qudi.util.datafitting

ToDo: Document

Functions

`is_fit_model`(cls)
`get_all_fit_models`()

Classes

`FitConfiguration`(name, model[, estimator, ...])
`FitConfigurationsModel`(*args[, configurations])
`FitContainer`(args, config_model, *kwargs)

class qudi.util.datafitting.FitConfiguration(name, model, estimator=None, custom_parameters=None)[source]

Bases: builtins.object

property available_estimators: !! processed by numpydoc !!

property custom_parameters: !! processed by numpydoc !!

property default_parameters: !! processed by numpydoc !!

property estimator: !! processed by numpydoc !!

classmethod from_dict(dict_repr)[source]

property model: !! processed by numpydoc !!

property name: !! processed by numpydoc !!

to_dict()[source]

class qudi.util.datafitting.FitConfigurationsModel(*args, configurations=None, **kwargs)[source]

Bases: PySide2.QtCore.QAbstractListModel

add_configuration(name, model)[source]

property configuration_names: !! processed by numpydoc !!

property configurations: !! processed by numpydoc !!

data(self, index: PySide2.QtCore.QModelIndex, role: int = PySide2.QtCore.Qt.ItemDataRole.DisplayRole) → Any[source]

dump_configs()[source]

Returns all currently held fit configurations as dicts representations containing only data types that can be dumped as YAML in qudi app status.

@return list: List of fit config dict representations.

flags(self, index: PySide2.QtCore.QModelIndex) → PySide2.QtCore.Qt.ItemFlags[source]

get_configuration_by_name(name)[source]

headerData(self, section: int, orientation: PySide2.QtCore.Qt.Orientation, role: int = PySide2.QtCore.Qt.ItemDataRole.DisplayRole) → Any[source]

load_configs(configs)[source]

Initializes or overwrites all currently held fit configurations with a given iterable of dictionary representations.

This method will reset the list model.

Parameters:

configsiterable: Iterable of FitConfiguration dictionary representations. See also: FitConfigurationsModel.dump_configs.

property model_default_parameters: !! processed by numpydoc !!

property model_estimators: !! processed by numpydoc !!

property model_names: !! processed by numpydoc !!

remove_configuration(name)[source]

rowCount(self, parent: PySide2.QtCore.QModelIndex = Invalid(PySide2.QtCore.QModelIndex)) → int[source]

setData(self, index: PySide2.QtCore.QModelIndex, value: Any, role: int = PySide2.QtCore.Qt.ItemDataRole.EditRole) → bool[source]

sigFitConfigurationsChanged: !! processed by numpydoc !!

staticMetaObject = <PySide2.QtCore.QMetaObject object>

class qudi.util.datafitting.FitContainer(*args, config_model, **kwargs)[source]

Bases: PySide2.QtCore.QObject

static dict_result(fit_result: None | lmfit.model.ModelResult, parameters_units: Mapping[str, str] | None = None, export_keys: Iterable[str] | None = ('value', 'stderr')) → dict[source]

property fit_configuration_names: !! processed by numpydoc !!

property fit_configurations: !! processed by numpydoc !!

fit_data(fit_config, x, data)[source]

static formatted_result(fit_result: None | lmfit.model.ModelResult, parameters_units: Mapping[str, str] | None = None) → str[source]

property last_fit: !! processed by numpydoc !!

sigFitConfigurationsChanged: !! processed by numpydoc !!

sigLastFitResultChanged: !! processed by numpydoc !!

staticMetaObject = <PySide2.QtCore.QMetaObject object>

qudi.util.datafitting.get_all_fit_models()[source]

qudi.util.datafitting.is_fit_model(cls)[source]