C++中armadillo矩阵库使用说明

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在http://blog.csdn.net/piaoxuezhong/article/details/58055709博文中介绍了eigen矩阵库的使用，这里介绍另一种矩阵库：armadillo~

Armadillo：C++下的Matlab替代品

armadillo是目前使用比较广的C++矩阵运算库之一，许多Matlab的矩阵操作函数都可以找到对应，这对习惯了Matlab的人来说实在是非常方便，另外如果要将Matlab下做研究的代码改写成C++，使用Armadillo也会很方便。下面列了一些Armadillo的特性：

支持整数，浮点数，和复数矩阵。
支持矩阵逐元素操作，包括abs · conj · conv_to · eps · imag/real · misc functions (exp, log, pow, sqrt, round, sign, ...) · trigonometric functions (cos, sin, ...)等等。
支持矩阵分块操作。
支持对整体矩阵的操作diagvec · min/max · prod · sum · statistics (mean, stddev, ...) · accu · as_scalar · det · dot/cdot/norm_dot · log_det · norm · rank · trace等等。
Matlab用户，你甚至可以找到你熟悉的hist · histc · unique · cumsum · sort_index · find · repmat · linspace等函数。
除了自带的矩阵基本运算之外，可自动检测是否安装有BLAS，或更快的 OpenBLAS, Intel MKL, AMD ACML，并使用他们替代自带基本运算实现。
提供接口使用LAPACK进行矩阵分解运算，svd · qr · lu · fft等等。
提供了稀疏矩阵类，支持常用操作，但暂时没有矩阵分解的实现。

可以使用OpenBLAS等库进行加速，安装教程参见：http://www.cnblogs.com/youthlion/archive/2012/05/15/2501465.html

vs下安装Armadillo

1、下载Armadillo，解压后把其中的include文件夹完整拷贝出来，放到某处，如D:\Armadillo；

2、修改D:\Armadillo\include\armadillo_bits\config.hpp，将

#define ARMA_USE_LAPACK
#define ARMA_USE_BLAS

这两句取消注释。表示使用这两个库。

3、安装lapack和blas。实际上第一步中下载的压缩包里自带了这两个库，但是在vs2010中用这两个库会出现卡死现象，其他编译环境没有测试。可以去http://icl.cs.utk.edu/lapack-for-windows/clapack/index.html下载blas.lib，libf2c.lib，lapack.lib三个库，并在编译环境的额外依赖库中添加这三个库。（linker-> input-> additional dependencies）

4、在编译器的include目录中添加include文件夹的路径以及第三步中三个库文件所在位置。如图：

矩阵类Mat简介：

Mat<type>为模板类，其中type可以是：float, double, std::complex, std::complex, short, int, long, and unsigned versions of short, int, long等。为方便起见，Armadillo C++已经预定义了以下类型：

mat  =  Mat<double>  //mat为double类型fmat =  Mat<float>   //fmat为float类型cx_mat  =  Mat<cx_double> //cx_表示复数类型cx_fmat =  Mat<cx_float>umat =  Mat<uword> //相当于unsign int类型imat  =  Mat<sword> //相当于int类型

创建方式：

mat()

mat(n_rows, n_cols)

mat(n_rows, n_cols, fill_type)

mat(size(X))

mat(size(X), fill_type)

mat(mat)

mat(sp_mat)

mat(vec)

mat(rowvec)

mat(initializer_list)

mat(string)

mat(std::vector)

cx_mat(mat,mat)

实例：

mat A(5, 5, fill::randu);double x = A(1,2);mat B = A + A;mat C = A * B;mat D = A % B;cx_mat X(A,B);B.zeros();B.set_size(10,10);B.ones(5,6);B.print("B:")

Armadillo中常见的功能说明：

Function/Variable Description:n rows
:n cols
:n elem number of rows (read only)
number of columns (read only)
total number of elements (read only)(i)
(r, c)
[i]
.at(r, c)
:memptr() access the i-th element, assuming a column-by-column layout
access the element at row r and columnc
as per (i), but no bounds check; use only after debugging
as per (r, c), but no bounds check; use only after debugging
obtain the raw memory pointer to element data:in range(i)
:in range(r, c) test whether the i-th element can be accessed
test whether the element at row r and columnc can be accessed:reset()
:copy size(A)
:set size(rows, cols)
.reshape(rows, cols)
.resize(rows, cols) set the number of elements to zero
set the size to be the same as matrix A
change size to specified dimensions, without preserving data (fast)
change size to specified dimensions, with elements copied column-wise (slow)
change size to specified dimensions, while preserving elements & their layout (slow):ones(rows, cols)
:zeros(rows, cols)
:randu(rows, cols)
:randn(rows, cols)
:fill(k)
:for each( [ ] (double& val)f...g)set all elements to one, optionally first resizing to specified dimensions
as above, but set all elements to zero
as above, but set elements to uniformly distributed random values in [0,1] interval
as above, but use a Gaussian/normal distribution with µ= 0 and σ = 1
set all elements to be equal to k
for each element, pass its reference to a lambda function (C++11 only):is empty()
:is finite()
:is square()
:is vec()
:is sorted() test whether there are no elements
test whether all elements are finite
test whether the matrix is square
test whether the matrix is a vector
test whether the matrix is sorted:has inf()
:has nan() test whether any element is ±1
test whether any element is not-a-number:begin()
:end()
:begin row(i)
:end row(j)
:begin col(i)
:end col(j) iterator pointing at the first element
iterator pointing at the past-the-end element
iterator pointing at first element of row i
iterator pointing at one element past row j
iterator pointing at first element of column i
iterator pointing at one element past column j:print(header)
:raw print(header)print elements to the coutstream, with an optional text header
as per .print(), but do not change stream settings:save(name, format)
:load(name, format)store matrix in the specified file, optionally specifying storage format
retrieve matrix from the specified file, optionally specifying format:diag(k)
:row(i)
:col(i)
:rows(a, b)
:cols(c, d)
:submat( span(a,b), span(c,d) )
:submat( p, q, size(A) )
:rows( vector of row indices )
:cols( vector of col indices )
:elem( vector of indices )read/write access to k-th diagonal
read/write access to row i
read/write access to column i
read/write access to submatrix, spanning from rowa to row b
read/write access to submatrix, spanning from columnc to column d
read/write access to submatrix spanning rows a to band columns c to d
read/write access to submatrix starting at row p and col qwith size same as matrix A
read/write access to rows corresponding to the specified indices
read/write access to columns corresponding to the specified indices
read/write access to matrix elements corresponding to the specified indices:each row()
:each col()
:swap rows(p, q)
:swap cols(p, q)
:insert rows(row, X)
:insert cols(col, X)
:shed rows(first row, last row)
:shed cols(first col, last col)repeat a vector operation on each row (eg.A.each row() += row vector)
repeat a vector operation on each column (eg. A.each col() += col vector)
swap the contents of specified rows
swap the contents of specified columns
insert a copy of X at the specified row
insert a copy of X at the specified column
remove the specified range of rows
remove the specified range of columns:min()
:max()
:index min()
:index max() return minimum value
return maximum value
return index of minimum value
return index of maximum value

实例：

mat A = randu<mat>(10,10);A(9,9) = 123.0;double x = A.at(9,9);double y = A[99];vec p = randu<vec>(10,1);p(9) = 123.0;double z = p[9];

