On Wed, Nov 01, 2006 at 08:16:59PM -0700, Tim Hochberg wrote: > Travis Oliphant wrote: > > Robert Kern wrote: > >> Travis Oliphant wrote: > >> > >>> It looks like 1.0-x is doing the right thing. > >>> > >>> The problem is 1.0*x for matrices is going to float64. For arrays it > >>> returns float32 just like the 1.0-x > >>> > >> Why is this the right thing? Python floats are float64. > >> > > Yeah, why indeed. Must be something with the scalar coercion code... > > This is one of those things that pops up every few years. I suspect that > the best thing to do here is to treat 1.0, and all Python floats as > having a kind (float), but no precision. Or, equivalently treat them as > the smallest precision floating point value. The rationale behind this > is that otherwise float32 array will be promoted whenever they are > multiplied by Python floating point scalars. If Python floats are > treated as Float64 for purposes of determining output precision then > anyone using float32 arrays is going to have to wrap all of their > literals in float32 to prevent inadvertent upcasting to float64. This > was the origin of the (rather clunky) numarray spacesaver flag.
I'm one of those people who made serious use of that clunky spacesaver flag for precisely this reason. I deal with several GB arrays of 32-bit floats (or 32-bit x2 complex numbers) on a regular basis. Having automatic upcasting from scalar operations can be a royal pain. Scott -- Scott M. Ransom Address: NRAO Phone: (434) 296-0320 520 Edgemont Rd. email: [EMAIL PROTECTED] Charlottesville, VA 22903 USA GPG Fingerprint: 06A9 9553 78BE 16DB 407B FFCA 9BFA B6FF FFD3 2989 ------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
