On Monday 17 July 2006 12:38, Travis Oliphant wrote: > Sebastian Haase wrote: > > On Monday 17 July 2006 12:10, Travis Oliphant wrote: > >> Sebastian Haase wrote: > >>> Traceback (most recent call last): > >>> File "<input>", line 1, in ? > >>> TypeError: array cannot be safely cast to required type > >>> > >>>>>> dd=d.astype(N.float32) > >>>>>> N.dot(dd,ccc) > >>> > >>> [[[ 1. 1. 1.] > >>> [ 1. 1. 1.] > >>> [ 1. 1. 1.]] > >>> > >>> [[ 2. 2. 2.] > >>> [ 2. 2. 2.] > >>> [ 2. 2. 2.]]] > >>> > >>> > >>> > >>> The TypeError looks like a numpy bug ! > >> > >> I don't see why this is a bug. You are trying to coerce a 32-bit > >> integer to a 32-bit float. That is going to lose precision and so you > >> get the error indicated. > >> > >> -Travis > > > > In numarray I do not get an error. Would the error go away if I had 64 > > bit float !? It seems though that having ones and twos in an int array > > should fit just fine into a float32 array !? > > This could be considered a bug in numarray. It's force-casting the > result. That isn't the normal behavior of mixed-type functions. > > Also, the policy on type-casting is not to search the array to see if > it's possible to do the conversion on every element (that would be slow > on large arrays). The policy is to base the decision only on the > data-types themselves (i.e. whether it's *possible* to lose precision*). > > -Travis > > > > *There is one exception to this policy in NumPy: 64-bit integers are > allowed to be cast to 64-bit doubles --- other-wise on you would get a > lot of non-standard long-doubles showing up on 64-bit systems. This > policy was decided after discussion last year.
OK - understood. Combining int32 with float64 proves to be less cumbersome ... Any idea on my main question ? What is the dot product of a 2x2 and 3x2x3 supposed to look like ? Why are numarray and numpy giving different answers ?? Thanks, Sebastian Haase ------------------------------------------------------------------------- Take Surveys. Earn Cash. Influence the Future of IT Join SourceForge.net's Techsay panel and you'll get the chance to share your opinions on IT & business topics through brief surveys -- and earn cash http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion