158 lines
4.3 KiB
C++
158 lines
4.3 KiB
C++
#include <iostream>
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#include <armadillo>
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using std::cout;
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using std::endl;
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using namespace arma;
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// Armadillo documentation is available at:
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// http://arma.sourceforge.net/docs.html
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// NOTE: the C++11 "auto" keyword is not recommended for use with Armadillo objects and functions
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int
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main(int argc, char** argv)
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{
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cout << "Armadillo version: " << arma_version::as_string() << endl;
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// construct a matrix according to given size and form of element initialisation
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mat A(2,3,fill::zeros);
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// .n_rows and .n_cols are read only
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cout << "A.n_rows: " << A.n_rows << endl;
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cout << "A.n_cols: " << A.n_cols << endl;
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A(1,2) = 456.0; // access an element (indexing starts at 0)
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A.print("A:");
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A = 5.0; // scalars are treated as a 1x1 matrix
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A.print("A:");
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A.set_size(4,5); // change the size (data is not preserved)
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A.fill(5.0); // set all elements to a specific value
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A.print("A:");
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A = { { 0.165300, 0.454037, 0.995795, 0.124098, 0.047084 },
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{ 0.688782, 0.036549, 0.552848, 0.937664, 0.866401 },
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{ 0.348740, 0.479388, 0.506228, 0.145673, 0.491547 },
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{ 0.148678, 0.682258, 0.571154, 0.874724, 0.444632 },
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{ 0.245726, 0.595218, 0.409327, 0.367827, 0.385736 } };
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A.print("A:");
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// determinant
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cout << "det(A): " << det(A) << endl;
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// inverse
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cout << "inv(A): " << endl << inv(A) << endl;
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// save matrix as a text file
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A.save("A.txt", raw_ascii);
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// load from file
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mat B;
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B.load("A.txt");
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// submatrices
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cout << "B( span(0,2), span(3,4) ):" << endl << B( span(0,2), span(3,4) ) << endl;
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cout << "B( 0,3, size(3,2) ):" << endl << B( 0,3, size(3,2) ) << endl;
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cout << "B.row(0): " << endl << B.row(0) << endl;
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cout << "B.col(1): " << endl << B.col(1) << endl;
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// transpose
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cout << "B.t(): " << endl << B.t() << endl;
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// maximum from each column (traverse along rows)
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cout << "max(B): " << endl << max(B) << endl;
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// maximum from each row (traverse along columns)
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cout << "max(B,1): " << endl << max(B,1) << endl;
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// maximum value in B
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cout << "max(max(B)) = " << max(max(B)) << endl;
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// sum of each column (traverse along rows)
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cout << "sum(B): " << endl << sum(B) << endl;
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// sum of each row (traverse along columns)
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cout << "sum(B,1) =" << endl << sum(B,1) << endl;
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// sum of all elements
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cout << "accu(B): " << accu(B) << endl;
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// trace = sum along diagonal
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cout << "trace(B): " << trace(B) << endl;
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// generate the identity matrix
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mat C = eye<mat>(4,4);
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// random matrix with values uniformly distributed in the [0,1] interval
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mat D = randu<mat>(4,4);
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D.print("D:");
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// row vectors are treated like a matrix with one row
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rowvec r = { 0.59119, 0.77321, 0.60275, 0.35887, 0.51683 };
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r.print("r:");
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// column vectors are treated like a matrix with one column
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vec q = { 0.14333, 0.59478, 0.14481, 0.58558, 0.60809 };
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q.print("q:");
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// convert matrix to vector; data in matrices is stored column-by-column
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vec v = vectorise(A);
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v.print("v:");
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// dot or inner product
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cout << "as_scalar(r*q): " << as_scalar(r*q) << endl;
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// outer product
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cout << "q*r: " << endl << q*r << endl;
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// multiply-and-accumulate operation (no temporary matrices are created)
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cout << "accu(A % B) = " << accu(A % B) << endl;
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// example of a compound operation
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B += 2.0 * A.t();
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B.print("B:");
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// imat specifies an integer matrix
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imat AA = { { 1, 2, 3 },
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{ 4, 5, 6 },
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{ 7, 8, 9 } };
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imat BB = { { 3, 2, 1 },
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{ 6, 5, 4 },
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{ 9, 8, 7 } };
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// comparison of matrices (element-wise); output of a relational operator is a umat
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umat ZZ = (AA >= BB);
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ZZ.print("ZZ:");
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// cubes ("3D matrices")
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cube Q( B.n_rows, B.n_cols, 2 );
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Q.slice(0) = B;
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Q.slice(1) = 2.0 * B;
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Q.print("Q:");
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// 2D field of matrices; 3D fields are also supported
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field<mat> F(4,3);
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for(uword col=0; col < F.n_cols; ++col)
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for(uword row=0; row < F.n_rows; ++row)
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{
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F(row,col) = randu<mat>(2,3); // each element in field<mat> is a matrix
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}
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F.print("F:");
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return 0;
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}
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