vj wrote:
> What should I be using to replace Numeric/arrayobject.h:
>
> numpy/arrayobject.h
>
> or
>
> numpy/oldnumeric.h
Replacing "numpy/oldnumeric.h" is the compatibility header. If you don't want to
convert your code to use the new APIs (and you might; it is much improved), then
that shoul
What should I be using to replace Numeric/arrayobject.h:
numpy/arrayobject.h
or
numpy/oldnumeric.h
Thanks,
VJ
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vj wrote:
>> Note that the mask needs to be a bool array.
>
mask = zeros(5)
mask = zeros(5, numpy.int8)
mask[1] = True
mask[2] = True
a = zeros(5)
a[mask] = [100, 200]
a
> array([ 100., 100.,0.,0.,0.])
>
> I found this strange. It should just give a
> Note that the mask needs to be a bool array.
>>> mask = zeros(5)
>>> mask = zeros(5, numpy.int8)
>>> mask[1] = True
>>> mask[2] = True
>>> a = zeros(5)
>>> a[mask] = [100, 200]
>>> a
array([ 100., 100.,0.,0.,0.])
I found this strange. It should just give an error if you try to use
vj wrote:
>> It is just a redirection to the [EMAIL PROTECTED] list. If you just
>> tried in the past hour or so, I've discovered that our DNS appears to be down
>> right now.
>
> I tried registering the twice the last couple of days and never got an
> email back.
Hmm. Odd. I just tried to regist
> It is just a redirection to the [EMAIL PROTECTED] list. If you just
> tried in the past hour or so, I've discovered that our DNS appears to be down
> right now.
I tried registering the twice the last couple of days and never got an
email back.
> No, that's not what insert() does. See the docstr
vj wrote:
> I've tried to post this to the numpy google group but it seems to be
> down.
It is just a redirection to the numpy-discussion@scipy.org list. If you just
tried in the past hour or so, I've discovered that our DNS appears to be down
right now.
> My migration seems to be going well. I c
I've tried to post this to the numpy google group but it seems to be
down. My migration seems to be going well. I currently have one issue
with using scipy_base.insert.
>>> a = zeros(5)
>>> mask = zeros(5)
>>> mask[1] = 1
>>> c = zeros(1)
>>> c[0] = 100
>>> numpy.insert(a, mask, c)
array([ 100.,
