pymatgen.io.qchem_io.utils module

lower_and_check_unique(dict_to_check)[source]

Takes a dictionary and makes all the keys lower case. Also replaces “jobtype” with “job_type” just so that key specifically can be called elsewhere without ambiguity. Finally, ensures that multiple identical keys, that differed only due to different capitalizations, are not present. If there are multiple equivalent keys, an Exception is raised.

Parameters:dict_to_check (dict) – The dictionary to check and standardize
Returns:
An identical dictionary but with all keys made
lower case and no identical keys present.
Return type:to_return (dict)
process_parsed_coords(coords)[source]

Takes a set of parsed coordinates, which come as an array of strings, and returns a numpy array of floats.

read_pattern(text_str, patterns, terminate_on_match=False, postprocess=<class 'str'>)[source]

General pattern reading on an input string

Parameters:
  • text_str (str) – the input string to search for patterns
  • patterns (dict) – A dict of patterns, e.g., {“energy”: r”energy(sigma->0)s+=s+([d-.]+)”}.
  • terminate_on_match (bool) – Whether to terminate when there is at least one match in each key in pattern.
  • postprocess (callable) – A post processing function to convert all matches. Defaults to str, i.e., no change.
Renders accessible:
Any attribute in patterns. For example, {“energy”: r”energy(sigma->0)s+=s+([d-.]+)”} will set the value of matches[“energy”] = [[-1234], [-3453], …], to the results from regex and postprocess. Note that the returned values are lists of lists, because you can grep multiple items on one line.
read_table_pattern(text_str, header_pattern, row_pattern, footer_pattern, postprocess=<class 'str'>, attribute_name=None, last_one_only=False)[source]

Parse table-like data. A table composes of three parts: header, main body, footer. All the data matches “row pattern” in the main body will be returned.

Args:

text_str (str): the input string to search for patterns header_pattern (str): The regular expression pattern matches the

table header. This pattern should match all the text immediately before the main body of the table. For multiple sections table match the text until the section of interest. MULTILINE and DOTALL options are enforced, as a result, the “.” meta-character will also match “
” in this
section.
row_pattern (str): The regular expression matches a single line in
the table. Capture interested field using regular expression groups.
footer_pattern (str): The regular expression matches the end of the
table. E.g. a long dash line.
postprocess (callable): A post processing function to convert all
matches. Defaults to str, i.e., no change.
attribute_name (str): Name of this table. If present the parsed data
will be attached to “data. e.g. self.data[“efg”] = […]
last_one_only (bool): All the tables will be parsed, if this option
is set to True, only the last table will be returned. The enclosing list will be removed. i.e. Only a single table will be returned. Default to be True.
Returns:
List of tables. 1) A table is a list of rows. 2) A row if either a list of attribute values in case the the capturing group is defined without name in row_pattern, or a dict in case that named capturing groups are defined by row_pattern.