Further improved plot display in plotreing

plots/plotreing.py

@@ -161,31 +161,22 @@ def plot_average_curve( alldata, indexes, ylabel, xlabel, xmax, ymax, col, ops,
         plt.gca().set_prop_cycle(None)
         ind = 0
         for op in ops:
-            #display(op)
             #add 100 points to plot on intervals of 100
-            #print(alldata[index][ind].iloc[1::100])
             alldata[index][ind].iloc[1::100].plot(kind='line',y=col, label=op, ax=ax, linestyle=ls, linewidth=1.0, legend=legend) #, marker='*', color='blue'
             ind += 1
     ax.set_xlabel(xlabel)  # Add an x-label to the axes.
     ax.set_xlim([0,xmax])
     ax.set_ylabel(ylabel)  # Add a y-label to the axes.
     ax.set_ylim([0,ymax])
-    #ax.set_ylim([0,100])
     ax.spines['top'].set_visible(False) # suppress top and right bars
     ax.spines['right'].set_visible(False)
-    #
-    #ax.set_title(label+" for "+pattern)  # Add a title to the axes.
-    #ax.set_title(ylabel)  # Add a title to the axes.
-    #ax.legend(loc='center', bbox_to_anchor=(0.5, -0.05), shadow=True, ncol=2)  # Add a legend.
-    #ax.legend() # ncol=2
     if legend == True:
-        lines = ax.get_lines()
-        ax.legend( handles=lines[:ind], loc='lower center', bbox_to_anchor=(0.5, 1.05), ncol=3 ) # ncol=2
-    #
+        ax.legend( loc='lower center', bbox_to_anchor=(0.5, 1.05), ncol= )
     plt.show()
 
+# JE 2023: That would be far better to have simple notations
 #dict_ops = {'Size':['Size','size'],'size':['Size','size'],'Success\\ rate':['Succes rate','srate'],'Success~rate':['Succes rate','srate'],'Success$~$rate':['Succes rate','srate'],'Success':['Succes rate','srate'],'F$-$measure':['F-measure','fmeas'],'Prec':['Precision','prec'],'Precicion':['Precision','prec'],'Precision':['Precision','prec'],'Rec':['Recall','rec'],'Recall':['Recall','rec']}
-dict_ops = {'size':['Size','size'],'successrate':['Succes rate','srate'],'f-measure':['F-measure','fmeas'],'precision':['Precision','prec'],'recall':['Recall','rec']}
+dict_ops = {'size':['Size','size'],'successrate':['Success rate','srate'],'f-measure':['F-measure','fmeas'],'precision':['Precision','prec'],'recall':['Recall','rec']}
 
 def print_datafiles( alldf, plotinfo, labelpatts, cols, nbiter ):
     [plotlabel,col] = dict_ops[plotinfo[0]]