Example #1
0
def cross_correlation_signals(signal):
    length = signal.shape[1]
    L = length
    max_lag = L - 1
    out = np.zeros((signal.shape[0] ** 2, 2 * L - 1), dtype=np.complex128)
    for lag in range(max_lag + 1):  # non-negative lags
        all_lags = np.dot(signal[:, lag:length], sc.hermitian(signal[:, : (length - lag)]))
        all_lags = all_lags.ravel(order="F") / float(length - lag)
        out[:, lag + max_lag] = all_lags
    for lag in range(max_lag + 1):  # non-positive lags
        all_lags = np.dot(signal[:, : length - lag], sc.hermitian(signal[:, lag:length]))
        all_lags = all_lags.ravel(order="F") / float(length - lag)
        out[:, max_lag - lag] = all_lags
    return out
Example #2
0
def cross_correlation_signals(signal):
    length = signal.shape[1]
    L = length
    max_lag = L - 1
    out = np.zeros((signal.shape[0]**2, 2 * L - 1), dtype=np.complex128)
    for lag in range(max_lag + 1):  # non-negative lags
        all_lags = np.dot(signal[:, lag:length],
                          sc.hermitian(signal[:, :(length - lag)]))
        all_lags = all_lags.ravel(order='F') / float(length - lag)
        out[:, lag + max_lag] = all_lags
    for lag in range(max_lag + 1):  # non-positive lags
        all_lags = np.dot(signal[:, :length - lag],
                          sc.hermitian(signal[:, lag:length]))
        all_lags = all_lags.ravel(order='F') / float(length - lag)
        out[:, max_lag - lag] = all_lags
    return out
Example #3
0
 def test_generate_csx(self):
     Cry = self.ref['Cry']
     R_pinv = self.ref['R_inv']
     R_pinv_h = sc.hermitian(R_pinv)
     Csx = self.detect.generate_Csx(Cry, R_pinv, R_pinv_h)
     Csx_ref = self.ref['Csx']
     np.testing.assert_array_almost_equal(Csx, Csx_ref)
Example #4
0
 def test_hermitian(self):
     matrix = np.array([[1 + 1j, 0 + 5j], [2 - 3j, 4 + 1j]])
     matrix_ref = np.array([[1 - 1j, 2 + 3j], [0 - 5j, 4 - 1j]])
     matrix_H = sc.hermitian(matrix)
     np.testing.assert_array_equal(matrix_H, matrix_ref)
 def test_hermitian(self):
     matrix = np.array([[1 + 1j, 0 + 5j], [2 - 3j, 4 + 1j]])
     matrix_ref = np.array([[1 - 1j, 2 + 3j], [0 - 5j, 4 - 1j]])
     matrix_H = sc.hermitian(matrix)
     np.testing.assert_array_equal(matrix_H, matrix_ref)