def _test_helper_scale_large_intensities(self, output_format, file_name):
# Arrange
DeleteTableRows(TableWorkspace=self._workspace, Rows=f'1-{self._workspace.getNumberPeaks()-1}') # only first pk
self._workspace.getPeak(0).setIntensity(2.5E8)
# Act
SaveReflections(InputWorkspace=self._workspace, Filename=file_name, Format=output_format)
# Read lines from file to be asserted in individual tests
with open(file_name, 'r') as actual_file:
lines = actual_file.readlines()
return lines
def action_delete_row(self):
selection_model = self.view.selectionModel()
if not selection_model.hasSelection():
show_no_selection_to_copy_toast()
return
selected_rows = selection_model.selectedRows()
selected_rows_list = [index.row() for index in selected_rows]
selected_rows_str = ",".join([str(row) for row in selected_rows_list])
DeleteTableRows(self.model.ws, selected_rows_str)
# Reverse the list so that we delete in order from bottom -> top
# this prevents the row index from shifting up when deleting rows above
for row in reversed(selected_rows_list):
self.view.removeRow(row)
def test_save_fullprof_format_constant_wavelength(self):
# Arrange
# leave only one peak (therefore a single wavelength in table)
DeleteTableRows(TableWorkspace=self._workspace, Rows=f'1-{self._workspace.getNumberPeaks() - 1:.0f}')
file_name = os.path.join(self._test_dir, "test_fullprof_cw.hkl")
output_format = "Fullprof"
# Act
SaveReflections(InputWorkspace=self._workspace, Filename=file_name, Format=output_format)
# Assert
wavelength = 0
with open(file_name, 'r') as file:
file.readline() # skip
file.readline() # skip
wavelength = float(file.readline().lstrip().split(' ')[0])
self.assertAlmostEqual(wavelength, self._workspace.getPeak(0).getWavelength(), delta=1e-4)
def purge_table(workspace: WorkspaceTypes, calibration_table: TableWorkspace,
tubes_fit_success: np.ndarray, output_table: str = None) -> None:
r"""
Remove the detectorID's corresponding to the failing tubes from the calibration table
Assumptions:
- Each tube has PIXELS_PER_TUBE number of pixels
- detector ID's in the calibration table are sorted according to tube number
:param workspace: input Workspace2D containing total neutron counts per pixel
:param calibration_table: input TableWorkspace containing one column for detector ID and one column
for its calibrated Y coordinates, in meters
:param tubes_fit_success: array of booleans of length TUBES_IN_BANK. `False` if a tube was unsuccessfully fitted.
:param output_table: name of the purged table. If `None`, the input `calibration_table` is purged.
"""
# validate input arguments
if False not in tubes_fit_success:
return # nothing to do
# validate the input workspace
message = f'Cannot process workspace {workspace}. Pass the name of an existing workspace or a workspace handle'
assert isinstance(workspace, (str, Workspace2D)), message
workspace_name = str(workspace)
assert AnalysisDataService.doesExist(workspace_name), f'Input workspace {workspace_name} does not exists'
# validate the input calibraton table
message = f'Cannot process table {calibration_table}. Pass the name of an existing TableWorkspace' \
' or a TableWorkspace handle'
assert isinstance(calibration_table, (str, TableWorkspace)), message
assert AnalysisDataService.doesExist(str(calibration_table)), f'Input table {calibration_table} does not exists'
if output_table is not None:
CloneWorkspace(InputWorkspace=calibration_table, OutputWorkspace=output_table)
else:
output_table = str(calibration_table)
tube_fail_indexes = np.where(tubes_fit_success == False)[0] # noqa E712 indexes of tubes unsuccessfully fitted
row_indexes_of_first_tube = np.arange(PIXELS_PER_TUBE) # 0, 1, ... 255
fail_rows = [row_indexes_of_first_tube + (i * PIXELS_PER_TUBE) for i in tube_fail_indexes]
fail_rows = np.array(fail_rows, dtype=int).flatten().tolist()
DeleteTableRows(output_table, fail_rows)
def remove_log_rows(self, row_numbers):
DeleteTableRows(TableWorkspace=self._log_workspaces, Rows=list(row_numbers))
self.update_log_group_name()
def delete_rows(self, selected_rows):
DeleteTableRows(self.ws, selected_rows)
def delete_rows(self, selected_rows):
from mantid.simpleapi import DeleteTableRows
DeleteTableRows(self.ws, selected_rows)