Armadillo与Matlab的对比：

Matlab & Octave Armadillo NotesA(1, 1)
A(k, k) A(0, 0)
A(k-1, k-1)indexing in Armadillo starts at 0, following C++ conventionsize(A,1)
size(A,2)
size(Q,3)
numel(A) A.n rows
A.n cols
Q.n slices
A.n elem member variables are read only
Q is a cube (3D array)
.n elem indicates the total number of elementsA(:, k)
A(k, :)
A(:, p:q)
A(p:q, :)
A(p:q, r:s) A.col(k)
A.row(k)
A.cols(p, q)
A.rows(p, q)
A( span(p, q), span(r, s) ) read/write access to a specific column
read/write access to a specific row
read/write access to a submatrix spanning the specified cols
read/write access to a submatrix spanning the specified rows
A( span(first row, last row), span(first col, last col) )Q(:, :, k)
Q(:, :, t:u) Q.slice(k)
Q.slices(t, u)Q is a cube (3D array)A0
A:0A.t() or trans(A)
A.st() or strans(A) transpose (for complex matrices the conjugate is taken)
simple transpose (for complex matrices the conjugate is not taken)A = zeros(size(A))
A = ones(size(A))
A = zeros(k)
A = ones(k) A.zeros()
A.ones()
A = zeros(k,k)
A = ones(k,k) set all elements to zero
set all elements to one
create a matrix with elements set to zero
create a matrix with elements set to oneC = complex(A,B) cx mat C = cx mat(A,B) construct a complex matrix out of two real matricesA ∗ B
A :∗ B
A := B
A n B
A = A + 1
A = A - 1 A ∗ B
A % B
A = B
solve(A,B)
A++
A--% indicates element-wise multiplication
= indicates element-wise division
solve a system of linear equationsA = [ 1 2;
3 4; ] A = f f 1, 2 g,
f 3, 4 g grequires C++11 compilerX = [ A B ]
X = [ A; B ] X = join rows(A,B)
X = join cols(A,B)AA.print(“A:”)
or
cout << A << endlprint the contents of a matrix to the standard outputsave -ascii ‘A.dat’ A
load -ascii ‘A.dat’ A.save(“A.dat”, raw ascii)
A.load(“A.dat”, raw ascii) Matlab/Octave matrices saved as ascii text are readable
by Armadillo (and vice-versa)A = rand(2,3);
B = randn(4,5);
F = f A; B g; mat A = randu(2,3);
mat B = randn(4,5);
field<mat>F(2,1);
F(0,0) = A; F(1,2) = B;randu generates uniformly distributed random numbers
the field class can store multiple varying size matrices

综合测试程序：

#include <iostream>#include <armadillo>using namespace std;using namespace arma;int main(int argc, char** argv){cout<<"Armadillo version: "<<arma_version::as_string()<<endl;mat A(2, 3);  // directly specify the matrix size (elements are uninitialised)cout<<"A.n_rows: "<<A.n_rows<<endl;  // .n_rows and .n_cols are read onlycout<<"A.n_cols: "<<A.n_cols<<endl;cout<<A.is_empty()<<endl;cout<<static_cast<bool>(A.memptr())<<endl;A(1, 2) = 456.0;  // directly access an element (indexing starts at 0)A.print("A:");A = 5.0;         // scalars are treated as a 1x1 matrixA.print("A:");A.set_size(4, 5); // change the size (data is not preserved)A.fill(5.0);     // set all elements to a particular valueA.print("A:");// endr indicates "end of row"A<<0.165300<<0.454037<<0.995795<<0.124098<<0.047084<<endr<<0.688782<<0.036549<<0.552848<<0.937664<<0.866401<<endr<<0.348740<<0.479388<<0.506228<<0.145673<<0.491547<<endr<<0.148678<<0.682258<<0.571154<<0.874724<<0.444632<<endr<<0.245726<<0.595218<<0.409327<<0.367827<<0.385736<<endr;A.print("A:");cout<<"det(A): "<<det(A)<<endl;cout<<"inv(A): "<<endl<<inv(A)<<endl;// save matrix as a text fileA.save("A.txt", raw_ascii);// load from filemat B;B.load("A.txt");// imat specifies an integer matriximat AA;imat BB;AA<<1<<2<<3<<endr<<4<<5<<6<<endr<<7<<8<<9;BB<<3<<2<<1<<endr<<6<<5<<4<<endr<<9<<8<<7;// comparison of matrices (element-wise); output of a relational operator is a umatumat ZZ = (AA>=BB);ZZ.print("ZZ:");// 2D field of matrices; 3D fields are also supportedfield<mat> F(4, 3);for (uword col = 0; col<F.n_cols; ++col)for (uword row = 0; row<F.n_rows; ++row){F(row, col) = randu<mat>(2, 3);  // each element in field<mat> is a matrix}F.print("F:");return 0;}

参考：

http://blog.csdn.net/jnulzl/article/details/46808515

http://www.cnblogs.com/einyboy/p/3852319.html

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