pyFAI.gui.helper package

pyFAI.gui.helper.MarkerManager module

class pyFAI.gui.helper.MarkerManager.MarkerManager(plot, markerModel, pixelBasedPlot=False)

Bases: object

Synchronize the display of markers from MarkerModel to a plot.

__init__(plot, markerModel, pixelBasedPlot=False)

createMarkGeometryAction(parent, mousePos)

createMarkPixelAction(parent, mousePos)

createRemoveClosestMaskerAction(parent, mousePos)

dataToChiTth(data): Returns chi and 2theta angles in radian from data coordinate

findClosestMarker(mousePos, delta=20)

getMarkerLocation(marker): Returns the location of the marker in the plot axes

updatePhysicalMarkerPixels(geometry)

updateProjection(geometry, radialUnit, wavelength, directDist, redraw=True)

pyFAI.gui.helper.ProcessingWidget module

pyFAI.gui.helper.ProcessingWidget.createProcessingWidgetOverlay(parent)

Create a widget overlay to show that the application is processing data to update the plot.

Parameters:: widget (qt.QWidget) – Widget containing the overlay
Return type:: qt.QWidget

pyFAI.gui.helper.RingCalibration module

class pyFAI.gui.helper.RingCalibration.GeometryRefinementContext(*args, **kwargs)

Bases: object

Store the full context of the GeometryRefinement object

Right now, GeometryRefinement store the bound but do not store the fixed constraints. It make the context difficult to manage and to trust.

PARAMETERS = ['dist', 'poni1', 'poni2', 'rot1', 'rot2', 'rot3', 'wavelength']

__init__(*args, **kwargs)

bounds()

chi2()

fixed()

getParams(): Returns list of parameters

guess_poni()

refine(maxiter)

setBounds(bounds)

setFixed(fixed)

setParams(params): Set the fit parameter values from the list of values

class pyFAI.gui.helper.RingCalibration.RingCalibration(image, mask, calibrant, detector, wavelength, peaks, method)

Bases: object

__init__(image, mask, calibrant, detector, wavelength, peaks, method)

defaultGeometryConstraintsModel()

Returns the default constraints

Not the one used, but the one initially set to the refinement engine.

fromGeometryConstraintsModel(constraintsModel)

fromGeometryModel(model, resetResidual=True)

getBeamCenter()

getIndexedRings()

Returns polygons of rings

Returns:: List of tuples with ring (index, angle) available
Return type:: dict[ringId] = angle

getMask(): Returns the mask used to compute the tth.

getPoni()

“Returns the PONI coord in image coordinate.

That’s an approximation of the PONI coordinate at pixel precision

getPyfaiGeometry()

getRings()

Returns polygons of rings

Returns:: List of ring angles available
Return type:: List[float]

getRms()

Returns the RMS (root mean square) computed from the current fitting.

The unit is the radian.

getTwoThetaArray(): Returns the 2th array corresponding to the calibrated image

init(peaks, method, geometry, constraintsModel)

isValid(): Returns true if it can be use to calibrate the data.

refine(max_iter=500, seconds=10): Contains the common geometry refinement part

toGeometryConstraintsModel(contraintsModel, reachFromGeoRef=True)

toGeometryModel(model)

update(image, mask, calibrant, detector, wavelength=None)

pyFAI.gui.helper.RingExtractor module

class pyFAI.gui.helper.RingExtractor.RingExtractorThread(parent)

Bases: QThread

Job to process data and collect peaks according to a diffraction ring modelization.

__init__(parent): Constructor

errorString(): Returns the error message in case of failure

isAborted(): Returns whether the theard was aborted or not.

Note

Aborted thead are not finished theads.

resultPeaks()

Returns the extracted peaks.

Return type:: dict

run(self)

runProcess()

Extract the peaks.

Raises:: ValueError – If a mandatory setting is not initialized.
Return type:: bool
Returns:: True if successed

setExperimentSettings(experimentSettings, copy)

Set the experiment data.

Parameters:

experimentSettings (..model.ExperimentSettingsModel.ExperimentSettingsModel) – Contains the modelization of the problem
copy (bool) – If true copy the data for a thread safe processing

setGeometryModel(geometryModel): Define a geometry model as source of the diffraction ring modelization

setMaxRings(maxRings): Set max ring to extract

setPeaksModel(peaksModel): Define a set of peaks as source of the diffraction ring modelization

setPointPerDegree(pointPerDegree): Specify the amount of peak to extract per degree

setRingNumbers(ringNumbers)

Specify a set of rings to extract

Parameters:: ringNumbers (List[int]) – List of number (1 is the 1st ring)

setUserData(name, value): Store key-value information from caller to be retrived when the processing finish.

sigProcessLocationChanged

pyqtSignal(*types, name: str = …, revision: int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

toGeometryModel(model)

userData(name): Returns a stored user data.

pyFAI.gui.helper.SynchronizeMaskToolColor module

Utils to update the plot background according to the changes of the application styles

class pyFAI.gui.helper.SynchronizeMaskToolColor.SynchronizeMaskToolColor(maskTool=None)

Bases: object

__init__(maskTool=None)

getMaskTool()

pyFAI.gui.helper.SynchronizePlotBackground module

Utils to update the plot background according to the changes of the application styles

class pyFAI.gui.helper.SynchronizePlotBackground.SynchronizePlotBackground(plot=None)

Bases: object

__init__(plot=None)

getPlot()

pyFAI.gui.helper.SynchronizeRawView module

class pyFAI.gui.helper.SynchronizeRawView.SynchronizeRawView

Bases: object

Synchronize the raw view of plots altogether.

The active plot of each tasks synchonizing a model containing information to reach the loacation of the view.

When the task is shown, the view of the visible plot is synchronized only if the shared view was changed.

__init__()

registerModel(model)

registerPlot(plot)

registerTask(task)

pyFAI.gui.helper.model_transform module

Helper to transform or extract information from the abstratc model.

pyFAI.gui.helper.model_transform.createControlPoints(model)

Create ControlPoints object from the calibration model

Return type:: pyFAI.control_points.ControlPoints

pyFAI.gui.helper.model_transform.createPeaksArray(model)

Create a contiguous peak array containing (y, x, ring number)

Parameters:: model (PeakSelectionModel) – A set of selected peaks
Return type:: numpy.ndarray

pyFAI.gui.helper.model_transform.createRing(points, peakSelectionModel, ringNumber=None, context=None)

Create a new ring from a group of points

Return type:: PeakModel

pyFAI.gui.helper.model_transform.filterControlPoints(filterCallback, peakSelectionModel, removedPeaks=None)

Filter each peaks of the model using a callback

Parameters:

filter (Callable[int,int,bool]) – Filter returning true is the peak have to stay in the result.
peakSelectionModel (PeakSelectionModel) – Model to filter
removedPeaks (List[Tuple[int,int]]) – Provide a list to feed it with removed peaks from the model.

pyFAI.gui.helper.model_transform.geometryModelToGeometry(geometryModel, geometry)

pyFAI.gui.helper.model_transform.initPeaksFromControlPoints(peakSelectionModel, controlPoints, context=None)

Initialize peak selection model using control points object

Return type:: pyFAI.control_points.ControlPoints

Module contents

Helper relative to the calibration app