prsctrl.measurement.settings.MeasurementParameters

class MeasurementParameters(measurement_time_s: float = 30, wait_time_s: Optional[float] = None, additional_wait_time_s: float = 0, pump_source: str = 'none', pump_power_mWcm2: Optional[float] = None, auto_gain: bool = False, auto_sensitivity: bool = True, wavelengths_nm: Union[tuple[float, float, float], list[float], NoneType] = None, energies_eV: Union[tuple[float, float, float], list[float], NoneType] = None, offset_strategy: Literal['none', 'start-end', 'time-interval'] = 'time-interval', offset_intervals_minutes: list[int] = <factory>)

Bases: SettingsClass

Methods

as_dict	Convenience wrapper for dataclasses.asdict(self)
from_dict	Recursively construct a SettingsClass from a dictionary.
get_metadata	Return the measurements settings converted to a metadata dictionary that contains only relevant information.
get_wavelengths_nm	Generate a list of wavelengths according to either the 'wavelengths_nm' or 'energies_eV' field.
get_wavelengths_nm_with_offsets	Generate a list of wavelengths according to either the 'wavelengths_nm' or 'energies_eV' field and offset measurements.
load_yaml
save_yaml

Attributes

additional_wait_time_s
auto_gain
auto_sensitivity
energies_eV
measurement_time_s
offset_strategy
pump_power_mWcm2
pump_source
wait_time_s
wavelengths_nm
offset_intervals_minutes

__annotations__ = {'additional_wait_time_s': <class 'float'>, 'auto_gain': <class 'bool'>, 'auto_sensitivity': <class 'bool'>, 'energies_eV': typing.Union[tuple[float, float, float], list[float], NoneType], 'measurement_time_s': <class 'float'>, 'offset_intervals_minutes': list[int], 'offset_strategy': typing.Literal['none', 'start-end', 'time-interval'], 'pump_power_mWcm2': typing.Optional[float], 'pump_source': <class 'str'>, 'wait_time_s': typing.Optional[float], 'wavelengths_nm': typing.Union[tuple[float, float, float], list[float], NoneType]}

__dataclass_fields__ = {'additional_wait_time_s': Field(name='additional_wait_time_s',type=<class 'float'>,default=0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Time in seconds to wait for the signal to stabilize after changing the wavelength.\nSet to `0` for no wait time, and to `None` to automatically choose a value based on the lock-in time constant.', 'valid': (0, 999999)}),kw_only=False,_field_type=_FIELD), 'auto_gain': Field(name='auto_gain',type=<class 'bool'>,default=False,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Whether to automatically adjust the gain during the measurement to stay in the optimum DC region. Not current implemented yet.'}),kw_only=False,_field_type=_FIELD), 'auto_sensitivity': Field(name='auto_sensitivity',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Whether to automatically increase the lock-in sensitivity on overloads.'}),kw_only=False,_field_type=_FIELD), 'energies_eV': Field(name='energies_eV',type=typing.Union[tuple[float, float, float], list[float], NoneType],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Energy range in eV. Must be either a list of values or a tuple (start, stop, step). Only one of ``wavelengths_nm`` or ``energies_eV`` may be set.', 'metadatas': {'tuple': {'metadatas': ({'decimals': 3, 'default': 1.55}, {'decimals': 3, 'default': 2.8}, {'decimals': 3, 'default': 0.005}), 'labels': ('Start', 'Stop', 'Step')}, 'list': {'metadatas': {'decimals': 3}}}}),kw_only=False,_field_type=_FIELD), 'measurement_time_s': Field(name='measurement_time_s',type=<class 'float'>,default=30,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Time in seconds where data is recorded at each wavelength.', 'valid': (0, 9999999)}),kw_only=False,_field_type=_FIELD), 'offset_intervals_minutes': Field(name='offset_intervals_minutes',type=list[int],default=<dataclasses._MISSING_TYPE object>,default_factory=<function MeasurementParameters.<lambda>>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': "How many minutes to wait after the last offset measurement. The last interval is repeated indefinetely.\nOnly applies when offset_strategy='time-interval'.\nStart and end offsets are always recorded, unless offset_strategy='none'."}),kw_only=False,_field_type=_FIELD), 'offset_strategy': Field(name='offset_strategy',type=typing.Literal['none', 'start-end', 'time-interval'],default='time-interval',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Which offset reduction strategy to use. Determines where offset measurements are added.'}),kw_only=False,_field_type=_FIELD), 'pump_power_mWcm2': Field(name='pump_power_mWcm2',type=typing.Optional[float],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Power in mW/cm^2. If ``pump_source`` is set and a conversion table exists for the source then the ``power_mW`` setting for lasers or the `current_A` setting for LEDs can be overwritten with the value corresponding to the ``power_mWcm2`` setting.'}),kw_only=False,_field_type=_FIELD), 'pump_source': Field(name='pump_source',type=<class 'str'>,default='none',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': "String describing which pump source is used.\nIf 'led', then the values from :py:attr:`PrsSettings.led` are applied. If 'laser', then the values from :py:attr:`PrsSettings.laser` are applied.", 'valid': ['laser', 'led', 'laser-manual', 'led-manual', 'none', 'manual']}),kw_only=False,_field_type=_FIELD), 'wait_time_s': Field(name='wait_time_s',type=typing.Optional[float],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Time in seconds to wait for the signal to stabilize after changing the wavelength.\nSet to `0` for no wait time, and to `None` to automatically choose a value based on the lock-in time constant.', 'valid': (0, 999999)}),kw_only=False,_field_type=_FIELD), 'wavelengths_nm': Field(name='wavelengths_nm',type=typing.Union[tuple[float, float, float], list[float], NoneType],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Wavelength range in nm. Must be either a list of values or a tuple (start, stop, step). Only one of ``wavelengths_nm`` or ``energies_eV`` may be set.', 'metadatas': {'tuple': {'metadatas': ({'decimals': 3, 'default': 420}, {'decimals': 3, 'default': 800}, {'decimals': 3, 'default': 1}), 'labels': ('Start', 'Stop', 'Step')}, 'list': {'metadatas': {'decimals': 3}}}}),kw_only=False,_field_type=_FIELD)}

