Data Set

The DataSet object is the interface between the data files and the data treatment and visualziation. It is both responsible for the conversion of raw ‘.h5’-files into ‘.nxs’-files as well as plotting these. Extracting values from this object results in a list of values where the first dimension is determined from the number of data files provided.

DataSet.DataSet

DataSet object to hold all informations about data.

DataSet.DataSet.convertDataFile

Conversion method for converting scan file(s) to hkl file.

DataSet.DataSet.cut1D

Wrapper for 1D cut through constant energy plane from q1 to q2 function returning binned intensity, monitor, normalization and normcount.

DataSet.DataSet.plotCut1D

plot new or already performed cut.

DataSet.DataSet.cutQE

Wrapper for cut data into maps of q and intensity between two q points and given energies.

DataSet.DataSet.plotCutQE

plot of intensity as function of Q between Q1 and Q2 and Energy.

DataSet.DataSet.cutPowder

Cut data powder map with intensity as function of the length of q and energy.

DataSet.DataSet.plotCutPowder

Plotting wrapper for the cutPowder method.

DataSet.DataSet.plotQPlane

Wrapper for plotting tool to show binned intensities in the Q plane between provided energies.

DataSet.DataSet.cutQELine

Method to perform Q-energy cuts from a variable number of points.

DataSet.DataSet.plotCutQELine

Plotting wrapper for the cutQELine method.

This is the data module inteded to be used as a stand-alone data reduction and visualization.

DataSet Object and Methods

Object to take care of all data conversion and treatment taking it from raw hdf5 files obtained at the instrument into re-binned data sets converted to S(q,omega).

DataSet.OxfordList(list)[source]

Create a comma separated string from the strings provided with last comma trailed by ‘and’.

DataSet.binData3D(dx, dy, dz, pos, data, norm=None, mon=None, bins=None)[source]

3D binning of data.

Parameters

  • dx (-) – Step size in x (required).

  • dy (-) – Step size in x (required).

  • dz (-) – Step size in x (required).

  • pos (-) – Position of data points as flattened lists (X,Y,Z) (required).

  • data (-) – Flattened data array (required).

Kwargs:

  • norm (array): Flattened normalization array.

  • mon (array): Flattened monitor array.

  • bins (list of arrays): Bins locating edges in the x, y, and z directions.

Returns

Re-binned intensity (and if provided Normalization, Monitor, and Normalization Count) and X, Y, and Z bins in 3 3D arrays.

Example:

>>> pos = [Qx,Qy,E]
>>> Data,bins = DataSet.binData3D(0.05,0.05,0.2,pos,I,norm=Norm,mon=Monitor)
DataSet.boundaryQ(file, plane, A4Extend=0.0, A3Extend=0.0)[source]

Calculate the boundary of a given scan in Q space A4Extend: in degrees A3Extend: in degrees

DataSet.calculateGrid3D(X, Y, Z)[source]
Generate 3D grid with centers given by X,Y, and Z.

Args:

X (3D array): 3D array of x values generated by np.meshgrid.

Y (3D array): 3D array of y values generated by np.meshgrid.

Z (3D array): 3D array of z values generated by np.meshgrid.

Example:

>>> x = np.linspace(-1.5,1.5,20)
>>> y = np.linspace(0,1.5,10)
>>> z = np.linspace(-1.0,5.5,66)
>>> X,Y,Z = np.meshgrid(x,y,z,indexing='ij')
>>> XX,YY,ZZ = calculateGrid3D(X,Y,Z)

Now XX is a 21x11x67 array containing all x coordinates of the edges exactly midway between the points. Same goes for YY and ZZ with y and z coordinates respectively.

DataSet.convertToHKL(sample, QxQy)[source]

Convert a given list og QPoints to QxQy from UB matrix of sample

Parameters

  • sample (-) – Sample from which the UB matrix is to be used

  • QxQy (-) – List of HKL points to be converted

Returns

List of QxQy points in same shape as provided

Return type

  • HKL (list)

DataSet.convertToQxQy(sample, QPoints)[source]

Convert a given list og QPoints to QxQy from UB matrix of sample

Parameters

  • sample (-) – Sample from which the UB matrix is to be used

  • QPoints (-) – List of HKL points to be converted

Returns

List of QxQy points in same shape as provided

Return type

  • Q (list)

DataSet.convexHullPoints(A3, A4)[source]

Calculate the convex hull of rectangularly spaced A3 and A4 values

DataSet.cut1D(positions, I, Norm, Monitor, q1, q2, width, minPixel, Emin, Emax, plotCoverage=False, extend=False, constantBins=False)[source]

Perform 1D cut through constant energy plane from q1 to q2 returning binned intensity, monitor, normalization and normcount. The full width of the line is width while height is given by Emin and Emax. the minimum step sizes is given by minPixel.

Note

Can only perform cuts for a constant energy plane of definable width.

Parameters

  • positions (-) – position in Qx, Qy, and E in flattend arrays.

  • I (-) – Flatten intensity array

  • Norm (-) – Flatten normalization array

  • Monitor (-) – Flatten monitor array

  • q1 (-) – Start position of cut in format (qx,qy).

  • q2 (-) – End position of cut in format (qx,qy).

  • width (-) – Full width of cut in q-plane.

  • minPixel (-) – Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel.

  • Emin (-) – Minimal energy to include in cut.

  • Emax (-) – Maximal energy to include in cut

Kwargs:

  • plotCoverage (bool): If True, generates plot of all points in the cutting plane and adds bounding box of cut in new figure, if axis, plots on top (default False).

  • extend (bool): Whether or not the cut from q1 to q2 is to be extended throughout the data (default true)

  • constantBins (bool): If True only bins of size minPixel is used (default False)

Returns

Intensity, monitor count, normalization and normalization counts binned in the 1D cut.

  • Bin list (3 arrays): Bin edge positions in plane of size (n+1,3), orthogonal positions of bin edges in plane of size (2,2), and energy edges of size (2).

Return type

  • Data list (4 arrays)

DataSet.cut1DE(positions, I, Norm, Monitor, E1, E2, q, width, minPixel, constantBins=False, background=None)[source]

Perform 1D cut through constant Q point returning binned intensity, monitor, normalization and normcount. The width of the cut is given by the width attribute.

Note

Can only perform cuts for a constant energy plane of definable width.

Parameters

  • positions (-) – position in Qx, Qy, and E in flattend arrays.

  • I (-) – Flatten intensity array

  • Norm (-) – Flatten normalization array

  • Monitor (-) – Flatten monitor array

  • E1 (-) – Start energy.

  • E2 (-) – End energy.

  • q (-) – Q point in (qx,qy)

  • width (-) – Full width of cut in q-plane.

  • minPixel (-) – Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel.

  • Emin (-) – Minimal energy to include in cut.

