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    "# %load http://matplotlib.org/mpl_examples/pylab_examples/contour_demo.py\n",
    "\"\"\"\n",
    "Illustrate simple contour plotting, contours on an image with\n",
    "a colorbar for the contours, and labelled contours.\n",
    "\n",
    "See also contour_image.py.\n",
    "\"\"\"\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.mlab as mlab\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "matplotlib.rcParams['xtick.direction'] = 'out'\n",
    "matplotlib.rcParams['ytick.direction'] = 'out'\n",
    "\n",
    "delta = 0.025\n",
    "x = np.arange(-3.0, 3.0, delta)\n",
    "y = np.arange(-2.0, 2.0, delta)\n",
    "X, Y = np.meshgrid(x, y)\n",
    "Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)\n",
    "Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)\n",
    "# difference of Gaussians\n",
    "Z = 10.0 * (Z2 - Z1)\n",
    "\n",
    "\n",
    "# Create a simple contour plot with labels using default colors.  The\n",
    "# inline argument to clabel will control whether the labels are draw\n",
    "# over the line segments of the contour, removing the lines beneath\n",
    "# the label\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z)\n",
    "plt.clabel(CS, inline=1, fontsize=10)\n",
    "plt.title('Simplest default with labels')\n",
    "\n",
    "\n",
    "# contour labels can be placed manually by providing list of positions\n",
    "# (in data coordinate). See ginput_manual_clabel.py for interactive\n",
    "# placement.\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z)\n",
    "manual_locations = [(-1, -1.4), (-0.62, -0.7), (-2, 0.5), (1.7, 1.2), (2.0, 1.4), (2.4, 1.7)]\n",
    "plt.clabel(CS, inline=1, fontsize=10, manual=manual_locations)\n",
    "plt.title('labels at selected locations')\n",
    "\n",
    "\n",
    "# You can force all the contours to be the same color.\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z, 6,\n",
    "                 colors='k',  # negative contours will be dashed by default\n",
    "                 )\n",
    "plt.clabel(CS, fontsize=9, inline=1)\n",
    "plt.title('Single color - negative contours dashed')\n",
    "\n",
    "# You can set negative contours to be solid instead of dashed:\n",
    "matplotlib.rcParams['contour.negative_linestyle'] = 'solid'\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z, 6,\n",
    "                 colors='k',  # negative contours will be dashed by default\n",
    "                 )\n",
    "plt.clabel(CS, fontsize=9, inline=1)\n",
    "plt.title('Single color - negative contours solid')\n",
    "\n",
    "\n",
    "# And you can manually specify the colors of the contour\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z, 6,\n",
    "                 linewidths=np.arange(.5, 4, .5),\n",
    "                 colors=('r', 'green', 'blue', (1, 1, 0), '#afeeee', '0.5')\n",
    "                 )\n",
    "plt.clabel(CS, fontsize=9, inline=1)\n",
    "plt.title('Crazy lines')\n",
    "\n",
    "\n",
    "# Or you can use a colormap to specify the colors; the default\n",
    "# colormap will be used for the contour lines\n",
    "plt.figure()\n",
    "im = plt.imshow(Z, interpolation='bilinear', origin='lower',\n",
    "                cmap=cm.gray, extent=(-3, 3, -2, 2))\n",
    "levels = np.arange(-1.2, 1.6, 0.2)\n",
    "CS = plt.contour(Z, levels,\n",
    "                 origin='lower',\n",
    "                 linewidths=2,\n",
    "                 extent=(-3, 3, -2, 2))\n",
    "\n",
    "# Thicken the zero contour.\n",
    "zc = CS.collections[6]\n",
    "plt.setp(zc, linewidth=4)\n",
    "\n",
    "plt.clabel(CS, levels[1::2],  # label every second level\n",
    "           inline=1,\n",
    "           fmt='%1.1f',\n",
    "           fontsize=14)\n",
    "\n",
    "# make a colorbar for the contour lines\n",
    "CB = plt.colorbar(CS, shrink=0.8, extend='both')\n",
    "\n",
    "plt.title('Lines with colorbar')\n",
    "#plt.hot()  # Now change the colormap for the contour lines and colorbar\n",
    "plt.flag()\n",
    "\n",
    "# We can still add a colorbar for the image, too.\n",
    "CBI = plt.colorbar(im, orientation='horizontal', shrink=0.8)\n",
    "\n",
    "# This makes the original colorbar look a bit out of place,\n",
    "# so let's improve its position.\n",
    "\n",
    "l, b, w, h = plt.gca().get_position().bounds\n",
    "ll, bb, ww, hh = CB.ax.get_position().bounds\n",
    "CB.ax.set_position([ll, b + 0.1*h, ww, h*0.8])\n",
    "\n",
    "\n",
    "plt.show()\n"
   ]
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   "execution_count": 5,
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:20: MatplotlibDeprecationWarning: The bivariate_normal function was deprecated in version 2.2.\n",
