{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# Axes Demo\n\nExample use of ``fig.add_axes`` to create inset Axes within the main plot Axes.\n\nPlease see also the `axes_grid_examples` section, and the following three\nexamples:\n\n- :doc:`/gallery/subplots_axes_and_figures/zoom_inset_axes`\n- :doc:`/gallery/axes_grid1/inset_locator_demo`\n- :doc:`/gallery/axes_grid1/inset_locator_demo2`\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\nnp.random.seed(19680801)  # Fixing random state for reproducibility.\n\n# create some data to use for the plot\ndt = 0.001\nt = np.arange(0.0, 10.0, dt)\nr = np.exp(-t[:1000] / 0.05)  # impulse response\nx = np.random.randn(len(t))\ns = np.convolve(x, r)[:len(x)] * dt  # colored noise\n\nfig, main_ax = plt.subplots()\nmain_ax.plot(t, s)\nmain_ax.set_xlim(0, 1)\nmain_ax.set_ylim(1.1 * np.min(s), 2 * np.max(s))\nmain_ax.set_xlabel('time (s)')\nmain_ax.set_ylabel('current (nA)')\nmain_ax.set_title('Gaussian colored noise')\n\n# this is an inset Axes over the main Axes\nright_inset_ax = fig.add_axes((.65, .6, .2, .2), facecolor='k')\nright_inset_ax.hist(s, 400, density=True)\nright_inset_ax.set(title='Probability', xticks=[], yticks=[])\n\n# this is another inset Axes over the main Axes\nleft_inset_ax = fig.add_axes((.2, .6, .2, .2), facecolor='k')\nleft_inset_ax.plot(t[:len(r)], r)\nleft_inset_ax.set(title='Impulse response', xlim=(0, .2), xticks=[], yticks=[])\n\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. tags::\n\n   component: axes\n   plot-type: line\n   plot-type: histogram\n   level: beginner\n\n"
      ]
    }
  ],
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