On Wed, Jul 2, 2014 at 7:57 AM, Mark Szepieniec <mszepien@gmail.com> wrote:
Looks this could be a float32 vs float64 problem:
that would explain it.
I guess users always be very careful when mixing floating point types, but should numpy prevent (or warn) the user from doing so in this case?
I don't think so -- this "uncertainty" is very much the nature of histogramming, particularly with floating point values -- you should expect to get different results with different data precisions. As you should for ANY floating point computation. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov