def __init__(self, queries, ole_input_dir, ole_result_files,
cognos_input_dir, cognos_result_files, ole_lr_dir):
self.queries_data, self.results = [], {"ole":[], "cognos":[]}
#self.queries_data, self.results = [], {"ole":[], "cognos":[], "ole_lr": []}
for c in queries:
tname = "".join(c["q"].split(" OR "))
lname = "".join(c["l"].split())
fn = tname+"_"+lname+"_"+str(0)+".csv"
if fn in ole_result_files:
fn_cognos = tname+"_"+lname+".csv"
self.queries_data.append(c)
self.results["ole"].append(get_fields_from_csv_file(ole_input_dir+fn))
self.results["cognos"].append(get_fields_from_csv_file(cognos_input_dir+\
fn_cognos))
#self.results["ole_lr"].append(get_fields_from_csv_file(ole_lr_dir+fn_cognos))
self.get_results_by_ranking_model(ole_lr_dir)
def format_data(self, input_dir, train_percent=70):
self.queries_data = []
self.results = {"ole": []}
all_files, all_fnames = [], []
for r, _, fs in os.walk(input_dir):
for f in fs:
all_files.append(r+"/"+f)
all_fnames.append(f)
for i in self.queries:
tname = "".join(i.split())
if tname not in Rank.topic_hash:
Rank.topic_hash[tname] = Rank.topic_ctr
Rank.topic_ctr += 1
for j in self.locations:
lname = "".join(j.split())
fname = get_filename("ole", tname, lname)
#include epsilon data also later
if fname in all_fnames:
ind = all_fnames.index(fname)
self.queries_data.append({"q": i, "l":j})
self.results["ole"].append(get_fields_from_csv_file(all_files[ind]))
self.data = []
indexes = range(len(self.queries_data))
shuffle(indexes)
l = len(indexes)
l_train = l*train_percent/100
train_indexes = indexes[:l_train]
test_indexes = indexes[l_train:]
self.train_data, self.test_data = [] , []
for i in train_indexes:
query = self.queries_data[i]
result = self.results["ole"][i]
self.train_data.append(Rank.get_data_obj(query, result, i))
for i in test_indexes:
query = self.queries_data[i]
result = self.results["ole"][i]
self.test_data.append(Rank.get_data_obj(query, result, i))
write_to_file("train.dat", self.train_data)
write_to_file("test.dat", self.test_data)
