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Import cross sections from csv #41

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Import cross sections from csv #41

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0a0270c
add test for process_pdos
Jun 23, 2021
d5c8552
fix the imports
Yaxuan-Lii Jun 29, 2021
553738f
removeed irrelevant files
Yaxuan-Lii Jul 1, 2021
5300d62
import is fixed
Yaxuan-Lii Jul 1, 2021
dab091b
try to remove irrelevant fils second time
Yaxuan-Lii Jul 1, 2021
d69d61b
remove irrelevant files second time
Yaxuan-Lii Jul 1, 2021
7984c15
delet irrelevant files
Yaxuan-Lii Jul 1, 2021
66b1c6f
remove irrelevant files
Yaxuan-Lii Jul 1, 2021
4fdafa7
delete .DS_Store
Yaxuan-Lii Jul 1, 2021
dca2d49
Modified test_process_pdos.py
Yaxuan-Lii Jul 2, 2021
eb079f6
add test.py
Yaxuan-Lii Jul 2, 2021
8190183
Restore some files that were accidentally deleted
ajjackson Jul 2, 2021
946efaa
use flake8 to optimise format
Yaxuan-Lii Jul 5, 2021
cd0f3c0
import cross-sections from CSV archives
Yaxuan-Lii Jul 15, 2021
8f48e5e
form modify
Yaxuan-Lii Jul 17, 2021
a959150
modify follow the comments
Yaxuan-Lii Jul 21, 2021
067c289
make corrections
Yaxuan-Lii Jul 21, 2021
a621ab0
make correction
Yaxuan-Lii Jul 21, 2021
13911d0
Revert changes to galore/__init__.py
ajjackson Jul 21, 2021
4fb993d
modified as comments
Yaxuan-Lii Aug 2, 2021
cd4dc0e
merge the change of galore/__init__.py
Yaxuan-Lii Aug 2, 2021
5c9c31c
add cli to install data and get cross sections
Yaxuan-Lii Aug 9, 2021
b138c4b
merge get_cross_sections_from_csv into get_cross_sections
Yaxuan-Lii Aug 10, 2021
bb8a526
modify and add new test
Yaxuan-Lii Aug 24, 2021
5cdb67b
add a IF statement
Yaxuan-Lii Aug 31, 2021
39651d5
modify as comments
Yaxuan-Lii Sep 9, 2021
a2441b5
modify as comments
Yaxuan-Lii Sep 9, 2021
f59b50a
mistakes fix
Yaxuan-Lii Sep 12, 2021
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70 changes: 46 additions & 24 deletions galore/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,13 +24,21 @@
from collections import OrderedDict
from collections.abc import Sequence
import logging
<<<<<<< HEAD

import galore.formats
=======
>>>>>>> 222f3f05787d36b754356ceb13dba854939c2d16
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from math import sqrt, log
import os.path

import numpy as np
from scipy.interpolate import interp1d

<<<<<<< HEAD
=======
import galore.formats
>>>>>>> 222f3f05787d36b754356ceb13dba854939c2d16
from galore.cross_sections import get_cross_sections, cross_sections_info
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Expand All @@ -52,9 +60,11 @@ def auto_limits(data_1d, padding=0.05):


def process_1d_data(input=['vasprun.xml'],
gaussian=None, lorentzian=None,
gaussian=None,
lorentzian=None,
sampling=1e-2,
xmin=None, xmax=None,
xmin=None,
xmax=None,
spikes=False,
**kwargs):
"""Read 1D data series from files, process for output
Expand Down Expand Up @@ -85,8 +95,7 @@ def process_1d_data(input=['vasprun.xml'],
input = input[0]

if not os.path.exists(input):
raise Exception(
"Input file {0} does not exist!".format(input))
raise Exception("Input file {0} does not exist!".format(input))
if galore.formats.is_xml(input):
xy_data = galore.formats.read_vasprun_totaldos(input)
elif galore.formats.is_gpw(input):
Expand All @@ -113,20 +122,29 @@ def process_1d_data(input=['vasprun.xml'],

