def parseData(strFileNameTrainFeatures, strFileNameTrainTimes):
# print "---------------------------------------------------------------------"
print 'Parsing Data'
print ' -> Reading Train Features :', strFileNameTrainFeatures
instIds, train_features = readfile_data(strFileNameTrainFeatures)
train_dict_features, train_list_names_features = makeDict(instIds, train_features)
train_array_features = train_features
print ' -> Reading Train Times :', strFileNameTrainTimes
instIds, train_times = readfile_data(strFileNameTrainTimes)
train_dict_times, train_list_names_times = makeDict(instIds, train_times)
train_array_features_orig = np.array(train_array_features)
nAlgs = len(train_dict_times[train_list_names_times[0]])
nFeatures = len(train_dict_features[train_list_names_features[1]])
print
print 'Basic Information on Data: '
print ' --> Number of Algorithms :', nAlgs
print ' --> Number of Features :', nFeatures
print ' --> Number of Train-Feature-vectors :', len(train_dict_features)
print ' --> Number of Train-Time-vectors :', len(train_dict_times)
# print "---------------------------------------------------------------------"
X_train = []
Y_train = []
for idTrainInstance in train_list_names_features:
X_train += [train_dict_features[idTrainInstance]]
Y_train += [train_dict_times[idTrainInstance]]
X_train = np.array(X_train)
Y_train = np.array(Y_train)
return X_train, Y_train
def parseData(strFileNameTestFeatures, strFileNameTestTimes):
# print "---------------------------------------------------------------------"
print 'Parsing Data'
print ' -> Reading Test Features :', strFileNameTestFeatures
instIds, test_features = readfile_data(strFileNameTestFeatures)
test_dict_features, test_list_names_features = makeDict(instIds, test_features)
print ' -> Reading Test Times :', strFileNameTestTimes
instIds, test_times = readfile_data(strFileNameTestTimes)
test_dict_times, test_list_names_times = makeDict(instIds, test_times)
nAlgs = len(test_dict_times[test_list_names_times[0]])
nFeatures = len(test_dict_features[test_list_names_features[0]])
print
print ' Basic Information on Data: '
print ' --> Number of Algorithms :', nAlgs
print ' --> Number of Features :', nFeatures
print ' --> Number of Test-Feature-vectors :', len(test_dict_features)
print ' --> Number of Test-Time-vectors :', len(test_dict_times)
# print "---------------------------------------------------------------------"
X_test = []
Y_test = []
for idTestInstance in test_list_names_features:
X_test += [test_dict_features[idTestInstance]]
Y_test += [test_dict_times[idTestInstance]]
X_test = np.array(X_test)
Y_test = np.array(Y_test)
return X_test, Y_test
def parseData(strFileNameTestFeatures, strFileNameTestTimes):
# print "---------------------------------------------------------------------"
print('Parsing Data')
print(' -> Reading Test Features :', strFileNameTestFeatures)
instIds, test_features = readfile_data(strFileNameTestFeatures)
test_dict_features, test_list_names_features = makeDict(
instIds, test_features)
print(' -> Reading Test Times :', strFileNameTestTimes)
instIds, test_times = readfile_data(strFileNameTestTimes)
test_dict_times, test_list_names_times = makeDict(instIds, test_times)
nAlgs = len(test_dict_times[test_list_names_times[0]])
nFeatures = len(test_dict_features[test_list_names_features[0]])
print()
print(' Basic Information on Data: ')
print(' --> Number of Algorithms :', nAlgs)
print(' --> Number of Features :', nFeatures)
print(' --> Number of Test-Feature-vectors :', len(test_dict_features))
print(' --> Number of Test-Time-vectors :', len(test_dict_times))
# print "---------------------------------------------------------------------"
X_test = []
Y_test = []
for idTestInstance in test_list_names_features:
X_test += [test_dict_features[idTestInstance]]
Y_test += [test_dict_times[idTestInstance]]
X_test = np.array(X_test)
Y_test = np.array(Y_test)
return X_test, Y_test
def parseData(strFileNameTrainFeatures, strFileNameTrainTimes):
# print "---------------------------------------------------------------------"
print ('Parsing Data')
print (' -> Reading Train Features :', strFileNameTrainFeatures)
instIds, train_features = readfile_data(strFileNameTrainFeatures)
train_dict_features, train_list_names_features = makeDict(instIds, train_features)
train_array_features = train_features
print (' -> Reading Train Times :', strFileNameTrainTimes)
instIds, train_times = readfile_data(strFileNameTrainTimes)
train_dict_times, train_list_names_times = makeDict(instIds, train_times)
train_array_features_orig = np.array(train_array_features)
nAlgs = len(train_dict_times[train_list_names_times[0]])
nFeatures = len(train_dict_features[train_list_names_features[1]])
print()
print ('Basic Information on Data: ')
print (' --> Number of Algorithms :', nAlgs)
print (' --> Number of Features :', nFeatures)
print (' --> Number of Train-Feature-vectors :', len(train_dict_features))
print (' --> Number of Train-Time-vectors :', len(train_dict_times))
# print "---------------------------------------------------------------------"
X_train = []
Y_train = []
for idTrainInstance in train_list_names_features:
X_train += [train_dict_features[idTrainInstance]]
Y_train += [train_dict_times[idTrainInstance]]
X_train = np.array(X_train)
Y_train = np.array(Y_train)
return X_train, Y_train
