2575 lines
1.1 MiB
2575 lines
1.1 MiB
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Tools - matplotlib\n",
|
||
"\n",
|
||
"*This notebook demonstrates how to use the matplotlib library to plot beautiful graphs.*"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Plotting your first graph"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"First let's make sure that this notebook works well in both python 2 and 3:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from __future__ import division\n",
|
||
"from __future__ import print_function\n",
|
||
"from __future__ import unicode_literals"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"First we need to import the `matplotlib` library."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import matplotlib"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Matplotlib can output graphs using various backend graphics libraries, such as Tk, wxPython, etc. When running python using the command line, the graphs are typically shown in a separate window. In a Jupyter notebook, we can simply output the graphs within the notebook itself by running the `%matplotlib inline` magic command."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"%matplotlib inline\n",
|
||
"# matplotlib.use(\"TKAgg\") # use this instead in your program if you want to use Tk as your graphics backend."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Now let's plot our first graph! :)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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gmJsUGUqRQ0aFiZJpq1bBokVq0lKbQkaNqCWCo0fhwgvDdpfjxsWuRvLCPVzO6/bb4Zvf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\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110d5a2b0>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"plt.plot([1, 2, 4, 9, 5, 3])\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Yep, it's as simple as calling the `plot` function with some data, and then calling the `show` function!\n",
|
||
"\n",
|
||
"If the `plot` function is given one array of data, it will use it as the coordinates on the vertical axis, and it will just use each data point's index in the array as the horizontal coordinate.\n",
|
||
"You can also provide two arrays: one for the horizontal axis `x`, and the second for the vertical axis `y`:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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iO6gBVIPXX49CublZeu45aciQcIfj1KnhnxMmRJNrcS8mxjmjTh1tDwBZc/hwCOJiKK9d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\njqAGgIwjqAEg4whqAMi4/wdVsJdm7PW8ggAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110debcf8>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot([-3, -2, 5, 0], [1, 6, 4, 3])\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The axes automatically match the extent of the data. We would like to give the graph a bit more room, so let's call the `axis` function to change the extent of each axis `[xmin, xmax, ymin, ymax]`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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jYq2P7Rg0SHr44bBeLoD61NMnJwf6WrlP7g8OJu6kV18N51sedVTsSYD8ok9uLoJ6G0k/\nzb/2QNBXnzxmDH1yMxDU2+js5EAiyqmePvm88+iTYyCot9HZybKmaH31np88ZkxYtJ93mHFxMHEL\nPT1hxbwXXqBXQ+vYUZ88ePDWl1bTJzcfBxN3wt/+Fu6RyF9WFBV9cmsiqLdAP42ioE8uF4J6CwQ1\n8og+GQT1Fjo7pU9/OvYUKLN6+mTOTy4fDib2eu+90E+/8UbYUwEarVafnAQzfXLr4mBiPz39dLjj\nOCGNrNEnY1cR1L3op5GFHfXJH/pQGsr0yegvgrpXZ6c0cWLsKVAkffXJSXVBn4ws0FH3Ov546fbb\nww8YsK1afXISzPTJ6I+G3DOxxm9Y2KB+5x3p8MOlri76wbKrp09OHh/7GH9fsGs4mNgP8+ZJJ57I\nD13Z0CejKAhqhX765JNjT4FGok9GkRHUCmtQf/KTsadAVmr1yePGsd4FioWOWmGv6v77paFDY0+C\n/qBPRtFxMLFOr78ujRghrV5NB5ln9fTJyYM+GUWR2cFEM9tD0kOSdu99/MHdv7HrI+bDnDmhn+YH\nOz9q9cmsd4GyqRnU7r7RzM5w9/VmtpukR81skrs/2oT5Gi65RyLiqKdPvuQS6YQT6JNRXnUdTHT3\n9b0f7iGpTVJXwyZqss5O6fLLY0/R+upd7+Kb36RPBrZVV0dtZm2S5kk6RtJ/ufvXtrNN4Tpqd+nA\nA8Pb6sMOiz1Na+nulu64Iw3lpE/eclU4+mSUXaYXvLh7j6QxZravpJlmdrq7P7jtdh0dHe9/XKlU\nVKlU6h44hiVLQngQ0tnbbTfpgQdChXHuufTJgCRVq1VVq9V+f1+/z/ows29JWu/uP9zm64Xbo77j\nDmnGDOmuu2JPAqCM6t2jbqvjiQ4ys/16Px4oaZqkBbs+YnwcSARQBDWDWtLhkh4ws/mSHpf0R3e/\nv7FjNQdrUAMogtJe8NLdHW699dproacGgGbLrPpoVc88E844IKQB5F1pg5p+GkBRlDao6acBFAVB\nDQA5V8qDie++Kx1ySLj11u67x54GQFlxMLEPTz4ZFvkhpAEUQSmDmtoDQJEQ1ACQc6UNam5mC6Ao\nShfUK1eGg4jHHht7EgCoT+mCOrn1Vlvp/s8BFFXp4op+GkDRlDKo6acBFEmpLnhxDxe6PPWUdMQR\nsacBUHZc8LIdL74o7bEHIQ2gWEoV1PTTAIqodEFNPw2gaEoV1KxBDaCISnMwcdOmcOut5cul/faL\nPQ0AcDDxAxYtkgYNIqQBFE9pgpp+GkBRlSao6acBFFVpgppT8wAUVc2DiWY2SNJtkg6V1CPpF+5+\n03a2y+3BxPXrpYMPltasCRe8AEAe1Hswsb2O59ok6avuvsDM9pE0z8xmuvuzuzxlk8yfL40YQUgD\nKKaa1Ye7v+7uC3o/XidpsaSPNHqwLFF7ACiyfnXUZnaUpNGSnmjEMI3CgUQARVZP9SFJ6q097pL0\nld496w/o6Oh4/+NKpaJKpbKL42Wjs1P61rdiTwGg7KrVqqrVar+/r64rE82sXdL/SfqTu/94B9vk\n8mDi6tXS0UeH229xVxcAeZL1lYn/LWnRjkI6z+bMkcaNI6QBFFfN+DKzSZI+J+lMM5tvZk+a2TmN\nHy0b9NMAiq5mR+3uj0rarQmzNERnpzR9euwpAGDntXQh4M6peQCKr6WD+uWXQzf9kUKd9Q0AW2vp\noE76aat5TBUA8qulg5raA0ArIKgBIOda9lZcmzeHW2+99FL4FQDypvS34nr2WemwwwhpAMXXskFN\n7QGgVRDUAJBzLR3U3MwWQCtoyYOJGzZIBx4orVolDRwYexoA2L5SH0xcsEAaPpyQBtAaWjKo6acB\ntJKWDWr6aQCtoiWDmjWoAbSSljuY2NUlDR4cft2tsKtoAyiD0h5MnDtXGjuWkAbQOlouqOmnAbSa\nlgxq+mkAraSlgppbbwFoRS0V1CtWSD090pFHxp4EALLTUkGd9NPcegtAK2m5oKb2ANBqaga1mf3K\nzN4ws4XNGGhXcKELgFZU84IXM5ssaZ2k29x9VB/bRb3gpacn3M1l6dKwch4A5F1mF7y4+yOSujKZ\nqoGee0466CBCGkDraZmOmn4aQKtqz/LJOjo63v+4UqmoUqlk+fR9Gj1aGjq0ab8dAPRbtVpVtVrt\n9/fVtSiTmQ2WdHeeO2oAKJqsF2Wy3gcAoMnqOT3vDkl/kTTMzF42s+mNHwsAkGi59agBoChKux41\nALQaghoAco6gBoCcI6gBIOcIagDIOYIaAHKOoAaAnCOoASDnCGoAyDmCGgByjqAGgJwjqAEg5whq\nAMg5ghoAco6gBoCcI6gBIOcIagDIOYIaAHKOoAaAnCOoASDnCGoAyDmCGgByrq6gNrNzzOxZM3ve\nzL7e6KEAAKmaQW1mbZJulvRxSSMlfcbMhjd6sCKrVquxR8gFXocUr0WK16L/6tmjHi/pBXd/yd27\nJf2PpAsaO1ax8Rcx4HVI8VqkeC36r56g/oikV7b4fHnv1wAATcDBRADIOXP3vjcwmyipw93P6f38\nWknu7t/bZru+nwgA8AHubrW2qSeod5P0nKSpkl6T1CnpM+6+OIshAQB9a6+1gbtvNrMrJM1UqEp+\nRUgDQPPU3KMGAMSV+cFEM7vazHrM7ICsn7sozOz7ZrbYzBaY2e/NbN/YMzUbF0kFZjbIzGab2V/N\n7GkzuzL2TLGZWZuZPWlmf4w9S0xmtp+Z/a43K/5qZhN2tG2mQW1mgyRNk/RSls9bQDMljXT30ZJe\nkPSvkedpKi6S2somSV9195GSTpF0eYlfi8RXJC2KPUQO/FjSPe5+nKQTJe2wUs56j/pGSddk/JyF\n4+73uXtP76ePSxoUc54IuEiql7u/7u4Lej9ep/DDWNrrEHp35s6V9MvYs8TU+y57irvfIknuvsnd\n397R9pkFtZl9QtIr7v50Vs/ZIv5J0p9iD9FkXCS1HWZ2lKTRkp6IO0lUyc5c2Q+ODZG0ysxu6a2B\nfm5mA3e0cc2zPrZkZrMkHbrllxRe8G9K+oZC7bHlf2tZfbwW17n73b3bXCep293viDAicsTM9pF0\nl6Sv9O5Zl46ZnSfpDXdfYGYVtXhG1NAuaayky919rpn9SNK1kq7f0cZ1c/dp2/u6mR0v6ShJT5mZ\nKbzVn2dm4939zf78HkWxo9ciYWb/qPAW78ymDJQvKyQducXng3q/Vkpm1q4Q0re7+x9izxPRJEmf\nMLNzJQ2U9CEzu83dPx95rhiWKzQQc3s/v0vSDg+6N+T0PDNbJmmsu3dl/uQFYGbnSPqhpNPcfXXs\neZqNi6S2Zma3SVrl7l+NPUtemNnpkq5290/EniUWM3tQ0j+7+/Nmdr2kvdx9u2Hdrz3qfnCV+23N\nf0raXdKs8AZDj7v7v8QdqXm4SCplZpMkfU7S02Y2X+Fn4xvufm/cyZADV0r6jZkNkLRU0vQdbcgF\nLwCQc6yeBwA5R1ADQM4R1ACQcwQ1AOQcQQ0AOUdQA0DOEdQAkHMENQDk3P8DSG5o2Q+JHoQAAAAA\nSUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110e74208>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot([-3, -2, 5, 0], [1, 6, 4, 3])\n",
|
||
"plt.axis([-4, 6, 0, 7])\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Now, let's plot a mathematical function. We use NumPy's `linspace` function to create an array `x` containing 500 floats ranging from -2 to 2, then we create a second array `y` computed as the square of `x` (to learn about NumPy, read the [NumPy tutorial](tools_numpy.ipynb))."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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SA69blJfDQQf5CpVdu4aORkTyaelSv5nQJ59Ed+cnDbxmqFYtuP56teZFStG990LPntFN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\nIqYkLyJSxJTkRUSKmJK8iEgR+/9JZLyXtkE0oAAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110ea3320>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"x = np.linspace(-2, 2, 500)\n",
|
||
"y = x**2\n",
|
||
"\n",
|
||
"plt.plot(x, y)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"That's a bit dry, let's add a title, and x and y labels, and draw a grid."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110e5b400>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot(x, y)\n",
|
||
"plt.title(\"Square function\")\n",
|
||
"plt.xlabel(\"x\")\n",
|
||
"plt.ylabel(\"y = x**2\")\n",
|
||
"plt.grid(True)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Line style and color"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"By default, matplotlib draws a line between consecutive points."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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dvR/A3V8ExrVioBK/onbY1SWXVkkS6KOA6cC33X068N+E5Zahq6BaFZWGFKXDri65tNqo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\ngg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1110cb710>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot([0, 100, 100, 0, 0, 100, 50, 0, 100], [0, 0, 100, 100, 0, 100, 130, 100, 0])\n",
|
||
"plt.axis([-10, 110, -10, 140])\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"You can pass a 3rd argument to change the line's style and color.\n",
|
||
"For example `\"g--\"` means \"green dashed line\"."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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dk/VDryARoVdsL6djGGOCYFP2JrJzs1nz6Bqa1m3qdJyAsDP0Cjp64ih7j+6lZUxLp6MY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\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1111bb470>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot([0, 100, 100, 0, 0, 100, 50, 0, 100], [0, 0, 100, 100, 0, 100, 130, 100, 0], \"g--\")\n",
|
||
"plt.axis([-10, 110, -10, 140])\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"You can plot multiple lines on one graph very simply: just pass `x1, y1, [style1], x2, y2, [style2], ...`\n",
|
||
"\n",
|
||
"For example:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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kF+aTsTuD9tPb88yKZygoKvC6JBEBPtv2GaN7j2b1b1czoO0AX4c5qIdeob7K/YqxqWP5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\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1110cb6a0>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot([0, 100, 100, 0, 0], [0, 0, 100, 100, 0], \"r-\", [0, 100, 50, 0, 100], [0, 100, 130, 100, 0], \"g--\")\n",
|
||
"plt.axis([-10, 110, -10, 140])\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Or simply call `plot` multiple times before calling `show`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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kF+aTsTuD9tPb88yKZygoKvC6JBEBPtv2GaN7j2b1b1czoO0AX4c5qIdeob7K/YqxqWP5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\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110f494a8>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot([0, 100, 100, 0, 0], [0, 0, 100, 100, 0], \"r-\")\n",
|
||
"plt.plot([0, 100, 50, 0, 100], [0, 100, 130, 100, 0], \"g--\")\n",
|
||
"plt.axis([-10, 110, -10, 140])\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"You can also draw simple points instead of lines. Here's an example with green dashes, red dotted line and blue triangles.\n",
|
||
"Check out [the documentation](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.plot) for the full list of style & color options."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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7sOHx6yD6mQ3n3Ajn3Grn3McttCnmc9fi8WV17swsLw/gWOBo4O/AyS20Wwrs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\ngv4/zWsyiRSjbi4AAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110e8c588>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1.4, 1.4, 30)\n",
|
||
"plt.plot(x, x, 'g--', x, x**2, 'r:', x, x**3, 'b^')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The plot function returns a list of `Line2D` objects (one for each line). You can set extra attributes on these lines, such as the line width, the dash style or the alpha level. See the full list of attributes in [the documentation](http://matplotlib.org/users/pyplot_tutorial.html#controlling-line-properties)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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Pdtu2wUEtedBVq5wc/aBB6W2TpEW0V//7F/RnzY1rOLCnU1b7xvo3mPfZPI45+JjkpqAr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\nHqTgLiLiQQruIiIe9P8Bt68WcL6/RNAAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110e3e668>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1.4, 1.4, 30)\n",
|
||
"line1, line2, line3 = plt.plot(x, x, 'g--', x, x**2, 'r:', x, x**3, 'b^')\n",
|
||
"line1.set_linewidth(3.0)\n",
|
||
"line1.set_dash_capstyle(\"round\")\n",
|
||
"line3.set_alpha(0.2)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Saving a figure\n",
|
||
"Saving a figure to disk is as simple as calling [`savefig`](http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.savefig) with the name of the file (or a file object). The available image formats depend on the graphics backend you use."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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0k6+Xln2vYJx1lvUHTpsWOolI4Vm6FO6/H66+OnSSaCrK9xMOGTLkl8+Li4spLi7Od4Ss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\nrkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110e41278>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1.4, 1.4, 30)\n",
