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From: <Rom...@ao...> - 2006-03-16 18:34:06
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Hi everyone
Since I wrote an N-dimensional cubic spline class back in 2003, I have
developed a framework for N-dimensional algoriths that allows incorporation of a
widely divergent set of 1-dimensional algorithms.into it. For example within
the library I have developed so far such entirely diffferent algoriths as
quintic_hermite interpolation and rational polinomial interpolation can be
chosen by the user to interpolate the same set of tabulated data. ...
Tthis programatic framework is implemented as a template class
instantiated using 1-dimensional algorithms along with number of dimensions as its
template parameters. The library features a uniform user friendly interface.
Thus the user, instead of going through the tedium of plugging the same set of
data into different algorithms for can choose and run any algorithm
implemented within the framework by choosing between a few typedefs. The choice of
an algorithb becomes a matte of a few clics of the mouth.
Among the algorithsI have implemented so far within this framework are
the following:
multi-linear interpolation, natural cubic spline interpolation; clamped
cubic spline interpolation, monotonicity preserving clamped cubic spline
interpolation, polinomial interpolation, rational polinomial interpolation,
cubic-hermite and quintic-hermite spline.
Also, since quintic-hermite spline implementation takes cubic spline as
its template parameter that means that the user have a choice of 3 flavors of
quintic-hermite spline.
Besides , every algorithm that uses second detivatives is implemented
in two ways: one that calculates second derivatives globally when memory is
not an issue, and locally when memory is at premium.
Though it may sound counterintuitive, this united approach to
implementation of different algorithms within united framework, besides being user
friendly, also made each of the library's implementations more efficient.
For example N-dimensional cubic spline as implemented within this
framework runs few times faster than the one currewntly implemented in the Quantlib
library, and on top of that the library as a whole and this the library's
cubic spline implementation's in particular features vastly improved memory
management.
I hope this library can be incorporated into the Quntlib.
Any feedback is welcome..
Roman Gitlin
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From: Toyin A. <toy...@ho...> - 2006-03-17 10:04:58
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Hi, I think this would be a great addition to quantlib. Any chance of sending me a copy of the library (source code) with some test code so that I can play with it a bit? This should be great, for example, for the extrapolation of volatility data from a 2D grid (maturity/strike) or (maturity/underlying length). Toy out. >From: Rom...@ao... >To: qua...@li... >Subject: [Quantlib-dev] Re: N-dimensional interpolation template library >Date: Thu, 16 Mar 2006 13:33:47 EST > > >Hi everyone > >Since I wrote an N-dimensional cubic spline class back in 2003, I have >developed a framework for N-dimensional algoriths that allows >incorporation of a >widely divergent set of 1-dimensional algorithms.into it. For example >within >the library I have developed so far such entirely diffferent algoriths as >quintic_hermite interpolation and rational polinomial interpolation can be >chosen by the user to interpolate the same set of tabulated data. ... > Tthis programatic framework is implemented as a template class >instantiated using 1-dimensional algorithms along with number of >dimensions as its >template parameters. The library features a uniform user friendly >interface. >Thus the user, instead of going through the tedium of plugging the same >set of >data into different algorithms for can choose and run any algorithm >implemented within the framework by choosing between a few typedefs. The >choice of >an algorithb becomes a matte of a few clics of the mouth. > Among the algorithsI have implemented so far within this framework >are >the following: >multi-linear interpolation, natural cubic spline interpolation; clamped >cubic spline interpolation, monotonicity preserving clamped cubic spline >interpolation, polinomial interpolation, rational polinomial >interpolation, >cubic-hermite and quintic-hermite spline. > Also, since quintic-hermite spline implementation takes cubic spline >as >its template parameter that means that the user have a choice of 3 flavors >of >quintic-hermite spline. > Besides , every algorithm that uses second detivatives is >implemented >in two ways: one that calculates second derivatives globally when memory >is >not an issue, and locally when memory is at premium. > Though it may sound counterintuitive, this united approach to >implementation of different algorithms within united framework, besides >being user >friendly, also made each of the library's implementations more efficient. > For example N-dimensional cubic spline as implemented within this >framework runs few times faster than the one currewntly implemented in >the Quantlib >library, and on top of that the library as a whole and this the library's >cubic spline implementation's in particular features vastly improved >memory >management. > I hope this library can be incorporated into the Quntlib. > Any feedback is welcome.. > > Roman Gitlin > |
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From: Luigi B. <lui...@gm...> - 2006-03-17 10:14:10
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On 03/17/2006 11:04:10 AM, Toyin Akin wrote:
> I think this would be a great addition to quantlib.
Likewise. But it might be of interest to more people than just quants.
Did you consider submitting it to Boost?
Later,
Luigi
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Ogden's Law:
The sooner you fall behind, the more time you have to catch up.
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