There is no specific date yet, but I plan to cut intermediate release(s) as
Incanter 1.9.x so you can try new functionality & report bugs if you find
some. After this stabilization phase (together with accepting pending pull
requests & fixing the issues) the version 2.0 will be released - I hope
that this will happen in October.

I'll send separate notification (together with longer blog post) when 1.9.0
will be pushed to clojar


On Mon, Aug 25, 2014 at 12:21 PM, Gadzhi Musaev <musaevgad...@gmail.com>
wrote:

> So, can you tell us, when Incanter 2.0 will be released?)
>
>
> On 25 August 2014 11:08, Ambrose Bonnaire-Sergeant <
> abonnaireserge...@gmail.com> wrote:
>
>> Fantastic!
>>
>> Thanks,
>> Ambrose
>>
>>
>> On Mon, Aug 25, 2014 at 2:15 AM, Mikera <mike.r.anderson...@gmail.com>
>> wrote:
>>
>>> Hi All,
>>>
>>> Prasant and Aleksandr have been working all summer making Clojure even
>>> better for data science / numerical computing. On behalf of myself and my
>>> co-mentor Alex Ott I want to offer congratulations to them both for
>>> successfully completing their Google Summer of Code projects!
>>>
>>> Thanks to Prasant, we now have full, idiomatic, linear algebra support
>>> for Clojure. The implementation (part of vectorz-clj) is pure JVM code -
>>> i.e. no need for native dependencies. In terms of performance, we are
>>> already competitive with many Java matrix implementations and with some
>>> further optimisation could easily be one of the fastest linear algebra
>>> libaries on the JVM. To see the results of Prasant's work, check out
>>> core.matrix, vectorz-clj and vectorz.
>>>
>>> https://github.com/mikera/core.matrix
>>> https://github.com/mikera/vectorz
>>> https://github.com/mikera/vectorz-clj
>>>
>>> Thanks to Aleksandr, we have completed the Incanter / core.matrix
>>> implementation work which will make it possible to use core.matrix
>>> implementations seamlessly within Incanter 2.0. You can use regular Clojure
>>> vectors (nested persistent vectors of numbers), vectorz-clj (pure JVM,
>>> double precision), Clatrix (native BLAS support) or any combination of
>>> these. There is also new, improved "Dataset" support which makes it
>>> possible to create custom dataset types by implementing some new dataset
>>> protocols. To see the results of Aleksandr's work, check out Incanter,
>>> Clatrix and core.matrix
>>>
>>> https://github.com/incanter/incanter
>>> https://github.com/tel/clatrix/commits/master
>>> https://github.com/mikera/core.matrix
>>>
>>> Taken together, these projects represent a significant step towards
>>> making Clojure a leading language for data science and analytics.
>>>
>>> Well done Prasant and Aleksandr!
>>>
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-- 
With best wishes,                    Alex Ott
http://alexott.net/
Twitter: alexott_en (English), alexott (Russian)
Skype: alex.ott

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