Question

I’m learning to use python for data analysis, etc. and I am a little confused about what is going on in this code from the scipy cookbook.

When the cookbook describes the integration and then plotting process, via matplotlib, it has first:

t = linspace(0, 15, 1000)
X0 = array([10,5])
X = scipy.integrate.odeint(dX_dt, X0, t)
rabbits, foxes = X.T

What does this code do?

rabbits, foxes = X.T

Specifically, what does X.T do?

Answer 1

X.T is the transpose of X. So, in that line, X must be an array with shape (N,2). When you transpose it you get an array of shape (2,N) which can be unpacked.

Consider:

>>> import numpy as np
>>> a = np.arange(10).reshape((5,2))
>>> a
array([[0, 1],
       [2, 3],
       [4, 5],
       [6, 7],
       [8, 9]])
>>> B,C = a
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: too many values to unpack
>>> B,C = a.T
>>> B
array([0, 2, 4, 6, 8])
>>> C
array([1, 3, 5, 7, 9])

Also note that wherever possible, the transpose will return a new view (the data won’t be copied), so this is a very efficient operation.