y ( ( P , N ) array_like ) – Data point coordinates.

d ( ( P , ... ) array_like ) – Data values at y .

neighbors ( int , optional ) – If specified, the value of the interpolant at each evaluation point will be computed using only this many nearest data points. All the data points are used by default.

smoothing ( float or ( P , ) array_like , optional ) – Smoothing parameter. The interpolant perfectly fits the data when this is set to 0. For large values, the interpolant approaches a least squares fit of a polynomial with the specified degree. Default is 0.

kernel ( str , optional ) –

Type of RBF. This should be one of

’linear’ : -r

’thin_plate_spline’ : r**2 * log(r)

’cubic’ : r**3

’quintic’ : -r**5

’multiquadric’ : -sqrt(1 + r**2)

’inverse_multiquadric’ : 1/sqrt(1 + r**2)

’inverse_quadratic’ : 1/(1 + r**2)

’gaussian’ : exp(-r**2)

epsilon ( float , optional ) – Shape parameter that scales the input to the RBF. If kernel is ‘linear’, ‘thin_plate_spline’, ‘cubic’, or ‘quintic’, this defaults to 1 and can be ignored because it has the same effect as scaling the smoothing parameter. Otherwise, this must be specified.

degree ( int , optional ) –

Degree of the added polynomial. For some RBFs the interpolant may not be well-posed if the polynomial degree is too small. Those RBFs and their corresponding minimum degrees are

’multiquadric’ : 0

’linear’ : 0

’thin_plate_spline’ : 1

’cubic’ : 1

’quintic’ : 2

\(P(y)\) must have full column rank. \(P(y)\) always has full column rank when degree is -1 or 0. When degree is 1, \(P(y)\) has full column rank if the data point locations are not all collinear (N=2), coplanar (N=3), etc.

If kernel is ‘multiquadric’, ‘linear’, ‘thin_plate_spline’, ‘cubic’, or ‘quintic’, then degree must not be lower than the minimum value listed above.

If smoothing is 0, then each data point location must be distinct.