prsctrl.measurement.pump_power_calibration.PowerCalibration

class PowerCalibration(light_source_type: Literal['led', 'laser'], light_source_name: str, power_meter_name: str, wavelength_nm: float, beam_area_cm2: float, calibration_data: NDArray, method: Literal['interpolate', 'polyfit'] = 'interpolate', polyfit_degree: int = 2)

Bases: SettingsClass

Class holding calibration data for converting an LED current in A or a laser power in mW to the effective power density in mW/cm^2 (and back).

Methods

as_dict	Convenience wrapper for dataclasses.asdict(self)
from_dict	Recursively construct a SettingsClass from a dictionary.
laser_power_mW_to_power_density_mWcm2
led_current_A_to_power_density_mWcm2
load_yaml
plot
power_density_mWcm2_to_laser_power_mW
power_density_mWcm2_to_led_current_A
power_density_mWcm2_to_setting
save_yaml
setting_to_power_density_mWcm2

Attributes

method
polyfit_degree
light_source_type
light_source_name
power_meter_name
wavelength_nm
beam_area_cm2
calibration_data

__annotations__ = {'beam_area_cm2': <class 'float'>, 'calibration_data': NDArray, 'light_source_name': <class 'str'>, 'light_source_type': typing.Literal['led', 'laser'], 'method': typing.Literal['interpolate', 'polyfit'], 'polyfit_degree': <class 'int'>, 'power_meter_name': <class 'str'>, 'wavelength_nm': <class 'float'>}

__dataclass_fields__ = {'beam_area_cm2': Field(name='beam_area_cm2',type=<class 'float'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Beam area in cm^2 for calibration (or active detector area).'}),kw_only=False,_field_type=_FIELD), 'calibration_data': Field(name='calibration_data',type=NDArray,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Calibration data with shape (n_steps, 2).\nFirst column is either laser power in mW or led current in A.\nSecond column is measured power density in mW/cm^2.'}),kw_only=False,_field_type=_FIELD), 'light_source_name': Field(name='light_source_name',type=<class 'str'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Name of the light source.'}),kw_only=False,_field_type=_FIELD), 'light_source_type': Field(name='light_source_type',type=typing.Literal['led', 'laser'],default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'method': Field(name='method',type=typing.Literal['interpolate', 'polyfit'],default='interpolate',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Method to use for conversion (both directions):\ninterpolate: linearly interpolate the data\npolyfit: fit a polynomial to the data (polynomial degree is set by polyfit_degree).'}),kw_only=False,_field_type=_FIELD), 'polyfit_degree': Field(name='polyfit_degree',type=<class 'int'>,default=2,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': "The degree of the polynomial to fit the calibration data (if method is polyfit').", 'valid': (1, 10)}),kw_only=False,_field_type=_FIELD), 'power_meter_name': Field(name='power_meter_name',type=<class 'str'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Name of the power meter that was used.'}),kw_only=False,_field_type=_FIELD), 'wavelength_nm': Field(name='wavelength_nm',type=<class 'float'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Wavelength of the light source in nm.'}),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.pump_power_calibration', '__firstlineno__': 17, '__annotations__': {'light_source_type': typing.Literal['led', 'laser'], 'light_source_name': <class 'str'>, 'power_meter_name': <class 'str'>, 'wavelength_nm': <class 'float'>, 'beam_area_cm2': <class 'float'>, 'calibration_data': NDArray, 'method': typing.Literal['interpolate', 'polyfit'], 'polyfit_degree': <class 'int'>}, '__doc__': 'Class holding calibration data for converting an LED current in A or a laser power in mW to the effective power density in mW/cm^2 (and back).', 'method': 'interpolate', 'polyfit_degree': 2, 'setting_to_power_density_mWcm2': <function PowerCalibration.setting_to_power_density_mWcm2>, 'power_density_mWcm2_to_setting': <function PowerCalibration.power_density_mWcm2_to_setting>, 'led_current_A_to_power_density_mWcm2': <function PowerCalibration.led_current_A_to_power_density_mWcm2>, 'power_density_mWcm2_to_led_current_A': <function PowerCalibration.power_density_mWcm2_to_led_current_A>, 'laser_power_mW_to_power_density_mWcm2': <function PowerCalibration.laser_power_mW_to_power_density_mWcm2>, 'power_density_mWcm2_to_laser_power_mW': <function PowerCalibration.power_density_mWcm2_to_laser_power_mW>, '_assert_device_type': <function PowerCalibration._assert_device_type>, 'plot': <function PowerCalibration.plot>, '__static_attributes__': (), '__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__': {'light_source_type': Field(name='light_source_type',type=typing.Literal['led', 'laser'],default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'light_source_name': Field(name='light_source_name',type=<class 'str'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Name of the light source.'}),kw_only=False,_field_type=_FIELD), 'power_meter_name': Field(name='power_meter_name',type=<class 'str'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Name of the power meter that was used.'}),kw_only=False,_field_type=_FIELD), 'wavelength_nm': Field(name='wavelength_nm',type=<class 'float'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Wavelength of the light source in nm.'}),kw_only=False,_field_type=_FIELD), 'beam_area_cm2': Field(name='beam_area_cm2',type=<class 'float'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Beam area in cm^2 for calibration (or active detector area).'}),kw_only=False,_field_type=_FIELD), 'calibration_data': Field(name='calibration_data',type=NDArray,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Calibration data with shape (n_steps, 2).\nFirst column is either laser power in mW or led current in A.\nSecond column is measured power density in mW/cm^2.'}),kw_only=False,_field_type=_FIELD), 'method': Field(name='method',type=typing.Literal['interpolate', 'polyfit'],default='interpolate',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': 'Method to use for conversion (both directions):\ninterpolate: linearly interpolate the data\npolyfit: fit a polynomial to the data (polynomial degree is set by polyfit_degree).'}),kw_only=False,_field_type=_FIELD), 'polyfit_degree': Field(name='polyfit_degree',type=<class 'int'>,default=2,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({'doc': "The degree of the polynomial to fit the calibration data (if method is polyfit').", 'valid': (1, 10)}),kw_only=False,_field_type=_FIELD)}, '__replace__': <function _replace>, '__hash__': None, '__init__': <function PowerCalibration.__init__>, '__repr__': <function PowerCalibration.__repr__>, '__eq__': <function PowerCalibration.__eq__>, '__match_args__': ('light_source_type', 'light_source_name', 'power_meter_name', 'wavelength_nm', 'beam_area_cm2', 'calibration_data', 'method', 'polyfit_degree')})

