xrayutilities package

Subpackages

Submodules

xrayutilities.config module

module to parse xrayutilities user-specific config file the parsed values are provide as global constants for the use in other parts of xrayutilities. The config file with the default constants is found in the python installation path of xrayutilities. It is however not recommended to change things there, instead the user-specific config file ~/.xrayutilities.conf or the local xrayutilities.conf file should be used.

xrayutilities.config.trytomake(obj, key, typefunc)[source]

xrayutilities.exception module

xrayutilities derives its own exceptions which are raised upon wrong input when calling one of xrayutilities functions. none of the pre-defined exceptions is made for that purpose.

exception xrayutilities.exception.InputError(msg)[source]

Bases: Exception

Exception raised for errors in the input. Either wrong datatype not handled by TypeError or missing mandatory keyword argument (Note that the obligation to give keyword arguments might depend on the value of the arguments itself)

Attibutes
expr – input expression in which the error occurred :msg: – explanation of the error

xrayutilities.experiment module

module helping with planning and analyzing experiments. various classes are provided for describing experimental geometries, calculationof angular coordinates of Bragg reflections, conversion of angular coordinates to Q-space and determination of powder diffraction peak positions.

The strength of the module is the versatile QConversion module which can be configured to describe almost any goniometer geometry.

class xrayutilities.experiment.Experiment(ipdir, ndir, **keyargs)[source]

Bases: object

base class for describing experiments users should use the derived classes: HXRD, GID, Powder

Ang2HKL(*args, **kwargs)[source]

angular to (h,k,l) space conversion. It will set the UB argument to Ang2Q and pass all other parameters unchanged. See Ang2Q for description of the rest of the arguments.

Parameters:

****kwargs: optional keyword arguments**

B:reciprocal space conversion matrix of a Crystal. You can specify the matrix B (default identiy matrix) shape needs to be (3,3)
mat:Crystal object to use to obtain a B matrix (e.g. xu.materials.Si) can be used as alternative to the B keyword argument B is favored in case both are given
U:orientation matrix U can be given. If none is given the orientation defined in the Experiment class is used.
dettype:detector type: one of (‘point’, ‘linear’, ‘area’) decides which routine of Ang2Q to call. default ‘point’
delta:giving delta angles to correct the given ones for misalignment. delta must be an numpy array or list of length 2. used angles are than (om,tt)-delta
wl:x-ray wavelength in angstroem (default: self._wl)
en:x-ray energy in eV (default: converted self._wl)
deg:flag to tell if angles are passed as degree (default: True)
sampledis:sample displacement vector in relative units of the detector distance (default: (0, 0, 0))
Returns:

H K L coordinates as numpy.ndarray with shape ( * , 3 )

where * corresponds to the number of points given in the input (*args)

Q2Ang(qvec)[source]
TiltAngle(q, deg=True)[source]

TiltAngle(q,deg=True): Return the angle between a q-space position and the surface normal.

Parameters:

**q: list or numpy array with the reciprocal space position**

**optional keyword arguments:**

deg:True/False whether the return value should be in degree or radians (default: True)
Transform(v)[source]

transforms a vector, matrix or tensor of rank 4 (e.g. elasticity tensor) to the coordinate frame of the Experiment class. This is for example necessary before any Q2Ang-conversion can be performed.

Parameters:

**v: object to transform, list or numpy array of shape**

(n,) (n,n), (n,n,n,n) where n is the rank of the transformation matrix

Returns:

transformed object of the same shape as v

energy
wavelength
class xrayutilities.experiment.GID(idir, ndir, **keyargs)[source]

Bases: xrayutilities.experiment.Experiment

class describing grazing incidence x-ray diffraction experiments the class helps with calculating the angles of Bragg reflections as well as it helps with analyzing measured data

the class describes a four circle (alpha_i,azimuth,twotheta,beta) goniometer to help with GID experiments at the ROTATING ANODE. 3D data can be treated with the use of linear and area detectors. see help self.Ang2Q

Using this class the default sample surface orientation is determined by the inner most sample rotation (which is usually the azimuth motor).

Ang2Q(ai, phi, tt, beta, **kwargs)[source]

angular to momentum space conversion for a point detector. Also see help GID.Ang2Q for procedures which treat line and area detectors

Parameters:

**ai,phi,tt,beta: sample and detector angles as numpy array, lists or**

Scalars must be given. All arguments must have the same shape or length. However, if one angle is always the same its enough to give one scalar value.

