[Numpy-discussion] byteorder question (original) (raw)

Travis Oliphant oliphant at ee.byu.edu
Fri Jun 30 19:01:10 EDT 2006

Jonathan Taylor wrote:

In some earlier code (at least one of) the following worked fine. I just want to get a new type that is a byteswap of, say, float64 because I want to memmap an array with a non-native byte order.

Any suggestions?

Last year the array scalars (like float64) were confused with the data-type objects dtype('=i4'). This was fortunately changed many months ago so the two are now separate concepts. This may be why your old code worked.

You want to get a data-type object itself:

d = numpy.dtype(numpy.float64) d = numpy.float64(1).dtype # you have to instantiate a float64 object to access it's data-type.

Then

d.newbyteorder('>') or d.newbyteorder('big') will work.

But, probably easier and clearer is just to use:

dlittle = numpy.dtype('<f8') dbig = numpy.dtype('>f8')

There are now full-fledged data-type objects in NumPy. These can be used everywhere old typecodes were used. In fact, all other aliases get converted to these data-type objects because they are what NumPy needs to construct the ndarray.

These data-type objects are an important part of the basearray concept being introduced to Python, so education about them is very timely.
They are an out-growth of the PyArray_Descr * structure that Numeric used to "represent" a data-type internally. Basically , the old PyArray_Descr * structure was enhanced and given an Object header.

Even just getting these data-type objects into Python would be a useful first-step to exchanging data.

For NumPy, the data-type objects have enabled very sophisticated data-type specification and are key to record-array support in NumPy.

Best,

-Travis

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