To remove in the future –– scipy.interpolate
.. currentmodule:: scipy.interpolate
    
               Sub-package for objects used in interpolation.
As listed below, this sub-package contains spline functions and classes, 1-D and multidimensional (univariate and multivariate) interpolation classes, Lagrange and Taylor polynomial interpolators, and wrappers for FITPACK and DFITPACK functions.
.. autosummary:: 
    :toctree:generated/
    interp1d
    BarycentricInterpolator
    KroghInterpolator
    barycentric_interpolate
    krogh_interpolate
    pchip_interpolate
    CubicHermiteSpline
    PchipInterpolator
    Akima1DInterpolator
    CubicSpline
    PPoly
    BPoly
Unstructured data:
.. autosummary:: 
    :toctree:generated/
    griddata
    LinearNDInterpolator
    NearestNDInterpolator
    CloughTocher2DInterpolator
    RBFInterpolator
    Rbf
    interp2d
               For data on a grid:
.. autosummary:: 
    :toctree:generated/
    interpn
    RegularGridInterpolator
    RectBivariateSpline
               
.. seealso:: 
    `scipy.ndimage.map_coordinates`
               Tensor product polynomials:
.. autosummary:: 
    :toctree:generated/
    NdPPoly
.. autosummary:: 
    :toctree:generated/
    BSpline
    make_interp_spline
    make_lsq_spline
               Functional interface to FITPACK routines:
.. autosummary:: 
    :toctree:generated/
    splrep
    splprep
    splev
    splint
    sproot
    spalde
    splder
    splantider
    insert
               Object-oriented FITPACK interface:
.. autosummary:: 
    :toctree:generated/
    UnivariateSpline
    InterpolatedUnivariateSpline
    LSQUnivariateSpline
For data on a grid:
.. autosummary:: 
    :toctree:generated/
    RectBivariateSpline
    RectSphereBivariateSpline
               For unstructured data:
.. autosummary:: 
    :toctree:generated/
    BivariateSpline
    SmoothBivariateSpline
    SmoothSphereBivariateSpline
    LSQBivariateSpline
    LSQSphereBivariateSpline
               Low-level interface to FITPACK functions:
.. autosummary:: 
    :toctree:generated/
    bisplrep
    bisplev
.. autosummary:: 
    :toctree:generated/
    lagrange
    approximate_taylor_polynomial
    pade
               
.. seealso:: 
    `scipy.ndimage.map_coordinates`,
    `scipy.ndimage.spline_filter`,
    `scipy.signal.resample`,
    `scipy.signal.bspline`,
    `scipy.signal.gauss_spline`,
    `scipy.signal.qspline1d`,
    `scipy.signal.cspline1d`,
    `scipy.signal.qspline1d_eval`,
    `scipy.signal.cspline1d_eval`,
    `scipy.signal.qspline2d`,
    `scipy.signal.cspline2d`.
                       pchip
 is an alias of PchipInterpolator
 for backward compatibility (should not be used in new code).
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.interpolate._fitpack2.UnivariateSpline.integralscipy.interpolate._fitpack2.UnivariateSpline.derivativesscipy.interpolate._pade.padescipy.interpolate._fitpack_py.splantiderscipy.interpolate._polyint.krogh_interpolatescipy.interpolate._cubic.pchip_interpolatescipy.interpolate._bsplines.BSplinescipy.interpolate._ndgriddata.NearestNDInterpolatorscipy.interpolate._polyint.KroghInterpolatorscipy.interpolate._fitpack_py.insertscipy.interpolate._bsplines.make_lsq_splinescipy.interpolate._fitpack2.UnivariateSpline.derivativescipy.interpolate._rbf.Rbfscipy.interpolate._fitpack2.UnivariateSpline.antiderivativescipy.interpolate._interpolate.RegularGridInterpolatorscipy.interpolate._fitpack_py.splderscipy.interpolate._fitpack2.LSQUnivariateSplinescipy.interpolate._fitpack2.UnivariateSplinescipy.interpolate._bsplines.BSpline.integratescipy.interpolate._fitpack2.RectSphereBivariateSplinescipy.interpolate._polyint.barycentric_interpolatescipy.interpolate._polyint._Interpolator1DWithDerivatives.derivativesscipy.interpolate._ndgriddata.griddatascipy.interpolate._fitpack_impl.splrepscipy.interpolate._interpolate.lagrangescipy.special._ellip_harm.ellip_harmscipy.interpolate._interpolate.PPoly.solvescipy.interpolate._fitpack2.LSQSphereBivariateSplinescipy.interpolate._fitpack2.SmoothSphereBivariateSplinescipy.interpolate._polyint.approximate_taylor_polynomialscipy.interpolate._interpolate.interpnscipy.interpolate._fitpack_impl.splantiderscipy.interpolate._fitpack2.InterpolatedUnivariateSplinescipy.interpolate._fitpack_py.splrepscipy.interpolate._cubic.CubicSplinescipy.interpolate._interpolate.interp2dscipy.interpolate._interpolate.BPolyscipy.interpolate.interpnd.LinearNDInterpolatorscipy.interpolate._rbfinterp.RBFInterpolatorscipy.interpolate._interpolate.interp1dscipy.interpolate._fitpack_impl.splderscipy.interpolate._bsplines.make_interp_splineHover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them