****kwargs: optional keyword arguments**

delta:giving delta angles to correct the given ones for misalignment delta must be an numpy array or list of length 4. Used angles are than ai,phi,tt,beta - delta
UB:matrix for conversion from (hkl) coordinates to Q of sample used to determine not Q but (hkl) :(default: identity matrix)
wl:x-ray wavelength in angstroem (default: self._wl)
deg:flag to tell if angles are passed as degree (default: True)
Returns:

reciprocal space positions as numpy.ndarray with shape ( * , 3 )

where * corresponds to the number of points given in the input

Q2Ang(Q, trans=True, deg=True, **kwargs)[source]

calculate the GID angles needed in the experiment the inplane reference direction defines the direction were the reference direction is parallel to the primary beam (i.e. lattice planes perpendicular to the beam)

Parameters:

**Q: a list or numpy array of shape (3) with**

q-space vector components

**optional keyword arguments:**

trans:True/False apply coordinate transformation on Q
deg:True/Flase (default True) determines if the angles are returned in radians or degrees
Returns:

a numpy array of shape (4) with the four GID scattering angles which

are [alpha_i, azimuth, twotheta, beta]

alpha_i:incidence angle to surface (at the moment always 0)
azimuth:sample rotation with respect to the inplane reference direction
twotheta:scattering angle
beta:exit angle from surface (at the moment always 0)
class xrayutilities.experiment.GISAXS(idir, ndir, **keyargs)[source]

Bases: xrayutilities.experiment.Experiment

class describing grazing incidence x-ray diffraction experiments the class helps with calculating the angles of Bragg reflections as well as it helps with analyzing measured data

the class describes a three circle (alpha_i,twotheta,beta) goniometer to help with GISAXS experiments at the ROTATING ANODE. 3D data can be treated with the use of linear and area detectors. see help self.Ang2Q

Ang2Q(ai, tt, beta, **kwargs)[source]

angular to momentum space conversion for a point detector. Also see help GISAXS.Ang2Q for procedures which treat line and area detectors

Parameters:

**ai,tt,beta: sample and detector angles as numpy array, lists or**

Scalars must be given. all arguments must have the same shape or length. Howevver, if one angle is always the same its enough to give one scalar value.

****kwargs: optional keyword arguments**

delta:giving delta angles to correct the given ones for misalignment delta must be an numpy array or list of length 3. Used angles are than ai,tt,beta - delta
UB:matrix for conversion from (hkl) coordinates to Q of sample used to determine not Q but (hkl) :(default: identity matrix)
wl:x-ray wavelength in angstroem (default: self._wl)
deg:flag to tell if angles are passed as degree (default: True)
Returns:

reciprocal space positions as numpy.ndarray with shape ( * , 3 )

where * corresponds to the number of points given in the input

Q2Ang(Q, trans=True, deg=True, **kwargs)[source]
class xrayutilities.experiment.HXRD(idir, ndir, geometry='hi_lo', **keyargs)[source]

Bases: xrayutilities.experiment.Experiment

class describing high angle x-ray diffraction experiments the class helps with calculating the angles of Bragg reflections as well as helps with analyzing measured data

the class describes a two circle (omega,twotheta) goniometer to help with coplanar x-ray diffraction experiments. Nevertheless 3D data can be treated with the use of linear and area detectors. see help self.Ang2Q

Ang2Q(om, tt, **kwargs)[source]

angular to momentum space conversion for a point detector. Also see help HXRD.Ang2Q for procedures which treat line and area detectors

Parameters:

**om,tt: sample and detector angles as numpy array, lists or**

Scalars must be given. All arguments must have the same shape or length. However, if one angle is always the same its enough to give one scalar value.

****kwargs: optional keyword arguments**

delta:giving delta angles to correct the given ones for misalignment. delta must be an numpy array or list of length 2. Used angles are than om,tt - delta
UB:matrix for conversion from (hkl) coordinates to Q of sample used to determine not Q but (hkl) :(default: identity matrix)
wl:x-ray wavelength in angstroem (default: self._wl)
deg:flag to tell if angles are passed as degree (default: True)
Returns:

reciprocal space positions as numpy.ndarray with shape ( * , 3 )

where * corresponds to the number of points given in the input

Q2Ang(*Q, **keyargs)[source]

Convert a reciprocal space vector Q to COPLANAR scattering angles. The keyword argument trans determines whether Q should be transformed to the experimental coordinate frame or not. The coplanar scattering angles correspond to a goniometer with sample rotations [‘x+’,’y+’,’z-‘] and detector rotation ‘x+’ and primary beam along y. This is a standard four circle diffractometer.

Parameters:

**Q: a list, tuple or numpy array of shape (3) with**

q-space vector components or 3 separate lists with qx,qy,qz

**optional keyword arguments:**

trans:

True/False apply coordinate transformation on Q (default True)

deg:

True/Flase (default True) determines if the angles are returned in radians or degrees

geometry:

determines the scattering geometry:

  • “hi_lo” high incidence and low exit
  • “lo_hi” low incidence and high exit
  • “real” general geometry with angles determined by q-coordinates (azimuth); this and upper geometries return [omega,0,phi,twotheta]
  • “realTilt” general geometry with angles determined by q-coordinates (tilt); returns [omega,chi,phi,twotheta]
default:self.geometry
refrac:

boolean to determine if refraction is taken into account :default: False if True then also a material must be given

mat:

Crystal object; needed to obtain its optical properties for refraction correction, otherwise not used

full_output:

boolean to determine if additional output is given to determine scattering angles more accurately in case refraction is set to True. default: False

fi,fd:

if refraction correction is applied one can optionally specify the facet through which the beam enters (fi) and exits (fd) fi, fd must be the surface normal vectors (not transformed & not necessarily normalized). If omitted the normal direction of the experiment is used.

