sas.qtgui.Perspectives.SizeDistribution package

Subpackages

Submodules

sas.qtgui.Perspectives.SizeDistribution.SizeDistributionLogic module

class sas.qtgui.Perspectives.SizeDistribution.SizeDistributionLogic.SizeDistributionLogic(data: Data1D | None = None)

Bases: object

All the data-related logic. This class deals exclusively with Data1D/2D No QStandardModelIndex here.

__dict__ = mappingproxy({'__module__': 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionLogic', '__firstlineno__': 23, '__doc__': '\nAll the data-related logic. This class deals exclusively with Data1D/2D\nNo QStandardModelIndex here.\n', '__init__': <function SizeDistributionLogic.__init__>, 'data': <property object>, 'isLoadedData': <function SizeDistributionLogic.isLoadedData>, 'setDataProperties': <function SizeDistributionLogic.setDataProperties>, 'computeDataRange': <function SizeDistributionLogic.computeDataRange>, 'computeBackground': <function SizeDistributionLogic.computeBackground>, 'computeTrustRange': <function SizeDistributionLogic.computeTrustRange>, 'fitBackground': <function SizeDistributionLogic.fitBackground>, 'newDataPlot': <function SizeDistributionLogic.newDataPlot>, 'newSizeDistrPlot': <function SizeDistributionLogic.newSizeDistrPlot>, '__static_attributes__': ('_data', 'background', 'data_fit', 'data_is_loaded', 'di_flag'), '__dict__': <attribute '__dict__' of 'SizeDistributionLogic' objects>, '__weakref__': <attribute '__weakref__' of 'SizeDistributionLogic' objects>, '__annotations__': {'_data': 'LoadData1D | None', 'data_is_loaded': 'bool', 'di_flag': 'bool', 'background': 'LoadData1D | None', 'data_fit': 'LoadData1D | None'}})
__doc__ = '\nAll the data-related logic. This class deals exclusively with Data1D/2D\nNo QStandardModelIndex here.\n'
__firstlineno__ = 23
__init__(data: Data1D | None = None) → None
__module__ = 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionLogic'
__static_attributes__ = ('_data', 'background', 'data_fit', 'data_is_loaded', 'di_flag')
__weakref__

list of weak references to the object

computeBackground(constant: float, scale: float, power: float) → None
computeDataRange() → tuple[float, float]

Compute the minimum and the maximum range of the data.

computeTrustRange(qmin: float, qmax: float) → list[float]

Compute the trusted range (green area in Irena).

property data: Data1D | None

Return the data.

fitBackground(power: float | None, qmin: float, qmax: float) → list[float] | None

Estimate the background power law, given by: scale * q^(power).

Parameters:

power – if a float is given, the power is fixed; if None, the power is fitted

Returns:

fit parameters; [scale] if power is fixed, or [scale, power] if power is fitted

isLoadedData() → bool

Return whether data is loaded.

newDataPlot() → tuple[Data1D, Data1D, Data1D | None]

Create a new 1D data instance.

newSizeDistrPlot(result: MaxEntResult, qmin: float, qmax: float) → tuple[Data1D, Data1D]

Create a new 1D data instance based on fitting results.

setDataProperties() → None

Analyze data and set up some properties important for the presentation layer.

sas.qtgui.Perspectives.SizeDistribution.SizeDistributionPerspective module

class sas.qtgui.Perspectives.SizeDistribution.SizeDistributionPerspective.SizeDistributionWindow(parent: QWidget | None = None)

Bases: QDialog, Ui_SizeDistribution, Perspective

The main window for the Size Distribution perspective.

__annotations__ = {'ext': <class 'str'>, 'name': <class 'str'>}
__doc__ = 'The main window for the Size Distribution perspective.'
__firstlineno__ = 46
__init__(parent: QWidget | None = None) → None
__module__ = 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionPerspective'
__static_attributes__ = ('_allowClose', '_data', '_manager', '_model_item', '_parent', '_path', 'backgd_plot', 'backgd_subtr_plot', 'communicator', 'fit_plot', 'fit_thread', 'is_calculating', 'logic', 'mapper', 'model', 'size_distr_plot', 'trust_plot')
allowBatch() → bool

Tell the caller we don’t accept batch data.

allowSwap() → bool

Tell the caller we don’t accept swapping data.

clearStatistics() → None

Clear the output box.

closeEvent(event: QCloseEvent) → None

Overwrite QDialog close method to allow for custom widget close.

data_plot_signal
enableButtons() → None

Enable buttons when data is present, else disable them.

eventFilter(widget: QObject, event: QEvent) → bool

Catch enter key presses and update data plot.

ext: str = 'ps'
fitComplete(result: MaxEntResult) → None

Receive and display fitting results.

