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我不知道是否有人熟悉 Dan Foreman-Mackley 的“emcee”Python 模块，但我正在使用它来对分布进行抽样。我正在使用 Parallel Tempering 采样器，因为我的发行版看起来很时髦。以下是相关代码：

from emcee import PTSampler

rendim = 6
renwalkers = 100
ntemps = 20


gauss2 = PTSampler(ntemps, renwalkers, rendim, lnlike, lnprior)

p0 = [[[np.random.rand()*0.24,np.random.rand()*3,np.random.rand()*1,np.random.rand()*1,np.random.rand()*3,np.random.rand()*1] for i in range(renwalkers)] for i in range(ntemps)]

for q, lnprob, lnlike in gauss2.sample(p0,iterations=1000):
    pass
gauss2.reset()

for q, lnprob, lnlike in gauss2.sample(p, lnprob0=lnprob,
                                       lnlike0=lnlike,
                                       iterations=10000, thin=10):
    pass

我不断收到“numpy.ndarray”对象不可调用的错误。这是完整的错误：

TypeError                                 Traceback (most recent call last)
<ipython-input-25-d5f2a1f4b7b0> in <module>()
     11 p0 = [[[np.random.rand()*0.24,np.random.rand()*3,np.random.rand()*1,np.random.rand()*1,np.random.rand()*3,np.random.rand()*1] for i in range(renwalkers)] for i in range(ntemps)]
     12 
---> 13 for q, lnprob, lnlike in gauss2.sample(p0,iterations=1000):
     14     pass
     15 gauss2.reset()

/Library/Python/2.7/site-packages/emcee-2.1.0-py2.7.egg/emcee/ptsampler.py in sample(self, p0, lnprob0, lnlike0, iterations, thin, storechain)
    255                              self.logpargs, self.loglkwargs, self.logpkwargs)
    256             if self.pool is None:
--> 257                 results = list(map(fn, p.reshape((-1, self.dim))))
    258             else:
    259                 results = list(self.pool.map(fn, p.reshape((-1, self.dim))))

/Library/Python/2.7/site-packages/emcee-2.1.0-py2.7.egg/emcee/ptsampler.py in __call__(self, x)
     94             return lp, lp
     95 
---> 96         return self.logl(x, *self.loglargs, **self.loglkwargs), lp
     97 
     98 

TypeError: 'numpy.ndarray' object is not callable

更新：这里是 lnlike 和 lnprior 函数：

def lnprior(theta):
    eta, mu1, sig1, h, mu2, sig2 = theta
    if 0 < eta < 0.24 and 0 < mu1 < 1.5 and 0 < sig1 < 1 and 0 < h < 1 and 0 < mu2 < 1.5 and 0 < sig2 < 1:
        return 0
    return -np.inf

def lnlike(theta):
    eta, mu1, sig1, h, mu2, sig2 = theta
    return -k*np.log(Nsamp)+np.sum(np.log(np.sum(MCetadist(eta,events,mu1,sig1,h,mu2,sig2),axis=1)))
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1 回答 1

-2

消息“TypeError: 'numpy.ndarray' object is not callable”表示您尝试作为函数调用的“numpy.ndarray”是模块或变量，因此不可调用。当你用 '()' 调用一个非函数时，你会遇到这种类型的错误。您可以在该引用之后删除“（）”，一切都会好起来的。

于 2017-03-28T02:06:07.140 回答