具有表面梯度的颜色 matplotlib plot_surface 命令 [英] Color matplotlib plot_surface command with surface gradient

问题描述

我想将来自 MATLAB 的 surf 命令转换为 ma​​tplotlib 中的 plot_surface 命令.

I would like to convert surf command from MATLAB to plot_surface command in matplotlib.

我面临的挑战是在 plot_surface 命令中使用 cmap 函数用渐变为表面着色.

The challenge I am facing is when using cmap function in plot_surface command to color the surface with gradient.

这是ma​​tlab脚本

% Matlab Commands
x = -5:.25:5; y = x
[x,y] = meshgrid(x);
R = sqrt(x.^2 + y.^2);
Z = sin(R)
surf(x,y,Z,gradient(Z))

可以在此处找到来自此类命令的图.(http://www.mathworks.com/help/techdoc/visualize/f0-18164.html#f0-46458)

The figure from such a command can be found here. (http://www.mathworks.com/help/techdoc/visualize/f0-18164.html#f0-46458)

这是python scipt当使用 python 和 matplotlib 创建一个类似的函数时，我无法用渐变为表面着色.

Here is the python scipt When using python and matplotlib to create a similar function I am unable to color the surface with a gradient.

# Python-matplotlib Commands
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=gradient(Z), linewidth=0, antialiased=False)
plt.show()

我收到以下错误消息:

Traceback (most recent call last):
  File "<ipython console>", line 1, in <module>
  File "C:Python26libsite-packagesspyderlibwidgetsexternalshellstartup.py", line 122, in runfile
    execfile(filename, glbs)
  File "C:Documents and SettingsmramachaMy DocumentsPythonCandela	mp.py", line 13, in <module>
    surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=gradient(Z), linewidth=0, antialiased=False)
  File "C:Python26libsite-packagesmpl_toolkitsmplot3daxes3d.py", line 729, in plot_surface
    polyc = art3d.Poly3DCollection(polys, *args, **kwargs)
  File "C:Python26libsite-packagesmpl_toolkitsmplot3dart3d.py", line 344, in __init__
    PolyCollection.__init__(self, verts, *args, **kwargs)
  File "C:Python26libsite-packagesmatplotlibcollections.py", line 570, in __init__
    Collection.__init__(self,**kwargs)
  File "C:Python26libsite-packagesmatplotlibcollections.py", line 86, in __init__
    cm.ScalarMappable.__init__(self, norm, cmap)
  File "C:Python26libsite-packagesmatplotlibcm.py", line 155, in __init__
    self.cmap = get_cmap(cmap)
  File "C:Python26libsite-packagesmatplotlibcm.py", line 126, in get_cmap
    if name in cmap_d:
TypeError: unhashable type: 'list'

任何输入都会有所帮助.

Any inputs would be helpful.

普拉布

推荐答案

首先，您似乎想要从渐变幅度映射颜色.您正在尝试使用梯度向量，这就是您收到列表"错误的原因.

First, it looks like you want the colors mapped from gradient magnitude. You are trying to use the gradient vectors which is why you are getting the 'list' error.

其次，您可以提供 cmap，但它仅定义您希望 Z 值如何映射到颜色.如果您想要新的面部颜色，请使用 facecolors论证.

Second, you can supply a cmap, but it only defines how you want the Z values mapped to a color. If you want new face colors then use the facecolors argument.

第三，您需要将值标准化为 0..1，然后通过颜色图映射它们.(我认为还有另一种方法，但是将幅度除以最大值非常简单)

Third, you'll want to normalize the values to 0..1 then map them thru a colormap. (I think there is another way, but dividing the magnitude by the max is pretty simple)

代码如下:

# Python-matplotlib Commands
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, .25)
Y = np.arange(-5, 5, .25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)
Gx, Gy = np.gradient(Z) # gradients with respect to x and y
G = (Gx**2+Gy**2)**.5  # gradient magnitude
N = G/G.max()  # normalize 0..1
surf = ax.plot_surface(
    X, Y, Z, rstride=1, cstride=1,
    facecolors=cm.jet(N),
    linewidth=0, antialiased=False, shade=False)
plt.show()

结果:

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