    from ipywidgets import Button
-
-button = Button(description="Test Button")
-display(button)
-
    -
    -
    -
    -
    -
    -
    -
    -
    def make_system_prompt(roughdraft):
-    system_prompt = (
-    "You are a researcher assigned the task of preparing the rough draft of a manuscript. "   
-    "You are tasked to produce a summary, and answer specific questions "
-    "Do not give your opinion. Do not use phrases like 'this report provides' or 'this study correlates' or 'according to the text' or 'this document' or anything like that. "
-    "State what the subject is, Answer the question completely and check your answers, use an authoritive voice. "
-    "You must give numerical examples from the report when you answer a question about the survey results. "
-    "Do not answer the questions twice. If the question is answered in the summary state this. If there are no questions pass, do not make any up. "
-    "there are instructions between the labels '<!--- INSTRUCTION_START INSTRUCTIONS_END -->' follow them always"
-    f"All answers should be in paragraph form. Here is the document:\n\n" 
-    f"{roughdraft}"
-    )
-    return system_prompt
-
    -
    -
    -
    -
    -
    -
    request = (
-    "Define sampling stratification and how it applies to the survey results, define land-use and how it applies to the survey report."
-)
-
-req_inf = (
-    "<!-- INSTRUCTION_START Define sampling stratification in the general sense and explain how it is used in this survey. Define what land use is. The land use categories for this report are listed in the column names"
-    "of the sampling stratification table. These are the land use categories that are used to stratify the results. Do not make up results, follow the defnitions and instructions explicitly."
-    " INSTRUCTION_END -->\n"
-    
-)
-insone = (
-    "<!-- INSTRUCTION_START In the 'sampling stratification' section there are instructions and an example on how to interpret the results from the table. Make sure to reference these instructions"
-    " and interpret the current results accordingly"
-    " INSTRUCTION_END -->\n"
-)
-
-instwo = (
-    "<!-- INSTRUCTION_START In the 'sampling stratifocation and trash density section there are instructions and an example on how to interpret the results. Make sure to reference these instructions"
-    " and interpret the current results accordingly"
-    " INSTRUCTION_END -->\n"
-)
-
-insthree = (
-    "<!-- INSTRUCTION_START Provide examples from the 'sampling stratification and trash density' consider the results from the buidlings, forest, streets, and undefined columns. "
-    "Find the two highest values and report the proportion of buffer they occupy. Report the values in your answer."
-    " INSTRUCTION_END -->\n"
-)
-
-insfour = (
-    "<!-- INSTRUCTION_START Recall the definition for urban and rural is provided in the document instructions. If the sampling stratification does not meet either criteria, say so and reply with "
-    "prportion of the buffer that contains the greates proportion of samples for buildings, forest and undefined "
-    " INSTRUCTION_END -->\n"
-)
-
-questions = (
-    f"1. How do I interpret the results in the sampling stratification table ?"
-    f"2. How do I interpret the results in the sampling stratification and trash density table ?{instwo}"
-    f"3. Under what landuse conditions would a surveyor expect to find the most trash ?{insthree}"
-    f"4. Given the results in the sampling stratification table, were these surveys collected in mostly urban environment or forested?{insfour}"
-     
-    
-)
-
-formatting_instructions = (
-    "\n<!-- INSTRUCTION_START\n"
-    "1. Label the summary 'Sampling stratification' (##)\n"
-    "2. The label for the questions section is 'Frequently asked questions' (###) \n"
-    "3. Repeat the question (in bold) DO NOT REPEAT the instructions. and then answer\n"
-    " INSTRUCTION_END -->\n"
-)
-
-def make_stratification_prompt():
-        
-    user_prompt = (        
-        f'{request}{req_inf}\n\n'
-        f'{questions}\n\n'
-        f'{formatting_instructions}'
-    )
-
-
-
-    return user_prompt
-
    -
    -
    -
    -
    -
    -
    messagesxxx = messages_for_chat_completion(system_prompt=make_system_prompt(sampstrat), user_prompt=make_stratification_prompt())
-completed_chatxxx = client.invoke(messagesxxx)
-sampling_stratification = completed_chatxxx.content
-
    -
    -
    -
    -
    -
    -
    def make_summary_prompt():
-        
-    user_prompt = f"""\n
-        
-    Provide a summary of the following sections: Administrative boundaries, Named features, Summary statistics, Municipal results, Material composition.
-    
-    The following must be included in the summary:
-
-    * The Name and number of the cities, lakes, rivers or parks in the report : <!--- INSTRUCTION_START The names of the lakes, rivers and parks are in the named features section, the municipal results are in the city total section INSTRUCTIONS_END -->
-    * The start and end date of the sampling and the name of the survey area(s)
-    * The numbar of samples, the average pcs/m, the maximum pcs/m and the total number of objects identified
-    * The material composition
-   
-
-    Frequently asked questions:
-
-    1. What were the five most common items found ? <!--- INSTRUCTION_START Provide the name of the object, the fail rate and the percent of total. Convert the fail rate to percent. define the fail rate. INSTRUCTIONS_END -->
-    2. Are these objects found on european beaches ? If so is their any data on how many per 100 m of beach ? <!--- INSTRUCTION_START you may use your base knowledge to answer this question, consider OSPAR results INSTRUCTIONS_END -->
-    3. What are possible sources of these specific objects objects ? <!--- INSTRUCTION_START you may use your base knowledge to answer this question INSTRUCTIONS_END -->
-    3. Which three cities had the highest average pcs/m ? Which three had the lowest ?
-    3. Can you please provide a table with the municipal results? 
-      
-    <!--- INSTRUCTION_START\n
-
-    formatting instructions:
-
-    1. Label the summary 'Sample results' (##)\n
-    2. The label for the questions section is 'Frequently asked questions' use markdown formatting for the label (###)\n
-    3. Repeat the question (in bold) DO NOT REPEAT the instructions. and then answer\n
-
-    INSTRUCTIONS_END -->
-    """
-    return user_prompt    
-
-messages = messages_for_chat_completion(system_prompt=make_system_prompt(asum), user_prompt=make_summary_prompt())
-completed_chat = client.invoke(messages)
-summary = completed_chat.content
-
    -
    -
    -
    -
    -
    -
    # grid forecast analysis
-request = (
-    "Summarize the grid forecast section. Include an explanation of what a grid forecast or gird approxmiation is and the "
-    "method used in this report. Define what a prior is in Bayesian statistics and the how this is relevant for field observations"
-    "Explain the different assumptions of the prior"
-)
-
-
-insone = (
-    "<!-- INSTRUCTION_START Consider whether the observed data is likely to be normally distributed (use the difference between the median "
-    "and mean in summary statistics section) you can use the coeficient of variation also. "
-    " INSTRUCTION_END -->\n"
-)
-
-insthree = (
-        "<!-- INSTRUCTION_START Cite the name of the prior and the expected average and median pcs/m. INSTRUCTION_END -->\n"
-    
-)
-
-insfour = (
-    "<!-- INSTRUCTION_START Consider that the prior is comprised only of locations that are in the same geographic boundary. "
-    "Recall that the posterior is a weighted average of the prior and likelihood, so if the in-boundary prior predicts an increase "
-    "it is likely that elevated values were observed in other locations within the boundary compared to the likelihood "
-    " INSTRUCTION_END -->\n"
-)
-
-insfive = (
-    "<!-- INSTRUCTION_START Consider that the prior is comprised only of locations that are outside the geographic boundary. "
-    "Recall that the posterior is a weighted average of the prior and likelihood, so if the out-boundary prior predicts an increase "
-    "it is likely that locations outside of the region had elevated values compared to the likelihood "
-    " INSTRUCTION_END -->\n"
-)
-
-inssix = (
-    "<!-- INSTRUCTION_START You will find the observed pcs/m in the Summary statistics section. Consider the average pcs/m result of each prior in relation to the observed average "
-    "Cite the numerical differences, given the standard deviation how likely is a person to notice the increase or decrease f they take one sample ? " 
-    " INSTRUCTION_END -->\n"
-)
-questions = (
-    f"1. Why is grid approximation a reasonable modeling technique given the data ?{insone}"
-    "1a. Do you have an example of other fields or domains that use a gird approximation or bayesien methods ?"
-    "2. What is the difference between grid approximation and linear or enemble regression ?"
-    f"3. Under what prior do we expect to find the most ? The least ?{insthree}"
-    f"4. If the in-boundary grid approxmation predicts an increase or decrease, what does that say about the other samples from within the boundary ?{insfour}"
-    f"5. If the out-boundary grid approxmation predicts an increase or decrease, what does that say about the other samples from outside of the boundary ?{insfive}"
-    f"6. How different are the expected results from the observed results ? Should an increase or decrease be expected ? {inssix}"
-    
-    
-)
-
-formatting_instructions = (
-    "\n<!-- INSTRUCTION_START \n"
-    "1. Label the summary 'Forecasts and methods' (##)\n"
-    "2. The label for the questions section is 'Frequently asked questions' (###) \n"
-    "3. Repeat the question (in bold) DO NOT REPEAT the instructions. and then answer\n"
-    " INSTRUCTION_END -->\n"
-)
-
-def make_grid_approximation_prompt():
-        
-    user_prompt = (
-        
-        f'{request}\n\n'
-        f'{questions}\n\n'
-        f'{formatting_instructions}'
-    )
-
-    return user_prompt    
-
    -
    -
    -
    -
    -
    -
    messagesx = messages_for_chat_completion(system_prompt=make_system_prompt(f'{grid_f}\n\n{asum}'), user_prompt=make_grid_approximation_prompt())
-completed_chatx = client.invoke(messagesx)
-grid_forecast = completed_chatx.content
-
    -
    -
    -
    -
    -
    -
    request = (
-    "Define cluster analysis (kmeans), linear regression and ensemble methods, explain the basic assumptions of each method"
-)
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-req_inst = (
-     "<!-- INSTRUCTION_START do not quote the regression results here. Expalin the methods compeletely, explain what role the decision tree plays in ensemble methods INSTRUCTION_END -->\n"
-    
-)
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-insone = (
-    "<!-- INSTRUCTION_START The document provides a table of results. Provide that table to user and write a narrative paragraph of all the results"
-    " INSTRUCTION_END -->\n"
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-insfour = (
-    "<!-- INSTRUCTION_START The average pcs/m is given as a table in the cluster analysis subsection and given as objects per meter. "
-    "The distribution of land use values is given in the cluster analysis subsection and given as a float value that represents "
-    "the average proportion of the buffer zone occupied by the land use category. The paragraph above the table explains how to interpret the table"
-    " when you provide the results for the cluster lable the results as % of buffer occupied by land use feature INSTRUCTION_END -->\n"
-)
-
-questions = (
-    f"1. What were the r² and MSE of each test ? {insone}"
-    f"2. Given the r² and MSE of the different methods employed, how reliable do you think predictions would be based on these models ?\n"
-    f"3. Can any conlusions be drawn from these results ?\n"
-    f"4. Accroding to the cluster analysis what is the cluster that has the greatest average pcs/m ? What is the distribution of land use values within the cluster ? {insfour}"   
-)
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-formatting_instructions = (
-    "\n<!-- INSTRUCTION_START \n"
-    "1. Label the summary 'Linear and ensemble methods' (##)\n"
-    "2. The label for the questions section is 'Frequently asked questions' (###) \n"
-    "3. Repeat the question (in bold) DO NOT REPEAT the instructions. and then answer\n"
-    " INSTRUCTION_END -->\n"
-)
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-def make_regression_prompt():
-        
-    user_prompt = (
-        
-        f'{request}{req_inst}\n\n'
-        f'{questions}\n\n'
-        f'{formatting_instructions}'
-    )
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-    return user_prompt    
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    messagesxx = messages_for_chat_completion(system_prompt=make_system_prompt(lin_f), user_prompt=make_regression_prompt())
-completed_chatxx = client.invoke(messagesxx)
-linear_methods = completed_chatxx.content
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    client = ChatOpenAI(model='gpt-4')
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-def make_system_prompt(roughdraft):
-    system_prompt = (
-    "You are a researcher assigned the task of preparing a manuscript from a rough draft. "   
-    "You are tasked to correct the first draft of report. You are to ensure that the draft given to you "
-    "by the user is correct. Ensure that answers are correct by comparing the users document to the rough draft. "
-    "Ensure that any conclusions are correct by reviewing the instructions in the original document and responses in the users document."
-    "Do not change the formatting of the users document. You must return all tables that are given by the user in your response especially if they reply to a particular question."
-    "Do not use phrases like 'this report provides' or 'this study correlates' or 'according to the text' or 'this document' or anything like that. "
-    "There are instructions in the document for analysis the instructions are labeled <!--- INSTRUCTION_START  INSTRUCTION_END -->"    
-    f"{roughdraft}"
-    )
-    return system_prompt
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-# grid forecast analysis
-request = (
-    "Please check the answers provided in this document to the rough draft document that you have. Any numerical float values should be rounded to two places. "
-    "Return the document with the corrections please. Do not add any comments about the corrections, just do them and return the corrected document."
-    
-)
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-req_inf = (
-    "<!-- INSTRUCTION_START We are concerned with numrical results and conclusions. Ensure that values that are used as answers to questions are correct according to the rough draft. "
-    "Ensure that any conclusions are correct according to standard practice and the methods explained in the instructions. Do not change the markdown formatting of the document."
-    " INSTRUCTION_END -->\n"
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-def make_corections_prompt(document):
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-    user_prompt = (
-        f'{request}{req_inf}\n'
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    def make_call_to_llm(system_prompt, user_prompt, user_args, sys_args, client):
-    messages = messages_for_chat_completion(system_prompt=system_prompt(sys_args), user_prompt=user_prompt(user_args))
-    completed_chat = client.invoke(messages)
-    return completed_chat
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-corrected_summary = make_call_to_llm(make_system_prompt, make_corections_prompt,summary, asum, client)
-corrected_sampling_strat = make_call_to_llm(make_system_prompt, make_corections_prompt, sampling_stratification, sampstrat, client)
-corrected_linear = make_call_to_llm(make_system_prompt, make_corections_prompt, linear_methods, lin_f, client)
-corrected_grid = make_call_to_llm(make_system_prompt, make_corections_prompt, grid_forecast, grid_f, client)
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    Sample results

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    The survey report covers the administrative boundaries of Bern canton lake from January 1, 2020, to April 8, 2021. It includes 13 cities: Biel/Bienne, Vinelz, Brienz (BE), Spiez, Lüscherz, Nidau, Gals, Unterseen, Erlach, Thun, Beatenberg, Ligerz, and Bönigen. There are three lakes identified: Bielersee, Brienzersee, and Thunersee. The survey area is identified as Aare.

