Question

我正试图在mplot3d表面下获得一个漂亮的contourf图。我希望它出现在3d轴立方体的地板上，与我的数据下限有一点偏移。现在我正在做这样的事情：

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

N = 50

fig = plt.figure()
ax = fig.gca(projection='3d')

surface = np.zeros((N,N))

# gaussian
for x in np.arange(N, dtype=float):
    for y in np.arange(N, dtype=float):
        sigma = 0.2
        xn = (x - N/2)/N
        yn = (y - N/2)/N
        r = np.sqrt(xn**2.0 + yn**2.0)
        surface[x,y] = np.exp((-r**2.0)/(2.0*sigma**2.0))

# mesh grid NxN points in [0,1]
gx, gy = np.meshgrid(np.linspace(0,1,N),np.linspace(0,1,N))

ax.plot_surface(gx, gy, surface, rstride=2, cstride=2, cmap=mpl.cm.Spectral)

# extend z axis limit to make room for contourf
ax.set_zlim3d(np.min(surface) - 0.5, np.max(surface))

# contour on the floor
levels = np.linspace(np.min(surface), np.max(surface), 20)
ax.contourf(gx, gy, surface, levels=levels,
            offset=(np.min(surface) - 0.5), cmap=mpl.cm.Spectral)

That plots this image

这看起来不错，但它添加了几个刻度，我在最小数据下扩展了zaxis。我不想在最小值下显示任何刻度，但仍然延伸zaxis以抵消contourf图。

有什么想法吗？如何在所有红色圆圈刻度中隐藏或不绘制？

Answer 1

这比我想象的容易，非常感谢@gboffi指出我正确的apis。

s_min = np.min(surface)
s_max = np.max(surface)

# filter out extra ticks that exceed data limits
ax.set_zticks(filter(lambda x: s_min <= x <= s_max, ax.get_zticks()))

mplot3d：contourf offset，limits和ticks

1 个答案: