如何通过Python获取3D彩色表面?

问题描述

如何通过Matplotlib获得以下表面?

How to obtain the following surface via Matplotlib?

通过以下方式在matlab中很容易

It is easy in matlab via:

mesh(peaks)

在matlab中，matplotlib似乎没有与mesh完全相同的副本.Wireframe plots没有任何colormap选项

It seems matplotlib does not have an exact counterpart of mesh in matlab.the Wireframe plots does not have any colormap option

推荐答案

使用matplotlib似乎是可能的，即使有点麻烦:

It seems to be possible with matplotlib even if it is a bit of a hack:

from mpl_toolkits.mplot3d import axes3d
from mpl_toolkits.mplot3d import art3d
import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
wire = ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)

# Retrive data from internal storage of plot_wireframe, then delete it
nx, ny, _  = np.shape(wire._segments3d)
wire_x = np.array(wire._segments3d)[:, :, 0].ravel()
wire_y = np.array(wire._segments3d)[:, :, 1].ravel()
wire_z = np.array(wire._segments3d)[:, :, 2].ravel()
wire.remove()

# create data for a LineCollection
wire_x1 = np.vstack([wire_x, np.roll(wire_x, 1)])
wire_y1 = np.vstack([wire_y, np.roll(wire_y, 1)])
wire_z1 = np.vstack([wire_z, np.roll(wire_z, 1)])
to_delete = np.arange(0, nx*ny, ny)
wire_x1 = np.delete(wire_x1, to_delete, axis=1)
wire_y1 = np.delete(wire_y1, to_delete, axis=1)
wire_z1 = np.delete(wire_z1, to_delete, axis=1)
scalars = np.delete(wire_z, to_delete)

segs = [list(zip(xl, yl, zl)) for xl, yl, zl in \
                 zip(wire_x1.T, wire_y1.T, wire_z1.T)]

# Plots the wireframe by a  a line3DCollection
my_wire = art3d.Line3DCollection(segs, cmap="hsv")
my_wire.set_array(scalars)
ax.add_collection(my_wire)

plt.colorbar(my_wire)
plt.show()

这篇关于如何通过Python获取3D彩色表面?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！