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Diffstat (limited to 'ml/dlib/examples/matrix_ex.cpp')
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diff --git a/ml/dlib/examples/matrix_ex.cpp b/ml/dlib/examples/matrix_ex.cpp new file mode 100644 index 000000000..a56dbfbb2 --- /dev/null +++ b/ml/dlib/examples/matrix_ex.cpp @@ -0,0 +1,276 @@ +// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt + +/* + This is an example illustrating the use of the matrix object + from the dlib C++ Library. +*/ + + +#include <iostream> +#include <dlib/matrix.h> + +using namespace dlib; +using namespace std; + +// ---------------------------------------------------------------------------------------- + +int main() +{ + // Let's begin this example by using the library to solve a simple + // linear system. + // + // We will find the value of x such that y = M*x where + // + // 3.5 + // y = 1.2 + // 7.8 + // + // and M is + // + // 54.2 7.4 12.1 + // M = 1 2 3 + // 5.9 0.05 1 + + + // First let's declare these 3 matrices. + // This declares a matrix that contains doubles and has 3 rows and 1 column. + // Moreover, it's size is a compile time constant since we put it inside the <>. + matrix<double,3,1> y; + // Make a 3 by 3 matrix of doubles for the M matrix. In this case, M is + // sized at runtime and can therefore be resized later by calling M.set_size(). + matrix<double> M(3,3); + + // You may be wondering why someone would want to specify the size of a + // matrix at compile time when you don't have to. The reason is two fold. + // First, there is often a substantial performance improvement, especially + // for small matrices, because it enables a number of optimizations that + // otherwise would be impossible. Second, the dlib::matrix object checks + // these compile time sizes to ensure that the matrices are being used + // correctly. For example, if you attempt to compile the expression y*y you + // will get a compiler error since that is not a legal matrix operation (the + // matrix dimensions don't make sense as a matrix multiplication). So if + // you know the size of a matrix at compile time then it is always a good + // idea to let the compiler know about it. + + + + + // Now we need to initialize the y and M matrices and we can do so like this: + M = 54.2, 7.4, 12.1, + 1, 2, 3, + 5.9, 0.05, 1; + + y = 3.5, + 1.2, + 7.8; + + + // The solution to y = M*x can be obtained by multiplying the inverse of M + // with y. As an aside, you should *NEVER* use the auto keyword to capture + // the output from a matrix expression. So don't do this: auto x = inv(M)*y; + // To understand why, read the matrix_expressions_ex.cpp example program. + matrix<double> x = inv(M)*y; + + cout << "x: \n" << x << endl; + + // We can check that it really worked by plugging x back into the original equation + // and subtracting y to see if we get a column vector with values all very close + // to zero (Which is what happens. Also, the values may not be exactly zero because + // there may be some numerical error and round off). + cout << "M*x - y: \n" << M*x - y << endl; + + + // Also note that we can create run-time sized column or row vectors like so + matrix<double,0,1> runtime_sized_column_vector; + matrix<double,1,0> runtime_sized_row_vector; + // and then they are sized by saying + runtime_sized_column_vector.set_size(3); + + // Similarly, the x matrix can be resized by calling set_size(num rows, num columns). For example + x.set_size(3,4); // x now has 3 rows and 4 columns. + + + + // The elements of a matrix are accessed using the () operator like so: + cout << M(0,1) << endl; + // The above expression prints out the value 7.4. That is, the value of + // the element at row 0 and column 1. + + // If we have a matrix that is a row or column vector. That is, it contains either + // a single row or a single column then we know that