pymc3/theano錯誤使用冪函數

Question

我試圖用pymc3重建貝葉斯PK/PD模型的這個例子中.....當

視頻顯示WinBUGS軟件代碼，我試圖將轉換爲pymc3

https://www.youtube.com/watch?v=AQDXRoBan6Y

模型這裏....

http://imgur.com/ckoKPRF

WinBUGS軟件代碼是在這裏....

http://imgur.com/TsViyBC

我的代碼....

from pymc3 import Model, Normal, Lognormal, Uniform 
import numpy as np 
import pandas as pd 

data = pd.read_csv('/Users/Home/Documents/pymc3/fxa.data.csv') 

cobs = np.array(data['cobs']) 
fxa = np.array(data['fxa.inh.obs']) 

pkpd_model = Model() 

with pkpd_model: 

    # Priors for unknown model parameters 
    emax = Uniform ('emax', lower =0, upper =100) 
    ec50 = Lognormal('ec50', mu=0, tau = 100000) 
    gamma = Uniform('gamma', lower=0, upper =10) 
    sigma = Uniform('sigma', lower = 0, upper = 1000) 


    # Expected value of outcome 
    fxaMean = emax*(np.power(cobs, gamma))/(np.power(ec50, gamma) + np.power(cobs, gamma)) 

    # Likelihood (sampling distribution) of observations 
    fxa = Normal('fxa', mu=fxaMean, sd=sigma, observed=fxa) 

但是當我運行我碰到下面的錯誤，這似乎涉及到的方式theano被解釋np.power函數的代碼。

我不知道如何繼續，因爲我是pomc3和theano以及PK/PD建模的小菜鳥！

在此先感謝

Applied interval-transform to emax and added transformed emax_interval to model. 
Applied log-transform to ec50 and added transformed ec50_log to model. 
Applied interval-transform to gamma and added transformed gamma_interval to model. 
Applied interval-transform to sigma and added transformed sigma_interval to model. 
--------------------------------------------------------------------------- 
AsTensorError        Traceback (most recent call last) 
<ipython-input-28-1fa311a15ed0> in <module>() 
    14 
    15  # Likelihood (sampling distribution) of observations 
---> 16  fxa = Normal('fxa', mu=fxaMean, sd=sigma, observed=fxa) 

//anaconda/lib/python2.7/site-packages/pymc3/distributions/distribution.pyc in __new__(cls, name, *args, **kwargs) 
    23    data = kwargs.pop('observed', None) 
    24    dist = cls.dist(*args, **kwargs) 
---> 25    return model.Var(name, dist, data) 
    26   elif name is None: 
    27    return object.__new__(cls) # for pickle 

//anaconda/lib/python2.7/site-packages/pymc3/model.pyc in Var(self, name, dist, data) 
    282      self.named_vars[v.name] = v 
    283   else: 
--> 284    var = ObservedRV(name=name, data=data, distribution=dist, model=self) 
    285    self.observed_RVs.append(var) 
    286    if var.missing_values: 

//anaconda/lib/python2.7/site-packages/pymc3/model.pyc in __init__(self, type, owner, index, name, data, distribution, model) 
    556    self.missing_values = data.missing_values 
    557 
--> 558    self.logp_elemwiset = distribution.logp(data) 
    559    self.model = model 
    560    self.distribution = distribution 

//anaconda/lib/python2.7/site-packages/pymc3/distributions/continuous.pyc in logp(self, value) 
    191   sd = self.sd 
    192   mu = self.mu 
--> 193   return bound((-tau * (value - mu)**2 + T.log(tau/np.pi/2.))/2., 
    194      tau > 0, sd > 0) 
    195 

//anaconda/lib/python2.7/site-packages/theano/tensor/var.pyc in __radd__(self, other) 
    232  # ARITHMETIC - RIGHT-OPERAND 
    233  def __radd__(self, other): 
--> 234   return theano.tensor.basic.add(other, self) 
    235 
    236  def __rsub__(self, other): 

//anaconda/lib/python2.7/site-packages/theano/gof/op.pyc in __call__(self, *inputs, **kwargs) 
    609   """ 
    610   return_list = kwargs.pop('return_list', False) 
--> 611   node = self.make_node(*inputs, **kwargs) 
    612 
    613   if config.compute_test_value != 'off': 

//anaconda/lib/python2.7/site-packages/theano/tensor/elemwise.pyc in make_node(self, *inputs) 
    541   using DimShuffle. 
    542   """ 
--> 543   inputs = list(map(as_tensor_variable, inputs)) 
    544   shadow = self.scalar_op.make_node(
    545    *[get_scalar_type(dtype=i.type.dtype).make_variable() 

//anaconda/lib/python2.7/site-packages/theano/tensor/basic.pyc in as_tensor_variable(x, name, ndim) 
    206   except Exception: 
    207    str_x = repr(x) 
--> 208   raise AsTensorError("Cannot convert %s to TensorType" % str_x, type(x)) 
    209 
    210 # this has a different name, because _as_tensor_variable is the 

AsTensorError: ('Cannot convert [Elemwise{mul,no_inplace}.0 Elemwise{mul,no_inplace}.0\n Elemwise{mul,no_inplace}.0 ..., Elemwise{mul,no_inplace}.0\n Elemwise{mul,no_inplace}.0 Elemwise{mul,no_inplace}.0] to TensorType', <type 'numpy.ndarray'>) 

Answer 1

衛生署 - 更換np.power有**！工作正常！