Adds sentence to the top of routines.fft.html explaining that scipy.fft
is a more comprehensive collection, per mailing list discussion
(http://numpy-discussion.10968.n7.nabble.com/Add-Chebyshev-cosine-transforms-implemented-via-FFTs-td48373.html#a48382)

The kwarg option norm=inverse leads to scaling of the transforms
inverse (opposite) to that of the default option norm=None; i.e. the
forward transform is normalized with 1/n whereas the backward one
with 1. The fft routines and their tests have been modified to
reflect the changes; all tests have been passed successfully.

Closes #16126

* modified _unitary, fft & ifft and their tests; tests passed

* modified rfft & irfft and their tests; tests passed

* modified hfft & ihfft and all tests; all modifications are now done

* correction in ihfft; all 79 fft tests passed successfully

* undo unnecessary docstrings changes made in my previous commits

* use norm=forward kwarg value name

* Update numpy/fft/__init__.py

Co-authored-by: Leo Fang <leofang@bnl.gov>

* add code review suggestions

Co-authored-by: Leo Fang <leofang@bnl.gov>

* add default norm=None alias norm=backward

* streamline private normalization functions

* modify hermitian FFTs

* add review suggestions

Co-authored-by: Leo Fang <leofang@bnl.gov>

* add review suggestions v2 (dict as module const)

* make review suggestions v3

* Apply suggestions from code review

Co-authored-by: Leo Fang <leofang@bnl.gov>

As numpy is Python 3 only, these import statements are now unnecessary
and don't alter runtime behavior.

* DOC: Note FFT type promotion

The NumPy FFT implementation will promote `float32` types to `float64` types. This may not be desired for some applications, but the SciPy implementation supports more data types.

Closes #14892

These aren't public, and should have been added with underscores.

pytesttester is used by every single subpackage, so making it depend on np.testing just creates cyclic dependencies that can lead to circular imports

Relates to #11457

Numpy can now be tested using the standard

    `python -c"import numpy; numpy.test()"`

construct.

The "bench" testing with the old bench files is no longer supported.
These days we use `runtests.py` and `asv`.