我想制作一個函式的曲面圖，該函式在引數空間中的某些值處不連續。在這些不連續點附近，繪圖的顏色會變得不正確，如下圖所示。我怎樣才能解決這個問題？
我的代碼如下：
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
def phase(mu_a, mu_b, t, gamma):
theta = 0.5*np.arctan2(2*gamma, mu_b-mu_a)
epsilon = 2*gamma**2/np.sqrt((mu_a-mu_b)**2 4*gamma**2)
y1 = np.arccos(0.5/t*(-mu_a*np.sin(theta)**2 -mu_b*np.cos(theta)**2 - epsilon))
y2 = np.arccos(0.5/t*(-mu_a*np.cos(theta)**2 -mu_b*np.sin(theta)**2 epsilon))
return y1 y2
fig = plt.figure()
ax = fig.gca(projection='3d')
# Make data.
X = np.arange(-2.5, 2.5, 0.01)
Y = np.arange(-2.5, 2.5, 0.01)
X, Y = np.meshgrid(X, Y)
Z = phase(X, Y, 1, 0.6)
# Plot the surface.
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm, linewidth=0, antialiased=False)
surf.set_clim(1, 5)
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()
uj5u.com熱心網友回復：
一個想法是使所有陣列一維，過濾掉 NaN 值，然后呼叫ax.plot_trisurf：
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
def phase(mu_a, mu_b, t, gamma):
theta = 0.5 * np.arctan2(2 * gamma, mu_b - mu_a)
epsilon = 2 * gamma ** 2 / np.sqrt((mu_a - mu_b) ** 2 4 * gamma ** 2)
with np.errstate(divide='ignore', invalid='ignore'):
y1 = np.arccos(0.5 / t * (-mu_a * np.sin(theta) ** 2 - mu_b * np.cos(theta) ** 2 - epsilon))
y2 = np.arccos(0.5 / t * (-mu_a * np.cos(theta) ** 2 - mu_b * np.sin(theta) ** 2 epsilon))
return y1 y2
fig = plt.figure()
ax = fig.add_subplot(projection='3d')
# Make data.
X = np.linspace(-2.5, 2.5, 200)
Y = np.linspace(-2.5, 2.5, 200)
X, Y = np.meshgrid(X, Y)
X = X.ravel() # make the array 1D
Y = Y.ravel()
Z = phase(X, Y, 1, 0.6)
mask = ~np.isnan(Z) # select the indices of the valid values
# Plot the surface.
surf = ax.plot_trisurf(X[mask], Y[mask], Z[mask], cmap=cm.coolwarm, linewidth=0, antialiased=False)
surf.set_clim(1, 5)
fig.colorbar(surf, shrink=0.5, aspect=5)
plt.show()
一些備注：
plot_trisurf將通過三角形連接 XY 值；這僅在域是凸的情況下才有效- to make things draw quicker, less points could be used (the original used 500x500 points, the code here reduces that to 200x200
- calling
fig.gca(projection='3d')has been deprecated; instead, you could callfig.add_subplot(projection='3d') - the warnings for dividing by zero or using arccos out of range can be temporarily suppressed; that way the warning will still be visible for situations when such isn't expected behavior
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標籤：Python matplotlib 阴谋 表面
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