# Interpolation (`cupyx.scipy.interpolate`)#

## Univariate interpolation#

 `BarycentricInterpolator`(xi[, yi, axis]) The interpolating polynomial for a set of points. `KroghInterpolator`(xi, yi[, axis]) Interpolating polynomial for a set of points. `barycentric_interpolate`(xi, yi, x[, axis]) Convenience function for polynomial interpolation. `krogh_interpolate`(xi, yi, x[, der, axis]) Convenience function for polynomial interpolation `pchip_interpolate`(xi, yi, x[, der, axis]) Convenience function for pchip interpolation. `CubicHermiteSpline`(x, y, dydx[, axis, ...]) Piecewise-cubic interpolator matching values and first derivatives. `PchipInterpolator`(x, y[, axis, extrapolate]) PCHIP 1-D monotonic cubic interpolation. `Akima1DInterpolator`(x, y[, axis]) Akima interpolator `PPoly`(c, x[, extrapolate, axis]) Piecewise polynomial in terms of coefficients and breakpoints The polynomial between `x[i]` and `x[i + 1]` is written in the local power basis. `BPoly`(c, x[, extrapolate, axis]) Piecewise polynomial in terms of coefficients and breakpoints. `CubicSpline`(x, y[, axis, bc_type, extrapolate]) Cubic spline data interpolator. `interp1d`(x, y[, kind, axis, copy, ...]) Interpolate a 1-D function.

## 1-D Splines#

 `BSpline`(t, c, k[, extrapolate, axis]) Univariate spline in the B-spline basis. `make_interp_spline`(x, y[, k, t, bc_type, ...]) Compute the (coefficients of) interpolating B-spline. `make_lsq_spline`(x, y, t[, k, w, axis, ...]) Construct a BSpline via an LSQ (Least SQuared) fit. `splder`(tck[, n]) Compute the spline representation of the derivative of a given spline `splantider`(tck[, n]) Compute the spline for the antiderivative (integral) of a given spline.

## Smoothing Splines#

 `UnivariateSpline`(x, y[, w, bbox, k, s, ext]) 1-D smoothing spline fit to a given set of data points. `InterpolatedUnivariateSpline`(x, y[, w, ...]) 1-D interpolating spline for a given set of data points. `LSQUnivariateSpline`(x, y, t[, w, bbox, k, ext]) 1-D spline with explicit internal knots.

## Multivariate interpolation#

Unstructured data:

 `LinearNDInterpolator`(points, values[, ...]) Piecewise linear interpolant in N > 1 dimensions. `NearestNDInterpolator`(x, y[, rescale, ...]) NearestNDInterpolator(x, y). `CloughTocher2DInterpolator`(points, values[, ...]) CloughTocher2DInterpolator(points, values, tol=1e-6). `RBFInterpolator`(y, d[, neighbors, ...]) Radial basis function (RBF) interpolation in N dimensions.

For data on a grid:

 `interpn`(points, values, xi[, method, ...]) Multidimensional interpolation on regular or rectilinear grids. `RegularGridInterpolator`(points, values[, ...]) Interpolator on a regular or rectilinear grid in arbitrary dimensions.

Tensor product polynomials:

 `NdPPoly`(c, x[, extrapolate]) Piecewise tensor product polynomial `NdBSpline`(t, c, k, *[, extrapolate]) Tensor product spline object.