neuer Plot Vergleich_Optimizer

TicTacToe/Vergleich_Optimizer/plot.py

@@ -7,14 +7,14 @@ condition_adam_32 = np.load("results/condition_2norm_adam_batch32.npy")
 loss_adam_32 = np.load("results/MSE_loss_adam_batch32.npy")
 condition_sgd_32 = np.load("results/condition_2norm_sgd_batch32.npy")
 loss_sgd_32 = np.load("results/MSE_loss_sgd_batch32.npy")
-condition_sgd_10 = np.load("results/condition_2norm_sgd_batch10.npy")
-loss_sgd_10 = np.load("results/MSE_loss_sgd_batch10.npy")
+#condition_sgd_10 = np.load("results/condition_2norm_sgd_batch10.npy")
+#loss_sgd_10 = np.load("results/MSE_loss_sgd_batch10.npy")
 
 # Konditions-Plot
 fig = plt.figure(figsize = (10, 7))
 plt.semilogy(condition_adam_32, label="Adam Batch=32")
 plt.semilogy(condition_sgd_32, label="SGD Batch=32")
-plt.semilogy(condition_sgd_10, label="SGD Batch=10")
+#plt.semilogy(condition_sgd_10, label="SGD Batch=10")
 plt.legend()
 plt.xlabel("n")
 plt.ylabel("Kondition der Hesse-Matrix")
@@ -24,7 +24,7 @@ plt.show()
 fig = plt.figure(figsize = (10, 7))
 plt.semilogy(loss_adam_32, label="Adam Batch=32")
 plt.semilogy(loss_sgd_32, label="SGD Batch=32")
-plt.semilogy(loss_sgd_10, label="SGD Batch=10")
+#plt.semilogy(loss_sgd_10, label="SGD Batch=10")
 plt.legend()
 plt.xlabel("n")
 plt.ylabel("Loss nach 10.000 Epochen")