def setUp(self): # Data paths file_noecho = './test_data/frame_no_echo.nc' file_v_zero = './test_data/frame_v_zero.nc' file_faulty = './test_data/frame_with_faulty_excitation.nc' file_noexci = './test_data/frame_with_no_excitation.nc' # Data loading self.frame_noecho = utilities.load_data_from_file(file_noecho) self.frame_v_zero = utilities.load_data_from_file(file_v_zero) self.frame_faulty = utilities.load_data_from_file(file_faulty) self.frame_noexci = utilities.load_data_from_file(file_noexci)
def test_load_data_from_file(self):
self.assertEqual(type(utilities.load_data_from_file(self.file_noecho)),
np.ndarray)
self.assertNotEqual(type(self.echoes_noecho), dict)
self.assertRaises(IOError, utilities.load_data_from_file,
'non_existent_file.nc')
from rebuild_operation import Rebuild_Operator
import utilities
import time
if __name__ == '__main__':
#should test with high padding mode to see the effectiveness
#only for rebuild mode
rebuild_mode = False
alpha = 256
client_state_folder = "tmp"
#select cluster to rebuild and all their corresponding keywords
key_folder = "data" + str(alpha)
fixed_clusters_keywords = utilities.load_data_from_file(
key_folder, "fixed_clusters_keywords")
prob_clusters = utilities.load_data_from_file(key_folder, "prob_clusters")
largest_cluster_index = prob_clusters.index(max(prob_clusters))
query_keywords = fixed_clusters_keywords[largest_cluster_index]
rebuild_operator = Rebuild_Operator(query_keywords, client_state_folder)
rebuild_operator.start()
rebuild_operator.join()
rebuild_operator.terminate()
time.sleep(10)
def test_load_data_from_file(self):
self.assertEqual(type(utilities.load_data_from_file(self.file_noecho)),
np.ndarray)
self.assertNotEqual(type(self.echoes_noecho), dict)
self.assertRaises(IOError, utilities.load_data_from_file,
'non_existent_file.nc')
