gradetable py3 ready

projects/README

@@ -1,3 +1,9 @@
+All projects:
+
+check for time information
+
+
+
 project_adaptation_fit
 OK, medium
 Add plotting of cost function

projects/gradetable.py

@@ -1,11 +1,5 @@
-import os
-import numpy as np
-import matplotlib.pylab as plt
-
-lecture = 'Models of Neural Systems, WS 16/17'
-exam = 1
-pmax = 33   # maximum available points
-p100 = 28   # points for 100%
+if __name__ == "__main__":
+    p100 = 33.0   # points for 100%
 
     # grades:
     gradestable = [ [ 0.9, 1.0 ], [ 0.84, 1.3 ], [ 0.80, 1.7 ], [ 0.76, 2.0 ], [ 0.72, 2.3 ],
@@ -13,14 +7,14 @@ gradestable = [ [ 0.9, 1.0 ], [ 0.84, 1.3 ], [ 0.80, 1.7 ], [ 0.76, 2.0 ], [ 0.7
 
     df = open('notentabelle.dat', 'w')
     df.write('# Notentabelle\n')
-print '# Notentabelle'
+    print('# Notentabelle')
     df.write('\n')
     df.write('#Key\n')
     s = '# Note\tProzent\tPunkte'
     df.write(s+'\n')
-print s
+    print(s)
     for f,g in gradestable :
-    s = '  \t%3.1f\t%5.0f\t%5.1f' % (g, 100.0*f, p100*f)
+        s = '  \t%3.1f\t%5.0f\t%5.0f' % (g, 100.0*f, p100*f)
         df.write(s+'\n')
-    print s
+        print(s)
     df.close()