class StateScale(StateBase):
shape = ClassTypeParameter(SampleShape)
thickness = PositiveFloatParameter()
width = PositiveFloatParameter()
height = PositiveFloatParameter()
scale = PositiveFloatParameter()
# Geometry from the file
shape_from_file = ClassTypeParameter(SampleShape)
thickness_from_file = PositiveFloatParameter()
width_from_file = PositiveFloatParameter()
height_from_file = PositiveFloatParameter()
def __init__(self):
super(StateScale, self).__init__()
# The default geometry
self.shape_from_file = SampleShape.Disc
# The default values are 1mm
self.thickness_from_file = 1.
self.width_from_file = 1.
self.height_from_file = 1.
def validate(self):
pass
class StateReductionMode(StateReductionBase, StateBase):
reduction_mode = ClassTypeParameter(ReductionMode)
reduction_dimensionality = ClassTypeParameter(ReductionDimensionality)
# Fitting
merge_fit_mode = ClassTypeParameter(FitModeForMerge)
merge_shift = FloatParameter()
merge_scale = FloatParameter()
merge_range_min = FloatWithNoneParameter()
merge_range_max = FloatWithNoneParameter()
# Map from detector type to detector name
detector_names = DictParameter()
def __init__(self):
super(StateReductionMode, self).__init__()
self.reduction_mode = ISISReductionMode.LAB
self.reduction_dimensionality = ReductionDimensionality.OneDim
# Set the shifts to defaults which essentially don't do anything.
self.merge_shift = 0.0
self.merge_scale = 1.0
self.merge_fit_mode = FitModeForMerge.NoFit
self.merge_range_min = None
self.merge_range_max = None
# Set the detector names to empty strings
self.detector_names = {
DetectorType.to_string(DetectorType.LAB): "",
DetectorType.to_string(DetectorType.HAB): ""
}
def get_merge_strategy(self):
return [ISISReductionMode.LAB, ISISReductionMode.HAB]
def get_all_reduction_modes(self):
return [ISISReductionMode.LAB, ISISReductionMode.HAB]
def get_detector_name_for_reduction_mode(self, reduction_mode):
if reduction_mode is ISISReductionMode.LAB:
bank_type = DetectorType.to_string(DetectorType.LAB)
elif reduction_mode is ISISReductionMode.HAB:
bank_type = DetectorType.to_string(DetectorType.HAB)
else:
raise RuntimeError(
"SANStateReductionISIS: There is no detector available for the"
" reduction mode {0}.".format(reduction_mode))
return self.detector_names[bank_type]
def validate(self):
pass
class StateWavelengthAndPixelAdjustment(StateBase):
wavelength_low = PositiveFloatParameter()
wavelength_high = PositiveFloatParameter()
wavelength_step = PositiveFloatParameter()
wavelength_step_type = ClassTypeParameter(RangeStepType)
adjustment_files = DictParameter()
idf_path = StringParameter()
def __init__(self):
super(StateWavelengthAndPixelAdjustment, self).__init__()
self.adjustment_files = {
DetectorType.to_string(DetectorType.LAB): StateAdjustmentFiles(),
DetectorType.to_string(DetectorType.HAB): StateAdjustmentFiles()
}
def validate(self):
is_invalid = {}
if one_is_none([
self.wavelength_low, self.wavelength_high,
self.wavelength_step, self.wavelength_step_type
]):
entry = validation_message(
"A wavelength entry has not been set.",
"Make sure that all entries are set.", {
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high,
"wavelength_step": self.wavelength_step,
"wavelength_step_type": self.wavelength_step_type
})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second(
[self.wavelength_low, self.wavelength_high]):
entry = validation_message(
"Incorrect wavelength bounds.",
"Make sure that lower wavelength bound is smaller then upper bound.",
{
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high
})
is_invalid.update(entry)
try:
self.adjustment_files[DetectorType.to_string(
DetectorType.LAB)].validate()
self.adjustment_files[DetectorType.to_string(
DetectorType.HAB)].validate()
except ValueError as e:
is_invalid.update({"adjustment_files": str(e)})
if is_invalid:
raise ValueError(
"StateWavelengthAndPixelAdjustment: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid)))
class StateWavelength(StateBase):
rebin_type = ClassTypeParameter(RebinType)
wavelength_low = PositiveFloatParameter()
wavelength_high = PositiveFloatParameter()
wavelength_step = PositiveFloatParameter()
wavelength_step_type = ClassTypeParameter(RangeStepType)
def __init__(self):
super(StateWavelength, self).__init__()
self.rebin_type = RebinType.Rebin
def validate(self):
is_invalid = dict()
if one_is_none(
[self.wavelength_low, self.wavelength_high, self.wavelength_step]):
entry = validation_message(
"A wavelength entry has not been set.",
"Make sure that all entries for the wavelength are set.", {
