code: def hz_to_mel(frequencies, htk=False):
      """Convert Hz to Mels
      Examples
      --------
      >>> librosa.hz_to_mel(60)
      0.9
      >>> librosa.hz_to_mel([110, 220, 440])
      array([ 1.65,  3.3 ,  6.6 ])
      Parameters
      ----------
      frequencies   : number or np.ndarray [shape=(n,)] , float
          scalar or array of frequencies
      htk           : bool
          use HTK formula instead of Slaney
      Returns
      -------
      mels        : number or np.ndarray [shape=(n,)]
          input frequencies in Mels
      See Also
      --------
      mel_to_hz
      """
  
      frequencies = np.asanyarray(frequencies)
  
      if htk:
          return 2595.0 * np.log10(1.0 + frequencies / 700.0)
  
      # Fill in the linear part
      f_min = 0.0
      f_sp = 200.0 / 3
  
      mels = (frequencies - f_min) / f_sp
  
      # Fill in the log-scale part
  
      min_log_hz = 1000.0  # beginning of log region (Hz)
      min_log_mel = (min_log_hz - f_min) / f_sp  # same (Mels)
      logstep = np.log(6.4) / 27.0  # step size for log region
  
      if frequencies.ndim:
          # If we have array data, vectorize
          log_t = frequencies >= min_log_hz
          mels[log_t] = (
              min_log_mel
              + np.log(frequencies[log_t] / min_log_hz) / logstep
          )
      elif frequencies >= min_log_hz:
          # If we have scalar data, heck directly
          mels = (
              min_log_mel + np.log(frequencies / min_log_hz) / logstep
          )
  
      return mels
  
file_path: nnAudio/Installation/nnAudio/librosa_functions.py
imports: import numpy
  import warnings
label_desc: Use image node_id 4 for calling a global function with example usage: hz_to_mel(frequencies, htk) and returns: mels, unknown