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