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我有一个使用 Triangulation/TriInterpolation 和 contourf 生成的等高线图，如下图所示。我还在轮廓的两侧绘制了两条曲线，它们是数据不应经过的边界。如左下角所示，数据溢出左侧线（由于三角剖分试图连接三角形，我敢肯定），我想找到一种方法来使用左侧线来强制上面的所有内容它被屏蔽或剪裁，因为我将添加更多数据，这无疑会做同样的事情。

我尝试通过 matplotlib.patches 和正常掩蔽使用剪辑，但似乎无法弄清楚。

左行的数据如下：

leftx = [0.319,0.373,0.407,0.432,0.452,0.469,0.483,0.495,0.506,0.516,0.525,0.533,0.541,0.548,0.554,0.560,0.566,0.571,0.576,505,0.589,7.554,0.560,0.566,0.571,0.576,505,0.589,7.55,0.589,0.5.5 ,0.600,0.604,0.607,0.610,0.613,0.616]

左撇子 = [0.5,1.0,1.5,2.0,2.5,3.0,3.5,4.0,4.5,5.0,5.5,6.0,6.5,7.0,7.5,8.0,8.5,9.0,9.5,10.0,10.5,11.0,11.5,12.0 ,12.5,13.0,13.5,14.0,14.5,15.0]

三角剖分/轮廓的网格是

xi = np.linspace(0, 1.2, 1000)
yi = np.linspace(0, 15.0, 1000)
Xi, Yi = np.meshgrid(xi, yi)
triang = tri.Triangulation(xdata,ydata)
interpolator = tri.LinearTriInterpolator(triang, zdata)
zi = interpolator(Xi, Yi)

我该怎么做呢？提前谢谢了！:)

等高线图

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1 回答 1

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您可以创建一个类似于这篇文章的 clip_path 。可以使用左曲线和右曲线的反转来创建剪辑形状。

请注意，clip_path 需要添加到绘图中。这是确保所有点都转换为正确轴所必需的。它可以被绘制color='none'以使其不可见。

这是一些测试代码，演示了它如何在您的情况下工作：

import matplotlib.pyplot as plt
from matplotlib import path as mpath
from matplotlib import patches as mpatches
import numpy as np

N = 100
xdata = np.random.uniform(0, 1.2, N)
ydata = np.random.uniform(0, 15, N)
zdata = np.random.uniform(0, 90, N)

leftx = np.array([0.319, 0.373, 0.407, 0.432, 0.452, 0.469, 0.483, 0.495, 0.506, 0.516, 0.525, 0.533, 0.541, 0.548, 0.554, 0.560, 0.566, 0.571, 0.576, 0.580, 0.585, 0.589, 0.593, 0.597, 0.600, 0.604, 0.607, 0.610, 0.613, 0.616])
lefty = np.array([0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0, 11.5, 12.0, 12.5, 13.0, 13.5, 14.0, 14.5, 15.0])
rightx = leftx + 0.6
righty = lefty
vertices = np.vstack([np.concatenate([leftx, rightx[::-1]]), np.concatenate([lefty, righty[::-1]])]).T
poly_codes = [mpath.Path.MOVETO] + (len(vertices) - 1) * [mpath.Path.LINETO]
path = mpath.Path(vertices, poly_codes)
clip_patch = mpatches.PathPatch(path, facecolor='none', edgecolor='none')
plt.gca().add_patch(clip_patch)

cont = plt.tricontourf(xdata, ydata, zdata, levels=10, cmap='hot')
for c in cont.collections:
    c.set_clip_path(clip_patch)

plt.show()

示例图

于 2020-09-07T20:58:11.457 回答