Source code for matador.scrapers.cif_scraper

# coding: utf-8
# Distributed under the terms of the MIT License.

""" This file implements the scraper functions for the CIF
(Crystallographic Information File) format.


import functools
from pathlib import Path
import numpy as np
from matador.scrapers.utils import scraper_function, get_flines_extension_agnostic
from matador.utils.cell_utils import (

EPS = 1e-13

[docs]@scraper_function def cif2dict(fname, **kwargs): """ Extract available information from .cif file and store as a dictionary. Raw cif data is stored under the `'_cif'` key. Symmetric sites are expanded by the symmetry operations and their occupancies are tracked. Parameters: fname (str/list): filename or list of filenames of .cif file(s) (with or without extension). Returns: (dict/str, bool): if successful, a dictionary containing scraped data and True, if not, then an error string and False. """ flines, fname = get_flines_extension_agnostic(fname, "cif") doc = dict() cif_dict = _cif_parse_raw(flines) doc['_cif'] = cif_dict doc['source'] = [str(Path(fname).resolve())] doc['atom_types'] = [] atom_labels = cif_dict.get("_atom_site_type_symbol", False) if not atom_labels: atom_labels = cif_dict.get("_atom_site_label", False) if not atom_labels: raise RuntimeError(f"Unable to find atom types in cif file {fname}.") for atom in atom_labels: symbol = '' for character in atom: if not character.isalpha(): break else: symbol += character doc['atom_types'].append(symbol) doc['positions_frac'] = [list(map(lambda x: float(x.split('(')[0]), vector)) for vector in zip(cif_dict['_atom_site_fract_x'], cif_dict['_atom_site_fract_y'], cif_dict['_atom_site_fract_z'])] if '_atom_site_occupancy' in cif_dict: doc['site_occupancy'] = [float(x.split('(')[0]) for x in cif_dict['_atom_site_occupancy']] else: doc['site_occupancy'] = [1.0 for _ in doc['positions_frac']] if '_atom_site_symmetry_multiplicity' in cif_dict: doc['site_multiplicity'] = [float(x.split('(')[0]) for x in cif_dict['_atom_site_symmetry_multiplicity']] else: doc['site_multiplicity'] = [1.0 for _ in doc['positions_frac']] doc['lattice_abc'] = [list(map(_cif_parse_float_with_errors, [cif_dict['_cell_length_a'], cif_dict['_cell_length_b'], cif_dict['_cell_length_c']])), list(map(_cif_parse_float_with_errors, [cif_dict['_cell_angle_alpha'], cif_dict['_cell_angle_beta'], cif_dict['_cell_angle_gamma']]))] doc['lattice_cart'] = abc2cart(doc['lattice_abc']) doc['cell_volume'] = cart2volume(doc['lattice_cart']) doc['stoichiometry'] = _cif_disordered_stoichiometry(doc) doc['num_atoms'] = len(doc['positions_frac']) if '_space_group_symop_operation_xyz' in doc['_cif'] and '_symmetry_equiv_pos_as_xyz' not in doc['_cif']: doc["_cif"]["_symmetry_equiv_pos_as_xyz"] = doc["_cif"]["_space_group_symop_operation_xyz"] if '_symmetry_equiv_pos_as_xyz' in doc['_cif']: _cif_set_unreduced_sites(doc) try: doc['space_group'] = get_spacegroup_spg(doc, check_occ=False) except RuntimeError: pass return doc, True
def _cif_parse_float_with_errors(x): """ Strip bracketed errors from end of float. """ return float(x.split('(')[0]) def _cif_disordered_stoichiometry(doc): """ Create a matador stoichiometry normalised to the smallest integer number of atoms, unless all occupancies are 1/0. Parameters: doc: dictionary containing `atom_types`, `site_occupancy` and `site_multiplicity` keys. Returns: list of tuples: a standard matador stoichiometry. """ from collections import defaultdict stoich = defaultdict(float) eps = 1e-8 disordered = False for ind, site in enumerate(doc['atom_types']): stoich[site] += doc['site_occupancy'][ind] * doc['site_multiplicity'][ind] if