__dataclass_params__ = _DataclassParams(init=True,repr=True,eq=True,order=False,unsafe_hash=False,frozen=False,match_args=True,kw_only=False,slots=False,weakref_slot=False)

__dict__ = mappingproxy({'__module__': 'prsctrl.measurement.settings', '__firstlineno__': 44, '__annotations__': {'measurement_time_s': <class 'float'>, 'wait_time_s': typing.Optional[float], 'additional_wait_time_s': <class 'float'>, 'pump_source': <class 'str'>, 'pump_power_mWcm2': typing.Optional[float], 'auto_gain': <class 'bool'>, 'auto_sensitivity': <class 'bool'>, 'wavelengths_nm': typing.Union[tuple[float, float, float], list[float], NoneType], 'energies_eV': typing.Union[tuple[float, float, float], list[float], NoneType], 'offset_strategy': typing.Literal['none', 'start-end', 'time-interval'], 'offset_intervals_minutes': list[int]}, 'measurement_time_s': 30, 'wait_time_s': None, 'additional_wait_time_s': 0, 'pump_source': 'none', 'pump_power_mWcm2': None, 'auto_gain': False, 'auto_sensitivity': True, 'wavelengths_nm': None, 'energies_eV': None, 'offset_strategy': 'time-interval', 'get_wavelengths_nm': <function MeasurementParameters.get_wavelengths_nm>, 'get_wavelengths_nm_with_offsets': <function MeasurementParameters.get_wavelengths_nm_with_offsets>, 'get_metadata': <function MeasurementParameters.get_metadata>, '__static_attributes__': ('energies_eV', 'wavelengths_nm'), '__doc__': "MeasurementParameters(measurement_time_s: float = 30, wait_time_s: Optional[float] = None, additional_wait_time_s: float = 0, pump_source: str = 'none', pump_power_mWcm2: Optional[float] = None, auto_gain: bool = False, auto_sensitivity: bool = True, wavelengths_nm: Union[tuple[float, float, float], list[float], NoneType] = None, energies_eV: Union[tuple[float, float, float], list[float], NoneType] = None, offset_strategy: Literal['none', 'start-end', 'time-interval'] = 'time-interval', offset_intervals_minutes: list[int] = <factory>)", '__dataclass_params__': _DataclassParams(init=True,repr=True,eq=True,order=False,unsafe_hash=False,frozen=False,match_args=True,kw_only=False,slots=False,weakref_slot=False), '__dataclass_fields__': {'measurement_time_s': Field(name='measurement_time_s',type=<class 'float'>,default=30,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Time in seconds where data is recorded at each wavelength.', 'valid': (0, 9999999)}),kw_only=False,_field_type=_FIELD), 'wait_time_s': Field(name='wait_time_s',type=typing.Optional[float],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Time in seconds to wait for the signal to stabilize after changing the wavelength.\nSet to `0` for no wait time, and to `None` to automatically choose a value based on the lock-in time constant.', 'valid': (0, 999999)}),kw_only=False,_field_type=_FIELD), 'additional_wait_time_s': Field(name='additional_wait_time_s',type=<class 'float'>,default=0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Time in seconds to wait for the signal to stabilize after changing the wavelength.\nSet to `0` for no wait time, and to `None` to automatically choose a value based on the lock-in time constant.', 'valid': (0, 999999)}),kw_only=False,_field_type=_FIELD), 'pump_source': Field(name='pump_source',type=<class 'str'>,default='none',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': "String describing which pump source is used.