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 "metadata": {
  "name": "",
  "signature": "sha256:d9e940da27f30a0d25b6d377dd67af69dced01eb79a73291cd94d66fbe9d9412"
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Matplotlib Tutorial: 4. Labeling and Annotation"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "An important part of making readable plots is labeling and annotating\n",
      "the axes.  We've already seen some of this with the ``set_xlabel``, ``set_ylabel``,\n",
      "and ``set_title`` commands.  In this section we will cover text and annotation\n",
      "using the ``text`` and ``annotate`` commands, and we will cover the fine-tuning\n",
      "of axis tick labels using ``Formatter`` and ``Locator`` instances.\n",
      "\n",
      "Again, we'll enter matplotlib inline mode & do some imports"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "\n",
      "from __future__ import print_function, division\n",
      "import numpy as np\n",
      "import matplotlib.pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Adding Text"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Text can be added to the axes in several ways.  The easiest way is to use the\n",
      "``text`` command. Here's a basic version of the command:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots()\n",
      "\n",
      "ax.text(0.5, 0.5, 'hello world: $\\int_0^\\infty e^x dx$', size=24, ha='center', va='center');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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EAkjhLiISQAp3EZEAUriLiASQwl1EJIAU7iIiAaRwFxEJIIW7iEgAKdxFRAJI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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x106cf28d0>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The above command places the text using data coordinates: that is,\n",
      "as we change the ``x`` and ``y`` limits the text will move around\n",
      "the axes.  It is also possible to place text at a static location\n",
      "on the figure.  The locations are between 0 and 1, from the bottom-left\n",
      "of the figure to the top-right:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig.text(0, 0, 'bottom-left corner')\n",
      "fig.text(1, 1, 'top-right corner', ha='left', va='top')\n",
      "fig"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "png": 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       "prompt_number": 3,
       "text": [
        "<matplotlib.figure.Figure at 0x106cf28d0>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "It is also possible to place text relative to the *axes* coordinates,\n",
      "but this is easier with the ``annotate`` command rather than the ``text``\n",
      "command:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots()\n",
      "\n",
      "ax.annotate('0.25 on axes', (0.25, 0.25), textcoords='axes fraction', size=20)\n",
      "ax.annotate('0.25 on data', (0.25, 0.25), textcoords='data', size=20)\n",
      "ax.set_ylim(0, 0.5);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Users/jakevdp/anaconda/envs/py3k/lib/python3.3/site-packages/matplotlib/text.py:1788: UserWarning: You have used the `textcoords` kwarg, but not the `xytext` kwarg.  This can lead to surprising results.\n",
        "  warnings.warn(\"You have used the `textcoords` kwarg, but not \"\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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GYbATERnGabCLyDAROSQiR0TE7m4NEekmIjtF5GcReap+pklERK6q8bNiRMQD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\nrkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x106fb75d0>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Annotate has some more powerful features as well: it can be used to\n",
      "automatically label parts of the axes with arrows."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots()\n",
      "\n",
      "ax.annotate('origin is here', (0, 0), (0.75, 0.75),\n",
      "            arrowprops=dict(arrowstyle='->', connectionstyle='arc3, rad=0.5'),\n",
      "            xycoords='data', textcoords='axes fraction');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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t9PkZwJxY1pAojyj3xS+BhqXPe6Xyvthr3NvAFODSoOsO6HuiEbAIaFG63CTo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\nTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x107269510>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are a number of different arrow styles available: the online\n",
      "documentation has a good set of examples."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Controlling Axis Properties"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Often you'd like to be able to fine-tune the tick labels\n",
      "on the axis, explicitly setting where they appear, adding\n",
      "minor ticks, or perhaps turning them off altogether.  This\n",
      "is accomplished through the ``Formatter`` and ``Locator``\n",
      "objects.\n",
      "\n",
      "``Locator`` objects control where ticks are located.  Here\n",
      "are some of the available choices:\n",
      "\n",
      "- ``plt.MultipleLocator``: locate ticks at a multiple of some value\n",
      "- ``plt.MaxNLocator``: use a maximum number of ticks for the given plot range\n",
      "- ``plt.NullLocator``: do not add ticks to the plot\n",
      "\n",
      "``Formatter`` objects control what labels are shown at the tick locations.\n",
      "Some useful options are:\n",
      "\n",
      "- ``plt.FormatStrFormatter``: use a format string (like ``'%.2g``) at each tick\n",
      "- ``plt.FuncFormatter``: specify a user-defined function\n",
      "- ``plt.NullFormatter``: do not label the ticks\n",
      "\n",
      "Any of these options may be applied to either major or minor ticks, using the\n",
      "functions\n",
      "\n",
      "- ``set_major_formatter``, ``set_major_locator``\n",
      "- ``set_minor_formatter``, ``set_minor_locator``\n",
      "\n",
      "We'll see some examples below"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig, ax = plt.subplots()\n",
      "\n",
      "x = np.linspace(0, 10)\n",
      "ax.plot(x, np.sin(x))\n",
      "\n",
      "ax.xaxis.set_major_locator(plt.MultipleLocator(0.8))\n",
      "ax.yaxis.set_major_locator(plt.MaxNLocator(3))\n",
      "\n",
      "ax.xaxis.set_minor_locator(plt.MultipleLocator(0.4))\n",
      "ax.yaxis.set_minor_locator(plt.NullLocator())  # no ticks (default)\n",
      "\n",
      "ax.xaxis.set_major_formatter(plt.FormatStrFormatter('%.2f'))  # float with two decimals\n",
      "\n",
      "\n",
      "def tickformat(val, pos):\n",
      "    if val > 0:\n",
      "        return \"positive\"\n",
      "    elif val < 0:\n",
      "        return \"negative\"\n",
      "    else:\n",
      "        return \"zero\"\n",
      "    \n",
      "ax.yaxis.set_major_formatter(plt.FuncFormatter(tickformat))\n",
      "ax.set_ylim(-1.2, 1.2);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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4/n9/FJIo60jgy6Csr4Dbi3j/BqIjQgpimZLsZ5XwutYEI5RSVS9K\nKyvEenFQ8P7NRP8QFVffw6gbRwNTg5jfREfUhF4vguNrAmsJEmEq6wXw54T3Zgj6RzJVfy9KLCvE\nejEuKGcmcGqq6kThL1vuwxhjTKni1sFtjDHGA0sWxhhjSmXJwhhjTKksWRhjjCmVJQtjjDGlsmRh\njDGmVJYsjDHGlMqShTHGmFL9P2FPBFcFnRvMAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x107328a90>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Using these combinations (as well as other options we haven't discussed)\n",
      "leads to some very flexible plots."
     ]
    }
   ],
   "metadata": {}
  }
 ]
}