Removed references to the R-Matrix; Comment changes

This commit is contained in:
Andreas Tsouchlos 2022-11-10 08:37:13 +01:00
parent 3a178f2d35
commit 5865a8683f
5 changed files with 3 additions and 44 deletions

View File

@ -10,13 +10,11 @@ class SoftDecisionDecoder:
one with the largest correlation.
"""
# TODO: Is 'R' actually called 'decoding matrix'?
def __init__(self, G: np.array, H: np.array):
"""Construct a new SoftDecisionDecoder object.
:param G: Generator matrix
:param H: Parity check matrix
:param R: Decoding matrix
"""
self._G = G
self._H = H

View File

@ -7,13 +7,11 @@ class ProximalDecoder:
by Tadashi Wadayama, and Satoshi Takabe.
"""
# TODO: Is 'R' actually called 'decoding matrix'?
def __init__(self, H: np.array, K: int = 100, step_size: float = 0.1,
gamma: float = 0.05, eta: float = 1.5):
"""Construct a new ProximalDecoder Object.
:param H: Parity Check Matrix
:param R: Decoding matrix
:param K: Max number of iterations to perform when decoding
:param step_size: Step size for the gradient descent process
:param gamma: Positive constant. Arises in the approximation of the prior PDF
@ -54,7 +52,7 @@ class ProximalDecoder:
"""Project a vector onto [-eta, eta]^n in order to avoid numerical instability.
Detailed in 3.2, p. 3 (Equation (15)).
:param x:
:param x: Vector to project
:return: x clipped to [-eta, eta]^n
"""
return np.clip(x, -self._eta, self._eta)

View File

@ -22,7 +22,7 @@ class CountBitErrorsTestCase(unittest.TestCase):
self.assertEqual(simulations.count_bit_errors(d3, y_hat3), 4)
# TODO: Is this correct?
# TODO: Rewrite tests for new SNR calculation
class NoiseAmpFromSNRTestCase(unittest.TestCase):
"""Test case for noise amplitude calculation."""

View File

@ -172,6 +172,7 @@ Gs = {'Hamming_7_4': np.array([[1, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1]]),
# TODO: Fix this. This code should be systematic
'BCH_63_45': np.array([[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1],
[0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0],
@ -244,15 +245,3 @@ def get_systematic_H(G: np.array) -> np.array:
H[:, n:] = np.identity(k-n)
return H
def get_systematic_R(G: np.array) -> np.array:
n, k = G.shape
I = G[:, :n]
assert np.array_equal(I, np.identity(n))
R = np.zeros(shape=G.shape)
R[:, :n] = np.identity(n)
return R

View File

@ -1,26 +0,0 @@
import numpy as np
# TODO: Unify the interface regarding [0, 1]^n and [-1, 1]^n
# TODO: Should the encoder be responsible for mapping the message from [0, 1]^n to [-1, 1]^n?
# (ie. should the encoder perform modulation?)
class Encoder:
"""Class implementing an encoder for block codes.
"""
def __init__(self, G: np.array):
"""Construct a new Encoder object.
:param G: Generator matrix
"""
self._G = G
def encode(self, d: np.array) -> np.array:
"""Map a given dataword onto the corresponding codeword.
The returned codeword is mapped from [0, 1]^n onto [-1, 1]^n.
:param d: Dataword (element of [0, 1]^n)
:return: Codeword (already element of [-1, 1]^n)
"""
# TODO: (0 -> 1), (1 -> -1); Not (0 -> -1), (-1 -> 1)
return np.dot(d, self._G) * 2 - 1