numpy 'module' object has no attribute 'stack'

Question

I am trying to run some code (which is not mine), where is used 'stack' from numpy library.

Looking into documentation, stack really exists in numpy: https://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.stack.html

but when I run the code, I got:

AttributeError: 'module' object has no attribute 'stack'

any idea how to fix this. code extract:

s_t = np.stack((x_t, x_t, x_t, x_t), axis = 2)

do I need some old libraries?

Thanks.

EDIT: for some reason, python uses older version of numpy library. pip2 freeze prints "numpy==1.10.4". I've also reinstalled numpy and I've got "Successfully installed numpy-1.10.4", but printing np.version.version in code gives me 1.8.2.

Answer 1

The function numpy.stack is new; it appeared in numpy == 1.10.0 . If you can't get that version running on your system, the code can be found at (near the end)

https://github.com/numpy/numpy/blob/f4cc58c80df5202a743bddd514a3485d5e4ec5a4/numpy/core/shape_base.py

I need to examine it a bit more, but the working part of the function is:

sl = (slice(None),) * axis + (_nx.newaxis,)
expanded_arrays = [arr[sl] for arr in arrays]
return _nx.concatenate(expanded_arrays, axis=axis)

So it adds a np.newaxis to each array, and then concatenate on that. So like, vstack , hstack and dstack it adjusts the dimensions of the inputs, and then uses np.concatenate . Nothing particularly new or magical.

So if x is (2,3) shape, x[:,np.newaxis] is (2,1,3) , x[:,:,np.newaxis] is (2,3,1) etc.

If x_t is 2d, then

np.stack((x_t, x_t, x_t, x_t), axis = 2)

is probably the equivalent of

np.dstack((x_t, x_t, x_t, x_t))

creating a new array that has size 4 on axis 2.

Or:

tmp = x_t[:,:,None]
np.concatenate((tmp,tmp,tmp,tmp), axis=2)

Answer 2

It is likely have 2 numpy libraries, one in your System libraries, and the other in your python's site packages which is maintained by pip. You have a few options to fix this.

• You should reorder the libraries in sys.path so your pip installed numpy library comes in front the native numpy library. Check this out to fix your path permanently.

• Also look into virtualenv or Anaconda , which will allow you to work with specific versions of a package when you have multiple versions on your system.

• Here's another suggestion about how to ensure pip installs the library on your user path (System Library).