# AssertionError and suggestions required to improve my model

**URL:** <https://discourse.pymc.io/t/assertionerror-and-suggestions-required-to-improve-my-model/2941>\
**Category:** Questions\
**Created:** [March 18, 2019, 3:47pm UTC](https://discourse.pymc.io/t/assertionerror-and-suggestions-required-to-improve-my-model/2941 "2019-03-18T15:47:45Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![Mahak](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mahak/32/1566_2.png) [@Mahak](https://discourse.pymc.io/u/Mahak)\
**Post date:** [March 18, 2019, 3:47pm UTC](https://discourse.pymc.io/t/assertionerror-and-suggestions-required-to-improve-my-model/2941/1 "2019-03-18T15:47:45Z")

</div>

Dear all, I am getting an error of AssertionError. Can You please help me.

**I also need your suggestions to improve my model because I am new with PyMC3 and theano**

_Please find the code below:_  
Thanking you all

```python
# This is the code used for pymc3 model

import numpy as np
import pymc3 as pm
import theano.tensor as tt

def test_model(p,q,r,stations):
    
    x,y=stations
    Azim=p
    DIP=q
    Wid=r
    U1 = np.zeros((np.size(x),3),dtype=object)
    
    for i in range(1,np.size(x)):
        U1[i,:]=get_Okada(Azim, DIP,Wid,y[0,i],x[0,i],0)
        
            
    return U1
        

def get_Okada(Azim, DIP,Wid,x,y,z):
    
   
    xrot=tt.stacklists([[tt.cos(Azim*np.pi/180), -tt.sin(Azim*np.pi/180), 0],\
                          [tt.sin(Azim*np.pi/180), tt.cos(Azim*np.pi/180), 0], 
                          [0, 0, 1]])
   
    new_x= xrot*(np.asarray([[x],[y],[z]]))
    
    h = new_x[2][0]
    
    st=tt.sin(DIP*np.pi/180)
   
    w = Wid/1000
       
    xpa =tt.exp(h)
    
    ypa = h + w*st
    
      
    (tmpX,tmpY,AZ) = FAULT(xpa,ypa,st)    
    (AX,AY,tmpZ) = FAULT(xpa,ypa,st)
    U1 =np.matrix([AX, AY, AZ])
    
    U2 = (xrot.transpose() * U1.transpose()).transpose()

    return U2

    
def FAULT(xpa,ypa,st):
    
    qs1=xpa**2 + ypa/2.0
    #import sys
    #sys.path.insert(0,'C:/Users/singh/Dropbox/Catania/Python_codes')
   
    [ux1,uy1,uz1] = DISLOK(qs1,st)
    
    ax=ux1/np.pi
    ay=uy1/2/np.pi
    az=uz1/2/np.pi
        
    return ax,ay,az
    
def DISLOK(qsi, st):
    
    r = pm.math.sqrt(qsi**2)
    xx = pm.math.sqrt(qsi**2 +78)
    
    atqe = tt.arctan(qsi * xx/r)
        
    fux=fuy=fuz=0.0
    
    ai_4 = (pm.math.log(r ) - st*pm.math.log(r + st))/st
    
    fuz = ai_4*st**2
    fux = fux/ai_4*st
    fuy = st*atqe  
        
    return fux, fuy,fuz 

### Now I call it as basic model
x0=np.random.rand(1,21)
y0=np.random.rand(1,21)
stations=x0,y0

import pymc3 as pm
import test_pymc_model as tpm

basic_model = pm.Model()

with basic_model:
    
    
    Azim=pm.Uniform('Azim',lower=0,upper=360)
    DIP=pm.Uniform('DIP',lower=10,upper=89.9)
    Wid=pm.Uniform('Wid',lower=100,upper=10000)
    sigma = pm.HalfNormal('sigma', sd=1)
    mu1 = tpm.test_model(Azim,DIP,Wid,stations)
    Y_obs = pm.Normal('Y_obs', mu=mu1, sd=sigma, observed=U)