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high,
"wavelength_step": self.wavelength_step
})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second(
[self.wavelength_low, self.wavelength_high]):
entry = validation_message(
"Incorrect wavelength bounds.",
"Make sure that lower wavelength bound is smaller then upper bound.",
{
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high
})
is_invalid.update(entry)
if is_invalid:
raise ValueError(
"StateWavelength: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid, indent=4)))
class StateTransmissionFit(StateBase):
fit_type = ClassTypeParameter(FitType)
polynomial_order = PositiveIntegerParameter()
wavelength_low = PositiveFloatWithNoneParameter()
wavelength_high = PositiveFloatWithNoneParameter()
def __init__(self):
super(StateTransmissionFit, self).__init__()
self.fit_type = FitType.Log
self.polynomial_order = 0
def validate(self): # noqa
is_invalid = {}
if self.fit_type is not FitType.Polynomial and self.polynomial_order != 0:
entry = validation_message(
"You can only set a polynomial order of you selected polynomial fitting.",
"Make sure that you select polynomial fitting.", {
"fit_type": self.fit_type,
"polynomial_order": self.polynomial_order
})
is_invalid.update(entry)
if not is_pure_none_or_not_none(
[self.wavelength_low, self.wavelength_high]):
entry = validation_message(
"Inconsistent wavelength setting.",
"Make sure that you have specified both wavelength bounds (or none).",
{
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high
})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second(
[self.wavelength_low, self.wavelength_high]):
entry = validation_message(
"Incorrect wavelength bounds.",
"Make sure that lower wavelength bound is smaller then upper bound.",
{
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high
})
is_invalid.update(entry)
if is_invalid:
raise ValueError(
"StateTransmissionFit: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid)))
class StateBaseTestClass(StateBase):
string_parameter = StringParameter()
bool_parameter = BoolParameter()
float_parameter = FloatParameter()
positive_float_parameter = PositiveFloatParameter()
positive_integer_parameter = PositiveIntegerParameter()
dict_parameter = DictParameter()
float_with_none_parameter = FloatWithNoneParameter()
positive_float_with_none_parameter = PositiveFloatWithNoneParameter()
float_list_parameter = FloatListParameter()
string_list_parameter = StringListParameter()
positive_integer_list_parameter = PositiveIntegerListParameter()
class_type_parameter = ClassTypeParameter(TestType)
class_type_list_parameter = ClassTypeListParameter(TestType)
def __init__(self):
super(StateBaseTestClass, self).__init__()
def validate(self):
pass
class StateMove(StateBase):
sample_offset = FloatParameter()
sample_offset_direction = ClassTypeParameter(Coordinates)
detectors = DictParameter()
monitor_names = DictParameter()
def __init__(self):
super(StateMove, self).__init__()
# Setup the sample offset
self.sample_offset = 0.0
# The sample offset direction is Z for the ISIS instruments
self.sample_offset_direction = CanonicalCoordinates.Z
def validate(self):
# No validation of the descriptors on this level, let potential exceptions from detectors "bubble" up
for key in self.detectors:
self.detectors[key].validate()
# If the detectors are empty, then we raise
if not self.detectors:
raise ValueError("No detectors have been set.")
class SimpleState(StateBase):
string_parameter = StringParameter()
bool_parameter = BoolParameter()
float_parameter = FloatParameter()
positive_float_parameter = PositiveFloatParameter()
positive_integer_parameter = PositiveIntegerParameter()
dict_parameter = DictParameter()
float_with_none_parameter = FloatWithNoneParameter()
positive_float_with_none_parameter = PositiveFloatWithNoneParameter()
float_list_parameter = FloatListParameter()
string_list_parameter = StringListParameter()
positive_integer_list_parameter = PositiveIntegerListParameter()
class_type_parameter = ClassTypeParameter(TestType)
class_type_list_parameter = ClassTypeListParameter(TestType)
sub_state_very_simple = TypedParameter(VerySimpleState,
validator_sub_state)
def __init__(self):
super(SimpleState, self).__init__()
self.string_parameter = "String_in_SimpleState"
self.bool_parameter = False
# We explicitly leave out the float_parameter
self.positive_float_parameter = 1.
self.positive_integer_parameter = 6
self.dict_parameter = {"1": 123, "2": "test"}
self.float_with_none_parameter = 325.