broadened_data = data_1d.copy()
if lorentzian:
broadened_data = galore.broaden(
broadened_data, d=d, dist='lorentzian', width=lorentzian)
broadened_data = galore.broaden(broadened_data,
d=d,
dist='lorentzian',
width=lorentzian)

if gaussian:
broadened_data = galore.broaden(
broadened_data, d=d, dist='gaussian', width=gaussian)
broadened_data = galore.broaden(broadened_data,
d=d,
dist='gaussian',
width=gaussian)

return (x_values, broadened_data)


def process_pdos(input=['vasprun.xml'],
gaussian=None, lorentzian=None,
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weighting=None, sampling=1e-2,
xmin=None, xmax=None, flipx=False, **kwargs):
gaussian=None,
lorentzian=None,
weighting=None,
sampling=1e-2,
xmin=None,
xmax=None,
flipx=False,
**kwargs):
"""Read PDOS from files, process for output

Args:
Expand Down Expand Up @@ -167,8 +185,7 @@ def process_pdos(input=['vasprun.xml'],
break

if not os.path.exists(pdos_file):
raise Exception("Input file {0} does not "
"exist!".format(input))
raise Exception("Input file {0} does not " "exist!".format(input))

basename = os.path.basename(pdos_file)
try:
Expand All @@ -189,13 +206,14 @@ def process_pdos(input=['vasprun.xml'],
assert data.dtype.names[0] == energy_label
except AssertionError as error:
error.args += ("Energy labels are not consistent "
"between input files",)
"between input files", )
raise

orbital_labels = data.dtype.names[1:]
pdos_data[element] = OrderedDict([('energy', data[energy_label])])
pdos_data[element].update(OrderedDict((orbital, data[orbital])
for orbital in orbital_labels))
pdos_data[element].update(
OrderedDict(
(orbital, data[orbital]) for orbital in orbital_labels))
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# Work out sampling details; 5% pad added to data if no limits specified
# In x-flip mode, the user specifies these as binding energies so values
Expand Down Expand Up @@ -232,20 +250,22 @@ def process_pdos(input=['vasprun.xml'],
broadened_data = pdos_resampled.copy()

if lorentzian:
broadened_data = galore.broaden(broadened_data, d=d,
broadened_data = galore.broaden(broadened_data,
d=d,
dist='lorentzian',
width=lorentzian)

if gaussian:
broadened_data = galore.broaden(broadened_data, d=d,
broadened_data = galore.broaden(broadened_data,
d=d,
dist='gaussian',
width=gaussian)

pdos_plotting_data[element][orbital] = broadened_data

if weighting:
cross_sections = galore.get_cross_sections(weighting,
elements=pdos_data.keys())
cross_sections = get_cross_sections(weighting,
elements=pdos_data.keys())
pdos_plotting_data = galore.apply_orbital_weights(
pdos_plotting_data, cross_sections)

Expand Down Expand Up @@ -295,9 +315,11 @@ def xy_to_1d(xy, x_values, spikes=False):
return spikes

else:
y_func = interp1d(xy[x_field], xy[y_field],
y_func = interp1d(xy[x_field],
xy[y_field],
assume_sorted=False,
bounds_error=False, fill_value=0)
bounds_error=False,
fill_value=0)
return y_func(x_values)


Expand Down Expand Up @@ -417,8 +439,8 @@ def apply_orbital_weights(pdos_data, cross_sections):
weighted_pdos_data = OrderedDict()
for el, orbitals in pdos_data.items():
if 'warning' in cross_sections[el]:
logging.warning(" {0}: {1}".format(
el, cross_sections[el]['warning']))
logging.warning(" {0}: {1}".format(el,
cross_sections[el]['warning']))
weighted_orbitals = OrderedDict()
for orbital, data in orbitals.items():
if orbital == 'energy':
Expand Down
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