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authorKarl Berry <karl@freefriends.org>2014-02-27 00:01:50 +0000
committerKarl Berry <karl@freefriends.org>2014-02-27 00:01:50 +0000
commit90ae413a94da014dbf7a6a8ab584f7c668483a5a (patch)
tree4e0528a2b2fb2004988e7fc804ea2f1354f1f5d5 /Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force
parent800cc56380d1edfe567a6a66bef13e8950eb2b0c (diff)
pgf 3.0.0
git-svn-id: svn://tug.org/texlive/trunk@33057 c570f23f-e606-0410-a88d-b1316a301751
Diffstat (limited to 'Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force')
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/CoarseGraph.lua435
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/Control.lua28
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlCoarsening.lua148
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlElectric.lua100
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlIteration.lua144
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlSprings.lua58
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlStart.lua40
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/QuadTree.lua280
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalHu2006.lua521
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalLayouts.lua54
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalWalshaw2000.lua516
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringHu2006.lua387
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringLayouts.lua36
-rw-r--r--Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/library.lua126
14 files changed, 2873 insertions, 0 deletions
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/CoarseGraph.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/CoarseGraph.lua
new file mode 100644
index 00000000000..c9739dcaf63
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/CoarseGraph.lua
@@ -0,0 +1,435 @@
+-- Copyright 2011 by Jannis Pohlmann
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/CoarseGraph.lua,v 1.1 2012/11/27 17:24:25 tantau Exp $
+
+
+--- A class for handling "coarse" versions of a graph. Such versions contain
+-- less nodes and edges than the original graph while retaining the overall
+-- structure.
+
+local Graph = require "pgf.gd.deprecated.Graph" -- we subclass from here
+local CoarseGraph = Graph.new()
+CoarseGraph.__index = CoarseGraph
+
+
+
+-- Namespace:
+local force = require "pgf.gd.force"
+force.CoarseGraph = CoarseGraph
+
+
+-- Imports
+local Node = require "pgf.gd.deprecated.Node"
+local Edge = require "pgf.gd.deprecated.Edge"
+
+local lib = require "pgf.gd.lib"
+
+
+-- Class setup
+
+CoarseGraph.COARSEN_INDEPENDENT_EDGES = 0 -- TT: Remark: These uppercase constants are *ugly*. Why do people do this?!
+CoarseGraph.COARSEN_INDEPENDENT_NODES = 1
+CoarseGraph.COARSEN_HYBRID = 2
+
+
+
+--- Creates a new coarse graph derived from an existing graph.
+--
+-- Generates a coarse graph for the input |Graph|.
+--
+-- Coarsening describes the process of reducing the amount of nodes in a graph
+-- by merging nodes into supernodes. There are different strategies, called
+-- schemes, that can be applied, like merging nodes that belong to edges in a
+-- maximal independent edge set or by creating supernodes based on a maximal
+-- independent node set.
+--
+-- Coarsening is not performed automatically. The functions |CoarseGraph:coarsen|
+-- and |CoarseGraph:interpolate| can be used to further coarsen the graph or
+-- to restore the previous state (while interpolating the node positions from
+-- the coarser version of the graph).
+--
+-- Note, however, that the input \meta{graph} is always modified in-place, so
+-- if the original version of \meta{graph} is needed in parallel to its
+-- coarse representations, a deep copy of \meta{grpah} needs to be passed over
+-- to |CoarseGraph.new|.
+--
+-- @param graph An existing graph that needs to be coarsened.
+-- @param scheme Coarsening scheme to use. Possible values are:\par
+-- |CoarseGraph.COARSEN_INDEPENDENT_EDGES|:
+-- Coarsen the input graph by computing a maximal independent edge set
+-- and collapsing edges from this set. The resulting coarse graph has
+-- at least 50% of the nodes of the input graph. This coarsening scheme
+-- gives slightly better results than
+-- |CoarseGraph.COARSEN_INDEPENDENT_NODES| because it is less aggressive.
+-- However, this comes at higher computational cost.\par
+-- |CoarseGraph.COARSEN_INDEPENDENT_NODES|:
+-- Coarsen the input graph by computing a maximal independent node set,
+-- making nodes from this set supernodes in the coarse graph, merging
+-- adjacent nodes into the supernodes and connecting the supernodes
+-- if their grpah distance is no greater than three. This scheme gives
+-- slightly worse results than |CoarseGraph.COARSEN_INDEPENDENT_EDGES|
+-- but is computationally more efficient.\par
+-- |CoarseGraph.COARSEN_HYBRID|: Combines the other schemes by starting
+-- with |CoarseGraph.COARSEN_INDEPENDENT_EDGES| and switching to
+-- |CoarseGraph.COARSEN_INDEPENDENT_NODES| as soon as the first scheme
+-- does not reduce the amount of nodes by a factor of 25%.
+--
+function CoarseGraph.new(graph, scheme)
+ local coarse_graph = {
+ graph = graph,
+ level = 0,
+ scheme = scheme or CoarseGraph.COARSEN_INDEPENDENT_EDGES,
+ ratio = 0,
+ }
+ setmetatable(coarse_graph, CoarseGraph)
+ return coarse_graph
+end
+
+
+
+local function custom_merge(table1, table2, first_metatable)
+ local result = table1 and lib.copy(table1) or {}
+ local first_metatable = first_metatable == true or false
+
+ for key, value in pairs(table2) do
+ if not result[key] then
+ result[key] = value
+ end
+ end
+
+ if not first_metatable or not getmetatable(result) then
+ setmetatable(result, getmetatable(table2))
+ end
+
+ return result
+end
+
+
+local function pairs_by_sorted_keys (t, f)
+ local a = {}
+ for n in pairs(t) do a[#a + 1] = n end
+ table.sort (a, f)
+ local i = 0
+ return function ()
+ i = i + 1
+ return a[i], t[a[i]]
+ end
+end
+
+
+
+function CoarseGraph:coarsen()
+ -- update the level
+ self.level = self.level + 1
+
+ local old_graph_size = #self.graph.nodes
+
+ if self.scheme == CoarseGraph.COARSEN_INDEPENDENT_EDGES then
+ local matching, unmatched_nodes = self:findMaximalMatching()
+
+ for _,edge in ipairs(matching) do
+ -- get the two nodes of the edge that we are about to collapse
+ local u, v = edge.nodes[1], edge.nodes[2]
+
+ assert(u ~= v, 'the edge ' .. tostring(edge) .. ' is a loop. loops are not supported by this algorithm')
+
+ -- create a supernode
+ local supernode = Node.new{
+ name = '(' .. u.name .. ':' .. v.name .. ')',
+ weight = u.weight + v.weight,
+ subnodes = { u, v },
+ subnode_edge = edge,
+ level = self.level,
+ }
+
+ -- add the supernode to the graph
+ self.graph:addNode(supernode)
+
+ -- collact all neighbours of the nodes to merge, create a node -> edge mapping
+ local u_neighbours = lib.map(u.edges, function(edge) return edge, edge:getNeighbour(u) end)
+ local v_neighbours = lib.map(v.edges, function(edge) return edge, edge:getNeighbour(v) end)
+
+ -- remove the two nodes themselves from the neighbour lists
+ u_neighbours = lib.map(u_neighbours, function (edge,node) if node ~= v then return edge,node end end)
