Added new alist file; Renamed files

sw/plot_heatmaps.py

@@ -32,7 +32,7 @@ def main():
     #     "sim_results/2d_dec_fails_w_log_k_lin_bch_31_11alist.csv",
     #     "sim_results/2d_dec_fails_w_log_k_lin_bch_31_26alist.csv",
     #     "sim_results/2d_dec_fails_w_log_k_lin_963965alist.csv",
-    #     "sim_results/2d_dec_fails_w_log_k_lin_2043486alist.csv",
+    #     "sim_results/2d_dec_fails_w_log_k_lin_20433486alist.csv",
     #     "sim_results/2d_dec_fails_w_log_k_lin_40833844alist.csv",
     # ]
 

sw/res/204.33.484.alist

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sw/sim_results/2d_dec_fails_BER_FER_DFR_2043486alist.csv

@@ -1,31 +0,0 @@
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sw/sim_results/2d_dec_fails_BER_FER_DFR_20455187alist.csv

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sw/sim_results/BER_FER_DFR_20433484alist.csv

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sw/sim_results/BER_FER_DFR_20433486alist.csv

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+8,0.23234512928677448,0.99800796812749,0.4995014955134596,0.15,2.5,502.0
+9,0.048497505511080174,0.9881656804733728,0.49702380952380953,0.01,2.5,507.0
+10,0.04989744124600195,0.8882978723404256,0.4704225352112676,0.05,2.0,564.0
+11,0.03527321781425748,0.9709302325581395,0.49262536873156343,0.01,3.0,516.0
+12,0.22164139093137256,0.978515625,0.4945705824284304,0.15,3.5,512.0
+13,0.23182993669908908,0.9862204724409449,0.4965312190287413,0.15,3.0,508.0
+14,0.03180314679063115,0.7613981762917933,0.4317789291882556,0.05,2.5,658.0
+15,0.01802387621715353,0.5680272108843537,0.361794500723589,0.05,3.0,882.0
+16,0.02512139071129397,0.947069943289225,0.48640776699029126,0.01,3.5,529.0
+17,0.21508051889957505,0.9524714828897338,0.4878286270691334,0.15,4.0,526.0
+18,0.21364457491249858,0.9616122840690979,0.49021526418786693,0.15,4.5,521.0
+19,0.0165879615371454,0.8743455497382199,0.4664804469273743,0.01,4.0,573.0
+20,0.010068495164182614,0.7511244377811095,0.4289383561643836,0.01,4.5,667.0
+21,0.008609724082869863,0.34575569358178054,0.2569230769230769,0.05,3.5,1449.0
+22,0.21323977488618848,0.9159049360146252,0.4780534351145038,0.15,5.0,547.0
+23,0.20020204027556968,0.8462837837837838,0.4583714547118024,0.15,5.5,592.0
+24,0.0057733016870870485,0.5463467829880043,0.3533145275035261,0.01,5.0,917.0
+25,0.004002959674435812,0.1890566037735849,0.15873015873015872,0.05,4.0,2650.0
+26,0.0028677176922642256,0.36095100864553314,0.2652196929592377,0.01,5.5,1388.0
+27,0.0014134971257579337,0.08048192771084338,0.07379854188364826,0.05,4.5,6225.0
+28,0.00014019607843137255,0.00885,0.008526670632559984,0.05,5.5,20000.0
+29,0.00046364251378946394,0.028477235264025465,0.027312434345109746,0.05,5.0,17593.0

