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Rewrote main to use SimulationManger

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This commit is contained in:
Andreas Tsouchlos 2022-11-16 19:49:37 +01:00
parent e9faba01d2
commit 5d14b383af
1 changed files with 43 additions and 32 deletions
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73
sw/main.py
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@ -2,14 +2,12 @@ import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import typing
from pathlib import Path
import os
from itertools import chain
from timeit import default_timer
import sys
from decoders import proximal, maximum_likelihood
from utility import simulations, codes, visualization
from utility import simulation, codes, visualization
# TODO: Fix spacing between axes and margins
@ -33,34 +31,47 @@ def plot_results():
def main():
# Path("sim_results").mkdir(parents=True, exist_ok=True)
#
# # used_code = "Hamming_7_4"
# # used_code = "Golay_24_12"
# used_code = "BCH_31_16"
# # used_code = "BCH_31_21"
# # used_code = "BCH_63_16"
#
# G = codes.Gs[used_code]
# H = codes.get_systematic_H(G)
#
# decoders = [
Path("sim_results").mkdir(parents=True, exist_ok=True)
sys.setrecursionlimit(10 * sys.getrecursionlimit())
sim_mgr = simulation.SimulationManager(results_dir="sim_results", save_dir="sim_saves")
if sim_mgr.unfinished_simulation_present():
print("Found unfinished simulation. Picking up where it was left of")
sim_mgr.load_unfinished()
sim_mgr.start()
else:
print("No unfinished simulation present. Starting a new one")
used_code = "Golay_24_12"
G = codes.Gs[used_code]
H = codes.get_systematic_H(G)
decoders = [
# maximum_likelihood.MLDecoder(G, H),
# proximal.ProximalDecoder(H, gamma=0.01),
# proximal.ProximalDecoder(H, gamma=0.05),
# proximal.ProximalDecoder(H, gamma=0.15)
# ]
#
# k, n = G.shape
# SNRs, BERs = simulations.test_decoders(n, k, decoders, N_max=30000, target_frame_errors=100)
#
# df = pd.DataFrame({"SNR": SNRs})
# df["BER_ML"] = BERs[0]
# df["BER_prox_0_01"] = BERs[0]
# df["BER_prox_0_05"] = BERs[1]
# df["BER_prox_0_15"] = BERs[2]
#
# df.to_csv(f"sim_results/{used_code}.csv")
proximal.ProximalDecoder(H, gamma=0.01),
proximal.ProximalDecoder(H, gamma=0.05),
proximal.ProximalDecoder(H, gamma=0.15)
]
k, n = G.shape
sim = simulation.Simulator(n=n, k=k, decoders=decoders, SNRs=np.arange(1, 6, 0.5), target_frame_errors=100)
sim_mgr.set_simulator(sim)
sim_mgr.start()
SNRs, BERs = sim_mgr.get_current_results()
df = pd.DataFrame({"SNR": SNRs})
# df["ML"] = BERs[0]
df["prox_0_01"] = BERs[0]
df["prox_0_05"] = BERs[1]
df["prox_0_15"] = BERs[2]
df.to_csv(f"sim_results/golay.csv")
plot_results()