Returns:

a numpy array of shape (4) with four scattering angles which are

[omega,chi,phi,twotheta]

omega:incidence angle with respect to surface
chi:sample tilt for the case of non-coplanar geometry
phi:sample azimuth with respect to inplane reference direction
twotheta:scattering angle/detector angle

if full_output:

a numpy array of shape (6) with five angles which are

[omega,chi,phi,twotheta,psi_i,psi_d]

psi_i:offset of the incidence beam from the scattering plane due to refraction
pdi_d:offset ot the diffracted beam from the scattering plane due to refraction
class xrayutilities.experiment.NonCOP(idir, ndir, **keyargs)[source]

Bases: xrayutilities.experiment.Experiment

class describing high angle x-ray diffraction experiments. The class helps with calculating the angles of Bragg reflections as well as helps with analyzing measured data for NON-COPLANAR measurements, where the tilt is used to align asymmetric peaks, like in the case of a polefigure measurement.

The class describes a four circle (omega,twotheta) goniometer to help with x-ray diffraction experiments. Linear and area detectors can be treated as described in “help self.Ang2Q”

Ang2Q(om, chi, phi, tt, **kwargs)[source]

angular to momentum space conversion for a point detector. Also see help NonCOP.Ang2Q for procedures which treat line and area detectors

Parameters:

**om,chi,phi,tt: sample and detector angles as numpy array, lists or**

Scalars must be given. All arguments must have the same shape or length. However, if one angle is always the same its enough to give one scalar value.

****kwargs: optional keyword arguments**

delta:giving delta angles to correct the given ones for misalignment delta must be an numpy array or list of length 4. Used angles are than om,chi,phi,tt - delta
UB:matrix for conversion from (hkl) coordinates to Q of sample used to determine not Q but (hkl) :(default: identity matrix)
wl:x-ray wavelength in angstroem (default: self._wl)
deg:flag to tell if angles are passed as degree (default: True)
Returns:

reciprocal space positions as numpy.ndarray with shape ( * , 3 )

where * corresponds to the number of points given in the input

Q2Ang(*Q, **keyargs)[source]

Convert a reciprocal space vector Q to NON-COPLANAR scattering angles. The keyword argument trans determines whether Q should be transformed to the experimental coordinate frame or not.

Parameters:

**Q: a list, tuple or numpy array of shape (3) with**

q-space vector components or 3 separate lists with qx,qy,qz

**optional keyword arguments:**

trans:True/False apply coordinate transformation on Q (default True)
deg:True/Flase (default True) determines if the angles are returned in radians or degree
Returns:

a numpy array of shape (4) with four scattering angles which are

[omega, chi, phi, twotheta]

omega:sample rocking angle
chi:sample tilt
phi:sample azimuth
twotheta:scattering angle (detector)
class xrayutilities.experiment.PowderExperiment(**kwargs)[source]

Bases: xrayutilities.experiment.Experiment

Experimental class for powder diffraction which helps to convert theta angles to momentum transfer space

Q2Ang(qpos, deg=True)[source]

Converts reciprocal space values to theta angles

class xrayutilities.experiment.QConversion(sampleAxis, detectorAxis, r_i, **kwargs)[source]

Bases: object

Class for the conversion of angular coordinates to momentum space for arbitrary goniometer geometries and X-ray energy. Both angular scans (where some goniometer angles change during data acquisition) and energy scans (where the energy is varied during acquisition) as well as mixed cases can be treated.

the class is configured with the initialization and does provide three distinct routines for conversion to momentum space for

* point detector: point(...) or __call__() * linear detector: linear(...) * area detector: area(...)

linear() and area() can only be used after the init_linear() or init_area() routines were called

UB
area(*args, **kwargs)[source]

angular to momentum space conversion for a area detector the center pixel defined by the init_area routine must be in direction of self.r_i when detector angles are zero

the detector geometry must be initialized by the init_area(...) routine

Parameters:

***args: sample and detector angles as numpy array, lists or**

Scalars in total len(self.sampleAxis)+len(detectorAxis) must be given, always starting with the outer most circle. all arguments must have the same shape or length but can be mixed with Scalars (i.e. if an angle is always the same it can be given only once instead of an array)

sAngles:sample circle angles, number of arguments must correspond to len(self.sampleAxis)
dAngles:detector circle angles, number of arguments must correspond to len(self.detectorAxis)

