python - Numpy array integer / float division -


this question has answer here:

i found following behaviour in python/numpy strange:

in [51]: = np.arange(10, 20) in [52]: = / 10.0 in [53]: out[53]: array([ 1. ,  1.1,  1.2,  1.3,  1.4,  1.5,  1.6,  1.7,  1.8,  1.9])  in [54]: = np.arange(10, 20) in [55]: /= 10.0 in [56]: out[56]: array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1]) 

i felt a=a/10.0 , a/=10.0 should return same result. inteded , documented somewhere?

the problem a /= 10.0 modifies array in place, , won't change the dtype of array, floats converted integers. on other hand a = / 10.0 created new array, , type can changed if new array being created.

from docs:

note assignments may result in changes if assigning higher types lower types (like floats ints) or exceptions (assigning complex floats or ints):


Comments

Popular posts from this blog

c# - Binding a comma separated list to a List<int> in asp.net web api -

Delphi 7 and decode UTF-8 base64 -

html - Is there any way to exclude a single element from the style? (Bootstrap) -