matplotlib & pandas

Python/matplotlab/gallery/mplot3d/trisurf3d_2.md

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+# 多三角三维曲面
+
+使用三角形网格绘制曲面的另外两个示例。
+
+第一个演示使用plot_trisurf的三角形参数，第二个设置Triangulation对象的蒙版并将对象直接传递给plot_trisurf。
+
+![多三角三维曲面示例](https://matplotlib.org/_images/sphx_glr_trisurf3d_2_001.png)
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.tri as mtri
+
+# This import registers the 3D projection, but is otherwise unused.
+from mpl_toolkits.mplot3d import Axes3D  # noqa: F401 unused import
+
+
+fig = plt.figure(figsize=plt.figaspect(0.5))
+
+#============
+# First plot
+#============
+
+# Make a mesh in the space of parameterisation variables u and v
+u = np.linspace(0, 2.0 * np.pi, endpoint=True, num=50)
+v = np.linspace(-0.5, 0.5, endpoint=True, num=10)
+u, v = np.meshgrid(u, v)
+u, v = u.flatten(), v.flatten()
+
+# This is the Mobius mapping, taking a u, v pair and returning an x, y, z
+# triple
+x = (1 + 0.5 * v * np.cos(u / 2.0)) * np.cos(u)
+y = (1 + 0.5 * v * np.cos(u / 2.0)) * np.sin(u)
+z = 0.5 * v * np.sin(u / 2.0)
+
+# Triangulate parameter space to determine the triangles
+tri = mtri.Triangulation(u, v)
+
+# Plot the surface.  The triangles in parameter space determine which x, y, z
+# points are connected by an edge.
+ax = fig.add_subplot(1, 2, 1, projection='3d')
+ax.plot_trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral)
+ax.set_zlim(-1, 1)
+
+
+#============
+# Second plot
+#============
+
+# Make parameter spaces radii and angles.
+n_angles = 36
+n_radii = 8
+min_radius = 0.25
+radii = np.linspace(min_radius, 0.95, n_radii)
+
+angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
+angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
+angles[:, 1::2] += np.pi/n_angles
+
+# Map radius, angle pairs to x, y, z points.
+x = (radii*np.cos(angles)).flatten()
+y = (radii*np.sin(angles)).flatten()
+z = (np.cos(radii)*np.cos(3*angles)).flatten()
+
+# Create the Triangulation; no triangles so Delaunay triangulation created.
+triang = mtri.Triangulation(x, y)
+
+# Mask off unwanted triangles.
+xmid = x[triang.triangles].mean(axis=1)
+ymid = y[triang.triangles].mean(axis=1)
+mask = np.where(xmid**2 + ymid**2 < min_radius**2, 1, 0)
+triang.set_mask(mask)
+
+# Plot the surface.
+ax = fig.add_subplot(1, 2, 2, projection='3d')
+ax.plot_trisurf(triang, z, cmap=plt.cm.CMRmap)
+
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: trisurf3d_2.py](https://matplotlib.org/_downloads/trisurf3d_2.py)
+- [下载Jupyter notebook: trisurf3d_2.ipynb](https://matplotlib.org/_downloads/trisurf3d_2.ipynb)