matplotlib & pandas

Python/matplotlab/gallery/mplot3d/tricontourf3d.md

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+# 三角形三维填充等高线图
+
+非结构化三角形网格的填充等高线图。
+
+使用的数据与trisurf3d_demo2的第二个图中的数据相同。 tricontour3d_demo显示此示例的未填充版本。
+
+![三角形三维填充等高线图示例](https://matplotlib.org/_images/sphx_glr_tricontourf3d_001.png)
+
+```python
+# This import registers the 3D projection, but is otherwise unused.
+from mpl_toolkits.mplot3d import Axes3D  # noqa: F401 unused import
+
+import matplotlib.pyplot as plt
+import matplotlib.tri as tri
+import numpy as np
+
+# First create the x, y, z coordinates of the points.
+n_angles = 48
+n_radii = 8
+min_radius = 0.25
+
+# Create the mesh in polar coordinates and compute x, y, z.
+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
+
+x = (radii*np.cos(angles)).flatten()
+y = (radii*np.sin(angles)).flatten()
+z = (np.cos(radii)*np.cos(3*angles)).flatten()
+
+# Create a custom triangulation.
+triang = tri.Triangulation(x, y)
+
+# Mask off unwanted triangles.
+triang.set_mask(np.hypot(x[triang.triangles].mean(axis=1),
+                         y[triang.triangles].mean(axis=1))
+                < min_radius)
+
+fig = plt.figure()
+ax = fig.gca(projection='3d')
+ax.tricontourf(triang, z, cmap=plt.cm.CMRmap)
+
+# Customize the view angle so it's easier to understand the plot.
+ax.view_init(elev=45.)
+
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: tricontourf3d.py](https://matplotlib.org/_downloads/tricontourf3d.py)
+- [下载Jupyter notebook: tricontourf3d.ipynb](https://matplotlib.org/_downloads/tricontourf3d.ipynb)