示例#1
0
def gauss_2d(nsamples=1000):
    """
    Another simple test plot
    1d gaussian sampled from each sampler visualized as a joint 2d gaussian
    """
    gaussian = misc.distributions.TestGaussian(ndims=1)
    control = Control(gaussian.Xinit, gaussian.E, gaussian.dEdX)
    experimental = ContinuousTimeHMC(gaussian.Xinit, gaussian.E, gaussian.dEdX)

    with sns.axes_style("white"):
        sns.jointplot(control.sample(nsamples)[0], experimental.sample(nsamples)[0], kind="hex", stat_func=None)
示例#2
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def hist_1d(distr, nsamples=1000, nbins=250):
    """
    plots a 1d histogram from each sampler
    distr is (an unitialized) class from distributions
    """
    distribution = distr(ndims=1)
    control = Control(distribution.Xinit, distribution.E, distribution.dEdX)
    experimental = ContinuousTimeHMC(distribution.Xinit, distribution.E, distribution.dEdX)

    plt.hist(control.sample(nsamples)[0], nbins, normed=True, label="Standard Control", alpha=0.5)
    plt.hist(experimental.sample(nsamples)[0], nbins, normed=True, label="Continuous-time Control", alpha=0.5)
    plt.legend()