# Scipy.root problem using PyMC3

**URL:** <https://discourse.pymc.io/t/scipy-root-problem-using-pymc3/1152>\
**Category:** Questions\
**Created:** [April 30, 2018, 6:43am UTC](https://discourse.pymc.io/t/scipy-root-problem-using-pymc3/1152 "2018-04-30T06:43:58Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![jmsureda](https://avatars.discourse-cdn.com/v4/letter/j/74df32/32.png) [@jmsureda](https://discourse.pymc.io/u/jmsureda)\
**Post date:** [April 30, 2018, 6:43am UTC](https://discourse.pymc.io/t/scipy-root-problem-using-pymc3/1152/1 "2018-04-30T06:43:59Z")

</div>

Hi, i’m currently working with PyMC3 and got an error when using scipy.root(). This rises this error: ‘error: Result from function call is not a proper array of floats.’. When i call the function dl(x,L,C) alone (out of PyMC3), giving L and C fixed, this works fine. Then, i think the problem appears when PyMC3 interacts with scipy.root, since in that line appears the error.

```auto
# Model function

def function(q,x,L,C):
    
    return np.divide(1,1+x)-np.divide(yt(q,L,C),yt(1.,L,C))
     
def YL(x,L,C):
    
    return root(function,1.,args=(x,L,C))['x'][0]

def yt(Y,L,C):
    
    return Y*np.sqrt(np.divide(1-np.divide(1.,3.)*L*Y*np.sqrt(C+Y),1-L*Y*np.sqrt(C+Y)))

def integrand(u,L,C):

    return np.divide(u,np.sqrt(C+u)*yt(u,L,C))

def dl(x,L,C):
    
    return c*(1+x)*np.sqrt(C)*np.divide(yt(1.,L,C),100.*np.sqrt(h2OmegaR))*(quad(integrand,YL(x,L,C),1.,args=(L,C))[0])

# define the model/function to be fitted.

with pymc3.Model(): 
    L = pymc3.Normal('L', 0., 1., testval= 0.505)
    C = pymc3.Normal('C', 0.00010, 0.0003, testval= 0.00020)
    #M = pymc3.Normal('M', -21, -19, testval= -19.5)
    
    Delta_m = pymc3.Deterministic('Delta_m',5.*np.log10(dl(x,L,C)) + 25. - 19.26)
    
    y = pymc3.Normal('y', mu=Delta_m, tau=1.0/np.power(f_error,2), observed = f)
    
    start = pymc3.find_MAP()
    step = pymc3.NUTS()
    trace = pymc3.sample(100,start=start)

```

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<div class="post-metadata">

**Author:** ![junpenglao](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/junpenglao/32/8_2.png) [@junpenglao](https://discourse.pymc.io/u/junpenglao)\
**Post date:** [April 30, 2018, 7:49am UTC](https://discourse.pymc.io/t/scipy-root-problem-using-pymc3/1152/2 "2018-04-30T07:49:06Z")

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PyMC3 variables are theano tensors, which means you can not apply numpy/scipy functions on them directly.

The most direct (and many cases slow) way to go around it is to wrap the numpy/scipy function as a theano function: [http://deeplearning.net/software/theano/extending/extending\_theano.html#as-op](http://deeplearning.net/software/theano/extending/extending_theano.html#as-op)  
a pymc3 example:  
[https://github.com/pymc-devs/pymc3/blob/master/pymc3/examples/disaster\_model\_theano\_op.py](https://github.com/pymc-devs/pymc3/blob/master/pymc3/examples/disaster_model_theano_op.py)

The ideal way is to rewrite the numpy/scipy function as a theano function. It could be a bit involve at times, but you can have a look at the doc for an example (which also finding the root of some function): [http://docs.pymc.io/advanced\_theano.html](http://docs.pymc.io/advanced_theano.html)