How to generate an animation composed of several plots in python?

Question

I'm having trouble plotting an animation with python. What I want to do is basically an animation that contains the superposition of many complete plots. In such a way that each frame will be a plot given by

plt.plot(r, Sevol[n])

The code and error displayed on the screen are below. Thanks for any help.

UserWarning: Animation was deleted without rendering anything. This is most likely not intended. To prevent deletion, assign the Animation to a variable, e.g. anim, that exists until you have outputted the Animation using plt.show() or anim.save().

import numpy as np import math import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation nr = 300 ri = 0 rf = 300 dr = (rf - ri) / (nr - 1) nt = 1000 dt = 0.1 r = np.linspace(ri, rf, num=nr) def rk3_step(t, h, y, f, *args): k1 = h * f(t , y , *args) k2 = h * f(t + h/2, y + 1/2 * k1 , *args) k3 = h * f(t + h , y - k1 + 2 * k2, *args) return y + 1/6*(k1 + 4*k2 + k3) def rhs_perturb(t, u): S = u.T[0] S_dot = u.T[1] F = u.T[2] F_dot = u.T[3] rhs = np.empty((nr, 4)) rhs[0] = np.array([S_dot[0], (S[2] - 2 * S[1] + S[0]) / (dr ** 2), # + F[0], F_dot[0], - S[0] + (F[2] - 2 * F[1] + F[0]) / (dr ** 2)]) rhs[-1] = np.array([S_dot[-1], (S[-1] - 2 * S[-2] + S[-3]) / (dr ** 2), # + F[-1], F_dot[-1], - S[-1] + (F[-1] - 2 * F[-2] + F[-3]) / (dr ** 2)]) for i in range(1, nr - 1): rhs[i] = np.array([S_dot[i], (S[i + 1] - 2 * S[i] + S[i - 1]) / (dr ** 2), # + F[i], F_dot[i], - S[i] + (F[i + 1] - 2 * F[i] + F[i - 1]) / (dr ** 2)]) return rhs sigma = 3 r0 = 100 F = np.empty(nr) F_dot = np.empty(nr) S = np.empty(nr) S_dot = np.empty(nr) for i in range(nr): F[i] = 0 F_dot[i] = 0 S_dot[i] = 0 S[i] = math.exp(-(r[i] - r0)**2 / sigma**2) uin = np.block([[S], [S_dot], [F], [F_dot]]).T u = np.copy(uin) uaux = np.copy(uin) nsave = 10 Sevol = np.empty((math.floor(nt/nsave),nr)) Sevol[0] = S Fevol = np.empty((math.floor(nt/nsave),nr)) Fevol[0] = F for n in range(nt): uaux = rk3_step(n * dt, dt, u, rhs_perturb) if np.any(np.isnan(uaux)): break u = uaux if (n + 1) % nsave == 0: Sevol[math.floor(n / nsave)] = u.T[0] Fevol[math.floor(n / nsave)] = u.T[2] fig = plt.figure() plt.xlabel('r') plt.xlabel('S') plt.grid() plt.xlim(ri, rf) def animate(i): numPlots = i //10 # how many plots (-1) will be shown based on the frame. for n in range(numPlots): plt.plot(r[n], Sevol[n], color='gold', markersize=3) ani = FuncAnimation(fig, animate, frames=100, interval=10, blit = False, repeat = False) plt.close() plt.show()

does it work if you don't call plt.close() before plt.show()? — Michael Delgado
– Michael Delgado, Commented Sep 20, 2022 at 23:49
Yes, but the previous plot does not disappear. And then there are several plots together and the image is confused. I wanted the next one to "erase" the previous one — User8563
– User8563, Commented Sep 21, 2022 at 0:14
I see. yeah you need to plot using the same axis object, not using plt.plot. I think you need to essentially grab the objects in the figure/axis and either clear or manipulate them. matplotlib's animation tools are super confusing to me tbh but I know you can't just create a ton of figures. — Michael Delgado
– Michael Delgado, Commented Sep 21, 2022 at 0:14

jylls · Accepted Answer · 2022-09-21 21:28:11Z

I would suggest initializing your animations with a list of empty placeholders plots. In your case, it looks like you need 100 plots. And then update the data for plot i at each frame with the actual values.

Below is what the animation code looks like:

import numpy as np import math import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation, PillowWriter N_plots=100 fig,ax = plt.subplots() color = plt.cm.viridis(np.linspace(0, 1, N_plots)) lns=[ax.plot([],[],color=color[i]) for i in range(N_plots)] lns=[lns[i][0] for i in range(N_plots)] plt.xlabel('r') plt.ylabel('S') plt.grid() plt.xlim(ri, rf) plt.ylim(-0.25, 1) def animate(i): lns[i].set_data(r,Sevol[i]) return lns ani = FuncAnimation(fig, animate, frames=N_plots, interval=100)

And the output gives:

EDIT:

Note that if instead of superimposing the curves you just want to replace them by the next, you can simply use set_data to update your one plot. See code below:

import numpy as np import math import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation, PillowWriter N_plots=100 fig,ax = plt.subplots() color = plt.cm.viridis(np.linspace(0, 1, N_plots)) ln,=ax.plot([],[]) plt.xlabel('r') plt.ylabel('S') plt.grid() plt.xlim(ri, rf) plt.ylim(-0.25, 1) def animate(i): ln.set_data(r,Sevol[i]) ln.set_color(color[i]) return ln ani = FuncAnimation(fig, animate, frames=N_plots, interval=100)

And the output gives:

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