Increase compatibility with numpypy and matplotlib

- numpy/lib/utils.py: get_include() now calls numpypy.get_include().
- numpy/core/fromnumeric.py: Add implementations for np.take() and
  np.ptp().
- numpy/distutils/misc_utip.py: Add comment what was done to
  deactivate building of external modules.
- numpy/f2py/rules.py: Replace array->data calls in wrapper
  generator by PyArray_DATA(array).
Start making f2py PyPy compatible

- numpy/f2py/f90mod_rules.py: Replace "np.intp().itemsize" by
  "np.dtype('intp').itemsize", since the latter is supported by
  PyPy.
- numpy/f2py/src/fortranobject.c: check_and_fix_dimensions():
  Refactor using PyArray_NDIM() and PyArray_DIM() instead of
  direct field access.

Tested by recompiling and testing CPython numpy. Works.
More refactoring of fortranobject.* for PyPy

- const PyArrayObject -> ArrayObject
- Use PyArray_ISCONTIGUOUS(), PyArray_FLAGS()
- Replace PyArray_MultiplyList() by direct loop.
- Deactivate swap_arrays() for now.
- PyArray_Size((PyObject*)arr) -> PyArray_Size(arr).
fortranobject.c compiles now with PyPy

- Manually copy arr->dimensions into array arr_dims[].
- Replace PyArray_FromAny() by PyArray_FROM_OTF(), to avoid the need
  to create a PyArray_Descr instance.
- Replace PyArray_DescrFromType() to investigate element size by
  PyArray_SimpleNew() + PyArray_ITEMSIZE().
- Modify docstrings and error messages that output character codes
  arr->descr->type, which are impossible to get with PyPy.
Reactivate building of lapack_lite

- numpy/linalg/lapack_lite.py: Delete placeholder file.
- numpy/distutils/misc_util.py: Add 'activate' flag to selectively
  activate building of a module. Use in numpy/linalg/setup.py.
  Note that numpy/core/include must be renamed so that the PyPy
  headers are found.
- numpy/core/multiarray.py: Add implemenations for copyto() and
  fastCopyAndTranspose().
- numpy/core/numeric.py: ones(): Use numpypy's implementation.
'setup.py install' works for a clean checkout
merge heads