From 57ffffcf99f8f83b54ec1908dd093de6b762579f Mon Sep 17 00:00:00 2001 From: OwenJohnsons Date: Thu, 7 Jul 2022 16:00:33 -0700 Subject: [PATCH] Quality of Life Updates --- overall/lofar_planner.py | 2 - overall/obs_table.csv | 547 ++++++++++++++++++++++++++++++++++ overall/overall_planner.ipynb | 348 +++++---------------- 3 files changed, 620 insertions(+), 277 deletions(-) create mode 100644 overall/obs_table.csv diff --git a/overall/lofar_planner.py b/overall/lofar_planner.py index c9e1dba..e31439e 100644 --- a/overall/lofar_planner.py +++ b/overall/lofar_planner.py @@ -11,8 +11,6 @@ # - Astro-packages import astropy.units as u -import astropy.coordinates as coord -import astropy.table from astropy.coordinates import SkyCoord, EarthLocation #- for tranformations, takes ref. from simbad. from astropy.time import Time from astropy.table import QTable, Table diff --git a/overall/obs_table.csv b/overall/obs_table.csv new file mode 100644 index 0000000..07c1dcd --- /dev/null +++ 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"cell_type": "code", - "execution_count": 7, + "execution_count": 121, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "['plotting_function.ipynb',\n", + "['lofar_lst.py',\n", " '.DS_Store',\n", - " 'images',\n", - " 'intial_development',\n", + " 'overall_planner.ipynb',\n", + " '__pycache__',\n", + " 'obs_table.csv',\n", " '.ipynb_checkpoints',\n", + " 'lofar_planner.py',\n", + " 'GUI_testing',\n", " 'data',\n", - " 'overall',\n", " 'targets_of_interest.csv']" ] }, - "execution_count": 7, + "execution_count": 121, "metadata": {}, "output_type": "execute_result" } @@ -27,13 +29,13 @@ "from lofar_lst import *\n", "from lofar_planner import *\n", "import os \n", - "\n", - "os.listdir()" + "from datetime import datetime\n", + "from datetime import timedelta" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -64,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +101,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -108,244 +110,14 @@ "text": [ "['2022-07-08 08:00:00.000' '2022-07-08 11:00:00.000']\n", "Number of objects that do not meet the criteria of both stations: 273\n", - "Number of previously observed targets: 27\n", + "Number of previously observed targets: 24\n", "Number of objects avalible for observation: 546\n", "['2022-07-08 09:00:00.000' '2022-07-08 12:00:00.000']\n", "Number of objects that do not meet the criteria of both stations: 273\n", - "Number of previously observed targets: 27\n", + "Number of previously observed targets: 24\n", "Number of objects avalible for observation: 546\n", "Number of possible targets: 546\n" ] - }, - { - "data": { - "text/html": [ - "
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176TIC37829107623.88090961.360260TrueTrueTrueTrue1.01.0
175TIC37835511623.88322660.481667TrueTrueTrueTrue1.01.0
174TIC47085253123.98274561.554089TrueTrueTrueTrue1.01.0
545TIC26546004323.99020768.384119TrueTrueTrueTrue1.01.0
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546 rows × 9 columns

\n", - "
" - ], - "text/plain": [ - " Name RA DEC Ever Observable(I-LOFAR) \\\n", - "0 TIC346929661 0.065170 59.334681 True \n", - "137 TIC347013211 0.074617 54.934497 True \n", - "374 TIC396356111 0.173304 58.489439 True \n", - "373 TIC461387302 0.201453 66.650523 True \n", - "372 TIC403256331 0.283289 58.679253 True \n", - ".. ... ... ... ... \n", - "177 TIC431585347 23.844936 50.354962 True \n", - "176 TIC378291076 23.880909 61.360260 True \n", - "175 TIC378355116 23.883226 60.481667 True \n", - "174 TIC470852531 23.982745 61.554089 True \n", - "545 TIC265460043 23.990207 68.384119 True \n", - "\n", - " Always Observable(I-LOFAR) Ever Observable(LOFAR-SE) \\\n", - "0 True True \n", - "137 True True \n", - "374 True True \n", - "373 True True \n", - "372 True True \n", - ".. ... ... \n", - "177 True True \n", - "176 True True \n", - "175 True True \n", - "174 True True \n", - "545 True True \n", - "\n", - " Always Observable(LOFAR-SE) Fraction of observable time (I-LOFAR) \\\n", - "0 True 1.0 \n", - "137 True 1.0 \n", - "374 True 1.0 \n", - "373 True 1.0 \n", - "372 True 1.0 \n", - ".. ... ... \n", - "177 True 1.0 \n", - "176 True 1.0 \n", - "175 True 1.0 \n", - "174 True 1.0 \n", - "545 True 1.0 \n", - "\n", - " Fraction of observable time (LOFAR-SE) \n", - "0 1.0 \n", - "137 1.0 \n", - "374 1.0 \n", - "373 1.0 \n", - "372 1.0 \n", - ".. ... \n", - "177 1.0 \n", - "176 1.0 \n", - "175 1.0 \n", - "174 1.0 \n", - "545 1.0 \n", - "\n", - "[546 rows x 9 columns]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -362,48 +134,74 @@ "Station_Alpha = setup(station_timezone(start, UTC_alpha), station_timezone(end, UTC_alpha), 30, 90, 20, 0.016, observatory_1, catalog, True)\n", "Station_Beta = setup(station_timezone(start, UTC_beta), station_timezone(end, UTC_beta), 30, 90, 20, 0.016, observatory_2, catalog, False)\n", "\n", - "test = dataframe_formatting(0.8)\n", - "test" + "observation_table = dataframe_formatting(0.8)\n", + "observation_table.to_csv('obs_table.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [], + "source": [ + "def find_nearest(array, value): # - Function to find the nearest value in a given array. \n", + " array = np.asarray(array); idx = (np.abs(array - value)).argmin()\n", + " return idx\n", + "\n", + "base_lst = 2.5 # - LST that is best suited to both stations, usually half-way between both. \n", + "target_numbers = 12; step = 0.25 # - The amount of targets to be observed along with the amount of targets \n", + "idx_array = []\n", + "\n", + "for i in range(0, target_numbers): # - Find targets that are visible and avalible at around 15 min intervals in the observation window. \n", + " trgt_idx = find_nearest(observation_table['RA'], base_lst)\n", + " base_lst += step \n", + " if trgt_idx in idx_array: \n", + " idx_array.append(trgt_idx + 1)\n", + " else: \n", + " idx_array.append(trgt_idx)\n", + "\n", + "trgt_tbl = observation_table.iloc[idx_array]" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 132, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "[390 TIC376353509\n", - " Name: Name, dtype: object, 387 TIC458914949\n", - " Name: Name, dtype: object, 383 TIC285674856\n", - " Name: Name, dtype: object, 380 TIC73104318\n", - " Name: Name, dtype: object, 379 TIC102672709\n", - " Name: Name, dtype: object, 377 TIC103195323\n", - " Name: Name, dtype: object, 306 TIC8400842\n", - " Name: Name, dtype: object, 341 TIC85031598\n", - " Name: Name, dtype: object, 342 TIC470381900\n", - " Name: Name, dtype: object, 299 TIC241225337\n", - " Name: Name, dtype: object, 298 TIC138168780\n", - " Name: Name, dtype: object, 297 TIC396740648\n", - " Name: Name, dtype: object]" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Name Time RA DEC freqrng dur \n", + "TIC249945230 07:03 0.677366 0.842536 110e6:190.2e6 15m\n", + "TIC302773669 07:19 0.740658 1.252328 110e6:190.2e6 15m\n", + "TIC251384275 07:35 0.780515 1.025123 110e6:190.2e6 15m\n", + "TIC82010657 07:51 0.850903 1.051355 110e6:190.2e6 15m\n", + "TIC285677945 08:07 0.926752 0.881375 110e6:190.2e6 15m\n", + "TIC104208182 08:23 0.951242 0.889335 110e6:190.2e6 15m\n", + "TIC87090944 08:39 1.020784 1.029191 110e6:190.2e6 15m\n", + "TIC267694283 08:55 1.103572 0.937016 110e6:190.2e6 15m\n", + "TIC103448870 09:11 1.166491 1.274504 110e6:190.2e6 15m\n", + "TIC9837861 09:27 1.231305 0.947575 110e6:190.2e6 15m\n", + "TIC321041369 09:43 1.425429 0.994203 110e6:190.2e6 15m\n", + "TIC311121985 09:59 1.493675 0.864173 110e6:190.2e6 15m\n" + ] } ], "source": [ - "step = 3\n", - "target_list = []\n", - "\n", - "for i in range(0, 12):\n", - " t = min(test['RA'], key=lambda x:abs(x - step))\n", - " target_list.append(test.loc[test['RA'] == t]['Name']) \n", - " test = test.drop(test.loc[test['RA'] == t].index)\n", - " step += 0.25\n", - "target_list" + "ra = (trgt_tbl['RA']).to_list(); dec = (trgt_tbl['DEC']).to_list()\n", + "trgt_coords = SkyCoord(ra*u.hourangle, dec*u.degree)\n", + "names = trgt_tbl['Name'].to_list()\n", + "\n", + "cur_time = datetime.strptime('07:03', '%H:%M')\n", + "cur_time_str = cur_time.strftime('%H:%M')\n", + "trgt_duration = 16 \n", + "\n", + "print('Name Time RA DEC freqrng dur ')\n", + "for i in range(0, len(ra)): \n", + " print(names[i], cur_time_str, '{:.6f}'.format(trgt_coords[i].ra.radian), '{:.6f}'.format(trgt_coords[i].dec.radian), '110e6:190.2e6', '15m')\n", + " cur_time = cur_time + timedelta(minutes=trgt_duration)\n", + " cur_time_str = cur_time.strftime('%H:%M')" ] } ],