Matplotlib - 在极坐标图中绘制一个平滑的圆
问题描述
我真的很喜欢 matplotlib 的极坐标图，并且很想继续使用它(因为无论如何我的数据点都是在极坐标中给出的，而且我的环境是圆形的).
I really like the polar plot of matplotlib and would love to keep working with it (since my data points are given in polar coordinates anyway and my environment is circular).
但是，在情节中，我想在特定点添加给定半径的圆.
However, in the plot, I would like to add circles of given radii at specific points.
通常，我会这样做:
ax = plt.subplot(111)
ax.scatter(data)
circle = plt.Circle((0,0), 0.5)
ax.add_artist(circle)
plt.show()
但是，在极坐标中，我不能使用圆形，因为它采用直角坐标.
However, in polar coordinates, I cannot use circle, since it assumes rectangular coordinates.
我想出的想法是:生成具有恒定径向坐标和 [0, 2PI] 中的角坐标的点数组或完全切换到直角坐标.两种解决方案都不太令人满意 - 使用 matplotlib 可以做得更好吗?
Ideas I have come up with are: generating an array of points with constant radial coordinate and an angular coordinate in [0, 2PI] or completely switching to rectangular coordinates. Both solutions are not really satisfactory - can one do any better with matplotlib?
谢谢！
解决方案
可以设置Circle的transform参数:
%matplotlib inline
import pylab as pl
import numpy as np
N = 100
theta = np.random.rand(N)*np.pi*2
r = np.cos(theta*2) + np.random.randn(N)*0.1
ax = pl.subplot(111, polar=True)
ax.scatter(theta, r)
circle = pl.Circle((0.5, 0.3), 0.2, transform=ax.transData._b, color="red", alpha=0.4)
ax.add_artist(circle)
输出:
或 transform=ax.transProjectionAffine + ax.transAxes 如果您不喜欢使用私有属性.
or transform=ax.transProjectionAffine + ax.transAxes if you don't like using the private attribute.
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