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

Changed test_decoder() to get n and k as arguments; Reimplemented test_decoders() in utility.simulations

Browse Source
This commit is contained in:
Andreas Tsouchlos 2022-11-10 11:21:39 +01:00
parent a6baad0201
commit df94fb33b6
1 changed files with 49 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

56
sw/utility/simulations.py
View File

@ -1,9 +1,9 @@
"""This file contains utility functions relating to tests and simulations of the decoders."""
import numpy as np
import typing
from tqdm import tqdm
from timeit import default_timer
from utility import noise
@ -18,7 +18,8 @@ def count_bit_errors(d: np.array, d_hat: np.array) -> int:
return np.sum(d != d_hat)
def test_decoder(x: np.array,
def test_decoder(n: int,
k: int,
decoder: typing.Any,
SNRs: typing.Sequence[float] = np.linspace(1, 7, 7),
target_frame_errors: int = 100,
@ -28,7 +29,8 @@ def test_decoder(x: np.array,
This function assumes the all-zeros assumption holds. Progress is printed to stdout.
:param x: Codeword to be sent (Element of [0, 1]^n)
:param n: Length of a codeword of the used code (n_cols of the H-matrix)
:param k: Length of a dataword of the used code (n_rows of the H-matrix)
:param decoder: Instance of the decoder to be tested
:param SNRs: List of SNRs for which the BER should be calculated
:param target_frame_errors: Number of frame errors after which to stop the simulation
@ -36,11 +38,13 @@ def test_decoder(x: np.array,
:return: Tuple of numpy arrays of the form (SNRs, BERs)
"""
x = np.zeros(n)
x_bpsk = 1 - 2 * x # Map x from [0, 1]^n to [-1, 1]^n
BERs = []
for SNR in tqdm(SNRs, desc="Calculating Bit-Error-Rates",
position=0,
for SNR in tqdm(SNRs,
desc=f"Calculating BERs for {decoder.__class__.__name__}",
position=1,
leave=False,
bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):
@ -48,8 +52,9 @@ def test_decoder(x: np.array,
total_bits = 0
total_frame_errors = 0
for n in tqdm(range(N_max), desc=f"Simulating for SNR = {SNR} dB",
position=1,
for n in tqdm(range(N_max),
desc=f"Simulating for SNR = {SNR} dB",
position=2,
leave=False,
bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):
@ -70,3 +75,40 @@ def test_decoder(x: np.array,
BERs.append(total_bit_errors / total_bits)
return np.array(SNRs), np.array(BERs)
def test_decoders(n: int,
k: int,
decoders: typing.List,
SNRs: typing.Sequence[float] = np.linspace(1, 7, 7),
target_frame_errors: int = 100,
N_max: int = 10000) \
-> typing.Tuple[np.array, np.array]:
"""Calculate the Bit Error Rate (BER) for a number of given decoders for a number of SNRs.
This function assumes the all-zeros assumption holds. Progress is printed to stdout.
:param n: Length of a codeword of the used code (n_cols of the H-matrix)
:param k: Length of a dataword of the used code (n_rows of the H-matrix)
:param decoders: List of decoder objects to be tested
:param SNRs: List of SNRs for which the BER should be calculated
:param target_frame_errors: Number of frame errors after which to stop the simulation
:param N_max: Maximum number of iterations to perform for each SNR
:return: Tuple of the form (SNRs, [BERs_1, BERs_2, ...]) where SNR and BERs_x are numpy arrays
"""
result_BERs = []
start_time = default_timer()
for decoder in tqdm(decoders,
desc="Calculating the answer to life, the universe and everything",
position=0,
leave=False,
bar_format="{l_bar}{bar}| {n_fmt}/{total_fmt}"):
_, BERs = test_decoder(n, k, decoder, SNRs, target_frame_errors, N_max)
result_BERs.append(BERs)
end_time = default_timer()
print(f"Elapsed time: {end_time - start_time:.2f}s")
return SNRs, result_BERs