How to force numpy array order to fortran style?

Question

I am using quite a lot of fortran libraries to do some mathematical computation. So all the arrays in numpy need to be Fortran-contiguous.
Currently I accomplish this with numpy.asfortranarray().

My questions are:

Is this a fast way of telling numpy that the array should be stored in fortran style or is there a faster one?
Is there the possibility to set some numpy flag, so that every array that is created is in fortran style?

milancurcic · Accepted Answer · 2011-10-07 14:58:03Z

14

Use optional argument order='F' (default 'C'), when generating numpy.array objects. This is the way I do it, probably does the same thing that you are doing. About number 2, I am not aware of setting default order, but it's easy enough to just include order optional argument when generating arrays.

answered Oct 7, 2011 at 14:58

milancurcic

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bdforbes · Accepted Answer · 2016-10-20 05:23:07Z

7

Regarding question 2: you may be concerned about retaining Fortran ordering after performing array transformations and operations. I had a similar issue with endianness. I loaded a big-endian raw array from file, but when I applied a log transformation, the resultant array would be little-endian. I got around the problem by first allocating a second big-endian array, then performing an in-place log:

b=np.zeros(a.shape,dtype=a.dtype)
np.log10(1+100*a,b)

In your case you would allocate b with Fortran ordering.

edited Oct 20, 2016 at 5:23

answered Oct 8, 2011 at 13:09

bdforbes

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