****kwargs: possible keyword arguments**

delta:giving delta angles to correct the given ones for misalignment delta must be an numpy array or list of len(*args). Used angles are than *args - delta
UB:matrix for conversion from (hkl) coordinates to Q of sample. Used to determine not Q but (hkl) (default: self.UB)
roi:region of interest for the detector pixels; e.g. [100, 900, 200, 800] (default: self._area_roi)
Nav:number of channels to average to reduce data size e.g. [2, 2] (default: self._area_nav)
wl:x-ray wavelength in angstroem (default: self._wl)
en:x-ray energy in eV (default is converted self._wl) both wavelength and energy can also be an array which enables the QConversion for energy scans. Note that the en keyword overrules the wl keyword!
deg:flag to tell if angles are passed as degree (default: True)
sampledis:sample displacement vector in same units as the detector distance (default: (0, 0, 0))
Returns:

reciprocal space position of all detector pixels in a numpy.ndarray of

shape ((*)*(self._area_roi[1] - self._area_roi[0]+1) *

(self._area_roi[3] - self._area_roi[2] + 1) , 3) were detectorDir1 is

the fastest varing

detectorAxis

property handler for _detectorAxis

Returns:list of detector axis following the syntax /[xyz][+-]/
energy
getDetectorDistance(*args, **kwargs)[source]

obtains the detector distance by applying the detector arm movements. This is especially interesting for the case of 1 or 2D detectors to perform certain geometric corrections.

Parameters:

***args: detector angles. Only detector arm angles as described by the**

detectorAxis attribute must be given.

**kwargs: optional keyword arguments
dim:dimension of the detector for which the position should be determined
roi:region of interest for the detector pixels; :(default: self._area_roi/self._linear_roi)
Nav:number of channels to average to reduce data size; :(default: self._area_nav/self._linear_nav)
deg:flag to tell if angles are passed as degree (default: True)
Returns:

numpy array with the detector distance

getDetectorPos(*args, **kwargs)[source]

obtains the detector position vector by applying the detector arm rotations.

Parameters:

***args: detector angles. Only detector arm angles as described by the**

detectorAxis attribute must be given.

**kwargs: optional keyword arguments
dim:dimension of the detector for which the position should be determined
roi:region of interest for the detector pixels; :(default: self._area_roi/self._linear_roi)
Nav:number of channels to average to reduce data size; :(default: self._area_nav/self._linear_nav)
deg:flag to tell if angles are passed as degree (default: True)
Returns:

numpy array of length 3 with vector components of the detector

direction. The length of the vector is k.

init_area(detectorDir1, detectorDir2, cch1, cch2, Nch1, Nch2, distance=None, pwidth1=None, pwidth2=None, chpdeg1=None, chpdeg2=None, detrot=0, tiltazimuth=0, tilt=0, **kwargs)[source]

initialization routine for area detectors detector direction as well as distance and pixel size or channels per degree must be given. Two separate pixel sizes and channels per degree for the two orthogonal directions can be given

Parameters:

**detectorDir1: direction of the detector (along the pixel**

direction 1); e.g. ‘z+’ means higher pixel numbers at larger z positions

detectorDir2:direction of the detector (along the pixel direction 2); e.g. ‘x+’
cch1,2:center pixel, in direction of self.r_i at zero detectorAngles
Nch1:number of detector pixels along direction 1
Nch2:number of detector pixels along direction 2
distance:distance of center pixel from center of rotation
pwidth1,2:width of one pixel (same unit as distance)
chpdeg1,2:channels per degree (only absolute value is relevant) sign determined through detectorDir1,2
detrot:angle of the detector rotation around primary beam direction (used to correct misalignments)
tiltazimuth:direction of the tilt vector in the detector plane (in degree)
tilt:tilt of the detector plane around an axis normal to the direction given by the tiltazimuth

Note

Note: Either distance and pwidth1,2 or chpdeg1,2 must be given !!

Note

Note: the channel numbers run from 0 .. NchX-1

****kwargs: optional keyword arguments**

Nav:number of channels to average to reduce data size :(default: [1, 1])
roi:region of interest for the detector pixels; e.g. [100, 900, 200, 800]
init_linear(detectorDir, cch, Nchannel, distance=None, pixelwidth=None, chpdeg=None, tilt=0, **kwargs)[source]

initialization routine for linear detectors detector direction as well as distance and pixel size or channels per degree must be given.

