# mapping from trial identifiers to corresponding input filenames trial_input_fnames = id2filenames(trial_dir, "input", trial_ids) # mapping from trial identifiers to corresponding gold standard filenames trial_gs_fnames = id2filenames(trial_dir, "gs", trial_ids) # mappings, ids and path for the 2014 test data test_dir = join(data_dir, "STS2014-test") test_ids = trial_ids test_input_fnames = id2filenames(test_dir, "input", test_ids) test_gs_fnames = id2filenames(test_dir, "gs", test_ids) # mapping from test dataset identifiers and feature names # to the corresponding feature files test_feat_fnames = map_id_to_feat_files(os.path.join(feat_dir, 'STS2014-test'), test_ids) def read_test_data(ids, features=[], convert_nan=True): """ Create feature vectors and labels for given dataset identifiers and features from STS13 test data """ return read_data(ids, test_feat_fnames, test_gs_fnames, features=features, convert_nan=convert_nan) def read_blind_test_data(ids, features=[], convert_nan=True):
define dirs, ids and filenames for STS13 test data """ import os from os.path import join from ntnu.io import read_data, map_id_to_feat_files, feat_dir from sts.io import data_dir, id2filenames # directory containing original STS 2103 test files test_dir = join(data_dir, "STS2013-test") # identifiers for different categories of test data test_ids = "FNWN", "headlines", "OnWN", "SMT" # mapping from test identifiers to corresponding input filenames test_input_fnames = id2filenames(test_dir, "input", test_ids) # mapping from test identifiers to corresponding gold standard filenames test_gs_fnames = id2filenames(test_dir, "gs", test_ids) test_feat_fnames = map_id_to_feat_files(os.path.join(feat_dir, 'STS2013-test'), test_ids) def read_test_data(ids, features=[], convert_nan=True): """ Create feature vectors and labels for given dataset identifiers and features from STS12 test data """ return read_data(ids, test_feat_fnames, test_gs_fnames, features=features, convert_nan=convert_nan )
""" define dirs and filenames of features for STS12 data """ from os.path import join from sts.sts12 import train_ids, test_ids, train_gs_fnames, test_gs_fnames from ntnu.io import feat_dir, read_data, map_id_to_feat_files # top directory containing train feature files train_dir = join(feat_dir, "STS2012-train") # mapping from train dataset identifiers and feature names # to the corresponding feature files train_feat_fnames = map_id_to_feat_files(train_dir, train_ids) def read_train_data(ids, features=[], convert_nan=True): """ Create feature vectors and labels for given dataset identifiers and features from STS12 train data """ return read_data(ids, train_feat_fnames, train_gs_fnames, features=features, convert_nan=convert_nan) # top directory containing test feature files
define dirs and filenames of features for STS14 data """ from os.path import join from sts.sts14 import trial_ids, trial_gs_fnames from ntnu.io import feat_dir, read_data, read_blind_data, map_id_to_feat_files # top directory containing trial feature files trial_dir = join(feat_dir, "STS2014-trial") # mapping from test dataset identifiers and feature names # to the corresponding feature files trial_feat_fnames = map_id_to_feat_files(trial_dir, trial_ids) def read_trial_data(ids, features=[], convert_nan=True): """ Create feature vectors and labels for given dataset identifiers and features from STS14 trial data """ return read_data(ids, trial_feat_fnames, trial_gs_fnames, features=features, convert_nan=convert_nan) def read_blind_trial_data(ids, features=[], convert_nan=True): return read_blind_data(ids, trial_feat_fnames, features=features, convert_nan=convert_nan )
""" from os.path import join from sts.sts12 import train_ids, test_ids, train_gs_fnames, test_gs_fnames from ntnu.io import feat_dir, read_data, map_id_to_feat_files # top directory containing train feature files train_dir = join(feat_dir, "STS2012-train") # mapping from train dataset identifiers and feature names # to the corresponding feature files train_feat_fnames = map_id_to_feat_files(train_dir, train_ids) def read_train_data(ids, features=[], convert_nan=True): """ Create feature vectors and labels for given dataset identifiers and features from STS12 train data """ return read_data(ids, train_feat_fnames, train_gs_fnames, features=features, convert_nan=convert_nan) # top directory containing test feature files test_dir = join(feat_dir, "STS2012-test") # mapping from test dataset identifiers and feature names
""" define dirs and filenames of features for STS14 data """ from os.path import join from sts.sts14 import trial_ids, trial_gs_fnames from ntnu.io import feat_dir, read_data, read_blind_data, map_id_to_feat_files # top directory containing trial feature files trial_dir = join(feat_dir, "STS2014-trial") # mapping from test dataset identifiers and feature names # to the corresponding feature files trial_feat_fnames = map_id_to_feat_files(trial_dir, trial_ids) def read_trial_data(ids, features=[], convert_nan=True): """ Create feature vectors and labels for given dataset identifiers and features from STS14 trial data """ return read_data(ids, trial_feat_fnames, trial_gs_fnames, features=features, convert_nan=convert_nan) def read_blind_trial_data(ids, features=[], convert_nan=True):
define dirs and filenames of features for STS13 data """ from os.path import join from sts.sts13 import test_ids, test_gs_fnames from ntnu.io import feat_dir, read_data, read_blind_data, map_id_to_feat_files # top directory containing test feature files test_dir = join(feat_dir, "STS2013-test") # mapping from test dataset identifiers and feature names # to the corresponding feature files test_feat_fnames = map_id_to_feat_files(test_dir, test_ids) def read_test_data(ids, features=[], convert_nan=True): """ Create feature vectors and labels for given dataset identifiers and features from STS13 test data """ return read_data(ids, test_feat_fnames, test_gs_fnames, features=features, convert_nan=convert_nan) def read_blind_test_data(ids, features=[], convert_nan=True): return read_blind_data(ids, test_feat_fnames, features=features, convert_nan=convert_nan )