(COLA) constraint is met.

Parameters
----------
window : str or tuple or array_like
    Desired window to use. If `window` is a string or tuple, it is
    passed to `get_window` to generate the window values, which are
    DFT-even by default. See `get_window` for a list of windows and
    required parameters. If `window` is array_like it will be used
    directly as the window and its length must be nperseg.
nperseg : int
    Length of each segment.
noverlap : int
    Number of points to overlap between segments.
tol : float, optional
    The allowed variance of a bin's weighted sum from the median bin
    sum.

Returns
-------
verdict : bool
    `True` if chosen combination satisfies COLA within `tol`,
    `False` otherwise

See Also
--------
check_NOLA: Check whether the Nonzero Overlap Add (NOLA) constraint is met
stft: Short Time Fourier Transform
istft: Inverse Short Time Fourier Transform

Notes
-----
In order to enable inversion of an STFT via the inverse STFT in
`istft`, it is sufficient that the signal windowing obeys the constraint of
"Constant OverLap Add" (COLA). This ensures that every point in the input
data is equally weighted, thereby avoiding aliasing and allowing full
reconstruction.

Some examples of windows that satisfy COLA:
    - Rectangular window at overlap of 0, 1/2, 2/3, 3/4, ...
    - Bartlett window at overlap of 1/2, 3/4, 5/6, ...
    - Hann window at 1/2, 2/3, 3/4, ...
    - Any Blackman family window at 2/3 overlap
    - Any window with ``noverlap = nperseg-1``

A very comprehensive list of other windows may be found in [2]_,
wherein the COLA condition is satisfied when the "Amplitude
Flatness" is unity.

.. versionadded:: 0.19.0

References
----------
.. [1] Julius O. Smith III, "Spectral Audio Signal Processing", W3K
       Publishing, 2011,ISBN 978-0-9745607-3-1.
.. [2] G. Heinzel, A. Ruediger and R. Schilling, "Spectrum and
       spectral density estimation by the Discrete Fourier transform
       (DFT), including a comprehensive list of window functions and
       some new at-top windows", 2002,
       http://hdl.handle.net/11858/00-001M-0000-0013-557A-5

Examples
--------
>>> from scipy import signal

Confirm COLA condition for rectangular window of 75% (3/4) overlap:

>>> signal.check_COLA(signal.windows.boxcar(100), 100, 75)
True

COLA is not true for 25% (1/4) overlap, though:

>>> signal.check_COLA(signal.windows.boxcar(100), 100, 25)
False

"Symmetrical" Hann window (for filter design) is not COLA:

>>> signal.check_COLA(signal.windows.hann(120, sym=True), 120, 60)
False

"Periodic" or "DFT-even" Hann window (for FFT analysis) is COLA for
overlap of 1/2, 2/3, 3/4, etc.:

>>> signal.check_COLA(signal.windows.hann(120, sym=False), 120, 60)
True

>>> signal.check_COLA(signal.windows.hann(120, sym=False), 120, 80)
True

>>> signal.check_COLA(signal.windows.hann(120, sym=False), 120, 90)
True

r