""" Functions to get and use HED queries. """
import pandas as pd
from hed.models import QueryHandler
[docs]def get_query_handlers(queries, query_names=None):
""" Return a list of query handlers, query names, and issues if any.
Parameters:
queries (list): A list of query strings.
query_names (list or None): A list of column names for results of queries. If missing --- query_1, query_2, etc.
Returns:
list - QueryHandlers for successfully parsed queries.
list - str names to assign to results of the queries.
list - issues if any of the queries could not be parsed or other errors occurred.
"""
if not queries:
return None, None, ["EmptyQueries: The queries list must not be empty"]
elif isinstance(queries, str):
queries = [queries]
expression_parsers = [None] * len(queries)
issues = []
if not query_names:
query_names = [f"query_{index}" for index in range(len(queries))]
if len(queries) != len(query_names):
issues.append(f"QueryNamesLengthBad: The query_names length {len(query_names)} must be empty or equal " +
f"to the queries length {len(queries)}.")
elif len(set(query_names)) != len(query_names):
issues.append(f"DuplicateQueryNames: The query names {str(query_names)} list has duplicates")
for index, query in enumerate(queries):
try:
expression_parsers[index] = QueryHandler(query)
except Exception:
issues.append(f"[BadQuery {index}]: {query} cannot be parsed")
return expression_parsers, query_names, issues
[docs]def search_strings(hed_strings, queries, query_names):
""" Return a DataFrame of factors based on results of queries.
Parameters:
hed_strings (list): A list of HedString objects (empty entries or None entries are 0's
queries (list): A list of query strings or QueryHandler objects.
query_names (list): A list of column names for results of queries.
Returns:
DataFrame: Contains the factor vectors with results of the queries.
:raises ValueError:
- If query names are invalid or duplicated.
"""
df_factors = pd.DataFrame(0, index=range(len(hed_strings)), columns=query_names)
for parse_ind, parser in enumerate(queries):
for index, next_item in enumerate(hed_strings):
if next_item:
match = parser.search(next_item)
if match:
df_factors.at[index, query_names[parse_ind]] = 1
return df_factors