def _process_trans_fit(self, command):
def fit_type_to_data_type(fit_type_to_convert):
return DataType.CAN if fit_type_to_convert is FitData.Can else DataType.SAMPLE
fit_data = command.values[0]
wavelength_low = command.values[1]
wavelength_high = command.values[2]
fit_type = command.values[3]
polynomial_order = command.values[4]
if fit_data is FitData.Both:
data_to_fit = [FitData.Sample, FitData.Can]
else:
data_to_fit = [fit_data]
new_state_entries = {}
for element in data_to_fit:
data_type = fit_type_to_data_type(element)
new_state_entries.update({
FitId.GENERAL:
fit_general(start=wavelength_low,
stop=wavelength_high,
fit_type=fit_type,
data_type=data_type,
polynomial_order=polynomial_order)
})
self.add_to_processed_state_settings(new_state_entries)
def _set_transmission_fit(self, data_type, start=None, stop=None, fit_type=None, polynomial_order=None):
if FitId.GENERAL in self._user_file_items:
# Gather all settings which correspond to the data type and where the data type is none
settings = self._user_file_items[FitId.GENERAL]
settings_general = [setting for setting in settings if setting.data_type is None]
settings_for_data_type = [setting for setting in settings if setting.data_type is data_type]
# We check if there are data-type specific settings.
# 1. There are data type specific settings. Then we are good.
# 2. There are no data type specific settings. We create one data type specific setting and populate it
# with a general setting if it exists else we create a new entry
if not settings_for_data_type:
if settings_general:
setting_general = settings_general[-1]
settings.append(fit_general(start=setting_general.start, stop=setting_general.stop,
data_type=data_type, fit_type=setting_general.fit_type,
polynomial_order=setting_general.polynomial_order))
else:
settings.append(fit_general(start=None, stop=None, data_type=data_type,
fit_type=FitType.NO_FIT, polynomial_order=2))
else:
settings = [fit_general(start=None, stop=None, data_type=data_type,
fit_type=FitType.NO_FIT, polynomial_order=2)]
new_settings = []
for setting in settings:
# We only want to modify the settings which are either the data type specific ones or the ones which
# don't have a specific data type
if setting.data_type is data_type and setting.data_type is not None:
new_start = start if start is not None else setting.start
new_stop = stop if stop is not None else setting.stop
new_fit_type = fit_type if fit_type is not None else setting.fit_type
new_polynomial_order = polynomial_order if polynomial_order is not None else setting.polynomial_order
new_settings.append(fit_general(start=new_start, stop=new_stop, fit_type=new_fit_type,
data_type=setting.data_type, polynomial_order=new_polynomial_order))
else:
new_settings.append(setting)
self._user_file_items.update({FitId.GENERAL: new_settings})
def _set_transmission_fit(self, data_type, start=None, stop=None, fit_type=None, polynomial_order=None):
if FitId.general in self._user_file_items:
# Gather all settings which correspond to the data type and where the data type is none
settings = self._user_file_items[FitId.general]
settings_general = [setting for setting in settings if setting.data_type is None]
settings_for_data_type = [setting for setting in settings if setting.data_type is data_type]