+ v_neighbours = lib.map(v_neighbours, function (edge,node) if node ~= u then return edge,node end end)
+
+ -- compute a list of neighbours u and v have in common
+ local common_neighbours = lib.map(u_neighbours,
+ function (edge,node)
+ if v_neighbours[node] ~= nil then return edge,node end
+ end)
+
+ -- create a node -> edges mapping for common neighbours
+ common_neighbours = lib.map(common_neighbours, function (edge, node)
+ return { edge, v_neighbours[node] }, node
+ end)
+
+ -- drop common edges from the neighbour mappings
+ u_neighbours = lib.map(u_neighbours, function (val,node) if not common_neighbours[node] then return val,node end end)
+ v_neighbours = lib.map(v_neighbours, function (val,node) if not common_neighbours[node] then return val,node end end)
+
+ -- merge neighbour lists
+ local disjoint_neighbours = custom_merge(u_neighbours, v_neighbours)
+
+ -- create edges between the supernode and the neighbours of the merged nodes
+ for neighbour, edge in pairs_by_sorted_keys(disjoint_neighbours, function (n,m) return n.index < m.index end) do
+
+ -- create a superedge to replace the existing one
+ local superedge = Edge.new{
+ direction = edge.direction,
+ weight = edge.weight,
+ subedges = { edge },
+ level = self.level,
+ }
+
+ -- add the supernode and the neighbour to the edge
+ if u_neighbours[neighbour] then
+ superedge:addNode(neighbour)
+ superedge:addNode(supernode)
+
+ else
+ superedge:addNode(supernode)
+ superedge:addNode(neighbour)
+
+ end
+
+ -- replace the old edge
+ self.graph:addEdge(superedge)
+ self.graph:deleteEdge(edge)
+ end
+
+ -- do the same for all neighbours that the merged nodes have
+ -- in common, except that the weights of the new edges are the
+ -- sums of the of the weights of the edges to the common neighbours
+ for neighbour, edges in pairs_by_sorted_keys(common_neighbours, function (n,m) return n.index < m.index end) do
+ local weights = 0
+ for _,e in ipairs(edges) do
+ weights = weights + edge.weight
+ end
+
+ local superedge = Edge.new{
+ direction = Edge.UNDIRECTED,
+ weight = weights,
+ subedges = edges,
+ level = self.level,
+ }
+
+ -- add the supernode and the neighbour to the edge
+ superedge:addNode(supernode)
+ superedge:addNode(neighbour)
+
+ -- replace the old edges
+ self.graph:addEdge(superedge)
+ for _,edge in ipairs(edges) do
+ self.graph:deleteEdge(edge)
+ end
+ end
+
+ -- delete the nodes u and v which were replaced by the supernode
+ assert(#u.edges == 1, 'node ' .. u.name .. ' is part of a multiedge') -- if this fails, then there is a multiedge involving u
+ assert(#v.edges == 1, 'node ' .. v.name .. ' is part of a multiedge') -- same here
+ self.graph:deleteNode(u)
+ self.graph:deleteNode(v)
+ end
+ else
+ assert(false, 'schemes other than CoarseGraph.COARSEN_INDEPENDENT_EDGES are not implemented yet')
+ end
+
+ -- calculate the number of nodes ratio compared to the previous graph
+ self.ratio = #self.graph.nodes / old_graph_size
+end
+
+
+
+function CoarseGraph:revertSuperedge(superedge)
+ -- TODO we can probably skip adding edges that have one or more
+ -- subedges with the same level. But that needs more testing.
+
+ -- TODO we might have to pass the corresponding supernode to
+ -- this method so that we can move subnodes to the same
+ -- position, right? Interpolating seems to work fine without
+ -- though...
+
+ if #superedge.subedges == 1 then
+ local subedge = superedge.subedges[1]
+
+ if not self.graph:findNode(subedge.nodes[1].name) then
+ self.graph:addNode(subedge.nodes[1])
+ end
+
+ if not self.graph:findNode(subedge.nodes[2].name) then
+ self.graph:addNode(subedge.nodes[2])
+ end
+
+ if not self.graph:findEdge(subedge) then
+ subedge.nodes[1]:addEdge(subedge)
+ subedge.nodes[2]:addEdge(subedge)
+ self.graph:addEdge(subedge)
+ end
+
+ if subedge.level and subedge.level >= self.level then
+ self:revertSuperedge(subedge)
+ end
+ else
+ for _,subedge in ipairs(superedge.subedges) do
+ if not self.graph:findNode(subedge.nodes[1].name) then
+ self.graph:addNode(subedge.nodes[1])
+ end
+
+ if not self.graph:findNode(subedge.nodes[2].name) then
+ self.graph:addNode(subedge.nodes[2])
+ end
+
+ if not self.graph:findEdge(subedge) then
+ subedge.nodes[1]:addEdge(subedge)
+ subedge.nodes[2]:addEdge(subedge)
+ self.graph:addEdge(subedge)
+ end
+
+ if subedge.level and subedge.level >= self.level then
+ self:revertSuperedge(subedge)
+ end
+ end
+ end
+end
+
+
+
+function CoarseGraph:interpolate()
+ -- FIXME TODO Jannis: This does not work now that we allow multi-edges
+ -- and loops! Reverting generates the same edges multiple times which leads
+ -- to distorted drawings compared to the awesome results we had before!
+
+ local nodes = lib.copy(self.graph.nodes)
+
+ for _,supernode in ipairs(nodes) do
+ assert(not supernode.level or supernode.level <= self.level)
+
+ if supernode.level and supernode.level == self.level then
+ -- move the subnode to the position of the supernode and add it to the graph
+ supernode.subnodes[1].pos.x = supernode.pos.x
+ supernode.subnodes[1].pos.y = supernode.pos.y
+
+ if not self.graph:findNode(supernode.subnodes[1].name) then
+ self.graph:addNode(supernode.subnodes[1])
+ end
+
+ -- move the subnode to the position of the supernode and add it to the graph
+ supernode.subnodes[2].pos.x = supernode.pos.x
+ supernode.subnodes[2].pos.y = supernode.pos.y
+
+ if not self.graph:findNode(supernode.subnodes[2].name) then
+ self.graph:addNode(supernode.subnodes[2])
+ end
+
+ if not self.graph:findEdge(supernode.subnode_edge) then
+ supernode.subnodes[1]:addEdge(supernode.subnode_edge)
+ supernode.subnodes[2]:addEdge(supernode.subnode_edge)
+ self.graph:addEdge(supernode.subnode_edge)
+ end
+
+ local superedges = lib.copy(supernode.edges)
+
+ for _,superedge in ipairs(superedges) do
+ self:revertSuperedge(superedge)
+ end
+
+ self.graph:deleteNode(supernode)
+ end
+ end
+
+ -- Make sure that the nodes and edges are in the correct order:
+ table.sort (self.graph.nodes, function (a, b) return a.index < b.index end)
+ table.sort (self.graph.edges, function (a, b) return a.index < b.index end)
+ for _, n in pairs(self.graph.nodes) do
+ table.sort (n.edges, function (a, b) return a.index < b.index end)
+ end
+
+ -- update the level
+ self.level = self.level - 1
+end
+
+
+
+function CoarseGraph:getSize()
+ return #self.graph.nodes
+end
+
+
+
+function CoarseGraph:getRatio()
+ return self.ratio
+end
+
+
+
+function CoarseGraph:getLevel()
+ return self.level
+end
+
+
+
+function CoarseGraph:getGraph()
+ return self.graph
+end
+
+
+
+function CoarseGraph:findMaximalMatching()
+ local matching = {}
+ local matched_nodes = {}
+ local unmatched_nodes = {}
+
+ -- iterate over nodes in random order
+ for _,j in ipairs(lib.random_permutation(#self.graph.nodes)) do
+ local node = self.graph.nodes[j]
+ -- ignore nodes that have already been matched
+ if not matched_nodes[node] then
+ -- mark the node as matched
+ matched_nodes[node] = true
+
+ -- filter out edges adjacent to neighbours already matched
+ local edges = lib.imap(node.edges,
+ function (edge)
+ if not matched_nodes[edge:getNeighbour(node)] then return edge end
+ end)
+
+ -- FIXME TODO We use a light-vertex matching here. This is
+ -- different from the algorithm proposed by Hu which collapses
+ -- edges based on a heavy-edge matching...
