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RASPA2 / data /python /output_parser.py
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#!/usr/bin/python
"""
Parses RASPA output, returning a mutable Python object.
String output is organized in Python dictionary object.
############## COMMON DATA ##################
Below shows how to retrieve some common values after running RASPA
info = RASPA.run(...)
1) Average loading absolute
info["Number of molecules"][MOLECULE_NAME][Unit_Name][0]
# specific example with Nitrogen molecule
info["Number of molecules:"]["N2"][insert below units][0]
5 units are specified from RASPA output
YOU MUST INSERT ENTIRE STRIG WITHIN BRACKETS
["Average loading absolute [molecules/unit cell]"]
["Average loading absolute [cm^3 (STP)/gr framework]"]
["Average loading absolute [mol/kg framework]"]
["Average loading absolute [milligram/gram framework]"]
["Average loading absolute [cm^3 (STP)/cm^3 framework]"]
2) Average loading excess
info["Number of molecules"][MOLECULE_NAME][Unit_Name][0]
# specific example with Nitrogen molecule
info["Number of molecules"]["N2"][insert below units][0]
5 units are specified from RASPA output
YOU MUST INSERT ENTIRE STRIG WITHIN BRACKETS
["Average loading excess [molecules/unit cell]"]
["Average loading excess [cm^3 (STP)/gr framework]"]
["Average loading excess [mol/kg framework]"]
["Average loading excess [milligram/gram framework]"]
["Average loading excess [cm^3 (STP)/cm^3 framework]"]
3) Helium Void Fraction
info["Average Widom Rosenbluth factor"]["Widom"][0]
4) Henry coefficient
info["Average Henry coefficient:"]["Henry"][0]
5) Heat of desorption values
info["Heat of desorption"]["[K]"][0]
" ["[KJ/MOL]"][0]
info["Heat of desorption (Host-Adsorbate contribution)"]["[K]"][0]
" ["[KJ/MOL]"][0]
info["Heat of desorption (Adsorbate-Adsorbate contribution)"]["[K]"][0]
" ["[KJ/MOL]"][0]
6) Geometric Surface Area:
info["Average Surface Area"]["[m^2/g]"][0]
info["Average Surface Area"]["[m^2/cm^3]"][0]
"""
import re
def parse(raspa_output):
"""Specific parsing of the output file.
Args:
raspa_output: A string representing unparsed RASPA output
Returns:
A data structure generated from the RASPA file
"""
# Reads the string into a newline-separated list, skipping useless lines
data = [row.strip() for row in raspa_output.splitlines() if row and
all(d not in row for d in ["-----", "+++++"])]
# Generally, categories in the output are delimited by equal signs
delimiters = [i for i, row in enumerate(data) if "=====" in row
and "Exclusion constraints energy" not in data[i - 1]]
# Append a row for "absolute adsorption:" and "excess adsorption:"
# These values are separated into two rows
abs_adsorp_rows = [i for i, row in enumerate(data)
if "absolute adsorption:" in row]
for row in abs_adsorp_rows:
data[row] += " " + data[row + 1]
data[row + 2] += data[row + 3]
data[row + 1], data[row + 3] = " ", " "
# Use the delimiters to make a high-level dict. Title is row before
# delimiter, and content is every row after delimiter, up to the next title
info = {data[n - 1].strip(":"): data[n + 1: delimiters[i + 1] - 1]
for i, n in enumerate(delimiters[:-1])}
# Let's PARSE!
for key, values in info.items():
d, note_index = {}, 1
for item in values:
# Takes care of all "Blocks[ #]", skipping hard-to-parse parts
if ("Block" in item and "Box-lengths" not in key
and "Van der Waals:" not in item):
blocks = _clean(item.split())
d["".join(blocks[:2])] = blocks[2:]
# Most of the average data values are parsed in this section
elif (any(s in item for s in ["Average ", "Surface area:"])
and "desorption" not in key):
average_data = _clean(item.split())
# Average values organized by its unit, many patterns here
if len(average_data) == 8:
del average_data[2:4]
d[" ".join(average_data[4:6])] = average_data[1:4]
elif len(average_data) == 5:
d[average_data[-1]] = average_data[1:4]
elif "Surface" in average_data[0]:
d[average_data[-1]] = average_data[2:5]
# This is the common case
else:
del average_data[2]
d[average_data[-1]] = average_data[1:4]
# Average box-lengths has its own pattern
elif "Box-lengths" in key:
box_lengths = _clean(item.split())
i = 3 if "angle" in item else 2
d[" ".join(box_lengths[:i])] = box_lengths[i:]
# "Heat of Desorption" section
elif "desorption" in key:
if "Note" in item:
notes = re.split("[:\s]{2,}", item)
d["%s %d" % (notes[0], note_index)] = notes[1]
note_index += 1
else:
heat_desorp = _clean(item.split())
# One line has "Average" in front, force it to be normal
if "Average" in item:
del heat_desorp[0]
d[heat_desorp[-1]] = heat_desorp[0:3]
# Parts where Van der Waals are included
elif ("Host-" in key or "-Cation" in key or
"Adsorbate-Adsorbate" in key) and "desorption" not in key:
van_der = item.split()
# First Column
if "Block" in van_der[0]:
sub_data = [_clean(s.split(":"))
for s in re.split("\s{2,}", item)[1:]]
sub_dict = {s[0]: s[1] for s in sub_data[:2]}
d["".join(van_der[:2])] = [float(van_der[2]), sub_dict]
# Average for each columns
elif "Average" in item:
avg = _clean(re.split("\s{2,}", item))
vdw, coulomb = [_clean(s.split(": ")) for s in avg[2:4]]
d[avg[0]] = avg[1]
d["Average %s" % vdw[0]] = vdw[1]
d["Average %s" % coulomb[0]] = coulomb[1]
else:
d["standard deviation"] = _clean(van_der)
# IMPORTANT STUFF
elif "Number of molecules" in key:
adsorb_data = _clean(item.rsplit(" ", 12))
if "Component" in item:
gas_name = adsorb_data[2].strip("[]")
d[gas_name] = {}
else:
d[gas_name][adsorb_data[0]] = adsorb_data[1:]
# Henry and Widom
elif "Average Widom" in item:
d["Widom"] = _clean(item.rsplit(" ", 5))[1:]
elif "Average Henry" in item:
d["Henry"] = _clean(item.rsplit(" ", 5))[1:]
# Ignore these
elif any(s in item for s in ["=====", "Starting simulation",
"Finishing simulation"]):
continue
# Other strings
else:
parsed_data = _clean(re.split("[()[\]:,\t]", item))
d[parsed_data[0]] = parsed_data[1:]
# Putting subdictionary back into main object
info[key] = d
return info
def _clean(split_list):
"""Strips and attempts to convert a list of strings to floats."""
def try_float(s):
try:
return float(s)
except ValueError:
return s
return [try_float(s.strip()) for s in split_list if s]
if __name__ == "__main__":
import sys
import json
with open(sys.argv[-1]) as in_file:
data = in_file.read()
print(json.dumps(parse(data), indent=4, sort_keys=True,
separators=[",", ":"]))