visualisation/gallery/symbol_with_text.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Simple symbol plotting with text on Cartesian projection\n",
    "\n",
    "Symbol plotting in Magics is the plotting of different types of symbols at selected locations. A symbol in this context is a number (the value at the location), a text string (given by the user) or a Magics marker.  \n",
    "\n",
    "List of all **msymbol** parameters you can find [in Magics documentation](https://confluence.ecmwf.int/display/MAGP/Symbol \"Symbol parameters\").\n",
    "More symbol plotting examples can be found in [Simple symbol plotting](../tutorials/Symbol_simple.ipynb \"Symbol simple\") and [Advanced symbol plotting](../tutorials/Advanced_simple.ipynb \"Symbol advanced\") notebook.\n",
    "\n",
    "This is a one cell notebook with example how to plot symbols with text on a graph."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Installing Magics\n",
    "If you don't have Magics installed, run the next cell to install Magics using conda."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "# Install Magics in the current Jupyter kernel\n",
    "import sys\n",
    "!conda install --yes --prefix {sys.prefix} Magics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import Magics.macro as magics\n",
    "import numpy as np\n",
    "\n",
    "# Setting the cartesian view\n",
    "cartesian_projection = magics.mmap( \n",
    "    subpage_y_position= 2., \n",
    "    subpage_map_projection = 'cartesian',\n",
    "    subpage_x_axis_type = 'regular',\n",
    "    subpage_y_axis_type = 'regular',\n",
    "    subpage_x_min = 10.,\n",
    "    subpage_x_max = 40.,\n",
    "    subpage_y_min = 20.,\n",
    "    subpage_y_max = 100.,\n",
    "    page_id_line  = \"off\")\n",
    "\n",
    "# Vertical axis\n",
    "vertical = magics.maxis(axis_orientation = \"vertical\",\n",
    "     axis_type = \"regular\",\n",
    "     axis_tick_label_height = 0.4,\n",
    "     axis_tick_label_colour = 'navy',\n",
    "     axis_grid =  \"on\",\n",
    "     axis_grid_colour = \"grey\",\n",
    "     axis_grid_thickness = 1,\n",
    "     axis_grid_line_style = \"dot\")\n",
    "\n",
    "# Horizontal axis\n",
    "horizontal = magics.maxis(axis_orientation = \"horizontal\",\n",
    "     axis_type = \"regular\",\n",
    "     axis_tick_label_height = 0.4,\n",
    "     axis_tick_label_colour = 'navy',\n",
    "     axis_grid =  \"on\",\n",
    "     axis_grid_colour = \"grey\",\n",
    "     axis_grid_thickness = 1,\n",
    "     axis_grid_line_style = \"dot\")\n",
    "\n",
    "# Some data\n",
    "x = np.array([15.,25.,35.])\n",
    "bottom = np.array([30.,30.,30.])\n",
    "left = np.array([45.,45.,45.])\n",
    "right = np.array([60.,60.,60.])\n",
    "top = np.array([75.,75.,75.])\n",
    "middle = np.array([90.,90.,90.])\n",
    "\n",
    "# Input for symbol with text above it\n",
    "topinput = magics.minput(\n",
    "    input_x_values = x,\n",
    "    input_y_values = top)\n",
    "\n",
    "#Define the graph \n",
    "toptext = magics.msymb( \n",
    "    symbol_type =  \"marker\",\n",
    "    symbol_colour =  \"navy\",\n",
    "    symbol_text_list = [\"top\", \"top\", \"top\"],\n",
    "    symbol_height =  1.,\n",
    "    symbol_text_font_size =  0.8,\n",
    "    symbol_text_font_colour =  \"black\",\n",
    "    symbol_text_position =  \"top\",\n",
    "    symbol_marker_index = 15\n",
    "    )\n",
    "\n",
    "# Input for symbol with text on the left side\n",
    "leftinput = magics.minput(\n",
    "    input_x_values = x,\n",
    "    input_y_values = left)\n",
    "\n",
    "#Define the graph \n",
    "lefttext = magics.msymb( \n",
    "    symbol_type =  \"marker\",\n",
    "    symbol_colour =  \"ochre\",\n",
    "    symbol_text_list = [\"left\", \"left\", \"left\"],\n",
    "    symbol_height =  1.,\n",
    "    symbol_text_font_size =  0.8,\n",
    "    symbol_text_font_colour =  \"black\",\n",
    "    symbol_text_position =  \"left\",\n",
    "    symbol_marker_index = 15\n",
    "    )\n",
    "\n",
    "# Input for symbol with text on the right side\n",
    "rightinput = magics.minput(\n",
    "    input_x_values = x,\n",
    "    input_y_values = right)\n",
    "\n",
    "#Define the graph \n",
    "righttext = magics.msymb( \n",
    "    symbol_type =  \"marker\",\n",
    "    symbol_colour =  \"chestnut\",\n",
    "    symbol_text_list = [\"one\",\"two\",\"five\"],\n",
    "    symbol_height =  1.,\n",
    "    symbol_text_font_size =  0.8,\n",
    "    symbol_text_font_colour =  \"black\",\n",
    "    symbol_text_position =  \"right\",\n",
    "    symbol_marker_index = 15\n",
    "    )\n",
    "\n",
    "# Input for symbol with text below it\n",
    "bottominput = magics.minput(\n",
    "    input_x_values = x,\n",
    "    input_y_values = bottom)\n",
    "\n",
    "#Define the graph \n",
    "bottomtext = magics.msymb( \n",
    "    symbol_type =  \"marker\",\n",
    "    symbol_colour =  \"rose\",\n",
    "    symbol_text_list = [\"bottom\"],\n",
    "    symbol_height =  1.,\n",
    "    symbol_text_font_size =  0.8,\n",
    "    symbol_text_font_colour =  \"black\",\n",
    "    symbol_text_position =  \"bottom\",\n",
    "    symbol_marker_index = 15\n",
    "    )\n",
    "\n",
    "# Input for symbol with text over it\n",
    "centreinput = magics.minput(\n",
    "    input_x_values = x,\n",
    "    input_y_values = middle)\n",
    "\n",
    "#Define the graph \n",
    "centretext = magics.msymb( \n",
    "    symbol_type =  \"marker\",\n",
    "    symbol_colour =  \"sky\",\n",
    "    symbol_text_list = [\"a\", \"b\", \"centre\"],\n",
    "    symbol_height =  1.2,\n",
    "    symbol_text_font_size =  0.8,\n",
    "    symbol_text_font_colour =  \"black\",\n",
    "    symbol_text_position =  \"centre\",\n",
    "    symbol_marker_index = 15\n",
    "    )\n",
    "\n",
    "magics.plot(cartesian_projection, vertical, horizontal, topinput, toptext, \n",
    "            leftinput, lefttext, bottominput, bottomtext,\n",
    "            rightinput, righttext, centreinput, centretext)"
   ]
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