# We check if there are data-type specific settings.
# 1. There are data type specific settings. Then we are good.
# 2. There are no data type specific settings. We create one data type specific setting and populate it
# with a general setting if it exists else we create a new entry
if not settings_for_data_type:
if settings_general:
setting_general = settings_general[-1]
settings.append(fit_general(start=setting_general.start, stop=setting_general.stop,
data_type=data_type, fit_type=setting_general.fit_type,
polynomial_order=setting_general.polynomial_order))
else:
settings.append(fit_general(start=None, stop=None, data_type=data_type,
fit_type=FitType.NoFit, polynomial_order=2))
else:
settings = [fit_general(start=None, stop=None, data_type=data_type,
fit_type=FitType.NoFit, polynomial_order=2)]
new_settings = []
for setting in settings:
# We only want to modify the settings which are either the data type specific ones or the ones which
# don't have a specific data type
if setting.data_type is data_type and setting.data_type is not None:
new_start = start if start is not None else setting.start
new_stop = stop if stop is not None else setting.stop
new_fit_type = fit_type if fit_type is not None else setting.fit_type
new_polynomial_order = polynomial_order if polynomial_order is not None else setting.polynomial_order
new_settings.append(fit_general(start=new_start, stop=new_stop, fit_type=new_fit_type,
data_type=setting.data_type, polynomial_order=new_polynomial_order))
else:
new_settings.append(setting)
self._user_file_items.update({FitId.general: new_settings})
def _process_trans_fit(self, command):
def fit_type_to_data_type(fit_type_to_convert):
return DataType.Can if fit_type_to_convert is FitData.Can else DataType.Sample
fit_data = command.values[0]
wavelength_low = command.values[1]
wavelength_high = command.values[2]
fit_type = command.values[3]
polynomial_order = command.values[4]
if fit_data is FitData.Both:
data_to_fit = [FitData.Sample, FitData.Can]
else:
data_to_fit = [fit_data]
new_state_entries = {}
for element in data_to_fit:
data_type = fit_type_to_data_type(element)
new_state_entries.update({FitId.general: fit_general(start=wavelength_low, stop=wavelength_high,
fit_type=fit_type, data_type=data_type,
polynomial_order=polynomial_order)})
self.add_to_processed_state_settings(new_state_entries)
def test_that_can_read_user_file(self):
# Arrange
user_file_path = create_user_file(sample_user_file)
reader = UserFileReader(user_file_path)
# Act
output = reader.read_user_file()
# Assert
expected_values = {LimitsId.wavelength: [simple_range(start=1.5, stop=12.5, step=0.125,
step_type=RangeStepType.Lin)],
LimitsId.q: [q_rebin_values(min=.001, max=.2, rebin_string="0.001,0.001,0.0126,-0.08,0.2")],
LimitsId.qxy: [simple_range(0, 0.05, 0.001, RangeStepType.Lin)],
BackId.single_monitors: [back_single_monitor_entry(1, 35000, 65000),
back_single_monitor_entry(2, 85000, 98000)],
DetectorId.reduction_mode: [ISISReductionMode.LAB],
GravityId.on_off: [True],
FitId.general: [fit_general(start=1.5, stop=12.5, fit_type=FitType.Logarithmic,
data_type=None, polynomial_order=0)],
MaskId.vertical_single_strip_mask: [single_entry_with_detector(191, DetectorType.LAB),
single_entry_with_detector(191, DetectorType.HAB),
single_entry_with_detector(0, DetectorType.LAB),
