SciPy offers a large range of methods from numerical linear algebra in its module scipy.linalg. Many of these methods are Python wrapping programs from LAPACK, a collection of well-approved FORTRAN subroutines used to solve linear equation systems and eigenvalue problems, see [5]. Linear algebra methods are the core of any method in scientific computing, and the fact that SciPy uses wrappers instead of pure Python code makes these central methods extremely fast. We present in detail here how two linear algebra problems are solved with Scipy to give you a flavor of this module.
You met before some linear algebra functions taken from the module numpy.linalg. Both packages NumPy and SciPy are compatible, but Scipy has its focus on scientific computing methods and is more comprehensive, while NumPy's focus is on the array datatype and it provides only some linear algebra methods for convenience.
