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)
