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@retifrav
Created September 3, 2020 10:07
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Python matplotlib animation issue on Mac OS
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import math
# define x coordinates
x0, x1 = 0, 1
n = 500
x = np.linspace(x0, x1, n)
dx = x[1] - x[0]
# define time coordinates
t0, t1 = 0, 1
m = 500
t = np.linspace(t0, t1, m)
dt = t[1] - t[0]
# define velocity
uleft, uright = 1.0, 1.0
c = np.linspace(uleft, uright, x.shape[0])
# calculate stability
stab = np.amax(c) * dt / dx
print(f"stability r: {stab}")
# position in x
xs = 0.5
# width of the wavelet
rick = 0.1
xxsq = np.square((x - xs) / rick)
r = (1 - 12 * np.pi * xxsq) * np.exp(-6 * np.pi * xxsq)
# define two subplots
fig, ax = plt.subplots(2)
# plot ricker wavelet
ax[0].plot(x,r)
ax[0].set(
xlabel="x",
ylabel="displacement",
title="initial displacement, Ricker wavelet",
ylim=[-1.0, 1.0]
)
# initial displacement
u0 = r
# make sure boundary conditions are fulfilled
u0[0], u0[-1] = 0, 0
# initial velocity
ut0 = np.zeros(n)
# estimate second space derivative at t = 0
uxx0 = np.concatenate((u0, np.zeros(2))) \
- 2 * np.concatenate((np.zeros(1), u0, np.zeros(1))) \
+ np.concatenate((np.zeros(2), u0))
# estimate the first time step
u1 = u0 + dt * ut0 + dt * dt / 2 / dx / dx * c * c * uxx0[1:-1]
# initialize u with zeros
u = np.zeros(n)
# define matrix to make all spatial derivatives at once
A = np.diag(2 * np.ones(n - 2)) \
+ np.diag(-np.ones(n - 3), -1) \
+ np.diag(-np.ones(n - 3), 1)
A = dt * dt / dx / dx * A
# the free inner points where no boundary conditions are prescribed
free = np.linspace(1, n - 2, n - 2, dtype="int")
# velocity squared
c2 = c * c
c2 = c2[free]
# time loop
tmp0 = u0[free] # first time step
tmp1 = u1[free] # second time step
#prepare the subplot for the displacement
ax[1].set(
ylim=(-1.0, 1.0),
xlabel="x",
ylabel="displacement",
title="explicit fd solution of 1d wave eqn"
)
def animate(it):
global tmp0, tmp1
# predict u in the next time step
u[free] = 2 * tmp1 - tmp0 - c2 * np.dot(A, tmp1)
# update the previous time steps
tmp0 = tmp1
tmp1 = u[free]
line, = ax[1].plot(x, u)
return line,
# total time of animation in ms
totaltime = 1000
tint = totaltime / m
ani = animation.FuncAnimation(
fig,
animate,
np.arange(m),
interval=tint,
blit=True,
repeat=False
)
plt.show()
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