def test_source_title_matching(articles_sample, output_filepath):
journal_titles = [
"THEORETICAL FOUNDATIONS OF CHEMICAL ENGINEERING", "DOWN BEAT"
]
matches = ArticleCollection(articles_sample).select(
SourceTitleMatcher(journal_titles), output_filepath)
assert sum(1 for article in matches) == 2
def test_reference_list_ids(single_article_path):
expected = [
'000303524000001.127', 'WOS:000074141300003', 'WOS:000076444100008',
'WOS:000084608600019', 'WOS:000169756700007', 'WOS:000185914300012',
'WOS:000264798000005.30', 'WOS:A1997XH27400004'
]
ref_list = ArticleCollection(single_article_path).reference_list()
assert sorted(ref_list.ids()) == expected
def test_id_matching(articles_sample, output_filepath):
ids = [
"WOS:000251423400047", "WOS:000249481100010", "WOS:not-in-sample-set"
]
matches = ArticleCollection(articles_sample).select(
IdMatcher(ids), output_filepath)
assert sum(1 for article in matches) == 2
assert sum(1 for line in open(output_filepath)) == len(ids) - 1
def test_affiliation_matching_from_list(affiliated_sample, output_filepath):
uwmadison_names = [
"University of Wisconsin Madison", "Univ Wisconsin",
"University Wisconsin Health"
]
matches = ArticleCollection(affiliated_sample).select(
AffiliationMatcher(uwmadison_names), output_filepath)
assert sum(1 for article in matches) == 1
def articles_sample_reflist(tmpdir, articles_sample):
return ArticleCollection(articles_sample).reference_list()
print("Find by WOS Export - Processing Data for Year:", year, cluster_id,
process_id)
finder_logging.configure(cluster_id, process_id)
match_collections = []
ids = [
article['UT']
for article in csv.DictReader(open(exported_file), delimiter='\t')
]
criteria = IdMatcher(ids)
for input_file in input_files:
output_file = os.path.splitext(
os.path.basename(input_file))[0] + "-article-matches.json"
match_collections.append(
ArticleCollection(input_file).select(criteria, output_file))
article_match_count = 0
reference_count = 0
for matched_collection in match_collections:
with open(references_file, 'a') as file:
for article in matched_collection:
article_match_count += 1
for reference in article.references():
reference_count += 1
year = reference['year'] if reference[
'year'] is not None else 'BLANK'
id = reference['id'] if reference['id'] is not None else ''
file.write('\t'.join([year, id]) + '\n')
print("Articles: ", article_match_count)
start = datetime.today()
output_dir = sys.argv[1]
year = sys.argv[2]
# A lookup table that maps output_files
output_files = {}
input_files = glob.glob(output_dir + "/*.json")
article_count = 0
reference_count = 0
wos_rec_refs = 0
# Loop thru the article collection and write the references out
for input_file in input_files:
print(input_file)
for article in ArticleCollection(input_file):
article_count += 1
for reference in article.references():
reference_count += 1
if reference['id'] is not None and matches_source_item(
reference['id']):
wos_rec_refs += 1
# First Hash the ID of the referenced article. This will help ensure that the output
# files are evenly distributed in size.
hash_id = hashlib.sha1(bytearray(reference['id'],
"utf-8")).hexdigest()
file = get_file_bin(output_files, hash_id, output_dir, year)
# Next write the entry to the output file corresponding to the current hash ID.
json_str = json.dumps({
def test_reference_list_years(single_article_path):
expected = ['1996', '1997', '1998', '1999', '2000', '2001', '2003']
ref_list = ArticleCollection(single_article_path).reference_list()
assert sorted(ref_list.years()) == expected
def test_article_parsing(articles_sample):
assert sum(1 for article in ArticleCollection(articles_sample)) == 10
def test_case_insensitive_phrase_matching(articles_sample, output_filepath):
matches = ArticleCollection(articles_sample).select(
PhraseMatcher('baker'), output_filepath)
assert sum(1 for article in matches) == 1
def test_citation_matching(articles_sample, output_filepath):
ids = ["WOS:000084608600019"]
matches = ArticleCollection(articles_sample).select(
CitationMatcher(ids), output_filepath)
assert sum(1 for article in matches) == 2
assert sum(1 for line in open(output_filepath)) == 2
start = datetime.today()
year = sys.argv[1]
cluster_id = sys.argv[2]
process_id = sys.argv[3]
input_files = glob.glob("data/*.json")
article_file = "articles.csv"
print( "Find Citing Records - Processing Data for Year:", year, cluster_id, process_id )
finder_logging.configure(cluster_id, process_id)
ids = set()
with open(article_file) as csv_file:
csv_reader = csv.DictReader(csv_file)
for row in csv_reader:
ids.add(row["ID"])
for input_file in input_files:
output_file = "output/" + os.path.splitext(os.path.basename(input_file))[0] + "-citing-records.json"
ArticleCollection(input_file).select(CitationMatcher(ids), output_file)
finish = datetime.today()
print( "Started: ", start )
print( "Finished: ", finish )
print( "Time Spent:", finish - start, "\n" )