code: def _histogram_binsize_weighted(a, w, start, width, n):
      
      return flib.weighted_fixed_binsize(a, w, start, width, n)
docs: histogram_even_weighted(a, start, width, n) -> histogram
  
      Return an histogram where the first bin counts the number of lower
      outliers and the last bin the number of upper outliers. Works only with
      fixed width bins.
  
      :Stochastics:
        a : array
          Array of samples.
        w : array
          Weights of samples.
        start : float
          Left-most bin edge.
        width : float
          Width of the bins. All bins are considered to have the same width.
        n : int
          Number of bins.
  
      :Return:
        H : array
          Array containing the number of elements in each bin. H[0] is the number
          of samples smaller than start and H[-1] the number of samples
          greater than start + n*width.