decrease verbosity
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@ -37,7 +37,7 @@ class AoA:
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H_sm_rows = [np.hstack(H_n[i : i + N // 2 + 1]) for i in range(N // 2)]
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H_sm = np.vstack(H_sm_rows)
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logger.info(f"Smoothed: {H_sm.shape}")
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logger.debug(f"Smoothed: {H_sm.shape}")
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return H_sm
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@ -65,7 +65,6 @@ class AoA:
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# The smallest eigenvectors span the noise subspace,
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# and the largest span the signal subspace.
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eigvals, eigvecs = np.linalg.eigh(R)
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print(eigvals)
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self.E_n = eigvecs[:, np.abs(eigvals) < config.EIGVAL_THRESHOLD]
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omega_base = np.exp(-2j * np.pi * config.DELTA_F)
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