single_entry_with_detector(0, DetectorType.HAB)],
MaskId.horizontal_single_strip_mask: [single_entry_with_detector(0, DetectorType.LAB),
single_entry_with_detector(0, DetectorType.HAB)],
MaskId.horizontal_range_strip_mask: [range_entry_with_detector(190, 191, DetectorType.LAB),
range_entry_with_detector(167, 172, DetectorType.LAB),
range_entry_with_detector(190, 191, DetectorType.HAB),
range_entry_with_detector(156, 159, DetectorType.HAB)
],
MaskId.time: [range_entry_with_detector(17500, 22000, None)],
MonId.direct: [monitor_file("DIRECTM1_15785_12m_31Oct12_v12.dat", DetectorType.LAB),
monitor_file("DIRECTM1_15785_12m_31Oct12_v12.dat", DetectorType.HAB)],
MonId.spectrum: [monitor_spectrum(1, True, True), monitor_spectrum(1, False, True)],
SetId.centre: [position_entry(155.45, -169.6, DetectorType.LAB)],
SetId.scales: [set_scales_entry(0.074, 1.0, 1.0, 1.0, 1.0)],
SampleId.offset: [53.0],
DetectorId.correction_x: [single_entry_with_detector(-16.0, DetectorType.LAB),
single_entry_with_detector(-44.0, DetectorType.HAB)],
DetectorId.correction_y: [single_entry_with_detector(-20.0, DetectorType.HAB)],
DetectorId.correction_z: [single_entry_with_detector(47.0, DetectorType.LAB),
single_entry_with_detector(47.0, DetectorType.HAB)],
DetectorId.correction_rotation: [single_entry_with_detector(0.0, DetectorType.HAB)],
LimitsId.events_binning: ["7000.0,500.0,60000.0"],
MaskId.clear_detector_mask: [True],
MaskId.clear_time_mask: [True],
LimitsId.radius: [range_entry(12, 15)],
TransId.spec_shift: [-70.],
PrintId.print_line: ["for changer"],
BackId.all_monitors: [range_entry(start=3500, stop=4500)],
FitId.monitor_times: [range_entry(start=1000, stop=2000)],
TransId.spec: [4],
BackId.trans: [range_entry(start=123, stop=466)],
TransId.radius: [7.0],
TransId.roi: ["test.xml", "test2.xml"],
TransId.mask: ["test3.xml", "test4.xml"],
SampleId.path: [True],
LimitsId.radius_cut: [200.0],
LimitsId.wavelength_cut: [8.0],
QResolutionId.on: [True],
QResolutionId.delta_r: [11.],
QResolutionId.collimation_length: [12.],
QResolutionId.a1: [13.],
QResolutionId.a2: [14.],
QResolutionId.moderator: ["moderator_rkh_file.txt"],
TubeCalibrationFileId.file: ["TUBE_SANS2D_BOTH_31681_25Sept15.nxs"]}
self.assertEqual(len(expected_values), len(output))
for key, value in list(expected_values.items()):
self.assertTrue(key in output)
self.assertEqual(len(output[key]), len(value))
elements = output[key]
# Make sure that the different entries are sorted
UserFileReaderTest._sort_list(elements)
UserFileReaderTest._sort_list(value)
self.assertEqual(elements, value, "{} is not {}".format(elements, value))
# clean up
if os.path.exists(user_file_path):
os.remove(user_file_path)
def test_that_can_read_user_file(self):
# Arrange
user_file_path = create_user_file(sample_user_file)
reader = UserFileReader(user_file_path)
# Act
output = reader.read_user_file()
# Assert
expected_values = {
LimitsId.wavelength: [
simple_range(start=1.5,
stop=12.5,
step=0.125,
step_type=RangeStepType.Lin)
],
LimitsId.q: [
q_rebin_values(min=.001,
max=.2,
rebin_string="0.001,0.001,0.0126,-0.08,0.2")
],
LimitsId.qxy: [simple_range(0, 0.05, 0.001, RangeStepType.Lin)],
BackId.single_monitors: [
back_single_monitor_entry(1, 35000, 65000),
back_single_monitor_entry(2, 85000, 98000)
],
DetectorId.reduction_mode: [ISISReductionMode.LAB],
