Changed the way the codewords are mapped onto [0, 1]^n
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@ -79,10 +79,9 @@ class ProximalDecoder:
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def _check_parity(self, y_hat: np.array) -> bool:
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def _check_parity(self, y_hat: np.array) -> bool:
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"""Perform a parity check for a given codeword.
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"""Perform a parity check for a given codeword.
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:param y_hat: codeword to be checked (element of [-1, 1]^n)
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:param y_hat: codeword to be checked (element of [0, 1]^n)
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:return: True if the parity check passes, i.e. the codeword is valid. False otherwise
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:return: True if the parity check passes, i.e. the codeword is valid. False otherwise
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"""
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"""
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y_hat_binary = (y_hat == 1) * 1 # Map the codeword from [-1, 1]^n to [0, 1]^n
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syndrome = np.dot(self._H, y_hat) % 2
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syndrome = np.dot(self._H, y_hat) % 2
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return not np.any(syndrome)
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return not np.any(syndrome)
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@ -96,15 +95,16 @@ class ProximalDecoder:
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and 'w' is noise)
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and 'w' is noise)
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:return: Most probably sent dataword (element of [0, 1]^k)
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:return: Most probably sent dataword (element of [0, 1]^k)
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"""
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"""
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s = 0
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s = np.zeros(y.size)
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x_hat = 0
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x_hat = np.zeros(y.size)
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for k in range(self._K):
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for k in range(self._K):
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r = s - self._step_size * self._L_awgn(s, y)
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r = s - self._step_size * self._L_awgn(s, y)
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s = r - self._gamma * self._grad_h(r)
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s = r - self._gamma * self._grad_h(r)
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s = self._projection(s) # Equation (15)
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s = self._projection(s) # Equation (15)
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x_hat = (np.sign(s) == 1) * 1
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x_hat = np.sign(s)
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x_hat = (x_hat == 1) * 1 # Map the codeword from [-1, 1]^n to [0, 1]^n
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if self._check_parity(x_hat):
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if self._check_parity(x_hat):
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break
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break
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