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    During the sampling period, a total of 74 samples were collected, yielding a total of 2,128 objects identified. The average density of objects found was approximately 0.69 pcs/m, with the maximum density reaching 3.88 pcs/m. The material composition of the identified objects was solely plastic, representing 100% of the total.

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    Frequently asked questions

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    1. What were the most common items found?
    -The most common items identified in the survey were:

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    • Cigarette filters: Fail rate of 83.78% (or 83.78% of the items were identified as failures in the survey), representing 73.45% of the total objects.

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    • Food wrappers; candy, snacks: Fail rate of 82.43% (or 82.43% of the items were identified as failures), representing 26.55% of the total objects.

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    2. Are these objects found on European beaches? If so, is there any data on how many per 100 m of beach?
    -Yes, these types of plastic objects, particularly cigarette filters and food wrappers, are commonly found on European beaches. Data from OSPAR indicates that the average density of litter on European beaches can range from 100 to 200 items per 100 meters of beach.

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    3. What are possible sources of these specific objects?
    -Possible sources of the identified objects include recreational activities, littering by beachgoers, and improper disposal of waste. Cigarette filters are often discarded by smokers, while food wrappers are commonly left behind from picnics and snacks enjoyed at the beach.

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    4. Which three cities had the highest average pcs/m? Which three had the lowest?
    -The three cities with the highest average pcs/m were:

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    1. Biel/Bienne: 1.79 pcs/m

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    2. Bönigen: 1.25 pcs/m

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    3. Ligerz: 1.55 pcs/m

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    The three cities with the lowest average pcs/m were:

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    1. Lüscherz: 0.06 pcs/m

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    2. Gals: 0.21 pcs/m

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    3. Spiez: 0.08 pcs/m

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    5. Can you please provide a table with the municipal results?

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    | City | Quantity | pcs/m | -|—————|———-|———–| -| Beatenberg | 29 | 0.67 | -| Biel/Bienne | 1001 | 1.79 | -| Brienz (BE) | 68 | 0.46 | -| Bönigen | 106 | 1.25 | -| Erlach | 28 | 0.49 | -| Gals | 8 | 0.21 | -| Ligerz | 24 | 1.55 | -| Lüscherz | 17 | 0.06 | -| Nidau | 15 | 0.6 | -| Spiez | 50 | 0.08 | -| Thun | 65 | 0.31 | -| Unterseen | 658 | 0.69 | -| Vinelz | 59 | 0.33 |

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    Sampling stratification

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    Sampling stratification refers to the process of dividing a population into distinct subgroups, or strata, that share similar characteristics. In the context of this survey, stratification is used to analyze how different land-use features within the buffer zones surrounding survey locations influence the survey results. Each survey location includes a buffer zone of 1,500 meters, which is characterized by various land-use features, such as buildings, wetlands, forest, public services, recreation areas, streets, vineyards, and orchards. The proportion of each land-use feature within the buffer zone helps determine the sampling stratification, allowing for a more targeted analysis of how litter density and other factors vary with different land uses.

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    Land use refers to the management and modification of natural environments into built environments such as fields, pastures, and settlements. In this report, land use categories are defined through the column names in the sampling stratification table. These categories include buildings, wetlands, forest, public services, recreation, undefined areas, streets, vineyards, and orchards, and they serve as the basis for analyzing the survey results related to litter density and environmental characteristics.

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    Frequently asked questions

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    1. How do I interpret the results in the sampling stratification table?
    -To interpret the results in the sampling stratification table, one should look at the proportion of samples collected for each land use feature across different buffer zone proportions. For example, for buildings, 31.08% of the samples were taken at locations where 0-20% of the buffer was dedicated to buildings, while 37.84% were taken where 20-40% of the buffer was dedicated to buildings. This allows for understanding how the distribution of land use within the buffer influences the survey results.

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    2. How do I interpret the results in the sampling stratification and trash density table?
    -The results in the sampling stratification and trash density table can be interpreted by examining the average objects per meter based on the proportion of buffer zones occupied by different land use features. For instance, where buildings occupy 0-20% of the buffer, the average objects per meter is 0.59, while at locations where buildings occupy 20-40% of the buffer, the average objects per meter is 0.22. This analysis reveals the relationship between land use and litter density.

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    3. Under what land use conditions would a surveyor expect to find the most trash?
    -A surveyor would expect to find the most trash in areas where buildings occupy 40-60% of the buffer, with an average of 1.79 objects per meter, and where streets occupy 60-80% of the buffer, with an average of 1.90 objects per meter. These locations indicate higher litter density associated with urban features compared to other land use categories.

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    4. Given the results in the sampling stratification table, were these surveys collected in mostly urban environments or forested?
    -The surveys were not collected in environments that strictly meet the definitions of urban or rural. The highest proportion of samples for buildings is 37.84% in the 20-40% buffer category, while for forest, it is 66.22% in the same category. Undefined areas account for 56.76% in the 40-60% buffer zone category, indicating a mixed environment rather than predominantly urban or forested.

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    Markdown(corrected_grid.content)
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    Forecasts and methods

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    Grid forecasting, or grid approximation, is a statistical method used to evaluate a function over a discretized parameter space, transforming unnormalized posterior distributions into valid probability distributions. The method employed in this report involves several steps: discretizing the continuous parameter space into a grid of points, evaluating the desired statistical function at each point, normalizing the values to ensure they sum to one, and finally calculating estimates by summing over the grid points. In this context, a prior in Bayesian statistics represents the information or beliefs about a parameter before observing the data. It’s relevant for field observations as it provides a foundation that can be updated with actual data to refine predictions. The prior assumptions in this report include the notion that land use is the best predictor of litter density, regardless of geographic location, and the similarity of land use features such as buildings and forests is crucial, with a defined similarity threshold of 0.69.

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    1. Why is grid approximation a reasonable modeling technique given the data? Grid approximation is reasonable because the observed data exhibits a significant difference between the mean (0.44) and the median (0.22), suggesting a skewed distribution rather than a normal one. The coefficient of variation of approximately 1.19 (calculated as standard deviation divided by mean) indicates considerable variability in the data, making grid approximation suitable for capturing this complexity.

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    1a. Do you have an example of other fields or domains that use a grid approximation or Bayesian methods? Grid approximation and Bayesian methods are commonly utilized in fields such as environmental science for modeling pollutant dispersion, finance for risk assessment, and machine learning for probabilistic inference.

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    1. What is the difference between grid approximation and linear or ensemble regression? The primary difference is that grid approximation evaluates a range of possible values over a parameter space, whereas linear regression finds a linear relationship between variables, and ensemble regression combines multiple models to improve predictive performance. Grid approximation does not assume a specific functional form for the relationship between variables, which allows for greater flexibility.

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    2. Under what prior do we expect to find the most? The least? The in-boundary prior is expected to yield the highest average litter density, with a mean of 0.44 pcs/m and a median of 0.22 pcs/m. Conversely, the out-boundary prior is expected to yield lower values, with a mean of 0.40 pcs/m and a median of 0.27 pcs/m.

      3. -

    3. If the in-boundary grid approximation predicts an increase or decrease, what does that say about the other samples from within the boundary? If the in-boundary prior predicts an increase, it suggests that elevated litter density values were observed in other locations within the geographic boundary, indicating a consistent trend across samples.

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    4. If the out-boundary grid approximation predicts an increase or decrease, what does that say about the other samples from outside of the boundary? If the out-boundary prior predicts an increase, it implies that locations outside the region had elevated litter density values compared to the likelihood, indicating that trends in litter density may be influenced by land use rather than just geographic location.

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    5. How different are the expected results from the observed results? Should an increase or decrease be expected? The observed average pcs/m is 0.44, while the in-boundary prior average is 0.44, indicating a difference of approximately 0.00. Given the standard deviation of 0.52 for the in-boundary prior, it is likely that a single sample may not statistically capture this increase, as observed values could fall within a range influenced by variability.

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    Linear and ensemble methods

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    Cluster analysis, specifically K-means clustering, is a method used to partition a dataset into distinct groups, or clusters, based on feature similarities. The K-means algorithm operates through an iterative process where it assigns data points to the nearest cluster centroid and then recalculates the centroids based on the assigned points. The key assumptions of K-means include that the clusters are spherical in shape, equally sized, and that the number of clusters (K) is predetermined.

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    Linear regression is a statistical approach for modeling the relationship between a dependent variable and one or more independent variables. It assumes a linear relationship between variables, meaning that changes in the independent variable(s) will lead to proportional changes in the dependent variable. Basic assumptions include linearity, independence of errors, homoscedasticity (constant variance of errors), and normality of error terms.

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    Ensemble methods combine multiple predictive models to improve performance. They often use decision trees as the base learners due to their ability to model complex relationships. The ensemble approach assumes that combining the predictions of multiple models can lead to better accuracy than any single model. Common ensemble methods include Bagging, which reduces variance by averaging predictions, and Boosting, which focuses on correcting errors made by previous models.

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    Frequently asked questions

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    What were the r² and MSE of each test?
    -The results for the different regression models are as follows:

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    • Linear Regression: R² = 0.27, MSE = 0.46

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    • Random Forest Regression: R² = 0.25, MSE = 0.47

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    • Gradient Boosting Regression: R² = 0.43, MSE = 0.36

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    • Theil-Sen Regressor: R² = 0.36, MSE = 0.41

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    • Bagging: Gradient Boosting Regression: R² = 0.42, MSE = 0.37

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    • Voting: R² = 0.37, MSE = 0.40

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    These results indicate the performance of each regression model, with R² values showing the proportion of variance explained and MSE indicating the average squared error of predictions.

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    Given the R² and MSE of the different methods employed, how reliable do you think predictions would be based on these models?
    -The R² values range from approximately 0.25 to 0.43, indicating that none of the models fit the data particularly well. The MSE values suggest moderate error levels, with the Gradient Boosting Regression showing the best performance in terms of both R² and MSE. Overall, predictions from these models may be considered somewhat reliable, but further tuning and validation would be necessary to enhance accuracy.

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    Can any conclusions be drawn from these results?
    -The results suggest that while some regression models perform better than others, there is room for improvement in both the R² and MSE metrics across the board. The Gradient Boosting Regression model demonstrates the highest R² value, indicating it captures more variability in the data compared to the other models. This suggests that ensemble methods can potentially enhance predictive performance, but the overall reliability of predictions remains limited.

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    According to the cluster analysis, what is the cluster that has the greatest average pcs/m? What is the distribution of land use values within the cluster?
    -Cluster 0 has the greatest average of 1.55 pcs/m. The distribution of land use values within this cluster is as follows: buildings occupy 14% of the buffer zone, wetlands occupy 0%, forest occupies 31%, public services occupy 19%, recreation occupies 1.4%, undefined land use occupies 30%, streets occupy 27%, vineyards occupy 19%, and orchards occupy 0%.

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    Empirical Bayes

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    Empirical Bayes#

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    We consider that forecasting or predicting is the process of making statements about events that have yet to occurr. In this case we are using historical results to form our opinion about the probability of an event in the future. The event we are considering is rather pedestrian:

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    What will I find at the beach today, given what has been found at other similar beaches or what was found at the beach in the past ?

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    Which means that the estimation of the most common objects we are likely to find is based on our own experience as well as the experience of others under similar conditions.

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    Our first consideration, however, is wether or not our research question is comensurate with our assumptions of the model. Otherwise no amount of mathematical manipulation will persuade a reasonable individual that an outstanding or extreme result is probable when there is no evidence that rises to the same level.

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    Assumptions of the model about the sample data#

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    The data is assumed to be subject to the experience of the surveyor and each survey is independent and identically distributed. We add to these basic assumptions the particularities of the domain:

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    1. Locations that have similar environmental conditions will yield similar survey results

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    2. There is an exchange of material (trash) between the beach and body of water

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    3. Following from two, the material recovered at the beach is a result of the assumed exchange

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    6. Surveys are not accurate

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      • Some objects will be misidentified

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    Following 1 through 6: the survey results are a reasonable estimate of the minimum number of objects that were present at the time the survey was completed.

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    Conditional probability#

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    Conditional probability is a fundamental concept in probability theory that describes the probability of an event occurring given that another event has already occurred. It is denoted as \(P(A∣B)\), which reads as “the probability of A given B”.

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    The conditional probability of event (A) given event (B) is defined as:

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    where:

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    • \(P(A \cap B)\) is the joint probability of both \(A\) and \(B\) occurring.

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    • \(P(B)\) is the probability of event \(B\) occurring, provided that \(P(B) > 0\).

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    Bayes’ theorem#

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    Bayes’ Theorem is a fundamental principle in probability theory and statistics that describes the probability of an event based on prior knowledge of conditions that might be related to the event. It allows for the updating of probabilities as new evidence or information becomes available. It is derived from the definition of conditional probability.

