Cross cost grid layout - Revision history

Lan@dote.ru: +stub message

2013-07-02T06:39:28Z

+stub message

Lan@dote.ru: /* See also */

2013-06-14T10:23:52Z

‎See also

Stan.lo@dote.ru at 10:19, 14 June 2013

2013-06-14T10:19:20Z

Lan@dote.ru at 08:57, 14 June 2013

2013-06-14T08:57:02Z

Lan@dote.ru: +picture

2013-06-14T08:26:33Z

+picture

Lan@dote.ru: +Category:Layout algorithms

2013-06-14T04:32:31Z

+Category:Layout algorithms

Stan.lo@dote.ru at 13:18, 13 June 2013

2013-06-13T13:18:33Z

Stan.lo@dote.ru: from the workbench help

2013-06-13T13:17:04Z

from the workbench help

New page

This is a grid-based algorithm that considers (a) edge-edge crossings, (b) node-edge crossings, (c) node-node crossings, (d) distances between nodes in its cost function . This algorithm uses a weight matrix representing the difference between two sequentially obtained layouts for computing the costs, takes a greedy algorithm for searching locally optimal solutions and simulated annealing for global optimization.

The following parameters of the algorithm must be set:
* GridX - positive integer parameter represents horizontal grid step in pixels
* GridY - positive integer parameter represents vertical grid step in pixels
* Number of iteration - positive integer parameter represents number of iterations during same temperature in simulated annealing
* Cooling coefficient - real number between 0 and 1 represents cooling coefficient of simulated annealing (small value decrease computation time but leads to quality loss)
* Perturbation threshold - real value parameter between 0 and 1 represents probability of layout perturbation during simulated annealing
* Max distance - positive integer parameter represents maximum repulsive distance expressed in number of grid steps (if distance between two nodes exceeds Max distance then there is no repulsion between them).

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 {{Layout algorithm|ru.biosoft.graph.CompartmentCrossCostGridLayouter}}
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 This is a grid-based algorithm that considers (a) edge-edge crossings, (b) node-edge crossings, (c) node-node crossings, (d) distances between nodes in its cost function . This algorithm uses a weight matrix representing the difference between two sequentially obtained  layouts for computing the costs, takes a greedy algorithm for searching locally optimal solutions and simulated annealing for global optimization.

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	==See also==		==See also==
−	* [[~~Diagram_document~~]]	+	* [[Diagram document]]

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	* Perturbation threshold - real value parameter between 0 and 1 represents probability of layout perturbation during simulated annealing		* Perturbation threshold - real value parameter between 0 and 1 represents probability of layout perturbation during simulated annealing
	* Max distance - positive integer parameter represents maximum repulsive distance expressed in number of grid steps (if distance between two nodes exceeds Max distance then there is no repulsion between them).		* Max distance - positive integer parameter represents maximum repulsive distance expressed in number of grid steps (if distance between two nodes exceeds Max distance then there is no repulsion between them).
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		+	==See also==
		+	* [[Diagram_document]]

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		+	[[File:Diagram cross cost grid layout.png\|thumb\|Diagram "Aguda1999_CellCycle" layouted using the cross cost grid layout algorithm.]]

	This is a grid-based algorithm that considers (a) edge-edge crossings, (b) node-edge crossings, (c) node-node crossings, (d) distances between nodes in its cost function . This algorithm uses a weight matrix representing the difference between two sequentially obtained layouts for computing the costs, takes a greedy algorithm for searching locally optimal solutions and simulated annealing for global optimization.		This is a grid-based algorithm that considers (a) edge-edge crossings, (b) node-edge crossings, (c) node-node crossings, (d) distances between nodes in its cost function . This algorithm uses a weight matrix representing the difference between two sequentially obtained layouts for computing the costs, takes a greedy algorithm for searching locally optimal solutions and simulated annealing for global optimization.

← Older revision		Revision as of 04:32, 14 June 2013
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	* Perturbation threshold - real value parameter between 0 and 1 represents probability of layout perturbation during simulated annealing		* Perturbation threshold - real value parameter between 0 and 1 represents probability of layout perturbation during simulated annealing
	* Max distance - positive integer parameter represents maximum repulsive distance expressed in number of grid steps (if distance between two nodes exceeds Max distance then there is no repulsion between them).		* Max distance - positive integer parameter represents maximum repulsive distance expressed in number of grid steps (if distance between two nodes exceeds Max distance then there is no repulsion between them).
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		+	[[Category:Layout algorithms]]

← Older revision		Revision as of 13:18, 13 June 2013
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	This is a grid-based algorithm that considers (a) edge-edge crossings, (b) node-edge crossings, (c) node-node crossings, (d) distances between nodes in its cost function . This algorithm uses a weight matrix representing the difference between two sequentially obtained layouts for computing the costs, takes a greedy algorithm for searching locally optimal solutions and simulated annealing for global optimization.		This is a grid-based algorithm that considers (a) edge-edge crossings, (b) node-edge crossings, (c) node-node crossings, (d) distances between nodes in its cost function . This algorithm uses a weight matrix representing the difference between two sequentially obtained layouts for computing the costs, takes a greedy algorithm for searching locally optimal solutions and simulated annealing for global optimization.