test_data.py 文件源码

def test_standard_scaler_trasform_with_partial_fit():
    # Check some postconditions after applying partial_fit and transform
    X = X_2d[:100, :]

    scaler_incr = StandardScaler()
    for i, batch in enumerate(gen_batches(X.shape[0], 1)):

        X_sofar = X[:(i + 1), :]
        chunks_copy = X_sofar.copy()
        scaled_batch = StandardScaler().fit_transform(X_sofar)

        scaler_incr = scaler_incr.partial_fit(X[batch])
        scaled_incr = scaler_incr.transform(X_sofar)

        assert_array_almost_equal(scaled_batch, scaled_incr)
        assert_array_almost_equal(X_sofar, chunks_copy)  # No change
        right_input = scaler_incr.inverse_transform(scaled_incr)
        assert_array_almost_equal(X_sofar, right_input)

        zero = np.zeros(X.shape[1])
        epsilon = np.nextafter(0, 1)
        assert_array_less(zero, scaler_incr.var_ + epsilon)  # as less or equal
        assert_array_less(zero, scaler_incr.scale_ + epsilon)
        # (i+1) because the Scaler has been already fitted
        assert_equal((i + 1), scaler_incr.n_samples_seen_)