正如@unutbu和@Martin Valgur的评论所示,我认为shapely是最好的选择。这个问题可能与之前的一个问题有些冗余,但下面是一段干净的代码片段,应该可以满足您的需求。
策略是首先创建您各种形状(矩形)的并集,然后绘制该并集。这样,您就将不同的形状“平铺”成一个单一的形状,因此在重叠区域中没有alpha问题。
import shapely.geometry as sg
import shapely.ops as so
import matplotlib.pyplot as plt
#constructing the first rect as a polygon
r1 = sg.Polygon([(0,0),(0,1),(1,1),(1,0),(0,0)])
#a shortcut for constructing a rectangular polygon
r2 = sg.box(0.5,0.5,1.5,1.5)
#cascaded union can work on a list of shapes
new_shape = so.cascaded_union([r1,r2])
#exterior coordinates split into two arrays, xs and ys
# which is how matplotlib will need for plotting
xs, ys = new_shape.exterior.xy
#plot it
fig, axs = plt.subplots()
axs.fill(xs, ys, alpha=0.5, fc='r', ec='none')
plt.show() #if not interactive