# We expliclty leave out the positive_float_with_none_parameter
self.float_list_parameter = [123., 234.]
self.string_list_parameter = ["test1", "test2"]
self.positive_integer_list_parameter = [1, 2, 3]
self.class_type_parameter = TestType.TypeA
self.class_type_list_parameter = [TestType.TypeA, TestType.TypeB]
self.sub_state_very_simple = VerySimpleState()
def validate(self):
pass
class StateNormalizeToMonitor(StateBase):
prompt_peak_correction_min = PositiveFloatWithNoneParameter()
prompt_peak_correction_max = PositiveFloatWithNoneParameter()
prompt_peak_correction_enabled = BoolParameter()
rebin_type = ClassTypeParameter(RebinType)
wavelength_low = PositiveFloatListParameter()
wavelength_high = PositiveFloatListParameter()
wavelength_step = PositiveFloatParameter()
wavelength_step_type = ClassTypeParameter(RangeStepType)
background_TOF_general_start = FloatParameter()
background_TOF_general_stop = FloatParameter()
background_TOF_monitor_start = DictParameter()
background_TOF_monitor_stop = DictParameter()
incident_monitor = PositiveIntegerParameter()
def __init__(self):
super(StateNormalizeToMonitor, self).__init__()
self.background_TOF_monitor_start = {}
self.background_TOF_monitor_stop = {}
self.prompt_peak_correction_enabled = False
# Default rebin type is a standard Rebin
self.rebin_type = RebinType.Rebin
def validate(self):
is_invalid = {}
# -----------------
# incident Monitor
# -----------------
if self.incident_monitor is None:
is_invalid.update(
{"incident_monitor": "An incident monitor must be specified."})
# -----------------
# Prompt peak
# -----------------
if not is_pure_none_or_not_none(
[self.prompt_peak_correction_min, self.prompt_peak_correction_max
]):
entry = validation_message(
"A prompt peak correction entry has not been set.",
"Make sure that either all prompt peak entries have been set or none.",
{
"prompt_peak_correction_min":
self.prompt_peak_correction_min,
"prompt_peak_correction_max":
self.prompt_peak_correction_max
})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second(
[self.prompt_peak_correction_min,
self.prompt_peak_correction_max]):
entry = validation_message(
"Incorrect prompt peak correction bounds.",
"Make sure that lower prompt peak time bound is smaller then upper bound.",
{
"prompt_peak_correction_min":
self.prompt_peak_correction_min,
"prompt_peak_correction_max":
self.prompt_peak_correction_max
})
is_invalid.update(entry)
# -----------------
# Wavelength rebin
# -----------------
if one_is_none([
self.wavelength_low, self.wavelength_high,
self.wavelength_step, self.wavelength_step_type
]):
entry = validation_message(
"A wavelength entry has not been set.",
"Make sure that all entries are set.", {
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high,
"wavelength_step": self.wavelength_step,
"wavelength_step_type": self.wavelength_step_type
})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second(
[self.wavelength_low, self.wavelength_high]):
entry = validation_message(
"Incorrect wavelength bounds.",
"Make sure that lower wavelength bound is smaller then upper bound.",
{
"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high
})
is_invalid.update(entry)
# ----------------------
# Background correction
# ----------------------
if not is_pure_none_or_not_none([
self.background_TOF_general_start,
self.background_TOF_general_stop
]):
entry = validation_message(
"A general background TOF entry has not been set.",
"Make sure that either all general background TOF entries are set or none.",
{
"background_TOF_general_start":
self.background_TOF_general_start,
"background_TOF_general_stop":
self.background_TOF_general_stop
})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second([
self.background_TOF_general_start,
self.background_TOF_general_stop
]):
entry = validation_message(
"Incorrect general background TOF bounds.",
"Make sure that lower general background TOF bound is smaller then upper bound.",
{
"background_TOF_general_start":
self.background_TOF_general_start,
"background_TOF_general_stop":
self.background_TOF_general_stop
})
is_invalid.update(entry)
if not is_pure_none_or_not_none([
self.background_TOF_monitor_start,
self.background_TOF_monitor_stop
]):
entry = validation_message(
"A monitor background TOF entry has not been set.",
"Make sure that either all monitor background TOF entries are set or none.",
