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## Diagram Orthogonal Graph Layout |

Nevron Diagram for .NET - Orthogonal Graph Layout

The research area of graph drawing has become an extensively studied field which presents an exciting connection between computational geometry and graph theory. The wide spectrum of applications includes VLSIlayout, software engineering, project management, database relations management, etc. There are a lot of algorithms out there that take as input a graph and try to produce a nice drawing of it. They use different approaches and make nice drawings for the type of graphs they are designed to draw best. For example tree layouts produce very nice drawings of trees but if the input graph is not a tree you will not be pleased by the result.
There's only one layout algorithm that can produce a nice drawing of almost every kind of graph. This is the Let G = (V; E) be a graph, n = |V|; m = |E|. A point where the drawing of an edge changes its direction is called a bend of this edge. If the drawing of an edge has at most k bends we call this edge k-bent. An orthogonal drawing is called an embedding in the rectangular grid if all vertices and bendpoints are drawn on integer coordinates.
Our algorithm takes as input a simple graph and produces an orthogonal grid drawing. Note that if the input graph is planar, the resulting drawing is also planar (i.e. without edge crossings). In the case of non-planar graphs the edge crossings are inevitable but the algorithm tries to keep their number as low as possible. For both planar and non-planar graphs the layout offers a great improvement in the readability of the graph by maintaining the following aesthetic criteria (given by their priority in descending order):
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In order to produce edge crossing free drawings of planar graphs, we should check if the graph is planar and if it is, then we must find a planar embedding of the graph. This means that we should reorder the adjacency list matrix of the graph in such a way that the neighbors of each vertex are listed in a clockwise direction as they will appear in the final drawing.
When planarity testing is completed and the planar topology of the graph is determined, we must obtain the faces of the planar graph. The execution of the algorithm can be viewed as person walking along the edges of the graph, continuously choosing the rightmost option at every vertex. An orthogonal drawing of a graph is an embedding in the plane such that all edges are drawn as sequences of horizontal and vertical segments. In particular for nonplanar and nonbiconnected planar graphs, this is a big improvement. The algorithm handles both planar and nonplanar graphs at the same time. After building the orthogonal shape we perform a compaction step which deals with 2 important tasks: compaction of the total area of the drawing and bend minimization. Finally we calculate the coordinates of the vertices and edges of the grid drawing and render them using the Nevron Diagram Rendering Engine. | ||||||

The NOrthogonalGraphLayout class is the class that implements the Nevron orthogonal layout algorithm. It is a direct descendant of the NGraphLayout which ensures that it is very easy to use and provides similar user experiences as all other layouts in the Nevron Diagramming Component. The layout accepts as input a simple graph and produces an orthogonal grid drawing. Note that if the input graph is planar, the resulting drawing is also planar (i.e. without edge crossings). In the case of non-planar graphs the edge crossings are inevitable but the algorithm tries to keep their number as low as possible. For both planar and non-planar graphs the layout offers a great improvement in the readability of the graph. The most important properties are:
**UseCompaction**– if set to true, a compaction algorithm will be applied to the embedded graph. This will decrease the total area of the drawing with 20 to 50 % (in the average case) at the cost of some additional time needed for the calculations. See the example below of a tree with 13 vertices and 12 edges:Fig. 1Fig. 2**GridCellSizeMode**– this property is an enum with 2 possible values:*GridCellSizeMode.GridBased*and*GridCellSizeMode.CellBased*. If set to the first the maximal size of a node in the graph is determined and all cells are scaled to that size. More area efficient is the second value - it causes the dimensions of each column and row dimensions to be determined according to the size of the cells they contain. See the pictures below for an example of the aforementioned cell sizing scenarios.Fig. 3Fig. 4**CellSpacing**– determines the distance between 2 grid cells. For example if a grid cell is calculated to have a size of 100 x 100 and the CellSpacing property is set to 10, then the cell size will be 120 x 120. Note that the node is always placed in the middle of the cell.
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The simulator, then, allows to emulate every single point of failure of the net and for each of them reconfigures the net for the best off-line time (breakers take several maneuvers and counter-maneuvers to operate correctly). At the end of the simulation an animation is recorded for the best solution found (time/price). The animation is then displayed , using Nevron Graph controls, allowing the electrical engineer to check the correctness of the result and the various “moves” that the simulator toke to get to the best solution. When the personnel is then satisfied with the solution it uses the client application to update the remote DB with a request to acquire the needed resources to build this new configuration on the real net.

Gian Piero Anselmi

**NIT - New Information Technology S.r.l.**