{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Dans un notebook précédent, on a vu comment créer une grille hexagonale et comment l'animer.\n",
"\n",
"On va maintenant utiliser MoviePy pour animer ces plots.\n",
"\n",
""
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from elasticite import EdgeGrid\n",
"e = EdgeGrid()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Cette librairie permet de faire des animations depuis diverses librairies de visualisation, comme:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import os\n",
"name = 'sinc_vispy'\n",
"fps = 25\n",
"if not os.path.isfile(os.path.join('../files/2015-10-14_elasticite/', name + '.mp4')):\n",
" from moviepy.editor import VideoClip\n",
" import numpy as np\n",
" from vispy import app, scene\n",
" app.use_app('pyglet')\n",
" from vispy.gloo.util import _screenshot\n",
"\n",
" canvas = scene.SceneCanvas(keys='interactive')\n",
" view = canvas.central_widget.add_view()\n",
" xx, yy = np.arange(-1,1,.02),np.arange(-1,1,.02)\n",
" X,Y = np.meshgrid(xx,yy)\n",
" R = np.sqrt(X**2+Y**2)\n",
" Z = lambda t : 0.1*np.sin(10*R-2*np.pi*t)\n",
" surface = scene.visuals.SurfacePlot(x= xx-0.1, y=yy+0.2, z= Z(0),\n",
" shading='smooth', color=(0.5, 0.5, 1, 1))\n",
" view.add(surface)\n",
"\n",
" # Use a 3D camera\n",
" # Manual bounds; Mesh visual does not provide bounds yet\n",
" # Note how you can set bounds before assigning the camera to the viewbox\n",
" cam = scene.TurntableCamera(elevation=30, azimuth=30, up='z', distance=2)\n",
" view.camera = cam\n",
"\n",
" canvas.show()\n",
"\n",
" # ANIMATE WITH MOVIEPY\n",
" def make_frame(t):\n",
" surface.set_data(z = Z(t)) # Update the mathematical surface\n",
" canvas.on_draw(None) # Update the image on Vispy's canvas\n",
" return _screenshot((0,0,canvas.size[0],canvas.size[1]))[:,:,:3]\n",
"\n",
" animation = VideoClip(make_frame, duration=1).resize(width=350)\n",
" animation.write_videofile('../files/2015-10-14_elasticite/' + name + '.mp4', fps=fps)\n",
"e.ipython_display(name)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Mais ce qui nous intéresse c'est de convertir nos trames construites avec matplotlib:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"name = 'sinc_mpl' \n",
"if not os.path.isfile(os.path.join('../files/2015-10-14_elasticite/', name + '.mp4')):\n",
" import matplotlib.pyplot as plt\n",
" import numpy as np\n",
" from moviepy.video.io.bindings import mplfig_to_npimage\n",
" import moviepy.editor as mpy\n",
"\n",
" # DRAW A FIGURE WITH MATPLOTLIB\n",
" duration = 2.\n",
"\n",
" fig_mpl, ax = plt.subplots(1,figsize=(5,3), facecolor='white')\n",
" xx = np.linspace(-2,2,200) # the x vector\n",
" zz = lambda d: np.sinc(xx**2)+np.sin(xx+d) # the (changing) z vector\n",
" ax.set_title(\"Elevation in y=0\")\n",
" ax.set_ylim(-1.5,2.5)\n",
" line, = ax.plot(xx, zz(0), lw=3)\n",
"\n",
" # ANIMATE WITH MOVIEPY (UPDATE THE CURVE FOR EACH t). MAKE A GIF.\n",
"\n",
" def make_frame_mpl(t):\n",
" line.set_ydata( zz(2*np.pi*t/duration)) # <= Update the curve\n",
" return mplfig_to_npimage(fig_mpl) # RGB image of the figure\n",
"\n",
" animation = mpy.VideoClip(make_frame_mpl, duration=duration)\n",
" animation.write_videofile('../files/2015-10-14_elasticite/' + name + '.mp4', fps=fps)\n",
"e.ipython_display(name)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"name = 'circle'\n",
"if not os.path.isfile(os.path.join('../files/2015-10-14_elasticite/', name + '.mp4')):\n",
" import matplotlib as mpl\n",
