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 ComplexState(StateBase):
float_parameter = FloatParameter()
positive_float_with_none_parameter = PositiveFloatWithNoneParameter()
sub_state_1 = TypedParameter(SimpleState, validator_sub_state)
dict_parameter = DictParameter()
def __init__(self):
super(ComplexState, self).__init__()
self.float_parameter = 23.
self.positive_float_with_none_parameter = 234.
self.sub_state_1 = SimpleState()
self.dict_parameter = {"A": SimpleState(), "B": SimpleState()}
def validate(self):
pass
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 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)))