{
"background_TOF_monitor_start":
self.background_TOF_monitor_start,
"background_TOF_monitor_stop":
self.background_TOF_monitor_stop
})
is_invalid.update(entry)
if self.background_TOF_monitor_start is not None and self.background_TOF_monitor_stop is not None:
if len(self.background_TOF_monitor_start) != len(
self.background_TOF_monitor_stop):
entry = validation_message(
"The monitor background TOF entries have a length mismatch.",
"Make sure that all monitor background TOF entries have the same length.",
{
"background_TOF_monitor_start":
self.background_TOF_monitor_start,
"background_TOF_monitor_stop":
self.background_TOF_monitor_stop
})
is_invalid.update(entry)
for key_start, value_start in list(
self.background_TOF_monitor_start.items()):
if key_start not in self.background_TOF_monitor_stop:
entry = validation_message(
"The monitor background TOF had spectrum number mismatch.",
"Make sure that all monitors have entries for start and stop.",
{
"background_TOF_monitor_start":
self.background_TOF_monitor_start,
"background_TOF_monitor_stop":
self.background_TOF_monitor_stop
})
is_invalid.update(entry)
else:
value_stop = self.background_TOF_monitor_stop[key_start]
if value_start > value_stop:
entry = validation_message(
"Incorrect monitor background TOF bounds.",
"Make sure that lower monitor background TOF bound is"
" smaller then upper bound.", {
"background_TOF_monitor_start":
self.background_TOF_monitor_start,
"background_TOF_monitor_stop":
self.background_TOF_monitor_stop
})
is_invalid.update(entry)
if is_invalid:
raise ValueError(
"StateMoveDetector: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid)))
class StateData(StateBase):
ALL_PERIODS = sans.common.constants.ALL_PERIODS
sample_scatter = StringParameter()
sample_scatter_period = PositiveIntegerParameter()
sample_transmission = StringParameter()
sample_transmission_period = PositiveIntegerParameter()
sample_direct = StringParameter()
sample_direct_period = PositiveIntegerParameter()
can_scatter = StringParameter()
can_scatter_period = PositiveIntegerParameter()
can_transmission = StringParameter()
can_transmission_period = PositiveIntegerParameter()
can_direct = StringParameter()
can_direct_period = PositiveIntegerParameter()
calibration = StringParameter()
sample_scatter_run_number = PositiveIntegerParameter()
sample_scatter_is_multi_period = BoolParameter()
instrument = ClassTypeParameter(SANSInstrument)
idf_file_path = StringParameter()
ipf_file_path = StringParameter()
def __init__(self):
super(StateData, self).__init__()
# Setup default values for periods
self.sample_scatter_period = StateData.ALL_PERIODS
self.sample_transmission_period = StateData.ALL_PERIODS
self.sample_direct_period = StateData.ALL_PERIODS
self.can_scatter_period = StateData.ALL_PERIODS
self.can_transmission_period = StateData.ALL_PERIODS
self.can_direct_period = StateData.ALL_PERIODS
# This should be reset by the builder. Setting this to NoInstrument ensure that we will trip early on,
# in case this is not set, for example by not using the builders.
self.instrument = SANSInstrument.NoInstrument
def validate(self):
is_invalid = dict()
# A sample scatter must be specified
if self.sample_scatter is None:
entry = validation_message(
"Sample scatter was not specified.",
"Make sure that the sample scatter file is specified.",
{"sample_scatter": self.sample_scatter})
is_invalid.update(entry)
# If the sample transmission/direct was specified, then a sample direct/transmission is required
if not is_pure_none_or_not_none(
[self.sample_transmission, self.sample_direct]):
entry = validation_message(
"If the sample transmission is specified then, the direct run needs to be "
"specified too.",
"Make sure that the transmission and direct runs are both specified (or none).",
{
"sample_transmission": self.sample_transmission,
"sample_direct": self.sample_direct
})
is_invalid.update(entry)
# If the can transmission/direct was specified, then this requires the can scatter
if (self.can_direct
or self.can_transmission) and (not self.can_scatter):
entry = validation_message(
"If the can transmission is specified then the can scatter run needs to be "
"specified too.",
"Make sure that the can scatter file is set.", {
"can_scatter": self.can_scatter,
"can_transmission": self.can_transmission,
"can_direct": self.can_direct
})
is_invalid.update(entry)
