def convolved_array_from_array_2d_and_mask(self, array_2d, mask):
"""
Convolve an array with this Kernel
Parameters
----------
image : ndarray
An array representing the image the Kernel is convolved with.
Returns
-------
convolved_image : ndarray
An array representing the image after convolution.
Raises
------
KernelException if either Kernel psf dimension is odd
"""
if self.mask.shape[0] % 2 == 0 or self.mask.shape[1] % 2 == 0:
raise exc.KernelException("Kernel Kernel must be odd")
mask_sub_1 = mask.mapping.mask_sub_1
return mask_sub_1.mapping.array_stored_1d_from_array_2d(
scipy.signal.convolve2d(array_2d, self.in_2d, mode="same"))
def convolved_array_from_array_and_mask(self, array, mask):
"""
Convolve an array with this Kernel2D
Parameters
----------
image : np.ndarray
An array representing the image the Kernel2D is convolved with.
Returns
-------
convolved_image : np.ndarray
An array representing the image after convolution.
Raises
------
KernelException if either Kernel2D psf dimension is odd
"""
if self.mask.shape[0] % 2 == 0 or self.mask.shape[1] % 2 == 0:
raise exc.KernelException("Kernel2D Kernel2D must be odd")
convolved_array_2d = scipy.signal.convolve2d(array,
self.native,
mode="same")
convolved_array_1d = array_2d_util.array_2d_slim_from(
mask_2d=mask, array_2d_native=convolved_array_2d, sub_size=1)
return array_2d.Array2D(array=convolved_array_1d, mask=mask.mask_sub_1)