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Announcing carray 0.4
What's new
The most prominent feature in 0.4 is the support of multidimensional
carrays. Than means that, for example, you can do::
>>> a = ca.arange(6).reshape((2,3))
Now, you can access any element in any dimension::
>>> a[:]
array([[0, 1, 2],
[3, 4, 5]])
>>> a[1]
array([3, 4, 5])
>>> a[1,::2]
array([3, 5])
>>> a[1,1]
Also, all the iterators in carray have received a couple of new
parameters that allows to `limit` or `skip` selected elements in
Finally, many performance improvements have been implemented (mainly
related with efficient zero-detection code). This allows for improved
query times when using iterators.
for an example on how fast the new iterators can do.
For more detailed info, see the release notes in:
What it is
carray is a chunked container for numerical data. Chunking allows for
efficient enlarging/shrinking of data container. In addition, it can
also be compressed for reducing memory needs. The compression process
is carried out internally by Blosc, a high-performance compressor that
is optimized for binary data.
carray comes with an exhaustive test suite and fully supports both
32-bit and 64-bit platforms. Also, it is typically tested on both UNIX
and Windows operating systems.
Visit the main carray site repository at:
You can download a source package from:
Home of Blosc compressor:
User's mail list:
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