Practically all the different areas of numerical analysis are contemplated in some SciPy module. For example, in order to compute values of special functions, we use the
scipy.special module. The
scipy.interpolate module takes care of interpolation, extrapolation, and regression. For optimization, we have the
scipy.optimize module, and finally, we have the
scipy.integrate module for numerical evaluation of integrals. This last module serves as the interface to perform numerical solutions of ordinary differential equations as well.
Thus, in this chapter, we will first extensively explore how to use SciPy to numerically evaluate the special functions that are commonly found in the field of mathematical physics. Then, we will discuss the modules available in SciPy to tackle regression, interpolation, and optimization problems.
The chapter ends with a solution of the chaotic Lorenz system as an illustration of the capabilities included in SciPy to find...