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      "source": [
        "\n# pcolor images\n\n`~.Axes.pcolor` generates 2D image-style plots, as illustrated below.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt\nimport numpy as np\n\nfrom matplotlib.colors import LogNorm\n\n# Fixing random state for reproducibility\nnp.random.seed(19680801)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## A simple pcolor demo\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "Z = np.random.rand(6, 10)\n\nfig, (ax0, ax1) = plt.subplots(2, 1)\n\nc = ax0.pcolor(Z)\nax0.set_title('default: no edges')\n\nc = ax1.pcolor(Z, edgecolors='k', linewidths=4)\nax1.set_title('thick edges')\n\nfig.tight_layout()\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Comparing pcolor with similar functions\n\nDemonstrates similarities between `~.axes.Axes.pcolor`,\n`~.axes.Axes.pcolormesh`, `~.axes.Axes.imshow` and\n`~.axes.Axes.pcolorfast` for drawing quadrilateral grids.\nNote that we call ``imshow`` with ``aspect=\"auto\"`` so that it doesn't force\nthe data pixels to be square (the default is ``aspect=\"equal\"``).\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "# make these smaller to increase the resolution\ndx, dy = 0.15, 0.05\n\n# generate 2 2d grids for the x & y bounds\ny, x = np.mgrid[-3:3+dy:dy, -3:3+dx:dx]\nz = (1 - x/2 + x**5 + y**3) * np.exp(-x**2 - y**2)\n# x and y are bounds, so z should be the value *inside* those bounds.\n# Therefore, remove the last value from the z array.\nz = z[:-1, :-1]\nz_min, z_max = -abs(z).max(), abs(z).max()\n\nfig, axs = plt.subplots(2, 2)\n\nax = axs[0, 0]\nc = ax.pcolor(x, y, z, cmap='RdBu', vmin=z_min, vmax=z_max)\nax.set_title('pcolor')\nfig.colorbar(c, ax=ax)\n\nax = axs[0, 1]\nc = ax.pcolormesh(x, y, z, cmap='RdBu', vmin=z_min, vmax=z_max)\nax.set_title('pcolormesh')\nfig.colorbar(c, ax=ax)\n\nax = axs[1, 0]\nc = ax.imshow(z, cmap='RdBu', vmin=z_min, vmax=z_max,\n              extent=[x.min(), x.max(), y.min(), y.max()],\n              interpolation='nearest', origin='lower', aspect='auto')\nax.set_title('image (nearest, aspect=\"auto\")')\nfig.colorbar(c, ax=ax)\n\nax = axs[1, 1]\nc = ax.pcolorfast(x, y, z, cmap='RdBu', vmin=z_min, vmax=z_max)\nax.set_title('pcolorfast')\nfig.colorbar(c, ax=ax)\n\nfig.tight_layout()\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Pcolor with a log scale\n\nThe following shows pcolor plots with a log scale.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "N = 100\nX, Y = np.meshgrid(np.linspace(-3, 3, N), np.linspace(-2, 2, N))\n\n# A low hump with a spike coming out.\n# Needs to have z/colour axis on a log scale, so we see both hump and spike.\n# A linear scale only shows the spike.\nZ1 = np.exp(-X**2 - Y**2)\nZ2 = np.exp(-(X * 10)**2 - (Y * 10)**2)\nZ = Z1 + 50 * Z2\n\nfig, (ax0, ax1) = plt.subplots(2, 1)\n\nc = ax0.pcolor(X, Y, Z, shading='auto',\n               norm=LogNorm(vmin=Z.min(), vmax=Z.max()), cmap='PuBu_r')\nfig.colorbar(c, ax=ax0)\n\nc = ax1.pcolor(X, Y, Z, cmap='PuBu_r', shading='auto')\nfig.colorbar(c, ax=ax1)\n\nplt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        ".. admonition:: References\n\n   The use of the following functions, methods, classes and modules is shown\n   in this example:\n\n   - `matplotlib.axes.Axes.pcolor` / `matplotlib.pyplot.pcolor`\n   - `matplotlib.axes.Axes.pcolormesh` / `matplotlib.pyplot.pcolormesh`\n   - `matplotlib.axes.Axes.pcolorfast`\n   - `matplotlib.axes.Axes.imshow` / `matplotlib.pyplot.imshow`\n   - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`\n   - `matplotlib.colors.LogNorm`\n\n"
      ]
    }
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