  • Emax (-) – Maximal energy to include in cut

Kwargs:

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • background (list): If provided perform background subtraction as well

Returns

Intensity, monitor count, normalization and normalization counts binned in the 1D cut.

  • Bin list (1 array): Bin edge positions in energy

Return type

  • Data list (4 arrays)

DataSet.cutPowder(positions, I, Norm, Monitor, EBins, QBins, background=None)[source]

Cut data powder map with intensity as function of the length of q and energy.

Parameters

  • positions (-) – position in Qx, Qy, and E in flattend arrays.

  • I (-) – Flatten intensity array

  • Norm (-) – Flatten normalization array

  • Monitor (-) – Flatten monitor array

  • EBins (-) – Energy bin edges.

  • QBins (-) – Q length bin edges.

Kwargs:

  • background (list): List of background values (default None)

Returns

DataFrame containing qx,qy,H,K,L,Intensity,Normalization,Monitor,BinCount,Int,binDistance for powder cut.

Return type

  • Data list (pandas DataFrame)

DataSet.func(self, function)

Symmetrize data by providing a custom function

Parameters

function (function) – Function to symmetrize

The signature of the function must be func(H,K,L) and must return (H,K,L). An example is

>>> def symmetrize(H,K,L):
>>>     return np.abs(H),np.abs(K),np.abs(L)
DataSet.load(filename)[source]

Function to load an object from a pickled file.

Note

It is not possible to un-pickle an object created in python 3 in python 2 or vice versa.

DataSet.plotA3A4(files, ax=None, planes=[], binningDecimals=3, log=False, returnPatches=False, singleFigure=False, plotTessellation=False, Ei_err=0.05, temperature_err=0.2, magneticField_err=0.2, electricField_err=0.2)[source]

Plot data files together with pixels created around each point in A3-A4 space. Data is binned in the specified planes through their A3 and A4 values. This can result in distorted binning when binning across large energy regions. Data is plotted using the pixels calculated for average plane value, i.e. binning 7,8,9,10, and 11 patches for plane 9 are used for plotting.

Parameters

files (-) – single file or list of files to be binned together

Kwargs:

  • ax (matplotlib axis): Axis into which the planes are to be plotted (Default None, i.e. new)

  • planes (list (of lists)): Planes to be plotted and binned (default [])

  • binningDecimals (int): Number of decimal places A3-A4 positions are rounded before binning (default 3)

  • log (bool): Whether or not to plot intensities as logarithm (default False)

  • returnPatches (bool): If true the method returns the patches otherwise plotted in the given axis (default False)

  • singleFigure (bool): If true, all planes are plotted in same figure (default False)

  • plotTessellation (bool): Plot Tessellation of points (default False)

  • Ei_err (float): Tolerance of E_i for which the values are equal (default = 0.05)

  • temperature_err (float): Tolerance of temperature for which the values are equal (default = 0.2)

  • magneticField_err (float): Tolerance of magnetic field for which the values are equal (default = 0.2)

  • electricField_err (float): Tolerance of electric field for which the values are equal (default = 0.2)

Returns

axis (list of) containing figures for plotted planes.

Return type

  • ax (matplotlib axis or list of)

Raises

- AttributeError –

Examples:

The following example will combine the two files and plot all of the available planes in different figures.

>>> DS = DataSet.DataSet(convertedFiles=[--.nxs,---.nxs])
>>> plt.figure()
>>> ax = plt.gca()
>>>
>>> DataSet.plotA3A4(DS.convertedFiles,ax=ax)

If only a subset of planes or different planes are to be combined the following will achieve this:

>>> DataSet.plotA3A4(DS.convertedFiles,ax=ax,planes=[0,1,2,3,[4,5,6],[8,9]])

Here planes 0 through 3 are plotted separately while 4,5, and 6 as well as 8 and 9 are binned.

Note

Binning planes from different analysers might result in nonsensible binnings.

class DataSet.DataSet(dataFiles=None, normalizationfiles=None, calibrationfiles=None, convertedFiles=None, **kwargs)[source]

DataSet object to hold all informations about data.

Kwargs:

  • dataFiles (string, DataFile or list of strings or DataFiles): List of datafiles or DataFile objects to be used in conversion (default None).

  • normalizationfiles (string or list of strings): Location of Vanadium normalization file(s) (default None).

  • calibrationfiles (string or list of strings): Location of calibration normalization file(s) (default None).

  • convertedFiles (string, DataFile or list of strings): Location of converted data files (default None).

Raises

  • - ValueError –

  • - NotImplementedError –

View3D(dQx, dQy, dE, rlu=True, log=False, grid=False, axis=2, counts=False, adjustable=True, customSlicer=False, instrumentAngles=False, outputFunction=<built-in function print>, backgroundSubtraction=False, cmap=None, CurratAxeBraggList=None, plotCurratAxe=False, cut1DFunctionRectangle=None, cut1DFunctionCircle=None, cut1DFunctionRectanglePerp=None, cut1DFunctionRectangleHorizontal=None, cut1DFunctionRectangleVertical=None, **kwargs)[source]

View data in the Viewer3D object.

Parameters

  • dQx (-) – step size in qx

  • dQy (-) – step size in qy

  • dE (-) – step size in E

Kwargs:

  • rlu (Bool): If true a rlu axis is used for plotting otherwise qx,qy (Default True).

  • log (Bool): If true logarithm of intensity is plotted

  • grid (Bool): If true, grid is plotted. If float or integer, value is used as zorder of grid (Default False)

  • axis (int): Axis shown initially (default 2)

  • counts (bool): If set true, data shown is number of neutrons/pixel

  • adjustable (bool): If set true, 2 sliders will be present allowing to fine tune the c-axis (Default True)

  • customSlicer (bool): If true, utilize the interactive viewer based on PyQtGraph (Default False)

  • instrumenAngles (bool): If true show also A3 and A4 calculations for HKL axis when hovering (Default False)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform backgorund subtraction (default False)

  • outputFunction (func): Function to print the format_coord when the user clicks the axis (default print)

  • CurratAxeBraggList (list): List of Bragg reflections used to calulcate Currat-Axe spurions (default None)

  • plotCurratAxe (bool): Flag to determine whether or not to plot the Currat-Axe spurions

  • cut1DFunctionRectangle (function): Function to be called when generating interactive rectangle cut (default None)

  • cut1DFunctionCircle (function): Function to be called when generating interactive circle cut (default None)

  • kwargs: The remaining kwargs are given to the createQAxis method, intended for tick mark positioning (see createQAxis)

If one plots not using RLU, everything is plotted in real units (1/AA), and the Qx and QY is not rotated. That is, the x axis in energy is not along the projection vector. The cuts of constant Qx and Qy does not represent any symmetry directions in the sample. However, if one utilizes the RLU flag, first Qx and Qy are rotated with first HKL vector along the x-axis. This thus means that cuts of constant Qx (or more correctly along the principal HKL vector) represents a symmetry direction. However, as the data is binned in equal sized voxels, constant Qy does not necessarily correspond to HKL vector 2 (it will in systems with 90 degrees between the two vectors).

