Source code for nabu.preproc.shift
from math import floor
import numpy as np
[docs]
class VerticalShift:
def __init__(self, radios_shape, shifts):
"""
This class is used when a vertical translation (along the tomography
rotation axis) occurred.
These translations are meant "per projection" and can be due either to
mechanical errors, or can be applied purposefully with known motor movements
to smear rings artefacts.
The object is initialised with an array of shifts: one shift for each projection.
A positive shifts means that the axis has moved in the positive Z direction.
The interpolation is done taking for a pixel (y,x) the pixel found at (y+shft,x)
in the recorded images.
The method apply_vertical_shifts performs the correctionson the radios.
Parameters
----------
radios_shape: tuple
Shape of the radios chunk, in the form (n_radios, n_y, n_x)
shifts: sequence of floats
one shift for each projection
Notes
------
During the acquisition, there might be other translations, each of them
orthogonal to the rotation axis.
- A "horizontal" translation in the detector plane: this is handled
directly in the Backprojection operation.
- A translation along the beam direction: this one is of no concern
for parallel-beam geometry
"""
self.radios_shape = radios_shape
self.shifts = shifts
self._init_interp_coefficients()
def _init_interp_coefficients(self):
self.interp_infos = []
for s in self.shifts:
s0 = int(floor(s))
f = s - s0
self.interp_infos.append([s0, f])
def _check(self, radios, iangles):
assert np.min(iangles) >= 0
assert np.max(iangles) < len(self.interp_infos)
assert len(iangles) == radios.shape[0]
[docs]
def apply_vertical_shifts(self, radios, iangles, output=None):
"""
Parameters
----------
radios: a sequence of np.array
The input radios. If the optional parameter is not given, they are modified in-place
iangles: a sequence of integers
Must have the same lenght as radios.
It contains the index at which the shift is found in `self.shifts`
given by `shifts` argument in the initialisation of the object.
output: a sequence of np.array, optional
If given, it will be modified to contain the shifted radios.
Must be of the same shape of `radios`.
"""
self._check(radios, iangles)
newradio = np.zeros_like(radios[0])
for radio, ia in zip(radios, iangles):
newradio[:] = 0
S0, f = self.interp_infos[ia]
s0 = S0
if s0 > 0:
newradio[:-s0] = radio[s0:] * (1 - f)
elif s0 == 0:
newradio[:] = radio[s0:] * (1 - f)
else:
newradio[-s0:] = radio[:s0] * (1 - f)
s0 = S0 + 1
if s0 > 0:
newradio[:-s0] += radio[s0:] * f
elif s0 == 0:
newradio[:] += radio[s0:] * f
else:
newradio[-s0:] += radio[:s0] * f
if output is None:
radios[ia] = newradio
else:
output[ia] = newradio