|
||
"plt.plot(x, x**2)\n",
|
||
"plt.savefig(\"my_square_function.png\", transparent=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Subplots\n",
|
||
"A matplotlib figure may contain multiple subplots. These subplots are organized in a grid. To create a subplot, just call the `subplot` function, and specify the number of rows and columns in the figure, and the index of the subplot you want to draw on (starting from 1, then left to right, and top to bottom). Note that pyplot keeps track of the currently active subplot (which you can get a reference to by calling `plt.gca()`), so when you call the `plot` function, it draws on the *active* subplot.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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Cv5j3SWRNVNWVwD4Z2ikwXkSmichVBcqMPDb7N6KGCDzxhAsi+/rrsLUpDZ5+GurVgzPP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\nMAzDKGPMCBiGYZQxZgQMwzDKmP8Pl7YRbugR7JEAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110dfe630>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1.4, 1.4, 30)\n",
|
||
"plt.subplot(2, 2, 1) # 2 rows, 2 columns, 1st subplot = top left\n",
|
||
"plt.plot(x, x)\n",
|
||
"plt.subplot(2, 2, 2) # 2 rows, 2 columns, 2nd subplot = top right\n",
|
||
"plt.plot(x, x**2)\n",
|
||
"plt.subplot(2, 2, 3) # 2 rows, 2 columns, 3rd subplot = bottow left\n",
|
||
"plt.plot(x, x**3)\n",
|
||
"plt.subplot(2, 2, 4) # 2 rows, 2 columns, 4th subplot = bottom right\n",
|
||
"plt.plot(x, x**4)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"* Note that `subplot(223)` is a shorthand for `subplot(2, 2, 3)`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"It is easy to create subplots that span across multiple grid cells like so:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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TMCmJ9EVEKmntWvjd7+D446FfPxg8GLbcMulcFRZ7qVSuKOhvwE9yTwQb6Nev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\nvCTeAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110d9cb00>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.subplot(2, 2, 1) # 2 rows, 2 columns, 1st subplot = top left\n",
|
||
"plt.plot(x, x)\n",
|
||
"plt.subplot(2, 2, 2) # 2 rows, 2 columns, 2nd subplot = top right\n",
|
||
"plt.plot(x, x**2)\n",
|
||
"plt.subplot(2, 1, 2) # 2 rows, *1* column, 2nd subplot = bottom\n",
|
||
"plt.plot(x, x**3)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"If you need more complex subplot positionning, you can use `subplot2grid` instead of `subplot`. You specify the number of rows and columns in the grid, then your subplot's position in that grid (top-left = (0,0)), and optionally how many rows and/or columns it spans. For example:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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Xw/HHw9tv+0JfHKxcCSecYCaaPfeMW5qS0zMwndYH3hWRPVT13eqDgUl1a1Xd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\nRK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11148c240>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.subplot2grid((3,3), (0, 0), rowspan=2, colspan=2)\n",
|
||
"plt.plot(x, x**2)\n",
|
||
"plt.subplot2grid((3,3), (0, 2))\n",
|
||
"plt.plot(x, x**3)\n",
|
||
"plt.subplot2grid((3,3), (1, 2), rowspan=2)\n",
|
||
"plt.plot(x, x**4)\n",
|
||
"plt.subplot2grid((3,3), (2, 0), colspan=2)\n",
|
||
"plt.plot(x, x**5)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"If you need even more flexibility in subplot positioning, check out the [GridSpec documentation](http://matplotlib.org/users/gridspec.html)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Multiple figures\n",
|
||
"It is also possible to draw multiple figures. Each figure may contain one or more subplots. By default, matplotlib creates `figure(1)` automatically. When you switch figure, pyplot keeps track of the currently active figure (which you can get a reference to by calling `plt.gcf()`), and the active subplot of that figure becomes the current subplot."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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XkYlAk+gvAQrcpqqjYr1OJm0aUlBgTTL33mvrpPfvbx2pPp7duSRp\n0sTG2xfXpNautT/A6B3K0lDKbRryv4uJfADckOlt8oWFNkLmzjttPfW77oKjj/Yau3Ohe+YZW0Hz\nttvCjiRQobfJl5Kxqa6oCN56CwYMsHkcTz1lE/eccyni0ku3bboZPx5ycrJ6dcxA2uRFpI+ILAc6\nAaNFZFwQ100VqjBqFBx6KNx/Pzz0kA2H9ATvXAoq/khdWGjLIW/ZEm48IfNlDSqgaguE3XGHbTR9\n9922xpI3yziXhubMscfpp4cdyXZLteaajPDRR9as9+OP1vbet68vje1cWisszMo/Yq/Jl/LDD3DD\nDfDJJ1ZzP+ssn1HtXEYaMAAuv9x2ok9x8dTks+9trRyFhTY7tV0729R6zhxbTsMTvHMZSNU2N955\n57AjSTivyWP7ol55JTRoYLNV27QJOyLnXFJNmWJj7E88MexIyuQ1+Spavx6uuAJ694brrrOFxDzB\nO5eFMninqqxM8qrw4ouW0KtXh3nz4JxzMvYeO+cq07Ej9Oplz1XhuedsX9oMkHWja2bPhquusiGR\no0bB4YeHHZFzLqX8+qvV/DKkQy6oyVAPisg8EZkhIm+KSIMgrhuk/HwbEtmtm+3C9PnnnuCdc2Wo\nX9/WsC9O8jNmWNtumgqquWYC0FZV2wOLgL8FdN1ALFoERx5p9+rrr62TNUPepJ1ziTZ6NHz5ZdhR\nVFngo2tEpA9wqqqeW8b3kjq6RtW227vpJhsSe/XV3u7unItDYaEtYlWjRlJfNtVmvF4EDE/AdbdL\n8ciZuXNt1Ey7dmFH5JxLeyNGwGef2fLGaSLmmnws68mLyG3Aoap6ajnXSEpN/qOPbCJT797wwANQ\np07CX9I5lw1UYdOmbXeqSoKk1ORV9bhKgrgA6AVUuDZjIjcNyc+3td3/8x97pOi8BudcuhIpSfBr\n19rCVoMHB74mTsptGiIiPYF/AV1U9acKzktYTf6bb2yj7EaN4PnnoWnThLyMc86ZzZth4kRbmjbB\nUmHG62NAfWCiiHwlIk8GdN1KqdoWfJ06Qb9+MGaMJ3jnXBLUqbNtgs/NtT1BU0wgHa+q2iqI62yv\nrVttxMwnn8CkSXDIIWFE4ZzLekVF1kZ8wAEpV8tM2wXK1q6FU0+1ReReftnmLzjnXCZKheaapJo9\n25aaOOoo23PVE7xzLqWcfbbNvEwBaVeTHz0aLroIHn7YFhVzzrmUM2tWyQqIAYinJp82SV4V/vUv\neOQRePNN62h1zrmUN2+ebVBSq1aVL5HxzTVbtljt/ZVXbLKZJ3jnXNp47LFQ175J+Zr8mjVwyinQ\nuLENlaxXL0HBOedcisrYmvysWdbB2q0bvPGGJ3jnXJp76CEbT59EKbtpyLvvwiWX2IzhM88MOxrn\nnAtAly6w555JfcmgljW4C+iNLVj2I3CBqq4o47yYmmuWLrWfxeuvQ4cOcYfnnHNpLRWaax5U1UMi\nm4a8CwyM52ItW8L8+emX4INaUChVefnSVyaXDTK/fPEIJMmr6i9Rh/Ww2nxc0nF54Ez/RfPypa9M\nLhtkfvniEVibvIjcA5wH5AEdg7quc865qou5Ji8iE0VkVtTj68i/JwGo6u2quifwPDAoUQE755yL\nXSL2eN0DGKuqv9twT0SSNyjfOecySKh7vIrIfqq6OHLYB5hR1nlVDdI551zVBDWE8g1gf6AQ+Ba4\nUlXXxH1h55xzcUnqsgbOOeeSK6HLGohIXxGZLSKFInJoBed9JyIzRWS6iExJZExB2o7y9RSR+SKy\nUERuTmaM8RCRRiIyQUQWiMh4ESlzi/p0un+x3AsRGSwii0Rkhoi0T3aM8aisfCLSVUQ2RLbp/EpE\nbg8jzqoQkWdFZLWIzKrgnHS+dxWWr8r3TlUT9gBaA62A94FDKzjvW6BRImMJq3zYG+lioCVQA+uv\nOCDs2GMs3wPATZHnNwP3p/P9i+VeACcAYyLPOwKfhx13wOXrCowMO9Yqlu9ooD0wq5zvp+29i7F8\nVbp3Ca3Jq+oCVV0EVNbhKqT4YmllibF8HYBFqrpUVfOB4dgSEOmgN/Bi5PmLWKd6WdLl/sVyL3oD\nLwGo6hfATiLSJLlhVlmsv2tpOQBCVScD6ys4JZ3vXSzlgyrcu1T5w1RgoohMFZFLww4mYC2A5VHH\nKyJfSweNVXU1gKr+ADQu57x0uX+x3IvS56ws45xUFevvWudIc8YYEWmTnNCSIp3vXay2+97FPYRS\nRCYC0e+Wgv3R36aqo2K8zFGqukpEdsOSxbzIu1roAipfyqqgfGW195XXS5+y98/9zjRgT1XNE5ET\ngHewkXEu9VXp3sWd5FX1uACusSry71oReRv72JkSSSKA8q0EotcW3T3ytZRQUfkinUBNVHW1iDQF\nyhwWm8r3r5RY7sVKYI9KzklVlZZPo9aZUtVxIvKkiOysquuSFGMipfO9q1RV710ym2vKbEsSkboi\nUj/yvB7QA5idxLiCUl5b2VRgPxFpKSI1gX7AyOSFFZeRwAWR5+djK4xuI83uXyz3YiS2BhMi0gnY\nUNxklQYqLV90G7WIdMCGUadTghfK/1tL53tXrNzyVfneJbi3uA/WRrYZWAWMi3y9GTA68nxvbBTA\ndOBr4Jawe7mDLF/kuCewAFiUZuXbGZgUiX0C0DDd719Z9wK4HLgs6pzHsVEqM6lgVFgqPiorH3A1\n9iY8HfgU6Bh2zNtRtmHA98AWYBlwYYbduwrLV9V755OhnHMug6XK6BrnnHMJ4EneOecymCd555zL\nYJ7knXMug3mSd865DOZJ3jnnMpgneeecy2Ce5J1zLoP9P3jSdhlrbfQYAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1115e7668>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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iIjsYNw5OOQVat44dyfYaTbDMbFdgs7u/b2YdgJOBG2pd9ihwETDGzI4C1rp7nRVTNROs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\nCfv/ST5WQayPGrYAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1110cb978>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1.4, 1.4, 30)\n",
|
||
"\n",
|
||
"plt.figure(1)\n",
|
||
"plt.subplot(211)\n",
|
||
"plt.plot(x, x**2)\n",
|
||
"plt.title(\"Square and Cube\")\n",
|
||
"plt.subplot(212)\n",
|
||
"plt.plot(x, x**3)\n",
|
||
"\n",
|
||
"plt.figure(2, figsize=(10, 5))\n",
|
||
"plt.subplot(121)\n",
|
||
"plt.plot(x, x**4)\n",
|
||
"plt.title(\"y = x**4\")\n",
|
||
"plt.subplot(122)\n",
|
||
"plt.plot(x, x**5)\n",
|
||
"plt.title(\"y = x**5\")\n",
|
||
"\n",
|
||
"plt.figure(1) # back to figure 1, current subplot is 212 (bottom)\n",
|
||
"plt.plot(x, -x**3, \"r:\")\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Pyplot's state machine: implicit *vs* explicit\n",
|
||
"So far we have used Pyplot's state machine which keeps track of the currently active subplot. Every time you call the `plot` function, pyplot just draws on the currently active subplot. It also does some more magic, such as automatically creating a figure and a subplot when you call `plot`, if they don't exist yet. This magic is convenient in an interactive environment (such as Jupyter).\n",
|
||
"\n",
|
||
"But when you are writing a program, *explicit is better than implicit*. Explicit code is usually easier to debug and maintain, and if you don't believe me just read the 2nd rule in the Zen of Python:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"The Zen of Python, by Tim Peters\n",
|
||
"\n",
|
||
"Beautiful is better than ugly.\n",
|
||
"Explicit is better than implicit.\n",
|
||
"Simple is better than complex.\n",
|
||
"Complex is better than complicated.\n",
|
||
"Flat is better than nested.\n",
|
||
"Sparse is better than dense.\n",
|
||
"Readability counts.\n",
|
||
"Special cases aren't special enough to break the rules.\n",
|
||
"Although practicality beats purity.\n",
|
||
"Errors should never pass silently.\n",
|
||
"Unless explicitly silenced.\n",
|
||
"In the face of ambiguity, refuse the temptation to guess.\n",
|
||
"There should be one-- and preferably only one --obvious way to do it.\n",
|
||
"Although that way may not be obvious at first unless you're Dutch.\n",
|
||
"Now is better than never.\n",
|
||
"Although never is often better than *right* now.\n",
|
||
"If the implementation is hard to explain, it's a bad idea.\n",
|
||
"If the implementation is easy to explain, it may be a good idea.\n",
|
||
"Namespaces are one honking great idea -- let's do more of those!\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import this"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Fortunately, Pyplot allows you to ignore the state machine entirely, so you can write beautifully explicit code. Simply call the `subplots` function and use the figure object and the list of axes objects that are returned. No more magic! For example:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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XK6a9/d69+UE11Mg9L0TA6uVp6N45TZGhXqMGR46PHvWzQYECwAMPcGjZYjIy+J7tT4Dv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MAAAA\nMklEQVSYiIiISJwpARMRERGJMyVgIiIiInGmBExEREQkzpSAiYiIiMSZEjARERGROPt/zncAD509\n4WEAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1114bfc18>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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+iCYWU4LPZYkk+UbAihKPP48/V1p7M5tnZlPN7MiURCcZtddeftrc5s1w7rl+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\nkhcRyWFK8iIiOUxJXkQkh/1/Rfi+v/OzAxcAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110db6278>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-2, 2, 200)\n",
|
||
"fig1, (ax_top, ax_bottom) = plt.subplots(2, 1, sharex=True)\n",
|
||
"fig1.set_size_inches(10,5)\n",
|
||
"line1, line2 = ax_top.plot(x, np.sin(3*x**2), \"r-\", x, np.cos(5*x**2), \"b-\")\n",
|
||
"line3, = ax_bottom.plot(x, np.sin(3*x), \"r-\")\n",
|
||
"ax_top.grid(True)\n",
|
||
"\n",
|
||
"fig2, ax = plt.subplots(1, 1)\n",
|
||
"ax.plot(x, x**2)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"For consistency, we will continue to use pyplot's state machine in the rest of this tutorial, but we recommend using the object-oriented interface in your programs.\n",
|
||
"\n",
|
||
"## Pylab *vs* Pyplot *vs* Matplotlib\n",
|
||
"\n",
|
||
"There is some confusion around the relationship between pylab, pyplot and matplotlib. It's simple: matplotlib is the full library, it contains everything including pylab and pyplot.\n",
|
||
"\n",
|
||
"Pyplot provides a number of tools to plot graphs, including the state-machine interface to the underlying object-oriented plotting library.\n",
|
||
"\n",
|
||
"Pylab is a convenience module that imports matplotlib.pyplot and NumPy in a single name space. You will find many examples using pylab, but it is no longer recommended (because *explicit* imports are better than *implicit* ones)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Drawing text\n",
|
||
"You can call `text` to add text at any location in the graph. Just specify the horizontal and vertical coordinates and the text, and optionally some extra attributes. Any text in matplotlib may contain TeX equation expressions, see [the documentation](http://matplotlib.org/users/mathtext.html) for more details."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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ORqnQ078/FC8uI1wLA53WIMD07w+VKsGoUU5HolTomTsXli6FMWOcjiQ4aEve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\ngg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11159cbe0>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1.5, 1.5, 30)\n",