Parameters:

**detectorDir: direction of the detector (along the pixel array);**

e.g. ‘z+’

cch:

center channel, in direction of self.r_i at zero detectorAngles

Nchannel:

total number of detector channels

distance:

distance of center channel from center of rotation

pixelwidth:

width of one pixel (same unit as distance)

chpdeg:

channels per degree (only absolute value is relevant) sign determined through detectorDir

!! Either distance and pixelwidth or chpdeg must be given !!

tilt:

tilt of the detector axis from the detectorDir (in degree)

Note

Note: the channel numbers run from 0 .. Nchannel-1

****kwargs: optional keyword arguments**

Nav:number of channels to average to reduce data size :(default: 1)
roi:region of interest for the detector pixels; e.g. [100,900]
linear(*args, **kwargs)[source]

angular to momentum space conversion for a linear detector the cch of the detector must be in direction of self.r_i when detector angles are zero

the detector geometry must be initialized by the init_linear(...) routine

Parameters:

***args: sample and detector angles as numpy array, lists or**

Scalars in total len(self.sampleAxis)+len(detectorAxis) must be given, always starting with the outer most circle. all arguments must have the same shape or length but can be mixed with Scalars (i.e. if an angle is always the same it can be given only once instead of an array)

sAngles:sample circle angles, number of arguments must correspond to len(self.sampleAxis)
dAngles:detector circle angles, number of arguments must correspond to len(self.detectorAxis)

****kwargs: possible keyword arguments**

delta:giving delta angles to correct the given ones for misalignment delta must be an numpy array or list of len(*args) used angles are than *args - delta
UB:matrix for conversion from (hkl) coordinates to Q of sample used to determine not Q but (hkl) (default: self.UB)
Nav:number of channels to average to reduce data size :(default: self._linear_nav)
roi:region of interest for the detector pixels; e.g. [100,900] (default: self._linear_roi)
wl:x-ray wavelength in angstroem (default: self._wl)
en:x-ray energy in eV (default is converted self._wl) both wavelength and energy can also be an array which enables the QConversion for energy scans. Note that the en keyword overrules the wl keyword!
deg:flag to tell if angles are passed as degree (default: True)
sampledis:sample displacement vector in same units as the detector distance (default: (0, 0, 0))
Returns:

reciprocal space position of all detector pixels in a numpy.ndarray of

shape ( (*)*(self._linear_roi[1]-self._linear_roi[0]+1) , 3 )

point(*args, **kwargs)[source]

angular to momentum space conversion for a point detector located in direction of self.r_i when detector angles are zero

Parameters:

***args: sample and detector angles as numpy array, lists**

or Scalars in total len(self.sampleAxis)+len(detectorAxis) must be given, always starting with the outer most circle. all arguments must have the same shape or length but can be mixed with Scalars (i.e. if an angle is always the same it can be given only once instead of an array)

sAngles:sample circle angles, number of arguments must correspond to len(self.sampleAxis)
dAngles:detector circle angles, number of arguments must correspond to len(self.detectorAxis)
**kwargs: optional keyword arguments
delta:giving delta angles to correct the given ones for misalignment delta must be an numpy array or list of len(*args) used angles are than *args - delta
UB:matrix for conversion from (hkl) coordinates to Q of sample used to determine not Q but (hkl) (default: self.UB)
wl:x-ray wavelength in angstroem (default: self._wl)
en:x-ray energy in eV (default is converted self._wl) both wavelength and energy can also be an array which enables the QConversion for energy scans. Note that the en keyword overrules the wl keyword!
deg:flag to tell if angles are passed as degree :(default: True)
sampledis:sample displacement vector in relative units of the detector distance (default: (0,0,0))
Returns:

reciprocal space positions as numpy.ndarray with shape ( * , 3 )

where * corresponds to the number of points given in the input

sampleAxis

property handler for _sampleAxis

Returns:list of sample axis following the syntax /[xyzk][+-]/
transformSample2Lab(vector, *args)[source]

transforms a vector from the sample coordinate frame to the laboratory coordinate system by applying the sample rotations from inner to outer circle.

Parameters:

**vector: vector to transform (sequence, list, numpy array)**

args:goniometer angles (sample angles or full goniometer angles can be given. If more angles than the sample circles are given they will be ignored)
Returns:

rotated vector as numpy.array

wavelength

xrayutilities.gridder module

class xrayutilities.gridder.FuzzyGridder1D(nx)[source]

Bases: xrayutilities.gridder.Gridder1D

An 1D binning class considering every data point to have a finite width. If necessary one data point will be split fractionally over different data bins. This is numerically more effort but represents better the typical case of a experimental data, which do not represent a mathematical point but have a finite width (e.g. X-ray data from a 1D detector).

class xrayutilities.gridder.Gridder[source]

Bases: object

Basis class for gridders in xrayutilities. A gridder is a function mapping irregular spaced data onto a regular grid by binning the data into equally sized elements.

There are different ways of defining the regular grid of a Gridder. In xrayutilities the data bins extend beyond the data range in the input data, but the given position being the center of these bins, extends from the minimum to the maximum of the data! The main motivation for this was to create a Gridder, which when feeded with N equidistant data points and gridded with N bins would not change the data position (not the case with numpy.histogramm functions!). Of course this leads to the fact that for homogeneous point density the first and last bin in any direction are not filled as the other bins.