doc['site_multiplicity'][ind] % 1 > 1e-5: disordered = True if disordered: min_int = 1e10 for atom in stoich: if abs(int(stoich[atom]) - stoich[atom]) < eps: if int(stoich[atom]) < min_int: min_int = int(stoich[atom]) if min_int == 1e10: min_int = 1 for atom in stoich: stoich[atom] /= min_int return sorted([[atom, stoich[atom]] for atom in stoich]) def _cif_parse_raw(flines): """ Parse raw CIF file data into a dictionary. Parameters: flines (:obj:`list` of :obj:`str`): contents of .cif file. Returns: dict: dictionary containing cif data with native fields/ordering. """ ind = 0 cif_dict = dict() cif_dict['loops'] = list() while ind < len(flines): jnd = 1 line = flines[ind].strip() # parse single (multi-line) tag if line.startswith('_'): line = line.split() key = line[0] data = '' if len(line) > 1: data += ' '.join(line[1:]) while ind + jnd < len(flines) and _cif_line_contains_data(flines[ind+jnd].strip()): data += flines[ind+jnd].strip().replace(';', '') jnd += 1 cif_dict[key] = data.strip() # parse loop block elif line.startswith('loop_'): # get loop keys keys = [] while flines[ind+jnd].strip().startswith('_'): keys.append(flines[ind+jnd].strip()) jnd += 1 for key in keys: cif_dict[key] = [] cif_dict['loops'].append(keys) while ind + jnd < len(flines) and _cif_line_contains_data(flines[ind+jnd].strip()): data = '' # loop over line and next lines while ind + jnd < len(flines) and _cif_line_contains_data(flines[ind+jnd]): data += flines[ind+jnd] jnd += 1 loop_dict = _cif_parse_loop(keys, data) cif_dict.update(loop_dict) ind += jnd return cif_dict def _cif_parse_loop(keys, data_block): """ A hacky way to parse CIF data loops that can be split by quotes or spaces. There must be a better way... Parameters: keys (list of str): list of keys for the loop. data_block (str): raw string of the entire data block. Returns: Dict[str, str]: a dictionary with keys from ``keys``, containing the data split by quotes and spaces. All data is left as strings for further processing. """ from collections import deque, defaultdict dq = deque(data_block) data_list = [] entry = None in_quotes = False while dq: char = dq.popleft() if not char.strip() and entry is None: continue elif (not char.strip() or char in [" ", ";"]) and entry is not None and not in_quotes: data_list.append(entry.strip()) entry = None elif not char.strip() and entry is not None and in_quotes: entry += " " elif char == "'" and entry and entry is not None: in_quotes = False data_list.append(entry.strip()) entry = None elif char == "'" and entry is None: entry = '' in_quotes = True else: if entry is None: entry = char else: entry += char loop_dict = defaultdict(list) for ind, entry in enumerate(data_list): ind = ind % len(keys) loop_dict[keys[ind]].append(entry) return loop_dict def _cif_set_unreduced_sites(doc): """ Expands sites by symmetry operations found under the key `symemtry_equiv_pos_as_xyz` in the cif_dict. Parameters: doc (dict): matador document to modify. Must contain symops under doc['_cif']['_symmetry_equiv_pos_as_xyz']. This doc is updated with new `positions_frac`, `num_atoms`, `atom_types` and `site_occupancy`. """ from matador.utils.cell_utils import wrap_frac_coords from matador.utils.cell_utils import calc_pairwise_distances_pbc from matador.fingerprints.pdf import PDF species_sites = dict() species_occ = dict() symmetry_ops = [] symmetry_functions = [] def _apply_sym_op(x=None, y=None, z=None, symmetry=None): """ Returns the site after the applied symmetry operation, in string representation. """ # cannot use a listcomp here due to interplay with functools return [eval(symmetry[0]), eval(symmetry[1]), eval(symmetry[2])] for symmetry in