```
import numpy as np
for i in range(len(x)):
if (np.floor(N[i]/2)==N[i]/2):
for j in range(N[i]/2):
pxd[i,j]=x[i]-(delta*j)*np.sin(s[i]*np.pi/180)
pyd[i,j]=y[i]-(delta*j)*np.cos(s[i]*np.pi/180)
else:
for j in range((N[i]-1)/2):
pxd[i,j]=x[i]-(delta*j)*np.sin(s[i]*np.pi/180)
pyd[i,j]=y[i]-(delta*j)*np.cos(s[i]*np.pi/180)
```

Does anyone has an idea of solving this problem? Running these codes successfully?

I came here with the same Error, though one with a different origin.

It is caused by unsupported float index in 1.12.0 and newer numpy versions even if the code should be considered as valid.

An `int`

type is expected, not a `np.float64`

Solution: Try to install `numpy 1.11.0`

```
sudo pip install -U numpy==1.11.0.
```

Similar situation. It was working. Then, I started to include pytables. At first view, no reason to errors. I decided to use another function, that has a domain constraint (elipse) and received the following error:

```
TypeError: 'numpy.float64' object cannot be interpreted as an integer
```

or

```
TypeError: 'numpy.float64' object is not iterable
```

The crazy thing: the previous function I was using, no code changed, started to return the same error. My intermediary function, already used was:

```
def MinMax(x, mini=0, maxi=1)
return max(min(x,mini), maxi)
```

The solution was avoid `numpy`

or `math`

:

```
def MinMax(x, mini=0, maxi=1)
x = [x_aux if x_aux > mini else mini for x_aux in x]
x = [x_aux if x_aux < maxi else maxi for x_aux in x]
return max(min(x,mini), maxi)
```

Then, everything calm again. It was like one library possessed `max`

and `min`

!

Source: Stackoverflow.com