def test_max_freq_filter(self): X = np.array([[1.0, 0.0, 0.0], [0.0, 0.0, 0.0], [1.0, 9.0, 0.0], [1.0, 9.0, 0.0], [1.0, 9.0, 0.0], [0.0, 0.0, 0.0]]) max_freq = 0.5 filt = MaxFreqFilter(max_freq=max_freq) Xt = filt.fit_transform(X) # expected X Xe = X[:,1:] assert_array_equal(Xt, Xe)
def test_max_freq_filter_sparse(self): X = sp.csr_matrix([[1.0, 0.0, 0.0], [0.0, 0.0, 0.0], [1.0, 9.0, 0.0], [1.0, 9.0, 0.0], [1.0, 9.0, 0.0], [0.0, 0.0, 0.0]]) filt = MaxFreqFilter(max_freq=0.5) Xt = filt.fit_transform(X) # expected X Xe = X[:,1:] assert Xt.shape == (6,2) # __eq__ is not properly implemented for sparse matrices # so apply this trick assert (Xt - Xe).nnz == 0