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    Deriving Bayes theorem

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    For events (A) and (B):

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    Prior knowledge#

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    In the context of Bayes’ theorem, the term “prior” refers to the prior probability, which is the probability of an event or hypothesis before any new evidence or data is taken into account. It represents the initial degree of belief in a particular outcome based on existing knowledge or assumptions.

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    In this use case the prior is what we beleive we will find at the beach, before we get to the beach, given everything we know about beaches and litter in Switzerland. Our beliefs are based on the cumulative experience from all previous visits to the beach, or beaches that are similar. Our beliefs come from what we have actually experienced.

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    Mathematically, if we are trying to determine the probability of a hypothesis A given new evidence B, the prior probability is denoted as P(A). It is the baseline probability of A before considering the new evidence provided by B.

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    Bayes’ Theorem uses the prior probability along with the likelihood of the evidence given the hypothesis and the marginal probability of the evidence to update the probability of the hypothesis. This updated probability is called the posterior probability.

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    Empirical Bayes#

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    Empirical Bayes methods are statistical techniques that combine the principles of Bayesian inference with empirical data. These methods use data to estimate the prior distribution, which is then used in the Bayesian framework to update probabilities and make inferences. Using this method means that our prior distribution is testable in the sense of Jaynes

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    A piece of information I concerning a parameter \(\theta\) will be called testable if, given any proposed prior probability assignment \(f( \theta )\) \(d\theta\), there is a procedure which will determine unambiguously whether \(f( \theta )\) does or does not agree with the information I. (Jaynes,1968)

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    In traditional Bayesian analysis, the prior distribution is chosen based on subjective beliefs or historical data. In contrast, empirical Bayes methods estimate the prior distribution directly from the observed data, making the process more objective and often more practical in large-scale problems. (Petrone, S. et al, 2014)

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    Conjugate prior#

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    In Bayesian statistics, a conjugate prior is a prior distribution that, when combined with a given likelihood through Bayes’ theorem, results in a posterior distribution of the same family as the prior. This property simplifies the computation of the posterior distribution.

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    1. Jaynes, E.T.: “Probability Theory: The Logic of Science”: Emphasized the logical consistency and practical advantages of conjugate priors.

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    2. Gelman, A. et al.: “Bayesian Data Analysis” : discusses conjugate priors in the context of hierarchical models and practical Bayesian analysis.

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    Deriving conjugate relationship#

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    The binomial, multinomial, and Dirichlet distributions are intrinsically linked through the concept of conjugate priors in Bayesian statistics. The binomial distribution describes the probability of a fixed number of successes in a series of independent trials, with a success probability p. When modeling this in a Bayesian framework, the Beta distribution is used as a conjugate prior for p. This means that the posterior distribution, after observing data, remains a Beta distribution, simplifying the update process.

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    Extending this to multiple categories, the multinomial distribution generalizes the binomial by modeling the counts of outcomes across multiple categories. The Dirichlet distribution serves as the conjugate prior for the multinomial distribution, just as the Beta distribution does for the binomial. When using a Dirichlet prior, the posterior distribution after observing data also remains a Dirichlet distribution.

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    The binomial distribution models the number of successes in n trials, given a success probability p:

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    -\[P(X = k | p) = \binom{n}{k} p^k (1 - p)^{n - k}\]
    -

    The Beta distribution is a conjugate prior for the binomial likelihood, parameterized by \(\alpha\) and \(\beta\):

    -
    -\[P(p | \alpha, \beta) = \frac{p^{\alpha - 1} (1 - p)^{\beta - 1}}{B(\alpha, \beta)}\]
    -
    -
    -
    -
    -
    -
    -
    -Posterior Distribution:
    -

    Combining the likelihood and prior using Bayes’ theorem gives the posterior distribution:

    -
    -\[P(p | k, n) \propto p^k (1 - p)^{n - k} \cdot p^{\alpha - 1} (1 - p)^{\beta - 1}\]
    -
    -\[P(p | k, n) \propto p^{k + \alpha - 1} (1 - p)^{n - k + \beta - 1}\]
    -

    Which is a Beta distribution:

    -
    -\[P(p | k, n) = \text{Beta}(p | k + \alpha, n - k + \beta)\]
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    -Generalize binomial to multinomial
    -

    The multinomial distribution generalizes the binomial to more than two categories. For counts -\(\mathbf{x} = (x_1, x_2, \ldots, x_K) \quad \text{in} \quad K \quad \text{categories, given probabilities} \quad \mathbf{p} = (p_1, p_2, \ldots, p_K)\):

    -
    -\[P(\mathbf{x} | \mathbf{p}) = \frac{n!}{x_1! x_2! \cdots x_K!} p_1^{x_1} p_2^{x_2} \cdots p_K^{x_K}\]
    -

    where: \(n = \sum_{i=1}^K x_i\)

    -
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    -The conjugate prior to the multinomial
    -

    The Dirichlet distribution is a conjugate prior for the multinomial distribution, parameterized by α=(α1​,α2​,…,αK​):

    -

    \(P(\mathbf{p} | \boldsymbol{\alpha}) = \frac{1}{B(\boldsymbol{\alpha})} \prod_{i=1}^K p_i^{\alpha_i - 1}\)

    -

    where B(α) is the multivariate Beta function.

    -
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    -
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    -
    -Posterior Distribution
    -

    The posterior distribution is a combination of the likelihood and prior:

    -
    -\[P(\mathbf{p} | \mathbf{x}) \propto \left( \prod_{i=1}^K p_i^{x_i} \right) \left( \prod_{i=1}^K p_i^{\alpha_i - 1} \right)\]
    -

    Which is a Dirichlet distribution:

    -

    \(P(\mathbf{p} | \mathbf{x}) \propto \prod_{i=1}^K p_i^{x_i + \alpha_i - 1}\)

    -
    -
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    -
    -
    -
    -
    -Posterior with updated parameters
    -
    -\[P(\mathbf{p}|\mathbf{x}) = \text{D}(\mathbf{p}|x_1 + \alpha_1, \ldots, x_K + \alpha_K)\]
    -

    Where D is a Dirichlet distribution

    -
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    -

    Grid Approximation#

    -

    Grid approximation is a technique used in numerical analysis and statistical inference to approximate the values of a continuous function or parameter by evaluating it at a discrete set of points. This involves creating a grid of possible values within a defined range and calculating the function or parameter at each grid point. We are using \(P(\mathbf{p}|\mathbf{x}) = \text{D}(\mathbf{p}|x_1 + \alpha_1, \ldots, x_K + \alpha_K)\) to approximate the grid.

    -
    -
    -
    -

    Empirical Bayes grid approximation using a conjugate prior#

    -

    Empirical Bayes grid approximations involves estimating the prior and posterior distributions of parameters using a discretized set of values. In the context of the multinomial-Dirichlet conjugate relationship, this method is particularly effective. The Dirichlet distribution serves as the prior for the multinomial likelihood, and empirical Bayes methods estimate this prior directly from the data. By defining a grid of possible parameter values, in this case spaced every 0.1 units from 0 to the maximum observed value or 100, the posterior distribution is approximated by evaluating the likelihood and updating the Dirichlet prior at each grid point.

    -

    This approach simplifies the computational complexity of Bayesian inference. Instead of integrating over a continuous parameter space, which can be analytically challenging, grid approximation transforms the problem into a finite summation. The multinomial-Dirichlet conjugate pair ensures that the posterior remains in the Dirichlet family, making the updates straightforward.

    -

    Adding probability

    -

    We have noticed that this method is sensitive to the max value of the likelihood. The further out the maximum is the more likely elevated values appear. This is because we are adding uncertainty to the points on the grid between the observed or designated max value and other observed values.

    -
    - -Default parameters and methods
    -

    Default parameters

    -
      -

    1. range of the default index \(X = \{ x \in \mathbb{R} \mid x = 0.1k, \; k \in \mathbb{Z}, \; 0 \leq x < 100 \}\)

      -
        -

      • or np.arange(0, 100, 0.1)

        • -
      -
      2. -

    2. Max range of forecast grid = \(\max_{i} \{ x_i \} \text{ or } P_{99} = \text{percentile}_{99} \{ x_i \}\)

      3. -

    3. The magnitude of the land use for each survey location is categorized in the following manner:

      4. -
    -
    -\[\begin{split} -\text{binning}(x) = -\begin{cases} -1 & \text{if } -1 \leq x < 0.2 \\ -2 & \text{if } 0.2 \leq x < 0.4 \\ -3 & \text{if } 0.4 \leq x < 0.6 \\ -4 & \text{if } 0.6 \leq x < 0.8 \\ -5 & \text{if } 0.8 \leq x \leq 1 -\end{cases}, -\text{ where x is the \% of land occupied by a land-use feature } -\end{split}\]
    -

    Distributions

    -

    The posterior distribution is \(P(\text{Likelihood} \mid \text{Prior}) \approx \text{Dirichlet}(\alpha)\) or more commonly: \(P(\theta \mid \mathbf{X}) \approx text{Dirichlet}(\alpha + \mathbf{n})\)

    -
      -

    1. \(\theta\) is the parameters of the Dirichlet distribution

      2. -

    2. \(\mathbf{X}\) is the observed data

      3. -

    3. \(\alpha\) is the parameters of the prior Dirichlet distribution

      4. -

    4. \(\mathbf{n}\) is the count data from the likelihood

      5. -
    -

    Forecasted samples

    -
    -\[\begin{split} -\begin{align*} -\theta &\sim \text{Dirichlet}(\alpha) \\ -\mathbf{X} \mid \theta &\sim \text{Multinomial}(N, \theta) -\end{align*} -\end{split}\]
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    -By the-team@ -

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    - - © Copyright 2023. -
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    Forecast

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    Canton Bern

    -

    Density of trash along lakes and rivers

    -

    This is a sample cantonal report. The structure and the format are based off of the federal report, (IQAASL). This version is intended for use as a decsion support tool. Thus, the user is expected to be familiar with the results in the federal report and the methods described in the Guide for Monitoring Marine Litter on European Seas -(The guide).

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    - -Initial assessments: stakeholder discussion and priorities.
    -

    Stakeholders should consider the following questions while consulting the report:

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    Sampling distribution:

    -
      -

    1. Are the major rivers and lakes included?

      2. -

    2. Does the sampling distribution reflect the topography and land-use of the canton?

      3. -

    3. Are the municipalities of strategic importance to the canton included?

      4. -

    4. Are their locations in the canton that should have been surveyed, according to cantonal priorities?

      5. -
    -

    Other sources of information:

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      -

    1. How do these results compare to assessments from other sources of information ?

      -
        -

      • EAWAG, EMPA other university or govt institutions

        • -

      • NGOs or volunteer assessments

        • -

      • Municipal and cantonal audits

        • -

      • Are these information sources comparable ?

        • -

      • What other sources of information are available ?

        • -
      -
      2. -

    2. Combined with t

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        -

      • In your opinion how can these different sources be

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      -
      3. -
    -

    Survey results:

    -
      -

    1. Was their more or less observed in 2021 vs the prior results?

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        -

      • What do the forecasts indicate?

        • -

      • Does this align with your personal experience?

        • -
      -
      2. -
    -

    Objects of interest:

    -
      -

    1. Are the most common currently the focus of reduction or prevention campaigns?

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        -

      • How does the canton decide priorties in this regard?

        • -

      • Did or does the object appear in any regional action plan or strategy?

        • -
      -
      2. -

    2. For objects that are the focus of prevention or reduction campaigns:

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        -

      • Are they on the most common objects list now?

        • -

      • Do they appear in the inventory ? What % of the total are they? How often are they found ?

        • -

      • What excatly was the mechanism or process that was intended to reduce the presence of the object?

        • -
      -
      3. -

    3. Are their products of regional interest that should be included in the cantonal report?

      4. -
    -

    With respect to the amount of resources attributed to prevention and mitigation:

    -
      -

    1. Are these results in line with expectations?

      2. -

    2. How do you feel the current strategy will help reduce the observed quantities?

      3. -
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    -
    -
    -
    - -Map of survey locations
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    -_images/a6ebbbcb0624c0be6e7a4f5957e7fa763651b139bf5da7efaf464eab387f89c1.png -
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    Vital statistics

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    Use case: Is their more or less ?

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    Ref : Survey report class

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    2017 - 2021

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    Features

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    lake

    count

    3

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    Administration

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    count

    location

    19

    city

    13

    canton

    1

    parent_boundary

    1

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    -_images/eafa2b53189e8c3f752fb112996c81d2d4173727331459b6c26033a911f646b2.png -
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    Survey total pcs/m 2020 - 2021 versus 2015 - 2019. All locations considered.

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    Material composition

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    - - - - - - - - - - - - - - - - - - - - -

    chemicals

    cloth

    glass

    metal

    paper

    plastic

    % of total

    1%

    1%

    5%

    3%

    2%

    84%

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    2017 - 2021

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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    result

    total

    9889

    nsamples

    98

    average

    2.81367

    5th

    0.3685

    25th

    0.88

    50th

    1.835

    75th

    3.69

    95th

    8.0485

    std

    2.63184

    max

    14.8

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    2020 - 2021

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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    result

    total

    8423

    nsamples

    74

    average

    3.08946

    5th

    0.3895

    25th

    0.9525

    50th

    2.145

    75th

    4.7575

    95th

    8.602

    std

    2.85335

    max

    14.8

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    2017 - 2019

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    result

    total

    1466

    nsamples

    24

    average

    1.96333

    5th

    0.3615

    25th

    0.455

    50th

    1.425

    75th

    3.085

    95th

    4.187

    std

    1.49082

    max

    5.48

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    - -How did we get this data ?
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    All samples Bern: 2015 - 2021

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    -_images/39cbcbbaee12e400f903272eed7a70fdb80c2fd3c9064aad2ae3ac0511b88690.png -
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    The data is a combination of observations from variety of groups in Switerland since 2015. The observations were recorded using an interpretation of the Guide for Monitoring Marine Litter on European Seas The guide. The guide and the monitoring of beach litter are part of decades of research, here is the brief history A Brief History of Marine Litter Research.

