def map_coordinates(image, coords, **kwargs):
# In the built-in scipy map_coordinates, the values are defined at the
# center of the pixels. This means that map_coordinates does not
# correctly treat pixels that are in the outer half of the outer pixels.
# We solve this by extending the array, updating the pixel coordinates,
# then getting rid of values that were sampled in the range -1 to -0.5
# and n to n - 0.5.
from scipy.ndimage import map_coordinates as scipy_map_coordinates
original_shape = image.shape
image = pad_edge_1(image)
values = scipy_map_coordinates(image, coords + 1, **kwargs)
reset = np.zeros(coords.shape[1], dtype=bool)
for i in range(coords.shape[0]):
reset |= (coords[i] < -0.5)
reset |= (coords[i] > original_shape[i] - 0.5)
values[reset] = kwargs.get('cval', 0.)
return values
def map_coordinates(image, coords, **kwargs):
# In the built-in scipy map_coordinates, the values are defined at the
# center of the pixels. This means that map_coordinates does not
# correctly treat pixels that are in the outer half of the outer pixels.
# We solve this by extending the array, updating the pixel coordinates,
# then getting rid of values that were sampled in the range -1 to -0.5
# and n to n - 0.5.
from scipy.ndimage import map_coordinates as scipy_map_coordinates
ny, nx = image.shape
image = pad_edge_1(image)
values = scipy_map_coordinates(image, coords + 1, **kwargs)
reset = ((coords[0] < -0.5) | (coords[0] > ny - 0.5) | (coords[1] < -0.5) |
(coords[1] > nx - 0.5))
values[reset] = kwargs.get('cval', 0.)
return values
def map_coordinates(image, coords, **kwargs):
# In the built-in scipy map_coordinates, the values are defined at the
# center of the pixels. This means that map_coordinates does not
# correctly treat pixels that are in the outer half of the outer pixels.
# We solve this by extending the array, updating the pixel coordinates,
# then getting rid of values that were sampled in the range -1 to -0.5
# and n to n - 0.5.
from scipy.ndimage import map_coordinates as scipy_map_coordinates
ny, nx = image.shape
image = pad_edge_1(image)
values = scipy_map_coordinates(image, coords + 1, **kwargs)
reset = ((coords[0] < -0.5) | (coords[0] > nx - 0.5) |
(coords[1] < -0.5) | (coords[1] > ny - 0.5))
values[reset] = kwargs.get('cval', 0.)
return values
def map_coordinates(image, coords, **kwargs):
# In the built-in scipy map_coordinates, the values are defined at the
# center of the pixels. This means that map_coordinates does not
# correctly treat pixels that are in the outer half of the outer pixels.
# We solve this by extending the array, updating the pixel coordinates,
# then getting rid of values that were sampled in the range -1 to -0.5
# and n to n - 0.5.
from scipy.ndimage import map_coordinates as scipy_map_coordinates
image = pad_edge_1(image)
values = scipy_map_coordinates(image, coords + 1, **kwargs)
reset = np.zeros(coords.shape[1], dtype=bool)
for i in range(coords.shape[0]):
reset |= (coords[i] < -0.5)
reset |= (coords[i] > image.shape[i] - 0.5)
values[reset] = kwargs.get('cval', 0.)
return values
