Vector creation

As mentioned in Chapter 2, Working with the NumPy Array As a First Step to SciPy, SciPy depends on NumPy's main object's ndarray data structure. You can look at one-dimensional arrays as vectors and vice versa (oriented points in an n-dimensional space). Consequently, a vector can be created via Numpy as follows:

>>> import numpy
>>> vectorA = numpy.array([1,2,3,4,5,6,7])
>>> vectorA

The output is shown as follows:

array([1, 2, 3, 4, 5, 6, 7])

We can also use already defined arrays to create a new candidate. Some examples were presented in the previous chapter. Here we can reverse the already created vector and assign it to a new one:

>>> vectorB = vectorA[::-1].copy()
>>> vectorB

The output is shown as follows:

array([7, 6, 5, 4, 3, 2, 1])

Notice that in this example, we have to make a copy of the reverse of the elements of vectorA and assign it to vectorB. This way, by changing elements of vectorB, the elements of vectorA...