+ if #edges > 0 then
+ -- sort edges by the weights of the node's neighbours
+ table.sort(edges, function (a, b)
+ return a:getNeighbour(node).weight < b:getNeighbour(node).weight
+ end)
+
+ -- match the node against the neighbour with minimum weight
+ matched_nodes[edges[1]:getNeighbour(node)] = true
+ table.insert(matching, edges[1])
+ end
+ end
+ end
+
+ -- generate a list of nodes that were not matched at all
+ for _,j in ipairs(lib.random_permutation(#self.graph.nodes)) do
+ local node = self.graph.nodes[j]
+ if not matched_nodes[node] then
+ table.insert(unmatched_nodes, node)
+ end
+ end
+
+ return matching, unmatched_nodes
+end
+
+
+-- done
+
+return CoarseGraph \ No newline at end of file
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/Control.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/Control.lua
new file mode 100644
index 00000000000..113f54b7ace
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/Control.lua
@@ -0,0 +1,28 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/Control.lua,v 1.3 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+---
+-- @section subsection {Controlling and Configuring Force-Based Algorithms}
+--
+-- All force-based algorithms are based on
+-- a general pattern which we detail in the following. Numerous options
+-- can be used to influence the behaviour of this general pattern; more
+-- specific options that apply only to individual algorithms are
+-- explained along with these algorithms.
+--
+-- @end
+
+
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlCoarsening.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlCoarsening.lua
new file mode 100644
index 00000000000..330f401d5b5
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlCoarsening.lua
@@ -0,0 +1,148 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlCoarsening.lua,v 1.3 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+
+---
+-- @section subsubsection {Coarsening}
+--
+-- @end
+
+
+---
+
+declare {
+ key = "coarsen",
+ type = "boolean",
+ initial = "true",
+
+ summary = [["
+ Defines whether or not a multilevel approach is used that
+ iteratively coarsens the input graph into graphs $G_1,\dots,G_l$
+ with a smaller and smaller number of nodes. The coarsening stops as
+ soon as a minimum number of nodes is reached, as set via the
+ |minimum coarsening size| option, or if, in the last iteration, the
+ number of nodes was not reduced by at least the ratio specified via
+ |downsize ratio|.
+ "]],
+ documentation = [["
+ A random initial layout is computed for the coarsest graph $G_l$ first.
+ Afterwards, it is laid out by computing the attractive and repulsive
+ forces between its nodes.
+
+ In the subsequent steps, the previous coarse graph $G_{l-1}$ is
+ restored and its node positions are interpolated from the nodes
+ in~$G_l$. The graph $G_{l-1}$ is again laid out by computing the forces
+ between its nodes. These steps are repeated with $G_{l-2},\dots,G_1$ until
+ the original input graph $G_0$ has been restored, interpolated
+ and laid out.
+
+ The idea behind this approach is that, by arranging recursively
+ formed supernodes first and then interpolating and arranging their
+ subnodes step by step, the algorithm is less likely to settle in a
+ local energy minimum (of which there can be many, particularly for
+ large graphs). The quality of the drawings with coarsening enabled is
+ expected to be higher than graphics where this feature is not applied.
+
+ The following example demonstrates how coarsening can improve the
+ quality of graph drawings generated with Walshaw's algorihtm
+ |spring electrical layout'|.
+ "]],
+ examples = [["
+ \tikz \graph [spring electrical layout', coarsen=false, vertical=3 to 4]
+ {
+ { [clique] 1, 2 } -- 3 -- 4 -- { 5, 6, 7 }
+ };
+
+ \tikz \graph [spring electrical layout', coarsen, vertical=3 to 4]
+ {
+ { [clique] 1, 2 } -- 3 -- 4 -- { 5, 6, 7 }
+ };
+ "]]
+}
+
+---
+
+declare {
+ key = "minimum coarsening size",
+ type = "number",
+ initial = 2,
+
+ summary = [["
+ Defines the minimum number of nodes down to which the graph is
+ coarsened iteratively. The first graph that has a smaller or equal
+ number of nodes becomes the coarsest graph $G_l$, where $l$ is the
+ number of coarsening steps. The algorithm proceeds with the steps
+ described in the documentation of the |coarsen| option.
+ "]],
+ documentation = [["
+ In the following example the same graph is coarsened down to two
+ and four nodes, respectively. The layout of the original graph is
+ interpolated from the random initial layout and is not improved
+ further because the forces are not computed (0 iterations). Thus,
+ in the two graphs, the nodes are placed at exactly two and four
+ coordinates in the final drawing.
+ "]],
+ examples = [["
+ \tikz \graph [spring layout, iterations=0,
+ minimum coarsening size=2]
+ { subgraph C_n [n=8] };
+
+ \tikz \graph [spring layout, iterations=0,
+ minimum coarsening size=4]
+ { subgraph C_n [n=8] };
+ "]]
+}
+
+---
+
+declare {
+ key = "downsize ratio",
+ type = "number",
+ initial = "0.25",
+
+ summary = [["
+ Minimum ratio between 0 and 1 by which the number of nodes between
+ two coarse graphs $G_i$ and $G_{i+1}$ need to be reduced in order for
+ the coarsening to stop and for the algorithm to use $G_{i+1}$ as the
+ coarsest graph $G_l$. Aside from the input graph, the optimal value
+ of |downsize ratio| mostly depends on the coarsening scheme being
+ used. Possible schemes are |collapse independent edges| and
+ |connect independent nodes|.
+ "]],
+ documentation = [["
+ Increasing this option possibly reduces the number of coarse
+ graphs computed during the coarsening phase as coarsening will stop as
+ soon as a coarse graph does not reduce the number of nodes
+ substantially. This may speed up the algorithm but if the size of the
+ coarsest graph $G_l$ is much larger than |minimum coarsening size|, the
+ multilevel approach may not produce drawings as good as with a lower
+ |downsize ratio|.
+ "]],
+ examples = [["
+ % 1. ratio too high, coarsening stops early, benefits are lost
+ \tikz \graph [spring electrical layout',
+ downsize ratio=1.0,
+ node distance=7mm, vertical=3 to 4]
+ { { [clique] 1, 2 } -- 3 -- 4 -- { 5, 6, 7 } };
+
+ % 2. ratio set to default, coarsening benefits are visible
+ \tikz \graph [spring electrical layout',
+ downsize ratio=0.2,
+ node distance=7mm, vertical=3 to 4]
+ { { [clique] 1, 2 } -- 3 -- 4 -- { 5, 6, 7 } };
+ "]]
+}
+
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlElectric.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlElectric.lua
new file mode 100644
index 00000000000..d708bd6d7b7
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlElectric.lua
@@ -0,0 +1,100 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlElectric.lua,v 1.3 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+
+---
+-- @section subsubsection {Forces and Their Effects: Electrical
+-- Repulsion}
+--
+-- @end
+
+
+---
+
+declare {
+ key = "electric charge",
+ type = "number",
+ initial = 1,
+
+ summary = [["
+ Defines the electric charge of the node. The stronger the
+ |electric charge| of a node the stronger the repulsion between the
+ node and others in the graph. A negative |electric charge| means that
+ other nodes are further attracted to the node rather than repulsed,
+ although in theory this effect strongly depends on how the
+ |spring electrical layout| algorithm works.
+ Two typcal effects of increasing the |electric charge| are distortion
+ of symmetries and an upscaling of the drawings.
+ "]],
+ examples = {
+ [["
+ \tikz \graph [spring electrical layout, horizontal=0 to 1]
+ { 0 [electric charge=1] -- subgraph C_n [n=10] };
+ "]],
+ [["
+ \tikz \graph [spring electrical layout, horizontal=0 to 1]
+ { 0 [electric charge=5] -- subgraph C_n [n=10] };
+ "]],
+ [["
+ \tikz \graph [spring electrical layout, horizontal=0 to 1]
+ { [clique] 1 [electric charge=5], 2, 3, 4 };
+ "]]
+ }
+}
+
+
+---
+
+declare {
+ key = "electric force order",
+ type = "number",
+ initial = "1",
+
+ summary = [["
+ Sometimes, when drawing symmetric and mesh-like graphs, the
+ peripheral distortion caused by long-range electric forces may be
+ undesired. Some electric force models allow to reduce long-range
+ forces and distortion effects by increasing
+ the order (epxonent) of electric forces. Values between 0 and 1
+ increase long-range electric forces and the scaling of the
+ generated layouts. Value greater than 1 decrease long-range
+ electric forces and results in shrinking drawings.
