code: def check_NOLA(window, nperseg, noverlap, tol=1e-10):
      r"""Check whether the Nonzero Overlap Add (NOLA) 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 the NOLA constraint within
          `tol`, `False` otherwise
  
      See Also
      --------
      check_COLA: Check whether the Constant OverLap Add (COLA) 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`, the signal windowing must obey the constraint of "nonzero
      overlap add" (NOLA):
  
      .. math:: \sum_{t}w^{2}[n-tH] \ne 0
  
      for all :math:`n`, where :math:`w` is the window function, :math:`t` is the
      frame index, and :math:`H` is the hop size (:math:`H` = `nperseg` -
      `noverlap`).
  
      This ensures that the normalization factors in the denominator of the
      overlap-add inversion equation are not zero. Only very pathological windows
      will fail the NOLA constraint.
  
      See [1]_, [2]_ 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")
      if noverlap < 0:
          raise ValueError("noverlap must be a nonnegative integer")
      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] ** 2
          for ii in range(nperseg // step)
      )
  
      if nperseg % step != 0:
          binsums[: nperseg % step] += win[-(nperseg % step) :] ** 2
  
      return cupy.min(binsums) > 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 6 for calling a global function with example usage: check_NOLA(window, nperseg, noverlap, tol) and returns: unknown