def tracker_timespace(filename, stats):
        classlist = list(stats.index.keys())
        classlist.sort()

        for snapshot in stats.snapshots:
            stats.annotate_snapshot(snapshot)

        timestamps = [fp.timestamp for fp in stats.snapshots]
        offsets = [0] * len(stats.snapshots)
        poly_labels = []
        polys = []
        for clsname in classlist:
            pct = [fp.classes[clsname]['pct'] for fp in stats.snapshots]
            if max(pct) > 3.0:
                sizes = [fp.classes[clsname]['sum'] for fp in stats.snapshots]
                sizes = [float(x) / (1024 * 1024) for x in sizes]
                sizes = [offset + size for offset, size in zip(offsets, sizes)]
                poly = matplotlib.mlab.poly_between(timestamps, offsets, sizes)
                polys.append((poly, {'label': clsname}))
                poly_labels.append(clsname)
                offsets = sizes

        fig = plt.figure(figsize=(10, 4))
        axis = fig.add_subplot(111)

        axis.set_title("Snapshot Memory")
        axis.set_xlabel("Execution Time [s]")
        axis.set_ylabel("Virtual Memory [MiB]")

        totals = [x.asizeof_total for x in stats.snapshots]
        totals = [float(x) / (1024 * 1024) for x in totals]
        axis.plot(timestamps, totals, 'r--', label='Total')
        tracked = [x.tracked_total for x in stats.snapshots]
        tracked = [float(x) / (1024 * 1024) for x in tracked]
        axis.plot(timestamps, tracked, 'b--', label='Tracked total')

        for (args, kwds) in polys:
            axis.fill(*args, **kwds)
        axis.legend(loc=2)  # TODO fill legend
        fig.savefig(filename)
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