Charles R Harris wrote:
On Fri, May 1, 2009 at 7:39 PM, Charles R Harris <charlesr.harris@gmail.com>wrote:
On Fri, May 1, 2009 at 7:24 PM, Neal Becker <ndbecker2@gmail.com> wrote:
Charles R Harris wrote:
On Fri, May 1, 2009 at 1:02 PM, Neal Becker <ndbecker2@gmail.com> wrote:
In [16]: (np.linspace (0, len (x)-1, len(x)).astype (np.uint64)*2).dtype Out[16]: dtype('uint64')
In [17]: (np.linspace (0, len (x)-1, len(x)).astype (np.uint64)*n).dtype Out[17]: dtype('float64')
In [18]: type(n) Out[18]: <type 'int'>
Now that's just strange. What's going on?
The n is signed, uint64 is unsigned. So a signed type that can hold uint64 is needed. There ain't no such integer, so float64 is used. I think the logic here is a bit goofy myself since float64 doesn't have the needed 64 bit precision and the conversion from int kind to float kind is confusing. I think it would be better to raise a NotAvailable error or some such. Lest you think this is an isolated oddity, sometimes numeric arrays can be converted to object arrays.
Chuck
I don't think that any type of integer arithmetic should ever be automatically promoted to float.
Besides that, what about the first example? There, I used '2' rather than 'n'. Is not '2' also an int?
What version of numpy are you using?
And what is the value of n?
Chuck
np.version.version Out[5]: '1.3.0' (I think the previous test was on 1.2.0 and did the same thing) (np.linspace (0, 1023,1024).astype(np.uint64)*2).dtype Out[2]: dtype('uint64') In [3]: n=-7 In [4]: (np.linspace (0, 1023,1024).astype(np.uint64)*n).dtype Out[4]: dtype('float64')