def test_gev_falls_back_to_pca_for_unity_noise_matrix(self): Phi_XX = hermitian(6, 6) Phi_NN = np.identity(6) W_gev = get_gev_vector(Phi_XX, Phi_NN) W_pca = get_pca_vector(Phi_XX) tc.assert_allclose(cos_similarity(W_gev, W_pca), 1.0, atol=1e-6)
def _w_gev(self): w_gev = beamformer.get_gev_vector(self._Cov_X, self._Cov_N, force_cython=True) if self.debug: print('w_gev', repr(w_gev)) return w_gev
def test_result_equal(self): import time F = 513 phi_XX = pos_def_hermitian(F, 6, 6) phi_NN = pos_def_hermitian(F, 6, 6) t = time.time() python_gev = _get_gev_vector(phi_XX, phi_NN) elapsed_time_python = time.time() - t t = time.time() cython_gev = get_gev_vector(phi_XX, phi_NN, True) elapsed_time_cython1 = time.time() - t tc.assert_allclose(cos_similarity(python_gev, cython_gev), 1.0, atol=1e-6) # assume speedup is bigger than 4 assert elapsed_time_python / elapsed_time_cython1 > 4
def test_gev_ban_dimensions(self): output = blind_analytic_normalization( get_gev_vector(pos_def_hermitian(self.shape_psd), pos_def_hermitian(self.shape_psd)), pos_def_hermitian(self.shape_psd)) tc.assert_equal(output.shape, self.shape_vector)
def test_gev_dimensions(self): output = get_gev_vector(pos_def_hermitian(self.shape_psd), pos_def_hermitian(self.shape_psd)) tc.assert_equal(output.shape, self.shape_vector)