" import matplotlib.pyplot as plt\n",
" import numpy as np\n",
" from moviepy.video.io.bindings import mplfig_to_npimage\n",
" import moviepy.editor as mpy\n",
" duration = 3.\n",
" fig_mpl, ax = plt.subplots(1, figsize=(6, 5), facecolor='white')\n",
"\n",
" def draw_elementary_pattern(ax, center):\n",
" ax.add_artist(mpl.patches.Wedge(center, 1., 0, 180, width=.1))\n",
"\n",
" def make_frame_mpl(t):\n",
" ax.cla()\n",
" draw_elementary_pattern(ax, t/duration)\n",
" return mplfig_to_npimage(fig_mpl) # RGB image of the figure\n",
"\n",
" animation = mpy.VideoClip(make_frame_mpl, duration=duration)\n",
" animation.write_videofile('../files/2015-10-14_elasticite/' + name + '.mp4', fps=fps)\n",
"e.ipython_display(name)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pour le plaisir, une autre animation"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"name = 'svm'\n",
"if not os.path.isfile(os.path.join('../files/2015-10-14_elasticite/', name + '.mp4')):\n",
" import numpy as np\n",
" import matplotlib.pyplot as plt\n",
" from sklearn import svm # sklearn = scikit-learn\n",
" from sklearn.datasets import make_moons\n",
" from moviepy.editor import VideoClip\n",
" from moviepy.video.io.bindings import mplfig_to_npimage\n",
"\n",
" X, Y = make_moons(50, noise=0.1, random_state=2) # semi-random data\n",
"\n",
" fig, ax = plt.subplots(1, figsize=(4, 4), facecolor=(1,1,1))\n",
" fig.subplots_adjust(left=0, right=1, bottom=0)\n",
" xx, yy = np.meshgrid(np.linspace(-2,3,500), np.linspace(-1,2,500))\n",
"\n",
" def make_frame(t):\n",
" ax.clear()\n",
" ax.axis('off')\n",
" ax.set_title(\"SVC classification\", fontsize=16)\n",
"\n",
" classifier = svm.SVC(gamma=2, C=1)\n",
" # the varying weights make the points appear one after the other\n",
" weights = np.minimum(1, np.maximum(0, t**2+10-np.arange(50)))\n",
" classifier.fit(X, Y, sample_weight=weights)\n",
" Z = classifier.decision_function(np.c_[xx.ravel(), yy.ravel()])\n",
" Z = Z.reshape(xx.shape)\n",
" ax.contourf(xx, yy, Z, cmap=plt.cm.bone, alpha=0.8,\n",
" vmin=-2.5, vmax=2.5, levels=np.linspace(-2,2,20))\n",
" ax.scatter(X[:,0], X[:,1], c=Y, s=50*weights, cmap=plt.cm.bone)\n",
"\n",
" return mplfig_to_npimage(fig)\n",
"\n",
" animation = VideoClip(make_frame, duration = 7)\n",
" animation.write_videofile('../files/2015-10-14_elasticite/' + name + '.mp4', fps=fps)\n",
"e.ipython_display(name)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pour notre cas, on veut animer nos grilles et on simplifie la syntaxte redondante:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"name = 'test_grid'\n",
"import numpy as np\n",
"\n",
"e = EdgeGrid(verb=False, structure=False)\n",
"def make_lames(e):\n",
" return e.t*np.pi/duration\n",
"\n",
"duration = 3.\n",
"e.make_anim(name, make_lames, duration=duration)\n",
"e.ipython_display(name)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
" "
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"name = 'test_grid2'\n",
"import numpy as np\n",
"\n",
"e = EdgeGrid(verb=False, structure=False)\n",
"\n",
"def make_lames(e):\n",
" return e.lames[0, :] * np.pi + e.t*np.pi/duration\n",
"\n",
"duration = 3.\n",
"e.make_anim(name, make_lames, duration=duration)\n",
"e.ipython_display(name)"
]
}
],
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"display_name": "Python 3",
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"codemirror_mode": {
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"file_extension": ".py",
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