Enhanced mathematical library for C++

I create a library for storing matrices and working with matrices in this bachelor’s thesis. In this case, the issues concern mainly so-called sparse matrices. C++ do not provide among the standard libraries tools for easy working with sparse matrices. The most frequent alternative is the application of two-dimensional array (2D array). 2D array may be realized as a double pointer representing the rows and the columns of the matrix. The basic problem is that behavior of 2D array is identical both to the sparse, and to the full non-zero matrix. 2D array ignores the possibility to store matrices more favorable. The library for storing matrices designed by me takes into account the storing of sparse matrices by several different ways. It offers the sparse format CSR (Compressed sparse rows), as well as alternatives to save the specially structured matrices. In the course of creating library the main emphasis first of all I put on the amount of memory that is necessary for storing matrices. Because it is a mathematical library, it contains different functions suitable for working with matrices, such as determinant calculation, inverse matrix calculation and so. When calculate these functions it is necessary to take into account used memory size as well. Intermediate results are stored also in sparse format, and removed as soon as possible after their use. I created also the second library that deals with the floating point numbers stored with greater precision than standard data types like float and double. The size of occupied memory increases according to precision of floating point number