Inverse.py 文件源码

def find_intersections(A,B):
  arrayMinimum = lambda x1, x2: np.where(x1<x2, x1, x2)
  arrayMaximum = lambda x1, x2: np.where(x1>x2, x1, x2)
  arrayAll = lambda abools: np.dstack(abools).all(axis=2)
  slope = lambda line: (lambda d: d[:,1]/d[:,0])(np.diff(line, axis=0))

  x11, x21 = np.meshgrid(A[:-1, 0], B[:-1, 0])
  x12, x22 = np.meshgrid(A[1:, 0], B[1:, 0])
  y11, y21 = np.meshgrid(A[:-1, 1], B[:-1, 1])
  y12, y22 = np.meshgrid(A[1:, 1], B[1:, 1])

  m1, m2 = np.meshgrid(slope(A), slope(B))
  # Here we use masked arrays to properly treat the rare case where a line segment is perfectly vertical
  _m1 = np.ma.masked_array(m1,m1==-np.inf)
  _m2 = np.ma.masked_array(m2,m2==-np.inf)
  yi = (_m1*(x21-x11-y21/_m2)+y11)/(1-_m1/_m2)
  xi = (yi-y21)/_m2+x21

  xconds = (arrayMinimum(x11, x12) < xi, xi <= arrayMaximum(x11, x12),
            arrayMinimum(x21, x22) < xi, xi <= arrayMaximum(x21, x22) )
  yconds = (arrayMinimum(y11, y12) < yi, yi <= arrayMaximum(y11, y12),
            arrayMinimum(y21, y22) < yi, yi <= arrayMaximum(y21, y22) )

  return xi[arrayAll(xconds)], yi[arrayAll(yconds)]