Created
April 30, 2020 01:05
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import numpy as np | |
# from: https://stackoverflow.com/questions/37951631/how-to-find-the-intersection-points-of-a-straight-line-and-a-curve-like-set-of-t | |
A = np.random.random((20, 2)) | |
A[:,0] = np.arange(20) | |
A[:,1] = A[:,1] * (7.5 + A[:,0]) # some kind of wiggly line | |
p0 = [-1.0,-6.5] # point 0 | |
p1 = [22.0, 20.0] # point 1 | |
b = (p1[1] - p0[1]) / (p1[0] - p0[0]) # gradient | |
a = p0[1] - b * p0[0] # intercept | |
B = (a + A[:,0] * b) - A[:,1] # distance of y value from line | |
ix = np.where(B[1:] * B[:-1] < 0)[0] # index of points where the next point is on the other side of the line | |
d_ratio = B[ix] / (B[ix] - B[ix + 1]) # similar triangles work out crossing points | |
cross_points = np.zeros((len(ix), 2)) # empty array for crossing points | |
cross_points[:,0] = A[ix,0] + d_ratio * (A[ix+1,0] - A[ix,0]) # x crossings | |
cross_points[:,1] = A[ix,1] + d_ratio * (A[ix+1,1] - A[ix,1]) # y crossings | |
print(ix, B, A, cross_points) |
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