upload

@@ -37,6 +37,10 @@ __author__ = 'egaytan'
 def savescreen(output, dic, path):
 def savescreen(output, dic, path):
   if output:
   if output:
       DF.from_dict(dic).to_csv(path+'.csv', sep = "\t", index = True)
       DF.from_dict(dic).to_csv(path+'.csv', sep = "\t", index = True)
+def plotMax(yvalues, size):
+    scorelist = list(yvalues)
+    maxscore = max(scorelist)
+    plt.plot(scorelist.index(maxscore), maxscore, markersize=size)
 
 
 ####################################################################################
 ####################################################################################
 #                                   MAIN PROGRAM                                  #
 #                                   MAIN PROGRAM                                  #
@@ -89,13 +93,15 @@ if __name__ == '__main__':
     plt.ylabel("score")
     plt.ylabel("score")
     plt.rcParams.update()
     plt.rcParams.update()
     plt.grid()
     plt.grid()
-    plt.plot(scoresTable['precision'],'co--', label='precision', linewidth=1, markersize=6)
-    plt.plot(scoresTable['f1-score'], 'bo--', label='F1', linewidth=1, markersize=6)
-    plt.plot(scoresTable['recall'], 'mo--', label='recall'  , linewidth=1, markersize=6)
-    plt.plot(scoresTable['CV'], 'ro--', label='CV' , linewidth=1, markersize=6)
+    plt.plot(scoresTable['precision'],'co--', label='precision', linewidth=1, markersize=4)
+    plotMax(scoresTable['precision'], 8)
+    plt.plot(scoresTable['f1-score'], 'bo--', label='F1', linewidth=1, markersize=4)
+    plt.plot(scoresTable['recall'], 'mo--', label='recall'  , linewidth=1, markersize=4)
+    plt.plot(scoresTable['CV'], 'ro--', label='CV' , linewidth=1, markersize=4)
     for k,v in dict(scoresTable).items():
     for k,v in dict(scoresTable).items():
         for a,b in zip(range(64), v):
         for a,b in zip(range(64), v):
             plt.text(a-0.5, float(b)+0.0020, b[0:6],  fontsize=5)
             plt.text(a-0.5, float(b)+0.0020, b[0:6],  fontsize=5)
+    #plt.plot(max(scoresTable['precision']), scoresTable['precision'].index(max(scoresTable['precision'])), markersize=8)
     plt.legend(loc='upper left')   
     plt.legend(loc='upper left')   
-    plt.xticks(range(64), list(scoresTable.index)[0:65], rotation=90, fontsize=8)   
+    plt.xticks(range(64), list(scoresTable.index)[0:65], rotation=270, fontsize=8)
     fig.savefig(imageName, bbox_inches='tight', pad_inches = 0.3)
     fig.savefig(imageName, bbox_inches='tight', pad_inches = 0.3)