diff --git a/sw/main.py b/sw/main.py
index 08079f7..da38090 100644
--- a/sw/main.py
+++ b/sw/main.py
@@ -33,34 +33,34 @@ def plot_results():
 
 
 def main():
-    # Path("sim_results").mkdir(parents=True, exist_ok=True)
-    #
-    # # used_code = "Hamming_7_4"
-    # # used_code = "Golay_24_12"
+    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 = [
-    #     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")
+    # used_code = "BCH_31_21"
+    # used_code = "BCH_63_16"
+
+    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, target_frame_errors=100)
+
+    df = pd.DataFrame({"SNR": SNRs})
+    df["BER_ML"] = BERs[0]
+    df["BER_prox_0_01"] = BERs[1]
+    df["BER_prox_0_05"] = BERs[2]
+    df["BER_prox_0_15"] = BERs[3]
+
+    df.to_csv(f"sim_results/{used_code}.csv")
 
     plot_results()