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    Common sense guidance:

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    1. The data should be considered as a reasonable estimate of the minimum amount of trash on the ground at the time of the survey.

      2. -

    2. There are many sources of variance. We have considered the following:

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      • litter density between sampling groups.

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      • litter density with respect to topographical features.

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      3. -

    3. There are differences in detect-ability and appearance for items of the same classification that are due to the effects of decomposition.

      4. -

    4. Many surveyors are volunteers and have different levels of experience or physical constraints that limit what will actually be collected and counted.

      5. -
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    -
    - -How to make a report
    -

    Survey and Land use

    -

    A report is the implementation of a SurveyReport and a LandUseReport. The SurveyReport is the basic -element and does the initial aggregating and descriptive statistics for a query.

    -

    The land-use-report accepts SurveyReport.sample_results and assigns the land-use attributes to the record. The -land-use-report provides the baseline assessment of litter density with reference to the surrounding environment.

    -

    The assessment accepts as variables the proportion of available space that a topographical feature occupies in a -circle of \(\pi r² \text{ where r = 1 500 meters}\) and the center of that circle is the survey location. -These proportions are compared to the average pieces per meter for an object or group of objects.

    -

    Create a report

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    A report can be intiated by providing the name of the canton. If your canton does not appear this is because we have no data. The prior dates will be calculated automatically, by taking all data prior to the start date of the querry.

    -
    import reports
-import geospatial
-import gridforecast
-
-# suppose you have defined your data into df
-observed_dates = {'start':'2020-01-01', 'end':'2021-12-31'}
-
-# everything that was seen before
-prior_dates = {'start':'2015-11-15', 'end':'2019-12-31'}
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-# name the canton
-canton = 'Bern'
-
-# define the data of interest
-data_of_interest = {'canton':canton, 'date_range':observed_dates}
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-# load the data
-df = session_config.collect_survey_data()
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-# filter the data. 
-filtered_data, locations = gridforeacast.filter_data(df, data_of_interest)
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-# make a survey report
-this_report = reports.SurveyReport(dfc=filtered_data)
-
-# generate the parameters for the landuse report
-target_df = this_report.sample_results
-features = geospatial.collect_topo_data(locations=target_df.location.unique())
-
-# make a landuse report
-this_land_use = geospatial.LandUseReport(target_df, features)
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    -
    -

    Each report and the inference method are documented: SurveyReport, LandUseReport, GridForecaster

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    Bern most common objects 2020 - 2021

    -

    Use case: Interpret observed values, Is their more or less ?, What % are identified

    -

    Ref : Survey report class

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    The most common objects account for 68% of all objects

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    The most common objects from the selected data. The most common objects are a combination of the top ten most abundant objects and those objects that are found in more than 50% of the samples. Some objects are found frequently but at low quantities.Other objects are found in fewer samples but at higher quantities.

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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    code

    quantity

    pcs/m

    % of total

    rate

    G27

    1671

    0.423708

    0.185091

    0.808989

    Gfrags

    1323

    0.45573

    0.146544

    0.88764

    G67

    686

    0.237753

    0.0759858

    0.775281

    G30

    589

    0.186292

    0.0652415

    0.797753

    Gfoams

    474

    0.12191

    0.0525033

    0.617978

    G200

    348

    0.121685

    0.0385467

    0.651685

    G941

    261

    0.0869663

    0.0289101

    0.494382

    G74

    240

    0.0335714

    0.026584

    0.775281

    Gcaps

    227

    0.0652809

    0.025144

    0.595506

    G112

    196

    0.0538202

    0.0217102

    0.325843

    G89

    160

    0.0566292

    0.0177226

    0.516854

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    The most common objects account for 74% of all objects

    -

    The most common objects from the selected data. The most common objects are a combination of the top ten most abundant objects and those objects that are found in more than 50% of the samples. Some objects are found frequently but at low quantities.Other objects are found in fewer samples but at higher quantities.

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    -
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    code

    quantity

    pcs/m

    % of total

    rate

    G27

    1563

    0.475676

    0.185563

    0.837838

    Gfrags

    1283

    0.535676

    0.152321

    0.945946

    G67

    661

    0.272432

    0.0784756

    0.864865

    G30

    565

    0.21527

    0.0670782

    0.824324

    Gfoams

    462

    0.142973

    0.0548498

    0.72973

    G200

    319

    0.136622

    0.0378725

    0.716216

    G941

    249

    0.101081

    0.0295619

    0.527027

    G74

    227

    0.0363971

    0.02695

    0.891892

    Gcaps

    216

    0.0747297

    0.0256441

    0.648649

    G112

    186

    0.0618919

    0.0220824

    0.364865

    G89

    159

    0.0677027

    0.0188769

    0.608108

    G904

    113

    0.0491892

    0.0134156

    0.527027

    G95

    107

    0.04

    0.0127033

    0.527027

    G25

    106

    0.0516216

    0.0125846

    0.513514

    G177

    89

    0.0331081

    0.0105663

    0.5

    -
    -
    -
    -
    -
    -
    -
    - -
    -
    -
    -
    -

    The most common objects account for 65% of all objects

    -

    The most common objects from the selected data. The most common objects are a combination of the top ten most abundant objects and those objects that are found in more than 50% of the samples. Some objects are found frequently but at low quantities.Other objects are found in fewer samples but at higher quantities.

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    -
    -
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    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    code

    quantity

    pcs/m

    % of total

    rate

    G98

    117

    0.292

    0.193388

    0.333333

    G27

    108

    0.167333

    0.178512

    0.666667

    Gfrags

    40

    0.0613333

    0.0661157

    0.6

    G200

    29

    0.048

    0.0479339

    0.333333

    G67

    25

    0.0666667

    0.0413223

    0.333333

    G30

    24

    0.0433333

    0.0396694

    0.666667

    G144

    17

    0.0306667

    0.0280992

    0.0666667

    G74

    13

    0.0122222

    0.0214876

    0.2

    G941

    12

    0.0173333

    0.0198347

    0.333333

    Gfoams

    12

    0.018

    0.0198347

    0.0666667

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    Bern land cover and land use 2020 - 2021

    -

    Use case: Find the cleanest locations

    -

    ref: Land use report, Calculating land use

    -

    Land use refers to the measurable topographic features within a cirlce of r = 1 500 m and area = \(\pi r²\) with the survey location in the middle (the buffer). The features, measured in meters squared, are given as a ratio \(\frac{\text{area of feature}}{\text{area of circle}}\). Thus a location with high percentage of buildings will have a rating or value between 60% and 100%. The pcs/m rating is the average of all locations with a land-use profile of the same rating.

    -

    The land use is further divided in to two groups: cover and use. Cover refers to those topographical features that do not overlap. That is cover features are mutually exclusive, a given area of the buffer is either one or the other of the cover features. The cover features are:

    -
      -

    • Buildings, orchards, forest, undefined, vineyards

      • -
    -

    Use refers to the activities or features that are present in one of the cover features. For example public services can be located within buildings (hospitals, schools) or in a forest (parks, nature areas). The use features are:

    -
      -

    • Pubilc services, streets

      • -
    -

    Streets

    -

    The streets are measured as the length of the road network in the cirlce with r= 1 500 m and area \(\pi r²\) and the survey location in the middle. The lengths for each location are normalized from 0 - 1. Thus in the table below, the locations that have the shortest road net work will be in category 1, the those with a more dense network will be higher. -

    -

    Land use/cover: distribution of samples and pcs/m by % of buffer attributed to the cover or use

    -
    - -
    -

    % of buffer attributed to land use or cover

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    buildings

    wetlands

    forest

    public-services

    recreation

    undefined

    streets

    vineyards

    orchards

    2

    0.314607

    0

    0.640449

    0.011236

    0

    0.123596

    0

    0

    0

    1

    0.303371

    1

    0.269663

    0.988764

    1

    0.348315

    0

    1

    1

    3

    0.258427

    0

    0.0898876

    0

    0

    0.516854

    0

    0

    0

    4

    0.101124

    0

    0

    0

    0

    0.011236

    0

    0

    0

    5

    0.0224719

    0

    0

    0

    0

    0

    0

    0

    0

    -
    -
    -

    Pieces per meter by % of buffer attributed to land use or cover

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    buildings

    wetlands

    forest

    public-services

    recreation

    undefined

    streets

    vineyards

    orchards

    1

    2.36778

    2.75809

    3.02

    2.78807

    2.75809

    3.22355

    0

    2.75809

    2.75809

    2

    2.525

    0

    2.85702

    0.12

    0

    3.09636

    0

    0

    0

    3

    4.08913

    0

    1.2675

    0

    0

    2.4187

    0

    0

    0

    4

    1.59

    0

    0

    0

    0

    0.22

    0

    0

    0

    5

    1.24

    0

    0

    0

    0

    0

    0

    0

    0

    -
    -
    - -
    -

    % of buffer attributed to land use or cover

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    buildings

    wetlands

    forest

    public-services

    recreation

    undefined

    streets

    vineyards

    orchards

    2

    0.378378

    0

    0.662162

    0

    0

    0.0810811

    0

    0

    0

    1

    0.310811

    1

    0.243243

    1

    1

    0.351351

    0

    1

    1

    3

    0.216216

    0

    0.0945946

    0

    0

    0.567568

    0

    0

    0

    4

    0.0675676

    0

    0

    0

    0

    0

    0

    0

    0

    5

    0.027027

    0

    0

    0

    0

    0

    0

    0

    0

    -
    -
    -

    Pieces per meter by % of buffer attributed to land use or cover

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    buildings

    wetlands

    forest

    public-services

    recreation

    undefined

    streets

    vineyards

    orchards

    1

    2.51652

    3.08946

    3.51444

    3.08946

    3.08946

    3.74692

    0

    3.08946

    3.08946

    2

    2.525

    0

    3.19959

    0

    0

    4.9

    0

    0

    0

    3

    5.3525

    0

    1.22571

    0

    0

    2.42381

    0

    0

    0

    4

    2.384

    0

    0

    0

    0

    0

    0

    0

    0

    5

    1.24

    0

    0

    0

    0

    0

    0

    0

    0

    -
    -
    - -
    -

    % of buffer attributed to land use or cover

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    buildings

    wetlands

    forest

    public-services

    recreation

    undefined

    streets

    vineyards

    orchards

    3

    0.466667

    0

    0.0666667

    0

    0

    0.266667

    0

    0

    0

    1

    0.266667

    1

    0.4

    0.933333

    1

    0.333333

    0

    1

    1

    4

    0.266667

    0

    0

    0

    0

    0.0666667

    0

    0

    0

    2

    0

    0

    0.533333

    0.0666667

    0

    0.333333

    0

    0

    0

    5

    0

    0

    0

    0

    0

    0

    0

    0

    0

    -
    -
    -

    Pieces per meter by % of buffer attributed to land use or cover

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    buildings

    wetlands

    forest

    public-services

    recreation

    undefined

    streets

    vineyards

    orchards

    1

    2.51652

    3.08946

    3.51444

    3.08946

    3.08946

    3.74692

    0

    3.08946

    3.08946

    2

    2.525

    0

    3.19959

    0

    0

    4.9

    0

    0

    0

    3

    5.3525

    0

    1.22571

    0

    0

    2.42381

    0

    0

    0

    4

    2.384

    0

    0

    0

    0

    0

    0

    0

    0

    5

    1.24

    0

    0

    0

    0

    0

    0

    0

    0

    -
    -
    -
    -
    -

    Forecast#

    -

    Use case: Interpret forecasted values

    -

    ref: Grid forecasts, Empirical Bayes

    -

    The applied method would best be classified as Empirical Bayes, in the sense that the prior is derived from the data (Bayesian Filtering and Smoothing or Empirical Bayes methods in classical and Bayesian inference).

    -

    Model assumptions

    -
      -

    1. Locations with similar land use attributes will have similar litter density rates

      2. -

    2. The data is a best estimate of what was present on the day of the survey

      3. -

    3. There are regional differences with respect to the density of specific objects

      4. -

    4. The locations surveyed are maintained by a public administration

      5. -
    -
    - -
    -
    -
    -
    -
    -
    -

    Weighted prior: The weighted prior is a random sample of survey results from locations outside the report area of interest with similar land use configurations. This can be interpreted as the forecast based on the assumption that the current area of interest is similar to anyother area of country. They are

    -
    -
    -
    -
    -
    -
    -_images/7d5d1ea88020e9795343fc4dee599a32d78352330700109b126298b974857970.png -
    -
    -

    Cumulative distribution of observed, sampling history and forecasts using to different priors.

    -
    -
    -
    -
    -
    -
    -
    -
    -

    Given the 99% interval of the likelihood

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    1.8149

    hdi min

    0.02

    hdi max

    6.71

    5th

    0.157

    25th

    0.535

    50th

    1.24

    75th

    2.16

    95th

    6.1115

    max predicted

    9.33

    -
    -
    -
    -

    Given the entire interval of the likelihood

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    1.8798

    hdi min

    0.06

    hdi max

    5.42

    5th

    0.1

    25th

    0.3775

    50th

    1.315

    75th

    2.84

    95th

    5.192

    max predicted

    11.39

    -
    -
    -
    -

    Given the results from similar locations (weighted prior)

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    10.1498

    hdi min

    0.24

    hdi max

    46.62

    5th

    0.427

    25th

    0.9925

    50th

    2.69

    75th

    11.26

    95th

    45.347

    max predicted

    48.13

    -
    -
    -
    -
    -
    - -
    -
    -
    -
    -
    -
    -

    Weighted prior: The weighted prior is a random sample of survey results from locations outside the report area of interest with similar land use configurations. This can be interpreted as the forecast based on the assumption that the current area of interest is similar to anyother area of country. They are

    -
    -
    -
    -
    -
    -
    -_images/482ca02bb20f3098d19fda254ee204b8489384c89d5ce713948e37ebcddaa5ff.png -
    -
    -

    Cumulative distribution of observed, sampling history and forecasts using to different priors.

