camera.snap captures the current state of the figure which is used to create the frames in the animation.Įdit: To quantify how much memory this uses I ran it through memory_profiler. Points = np.random.random((2, numpoints))Ĭolors = cm.rainbow(np.linspace(0, 1, numpoints)) It's probably easiest to show by example: import matplotlib.pyplot as plt X, y, c = np.random.random((3, numpoints))Īni = animation.FuncAnimation(fig, update_plot, frames=range(numframes), The performance will suffer, but the example should run correctly on OSX with blitting disabled.įor a simpler example, which just updates the colors, have a look at the following: import matplotlib.pyplot as pltĬolor_data = np.random.random((numframes, numpoints)) The OSX backend doesn't fully support blitting. If you're on OSX and using the OSX backend, you'll need to change blit=True to blit=False in the FuncAnimation initialization below. # We need to return the updated artist for FuncAnimation to draw. S, c = np.random.random((self.numpoints, 2)).T """Generate a random walk (brownian motion). # Note that it expects a sequence of artists, thus the trailing comma. # For FuncAnimation's sake, we need to return the artist we'll be using Self.scat = self.ax.scatter(x, y, c=c, s=s, vmin=0, vmax=1, """Initial drawing of the scatter plot.""" ![]() Self.ani = animation.FuncAnimation(self.fig, self.update, interval=5, For the older code see revision history) import matplotlib.pyplot as plt (Code edited April 2019 to be compatible with current versions. It's slightly more complex than it has to be, but this should give you a framework to do fancier things. Here's a quick example using the animation module. Where array is a 1D array of values which will be colormapped. Where array is a 1D array of sizes in points. Where array is a N x 2 shaped array of x and y coordinates. (I added some nice indexing slicing in order to get the even and odd parts) # plotting and creating an interactive figureįrom mpl_interactions import ipyplot as ipltĬtrls = iplt.scatter(indexer(sols, "T"), indexer(sols, "T"), T=np.arange(50))Ĭtrls.save_animation('out.Suppose you have a scatter plot, scat = ax.scatter(.), then you canĬhange the positions t_offsets(array) In your case you could drop the animate function and just do the following for making a plot. Pastebin is a website where you can store text online for a set period of time.Īlso you can avoid having to deal with things like set_offsets if you use mpl-interactions which makes it easy to make dynamic plots where you control parameters (in this case time) using sliders and then to save animations of them. is the number one paste tool since 2002. Pastebin import matplotlib.pyplot as pltimport numpy as npfrom scipy.integrate import. Scatter = plt.scatter(,, animated=True)Īnim = FuncAnimation(fig, func=animate, frames=N, init_func=partial(init, fig, axes, scatter), blit=True, fargs=(sols, scatter, odds, evens), repeat=False) Sols = odeint(van_der_pol, init_conds, t, args=(mu, evens, odds, ones))įig, axes = plt.figure(), plt.axes(frameon=True) ![]() Init_conds = np.array()Įvens, odds = np.array(), np.array() #will be used to extract the x and y coordinates t_offsets(np.array(*evens), np.trim_zeros(sols*odds)])) X_shift = np.roll(x, 1) #for use in computationĭef animate(t, sols, scatter, odds, evens): Any help would be greatly appreciated!įrom matplotlib.animation import FuncAnimationĭef van_der_pol(coords, t, mu, evens, odds, ones): ![]() The output should look like fluid rotating. When I try to animate, however, I get a mess (so I think it has to be in how I’m animating it). I know the computations and data set are right because when I plot each frame individually I get the desired result. Hey, I’ve been at this for a couple hours so hopefully y’all have better luck.
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