Why does np.arccos(1.0) give nan if fed by np.arange?

Question

Can anyone replicate this?

import numpy as np
print np.arccos(1.0)
print np.arccos(1)
for x in np.arange(0.7,1,0.05):
    print x
    print np.arccos(x)

Output:

0.0
0.0
0.7
0.795398830184
0.75
0.722734247813
0.8
0.643501108793
0.85
0.55481103298
0.9
0.451026811796
0.95
0.317560429292
1.0
nan

Note the last value,which should be np.arccos(1.0), is nan. When I do np.arccos(1.0) in the console it is 0.0 as I would expect. What is causing this behaviour?

Note, I am using Python 2.7.6 Spyder IDE Win7

Answer 1

This is normal floating point inaccuracy. Adding 0.05 many times to 0.7 does not necessarily add up to 1 exactly.

Changing print x to print repr(x) outputs 1.0000000000000002 for the last x.

>>> np.arccos(1.0000000000000002)
__main__:1: RuntimeWarning: invalid value encountered in arccos
nan