|
||
"px = 0.8\n",
|
||
"py = px**2\n",
|
||
"\n",
|
||
"plt.plot(x, x**2, \"b-\", px, py, \"ro\")\n",
|
||
"\n",
|
||
"plt.text(0, 1.5, \"Square function\\n$y = x^2$\", fontsize=20, color='blue', horizontalalignment=\"center\")\n",
|
||
"plt.text(px - 0.08, py, \"Beautiful point\", ha=\"right\", weight=\"heavy\")\n",
|
||
"plt.text(px, py, \"x = %0.2f\\ny = %0.2f\"%(px, py), rotation=50, color='gray')\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"* Note: `ha` is an alias for `horizontalalignment`\n",
|
||
"\n",
|
||
"For more text properties, visit [the documentation](http://matplotlib.org/users/text_props.html#text-properties).\n",
|
||
"\n",
|
||
"It is quite frequent to annotate elements of a graph, such as the beautiful point above. The `annotate` function makes this easy: just indicate the location of the point of interest, and the position of the text, plus optionally some extra attributes for the text and the arrow."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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Tmt+6FfLlszoaIbLv2LFj3FHvDvpH9ie0digAB346wOdDPid6dzSFCxd26vG6\ndYOKFaVUiHTX2ET37ma5QFlFXthVmTJlmDp5KpH/jiQx3qwaVbV5Vaq1rsazzz/r1GN99hns3u39\nxcdcTVrybnbypPn4+dVXEJ5hrU4hPJvWmvva3Uf+xvm57z/3AXDlwhVeb/46C+cupHXr1rk+xokT\npntz2TJo3DjXu7M96a6xmSVL4JVXYPt2CAqyOhohsu/IkSPUbViXwcsGU6pGKQCif4hmxQsriN4T\nTYFcTEfVGh55xKzVKmPiDemusZmuXaFePRg1yupIhMiZ8uXLM2HsBCKfjiQp0awaVfO+mpS/uzwv\nDH/hhm211pw/f97hfX/6Kfz2G7z6qlND9lnSkrfI33+bbpvISLjrLqujESL7kpKSaHFvC0LuCyFi\nSAQAl85d4vW7X+fLxV/SvHlzDh06RN8Bffn71N/s2bkny30eP24aQN98Aw0buvgEbERa8jZUvLgp\nk9q3L1y8aHU0QmSfn58fH879kNXTV3Pq4CkA8hfOT6cpnej9eG+mz5hOvTvrEdQgiJg/YrKsXKk1\nDBxoviTBO48keQt17gwtWpiqevIBR9hR5cqVGTViFJHPRKYu9l27Q21KNyjNO5++w1MrnqLdS+1Q\n/oqzZ8/ecl/TppmBCa+84o7IfYd011js8mUzymbIENOCEcJuEhMTCW8WTsVHKtKsfzPA9MOrNCtr\nT28+nS8//pJ69epluI/1602jZ9MmqFDBLWHbinTX2FhQkBltM2KEGW0jhN34+/vz8osvs3z0cq7G\nmQVG0iZ4gCKhRThy5EiGP//339CjB8ydKwneFSTJe4Bq1eCtt8zsvgsXrI5GCMfFx8czbvw4+g3s\nx4PjHiRvcMYV+AqVLZRhkk9KMiW5e/SAjh1dHa1vCrA6AGH06GGWNBswABYvNmWKhfBk586do1lE\nM3RhzTOrnqFIaJFMty0YWpCYQzE3vf7aa6ZhI2suuI605D3ItGnw++++szixsLd8+fJRp04dTvx2\nggM/HUi98ZqRIqFFiIm9McmvXQvTp5tx8bLgvetIkvcg+fKZ/vmxY03teSE8Wb58+Vi0YBHLv1hO\n9PxoZrWbxaEthzLctkhoEQ4fOZz6/ORJU4J7/nwIDXVPvL5KkryHqVwZ3nnH9M9nMeJMCI8QHh7O\nll+2MGLICBY+tpDFQxZz/q8bZ7gWCS3C0dijACQmwqOPmjki7dpZELCPkSTvgR55BB54APr1k/Hz\nwh78/PzkKd2AAAAOcUlEQVTo27cvB389yF2hdzGt+TR+nPFj6gIjhUoV4szJM8THxzNhAsTHSzVW\nd5Ek76GmTIFjx0yfpRB2UbBgQaa+NpUtv2whfms8rzd7nT3/24Ofvx8FCudnQN3mRE78F1MmxxAg\nwz7cQiZDebBDh6BJE7NKvZQlFnb03XffMXjoIAJDAjgfc4rP/rpAQ+DVypX59/ffU6FSJatDtAWZ\nDOWlKlaE994zi42cPm11NEJkX9u2bend6C76bfyDS3//w2kgGBhz8CDzpX6BW0iS93APPmhKE/fp\nYyaOCGE36vhxhidpjickkbIKbDCQdOyYlWH5DEnyNjBxohlpM2WK1ZEIkX1/qbLEYRJ7Sjd8HOBX\npox1QfkQ6ZO3idhYaNTIrHvZooXV0QjhmKNHoUH9GLoGtua1YwcJxiR46ZPPHln+z0esXAmPPQY/\n/2zG0wvhyS5ehObNzZj4bl1imP/KKyQdO4ZfmTL0HTdOEnw2SJL3IbNnwxtvmNKsxYpZHY0QGUtI\nMPeTQkPh3XelFlNuSZL3MS+8ABs3wvffQ96Mi/4JYRmtzfoIBw/C8uVSl8YZJMn7mKQkU/Ygb174\n+GNpJQnP8vrr8OGHpluxUCGro/EOMk7ex/j5wUcfmZbSqFFWRyPEdZ9/broTV6yQBO8pHErySql2\nSqn9SqnflFL/zeD7LZVS55RS25K/Rjo/VJFWUBAsWwYLF8K8eVZHI4TpQhw82PxelitndTQiRZbV\nI5RSfsDbQCvgGLBZKbVUa70/3aZrtdYPuiBGkYkSJUyLKSICypeHVq2sjkj4qpgYs0brvHnQoIHV\n0Yi0HGnJNwYOaK0Pa63jgU+BhzLYTnqGLVCzpllJqmdP2LfP6miELzp7Fjp0gJdfliX8PJEjSb4s\nEJvm+dHk19JrqpTaoZRaoZQKc0p0wiERETB1Ktx/P/z1l9XRCF9y7Zopjd2uHQwdanU0IiPOKva5\nFSivtb6klGoPfAVUy2jD0WmKSEdERBAREeGkEHxbnz7wxx9mbHJUFOTPb3VEwttpDU88YW6wTp1q\ndTTeJSoqiqioKKfsK8shlEqpcGC01rpd8vPhgNZaT77Fz8QADbXWZ9K9LkMoXUhrMyP24kWIjAR/\nf6sjEt5s7Fj4+mvTqAgOtjoa7+bqIZSbgSpKqQpKqUCgB7AsXQAl0zxujHnzOINwK6VMaeKzZ82E\nKSFc5eOP4YMPTJKXBO/Zsuyu0VonKqWGAisxbwpztdbRSqlB5tt6DtBFKfUkEA9cBrq7MmiRubx5\n4csvoWlTU99myBCrIxLeZs0a+M9/YPVqKFXK6mhEVmTGq5f64w9o1syUJ370UaujEd5i82Yzgmbh\nQrjvPquj8R256a6RVRa91O23m9o2rVubvvp//cvqiITdbdpkFph//31J8HYiSd6L1aoFP/xg/iCT\nkswIHCFyYuNGk+A/+EDGwtuNJHkvFxZmEn1Ki/6xx6yOSNjNL7+Yobnz5pm5GMJeJMn7gLAw+PFH\nU/ZAa+jb1+qIhF1s2AAPPWSqSrZvb3U0IickyfuIGjVg1SqT6JOS4PHHrY5IeLp160w9mgULzIxW\nYU+S5H1I9erXW/RJSTBggNURCU/188/w8MOmpHXbtlZHI3JDkryPqV79eos+ZVq6EGn99JNJ8AsX\nQps2VkcjckuSvA+qVu3GRD9woNURCU+xdi106QKffCLDJL2FJHkfVbWqSfT33mu6bgYPtjoiYbU1\na6BrV5PgZW0C7yFJ3odVqWKmpqck+qeesjoiYZXVq826wYsXm98H4T0kyfu4ypXNH/g998DVq/DM\nM7IwuK/57jszI3rJErM2gfAuspC34PbbzUf1uXNNt821a1ZHJNxBa5gxw8yb+OorSfDeSgqUiVQX\nLphiZin16IsXtzoi4SrXrpkKpRs3moW3K1a0OiJxK66uJy98RKFCpkUXHg5NmsDevVZHJFzh1ClT\n5uLkSTPhSRK8d5MkL27g7w+TJsHo0aaffvlyqyMSzrR7t3kDv/tus+5AwYJWRyRcTbprRKZ++cUs\n0vzMM/D883JD1u6WLTOznKdPh169rI5GZEduumskyYtbio01Bapq14Z334V8+ayOSGSX1jB5Mrz9\nNnzxBTRubHVEIrukT164TLlyZpr7pUtm/PRff1kdkciOK1egd29zI33jRknwvkiSvMhScLCZJNO2\nrenP3b7d6oiEI44fN8MiExJMuYKyZa2OSFhBkrxwiJ8fvPoqTJ1qilZ9/rnVEYlb2brVvCF37GjK\nFOTPb3VEwirSJy+ybds2U2f8/vtNX6+M0PAciYkwbRq89pq5h/Lww1ZHJJxB+uSFWzVoADt2wOXL\nUKeOqVEvrBcdbYZGfvON6X+XBC9AkrzIoSJFzJqfs2ZBv34waJCZMSvcLyHBzG1o0cKs4fvjj6ZU\nhRAgSV7kUvv2ZoJNUpIZZvndd1ZH5Fv27IGmTU1i37wZnnzS3D8RIoX8Oohcu+02eO89eP9906Lv\n3x/OnbM6Ku8WHw/jx5tZyQMHwsqVUp5AZEySvHCa1q1Nqz4w0LTqv/nG6oi8065dZuTMzz+bUTRP\nPCGzkUXmZHSNcIlVq8wU+hYt4I03TB++yJ1r12DiRJg504xq6ttXkruvkNE1wuPce69pcRYsaFr1\nkZFmer3ImQ0boFEj0+++fbu52S0JXjhCWvLC5dauNUXOkpJg1Cjo1EluDjpqwwYYMwb27YMJE8wK\nTpLcfY8UKBMeT2tTtnj0aDPk75VXzDhuSfYZW7fOJPfffoOXXjJdM3nzWh2VsIokeWEbWsOKFSaB\nXblikn2XLpLsU/z0k/m/OXgQXn7ZjHsPDLQ6KmE1SfLCdrSGb781Ce2ff0w3TpcuZtESX7Rmjfm/\nOHQIRoyAPn0gTx6roxKeQpK8sC2tzQSq0aPNjNlXXoFu3Xwn2UdFmXOPjYWRI02fuyR3kZ4keWF7\nWpsJPWPGwJkzZvhlly7eOcHn9Gmzlu78+aYc8MiRZgF1Se4iM5LkhdfQ2rRuFy40ifD226FrV5Pw\nK1WyOrqc+/tvcz5LlpgRM61bQ/fu5uZzQIDV0QlP5/Ikr5RqB0zHjKufq7WenME2bwLtgTigr9Z6\nRwbbSJIXDouPNwl/yRKz6HTFitcTvh0KcJ06ZeJesgQ2bTJ1+Lt2hQ4doEABq6MTduLSyVBKKT/g\nbaAtUAvoqZSqkW6b9kBlrXVVYBAwOyfB2F1UVJTVIbiUu88vTx7T4p0zx3RrTJoEf/wB4eHQsKF5\nfvCg847njPM7eRJmz4b77oMqVUzhsEGD4Ngxk+y7dbMmwcvvpu9yZOBaY+CA1vqw1joe+BR4KN02\nDwELALTWG4HblFIlnRqpDXj7L5qV5xcQAK1amQR67BhMmQJHjpj66WFh0KMHjB1rVqyKjjafArIr\nO+eXlAQxMWY46JQpZhx7o0ZQrZoZKfPUU+aNafFi88kjODj78TiT/G76Lkd6A8sCsWmeH8Uk/ltt\n82fyaydyFZ0QGQgIMGUT7r0X3nrLlE/Yu9fMCv3oI/P46FGoXNm8AdSqZf4NC4OqVbM37jwpyQxr\nTNn/vn3m8f79ph5Pyv6bNTPVIOvXh6Agl526ENkmt3yErfn7m8Rav/6Nr1++bGaLpiTnTz4xjw8f\nhnz5Mt7XlSswffqNr129CiVKXH+TaNnS1GyvWdOUWBbC02V541UpFQ6M1lq3S34+HNBpb74qpWYD\nq7XWi5Of7wdaaq1PpNuX3HUVQogcyOmNV0da8puBKkqpCsBxoAfQM902y4AhwOLkN4Vz6RN8boIU\nQgiRM1kmea11olJqKLCS60Moo5VSg8y39Ryt9TdKqQ5Kqd8xQyj7uTZsIYQQjnDrZCghhBDu5dLa\nf0qpLkqpPUqpRKVUg1tsd0gptVMptV0ptcmVMTlTNs6vnVJqv1LqN6XUf90ZY24opYoopVYqpX5V\nSn2nlMrwVqOdrp8j10Ip9aZS6oBSaodSqp67Y8yNrM5PKdVSKXVOKbUt+WukFXHmhFJqrlLqhFJq\n1y22sfO1u+X55fjaaa1d9gVUB6oCq4AGt9juD6CIK2Ox6vwwb6S/AxWAPMAOoIbVsTt4fpOBF5Mf\n/xeYZOfr58i1wMzaXpH8uAnwi9VxO/n8WgLLrI41h+fXDKgH7Mrk+7a9dg6eX46unUtb8lrrX7XW\nB4CsbrgqbLgUoYPn58hkMk/1EPBh8uMPgU6ZbGeX6+ftE/sc/V2z5QAIrfXPwNlbbGLna+fI+UEO\nrp2n/GFq4Hul1Gal1BNWB+NkGU0mK2tRLNlVQiePktJa/wWUyGQ7u1w/R65FZhP77MDR37Wmyd0Z\nK5RSYe4JzS3sfO0cle1rl+vJUEqp74G075YK80c/Qmv9tYO7uVtrfVwpFYJJFtHJ72qWc9L5eaxb\nnF9G/X2Z3aX32OsnbrIVKK+1vpRcc+oroJrFMQnH5Oja5TrJa61bO2Efx5P/PaWU+hLzsdMjkoQT\nzu9PoHya56HJr3mEW51f8k2gklrrE0qpUsDJTPbhsdcvHUeuxZ9AuSy28VRZnp/W+p80j79VSs1S\nShXVWp9xU4yuZOdrl6WcXjt3dtdk2JeklMqvlCqQ/DgYaAPscWNczpJZX1nqZDKlVCBmMtky94WV\nK8uAvsmPHwOWpt/AZtfPkWuxDOgDqbO9M5zY56GyPL+0fdRKqcaYYdR2SvCKzP/W7HztUmR6fjm+\ndi6+W9wJ00d2GTNb9tvk10sDy5MfV8KMAtgO7AaGW32X25nnl/y8HfArcMBm51cU+CE59pVAYbtf\nv4yuBaY89sA027yNGaWyk1uMCvPEr6zODzMzfU/y9VoPNLE65myc2yLgGHAVOIKZdOlN1+6W55fT\nayeToYQQwot5yugaIYQQLiBJXgghvJgkeSGE8GKS5IUQwotJkhdCCC8mSV4IIbyYJHkhhPBikuSF\nEMKL/T8NEj13fbb1AwAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1113296a0>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot(x, x**2, px, py, \"ro\")\n",
|
||
"plt.annotate(\"Beautiful point\", xy=(px, py), xytext=(px-1.3,py+0.5),\n",
|
||
" color=\"green\", weight=\"heavy\", fontsize=14,\n",
|
||
" arrowprops={\"facecolor\": \"lightgreen\"})\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"You can also add a bounding box around your text by using the `bbox` attribute:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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L9FzTphHaz8/P7vGmTftM+/n56enTZ2favmvXUbv7DxkyXPv5+elZs77OtH3o0EitlNLF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\nhPBh/w/hvOQ+vYnpVgAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x111571e80>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.plot(x, x**2, px, py, \"ro\")\n",
|
||
"\n",
|
||
"bbox_props = dict(boxstyle=\"rarrow,pad=0.3\", ec=\"b\", lw=2, fc=\"lightblue\")\n",
|
||
"plt.text(px-0.2, py, \"Beautiful point\", bbox=bbox_props, ha=\"right\")\n",
|
||
"\n",
|
||
"bbox_props = dict(boxstyle=\"round4,pad=1,rounding_size=0.2\", ec=\"black\", fc=\"#EEEEFF\", lw=5)\n",
|
||
"plt.text(0, 1.5, \"Square function\\n$y = x^2$\", fontsize=20, color='black', ha=\"center\", bbox=bbox_props)\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Just for fun, if you want an [xkcd](http://xkcd.com)-style plot, just draw within a `with plt.xkcd()` section:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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L4VT8LRYLAHoAv/0GfPwxMGEClxalN9XV1XjxxRfx66+/oqysDJWVlTCZTFybxcPTIMFg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\nJCRqIZL4S0hISNRCJPGXkJCQqIX8PyYRQlLDn769AAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11159c898>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"with plt.xkcd():\n",
|
||
" plt.plot(x, x**2, px, py, \"ro\")\n",
|
||
"\n",
|
||
" bbox_props = dict(boxstyle=\"rarrow,pad=0.3\", ec=\"b\", lw=2, fc=\"lightblue\")\n",
|
||
" plt.text(px-0.2, py, \"Beautiful point\", bbox=bbox_props, ha=\"right\")\n",
|
||
"\n",
|
||
" bbox_props = dict(boxstyle=\"round4,pad=1,rounding_size=0.2\", ec=\"black\", fc=\"#EEEEFF\", lw=5)\n",
|
||
" plt.text(0, 1.5, \"Square function\\n$y = x^2$\", fontsize=20, color='black', ha=\"center\", bbox=bbox_props)\n",
|
||
"\n",
|
||
" plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Legends\n",
|
||
"The simplest way to add a legend is to set a label on all lines, then just call the `legend` function."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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A4O/vT2hoKC1atAD++fR1t+dla5al1exWPF/zeUJvhqbn6irxOer5rZ+5SjyO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\nJMVdCCEsSIq7EEJYkBR3IYSwoP8Pty27aLnc6mkAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1115ed160>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1.4, 1.4, 50)\n",
|
||
"plt.plot(x, x**2, \"r--\", label=\"Square function\")\n",
|
||
"plt.plot(x, x**3, \"g-\", label=\"Cube function\")\n",
|
||
"plt.legend(loc=\"best\")\n",
|
||
"plt.grid(True)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Non linear scales\n",
|
||
"Matplotlib supports non linear scales, such as logarithmic or logit scales."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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4c6XcNOAOM1tCcPXOlTHn+RB3f4Zg5tingGcI/qHNiTVUBjO7E3gM\nOMrM1pjZJOBq4DNm9iLBl1SHl+/FkPHHwD7A/4X/jn4aZ0ZoM2cmJwHlnTZy/jdwuJk9C9wJdHiQ\np5uzRESqSNzlHRERKSMN+iIiVUSDvohIFdGgLyJSRTToi4hUEQ36IiJVRIO+iEgV0aAvIlJF/j99\n91seM1/U/gAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110fd3588>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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BdgSeUdXxNbxGVZXp0+H++916NSa/TJ0Kl1wCF10Ef/wjNG0adiJj4i8WYwKqukBVL8It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\nCBhjTAGzImCMMQXMioAxxhSw/weDLj/d6TgbZQAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1115c6198>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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9tuomm6g+9VTymqJozc8zDVxnsmRZZ319vdbV1ZU1D6M7sJ6IjATWAaIWVkb5dMM2P3oG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\nU+3PszWdZ/F55o6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UrXpX/XgMowJkWVsY15ksrjNZsqqzVy/LBJ8+HY45Bh55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\n6TgSU7M0AAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11101acc0>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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MuiVHbnfmnWVzzOwjZjbTzJ5P3teD8s7UlpldlGR72sxuNbMt884E7Z+WbWYf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\nAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x111555160>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(0.1, 15, 500)\n",
|
||
"y = x**3/np.exp(2*x)\n",
|
||
"\n",
|
||
"plt.figure(1)\n",
|
||
"plt.plot(x, y)\n",
|
||
"plt.yscale('linear')\n",
|
||
"plt.title('linear')\n",
|
||
"plt.grid(True)\n",
|
||
"\n",
|
||
"plt.figure(2)\n",
|
||
"plt.plot(x, y)\n",
|
||
"plt.yscale('log')\n",
|
||
"plt.title('log')\n",
|
||
"plt.grid(True)\n",
|
||
"\n",
|
||
"plt.figure(3)\n",
|
||
"plt.plot(x, y)\n",
|
||
"plt.yscale('logit')\n",
|
||
"plt.title('logit')\n",
|
||
"plt.grid(True)\n",
|
||
"\n",
|
||
"plt.figure(4)\n",
|
||
"plt.plot(x, y - y.mean())\n",
|
||
"plt.yscale('symlog', linthreshy=0.05)\n",
|
||
"plt.title('symlog')\n",
|
||
"plt.grid(True)\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Ticks and tickers\n",
