您可以考慮創(chuàng)建多邊形的集合而不是單個多邊形。

舉個例子：

import numpy as np

import matplotlib.pyplot as plt

from matplotlib.collections import PolyCollection

import matplotlib as mpl

# Generate data. In this case, we'll make a bunch of center-points and generate

# verticies by subtracting random offsets from those center-points

numpoly, numverts = 100, 4

centers = 100 * (np.random.random((numpoly,2)) - 0.5)

offsets = 10 * (np.random.random((numverts,numpoly,2)) - 0.5)

verts = centers + offsets

verts = np.swapaxes(verts, 0, 1)

# In your case, "verts" might be something like:

# verts = zip(zip(lon1, lat1), zip(lon2, lat2), ...)

# If "data" in your case is a numpy array, there are cleaner ways to reorder

# things to suit.

# Color scalar...

# If you have rgb values in your "colorval" array, you could just pass them

# in as "facecolors=colorval" when you create the PolyCollection

z = np.random.random(numpoly) * 500

fig, ax = plt.subplots()

# Make the collection and add it to the plot.

coll = PolyCollection(verts, array=z, cmap=mpl.cm.jet, edgecolors='none')

ax.add_collection(coll)

ax.autoscale_view()

# Add a colorbar for the PolyCollection

fig.colorbar(coll, ax=ax)

plt.show()

HTH，

總結(jié)

以上是生活随笔為你收集整理的python画多边形_python – 使用matplotlib更有效地绘制多边形的全部內(nèi)容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網(wǎng)站內(nèi)容還不錯，歡迎將生活随笔推薦給好友。