plot-plot

main.py

@@ -1,5 +1,5 @@
 import argparse
-import config
+import sys
 
 def print_train_outcome(outcome, init_ep = 0):
     format_vars = { 'init_ep': init_ep,
@@ -67,6 +67,7 @@ if args.train:
             eval_outcomes = g.eval(init_ep = eps)
             print_eval_outcomes(eval_outcomes, init_ep = eps)
         eps += episode_count
+        sys.stdout.flush()
 elif args.eval:
     outcomes = g.eval()
     print_eval_outcomes(outcomes, init_ep = 0)

network.py

@@ -3,7 +3,6 @@ from cup import Cup
 import numpy as np
 from board import Board
 import os
-import config
     
 class Network:
     hidden_size = 40

plot.py

@@ -7,22 +7,28 @@ import matplotlib.ticker as mtick
 import matplotlib.dates as mdates
 from matplotlib.backends.backend_pdf import PdfPages
 headers = ['Phase', 'Method', 'Total episodes', 'Episodes', 'Sum', 'Mean']
-df = pd.read_csv(sys.stdin, sep=";", names=headers)
-
-print(df)
-
-x = df['Total episodes']
-y = df['Mean']
 
 fig, ax = plt.subplots(1, 1)
+
+plt.ion()
 plt.title('Mean over episodes')
 plt.xlabel('Episodes')
 plt.ylabel('Mean')
 plt.grid(True)
 
-plt.plot(x,y)
+#ax.set_xlim(left=0)
+ax.set_ylim([-2, 2])
+
 plt.show()
 
-pp = PdfPages(sys.argv[1])
+while True:
-pp.savefig()
+    #df = pd.read_csv(sys.stdin, sep=";", names=headers)
-pp.close()
+    df = pd.read_csv('log', sep=";", names=headers)
+
+    x = df['Total episodes']
+    y = df['Mean']
+    
+    plt.scatter(x, y, c=[[1,0.5,0]])
+    print("draw")
+    #fig.canvas.draw()
+    plt.pause(2)