def get_distances(self):
""" This returns the distance of each neighbor to the pixel """
D = np.zeros((self.N, self.A))
for i in xrange(self.N):
pi = self.flattening.index2cell[i]
for jj in xrange(self.A):
j = self.neighbor_indices_flat[i, jj]
pj = self.flattening.index2cell[j]
dx = pi[0] - pj[0]
dy = pi[1] - pj[1]
dxn = dmod(dx, self.shape[0] / 2)
dyn = dmod(dy, self.shape[1] / 2)
d = np.hypot(dxn, dyn)
D[i, jj] = d
return D
def get_distances(self):
""" This returns the distance of each neighbor to the pixel """
D = np.zeros((self.N, self.A))
for i in xrange(self.N):
pi = self.flattening.index2cell[i]
for jj in xrange(self.A):
j = self.neighbor_indices_flat[i, jj]
pj = self.flattening.index2cell[j]
dx = pi[0] - pj[0]
dy = pi[1] - pj[1]
dxn = dmod(dx, self.shape[0] / 2)
dyn = dmod(dy, self.shape[1] / 2)
d = np.hypot(dxn, dyn)
D[i, jj] = d
return D
def get_distances_to_area_center(self):
"""
This returns the distance of each neighbor to the center
of the area border. This is the same thing as get_distances()
only if the area center is on the nominal pixel.
"""
D = np.zeros((self.N, self.A))
for i in xrange(self.N):
pi = self.flattening.index2cell[i]
area_center = self.get_center_for_cell_area(pi)
js = self.neighbor_indices_flat[i, :]
pjs = self.flattening.index2cell[js]
assert pjs.shape[1] == 2
dx = area_center[0] - pjs[:, 0]
dy = area_center[1] - pjs[:, 1]
dxn = dmod(dx, self.shape[0] / 2)
dyn = dmod(dy, self.shape[1] / 2)
d = np.hypot(dxn, dyn)
D[i, :] = d
return D
def get_distances_to_area_center(self):
"""
This returns the distance of each neighbor to the center
of the area border. This is the same thing as get_distances()
only if the area center is on the nominal pixel.
"""
D = np.zeros((self.N, self.A))
for i in xrange(self.N):
pi = self.flattening.index2cell[i]
area_center = self.get_center_for_cell_area(pi)
js = self.neighbor_indices_flat[i, :]
pjs = self.flattening.index2cell[js]
assert pjs.shape[1] == 2
dx = area_center[0] - pjs[:, 0]
dy = area_center[1] - pjs[:, 1]
dxn = dmod(dx, self.shape[0] / 2)
dyn = dmod(dy, self.shape[1] / 2)
d = np.hypot(dxn, dyn)
D[i, :] = d
return D
