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newknots = newknt(f,newl)
newknt(f)
[...,distfn] = newknt(...)
newknots = newknt(f,newl) returns the knot sequence whose interior knots cut the basic interval of f into newl pieces, in such a way that a certain piecewise linear monotone function related to the high derivative of f is equidistributed.
The intent is to choose a knot sequence suitable to the fine
approximation of a function
whose rough approximation in f is
assumed to contain enough information about
to make this
feasible.
newknt(f) uses for newl its default value, namely the number of polynomial pieces in f.
[...,distfn] = newknt(...) also returns, in distfn, the ppform of that piecewise linear monotone function being equidistributed.
If the error in the least-squares approximation sp to some data x,y by a spline of order k seems uneven, you might try for a more equitable distribution of knots by using
spap2(newknt(sp),k,x,y);
For another example, see the last part of the demo "Solving an ODE by Collocation".
This is the Fortran routine NEWNOT in PGS. With
the order of the piecewise-polynomial
function
in pp, the function
is approximated
by a piecewise constant function obtained by local, discrete, differentiation of the variation of
. The new break
sequence is chosen to subdivide the basic interval of the piecewise-polynomial
in such a way
that
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![]() | knt2brk, knt2mlt | optknt | ![]() |

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