    -
    -
    -
    -
    -
    -
    -
    -
    -

    Given the 99% interval of the likelihood

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    2.8944

    hdi min

    0.36

    hdi max

    8.31

    5th

    0.37

    25th

    0.87

    50th

    2.36

    75th

    3.94

    95th

    8.21

    max predicted

    9.68

    -
    -
    -
    -

    Given the entire interval of the likelihood

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    3.0586

    hdi min

    0.03

    hdi max

    10.47

    5th

    0.36

    25th

    0.84

    50th

    2.63

    75th

    3.535

    95th

    10.47

    max predicted

    14.79

    -
    -
    -
    -

    Given the results from similar locations (weighted prior)

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    15.9398

    hdi min

    0.16

    hdi max

    58.99

    5th

    0.287

    25th

    1.4025

    50th

    5.365

    75th

    28.8725

    95th

    58.857

    max predicted

    72.48

    -
    -
    -
    -
    -
    - -
    -
    -
    -
    -
    -
    -

    Weighted prior: The weighted prior is a random sample of survey results from locations outside the report area with similar land use configurations. This can be interpreted as the forecast based on the assumption that the current area of interest is similar to any other area of country.

    -
    -
    -
    -
    -
    -
    -_images/e0f7317ad7efa6ddc267415b228bfa526d5d75efbc3b310034c86b9b8b7cd8e5.png -
    -
    -

    Cumulative distribution of observed, sampling history and forecasts using to different priors.

    -
    -
    -
    -
    -
    -
    -
    -
    -

    Given the 99% interval of the likelihood

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    1.4282

    hdi min

    0.02

    hdi max

    6.59

    5th

    0.06

    25th

    0.2825

    50th

    1.06

    75th

    1.71

    95th

    6.457

    max predicted

    7.89

    -
    -
    -
    -

    Given the entire interval of the likelihood

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    1.6584

    hdi min

    0.06

    hdi max

    6.08

    5th

    0.1

    25th

    0.24

    50th

    1.05

    75th

    2.07

    95th

    6.08

    max predicted

    7.89

    -
    -
    -
    -

    Given the results from similar locations (weighted prior)

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    expected

    average

    1.3009

    hdi min

    0.02

    hdi max

    3.68

    5th

    0.16

    25th

    0.22

    50th

    0.87

    75th

    1.56

    95th

    3.68

    max predicted

    5.39

    -
    -
    -
    -
    -
    -
    -
    -
    -

    Lakes and rivers sampled - all data#

    -
    -
    -
    -

    Lakes sampled

    -
    - - - - - - - - - - - - - - - - - - - - -

    feature_name

    sample_id

    pcs/m

    bielersee

    50

    4.0752

    brienzersee

    5

    3.962

    thunersee

    43

    1.21326

    -
    -
    -
    -

    Rivers sampled

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    feature_name

    sample_id

    pcs/m

    aare

    61

    1.2723

    aarenidau-buren-kanal

    3

    1.25667

    emme

    9

    0.598889

    langeten

    11

    1.93909

    schuss

    2

    1.035

    zulg

    11

    0.634545

    -
    -
    -
    -
    -
    -
    -

    Municipal results lakes and rivers#

    -
    -
    -
    -

    Lakes sampled

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    city

    sample_id

    quantity

    pcs/m

    Beatenberg

    2

    104

    2.425

    Biel/Bienne

    15

    3209

    5.61333

    Brienz (BE)

    3

    696

    4.48667

    Bönigen

    2

    277

    3.175

    Erlach

    1

    101

    1.83

    Gals

    2

    48

    1.28

    Ligerz

    3

    163

    7.4

    Lüscherz

    5

    202

    0.746

    Nidau

    1

    63

    2.52

    Spiez

    26

    838

    0.786923

    Thun

    3

    276

    1.4

    Unterseen

    12

    1879

    1.88833

    Vinelz

    23

    2033

    3.77043

    -
    -
    -
    -

    Rivers sampled

    -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

    city

    sample_id

    quantity

    pcs/m

    Belp

    11

    60

    0.111818

    Bern

    32

    1892

    1.02219

    Biel/Bienne

    2

    98

    1.035

    Brügg

    1

    36

    1.02

    Burgdorf

    1

    41

    0.87

    Kallnach

    2

    82

    1.315

    Köniz

    12

    757

    2.86333

    Langenthal

    11

    301

    1.93909

    Muri bei Bern

    2

    90

    1.63

    Port

    2

    118

    1.375

    Rubigen

    1

    57

    3.2

    Steffisburg

    11

    114

    0.634545

    Utzenstorf

    8

    41

    0.565

    Walperswil

    1

    14

    0.22

    -
    -
    -
    -
    -
    - - - - -
    - - - - - - - - -
    - - - -
    - - -
    -
    - Contents -
    -
    - -
    - - -
    -
    - -
    - -
    - -

    -By the-team@ -

    - -
    - -
    - - -

    - - © Copyright 2023. -
    - -

    - -
    - -
    - -
    - -
    - -
    - -
    -
    - - -
    -
    -
    - - - - - -
    -
    - - \ No newline at end of file diff --git a/docs/objects.inv b/docs/objects.inv index b5c9e70..2833329 100644 Binary files a/docs/objects.inv and b/docs/objects.inv differ diff --git a/docs/project.html b/docs/project.html index fac763f..5dd6427 100644 --- a/docs/project.html +++ b/docs/project.html @@ -60,8 +60,8 @@ - - + + @@ -167,35 +167,27 @@ -

    Data and reporting

    +

    Situation and solutions

    -

    Methods and classes

    +

    Example reports

    Annex

    @@ -359,28 +351,39 @@

    Contents

    Proposal#

    -

    The challenge in front of us is to transform the observations into accurate and actionable information for two different purposes. There is the administration of the territory and identification of priorities with regard to plastics in the environment. Then, once the priorities have been established these new indicators must be reported on. This project concerns the infrastructure and processes necessary to identify priorities and develop indicators to reduce plastics in the environment from litter density counts.

    -

    Therefore, we propose a haromnised reporting system that is administered by regional or national NGOS in collaboration with an academic partner with the stated goal of producing reliable reports for the public administration and others who communicate on such matters. This allows administrations to identify priorities and set baseline values according to agreed upon and observed indicators.

    -

    The first report proved that a relatively small team could cover a large territory with the correct technology. This remains the case. That is why we see this project, in its current itteration, specifically attractive to stakeholders with an internal data-science team. Stakeholders with experience in python or R will feel right at home in the development environment and will be the source of many improvements. For those interested in learning the basics, we are here to coach them and help them in their projects.

    -

    The proposal is thus to establish a hub that is dedicated to the collection, cleaning, aggregating and distribution of litter density data. The distribution of the data has the primary goal of producing decision support products to local administrations and other organizations charged with reducing plastics in the environment. The hub is staffed by three people and who conduct surveys, produce value added research, teach other NGOs to collect samples, and respond to requests from local administrations. Activites or changes in protocol are considered in consultation with academic advising team.

    +

    The challenge in front of us is to transform the observations into accurate and actionable information for two different purposes. There is the +administration of the territory and identification of priorities with regard to plastics in the environment. Then, once the priorities have been established these +new indicators must be reported on. This project concerns the infrastructure and processes necessary to identify priorities and develop indicators to reduce plastics +in the environment from litter density counts.

    +

    Therefore, we propose a harmonised reporting system that is administered by regional or national NGOS in collaboration with an academic partner with +the stated goal of producing reliable reports for the public administration and others who communicate on such matters. This allows administrations to +identify priorities and set baseline values according to agreed upon and observed indicators.

    +

    The first report proved that a relatively small team could cover a large territory with the correct technology. This remains the case. +That is why we see this project, in its current iteration, specifically attractive to stakeholders with an internal data-science team. +Stakeholders with experience in python or R will feel right at home in the development environment and will be the source of many improvements. +For those interested in learning the basics, we are here to coach them and help them in their projects.

    +

    The proposal is thus to establish a hub that is dedicated to the collection, cleaning, aggregating and distribution of litter density data. +The distribution of the data has the primary goal of producing decision support products to local administrations and other organizations charged with +reducing plastics in the environment. The hub is staffed by three people and who conduct surveys, produce value added research, teach other +NGOs to collect samples, and respond to requests from local administrations. Activities or changes in protocol are considered in consultation with academic advising team.

    Goals#

    • Develop a reporting and research tool for stakeholders in the waste management, life cycle assessment and environmental monitoring sectors.

    • Increase capacity of stakeholders to monitor and report observations according to the current standard in the federal report using open source tools.

      • -

    • Assisst in the reduction and prevention of plastics in the environment

      • +

    • Assist in the reduction and prevention of plastics in the environment

    -Deliverables: three year contract
    +Deliverables: four year contract
      -

    1. 700 samples

      2. +

    2. 800 samples

    3. Revised updated federal report

    4. New cantonal and municipal reports

    5. Cloud service for cantonal and municipal reporting

      6. -

    6. Article for publication

      7. +

    7. Chat service for endusers to develop indi

    @@ -410,7 +413,7 @@

    Goals#<

  • Develop training materials and protocols with ASL

-

  • Strucutre report specifically for cantonal and municipal reporting

    +

  • Structure report specifically for cantonal and municipal reporting

    • Revise and improve the current report

    • Consider the format of the report given cantonal requirements (attached)

      • @@ -433,7 +436,7 @@

      Goals#<

    • Develop a cloud first infrastructure and chat agent

        -

      • Move all data and software assests to Infrastructure as a Service (IaaS)

        • +

      • Move all data and software assets to Infrastructure as a Service (IaaS)

      • Develop machine learning and artificial intelligence pipelines for data analysis

      • Develop Automated programming interfaces (APIs) for data collection and reporting

      • Develop a user interface for data collection and reporting

        • @@ -446,7 +449,7 @@

        Goals#< Benchmarks
          -

        1. Year one: Proposed updates and revisions to the fedral report. Prposed model for cantonal and municipal reporting.

          +

        2. Year one: Proposed updates and revisions to the federal report. Proposed model for cantonal and municipal reporting.

          • Formal research proposal for polymer identification

          • Formal research proposal for topographical features

            • @@ -457,7 +460,7 @@

            Goals#<

          • Year two:

              -

            • Assesment of software and data collection

              • +

            • Assessment of software and data collection

            • Revised report with current data

            • Update on capacity building

            • End of year two:

              @@ -477,13 +480,19 @@

              Goals#<

            • Proposed changes to app and report

            • Final report:

                -

              1. implementation of feeedback

                2. +

              2. implementation of feedback

              3. 200 samples

              4. cloud service for cantonal and municipal reporting

            • +

          • Year four:

            +
              +

            • Testing and implementation

              • +

            • 100 samples

              • +
            +

        @@ -531,20 +540,20 @@

        Interested ?

        previous

        -

        Forecast

        +

        The role of the llm assistant

        next

        -

        Survey report class

        +

        References

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      -

      Problem and objectives

      +

      Situation and solutions

      • The role of the llm assistant
      • Proposal
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        Rough draft Survey report

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        Rough draft Survey report#

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        Title : <Survey report canton Bern 2015-11-15 2021-12-31>#

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        Objects in data

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        Cigarette filters, Food wrappers; candy, snacks, Straws and stirrers, Cigarette filters, Food wrappers; candy, snacks, Straws and stirrers

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        Administrative boundaries Bern 2015-11-15 2021-12-31 : Cities, cantons, survey areas and survey locations#

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        The number and and names of the cities, cantons and surveys included in this report

        -

        The analysis encompasses a total of 19 survey locations, which are situated across 13 different cities. The sole canton represented in this data is Bern. There is one designated survey area, named Aare. The cities included are Unterseen, Biel/Bienne, Vinelz, Thun, Brienz (BE), Spiez, Lüscherz, Nidau, Beatenberg, Ligerz, Bönigen, Gals, and Erlach. Each of these locations contributes to the comprehensive dataset being analyzed.

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        count

        location

        19

        city

        13

        canton

        1

        survey areas

        1

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        Named features Bern 2015-11-15 2021-12-31 : The lakes, rivers and parks#

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        The number and names of the lakes, rivers or parks included in this report

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        In the survey data analyzed, three lakes were identified: Thunersee, Bielersee, and Brienzersee. No rivers or parks were included in the data set.

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        lake

        count

        3

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        Summary statistics Bern 2015-11-15 2021-12-31: The descriptive statistics of the survey results#

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        Bern: The average pcs/m (objects per meter or trash per meter), standard deviation, number of samples, date range, the percentile distribution included in this report.

        -

        During our beach-litter survey analysis, a total of 2,180 litter objects were identified across 74 samples collected. The average number of objects per meter was approximately 0.71. The data revealed varying levels of litter density, with the 5th percentile showing a minimal presence of 0.02 objects per meter and the 25th percentile at 0.145 objects per meter. The median, or 50th percentile, was found to be 0.355 objects per meter, while the 75th percentile climbed to 0.745 objects per meter. Notably, the 95th percentile indicated a peak of 2.598 objects per meter. The standard deviation in the litter count was 0.912, which illustrates the variability in litter presence, with a maximum recorded density of 4.04 objects per meter. The data collection spanned from January 26, 2020, to April 8, 2021.

