Hi,
I am sorry for the late reply.
Benjamin has hit the nail on the head. I guess I am seeing numpy
"fancy indexing" as equivalent to integer based coordinate sampling
and trying to compare numpy's fancy indexing to something like
map_coordinates in scipy.
I have never used np.ravel_multi_index(
On Mon, Jan 16, 2012 at 3:30 PM, Benjamin Root wrote:
>
>
> On Mon, Jan 16, 2012 at 3:24 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Sat, Jan 14, 2012 at 4:53 PM, Nathan Faggian > > wrote:
>>
>>> Hi,
>>>
>>> I am finding it less than useful to have the negative index
On Mon, Jan 16, 2012 at 3:24 PM, Charles R Harris wrote:
>
>
> On Sat, Jan 14, 2012 at 4:53 PM, Nathan Faggian
> wrote:
>
>> Hi,
>>
>> I am finding it less than useful to have the negative index wrapping on
>> nd-arrays. Here is a short example:
>>
>> import numpy as np
>> a = np.zeros((3, 3))
>
On Sat, Jan 14, 2012 at 4:53 PM, Nathan Faggian wrote:
> Hi,
>
> I am finding it less than useful to have the negative index wrapping on
> nd-arrays. Here is a short example:
>
> import numpy as np
> a = np.zeros((3, 3))
> a[:,2] = 1000
> print a[0,-1]
> print a[0,-1]
> print a[-1,-1]
>
> In all c
On Sun, Jan 15, 2012 at 6:54 AM, David Cournapeau wrote:
> On Sat, Jan 14, 2012 at 11:53 PM, Nathan Faggian
> wrote:
> > Hi,
> >
> > I am finding it less than useful to have the negative index wrapping on
> nd-arrays. Here is a short example:
> >
> > import numpy as np
> > a = np.zeros((3, 3))
>
On Sat, Jan 14, 2012 at 11:53 PM, Nathan Faggian
wrote:
> Hi,
>
> I am finding it less than useful to have the negative index wrapping on
> nd-arrays. Here is a short example:
>
> import numpy as np
> a = np.zeros((3, 3))
> a[:,2] = 1000
> print a[0,-1]
> print a[0,-1]
> print a[-1,-1]
>
> In all
On 15/01/12 00:53, Nathan Faggian wrote:
> Hi,
>
> I am finding it less than useful to have the negative index wrapping
> on nd-arrays. Here is a short example:
>
> import numpy as np
> a = np.zeros((3, 3))
> a[:,2] = 1000
> print a[0,-1]
> print a[0,-1]
> print a[-1,-1]
>
> In all cases 1000 is
Hi,
I am finding it less than useful to have the negative index wrapping on
nd-arrays. Here is a short example:
import numpy as np
a = np.zeros((3, 3))
a[:,2] = 1000
print a[0,-1]
print a[0,-1]
print a[-1,-1]
In all cases 1000 is printed out.
What I am after is a way to say "please don't wrap