# If a can transmission/direct was specified, then the other can entries need to be specified as well.
if self.can_scatter and not is_pure_none_or_not_none(
[self.can_transmission, self.can_direct]):
entry = validation_message(
"Inconsistent can transmission setting.",
"Make sure that the can transmission and can direct runs are set (or none of"
" them).", {
"can_transmission": self.can_transmission,
"can_direct": self.can_direct
})
is_invalid.update(entry)
if is_invalid:
raise ValueError("StateData: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid)))
class StateReductionMode(StateReductionBase, StateBase):
reduction_mode = ClassTypeParameter(ReductionMode)
reduction_dimensionality = ClassTypeParameter(ReductionDimensionality)
merge_max = FloatWithNoneParameter()
merge_min = FloatWithNoneParameter()
merge_mask = BoolParameter()
# Fitting
merge_fit_mode = ClassTypeParameter(FitModeForMerge)
merge_shift = FloatParameter()
merge_scale = FloatParameter()
merge_range_min = FloatWithNoneParameter()
merge_range_max = FloatWithNoneParameter()
# Map from detector type to detector name
detector_names = DictParameter()
def __init__(self):
super(StateReductionMode, self).__init__()
self.reduction_mode = ISISReductionMode.LAB
self.reduction_dimensionality = ReductionDimensionality.OneDim
# Set the shifts to defaults which essentially don't do anything.
self.merge_shift = 0.0
self.merge_scale = 1.0
self.merge_fit_mode = FitModeForMerge.NoFit
self.merge_range_min = None
self.merge_range_max = None
self.merge_max = None
self.merge_min = None
self.merge_mask = False
# Set the detector names to empty strings
self.detector_names = {
DetectorType.to_string(DetectorType.LAB): "",
DetectorType.to_string(DetectorType.HAB): ""
}
def get_merge_strategy(self):
return [ISISReductionMode.LAB, ISISReductionMode.HAB]
def get_all_reduction_modes(self):
return [ISISReductionMode.LAB, ISISReductionMode.HAB]
def get_detector_name_for_reduction_mode(self, reduction_mode):
if reduction_mode is ISISReductionMode.LAB:
bank_type = DetectorType.to_string(DetectorType.LAB)
elif reduction_mode is ISISReductionMode.HAB:
bank_type = DetectorType.to_string(DetectorType.HAB)
else:
raise RuntimeError(
"SANStateReductionISIS: There is no detector available for the"
" reduction mode {0}.".format(reduction_mode))
return self.detector_names[bank_type]
def validate(self):
is_invalid = {}
if self.merge_max and self.merge_min:
if self.merge_min > self.merge_max:
is_invalid.update({
"StateReduction":
"The minimum of the merge region is greater than the maximum."
})
if is_invalid:
raise ValueError(
"StateReduction: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid)))
class StateCalculateTransmission(StateBase):
# -----------------------
# Transmission
# -----------------------
transmission_radius_on_detector = PositiveFloatParameter()
transmission_roi_files = StringListParameter()
transmission_mask_files = StringListParameter()
default_transmission_monitor = PositiveIntegerParameter()
transmission_monitor = PositiveIntegerParameter()
default_incident_monitor = PositiveIntegerParameter()
incident_monitor = PositiveIntegerParameter()
# ----------------------
# Prompt peak correction
# ----------------------
prompt_peak_correction_min = PositiveFloatParameter()
prompt_peak_correction_max = PositiveFloatParameter()
prompt_peak_correction_enabled = BoolParameter()
# ----------------
# Wavelength rebin
# ----------------
rebin_type = ClassTypeParameter(RebinType)
wavelength_low = PositiveFloatParameter()
wavelength_high = PositiveFloatParameter()
wavelength_step = PositiveFloatParameter()
wavelength_step_type = ClassTypeParameter(RangeStepType)
use_full_wavelength_range = BoolParameter()
wavelength_full_range_low = PositiveFloatParameter()
wavelength_full_range_high = PositiveFloatParameter()
# -----------------------
# Background correction
# ----------------------
background_TOF_general_start = FloatParameter()
background_TOF_general_stop = FloatParameter()
background_TOF_monitor_start = DictParameter()
background_TOF_monitor_stop = DictParameter()
background_TOF_roi_start = FloatParameter()
background_TOF_roi_stop = FloatParameter()
# -----------------------
# Fit
# ----------------------
fit = DictParameter()
def __init__(self):
super(StateCalculateTransmission, self).__init__()