absoluteNormalize(sampleMass=None, sampleMolarMass=None, sampleChemicalFormula=None, formulaUnitsPerUnitCell=1.0, sampleGFactor=2.0, correctVanadium=False, vanadiumMass=15.25, vanadiumMonitor=100000, vanadiumSigmaIncoherent=5.08, vanadiumChemicalFormula='V', vanadiumGFactor=2.0, vanadiumUnitsPerUnitCell=1.0, vanadiumMolarMass=None)[source]

Normaliza dataset to absolute units () by

Kwargs:

  • sampleMass (float): Mass of sample in gram

  • sampleChemicalFormula (string): Chemical formula of sample

  • formulaUnitsPerUnitCell (float): Number of formula units per unit cell (default 1.0)

  • sampleDebyeWaller (float): Debye Waller factor (default 1.0)

  • sampleGFactor (float): Magnetic G factor for sample (defalt 2.0)

  • sampleFormFactor (float): Formfactor of sample (default 1.0)

  • correctVanadium (bool): If normalization files have not been updated set this to True (default False)

  • vanadiumMass (float): Mass of vanadium used in normalization in gram (default 15.25)

  • vanadiumMonitor (int): Monitor count used in normalization scan (default 100000)

  • vanadiumSigmaIncoherent (float): Incoherent scattering strength of Vanadium (default 5.08)

autoSort(sortFunction=None)[source]

Sort datafiles according to lowest energy, then abs(2Theta), then scan direction in A3, then A3 start position.

Kwargs:

  • sortFunction (function): Takes enumerate and data file (Default as described above)

Sorting function takes in (index, dataFile) and should return a tuple of sorting values in descending priority.

Default sorting function is:

>>> def sortFunction(IdxDf):
>>>     df = IdxDf[1]
>>>     return (np.round(df.Ei[0],1), np.abs(np.round(df.twotheta[0],1)), -np.sign(np.diff(df.A3[:2]))[0], np.round(df.A3[0],2))
binData3D(dx, dy, dz, rlu=True, dataFiles=None, backgroundSubtraction=False, noApproximation=False)[source]

Bin a converted data file into voxels with sizes dx*dy*dz. Wrapper for the binData3D functionality.

Parameters

  • dx (-) – step sizes along the x direction (required).

  • dy (-) – step sizes along the y direction (required).

  • dz (-) – step sizes along the z direction (required).

Kwargs:

  • rlu (bool): If True, the rotate QX,QY is used for binning (default True)

  • datafile (string or list of strings): Location(s) of data file to be binned (default converted file in DataSet).

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Raises

- AttributeError –

Returns

List of converted data files having 4 sub arrays: Intensity(counts), Monitor, Normalization, Normalization count

  • bins: 3 arrays containing edge positions in x, y, and z directions.

Return type

  • Datalist

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

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

List of boolean numpy arrays with shapes equal to df.I.shape

Return type

  • mask (list)

Note

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

calculateResolutionMatrix(position, Ei, Ef, rlu=True)[source]

Calculate the resolution ellipsoid matrix at a specific point in reciprocal space

Parameters

  • position (-) – Position in either HKL or Qx,Qy

  • Ei (-) – Incoming energy in meV

  • Ef (-) – Outgoing energy in meV

Kwargs:

  • rlu (bool): If true, position is calculated in reciprocal lattice units, otherwise in QxQy (default True)

Method is based on thew updated calculation from “Analytiucal approach to the 4D-resolution functiuon of three axes neutron spectrometers with focussing monochromators ananalysers” - C. Eckold, O. Sobolev doi: 10.1016/j.nima.2014.03.019

calculateResolutionMatrixAndVectors(position, projectionVector1, projectionVector2, Ei, Ef, rlu=True, rluAxis=False)[source]

Calculate the resolution ellipsoid matrix at a specific point in reciprocal space and project to plane

Parameters

  • position (-) – Position in either HKL or Qx,Qy

  • projectionVector1 (-) – Projection vector in 4D of unit length

  • Ei (-) – Incoming energy in meV

  • Ef (-) – Outgoing energy in meV

Kwargs:

  • rlu (bool): If true, position is calculated in reciprocal lattice units, otherwise in QxQy (default True)

  • rluAxis (bool): If plotting on rluAxis counter rotate eigen vectors with RotMat (default False)

Projection matrix is given by two projections vectors with unit length.

checkSecondOrderElastic(EPeaks, atol=0.2, printing=True)[source]

Check if peaks at certain energies corresponds with second order elastic scattering in data set

Parameters

EPeaks (-) – List of peaks to check

Kwargs:

  • atol (float): Tolerance of Ei calculation (default 0.2 meV)

  • printing (bool): Boolean flag to control printing (default True)

Returns

List of Ei’s corresponding to second order elastic for all peaks. If no Ei is found nan is returned

Return type

  • Eis (list)

convertDataFile(dataFiles=None, binning=None, saveLocation=None, saveFile=False, printFunction=None, deleteOnConvert=True)[source]

Conversion method for converting scan file(s) to hkl file. Converts the given hdf file into NXsqom format and saves in a file with same name, but of type .nxs. Copies all of the old data file into the new to ensure complete redundancy. Determines the binning wanted from the file name of normalization file.

Kwargs:

  • dataFiles (DataFile, string or list of): File path(s), file must be of hdf format (default self.dataFiles).

  • binning (int): Binning to be used when converting files (default 8).

  • saveLocation (string): File path to save location of data file(s) (defaults to same as raw file).

  • saveFile (bool): If true, the file(s) will be saved as nxs-files. Otherwise they will only persis in memory.

  • printFunction (function): Function called if a message is to be printed (default None, uses warning)

  • deleteOnConvert (bool): If true, delete raw data files when a conversion has been done (default False)

Raises

  • - IOError –

  • - AttributeError –

convertToHKL(QxQy)[source]

Convert array or vector of QxQy point(s) to corresponding HKL

Parameters

QxQy (-) – array or vector of QxQy point(s)

Returns

  • HKL (array): Converted QxQy points in HKL

convertToQxQy(HKL)[source]

Convert array or vector of HKL point(s) to corresponding Qx and QY

Parameters

HKL (-) – array or vector of HKL point(s)

Returns

  • Q (array): Converted HKL points in Qx QY of un-rotated coordinate system.

createQAxis(rlu=True, withoutOnClick=False, figure=None, ids=[1, 1, 1], basex=None, basey=None)

Create a reciprocal lattice plot for a given DataSet object.

Parameters

Dataset (-) – DataSet object for which the RLU plot is to be made.

