blocks|key|2577345|text|看看Armadillo，文档中有一个面向Matlab用户的syntax+conversion+table，网站上还有针对其他C%2B%2B矩阵库的基准测试。我发现它对用户非常友好。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2577346|entityMap|0|LINK|mutability|MUTABLE|url|http://arma.sourceforge.net/|1|http://arma.sourceforge.net/docs.html#syntax^0|2|9|0|T|N|1|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]|$A|R|B|S|1|T]]|C|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]|L|$5|G|H|I|C|$J|M]]]]

Have a look at <a href="http://arma.sourceforge.net/" rel="noreferrer">Armadillo</a>, the docs have a <a href="http://arma.sourceforge.net/docs.html#syntax" rel="noreferrer">syntax conversion table</a> for Matlab users and there are benchmarks against other C++ matrix libraries in the website. I find it very user friendly.

blocks|key|807628|text|我同时使用Eigen和Matlab语言，我非常喜欢它们。Eigen支持SIMD和lazy评估以获得额外的性能。但用户不需要为内部结构而烦恼。Eigen的界面非常简单直观。从Matlab到Eigen应该是相对简单的，我不能说uBLAS或LAPACK。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|807629|编辑:这里是Eigen+Quick+Reference+for+Matlab+Users|807630|entityMap|0|LINK|mutability|MUTABLE|url|http://eigen.tuxfamily.org/|1|http://eigen.tuxfamily.org/dox-devel/AsciiQuickReference.txt^0|5|5|0|0|6|12|1|0^^$0|@$1|2|3|4|5|6|7|P|8|@]|9|@$A|Q|B|R|1|S]]|C|$]]|$1|D|3|E|5|6|7|T|8|@]|9|@$A|U|B|V|1|W]]|C|$]]|$1|F|3|-4|5|6|7|X|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]|N|$5|I|J|K|C|$L|O]]]]

I use both <a href="http://eigen.tuxfamily.org" rel="noreferrer">Eigen</a> and Matlab and like both of them a lot. Eigen supports SIMD and lazy evaluations for extra performance. But users don't need to bother with internals. Eigen's interface is very simple and intuitive. Going from Matlab to Eigen should be relatively straightforward, which I can't say about uBLAS or LAPACK.

EDIT: Here is <a href="http://eigen.tuxfamily.org/dox-devel/AsciiQuickReference.txt" rel="noreferrer">Eigen Quick Reference for Matlab Users</a>

blocks|key|3985271|text|boost有一个能够处理矩阵代数的数学库--+uBLAS。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|3985272|entityMap|0|LINK|mutability|MUTABLE|url|http://www.boost.org/doc/libs/1_43_0/libs/numeric/ublas/doc/index.htm^0|N|5|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

boost has a math library capable of matrix algebra - <a href="http://www.boost.org/doc/libs/1_43_0/libs/numeric/ublas/doc/index.htm" rel="noreferrer">uBLAS</a>.

blocks|key|1549970|text|Boost生态系统中有两个新的线性代数Libs，即NT2和Boost+LA+AFAIK，目前正在进行中(甚至已经完成了一半？)使它们与Boost+uBlas兼容。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1549971|entityMap|0|LINK|mutability|MUTABLE|url|http://nt2.sourceforge.net/publication.html|1|http://www.revergestudios.com/boost-la/^0|P|3|0|T|8|1|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]|$A|R|B|S|1|T]]|C|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]|L|$5|G|H|I|C|$J|M]]]]

There are two new Linear Algebra Libs in the Boost ecosystem namely <a href="http://nt2.sourceforge.net/publication.html" rel="nofollow noreferrer">NT2</a> and <a href="http://www.revergestudios.com/boost-la/" rel="nofollow noreferrer">Boost LA</a> AFAIK there is work underway (even halfway done?) to make them compatible with Boost uBlas.

blocks|key|1549984|text|NIST有TNT+(模板数值工具包)。非常轻量级和简单。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1549985|entityMap|0|LINK|mutability|MUTABLE|url|http://math.nist.gov/tnt/download.html^0|5|3|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

NIST has the <a href="http://math.nist.gov/tnt/download.html" rel="nofollow noreferrer">TNT</a> (template numerical toolkit). Very lightweight and simple.

blocks|key|3985532|text|半严肃的回答(直接来自Stroustrup)：http://www.stroustrup.com/Programming/Matrix/index.html|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|3985533|entityMap|0|LINK|mutability|MUTABLE|url|http://www.stroustrup.com/Programming/Matrix/index.html^0|N|1J|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

A semi-serious answer (straight from Stroustrup): <a href="http://www.stroustrup.com/Programming/Matrix/index.html" rel="nofollow">http://www.stroustrup.com/Programming/Matrix/index.html</a>

blocks|key|1554122|text|在www.embedded.com上阅读Jack+Crenshaw的文章。多年来，他一直在开发一个矩阵类，同时开发与之配套并使用它的数值方法代码。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1554123|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

Read Jack Crenshaw's articles over at www.embedded.com. He's been working up a matrix class for a number of years, while developing the numerical methods code that goes with it and uses it.

blocks|key|2577480|text|我刚刚开始使用Gmm%2B%2B库。它只支持头文件，支持稀疏矩阵，具有广泛的求解器阵列，并提供LAPACK和BLAS接口。它的界面看起来不像Eigen那么好，但它更完整。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2577481|entityMap|0|LINK|mutability|MUTABLE|url|http://download.gna.org/getfem/html/homepage/gmm.html^0|7|5|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I just started using the <a href="http://download.gna.org/getfem/html/homepage/gmm.html" rel="nofollow noreferrer">Gmm++</a> library. It's header-files only, supports sparse matrices, has a wide array of solvers, and interfaces for LAPACK and BLAS. Its interface doesn't seem as nice as Eigen, but it is more complete.

Greetings,
googling for that subject brings, e.g., <a href="http://osl.iu.edu/research/mtl/" rel="nofollow noreferrer">MTL</a>, <a href="http://exmat.sourceforge.net/" rel="nofollow noreferrer">exmat</a>, <a href="http://www.netlib.org/lapack/" rel="nofollow noreferrer">LAPACK</a> and also <a href="https://stackoverflow.com/questions/1997632/matrix-standard-library">here</a>. I also seem to remember that Microsoft Research released one, but can't put my hands on it.
I look for advice from someone who actually used (or developed...) one of those, hoping to achieve a Matlab experience inside C++ (as much as possible).
Thanks in advance, Robi

Looking for an elegant and efficient C++ matrix library

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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问候，谷歌搜索该主题，例如，，，和。我似乎还记得微软研究院发布了一个，但我不能亲手拿到它。我从实际使用(或开发...)的人那里寻求建议。其中之一，希望在C++中实现Matlab体验(尽可能多)。提前谢谢你，罗比

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