# The keys of this dictionaries are the spectrum number of the monitors (as a string)
self.background_TOF_monitor_start = {}
self.background_TOF_monitor_stop = {}
self.fit = {DataType.to_string(DataType.Sample): StateTransmissionFit(),
DataType.to_string(DataType.Can): StateTransmissionFit()}
self.use_full_wavelength_range = False
# Default rebin type is a standard Rebin
self.rebin_type = RebinType.Rebin
self.prompt_peak_correction_enabled = False
def validate(self): # noqa
is_invalid = {}
# -----------------
# Incident monitor
# -----------------
if self.incident_monitor is None and self.default_incident_monitor is None:
entry = validation_message("No incident monitor was specified.",
"Make sure that incident monitor has been specified.",
{"incident_monitor": self.incident_monitor,
"default_incident_monitor": self.default_incident_monitor})
is_invalid.update(entry)
# --------------
# Transmission, either we need some ROI (ie radius, roi files /mask files) or a transmission monitor
# --------------
has_no_transmission_monitor_setting = self.transmission_monitor is None and\
self.default_transmission_monitor is None # noqa
has_no_transmission_roi_setting = self.transmission_radius_on_detector is None and\
self.transmission_roi_files is None # noqa
if has_no_transmission_monitor_setting and has_no_transmission_roi_setting:
entry = validation_message("No transmission settings were specified.",
"Make sure that transmission settings are specified.",
{"transmission_monitor": self.transmission_monitor,
"default_transmission_monitor": self.default_transmission_monitor,
"transmission_radius_on_detector": self.transmission_radius_on_detector,
"transmission_roi_files": self.transmission_roi_files})
is_invalid.update(entry)
# -----------------
# Prompt peak
# -----------------
if not is_pure_none_or_not_none([self.prompt_peak_correction_min, self.prompt_peak_correction_max]):
entry = validation_message("Inconsistent prompt peak setting.",
"Make sure that you have specified both prompt peak bounds (or none).",
{"prompt_peak_correction_min": self.prompt_peak_correction_min,
"prompt_peak_correction_max": self.prompt_peak_correction_max})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second([self.prompt_peak_correction_min, self.prompt_peak_correction_max]):
entry = validation_message("Incorrect prompt peak bounds.",
"Make sure that lower prompt peak bound is smaller then upper bound.",
{"prompt_peak_correction_min": self.prompt_peak_correction_min,
"prompt_peak_correction_max": self.prompt_peak_correction_max})
is_invalid.update(entry)
# -----------------
# Wavelength rebin
# -----------------
if one_is_none([self.wavelength_low, self.wavelength_high, self.wavelength_step, self.wavelength_step_type,
self.wavelength_step_type, self.rebin_type]):
entry = validation_message("A wavelength entry has not been set.",
"Make sure that all entries are set.",
{"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high,
"wavelength_step": self.wavelength_step,
"wavelength_step_type": self.wavelength_step_type,
"rebin_type": self.rebin_type})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second([self.wavelength_low, self.wavelength_high]):
entry = validation_message("Incorrect wavelength bounds.",
"Make sure that lower wavelength bound is smaller then upper bound.",
{"wavelength_low": self.wavelength_low,
"wavelength_high": self.wavelength_high})
is_invalid.update(entry)
if self.use_full_wavelength_range:
if self.wavelength_full_range_low is None or self.wavelength_full_range_high is None:
entry = validation_message("Incorrect full wavelength settings.",
"Make sure that both full wavelength entries have been set.",
{"wavelength_full_range_low": self.wavelength_full_range_low,
"wavelength_full_range_high": self.wavelength_full_range_high})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second([self.wavelength_full_range_low,
self.wavelength_full_range_high]):
entry = validation_message("Incorrect wavelength bounds.",
"Make sure that lower full wavelength bound is smaller then upper bound.",
{"wavelength_full_range_low": self.wavelength_full_range_low,
"wavelength_full_range_high": self.wavelength_full_range_high})
is_invalid.update(entry)
# ----------------------
# Background correction
# ----------------------
if not is_pure_none_or_not_none([self.background_TOF_general_start, self.background_TOF_general_stop]):