Parameters:

result – MaxEnt fitting result object containing the calculated statistics and fitted data used to update the plots and output.

fittingCompleted(result: MaxEntResult | None) → None

Send the finish message from calculate threads to main thread.

fittingError(etype: type[BaseException], value: BaseException, traceback: TracebackType | None) → None

Handle error in the calculation thread.

fittingFinishedSignal
getBackgroundParams() → tuple[float, float, float]

Collect background parameters from the GUI state.

getFlatBackgroundRange() → tuple[float, float]

Collect background range from the GUI state.

getMaxEntParams() → MaxEntParameters

Collect Max Ent parameters from the GUI state.

getPage() → dict[str, str | bool]

Serializes full state of this fit page into a dictionary.

Returns:

a dictionary of {param_name: value}

getPowerLawBackgroundRange() → tuple[float, float]

Collect power law range from the GUI state.

getState() → dict[str, str | bool]

Collects all active params into a dictionary.

Returns:

a dictionary of {name: value}

getWeightType() → WeightType | None

Return the weight type based on the checked radio button.

help() → None

Open the Size Distribution help.

isClosable() → bool

Return whether this widget is currently closable.

isSerializable() → bool

Tell the caller that this perspective writes its state.

name: str = 'SizeDistribution'
onFitFlatBackground() → None

Fit flat background and update plot.

onFitPowerLaw() → None

Fit background power law and update plot.

onFullFit() → None

Perform a full fit of the size distribution.

onLowQStateChanged(state: int) → None

Slot for state change of the subtract power law checkbox.

onQuickFit() → None

Perform a quick fit of the size distribution.

onRangeReset() → None

Callback for resetting qmin/qmax.

plotData() → None

Plot data, background and background subtracted data.

removeData(data_list: list | None = None) → None

Remove the existing data reference from the Size Distribution Perspective.

reset() → None

Reset the size distribution perspective to an empty state.

resetWindow() → None

Reset the state of input widgets and data structures to default values.

serializeAll() → dict

Serialize the size distribution state so data can be saved. Size distribution is not batch-ready so this will only effect a single page.

Returns:

a dictionary of {data-id: {self.name: {inversion-state}}}

serializeCurrentPage() → dict

Serialize and return a dictionary representing the current state of the size distribution page. Return empty dictionary if no data.

Returns:

a dictionary of {data-id: {self.name: {invariant - state}}}

setClosable(value: bool = True) → None

Allow outsiders close this widget.

setData(data_item: list | None = None, is_batch: bool = False) → None

Obtain a QStandardItem object and parse it to get Data1D/2D Pass it over to the calculator

setupMapper() → None

Set up the mapper.

setupModel() → None

Update boxes with initial values.

setupSlots() → None

Connect the use controls to their appropriate methods.

setupValidators() → None

Apply validators to editable line edits.

setupWindow() → None

Initialize base window state on startup.

staticMetaObject = PySide6.QtCore.QMetaObject("SizeDistributionWindow" inherits "QDialog": Methods:   #41 type=Signal, signature=fittingFinishedSignal(PyObject), parameters=PyObject   #42 type=Signal, signature=data_plot_signal() )
property title: str

Return the window title.

updateBackground() → None

Update the background data.

updateFromParameters(params: dict) → None

Update the GUI state based on a dictionary of parameters. Called by Open Project, Open Analysis, and removeData.

