prysm.convolution¶
Recipes for numerical convolution.
- prysm.convolution.conv(obj, psf)¶
Convolve an object and psf.
- Parameters
obj (numpy.ndarray) – array representing the object, of shape (M, N)
psf (numpy.ndarray) – array representing the psf, of shape (M, N)
- Returns
ndarray after undergoing convolution
- Return type
numpy.ndarray
- prysm.convolution.apply_transfer_functions(obj, dx, tfs, fx=None, fy=None, ft=None, fr=None, shift=False)¶
Blur an object by N transfer functions.
- Parameters
obj (numpy.ndarray) – array representing the object, of shape (M, N)
dx (float) – sample spacing of the object. Ignored if fx, etc are defined.
tfs (sequence of callables, or arrays) – transfer functions. If a callable, should be functions which take arguments of any of fx, fy, ft, fr. Use functools partial or class methods to curry other parameters
fx (numpy.ndarray) –
- arrays defining the frequency domain, of shape (M, N)
cartesian X frequency cartesian Y frequency azimuthal frequency radial frequency
The latter two are simply the atan2 of the former two.
fy (numpy.ndarray) –
- arrays defining the frequency domain, of shape (M, N)
cartesian X frequency cartesian Y frequency azimuthal frequency radial frequency
The latter two are simply the atan2 of the former two.
ft (numpy.ndarray) –
- arrays defining the frequency domain, of shape (M, N)
cartesian X frequency cartesian Y frequency azimuthal frequency radial frequency
The latter two are simply the atan2 of the former two.
fr (numpy.ndarray) –
- arrays defining the frequency domain, of shape (M, N)
cartesian X frequency cartesian Y frequency azimuthal frequency radial frequency
The latter two are simply the atan2 of the former two.
shift (bool, optional) – if True, fx, fy, ft, fr are assumed to have the origin in the center of the array, and tfs are expected to be consistent with that. If False, the origin is assumed to be the [0,0]th sample of fr, fx, fy.
- Returns
image after being blurred by each transfer function
- Return type
numpy.ndarray