#!/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=[",", ":"]))