According to the official documentation:

Disabling ATLAS and other accelerated libraries

Usage of ATLAS and other accelerated libraries in Numpy can bedisabled via:

  BLAS=None LAPACK=None ATLAS=None python setup.py build

However, this information seems to be out of date, since I found that even with these options numpy v1.9.2 was still automatically finding libopenblas.so:

numpy_source_dir/$ BLAS=None LAPACK=None ATLAS=None python setup.py config...openblas_info:  FOUND:    libraries = ['openblas', 'openblas']    library_dirs = ['/opt/OpenBLAS/lib']    language = f77  FOUND:    libraries = ['openblas', 'openblas']    library_dirs = ['/opt/OpenBLAS/lib']    language = f77...

One workaround is to copy site.cfg.example to site.cfg, then edit it to make the paths to the relevant BLAS/LAPACK libraries invalid:

[openblas]libraries =library_dirs =include_dirs =

When you subsequently call BLAS=None LAPACK=None ATLAS=None python setup.py config you should get an output containing this:

...openblas_info:/home/alistair/src/python/numpy/numpy/distutils/system_info.py:594: UserWarning: Specified path  is invalid.  warnings.warn('Specified path %s is invalid.' % d)  libraries  not found in []  NOT AVAILABLE...

I expect that the same approach will work for ATLAS and MKL, although I don't have these libraries installed in order to do a proper test.

You should, of course, be aware that not having accelerated BLAS/LAPACK libraries will have a big detrimental effect on performance for linear algebra ops.

Update

As mentioned in the comments below, you didn't actually "compile" your current version of numpy, but rather installed it from a binary distribution. The approach I gave above would require you to build numpy from source, which is not an easy thing to do in Windows (although there are official instructions here).

A much easier option would be to install one of the unoptimized numpy binaries available from Christoph Gohlke's website here.