Kwargs:

  • rlu (bool): If true, plot in reciprocal lattice units, else in Qx, Qy (default True)

  • withoutOnClick (bool): If False, utilize the updated onClick method (default False)

  • figure: Matplotlib figure in which the axis is to be put (default None)

  • ids (array): List of integer numbers provided to the SubplotHost ids attribute (default [1,1,1])

  • basex (float): Ticks are positioned at multiples of this value along x (default None)

  • basey (float): Ticks are positioned at multiples of this value along y (default None)

Returns

Axes containing the RLU plot.

Return type

  • ax (Matplotlib axes)

Note

When rlu axis is created, the orientation of Qx and Qy is assumed to be rotated as well. This is to be done in the self.View3D method call!

Note

When using python 2 the changing of tick marks is not supported due to limitations in matplotlib. However, if python 3 is used, the number of ticks and their location can be change after the initialization using the set_xticks_number, set_yticks_number chaning the wanted number of tick marks, or the set_xticks_base or set_yticks_base to change the base number, see RLU tutorial under Tools. As default a sufficient base number is found and will update when zooming.

createQEAxes(axis=0, figure=None, projectionVector1=None, projectionVector2=None, rlu=True, figurePos=[1, 1, 1])

Function to create Q E plot

Kwargs:

  • DataSet (DataSet): If provided and no projections vectors creates QE axis for main direction (default None)

  • axis (int): Whether to create axis 0 or 1 (projection vector 0 or orthogonal to this, default 0)

  • figure (figure): If provided, this is used to create the axis within (default None)

  • projectionVector1 (vec): Projection vector along which data is plotted. If not provided sample vector is used (default None)

  • projectionVector2 (vec): Projection vector orthogonal to data. If not provided sample vector is used (default None)

  • rlu (Bool): Boolean to control if rlu or qxqy (default True)

cut1D(q1, q2, width, minPixel, Emin, Emax, rlu=True, plotCoverage=False, extend=False, dataFiles=None, constantBins=False, positions=None, I=None, Norm=None, Monitor=None, backgroundSubtraction=False, ufit=False)[source]

Wrapper for 1D cut through constant energy plane from q1 to q2 function returning binned intensity, monitor, normalization and normcount. The full width of the line is width while height is given by Emin and Emax. the minimum step sizes is given by minPixel.

Note

Can only perform cuts for a constant energy plane of definable width.

Parameters

  • q1 (-) – Start position of cut in format (h,k,l) or (qx,qy) depending on rlu flag.

  • q2 (-) – End position of cut in format (h,k,l) or (qx,qy) depending on rlu flag.

  • width (-) – Full width of cut in q-plane in 1/AA.

  • minPixel (-) – Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel.

  • Emin (-) – Minimal energy to include in cut.

  • Emax (-) – Maximal energy to include in cut

Kwargs:

  • rlu (bool): If True, coordinates given are interpreted as (h,k,l) otherwise as (qx,qy)

  • plotCoverage (bool): If True, generates plot of all points in the cutting plane and adds bounding box of cut (default False).

  • extend (bool): Whether or not the cut from q1 to q2 is to be extended throughout the data (default true)

  • dataFiles (list): List of dataFiles to cut (default None). If none, the ones in the object will be used.

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

  • ufit (bool): If True a uFit Dataset object is returned in stead of pandas data frame

Returns

See below

  • Bin list (3 arrays): Bin edge positions in plane of size (n+1,3), orthogonal positions of bin edges in plane of size (2,2), and energy edges of size (2).

    A Pandas data frame returns is returned with the following columns:

  • Qx: X component of scattering vector in instrument frame of reference

  • Qy: Y component of scattering vector in instrument frame of reference

  • H: H component of scattering vector in sample frame of reference

  • K: H component of scattering vector in sample frame of reference

  • L: H component of scattering vector in sample frame of reference

  • Int: Normalized intensity proportional to S(Q,Omega)

  • Int_err: Error of normalized intensity

  • intensity: Accumulated neutron number - either background subtracted or true neutron count

  • Monitor: Accumulated monitor in bin

  • Normalization: Accumulated normalization in bin

  • BinCount: Number of insertions into bin

  • BinDistance: If present, describes plotting position in axis

Return type

  • Data list (pandas DataFrame)

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

cut1DE(E1, E2, q, rlu=True, width=0.02, minPixel=0.1, dataFiles=None, constantBins=False, ufit=False, backgroundSubtraction=False)[source]

Perform 1D cut through constant Q point returning binned intensity, monitor, normalization and normcount. The width of the cut is given by the width attribute.

Parameters

  • E1 (-) – Start energy.

  • E2 (-) – End energy.

  • q (-) – Q point

Kwargs:

  • rlu (bool): If True, provided Q point is interpreted as (h,k,l) otherwise as (qx,qy), (Default true)

  • width (float): Full width of cut in q-plane (default 0.02).

  • minPixel (float): Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel (default 0.1).

  • dataFiles (list): Data files to be used. If none provided use the ones in self (default None)

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • ufit (bool): If True a uFit Dataset object is returned in stead of pandas data frame

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Returns

See below.

  • Bin list (1 array): Bin edge positions in energy

    A Pandas data frame returns is returned with the following columns:

  • Qx: X component of scattering vector in instrument frame of reference

  • Qy: Y component of scattering vector in instrument frame of reference

  • H: H component of scattering vector in sample frame of reference

  • K: H component of scattering vector in sample frame of reference

  • L: H component of scattering vector in sample frame of reference

  • Int: Normalized intensity proportional to S(Q,Omega)

  • Int_err: Error of normalized intensity

  • intensity: Accumulated neutron number - either background subtracted or true neutron count

  • Monitor: Accumulated monitor in bin

  • Normalization: Accumulated normalization in bin

  • BinCount: Number of insertions into bin

  • BinDistance: If present, describes plotting position in axis

Return type

  • Data list (pandas DataFrame)

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

cutELine(Q1, Q2, Emin=None, Emax=None, energyWidth=0.05, minPixel=0.02, width=0.02, rlu=True, dataFiles=None, constantBins=False, backgroundSubtraction=False)[source]

Perform cut along energy in steps between two Q Point

Parameters

  • Q1 (-) – Starting point for energy cut.

  • Q2 (-) – End of energy cut

Kwargs:

  • Emin (float): Start energy (default is self.Energy.min() for data in cut).

  • Emax (float): End energy (default is self.Energy.max() for data in cut).

  • energyWidth (float): Height of energy bins (default 0.05 meV)

  • minPixel (float): Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel (default 0.1).

  • width (float): Full width of cut in q-plane (default 0.02).

  • rlu (bool): If True, provided Q point is interpreted as (h,k,l) otherwise as (qx,qy), (Default true)

  • dataFiles (list): Data files to be used. If none provided use the ones in self (default None)

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Returns

DataFrame containing qx,qy,H,K,L,Intensity,Normalization,Monitor,BinCount,Int,binDistance for 1D cut.

