code: def window_sumsquare(
      *,
      window: _WindowSpec,
      n_frames: int,
      hop_length: int = 512,
      win_length: Optional[int] = None,
      n_fft: int = 2048,
      dtype: DTypeLike = np.float32,
      norm: Optional[float] = None,
  ) -> np.ndarray:
      """Compute the sum-square envelope of a window function at a given hop length.
  
      This is used to estimate modulation effects induced by windowing observations
      in short-time Fourier transforms.
  
      Parameters
      ----------
      window : string, tuple, number, callable, or list-like
          Window specification, as in `get_window`
      n_frames : int > 0
          The number of analysis frames
      hop_length : int > 0
          The number of samples to advance between frames
      win_length : [optional]
          The length of the window function.  By default, this matches ``n_fft``.
      n_fft : int > 0
          The length of each analysis frame.
      dtype : np.dtype
          The data type of the output
      norm : {np.inf, -np.inf, 0, float > 0, None}
          Normalization mode used in window construction.
          Note that this does not affect the squaring operation.
  
      Returns
      -------
      wss : np.ndarray, shape=``(n_fft + hop_length * (n_frames - 1))``
          The sum-squared envelope of the window function
  
      Examples
      --------
      For a fixed frame length (2048), compare modulation effects for a Hann window
      at different hop lengths:
  
      >>> n_frames = 50
      >>> wss_256 = librosa.filters.window_sumsquare(window='hann', n_frames=n_frames, hop_length=256)
      >>> wss_512 = librosa.filters.window_sumsquare(window='hann', n_frames=n_frames, hop_length=512)
      >>> wss_1024 = librosa.filters.window_sumsquare(window='hann', n_frames=n_frames, hop_length=1024)
  
      >>> import matplotlib.pyplot as plt
      >>> fig, ax = plt.subplots(nrows=3, sharey=True)
      >>> ax[0].plot(wss_256)
      >>> ax[0].set(title='hop_length=256')
      >>> ax[1].plot(wss_512)
      >>> ax[1].set(title='hop_length=512')
      >>> ax[2].plot(wss_1024)
      >>> ax[2].set(title='hop_length=1024')
      """
      if win_length is None:
          win_length = n_fft
  
      n = n_fft + hop_length * (n_frames - 1)
      x = np.zeros(n, dtype=dtype)
  
      # Compute the squared window at the desired length
      win_sq = get_window(window, win_length)
      win_sq = util.normalize(win_sq, norm=norm) ** 2
      win_sq = util.pad_center(win_sq, size=n_fft)
  
      # Fill the envelope
      __window_ss_fill(x, win_sq, n_frames, hop_length)
  
      return x
  
imports: import warnings
  import numpy
  import scipy
  import scipy.signal
  import scipy.ndimage
  from numba import jit
  from ._cache import cache
  from .None import util
  from .util.exceptions import ParameterError
  from .util.decorators import deprecated
  from .core.convert import note_to_hz, hz_to_midi, midi_to_hz, hz_to_octs
  from .core.convert import fft_frequencies, mel_frequencies
  from numpy.typing import ArrayLike, DTypeLike
  from typing import Any, List, Optional, Tuple, Union
  from typing_extensions import Literal
  from ._typing import _WindowSpec, _FloatLike_co
label_desc: Use image node_id 16 for calling a global function with example usage: window_sumsquare() and returns: x