+ "]]
+ }
+
+
+---
+
+declare {
+ key = "approximate remote forces",
+ type = "boolean",
+
+ summary = [["
+ Force based algorithms often need to compute a force for each pair
+ of vertices, which, for larger numbers of vertices, can lead to a
+ significant time overhead. This problem can be addressed by
+ approximating these forces: For a vertex far removed from a cluster
+ of vertices, instead of computing the force contribution of each
+ vertex of the cluster indiviually, we form a sort of
+ ``supervertex'' at the ``gravitational center'' of the cluster and
+ then compute only the force between this supervertex and the single
+ vertex.
+
+ \emph{Remark:} Currently, the implementation seems to be broken, at
+ least the results are somewhat strange when this key is used.
+ "]]
+ }
+
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlIteration.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlIteration.lua
new file mode 100644
index 00000000000..f07f23aeac3
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlIteration.lua
@@ -0,0 +1,144 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlIteration.lua,v 1.3 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+
+
+---
+-- @section subsubsection {The Iterative Process and Cooling}
+--
+-- @end
+
+
+
+---
+
+declare {
+ key = "iterations",
+ type = "number",
+ initial = "500",
+
+ summary = [["
+ Limits the number of iterations of algorithms for force-based
+ layouts to \meta{number}.
+ "]],
+ documentation = [["
+ Depending on the characteristics of the input graph and the parameters
+ chosen for the algorithm, minimizing the system energy may require
+ many iterations.
+
+ In these situations it may come in handy to limit the number of
+ iterations. This feature can also be useful to draw the same graph
+ after different iterations and thereby demonstrate how the spring or
+ spring-electrical algorithm improves the drawing step by step.
+
+ The examples shows two drawings generated using two
+ different |iteration| limits.
+ "]],
+ examples = {
+ [["
+ \tikz \graph [spring layout, iterations=10] { subgraph K_n [n=4] };
+ "]],
+ [["
+ \tikz \graph [spring layout, iterations=500] { subgraph K_n [n=4] };
+ "]],
+ [["
+ \tikz \graph [spring electrical layout, iterations=10]
+ { subgraph K_n [n=4] };
+ "]],
+ [["
+ \tikz \graph [spring electrical layout, iterations=500]
+ { subgraph K_n [n=4] };
+ "]]
+ }
+}
+
+---
+
+declare {
+ key = "initial step length",
+ type = "length",
+ initial = "0",
+
+ summary = [["
+ This parameter specifies the amount by which nodes will be
+ displaced in each iteration, initially. If set to |0| (which is the
+ default), an appropriate value is computed automatically.
+ "]]
+ }
+
+---
+
+declare {
+ key = "cooling factor",
+ type = "number",
+ initial = "0.95",
+
+ summary = [["
+ This parameter helps in controlling how layouts evolve over
+ time. It is used to gradually reduce the step size
+ between one iteration to the next.
+ "]],
+ documentation = [["
+ A small positive cooling factor
+ $\ge 0$ means that the movement of nodes is quickly or abruptly
+ reduced, while a large cooling factor $\le 1$ allows for a smoother
+ step by step layout refinement at the cost of more iterations. The
+ following example demonstrates how a smaller cooling factor may
+ result in a less balanced drawing. By default, Hu2006 spring,
+ Hu2006 spring electrical, and Walshaw2000 spring electrical use a
+ cooling factor of |0.95|.
+ "]],
+ examples = {
+ [["
+ \tikz \graph [spring layout, cooling factor=0.1]
+ { a -> b -> c -> a };
+ "]],
+ [["
+ \tikz \graph [spring layout, cooling factor=0.5]
+ { a -> b -> c -> a };
+ "]]
+ }
+}
+
+---
+
+declare {
+ key = "convergence tolerance",
+ type = "number",
+ initial = "0.01",
+
+ summary = [["
+ All spring and spring-electrical algorithms implemented in the
+ thesis terminate as soon as the maximum movement of any node drops
+ below $k \cdot \meta{tolerance}$. This tolerance factor can be changed
+ with the convergence tolerance option:
+ "]],
+ examples = {
+ [["
+ \tikz \graph [spring layout, convergence tolerance=0.001]
+ { { [clique] 1, 2 } -- 3 -- 4 -- { 5, 6, 7 } };
+ "]],
+ [["
+ \tikz \graph [spring layout, convergence tolerance=1.0]
+ { { [clique] 1, 2 } -- 3 -- 4 -- { 5, 6, 7 } };
+ "]]
+ }
+}
+
+
+
+
+
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlSprings.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlSprings.lua
new file mode 100644
index 00000000000..2ef55169bca
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlSprings.lua
@@ -0,0 +1,58 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlSprings.lua,v 1.3 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+---
+-- @section subsubsection {Forces and Their Effects: Springs}
+--
+-- The most important parameter of springs is their ``natural
+-- length'', which can be configured using the general-purpose
+-- |node distance| parameter. It is the ``equilibrium length'' of a
+-- spring between two nodes in the graph. When an edge has this
+-- lenght, no forces will ``push'' or ``pull'' along the edge.
+--
+-- The following examples shows how a simple graph can be scaled by
+-- changing the |node distance|:
+-- \begin{codeexample}[]
+-- \tikz \graph [spring layout, node distance=7mm] { subgraph C_n[n=3] };
+-- \tikz \graph [spring layout] { subgraph C_n[n=3] };
+-- \tikz \graph [spring layout, node distance=15mm]{ subgraph C_n[n=3] };
+-- \end{codeexample}
+-- \begin{codeexample}[]
+-- \tikz \graph [spring electrical layout, node distance=0.7cm] { subgraph C_n[n=3] };
+-- \tikz \graph [spring electrical layout] { subgraph C_n[n=3] };
+-- \tikz \graph [spring electrical layout, node distance=1.5cm] { subgraph C_n[n=3] };
+-- \end{codeexample}
+--
+-- @end
+
+
+
+---
+
+declare {
+ key = "spring constant",
+ type = "number",
+ initial = "0.01",
+
+ summary = [["
+ The ``spring constant'' is a factor from Hooke's law describing the
+ ``stiffness'' of a spring. This factor is used inside spring-based
+ algorithms to determine how strongly edges ``pull'' and ``push'' at
+ the nodes they connect.
+ "]]
+ }
+
+
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlStart.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlStart.lua
new file mode 100644
index 00000000000..6b93f311290
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlStart.lua
@@ -0,0 +1,40 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/ControlStart.lua,v 1.3 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+
+
+---
+-- @section subsubsection {Start Configuration}
+--
+-- Currently, the start configuration for force-based algorithms is a
+-- random distribution of the vertices. You can influence it by
+-- changing the |random seed|:
+--
+--\begin{codeexample}[]
+--\tikz \graph [random seed=10, spring layout] {
+-- a -- {b, c, d} -- e -- f -- {g,h} -- {a,b,e};
+--};
+--\end{codeexample}
+--\begin{codeexample}[]
+--\tikz \graph [random seed=11, spring layout] {
+-- a -- {b, c, d} -- e -- f -- {g,h} -- {a,b,e};
+--};
+--\end{codeexample}
+--
+-- Other methods, like a planar preembedding, are not implemented
+-- currently.
+--
+-- @end \ No newline at end of file
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/QuadTree.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/QuadTree.lua
new file mode 100644
index 00000000000..1a7d0abf25a
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/QuadTree.lua
@@ -0,0 +1,280 @@
+-- Copyright 2011 by Jannis Pohlmann
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/QuadTree.lua,v 1.1 2012/11/27 17:24:25 tantau Exp $
+
+
+--- An implementation of a quad trees.
+--
+-- The class QuadTree provides methods form handling quadtrees.
+--
+
+local QuadTree = {
+ -- Subclases
+ Particle = {},
+ Cell = {}
+}
+QuadTree.__index = QuadTree
+
+-- Namespace:
+require("pgf.gd.force").QuadTree = QuadTree
+
+-- Imports:
+local Vector = require "pgf.gd.deprecated.Vector"
+local lib = require "pgf.gd.lib"
+
+
+--- Creates a new quad tree.
+--
+-- @return A newly-allocated quad tree.
