classify4me_prototypes.py 9.53 KB
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#! /usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Includes function that reads json files and classifies the stuctures 
included on the basis of encyclopedia and the calculated in the preprocessor 
space_group and normalized_wyckoff, and returns a dictionary with key - json
 file name and value - classification_name (with labels in the same format as 
in the read_prototypes function).
"""

from __future__ import absolute_import

__author__ = "Daria M. Tomecka and Fawzi Mohamed"
__copyright__ = "Copyright 2017, The NOMAD Project"
__maintainer__ = "Daria M. Tomecka"
__email__ = "tomeckadm@gmail.com;"
__date__ = "18/05/17"

import sys
import ase.io
import json
import numpy as np
import time
import datetime
import os, os.path
import logging

import setup_paths
#from nomad_sim.wrappers import get_json_list
#from nomad_sim.wrappers import plot, logger
#from nomad_sim.utils_crystals import get_spacegroup
#from nomad_sim.utils_crystals import create_supercell
#from nomad_sim.wrappers import get_json_list
#from nomad_sim.nomad_structures import NOMADStructure
###
from nomadcore.structure_types import \
    structure_types_by_spacegroup as str_types_by_spg
from nomadcore.parse_streamed_dicts import ParseStreamedDicts
from nomadcore.local_meta_info import loadJsonFile, InfoKindEl
from nomadcore.parser_backend import JsonParseEventsWriterBackend


#prototypes_file = os.path.normpath("/nomad-lab-base/analysis-tools/structural-similarity/python-modules/nomad_sim/structure_types.py")
#Classification of json calculartion using encyclopedia preprocessor

import sys
#print(sys.path)
sys.path.append('/home/beaker/py3k/lib/python3.5/')
import spglib
#import Nomad
import logging
#from Nomad.Preprocessing.System import structure, preprocessormaterial3d
#from Nomad import ProcessingEngine

#LOGGER = logging.getLogger(__name__)
#logging.basicConfig(level=logging.ERROR)

#json_list = beaker.json_list

atomSpecies = None
#atomSpecies = atom_species

def get_normalized_wyckoff(atomic_number, wyckoff):
    """Returns a normalized Wyckoff sequence for the given atomic numbers and
    wyckoff symbols.
    """
    # print("at", atomic_number, wyckoff)
    atomCount = {}
    for nr in atomic_number:
        atomCount[nr] = atomCount.get(nr, 0) + 1
    wycDict = {}
    for i, wk in enumerate(wyckoff):
        oldVal = wycDict.get(wk, {})
        nr = atomic_number[i]
        oldVal[nr] = oldVal.get(nr, 0) + 1
        wycDict[wk] = oldVal
    sortedWyc = list(wycDict.keys())
    sortedWyc.sort()

    def cmpp(a, b):
        return ((a < b) - (a > b))

    def compareAtNr(at1, at2):
        """Returns a normalized Wyckoff sequence for the given atomic numbers and
        wyckoff symbols.
        """
        # print("at", atomic_number, wyckoff)
        atomCount = {}
        for nr in atomic_number:
            atomCount[nr] = atomCount.get(nr, 0) + 1
        wycDict = {}
        for i, wk in enumerate(wyckoff):
            oldVal = wycDict.get(wk, {})
            nr = atomic_number[i]
            oldVal[nr] = oldVal.get(nr, 0) + 1
            wycDict[wk] = oldVal
        sortedWyc = list(wycDict.keys())
        sortedWyc.sort()

    def cmpp(a, b):
        return ((a < b) - (a > b))

    def compareAtNr(at1, at2):
        c = cmpp(atomCount[at1], atomCount[at2])
        if (c != 0):
            return c
        for wk in sortedWyc:
            p = wycDict[wk]
            c = cmpp(p.get(at1, 0), p.get(at2, 0))
            if c != 0:
                return c
        return 0
    sortedAt = list(atomCount.keys())
    sortedAt.sort(key=functools.cmp_to_key(compareAtNr))
    standardAtomNames = {}
    for i, at in enumerate(sortedAt):
        standardAtomNames[at] = ("X_%d" % i)
    standardWyc = {}
    for wk, ats in wycDict.items():
        stdAts = {}
        for at, count in ats.items():
            stdAts[standardAtomNames[at]] = count
        standardWyc[wk] = stdAts
    if standardWyc:
        if (c != 0):
            return c
        for wk in sortedWyc:
            p = wycDict[wk]
            c = cmpp(p.get(at1, 0), p.get(at2, 0))
            if c != 0:
                return c
        return 0
    sortedAt = list(atomCount.keys())
    sortedAt.sort(key=functools.cmp_to_key(compareAtNr))
    standardAtomNames = {}
    for i, at in enumerate(sortedAt):
        standardAtomNames[at] = ("X_%d" % i)
    standardWyc = {}
    for wk, ats in wycDict.items():
        stdAts = {}
        for at, count in ats.items():
            stdAts[standardAtomNames[at]] = count
        standardWyc[wk] = stdAts
    if standardWyc:
        counts = [c for x in standardWyc.values() for c in x.values()]
        # logging.error("counts: %s", counts)
        gcd = counts[0]
        for c in counts[1:]:
            gcd = fractions.gcd(gcd,c)
        if gcd != 1:
            for wk,d in standardWyc.items():
                for at,c in d.items():
                    d[at] = c // gcd
    return standardWyc



def get_structure_type(space_group, norm_wyckoff):
    """Returns the information on the prototype.
    """
    structure_type_info = {}
    #wyckoff_letters_compact = "".join(sorted(set(wyckoff_letters)))

