 Matrix and Vector Types
 Initialization
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Matrices and vectors
A matrix is a twodimensional array of double, float, or complex numbers.
A vector is a onedimensional array of double, float, or complex numbers. The vector has no indication of whether it is vertical or horizontal. It is determined from the use context. For example, the vector operation Dot assumes that the left vector is horizontal and the right one is vertical. If the type indication is required, onerow or onecolumn matrices can be used. However, this is generally not necessary.
Matrices and vectors allocate memory for data dynamically. In fact, matrices and vectors are objects that have certain properties, such as the type of data they contain and dimensions. Matrix and vector properties can be obtained using methods such as vector_a.Size(), matrix_b.Rows(), vector_c.Norm(), matrix_d.Cond() and others. Any dimension can be changed.
When creating and initializing matrices, socalled static methods are used (these are like static methods of a class). For example: matrix::Eye(), matrix::Identity(), matrix::Ones(), vector::Ones(), matrix: :Zeros(), vector::Zeros(), matrix::Full(), vector::Full(), matrix::Tri().
At the moment, matrix and vector operations do not imply the use of the complex data type, as this development direction has not yet been completed.
MQL5 supports passing of matrices and vectors to DLLs. This enables the import of functions utilizing the relevant types, from external variables.
Matrices and vectors are passed to a DLL as a pointer to a buffer. For example, to pass a matrix of type float, the corresponding parameter of the function exported from the DLL must take a floattype buffer pointer.
MQL5
#import "mmlib.dll"

C++
extern "C" __declspec(dllexport) bool sgemm(UINT flags, float *C, const float *A, const float *B, UINT64 M, UINT64 N, UINT64 K, float alpha, float beta) 
In addition to buffers, you should pass matrix and vector sizes for correct processing.
All matrix and vector methods are listed below in alphabetical order.
Function 
Action 
Category 

Compute activation function values and write them to the passed vector/matrix 

Return the index of the maximum value 

Return the index of the minimum value 

Return the sorted index 

Copies a matrix, vector or array with auto cast 

Compute the weighted average of matrix/vector values 

Compute the Cholesky decomposition 

Limits the elements of a matrix/vector to a given range of valid values 

Return a column vector. Write a vector to the specified column. 

Return the number of columns in a matrix 

Compare the elements of two matrices/vectors with the specified precision 

Compare the elements of two matrices/vectors with the significant figures precision 

Compute the condition number of a matrix 

Return the discrete, linear convolution of two vectors 

Return a copy of the given matrix/vector 

Get the data of the specified indicator buffer in the specified quantity to a vector 

Gets the historical series of the MqlRates structure of the specified symbolperiod in the specified amount into a matrix or vector 

Get ticks from an MqlTick structure into a matrix or a vector 

Get ticks from an MqlTick structure into a matrix or a vector within the specified date range 

Compute the Pearson correlation coefficient (linear correlation coefficient) 

Compute the crosscorrelation of two vectors 

Compute the covariance matrix 

Return the cumulative product of matrix/vector elements, including those along the given axis 

Return the cumulative sum of matrix/vector elements, including those along the given axis 

Compute activation function derivative values and write them to the passed vector/matrix 

Compute the determinant of a square invertible matrix 

Extract a diagonal or construct a diagonal matrix 

Dot product of two vectors 

Computes the eigenvalues and right eigenvectors of a square matrix 

Computes the eigenvalues of a general matrix 

Return a matrix with ones on the diagonal and zeros elsewhere 

Fill an existing matrix or vector with the specified value 

Access a matrix element through one index instead of two 

Create and return a new matrix filled with the given value 

The GeMM (General Matrix Multiply) method implements the general multiplication of two matrices 

Return the number of NaN values in a matrix/vector 

Split a matrix horizontally into multiple submatrices. Same as Split with axis=0 

Create an identity matrix of the specified size 

Matrix or vector initialization 

Inner product of two matrices 

Compute the multiplicative inverse of a square invertible matrix by the JordanGauss method 

Return Kronecker product of two matrices, matrix and vector, vector and matrix or two vectors 

Compute loss function values and write them to the passed vector/matrix 

Return the leastsquares solution of linear algebraic equations (for nonsquare or degenerate matrices) 

Implement an LU decomposition of a matrix: the product of a lower triangular matrix and an upper triangular matrix 

Implement an LUP factorization with partial permutation, which refers to LU decomposition with row permutations only: PA=LU 

Matrix product of two matrices 

Return the maximum value in a matrix/vector 

Compute the arithmetic mean of element values 

Compute the median of the matrix/vector elements 

Return the minimum value in a matrix/vector 

Return matrix or vector norm 

Create and return a new matrix filled with ones 

Compute the outer product of two matrices or two vectors 

Return the specified percentile of values of matrix/vector elements or elements along the specified axis 

Compute the pseudoinverse of a matrix by the MoorePenrose method 

Raise a square matrix to an integer power 

Return the product of matrix/vector elements, which can also be executed for the given axis 

Return the range of values of a matrix/vector or of the given matrix axis 

Compute the qr factorization of a matrix 

Return the specified quantile of values of matrix/vector elements or elements along the specified axis 

Return matrix rank using the Gaussian method 

Compute the regression metric as the deviation error from the regression line constructed on the specified data array 

Change the shape of a matrix without changing its data 

Return a new matrix with a changed shape and size 

Return a row vector. Write the vector to the specified row 

Return the number of rows in a matrix 

Sets the value for a vector element by the specified index 

Return the size of vector 

Compute the sign and logarithm of the determinant of an matrix 

Solve a linear matrix equation or a system of linear algebraic equations 

Sort by place 

Compute spectrum of a matrix as the set of its eigenvalues from the product AT*A 

Split a matrix into multiple submatrices 

Return the standard deviation of values of matrix/vector elements or elements along the specified axis 

Return the sum of matrix/vector elements, which can also be executed for the given axis (axes) 

Singular value decomposition 

Swap columns in a matrix 

Swap rows in a matrix 

Return the sum along diagonals of the matrix 

Transpose (swap the axes) and return the modified matrix 

Construct a matrix with ones on a specified diagonal and below, and zeros elsewhere 

Return a copy of a matrix with elements above the kth diagonal zeroed. Lower triangular matrix 

Return a copy of a matrix with the elements below the kth diagonal zeroed. Upper triangular matrix 

Compute the variance of values of matrix/vector elements 

Split a matrix vertically into multiple submatrices. Same as Split with axis=1 

Create and return a new matrix filled with zeros 