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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 deleted file mode 100644 index a56dbfbb2..000000000 --- a/ml/dlib/examples/matrix_ex.cpp +++ /dev/null @@ -1,276 +0,0 @@ -// 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); -} - -// ---------------------------------------------------------------------------------------- - - |