Source code for nxtomomill.converter.hdf5.acquisition.xrd3dacquisition

# coding: utf-8
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"""
module to define a standard tomography acquisition (made by bliss)
"""

__authors__ = [
    "H. Payno",
    "J. Garriga",
]
__license__ = "MIT"
__date__ = "19/04/2021"


import logging

from nxtomomill.converter.hdf5.acquisition.standardacquisition import (
    StandardAcquisition,
)

_logger = logging.getLogger(__name__)


[docs]class XRD3DAcquisition(StandardAcquisition):
[docs] def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._rocking = None self._n_steps_rotation = [] self._n_steps_rocking = 0
@property def rocking(self): return self._rocking @rocking.setter def rocking(self, rocking): self._rocking = rocking @property def n_steps_rocking(self): return self._n_steps_rocking @n_steps_rocking.setter def n_steps_rocking(self, n_steps_rocking): self._n_steps_rocking = n_steps_rocking @property def n_steps_rotation(self): return self._n_steps_rotation @n_steps_rotation.setter def n_steps_rotation(self, n_steps_rotation): self._n_steps_rotation = n_steps_rotation def _get_rocking_dataset(self, entry, n_frames): for grp in self._get_positioners_node(entry), entry: try: rocking, unit = self._get_node_values_for_frame_array( node=grp, n_frame=n_frames, keys=self.configuration.rocking_keys, info_retrieve="rocking", expected_unit=None, ) except (ValueError, KeyError): pass else: return rocking, None _url_path = self.root_url.path() if self.root_url is not None else "?" mess = f"Unable to find rocking for {_url_path}" if self.raise_error_if_issue: raise ValueError(mess) else: mess += "default value will be set. (0)" _logger.warning(mess) return [0] * n_frames, None def _treate_valid_camera( self, detector_node, entry, frame_type, input_file_path, entry_path, entry_url, ): super()._treate_valid_camera( detector_node=detector_node, entry=entry, frame_type=frame_type, input_file_path=input_file_path, entry_path=entry_path, entry_url=entry_url, ) # store rocking information rocking, _ = self._get_rocking_dataset( entry=entry, n_frames=self._current_scan_n_frame ) self._rocking.extend(rocking) self._n_steps_rocking += 1 self._n_steps_rotation += [self._current_scan_n_frame] def _preprocess_registered_entries(self): self._rocking = [] super()._preprocess_registered_entries() def to_NXtomos(self, request_input, input_callback, check_tomo_n=True) -> tuple: nx_tomo = super().to_NXtomos(request_input, input_callback, check_tomo_n)[0] # define sample information for 3dxrd nx_tomo.sample.rocking = self.rocking nx_tomo.sample.n_steps_rocking = self.n_steps_rocking nx_tomo.sample.n_steps_rotation = self.n_steps_rotation return (nx_tomo,)