  • Bin (1 array): Bin edge positions in energy

Return type

  • Data (pandas DataFrame)

cutPowder(EBins, QBins, dataFiles=None, constantBins=False, backgroundSubtraction=False)[source]

Cut data powder map with intensity as function of the length of q and energy.

Parameters

  • EBins (-) – Energy bin edges.

  • QBins (-) – Q length bin edges.

Kwargs:

  • dataFiles (list): List of dataFiles to cut (default None). If none, the ones in the object will be used.

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Returns

DataFrame containing qx,qy,H,K,L,Intensity,Normalization,Monitor,BinCount,Int,binDistance for powder cut.

  • qbins (n arrays): n arrays holding the bin edges along the length of q

Return type

  • Data list (pandas DataFrame)

cutQE(q1, q2, width, minPixel, EMin=None, EMax=None, dE=None, EnergyBins=None, rlu=True, extend=True, dataFiles=None, constantBins=False, smoothing=None, backgroundSubtraction=False, scaledEnergy=False, scaleFunction=<function scale>, rescaleFunction=<function rescale>)[source]

Wrapper for cut data into maps of q and intensity between two q points and given energies. This is performed by doing consecutive constant energy planes.

Parameters

  • q1 (-) – Start position of cut in format (h,k,l) or (qx,qy) depending on rlu flag.

  • q2 (-) – End position of cut in format (h,k,l) or (qx,qy) depending on rlu flag.

  • width (-) – Full width of cut in q-plane.

  • minPixel (-) – Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel.

  • EnergyBins (-) – Bin edges between which the 1D constant energy cuts are performed.

Kwargs:

  • rlu (bool): If True, coordinates given are interpreted as (h,k,l) otherwise as (qx,qy)

  • extend (bool): If True, cut is extended to edge of measured area instead of only between provided points.

  • dataFiles (list): List of dataFiles to cut (default None). If none, the ones in the object will be used.

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Returns

See below

  • Bin list (n * 3 arrays): n instances of bin edge positions in plane of size (m+1,3), orthogonal positions of bin edges in plane of size (2,2), and energy edges of size (2).

  • center position (n * 3D arrays): n instances of center positions for the bins.

  • binDistance (n arrays): n instances of arrays holding the distance in q to q1.

    A Pandas data frame returns is returned with the following columns:

  • Qx: X component of scattering vector in instrument frame of reference

  • Qy: Y component of scattering vector in instrument frame of reference

  • H: H component of scattering vector in sample frame of reference

  • K: H component of scattering vector in sample frame of reference

  • L: H component of scattering vector in sample frame of reference

  • Int: Normalized intensity proportional to S(Q,Omega)

  • Int_err: Error of normalized intensity

  • intensity: Accumulated neutron number - either background subtracted or true neutron count

  • Monitor: Accumulated monitor in bin

  • Normalization: Accumulated normalization in bin

  • BinCount: Number of insertions into bin

  • BinDistance: If present, describes plotting position in axis

Return type

  • Data list (pandas DataFrame)

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

cutQELine(QPoints, EnergyBins, width=0.1, minPixel=0.01, rlu=True, dataFiles=None, constantBins=False, backgroundSubtraction=False)[source]

Method to perform Q-energy cuts from a variable number of points. The function takes both qx/qy or hkl positions. In the case of using only two Q points, the method is equivalent to cutQE.

Parameters

  • QPoints (-) – Q positions between which cuts are performed. Can be specified with both qx, qy or hkl positions dependent on the choice of format.

  • EnergyBins (-) – Energy bins for which the cuts are performed

Kwargs:

  • width (float): Width of the cut in 1/AA (default 0.1).

  • minPixel (float): Minimal size of binning along the cutting directions. Points will be binned if they arecloser than minPixel (default=0.01)

  • rlu (bool): If True, provided QPoints are interpreted as (h,k,l) otherwise as (qx,qy), (default True).

  • dataFiles (list): List of dataFiles to cut. If none, the ones in the object will be used (default None).

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Warning

The way the binning works is by extending the end points with 0.5*minPixel, but the method sorts away points not between the two Q points given and thus the start and end bins are only half filled. This might result in discrepancies between a single cut and the same cut split into different steps. Further, splitting lines into sub-cuts forces a new binning to be done and the bin positions can then differ from the case where only one cut is performed.

Returns: m = Q points, n = energy bins

  • Data list (pandas DataFrame): See below

Bin list (m * n * 3 arrays): n instances of bin edge positions in plane of size (m+1,3), orthogonal positions of bin edges in plane of size (2,2), and energy edges of size (2).

Note

If an HKL point outside of the scattering plane is given, the program will just take the projection onto the scattering plane.

A Pandas data frame returns is returned with the following columns:

  • Qx: X component of scattering vector in instrument frame of reference

  • Qy: Y component of scattering vector in instrument frame of reference

  • H: H component of scattering vector in sample frame of reference

  • K: H component of scattering vector in sample frame of reference

  • L: H component of scattering vector in sample frame of reference

  • Int: Normalized intensity proportional to S(Q,Omega)

  • Int_err: Error of normalized intensity

  • intensity: Accumulated neutron number - either background subtracted or true neutron count

  • Monitor: Accumulated monitor in bin

  • Normalization: Accumulated normalization in bin

  • BinCount: Number of insertions into bin

  • BinDistance: If present, describes plotting position in axis

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

cutRaw1D(detectorSelection=None, analyzerSelection=None)[source]

cut 1D data to be used for 1D raw plot using specified DASEL.

kwargs:

detectorSelection (int): Detector to be used (default from file)

analyzerSelection (int): Analyzer segment to be used (default from file)

returns:

extractData(A4=None, A4Id=None, Ef=None, EfId=None, raw=False, A4Tolerance=0.1, EfTolerance=0.1)[source]

Extract data given A4 value and Ef (or the corresponding indices).

Kwargs:

  • A4 (float): Wanted A4 value in degrees (default None)

  • A4Id (int): Id of wedge which is a number between 0 and 103 (default None)

  • Ef (float): Wanted Ef value in meV (default None)

  • EfId (int): Wanted Id of analyser energy, number between 0-7 (default None)

  • raw (bool): If true method returns Intensity,Normalization,Monitor, else returns Intensity/(Norm*Monitor) (default False)

  • A4Tolerance (float): Tolerance between found and wanted A4 value in degrees (default 0.1)

  • EfTolerance (float): Tolerance between found and wanted Ef value in meV (default 0.1)

Note

If A4 or Ef is provided, then these will be used instead of A4Id or EfId.

generateBackgroundModel(backgroundMask=None, dQ=0.025, dE=0.05, combineForegroundMask=False)[source]

Generate a background model using powder average

Kwargs:

  • dQ (float): Step size along the q direction in the powder average bin in 1/AA (default 0.02)

  • dE (float): Step size along the energy direction in the powder average bin in meV (default 0.1)

  • backgroundMask (Mask): Masking object to utilize for background generation. If none use DataSet mask (default None)

  • combineForegroundMask (bool): If true, combine background mask with foreground (default False)

generateUFitDataset(pdData, q1, q2, rlu, width, minPixel, Emin, Emax, QDirection=True)[source]

Generate uFitDataset from cut.

