Commit 42196fc2 authored by Christian Nemoz's avatar Christian Nemoz Committed by Nicola Vigano
Browse files

Alignment: updated docstring of DetectorTranslationAlongBeam

Signed-off-by: Nicola Vigano's avatarNicola VIGANÒ <>
parent 549d1a86
Pipeline #28338 passed with stages
in 3 minutes and 45 seconds
......@@ -630,9 +630,8 @@ class DetectorTranslationAlongBeam(AlignmentBase):
high_pass: float or sequence of two floats
High-pass filter properties, as described in `nabu.misc.fourier_filters`.
return_shifts: boolean, optional
if a True a list, containing for each given image of the stack a tuple of shifts, will
be return together with the increment per unit-distance.
This slot is intended for introspection.
Adds a third returned argument, containing the pixel shifts of each
image with respect to the first one in the stack. Defaults to False.
use_adjacent_imgs: boolean, optional
Compute correlation between adjacent images.
It can be used when dealing with large shifts, to avoid overflowing the shift.
......@@ -641,15 +640,16 @@ class DetectorTranslationAlongBeam(AlignmentBase):
tuple(float, float)
Estimated (vertical, horizontal) increment per unit-distance of the
ratio between pixel-size and detector translation.
Optionally a tuple containing the shifts per each image are found if optional argument
return_shifts is true
coeff_v: float
Estimated vertical shift in pixel per unit-distance of the detector translation.
coeff_h: float
Estimated horizontal shift in pixel per unit-distance of the detector translation.
shifts_vh: list, optional
The pixel shifts of each image with respect to the first image in the stack.
Activated if return_shifts is True.
The example below builds first a stack of four imagew, each one correspondng to a motor step.
At each step the same feature is shifted by 2.468, 1.234 pixels (vertical, horizontal).
Moreover, to show the filtering option, a spurious low frequency feature is added
......@@ -659,7 +659,6 @@ class DetectorTranslationAlongBeam(AlignmentBase):
second call argument. Here we use a high-pass filter, due to the presence of some low-frequency
noise component.
>>> import numpy as np
... import scipy as sp
... import scipy.ndimage
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