graph_ABC.py 文件源码

def plot(samples, path = None, true_value = 5, title = 'ABC posterior'): 
    Bayes_estimate = np.mean(samples, axis = 0)
    theta = true_value
    xmin, xmax = max(samples[:,0]), min(samples[:,0])
    positions = np.linspace(xmin, xmax, samples.shape[0])
    gaussian_kernel = gaussian_kde(samples[:,0].reshape(samples.shape[0],))
    values = gaussian_kernel(positions)
    plt.figure()
    plt.plot(positions,gaussian_kernel(positions))
    plt.plot([theta, theta],[min(values), max(values)+.1*(max(values)-min(values))])
    plt.plot([Bayes_estimate, Bayes_estimate],[min(values), max(values)+.1*(max(values)-min(values))])
    plt.ylim([min(values), max(values)+.1*(max(values)-min(values))])
    plt.xlabel(r'$\theta$')
    plt.ylabel('density')
    #plt.xlim([0,1])
    plt.rc('axes', labelsize=15) 
    plt.legend(loc='best', frameon=False, numpoints=1)
    font = {'size'   : 15}
    plt.rc('font', **font)
    plt.title(title)
    if path is not None :
        plt.savefig(path)
    return plt