tmdsimpy.postprocess.continuation.hermite_interp

tmdsimpy.postprocess.continuation.hermite_interp(XlamP_full, XlamP_grad_full, lams)

Use cubic Hermite splines to interpolate solutions to new points.

Parameters:

XlamP_full(M, N) numpy.ndarray

Solution points calculated with continuation. First dimension corresponds to M individual solutions. Second dimension corresponds to degrees of freedom at each solution point (N). The last column corresponds to the continuation control parameter lam and must be monotonically increasing for this function.

XlamP_grad_full(M, N) numpy.ndarray

Gradients (prediction directions) at each of the continuation steps. The last column corresponds to the continuation control parameter lam and must be strictly greater than 0 for this function.

lams(Minterp,) numpy.ndarray

Values of the last variable of XlamP to interpolate solutions to. In other words, XlamP_interp[:, -1] = lams.

Returns:

XlamP_interp(Minterp, N) numpy.ndarray

Solutions at interpolated points.

See also

hermite_upsample

Cubic Hermite Spline interpolation function that adds more points.

linear_interp

Linear interpolation function with similar format.

Notes

The use of cubic spline interpolation may result in artificial effects if the interpolated function is not smooth and well behaved.