\nIf 'led', then the values from :py:attr:`PrsSettings.led` are applied. If 'laser', then the values from :py:attr:`PrsSettings.laser` are applied.", 'valid': ['laser', 'led', 'laser-manual', 'led-manual', 'none', 'manual']}),kw_only=False,_field_type=_FIELD), 'pump_power_mWcm2': Field(name='pump_power_mWcm2',type=typing.Optional[float],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Power in mW/cm^2. If ``pump_source`` is set and a conversion table exists for the source then the ``power_mW`` setting for lasers or the `current_A` setting for LEDs can be overwritten with the value corresponding to the ``power_mWcm2`` setting.'}),kw_only=False,_field_type=_FIELD), 'auto_gain': Field(name='auto_gain',type=<class 'bool'>,default=False,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Whether to automatically adjust the gain during the measurement to stay in the optimum DC region. Not current implemented yet.'}),kw_only=False,_field_type=_FIELD), 'auto_sensitivity': Field(name='auto_sensitivity',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Whether to automatically increase the lock-in sensitivity on overloads.'}),kw_only=False,_field_type=_FIELD), 'wavelengths_nm': Field(name='wavelengths_nm',type=typing.Union[tuple[float, float, float], list[float], NoneType],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Wavelength range in nm. Must be either a list of values or a tuple (start, stop, step). Only one of ``wavelengths_nm`` or ``energies_eV`` may be set.', 'metadatas': {'tuple': {'metadatas': ({'decimals': 3, 'default': 420}, {'decimals': 3, 'default': 800}, {'decimals': 3, 'default': 1}), 'labels': ('Start', 'Stop', 'Step')}, 'list': {'metadatas': {'decimals': 3}}}}),kw_only=False,_field_type=_FIELD), 'energies_eV': Field(name='energies_eV',type=typing.Union[tuple[float, float, float], list[float], NoneType],default=None,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Energy range in eV. Must be either a list of values or a tuple (start, stop, step). Only one of ``wavelengths_nm`` or ``energies_eV`` may be set.', 'metadatas': {'tuple': {'metadatas': ({'decimals': 3, 'default': 1.55}, {'decimals': 3, 'default': 2.8}, {'decimals': 3, 'default': 0.005}), 'labels': ('Start', 'Stop', 'Step')}, 'list': {'metadatas': {'decimals': 3}}}}),kw_only=False,_field_type=_FIELD), 'offset_strategy': Field(name='offset_strategy',type=typing.Literal['none', 'start-end', 'time-interval'],default='time-interval',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Which offset reduction strategy to use. Determines where offset measurements are added.'}),kw_only=False,_field_type=_FIELD), 'offset_intervals_minutes': Field(name='offset_intervals_minutes',type=list[int],default=<dataclasses._MISSING_TYPE object>,default_factory=<function MeasurementParameters.<lambda>>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': "How many minutes to wait after the last offset measurement. The last interval is repeated indefinetely.\nOnly applies when offset_strategy='time-interval'.\nStart and end offsets are always recorded, unless offset_strategy='none'."}),kw_only=False,_field_type=_FIELD)}, '__replace__': <function _replace>, '__hash__': None, '__init__': <function MeasurementParameters.__init__>, '__repr__': <function MeasurementParameters.__repr__>, '__eq__': <function MeasurementParameters.__eq__>, '__match_args__': ('measurement_time_s', 'wait_time_s', 'additional_wait_time_s', 'pump_source', 'pump_power_mWcm2', 'auto_gain', 'auto_sensitivity', 'wavelengths_nm', 'energies_eV', 'offset_strategy', 'offset_intervals_minutes')})

__eq__(other)

Return self==value.

