package scipy

  1. Overview
  2. Docs
package scipy
Legend:
Library
Module
Module type
Parameter
Class
Class type
type tag = [
  1. | `LSQBivariateSpline
]
type t = [ `LSQBivariateSpline | `Object ] Obj.t
val of_pyobject : Py.Object.t -> t
val to_pyobject : [> tag ] Obj.t -> Py.Object.t
val create : ?w:[> `Ndarray ] Np.Obj.t -> ?bbox:Py.Object.t -> ?kx:Py.Object.t -> ?ky:Py.Object.t -> ?eps:float -> x:Py.Object.t -> y:Py.Object.t -> z:Py.Object.t -> tx:Py.Object.t -> ty:Py.Object.t -> unit -> t

Weighted least-squares bivariate spline approximation.

Parameters ---------- x, y, z : array_like 1-D sequences of data points (order is not important). tx, ty : array_like Strictly ordered 1-D sequences of knots coordinates. w : array_like, optional Positive 1-D array of weights, of the same length as `x`, `y` and `z`. bbox : (4,) array_like, optional Sequence of length 4 specifying the boundary of the rectangular approximation domain. By default, ``bbox=min(x,tx),max(x,tx), min(y,ty),max(y,ty)``. kx, ky : ints, optional Degrees of the bivariate spline. Default is 3. eps : float, optional A threshold for determining the effective rank of an over-determined linear system of equations. `eps` should have a value between 0 and 1, the default is 1e-16.

See Also -------- bisplrep : an older wrapping of FITPACK bisplev : an older wrapping of FITPACK UnivariateSpline : a similar class for univariate spline interpolation SmoothBivariateSpline : create a smoothing BivariateSpline

Notes ----- The length of `x`, `y` and `z` should be at least ``(kx+1) * (ky+1)``.

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 : Format.formatter -> t -> unit

Pretty-print the object to a formatter.

OCaml

Innovation. Community. Security.

GitHub Discord Twitter Peertube RSS
About
Changelog Releases Industrial Users Academic Users Why OCaml
Ecosystem
Packages Community Events OCaml Planet Jobs
Resources
Install OCaml Get Started Platform Tools Language Manual Standard Library API Books Exercises Papers OCaml Playground Logo
Policies
Carbon Footprint Governance Privacy Code of Conduct