plot-02-demo=vb_single_run-model=dp_mix+gauss.py 文件源码

def show_clusters_over_time(
        task_output_path=None,
        query_laps=[0, 1, 2, 5, 10, None],
        nrows=2):
    ''' Read model snapshots from provided folder and make visualizations

    Post Condition
    --------------
    New matplotlib plot with some nice pictures.
    '''
    ncols = int(np.ceil(len(query_laps) // float(nrows)))
    fig_handle, ax_handle_list = pylab.subplots(
        figsize=(FIG_SIZE[0] * ncols, FIG_SIZE[1] * nrows),
        nrows=nrows, ncols=ncols, sharex=True, sharey=True)
    for plot_id, lap_val in enumerate(query_laps):
        cur_model, lap_val = bnpy.load_model_at_lap(task_output_path, lap_val)
        # Plot the current model
        cur_ax_handle = ax_handle_list.flatten()[plot_id]
        bnpy.viz.PlotComps.plotCompsFromHModel(
            cur_model, Data=dataset, ax_handle=cur_ax_handle)
        cur_ax_handle.set_xticks([-2, -1, 0, 1, 2])
        cur_ax_handle.set_yticks([-2, -1, 0, 1, 2])
        cur_ax_handle.set_xlabel("lap: %d" % lap_val)
    pylab.tight_layout()

###############################################################################
#
# Show the estimated clusters over time