class_docstr: Rbf(*args)
  
  A class for radial basis function interpolation of functions from
  N-D scattered data to an M-D domain.
  
  .. note::
      `Rbf` is legacy code, for new usage please use `RBFInterpolator`
      instead.
  
  Parameters
  ----------
  *args : arrays
      x, y, z, ..., d, where x, y, z, ... are the coordinates of the nodes
      and d is the array of values at the nodes
  function : str or callable, optional
      The radial basis function, based on the radius, r, given by the norm
      (default is Euclidean distance); the default is 'multiquadric'::
  
          'multiquadric': sqrt((r/self.epsilon)**2 + 1)
          'inverse': 1.0/sqrt((r/self.epsilon)**2 + 1)
          'gaussian': exp(-(r/self.epsilon)**2)
          'linear': r
          'cubic': r**3
          'quintic': r**5
          'thin_plate': r**2 * log(r)
  
      If callable, then it must take 2 arguments (self, r). The epsilon
      parameter will be available as self.epsilon. Other keyword
      arguments passed in will be available as well.
  
  epsilon : float, optional
      Adjustable constant for gaussian or multiquadrics functions
      - defaults to approximate average distance between nodes (which is
      a good start).
  smooth : float, optional
      Values greater than zero increase the smoothness of the
      approximation. 0 is for interpolation (default), the function will
      always go through the nodal points in this case.
  norm : str, callable, optional
      A function that returns the 'distance' between two points, with
      inputs as arrays of positions (x, y, z, ...), and an output as an
      array of distance. E.g., the default: 'euclidean', such that the result
      is a matrix of the distances from each point in ``x1`` to each point in
      ``x2``. For more options, see documentation of
      `scipy.spatial.distances.cdist`.
  mode : str, optional
      Mode of the interpolation, can be '1-D' (default) or 'N-D'. When it is
      '1-D' the data `d` will be considered as 1-D and flattened
      internally. When it is 'N-D' the data `d` is assumed to be an array of
      shape (n_samples, m), where m is the dimension of the target domain.
  
  
  Attributes
  ----------
  N : int
      The number of data points (as determined by the input arrays).
  di : ndarray
      The 1-D array of data values at each of the data coordinates `xi`.
  xi : ndarray
      The 2-D array of data coordinates.
  function : str or callable
      The radial basis function. See description under Parameters.
  epsilon : float
      Parameter used by gaussian or multiquadrics functions. See Parameters.
  smooth : float
      Smoothing parameter. See description under Parameters.
  norm : str or callable
      The distance function. See description under Parameters.
  mode : str
      Mode of the interpolation. See description under Parameters.
  nodes : ndarray
      A 1-D array of node values for the interpolation.
  A : internal property, do not use
  
  See Also
  --------
  RBFInterpolator
  
  Examples
  --------
  >>> from scipy.interpolate import Rbf
  >>> rng = np.random.default_rng()
  >>> x, y, z, d = rng.random((4, 50))
  >>> rbfi = Rbf(x, y, z, d)  # radial basis function interpolator instance
  >>> xi = yi = zi = np.linspace(0, 1, 20)
  >>> di = rbfi(xi, yi, zi)   # interpolated values
  >>> di.shape
  (20,)
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code: def A(self):
      # this only exists for backwards compatibility: self.A was available
      # and, at least technically, public.
      r = squareform(pdist(self.xi.T, self.norm))  # Pairwise norm
      return self._init_function(r) - np.eye(self.N) * self.smooth
  
file_path: catboost/contrib/python/scipy/py3/scipy/interpolate/rbf.py
imports: import numpy
  from scipy import linalg
  from scipy.special import xlogy
  from scipy.spatial.distance import cdist, pdist, squareform
label_desc: Use image node_id 10 for calling the Rbf obj's underlying member method code with example usage: obj.A() and returns: unknown