Hi,
Is there any documentation about algorithms available in Moose-Algos-Graph? It looks interesting but there is no class comment ...
Thanks, Christophe.
Just found this: MalGraphFixture class>>view:
It contains several examples. For example: MalGraphFixture view: #moduleGraph: MalGraphFixture view: #nestedCycleGraph:
Hope this is useful…
Alexandre
On Mar 20, 2015, at 2:02 PM, Christophe Demarey Christophe.Demarey@inria.fr wrote:
Hi,
Is there any documentation about algorithms available in Moose-Algos-Graph? It looks interesting but there is no class comment ...
Thanks, Christophe._______________________________________________ Moose-dev mailing list Moose-dev@iam.unibe.ch https://www.iam.unibe.ch/mailman/listinfo/moose-dev
Le 20 mars 2015 à 19:11, Alexandre Bergel a écrit :
Just found this: MalGraphFixture class>>view:
It contains several examples. For example: MalGraphFixture view: #moduleGraph: MalGraphFixture view: #nestedCycleGraph:
Hope this is useful…
I also saw that. It is useful to understand tests / examples. The point is that you don't know what algorithms do. For some well known algorithm, it is obvious but not for others. I'm adding comments where I can.
Thanks, Christophe
It would be fantastic to have a Roassal illustration of the algorithm.
Alexandre
Le 24 mars 2015 à 07:15, Christophe Demarey Christophe.Demarey@inria.fr a écrit :
Le 20 mars 2015 à 19:11, Alexandre Bergel a écrit :
Just found this: MalGraphFixture class>>view:
It contains several examples. For example: MalGraphFixture view: #moduleGraph: MalGraphFixture view: #nestedCycleGraph:
Hope this is useful…
I also saw that. It is useful to understand tests / examples. The point is that you don't know what algorithms do. For some well known algorithm, it is obvious but not for others. I'm adding comments where I can.
Thanks, Christophe
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On Tue, Mar 24, 2015 at 12:45 PM, Alexandre Bergel alexandre.bergel@me.com wrote:
It would be fantastic to have a Roassal illustration of the algorithm.
Yes !
Meanwhile, you can have a look to some basic complex network generation algorithms I have done some months ago: http://smalltalkhub.com/#!/~SergeStinckwich/Moose-Algos-Graph-Generators
Run in a playground:
| v g nodes edges | v := RTView new. g := MalErdosRenyiGNMGraphGenerator new. g nodes: (1 to: 1000); edgesNumber: 700. g run. nodes := (RTEllipse new color: (Color purple alpha: 0.3); size:10) elementsOn: g nodes. nodes @ RTDraggable. v addAll: nodes. edges := RTEdge buildEdgesFromObjects: (g edges) from:#from to:#to using: (RTLine new color: (Color purple alpha:0.2)) inView:v. edges do: [: e| e trachelShape pushBack]. v addAnimation: (RTSpringLayoutStepping new view: v). v @ RTDraggableView. v
Regards,
Wow!
What is that?
Alexandre
On Mar 24, 2015, at 9:44 AM, Serge Stinckwich serge.stinckwich@gmail.com wrote:
On Tue, Mar 24, 2015 at 12:45 PM, Alexandre Bergel alexandre.bergel@me.com wrote:
It would be fantastic to have a Roassal illustration of the algorithm.
Yes !
Meanwhile, you can have a look to some basic complex network generation algorithms I have done some months ago: http://smalltalkhub.com/#!/~SergeStinckwich/Moose-Algos-Graph-Generators
Run in a playground:
| v g nodes edges | v := RTView new. g := MalErdosRenyiGNMGraphGenerator new. g nodes: (1 to: 1000); edgesNumber: 700. g run. nodes := (RTEllipse new color: (Color purple alpha: 0.3); size:10) elementsOn: g nodes. nodes @ RTDraggable. v addAll: nodes. edges := RTEdge buildEdgesFromObjects: (g edges) from:#from to:#to using: (RTLine new color: (Color purple alpha:0.2)) inView:v. edges do: [: e| e trachelShape pushBack]. v addAnimation: (RTSpringLayoutStepping new view: v). v @ RTDraggableView. v
Regards,
Serge Stinckwich UCBN & UMI UMMISCO 209 (IRD/UPMC) Every DSL ends up being Smalltalk http://www.doesnotunderstand.org/ <Screen Shot 2015-03-24 at 13.42.06.png>_______________________________________________ Moose-dev mailing list Moose-dev@iam.unibe.ch https://www.iam.unibe.ch/mailman/listinfo/moose-dev
What do you want to know ?
I just create a random Erdos-Renyi G(N,M) random network with 1000 nodes (N) and 700 edges between nodes (M). The graph is chosen uniformly at random from the collection of all graphs with N nodes and M edges.
More informations here: https://en.wikipedia.org/wiki/Erd%C5%91s%E2%80%93R%C3%A9nyi_model
There is many ways to generate random graphs. The most common one are the Erdos-Renyi and Babarasi-Albert algorithms.
On Tue, Mar 24, 2015 at 11:50 PM, Alexandre Bergel alexandre.bergel@me.com wrote:
Wow!
What is that?
Alexandre
On Mar 24, 2015, at 9:44 AM, Serge Stinckwich serge.stinckwich@gmail.com wrote:
On Tue, Mar 24, 2015 at 12:45 PM, Alexandre Bergel alexandre.bergel@me.com wrote:
It would be fantastic to have a Roassal illustration of the algorithm.
Yes !
Meanwhile, you can have a look to some basic complex network generation algorithms I have done some months ago: http://smalltalkhub.com/#!/~SergeStinckwich/Moose-Algos-Graph-Generators
Run in a playground:
| v g nodes edges | v := RTView new. g := MalErdosRenyiGNMGraphGenerator new. g nodes: (1 to: 1000); edgesNumber: 700. g run. nodes := (RTEllipse new color: (Color purple alpha: 0.3); size:10) elementsOn: g nodes. nodes @ RTDraggable. v addAll: nodes. edges := RTEdge buildEdgesFromObjects: (g edges) from:#from to:#to using: (RTLine new color: (Color purple alpha:0.2)) inView:v. edges do: [: e| e trachelShape pushBack]. v addAnimation: (RTSpringLayoutStepping new view: v). v @ RTDraggableView. v
Regards,
Serge Stinckwich UCBN & UMI UMMISCO 209 (IRD/UPMC) Every DSL ends up being Smalltalk http://www.doesnotunderstand.org/ <Screen Shot 2015-03-24 at 13.42.06.png>_______________________________________________ Moose-dev mailing list Moose-dev@iam.unibe.ch https://www.iam.unibe.ch/mailman/listinfo/moose-dev
-- _,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;: Alexandre Bergel http://www.bergel.eu ^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;.
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