[NumPy-Tickets] [NumPy] #1619: Loading aligned dtype error

NumPy Trac numpy-tickets@scipy....
Wed Mar 16 01:58:58 CDT 2011

#1619: Loading aligned dtype error
 Reporter:  Ihor.Melnyk      |       Owner:  somebody  
     Type:  defect           |      Status:  needs_work
 Priority:  highest          |   Milestone:  2.0.0     
Component:  numpy.core       |     Version:  devel     
 Keywords:  dtype alignment  |  
Changes (by mwiebe):

  * status:  needs_review => needs_work


 I think the bug here is in __repr__ not producing a good string to
 reconstruct the data type. Rather than coming up with an awkward
 workaround, I would suggest __repr__ print the following when the exact
 type would not be reconstructed with the normal repr:

 dtype({'names': ['f0', 'f1', 'f2'], 'formats': [dtype('int8'),
 dtype('int32'), dtype('int8')], 'offsets': [0, 4, 8]})

 Unfortunately, however, this is still not good enough! It produces a type
 with itemsize 9 instead of 12. I think it's also necessary to extend the
 dtype construction syntax to something like:

 dtype({'names': ['f0', 'f1', 'f2'], 'formats': [dtype('int8'),
 dtype('int32'), dtype('int8')], 'offsets': [0, 4, 8]}, itemsize=12)

 Also, to see why the proposed patch doesn't work, consider the following

 >>> t = np.dtype('i4, i1', align=True)
 >>> s = eval(repr(t))
 >>> t
 dtype([('f0', '<i4'), ('f1', '|i1')])
 >>> s
 dtype([('f0', '<i4'), ('f1', '|i1')])
 >>> t.itemsize
 >>> s.itemsize

 Here there is no clue provided to get the correct itemsize, extending the
 dtype constructor to have an itemsize parameter is the only reasonable way
 I can think of to make this work in general.

Ticket URL: <http://projects.scipy.org/numpy/ticket/1619#comment:3>
NumPy <http://projects.scipy.org/numpy>
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