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From: Jason D Schmidt (jd.schmidt_at_[hidden])
Date: 2002-09-17 19:55:47


I'm kind of new to Boost (I've used it a little, I've been on the
developers' list for a few months, but I haven't submitted any code), so
wondering about what direction Boost is going regarding math & numerics.
see a number of directories/files in the CVS, like
math/quaternion.hpp, math/octonion.hpp, mpl/, multi-array/, numeric/mtl/,
and numeric/ublas. I have a number of questions:

1. Will Boost add more special functions to make its library more
like Gamma functions, Bessel functions, Hermite functions, etc.?
2. What are the various roles of array.hpp, multi-array, mpl, mtl, and
uBLAS? Is uBLAS just for linear algebra, but multi-array more for data
analysis-type things like slicing, element-wise operations (* /), and
applying things like integration, interpolation, ffts, etc.? What are
mpl &
mtl? Does mtl stand for Matrix Template Library? If so, why have two
linear algebra packages?
3. Would multi-array replace std::valarray<T>? If so, could valarray be
removed from the standard in favor of multi-array or something even
4. Are Boost developers interested in adding more numerical support for
their array classes, like root-finding, derivatives, integrals,
interpolation, curve fitting, solving differential equations, fourier
transforms, statistics?

I know there are a lot of great numerical packages for C++ (Blitz++, MTL,
more), and people can write their own from Numerical Recipes, but it
be really nice if some of it got into Boost. It would be advantageous
C++ users because Boost is peer-reviewed, it would provide a single
for comp. sci. and numerical needs that seamlessly work together, and it
ensures that container classes (matrices, vectors, arrays of data) are
STL-compliant. Plus, it would be great to see more numerical support in
next standard of C++. C++ would gain a lot of users in the science &
engineering community if it added more numerical support either in Boost
in the next standard. Finally, C++ and its Boost extensions really
well-written code and good software engineering, which, from my
are sorely lacking in the scientific & engineering community.

Jason Schmidt

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