entry = validation_message("A general background TOF entry has not been set.",
"Make sure that either all general background TOF entries are set or none.",
{"background_TOF_general_start": self.background_TOF_general_start,
"background_TOF_general_stop": self.background_TOF_general_stop})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second([self.background_TOF_general_start,
self.background_TOF_general_stop]):
entry = validation_message("Incorrect general background TOF bounds.",
"Make sure that lower general background TOF bound is smaller then upper bound.",
{"background_TOF_general_start": self.background_TOF_general_start,
"background_TOF_general_stop": self.background_TOF_general_stop})
is_invalid.update(entry)
if not is_pure_none_or_not_none([self.background_TOF_roi_start, self.background_TOF_roi_stop]):
entry = validation_message("A ROI background TOF entry has not been set.",
"Make sure that either all ROI background TOF entries are set or none.",
{"background_TOF_roi_start": self.background_TOF_roi_start,
"background_TOF_roi_stop": self.background_TOF_roi_stop})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second([self.background_TOF_roi_start,
self.background_TOF_roi_stop]):
entry = validation_message("Incorrect ROI background TOF bounds.",
"Make sure that lower ROI background TOF bound is smaller then upper bound.",
{"background_TOF_roi_start": self.background_TOF_roi_start,
"background_TOF_roi_stop": self.background_TOF_roi_stop})
is_invalid.update(entry)
if not is_pure_none_or_not_none([self.background_TOF_monitor_start, self.background_TOF_monitor_stop]):
entry = validation_message("A monitor background TOF entry has not been set.",
"Make sure that either all monitor background TOF entries are set or none.",
{"background_TOF_monitor_start": self.background_TOF_monitor_start,
"background_TOF_monitor_stop": self.background_TOF_monitor_stop})
is_invalid.update(entry)
if self.background_TOF_monitor_start is not None and self.background_TOF_monitor_stop is not None:
if len(self.background_TOF_monitor_start) != len(self.background_TOF_monitor_stop):
entry = validation_message("The monitor background TOF entries have a length mismatch.",
"Make sure that all monitor background TOF entries have the same length.",
{"background_TOF_monitor_start": self.background_TOF_monitor_start,
"background_TOF_monitor_stop": self.background_TOF_monitor_stop})
is_invalid.update(entry)
for key_start, value_start in list(self.background_TOF_monitor_start.items()):
if key_start not in self.background_TOF_monitor_stop:
entry = validation_message("The monitor background TOF had spectrum number mismatch.",
"Make sure that all monitors have entries for start and stop.",
{"background_TOF_monitor_start": self.background_TOF_monitor_start,
"background_TOF_monitor_stop": self.background_TOF_monitor_stop})
is_invalid.update(entry)
else:
value_stop = self.background_TOF_monitor_stop[key_start]
if value_start > value_stop:
entry = validation_message("Incorrect monitor background TOF bounds.",
"Make sure that lower monitor background TOF bound is"
" smaller then upper bound.",
{"background_TOF_monitor_start": self.background_TOF_monitor_start,
"background_TOF_monitor_stop": self.background_TOF_monitor_stop})
is_invalid.update(entry)
# -----
# Fit
# -----
self.fit[DataType.to_string(DataType.Sample)].validate()
self.fit[DataType.to_string(DataType.Can)].validate()
if is_invalid:
raise ValueError("StateCalculateTransmission: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid)))
class StateConvertToQ(StateBase):
reduction_dimensionality = ClassTypeParameter(ReductionDimensionality)
use_gravity = BoolParameter()
gravity_extra_length = PositiveFloatParameter()
radius_cutoff = PositiveFloatParameter()
wavelength_cutoff = PositiveFloatParameter()
# 1D settings
q_min = PositiveFloatParameter()
q_max = PositiveFloatParameter()
q_1d_rebin_string = StringParameter()
# 2D settings
q_xy_max = PositiveFloatParameter()
q_xy_step = PositiveFloatParameter()
q_xy_step_type = ClassTypeParameter(RangeStepType)
# -----------------------
# Q Resolution specific
# ---------------------
use_q_resolution = BoolParameter()
q_resolution_collimation_length = PositiveFloatParameter()
