Converting bool to float

Charles R Harris charlesr.harris at gmail.com
Wed Nov 1 21:19:45 CST 2006


On 11/1/06, Keith Goodman <kwgoodman at gmail.com> wrote:
>
> On 11/1/06, Travis Oliphant <oliphant at ee.byu.edu> 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
> >
> > This can't be changed at this point until 1.1
> >
> > We will fix the bug in 1.0*x producing float64, however.  I'm still not
> > sure what's causing it, though.
>
> I think it would be great if float64 was the default in numpy. That
> way most people wouldn't have to worry about dtypes when crunching
> numbers. And then numpy could apply for a trademark on 'it just
> works'.
>
> Having to worry about dtypes makes users (me) nervous.
>
> I imagine a change like this would not be an overnight change, more of
> a long-term goal.
>
> This one, from a previous thread, also makes me nervous:
>
> >> sum(M.ones((300,1)) == 1)
> matrix([[44]], dtype=int8)


That one seems to be fixed:

In [1]: sum(ones((300,1)) == 1)
Out[1]: 300

In [2]: (ones((300,1)) == 1).sum()
Out[2]: 300

The matrix version also returns a numpy scalar, however.

In [20]: sum(matrix(ones((300,1)) == 1))
Out[20]: 300

I wonder if that is expected?

Chuck
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