To efficiently resize an Eigen matrix in C, you can use the resize() function provided by the Eigen library. This function allows you to change the size of the matrix while preserving its data and minimizing memory reallocation. Simply call matrix.resize(newRows, newCols) to resize the matrix to the desired dimensions.
The C matrix library provides features for creating and manipulating matrices, including functions for matrix addition, subtraction, multiplication, and transposition. It also offers capabilities for solving linear equations, calculating determinants, and performing matrix decompositions. Additionally, the library supports various matrix operations such as inversion, eigenvalue calculation, and singular value decomposition.
[abc][k] [10] [a,-b] [01] [-c,k]
---- I had a similar problem in Linux and, after MUCHfrustration, digging, trial-and-error, I have answered my own question. I think this can help you as well.My problem was that I could not delete or resize two "unallocated partitions on my hard drive. All the options (unmount, resize, delete, etc.) were grayed out. I could not unmount them because they were in use.The answer was to download the GParted LIVE CD from: http://gparted.sourceforge.net.I simply inserted the GParted LIVE CD, rebooted, and -- voila! -- I could move, resize, and delete all my partitions at will! I believe this program will work in Windows as well, since it is dealing with hard drive partitions, and ot Operating systems on the drive.IMHO, the GParted utility is much easier to use then Partition Magic, and best of all, it is FREE!I hope this post can help others with a similar problem.Lloyd----
A file in C means a file found in your computer's C Drive. Start > My Computer > C Drive
Class C.
It's matrix C.
is C or D
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int matrix[][]; // the matrix to find the max in int max = matrix[0][0]; int r,c; for(r = 0; r < 3; ++r) { for(c = 0; c < 3; ++c) { if(matrix[r][c] > max) { max = matrix[r][c]; } } } // max is now the maximum number in matrix
How we can addition Two Matrix plz send coding in C language mahesh dhanotiya astah_mahesh@rediff.com how i can built a square matrix in c,
A Hadamard Matrix is a square matrix composed of 1 or -1. Using a square matrix system the hadamard matrix could be created
Write a program in c++ that take input in a integer matrix of size 4*4 and find out if the entered matrix is diagonal or not.
#include<iostream> #include<vector> #include<random> template<const size_t R, const size_t C> class Matrix { public: using row_type = int[C]; private: // attributes int m_data[R][C]; public: // construction/assignment Matrix (); Matrix (const Matrix& source); Matrix (Matrix&& source); Matrix& operator= (const Matrix<R,C>& source); Matrix& operator= (Matrix<R,C>&& source); ~Matrix () {} public: // accessors row_type& row (const size_t index) { return m_data[index]; } const row_type& row (const size_t index) const { return m_data[index]; } row_type& operator[] (const size_t index) { return m_data[index]; } const row_type& operator[] (const size_t index) const { return m_data[index]; } size_t size() const { return R * C; } size_t rows() const { return R; } size_t cols() const { return C; } void randomise(std::uniform_int_distribution<int>& distribution, std::default_random_engine& generator); public: // operations Matrix<R,C>& operator+= (const Matrix<R,C>&); Matrix<R,C>& operator-= (const Matrix<R,C>&); }; template<const size_t R, const size_t C> void Matrix<R,C>::randomise(std::uniform_int_distribution<int>& distribution, std::default_random_engine& generator) { for (size_t row=0; row!=R; ++row) { for (size_t col=0; col!=C; ++col) { m_data[row][col] = distribution (generator); } } } template<const size_t R, const size_t C> Matrix<R,C>::Matrix() { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = 0; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator+= (const Matrix<R,C>& rhs) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] += rhs.