+--
+function QuadTree.new(x, y, width, height, max_particles)
+ local tree = {
+ root_cell = QuadTree.Cell.new(x, y, width, height, max_particles)
+ }
+ setmetatable(tree, QuadTree)
+ return tree
+end
+
+
+
+--- Inserts a particle
+--
+-- @param param A particle of type QuadTree.Particle
+--
+function QuadTree:insert(particle)
+ self.root_cell:insert(particle)
+end
+
+
+
+--- Computes the interactions of a particle with other cells
+--
+-- @param particle A particle
+-- @param test_func A test function, which on input of a cubical cell and a particle should
+-- decide whether the cubical cell should be inserted into the result
+-- @param cells An optional array of cells, to which the found cells will be added
+--
+-- @return The cells array or a new array, if it was empty.
+--
+function QuadTree:findInteractionCells(particle, test_func, cells)
+ local test_func = test_func or function (cell, particle) return true end
+ cells = cells or {}
+
+ self.root_cell:findInteractionCells(particle, test_func, cells)
+
+ return cells
+end
+
+
+
+
+--- Partical subclass
+QuadTree.Particle.__index = QuadTree.Particle
+
+
+
+--- Creates a new particle.
+--
+-- @return A newly-allocated particle.
+--
+function QuadTree.Particle.new(pos, mass)
+ local particle = {
+ pos = pos:copy(),
+ mass = mass or 1,
+ subparticles = {},
+ }
+ setmetatable(particle, QuadTree.Particle)
+ return particle
+end
+
+
+
+--- A cell of a quadtree
+--
+-- TT: Why is it called "cubical", by the way?!
+
+QuadTree.Cell.__index = QuadTree.Cell
+
+
+
+--- Creates a new cubicle cell.
+--
+-- @return a newly-allocated cubicle cell.
+--
+function QuadTree.Cell.new(x, y, width, height, max_particles)
+ local cell = {
+ x = x,
+ y = y,
+ width = width,
+ height = height,
+ max_particles = max_particles or 1,
+ subcells = {},
+ particles = {},
+ center_of_mass = nil,
+ mass = 0,
+ }
+ setmetatable(cell, QuadTree.Cell)
+ return cell
+end
+
+
+
+function QuadTree.Cell:containsParticle(particle)
+ return particle.pos.x >= self.x and particle.pos.x <= self.x + self.width
+ and particle.pos.y >= self.y and particle.pos.y <= self.y + self.height
+end
+
+
+
+function QuadTree.Cell:findSubcell(particle)
+ return lib.find(self.subcells, function (cell)
+ return cell:containsParticle(particle)
+ end)
+end
+
+
+
+function QuadTree.Cell:createSubcells()
+ assert(type(self.subcells) == 'table' and #self.subcells == 0)
+ assert(type(self.particles) == 'table' and #self.particles <= self.max_particles)
+
+ if #self.subcells == 0 then
+ for _,x in ipairs({self.x, self.x + self.width/2}) do
+ for _,y in ipairs({self.y, self.y + self.height/2}) do
+ local cell = QuadTree.Cell.new(x, y, self.width/2, self.height/2, self.max_particles)
+ table.insert(self.subcells, cell)
+ end
+ end
+ end
+end
+
+
+
+function QuadTree.Cell:insert(particle)
+ -- check if we have a particle with the exact same position already
+ local existing = lib.find(self.particles, function (other)
+ return other.pos:equals(particle.pos)
+ end)
+
+ if existing then
+ -- we already have a particle at the same position; splitting the cell
+ -- up makes no sense; instead we add the new particle as a
+ -- subparticle of the existing one
+ table.insert(existing.subparticles, particle)
+ else
+ if #self.subcells == 0 and #self.particles < self.max_particles then
+ table.insert(self.particles, particle)
+ else
+ if #self.subcells == 0 then
+ self:createSubcells()
+ end
+
+ -- move particles to the new subcells
+ for _,existing in ipairs(self.particles) do
+ local cell = self:findSubcell(existing)
+ assert(cell, 'failed to find a cell for particle ' .. tostring(existing.pos))
+ cell:insert(existing)
+ end
+
+ self.particles = {}
+
+ local cell = self:findSubcell(particle)
+ assert(cell)
+ cell:insert(particle)
+ end
+ end
+
+ self:updateMass()
+ self:updateCenterOfMass()
+
+ assert(self.mass)
+ assert(self.center_of_mass)
+end
+
+
+
+function QuadTree.Cell:updateMass()
+ -- reset mass to zero
+ self.mass = 0
+
+ if #self.subcells == 0 then
+ -- the mass is the number of particles of the cell
+ for _,particle in ipairs(self.particles) do
+ self.mass = self.mass + particle.mass
+ for _,subparticle in ipairs(particle.subparticles) do
+ self.mass = self.mass + subparticle.mass
+ end
+ end
+ else
+ -- the mass is the sum of the masses of the subcells
+ for _,subcell in ipairs(self.subcells) do
+ self.mass = self.mass + subcell.mass
+ end
+ end
+end
+
+
+
+function QuadTree.Cell:updateCenterOfMass()
+ -- reset center of mass, assuming the cell is empty
+ self.center_of_mass = nil
+
+ if #self.subcells == 0 then
+ -- the center of mass is the average position of the particles
+ -- weighted by their masses
+ self.center_of_mass = Vector.new (2)
+ for _,p in ipairs(self.particles) do
+ for _,sp in ipairs(p.subparticles) do
+ self.center_of_mass = self.center_of_mass:plus(sp.pos:timesScalar(sp.mass))
+ end
+ self.center_of_mass = self.center_of_mass:plus(p.pos:timesScalar(p.mass))
+ end
+ self.center_of_mass = self.center_of_mass:dividedByScalar(self.mass)
+ else
+ -- the center of mass is the average of the weighted centers of mass
+ -- of the subcells
+ self.center_of_mass = Vector.new(2)
+ for _,sc in ipairs(self.subcells) do
+ if sc.center_of_mass then
+ self.center_of_mass = self.center_of_mass:plus(sc.center_of_mass:timesScalar(sc.mass))
+ else
+ assert(sc.mass == 0)
+ end
+ end
+ self.center_of_mass = self.center_of_mass:dividedByScalar(self.mass)
+ end
+end
+
+
+
+function QuadTree.Cell:findInteractionCells(particle, test_func, cells)
+ if #self.subcells == 0 or test_func(self, particle) then
+ table.insert(cells, self)
+ else
+ for _,subcell in ipairs(self.subcells) do
+ subcell:findInteractionCells(particle, test_func, cells)
+ end
+ end
+end
+
+
+function QuadTree.Cell:__tostring()
+ return '((' .. self.x .. ', ' .. self.y .. ') '
+ .. 'to (' .. self.x + self.width .. ', ' .. self.y + self.height .. '))'
+ .. (self.particle and ' => ' .. self.particle.name or '')
+ .. (self.center_of_mass and ' mass ' .. self.mass .. ' at ' .. tostring(self.center_of_mass) or '')
+end
+
+
+
+-- done
+
+return QuadTree \ No newline at end of file
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalHu2006.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalHu2006.lua
new file mode 100644
index 00000000000..54ceddcc25a
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalHu2006.lua
@@ -0,0 +1,521 @@
+-- Copyright 2011 by Jannis Pohlmann
+--
+-- This file may be distributed and/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalHu2006.lua,v 1.1 2012/11/27 17:24:25 tantau Exp $
+
+
+local SpringElectricalHu2006 = {}
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+
+
+---
+
+declare {
+ key = "spring electrical Hu 2006 layout",
+ algorithm = SpringElectricalHu2006,
+
+ preconditions = {
+ connected = true,
+ loop_free = true,
+ simple = true,
+ },
+
+ old_graph_model = true,
+
+ summary = [["
+ Implementation of a spring electrical graph drawing algorithm based on
+ a paper by Hu.
+ "]],
+ documentation = [["
+ \begin{itemize}
+ \item
+ Y. Hu.
+ \newblock Efficient, high-quality force-directed graph drawing.
+ \newblock \emph{The Mathematica Journal}, 2006.
+ \end{itemize}
+
+ There are some modifications compared to the original algorithm,
+ see the Diploma thesis of Pohlmann for details.
