def get_adjudication_data_api():
global runs_df
global qrels_df
global LOGS_PATH
method = request.args.get('method')
topic = int(request.args.get('topic'))
pool_size = int(request.args.get('poolDepth'))
runs_filtered = get_runs.by_topic(runs_df, topic)
qrels_filtered = get_qrels.by_topic(qrels_df, topic)
if method == 'round_robin':
adjudication_result = round_robin.round_robin_alg(
runs_filtered, qrels_filtered, pool_size, LOGS_PATH)
if method == 'max_mean':
adjudication_result = max_mean.max_mean_alg(runs_filtered,
qrels_filtered, pool_size,
LOGS_PATH)
response = make_response(
jsonify(adjudication_result),
200,
)
response.headers["Content-Type"] = "application/json"
return response
def get_runs_api():
global runs_df
if (runs_df.empty or request.args.get('topic') is None):
return make_response(
"",
404,
)
else:
topic = int(request.args.get('topic'))
# dataframe filtered by topic
runs_filtered = get_runs.by_topic(runs_df, topic)
# shorten the run size to avoid sending too large data
runs_filtered = get_runs.by_run_size(runs_filtered, 100)
# dataframe with index ['RANK', 'RUN']
runs_by_rank = get_runs.indexed_by_rank(runs_filtered)
response = make_response(
jsonify(convert_data.get_dict_from_df(runs_by_rank)),
200,
)
response.headers["Content-Type"] = "application/json"
return response
# parameters
topic = 402
pool_size = 300
logging.basicConfig(filename=LOGS_PATH + 'round_robin.log',
filemode='w',
format='%(message)s',
level=logging.DEBUG)
pd.set_option("display.max_rows", None, "display.max_columns", 1000,
"display.max_colwidth", None, "display.width", 100000)
# load the txt files into a dataframe runs
# print("➡️ Loading runs from file.")
runs_df = convert_data.read_csv_into_df(RUNS_PATH, "RUNS", 30, 0)
# load the txt files into a dataframe qrels
# print("➡️ Loading qrels from file.")
qrels_df = convert_data.read_csv_into_df(QRELS_PATH, "QRELS", 1, 0)
# filter both runs & qrels by topic
runs_filtered = get_runs.by_topic(runs_df, topic)
qrels_filtered = get_qrels.by_topic(qrels_df, topic)
# print("Start adjudication by pressing enter")
# start_adjudication = str(input())
# round_robin.round_robin_alg(runs_filtered, qrels_filtered, pool_size, LOGS_PATH)
max_mean_results = max_mean.max_mean_alg(runs_filtered, qrels_filtered,
pool_size, LOGS_PATH)