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gbeckers committed Sep 21, 2023
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Expand Up @@ -26,10 +26,10 @@ conclusions can be drawn:

- Float16 is not widely supported, but it is supported by two modern,
open source computing packages: Julia and Python with Numpy. It is best
avoided. Use float32, unless there are disk space concerns. Matlab can read
float16 indirectly, using a temporary array and type casting, which can be
problematic when arrays are very large and RAM is limited. Octave does not
support it (yet).
avoided from a compatibility perspective. Use float32, unless there are disk
space concerns. Matlab can read float16 indirectly, using a temporary array
and type casting, which can be problematic when arrays are very large and
RAM is limited. Octave does not support it (yet).

- If compatibility with R is important to you, have a good look at the table
in :doc:`Reading data in other environments <readcode>`. Despite all its
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