Parameters

  • pdData (-) – Data generated from 1D cut

  • q1 (-) – Start point for cut

  • q2 (-) – End point for cut

  • rlu (-) – If in reciprocal lattice unites or not

  • width (-) – Width size (used for rounding of labels)

  • minPixel (-) – Minimum pixel size (used for rounding of labels)

  • Emin (-) – Minimum energy

  • Emax (-) – Maximum energy

Kwargs:

  • QDirection (bool): If true ufitdata is created along Q, otherwise energy (default True)

plotA3A4(dataFiles=None, ax=None, planes=[], log=False, returnPatches=False, binningDecimals=3, singleFigure=False, plotTessellation=False, Ei_err=0.05, temperature_err=0.2, magneticField_err=0.2, electricField_err=0.2)[source]

Plot data files together with pixels created around each point in A3-A4 space. Data is binned in the specified planes through their A3 and A4 values. This can result in distorted binning when binning across large energy regions. Data is plotted using the pixels calculated for average plane value, i.e. binning 7,8,9,10, and 11 patches for plane 9 are used for plotting.

Kwargs:

  • dataFiles (DataFiles): single file or list of files to be binned together (Default self.convertedFiles)

  • ax (matplotlib axis): Axis into which the planes are to be plotted (Default None, i.e. new)

  • planes (list (of lists)): Planes to be plotted and binned (default [])

  • log (bool): Whether or not to plot intensities as logarithm (default False)

  • returnPatches (bool): If true the method returns the patches otherwise plotted in the given axis (default False)

  • binningDecimals (int): Number of decimal places Q positions are rounded before binning (default 3)

  • singleFigure (bool): If true, all planes are plotted in same figure (default False)

  • plotTessellation (bool): Plot Tessellation of points (default False)

  • Ei_err (float): Tolerance of E_i for which the values are equal (default = 0.05)

  • temperature_err (float): Tolerance of temperature for which the values are equal (default = 0.2)

  • magneticField_err (float): Tolerance of magnetic field for which the values are equal (default = 0.2)

  • electricField_err (float): Tolerance of electric field for which the values are equal (default = 0.2)

Returns

axis (list of) containing figures for plotted planes.

Return type

  • ax (matplotlib axis or list of)

Raises

- NotImplimentedError –

Examples:

The following example will combine the two files and plot all of the available planes in different figures.

>>> DS = DataSet.DataSet(convertedFiles=[--.nxs,---.nxs])
>>> plt.figure()
>>> ax = plt.gca()
>>>
>>> DataSet.plotA3A4(DS.convertedFiles,ax=ax)

If only a subset of planes or different planes are to be combined the following will achieve this:

>>> DataSet.plotA3A4(DS.convertedFiles,ax=ax,planes=[0,1,2,3,[4,5,6],[8,9]])

Here planes 0 through 3 are plotted separately while 4,5, and 6 as well as 8 and 9 are binned.

Note

Binning planes from different analysers might result in nonsensible binnings.

plotCut1D(q1, q2, width, minPixel, Emin, Emax, rlu=True, ax=None, plotCoverage=False, showEnergy=True, counts=False, extend=False, data=None, dataFiles=None, constantBins=False, backgroundSubtraction=False, ufit=False, plotForeground=False, plotBackground=False, outputFunction=<built-in function print>, **kwargs)[source]

plot new or already performed cut.

Parameters

  • q1 (-) – Start position of cut in format (h,k,l) or (qx,qy) depending on rlu flag.

  • q2 (-) – End position of cut in format (h,k,l) or (qx,qy) depending on rlu flag.

  • width (-) – Full width of cut in q-plane in 1/AA, only needed for new cut (default None)

  • minPixel (-) – Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel.

  • Emin (-) – Minimal energy to include in cut.

  • Emax (-) – Maximal energy to include in cut.

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

plotCut1DE(E1, E2, q, rlu=True, width=0.02, minPixel=0.1, showQ=True, counts=False, dataFiles=None, constantBins=False, ax=None, ufit=False, data=None, backgroundSubtraction=False, plotForeground=False, plotBackground=False, outputFunction=<built-in function print>, **kwargs)[source]

Perform 1D cut through constant Q point returning binned intensity, monitor, normalization and normcount. The width of the cut is given by the width attribute.

Parameters

  • E1 (-) – Start energy.

  • E2 (-) – End energy.

  • q (-) – Q point

Kwargs:

  • rlu (bool): If True, provided Q point is interpreted as (h,k,l) otherwise as (qx,qy), (Default true)

  • width (float): Full width of cut in q-plane (default 0.02).

  • minPixel (float): Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel (default 0.1).

  • showQ (bool): If True show the current Q point on the x-axus (default True)

  • counts (bool): If True, plot raw counts, if False plot intensity, if ‘sensitivity’ plot mean sensitivity (Default False)

  • dataFiles (list): Data files to be used. If none provided use the ones in self (default None)

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • ufit (bool): If True a uFit Dataset object is returned in stead of pandas data frame

  • ax (matplotlib.axes): If None, new axis is created in which to plot (default None)

  • data ([data Pandas Dataframe, bins]): Data and bins from previously created cut (default None)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

  • plotForeground (bool): If true, and background subtraction is true, plot the unsubtracted foreground data (default False)

  • plotBackground (bool): If true, and background subtraction is true, plot the corresponding background data (default False)

  • kwargs: Pass on to the ax.errorbar method used to plot

Returns

See below

  • Bin list (1 array): Bin edge positions in energy

    A Pandas data frame returns is returned with the following columns:

  • Qx: X component of scattering vector in instrument frame of reference

  • Qy: Y component of scattering vector in instrument frame of reference

  • H: H component of scattering vector in sample frame of reference

  • K: H component of scattering vector in sample frame of reference

  • L: H component of scattering vector in sample frame of reference

  • Int: Normalized intensity proportional to S(Q,Omega)

  • Int_err: Error of normalized intensity

  • intensity: Accumulated neutron number - either background subtracted or true neutron count

  • Monitor: Accumulated monitor in bin

  • Normalization: Accumulated normalization in bin

  • BinCount: Number of insertions into bin

  • BinDistance: If present, describes plotting position in axis

Return type

  • Data list (pandas DataFrame)

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

plotCutELine(Q1, Q2, ax=None, Emin=None, Emax=None, energyWidth=0.05, minPixel=0.02, width=0.02, rlu=True, counts=False, dataFiles=None, constantBins=False, Vmin=None, Vmax=None, backgroundSubtraction=False, **kwargs)[source]

Perform cut along energy in steps between two Q Point

Parameters

  • Q1 (-) – Starting point for energy cut.

