def solvedp_by_roomset(pssa,name_to_value,name, xname, xdomain=None):
''' pssa : PssAnalyzer
name_to_value : function converts agent name to numerical value
'''
pylab.axvline(ymin=0, ymax=100)
if xdomain != None:
pylab.axhline(xmin=xdomain[0],xmax=xdomain[1])
for roomset_name in rooomsets_names:
#filtered pssa
filtered_pssa = pssa.select(".*", roomset_pattern=roomset_name)
# list [(agent name, percent),...]
list = filtered_pssa.solved_percent()
print_list(list)
width_vs_solved = [(name_to_value(n), p) for n,p in list ]
#print_list(width_vs_solved);exit()
#table [(20,80%),(40,90%),...]
#xmin= min(zip(*width_vs_solved)[0])
width_vs_solved_table = do_by_key(sorted, width_vs_solved, 1, reverse=True )
#vectors [[20,40,...],[80%,90%]]
width_vs_solved_vectors = zip(*sorted(width_vs_solved))
x,y = width_vs_solved_vectors
print width_vs_solved_vectors
xplot.html.plot( ((xname, x),(' % solved', y)), title=name, label = roomset_name )
for row in width_vs_solved:
pylab.axvline(row[0],0,row[1],linestyle='--',color='b' )
xplot.html.add_table(width_vs_solved_table, name + " " + roomset_name, header=[name,"%solved"])
# end
fname = name + xname + ".png"
xplot.html.add_img_plot(fname)
pylab.figure()
def table_report(table):
print_list(table)
