Normalize module

The normalize module offers the following functions to normalize a scan:

Function

Description

find_e0()

Calculates the absorption threshold energy of a scan.

guess_edge()

Estimates the nearest absorption edge for a scan.

pre_edge()

Pre-edge substaction and normalization of a scan.
araucaria.xas.normalize.find_e0(group, method='maxder', tol=0.0001, pre_edge_kws=None, use_mu_ref=False, update=False)[source]

Calculates the absorption threshold energy of a XAFS scan.

Parameters

  • group (Group) – Group containing the spectrum to calculate e0.

  • method (str) – Name of the method to find e0. Valid names are ‘maxder’ and ‘halfedge’. See Notes for details. The default is ‘maxder’.

  • tol (float) – Tolerance value for convergence of e0 calculation. Only used if method='halfedge'. The defailt is 1e-4.

  • pre_edge_kws (Optional[dict]) – Dictionary with arguments for pre_edge(). Only used if method='halfedge'. The defailt is None, which considers default values for normalization.

  • use_mu_ref (bool) – Indicates if e0 should be calculated with the reference scan. The default is False.

  • update (bool) – Indicates if the group should be updated with the value of e0. The default is False.

Return type

float

Returns

Value of e0.

Raises

  • TypeError – If group is not a valid Group instance.

  • AttributeError – If attribute energy does not exist in group.

  • AttributeError – If attribute mu_ref does not exist in group when use_mu_ref = True.

  • ValueError – If method is not recocgnized.

Notes

If method=maxder the absorption threshold will be calculated as the maximum derivative in absorption.

If method=halfedge the absorption threshold will be calculated iteratively as half the edge step. This method calls pre_edge() to compute the edge step at each iteration. Parameters for the pre-edge calculation can be passed with the pre_edge_kws parameter. A tolerance for the error between iterations can be set with the tol parameter.

If use_mu_ref=False the absorption threshold will be calculated for the scan attribute of group, as determined by the get_mode() method. This is the default behavior.

If use_mu_ref=True the absorption threshold will be calculated for the group.mu_ref attribute.

If update=True the following attribute will be created in group:

  • group.e0: absorption threshold energy \(E_0\).

Important

Computing e0 with method=halfedge is sensitive to the parameters used to compute the edge step by pre_edge(). Therefore, different parameters for calculation of the edge step will yield different values of e0 by this method.

Currently method=halfedge considers a maximum of 10 iterations to compute e0.

Examples

>>> # computing e0 as the maximum derivative
>>> from araucaria.testdata import get_testpath
>>> from araucaria.io import read_dnd
>>> from araucaria.xas import find_e0
>>> fpath = get_testpath('dnd_testfile1.dat')
>>> # extracting mu and mu_ref scans
>>> group = read_dnd(fpath, scan='mu')
>>> # find e0 of reference scan
>>> find_e0(group, use_mu_ref=True)
29203.249

>>> # computing e0 as half the edge step
>>> find_e0(group, method='halfedge', use_mu_ref=True)
29200.62
araucaria.xas.normalize.guess_edge(group, e0=None, update=False)[source]

Estimates the nearest absorption edge for a XAFS scan.

Parameters

  • group (Group) – Group containing the spectrum for pre-edge substraction and normalization.

  • e0 (Optional[float]) – Absorption threshold energy. If None it will seach for the value stored in group.e0. Otherwise it will be calculated using find_e0(). with default parameters.

  • update (bool) – Indicates if the group should be updated with the normalization attributes. The default is False.

Return type

dict

Returns

Dictionary with the following arguments:

  • atsym : atomic symbol for the absorption edge.

  • edge : absorption edge in Siegbanh notation.

Raises

  • TypeError – If group is not a valid Group instance.

  • AttributeError – If attribute energy does not exist in group.

  • IndexError – If e0 is outside the range of group.energy.

See also

nearest_edge()

Returns the nearest x-ray edge for a given energy.