A different definition is used by numpy histogram functions where the bins extend only to the end of the data range. (see numpy histogram, histrogram2d, ...)

Clear()[source]

Clear so far gridded data to reuse this instance of the Gridder

KeepData(bool)[source]
Normalize(bool)[source]

set or unset the normalization flag. Normalization needs to be done to obtain proper gridding but may want to be disabled in certain cases when sequential gridding is performed

data

return gridded data (performs normalization if switched on)

class xrayutilities.gridder.Gridder1D(nx)[source]

Bases: xrayutilities.gridder.Gridder

dataRange(min, max, fixed=True)[source]

define minimum and maximum data range, usually this is deduced from the given data automatically, however, for sequential gridding it is useful to set this before the first call of the gridder. data outside the range are simply ignored

Parameters:

**min: minimum value of the gridding range**

max:maximum value of the gridding range
fixed:flag to turn fixed range gridding on (True (default)) or off (False)
savetxt(filename, header='')[source]

save gridded data to a txt file with two columns. The first column is the data coordinate and the second the corresponding data value

Parameters:

**filename: output filename**

header:optional header for the data file.
xaxis

Returns the xaxis of the gridder the returned values correspond to the center of the data bins used by the gridding algorithm

xrayutilities.gridder.axis(min_value, max_value, n)[source]

Compute the a grid axis.

Parameters:

**min_value ........... axis minimum value**

**max_value ........... axis maximum value**

**n ................... number of steps**

xrayutilities.gridder.delta(min_value, max_value, n)[source]

Compute the stepsize along an axis of a grid.

Parameters:

**min_value ........... axis minimum value**

**max_value ........... axis maximum value**

**n ................... number of steps**

class xrayutilities.gridder.npyGridder1D(nx)[source]

Bases: xrayutilities.gridder.Gridder1D

xaxis

Returns the xaxis of the gridder the returned values correspond to the center of the data bins used by the numpy.histogram function

xrayutilities.gridder.ones(*args)[source]

Compute ones for matrix generation. The shape is determined by the number of input arguments.

xrayutilities.gridder2d module

class xrayutilities.gridder2d.FuzzyGridder2D(nx, ny)[source]

Bases: xrayutilities.gridder2d.Gridder2D

An 2D binning class considering every data point to have a finite area. If necessary one data point will be split fractionally over different data bins. This is numerically more effort but represents better the typical case of a experimental data, which do not represent a mathematical point but have a finite size (e.g. X-ray data from a 2D detector or reciprocal space maps measured with point/linear detector).

Currently only a rectangular area can be considered during the gridding.

class xrayutilities.gridder2d.Gridder2D(nx, ny)[source]

Bases: xrayutilities.gridder.Gridder

SetResolution(nx, ny)[source]

Reset the resolution of the gridder. In this case the original data stored in the object will be deleted.

Parameters:

**nx ............ number of points in x-direction**

**ny ............ number of points in y-direction**

dataRange(xmin, xmax, ymin, ymax, fixed=True)[source]

define minimum and maximum data range, usually this is deduced from the given data automatically, however, for sequential gridding it is useful to set this before the first call of the gridder. data outside the range are simply ignored

Parameters:

**xmin,ymin: minimum value of the gridding range in x,y**

xmax,ymax:maximum value of the gridding range in x,y
fixed:flag to turn fixed range gridding on (True (default)) or off (False)
savetxt(filename, header='')[source]

save gridded data to a txt file with two columns. The first two columns are the data coordinates and the last one the corresponding data value.

Parameters:

**filename: output filename**

header:optional header for the data file.
xaxis
xmatrix
yaxis
ymatrix
class xrayutilities.gridder2d.Gridder2DList(nx, ny)[source]

Bases: xrayutilities.gridder2d.Gridder2D

special version of a 2D gridder which performs no actual averaging of the data in one grid/bin but just collects the data-objects belonging to one bin for further treatment by the user

Clear()[source]
data

return gridded data, in this special version no normalization is defined!

xrayutilities.gridder3d module

class xrayutilities.gridder3d.FuzzyGridder3D(nx, ny, nz)[source]

Bases: xrayutilities.gridder3d.Gridder3D

An 3D binning class considering every data point to have a finite volume. If necessary one data point will be split fractionally over different data bins. This is numerically more effort but represents better the typical case of a experimental data, which do not represent a mathematical point but have a finite size.

