Dear all,
I have a code using lots of numpy.where to make some constrained
calculations as in:
data = arange(10)
result = np.where(data == 0, 0., 1./data)
# or
data1 = arange(10)
data2 = arange(10)+1.0
result = np.where(data1 data2, np.sqrt(data1-data2), np.sqrt(data2-data2))
which then
On Sat, Jan 5, 2013 at 2:15 PM, Eric Emsellem eric.emsel...@eso.org wrote:
Dear all,
I have a code using lots of numpy.where to make some constrained
calculations as in:
data = arange(10)
result = np.where(data == 0, 0., 1./data)
# or
data1 = arange(10)
data2 = arange(10)+1.0
result =
Thanks!
This makes sense of course. And yes the operation I am trying to do is
rather complicated so I need to rely on a prior selection.
Now I would need to optimise this for large arrays and the code does go
through these command line many many times.
When I have to operate on the two
Thanks!
This makes sense of course. And yes the operation I am trying to do is
rather complicated so I need to rely on a prior selection.
Now I would need to optimise this for large arrays and the code does go
through these command line many many times.
When I have to operate on the two
Thanks!
This makes sense of course. And yes the operation I am trying to do is
rather complicated so I need to rely on a prior selection.
Now I would need to optimise this for large arrays and the code does go
through these command line many many times.
When I have to operate on the two
On Sat, Jan 5, 2013 at 10:07 PM, Eric Emsellem eric.emsel...@eso.org wrote:
Thanks!
This makes sense of course. And yes the operation I am trying to do is
rather complicated so I need to rely on a prior selection.
Now I would need to optimise this for large arrays and the code does go