Parameters:

params – a dictionary of {param_name: value}; default values used if not valid

updateQRange(q_range_min: float, q_range_max: float) → None

Update the local model based on calculated values.

updateStatistics(result: MaxEntResult) → None

Update the output box with statistics.

sas.qtgui.Perspectives.SizeDistribution.SizeDistributionThread module

class sas.qtgui.Perspectives.SizeDistribution.SizeDistributionThread.SizeDistributionThread(data: Data1D, background: Data1D, params: MaxEntParameters, completefn: Callable[[MaxEntResult], None] | None = None, updatefn: Callable | None = None, yieldtime: float = 0.01, worktime: float = 0.01, exception_handler: Callable | None = None)

Bases: CalcThread

Thread performing the fit.

__annotations__ = {}
__doc__ = 'Thread performing the fit.'
__firstlineno__ = 16
__init__(data: Data1D, background: Data1D, params: MaxEntParameters, completefn: Callable[[MaxEntResult], None] | None = None, updatefn: Callable | None = None, yieldtime: float = 0.01, worktime: float = 0.01, exception_handler: Callable | None = None) → None
__module__ = 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionThread'
__static_attributes__ = ('background', 'data', 'params', 'starttime')
compute(*args, **kwargs) → None

Perform the size distribution fit.

sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils module

class sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils.MaxEntParameters(qmin: float = 0.0, qmax: float = 0.1, dmin: float = 10.0, dmax: float = 1000.0, num_bins: int = 100, log_binning: bool = True, model: str = 'ellipsoid', aspect_ratio: float = 1.0, contrast: float = 1.0, sky_background: float = 1e-06, max_iterations: int = 100, use_weights: bool = True, weight_type: WeightType | None = WeightType.DI, weight_factor: float = 1.0, weight_percent: float = 1.0, full_fit: bool = True)

Bases: object

Parameters for the maximum entropy size distribution fit.

__annotations__ = {'aspect_ratio': <class 'float'>, 'contrast': <class 'float'>, 'dmax': <class 'float'>, 'dmin': <class 'float'>, 'full_fit': <class 'bool'>, 'log_binning': <class 'bool'>, 'max_iterations': <class 'int'>, 'model': <class 'str'>, 'num_bins': <class 'int'>, 'qmax': <class 'float'>, 'qmin': <class 'float'>, 'sky_background': <class 'float'>, 'use_weights': <class 'bool'>, 'weight_factor': <class 'float'>, 'weight_percent': <class 'float'>, 'weight_type': sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils.WeightType | None}
__dataclass_fields__ = {'aspect_ratio': Field(name='aspect_ratio',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'contrast': Field(name='contrast',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'dmax': Field(name='dmax',type=<class 'float'>,default=1000.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'dmin': Field(name='dmin',type=<class 'float'>,default=10.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'full_fit': Field(name='full_fit',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'log_binning': Field(name='log_binning',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'max_iterations': Field(name='max_iterations',type=<class 'int'>,default=100,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'model': Field(name='model',type=<class 'str'>,default='ellipsoid',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'num_bins': Field(name='num_bins',type=<class 'int'>,default=100,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'qmax': Field(name='qmax',type=<class 'float'>,default=0.1,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'qmin': Field(name='qmin',type=<class 'float'>,default=0.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'sky_background': Field(name='sky_background',type=<class 'float'>,default=1e-06,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'use_weights': Field(name='use_weights',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'weight_factor': Field(name='weight_factor',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'weight_percent': Field(name='weight_percent',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'weight_type': Field(name='weight_type',type=sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils.WeightType | None,default=<WeightType.DI: 'dI'>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),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__': 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils', '__firstlineno__': 39, '__annotations__': {'qmin': <class 'float'>, 'qmax': <class 'float'>, 'dmin': <class 'float'>, 'dmax': <class 'float'>, 'num_bins': <class 'int'>, 'log_binning': <class 'bool'>, 'model': <class 'str'>, 'aspect_ratio': <class 'float'>, 'contrast': <class 'float'>, 'sky_background': <class 'float'>, 'max_iterations': <class 'int'>, 'use_weights': <class 'bool'>, 'weight_type': sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils.WeightType | None, 'weight_factor': <class 'float'>, 'weight_percent': <class 'float'>, 'full_fit': <class 'bool'>}, '__doc__': 'Parameters for the maximum entropy size distribution fit.', 'qmin': 0.0, 'qmax': 0.1, 'dmin': 10.0, 'dmax': 1000.0, 'num_bins': 100, 'log_binning': True, 'model': 'ellipsoid', 'aspect_ratio': 1.0, 'contrast': 1.0, 'sky_background': 1e-06, 'max_iterations': 100, 'use_weights': True, 'weight_type': <WeightType.DI: 'dI'>, 'weight_factor': 1.0, 'weight_percent': 1.0, 'full_fit': True, '__static_attributes__': (), '__dict__': <attribute '__dict__' of 'MaxEntParameters' objects>, '__weakref__': <attribute '__weakref__' of 'MaxEntParameters' objects>, '__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__': {'qmin': Field(name='qmin',type=<class 'float'>,default=0.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'qmax': Field(name='qmax',type=<class 'float'>,default=0.1,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'dmin': Field(name='dmin',type=<class 'float'>,default=10.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'dmax': Field(name='dmax',type=<class 'float'>,default=1000.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'num_bins': Field(name='num_bins',type=<class 'int'>,default=100,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'log_binning': Field(name='log_binning',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'model': Field(name='model',type=<class 'str'>,default='ellipsoid',default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'aspect_ratio': Field(name='aspect_ratio',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'contrast': Field(name='contrast',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'sky_background': Field(name='sky_background',type=<class 'float'>,default=1e-06,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'max_iterations': Field(name='max_iterations',type=<class 'int'>,default=100,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'use_weights': Field(name='use_weights',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'weight_type': Field(name='weight_type',type=sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils.WeightType | None,default=<WeightType.DI: 'dI'>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'weight_factor': Field(name='weight_factor',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'weight_percent': Field(name='weight_percent',type=<class 'float'>,default=1.0,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'full_fit': Field(name='full_fit',type=<class 'bool'>,default=True,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD)}, '__replace__': <function _replace>, '__hash__': None, '__init__': <function MaxEntParameters.__init__>, '__repr__': <function MaxEntParameters.__repr__>, '__eq__': <function MaxEntParameters.__eq__>, '__match_args__': ('qmin', 'qmax', 'dmin', 'dmax', 'num_bins', 'log_binning', 'model', 'aspect_ratio', 'contrast', 'sky_background', 'max_iterations', 'use_weights', 'weight_type', 'weight_factor', 'weight_percent', 'full_fit')})
__doc__ = 'Parameters for the maximum entropy size distribution fit.'
__eq__(other)