q_resolution_delta_r = PositiveFloatParameter()
moderator_file = StringParameter()
# Circular aperture settings
q_resolution_a1 = PositiveFloatParameter()
q_resolution_a2 = PositiveFloatParameter()
# Rectangular aperture settings
q_resolution_h1 = PositiveFloatParameter()
q_resolution_h2 = PositiveFloatParameter()
q_resolution_w1 = PositiveFloatParameter()
q_resolution_w2 = PositiveFloatParameter()
def __init__(self):
super(StateConvertToQ, self).__init__()
self.reduction_dimensionality = ReductionDimensionality.OneDim
self.use_gravity = False
self.gravity_extra_length = 0.0
self.use_q_resolution = False
self.radius_cutoff = 0.0
self.wavelength_cutoff = 0.0
def validate(self):
is_invalid = {}
# 1D Q settings
if not is_pure_none_or_not_none([self.q_min, self.q_max]):
entry = validation_message(
"The q boundaries for the 1D reduction are inconsistent.",
"Make sure that both q boundaries are set (or none).", {
"q_min": self.q_min,
"q_max": self.q_max
})
is_invalid.update(entry)
if is_not_none_and_first_larger_than_second([self.q_min, self.q_max]):
entry = validation_message(
"Incorrect q bounds for 1D reduction.",
"Make sure that the lower q bound is smaller than the upper q bound.",
{
"q_min": self.q_min,
"q_max": self.q_max
})
is_invalid.update(entry)
if self.reduction_dimensionality is ReductionDimensionality.OneDim:
if self.q_min is None or self.q_max is None:
entry = validation_message(
"Q bounds not set for 1D reduction.",
"Make sure to set the q boundaries when using a 1D reduction.",
{
"q_min": self.q_min,
"q_max": self.q_max
})
is_invalid.update(entry)
if self.q_1d_rebin_string is not None:
if self.q_1d_rebin_string == "":
entry = validation_message(
"Q rebin string does not seem to be valid.",
"Make sure to provide a valid rebin string",
{"q_1d_rebin_string": self.q_1d_rebin_string})
is_invalid.update(entry)
elif not is_valid_rebin_string(self.q_1d_rebin_string):
entry = validation_message(
"Q rebin string does not seem to be valid.",
"Make sure to provide a valid rebin string",
{"q_1d_rebin_string": self.q_1d_rebin_string})
is_invalid.update(entry)
# QXY settings
if self.reduction_dimensionality is ReductionDimensionality.TwoDim:
if self.q_xy_max is None or self.q_xy_step is None:
entry = validation_message(
"Q bounds not set for 2D reduction.",
"Make sure that the q_max value bound and the step for the 2D reduction.",
{
"q_xy_max": self.q_xy_max,
"q_xy_step": self.q_xy_step
})
is_invalid.update(entry)
# Q Resolution settings
if self.use_q_resolution:
if not is_pure_none_or_not_none(
[self.q_resolution_a1, self.q_resolution_a2]):
entry = validation_message(
"Inconsistent circular geometry.",
"Make sure that both diameters for the circular apertures are set.",
{
"q_resolution_a1": self.q_resolution_a1,
"q_resolution_a2": self.q_resolution_a2
})
is_invalid.update(entry)
if not is_pure_none_or_not_none([
self.q_resolution_h1, self.q_resolution_h2,
self.q_resolution_w1, self.q_resolution_w2
]):
entry = validation_message(
"Inconsistent rectangular geometry.",
"Make sure that both diameters for the circular apertures are set.",
{
"q_resolution_h1": self.q_resolution_h1,
"q_resolution_h2": self.q_resolution_h2,
"q_resolution_w1": self.q_resolution_w1,
"q_resolution_w2": self.q_resolution_w2
})
is_invalid.update(entry)
if all(element is None for element in [
self.q_resolution_a1, self.q_resolution_a2,
self.q_resolution_w1, self.q_resolution_w2,
self.q_resolution_h1, self.q_resolution_h2
]):
entry = validation_message(
"Aperture is undefined.",
"Make sure that you set the geometry for a circular or a "
"rectangular aperture.", {
"q_resolution_a1": self.q_resolution_a1,
"q_resolution_a2": self.q_resolution_a2,
"q_resolution_h1": self.q_resolution_h1,
"q_resolution_h2": self.q_resolution_h2,
"q_resolution_w1": self.q_resolution_w1,
"q_resolution_w2": self.q_resolution_w2
})
is_invalid.update(entry)
if self.moderator_file is None:
entry = validation_message(
"Missing moderator file.",
"Make sure to specify a moderator file when using q resolution.",
{"moderator_file": self.moderator_file})
is_invalid.update(entry)
is_invalid.update({
"moderator_file":
"A moderator file is required for the q resolution calculation."
})
if is_invalid:
raise ValueError(
"StateMoveDetectorISIS: The provided inputs are illegal. "
"Please see: {0}".format(json.dumps(is_invalid)))
