public release 2.2.0 - see README.md and CHANGES.md for details
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pmsco/elements/photoionization.py
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pmsco/elements/photoionization.py
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"""
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@package pmsco.elements.photoionization
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photoionization cross-sections of the elements
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extends the element table of the `periodictable` package
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(https://periodictable.readthedocs.io/en/latest/index.html)
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by a table of photoionization cross-sections.
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the data is available from (https://vuo.elettra.eu/services/elements/)
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or (https://figshare.com/articles/dataset/Digitisation_of_Yeh_and_Lindau_Photoionisation_Cross_Section_Tabulated_Data/12389750).
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both sources are based on the original atomic data tables by Yeh and Lindau (1985).
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the Elettra data includes interpolation at finer steps,
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whereas the Kalha data contains only the original data points by Yeh and Lindau
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plus an additional point at 8 keV.
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the tables go up to 1500 eV photon energy and do not resolve spin-orbit splitting.
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usage
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-----
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this module requires python 3.6, numpy and the periodictable package (https://pypi.python.org/pypi/periodictable).
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~~~~~~{.py}
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import numpy as np
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import periodictable as pt
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import pmsco.elements.photoionization
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# read any periodictable's element interfaces as follows.
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# eph and cs are numpy arrays of identical shape that hold the photon energies and cross sections.
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eph, cs = pt.gold.photoionization.cross_section['4f']
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eph, cs = pt.elements.symbol('Au').photoionization.cross_section['4f']
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eph, cs = pt.elements.name('gold').photoionization.cross_section['4f']
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eph, cs = pt.elements[79].photoionization.cross_section['4f']
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# interpolate for specific photon energy
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print(np.interp(photon_energy, eph, cs)
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~~~~~~
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the data is loaded from the cross-sections.dat file which is a python-pickled data file.
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to switch between data sources, use one of the load functions defined here
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and dump the data to the cross-sections.dat file.
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@author Matthias Muntwiler
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@copyright (c) 2020 by Paul Scherrer Institut @n
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Licensed under the Apache License, Version 2.0 (the "License"); @n
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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"""
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import numpy as np
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from pathlib import Path
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import periodictable as pt
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import pickle
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import urllib.request
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import urllib.error
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from . import bindingenergy
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def load_kalha_data():
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"""
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load all cross-sections from csv-files by Kalha et al.
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the files must be placed in the 'kalha' directory next to this file.
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@return: cross-section data in a nested dictionary, cf. load_pickled_data().
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"""
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data = {}
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p = Path(Path(__file__).parent, "kalha")
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for entry in p.glob('*_*.csv'):
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if entry.is_file():
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try:
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element = int(entry.stem.split('_')[0])
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except ValueError:
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pass
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else:
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data[element] = load_kalha_file(entry)
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return data
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def load_kalha_file(path):
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"""
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load the cross-sections of an element from a csv-file by Kalha et al.
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@param path: file path
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@return: (dict) dictionary of 'nl' terms.
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the data items are tuples (photon_energy, cross_sections) of 1-dimensional numpy arrays.
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"""
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a = np.genfromtxt(path, delimiter=',', names=True)
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b = ~np.isnan(a['Photon_Energy__eV'])
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a = a[b]
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eph = a['Photon_Energy__eV'].copy()
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data = {}
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for n in range(1, 8):
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for l in 'spdf':
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col = f"{n}{l}"
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try:
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data[col] = (eph, a[col].copy())
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except ValueError:
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pass
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return data
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def load_kalha_configuration(path):
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"""
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load the electron configuration from a csv-file by Kalha et al.
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@param path: file path
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@return: (dict) dictionary of 'nl' terms mapping to number of electrons in the sub-shell.
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"""
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p = Path(path)
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subshells = []
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electrons = []
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config = {}
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with p.open() as f:
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for l in f.readlines():
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s = l.split(',')
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k_eph = "Photon Energy"
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k_el = "#electrons"
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if s[0][0:len(k_eph)] == k_eph:
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subshells = s[1:]
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elif s[0][0:len(k_el)] == k_el:
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electrons = s[1:]
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for i, sh in enumerate(subshells):
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if sh:
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config[sh] = electrons[i]
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return config
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def load_elettra_file(symbol, nl):
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"""
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download the cross sections of one level from the Elettra webelements web site.
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@param symbol: (str) element symbol
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@param nl: (str) nl term, e.g. '2p' (no spin-orbit)
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@return: (photon_energy, cross_section) tuple of 1-dimensional numpy arrays.
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"""
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url = f"https://vuo.elettra.eu/services/elements/data/{symbol.lower()}{nl}.txt"
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try:
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data = urllib.request.urlopen(url)
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except urllib.error.HTTPError:
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eph = None
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cs = None
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else:
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a = np.genfromtxt(data)
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try:
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eph = a[:, 0]
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cs = a[:, 1]
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except IndexError:
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eph = None
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cs = None
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return eph, cs
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def load_elettra_data():
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"""
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download the cross sections from the Elettra webelements web site.
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@return: cross-section data in a nested dictionary, cf. load_pickled_data().
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"""
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data = {}
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for element in pt.elements:
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element_data = {}
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for nlj in element.binding_energy:
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nl = nlj[0:2]
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eb = element.binding_energy[nlj]
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if nl not in element_data and eb <= 2000:
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eph, cs = load_elettra_file(element.symbol, nl)
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if eph is not None and cs is not None:
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element_data[nl] = (eph, cs)
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if len(element_data):
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data[element.symbol] = element_data
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return data
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def save_pickled_data(path, data):
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"""
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save a cross section data dictionary to a python-pickled file.
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@param path: file path
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@param data: cross-section data in a nested dictionary, cf. load_pickled_data().
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@return: None
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"""
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with open(path, "wb") as f:
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pickle.dump(data, f)
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def load_pickled_data(path):
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"""
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load the cross section data from a python-pickled file.
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the file can be generated by the save_pickled_data() function.
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@param path: file path
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@return: cross-section data in a nested dictionary.
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the first-level keys are element symbols.
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the second-level keys are 'nl' terms (e.g. '2p').
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note that the Yeh and Lindau tables do not resolve spin-orbit splitting.
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the data items are (photon_energy, cross_sections) tuples
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of 1-dimensional numpy arrays holding the data table.
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cross section values are given in Mb.
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"""
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with open(path, "rb") as f:
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data = pickle.load(f)
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return data
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class Photoionization(object):
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def __init__(self):
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self.cross_section = {}
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self.cross_section_units = "Mb"
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def init(table, reload=False):
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"""
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loads cross section data into the periodic table.
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this function is called by the periodictable to load the data on demand.
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@param table:
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@param reload:
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@return:
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"""
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if 'photoionization' in table.properties and not reload:
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return
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table.properties.append('photoionization')
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# default value
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pt.core.Element.photoionization = Photoionization()
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p = Path(Path(__file__).parent, "cross-sections.dat")
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data = load_pickled_data(p)
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for el_key, el_data in data.items():
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try:
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el = table[int(el_key)]
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except ValueError:
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el = table.symbol(el_key)
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pi = Photoionization()
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pi.cross_section = el_data
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pi.cross_section_units = "Mb"
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el.photoionization = pi
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