Currently only a quader can be considered as volume during the gridding.

class xrayutilities.gridder3d.Gridder3D(nx, ny, nz)[source]

Bases: xrayutilities.gridder.Gridder

SetResolution(nx, ny, nz)[source]
dataRange(xmin, xmax, ymin, ymax, zmin, zmax, fixed=True)[source]

define minimum and maximum data range, usually this is deduced from the given data automatically, however, for sequential gridding it is useful to set this before the first call of the gridder. data outside the range are simply ignored

Parameters:

**xmin,ymin,zmin: minimum value of the gridding range in x,y,z**

xmax,ymax,zmax:maximum value of the gridding range in x,y,z
fixed:flag to turn fixed range gridding on (True (default)) or off (False)
xaxis
xmatrix
yaxis
ymatrix
zaxis
zmatrix

xrayutilities.normalize module

module to provide functions that perform block averaging of intensity arrays to reduce the amount of data (mainly for PSD and CCD measurements

and

provide functions for normalizing intensities for

* count time * absorber (user-defined function) * monitor * flatfield correction

class xrayutilities.normalize.IntensityNormalizer(det='', **keyargs)[source]

Bases: object

generic class for correction of intensity (point detector,or MCA, single CCD frames) for count time and absorber factors the class must be supplied with a absorber correction function and works with data structures provided by xrayutilities.io classes or the corresponding objects from hdf5 files

absfun

absfun property handler

returns the costum correction function or None

avmon

av_mon property handler

returns the value of the average monitor or None if average is calculated from the monitor field

darkfield

flatfield property handler

returns the current set darkfield of the detector or None if not set

det

det property handler

returns the detector field name

flatfield

flatfield property handler

returns the current set flatfield of the detector or None if not set

mon

mon property handler

returns the monitor field name or None if not set

time

time property handler

returns the count time or the field name of the count time or None if time is not set

xrayutilities.normalize.blockAverage1D(data, Nav)[source]

perform block average for 1D array/list of Scalar values all data are used. at the end of the array a smaller cell may be used by the averaging algorithm

Parameters:

**data: data which should be contracted (length N)**

Nav:number of values which should be averaged
Returns:

block averaged numpy array of data type numpy.double

(length ceil(N/Nav))

xrayutilities.normalize.blockAverage2D(data2d, Nav1, Nav2, **kwargs)[source]

perform a block average for 2D array of Scalar values all data are used therefore the margin cells may differ in size

Parameters:

**data2d: array of 2D data shape (N,M)**

Nav1,2:a field of (Nav1 x Nav2) values is contracted

****kwargs: optional keyword argument**

roi:region of interest for the 2D array. e.g. [20,980,40,960] N = 980-20; M = 960-40
Returns:

block averaged numpy array with type numpy.double with shape

( ceil(N/Nav1), ceil(M/Nav2) )

xrayutilities.normalize.blockAveragePSD(psddata, Nav, **kwargs)[source]

perform a block average for serveral PSD spectra all data are used therefore the last cell used for averaging may differ in size

Parameters:

**psddata: array of 2D data shape (Nspectra,Nchannels)**

Nav:number of channels which should be averaged

****kwargs: optional keyword argument**

roi:region of interest for the 2D array. e.g. [20,980] Nchannels = 980-20
Returns:

block averaged psd spectra as numpy array with type numpy.double

of shape ( Nspectra , ceil(Nchannels/Nav) )

xrayutilities.q2ang_fit module

Module provides functions to convert a q-vector from reciprocal space to angular space. a simple implementation uses scipy optimize routines to perform a fit for a arbitrary goniometer.

The user is, however, expected to use the bounds variable to put restrictions to the number of free angles to obtain reproducible results. In general only 3 angles are needed to fit an arbitrary q-vector (2 sample + 1 detector angles or 1 sample + 2 detector). More complicated restrictions can be implemented using the lmfit package. (done upon request!)

The function is based on a fitting routine. For a specific goniometer also analytic expressions from literature can be used as they are implemented in the predefined experimental classes HXRD, NonCOP, and GID.

xrayutilities.q2ang_fit.Q2AngFit(qvec, expclass, bounds=None, ormat=array([[ 1., 0., 0.], [ 0., 1., 0.], [ 0., 0., 1.]]), startvalues=None, constraints=())[source]

Functions to convert a q-vector from reciprocal space to angular space. This implementation uses scipy optimize routines to perform a fit for a goniometer with arbitrary number of goniometer angles.

The user *must* use the bounds variable to put restrictions to the number of free angles to obtain reproducible results. In general only 3 angles are needed to fit an arbitrary q-vector (2 sample + 1 detector angles or 1 sample + 2 detector).

Parameters:

**qvec: q-vector for which the angular positions should be calculated**

expclass:experimental class used to define the goniometer for which the angles should be calculated.
keyword arguments(optional):
bounds:list of bounds of the goniometer angles. The number of bounds must correspond to the number of goniometer angles in the expclass. Angles can also be fixed by supplying only one value for a particular angle. e.g.: ((low, up), fix, (low2, up2), (low3, up3))
ormat:orientation matrix of the sample to be used in the conversion
startvalues:start values for the fit, which can significantly speed up the conversion. The number of values must correspond to the number of angles in the goniometer of the expclass
constraints:sequence of constraint dictionaries. This allows applying arbitrary (e.g. pseudo-angle) contraints by supplying according constraint functions. (see scipy.optimize.minimize). The supplied function will be called with the arguments (angles, qvec, Experiment, U).
Returns:

fittedangles, qerror, errcode:

list of fitted goniometer angles, the error in reciprocal space and the errcode of the scipy minimize function. for a successful fit the error code should be <=2

xrayutilities.q2ang_fit.exitAngleConst(angles, alphaf, hxrd)[source]

helper function for an pseudo-angle constraint for the Q2AngFit-routine.

