package scipy

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package scipy
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type tag = [
  1. | `BivariateSpline
]
type t = [ `BivariateSpline | `Object ] Obj.t
val of_pyobject : Py.Object.t -> t
val to_pyobject : [> tag ] Obj.t -> Py.Object.t
val create : unit -> t

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 bivariate spline through the given points LSQBivariateSpline : to create a bivariate spline using weighted least-squares fitting RectSphereBivariateSpline : to create a bivariate spline over a rectangular mesh on a sphere SmoothSphereBivariateSpline : to create a smooth bivariate spline in spherical coordinates LSQSphereBivariateSpline : to create a bivariate spline in spherical coordinates using weighted least-squares fitting bisplrep : older wrapping of FITPACK bisplev : older wrapping of FITPACK

val ev : ?dx:int -> ?dy:int -> xi:Py.Object.t -> yi:Py.Object.t -> [> tag ] Obj.t -> Py.Object.t

Evaluate the spline at points

Returns the interpolated value at ``(xii, yii), i=0,...,len(xi)-1``.

Parameters ---------- xi, yi : array_like Input coordinates. Standard Numpy broadcasting is obeyed. dx : int, optional Order of x-derivative

.. versionadded:: 0.14.0 dy : int, optional Order of y-derivative

.. versionadded:: 0.14.0

val get_coeffs : [> tag ] Obj.t -> Py.Object.t

Return spline coefficients.

val get_knots : [> tag ] Obj.t -> Py.Object.t

Return a tuple (tx,ty) where tx,ty contain knots positions of the spline with respect to x-, y-variable, respectively. The position of interior and additional knots are given as tk+1:-k-1 and t:k+1=b, t-k-1:=e, respectively.

val get_residual : [> tag ] Obj.t -> Py.Object.t

Return weighted sum of squared residuals of the spline approximation: sum ((wi*(zi-s(xi,yi)))**2,axis=0)

val integral : xa:Py.Object.t -> xb:Py.Object.t -> ya:Py.Object.t -> yb:Py.Object.t -> [> tag ] Obj.t -> float

Evaluate the integral of the spline over area xa,xb x ya,yb.

Parameters ---------- xa, xb : float The end-points of the x integration interval. ya, yb : float The end-points of the y integration interval.

Returns ------- integ : float The value of the resulting integral.

val to_string : t -> string

Print the object to a human-readable representation.

val show : t -> string

Print the object to a human-readable representation.

val pp : Stdlib.Format.formatter -> t -> unit

Pretty-print the object to a formatter.