code: def check_COLA(window, nperseg, noverlap, tol=1e-10):
      r"""Check whether the Constant OverLap Add (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. See [1]_ for more information.
  
      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
  
      """
      nperseg = int(nperseg)
  
      if nperseg < 1:
          raise ValueError("nperseg must be a positive integer")
  
      if noverlap >= nperseg:
          raise ValueError("noverlap must be less than nperseg.")
      noverlap = int(noverlap)
  
      if isinstance(window, str) or type(window) is tuple:
          win = get_window(window, nperseg)
      else:
          win = cupy.asarray(window)
          if len(win.shape) != 1:
              raise ValueError("window must be 1-D")
          if win.shape[0] != nperseg:
              raise ValueError("window must have length of nperseg")
  
      step = nperseg - noverlap
      binsums = sum(
          win[ii * step : (ii + 1) * step]
          for ii in range(nperseg // step)
      )
  
      if nperseg % step != 0:
          binsums[: nperseg % step] += win[-(nperseg % step) :]
  
      deviation = binsums - cupy.median(binsums)
      return cupy.max(cupy.abs(deviation)) < tol
  
file_path: cupy/cupyx/scipy/signal/_spectral.py
imports: import warnings
  import cupy
  from cupyx.scipy.signal.windows._windows import get_window
  from cupyx.scipy.signal._spectral_impl import _lombscargle, _spectral_helper, _median_bias, _triage_segments
label_desc: Use image node_id 5 for calling a global function with example usage: check_COLA(window, nperseg, noverlap, tol) and returns: unknown