plot-01-demo=vb_algs-model=mix_gauss.py 文件源码

def show_clusters_over_time(
        task_output_path=None,
        query_laps=[0, 1, 2, 10, 20, None],
        nrows=2):
    ''' Show 2D elliptical contours overlaid on raw data.
    '''
    ncols = int(np.ceil(len(query_laps) // float(nrows)))
    fig_handle, ax_handle_list = pylab.subplots(
        figsize=(SMALL_FIG_SIZE[0] * ncols, SMALL_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)
        cur_ax_handle = ax_handle_list.flatten()[plot_id]
        bnpy.viz.PlotComps.plotCompsFromHModel(
            cur_model, dataset=dataset, ax_handle=cur_ax_handle)
        cur_ax_handle.set_title("lap: %d" % lap_val)
        cur_ax_handle.set_xlabel(dataset.column_names[0])
        cur_ax_handle.set_ylabel(dataset.column_names[1])
        cur_ax_handle.set_xlim(data_ax_h.get_xlim())
        cur_ax_handle.set_ylim(data_ax_h.get_ylim())
    pylab.tight_layout()


###############################################################################
#
# *DiagGauss* observation model
# -----------------------------
#
# Assume diagonal covariances.
#
# Start with too many clusters (K=20)