  • Q2 (-) – End of energy cut

Kwargs:

  • ax (matplotlib axis): Axis into which the plot is to go (default None, new created)

  • Emin (float): Start energy (default is self.Energy.min() for data in cut).

  • Emax (float): End energy (default is self.Energy.max() for data in cut).

  • energyWidth (float): Height of energy bins (default 0.05 meV)

  • minPixel (float): Minimal size of binning along the cutting direction. Points will be binned if they are closer than minPixel (default 0.1).

  • width (float): Full width of cut in q-plane (default 0.02).

  • rlu (bool): If True, provided Q point is interpreted as (h,k,l) otherwise as (qx,qy), (Default true)

  • counts (bool): If True, plot raw counts, if False plot intensity, if ‘sensitivity’ plot mean sensitivity (Default False)

  • dataFiles (list): Data files to be used. If none provided use the ones in self (default None)

  • constantBins (bool): If True only bins of size minPixel is used (default False)

  • Vmin (float): Lower limit for colorbar (default min(Intensity)).

  • Vmax (float): Upper limit for colorbar (default max(Intensity)).

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Returns

DataFrame containing qx,qy,H,K,L,Intensity,Normalization,Monitor,BinCount,Int,binDistance for 1D cut.

  • Bin list (1 array): Bin edge positions in energy

Return type

  • Data list (pandas DataFrame)

plotCutPowder(EBins, QBins, ax=None, dataFiles=None, log=False, colorbar=True, backgroundSubtraction=False, vmin=None, vmax=None, outputFunction=<built-in function print>, **kwargs)[source]

Plotting wrapper for the cutPowder method. Generates a 2D plot of powder map with intensity as function of the length of q and energy.

Note

Can only perform cuts for a constant energy plane of definable width.

Parameters

  • EBins (-) – Energy bin edges.

  • QBins (-) – Q length bin edges.

Kwargs:

  • ax (matplotlib axis): Figure axis into which the plots should be done (default None). If not provided, a new figure will be generated.

  • dataFiles (list): List of dataFiles to cut (default None). If none, the ones in the object will be used.

  • log (bool): If true, logarithm to intensity is plotted (default False)

  • colorbar (bool): If True a colorbar is added to the figure (default True)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

  • vmin (float): Minimum value for color scale

  • vmax (float): Maximum value for color scale

  • outputFunction (function): Function called on output strung (default print)

  • kwargs: All other keywords will be passed on to the ax.pcolormesh method.

Returns

Matplotlib axis into which the plot was put.

  • Data list (pandas DataFrame): DataFrame containing qx,qy,H,K,L,Intensity,Normalization,Monitor,BinCount,Int,binDistance for poweder cut.

Return type

  • ax (matplotlib axis)

plotCutQE(q1, q2, EMin=None, EMax=None, dE=None, EnergyBins=None, minPixel=0.05, width=0.1, rlu=True, counts=False, smoothing=None, ax=None, grid=False, cmap=None, colorbar=False, outputFunction=<built-in function print>, dataFiles=None, backgroundSubtraction=False, scaledEnergy=False, scaleFunction=<function scale>, rescaleFunction=<function rescale>, cut1DFunctionRectanglePerpendicular=None, cut1DFunctionRectangleHorizontal=None, cut1DFunctionRectangleVertical=None, **kwargs)[source]

plot of intensity as function of Q between Q1 and Q2 and Energy.

Parameters

  • q1 (-) – List of HKL or QxQy position of start of cut

  • q2 (-) – List of HKL or QxQy position of end of cut

Kwargs:

  • EMin (float): Minimal energy of cut (default None, see note below)

  • EMax (float): Maximal energy of cut (default None, see note below)

  • dE (float): Energy step of cut (default None, see note below)

  • EnergyBins (list): List of energy bin edges (default None, see note below)

  • scaledEnergy (bool/float): If true or float, rescale energy axis by E*f (default False)

  • scaleFunction (function): Function used to scale energy bins (default _tools.scale)

  • rescaleFunction (function): Function used to reverse energy bins (default _tools.rescale)

  • minPixel (float): Step size in 1/A along cut (default 0.05)

  • width (float): Integration width in 1/A perpendicular to cut (default 0.1)

  • rlu (bool): If True, plot as function of HKL otherwise QxQy (default True)

  • counts (bool): If True, plot raw counts, if False plot intensity, if ‘sensitivity’ plot mean sensitivity (Default False)

  • smoothing (float): Gaussian smoothing applied to data after cut (default None, see scipy.ndimage.gaussian_filter)

  • ax (plt axes): Axis into which data is plotted (default None, creates new, if False no plotting)

  • grid (float): If True, plot grid. If number provided plot grid with this z value (default False)

  • cmap (str): Color map used for plotting (default viridis)

  • vmin (float): Lower value of color scale (default None, minimum of intensity)

  • vmax (float): Upper value of color scale (default None, maxmimum of intensity)

  • log (bool): If true the plotted intensity is the logarithm of the intensity (default False)

  • colorbar (bool): If True, plot colorbar (default False)

  • outputFunction (function): Function called when onclick on axis is triggered (default print)

  • cut1DFunctionRectanglePerpendicular (function): Function called when performing a perpendicular cut

  • cut1DFunctionRectangleHorizontal (function): Function called when performing horizontal cut in the curren view

  • cut1DFunctionRectangleVertical (function): Function called when performing horizontal cut in the curren view

  • dataFiles (list): List of dataFiles to cut (default None). If none, the ones in the object will be used.

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Returns

Matplotlib axis in which data is plotted

  • Data (pandas DataFrame): See below

  • Bins

Return type

  • ax (plt axes)

Raises

- AttributeError –

Note

When EnergyBins is provided, this overwrites EMin, EMax, and dE. Otherwise bins are created linearly between EMin and EMax in steps of dE, np.arange(EMin,EMax+dE,dE) with length n.

A Pandas data frame returns is returned with the following columns:

  • Qx: X component of scattering vector in instrument frame of reference

  • Qy: Y component of scattering vector in instrument frame of reference

  • H: H component of scattering vector in sample frame of reference

  • K: H component of scattering vector in sample frame of reference

  • L: H component of scattering vector in sample frame of reference

  • Int: Normalized intensity proportional to S(Q,Omega)

  • Int_err: Error of normalized intensity

  • intensity: Accumulated neutron number - either background subtracted or true neutron count

  • Monitor: Accumulated monitor in bin

  • Normalization: Accumulated normalization in bin

  • BinCount: Number of insertions into bin

  • BinDistance: If present, describes plotting position in axis

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

plotCutQELine(QPoints, EnergyBins, width=0.1, minPixel=0.01, rlu=True, ax=None, dataFiles=None, constantBins=True, outputFunction=<built-in function print>, backgroundSubtraction=False, **kwargs)[source]

Plotting wrapper for the cutQELine method. Plots the scattering intensity as a function of Q and E for cuts between specified Q-points.

