Re: [eigen] eigen based splines
• To: eigen@xxxxxxxxxxxxxxxxxxx
• Subject: Re: [eigen] eigen based splines
• Date: Wed, 17 Feb 2010 17:01:54 +0300

```Hey very cool stuff!  I want a more in-depth look at the conference!

A

On Wed, Feb 17, 2010 at 4:57 PM, Hauke Heibel
<hauke.heibel@xxxxxxxxxxxxxx> wrote:
> Hi,
>
> I created a fork with an initial implementation of Eigen based
> B-Splines. It is located over here:
> http://bitbucket.org/hauke/eigen_splines/
>
> The splines have three template parameters; Scalar type, dimension and
> (optional) degree. Manually defining the degree allows us to prevent
> heap allocations.
>
> Currently I have implemented the following functions (ReturnByValue
> will be abbreviated as rbv):
>
> --------------------
>
> /* ctor */
> Spline::Spline(const Vec& knots, const Mat& ctrls)
> template <int OtherDegree>
> Spline::Spline(const Spline<Scalar, Dimension, OtherDegree>& spline)
>
> /* const access */
> const Vec& Spline::knots() const
> const Mat& Spline::ctrls() const
>
> /* spline value */
> rbv Spline::operator(Scalar u) const
>
> /* derivative order+1 derivative points */
> rbv Spline::getDerValues(Scalar u, int order) const
>
> /* no heap allocs, derivative order+1 derivative points */
> template <int DerivativeOrder>
> rbv Spline::getDerValues(Scalar u, int order = DerivativeOrder)
>
> /* non-zero basis functions */
> rbv Spline::basisFunctions(Scalar u) const
>
> /* (order+1) - by - (degree+1) non-zero basis function derivatives */
> rbv Spline::basisFunctionDerivatives(Scalar u, int order)
>
> /* no heap allocs, (order+1) - by - (degree+1) non-zero basis function
> derivatives */
> tempalte <int DerivativeOrder>
> rbv Spline::basisFunctionDerivatives(Scalar u, int order = DerivativeOrder)
>
> int Spline::degree() const
> int Spline::span(Scalar u) const
>
> --------------------
>
> I'll be adding least-squares fitting soon and I am happy regarding any
> kind of feedback and proposals regarding the interface...
>
> Cheers,
> Hauke
>
>
>

```

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