|
||
"The axes have little marks called \"ticks\". To be precise, \"ticks\" are the *locations* of the marks (eg. (-1, 0, 1)), \"tick lines\" are the small lines drawn at those locations, \"tick labels\" are the labels drawn next to the tick lines, and \"tickers\" are objects that are capable of deciding where to place ticks. The default tickers typically do a pretty good job at placing ~5 to 8 ticks at a reasonable distance from one another.\n",
|
||
"\n",
|
||
"But sometimes you need more control (eg. there are too many tick labels on the logit graph above). Fortunately, matplotlib gives you full control over ticks. You can even activate minor ticks.\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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RxSlS1ur/Ym7Ih865Zc65q/EHc3udtlqVnfJk/sz2ocBpzrn5zrmlzrnSs3OrmNlV+I5l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\nE+KuiZem+GRmFwGLnHNXtXpe8UmkRk8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mSXp8MrP9gYXAHRqkSaiefRaOPx5eew3WWivu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\nLrzQTSvs1i2ZAZrvPvsSa79DptwUrjlzXP457jhXhnHBBS7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dhYjIwgYNgvXXh6239h2J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\nAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x111380f28>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-2, 2, 100)\n",
|
||
"\n",
|
||
"plt.figure(1, figsize=(15,10))\n",
|
||
"plt.subplot(131)\n",
|
||
"plt.plot(x, x**3)\n",
|
||
"plt.grid(True)\n",
|
||
"plt.title(\"Default ticks\")\n",
|
||
"\n",
|
||
"ax = plt.subplot(132)\n",
|
||
"plt.plot(x, x**3)\n",
|
||
"ax.xaxis.set_ticks(np.arange(-2, 2, 1))\n",
|
||
"plt.grid(True)\n",
|
||
"plt.title(\"Manual ticks on the x-axis\")\n",
|
||
"\n",
|
||
"ax = plt.subplot(133)\n",
|
||
"plt.plot(x, x**3)\n",
|
||
"plt.minorticks_on()\n",
|
||
"ax.tick_params(axis='x', which='minor', bottom='off')\n",
|
||
"ax.xaxis.set_ticks([-2, 0, 1, 2])\n",
|
||
"ax.yaxis.set_ticks(np.arange(-5, 5, 1))\n",
|
||
"ax.yaxis.set_ticklabels([\"min\", -4, -3, -2, -1, 0, 1, 2, 3, \"max\"])\n",
|
||
"plt.title(\"Manual ticks and tick labels\\n(plus minor ticks) on the y-axis\")\n",
|
||
"\n",
|
||
"\n",
|
||
"plt.grid(True)\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Polar projection\n",
|
||
"Drawing a polar graph is as easy as setting the `projection` attribute to `\"polar\"` when creating the subplot."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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W9jgAN0tF6pZ4pSKEcBNCfP/jjz/mPMXWghiNxiKJ1Jw+fTpSUlKwbt26p0qy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\nKy6h4sKFC7vy/yOFll8u6LhAAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11134d518>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"radius = 1\n",
|
||
"theta = np.linspace(0, 2*np.pi*radius, 1000)\n",
|
||
"\n",
|
||
"plt.subplot(111, projection='polar')\n",
|
||
"plt.plot(theta, np.sin(5*theta), \"g-\")\n",
|
||
"plt.plot(theta, 0.5*np.cos(20*theta), \"b-\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 3D projection\n",
|
||
"\n",
|
||
"Plotting 3D graphs is quite straightforward. You need to import `Axes3D`, which registers the `\"3d\"` projection. Then create a subplot setting the `projection` to `\"3d\"`. This returns an `Axes3DSubplot` object, which you can use to call `plot_surface`, giving x, y, and z coordinates, plus optional attributes."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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G5YUV+oAHmpZupTVTfJ5JnZASkghd+/JdykoT2RLtO4iUD5k0R09OcPy1j9D32CM8/Man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FsBMRL7RRwXPouv0sVmRsd+Al58a4VoLEk6W0av05LNJBkdHSHoc6E29iMVS3jmuRdOPZ+HjfdS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\ndTyeQattLQaQL1Tbp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RifZmtVsMQaGJnE79lBpzeSz+WQSKXIZXVUWgMylYVCVUMhm0Sj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\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x111332e80>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from mpl_toolkits.mplot3d import Axes3D\n",
|
||
"\n",
|
||
"x = np.linspace(-5, 5, 50)\n",
|
||
"y = np.linspace(-5, 5, 50)\n",
|
||
"X, Y = np.meshgrid(x, y)\n",
|
||
"R = np.sqrt(X**2 + Y**2)\n",
|
||
"Z = np.sin(R)\n",
|
||
"\n",
|
||
"figure = plt.figure(1, figsize = (12, 4))\n",
|
||
"subplot3d = plt.subplot(111, projection='3d')\n",
|
||
"surface = subplot3d.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=matplotlib.cm.coolwarm, linewidth=0.1)\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Another way to display this same data is *via* a contour plot."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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kOW5VCTtGYOC0j17LOhZF0x+hos6KS7o4bRW2R9fdo7eyrir9EUPUWfFoOi5lCTuNoimR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\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1113cc0b8>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.contourf(X, Y, Z, cmap=matplotlib.cm.coolwarm)\n",
|
||
"plt.colorbar()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Scatter plot"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"To draw a scatter plot, simply provide the x and y coordinates of the points."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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ko8aRuQcOPM299945J8d7w4Y/4vzzL8x17noevT5/UhW4DthObZG/79WfvyWzC6/mdsoP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\nICJSYgoCIiIlpiAgIlJi/x/3fM91UuyZkgAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1115a1278>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from numpy.random import rand\n",
|
||
"x, y = rand(2, 100)\n",
|
||
"plt.scatter(x, y)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"You may also optionally provide the scale of each point."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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4h9V6A6+/PpqHHx6ZZ825c+fyyCM/4HBMpmLF7iQmHs+zvjfcd99o\ngoICmDv3Xd1ll2ScTidVqlxFcnIj4GOgVh61z+B52IgBOvLCCxWYNGlSjjVXrFjBwIFDABsu11nm\nzJnJvfcO1tt8hRdomoaIeLcF3dvJhKIqlIOJ4dKCy+WS/v3vyZ4MTMxnMvik2Gxt5aGHxhYoi9fB\ngwelQoVwMZvDZOzYJ4vM/rwyrJVF3G633H773aJpvQQyCjiR7xYYI3CVvPhi3oluHA6HHDhwQFJT\nU4upRYqCgJoYVhQFBoOBL774iKFDW2M2NyQo6Alg/2W1dmIyPYzZ3IRx4/rwwQfTCxQTp169ehw9\nuo9duzYyffrUIrM/v1wIZY3Vq1fz44/bEfkKCCzgWRrwDlCd48dj86xpNpupX78+VqvVR0sVJQU1\nHFQMnDp1ioULF7Fr1wESE89ht1uJiKjO4MH/KTFZu/Lj0KFDzJjxAR9+OB+XKwijMRiX6zxBQcLo\n0Q8xevRwata8PIidorjp0qUv0dG3A8O8OHsNERHjOHhwe4kNbnfw4EE2b96MpmlERkZSp04df5tU\nIvBlOEg5gSJkw4YNTJv2PqtWrUDT+uFwXIdndUYaAQEHCQxcRLNmTZgwYTT9+vUjIKC4grp6T0ZG\nBidPniQ5OZnQ0FDCw8NLhd3lgcOHD9OkSRvS04/iCdFVWASbrTGrV8/LMaqsP4mJiWHo0LFs2bKF\nwMAbASEzM5oOHTqxYMF75d4ZqDmBEobL5ZIxY54Qq7WOaNqbknvQK6fAZ2K3R0q7dl1UYDGFT0yf\nPl3M5ge93ODnKZr2oowd+4S/m3IJMTExUqFCdTEY3hRIu8jeFDEaX5KwsNpy7Ngxf5vpV1BzAiUH\nEWHQoGHMn7+JtLRtiDzOpcHdLiYIGEhKyjr+97/mtGlzI2fPni1GaxVliVOnTpOentdKoPwRqUlc\nXE55f4sfyR4RGDHiCc6fH4fb/TiXrlKz4XI9S1LSEB59tGiWGZcHlBPQmWefncKKFXtJS1tN7jf/\nyzGSkfEOx4/fSI8ed+S5+7K4OHz4CHFxcf42Q1EIPInrfR3L13C73XqY4zMHDx5i8+bNrF//G273\n6FzruVyPsWLFck6fLhnOq7ShnICOnD59mrffnk5q6jIKPyar4XS+za5d51i9enVRmFcowsIqExYW\n5m8zFIUgLKwSJlO8j1ISqFatoA8vvvPrr7+yYsWKHI/VqVObkydPYjK1J++Q5pUxm5uze3e5i06v\nC8oJ6MiHH85H0/oB4V5KMJKSMpapU//NhZqWlsaSJUtYsWLFP93j4sButxMUFJR/RUWJoUePHhgM\nS/HsCvYGwW7/jNtuy3u3t55MnPgq48c/n+OxwMDA7HAUmQWQlFnulgPrhVodpBMul4saNRqSkPA5\n4EsANwdmcx127dpInTp1uO66zhw8aEMknnvvvZlZs97Wy2RFGaRNmy5s3ToKGODF2RupVu1u4uL2\nF9sNNSkpiczMTKpWrZrj8dOnT1OrVgOczgNA5VykHMdiaUF8/JEylUe4MPiyOki5Tp3YsmULDocV\n3xwAgAWXayBfffUVMTExHDgQR0rKBFJTR7Nw4UI9TFWUYSZMGI3N9hZQ2KxhgsXyBo8/PqpYn6gr\nVqyYqwMACAsL49Zb+xEY+HIuNQSTaQqDBw8utw7AV5QT0ImEhAQMhghdZGVm1iU2NoHq1aujaanA\nbgyGbTRsWDo2lin8Q0ZGBnXr1qV+fQgKGsO/IaPzJyBgKjVq7GPUqBFFZ6CXzJz5BtWrryIoaDRw\n7KIjhzCZhlG37lbeeOMlf5lX6lFOQCccDgdut1knaRaSk9MIDQ3lp5+Wc9NNv9Cvn4MVKz7XSb6i\nLHHu3DmeeupZqlSpQ9euD3DkiIvMzCVo2n/wRAzNiwwCAydQrdp8oqNXlMin6bCwMP78cx1Dhhix\nWFoSEnItISEtsdna8tBDldi8OZrQ0FB/m1lqUVs9dSI0NBSD4bxO0s5RpYonGXlkZCRr1izTSa6i\nrHHq1Cnat7+JuLjWOJ3RQOPsI0lAP6AaRuNQXK4xeHIIXOAoAQFzCAycS5s2rVm69PcSvRqscuXK\nzJnzHm+//Rq7du0iICCAJk2aYLEUJLqtIi9UT0AnGjZsSEbGdsDpsyy7fSNNmlzts5zExMQSs+Zb\nUTT0738fx4/3xun8iH8dAEBFYC2wGk1bjNXaEbO5Cnb7VVgs1bBYWjJs2Hm2bPmFX39dWaIdAEBs\nbCxjxz5BeHgE7dtHEhXVg6effo4TJ07427TSj7dbjYuqUIrDRrRv31VgsU/b9uGwWK2VJCUlxSdb\nRo4cJ0ajSVq27CAZGRk6tVBRkti1a5dYLNXzDRmtae9Jz553Snx8vOzbt0/i4uLE6XT62/wCs3fv\nXqlYsYYEBo4TOJAd+nqfBAY+IpUr15aYmBh/m+h3UInmSwZLly6V4OAOPjmBgID/k5EjH/XZluDg\nqgKbxWSqLPv379ehdYqSxvjxz0hAwNMF+F6dlaAguyQnJ/vb5ELjdrulSZO2ommzcmybwTBdrr22\nk7/N9Du+OAFdhoM0TeuhadpeTdP2aZo2IY96bTVNy9Q0rb8eeksaffv2xWQ6BqzyUsIxAgM/5NFH\n887KVRDGjx+H0diRqKgbqV+/vs/yFCWPw4fjyMpqWICaoQQGVuTMmTNFbpPebNmyhaNHTyMyPMfj\nbvdo9u07zPbt24vZsrKDz05A0zQDMAPoDjQDBmma1jiXeq8BP/iqs6QSEBDAN998itU6BNhayLPP\nYLX2ZPLkp2nc+IrLV2iee+5psrKcrF79tdpJWUapUMEOJBagpovMzHPYbHmFXiiZbNy4EZerB1fe\nqgR4HfgWuIVNmzYVu21lBT3uDu2A/SJyREQygc+A23KoNxb4CkjQQWeJpVOnTnzyyYdYLD2A7yjY\nWu2/sVo7MHLkrTz55LgitlBRVrjjjj7YbJ+Q/3dsBQ0bNs1z8jctLY1bbx3EE088q6uNvhIQEIDB\nkNNiizPABGAimuZUOS18wdtxpAsFuAOYc9Hre4B3L6tTA/hv9v8LgP55yCuKIbNiZ926dRIeXl/s\n9lYCcwVSLxvPdAmsFJutj1itlWTGjFn+NllRykhISBCDIURgWR7zAelitbaThQsX5ilrw4YNYjCY\nRdMMkpmZWUwtyJ/9+/eL2VxFwJFD21YJ/C5mcyU5cuTIFefGx8fL3LlzZerUqTJz5kw5cOCAH1pQ\nPODDnEBxuc938LjtC+QZ42Ly5Mn//B8VFUVUVFSRGFWUdOzYkdjY/fz444+8/vpMNmx4CpOpIRAK\npJKZeZiaNavx9NMP85//fK5ytioKzXvvzcJo7ITb/SDgwBMv6OLO/QngHsLDHQwePDhPWe3ateOd\nd6ZRp07tEvVU3aBBAzp2vJ7ffnuGjIy3uPTW0R2T6WFuvrnrJZnFYmNjGTPmKVavXonR2BOnswaB\ngXt5/PFJtG3bnpkzp3LNNdcUe1v0JDo6mujoaF1k+RxATtO0SGCyiPTIfv00Hq809aI6By/8C4Th\n2cY4XES+y0Ge+GpTSeTEiRMcPnyYc+fOYbVaCQ8Pp2HDhiU2l6uiZON2u6lSpS6Jid/j2ZsyEjiH\np2NuA3YCPwP9CQlZwZkzx0vUzb0wJCYm0qlTd44dCyEl5WHgKmAfdvsM6tXL4LffVv+zY/jw4cO0\nbXsjSUn34nI9gWe/xAUcwHzs9in8/PNy2rdvX/yNKSL8mmNY0zQj8DdwM55Hj03AIBHZk0v9BcBy\nEVmay/Ey6QQUCj1JSkoiPLweGRkXMtEJsBFYg8cp1AHuAkIxm6ty6NAOwsO9DXFeMBITE5k+/X02\nbvyLzp2vY8yYUYSEhOgi2+l08uWXX/Leex9z8uRJqlevziOP3M+dd975T8hzEaFx4+uIibkPt/ux\nPKStIDT0QY4f34/dbtfFPn/j90Tzmqb1AKbj6YvOE5HXNE0bgadHMOeyuvOB75UTUCi859y5c1Sp\nUpPMzGTyHl0VTKbKHDv2N1WqVPFZ7/bt25kxYy779h3hmmsaMHbscBo3bkxaWhpNm7bh5Ml2OJ3d\nMZuXERFxgB07NhAYGFhg+enp6ezcuZPExEQMBgN16tShQYMGBVrhFh0dTd++D5OSspP8MqzZbP14\n881ejBiR89LT0obfnYCeKCegUOSPiFCvXnOOHHkXuCmPmuuoUWMYx4//XaChx7S0NFauXMmGDZvZ\nuHEnyckpmExBXHNNQ9LSzvLttz+TmTkWl6sFAQFbCAz8gFmz3kTExZgxX5KaeiFLmGC338CiRePp\n169fnjpTU1P55JNPeeedeezfvwOrtQGaVg1wkZV1CJcrkRtuuJknnxzFzTffnKtD6N//XpYta4fI\n2HzbCT/SqNFE9u4tG0tLfXECRbLr15dCGVkdpFAUNTNmvC9W6y3ZK81yWhnkEoult7zxxlv5yjp1\n6pSMGvWY2GyVJTi4mxgMLwh8K/BfgdUCbwn0FQgVuEvgr2wde8Rsrijjx48Xg+GpS/SbTCNk+vTp\neer94osvJDQ0XOz2WwVWCqTl0I5TAh+I3d5CmjVrJ7t27cpRVtOm1wusK+Du/ASxWit5dd1LIqiw\nEQpF+SM9PV3atLlRzOb7BM5edpM7JybTg9KyZQdJS0vLU84333wjoaHVJShojMChfENQeBxCmMCL\nAlliMg2XkSNHidVaRyA+u94xsViq5XrDzsjIkIED7xertZHA7wW8cbtF02aJxVJZ5s//6AqZ11zT\nSSC6gLJOSHBwVV0+h5KAL05AbSVVKEopJpOJ6OgV3HqrAZMpArP5fuB5zOZhmM0R9OqVzm+/rc4z\n3PK0aW8zePCjnDv3BRkZ7wER+WgNBcbh2RH/EzAIp/Nq3O5AHn10KCZTI0JDozCbm/Pcc0/StGnT\nKyS4XC7697+H5cvjSUv7E7i+gC3WEBmJw7GOhx+exLx5Cy45Ghl5LUbjLwWUtYZmzVoWsG4Zx1vv\nUVQF1RNQKApNXFycvPfee/L888/Lu+++K8ePH8/3nI8+WihWa4TA0QI+PV9eHAI9xWhsJDNmvC8i\nIrGxsfLzzz9LfHx8rnpffXWaWK0dc9kAVtCyVyyWMNm+ffs/cv/666/sqKrOfHsUdvv1snTpUt8v\nfAkBH3oCamJYoSghJCQkEBQURIUKFYpc19GjR2na9DpSU38BmvsgKRVoyKefvsmgQYPyrb1v3z6u\nvbYDDscmwLfAhpo2n4YNZ7Br16Z/9kB063Y7v/5aCafzQ3KLimM0vkZExBL27t1aavdOXI5KNK9Q\nlGJEhFGjxlG79tWEh9dh7twF+Z/kI8OHj8PpfAzfHAB4NqZ9xpgxT+J05p9Q6YUXppGR8Si+OgAA\nkaHExQWyYsWKf977+uuFNGu2H4ulD/A7l8ZV2oXJNJTq1RcQHb2izDgAX1E9AUWJJC0tjSVLlrBq\n1a+cPn2WgAAj1auHMWhQP7p3747RaPS3ibrheTq+EYfjb+AEJlMbHI7zRbab/MiRIzRu3Jr09GOA\nPuFKgoNvYfbsodx999251jl79izVq9cjPX0vUE0XvbCI669fzO+//xucOD09nRkzZvLWW7NJTtYw\nGmsgkoimnWL06IcYP/5RKlWqpJP+koHaJ6AoMxw+fJjXX5/OwoWL0LQOpKTcBlQGXEAsdvtCrNZE\nxo0byejRI3XbkaoHR48eZcGChcTEHCM8vDL33TeI5s3zf9KOiYmhRYtOOBy7gVjM5k6kpZ0tMifw\n/PMv8NprZ8jImK6j1K9p02YmmzevybXG8uXLueee9zh//kcd9aYRGBhGcnISJpPpkiNut5sdO3aQ\nmJiI3W6nVatWhdq4VppQ+wQUZYK1a9dKcHBVCQyckM9SxU1iNg+QevWaydGjR/1ttrhcLhk1apyY\nzZWyl1nOFKPxGbFYakj37v0LlCp0/PhnJTDQKiaTXRYv/rRI7Y2M7C6ePQDeTsrmVBLFZLJLVlZW\nrnonTnxejMZndNYrEhLSXDZv3lyk16ykg9onoCjtrFu3TqzWMIGfC/jjd4vR+KZUrRohJ06c8Kvt\njz/+TPZql6TLbHSK2TxYuna9tUByzp07Jw6Ho4itvZB69JjuN2O7vb7s2bMnV739+98nML8InEB/\n+eKLL4r8upVkfHECamJY4XcSEhLo1esO0tIW44lDWBA0XK7HSUoaSvfu/S88QBQ7Z86cYebMWaSl\nLQUuX9UTRHr6An7/fTtbtmzJV1ZISAhms7lI7LyY1NREoKruco3GqiQm5p7pLCvLBUUQvV4kAJfL\npbvc8oJyAgq/M2fOPDIyeuPJUFo4MjMncfBgEuvWrdPfsAKwdOlSDIbu5H5TDSQ9/QHmzVtcnGbl\niSfTq7sIJLvyDPRWrVpF4LTuWg2G01SsWDH/ioocUU6gnOB0Ogu0hK+4cblcTJ8+m/T0h72UoJGa\nOorXX39fV7sKSkJCAunp9fKs43ZHEBt7qpgsyp+wsNrAwXzrFQ7B6Tx4SXKXy2nf/lpstj9115ue\nvo1rr71WZ7nlB+UEygmZmZlkZWX5RXdWVhanT58mNjaWtLS0S46tXLkSp7M60Npr+SL38dNPPxAf\nH++jpYWnRo0aWCz78qxjNO4jIqJ6MVmUP61bX4cn7IOeHMVkCqRGjRq51oiMjERkLZ6VXnqxnZCQ\nUKpV02vJaflDOYFygt1ux2azFavOrVu3cvfdD2CzVaBWrUY0bNiGkJBKNG7clgULFuBwOPjzz22k\npHT1UVMFzOZr2blzpy52F4b+/fvjcv0CHMulRjpBQfN56KEhxWlWntx2283YbN/oKlPTvqFLl7xC\nWkOzZs2oW7c6sEo3vWbzLEaNGqabvHKJtzPKRVVQq4NKPUeOHJEWLTqI1VpXDIbXBBIuWs2RJbBC\n7PbeYrNVlqioWwTe0GGFyO3y1Vdf+aW9kye/IlbrtQKxl9mVLBZLX7n99sG66UpPT5eEhIR8I4Pm\nRXJyslgsFQWO6LRCxyU229Xy22+/5at78eLFYrO1FcjUQW+MWCyVJC4uzutrUVZALRFVlBT27Nkj\nlSrVFKPxjewbfl4/4l0SEFBHoJvPN4TQ0J7y/fff+6XNbrdbJk16QczmULFY7hZ4SYKCRorZXEnu\nvvsBSU9P90m+y+WS77//Xjp37iVGo0lMpkpiNAZJy5adZMmSJeJ0Ogstc/z4/xOrtb+A2+drbzBM\nl2uv7SRut7tAbWnf/iYxGl/1UW+W2Gyd5fXX3/TmkpY5lBNQlAgSEhKkWrV6omnzCvFjPilQW3xb\nP+4Wu72R3zcMnT59WmbMmCFPPfWMTJs2TY4cOeKzzNTUVLn55r5it7fMvkYXkq5kCHwldntnadas\nnbpBV94AABqySURBVCQkJBRKrsPhkDp1mggs9PFmvFsslsry999/F1j3oUOHJDQ0XOArL3W6xGQa\nLu3b35Tn5rTyhHICihLBU089K0FBD3nxo94hUFUg3cubwnqpXr2huFwuf18CXXG5XHLzzX3FbB6U\nfdPP2QEGBj4pTZq0kdTU1ELJ3759u9jtVQS+8/K6/y0WS21ZsODjQrdt69atEhJSTQyGNyX/HuPF\n5YyYzXfJtdd2lHPnzhVab1lFOQGF33E6ndlPd7u9vKFECXzi1blW6+ACpVAsbaxcuVLs9hZ5OIB/\nHYHV2kvef39moXVs2rRJQkPDJTDw2UI4YbfAJ2KxVJU5c+Z63b6YmBhp3foGsdk6CqyRvIemUgXm\nisVSQ0aMeKTQDq+so5yAwu989tlnYrd38dIBiMA3ApFePY2azRUkMTHR35dAd6Ki+ggUdGhtjURE\nXFOgcfnLOXHihNxyy21iszUSmCVwPhcdWQLfis12s0RENNNl+M3lcsmcOR9K3brNxG6/WkymUQJz\nBZYLLBN4S2y2u8VsrixRUX0KNPlcHvHFCagoogpdeOihscydexXwmJcSsgATkALkng7xUk5itXbk\n7befYfjwB73UWzLJzMzEYrHjciVRsHDPgtVamx071nLVVVcVWp+I8MsvvzB16vtER/+IxdKMzMyW\nZGaGYjSmYzLtxun8k/r1r+bppx9m4MCBV0Tt9AURYdOmTWzYsIHffvuT+PgzGAwGGjasQ6dObejS\npQsRERG66Str+BJFVGVVUOhCQkISUNgY7el48tTGA2bAhMXSHYfja6BKPufuwGq9jaeeGl7mHABA\ncnIyxv9v796jo6ruBY5/d57zyItHACWgQEAUoQgWqYAGQQGlFrxoUS+KVgUVxFqRtFUeIihKrTwu\nWq3cFh/gpayKWuCiSMgVAQMiIE8jxQDyMJBAyIOQ5Hf/mEEjJjOTmcmcCfP7rDVrzWT2nPPbJ3Pm\nd84+e+8Tbaey0tf5/g0xMc0oLCz0a33GGPr160e/fv0oKiriiy++YNu2bZw6dYq4uDguueRGunXr\nVm+DsowxXHXVVVx11VU86u9xhPJLUJKAMWYg8BKuwWevi8iMc96/A5jgflkEPCgi24KxbhUeHA4b\n4Ou0FEXANGA+cDnQBigBoklOPkJlZVuio2+htPQhoAdw9gCnAviAhIR5GLOF2bNfYOTIu4JbkTDh\ndDqpqCgByoE4Hz4hVFYWkJiYGPC6ExMT6dOnD3369Al4WSr8BZwEjGs2qrm4pn/8FsgxxiwVkV3V\niu0FrhGRE+6E8RrQM9B1q/CRnp5GbOwuzpzxVvIYrq9KF1y3/0uv9l4phw+/g90+gSFDqvj44zs4\nebKE2NgmiFRQXn6EDh0uY8KEhxg2bFhQmyPCTXx8PN269WbjxneB23z4RA4JCVGkp6d7L6pUNQFf\nEzDG9AQmicgg9+tMXBcpZtRSPgXYJiKtanlfrwk0QLm5uXTufDVlZXm4mnZq0x+4AnieH47wz7UN\nu70f2dnLaNGiBQUFBcTExNCkSROaNQv+FMjhavHixdx77yxOncrG2wwvdvudTJrUlQkTxocmOBVW\nrL7RfEt+PHHKAfffanMfwZw8RIWF9PR0unXrBiz2UCoH10nhc9SeAAA6U1aWyfTpL5GWlkbnzp25\n9NJLIyoBAAwZMoR27YTY2PFA7QdGUVGzadw4h1Gj7q+XOPLz85k+fQa9e9/EgAHDWLhwIeXl5fWy\nLhV6Ib0wbIzpC9wD9PZUbvLkyd8/z8jIICMjo17jUsHx5JPjGDZsDCUlA6n5wu7LwGjA+03iRUay\nfPlUvvvuO1JTvV0kts7x48cpLi6mVasaT2wDEhsby6pV75GRcRN79w6ipOR3uJrSonAlhc+w22fR\nuPFGsrNXkJJy7k1tArdt2zauuWYAp08PoLT0AeAka9fOY+bMl8nOXh7ySQmVS1ZWFllZWcFZmL99\nS88+cLXtr6j2OhOYUEO5LsBXQDsvywtCr1llFdecNN3lx5PGnX10Fdjo8xiA5ORekp2dbXWVPNq0\naZN89FH9xlhSUiKvvPIXadu2i9jtLSQpqYs4na2lRYt28vzzM6WgoKBe1ltVVSVt23YW+Ps5/5tK\niY8fLo8++kS9rFfVHVaOEzDGRAO7cR2iHAI+A24XkZ3VyrQGVgEjRGS9l+VJoDEp64gImZkTmTv3\nLUpK/gjczg/93C8H3sZ1POBdcnJflix5kn79fL3l5PlNRNi3bx+FhYUkJCTQrl07j3fyCtT69eu5\n/vqRnDq1k5823+WSkPALTpw4Uq8xKN9YOk5ARCqNMWOAlfzQRXSnMWaU6215FXgKVyfyecYYA5wR\nkR6BrluFH2MMM2ZMpX//a3j22TmsWzeBqqrbKS9vj6ur4w58SwIVnDmzp16aWRoqYwxt2ni+i1kw\n5eXlYczl1Hz9Jp2ysmJKSkpISEgIWUwq+HTEsEUqKiooLCzk9OnTpKSk4HA4cOXH88u+fft4++2F\n/Pvf37Jr1w42bCjlzJlPffjku3Tu/AJbt66t9xhVzTZu3EhGxq8pLv6Kn/Yh2UVSUgYFBd/qmUAY\nsLp3kPKRiLBmzRoGD/41dnsCaWkdaN/+SlJSmtKy5SXMnPkix48ftzrMoLr44ov5wx9+z2uvzWHV\nquUkJuYBK7x8qhincwqZmf7ed1gFQ/fu3UlLa4QxfznnnQrs9t/z0EMPaAI4D+iZQIisWrWK3/xm\nHMeOVVJc/BAidwHJ7ncFWIfDMY+qqg+4/fY7mTfvT9hsnvrbN0xr167lhhuGUFLyKjCEnzY1HMHh\n+DW//GUbFi6cX+PZkYicl2dN4WjPnj306nU9paU/p7h4CHCShIS/csUVzfjww6Xn9YC9hiSQMwFN\nAiGwYMGbjB79O0pLXwduwnMf+aPY7WPo2PEQq1d/QHJysoeyDdP69esZNuxuTpyI59Sp+3BNG1GK\nw/EeVVX/4sEHRzNz5jSPR5maCEKnqKiIBQveYNmybJxOG3fffSsDBw4kOtp7V99wcvLkSa699iZy\nc3eyYMFfGTp0iNUhBY0mgTCxefNmXn/9Ddas+Yyvv/6S8vISoqLiqaiIR2QwMBbo7sOSqoiLe5hu\n3b5izZplxMX5MndMwyLuWStfe+0tDhw4gt1uY8CAXtx770gaN67rRHTKV19//TXLli3D6XQydOhQ\nGjVqZHVIIbNkyRLuvvsliosfpEuXV9iyJdvqkIImkCQQ8DiBYD9ogOMEtm7dKl279haHo5VER092\n3yDjO/dNOvIFVgs8LXCRwC8ENvvQT75C7PZBMn36DKurp84TEyc+IzZbU7HZ7henc5g4nU1k5cqV\nVocVMvv375eUlBYSH99Ipk17wepwggq9n4B1Xnjhz0yaNJ2ysumI3IPnXreVwAJcE6o+DozHc9PQ\nRlJTb+XQodwGd+rtyZEjRzh48CBXXHGFNumESE5ODhkZt1BSshE4Ox10NklJt3LkyDfn5fWnmhQV\nFVFQUEDr1q2tDiWotHeQRZ566mkmT/4rpaWbELkf78MuonHNmvE58Bau4ROeXElZWSrLl58/Uy19\n9913dOjQhd69b2bGjBetDidivPPOEsrK7gXygbPjNa8BOrBmzRrrAguxxMTE8y4BBEpvKuOnpUuX\n8uKLf6OkZB0/HFn5Kg3XAOqrgZ8Bt9ZasqjoQWbNep3Bgwf7HWt9KSwsZNeuXZw6dYqkpCQ6derk\ndS6Zo0ePcuaM4fTp69iyZQclJSUsW7aMgwcPUl5eTqNGjejbt69fd8dSnonkA31wzfL6KhCc71R+\nfj7vv/8+x48fp3nz5tx8880kJSV9/35ZWRmlpaURdf2hQfG3Ham+HjSAawLHjx+XlJQLBLIDuKeu\nCKwTaO6+flBbmU3Spk1Xq6v8Izk5OTJ8+D1is6VIcvLPJTm5ryQldROHo7E88MBY2bFjh8fPz5kz\nT4YMGS4jR44Sp7OJJCYOkPj4sRIT85g4HHeLzZYqvXoNlKVLl0plZWWIamWdioqKeq9nTk6O2GzN\nBJoKtBdYKLBGkpKaSVlZmV/LLC4ulhEjHpD4+GRxOm+VuLhHJSHhV2K3p8iYMY9LeXm5bN++XZKS\nmklsrFNefHF2kGulzkJvNB9a06Y9JzbbXQEmgLOP+9wXjWt7f480a9bW6iqLiOvHatSoR8ThaCVR\nUc/VMElcnsTEPCl2ezN5+unptd70/K233haHo6nExmYK7K2hzqUCCyQhoasMGDBUiouLQ1zT0ApF\nEhARmTTpGYmNTZLY2H7icNwiDkdj+fDDD/1aVllZmfTo0VdstjvdnR+q//8OisNxowwa9B/y1FMT\nxZhxAmslLe3SINdInaVJIIQqKyslNfVigZwgJYEvBFoKVIT1mUBVVZWMGHG/OBzXChR4qdMBcTi6\nyJNPTvnJct544y1xONIEtvqwbcrEZrtDrr66v5SXl1tQ6/NPbm6uzJkzR+bPnx/Q7KOzZ88Rh+MG\ngcpa/3dOZ3eZMmWK2O1NxOlsJw899FgQa6Kq0yQQQnv27BGHo1WQEsDZRzuB7bW89ze57rpfWV1t\nefPNN8Xp/JnASR/rdEgcjtby8ccff7+M7du3i8ORKrCtDtvmjDgcg+WRR8ZbWHtVXVVVlbRqdalA\nlpf/3SLp3j1DcnNz5dNPP631zFAFTpNACC1cuFASE4cGOQncJrCgxvcSE3vK0qVLra62dOz4c4EP\n6livl+X664d+v4yRI0dLdPQUP7bPfrHbG0lRUZGFW0CdlZ+fL3FxyQJVXv5vpRIVFaM//iEQSBLQ\nLqJ1dOjQIU6fDnYXs4uAb2v4++fEx3/LTTfdFOT11U1OTg77938HDKzjJ+8kOzuLAwcOcPLkSRYt\nWkRl5X1+RJBGVFQGb775lh+fVcFWWVlJVFQsnse4AMRQVVVFZuYkKisrQxGa8oMmgTpyDW6SIC9V\n+OkOVYndPolx40bX20CxtWvX8thjTzB16jT2799fa7nly1dQWnobvtwW8scSiYkZxMqVK1myZAnR\n0X2BC/2Ktbh4FHPm/M2vz6rgatKkCfHxsbjuDeHJ/wEdmDv3/xg7dnwIIlP+0CRQRxdeeCE22zdB\nXuo3QMtqr4W4uN/SqVMR48c/FuR1uUyf/gI33HAHL72UwDPPHOayy7qzcePGGssePVpAVZV/N3k/\nc6YZBQUF5OXtp6SkUwARX8ahQ7UnKhU60dHRjB79G+LjX/JQSoA/A2MoKVnM/Pnzyc/PD1GEqi40\nCdRR9+7dqajYSHDPBjbxw8Ryx7DZ/pNLLslh5cp/1stUvQUFBUydOp2SkrWITKS8fA6nTj3LI4/8\nscbyDkc8UObXuqKjy7DZbJSUlCESyNQENsrL/YtBBd/vfvcIKSkfERX1Ej/dF6qAPwJ5wEigKTbb\nlWzatCnEUSpfaBKoo7Zt25KUZMN1K+Vg2ARUACew2+/BZktn2DAnGzZ8XG8jLHfv3k1cXDqukctn\nDWL79i01lu/YsT1OZ81nCd7ExGykffv2NGmSQkzMMb+W4XIcpzMlgM9HhrKyMlasWEFVVVW9ric1\nNZUNG1aTnr6AhITLMWYmrvtHTwXaA5/iuuOsExAqKw+dl9Oinxf8vaJcXw/CvHeQiMjzz88Uu/2O\nIPUMGi5RUXZJTb1Ynn12hhw9erTe4z927JjYbCkCB6vFMV969ry+xvInT54Uu72RwP461u0zSU29\nWCoqKmTt2rXidKZL7f3KPT+iombIbbfdXe/bpqF79913pVGjFvLll1+GZH1VVVWyevVqueeeB+Xa\nawdLdHSywPvn9BxaKhdckB4Ro7+tgnYRDa3CwkJp3DhNXFNGB5IAsiUpqYXs3bs35N3opkx5VhyO\ni8WYZyQubpw4nU1lw4YNtZa///4xEhMzoU71s9nukGnTnhMR149F27Y/E/hfP7ZThTidbTzGp1wq\nKipk8+bNlnXLnD79BXE4WkpU1AyBf0pc3COSkJAqn3zyiSXxRApNAhZYtmyZOBytBQ74mQAOicPR\nRt59913L6rBmzRp5+OHfysSJU2Tfvn0ey+bl5UmjRhcKLPbxyH2WpKV1+NGo1Fde+Yt7lKm3/uXn\nPhZLhw7dtb95A7FhwwYZMeIBueaaX8qECU9KXl6e1SGd9zQJWGTq1OfE4Wgv8FUdf9T2isPRUSZO\nnGp1Ferk888/l+TkC9xHeUW11O2YxMY+IS1atJW9e/f+6POlpaXSuXNP95xBviaCzWK3p0p2drZF\ntVYq/GkSsNDcuS+L3d5EoqJmCZz28oN2Woz5L7Hbm3qdUbGqqkpmzPiTpKVdJq1adZIXX5wVFkfC\nubm50r//ELHZGktc3FiBpeJqFlsidrtrZtFbbvlPOXz4cI2fP3r0qLRr10Xi40cLnPCwraoE3hO7\nPVUWL/5HiGupVMNieRLANZR0F7AHmFBLmdnAV8AXQFcPy6qnzVR/du/eLVdffYPY7c0lJuYJcV0Y\nyxPXRGv7Bf4lMTGZYre3kB49rvM61bKIyKxZc8Xh6CzwmcAGcTovk3nz/hKC2vgmLy9PMjOfkj59\nBkvXrhly7bU3yzPPPOvThe0TJ07I0KF3is3WSOLjHxT4XOCUQLnAt2LMHElIuFRat75MsrKyQlAb\npRo2S5MArm6mubjmPoh1/8h3PKfMIOBf7udXAes9LK/eNlR927FjhzzxxB+kR4/rJSmphdhsSZKU\n1EKuvLKfPP54Zp16bFx+eS+Bj6odGS+Xbt361mP0oXfw4EF56qkp0rx5O4mNtUtUVLQ4nU3kxhtv\nlaysrLA481Ghs2vXLvntb8f7fX+DSBZIEgj4HsPGmJ7AJBEZ5H6d6Q5oRrUyrwCrReQd9+udQIaI\nHKlheRJoTOeDK6/sx6ZNY4Ch7r+8Q8+e/826dSusDKteiYjecziCLVq0iLFjx7NlywYuvNC/6UUi\nldX3GG4JVB/Pf4Afz4FQU5mDNZRR1UycOA67/WFgPvBX7PZxTJw4zuqw6pUmgMg2fPhwDh/epwkg\nxMLyHsOTJ0/+/nlGRgYZGRmWxWKVm2++mX/+M57Zs/8bYwyPPvom/fv3tzospepVfU2WeL7Jysoi\nKysrKMsKVnPQZBEZ6H7tS3PQLuBabQ5SSqnAWd0clAOkG2MuMsbEAcOB984p8x5wF3yfNAprSgBK\nKaVCK+DmIBGpNMaMwTVbVBTwuojsNMaMcr0tr4rIMmPMjcaYXKAYuCfQ9SqllApcwM1BwabNQUop\nVTdWNwcppZRqoDQJKKVUBNMkoJRSEUyTgFJKRTBNAkopFcE0CSilVATTJKCUUhFMk4BSSkUwTQJK\nKRXBNAkopVQE0ySglFIRTJOAUkpFME0CSikVwTQJKKVUBNMkoJRSEUyTgFJKRTBNAkopFcE0CSil\nVATTJKCUUhFMk4BSSkUwTQJKKRXBNAkopVQECygJGGMaGWNWGmN2G2P+1xiTXEOZNGPMx8aY7caY\nbcaYRwJZp1JKqeAJ9EwgE/hIRC4BPgZ+X0OZCuAxEekE/AJ42BjTMcD1hqWsrCyrQwiIxm8tjd9a\nDT1+fwWaBH4F/N39/O/AkHMLiMhhEfnC/fwUsBNoGeB6w1JD/xJp/NbS+K3V0OP3V6BJoJmIHAHX\njz3QzFNhY8zFQFdgQ4DrVUopFQQx3goYYz4Emlf/EyDAkzUUFw/LSQD+AYxznxEopZSymBGp9Xfb\n+4eN2QlkiMgRY0wLYLWIXFpDuRjgA2C5iMzyskz/A1JKqQglIsafz3k9E/DiPWAkMAO4G1haS7n5\nwA5vCQD8r4hSSqm6C/RMoDHwP0Ar4BvgNhEpNMZcALwmIoONMb2AbGAbruYiAf4gIisCjl4ppVRA\nAkoCSimlGjZLRww31MFmxpiBxphdxpg9xpgJtZSZbYz5yhjzhTGma6hj9MRb/MaYO4wxW9yPT4wx\nna2Isza+bH93uZ8bY84YY24JZXze+Pj9yTDGbDbGfGmMWR3qGGvjw3eniTFmuft7v80YM9KCMGtl\njHndGHPEGLPVQ5lw3nc9xu/Xvisilj1wXUt4wv18AvBcDWVaAF3dzxOA3UBHC2OOAnKBi4BY4Itz\n4wEGAf9yP78KWG/ldvYj/p5Asvv5wIYWf7Vyq3B1SLjF6rjruP2Tge1AS/frplbHXYfYJwHPno0b\nOAbEWB17tfh64+qmvrWW98N23/Ux/jrvu1bPHdQQB5v1AL4SkW9E5AywCFc9qvsVsABARDYAycaY\n5oQHr/GLyHoROeF+uZ7wGtzny/YHGIurS/LRUAbnA1/ivwNYIiIHAUQkP8Qx1saX2A8Die7nicAx\nEakIYYweicgnQIGHIuG873qN35991+ok0BAHm7UE9ld7fYCfbuhzyxysoYxVfIm/uvuA5fUaUd14\njd8YcyEwRERexjWuJZz4sv07AI2NMauNMTnGmBEhi84zX2J/DehkjPkW2AKMC1FswRLO+25d+bTv\nBtpF1CsdbNZwGWP6AvfgOgVtSF7C1bx4VrglAm9igG7AdYATWGeMWSciudaG5ZPfA1tEpK8xph3w\noTGmi+6zoVWXfbfek4CIXF/be+4LHM3lh8FmNZ66uweb/QN4Q0RqG4sQKgeB1tVep7n/dm6ZVl7K\nWMWX+DHGdAFeBQaKiKfT51DzJf4rgUXGGIOrXXqQMeaMiLwXohg98SX+A0C+iJQBZcaYbOBnuNrj\nreRL7L2AaQAi8rUx5t9AR2BjSCIMXDjvuz6p675rdXPQ2cFmEKTBZiGQA6QbYy4yxsQBw3HVo7r3\ngLsAjDE9gcKzzV5hwGv8xpjWwBJghIh8bUGMnniNX0Tauh9tcB08PBQmCQB8+/4sBXobY6KNMQ5c\nFyh3hjjOmvgS+06gP4C7Lb0DsDekUXpnqP3sMJz33bNqjd+vfdfiK92NgY9w9fhZCaS4/34B8IH7\neS+gEldPhM3A57gynJVxD3TH/BWQ6f7bKOCBamXm4jpy2wJ0szLeusaPq133mHtbbwY+szrmum7/\namXnE0a9g+rw/XkcVw+hrcBYq2Ouw3enKfC++3u/Fbjd6pjPif9t4FvgNJCHq8mkIe27HuP3Z9/V\nwWJKKRXBrG4OUkopZSFNAkopFcE0CSilVATTJKCUUhFMk4BSSkUwTQJKKRXBNAkopVQE0ySglFIR\n7P8Br1c6FhRfUgsAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110e852e8>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x, y, scale = rand(3, 100)\n",
|
||
"scale = 500 * scale ** 5\n",
|
||
"plt.scatter(x, y, s=scale)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"And as usual there are a number of other attributes you can set, such as the fill and edge colors and the alpha level."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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Hi+Aax2Dc/egaqE1x61aEE0fqOX/+7IbWdFOTiHvcG0zOZBTCYejqKCJJK19EVZXY/4UX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\niiNHivtOnU6EUWpqih8HwMPxMN66/dWztHrDDE/Eqa1dXXUvLYkGt7V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vfbnCFgsLMPR2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\npoz9D/i6U4+PkWyUAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11186fa58>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"for color in ['red', 'green', 'blue']:\n",
|
||
" n = 100\n",
|
||
" x, y = rand(2, n)\n",
|
||
" scale = 500.0 * rand(n) ** 5\n",
|
||
" plt.scatter(x, y, s=scale, c=color, alpha=0.3, edgecolors='blue')\n",
|
||
"\n",
|
||
"plt.grid(True)\n",
|
||
"\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Lines\n",
|
||
"You can draw lines simply using the `plot` function, as we have done so far. However, it is often convenient to create a utility function that plots a (seemingly) infinite line across the graph, given a slope and an intercept. You can also use the `hlines` and `vlines` functions that plot horizontal and vertical line segments.\n",
|
||
"For example:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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tqQsiCFXIsoCq5jI93UltrcbAwBQeT4yhoTtcu/YYm83J6dP5vPfemU0160hk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\n2YNI5S2RSCR7EKm8JRKJZA/y/wFa3KKHN//+lQAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x110e04358>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from numpy.random import randn\n",
|
||
"\n",
|
||
"def plot_line(axis, slope, intercept, **kargs):\n",
|
||
" xmin, xmax = axis.get_xlim()\n",
|
||
" plt.plot([xmin, xmax], [xmin*slope+intercept, xmax*slope+intercept], **kargs)\n",
|
||
"\n",
|
||
"x = randn(1000)\n",
|
||
"y = 0.5*x + 5 + randn(1000)*2\n",
|
||
"plt.axis([-2.5, 2.5, -5, 15])\n",
|
||
"plt.scatter(x, y, alpha=0.2)\n",
|
||
"plt.plot(1, 0, \"ro\")\n",
|
||
"plt.vlines(1, -5, 0, color=\"red\")\n",
|
||
"plt.hlines(0, -2.5, 1, color=\"red\")\n",
|
||
"plot_line(axis=plt.gca(), slope=0.5, intercept=5, color=\"magenta\")\n",
|
||
"plt.grid(True)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Histograms"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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DxwJbgKebu4tmo59ZfBzYOl1ySLK6qnY05yczSFoPt7WVJC2drp9BnAScMNc/4ZOsB94C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\nTjAo4A1y6gAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1111135f8>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"data = [1, 1.1, 1.8, 2, 2.1, 3.2, 3, 3, 3, 3]\n",
|
||
"plt.subplot(211)\n",
|
||
