Esempio n. 1
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 def test_A(self):
     """Test if A_est is elementwise almost equal A."""
     W, A_est, d = calculate_spoc(self.epo)
     # A and A_est can have a different scaling, after normalizing
     # and correcting for sign, the first pattern should be almost
     # equal the source pattern
     idx = np.argmax(np.abs(A_est[:, 0]))
     A_est[:, 0] /= A_est[idx, 0]
     idx = np.argmax(np.abs(self.A[:, 0]))
     self.A[:, 0] /= self.A[idx, 0]
     # check elementwise if A[:, 0] almost A_est[:, 0]
     epsilon = 0.01
     diff = self.A[:, 0] - A_est[:, 0]
     diff = np.abs(diff)
     diff = np.sum(diff) / self.A.shape[0]
     self.assertTrue(diff < epsilon)
 def test_A(self):
     """Test if A_est is elementwise almost equal A."""
     W, A_est, d = calculate_spoc(self.epo)
     # A and A_est can have a different scaling, after normalizing
     # and correcting for sign, the first pattern should be almost
     # equal the source pattern
     idx = np.argmax(np.abs(A_est[:, 0]))
     A_est[:, 0] /= A_est[idx, 0]
     idx = np.argmax(np.abs(self.A[:, 0]))
     self.A[:, 0] /= self.A[idx, 0]
     # check elementwise if A[:, 0] almost A_est[:, 0]
     epsilon = 0.01
     diff = self.A[:, 0] - A_est[:, 0]
     diff = np.abs(diff)
     diff = np.sum(diff) / self.A.shape[0]
     self.assertTrue(diff < epsilon)
Esempio n. 3
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    def test_s(self):
        """Test if s_est is elementwise almost equal s."""
        W, A_est, d = calculate_spoc(self.epo)
        # applying the filter to X gives us s_est which should be almost
        # equal s
        s_est = np.empty(self.s.shape[:2])
        for i in range(self.EPOCHS):
            s_est[i] = np.dot(self.X[i], W[:, 0])
        s_true = self.s[..., 0]
        epsilon = 0.001

        # correct for scale
        s_true /= s_true.std()
        s_est /= s_est.std()

        # correct for sign
        s_true = np.abs(s_true)
        s_est = np.abs(s_est)

        diff = np.sum(s_true - s_est) / (self.s.shape[0] * self.s.shape[1])
        self.assertTrue(diff < epsilon)
    def test_s(self):
        """Test if s_est is elementwise almost equal s."""
        W, A_est, d = calculate_spoc(self.epo)
        # applying the filter to X gives us s_est which should be almost
        # equal s
        s_est = np.empty(self.s.shape[:2])
        for i in range(self.EPOCHS):
            s_est[i] = np.dot(self.X[i], W[:, 0])
        s_true = self.s[..., 0]
        epsilon = 0.001

        # correct for scale
        s_true /= s_true.std()
        s_est /= s_est.std()

        # correct for sign
        s_true = np.abs(s_true)
        s_est = np.abs(s_est)

        diff = np.sum(s_true - s_est) / (self.s.shape[0] * self.s.shape[1])
        self.assertTrue(diff < epsilon)
Esempio n. 5
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 def test_calculate_signed_r_square_copy(self):
     """caluclate_r_square must not modify argument."""
     cpy = self.epo.copy()
     calculate_spoc(self.epo)
     self.assertEqual(self.epo, cpy)
Esempio n. 6
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 def test_d(self):
     """Test if the list of lambdas is reverse-sorted and the first one > 0."""
     W, A_est, d = calculate_spoc(self.epo)
     self.assertTrue(d[0] > 0)
     self.assertTrue(np.all(d == np.sort(d)[::-1]))
 def test_d(self):
     """Test if the list of lambdas is reverse-sorted and the first one > 0."""
     W, A_est, d = calculate_spoc(self.epo)
     self.assertTrue(d[0] > 0)
     self.assertTrue(np.all(d == np.sort(d)[::-1]))
 def test_calculate_signed_r_square_copy(self):
     """caluclate_r_square must not modify argument."""
     cpy = self.epo.copy()
     calculate_spoc(self.epo)
     self.assertEqual(self.epo, cpy)