I'm trying to fix some code in statsmodels that creates Deprecation Warnings from numpy

Most of it are quite easy to fix, mainly cases where we use floats to avoid integer division

I have two problems

first, I get Deprecation warnings in the test run that don't specify where they happen.

I try to find them with file searches, but I don't see a `np.ones` that might cause a problem 

(needle in a haystack: Close to 4000 unittests and more than 100,000 lines of numpython)

Also, I'm not sure the warnings are only from statsmodels, they could be in numpy, scipy or pandas, couldn't they?

second, what's wrong with non-integers in `np.r_[[np.nan] * head, x, [np.nan] * tail]` (see below)

I tried to set the warnings filter to `error` but then Python itself errored right away.

Thanks for any clues

Josef

>nosetests  -s --pdb-failures --pdb "M:\j\statsmodels\statsmodels_py34\statsmodels\tsa\tests"

..................C:\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\sit

e-packages\numpy\core\numeric.py:183: DeprecationWarning: using a non-integer nu

mber instead of an integer will result in an error in the future

  a = empty(shape, dtype, order)

..........

.......M:\j\statsmodels\stat

smodels_py34\statsmodels\tsa\filters\filtertools.py:28: DeprecationWarning: usin

g a non-integer number instead of an integer will result in an error in the futu

re

  return np.r_[[np.nan] * head, x, [np.nan] * tail]

..........................

...................C:\WinPython-64bit-3.4.3.1

\python-3.4.3.amd64\lib\site-packages\numpy\lib\twodim_base.py:231: DeprecationW

arning: using a non-integer number instead of an integer will result in an error

 in the future

  m = zeros((N, M), dtype=dtype)

C:\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\numpy\l

ib\twodim_base.py:238: DeprecationWarning: using a non-integer number instead of

 an integer will result in an error in the future

  m[:M-k].flat[i::M+1] = 1

...........