Exemplos de Log.set_loglevel em Python

Exemplo n.º 1

Arquivo: demo_mcmc_other_metropolis.py Projeto: littlefoxhome/kernel_hmc

from kernel_hmc.mini_mcmc.mini_mcmc import mini_mcmc
from kernel_hmc.proposals.metropolis import StandardMetropolis,\
    AdaptiveMetropolis, KernelAdaptiveMetropolis
from kernel_hmc.tools.log import Log
import matplotlib.pyplot as plt
import numpy as np


# banana gradient depends on theano, which is an optional dependency
try:
    from kernel_hmc.densities.banana import Banana
    banana_available = True
except ImportError:
    banana_available = False

Log.set_loglevel(20)

if __name__ == '__main__':
    """
    This example shows how to run all Metropolis-Hastings sampler (including
    the Kernel Adaptive Metropolis-Hastings) from the paper on a simple target.
    """
    # possible to change
    D = 2
    N = 1000
    
    # target is banana density, fallback to Gaussian if theano is not present
    if banana_available:
        target = Banana(D=D)
    else:
        target = IsotropicZeroMeanGaussian(D=D)

Exemplo n.º 2

from kernel_hmc.examples.plotting import visualise_trace
from kernel_hmc.mini_mcmc.mini_mcmc import mini_mcmc
from kernel_hmc.proposals.metropolis import StandardMetropolis,\
    AdaptiveMetropolis, KernelAdaptiveMetropolis
from kernel_hmc.tools.log import Log
import matplotlib.pyplot as plt
import numpy as np

# banana gradient depends on theano, which is an optional dependency
try:
    from kernel_hmc.densities.banana import Banana
    banana_available = True
except ImportError:
    banana_available = False

Log.set_loglevel(20)

if __name__ == '__main__':
    """
    This example shows how to run all Metropolis-Hastings sampler (including
    the Kernel Adaptive Metropolis-Hastings) from the paper on a simple target.
    """
    # possible to change
    D = 2
    N = 1000

    # target is banana density, fallback to Gaussian if theano is not present
    if banana_available:
        target = Banana(D=D)
    else:
        target = IsotropicZeroMeanGaussian(D=D)