+ "]]
+}
+
+-- Imports
+
+local PathLengths = require "pgf.gd.lib.PathLengths"
+local Vector = require "pgf.gd.deprecated.Vector"
+
+local QuadTree = require "pgf.gd.force.QuadTree"
+local CoarseGraph = require "pgf.gd.force.CoarseGraph"
+
+local lib = require "pgf.gd.lib"
+
+
+function SpringElectricalHu2006:run()
+
+ -- Setup properties
+ local options = self.digraph.options
+
+ self.iterations = options['iterations']
+ self.cooling_factor = options['cooling factor']
+ self.initial_step_length = options['initial step length']
+ self.convergence_tolerance = options['convergence tolerance']
+
+ self.natural_spring_length = options['node distance']
+ self.spring_constant = options['spring constant']
+
+ self.approximate_repulsive_forces = options['approximate remote forces']
+ self.repulsive_force_order = options['electric force order']
+
+ self.coarsen = options['coarsen']
+ self.downsize_ratio = options['downsize ratio']
+ self.minimum_graph_size = options['minimum coarsening size']
+
+ -- Adjust types
+ self.downsize_ratio = math.max(0, math.min(1, self.downsize_ratio))
+ self.graph_size = #self.graph.nodes
+ self.graph_density = (2 * #self.graph.edges) / (#self.graph.nodes * (#self.graph.nodes - 1))
+
+ -- validate input parameters
+ assert(self.iterations >= 0, 'iterations (value: ' .. self.iterations .. ') need to be greater than 0')
+ assert(self.cooling_factor >= 0 and self.cooling_factor <= 1, 'the cooling factor (value: ' .. self.cooling_factor .. ') needs to be between 0 and 1')
+ assert(self.initial_step_length >= 0, 'the initial step length (value: ' .. self.initial_step_length .. ') needs to be greater than or equal to 0')
+ assert(self.convergence_tolerance >= 0, 'the convergence tolerance (value: ' .. self.convergence_tolerance .. ') needs to be greater than or equal to 0')
+ assert(self.natural_spring_length >= 0, 'the natural spring dimension (value: ' .. self.natural_spring_length .. ') needs to be greater than or equal to 0')
+ assert(self.spring_constant >= 0, 'the spring constant (value: ' .. self.spring_constant .. ') needs to be greater or equal to 0')
+ assert(self.downsize_ratio >= 0 and self.downsize_ratio <= 1, 'the downsize ratio (value: ' .. self.downsize_ratio .. ') needs to be between 0 and 1')
+ assert(self.minimum_graph_size >= 2, 'the minimum coarsening size of coarse graphs (value: ' .. self.minimum_graph_size .. ') needs to be greater than or equal to 2')
+
+ -- initialize node weights
+ for _,node in ipairs(self.graph.nodes) do
+ node.weight = node:getOption('electric charge')
+ end
+
+ -- initialize edge weights
+ for _,edge in ipairs(self.graph.edges) do
+ edge.weight = 1
+ end
+
+ -- initialize the coarse graph data structure. note that the algorithm
+ -- is the same regardless whether coarsening is used, except that the
+ -- number of coarsening steps without coarsening is 0
+ local coarse_graph = CoarseGraph.new(self.graph)
+
+ -- check if the multilevel approach should be used
+ if self.coarsen then
+ -- coarsen the graph repeatedly until only minimum_graph_size nodes
+ -- are left or until the size of the coarse graph was not reduced by
+ -- at least the downsize ratio configured by the user
+ while coarse_graph:getSize() > self.minimum_graph_size
+ and coarse_graph:getRatio() <= (1 - self.downsize_ratio)
+ do
+ coarse_graph:coarsen()
+ end
+ end
+
+ if self.coarsen then
+ -- use the natural spring length as the initial natural spring length
+ local spring_length = self.natural_spring_length
+
+ -- compute a random initial layout for the coarsest graph
+ self:computeInitialLayout(coarse_graph.graph, spring_length)
+
+ -- set the spring length to the average edge length of the initial layout
+ spring_length = 0
+ for _,edge in ipairs(coarse_graph.graph.edges) do
+ spring_length = spring_length + edge.nodes[1].pos:minus(edge.nodes[2].pos):norm()
+ end
+ spring_length = spring_length / #coarse_graph.graph.edges
+
+ -- additionally improve the layout with the force-based algorithm
+ -- if there are more than two nodes in the coarsest graph
+ if coarse_graph:getSize() > 2 then
+ self:computeForceLayout(coarse_graph.graph, spring_length, SpringElectricalHu2006.adaptive_step_update)
+ end
+
+ -- undo coarsening step by step, applying the force-based sub-algorithm
+ -- to every intermediate coarse graph as well as the original graph
+ while coarse_graph:getLevel() > 0 do
+
+ -- compute the diameter of the parent coarse graph
+ local parent_diameter = PathLengths.pseudoDiameter(coarse_graph.graph)
+
+ -- interpolate the previous coarse graph from its parent
+ coarse_graph:interpolate()
+
+ -- compute the diameter of the current coarse graph
+ local current_diameter = PathLengths.pseudoDiameter(coarse_graph.graph)
+
+ -- scale node positions by the quotient of the pseudo diameters
+ for _,node in ipairs(coarse_graph.graph) do
+ node.pos:update(function (n, value)
+ return value * (current_diameter / parent_diameter)
+ end)
+ end
+
+ -- compute forces in the graph
+ self:computeForceLayout(coarse_graph.graph, spring_length, SpringElectricalHu2006.conservative_step_update)
+ end
+ else
+ -- compute a random initial layout for the coarsest graph
+ self:computeInitialLayout(coarse_graph.graph, self.natural_spring_length)
+
+ -- set the spring length to the average edge length of the initial layout
+ spring_length = 0
+ for _,e in ipairs(coarse_graph.graph.edges) do
+ spring_length = spring_length + edge.nodes[1].pos:minus(edge.nodes[2].pos):norm()
+ end
+ spring_length = spring_length / #coarse_graph.graph.edges
+
+ -- improve the layout with the force-based algorithm
+ self:computeForceLayout(coarse_graph.graph, spring_length, SpringElectricalHu2006.adaptive_step_update)
+ end
+end
+
+
+
+function SpringElectricalHu2006:computeInitialLayout(graph, spring_length)
+ -- TODO how can supernodes and fixed nodes go hand in hand?
+ -- maybe fix the supernode if at least one of its subnodes is
+ -- fixated?
+
+ -- fixate all nodes that have a 'desired at' option. this will set the
+ -- node.fixed member to true and also set node.pos.x and node.pos.y
+ self:fixateNodes(graph)
+
+ if #graph.nodes == 2 then
+ if not (graph.nodes[1].fixed and graph.nodes[2].fixed) then
+ local fixed_index = graph.nodes[2].fixed and 2 or 1
+ local loose_index = graph.nodes[2].fixed and 1 or 2
+
+ if not graph.nodes[1].fixed and not graph.nodes[2].fixed then
+ -- both nodes can be moved, so we assume node 1 is fixed at (0,0)
+ graph.nodes[1].pos.x = 0
+ graph.nodes[1].pos.y = 0
+ end
+
+ -- position the loose node relative to the fixed node, with
+ -- the displacement (random direction) matching the spring length
+ local direction = Vector.new{x = math.random(1, spring_length), y = math.random(1, spring_length)}
+ local distance = 3 * spring_length * self.graph_density * math.sqrt(self.graph_size) / 2
+ local displacement = direction:normalized():timesScalar(distance)
+
+ graph.nodes[loose_index].pos = graph.nodes[fixed_index].pos:plus(displacement)
+ else
+ -- both nodes are fixed, initial layout may be far from optimal
+ end
+ else
+
+ -- use a random positioning technique
+ local function positioning_func(n)
+ local radius = 3 * spring_length * self.graph_density * math.sqrt(self.graph_size) / 2
+ return math.random(-radius, radius)
+ end
+
+ -- compute initial layout based on the random positioning technique
+ for _,node in ipairs(graph.nodes) do
+ if not node.fixed then
+ node.pos.x = positioning_func(1)
+ node.pos.y = positioning_func(2)
+ end
+ end
+ end
+end
+
+
+
+function SpringElectricalHu2006:computeForceLayout(graph, spring_length, step_update_func)
+ -- global (=repulsive) force function
+ function accurate_repulsive_force(distance, weight)
+ -- note: the weight is taken into the equation here. unlike in the original
+ -- algorithm different electric charges are allowed for each node in this
+ -- implementation
+ return - weight * self.spring_constant * math.pow(spring_length, self.repulsive_force_order + 1) / math.pow(distance, self.repulsive_force_order)
+ end
+
+ -- global (=repulsive, approximated) force function
+ function approximated_repulsive_force(distance, mass)
+ return - mass * self.spring_constant * math.pow(spring_length, self.repulsive_force_order + 1) / math.pow(distance, self.repulsive_force_order)
+ end
+
+ -- local (spring) force function
+ function attractive_force(distance)
+ return (distance * distance) / spring_length
+ end
+
+ -- define the Barnes-Hut opening criterion
+ function barnes_hut_criterion(cell, particle)
+ local distance = particle.pos:minus(cell.center_of_mass):norm()
+ return cell.width / distance <= 1.2
+ end
+
+ -- fixate all nodes that have a 'desired at' option. this will set the
+ -- node.fixed member to true and also set node.pos.x and node.pos.y
+ self:fixateNodes(graph)
+
+ -- adjust the initial step length automatically if desired by the user
+ local step_length = self.initial_step_length == 0 and spring_length or self.initial_step_length
+
+ -- convergence criteria etc.
