Removed confusion relating to n and k
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@ -238,7 +238,7 @@ def get_systematic_H(G: np.array) -> np.array:
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P = G[:, k:]
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H = np.zeros(shape=(n - k, k + n - k))
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H = np.zeros(shape=(n - k, n))
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H[:, :k] = P.T
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H[:, k:] = np.identity(n - k)
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@ -29,8 +29,8 @@ def test_decoder(n: int,
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This function assumes the all-zeros assumption holds. Progress is printed to stdout.
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:param n: Length of a codeword of the used code (n_cols of the H-matrix)
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:param k: Length of a dataword of the used code (n_rows of the H-matrix)
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:param n: Length of a codeword of the used code
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:param k: Length of a dataword of the used code
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:param decoder: Instance of the decoder to be tested
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:param SNRs: List of SNRs for which the BER should be calculated
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:param target_frame_errors: Number of frame errors after which to stop the simulation
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@ -88,8 +88,8 @@ def test_decoders(n: int,
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This function assumes the all-zeros assumption holds. Progress is printed to stdout.
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:param n: Length of a codeword of the used code (n_cols of the H-matrix)
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:param k: Length of a dataword of the used code (n_rows of the H-matrix)
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:param n: Length of a codeword of the used code
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:param k: Length of a dataword of the used code
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:param decoders: List of decoder objects to be tested
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:param SNRs: List of SNRs for which the BER should be calculated
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:param target_frame_errors: Number of frame errors after which to stop the simulation
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