Return self==value.

__firstlineno__ = 39
__hash__ = None
__init__(qmin: float = 0.0, qmax: float = 0.1, dmin: float = 10.0, dmax: float = 1000.0, num_bins: int = 100, log_binning: bool = True, model: str = 'ellipsoid', aspect_ratio: float = 1.0, contrast: float = 1.0, sky_background: float = 1e-06, max_iterations: int = 100, use_weights: bool = True, weight_type: WeightType | None = WeightType.DI, weight_factor: float = 1.0, weight_percent: float = 1.0, full_fit: bool = True) → None
__match_args__ = ('qmin', 'qmax', 'dmin', 'dmax', 'num_bins', 'log_binning', 'model', 'aspect_ratio', 'contrast', 'sky_background', 'max_iterations', 'use_weights', 'weight_type', 'weight_factor', 'weight_percent', 'full_fit')
__module__ = 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils'
__replace__(**changes)
__repr__()

Return repr(self).

__static_attributes__ = ()
__weakref__

list of weak references to the object

aspect_ratio: float = 1.0
contrast: float = 1.0
dmax: float = 1000.0
dmin: float = 10.0
full_fit: bool = True
log_binning: bool = True
max_iterations: int = 100
model: str = 'ellipsoid'
num_bins: int = 100
qmax: float = 0.1
qmin: float = 0.0
sky_background: float = 1e-06
use_weights: bool = True
weight_factor: float = 1.0
weight_percent: float = 1.0
weight_type: WeightType | None = 'dI'
class sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils.MaxEntResult(convergences: list[bool], num_iters: list[int], chisq: float, bins: list[float], bin_mag: list[float], bin_diff: list[float], bin_err: list[float], data_max_ent: Data1D, statistics: dict)

Bases: object

Results of the maximum entropy size distribution fit.