Example

>>> from araucaria.testdata import get_testpath
>>> from araucaria import Group
>>> from araucaria.io import read_dnd
>>> from araucaria.xas import find_e0
>>> from araucaria.utils import check_objattrs
>>> fpath = get_testpath('dnd_testfile1.dat')
>>> group = read_dnd(fpath, scan='mu')  # extracting mu and mu_ref scans
>>> attrs = ['atsym', 'edge']
>>> e0    = find_e0(group)
>>> edge  = guess_edge(group, e0, update=True)
>>> check_objattrs(group, Group, attrs)
[True, True]
>>> print(edge)
{'atsym': 'Sn', 'edge': 'K'}
araucaria.xas.normalize.pre_edge(group, e0=None, nvict=0, nnorm=2, pre_range=[- inf, - 50], post_range=[100, inf], update=False)[source]

Pre-edge substaction and normalization of a XAFS scan.

Parameters

  • group (Group) – Group containing the spectrum for pre-edge substraction and normalization.

  • e0 (Optional[float]) – Absorption threshold energy. If None it will seach for the value stored in group.e0. Otherwise it will be calculated using find_e0(). with default parameters.

  • nvict (int) – Energy exponent for pre-edge fit with a Victoreen polynomial. The default is 0. See Notes for details.

  • nnorm (int) – Degree of polynomial for post-edge fit. The default is 2.

  • pre_range (list) – Energy range with respect to e0 for the pre-edge fit. The default is [-inf, -50].

  • post_range (list) – Energy range with respect to e0 for the post-edge fit. The default is [100, inf].

  • update (bool) – Indicates if the group should be updated with the normalization attributes. The default is False.

Return type

dict

Returns

Dictionary with the following arguments:

  • e0 : absorption threshold energy \(E_0\).

  • edge_step : absorption edge step \(\Delta \mu(E_0)\).

  • norm : array with normalized \(\mu(E)\).

  • flat : array with flattened \(\mu(E)\).

  • pre_edge : fitted pre-edge polynomial.

  • post_edge : fitted post-edge polynomial.

  • pre_coefs : coefficients for the pre-edge Victoreen polynomial.

  • post_coefs : coefficients for the post-edge polynomial.

  • pre_edge_pars: dictionary with pre-edge parameters.

Raises

  • TypeError – If group is not a valid Group instance.

  • AttributeError – If attribute energy does not exist in group.

  • IndexError – If e0 is outside the range of group.energy.

  • ValueError – If pre_range contains less than two energy points.

  • ValueError – If post_range contains less than two energy points.

Warning

A warning will be raised if the degree of the post-edge polynomial is larger than 3.

See also

fig_pre_edge()

Plot the results of pre-edge substraction and normalization.

Notes

Pre-edge substraction and normalization is performed as follows:

  1. The absorption threshold is determined (if e0 or group.e0 is not supplied).

  2. A Victoreen polymonial with energy exponent nvict is fitted to the region below the edge, as specified by pre_range (2 coefficients are fitted):

    \(\mu(E) \cdot E^{nvict} = m \cdot E + b\)

  3. A polymonial of degree nnorm is fitted to the region above the edge, as specified by post_range (nnorm + 1 coefficients are fitted).

  4. The edge step is deterimned by extrapolating both curves to e0.

  5. A flattetned spectrum is calculated by removing the polynomial above the edge from the normalized spectrum, while maintaining the offset of the polynomial at e0.

If update=True the contents of the returned dictionary will be included as attributes of group.

Example

>>> from araucaria.testdata import get_testpath
>>> from araucaria import Group
>>> from araucaria.io import read_dnd
>>> from araucaria.xas import pre_edge
>>> from araucaria.utils import check_objattrs
>>> fpath = get_testpath('dnd_testfile1.dat')
>>> group = read_dnd(fpath, scan='mu')  # extracting mu and mu_ref scans
>>> attrs = ['e0', 'edge_step', 'pre_edge', 'post_edge', 'norm', 'flat']
>>> pre   = pre_edge(group, update=True)
>>> check_objattrs(group, Group, attrs)
[True, True, True, True, True, True]