In my for loop, my code generates a list like this one:
list([0.0,0.0]/sum([0.0,0.0]))
The loop generates all sort of other number vectors but
I think this makes sense because of your pulling numpy
into scope indirectly via the star import.
>>> import numpy as np
>>> [0.0,0.0]/0
Traceback (most recent call last):
File "", line 1, in
[0.0,0.0]/0
TypeError: unsupported operand type(s) for /: 'list' and 'int'
>>> [0.0,0.0]/np.float64(0)
array([ nan, nan])
When you did
from matplotlib.pylab import *
it pulled in numpy.sum
:
>>> from matplotlib.pylab import *
>>> sum is np.sum
True
>>> [0.0,0.0]/sum([0.0, 0.0])
array([ nan, nan])
You can test that this nan
object (nan
isn't unique in general) is in a list via identity, but if you try it in an array
it seems to test via equality, and nan != nan
:
>>> nan == nan
False
>>> nan == nan, nan is nan
(False, True)
>>> nan in [nan]
True
>>> nan in np.array([nan])
False
You could use np.isnan
:
>>> np.isnan([nan, nan])
array([ True, True], dtype=bool)
>>> np.isnan([nan, nan]).any()
True