+ local converged = false
+ local energy = math.huge
+ local iteration = 0
+ local progress = 0
+
+ while not converged and iteration < self.iterations do
+ -- remember old node positions
+ local old_positions = lib.map(graph.nodes, function (node)
+ return node.pos:copy(), node
+ end)
+
+ -- remember the old system energy and reset it for the current iteration
+ local old_energy = energy
+ energy = 0
+
+ -- build the quadtree for approximating repulsive forces, if desired
+ local quadtree = nil
+ if self.approximate_repulsive_forces then
+ quadtree = self:buildQuadtree(graph)
+ end
+
+ for _,v in ipairs(graph.nodes) do
+ if not v.fixed then
+ -- vector for the displacement of v
+ local d = Vector.new(2)
+
+ -- compute repulsive forces
+ if self.approximate_repulsive_forces then
+ -- determine the cells that have a repulsive influence on v
+ local cells = quadtree:findInteractionCells(v, barnes_hut_criterion)
+
+ -- compute the repulsive force between these cells and v
+ for _,cell in ipairs(cells) do
+ -- check if the cell is a leaf
+ if #cell.subcells == 0 then
+ -- compute the forces between the node and all particles in the cell
+ for _,particle in ipairs(cell.particles) do
+ local real_particles = lib.copy(particle.subparticles)
+ table.insert(real_particles, particle)
+
+ for _,real_particle in ipairs(real_particles) do
+ local delta = real_particle.pos:minus(v.pos)
+
+ -- enforce a small virtual distance if the node and the cell's
+ -- center of mass are located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the repulsive force vector
+ local repulsive_force = approximated_repulsive_force(delta:norm(), real_particle.mass)
+ local force = delta:normalized():timesScalar(repulsive_force)
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+ end
+ else
+ -- compute the distance between the node and the cell's center of mass
+ local delta = cell.center_of_mass:minus(v.pos)
+
+ -- enforce a small virtual distance if the node and the cell's
+ -- center of mass are located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the repulsive force vector
+ local repulsive_force = approximated_repulsive_force(delta:norm(), cell.mass)
+ local force = delta:normalized():timesScalar(repulsive_force)
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+ end
+ else
+ for _,u in ipairs(graph.nodes) do
+ if v ~= u then
+ -- compute the distance between u and v
+ local delta = u.pos:minus(v.pos)
+
+ -- enforce a small virtual distance if the nodes are
+ -- located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the repulsive force vector
+ local repulsive_force = accurate_repulsive_force(delta:norm(), u.weight)
+ local force = delta:normalized():timesScalar(repulsive_force)
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+ end
+ end
+
+ -- compute attractive forces between v and its neighbours
+ for _,edge in ipairs(v.edges) do
+ local u = edge:getNeighbour(v)
+
+ -- compute the distance between u and v
+ local delta = u.pos:minus(v.pos)
+
+ -- enforce a small virtual distance if the nodes are
+ -- located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the spring force vector between u and v
+ local attr_force = attractive_force(delta:norm())
+ local force = delta:normalized():timesScalar(attr_force)
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+
+ -- really move the node now
+ -- TODO note how all nodes are moved by the same amount (step_length)
+ -- while Walshaw multiplies the normalized force with min(step_length,
+ -- d:norm()). could that improve this algorithm even further?
+ v.pos = v.pos:plus(d:normalized():timesScalar(step_length))
+
+ -- TODO Hu doesn't mention this but the energy of a particle is
+ -- typically considered as the product of its mass and the square of
+ -- its forces. This means we should probably take the weight of
+ -- the node v into the equation, doesn't it?
+ --
+ -- update the energy function
+ energy = energy + math.pow(d:norm(), 2)
+ end
+ end
+
+ -- update the step length and progress counter
+ step_length, progress = step_update_func(step_length, self.cooling_factor, energy, old_energy, progress)
+
+ -- compute the maximum node movement in this iteration
+ local max_movement = 0
+ for _,x in ipairs(graph.nodes) do
+ local delta = x.pos:minus(old_positions[x])
+ max_movement = math.max(delta:norm(), max_movement)
+ end
+
+ -- the algorithm will converge if the maximum movement is below a
+ -- threshold depending on the spring length and the convergence
+ -- tolerance
+ if max_movement < spring_length * self.convergence_tolerance then
+ converged = true
+ end
+
+ -- increment the iteration counter
+ iteration = iteration + 1
+ end
+end
+
+
+
+-- Fixes nodes at their specified positions.
+--
+function SpringElectricalHu2006:fixateNodes(graph)
+ local number_of_fixed_nodes = 0
+
+ for _,node in ipairs(graph.nodes) do
+ -- read the 'desired at' option of the node
+ local coordinate = node:getOption('desired at')
+
+ if coordinate then
+ -- apply the coordinate
+ node.pos.x = coordinate.x
+ node.pos.y = coordinate.y
+
+ -- mark the node as fixed
+ node.fixed = true
+
+ number_of_fixed_nodes = number_of_fixed_nodes + 1
+ end
+ end
+ if number_of_fixed_nodes > 1 then
+ self.growth_direction = "fixed" -- do not grow, orientation is now fixed
+ end
+end
+
+
+
+function SpringElectricalHu2006:buildQuadtree(graph)
+ -- compute the minimum x and y coordinates of all nodes
+ local min_pos = graph.nodes[1].pos
+ for _,node in ipairs(graph.nodes) do
+ min_pos = Vector.new(2, function (n) return math.min(min_pos[n], node.pos[n]) end)
+ end
+
+ -- compute maximum x and y coordinates of all nodes
+ local max_pos = graph.nodes[1].pos
+ for _,node in ipairs(graph.nodes) do
+ max_pos = Vector.new(2, function (n) return math.max(max_pos[n], node.pos[n]) end)
+ end
+
+ -- make sure the maximum position is at least a tiny bit
+ -- larger than the minimum position
+ if min_pos:equals(max_pos) then
+ max_pos = max_pos:plus(Vector.new(2, function (n)
+ return 0.1 + math.random() * 0.1
+ end))
+ end
+
+ -- make sure to make the quadtree area slightly larger than required
+ -- in theory; for some reason Lua will otherwise think that nodes with
+ -- min/max x/y coordinates are outside the box... weird? yes.