__eq__(other)

Return self==value.

__firstlineno__ = 17

__hash__ = None

__init__(light_source_type: Literal['led', 'laser'], light_source_name: str, power_meter_name: str, wavelength_nm: float, beam_area_cm2: float, calibration_data: NDArray, method: Literal['interpolate', 'polyfit'] = 'interpolate', polyfit_degree: int = 2) → None

__match_args__ = ('light_source_type', 'light_source_name', 'power_meter_name', 'wavelength_nm', 'beam_area_cm2', 'calibration_data', 'method', 'polyfit_degree')

__module__ = 'prsctrl.measurement.pump_power_calibration'

__or__(other)

Merge with another settings class or a dictionary.

__replace__(**changes)

__repr__()

Return repr(self).

__static_attributes__ = ()

__weakref__

list of weak references to the object

_assert_device_type(device_type)

as_dict() → dict

Convenience wrapper for dataclasses.asdict(self)

beam_area_cm2: float

calibration_data: NDArray

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

laser_power_mW_to_power_density_mWcm2(power_mW: float) → float

Parameters:

power_mW – Laser power in mW

Returns:

Power density in mW/cm^2

led_current_A_to_power_density_mWcm2(current_A: float) → float

Parameters:

current_A – LED current in A

Returns:

Power density in mW/cm^2

light_source_name: str

light_source_type: Literal['led', 'laser']

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

method: Literal['interpolate', 'polyfit'] = 'interpolate'

plot(fig=None, axs=None)

polyfit_degree: int = 2

power_density_mWcm2_to_laser_power_mW(power_density_mWcm2: float) → float

Parameters:

power_density_mWcm2 – Power density in mW/cm^2

Returns:

Laser power in mW

power_density_mWcm2_to_led_current_A(power_density_mWcm2: float) → float

Parameters:

power_density_mWcm2 – Power density in mW/cm^2

Returns:

LED current in A

power_density_mWcm2_to_setting(p_mWcm2: float) → float

Parameters:

p – Power density in mW/cm^2

Returns:

Power setting, either LED current in A or laser power in mW

power_meter_name: str

save_yaml(yaml_path: str)

setting_to_power_density_mWcm2(x: float) → float

Parameters:

x – LED current or laser power density

Returns:

Power density in mW/cm^2

wavelength_nm: float