XASutils module¶

The xasutils module offers the following XAFS utility functions :

Function	Description
`etok()`	Converts photo-electron energy to wavenumber.
`ktoe()`	Converts photo-electron wavenumber to energy.
`get_mapped_data()`	Returns data mapped to a common domain in a collection.

araucaria.xas.xasutils.etok(energy)[source]¶

Converts photo-electron energy to wavenumber.

Parameters: energy (ndarray) – Array of photo-electron energies (eV).
Return type: ndarray
Returns: Array of photo-electron wavenumbers (\(Å^{-1}\)).

Notes

Conversion is performed considering the non-relativistic approximation:

\[k = \frac{\sqrt{2mE}}{\hbar}\]

Where

\(k\): photo-electron wavenumber.
\(E\): kinetic energy of the photo-electron.
\(m\): electron mass.
\(\hbar\): reduced Planck constant.

Example

>>> from araucaria.xas import etok
>>> e = 400      # eV
>>> k = etok(e)  # A^{-1}
>>> print('%1.5f' % k)
10.24633

araucaria.xas.xasutils.ktoe(k)[source]¶

Converts photo-electron wavenumber to energy.

Parameters: k (ndarray) – Array with photo-electron wavenumbers (\(Å^{-1}\)).
Return type: ndarray
Returns: Array with photo-electron energies (eV).

See also

etok: Converts photo-electron energy to wavenumber.

Example

>>> from araucaria.xas import ktoe
>>> k = 10      # A^{-1}
>>> e = ktoe(k)  # eV
>>> print('%1.5f' % e)
380.99821

araucaria.xas.xasutils.get_mapped_data(collection, taglist=['all'], region='xanes', domain=None, range=[- inf, inf], kweight=2)[source]¶

Returns data mapped to a common domain in a collection.

Parameters

collection (Collection) – Collection with group datasets.
taglist (List[str]) – List with keys to filter groups based on their tags attributes in the Collection. The default is [‘all’].
region (str) – XAS region to perform mapping. Accepted values are ‘dxanes’, ‘xanes’, ‘exafs’. The default is ‘xanes’.
domain (Optional[ndarray]) – Domain values to perform mapping. Energy units are expected for ‘dxanes’ or ‘xanes’, while wavenumber (k) units are expected for ‘exafs’. It overrides the range parameter.
range (list) – Domain range in absolute values. Energy units are expected for ‘dxanes’ or ‘xanes’, while wavenumber (k) units are expected for ‘exafs’. The default is [-inf, inf].
kweight (int) – Exponent for weighting chi(k) by k^kweight. Only valid for region='exafs'. The default is 2.

Return type

Tuple[ndarray, ndarray]

Returns

1-D array containing the domain values for mapping.
Array containing in each column the mapped values of groups.

Raises

TypeError – If collection is not a valid Collection instance.
AttributeError – If collection has no tags attribute.
AttributeError – If groups in collection have no energy or norm attribute. Only verified if region=dxanes or region=xanes.
AttributeError – If groups in collection have no k or chi attribute. Only verified if region='exafs'.
KeyError – If items in taglist are not keys of the tags attribute.
ValueError – If region is not recognized.
ValueError – If range or domain is outside the domain of a group in collection.

Notes

Exploratory data analysis assumes that data is mapped to a common domain range. However, datasets in a Collection are often mapped to different domain ranges.

get_mapped_data() establishes a common domain based on the specified region and range variables, and returns an array with the interpolated values.

Alternatively, if a domain array is provided, get_mapped_data() returns an array with the interpolated values.

Example

>>> from numpy import allclose
>>> from araucaria.testdata import get_testpath
>>> from araucaria.xas import pre_edge
>>> from araucaria.stats import get_mapped_data
>>> from araucaria.io import read_collection_hdf5
>>> fpath      = get_testpath('Fe_database.h5')
>>> collection = read_collection_hdf5(fpath)
>>> collection.apply(pre_edge)
>>> ener, data = get_mapped_data(collection, region='xanes')
>>> allclose(ener.shape[0], data.shape[0])
True

>>> # passing a domain argument
>>> nener, ndata = get_mapped_data(collection, region='xanes',
...                                domain=ener)
>>> allclose(data, ndata)
True