从python中的圆圈中获取数据-Takedatafromacircleinpython

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I made a different input image to help verifying correctness:

我制作了一个不同的输入图像来帮助验证正确性:

import numpy as np
import scipy as sp
import scipy.interpolate
import matplotlib.pyplot as plt

# Mock up an image.
W = 100
x = np.arange(W)
y = np.arange(W)
xx,yy = np.meshgrid(x,y)

image = xx//5*5 + yy//5*5
image = image / np.max(image)  # scale into [0,1]

plt.imshow(image, interpolation='nearest', cmap='gray')
plt.show()

To sample values from circular paths in the image, we first build an interpolator because we want to access arbitrary locations. We also vectorize it to be faster.
Then, we generate the coordinates of N points on the circle's circumference using the parametric definition of the circle x(t) = sin(t), y(t) = cos(t).
N should be at least twice the circumference (Nyquist–Shannon sampling theorem).

要从图像中的圆形路径中采样值,我们首先构建插值器,因为我们想要访问任意位置。我们还将它矢量化为更快。然后,我们使用圆x(t)= sin(t),y(t)= cos(t)的参数定义在圆周上生成N个点的坐标。 N应该至少是圆周的两倍(奈奎斯特 - 香农采样定理)。

interp = sp.interpolate.interp2d(x, y, image)
vinterp = np.vectorize(interp)

for r in (15, 30, 45):    # radii for circles around image's center
    xcenter = len(x)/2
    ycenter = len(y)/2
    arclen = 2*np.pi*r
    angle = np.linspace(0, 2*np.pi, arclen*2, endpoint=False)
    value = vinterp(xcenter + r*np.sin(angle),
                    ycenter + r*np.cos(angle))
    plt.plot(angle, value, label='r={}'.format(r))

plt.legend()
plt.show()