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator-= (const Matrix<R,C>& rhs) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] -= rhs.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C> operator+ (const Matrix<R,C>& lhs, const Matrix<R,C>& rhs) { Matrix<R,C> sum (lhs); return sum += rhs; } template<const size_t R, const size_t C> Matrix<R,C> operator- (const Matrix<R,C>& lhs, const Matrix<R,C>& rhs) { Matrix<R,C> sub (lhs); return sub -= rhs; } template<const size_t R, const size_t C, const size_t R1, const size_t C1> Matrix<R,C1> operator* (const Matrix<R,C>& lhs, const Matrix<R1,C1>& rhs) { static_assert (C==R1, "Matrix dimension mismatch!"); Matrix<R,C1> mul; for (size_t x=0; x!=R; ++x) { for (size_t y=0; y!=C1; ++y) { int prod = 0; for (size_t z=0; z!=C; ++z) { prod += lhs[x][z] * rhs[z][y]; } mul[x][y] = prod; } } return mul; } template<const size_t R, const size_t C> std::ostream& operator<< (std::ostream& os, const Matrix<R,C>& m) { for (size_t row=0; row<R; ++row) { for (size_t col=0; col<C; ++col) { std::cout << m[row][col] << '\t'; } std::cout << std::endl; } return os; } int main() { std::default_random_engine generator; std::uniform_int_distribution<int> distribution (1,9); const size_t rows = 2; const size_t cols = 3; Matrix<rows, cols> a, b; a.randomise (distribution, generator); b.randomise (distribution, generator); std::cout << "Matrix a:\n\n" << a << '\n' << std::endl; std::cout << "Matrix b:\n\n" << b << '\n' << std::endl; std::cout << "Matrix a + b:\n\n" << a + b << '\n' << std::endl; std::cout << "Matrix a - b:\n\n" << a - b << '\n' << std::endl; Matrix<cols, rows> c; c.randomise (distribution, generator); std::cout << "Matrix c:\n\n" << c << '\n' << std::endl; std::cout << "Matrix a * c:\n\n" << a * c << '\n' << std::endl; }
#include<iostream> #include<vector> #include<random> template<const size_t R, const size_t C> class Matrix { public: using row_type = int[C]; private: // attributes int m_data[R][C]; public: // construction/assignment Matrix (); Matrix (const Matrix& source); Matrix (Matrix&& source); Matrix& operator= (const Matrix<R,C>& source); Matrix& operator= (Matrix<R,C>&& source); ~Matrix () {} public: // accessors row_type& row (const size_t index) { return m_data[index]; } const row_type& row (const size_t index) const { return m_data[index]; } row_type& operator[] (const size_t index) { return m_data[index]; } const row_type& operator[] (const size_t index) const { return m_data[index]; } size_t size() const { return R * C; } size_t rows() const { return R; } size_t cols() const { return C; } public: // operations Matrix<R,C>& operator+= (const Matrix<R,C>&); Matrix<R,C>& operator-= (const Matrix<R,C>&); }; template<const size_t R, const size_t C> Matrix<R,C>::Matrix() { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = 0; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator+= (const Matrix<R,C>& rhs) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] += rhs.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator-= (const Matrix<R,C>& rhs) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] -= rhs.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C> operator+ (const Matrix<R,C>& lhs, const Matrix<R,C>& rhs) { Matrix<R,C> sum (lhs); return sum += rhs; } template<const size_t R, const size_t C> Matrix<R,C> operator- (const Matrix<R,C>& lhs, const Matrix<R,C>& rhs) { Matrix<R,C> sub (lhs); return sub -= rhs; } template<const size_t R, const size_t C, const size_t R1, const size_t C1> Matrix<R,C1> operator* (const Matrix<R,C>& lhs, const Matrix<R1,C1>& rhs) { static_assert (C==R1, "Matrix dimension mismatch!"); Matrix<R,C1> mul; for (size_t x=0; x!=R; ++x) { for (size_t y=0; y!=C1; ++y) { int prod = 0; for (size_t z=0; z!