Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-27 Thread Nils Grunwald
Awsome! Thanks a lot, I can't wait to test this!

On Monday, August 25, 2014 8:15:51 AM UTC+2, Mikera 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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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread Ambrose Bonnaire-Sergeant
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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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread Gadzhi Musaev
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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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread Alex Ott
I join to congratulations - this is fantastic work!


On Mon, Aug 25, 2014 at 8:15 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!




-- 
With best wishes,Alex Ott
http://alexott.net/
Twitter: alexott_en (English), alexott (Russian)
Skype: alex.ott

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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread Alex Ott
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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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread Mars0i
Thank you! to Prasant and Aleksandr.

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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread Ashton Kemerling
Very Nice! I'd be particularly interested to see some benchmarks to show
off the improvements.

--
Ashton Kemerling


On Mon, Aug 25, 2014 at 12:57 PM, Mars0i marsh...@logical.net wrote:

 Thank you! to Prasant and Aleksandr.

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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread john walker
Thanks so much for your work! I'd be very interested to read more in detail 
about some of the work you did this summer.

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Re: GSoC: Congratulations Aleksandr and Prasant!

2014-08-25 Thread Michael O'Keefe
Awesome! Very much appreciated!

Michael

On Monday, August 25, 2014 12:15:51 AM UTC-6, Mikera 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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