Hi nice numpy people
I was wondering if anyone could shed some light on how to distinguish an
empty array of a given shape and an zeros array of the same dimensions.
Thanks
Andy
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It does indeed work
Thanks for the help
Andy
LB wrote:
> If you just want to add your matrix to an existing ascii file, you can
> open this file in append mode and give the file handle to
> numpy.savetxt :
>
> f_handle = file('my_file.dat', 'a')
> savetxt(f_handle, my_matrix)
> f_handle.close()
Hi people,
Just a quick question, how do I append a numpy array to an existing
ascii output file? I've looked at the numpy.savetxt function and it
performs all the formating functions I desire for my output file but it
doesn't let me specify how I save my array type
Is there a clever work aroun
Dear nice people
I'm trying to match a row (b) within a large numpy array (a). My most
successful attempt is below
hit = equal(b, a)
total_hits = add.reduce(hit, 1)
max_hit = argmax(total_hits, 0)
answer = a[max_hit]
where ...
a = array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
u already knew that one, as it
> is b)
>
> a[row]
>
> or the row index
>
> find(row==True)
>
> Mark
>
> On Aug 15, 11:53 am, Andy Cheesman <[EMAIL PROTECTED]>
> wrote:
>> Dear nice people
>>
>> I'm trying to match a row (b) withi
Dear nice people
I'm trying to match a row (b) within a large numpy array (a). My most
successful attempt is below
hit = equal(b, a)
total_hits = add.reduce(hit, 1)
max_hit = argmax(total_hits, 0)
answer = a[max_hit]
where ...
a = array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
Hi people,
I was wondering if people could give me a pointer or two upon the
efficient identification of neighbouring sites for a given point upon a
numpy array which has periodic conditions.
Suggestions upon the web I've seen seem to use lots of loops which does
not seem to be the most economical