doc['_cif']['_symmetry_equiv_pos_as_xyz']: symmetry = tuple(elem.strip() for elem in symmetry.strip('\'').split(',')) # check the element before doing an eval, as it is so unsafe allowed_chars = ['x', 'y', 'z', '.', '/', '+', '-', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] for element in symmetry: for character in element: if character not in allowed_chars: raise RuntimeError('You are trying to do something naughty with the symmetry element {}' .format(element)) symmetry_ops.append(symmetry) symmetry_functions.append(functools.partial(_apply_sym_op, symmetry=symmetry)) for ind, site in enumerate(doc['positions_frac']): species = doc['atom_types'][ind] occupancy = doc['site_occupancy'][ind] if doc['atom_types'][ind] not in species_sites: species_sites[species] = [] species_occ[species] = [] for symmetry in symmetry_functions: x, y, z = site new_site = symmetry(x=x, y=y, z=z) new_site = wrap_frac_coords([new_site])[0] species_sites[species].append(new_site) species_occ[species].append(occupancy) unreduced_sites = [] unreduced_occupancies = [] unreduced_species = [] # this loop assumes that no symmetry operation can map 2 unlike sites upon one another for species in species_sites: unreduced_sites.extend(species_sites[species]) unreduced_occupancies.extend(species_occ[species]) unreduced_species.extend(len(species_sites[species]) * [species]) # check that the symmetry procedure has not generated overlapping atoms # this can happen for certain symmetries/cells if positions are not # reported to sufficient precision images = PDF._get_image_trans_vectors_auto( doc['lattice_cart'], 0.1, 0.01, max_num_images=1, ) poscarts = frac2cart(doc['lattice_cart'], unreduced_sites) distances = calc_pairwise_distances_pbc( poscarts, images, doc['lattice_cart'], 0.01, compress=False, filter_zero=False, per_image=True ) dupe_set = set() for img in distances: try: i_s, j_s = np.where(~img.mask) except ValueError: # ValueError will be raised if there is only one atom as i_s, j_s cannot be unpacked continue for i, j in zip(i_s, j_s): if i == j: continue else: # sites can overlap if they have partial occupancy if i not in dupe_set and unreduced_species[i] == unreduced_species[j]: dupe_set.add(j) doc['positions_frac'] = unreduced_sites doc['site_occupancy'] = unreduced_occupancies doc['atom_types'] = unreduced_species doc['site_occupancy'] = [ atom for ind, atom in enumerate(unreduced_occupancies) if ind not in dupe_set ] doc['atom_types'] = [ atom for ind, atom in enumerate(unreduced_species) if ind not in dupe_set ] doc['positions_frac'] = [ atom for ind, atom in enumerate(unreduced_sites) if ind not in dupe_set ] _num_atoms = np.sum(doc['site_occupancy']) if abs(_num_atoms - round(_num_atoms, 0)) < EPS: _num_atoms = int(round(_num_atoms, 0)) doc['num_atoms'] = _num_atoms if len(doc['site_occupancy']) != len(doc['positions_frac']): raise RuntimeError('Size mismatch between positions and occs, {} vs {}' .format(len(doc['site_occupancy']), len(doc['positions_frac']))) if len(doc['positions_frac']) != len(doc['atom_types']): raise RuntimeError('Size mismatch between positions and types') def _cif_line_contains_data(line): """ Check if string contains cif-style data. """ return not any([line.startswith('_'), line.startswith('#'), line.startswith('loop_')]) @scraper_function def _ase_cif2dict(fname): """ Read cif file into ASE object, then convert ASE Atoms into matador document. Parameters: fname (str): cif filename Returns: (dict, bool): simple matador document with error status. """ import from matador.utils.ase_utils import ase2dict fname = fname.replace('.cif', '') atoms = + '.cif') doc = ase2dict(atoms) return doc, True