    #print("Wyckoff1", norm_wyckoff)#_compact)
    #print("Space Gr", space_group)

    for type_description in str_types_by_spg.get((space_group), []):
        #current_bravais_lattice = type_description['Pearsons Symbol'][0:2]
        #current_wyckoffs = type_description['Wyckoff Positions']

        #if current_bravais_lattice == bravais_lattice \
         #       and current_wyckoffs == wyckoff_letters_compact:        current_norm_wyckoffs = type_description.get('normalized_wyckoff')
        current_norm_wyckoffs = type_description.get("normalized_wyckoff")
        if current_norm_wyckoffs and current_norm_wyckoffs == norm_wyckoff:
            structure_type_info = type_description
            break
    if structure_type_info:
        return structure_type_info
    else:
        return None



#from preprocessor

def _structure_type_info(self):
    """Known structure types"""
    return structure.get_structure_type(
        self.space_group,
        self.normalized_wyckoff)

def toAtomNr(str):
    "returns the atom number of the given symbol"
    baseStr = str[:3].title()
    if baseStr.startswith("Uu") and baseStr in chemical_symbols[1:]:
        return chemical_symbols.index(baseStr)
    if baseStr[:2] in chemical_symbols[1:]:
        return chemical_symbols.index(baseStr[:2])
    elif baseStr[:1] in chemical_symbols[1:]:
        return chemical_symbols.index(baseStr[:1])
    else:
        return 0


def classify_by_norm_wyckoff(sectionSystem):
    try:
        #try:
        #    simulation_cell = json_file_name.get('lattice_vectors')
        #    labels = json_file_name.get('atom_labels')
        #    atom_pos = json_file_name.get('atom_positions')
        #    if not simulation_cell or not labels or not atom_pos:
        #        raise Exception("Parsed invalid geometry for space group %d, %s" % (spaceGroupNr, protoDict))

        #    proc = ProcessingEngine(mode="debug")
        #results = proc.process(json_file_name)
        ###
        #atomic_number = atom_species
        #as in the normalized version

        #norm_wyckoff = get_normalized_wyckoff

        # preprocessor = list(results.values())
        # if len(preprocessor) == 1:
        #     preprocessor = preprocessor[0]
        #     spg_nr = preprocessor["space_group"]
        #     norm_wyckoff = preprocessor["normalized_wyckoff"]

        ###
        conf = sectionSystem
        lab = conf.get("atom_labels", None)
        periodicDirs = conf.get("configuration_periodic_dimensions", periodicDirs)
        atomSpecies = [toAtomNr(l) for l in lab]

        symm = None
        symm = spglib.get_symmetry_dataset(filename)
        #                                  sym = spglib.get_symmetry_dataset((number,wyckoff, pearsons_symbol)


        wyckoffs = str(symm.get("wyckoffs"))
        spg_nr = symm.get("number")
        #                pearson - symm.get("xxx")
        #space_group = symmetry_dataset["number"]

        ###
        norm_wyckoff = get_normalized_wyckoff(atomSpecies,wyckoffs) 
        protoDict = structure.get_structure_type(spg_nr, norm_wyckoff)

        if protoDict is None:
            proto = "%d-_" % spg_nr
        else:
            #if protoDict.get("Notes","") not in ["", "_", "-", "–"]:
            #    proto = '%d-%s' % (spg_nr, protoDict)
            #else:
            #proto = '%d-%s' % (spg_nr, protoDict)
            proto = '%d-%s-%s' % (spg_nr, protoDict.get("Prototype","-"),protoDict.get("Pearsons Symbol","-"))
        return proto
    except:
        logging.exception("failure while computing for %r",json_file_name)

    return None

#classify_by_norm_wyckoff(json_list)
            

def main():
    metapath = '../../../../nomad-meta-info/meta_info/nomad_meta_info/' +\
          'common.nomadmetainfo.json'
    metaInfoPath = os.path.normpath(
    os.path.join(os.path.dirname(os.path.abspath(__file__)), metapath))
  
    metaInfoEnv, warns = loadJsonFile(filePath=metaInfoPath,
                                      dependencyLoader=None,
                                      extraArgsHandling=InfoKindEl.ADD_EXTRA_ARGS,
                                      uri=None)
    backend = JsonParseEventsWriterBackend(metaInfoEnv)
    dictReader = ParseStreamedDicts(sys.stdin)
    while True:
        sectSys = dictReader.readNextDict()
        if sectSys is None:
            break
        label = classify_by_norm_wyckoff(sectSys)
        if label:
            backend.openContext(sectSys.uri)
            backend.addValue("prototype_label", label)
            backend.closeContext(sectSys.uri)

if __name__ == '__main__':
    main()