code: def hist(signal, nbins=10, r=1):
      """Computes histogram of the signal.
  
      Feature computational cost: 1
  
      Parameters
      ----------
      signal : nd-array
          Input from histogram is computed
      nbins : int
          The number of equal-width bins in the given range
      r : float
          The lower(-r) and upper(r) range of the bins
  
      Returns
      -------
      nd-array
          The values of the histogram
  
      """
      histsig, bin_edges = np.histogram(
          signal, bins=nbins, range=[-r, r]
      )  # TODO:subsampling parameter
  
      return tuple(histsig)
  
imports: import scipy.signal
  from tsfel.feature_extraction.features_utils import *
label_desc: Use image node_id 18 for calling a global function with example usage: hist(signal, nbins, r) and returns: tuple