def test_fast_ica():
"""Assert that the TPOT FastICA preprocessor outputs the input dataframe
when the number of training features is 0"""
tpot_obj = TPOT()
assert np.array_equal(tpot_obj._fast_ica(training_testing_data.ix[:, -3:], 1.0),
training_testing_data.ix[:, -3:])
def test_fast_ica():
"""Assert that the TPOT FastICA preprocessor outputs the input dataframe
when the number of training features is 0"""
tpot_obj = TPOT()
assert np.array_equal(tpot_obj._fast_ica(training_testing_data.ix[:, -3:], 1.0),
training_testing_data.ix[:, -3:])
def test_fast_ica_2():
"""Assert that FastICA returns the same object type as the input object type.
Also assert that the number of rows is identical between the input dataframe
and output dataframe.
"""
tpot_obj = TPOT()
input_df = training_testing_data
output_df = tpot_obj._fast_ica(input_df, 1.0)
assert type(input_df) == type(output_df)
(in_rows, in_cols) = input_df.shape
(out_rows, out_cols) = output_df.shape
assert in_rows == out_rows
def test_fast_ica_2():
"""Assert that FastICA returns the same object type as the input object type.
Also assert that the number of rows is identical between the input dataframe
and output dataframe.
"""
tpot_obj = TPOT()
input_df = training_testing_data
output_df = tpot_obj._fast_ica(input_df, 1.0)
assert type(input_df) == type(output_df)
(in_rows, in_cols) = input_df.shape
(out_rows, out_cols) = output_df.shape
assert in_rows == out_rows
