On Wed, Sep 8, 2010 at 14:44, Michael Gilbert <michael.s.gilb...@gmail.com> wrote: > On Wed, Sep 8, 2010 at 12:23 PM, Charles R Harris wrote: >> >> >> On Wed, Sep 8, 2010 at 9:46 AM, Michael Gilbert >> <michael.s.gilb...@gmail.com> wrote: >>> >>> On Wed, 8 Sep 2010 09:43:56 -0600, Charles R Harris wrote: >>> > On Wed, Sep 8, 2010 at 9:26 AM, Michael Gilbert >>> > <michael.s.gilb...@gmail.com >>> > > wrote: >>> > >>> > > Hi, >>> > > >>> > > Are there any plans to add support for decimal floating point >>> > > arithmetic, as defined in the 2008 revision of the IEEE 754 standard >>> > > [0], in numpy? >>> > > >>> > > >>> > Not at the moment. There is currently no hardware or C support and >>> > adding >>> > new types to numpy isn't trivial. You can get some limited Decimal >>> > functionality by using python classes and object arrays, for instance >>> > the >>> > Decimal class in the python decimal module, but the performance isn't >>> > great. >>> > >>> > What is your particular interest in decimal support? >>> >>> Primarily avoiding catastrophic cancellation when subtracting >>> large values. I was planning to use the decimal class, but was >>> curious whether support for the IEEE standard was coming any time soon. >>> >> >> If you just need more precision, mpmath has better performance than the >> Decimal class. Also, it might be possible to avoid the loss of precision by >> changing the computation, but I don't know the details of what you are >> doing. > > Just wanted to say that numpy object arrays + decimal solved all of my > problems, which were all caused by the disconnect between decimal and > binary representation of floating point numbers.
Are you sure? Unless if I'm failing to think through this properly, catastrophic cancellation for large numbers is an intrinsic property of fixed-precision floating point regardless of the base. decimal and mpmath both help with that problem because they have arbitrary precision. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