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        total

        nsamples

        average

        5th

        25th

        50th

        75th

        95th

        std

        max

        start

        end

        result

        2180

        74

        0.710946

        0.02

        0.145

        0.355

        0.745

        2.598

        0.912234

        4.04

        2020-01-26 00:00:00

        2021-04-08 00:00:00

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        Material composition of objects Bern 2015-11-15 2021-12-31: estimated material composition#

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        Bern: The proportion of each material type according to material category

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        In the analysis of material composition, it becomes evident that plastic constitutes the entirety of the total, representing a full 100%. This singular focus on plastic highlights its dominant presence in the context under consideration.

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        material

        % of total

        plastic

        100%

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        Inventory items Bern 2015-11-15 2021-12-31 : The complete list of the objects found and indentified included in this report.#

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        The quantity, average density, % of total and fail rate per object category

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        At the beach, a comprehensive survey revealed a variety of objects. The most prevalent object identified was the cigarette filters, categorized under code G27, with a total quantity of 1,563 found, representing 71.7% of the total objects collected. Following this, food wrappers, specifically candy and snacks, accounted for 565 items under code G30, making up 25.9% of the total. Lastly, straws and stirrers were recorded under code G35 with 52 units found, which contributed to 2.4% of the total count. Together, these three categories constituted a significant majority of the beach debris collected, emphasizing the ongoing issue of waste found along coastal environments.

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        code

        quantity

        pcs/m

        % of total

        sample_id

        fails

        rate

        object

        G27

        1563

        0.475676

        0.716972

        74

        62

        0.837838

        Cigarette filters

        G30

        565

        0.21527

        0.259174

        74

        61

        0.824324

        Food wrappers; candy, snacks

        G35

        52

        0.02

        0.0238532

        74

        29

        0.391892

        Straws and stirrers

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        Sampling stratification Bern 2015-11-15 2021-12-31: The environmental features surrounding the survey location.#

        -

        Each survey location is surounded by a buffer zone of radius = 1 500 meters. The buffer zone is comprised of land-use features, each land use feature occupies a proportion of the buffer zone (0 - 100%). The land-use-profile is measured by considering the proportion of the buffer dedicated to each of land use feature that is present in the buffer zone. Each location has the same size buffer zone. What changes is how the land use features are distributed within the buffer zone, That is we can group locations by the similarity of the measured topographical features present in the buffer

        -

        The sampling stratification of the surveys revealed several key distributions of land use features. In locations where 0-20% of the buffer was dedicated to buildings, 31% of the samples were collected. Conversely, in this same proportion of buffer allocation, 100% of the samples were taken from wetlands, while 24% were associated with forest. Interestingly, 100% of the surveys included public services, recreation, and there was a 35% collection for undefined categories. Streets accounted for 45% of the samples, and all samples were taken from locations with 0-20% of the buffer dedicated to vineyards and orchards.

        -

        In the buffer zone where 20-40% was allocated, 38% of the samples were linked to buildings, with 66% in forest areas, while no samples were found in wetlands or public services. Recreation and undefined categories both accounted for 8% of the samples, and again, no data was collected on vineyards or orchards.

        -

        For areas where 40-60% of the buffer was allocated, 22% of samples were linked to buildings, while no samples were recorded for wetlands or public services. In this category, 9% of the buffers were composed of forest, with a notable 57% allocated to the undefined feature and 19% to streets.

        -

        In locations with 60-80% of the buffer dedicated to land use, only 7% of the samples were linked to buildings, and again, no samples were associated with wetlands or public services. However, 20% of the buffer was dedicated to streets with no relevant data on vineyards or orchards.

        -

        Finally, in the 80-100% buffer category, only 3% of the samples were connected to buildings, and no data was obtained from any other land use features.

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        proportion of buffer

        (‘Proportion of samples collected’, ‘buildings’)

        (‘Proportion of samples collected’, ‘wetlands’)

        (‘Proportion of samples collected’, ‘forest’)

        (‘Proportion of samples collected’, ‘public-services’)

        (‘Proportion of samples collected’, ‘recreation’)

        (‘Proportion of samples collected’, ‘undefined’)

        (‘Proportion of samples collected’, ‘streets’)

        (‘Proportion of samples collected’, ‘vineyards’)

        (‘Proportion of samples collected’, ‘orchards’)

        0-20%

        0.310811

        1

        0.243243

        1

        1

        0.351351

        0.445946

        1

        1

        20-40%

        0.378378

        0

        0.662162

        0

        0

        0.0810811

        0.0810811

        0

        0

        40-60%

        0.216216

        0

        0.0945946

        0

        0

        0.567568

        0.189189

        0

        0

        60-80%

        0.0675676

        0

        0

        0

        0

        0

        0.202703

        0

        0

        80-100%

        0.027027

        0

        0

        0

        0

        0

        0.0810811

        0

        0

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        Topography and trash density Bern 2015-11-15 2021-12-31: The changes in the observed litter density and the changes in land use#

        -

        The land use profile allows us to group locations according to the topography. Here we consdider how the observed litter density changes based on the land use feature and the proportion of the buffer-zone that the feature occupies

        -

        In the analysis of the average pieces of trash per meter observed at various topographical features, the first index, corresponding to features occupying 0-20% of the buffer, showed buildings with 0.608261, wetlands at 0.710946, forest at 0.359444, public-services at 0.710946, recreation at 0.710946, undefined at 1.14731, streets at 0.350606, vineyards at 0.710946, and orchards at 0.710946. For the second index, representing features occupying 20-40% of the buffer, buildings had an observation of 0.235714, while wetlands, public-services, and recreation had 0, forest observed 0.907959, undefined was at 1.175, streets recorded 0.681667, and both vineyards and orchards had 0. In the third index, for features occupying 40-60% of the buffer, buildings were recorded at 1.83188, with wetlands and public-services at 0, forest at 0.235714, undefined at 0.374524, streets at 0.344286, and vineyards and orchards again at 0. In the fourth index, indicating 60-80% buffer occupancy, buildings had 0.414, wetlands, forest, public-services, and recreation recorded 0, undefined at 0, and streets had a significant 1.942, while vineyards and orchards were 0. Lastly, for the fifth index, reflecting 80-100% of the buffer, buildings had 0.32, while wetlands, forest, public-services, recreation, and undefined registered 0, streets at 0.5, and both vineyards and orchards again noted 0.

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        buildings

        wetlands

        forest

        public-services

        recreation

        undefined

        streets

        vineyards

        orchards

        1

        0.608261

        0.710946

        0.359444

        0.710946

        0.710946

        1.14731

        0.350606

        0.710946

        0.710946

        2

        0.235714

        0

        0.907959

        0

        0

        1.175

        0.681667

        0

        0

        3

        1.83188

        0

        0.235714

        0

        0

        0.374524

        0.344286

        0

        0

        4

        0.414

        0

        0

        0

        0

        0

        1.942

        0

        0

        5

        0.32

        0

        0

        0

        0

        0

        0.5

        0

        0

        -
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        Cluster analysis Bern 2015-11-15 2021-12-31#

        -

        The survey locations were grouped using K-Means clustering, the optimal amoount of clusters was determined using the the elbow method. We consider the cluster composition and the proportion of each cluster dedicated to a particular land use. For example if the value for forest, cluster 1 = .45 then that means that in cluster 1, the average sample was taken from a location whose buffer zone was 45% dedicated to forest.

        -

        Bern: Cluster composition

        -

        In cluster 0, the average proportions of land use features are as follows: public services at 0.024, buildings at 0.591, forest at 0.22, undefined at 0.189, vineyards at 0, streets at 0.363896, and recreation at 0.005. In cluster 1, the values are: public services at 0.007, buildings at 0.159, forest at 0.537, undefined at 0.245, vineyards at 0, streets at 0.0845193, and recreation at 0.005. For cluster 2, the average proportions are: public services at 0.061, buildings at 0.309, forest at 0.107, undefined at 0.541, vineyards at 0.02, streets at 0.49708, and recreation at 0.025. In cluster 3, the features are distributed as follows: public services at 0.003, buildings at 0.047, forest at 0.271, undefined at 0.55, vineyards at 0, streets at 0, and recreation at 0.155. Finally, in cluster 4, the values are: public services at 0.044, buildings at 0.682, forest at 0.153, undefined at 0.149, vineyards at 0.015, streets at 0.251846, and recreation at 0.005.

        -
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        cluster

        public-services

        buildings

        forest

        undefined

        vineyards

        streets

        recreation

        0

        0.024

        0.591

        0.22

        0.189

        0

        0.363896

        0.005

        1

        0.007

        0.159

        0.537

        0.245

        0

        0.0845193

        0.005

        2

        0.061

        0.309

        0.107

        0.541

        0.02

        0.49708

        0.025

        3

        0.003

        0.047

        0.271

        0.55

        0

        0

        0.155

        4

        0.044

        0.682

        0.153

        0.149

        0.015

        0.251846

        0.005

        -
        -

        Bern: Average density per cluster

        -

        In cluster 0, the observed average is 1.23192 objects per meter of beach, while cluster 1 shows an average of 0.147857 objects. Cluster 2 has a slightly higher average at 0.492941 objects per meter. The average in cluster 3 is 0.695833 objects, and finally, cluster 4 records an average of 0.356 objects per meter of beach.

        -
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        Summary of regression methods Bern 2015-11-15 2021-12-31: The different linear models the data were tested on#

        -

        In addition to grid approximation using Bayesian techniques the following linear and ensemble regression models were used. The feature variables are the land-use features identified in the land-use profile. From the scikit-learn standard package: LinearRegression, RandomForestRegressor, GradientBoostingRegressor, TheilSennRegressor. The model with the lowest r² is then used in the BaggingRegressor and the VotingRegressor.

        -

        The regression analysis results reveal varying performance across different models. The Linear Regression model achieved an R² value of 0.322546 with a mean squared error (MSE) of 0.420651. In contrast, the Random Forest Regression model produced a lower R² of 0.260129 and a higher MSE of 0.459407. The Gradient Boosting Regression stood out with an R² of 0.440842 and an MSE of 0.347197, indicating a strong fit. The Theil-Sen Regressor recorded an R² value of 0.373587 and an MSE of 0.388957, showcasing a moderate performance. The Bagging: Gradient Boosting Regression model followed closely with an R² of 0.405025 and an MSE of 0.369437. Finally, the Voting model reported an R² of 0.381679 and an MSE of 0.383933, suggesting it performed reasonably among the tested models. Overall, the Gradient Boosting Regression model emerged as the most effective based on the highest R² and the lowest MSE.

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        Model

        R²

        MSE

        0

        Linear Regression

        0.322546

        0.420651

        1

        Random Forest Regression

        0.260129

        0.459407

        2

        Gradient Boosting Regression

        0.440842

        0.347197

        3

        Theil-Sen Regressor

        0.373587

        0.388957

        4

        Bagging:Gradient Boosting Regression

        0.405025

        0.369437

        5

        Voting

        0.381679

        0.383933

        -
        -
        -
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        Feature and permutation importance Bern 2015-11-15 2021-12-31#

        -

        Model feature importance

        -

        Feature importance is a technique used in machine learning to identify and quantify the significance of different input variables (features) in predicting the target variable. In models like decision trees, random forests, and gradient boosting machines, feature importance is often calculated by measuring how much the model’s accuracy or error changes when a particular feature is included versus when it is excluded.

        -

        The model feature importance values indicate that streets have an importance of 0.504974, followed by forest with an importance of 0.217429. Recreation is assigned an importance of 0.140989, while public-services has an importance of 0.0725408. Vineyards have an importance of 0.0534952, and buildings are given an importance of 0.00789937. Lastly, the undefined feature holds an importance of 0.0026724.

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        Feature

        Importance

        5

        streets

        0.504974

        2

        forest

        0.217429

        6

        recreation

        0.140989

        0

        public-services

        0.0725408

        4

        vineyards

        0.0534952

        1

        buildings

        0.00789937

        3

        undefined

        0.0026724

        -
        -

        Permutation feature importance

        -

        Permutation importance is a model-agnostic method for assessing the importance of individual features in a predictive model. It is particularly useful because it can be applied to any type of model, whether it’s a linear model, a decision tree, or a complex ensemble model. This method involves randomly shuffling the values of a feature in the dataset and observing the impact on the model’s performance. A significant drop in performance indicates that the feature is important.

        -

        In the model feature importance, streets have an importance value of 0.399419, followed by forest with 0.147153. Recreation holds an importance of 0.0259323, while public-services has a value of 0.0239799. Buildings have an importance of 0.0131419, and vineyards show no importance with a value of 0. The undefined feature has a minor negative importance of -0.00209017.

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        Feature

        Importance

        5

        streets

        0.399419

        2

        forest

        0.147153

        6

        recreation

        0.0259323

        0

        public-services

        0.0239799

        1

        buildings

        0.0131419

        4

        vineyards

        0

        3

        undefined

        -0.00209017

        -
        -
        -
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        Forecasts grid approximation Bern 2015-11-15 2021-12-31#

        -

        Grid approximation of the posterior is a technique used in Bayesian inference to estimate the posterior distribution of parameters by discretizing the parameter space and evaluating the posterior probability at each point on a grid. This method is especially useful when the posterior distribution does not have a closed-form solution and when the parameter space is of low dimensionality, allowing for a feasible grid search. We use two priors, one is a weigheted combination of survey results from locations similar to the likelihood. The other prior uses the samples taken from the same location, but prior to the specified date range

        -

        Bern: Weighted prior forecast

        -

        The expected average sample total is 1.3861. The minimum of the 90% Highest Density Interval (HDI) is 0.0000, while the maximum is 7.3900. The percentile rankings indicate that the 5th percentile is 0.0100, the 25th percentile is 0.2200, the median at the 50th percentile is 0.4200, the 75th percentile is 1.5000, and the 95th percentile reaches 5.8700. Finally, the maximum value predicted by the model is 13.4900.