any access is always either + // to row 0 or column 0 so we can omit that 0 and use the following syntax. + cout << y(1) << endl; + // The above expression prints out the value 1.2 + + + // Let's compute the sum of elements in the M matrix. + double M_sum = 0; + // loop over all the rows + for (long r = 0; r < M.nr(); ++r) + { + // loop over all the columns + for (long c = 0; c < M.nc(); ++c) + { + M_sum += M(r,c); + } + } + cout << "sum of all elements in M is " << M_sum << endl; + + // The above code is just to show you how to loop over the elements of a matrix. An + // easier way to find this sum is to do the following: + cout << "sum of all elements in M is " << sum(M) << endl; + + + + + // Note that you can always print a matrix to an output stream by saying: + cout << M << endl; + // which will print: + // 54.2 7.4 12.1 + // 1 2 3 + // 5.9 0.05 1 + + // However, if you want to print using comma separators instead of spaces you can say: + cout << csv << M << endl; + // and you will instead get this as output: + // 54.2, 7.4, 12.1 + // 1, 2, 3 + // 5.9, 0.05, 1 + + // Conversely, you can also read in a matrix that uses either space, tab, or comma + // separated values by uncommenting the following: + // cin >> M; + + + + // ----------------------------- Comparison with MATLAB ------------------------------ + // Here I list a set of Matlab commands and their equivalent expressions using the dlib + // matrix. Note that there are a lot more functions defined for the dlib::matrix. See + // the HTML documentation for a full listing. + + matrix<double> A, B, C, D, E; + matrix<int> Aint; + matrix<long> Blong; + + // MATLAB: A = eye(3) + A = identity_matrix<double>(3); + + // MATLAB: B = ones(3,4) + B = ones_matrix<double>(3,4); + + // MATLAB: B = rand(3,4) + B = randm(3,4); + + // MATLAB: C = 1.4*A + C = 1.4*A; + + // MATLAB: D = A.*C + D = pointwise_multiply(A,C); + + // MATLAB: E = A * B + E = A*B; + + // MATLAB: E = A + B + E = A + C; + + // MATLAB: E = A + 5 + E = A + 5; + + // MATLAB: E = E' + E = trans(E); // Note that if you want a conjugate transpose then you need to say conj(trans(E)) + + // MATLAB: E = B' * B + E = trans(B)*B; + + double var; + // MATLAB: var = A(1,2) + var = A(0,1); // dlib::matrix is 0 indexed rather than starting at 1 like Matlab. + + // MATLAB: C = round(C) + C = round(C); + + // MATLAB: C = floor(C) + C = floor(C); + + // MATLAB: C = ceil(C) + C = ceil(C); + + // MATLAB: C = diag(B) + C = diag(B); + + // MATLAB: B = cast(A, "int32") + Aint = matrix_cast<int>(A); + + // MATLAB: A = B(1,:) + A = rowm(B,0); + + // MATLAB: A = B([1:2],:) + A = rowm(B,range(0,1)); + + // MATLAB: A = B(:,1) + A = colm(B,0); + + // MATLAB: A = [1:5] + Blong = range(1,5); + + // MATLAB: A = [1:2:5] + Blong = range(1,2,5); + + // MATLAB: A = B([1:3], [1:2]) + A = subm(B, range(0,2), range(0,1)); + // or equivalently + A = subm(B, rectangle(0,0,1,2)); + + + // MATLAB: A = B([1:3], [1:2:4]) + A = subm(B, range(0,2), range(0,2,3)); + + // MATLAB: B(:,:) = 5 + B = 5; + // or equivalently + set_all_elements(B,5); + + + // MATLAB: B([1:2],[1,2]) = 7 + set_subm(B,range(0,1), range(0,1)) = 7; + + // MATLAB: B([1:3],[2:3]) = A + set_subm(B,range(0,2), range(1,2)) = A; + + // MATLAB: B(:,1) = 4 + set_colm(B,0) = 4; + + // MATLAB: B(:,[1:2]) = 4 + set_colm(B,range(0,1)) = 4; + + // MATLAB: B(:,1) = B(:,2) + set_colm(B,0) = colm(B,1); + + // MATLAB: B(1,:) = 4 + set_rowm(B,0) = 4; + + // MATLAB: B(1,:) = B(2,:) + set_rowm(B,0) = rowm(B,1); + + // MATLAB: var = det(E' * E) + var = det(trans(E)*E); + + // MATLAB: C = pinv(E) + C = pinv(E); + + // MATLAB: C = inv(E) + C = inv(E); + + // MATLAB: [A,B,C] = svd(E) + svd(E,A,B,C); + + // MATLAB: A = chol(E,'lower') + A = chol(E); + + // MATLAB: var = min(min(A)) + var = min(A); +} + +// ---------------------------------------------------------------------------------------- + + |