Data File

DataFile.DataFile	Object to load and keep track of HdF files and their conversions
DataFile.DataFile.difference	Return the difference between two data files by keys
DataFile.DataFile.loadBinning	Small function to check if current binning is equal to wanted binning and if not reloads to binning wanted
DataFile.DataFile.loadMultiFLEXXData	"Dedicated loader for MultiFLEXX data.
DataFile.DataFile.plotA4	Method to plot the fitted A4 values of the normalization table
DataFile.DataFile.plotEf	Method to plot the fitted Ef values of the normalization table
DataFile.DataFile.plotEfOverview	Method to plot the fitted Ef values of the normalization table
DataFile.DataFile.plotNormalization	Method to plot the fitted integrated intensities of the normalization table
DataFile.DataFile.saveNXsqom	Save converted file into an NXsqom.
DataFile.createEmptyDataFile	Create an empty data file with a given sample and measurement parameters.

DataFile Object and Methods

class DataFile.DataFile(fileLocation=None, McStas=False)

Object to load and keep track of HdF files and their conversions

calculateCurratAxeMask(BraggPeaks, dqx=None, dqy=None, dH=None, dK=None, dL=None, spurionType='both', maskInside=True)

Generate an elliptical mask centered on the Currat-Axe spurion.

Parameters

BraggPeaks (-) – List of Bragg peaks to be used for mask. Shape is given by [[H1,K1,L1], [H2,K2,L2], … [HN,KN,LN]]

Kwargs:

• dqx (float): Radius used for masking along qx (default None)

• dqy (float): Radius used for masking along qy (default None)

• dH (float): Radius used for masking along H (default None)

• dK (float): Radius used for masking along K (default None)

• dL (float): Radius used for masking along L (default None)

• spurionType (str): Either monochromator, analyser or both (default ‘both’)

• maskInside (bool): If true, points inside is masked otherwise outside (default True)

Returns

Boolean numpy array with shape equal to self.I.shape

Return type

• mask (list)

Note

If either dqx or dqy is None, utilizes the dH, dK, dL instead.

difference(other, keys={'Ei', 'I', 'Monitor', '_A3', '_A4', '_binning', 'instrument', 'sample', 'scanParameters'})

Return the difference between two data files by keys

loadBinning(binning)

Small function to check if current binning is equal to wanted binning and if not reloads to binning wanted

loadMultiFLEXXData(fileLocation, calibrationFile=None)

“Dedicated loader for MultiFLEXX data.

Parameters

fileLocation (-) – Location of file

Kwargs:

• calibrationFile (str): Location of calibration file (default None: uses shipped calibration)

plotA4(binning=None)

Method to plot the fitted A4 values of the normalization table

Kwargs:

• binning (int): Binning for the corresponding normalization table (default self.binning or 8)

Returns

Figure into which the A4 values are plotted

Return type

• fig (matplotlib figure)

plotEf(binning=None)

Method to plot the fitted Ef values of the normalization table

Kwargs:

• binning (int): Binning for the corresponding normalization table (default self.binning or 8)

Returns

Figure into which the Ef values are plotted

Return type

• fig (matplotlib figure)

plotEfOverview(binning=None)

Method to plot the fitted Ef values of the normalization table

Kwargs:

• binning (int): Binning for the corresponding normalization table (default self.binning or 8)

Returns

Figure into which the Ef values are plotted

Return type

• fig (matplotlib figure)

plotNormalization(binning=None)

Method to plot the fitted integrated intensities of the normalization table

Kwargs:

• binning (int): Binning for the corresponding normalization table (default self.binning or 8)

Returns

Figure into which the Ef values are plotted

Return type

• fig (matplotlib figure)

saveHDF(saveFileName)

Save current HDF file object into an HDF file.

Parameters

saveFileName (-) – File name to be saved into.

saveNXsqom(saveFileName)

Save converted file into an NXsqom.

Parameters

saveFileName (-) – File name to be saved into.

updateCalibration(calibrationFile, overwrite=False)

Update calibrations for the data file. Does not save the changes.

Args:

• calibrationFile (string or list): calibration file, as generated from MJOLNIR.Geometry.Instrument or list of these.

Kwargs:

• overwrite (bool): If true, previous binnings will be overwritten if new files contain same binning (default False)

Note

Changes performed by this method is not saved to disk. If this is wanted, use the saveNXsqom method.

updateSampleParameters(unitCell)

Update unit cell parameters and corresponding UB matrix

Parameters

unitCell (-) – List of cell parameters (a,b,c,alpha,beta,gamma)

DataFile.createEmptyDataFile(A3, A4, Ei, sample, Monitor=50000, A3Off=0.0, A4Off=0.0, title='EmptyDataFileTitle', name='EmptyDataFile', temperature=None, electricField=None, magneticField=None, detectors=104, pixels=1024, normalizationFiles=None)

Create an empty data file with a given sample and measurement parameters.

Parameters

• A3 (-) – Value(s) of measurement A3.

• A4 (-) – Value(s) of measurement A4.

• Ei (-) – Value(s) of measurement Ei.

• sample (-) – Sample measured in data file.

Kwargs:

• Monitor (int): Monitor count for datafile (default 50 000)

• A3Off (float): Offset in A3 used in datafile (default 0.0)

• A4Off (float): Offset in A4 used in datafile (default 0.0)

• title (string): Title of datafile (default EmptyDataFileTitle)

• name (string): name of datafile (default EmptyDataFile)

• temperature (double): Sample temperature (default None)

• electricField (double): Sample electricField (default None)

• magneticField (double): Sample magneticField (default None)

• detectors (int): Number of detectors in spectrometer (default 104)

• pixels (int): Number of pixels/detector in spectrometer (default 1024)

• normalizationFiles (list or string): List or string to normalization file (default None)

Warning

If no normalization file(s) is/are provided, the resulting data file cannot be converted to HKL!