[NumPy-Tickets] [NumPy] #1386: 100 times poorer performance indexing scalar record array

[NumPy Trac]

#1386: 100 times poorer performance indexing scalar record array
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 Reporter:  oscar.bristol  |       Owner:  somebody
     Type:  defect         |      Status:  new     
 Priority:  normal         |   Milestone:          
Component:  numpy.core     |     Version:          
 Keywords:                 |  
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 Assigning to a field in a scalar record array like this
 B['a'] = A['a']
 takes around 50 times as long as assigning like this:
 B['a'][:] = A['a']
 and 100 times as long as assigning to a size 1 record array.
 I've attached a script (test.py) that compares scalars and size 1 arrays
 and the two different methods of indexing above. On my machine, the
 results are:

 $ python test.py 100000
 array,  B['a'][:] = A['a']      0.25 seconds
 array,  B['a']    = A['a']      0.213 seconds
 scalar, B['a'][:] = A['a']      0.395 seconds
 scalar, B['a']    = A['a']      22.0 seconds

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Ticket URL: <http://projects.scipy.org/numpy/ticket/1386>
NumPy <http://projects.scipy.org/numpy>
My example project