"plt.hist(data, bins = 10, rwidth=0.8)\n",
|
||
"\n",
|
||
"plt.subplot(212)\n",
|
||
"plt.hist(data, bins = [1, 1.5, 2, 2.5, 3], rwidth=0.95)\n",
|
||
"plt.xlabel(\"Value\")\n",
|
||
"plt.ylabel(\"Frequency\")\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 37,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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QWAJMARCRIcBoYDBwAYFut+51RTDGxJxNXxrZ008/zerVq9mzZw933XUXV1xx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\nQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11219bc18>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"data1 = np.random.randn(400)\n",
|
||
"data2 = np.random.randn(500) + 3\n",
|
||
"data3 = np.random.randn(450) + 6\n",
|
||
"data4a = np.random.randn(200) + 9\n",
|
||
"data4b = np.random.randn(100) + 10\n",
|
||
"\n",
|
||
"plt.hist(data1, bins=5, color='g', alpha=0.75, label='bar hist') # default histtype='bar'\n",
|
||
"plt.hist(data2, color='b', alpha=0.65, histtype='stepfilled', label='stepfilled hist')\n",
|
||
"plt.hist(data3, color='r', histtype='step', label='step hist')\n",
|
||
"plt.hist((data4a, data4b), color=('r','m'), alpha=0.55, histtype='barstacked', label=('barstacked a', 'barstacked b'))\n",
|
||
"\n",
|
||
"plt.xlabel(\"Value\")\n",
|
||
"plt.ylabel(\"Frequency\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid(True)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Images\n",
|
||
"Reading, generating and plotting images in matplotlib is quite straightforward.\n",
|
||
"\n",
|
||
"To read an image, just import the `matplotlib.image` module, and call its `imread` function, passing it the file name (or file object). This returns the image data, as a NumPy array. Let's try this with the `my_square_function.png` image we saved earlier."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 38,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"(288, 432, 4) float32\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.image as mpimg\n",
|
||
"\n",
|
||
"img = mpimg.imread('my_square_function.png')\n",
|
||
"print(img.shape, img.dtype)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"We have loaded a 288x432 image. Each pixel is represented by a 4-element array: red, green, blue, and alpha levels, stored as 32-bit floats between 0 and 1. Now all we need to do is to call `imshow`:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 39,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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SU3MZOVIKuhDnKy0t5fXXvVi2rG0n4bJW5x/s/jRZYHNaespFNbx+sga4s+H9HcCnjdpn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\nRiqHmQAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x111559550>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.imshow(img)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Tadaaa! You may want to hide the axes when you are displaying an image:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 40,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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q7+b4qWY21cwGm1nDGBmL5DnGzEZlMlcpcqyhmX2aeWyj3VO0uMfMzH6ayfio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\nP7kre5pDEhmNAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x1126f8748>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.imshow(img)\n",
|
||
"plt.axis('off')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"It's just as easy to generate your own image:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 41,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"[[ 0 1 2 ..., 97 98 99]\n",
|
||
" [ 100 101 102 ..., 197 198 199]\n",
|
||
" [ 200 201 202 ..., 297 298 299]\n",
|
||
" ..., \n",
|
||
" [9700 9701 9702 ..., 9797 9798 9799]\n",
|
||
" [9800 9801 9802 ..., 9897 9898 9899]\n",
|
||
" [9900 9901 9902 ..., 9997 9998 9999]]\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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XULr1luIWURf0t5Hyvo+huu5VD0xdjL8TuAh4t7vfbWYfZljSj6uYqkrlo5uGcyANLaWx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\nRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x112c0a5c0>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"img = np.arange(100*100).reshape(100, 100)\n",
|
||
"print(img)\n",
|
||
"plt.imshow(img)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"As we did not provide RGB levels, the `imshow` function automatically maps values to a color gradient. By default, the color gradient goes from blue (for low values) to red (for high values), but you can select another color map. For example:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 42,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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gGlX9qrpSUI1BrN6W1+OLJfAtFDWlohqDqq4UxOptWcYXStwRiBXqzKjGoKorBbEY6l/c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\nHEyyGAAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x112c16ac8>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.imshow(img, cmap=\"hot\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"You can also generate an RGB image directly:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 43,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAW0AAAD7CAYAAAChScXIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x11269c240>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"img = np.empty((20,30,3))\n",
|
||
"img[:, :10] = [0, 0, 0.6]\n",
|
||
"img[:, 10:20] = [1, 1, 1]\n",
|
||
"img[:, 20:] = [0.6, 0, 0]\n",
|
||
"plt.imshow(img)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Since the `img` array is just quite small (20x30), when the `imshow` function displays it, it grows the image to the figure's size. By default it uses [bilinear interpolation](https://en.wikipedia.org/wiki/Bilinear_interpolation) to fill the added pixels. This is why the edges look blurry.\n",
|
||
"You can select another interpolation algorithm, such as copying the color of the nearest pixel:"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 44,
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAW0AAAD7CAYAAAChScXIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACjpJREFUeJzt20GopfdZx/HfE4Yu2kIIxSSQ2GopM4IgQ8Vs4mJKtQlC\nSOlCYzZtFzULoy6tbjLLxkWwIAVtY4jSUFSIyWTRplKCBNEO1phG05mCJm1qMg0Sxe6CeVzcE3Mz\nc+/cyz3n3pvn7ecDlznnve857/8/75nvfed/zq3uDgAzXHPcAwBg/0QbYBDRBhhEtAEGEW2AQUQb\nYJATh32AqvKZQoAD6O66fNta0a6q25P8Ybau2B/s7vt33vOPd9h2Lskd6xz+HWw5c+v+jSu2nT17\nNmfPnj36wRyRJc3vT+qKf/MLenXubCnzu2eX7QdeHqmqa5L8UZLbkvxskl+vqp856PMBsLd11rRv\nSfLd7n6xu19P8pUkd25mWADsZJ1o35Tk+9vuv7Tatk8n1zj0O92S55acOXPmuIdwqJY+v2W/Opc/\nv0N/I3LLuW23TyY5tfpaqiXPbflRW/r8lv3qnDu/C0ku7mO/daL9gyTv33b/5tW2HSzhbQGAw3P5\npewTu+y3zvLI+SQfqqoPVNW7ktyV5PE1ng+APRz4Sru7/7eq7k3yZN76yN/zGxsZAFdYa027u7+a\nuUtIAOP4NXaAQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQb\nYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2A\nQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEG\nEW2AQUQbYBDRBhjkxDoPrqoXkvx3kjeSvN7dt2xiUADsbK1oZyvWZ7r7tU0MBoCrW3d5pDbwHADs\n07rB7SRfr6rzVfWZTQwIgN2tuzxya3e/XFU/ka14P9/dT1+527ltt08mObXmYQGW5UKSi/vYb61o\nd/fLqz9frapHk9ySZIdo37HOYQAW71Tefjn7xC77HXh5pKreXVXvXd1+T5KPJXnuoM8HwN7WudK+\nIcmjVdWr5/lydz+5mWEBsJMDR7u7/z3J6Q2OBYA9+LgewCCiDTCIaAMMItoAg4g2wCCiDTCIaAMM\nItoAg4g2wCCiDTCIaAMMItoAg4g2wCCiDTCIaAMMItoAg4g2wCCiDTCIaAMMItoAg4g2wCCiDTCI\naAMMItoAg4g2wCCiDTCIaAMMItoAg4g2wCCiDTCIaAMMItoAg4g2wCCiDTCIaAMMItoAg4g2wCCi\nDTCIaAMMItoAg4g2wCCiDTCIaAMMItoAg4g2wCCiDTDIntGuqger6lJVPbtt23VV9WRVXaiqr1XV\ntYc7TACS/V1pP5Tktsu2fTbJ33T3qSTfSPJ7mx4YAFfaM9rd/XSS1y7bfGeSh1e3H07y8Q2PC4Ad\nHHRN+/ruvpQk3f1Kkus3NyQAdrOpNyJ7Q88DwFWcOODjLlXVDd19qapuTPLDq+9+btvtk0lOHfCw\nAMt0IcnFfey332jX6utNjyf5VJL7k3wyyWNXf/gd+zwMwI+nU3n75ewTu+y3n4/8PZLk75KcrKrv\nVdWnk3wuyS9X1YUkH13dB+CQ7Xml3d137/KtX9rwWADYg9+IBBhEtAEGEW2AQUQbYBDRBhhEtAEG\nEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhE\ntAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDR\nBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQUQbYBDRBhhEtAEGEW2AQfaMdlU9WFWXqurZbdvuq6qX\nqupbq6/bD3eYACT7u9J+KMltO2x/oLs/vPr66obHBcAO9ox2dz+d5LUdvlWbHw4AV7POmva9VfVM\nVX2pqq7d2IgA2NVBo/2FJB/s7tNJXknywOaGBMBuThzkQd396ra7X0xy7uqP2P7tk0lOHeSwAIt1\nIcnFfey332hXtq1hV9WN3f3K6u4nkjx39Yffsc/DAPx4OpW3X84+sct+e0a7qh5JcibJ+6rqe0nu\nS/KRqjqd5I0kLyS5Z53BArA/e0a7u+/eYfNDhzAWAPbgNyIBBhFtgEFEG2AQ0QYYRLQBBhFtgEFE\nG2AQ0QYYRLQBBhFtgEFEG2AQ0QYYRLQBBhFtgEFEG2AQ0QYYRLQBBhFtgEFEG2AQ0QYYRLQBBhFt\ngEFEG2AQ0QYYRLQBBhFtgEFEG2AQ0QYYRLQBBhFtgEFEG2AQ0QYYRLQBBhFtgEFEG2AQ0QYYRLQB\nBhFtgEFEG2AQ0QYYRLQBBhFtgEGOMdoXju/Qh27Jc0ueeuqp4x7CoVr6/Jb96lz+/I4x2heP79CH\nbslzW37Ulj6/Zb86lz8/yyMAg4g2wCDV3Yd7gKrDPQDAQnV3Xb7t0KMNwOZYHgEYRLQBBjnyaFfV\n7VX1naq6WFW/e9THP2xV9UJV/XNV/VNVffO4x7Ouqnqwqi5V1bPbtl1XVU9W1YWq+lpVXXucY1zH\nLvO7r6peqqpvrb5uP84xHlRV3VxV36iqf6mqb1fVb6+2L+L87TC/31ptX8T5282RrmlX1TXZ+hjl\nR5P8R5LzSe7q7u8c2SAOWVX9W5Kf7+7Xjnssm1BVv5jkR0n+rLt/brXt/iT/2d1/sPrBe113f/Y4\nx3lQu8zvviT/090PHOvg1lRVNya5sbufqar3JvnHJHcm+XQWcP6uMr9fywLO326O+kr7liTf7e4X\nu/v1JF/J1l/yklQWtOzU3U8nufwH0J1JHl7dfjjJx490UBu0y/ySrfM4Wne/0t3PrG7/KMnzSW7O\nQs7fLvO7afXt8edvN0cdl5uSfH/b/Zfy1l/yUnSSr1fV+ar6zHEP5pBc392Xkq1/OEmuP+bxHIZ7\nq+qZqvrS1OWD7arqp5KcTvL3SW5Y2vnbNr9/WG1a1PnbbjFXhO8gt3b3h5P8SpLfXP33e+mW9rnR\nLyT5YHefTvJKktH/zV4tHfxVkt9ZXZFefr5Gn78d5reo83e5o472D5K8f9v9m1fbFqO7X179+WqS\nR7O1JLQ0l6rqhuT/1xV/eMzj2ajufrXferPni0l+4TjHs46qOpGtoP15dz+22ryY87fT/JZ0/nZy\n1NE+n+RDVfWBqnpXkruSPH7EYzg0VfXu1U/9VNV7knwsyXPHO6qNqLx9jfDxJJ9a3f5kkscuf8Aw\nb5vfKmRv+kRmn8M/TfKv3f35bduWdP6umN/Czt8Vjvw3Ilcfv/l8tn5gPNjdnzvSARyiqvrpbF1d\nd5ITSb48fX5V9UiSM0nel+RSkvuS/HWSv0zyk0leTPKr3f1fxzXGdewyv49ka330jSQvJLnnzTXg\nSarq1iR/m+Tb2XpNdpLfT/LNJH+R4efvKvO7Ows4f7vxa+wAg3gjEmAQ0QYYRLQBBhFtgEFEG2AQ\n0QYYRLQBBhFtgEH+DzauLdnV5hW0AAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<matplotlib.figure.Figure at 0x112604978>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.imshow(img, interpolation=\"nearest\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Animations\n",
|
||
"Although matplotlib is mostly used to generate images, it is also capable of displaying animations, depending on the Backend you use. In a Jupyter notebook, we need to use the `nbagg` backend to use interactive matplotlib features, including animations. We also need to import `matplotlib.animation`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 45,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"%matplotlib nbagg\n",
|
||
"import matplotlib.animation as animation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"In this example, we start by creating data points, then we create an empty plot, we define the update function that will be called at every iteration of the animation, and finally we add an animation to the plot by creating a `FuncAnimation` instance.\n",
|
||
"\n",
|
||
"The `FuncAnimation` constructor takes a figure, an update function and optional arguments. We specify that we want a 100-frame long animation, with 20ms between each frame. At each iteration, `FuncAnimation` calls our update function and passes it the frame number `num` (from 0 to 99 in our case) followed by the extra arguments that we specified with `fargs`.\n",
|
||
"\n",
|
||
"Our update function simply sets the line data to be the first `num` data points (so the data gets drawn gradually), and just for fun we also add a small random number to each data point so that the line appears to wiggle."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 46,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/javascript": [
|
||
"/* Put everything inside the global mpl namespace */\n",
|
||
"window.mpl = {};\n",
|
||
"\n",
|
||
"mpl.get_websocket_type = function() {\n",
|
||
" if (typeof(WebSocket) !== 'undefined') {\n",
|
||
" return WebSocket;\n",
|
||
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
|
||
" return MozWebSocket;\n",
|
||
" } else {\n",
|
||
" alert('Your browser does not have WebSocket support.' +\n",
|
||
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
|
||
" 'Firefox 4 and 5 are also supported but you ' +\n",
|
||
" 'have to enable WebSockets in about:config.');\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
|
||
" this.id = figure_id;\n",
|
||
"\n",
|
||
" this.ws = websocket;\n",
|
||
"\n",
|
||
" this.supports_binary = (this.ws.binaryType != undefined);\n",
|
||
"\n",
|
||
" if (!this.supports_binary) {\n",
|
||
" var warnings = document.getElementById(\"mpl-warnings\");\n",
|
||
" if (warnings) {\n",
|
||
" warnings.style.display = 'block';\n",
|
||
" warnings.textContent = (\n",
|
||
" \"This browser does not support binary websocket messages. \" +\n",
|
||
" \"Performance may be slow.\");\n",
|
||
" }\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj = new Image();\n",
|
||
"\n",
|
||
" this.context = undefined;\n",
|
||
" this.message = undefined;\n",
|
||
" this.canvas = undefined;\n",
|
||
" this.rubberband_canvas = undefined;\n",
|
||
" this.rubberband_context = undefined;\n",
|
||
" this.format_dropdown = undefined;\n",
|
||
"\n",
|
||
" this.image_mode = 'full';\n",
|
||
"\n",
|
||
