[NumPy-Tickets] [NumPy] #2054: f2py's handling of strided arrays.

[NumPy Trac]

#2054: f2py's handling of strided arrays.
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 Reporter:  pch          |       Owner:  pearu      
     Type:  enhancement  |      Status:  new        
 Priority:  normal       |   Milestone:  Unscheduled
Component:  numpy.f2py   |     Version:  1.6.1      
 Keywords:               |  
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Comment(by pearu):

 At the moment I don't have time to implement/test the strided array
 support for f2py.

 However, when copying data is not an issue, then below follows a temporary
 workaround
 of the issue.

 1) Wrap the multiply_me Fortran subroutine with f2py as usual. For
 example,
 {{{
 f2py -c -m foo foo.f90
 }}}

 2) Create the following Python function:
 {{{
 def multiply_me(a):
     import foo
     b = a.copy(order='F')
     foo.multiply_me(b)
     a[:] = b
 }}}
 and use it instead of foo.multiply_me.

 For example:
 {{{
 >>> def multiply_me(a):
 ...:         import foo
 ...:         b = a.copy(order='F')
 ...:         foo.multiply_me(b)
 ...:         a[:] = b
 ...:
 >>> import numpy as np
 >>> a = np.ones((2,4), np.int64)
 >>> multiply_me(a[:,1:3])
 >>> print a
 [[1 2 2 1]
  [1 2 2 1]]
 }}}

 HTH

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/2054#comment:2>
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