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locks; strict;
comment	@# @;


1.1
date	2003.01.23.19.27.12;	author wiz;	state Exp;
branches
	1.1.1.1;
next	;

1.1.1.1
date	2003.01.23.19.27.12;	author wiz;	state Exp;
branches;
next	;


desc
@@



1.1
log
@Initial revision
@
text
@In contrast to Graphviz and other graph optimizers, graphopt does
not use a heuristic approach to layout optimization.  Instead, it
uses basic principles of physics to iteratively determine optimal
layout.  Each node is given mass and an electric charge, and each
edge is represented as a spring.  Node mass, electric charge,
optimal spring length, and the spring constant are tweakable in
the gui in realtime.

For most graphs, this is all that is needed - hit 'go' and the
graph organizes itself much as the analagous real-life system would
if constrained to two dimensions.  For more complex graphs, some
fiddling with the physical parameters at different stages of
optimization usually does the trick.

To accomodate very large graphs, an additional mechanism called
layering was added.  When a graph is loaded, nodes are assigned to
layers based on their relative positions.  During optimization,
you can choose to hide any number of layers.  Any nodes assigned
to a layer lower than the selected layer are not only hidden, but
neither their electric charges nor the forces of the springs attached
to them are figured into the forces acting on the visible nodes.
In effect, those nodes cease to exist, and a smaller graph is
allowed to lay itself out without being constrained by an excessive
number of nodes.
@


1.1.1.1
log
@Initial import of graphopt-0.1, a graph layout optimizer:
In contrast to Graphviz and other graph optimizers, graphopt does
not use a heuristic approach to layout optimization.  Instead, it
uses basic principles of physics to iteratively determine optimal
layout.  Each node is given mass and an electric charge, and each
edge is represented as a spring.  Node mass, electric charge,
optimal spring length, and the spring constant are tweakable in
the gui in realtime.

For most graphs, this is all that is needed - hit 'go' and the
graph organizes itself much as the analagous real-life system would
if constrained to two dimensions.  For more complex graphs, some
fiddling with the physical parameters at different stages of
optimization usually does the trick.

To accomodate very large graphs, an additional mechanism called
layering was added.  When a graph is loaded, nodes are assigned to
layers based on their relative positions.  During optimization,
you can choose to hide any number of layers.  Any nodes assigned
to a layer lower than the selected layer are not only hidden, but
neither their electric charges nor the forces of the springs attached
to them are figured into the forces acting on the visible nodes.
In effect, those nodes cease to exist, and a smaller graph is
allowed to lay itself out without being constrained by an excessive
number of nodes.
@
text
@@