Re: [Numpy-discussion] numpy.mean still broken for largefloat32arrays
At 01:22 AM 7/25/2014, you wrote:
Actually the maximum precision I am not so sure of, as I personally prefer to make an informed decision about precision used, and get an error on a platform that does not support the specified precision, rather than obtain subtly or horribly broken results without warning when moving your code to a different platform/compiler whatever.
We were talking on this in the office, as we realized it does affect a couple of lines dealing with large arrays, including complex64. As I expect Python modules to work uniformly cross platform unless documented otherwise, to me that includes 32 vs 64 bit platforms, implying that the modules should automatically use large enough accumulators for the data type input. http://docs.scipy.org/doc/numpy/reference/generated/numpy.mean.html does mention inaccuracy. http://docs.scipy.org/doc/scipy-0.13.0/reference/generated/scipy.stats.mstat... http://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html etc do not, exactly - Ray
On Fri, Jul 25, 2014 at 3:11 PM, RayS <rays@blue-cove.com> wrote:
At 01:22 AM 7/25/2014, you wrote:
Actually the maximum precision I am not so sure of, as I personally prefer to make an informed decision about precision used, and get an error on a platform that does not support the specified precision, rather than obtain subtly or horribly broken results without warning when moving your code to a different platform/compiler whatever.
We were talking on this in the office, as we realized it does affect a couple of lines dealing with large arrays, including complex64. As I expect Python modules to work uniformly cross platform unless documented otherwise, to me that includes 32 vs 64 bit platforms, implying that the modules should automatically use large enough accumulators for the data type input.
The 32/64-bitness of your platform has nothing to do with floating point. Nothing discussed in this thread is platform-specific (modulo some minor details about the hardware FPU, but that should be taken as read). -- Robert Kern
participants (2)
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RayS
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Robert Kern