parse data from xml using python 3

Question

Please find the mwe xml file (The actual file is 81k lines long, I am showing a tiny part).

<?xml version="1.0" encoding="ISO-8859-1"?>
<modeling>
  <dos>
    <i name="efermi">     -2.48501882 </i>
    <total>
      <array>
        <dimension dim="1">gridpoints</dimension>
        <dimension dim="2">spin</dimension>
        <field>energy</field>
        <field>total</field>
        <field>integrated</field>
        <set>
          <set comment="spin 1">
            <r>   -55.6029     0.0000     0.0000 </r>
            <r>   -55.3940     0.0000     0.0000 </r>
            <r>   -55.1850     0.0000     0.0000 </r>
            <r>   -54.9761     0.0000     0.0000 </r>
          </set>
          <set comment="spin 2">
            <r>   -55.6029     0.0000     0.0000 </r>
            <r>   -55.3940     0.0000     0.0000 </r>
            <r>   -55.1850     0.0000     0.0000 </r>
            <r>   -54.9761     0.0000     0.0000 </r>
          </set>
        </set>
      </array>
    </total>
    <partial>
      <array>
        <dimension dim="1">gridpoints</dimension>
        <dimension dim="2">spin</dimension>
        <dimension dim="3">ion</dimension>
        <field>energy</field>
        <field>    s</field>
        <field>   py</field>
        <field>   pz</field>
        <field>   px</field>
        <field>  dxy</field>
        <field>  dyz</field>
        <field>  dz2</field>
        <field>  dxz</field>
        <field>x2-y2</field>
        <set>
          <set comment="ion 1">
            <set comment="spin 1">
              <r>   -55.6029     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
              <r>   -55.3940     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
              <r>   -55.1850     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
              <r>   -54.9761     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
            </set>
            <set comment="spin 2">
              <r>   -55.6029     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
              <r>   -55.3940     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
              <r>   -55.1850     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
              <r>   -54.9761     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000     0.0000 </r>
            </set>
          </set>
        </set>
      </array>
    </partial>
  </dos>
</modeling>

The dos tag nested well below, and the values in the component spin 1 etc are not necessarily 0. I have managed to reach till dos tag, and get the efermi value, but don't understand how to get the sets separately and selectively so that I can plot it using matplotlib.

This is my current code:

#!/usr/bin/env python
import xml.etree.ElementTree as ET

tree = ET.parse("trial.xml")
root = tree.getroot()

for elem in root:
  print(elem.tag)
  if elem.tag == 'dos':
    for x in elem:
      print(x.attrib.get('name'), x.text)

Bhanuchander Udhayakumar · Accepted Answer · 2022-01-11 16:21:11Z

1

You can get the sets directly using https://docs.python.org/3/library/xml.etree.elementtree.html#xml.etree.ElementTree.Element.findall and xpath (like : 'node_a.node_b.etc.req_node') like shown below code... (also can access the comment text)

import xml.etree.ElementTree as ET
import pandas as pd
from matplotlib import pyplot as plt

tree = ET.fromstring("test.xml")
root = tree.getroot()


for elem in root.findall('./dos/partial/array/set/set/set'):
    comment = elem.get('comment')
    print(comment)
    data = list()
    for row in elem.findall('r'):
        data.append(list(map(float, row.text.split())))
    df = pd.DataFrame(data)
    print(df)
    df.plot()
    plt.show()

answered Jan 11, 2022 at 16:21

Bhanuchander Udhayakumar

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