sw/sim_results/BER_FER_DFR_20455187alist.csv

@@ -0,0 +1,31 @@
+,BER,FER,DFR,gamma,SNR,num_iter
+0,0.12672693828030215,1.0,0.5,0.01,1.0,501.0
+1,0.4496301514617823,1.0,0.5,0.15,2.0,501.0
+2,0.11118229470005823,0.9920792079207921,0.49801192842942343,0.05,1.5,505.0
+3,0.08747211459434073,1.0,0.5,0.01,2.0,501.0
+4,0.13200070447340612,1.0,0.5,0.05,1.0,501.0
+5,0.44625454972408124,1.0,0.5,0.15,1.0,501.0
+6,0.44436616962154124,1.0,0.5,0.15,1.5,501.0
+7,0.10764745019764393,1.0,0.5,0.01,1.5,501.0
+8,0.08641697596820755,0.9579349904397706,0.4892578125,0.05,2.0,523.0
+9,0.4383390082579938,1.0,0.5,0.15,2.5,501.0
+10,0.06696428571428571,0.9940476190476191,0.49850746268656715,0.01,2.5,504.0
+11,0.43306524206488983,1.0,0.5,0.15,3.0,501.0
+12,0.06321687888035357,0.8962432915921288,0.47264150943396227,0.05,2.5,559.0
+13,0.049638301922710834,0.9728155339805825,0.49311023622047245,0.01,3.0,515.0
+14,0.4251497005988024,1.0,0.5,0.15,3.5,501.0
+15,0.040927482103952695,0.7229437229437229,0.41959798994974873,0.05,3.0,693.0
+16,0.41951391334977106,1.0,0.5,0.15,4.0,501.0
+17,0.0338777979431337,0.9092558983666061,0.4762357414448669,0.01,3.5,551.0
+18,0.3925249941873983,0.9901185770750988,0.49751737835153925,0.15,4.5,506.0
+19,0.02079547266060896,0.8146341463414634,0.4489247311827957,0.01,4.0,615.0
+20,0.022373307775248593,0.5101832993890021,0.3378287255563048,0.05,3.5,982.0
+21,0.011007911936704506,0.6278195488721805,0.3856812933025404,0.01,4.5,798.0
+22,0.3600271791885071,0.9920792079207921,0.49801192842942343,0.15,5.0,505.0
+23,0.310473411154345,0.9747081712062257,0.4935960591133005,0.15,5.5,514.0
+24,0.0095717802539518,0.2758810572687225,0.21622788088044886,0.05,4.0,1816.0
+25,0.004614500121036069,0.38657407407407407,0.27879799666110183,0.01,5.0,1296.0
+26,0.0032538300058064227,0.11412300683371299,0.10243304027806174,0.05,4.5,4390.0
+27,0.001913352466858002,0.2054120541205412,0.1704081632653061,0.01,5.5,2439.0
+28,0.00015980392156862746,0.0085,0.00842835894893406,0.05,5.5,10000.0
+29,0.0008588235294117647,0.0355,0.034282955094157415,0.05,5.0,10000.0

sw/simulate_2d_dec_fails.py

@@ -75,7 +75,7 @@ def main():
     sim_name = "w_log_k_lin_zoomed_in"
 
     # H_file = "96.3.965.alist"
-    # H_file = "204.3.486.alist"
+    # H_file = "204.33.486.alist"
     # H_file = "408.33.844.alist"
     H_file = "BCH_31_26.alist"
     SNR = 3

sw/simulate_BER_curve.py

@@ -10,7 +10,7 @@ from utility import codes, noise, misc
 from utility.simulation.simulators import GenericMultithreadedSimulator
 
 # from cpp_modules.cpp_decoders import ProximalDecoder
-from cpp_modules.cpp_decoders import ProximalDecoder_7_3 as ProximalDecoder
+from cpp_modules.cpp_decoders import ProximalDecoder_204_102 as ProximalDecoder
 
 
 def count_bit_errors(d: np.array, d_hat: np.array) -> int:
@@ -44,7 +44,7 @@ def task_func(params):
         if k_max == -1:
             dec_fails += 1
 
-        if total_frame_errors > 4000:
+        if total_frame_errors > 500:
             break
 
     BER = total_bit_errors / (num_iterations * n)
@@ -106,15 +106,16 @@ def main():
     sim_name = "BER_FER_DFR"
 
     # H_file = "96.3.965.alist"
-    # H_file = "204.3.486.alist"
+    H_file = "204.33.486.alist"
+    # H_file = "204.33.484.alist"
     # H_file = "204.55.187.alist"
     # H_file = "408.33.844.alist"
-    H_file = "BCH_7_4.alist"
+    # H_file = "BCH_7_4.alist"
     # H_file = "BCH_31_11.alist"
     # H_file = "BCH_31_26.alist"
     SNRs = np.arange(1, 6, 0.5)
 
-    max_iterations = 10000
+    max_iterations = 20000
     # omega = 0.005
     # K = 60
     omega = 0.05
@@ -132,7 +133,7 @@ def main():
     df = reformat_data(results, SNRs, gammas)
 
     df.to_csv(
-        f"sim_results/2d_dec_fails_{sim_name}_{misc.slugify(H_file)}.csv")
+        f"sim_results/{sim_name}_{misc.slugify(H_file)}.csv")
 
     sns.set_theme()
     ax = sns.lineplot(data=df, x="SNR", y="BER", hue="gamma")