Probably correct, Quincey might know better how far the hyperslab
implementation could be modified to allow a negative stride. Maybe it
wouldn't be much of a change, just there was no need so far to do it. If
that is the case, then at least it would mean that the "hyperslab
grammar" would indeed allow operations like transpose (and rotation) of
a dataset, just the implementation does not support it. That aside, it's
probably not efficient as it would require multiple hyperslab
operations, so a point selection would be faster, but for big data and
out-of-core data management, sometimes seemingly inefficient operations
turn out to be better.
On 26.04.2017 00:13, Isaac Gerg wrote:
I am not sure if you are allowed a negative stride but even if you
are, I believe the transpose still won't work because the stride
doesnt stride dimension like numpy but strides across the memory space
and wrap is not allowed. Does this line of thinking make sense?
On Tue, Apr 25, 2017 at 6:06 PM, Werner Benger <[email protected]
<mailto:[email protected]>> wrote:
Hi Isaac,
it's just thought that it could be done like this:
Copy operation: start = 0, stride = 1
target_index = 0 + source_index * 1
Reflection: start = max_index, stride = -1
target_index = max_index + source_index * -1
So a negative stride in one dimensions would go "backwards", thus
do a reflection in this direction. In practice the stride
parameter is probably an unsigned integer and thus running out of
bounds instead of going backwards, as you say.
Werner
On 25.04.2017 23:48, Isaac Gerg wrote:
Hi Werner, thanks for the reply. Let's wrestle with this a bit.
So numpy does their indexing by strides, the stride for each
dimension. hdf5 does their "striding" across the data in the
sense of more of a selection than a stride. I would be inclined
to say that even a negative stride wouldnt allow this. The
problem is the stride is a simply stride and not one based on
dimension index so the stride can't wrap so you end up with out
of bounds issues with the datasets. Does this seem right?
On Tue, Apr 25, 2017 at 5:29 PM, Werner Benger
<[email protected] <mailto:[email protected]>> wrote:
Hi Isaac,
without proof, but I could imagine it's possible to
implement a shear operation via hyperslabs. If so, then
hyperslabs could be used to implement rotations:
e.g.
https://www.ocf.berkeley.edu/~fricke/projects/israel/paeth/rotation_by_shearing.html
<https://www.ocf.berkeley.edu/%7Efricke/projects/israel/paeth/rotation_by_shearing.html>
To do a transpose, one would need a reflection in addition to
rotation (e.g. http://techieme.in/matrix-rotation/
<http://techieme.in/matrix-rotation/> ) , and I guess doing
this operation of a reflection is not possible via
hyperslabs, so doing a transpose is out of reach. Probably it
would require to allow something like a negative stride value...
Werner
On 25.04.2017 22:24, Isaac Gerg wrote:
Hi Quincy, I just was reading about point selections and was
wondering if that's the way we would go. Thanks for confirming!
On Tue, Apr 25, 2017 at 4:21 PM, Quincey Koziol
<[email protected] <mailto:[email protected]>> wrote:
> On Apr 25, 2017, at 1:02 PM, Isaac Gerg
<[email protected] <mailto:[email protected]>>
wrote:
>
> A coworker and I are mulling over if its possible to
take a simple 3x3 matrix (stored row major) in a
dataspace and write it out transposed to disk using a
hyperslab. It seems that the grammer provided by
start, stride, blocks, and count won't allow for this.
We hope we are wrong! It is possible to do this?
Hyperslabs won’t do this, but you could use a
point selection instead.
Quincey
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___________________________________________________________________________
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Center for Computation & Technology at Louisiana State University (CCT/LSU)
2019 Digital Media Center, Baton Rouge, Louisiana 70803
Tel.:+1 225 578 4809 <tel:%28225%29%20578-4809> Fax.:+1 225 578-5362 <tel:%28225%29%20578-5362>
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Center for Computation & Technology at Louisiana State University (CCT/LSU)
2019 Digital Media Center, Baton Rouge, Louisiana 70803
Tel.: +1 225 578 4809 Fax.: +1 225 578-5362
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