code: def gaussian_radial_kernel(distance, bandwidth=1.0):
      """Gaussian radial kernel.
  
      Parameters
      ----------
      distance : array-like
          Array of non-negative real values.
      bandwidth : float, optional (default=1.0)
          Positive scale parameter of the kernel.
  
      Returns
      -------
      weight : array-like
          Array of non-negative real values of the same shape than
          parameter 'distance'.
  
      References
      ----------
      .. [1] https://en.wikipedia.org/wiki/Kernel_(statistics)
      .. [2] https://en.wikipedia.org/wiki/Radial_basis_function
      """
      distance = _check_distance(distance)
      bandwidth = _check_bandwidth(bandwidth)
      scaled_distance = distance / bandwidth
      weight = gs.exp(-(scaled_distance**2) / 2)
      return weight
  
file_path: geomstats/geomstats/learning/radial_kernel_functions.py
imports: import geomstats.backend
label_desc: Use image node_id 9 for calling a global function with example usage: gaussian_radial_kernel(distance, bandwidth) and returns: weight