        -
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        expected

        average

        1.3861

        hdi min

        0

        hdi max

        7.39

        5th

        0.01

        25th

        0.22

        50th

        0.42

        75th

        1.5

        95th

        5.87

        max predicted

        13.49

        -
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        Bern: Observed 99th percentile forecast

        -

        The expected average sample total is 0.5074, with a 90% Highest Density Interval ranging from a minimum of 0 to a maximum of 1.76. The percentile rankings indicate that the 5th percentile is 0, the 25th percentile is 0.1275, the 50th percentile is 0.21, the 75th percentile is 0.68, and the 95th percentile is 1.76. The maximum value predicted by the model is 3.75.

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        expected

        average

        0.5074

        hdi min

        0

        hdi max

        1.76

        5th

        0

        25th

        0.1275

        50th

        0.21

        75th

        0.68

        95th

        1.76

        max predicted

        3.75

        -
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        Municipal results Bern 2015-11-15 2021-12-31 : The average pcs/m by municipality.#

        -

        The average sample total for each municipality in the report

        -

        In an analysis of various municipalities, Beatenberg reported a total quantity of 29 objects with an average of 0.665 pieces per meter. Biel/Bienne showed a significantly higher quantity of 1,028 objects, boasting an average of 1.83667 pieces per meter. Brienz (BE) had a total of 70 objects, maintaining an average of 0.49 pieces per meter, while Bönigen accounted for 107 objects with an average of 1.255 pieces per meter. Erlach mirrored Beatenberg with 29 objects but had a lower average of 0.51 pieces per meter. Gals had a small quantity of 9 objects, yielding an average of 0.24 pieces per meter, contrasted by Ligerz, which had 25 objects at a much higher average of 1.605 pieces per meter. Lüscherz, with only 18 objects, had an exceptionally low average of 0.064 pieces per meter, whereas Nidau reported 15 objects with a 0.6 average. Spiez had a total of 51 objects, but the average stood low at 0.0814286 pieces per meter. Thun recorded 67 objects, averaging 0.32 pieces per meter. Notably, Unterseen had a substantial quantity of 669 objects and an average of 0.695833 pieces per meter, while Vinelz contributed 63 objects with an average of 0.348333 pieces per meter.

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        city

        quantity

        pcs/m

        Beatenberg

        29

        0.665

        Biel/Bienne

        1028

        1.83667

        Brienz (BE)

        70

        0.49

        Bönigen

        107

        1.255

        Erlach

        29

        0.51

        Gals

        9

        0.24

        Ligerz

        25

        1.605

        Lüscherz

        18

        0.064

        Nidau

        15

        0.6

        Spiez

        51

        0.0814286

        Thun

        67

        0.32

        Unterseen

        669

        0.695833

        Vinelz

        63

        0.348333

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        Data and reporting

        +

        Situation and solutions

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        Methods and classes

        +

        Example reports

        Annex

        diff --git a/docs/searchindex.js b/docs/searchindex.js index dfab252..b7f56e6 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"A point and a buffer": [[2, "a-point-and-a-buffer"]], "Adding features": [[13, "adding-features"]], "Administrative boundaries": [[0, "administrative-boundaries"]], "Administrative boundaries Bern 2015-11-15 2021-12-31 : Cities, cantons, survey areas and survey locations": [[12, "administrative-boundaries-bern-2015-11-15-2021-12-31-cities-cantons-survey-areas-and-survey-locations"]], "Assumptions of the model about the sample data": [[9, "assumptions-of-the-model-about-the-sample-data"]], "Bayes\u2019 theorem": [[9, "bayes-theorem"]], "Building a map of land cover": [[2, "building-a-map-of-land-cover"]], "Canton Bern Lakes": [[3, "canton-bern-lakes"]], "Categorical land use": [[6, "categorical-land-use"]], "Chroma vector store": [[5, "chroma-vector-store"]], "Cluster analysis Bern 2015-11-15 2021-12-31": [[12, "cluster-analysis-bern-2015-11-15-2021-12-31"]], "Cluster analysis and land-use": [[3, "cluster-analysis-and-land-use"]], "Conditional probability": [[9, "conditional-probability"]], "Conjugate prior": [[9, "conjugate-prior"]], "Continuous land use": [[6, "continuous-land-use"]], "Corelated pairs": [[6, "corelated-pairs"]], "Corelation matrix": [[6, "corelation-matrix"]], "Date range, number of samples, total quantity": [[0, "date-range-number-of-samples-total-quantity"]], "Deriving conjugate relationship": [[9, "deriving-conjugate-relationship"]], "Empirical Bayes": [[9, "empirical-bayes"], [9, "id1"]], "Empirical Bayes grid approximation using a conjugate prior": [[9, "empirical-bayes-grid-approximation-using-a-conjugate-prior"]], "Extracting land use values": [[2, "extracting-land-use-values"]], "Extracting street lengths": [[2, "extracting-street-lengths"]], "Fail rate": [[0, "fail-rate"]], "Feature and permutation importance Bern 2015-11-15 2021-12-31": [[12, "feature-and-permutation-importance-bern-2015-11-15-2021-12-31"]], "Feature inventory": [[0, "feature-inventory"]], "Forecast": [[10, "forecast"]], "Forecasts grid approximation Bern 2015-11-15 2021-12-31": [[12, "forecasts-grid-approximation-bern-2015-11-15-2021-12-31"]], "Goals": [[11, "goals"]], "Grid Approximation": [[9, "grid-approximation"]], "Grid forecast class": [[4, "grid-forecast-class"]], "Grid forecaster methods": [[4, "grid-forecaster-methods"]], "Haystack agents": [[5, "haystack-agents"]], "How much of the items are single use plastics (SUP) ?": [[15, "how-much-of-the-items-are-single-use-plastics-sup"]], "How much of the items can you identify ?": [[15, "how-much-of-the-items-can-you-identify"]], "Important dates": [[13, "important-dates"]], "In memory vector store : Report results": [[5, "in-memory-vector-store-report-results"]], "Interested ?": [[11, "interested"]], "Inventory items Bern 2015-11-15 2021-12-31 : The complete list of the objects found and indentified included in this report.": [[12, "inventory-items-bern-2015-11-15-2021-12-31-the-complete-list-of-the-objects-found-and-indentified-included-in-this-report"]], "Is their more now than there was before ?": [[15, "is-their-more-now-than-there-was-before"]], "Lakes and rivers sampled - all data": [[10, "lakes-and-rivers-sampled-all-data"]], "Land use class": [[6, "land-use-class"]], "Land-cover": [[2, "land-cover"]], "Land-use": [[2, "land-use"]], "Langchain agents": [[7, "langchain-agents"]], "Locations per feature": [[6, "locations-per-feature"]], "Make a land use object": [[6, "make-a-land-use-object"]], "Make a report class": [[0, "make-a-report-class"]], "Markdown documents": [[5, "markdown-documents"]], "Material composition of objects Bern 2015-11-15 2021-12-31: estimated material composition": [[12, "material-composition-of-objects-bern-2015-11-15-2021-12-31-estimated-material-composition"]], "Material report": [[0, "material-report"]], "Municipal results Bern 2015-11-15 2021-12-31 : The average pcs/m by municipality.": [[12, "municipal-results-bern-2015-11-15-2021-12-31-the-average-pcs-m-by-municipality"]], "Municipal results lakes and rivers": [[10, "municipal-results-lakes-and-rivers"]], "Named features Bern 2015-11-15 2021-12-31 : The lakes, rivers and parks": [[12, "named-features-bern-2015-11-15-2021-12-31-the-lakes-rivers-and-parks"]], "Number of samples per feature": [[6, "number-of-samples-per-feature"]], "Object summary": [[0, "object-summary"]], "Observation data": [[13, "observation-data"]], "Posterior Dirichlet counts": [[4, "posterior-dirichlet-counts"]], "Prior knowledge": [[9, "prior-knowledge"]], "Prompts and agent tools": [[1, "prompts-and-agent-tools"]], "Proposal": [[11, "proposal"]], "Public services: land-use": [[2, "public-services-land-use"]], "Quantity per feature": [[6, "quantity-per-feature"]], "Regression Analysis": [[3, "regression-analysis"]], "Report contents": [[0, "report-contents"], [6, "report-contents"]], "Retrieve location attributes: land-cover": [[2, "retrieve-location-attributes-land-cover"]], "Rivers: intersection, size and class": [[2, "rivers-intersection-size-and-class"]], "Rough draft Survey report": [[12, "rough-draft-survey-report"]], "Sample results": [[0, "sample-results"]], "Sample results summary": [[0, "sample-results-summary"]], "Sample the posterior distribution": [[4, "sample-the-posterior-distribution"]], "Sampling stratification Bern 2015-11-15 2021-12-31: The environmental features surrounding the survey location.": [[12, "sampling-stratification-bern-2015-11-15-2021-12-31-the-environmental-features-surrounding-the-survey-location"]], "Select prior data by feature weight": [[4, "select-prior-data-by-feature-weight"]], "Streets": [[2, "streets"]], "Summary of regression methods Bern 2015-11-15 2021-12-31: The different linear models the data were tested on": [[12, "summary-of-regression-methods-bern-2015-11-15-2021-12-31-the-different-linear-models-the-data-were-tested-on"]], "Summary statistics Bern 2015-11-15 2021-12-31: The descriptive statistics of the survey results": [[12, "summary-statistics-bern-2015-11-15-2021-12-31-the-descriptive-statistics-of-the-survey-results"]], "Survey report class": [[0, "survey-report-class"]], "Technical requirements": [[2, "technical-requirements"]], "The 90% HDI": [[4, "the-90-hdi"]], "The 90% interval of the predictions": [[4, "the-90-interval-of-the-predictions"]], "The counts": [[4, "the-counts"]], "The current survey data:": [[13, "the-current-survey-data"]], "The descriptive statistices": [[4, "the-descriptive-statistices"]], "The expected mean": [[4, "the-expected-mean"]], "The grid size": [[4, "the-grid-size"]], "The litter assistant": [[14, "the-litter-assistant"]], "The posterior parameters": [[4, "the-posterior-parameters"]], "The probability of x": [[4, "the-probability-of-x"]], "The survey data": [[13, "the-survey-data"]], "Title : ": [[12, "title-survey-report-canton-bern-2015-11-15-2021-12-31"]], "Topography and trash density Bern 2015-11-15 2021-12-31: The changes in the observed litter density and the changes in land use": [[12, "topography-and-trash-density-bern-2015-11-15-2021-12-31-the-changes-in-the-observed-litter-density-and-the-changes-in-land-use"]], "Undefined areas": [[2, "undefined-areas"]], "Use cases": [[15, "use-cases"]], "Using QGIS": [[2, "using-qgis"]], "Vital Statistics": [[3, "vital-statistics"]], "What is important?": [[6, "what-is-important"]], "What is the chance of finding X ?": [[15, "what-is-the-chance-of-finding-x"]], "What objects are common to all cantons ?": [[15, "what-objects-are-common-to-all-cantons"]], "Where is the cleanest beach ?": [[15, "where-is-the-cleanest-beach"]], "Why is this important?": [[6, "why-is-this-important"]], "density per feature": [[6, "density-per-feature"]], "distance to intersection": [[2, "distance-to-intersection"]], "intersection, size and class": [[2, "intersection-size-and-class"]], "machine learning": [[8, "machine-learning"]]}, "docnames": ["a_report_class", "agent_prompts_relations", "extracting_topo_data", "final_report", "forecasts", "haystackagents", "landuse_class", "langchainagents", "machine_learning", "multinomial_conjugate", "new_report", "project", "report_results-rough-draft", "the_survey_data", "titlepage", "use_cases"], "envversion": {"sphinx": 61, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1}, "filenames": ["a_report_class.ipynb", "agent_prompts_relations.ipynb", "extracting_topo_data.ipynb", "final_report.ipynb", "forecasts.ipynb", "haystackagents.ipynb", "landuse_class.ipynb", "langchainagents.ipynb", "machine_learning.ipynb", "multinomial_conjugate.md", "new_report.ipynb", "project.md", "report_results-rough-draft.md", 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5, "math": 7, "method": [0, 1, 2, 3, 4], "minimum": 5, "monitor": 8, "municip": 8, "never": 5, "observ": [8, 9], "one": 5, "previou": 7, "profil": 5, "propos": 6, "protect": 8, "protocol": 7, "qgi": 5, "refer": 7, "regress": 3, "report": [8, 9], "resourc": 8, "result": [0, 1, 2, 3, 4], "role": 8, "sampl": [0, 1, 2, 3, 4, 5], "similar": 5, "solut": 8, "stratif": [0, 1, 2, 3, 4], "studi": 7, "summari": [0, 1, 2, 3, 4], "survei": [0, 1, 2, 3, 4, 8], "switzerland": 7, "us": 5, "valu": 5, "volunt": [8, 9]}}) \ No newline at end of file diff --git a/_build/html/the_llm_assistant.html b/docs/the_llm_assistant.html similarity index 99% rename from _build/html/the_llm_assistant.html rename to docs/the_llm_assistant.html index 31b21e0..13a9e66 100644 --- a/_build/html/the_llm_assistant.html +++ b/docs/the_llm_assistant.html @@ -171,7 +171,7 @@
      -

      Problem and objectives

      +

      Situation and solutions

      • The role of the llm assistant
      • Proposal
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        The survey data#

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        Once the surveyor has entered the data for the observations, there are labels attached to each record that identify attributes of the survey location. These labels are used for grouping records or collecting additional information about the survey location or the object found. Once the labels are complete the data is ready for analysis.

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        Observation data#

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        This data is received from the client in two packets:

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        ** The data is all formatted in pcs/m, this is set to the units used for reporting baseline values

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        Adding features#

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        Survey locations are predefined, or must be configured before entering data for a survey. The configuration process has several steps.