Parameters

  • QPoints (-) – List of Q points in either RLU (3D) or QxQy (2D).

  • EnergyBins (-) – List of bin edges in the energy direction.

Kwargs:

  • width (float): Width perpendicular to Q-direction for cuts (default 0.1)

  • minPixel (float): Minimum size of pixel for cut (default 0.01)

  • rlu (bool): If True, provided points are interpreted as (h,k,l) otherwise (qx,qy), (default RLU)

  • ax (matplotlib axis): Axis into whiht the data is plotted. If None a new will be created (default None).

  • dataFiles (DataFile(s)): DataFile or list of, from which data is to be taken. If None all datafiles in self is taken (default None).

  • vmin (float): Lower limit for colorbar (default min(Intensity)).

  • vmax (float): Upper limit for colorbar (default max(Intensity)).

  • ticks (int): Number of ticks in plot, minimum equal to number of Q points (default None - adaptive).

  • plotSeperator (bool): If true, vertical lines are plotted at Q points (default True).

  • seperatorWidth (float): Width of seperator line (default 2).

  • seperatorColor (str or list): Color of the seperator line (default k)

  • log (bool): If true the plotted intensity is the logarithm of the intensity (default False)

  • constantBins (bool): If True only bins of size minPixel is used (default True)

  • outputFunction (function): Function called on output string (default print)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

Return: m = Q points, n = energy bins

  • ax: matplotlib axis in which the data is plotted

  • Data list (pandas DataFrame): DataFrame containing qx,qy,H,K,L,Intensity,Normalization,Monitor,BinCount,Int,binDistance for all 2D cuts.

  • Bin list (m * n * 3 arrays): n instances of bin edge positions in plane of size (m+1,3), orthogonal positions of bin edges in plane of size (2,2), and energy edges of size (2).

Note

The ax.set_clim function is created to change the colour scale. It takes inputs vmin,vmax. This function does however not work in 3D….

plotQPlane(EMin=None, EMax=None, EBins=None, binning='xy', xBinTolerance=0.05, yBinTolerance=0.05, enlargen=False, log=False, ax=None, rlu=True, dataFiles=None, xScale=1.0, yScale=1.0, backgroundSubtraction=False, outputFunction=<built-in function print>, cut1DFunctionRectangle=None, cut1DFunctionCircle=None, scaleFunction=None, **kwargs)[source]

Wrapper for plotting tool to show binned intensities in the Q plane between provided energies.

Kwargs:

  • EMin (float): Lower energy limit (Default None).

  • EMax (float): Upper energy limit (Default None).

  • EBins (list): List of energy bins (Default None).

  • binning (str): Binning scheme, either ‘xy’ or ‘polar’ (default ‘xy’).

  • xBinTolerance (float): bin sizes along x direction (default 0.05). If enlargen is true, this is the minimum bin size.

  • yBinTolerance (float): bin sizes along y direction (default 0.05). If enlargen is true, this is the minimum bin size.

  • enlargen (bool): If the bin sizes should be adaptive (default False). If set true, bin tolerances are used as minimum bin sizes.

  • log (bool): Plot intensities as the logarithm (default False).

  • ax (matplotlib axes): Axes in which the data is plotted (default None). If None, the function creates a new axes object.

  • rlu (bool): If true and axis is None, a new reciprocal lattice axis is created and used for plotting (default True).

  • dataFiles (DataFile): If set, method uses these converted data files instead of the ones in self (default None)

  • vmin (float): Lower limit for colorbar (default min(Intensity)).

  • vmax (float): Upper limit for colorbar (default max(Intensity)).

  • colorbar (bool): If True, a colorbar is created in figure (default False)

  • zorder (int): If provided decides the z ordering of plot (default 10)

  • outputFunction (function): Function called on output string (default print)

  • cut1DFunctionRectangle (function): Function to be called when a 1D rectangular cut is created (default None)

  • cut1DFunctionCircle (function): Function to be called when a circuar cut is created (default None)

  • backgroundSubtraction (bool): If true, utilize the Background object on the data set to perform background subtraction (default False)

  • scaleFunction (function): Function to rescale the plotted intensity (default None)

  • other: Other key word arguments are passed to the pcolormesh plotting algorithm.

Returns

See below

  • ax (matplotlib axes): Returns provided matplotlib axis

Return type

  • data (Pandas datafrane)

Note

The axes object has a new method denoted ‘set_clim’ taking two parameters (VMin and VMax) used to change axes colouring.

Note

If a 3D matplotlib axis is provided, the planes are plotted in 3D with the provided energy bins. As the method contourf is used and it needs X,Y, and Z to have same shape, x and y are found as middle of bins.

A Pandas data frame returns is returned with the following columns:

  • Qx: X component of scattering vector in instrument frame of reference

  • Qy: Y component of scattering vector in instrument frame of reference

  • H: H component of scattering vector in sample frame of reference

  • K: H component of scattering vector in sample frame of reference

  • L: H component of scattering vector in sample frame of reference

  • Int: Normalized intensity proportional to S(Q,Omega)

  • Int_err: Error of normalized intensity

  • intensity: Accumulated neutron number - either background subtracted or true neutron count

  • Monitor: Accumulated monitor in bin

  • Normalization: Accumulated normalization in bin

  • BinCount: Number of insertions into bin

  • BinDistance: If present, describes plotting position in axis

If a background subtraction is performed, the following columns are also present:

  • Int_Fg: Normalized foreground intensity

  • Int_Bg: Normalized background intensity

  • Int_Fg_err: Normalized foreground error

  • Int_Bg_err: Normalized background error

  • intensity_Fg: Accumulated foreground neutron number

  • intensity_Bg: Accumulated background neutron number

plotRaw1D(detectorSelection=None, analyzerSelection=None, legend=True, grid=-10, outputFunction=<built-in function print>)[source]

plot 1D figures of data in the specified DASEL.

kwargs:

detectorSelection (int): Detector to be used (default from file)

analyzerSelection (int): Analyzer segment to be used (default from file)

legend (bool list): Insert legend with provided names or file names (default True)

grid (bool, Int): If true plot at grid on figure. If integer set zorder of grid (default -10)

Returns

List of axes in which data are plotted.

Return type

Ax (list)

symmetrize(function)[source]

Symmetrize data by providing a custom function

Parameters

function (function) – Function to symmetrize

The signature of the function must be func(H,K,L) and must return (H,K,L). An example is

>>> def symmetrize(H,K,L):
>>>     return np.abs(H),np.abs(K),np.abs(L)
undoAbsoluteNormalize()[source]

Undo normalization previously performed

updateCalibration(calibFiles, overwrite=False)[source]

Update calibrations for all data files in data set. 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.

updateSampleParameters(unitCell)[source]

Update unit cell parameters and corresponding UB matrix

Parameters

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