Le 27/6/15 12:40, Serge Stinckwich a écrit :
Good job Pierre !

I was looking exactly to the same document recently and thought that I could try to reproduce some examples from chapter 3.

Yes I pass it to alex because pierre will visit us and I propose to enhance the statistical part as well build on top of NeoCSV to improve
data collection.
Maybe we can join our effort and reproduce the examples as a Pillar chapter somewhere ?
Serge the histogram objects (not the drawer) should be packaged in SciSmalltalk.



On Sat, Jun 27, 2015 at 12:16 AM, Pierre CHANSON <chans.pierre@gmail.com> wrote:
Hola todos,

These days I am working on compete with R. I am taking the datasets and examples from http://cran.r-project.org/doc/contrib/Zhao_R_and_data_mining.pdf and make it with Roassal even better ! Or almost... ;)

First chapter first pages, the histograms... In Roassal they were not working so well.

So lately I restructured the RTDistribution package. This, by default make a classical frequency distribution, with an optimized number of classes. The method #strategyBlock: allows to change the strategy for the distribution.

I also worked on the RTHistogramSet and method #histogram of SequenceableCollection to improve a bit the looking. There  is still here some work to do  but at least the histogram works well and looks fine.

We worked with Alejandro on the algorithm of frequency distribution to make it efficient compared to the classic one (Only one iteration on datas during the algo itself).

Here are some examples, don't hesitate to try a bit and give me feedbacks if any bugs, so I can move on the next graphs ;)

#(5 3 8 6 5 4 2 9 1 2) histogram.

#(1 2 3) histogram.

#(555 1 1 2) histogram.

((1 to: 1000) collect: [:i | i atRandom ]) histogram.

Also, I found this page and thought it was really nice animations !! http://bost.ocks.org/mike/algorithms/



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Serge Stinckwich
Every DSL ends up being Smalltalk

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