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        1. Identify the correct city and canton name

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        3. Identify the riverbassin or geographic area of the location

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        4. Calculate the land use ratios for the location

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        5. For lakes, determine the location and distance to river intersections

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        6. The plain english (french, german) description of the code/object

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        The following codes are aggregated together unless otherwise specified:

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        • ‘Gfoams’: ‘G81’, ‘G82’, ‘G83’

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        • ‘Gfrags’: ‘G78’, ‘G79’, ‘G80’, ‘G75’, ‘G76’, ‘G77’

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        • ‘Gcaps’: ‘G21’, ‘G22’, ‘G23’, ‘G24’

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        The unaggregated data is available on the repo using the following file files from the data/end_process/ directory:

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        Important dates#

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        The dates of the sampling campaigns are expanded to include the surveys that happened between large organized campaigns. The start and end dates are defined below.

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        Attention!! The codes used for each survey campaign are different. Different groups organized and conducted surveys using the MLW protocol. The data was then sent to us.

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        MCBP: November 2015 - November 2016. The initial sampling campaign. Fragmented plastics (Gfrags/G79/G78/G76) were not sorted by size. All unidentified hard plastic items were classified in this manner.

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        • start_date = 2015-11-15

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        • end_date = 2017-03-31

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        SLR: April 2017 - May 2018. Sampling campaign by the WWF. Objects less than 2.5 cm were not counted.

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        • start_date = 2017-04-01

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        • end_date = 2020-03-31

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        IQAASL: April 2020 - May 2021. Sampling campaign mandated by the Swiss confederation. Additional codes were added for regional objects.

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        • start_date = 2020-04-01

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        • end_date = 2021-05-31

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        Plastock (not added yet): January 2022 - December 2022. Sampling campaign from the Association pour la Sauvegarde du Léman. Not all objects were counted, They only identified a limited number of objects.

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        The current survey data:#

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        <class 'pandas.core.frame.DataFrame'>
-Index: 298848 entries, 0 to 88214
-Data columns (total 16 columns):
- #   Column           Non-Null Count   Dtype  
----  ------           --------------   -----  
- 0   sample_id        298848 non-null  object 
- 1   code             298848 non-null  object 
- 2   quantity         298848 non-null  int64  
- 3   pcs/m            298848 non-null  float64
- 4   feature_name     298848 non-null  object 
- 5   location         298848 non-null  object 
- 6   parent_boundary  298848 non-null  object 
- 7   length           298848 non-null  float64
- 8   groupname        298848 non-null  object 
- 9   city             298848 non-null  object 
- 10  canton           298848 non-null  object 
- 11  feature_type     298848 non-null  object 
- 12  en               298848 non-null  object 
- 13  fr               298848 non-null  object 
- 14  de               298848 non-null  object 
- 15  date             298848 non-null  object 
-dtypes: float64(2), int64(1), object(13)
-memory usage: 38.8+ MB
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        Author: hammerdirt-analyst
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        Data and reporting

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        Situation and solutions

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        Methods and classes

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        Example reports

        Annex

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        The litter assistant

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        Reporting volunteer observations

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        The litter assistant

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        The litter assistant#

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        Reporting volunteer observations#

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        This is the proof of concept for a distributed reporting system of marine litter density using data from volunteers.

        Recent changes
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        September 25: Added llm assisted reporting

        June 24: Added responses to use cases

        June 22: Added methods to calculate landuse profile using Geopandas.

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        This is the proposed format and layout for an up-dated survey of the trash along swiss rivers, lakes and hiking trails. We have created reports for five cantons and one that provides a federal perspective.

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        There have been developments in the domain of beach litter reporting since the first federal project. The Guide for Monitoring Litter on European seas was updated in 2023, the code system has changed for classifying objects and in May 2024 a guide for monitoring and removing plastics from inland waters was released.

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        Developments in the fields of machine learning (ML) and artificial intelligence (AI) give us new ways to assess the results of surveys and synthesise the current research. Topics of interest for those charged with reducing or preventing plastics in the environment.

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        This is an application of large language models (llms) and machine learning to provide summary reports of volunteer observations +of marine litter using the OSPAR, JRC or NOAA methods for counting beach litter.

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        The application provides summary reports of exising data and provides forecasts for a region, city or body of water. The llm +acts first as a transcriber of test results and then as an assistant to provide a written report and resource package that can +be either used directly or integrated into other documents.

        @@ -376,6 +372,9 @@

        The litter assistant
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        This application minimizes the cost of reporting and evaluating beach litter density and uses geospatial analysis to leverage +the use of data from other disparate locations. Most importantly, decision makers and stakeholders have access to reliable, +readable reports that allow them to communicate effectively and make informed decisions.

        The data in these reports is a combination of observations from variety of groups in Switerland since 2015. The observations were recorded using an interpretation of the Guide for Monitoring Marine Litter on European Seas The guide. The guide and the monitoring of beach litter are part of decades of research, here is the brief history A Brief History of Marine Litter Research.

        @@ -433,11 +432,11 @@

        The litter assistant

        next

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        Canton Bern Lakes

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        The role of the llm assistant

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        Use cases#

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        How each stake holder interprets the data is dependent on the use case. Here we present the answers to some of the most common questions that can be answered using the report or the methods desccribed in this document.

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        For an example we will use the results from the lakes in Bern.

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        Is their more now than there was before ?#

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        How do you know ? The best way to verify is to take more samples. However, the previous results in the canton and the results from locations outside the canton with similar land-use cahracteristics are good indicators.

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        From the report we can identify several key pieces of information that will help us make the determination.

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        Consider the observed results

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        ref: Bern vital statistics, ref: Bern most common

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        1. Vital statisitics: The average pcs/m of trash was greater in 2021 than 2017-2019

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        2. The combined pcs/m of the most common objects (74% of all objects) is 2.3 pcs/m. That is .4 pcs/m greater than all the objects from 2017-2019

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        Consider the forecasted values

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        ref: Bern forecasts, ref: Empirical Bayes, ref: Forecast class

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        1. Given the 99th percenitle of 2021, we expect the values for 2025 to be approximately equal 2017-2019

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        2. If we assume the maximum value of 2021 was not a mistake, on average we expect to find more in 2025

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        3. Considering random samples from locations outside of the canton from locations with similar land-cover we expect to find more

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        Conclusion: The expected average survey result for lakes in the canton of Bern is expected to increase from 1.96 pcs/m in 2017 - 2019 to 3.06 in 2025. The campaign of 2017-2019 only had 24 samples versus 74 in 2021. Given that the sampling campaigns were managed by different organizations and were initiated for different purposes we can not be sure about the magnitude of the increase. However, the results from other lakes in Switzerland suggest that an increase is more likely than a decrease.

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        Notes: Comparing the sample totals is not the best way to make this type of analysis. We know that 74% of the total can be accounted for by 15 different objects. Comparing like items or grouping like items would provide a more accurate representation of the expected sample results for 2025.

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        Recommended actions: Set a sampling strategy for the canton. Collect at least as many samples from the same lakes as 2021 and be sure that a portion of those samples come from the same locations as 2021.

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        Where is the cleanest beach ?#

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        How do you find the cleanest locations ? We can make a determination based on the sampling history or we can use the land-use profile to define the characteristics of what the cleanest beach may look like.

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        Use the sampling history

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        ref: Bern municipal results

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        The municipalites with lowest average pcs/m and more than three samples is Lüscherz with 0.75 pcs/m (Bielersee) and Spiez with 0.79 pcs/m (Thunersee).

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        Use the land use profile

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        ref: Bern rate per feature, ref: land-use, ref: Land use classe

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        Survey locations with at least 40% - 60% of the land attributed to forest or undefined use have the lowest average pcs/m. Together these two land-use categories account for 50% of samples. Notice that urban locations (80% - 100% buildings) also have a very low average result. This is the inverse of what is expected in general.

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        Conclusion: The two locations with the lowest observed average pcs/m fit the expected land-use profile. However, the results in urban locations may be of interest given that that the average results is 50% less than we would find in other cantons under the same land-profile.

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        Notes: The sampling profile should approximate the profile of the canton. For example if the region is mainly agricultural and all the samples come from the urban centers then the sampling is not representative of the envrironment.

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        Recommended actions: Set a sampling strategy for the canton. With local and regional stakeholders identify the sampling locations that best represent the geography of the canton.

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        How much of the items are single use plastics (SUP) ?#

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        How are you defining single use plastics ? The definition of SUP has not been established by federal or cantonal authorities. Here we consider the obvious choices and exclude cigarette end and other tobaco products.

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        Single use plastics:

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        1. PET bottles

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        2. Plastic bottle caps

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        3. Straws, stirrers

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        4. Plastic cotton swabs

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        5. Fast food or to go containters

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        6. Plastic bags

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        10. Cups, lids, single use foamed and hard plastics

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        11. Medical; containers/tubes/ packaging

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        12. Diapers, wipes and sanitary pads

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        Use the object inventory

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        ref: Survey reports

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        The object inventory is included with each report. It gives the summary result of all objects identified from the surveys (below). By adding up the % of total of the all the objects identified as single use plastics we find that on the shores of lakes in Bern 14% (1190/8423) of the trash was single use plastics.

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        Conclusion: SUP are about 14% of the total found in 2021. Which means that approximately 80% of the objects found are not classified as SUP.

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        Notes: This finding is in agreement with massive amount of pressure on consumers to do the the right thing. Furthermore, municipalities invest a siginifigant portion of their budgets in maintaining the shoreline of lakes.

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        Recommended actions: Stakeholders should define a list of objects that can be standardized and takes into account observations in the field.

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        Object inventory Bern lakes, single use plastics

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        quantitypcs/m% of totalfail rate
        description
        Food containers single use foamed or plastic440.020.010.36
        Medical; containers/tubes/ packaging190.010.000.22
        plastic caps, lid rings: G21, G22, G23, G242160.070.030.65
        Cotton bud/swab sticks1070.040.010.53
        Food wrappers; candy, snacks5650.220.070.82
        Lollypop sticks530.020.010.36
        Cups, lids, single use foamed and hard plastic400.020.000.30
        Cutlery, plates and trays140.010.000.16
        Straws and stirrers520.020.010.39
        Drink bottles > 0.5L10.000.000.01
        Drink bottles < = 0.5L60.000.000.05
        Bottles and containers, plastic non food/drink30.000.000.01
        Generic plastic bags10.000.000.01
        Small plastic bags; freezer, zip-lock etc.140.010.000.12
        Mesh bags40.000.000.05
        Dog feces bag90.000.000.08
        Bags60.000.000.04
        Sanitary pads /panty liners/tampons and applicators130.010.000.15
        Diapers - wipes230.010.000.22
        -
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        How much of the items can you identify ?#

        -

        Preventing or mittigating plastics in the environment depends on how well you can identify the objects that are present.

        -

        Unidentified items: Gfrags, Gfoams

        -

        ref: Bern most common

        -

        There are two categories that are specifically for objects that are found but can not be identified. Note that if an object is found AND it can be indentified but it does not fit into and existing category a new category is created.

        -

        Conclusion: About 20% of the objects found in the canton were unidentified.

        -

        Notes: The correct idenitification of objects is a team effort. Surveyors with little experience tend to have a greater percentage of unidentified objects in their surveys.

        -

        Recommended actions: Stakeholders should define a list of objects that can be standardized and take into account observations in the field. Encourage joint operations with surveyors from different regions. Items that are rare in one location maybe fairly common elsewhere.

        -
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        What objects are common to all cantons ?#

        -

        ref: Combined cantons, ref: Bern most common

        -

        Use the most common items

        -

        For each report their is a detail of the most common items. If we use the combined results this will tell you, given the results from all the lakes and the cantons under consideration, exactly what the most common items are.

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        Common to all cantons

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        1. Fragmented plastics

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        2. Cigarette filters

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        3. Expanded polystyrene

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        4. Food wrappers; candy, snacks

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        5. Industrial sheeting

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        6. Industrial pellets (nurdles)

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        7. plastic caps, lid rings: G21, G22, G23, G24

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        8. Glass drink bottles, pieces

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        10. Cotton bud/swab sticks

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        11. Plastic construction waste

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        12. Metal bottle caps, lids & pull tabs from cans

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        13. Tobacco; plastic packaging, containers

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        14. Foil wrappers, aluminum foil

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        Common to Bern

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        2. Fragmented plastics

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        3. Industrial sheeting

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        4. Food wrappers; candy, snacks

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        6. Glass drink bottles, pieces

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        7. Packaging films nonfood or unknown

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        8. Foam packaging/insulation/polyurethane

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        9. plastic caps, lid rings: G21, G22, G23, G24

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        10. Industrial pellets (nurdles)

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        11. Plastic construction waste

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        12. Fireworks; rocket caps, exploded parts & packaging

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        13. Cotton bud/swab sticks

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        14. Tobacco; plastic packaging, containers

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        15. Foil wrappers, aluminum foil

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        Conclusion: 14/15 of the most common items in Bern are also common to the rest of the cantons.

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        Notes: This may be more pertinent for cantons that have a common river or lake.

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        Recommended actions: Neighbor cantons should consult the most common items in their respective areas to find possible points of collaboration.

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        What is the chance of finding X ?#

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        How often an object or category of objects is found is an excellent indeicator of the distribution of the item in the environment.

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        Use the most common or the object inventory

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        ref: Combined cantons, ref: Forecast class

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        How likely are you to find:

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        1. PET bottle on the shore of a lake in Bern: about 7% of surveys will yield a plastic bottle

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        2. Plastic bottle top: about 65% of surveys will yield a plastic bottle top

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        3. Diaper of babywipe: 22% of surveys will yield a diaper or babywipe

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        Conclusion: The standard report will tell you how likely you are to find at least one an object.

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        Notes: This is a simple calculation using the most likely estimate of a binomial distribution.

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        Recommended actions: None

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