GravityId.on_off: [True],
FitId.general: [
fit_general(start=1.5,
stop=12.5,
fit_type=FitType.Logarithmic,
data_type=None,
polynomial_order=0)
],
MaskId.vertical_single_strip_mask: [
single_entry_with_detector(191, DetectorType.LAB),
single_entry_with_detector(191, DetectorType.HAB),
single_entry_with_detector(0, DetectorType.LAB),
single_entry_with_detector(0, DetectorType.HAB)
],
MaskId.horizontal_single_strip_mask: [
single_entry_with_detector(0, DetectorType.LAB),
single_entry_with_detector(0, DetectorType.HAB)
],
MaskId.horizontal_range_strip_mask: [
range_entry_with_detector(190, 191, DetectorType.LAB),
range_entry_with_detector(167, 172, DetectorType.LAB),
range_entry_with_detector(190, 191, DetectorType.HAB),
range_entry_with_detector(156, 159, DetectorType.HAB)
],
MaskId.time: [range_entry_with_detector(17500, 22000, None)],
MonId.direct: [
monitor_file("DIRECTM1_15785_12m_31Oct12_v12.dat",
DetectorType.LAB),
monitor_file("DIRECTM1_15785_12m_31Oct12_v12.dat",
DetectorType.HAB)
],
MonId.spectrum: [
monitor_spectrum(1, True, True),
monitor_spectrum(1, False, True)
],
SetId.centre: [position_entry(155.45, -169.6, DetectorType.LAB)],
SetId.scales: [set_scales_entry(0.074, 1.0, 1.0, 1.0, 1.0)],
SampleId.offset: [53.0],
DetectorId.correction_x: [
single_entry_with_detector(-16.0, DetectorType.LAB),
single_entry_with_detector(-44.0, DetectorType.HAB)
],
DetectorId.correction_y:
[single_entry_with_detector(-20.0, DetectorType.HAB)],
DetectorId.correction_z: [
single_entry_with_detector(47.0, DetectorType.LAB),
single_entry_with_detector(47.0, DetectorType.HAB)
],
DetectorId.correction_rotation:
[single_entry_with_detector(0.0, DetectorType.HAB)],
LimitsId.events_binning: ["7000.0,500.0,60000.0"],
MaskId.clear_detector_mask: [True],
MaskId.clear_time_mask: [True],
LimitsId.radius: [range_entry(12, 15)],
TransId.spec_shift: [-70.],
PrintId.print_line: ["for changer"],
BackId.all_monitors: [range_entry(start=3500, stop=4500)],
FitId.monitor_times: [range_entry(start=1000, stop=2000)],
TransId.spec: [4],
BackId.trans: [range_entry(start=123, stop=466)],
TransId.radius: [7.0],
TransId.roi: ["test.xml", "test2.xml"],
TransId.mask: ["test3.xml", "test4.xml"],
SampleId.path: [True],
LimitsId.radius_cut: [200.0],
LimitsId.wavelength_cut: [8.0],
QResolutionId.on: [True],
QResolutionId.delta_r: [11.],
QResolutionId.collimation_length: [12.],
QResolutionId.a1: [13.],
QResolutionId.a2: [14.],
QResolutionId.moderator: ["moderator_rkh_file.txt"],
TubeCalibrationFileId.file:
["TUBE_SANS2D_BOTH_31681_25Sept15.nxs"]
}
self.assertTrue(len(expected_values) == len(output))
for key, value in list(expected_values.items()):
self.assertTrue(key in output)
self.assertTrue(len(output[key]) == len(value))
elements = output[key]
# Make sure that the different entries are sorted
UserFileReaderTest._sort_list(elements)
UserFileReaderTest._sort_list(value)
self.assertTrue(elements == value)
# clean up
if os.path.exists(user_file_path):
os.remove(user_file_path)
def test_that_can_read_user_file(self):
# Arrange
user_file_path = create_user_file(sample_user_file)
reader = UserFileReader(user_file_path)
# Act
output = reader.read_user_file()
# Assert
expected_values = {
LimitsId.WAVELENGTH: [
simple_range(start=1.5,
stop=12.5,
step=0.125,
step_type=RangeStepType.LIN)
],
LimitsId.Q: [
q_rebin_values(min=.001,
