This chapter covers matrices and universal functions (ufuncs). Matrices are well known in mathematics and have their representation in NumPy as well. Universal functions work on arrays, element-by-element, or on scalars. ufuncs expect a set of scalars as input and produce a set of scalars as output. Universal functions can typically be mapped to mathematical counterparts, such as add, subtract, divide, multiply, and likewise. We will also be introduced to trigonometric, bitwise, and comparison universal functions.
In this chapter, we shall cover the following topics:
Matrices in NumPy are subclasses of ndarray
. Matrices can be created using a special string format. They are, just like in mathematics, two-dimensional. Matrix multiplication is, as you would expect, different from the normal NumPy multiplication. The same is true for the power operator. We can create matrices with the mat
, matrix
, and bmat
functions.