an.tsouchlos/ba-thesis
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases 1 Wiki Activity

Moved calculation of A and B sets from ProximalDecoder::_grad_h() to ProximalDecoder::__init__()

Browse Source
This commit is contained in:
Andreas Tsouchlos 2022-11-07 14:38:30 +01:00
parent 296feaf1fb
commit d129a222bc
1 changed files with 13 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

23
sw/decoders/proximal.py
View File

@ -27,6 +27,17 @@ class ProximalDecoder:
self._gamma = gamma self._gamma = gamma
self._eta = eta self._eta = eta
self._A = []
self._B = []
for row in self._H:
A_k = np.argwhere(row == 1)
self._A.append(A_k[:, 0])
for column in self._H.T:
B_k = np.argwhere(column == 1)
self._B.append(B_k[:, 0])
@staticmethod @staticmethod
def _L_awgn(s: np.array, y: np.array) -> np.array: def _L_awgn(s: np.array, y: np.array) -> np.array:
"""Variation of the negative log-likelihood for the special case of AWGN noise. """Variation of the negative log-likelihood for the special case of AWGN noise.
@ -44,19 +55,11 @@ class ProximalDecoder:
# Calculate second term # Calculate second term
for k, x_k in enumerate(x): for k, x_k in enumerate(x):
# TODO: Perform this operation for each row simultaneously
B_k = np.argwhere(self._H[:, k] == 1)
B_k = B_k[:, 0] # Get rid of one layer of arrays
# TODO: Perform the summation with np.sum() # TODO: Perform the summation with np.sum()
sum_result = 0 sum_result = 0
for i in B_k: for i in self._B[k]:
# TODO: Perform this operation for each column simultaneously
A_i = np.argwhere(self._H[i] == 1)
A_i = A_i[:, 0] # Get rid of one layer of arrays
prod = 1 prod = 1
for j in A_i: for j in self._A[i]:
prod *= x[j] prod *= x[j]
sum_result += prod**2 - prod sum_result += prod**2 - prod