Parameters:

**angles: fit parameters of Q2AngFit**

alphaf:the exit angle which should be fixed
hxrd:the Experiment object to use for qconversion

xrayutilities.utilities module

xrayutilities utilities contains a conglomeration of useful functions which do not fit into one of the other files

xrayutilities.utilities.maplog(inte, dynlow='config', dynhigh='config', **keyargs)[source]

clips values smaller and larger as the given bounds and returns the log10 of the input array. The bounds are given as exponent with base 10 with respect to the maximum in the input array. The function is implemented in analogy to J. Stangl’s matlab implementation.

Parameters:

**inte** : numpy.array, values to be cut in range

dynlow:10^(-dynlow) will be the minimum cut off
dynhigh:10^(-dynhigh) will be the maximum cut off

**optional keyword arguments (NOT IMPLEMENTED):**

abslow:10^(abslow) will be taken as lower boundary
abshigh:10^(abshigh) will be taken as higher boundary
Returns:

numpy.array of the same shape as inte, where values smaller/larger then

10^(-dynlow,dynhigh) were replaced by 10^(-dynlow,dynhigh)

Examples

>>> lint = maplog(int,5,2)

xrayutilities.utilities_noconf module

xrayutilities utilities contains a conglomeration of useful functions this part of utilities does not need the config class

xrayutilities.utilities_noconf.clear_bit(f, offset)[source]

clears the bet at an offset

xrayutilities.utilities_noconf.en2lam(inp)[source]

converts the input energy in eV to a wavelength in Angstrom

Parameters:**inp** : energy in eV
Returns:float, wavlength in Angstrom

Examples

>>> wavelength = en2lam(8048)
xrayutilities.utilities_noconf.energy(en)[source]

convert common energy names to energies in eV

so far this works with CuKa1, CuKa2, CuKa12, CuKb, MoKa1

Parameters:

**en: energy either as scalar or array with value in eV, which**

will be returned unchanged; or string with name of emission line

Returns:

energy in eV as float

xrayutilities.utilities_noconf.exchange_filepath(orig, new, keep=0)[source]

function to exchange the root of a filename with the option of keeping the inner directory structure. This for example includes such a conversion /dir_a/subdir/sample/file.txt -> /home/user/data/sample/file.txt where the innermost directory name is kept (keep=1)

Parameters:

**orig: original filename which should have its data root replaced**

new:new path which should be used instead
keep:(optional) number of inner most directory names which should be kept the same in the output (default = 0). Note that the filename is always return unchanged also with keep=0.
Returns:

filename string

Examples

>>> exchange_filepath('/dir_a/subdir/sam/file.txt', '/data', 1)
'/data/sam/file.txt'
xrayutilities.utilities_noconf.exchange_path(orig, new, keep=0)[source]

function to exchange the root of a path with the option of keeping the inner directory structure. This for example includes such a conversion /dir_a/subdir/images/sample -> /home/user/data/images/sample where the two innermost directory names are kept (keep=2)

Parameters:

**orig: original path which should be replaced by the new path**

new:new path which should be used instead
keep:(optional) number of inner most directory names which should be kept the same in the output (default = 0)
Returns:

directory path string

Examples

>>> exchange_path('/dir_a/subdir/img/sam', '/home/user/data', 2)
'/home/user/data/img/sam'
xrayutilities.utilities_noconf.lam2en(inp)[source]

converts the input wavelength in Angstrom to an energy in eV

Parameters:**inp** : wavelength in Angstrom
Returns:float, energy in eV

Examples

>>> energy = lam2en(1.5406)
xrayutilities.utilities_noconf.set_bit(f, offset)[source]

sets the bit at an offset

xrayutilities.utilities_noconf.wavelength(wl)[source]

convert common energy names to energies in eV

so far this works with CuKa1, CuKa2, CuKa12, CuKb, MoKa1

Parameters:

**wl: wavelength; If scalar or array the wavelength in Angstrom will be**

returned unchanged, string with emission name is converted to wavelength

Returns:

wavelength in Angstrom as float

Module contents

xrayutilities is a Python package for assisting with x-ray diffraction experiments. Its the python package included in *xrayutilities*.

It helps with planning experiments as well as analyzing the data.

Authors:Dominik Kriegner <dominik.kriegner@gmail.com> and Eugen Wintersberger <eugen.wintersberger@desy.de>