{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2D plots\n",
    "Demonstration of the 2D plot capabilities\n",
    "\n",
    "The ``plot2d`` plot method make plots of 2-dimensional scalar data\n",
    "using matplotlibs ``pcolormesh`` or the ``contourf`` functions.\n",
    "\n",
    "Note that this method is extended by the [mapplot](http://psyplot.readthedocs.io/projects/psy-maps/en/latest/examples/example_mapplotters.html) plot method of the [psy-maps](http://psyplot.readthedocs.io/projects/psy-maps/en/latest/index.html) plugin for visualization on the projected globe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/psommer/miniconda3/lib/python3.6/site-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated since IPython 4.0. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
      "  \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n"
     ]
    }
   ],
   "source": [
    "import psyplot.project as psy\n",
    "import xarray as xr\n",
    "%matplotlib inline\n",
    "%config InlineBackend.close_figures = False\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we create some sample data in the form of a 2D parabola"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = np.linspace(-1, 1.)\n",
    "y = np.linspace(-1, 1.)\n",
    "x2d, y2d = np.meshgrid(x, y)\n",
    "z = - x2d**2 - y2d**2\n",
    "ds = xr.Dataset(\n",
    "    {'z': xr.Variable(('x', 'y'), z)},\n",
    "    {'x': xr.Variable(('x', ), x), 'y': xr.Variable(('y', ), y)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For a simple 2D plot of a scalar field, we can use the\n",
    "[plot2d](http://psyplot.readthedocs.io/projects/psy-simple/en/latest/generated/psyplot.project.plot.plot2d.html#psyplot.project.plot.plot2d) plot method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "nbsphinx-thumbnail": {
     "tooltip": "Visualize simple 2D scalar fields"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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lrvsgSWqRP+CSpMIY+CWpMAZ+SSpMrSd3q5jnyz6ssW+XA1cAh4B3ZeZtbfevqoh4DvAx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\ngV+SCmPgl6TCGPglqTAGfkkqzP8HXb5FCHBMk9MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11208cac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = psy.plot.plot2d(ds, cmap='Reds', name='z')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ``plot`` formatoption controls, how the plot is made. The default is a \n",
    "[pcolormesh](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.pcolormesh) \n",
    "plot, but we can also make a \n",
    "[filled contour](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.contourf) \n",
    "plot. The levels of the contour plot are determined through the ``levels`` formatoption."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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STgbWAz+b0LLMzGwIha7q6SVpC3AoInZK2gHsA/4E3BkRvxrnsszMbDRTc3NzVffBzMxK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\nXkDr3IU00wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11208cac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p.update(plot='contourf', levels=5)\n",
    "p.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ``plot2d`` method has several formatoptions controlling the color coding of your plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------+-------------+-------------+-------------+\n",
      "| levels      | miss_color  | cmap        | bounds      |\n",
      "+-------------+-------------+-------------+-------------+\n",
      "| extend      | cbar        | cbarspacing | cticksize   |\n",
      "+-------------+-------------+-------------+-------------+\n",
      "| ctickweight | ctickprops  |             |             |\n",
      "+-------------+-------------+-------------+-------------+\n"
     ]
    }
   ],
   "source": [
    "p.keys('colors')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most important ones are\n",
    "\n",
    "- ``cbar``: To specify the location of the colorbar\n",
    "- ``bounds``: To specify the boundaries for the color coding, i.e.\n",
    "  the categories which data range belongs to which color\n",
    "- ``cmap``: To specify the colormap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "psy.close('all')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}