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Made the way simulations are done and plotted more scalable

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Andreas Tsouchlos 2022-11-07 12:10:06 +01:00
parent cc855b8941
commit 0ea297ad45
1 changed files with 25 additions and 11 deletions
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36
sw/main.py
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@ -21,30 +21,44 @@ def main():
[0, 1, 1, 0, 0, 1, 1],
[0, 0, 0, 1, 1, 1, 1]])
# Define encoder and decoders
encoder = channel.Encoder(G)
proximal_decoder = proximal.ProximalDecoder(H, K=100, gamma=0.01)
soft_decision_decoder = naive_soft_decision.SoftDecisionDecoder(G, H)
decoders = {"naive_soft_decision": naive_soft_decision.SoftDecisionDecoder(G, H),
# "proximal": proximal.ProximalDecoder(H, K=100, gamma=0.01),
}
# Test decoder
# Test decoders
k, n = G.shape
d = np.zeros(k) # All-zeros assumption
SNRs_sd, BERs_sd = utility.test_decoder(encoder=encoder,
decoder=soft_decision_decoder,
d=d,
SNRs=np.linspace(1, 7, 9),
target_bit_errors=500)
SNRs = np.linspace(1, 7, 9)
data = pd.DataFrame({"SNR": SNRs})
data = pd.DataFrame({"SNR": SNRs_sd, "BER_sd": BERs_sd})
for decoder_name in decoders:
decoder = decoders[decoder_name]
_, BERs_sd = utility.test_decoder(encoder=encoder,
decoder=decoder,
d=d,
SNRs=SNRs)
data[f"BER_{decoder_name}"] = BERs_sd
# Plot results
ax = sns.lineplot(data=data, x="SNR", y="BER_sd")
fig, axes = plt.subplots(1, 1)
fig.suptitle("Bit-Error-Rates of various decoders")
for decoder_name in decoders:
ax = sns.lineplot(data=data, x="SNR", y=f"BER_{decoder_name}", label=f"{decoder_name}")
ax.set_title("Hamming(7,4) Code")
ax.set(yscale="log")
ax.set_yticks([10e-5, 10e-4, 10e-3, 10e-2, 10e-1, 10e0])
# ax.set_ylim([10e-6, 10e0])
ax.legend()
plt.show()