In this chapter, we will continue exploring the different SciPy modules through meaningful examples. We will start with the treatment of matrices (whether normal or sparse) with the modules on Linear Algebra—linalg and sparse. Note that linalg expands on the NumPy module with the same name.

This discipline of mathematics studies vector spaces and linear mappings between them. Matrices represent objects in this field in such a way that any property of the underlying objects may be obtained by performing adequate operations on the representing matrices. In this chapter, we assume that you are familiar with at least the basics of linear algebra, in particular with the notion of matrix multiplication, finding the determinant and inverse of a matrix, as well as their immediate applications in vector calculus.

Accordingly, in this chapter, we will explore how vectors and matrices are handled in Numpy/SciPy, how to create them, how to program standard mathematical...