In this chapter, we have explored in depth the creation and basic manipulation of the object array used by SciPy, as an overview of the NumPy libraries. In particular, we have seen the principles of slicing and masking, which simplify the coding of algorithms to the point of transforming an otherwise unreadable sequence of loops and primitive commands into an intuitive and self-explanatory set of object calls and methods. You also learned that the nonbasic modules in NumPy are replicated as modules in SciPy itself. The chapter roughly followed the same structure as the official NumPy reference (which the reader can access at the SciPy pages http://docs.scipy.org/doc/numpy/reference/). There are other good sources that cover NumPy with rigor, and we refer you to any of that material for a more detailed coverage of this topic.

In the next five chapters, we will be accessing the commands that make SciPy a powerful tool in numerical computing. The structure of those chapters is basically a reflection of the different SciPy modules structured in an order that allows building applications on top of each other.