docs: def histogram_cumulative(data,**kwargs):
    r'''
  Compute cumulative histogram.
  See `numpy.histrogram <https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram.html>`_
  
  :extra options:
  
    **return_edges** ([``True``] | [``False``])
      Return the bin edges if set to ``True``, return their midpoints otherwise.
  
    **normalize** ([``False``] | ``True``)
      Normalize such that the final probability is one. In this case the function returns the (binned)
      cumulative probability density.
    '''
  
    return_edges = kwargs.pop('return_edges', True)
  
    norm = kwargs.pop('normalize', False)
  
    P, edges = np.histogram(data, **kwargs)
  
    P = np.cumsum(P)
  
    if norm: P = P/P[-1]
  
    if not return_edges: edges = np.diff(edges) / 2. + edges[:-1]
  
    return P, edges