" this.root = $('<div/>');\n",
|
||
" this._root_extra_style(this.root)\n",
|
||
" this.root.attr('style', 'display: inline-block');\n",
|
||
"\n",
|
||
" $(parent_element).append(this.root);\n",
|
||
"\n",
|
||
" this._init_header(this);\n",
|
||
" this._init_canvas(this);\n",
|
||
" this._init_toolbar(this);\n",
|
||
"\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" this.waiting = false;\n",
|
||
"\n",
|
||
" this.ws.onopen = function () {\n",
|
||
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
|
||
" fig.send_message(\"send_image_mode\", {});\n",
|
||
" fig.send_message(\"refresh\", {});\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.imageObj.onload = function() {\n",
|
||
" if (fig.image_mode == 'full') {\n",
|
||
" // Full images could contain transparency (where diff images\n",
|
||
" // almost always do), so we need to clear the canvas so that\n",
|
||
" // there is no ghosting.\n",
|
||
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
|
||
" }\n",
|
||
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
|
||
" };\n",
|
||
"\n",
|
||
" this.imageObj.onunload = function() {\n",
|
||
" this.ws.close();\n",
|
||
" }\n",
|
||
"\n",
|
||
" this.ws.onmessage = this._make_on_message_function(this);\n",
|
||
"\n",
|
||
" this.ondownload = ondownload;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_header = function() {\n",
|
||
" var titlebar = $(\n",
|
||
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
|
||
" 'ui-helper-clearfix\"/>');\n",
|
||
" var titletext = $(\n",
|
||
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
|
||
" 'text-align: center; padding: 3px;\"/>');\n",
|
||
" titlebar.append(titletext)\n",
|
||
" this.root.append(titlebar);\n",
|
||
" this.header = titletext[0];\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_canvas = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var canvas_div = $('<div/>');\n",
|
||
"\n",
|
||
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
|
||
"\n",
|
||
" function canvas_keyboard_event(event) {\n",
|
||
" return fig.key_event(event, event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
|
||
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
|
||
" this.canvas_div = canvas_div\n",
|
||
" this._canvas_extra_style(canvas_div)\n",
|
||
" this.root.append(canvas_div);\n",
|
||
"\n",
|
||
" var canvas = $('<canvas/>');\n",
|
||
" canvas.addClass('mpl-canvas');\n",
|
||
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
|
||
"\n",
|
||
" this.canvas = canvas[0];\n",
|
||
" this.context = canvas[0].getContext(\"2d\");\n",
|
||
"\n",
|
||
" var rubberband = $('<canvas/>');\n",
|
||
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
|
||
"\n",
|
||
" var pass_mouse_events = true;\n",
|
||
"\n",
|
||
" canvas_div.resizable({\n",
|
||
" start: function(event, ui) {\n",
|
||
" pass_mouse_events = false;\n",
|
||
" },\n",
|
||
" resize: function(event, ui) {\n",
|
||
" fig.request_resize(ui.size.width, ui.size.height);\n",
|
||
" },\n",
|
||
" stop: function(event, ui) {\n",
|
||
" pass_mouse_events = true;\n",
|
||
" fig.request_resize(ui.size.width, ui.size.height);\n",
|
||
" },\n",
|
||
" });\n",
|
||
"\n",
|
||
" function mouse_event_fn(event) {\n",
|
||
" if (pass_mouse_events)\n",
|
||
" return fig.mouse_event(event, event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" rubberband.mousedown('button_press', mouse_event_fn);\n",
|
||
" rubberband.mouseup('button_release', mouse_event_fn);\n",
|
||
" // Throttle sequential mouse events to 1 every 20ms.\n",
|
||
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
|
||
"\n",
|
||
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
|
||
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
|
||
"\n",
|
||
" canvas_div.on(\"wheel\", function (event) {\n",
|
||
" event = event.originalEvent;\n",
|
||
" event['data'] = 'scroll'\n",
|
||
" if (event.deltaY < 0) {\n",
|
||
" event.step = 1;\n",
|
||
" } else {\n",
|
||
" event.step = -1;\n",
|
||
" }\n",
|
||
" mouse_event_fn(event);\n",
|
||
" });\n",
|
||
"\n",
|
||
" canvas_div.append(canvas);\n",
|
||
" canvas_div.append(rubberband);\n",
|
||
"\n",
|
||
" this.rubberband = rubberband;\n",
|
||
" this.rubberband_canvas = rubberband[0];\n",
|
||
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
|
||
" this.rubberband_context.strokeStyle = \"#000000\";\n",
|
||
"\n",
|
||
" this._resize_canvas = function(width, height) {\n",
|
||
" // Keep the size of the canvas, canvas container, and rubber band\n",
|
||
" // canvas in synch.\n",
|
||
" canvas_div.css('width', width)\n",
|
||
" canvas_div.css('height', height)\n",
|
||
"\n",
|
||
" canvas.attr('width', width);\n",
|
||
" canvas.attr('height', height);\n",
|
||
"\n",
|
||
" rubberband.attr('width', width);\n",
|
||
" rubberband.attr('height', height);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
|
||
" // upon first draw.\n",
|
||
" this._resize_canvas(600, 600);\n",
|
||
"\n",
|
||
" // Disable right mouse context menu.\n",
|
||
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
|
||
" return false;\n",
|
||
" });\n",
|
||
"\n",
|
||
" function set_focus () {\n",
|
||
" canvas.focus();\n",
|
||
" canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" window.setTimeout(set_focus, 100);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var nav_element = $('<div/>')\n",
|
||
" nav_element.attr('style', 'width: 100%');\n",
|
||
" this.root.append(nav_element);\n",
|
||
"\n",
|
||
" // Define a callback function for later on.\n",
|
||
" function toolbar_event(event) {\n",
|
||
" return fig.toolbar_button_onclick(event['data']);\n",
|
||
" }\n",
|
||
" function toolbar_mouse_event(event) {\n",
|
||
" return fig.toolbar_button_onmouseover(event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" for(var toolbar_ind in mpl.toolbar_items) {\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) {\n",
|
||
" // put a spacer in here.\n",
|
||
" continue;\n",
|
||
" }\n",
|
||
" var button = $('<button/>');\n",
|
||
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
|
||
" 'ui-button-icon-only');\n",
|
||
" button.attr('role', 'button');\n",
|
||
" button.attr('aria-disabled', 'false');\n",
|
||
" button.click(method_name, toolbar_event);\n",
|
||
" button.mouseover(tooltip, toolbar_mouse_event);\n",
|
||
"\n",
|
||
" var icon_img = $('<span/>');\n",
|
||
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
|
||
" icon_img.addClass(image);\n",
|
||
" icon_img.addClass('ui-corner-all');\n",
|
||
"\n",
|
||
" var tooltip_span = $('<span/>');\n",
|
||
" tooltip_span.addClass('ui-button-text');\n",
|
||
" tooltip_span.html(tooltip);\n",
|
||
"\n",
|
||
" button.append(icon_img);\n",
|
||
" button.append(tooltip_span);\n",
|
||
"\n",
|
||
" nav_element.append(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fmt_picker_span = $('<span/>');\n",
|
||
"\n",
|
||
" var fmt_picker = $('<select/>');\n",
|
||
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
|
||
" fmt_picker_span.append(fmt_picker);\n",
|
||
" nav_element.append(fmt_picker_span);\n",
|
||
" this.format_dropdown = fmt_picker[0];\n",
|
||
"\n",
|
||
" for (var ind in mpl.extensions) {\n",
|
||
" var fmt = mpl.extensions[ind];\n",
|
||
" var option = $(\n",
|
||
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
|
||
" fmt_picker.append(option)\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add hover states to the ui-buttons\n",
|
||
" $( \".ui-button\" ).hover(\n",
|
||
" function() { $(this).addClass(\"ui-state-hover\");},\n",
|
||
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
|
||
" );\n",
|
||
"\n",
|
||
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
|
||
" nav_element.append(status_bar);\n",
|
||
" this.message = status_bar[0];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
|
||
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
|
||
" // which will in turn request a refresh of the image.\n",
|
||
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_message = function(type, properties) {\n",
|
||
" properties['type'] = type;\n",
|
||
" properties['figure_id'] = this.id;\n",
|
||
" this.ws.send(JSON.stringify(properties));\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.send_draw_message = function() {\n",
|
||
" if (!this.waiting) {\n",
|
||
" this.waiting = true;\n",
|
||
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
|
||
" var format_dropdown = fig.format_dropdown;\n",
|
||
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
|
||
" fig.ondownload(fig, format);\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
|
||
" var size = msg['size'];\n",
|
||
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
|
||
" fig._resize_canvas(size[0], size[1]);\n",
|
||
" fig.send_message(\"refresh\", {});\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
|
||
" var x0 = msg['x0'];\n",
|
||
" var y0 = fig.canvas.height - msg['y0'];\n",
|
||
" var x1 = msg['x1'];\n",
|
||
" var y1 = fig.canvas.height - msg['y1'];\n",
|
||
" x0 = Math.floor(x0) + 0.5;\n",
|
||
" y0 = Math.floor(y0) + 0.5;\n",
|
||
" x1 = Math.floor(x1) + 0.5;\n",
|
||
" y1 = Math.floor(y1) + 0.5;\n",
|
||
" var min_x = Math.min(x0, x1);\n",
|
||
" var min_y = Math.min(y0, y1);\n",
|
||
" var width = Math.abs(x1 - x0);\n",
|
||
" var height = Math.abs(y1 - y0);\n",
|
||
"\n",
|
||
" fig.rubberband_context.clearRect(\n",
|
||
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
|
||
"\n",
|
||
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
|
||
" // Updates the figure title.\n",
|
||
" fig.header.textContent = msg['label'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
|
||
" var cursor = msg['cursor'];\n",
|
||
" switch(cursor)\n",
|
||
" {\n",
|
||
" case 0:\n",
|
||
" cursor = 'pointer';\n",
|
||
" break;\n",
|
||
" case 1:\n",
|
||
" cursor = 'default';\n",
|
||
" break;\n",
|
||
" case 2:\n",
|
||
" cursor = 'crosshair';\n",
|
||
" break;\n",
|
||
" case 3:\n",
|
||
" cursor = 'move';\n",
|
||
" break;\n",
|
||
" }\n",
|
||
" fig.rubberband_canvas.style.cursor = cursor;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
|
||
" fig.message.textContent = msg['message'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
|
||
" // Request the server to send over a new figure.\n",
|
||
" fig.send_draw_message();\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
|
||
" fig.image_mode = msg['mode'];\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function() {\n",
|
||
" // Called whenever the canvas gets updated.\n",
|
||
" this.send_message(\"ack\", {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"// A function to construct a web socket function for onmessage handling.\n",
|
||
"// Called in the figure constructor.\n",
|
||
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
|
||
" return function socket_on_message(evt) {\n",
|
||
" if (evt.data instanceof Blob) {\n",
|
||
" /* FIXME: We get \"Resource interpreted as Image but\n",
|
||
" * transferred with MIME type text/plain:\" errors on\n",
|
||
" * Chrome. But how to set the MIME type? It doesn't seem\n",
|
||
" * to be part of the websocket stream */\n",
|
||
" evt.data.type = \"image/png\";\n",
|
||
"\n",
|
||
" /* Free the memory for the previous frames */\n",
|
||
" if (fig.imageObj.src) {\n",
|
||
" (window.URL || window.webkitURL).revokeObjectURL(\n",
|
||
" fig.imageObj.src);\n",
|
||
" }\n",
|
||
"\n",
|
||
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
|
||
" evt.data);\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
|
||
" fig.imageObj.src = evt.data;\n",
|
||
" fig.updated_canvas_event();\n",
|
||
" fig.waiting = false;\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var msg = JSON.parse(evt.data);\n",
|
||
" var msg_type = msg['type'];\n",
|
||
"\n",
|
||
" // Call the \"handle_{type}\" callback, which takes\n",
|
||
" // the figure and JSON message as its only arguments.\n",
|
||
" try {\n",
|
||
" var callback = fig[\"handle_\" + msg_type];\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" if (callback) {\n",
|
||
" try {\n",
|
||
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
|
||
" callback(fig, msg);\n",
|
||
" } catch (e) {\n",
|
||
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
|
||
" }\n",
|
||
" }\n",
|
||
" };\n",
|
||
"}\n",
|
||
"\n",
|
||
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
|
||
"mpl.findpos = function(e) {\n",
|
||
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
|
||
" var targ;\n",
|
||
" if (!e)\n",
|
||
" e = window.event;\n",
|
||
" if (e.target)\n",
|
||
" targ = e.target;\n",
|
||
" else if (e.srcElement)\n",
|
||
" targ = e.srcElement;\n",
|
||
" if (targ.nodeType == 3) // defeat Safari bug\n",
|
||
" targ = targ.parentNode;\n",
|
||
"\n",
|
||
" // jQuery normalizes the pageX and pageY\n",
|
||
" // pageX,Y are the mouse positions relative to the document\n",
|
||
" // offset() returns the position of the element relative to the document\n",
|
||
" var x = e.pageX - $(targ).offset().left;\n",
|
||
" var y = e.pageY - $(targ).offset().top;\n",
