[NumPy-Tickets] [NumPy] #2051: Use the shortest repr for np.float32/float64

[NumPy Trac]

#2051: Use the shortest repr for np.float32/float64
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 Reporter:  beaujolais   |       Owner:  somebody   
     Type:  enhancement  |      Status:  new        
 Priority:  normal       |   Milestone:  Unscheduled
Component:  Other        |     Version:  1.6.1      
 Keywords:               |  
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 Python 2.7 and 3.1 now always use the shortest decimal representation for
 numbers that are not exactly representable by a binary float (see
 [http://bugs.python.org/issue1580]).

 This causes some very surprising inconsistencies with NumPy's own repr:
 >>> x = 0.1
 >>> x
 0.1
 >>> a = np.array([x])
 >>> a
 array([ 0.1])
 >>> a[0]
 0.10000000000000001
 >>> float(a[0])
 0.1
 >>> type(a[0])
 <class 'numpy.float64'>

 For the sake of consistency I suggest adopting the same __repr__ in NumPy.

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/2051>
NumPy <http://projects.scipy.org/numpy>
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