# scipy.interpolate.interp2d.__call__

interp2d.__call__(x, y, dx=0, dy=0, assume_sorted=False)

  `interp2d` is deprecated! `interp2d` is deprecated in SciPy 1.10 and will be removed in SciPy 1.13.0.

  For legacy code, nearly bug-for-bug compatible replacements are `RectBivariateSpline` on regular grids, and `bisplrep`/`bisplev` for scattered 2D data.

  In new code, for regular grids use `RegularGridInterpolator` instead. For scattered data, prefer `LinearNDInterpolator` or `CloughTocher2DInterpolator`.

  For more details see https://scipy.github.io/devdocs/notebooks/interp_transition_guide.html

  Interpolate the function.

  Parameters:
    x 1-D array

      x-coordinates of the mesh on which to interpolate.

    y 1-D array

      y-coordinates of the mesh on which to interpolate.

    dx int >= 0, < kx

      Order of partial derivatives in x.

    dy int >= 0, < ky

      Order of partial derivatives in y.

    assume_sorted bool, optional

      If False, values of x and y can be in any order and they are sorted first. If True, x and y have to be arrays of monotonically increasing values.

  Returns:
    z 2-D array with shape (len(y), len(x))

      The interpolated values.