Question

Executing the following code in a fresh Python 2.7.3 interpreter on my ubuntu linux machine gives the output shown after the code.

import numpy as np
p = [1/3., 1/2., 23/25., 1]
q = np.array(p)
r = list(q)
print p; print q; print r

Output:

[0.3333333333333333, 0.5, 0.92, 1]
[ 0.33333333  0.5         0.92        1.        ]
[0.33333333333333331, 0.5, 0.92000000000000004, 1.0]

I’m trying to figure out why p and r print out differently, but so far haven’t got a plausible theory. Any ideas on why they differ?

Answer 1

They print differently because p is a list of float and int, whereas r is a list of numpy.float64:

In [23]: map(type, p)
Out[23]: [float, float, float, int]

In [24]: map(type, r)
Out[24]: [numpy.float64, numpy.float64, numpy.float64, numpy.float64]

This happens because NumPy arrays are of a uniform type, so everything gets widened to float64 when you create q.

The values in two lists compare equal, so it’s purely a difference in formatting:

In [22]: p == r
Out[22]: True