__annotations__ = {'bin_diff': list[float], 'bin_err': list[float], 'bin_mag': list[float], 'bins': list[float], 'chisq': <class 'float'>, 'convergences': list[bool], 'data_max_ent': <class 'sasdata.dataloader.data_info.Data1D'>, 'num_iters': list[int], 'statistics': <class 'dict'>}
__dataclass_fields__ = {'bin_diff': Field(name='bin_diff',type=list[float],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), 'bin_err': Field(name='bin_err',type=list[float],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), 'bin_mag': Field(name='bin_mag',type=list[float],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), 'bins': Field(name='bins',type=list[float],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), 'chisq': Field(name='chisq',type=<class 'float'>,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), 'convergences': Field(name='convergences',type=list[bool],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), 'data_max_ent': Field(name='data_max_ent',type=<class 'sasdata.dataloader.data_info.Data1D'>,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), 'num_iters': Field(name='num_iters',type=list[int],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), 'statistics': Field(name='statistics',type=<class 'dict'>,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)}
__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__': 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils', '__firstlineno__': 60, '__annotations__': {'convergences': list[bool], 'num_iters': list[int], 'chisq': <class 'float'>, 'bins': list[float], 'bin_mag': list[float], 'bin_diff': list[float], 'bin_err': list[float], 'data_max_ent': <class 'sasdata.dataloader.data_info.Data1D'>, 'statistics': <class 'dict'>}, '__doc__': 'Results of the maximum entropy size distribution fit.', '__static_attributes__': (), '__dict__': <attribute '__dict__' of 'MaxEntResult' objects>, '__weakref__': <attribute '__weakref__' of 'MaxEntResult' objects>, '__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__': {'convergences': Field(name='convergences',type=list[bool],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), 'num_iters': Field(name='num_iters',type=list[int],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), 'chisq': Field(name='chisq',type=<class 'float'>,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), 'bins': Field(name='bins',type=list[float],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), 'bin_mag': Field(name='bin_mag',type=list[float],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), 'bin_diff': Field(name='bin_diff',type=list[float],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), 'bin_err': Field(name='bin_err',type=list[float],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), 'data_max_ent': Field(name='data_max_ent',type=<class 'sasdata.dataloader.data_info.Data1D'>,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), 'statistics': Field(name='statistics',type=<class 'dict'>,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)}, '__replace__': <function _replace>, '__hash__': None, '__init__': <function MaxEntResult.__init__>, '__repr__': <function MaxEntResult.__repr__>, '__eq__': <function MaxEntResult.__eq__>, '__match_args__': ('convergences', 'num_iters', 'chisq', 'bins', 'bin_mag', 'bin_diff', 'bin_err', 'data_max_ent', 'statistics')})
__doc__ = 'Results of the maximum entropy size distribution fit.'
__eq__(other)

Return self==value.

__firstlineno__ = 60
__hash__ = None
__init__(convergences: list[bool], num_iters: list[int], chisq: float, bins: list[float], bin_mag: list[float], bin_diff: list[float], bin_err: list[float], data_max_ent: Data1D, statistics: dict) → None
__match_args__ = ('convergences', 'num_iters', 'chisq', 'bins', 'bin_mag', 'bin_diff', 'bin_err', 'data_max_ent', 'statistics')
__module__ = 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils'
__replace__(**changes)
__repr__()

Return repr(self).

__static_attributes__ = ()
__weakref__

list of weak references to the object

bin_diff: list[float]
bin_err: list[float]
bin_mag: list[float]
bins: list[float]
chisq: float
convergences: list[bool]
data_max_ent: Data1D
num_iters: list[int]
statistics: dict
class sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils.WeightType(*values)

Bases: StrEnum

Enumeration of weight types for the size distribution fit.

DI = 'dI'
NONE = 'None'
PERCENT_I = 'percentI'
SQRT_I = 'sqrt(I Data)'
__doc__ = 'Enumeration of weight types for the size distribution fit.'
__format__(format_spec, /)

Return a formatted version of the string as described by format_spec.

__module__ = 'sas.qtgui.Perspectives.SizeDistribution.SizeDistributionUtils'
__new__(value)
__str__()

Return str(self).

static _generate_next_value_(name, start, count, last_values)

Return the lower-cased version of the member name.

Module contents