def run(target_folder,
journals_path=None,
authors_path=None,
keywords_path=None,
mesh_terms_path=None,
from_date=None,
to_date=None,
date_interval_in_years=None):
target_path = join(target_folder, 'results.csv')
# Input retrieval
journals = load_unique_lines(journals_path)
text_words = load_unique_lines(keywords_path)
mesh_terms = load_unique_lines(mesh_terms_path)
authors = load_unique_lines(authors_path)
# Get list containing tuples of date ranges based on interval
try:
date_ranges = get_date_ranges(from_date, to_date,
date_interval_in_years)
except ToolError as e:
exit('to_date.error = %s' % e)
query_list = journals if journals else authors
search_journals = True if journals else False
# Tabulate keywords
results = tabulate(query_list, date_ranges, text_words, mesh_terms,
search_journals)
search_counts = results['search_counts']
queries = results['queries']
query_totals = results['query_totals']
# Output setup
log_path = join(target_folder, 'log_results.txt')
with open(log_path, 'w') as f:
f.write(queries)
f.write(query_totals)
dates_index = [str(x)[:10] + ' to ' + str(y)[:10] for x, y in date_ranges]
results_table = DataFrame(search_counts, index=dates_index)
results_table.to_csv(target_path)
# Required print statement for crosscompute tool
print('results_table_path = ' + target_path)
print('log_text_path = ' + log_path)
def run(
target_folder, journals_path=None, authors_path=None,
keywords_path=None, mesh_terms_path=None,
from_date=None, to_date=None, date_interval_in_years=None):
target_path = join(target_folder, 'results.csv')
# Input retrieval
journals = load_unique_lines(journals_path)
text_words = load_unique_lines(keywords_path)
mesh_terms = load_unique_lines(mesh_terms_path)
authors = load_unique_lines(authors_path)
# Get list containing tuples of date ranges based on interval
try:
date_ranges = get_date_ranges(
from_date, to_date, date_interval_in_years)
except ToolError as e:
exit('to_date.error = %s' % e)
query_list = journals if journals else authors
search_journals = True if journals else False
# Tabulate keywords
results = tabulate(
query_list, date_ranges, text_words, mesh_terms, search_journals)
search_counts = results['search_counts']
queries = results['queries']
query_totals = results['query_totals']
# Output setup
log_path = join(target_folder, 'log_results.txt')
with open(log_path, 'w') as f:
f.write(queries)
f.write(query_totals)
dates_index = [
str(x)[:10] + ' to ' + str(y)[:10] for x, y in date_ranges]
results_table = DataFrame(search_counts, index=dates_index)
results_table.to_csv(target_path)
# Required print statement for crosscompute tool
print('results_table_path = ' + target_path)
print('log_text_path = ' + log_path)
def test_load_unique_lines():
lines = load_unique_lines(join(TEST_FOLDER, 'lines.txt'))
assert lines == ['one', 'two']