=C; ++z) { prod += lhs[x][z] * rhs[z][y]; } mul[x][y] = prod; } } return mul; } template<const size_t R, const size_t C> std::ostream& operator<< (std::ostream& os, const Matrix<R,C>& m) { for (size_t row=0; row<R; ++row) { for (size_t col=0; col<C; ++col) { std::cout << m[row][col] << '\t'; } std::cout << std::endl; } return os; } int main() { std::default_random_engine generator; std::uniform_int_distribution<int> distribution (1,9); const size_t rows = 2; const size_t cols = 3; Matrix<rows, cols> a, b; for (size_t row=0; row<rows; ++row) { for (size_t col=0; col<cols; ++col) { a[row][col] = distribution (generator); b[row][col] = distribution (generator); } } std::cout << "Matrix a:\n\n" << a << '\n' << std::endl; std::cout << "Matrix b:\n\n" << b << '\n' << std::endl; std::cout << "Matrix a + b:\n\n" << a + b << '\n' << std::endl; std::cout << "Matrix a - b:\n\n" << a - b << '\n' << std::endl; Matrix<cols, rows> c; for (size_t row=0; row<rows; ++row) { for (size_t col=0; col<cols; ++col) { c[col][row] = distribution (generator); } } std::cout << "Matrix c:\n\n" << c << '\n' << std::endl; std::cout << "Matrix a * c:\n\n" << a * c << '\n' << std::endl; }
Alfred C. H. Yu has written: 'Eigen-based signal processing methods for ultrasound color flow imaging'
#include<iostream> #include<vector> #include<time.h> template<const size_t R, const size_t C> class Matrix { public: using row_type = int[C]; private: // attributes int m_data[R][C]; public: // construction/assignment Matrix (); Matrix (const Matrix& source); Matrix (Matrix&& source); Matrix& operator= (const Matrix<R,C>& source); Matrix& operator= (Matrix<R,C>&& source); ~Matrix () {} public: // accessors row_type& row (const size_t index) { return m_data[index]; } const row_type& row (const size_t index) const { return m_data[index]; } row_type& operator[] (const size_t index) { return m_data[index]; } const row_type& operator[] (const size_t index) const { return m_data[index]; } size_t size() const { return R * C; } size_t rows() const { return R; } size_t cols() const { return C; } public: // operations Matrix<R,C>& operator+= (const Matrix<R,C>&); }; template<const size_t R, const size_t C> Matrix<R,C>::Matrix() { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = 0; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; } template<const size_t R, const size_t C> Matrix<R,C>::Matrix(Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (const Matrix<R,C>& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = source.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator= (Matrix<R,C>&& source) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] = std::move (source.m_data[row][col]); return *this; } template<const size_t R, const size_t C> Matrix<R,C>& Matrix<R,C>::operator+= (const Matrix<R,C>& rhs) { for (size_t row=0; row<R; ++row) for (size_t col=0; col<C; ++col) m_data[row][col] += rhs.m_data[row][col]; return *this; } template<const size_t R, const size_t C> Matrix<R,C> operator+ (const Matrix<R,C>& lhs, const Matrix<R,C>& rhs) { Matrix<R,C> sum (lhs); return sum += rhs; } template<const size_t R, const size_t C> std::ostream& operator<< (std::ostream& os, const Matrix<R,C>& m) { for (size_t row=0; row<R; ++row) { for (size_t col=0; col<C; ++col) { std::cout << m[row][col] << '\t'; } std::cout << std::endl; } return os; } int main() { srand ((unsigned)time(nullptr)); const size_t rows = 3; const size_t cols = 3; Matrix<rows, cols> a, b, c; for (size_t row=0; row<rows; ++row) { for (size_t col=0; col<cols; ++col) { a[row][col] = rand() % 10; b[row][col] = rand() % 10; } } std::cout << "Matrix a:\n\n" << a << '\n' << std::endl; std::cout << "Matrix b:\n\n" << b << '\n' << std::endl; std::cout << "Matrix a + b:\n\n" << a + b << '\n' << std::endl; }
A C program to square matrix is a math problem. In the math problem you write down all the outer boundary values of matrix in a circle, then write down the inner value.