max=.2,
rebin_string="0.001,0.001,0.0126,-0.08,0.2")
],
LimitsId.QXY: [simple_range(0, 0.05, 0.001, RangeStepType.LIN)],
BackId.SINGLE_MONITORS: [
back_single_monitor_entry(1, 35000, 65000),
back_single_monitor_entry(2, 85000, 98000)
],
DetectorId.REDUCTION_MODE: [ReductionMode.LAB],
GravityId.ON_OFF: [True],
FitId.GENERAL: [
fit_general(start=1.5,
stop=12.5,
fit_type=FitType.LOGARITHMIC,
data_type=None,
polynomial_order=0)
],
MaskId.VERTICAL_SINGLE_STRIP_MASK: [
single_entry_with_detector(191, DetectorType.LAB),
single_entry_with_detector(191, DetectorType.HAB),
single_entry_with_detector(0, DetectorType.LAB),
single_entry_with_detector(0, DetectorType.HAB)
],
MaskId.HORIZONTAL_SINGLE_STRIP_MASK: [
single_entry_with_detector(0, DetectorType.LAB),
single_entry_with_detector(0, DetectorType.HAB)
],
MaskId.HORIZONTAL_RANGE_STRIP_MASK: [
range_entry_with_detector(190, 191, DetectorType.LAB),
range_entry_with_detector(167, 172, DetectorType.LAB),
range_entry_with_detector(190, 191, DetectorType.HAB),
range_entry_with_detector(156, 159, DetectorType.HAB)
],
MaskId.TIME: [range_entry_with_detector(17500, 22000, None)],
MonId.DIRECT: [
monitor_file("DIRECTM1_15785_12m_31Oct12_v12.dat",
DetectorType.LAB),
monitor_file("DIRECTM1_15785_12m_31Oct12_v12.dat",
DetectorType.HAB)
],
MonId.SPECTRUM: [
monitor_spectrum(1, True, True),
monitor_spectrum(1, False, True)
],
SetId.CENTRE: [position_entry(155.45, -169.6, DetectorType.LAB)],
SetId.SCALES: [set_scales_entry(0.074, 1.0, 1.0, 1.0, 1.0)],
SampleId.OFFSET: [53.0],
DetectorId.CORRECTION_X: [
single_entry_with_detector(-16.0, DetectorType.LAB),
single_entry_with_detector(-44.0, DetectorType.HAB)
],
DetectorId.CORRECTION_Y:
[single_entry_with_detector(-20.0, DetectorType.HAB)],
DetectorId.CORRECTION_Z: [
single_entry_with_detector(47.0, DetectorType.LAB),
single_entry_with_detector(47.0, DetectorType.HAB)
],
DetectorId.CORRECTION_ROTATION:
[single_entry_with_detector(0.0, DetectorType.HAB)],
LimitsId.EVENTS_BINNING: ["7000.0,500.0,60000.0"],
MaskId.CLEAR_DETECTOR_MASK: [True],
MaskId.CLEAR_TIME_MASK: [True],
LimitsId.RADIUS: [range_entry(12, 15)],
TransId.SPEC_4_SHIFT: [-70.],
PrintId.PRINT_LINE: ["for changer"],
BackId.ALL_MONITORS: [range_entry(start=3500, stop=4500)],
FitId.MONITOR_TIMES: [range_entry(start=1000, stop=2000)],
TransId.SPEC: [4],
BackId.TRANS: [range_entry(start=123, stop=466)],
TransId.RADIUS: [7.0],
TransId.ROI: ["test.xml", "test2.xml"],
TransId.MASK: ["test3.xml", "test4.xml"],
SampleId.PATH: [True],
LimitsId.RADIUS_CUT: [200.0],
LimitsId.WAVELENGTH_CUT: [8.0],
QResolutionId.ON: [True],
QResolutionId.DELTA_R: [11.],
QResolutionId.COLLIMATION_LENGTH: [12.],
QResolutionId.A1: [13.],
QResolutionId.A2: [14.],
QResolutionId.MODERATOR: ["moderator_rkh_file.txt"],
TubeCalibrationFileId.FILE:
["TUBE_SANS2D_BOTH_31681_25Sept15.nxs"]
}
self.assertEqual(len(expected_values), len(output))
for key, value in list(expected_values.items()):
self.assertTrue(key in output)
self.assertEqual(len(output[key]), len(value))
elements = output[key]
# Make sure that the different entries are sorted
UserFileReaderTest._sort_list(elements)
UserFileReaderTest._sort_list(value)
self.assertEqual(elements, value,
"{} is not {}".format(elements, value))
# clean up
if os.path.exists(user_file_path):
os.remove(user_file_path)