      "/opt/conda/lib/python3.6/site-packages/ipykernel_launcher.py:21: MatplotlibDeprecationWarning: The bivariate_normal function was deprecated in version 2.2.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
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     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Illustrate simple contour plotting, contours on an image with\n",
    "a colorbar for the contours, and labelled contours.\n",
    "\n",
    "See also contour_image.py.\n",
    "\"\"\"\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.mlab as mlab\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "matplotlib.rcParams['xtick.direction'] = 'out'\n",
    "matplotlib.rcParams['ytick.direction'] = 'out'\n",
    "\n",
    "delta = 0.025\n",
    "x = np.arange(-3.0, 3.0, delta)\n",
    "y = np.arange(-2.0, 2.0, delta)\n",
    "X, Y = np.meshgrid(x, y)\n",
    "Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)\n",
    "Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)\n",
    "# difference of Gaussians\n",
    "Z = 10.0 * (Z2 - Z1)\n",
    "\n",
    "\n",
    "# Create a simple contour plot with labels using default colors.  The\n",
    "# inline argument to clabel will control whether the labels are draw\n",
    "# over the line segments of the contour, removing the lines beneath\n",
    "# the label\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z)\n",
    "plt.clabel(CS, inline=1, fontsize=10)\n",
    "plt.title('Simplest default with labels')\n",
    "\n",
    "\n",
    "# contour labels can be placed manually by providing list of positions\n",
    "# (in data coordinate). See ginput_manual_clabel.py for interactive\n",
    "# placement.\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z)\n",
    "manual_locations = [(-1, -1.4), (-0.62, -0.7), (-2, 0.5), (1.7, 1.2), (2.0, 1.4), (2.4, 1.7)]\n",
    "plt.clabel(CS, inline=1, fontsize=10, manual=manual_locations)\n",
    "plt.title('labels at selected locations')\n",
    "\n",
    "\n",
    "# You can force all the contours to be the same color.\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z, 6,\n",
    "                 colors='k',  # negative contours will be dashed by default\n",
    "                 )\n",
    "plt.clabel(CS, fontsize=9, inline=1)\n",
    "plt.title('Single color - negative contours dashed')\n",
    "\n",
    "# You can set negative contours to be solid instead of dashed:\n",
    "matplotlib.rcParams['contour.negative_linestyle'] = 'solid'\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z, 6,\n",
    "                 colors='k',  # negative contours will be dashed by default\n",
    "                 )\n",
    "plt.clabel(CS, fontsize=9, inline=1)\n",
    "plt.title('Single color - negative contours solid')\n",
    "\n",
    "\n",
    "# And you can manually specify the colors of the contour\n",
    "plt.figure()\n",
    "CS = plt.contour(X, Y, Z, 6,\n",
    "                 linewidths=np.arange(.5, 4, .5),\n",
    "                 colors=('r', 'green', 'blue', (1, 1, 0), '#afeeee', '0.5')\n",
    "                 )\n",
    "plt.clabel(CS, fontsize=9, inline=1)\n",
    "plt.title('Crazy lines')\n",
    "\n",
    "\n",
    "# Or you can use a colormap to specify the colors; the default\n",
    "# colormap will be used for the contour lines\n",
    "plt.figure()\n",
    "im = plt.imshow(Z, interpolation='bilinear', origin='lower',\n",
    "                cmap=cm.gray, extent=(-3, 3, -2, 2))\n",
    "levels = np.arange(-1.2, 1.6, 0.2)\n",
    "CS = plt.contour(Z, levels,\n",
    "                 origin='lower',\n",
    "                 linewidths=2,\n",
    "                 extent=(-3, 3, -2, 2))\n",
    "\n",
    "# Thicken the zero contour.\n",
    "zc = CS.collections[6]\n",
    "plt.setp(zc, linewidth=4)\n",
    "\n",
    "plt.clabel(CS, levels[1::2],  # label every second level\n",
    "           inline=1,\n",
    "           fmt='%1.1f',\n",
    "           fontsize=14)\n",
    "\n",
    "# make a colorbar for the contour lines\n",
    "CB = plt.colorbar(CS, shrink=0.8, extend='both')\n",
    "\n",
    "plt.title('Lines with colorbar')\n",
    "#plt.hot()  # Now change the colormap for the contour lines and colorbar\n",
    "plt.flag()\n",
    "\n",
    "# We can still add a colorbar for the image, too.\n",
    "CBI = plt.colorbar(im, orientation='horizontal', shrink=0.8)\n",
    "\n",
    "# This makes the original colorbar look a bit out of place,\n",
    "# so let's improve its position.\n",
    "\n",
    "l, b, w, h = plt.gca().get_position().bounds\n",
    "ll, bb, ww, hh = CB.ax.get_position().bounds\n",
    "CB.ax.set_position([ll, b + 0.1*h, ww, h*0.8])\n",
    "\n",
    "\n",
    "plt.show()"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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