invResults.py 文件源码

def plot_deviance(sol, save=False, draw=True, save_as_png=True, fig_dpi=144):
    if save_as_png:
        save_as = 'png'
    else:
        save_as = 'pdf'
    filename = sol.filename.replace("\\", "/").split("/")[-1].split(".")[0]
    model = get_model_type(sol)
    if draw or save:
        fig, ax = plt.subplots(figsize=(4,3))
        deviance = sol.MDL.trace('deviance')[:]
        sampler_state = sol.MDL.get_state()["sampler"]
        x = np.arange(sampler_state["_burn"]+1, sampler_state["_iter"]+1, sampler_state["_thin"])
        plt.plot(x, deviance, "-", color="C3", label="Model deviance\nDIC = %.2f\nBPIC = %.2f" %(sol.MDL.DIC,sol.MDL.BPIC))
        plt.xlabel("Iteration")
        plt.ylabel("Model deviance")
        plt.legend(numpoints=1, loc="best")
        plt.grid('on')
        if sampler_state["_burn"] == 0:
            plt.xscale('log')
        else:
            plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
        ax.yaxis.set_major_locator(MaxNLocator(integer=True))
        fig.tight_layout()
    if save:
        save_where = '/Figures/ModelDeviance/'
        working_path = getcwd().replace("\\", "/")+"/"
        save_path = working_path+save_where
        print("\nSaving model deviance figure in:\n", save_path)
        if not path.exists(save_path):
            makedirs(save_path)
        fig.savefig(save_path+'ModelDeviance-%s-%s.%s'%(model,filename,save_as), dpi=fig_dpi, bbox_inches='tight')
    try:    plt.close(fig)
    except: pass
    if draw:    return fig
    else:       return None