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scipy.interpolate.BivariateSpline.__call__

# scipy.interpolate.BivariateSpline

class `scipy.interpolate.``BivariateSpline`

  Base class for bivariate splines.

  This describes a spline `s(x, y)` of degrees `kx` and `ky` on the rectangle `[xb, xe] * [yb, ye]` calculated from a given set of data points `(x, y, z)`.

  This class is meant to be subclassed, not instantiated directly. To construct these splines, call either `SmoothBivariateSpline` or `LSQBivariateSpline`.

  See also

  `UnivariateSpline`
    a similar class for univariate spline interpolation
  `SmoothBivariateSpline`
    to create a BivariateSpline through the given points
  `LSQBivariateSpline`
    to create a BivariateSpline using weighted least-squares fitting
  `SphereBivariateSpline`
    bivariate spline interpolation in spherical cooridinates
  `bisplrep`
    older wrapping of FITPACK
  `bisplev`
    older wrapping of FITPACK

  Methods

  `__call__`(x, y[, mth, dx, dy, grid]) | Evaluate the spline or its derivatives at given positions.
  `ev`(xi, yi[, dx, dy]) | Evaluate the spline at points Returns the interpolated value at `(xi[i], yi[i]), i=0,...,len(xi)-1`.
  `get_coeffs`() | Return spline coefficients.
  `get_knots`() | Return a tuple (tx,ty) where tx,ty contain knots positions of the spline with respect to x-, y-variable, respectively.
  `get_residual`() | Return weighted sum of squared residuals of the spline
  `integral`(xa, xb, ya, yb) | Evaluate the integral of the spline over area [xa,xb] x [ya,yb].