```

I got the following error

```python
Traceback (most recent call last):
  File "test_pymc.py", line 40, in <module>
    mu1 = tpm.test_model(Azim,DIP,Wid,stations)
  File "F:\Python_codes\dummy_codes\test_pymc_model.py", line 16, in test_model
    U1[i,:]=get_Okada(Azim, DIP,Wid,y[0,i],x[0,i],0)
  File "F:\Python_codes\dummy_codes\test_pymc_model.py", line 46, in get_Okada
    U2 = (xrot.transpose() * U1.transpose()).transpose()
  File "C:\Users\singh.CT\AppData\Local\Continuum\anaconda3\lib\site-packages\theano\tensor\var.py", line 155, in __mul__
    return theano.tensor.mul(self, other)
  File "C:\Users\singh.CT\AppData\Local\Continuum\anaconda3\lib\site-packages\theano\gof\op.py", line 615, in __call__
    node = self.make_node(*inputs, **kwargs)
  File "C:\Users\singh.CT\AppData\Local\Continuum\anaconda3\lib\site-packages\theano\tensor\elemwise.py", line 480, in make_node
    inputs = list(map(as_tensor_variable, inputs))
  File "C:\Users\singh.CT\AppData\Local\Continuum\anaconda3\lib\site-packages\theano\tensor\basic.py", line 194, in as_tensor_variable
    return constant(x, name=name, ndim=ndim)
  File "C:\Users\singh.CT\AppData\Local\Continuum\anaconda3\lib\site-packages\theano\tensor\basic.py", line 232, in constant
    x_ = scal.convert(x, dtype=dtype)
  File "C:\Users\singh.CT\AppData\Local\Continuum\anaconda3\lib\site-packages\theano\scalar\basic.py", line 284, in convert
    assert type(x_) in [np.ndarray, np.memmap]
AssertionError

```

---

<div class="post-metadata">

**Author:** ![Mahak](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mahak/32/1566_2.png) [@Mahak](https://discourse.pymc.io/u/Mahak)\
**Post date:** [March 18, 2019, 4:28pm UTC](https://discourse.pymc.io/t/assertionerror-and-suggestions-required-to-improve-my-model/2941/2 "2019-03-18T16:28:37Z")

</div>

In case you need it , this is my actual model with that I calculate my data (U). I want to invert U for estimating the (p,q,r OR Azim, DIP, Wid)

import numpy as np  
def test\_model(p,q,r,stations):  
x,y=stations  
Azim=p  
DIP=q  
Wid=r  
U1 = np.zeros((np.size(x),3),dtype=object)

```
for i in range(1,np.size(x)):
    U1[i,:]=getOkada(Azim, DIP,Wid,y[0,i],x[0,i],0)
    
 return U1

```

def getOkada(Azim, DIP,Wid,x,y,z):

```
xrot=np.matrix([[np.cos(np.radians(Azim)),\
      -np.sin(np.radians(Azim)), 0],\
      [np.sin(np.radians(Azim)),\
      np.cos(np.radians(Azim)),\
      0], [0, 0, 1]])

new_x= xrot*(np.asarray([[x],[y],[z]]))

h = new_x[2][0]

st=np.sin(DIP*np.pi/180)

w = Wid/1000
   
xpa =np.exp(h)

ypa = h + w*st   
  
(tmpX,tmpY,AZ) = FAULT(xpa,ypa,st)    
(AX,AY,tmpZ) = FAULT(xpa,ypa,st)
AX=float(AX)
AY=float(AY)
AZ=float(AZ)
U1 =np.matrix([AX, AY, AZ])

U2 = (xrot.transpose() * U1.transpose()).transpose()

return U2

```

def FAULT(xpa,ypa,st):  
qs1=xpa\*\*2 + ypa/2.0

```
[ux1,uy1,uz1] = DISLOK(qs1,st)

ax=ux1/np.pi
ay=uy1/2/np.pi
az=uz1/2/np.pi
    
return ax,ay,az

