code: def _compute_mt_params(
      n_times, sfreq, bandwidth, low_bias, adaptive, verbose=None
  ):
      """Triage windowing and multitaper parameters."""
      # Compute standardized half-bandwidth
      if isinstance(bandwidth, str):
          logger.info(
              '    Using standard spectrum estimation with "%s" window'
              % (bandwidth,)
          )
          window_fun = get_window(bandwidth, n_times)[np.newaxis]
          return window_fun, np.ones(1), False
  
      if bandwidth is not None:
          half_nbw = float(bandwidth) * n_times / (2.0 * sfreq)
      else:
          half_nbw = 4.0
      if half_nbw < 0.5:
          raise ValueError(
              "bandwidth value %s yields a normalized half-bandwidth of "
              "%s < 0.5, use a value of at least %s"
              % (bandwidth, half_nbw, sfreq / n_times)
          )
  
      # Compute DPSS windows
      n_tapers_max = int(2 * half_nbw)
      window_fun, eigvals = dpss_windows(
          n_times, half_nbw, n_tapers_max, sym=False, low_bias=low_bias
      )
      logger.info(
          "    Using multitaper spectrum estimation with %d DPSS "
          "windows" % len(eigvals)
      )
  
      if adaptive and len(eigvals) < 3:
          warn(
              "Not adaptively combining the spectral estimators due to a "
              "low number of tapers (%s < 3)." % (len(eigvals),)
          )
          adaptive = False
  
      return window_fun, eigvals, adaptive
  
file_path: mne-python/mne/time_frequency/multitaper.py
imports: import numpy
  from scipy.fft import rfft, rfftfreq
  from scipy.integrate import trapezoid
  from scipy.signal import get_window
  from scipy.signal.windows import dpss
  from ..parallel import parallel_func
  from ..utils import _check_option, logger, verbose, warn
label_desc: Use image node_id 6 for calling a global function with example usage: _compute_mt_params(n_times, sfreq, bandwidth, low_bias, adaptive, verbose) and returns: window_fun,  eigvals,  adaptive, window_fun,  np,  False