__firstlineno__ = 44

__hash__ = None

__init__(measurement_time_s: float = 30, wait_time_s: float | None = None, additional_wait_time_s: float = 0, pump_source: str = 'none', pump_power_mWcm2: float | None = None, auto_gain: bool = False, auto_sensitivity: bool = True, wavelengths_nm: tuple[float, float, float] | list[float] | None=None, energies_eV: tuple[float, float, float] | list[float] | None=None, offset_strategy: Literal['none', 'start-end', 'time-interval']='time-interval', offset_intervals_minutes: list[int] = <factory>) → None

__match_args__ = ('measurement_time_s', 'wait_time_s', 'additional_wait_time_s', 'pump_source', 'pump_power_mWcm2', 'auto_gain', 'auto_sensitivity', 'wavelengths_nm', 'energies_eV', 'offset_strategy', 'offset_intervals_minutes')

__module__ = 'prsctrl.measurement.settings'

__or__(other)

Merge with another settings class or a dictionary.

__replace__(**changes)

__repr__()

Return repr(self).

__static_attributes__ = ('energies_eV', 'wavelengths_nm')

__weakref__

list of weak references to the object

additional_wait_time_s: float = 0

as_dict() → dict

Convenience wrapper for dataclasses.asdict(self)

auto_gain: bool = False

auto_sensitivity: bool = True

energies_eV: tuple[float, float, float] | list[float] | None = None

classmethod from_dict(data: dict)

Recursively construct a SettingsClass from a dictionary.

If the value of a field is another SettingsClass, from_dict() will be called for that field as well. Handled are:

• SettingsClass

• list[SettingsClass]

• dict[<any>, SettingsClass]

• all of the above as Optional (Union with None)

• a Union with any handled types

Raises:

• ValueError – If data contains a value that has the wrong type for the field of cls (ONLY if the type is a subclass of SettingsClass! Other types are not enforced)

• KeyError – If data contains a key that is not a field name of cls

get_metadata() → dict[str, Any]

Return the measurements settings converted to a metadata dictionary that contains only relevant information.

Leaves out wavelengths and energies, as those will be contained in the data as columns anyways. Leaves out optional values that are set to None.

get_wavelengths_nm(round_to_digits: int | None = 2, update_field: bool = False) → list[float]

Generate a list of wavelengths according to either the ‘wavelengths_nm’ or ‘energies_eV’ field.

Either field may already be a list of values, or a tuple (start, stop, step size).

Parameters:

• round_to_digits – Optional number of digits to round the values to.

• update_field – If True, overwrite the value of ‘wavelengths_nm’ with the returned array and ‘energies_eV’ with None.

Returns:

list of wavelengths in nm

get_wavelengths_nm_with_offsets(time_per_wavelength: int, round_to_digits: int | None = 2, update_field: bool = False) → list[float | str]

Generate a list of wavelengths according to either the ‘wavelengths_nm’ or ‘energies_eV’ field and offset measurements.

Parameters:

• time_per_wavelength – Estimated runtime per wavelength measurements. Required when offset_strategy==”time-interval”.

• round_to_digits – Optional number of digits to round the values to.

• update_field – If True, overwrite the value of ‘wavelengths_nm’ with the returned array and ‘energies_eV’ with None.

Returns:

list of wavelengths in nm and offset measurements

classmethod load_yaml(yaml_path: str, loader=<class 'yaml.loader.Loader'>)

measurement_time_s: float = 30

offset_intervals_minutes: list[int]

offset_strategy: Literal['none', 'start-end', 'time-interval'] = 'time-interval'

pump_power_mWcm2: float | None = None

pump_source: str = 'none'

save_yaml(yaml_path: str)

wait_time_s: float | None = None

wavelengths_nm: tuple[float, float, float] | list[float] | None = None