```

def DISLOK(qsi, st):  
r = np.sqrt(qsi**2)  
xx = np.sqrt(qsi**2 +78)  
atqe = np.arctan(qsi \* xx/r)

```
fux=fuy=fuz=0.0

ai_4 = (np.log(r ) - st*np.log(r + st))/st

fuz = ai_4*st**2
fux = fux/ai_4*st
fuy = st*atqe  
    
return fux, fuy,fuz

```

# I call it like this

import numpy as np  
import matplotlib.pyplot as plt

p=89.9  
q=75  
r=1000

x0=np.random.rand(1,21)  
y0=np.random.rand(1,21)  
stations=x0,y0

import test\_model as TM

U=TM.test\_model(p,q,r,stations)

---

<div class="post-metadata">

**Author:** ![lucianopaz](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/lucianopaz/32/2186_2.png) [@lucianopaz](https://discourse.pymc.io/u/lucianopaz)\
**Post date:** [March 18, 2019, 5:36pm UTC](https://discourse.pymc.io/t/assertionerror-and-suggestions-required-to-improve-my-model/2941/3 "2019-03-18T17:36:54Z")

</div>

> [@Mahak](#):
>
> ```python
> U1 =np.matrix([AX, AY, AZ])
> 
> ```

numpy is not aware of theano tensors so the quoted line makes a matrix of `dtype=object`. You need to replace that line with an appropriate `theano.stack`.

> [@Mahak](#):
>
> ```python
> U1 = np.zeros((np.size(x),3),dtype=object)
> for i in range(1,np.size(x)): 
> U1[i,:]=get_Okada(Azim, DIP,Wid,y[0,i],x[0,i],0)
> 
> ```

Furthermore `U1` should be created as a tensor of floats using `theano.tensor.zeros`, and finally you cannot set its elements like you did in the for loop, you need to use `inc_subtensor` or one of its variants from `theano.tensor`.

---

<div class="post-metadata">

**Author:** ![Mahak](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mahak/32/1566_2.png) [@Mahak](https://discourse.pymc.io/u/Mahak)\
**Post date:** [March 19, 2019, 10:36am UTC](https://discourse.pymc.io/t/assertionerror-and-suggestions-required-to-improve-my-model/2941/4 "2019-03-19T10:36:15Z")

</div>

Thank You very much for your reply. I am trying to adopt your suggestions. However, is there any alternative way to get rid of the loop.

Actually I have the **N** number of data points which are calculated by calling the model **N** times. So, when writing the following line in pymc3 model:

**Y\_obs = pm.Normal(‘Y\_obs’, mu=mu1, sd=sigma, observed=U)**

the length/size of _mu1_ and _U_ should be the same. For that reason, I have to use loop so _mu1_ return with the same length/size as of _U_. My precise question, can I some how calculate _mu1_ iteratively within pymc3 model ? if its possible then I don’t need to use loop inside my customized forward model. I would appriciate if you could forward some particular example of vectorized model or where observed data has to be calculated iteratively.  
Thank You!

---

<div class="post-metadata">

**Author:** ![lucianopaz](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/lucianopaz/32/2186_2.png) [@lucianopaz](https://discourse.pymc.io/u/lucianopaz)\
**Post date:** [March 19, 2019, 11:07am UTC](https://discourse.pymc.io/t/assertionerror-and-suggestions-required-to-improve-my-model/2941/5 "2019-03-19T11:07:02Z")

</div>

> [@Mahak](#):
>
> My precise question, can I some how calculate _mu1_ iteratively within pymc3 model ?

I think that what you are trying to do is called vectorize the loop. The answer can be yes, but you’ll have to work hard to make `get_Okada` to work with

- `Azim`, `DIP` and `Wid` that are scalar floats or scalar random variables.
- `x` and `y` that are 1 dimensional arrays.

Your function should then output an `(N, 3)` array that would set all the elements of `U1` without using a for loop. One thing I hadn’t noticed before was that `mu1` ends up being a 2 dimensional tensor, so your observations must also be 2 dimensional, and in particular have `(N, 3)` shape!