Hi, On Wed, Jul 6, 2011 at 5:48 PM, Peter <numpy-discuss...@maubp.freeserve.co.uk> wrote: > On Wed, Jul 6, 2011 at 5:38 PM, Matthew Brett <matthew.br...@gmail.com> wrote: >> >> Hi, >> >> On Wed, Jul 6, 2011 at 4:40 PM, Mark Wiebe <mwwi...@gmail.com> wrote: >>> It appears to me that one of the biggest reason some of us have been talking >>> past each other in the discussions is that different people have different >>> definitions for the terms being used. Until this is thoroughly cleared up, I >>> feel the design process is tilting at windmills. >>> In the interests of clarity in our discussions, here is a starting point >>> which is consistent with the NEP. These definitions have been added in a >>> glossary within the NEP. If there are any ideas for amendments to these >>> definitions that we can agree on, I will update the NEP with those >>> amendments. Also, if I missed any important terms which need to be added, >>> please propose definitions for them. >>> NA (Not Available) >>> A placeholder for a value which is unknown to computations. That >>> value may be temporarily hidden with a mask, may have been lost >>> due to hard drive corruption, or gone for any number of reasons. >>> This is the same as NA in the R project. >> >> Really? Can one implement NA with a mask in R? I thought an NA was >> always bitpattern in R? > > I don't think that was what Mark was saying, see this bit later in this email:
I think it would make a difference if there was an implementation that had conflated masking with bitpatterns in terms of API. I don't think R is an example. >>> The most important distinctions I'm trying to draw are: >>> 1) NA vs IGNORE and bitpattern vs mask are completely independent. Any >>> combination of NA as bitpattern, NA as mask, IGNORE as bitpattern, and >>> IGNORE as mask are reasonable. > > This point as I understood it is there is the semantics of the special values > (not available vs ignore), and there is the implementation (bitpattern vs > mask), and they are independent. Yes. Although, we can see from the implementations that we have to hand that a) bitpatterns -> propagation (NaN-like) semantics by default (R) b) masks -> ignore semantics by default (masked arrays) I don't think Mark accepts that there is any reason for this tendency of implementations to semantics, but Nathaniel was arguing otherwise in the alterNEP. I think we all accept that it's possible to imagine masking have propagation semantics and bitpatterns having ignore semantics. Cheers, Matthew _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