|
||
"\n",
|
||
" return {\"x\": x, \"y\": y};\n",
|
||
"};\n",
|
||
"\n",
|
||
"/*\n",
|
||
" * return a copy of an object with only non-object keys\n",
|
||
" * we need this to avoid circular references\n",
|
||
" * http://stackoverflow.com/a/24161582/3208463\n",
|
||
" */\n",
|
||
"function simpleKeys (original) {\n",
|
||
" return Object.keys(original).reduce(function (obj, key) {\n",
|
||
" if (typeof original[key] !== 'object')\n",
|
||
" obj[key] = original[key]\n",
|
||
" return obj;\n",
|
||
" }, {});\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
|
||
" var canvas_pos = mpl.findpos(event)\n",
|
||
"\n",
|
||
" if (name === 'button_press')\n",
|
||
" {\n",
|
||
" this.canvas.focus();\n",
|
||
" this.canvas_div.focus();\n",
|
||
" }\n",
|
||
"\n",
|
||
" var x = canvas_pos.x;\n",
|
||
" var y = canvas_pos.y;\n",
|
||
"\n",
|
||
" this.send_message(name, {x: x, y: y, button: event.button,\n",
|
||
" step: event.step,\n",
|
||
" guiEvent: simpleKeys(event)});\n",
|
||
"\n",
|
||
" /* This prevents the web browser from automatically changing to\n",
|
||
" * the text insertion cursor when the button is pressed. We want\n",
|
||
" * to control all of the cursor setting manually through the\n",
|
||
" * 'cursor' event from matplotlib */\n",
|
||
" event.preventDefault();\n",
|
||
" return false;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
|
||
" // Handle any extra behaviour associated with a key event\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.key_event = function(event, name) {\n",
|
||
"\n",
|
||
" // Prevent repeat events\n",
|
||
" if (name == 'key_press')\n",
|
||
" {\n",
|
||
" if (event.which === this._key)\n",
|
||
" return;\n",
|
||
" else\n",
|
||
" this._key = event.which;\n",
|
||
" }\n",
|
||
" if (name == 'key_release')\n",
|
||
" this._key = null;\n",
|
||
"\n",
|
||
" var value = '';\n",
|
||
" if (event.ctrlKey && event.which != 17)\n",
|
||
" value += \"ctrl+\";\n",
|
||
" if (event.altKey && event.which != 18)\n",
|
||
" value += \"alt+\";\n",
|
||
" if (event.shiftKey && event.which != 16)\n",
|
||
" value += \"shift+\";\n",
|
||
"\n",
|
||
" value += 'k';\n",
|
||
" value += event.which.toString();\n",
|
||
"\n",
|
||
" this._key_event_extra(event, name);\n",
|
||
"\n",
|
||
" this.send_message(name, {key: value,\n",
|
||
" guiEvent: simpleKeys(event)});\n",
|
||
" return false;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
|
||
" if (name == 'download') {\n",
|
||
" this.handle_save(this, null);\n",
|
||
" } else {\n",
|
||
" this.send_message(\"toolbar_button\", {name: name});\n",
|
||
" }\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
|
||
" this.message.textContent = tooltip;\n",
|
||
"};\n",
|
||
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
|
||
"\n",
|
||
"mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
|
||
"\n",
|
||
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
|
||
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
|
||
" // object with the appropriate methods. Currently this is a non binary\n",
|
||
" // socket, so there is still some room for performance tuning.\n",
|
||
" var ws = {};\n",
|
||
"\n",
|
||
" ws.close = function() {\n",
|
||
" comm.close()\n",
|
||
" };\n",
|
||
" ws.send = function(m) {\n",
|
||
" //console.log('sending', m);\n",
|
||
" comm.send(m);\n",
|
||
" };\n",
|
||
" // Register the callback with on_msg.\n",
|
||
" comm.on_msg(function(msg) {\n",
|
||
" //console.log('receiving', msg['content']['data'], msg);\n",
|
||
" // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
|
||
" ws.onmessage(msg['content']['data'])\n",
|
||
" });\n",
|
||
" return ws;\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.mpl_figure_comm = function(comm, msg) {\n",
|
||
" // This is the function which gets called when the mpl process\n",
|
||
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
|
||
"\n",
|
||
" var id = msg.content.data.id;\n",
|
||
" // Get hold of the div created by the display call when the Comm\n",
|
||
" // socket was opened in Python.\n",
|
||
" var element = $(\"#\" + id);\n",
|
||
" var ws_proxy = comm_websocket_adapter(comm)\n",
|
||
"\n",
|
||
" function ondownload(figure, format) {\n",
|
||
" window.open(figure.imageObj.src);\n",
|
||
" }\n",
|
||
"\n",
|
||
" var fig = new mpl.figure(id, ws_proxy,\n",
|
||
" ondownload,\n",
|
||
" element.get(0));\n",
|
||
"\n",
|
||
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
|
||
" // web socket which is closed, not our websocket->open comm proxy.\n",
|
||
" ws_proxy.onopen();\n",
|
||
"\n",
|
||
" fig.parent_element = element.get(0);\n",
|
||
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
|
||
" if (!fig.cell_info) {\n",
|
||
" console.error(\"Failed to find cell for figure\", id, fig);\n",
|
||
" return;\n",
|
||
" }\n",
|
||
"\n",
|
||
" var output_index = fig.cell_info[2]\n",
|
||
" var cell = fig.cell_info[0];\n",
|
||
"\n",
|
||
"};\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
|
||
" fig.root.unbind('remove')\n",
|
||
"\n",
|
||
" // Update the output cell to use the data from the current canvas.\n",
|
||
" fig.push_to_output();\n",
|
||
" var dataURL = fig.canvas.toDataURL();\n",
|
||
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
|
||
" // the notebook keyboard shortcuts fail.\n",
|
||
" IPython.keyboard_manager.enable()\n",
|
||
" $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
|
||
" fig.close_ws(fig, msg);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
|
||
" fig.send_message('closing', msg);\n",
|
||
" // fig.ws.close()\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
|
||
" // Turn the data on the canvas into data in the output cell.\n",
|
||
" var dataURL = this.canvas.toDataURL();\n",
|
||
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.updated_canvas_event = function() {\n",
|
||
" // Tell IPython that the notebook contents must change.\n",
|
||
" IPython.notebook.set_dirty(true);\n",
|
||
" this.send_message(\"ack\", {});\n",
|
||
" var fig = this;\n",
|
||
" // Wait a second, then push the new image to the DOM so\n",
|
||
" // that it is saved nicely (might be nice to debounce this).\n",
|
||
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._init_toolbar = function() {\n",
|
||
" var fig = this;\n",
|
||
"\n",
|
||
" var nav_element = $('<div/>')\n",
|
||
" nav_element.attr('style', 'width: 100%');\n",
|
||
" this.root.append(nav_element);\n",
|
||
"\n",
|
||
" // Define a callback function for later on.\n",
|
||
" function toolbar_event(event) {\n",
|
||
" return fig.toolbar_button_onclick(event['data']);\n",
|
||
" }\n",
|
||
" function toolbar_mouse_event(event) {\n",
|
||
" return fig.toolbar_button_onmouseover(event['data']);\n",
|
||
" }\n",
|
||
"\n",
|
||
" for(var toolbar_ind in mpl.toolbar_items){\n",
|
||
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
|
||
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
|
||
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
|
||
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
|
||
"\n",
|
||
" if (!name) { continue; };\n",
|
||
"\n",
|
||
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
|
||
" button.click(method_name, toolbar_event);\n",
|
||
" button.mouseover(tooltip, toolbar_mouse_event);\n",
|
||
" nav_element.append(button);\n",
|
||
" }\n",
|
||
"\n",
|
||
" // Add the status bar.\n",
|
||
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
|
||
" nav_element.append(status_bar);\n",
|
||
" this.message = status_bar[0];\n",
|
||
"\n",
|
||
" // Add the close button to the window.\n",
|
||
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
|
||
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
|
||
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
|
||
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
|
||
" buttongrp.append(button);\n",
|
||
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
|
||
" titlebar.prepend(buttongrp);\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._root_extra_style = function(el){\n",
|
||
" var fig = this\n",
|
||
" el.on(\"remove\", function(){\n",
|
||
"\tfig.close_ws(fig, {});\n",
|
||
" });\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
|
||
" // this is important to make the div 'focusable\n",
|
||
" el.attr('tabindex', 0)\n",
|
||
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
|
||
" // off when our div gets focus\n",
|
||
"\n",
|
||
" // location in version 3\n",
|
||
" if (IPython.notebook.keyboard_manager) {\n",
|
||
" IPython.notebook.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
" else {\n",
|
||
" // location in version 2\n",
|
||
" IPython.keyboard_manager.register_events(el);\n",
|
||
" }\n",
|
||
"\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
|
||
" var manager = IPython.notebook.keyboard_manager;\n",
|
||
" if (!manager)\n",
|
||
" manager = IPython.keyboard_manager;\n",
|
||
"\n",
|
||
" // Check for shift+enter\n",
|
||
" if (event.shiftKey && event.which == 13) {\n",
|
||
" this.canvas_div.blur();\n",
|
||
" event.shiftKey = false;\n",
|
||
" // Send a \"J\" for go to next cell\n",
|
||
" event.which = 74;\n",
|
||
" event.keyCode = 74;\n",
|
||
" manager.command_mode();\n",
|
||
" manager.handle_keydown(event);\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
|
||
" fig.ondownload(fig, null);\n",
|
||
"}\n",
|
||
"\n",
|
||
"\n",
|
||
"mpl.find_output_cell = function(html_output) {\n",
|
||
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
|
||
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
|
||
" // IPython event is triggered only after the cells have been serialised, which for\n",
|
||
" // our purposes (turning an active figure into a static one), is too late.\n",
|
||
" var cells = IPython.notebook.get_cells();\n",
|
||
" var ncells = cells.length;\n",
|
||
" for (var i=0; i<ncells; i++) {\n",
|
||
" var cell = cells[i];\n",
|
||
" if (cell.cell_type === 'code'){\n",
|
||
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
|
||
" var data = cell.output_area.outputs[j];\n",
|
||
" if (data.data) {\n",
|
||
" // IPython >= 3 moved mimebundle to data attribute of output\n",
|
||
" data = data.data;\n",
|
||
" }\n",
|
||
" if (data['text/html'] == html_output) {\n",
|
||
" return [cell, data, j];\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
" }\n",
|
||
"}\n",
|
||
"\n",
|
||
"// Register the function which deals with the matplotlib target/channel.\n",
|
||
"// The kernel may be null if the page has been refreshed.\n",
|
||
"if (IPython.notebook.kernel != null) {\n",
|
||
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
|
||
"}\n"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.Javascript object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<img 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\">"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"x = np.linspace(-1, 1, 100)\n",
|
||
"y = np.sin(x**2*25)\n",
|
||
"data = np.array([x, y])\n",
|
||
"\n",
|
||
"fig = plt.figure()\n",
|
||
"line, = plt.plot([], [], \"r-\") # start with an empty plot\n",
|
||
"plt.axis([-1.1, 1.1, -1.1, 1.1])\n",
|
||
"plt.plot([-0.5, 0.5], [0, 0], \"b-\", [0, 0], [-0.5, 0.5], \"b-\", 0, 0, \"ro\")\n",
|
||
"plt.grid(True)\n",
|
||
"plt.title(\"Marvelous animation\")\n",
|
||
"\n",
|
||
"# this function will be called at every iteration\n",
|
||
"def update_line(num, data, line):\n",
|
||
" line.set_data(data[..., :num] + np.random.rand(2, num) / 25) # we only plot the first `num` data points.\n",
|
||
" return line,\n",
|
||
"\n",
|
||
"line_ani = animation.FuncAnimation(fig, update_line, frames=100, fargs=(data, line), interval=67)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Saving animations to video files\n",
|
||
"Matplotlib relies on 3rd-party libraries to write videos such as [FFMPEG](https://www.ffmpeg.org/) or `mencoder`. In this example we will be using FFMPEG so be sure to install it first."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 47,
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"Writer = animation.writers['ffmpeg']\n",
|
||
"writer = Writer(fps=15, metadata=dict(artist='Me'), bitrate=1800)\n",
|
||
"line_ani.save('my_wiggly_animation.mp4', writer=writer)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## What next?\n",
|
||
"Now you know all the basics of matplotlib, but there are many more options available. The best way to learn more, is to visit the [gallery](http://matplotlib.org/gallery.html), look at the images, choose a plot that you are interested in, then just copy the code in a Jupyter notebook and play around with it."
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
|
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"name": "python3"
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||
},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
|
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
|
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}
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