def plot_stats()

in c3dm/tools/stats.py [0:0]

• 77 lines of code
• 21 McCabe index (conditional complexity)

    def plot_stats( self, visdom_env=None, plot_file=None, \
                        visdom_server=None, visdom_port=None ):
            
        # use the cached visdom env if none supplied
        if visdom_env is None:    visdom_env    = self.visdom_env
        if visdom_server is None: visdom_server = self.visdom_server
        if visdom_port is None:   visdom_port   = self.visdom_port
        if plot_file is None:      plot_file     = self.plot_file

        stat_sets = list(self.stats.keys())

        print("printing charts to visdom env '%s' (%s:%d)" % \
                (visdom_env,visdom_server,visdom_port) )

        novisdom = False
        
        viz = get_visdom_connection(server=visdom_server,port=visdom_port)
        if not viz.check_connection():
            print("no visdom server! -> skipping visdom plots")
            novisdom = True

        lines = []

        # plot metrics
        if not novisdom:
            viz.close(env=visdom_env,win=None)
        
        for stat in self.log_vars:
            vals = []
            stat_sets_now = []
            for stat_set in stat_sets: 
                val = self.stats[stat_set][stat].get_epoch_averages()
                if val is None:
                    continue;
                else:
                    val = np.array(val)[:,None]
                    stat_sets_now.append(stat_set)
                vals.append(val)

            if len(vals)==0:
                continue

            # pad for skipped test evals
            size = np.max([val.shape[0] for val in vals])
            vals = [
                np.pad(val, ((0, size - val.shape[0]), (0, 0)), mode='edge')
                for val in vals
            ]

            try:
                vals = np.concatenate(vals, axis=1)
            except:
                print('cant plot %s!' % stat)
                continue
            x = np.arange(vals.shape[0])
            
            lines.append( (stat_sets_now,stat,x,vals,) )        

        if not novisdom:
            for idx , ( tmodes, stat , x , vals ) in enumerate( lines ):
                if vals.shape[1] == 1:  # eval
                    continue

                title = "%s" % stat
                opts = dict(title=title,legend=list(tmodes))
                try:
                    viz.line( Y=vals,X=x,env=visdom_env,opts=opts)
                except:
                    print("Warning: problem adding data point", x.shape, vals.shape)
            
        if plot_file:
            print("exporting stats to %s" % plot_file)
            ncol = 3
            nrow = int(np.ceil(float(len(lines))/ncol))
            matplotlib.rcParams.update({'font.size': 5})
            color=cycle(plt.cm.tab10(np.linspace(0,1,10)))
            fig = plt.figure(1); plt.clf()
            for idx , ( tmodes, stat , x , vals ) in enumerate( lines ):
                c=next(color)
                plt.subplot(nrow,ncol,idx+1)
                ax = plt.gca()
                for vali,vals_ in enumerate(vals.T):
                    c_ = c * ( 1. - float(vali) * 0.3 )
                    plt.plot( x, vals_, c = c_, linewidth=1 )
                plt.ylabel( stat )
                plt.xlabel( "epoch" )
                plt.gca().yaxis.label.set_color(c[0:3]*0.75)
                plt.legend(tmodes)
                gcolor = np.array(mcolors.to_rgba('lightgray'))
                plt.grid(b=True, which='major', color=gcolor, linestyle='-', linewidth=0.4)
                plt.grid(b=True, which='minor', color=gcolor, linestyle='--', linewidth=0.2)
                plt.minorticks_on()
            
            plt.tight_layout()
            plt.show()
            fig.savefig( plot_file )