+ min_pos = min_pos:minus({1,1})
+ max_pos = max_pos:plus({1,1})
+
+ -- create the quadtree
+ quadtree = QuadTree.new(min_pos.x, min_pos.y,
+ max_pos.x - min_pos.x,
+ max_pos.y - min_pos.y)
+
+ -- insert nodes into the quadtree
+ for _,node in ipairs(graph.nodes) do
+ local particle = QuadTree.Particle.new(node.pos, node.weight)
+ particle.node = node
+ quadtree:insert(particle)
+ end
+
+ return quadtree
+end
+
+
+
+function SpringElectricalHu2006.conservative_step_update(step, cooling_factor)
+ return cooling_factor * step, nil
+end
+
+
+
+function SpringElectricalHu2006.adaptive_step_update(step, cooling_factor, energy, old_energy, progress)
+ if energy < old_energy then
+ progress = progress + 1
+ if progress >= 5 then
+ progress = 0
+ step = step / cooling_factor
+ end
+ else
+ progress = 0
+ step = cooling_factor * step
+ end
+ return step, progress
+end
+
+
+-- done
+
+return SpringElectricalHu2006 \ No newline at end of file
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalLayouts.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalLayouts.lua
new file mode 100644
index 00000000000..f8854e71618
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalLayouts.lua
@@ -0,0 +1,54 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalLayouts.lua,v 1.4 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+---
+-- @section subsection {Spring Electrical Layouts}
+--
+-- @end
+
+
+
+---
+
+declare {
+ key = "spring electrical layout",
+ use = {
+ { key = "spring electrical Hu 2006 layout" },
+ { key = "spring constant", value = "0.2" }
+ },
+
+ summary = [["
+ This key selects Hu's 2006 spring electrical layout with
+ appropriate settings for some parameters.
+ "]]
+ }
+
+
+---
+
+declare {
+ key = "spring electrical layout'",
+ use = {
+ { key = "spring electrical Walshaw 2000 layout" },
+ { key = "spring constant", value = "0.01" },
+ { key = "convergence tolerance", value = "0.001" },
+ },
+
+ summary = [["
+ This key selects Walshaw's 2000 spring electrical layout with
+ appropriate settings for some parameters.
+ "]]
+ }
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalWalshaw2000.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalWalshaw2000.lua
new file mode 100644
index 00000000000..25782bc9c3c
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalWalshaw2000.lua
@@ -0,0 +1,516 @@
+-- Copyright 2011 by Jannis Pohlmann
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed and/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringElectricalWalshaw2000.lua,v 1.1 2012/11/27 17:24:25 tantau Exp $
+
+
+
+
+local SpringElectricalWalshaw2000 = {}
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+
+
+---
+
+declare {
+ key = "spring electrical Walshaw 2000 layout",
+ algorithm = SpringElectricalWalshaw2000,
+
+ preconditions = {
+ connected = true,
+ loop_free = true,
+ simple = true,
+ },
+
+ old_graph_model = true,
+
+ summary = [["
+ Implementation of a spring electrical graph drawing algorithm based on
+ a paper by Walshaw.
+ "]],
+ documentation = [["
+ \begin{itemize}
+ \item
+ C. Walshaw.
+ \newblock A multilevel algorithm for force-directed graph
+ drawing.
+ \newblock In J. Marks, editor, \emph{Graph Drawing}, Lecture Notes in
+ Computer Science, 1984:31--55, 2001.
+ \end{itemize}
+
+ The following modifications compared to the original algorithm were applied:
+ \begin{itemize}
+ \item An iteration limit was added.
+ \item The natural spring length for all coarse graphs is computed based
+ on the formula presented by Walshaw, so that the natural spring
+ length of the original graph (coarse graph 0) is the same as
+ the value requested by the user.
+ \item Users can define custom node and edge weights.
+ \item Coarsening stops when $|V(G_i+1)|/|V(G_i)| < p$ where $p = 0.75$.
+ \item Coarsening stops when the maximal matching is empty.
+ \item Theruntime of the algorithm is improved by use of a quadtree
+ data structure like Hu does in his algorithm.
+ \item A limiting the number of levels of the quadtree is not implemented.
+ \end{itemize}
+ "]]
+}
+
+-- TODO Implement the following keys (or whatever seems appropriate
+-- and doable for this algorithm):
+-- - /tikz/desired at
+-- - /tikz/influence cutoff distance
+-- - /tikz/spring stiffness (could this be the equivalent to the electric
+-- charge of nodes?
+-- - /tikz/natural spring dimension per edge
+--
+-- TODO Implement the following features:
+-- - clustering of nodes using color classes
+-- - different cluster layouts (vertical line, horizontal line,
+-- normal cluster, internally fixed subgraph)
+
+
+
+local Vector = require "pgf.gd.deprecated.Vector"
+
+local QuadTree = require "pgf.gd.force.QuadTree"
+local CoarseGraph = require "pgf.gd.force.CoarseGraph"
+
+
+local lib = require "pgf.gd.lib"
+
+
+function SpringElectricalWalshaw2000:run()
+
+ -- Setup parameters
+ local options = self.digraph.options
+
+ self.iterations = options['iterations']
+ self.cooling_factor = options['cooling factor']
+ self.initial_step_length = options['initial step length']
+ self.convergence_tolerance = options['convergence tolerance']
+
+ self.natural_spring_length = options['node distance']
+ self.spring_constant = options['spring constant']
+
+ self.approximate_repulsive_forces = options['approximate remote forces']
+ self.repulsive_force_order = options['electric force order']
+
+ self.coarsen = options['coarsen']
+ self.downsize_ratio = options['downsize ratio']
+ self.minimum_graph_size = options['minimum coarsening size']
+
+ -- Adjust types
+ self.downsize_ratio = math.max(0, math.min(1, self.downsize_ratio))
+ self.graph_size = #self.graph.nodes
+ self.graph_density = (2 * #self.graph.edges) / (#self.graph.nodes * (#self.graph.nodes - 1))
+
+ -- validate input parameters
+ assert(self.iterations >= 0, 'iterations (value: ' .. self.iterations .. ') need to be greater than 0')
+ assert(self.cooling_factor >= 0 and self.cooling_factor <= 1, 'the cooling factor (value: ' .. self.cooling_factor .. ') needs to be between 0 and 1')
+ assert(self.initial_step_length >= 0, 'the initial step length (value: ' .. self.initial_step_length .. ') needs to be greater than or equal to 0')
+ assert(self.convergence_tolerance >= 0, 'the convergence tolerance (value: ' .. self.convergence_tolerance .. ') needs to be greater than or equal to 0')
+ assert(self.natural_spring_length >= 0, 'the natural spring dimension (value: ' .. self.natural_spring_length .. ') needs to be greater than or equal to 0')
+ assert(self.spring_constant >= 0, 'the spring constant (value: ' .. self.spring_constant .. ') needs to be greater or equal to 0')
+ assert(self.downsize_ratio >= 0 and self.downsize_ratio <= 1, 'the downsize ratio (value: ' .. self.downsize_ratio .. ') needs to be between 0 and 1')
+ assert(self.minimum_graph_size >= 2, 'the minimum coarsening size of coarse graphs (value: ' .. self.minimum_graph_size .. ') needs to be greater than or equal to 2')
+
+ -- initialize node weights
+ for _,node in ipairs(self.graph.nodes) do
+ node.weight = node:getOption('electric charge')
+
+ -- a node is charged if its weight derives from the default setting
+ -- of 1 (where it has no influence on the forces)
+ node.charged = node.weight ~= 1
+ end
+
+ -- initialize edge weights
+ for _,edge in ipairs(self.graph.edges) do
+ edge.weight = 1
+ end
+
+
+ -- initialize the coarse graph data structure. note that the algorithm
+ -- is the same regardless whether coarsening is used, except that the
+ -- number of coarsening steps without coarsening is 0
+ local coarse_graph = CoarseGraph.new(self.graph)
+
+ -- check if the multilevel approach should be used
+ if self.coarsen then
+ -- coarsen the graph repeatedly until only minimum_graph_size nodes
+ -- are left or until the size of the coarse graph was not reduced by
+ -- at least the downsize ratio configured by the user
+ while coarse_graph:getSize() > self.minimum_graph_size
+ and coarse_graph:getRatio() < (1 - self.downsize_ratio)
+ do
+ coarse_graph:coarsen()
+ end
+ end
+
+ -- compute the natural spring length for the coarsest graph in a way
+ -- that will result in the desired natural spring length in the
+ -- original graph
+ local spring_length = self.natural_spring_length / math.pow(math.sqrt(4/7), coarse_graph:getLevel())
+
+ if self.coarsen then
+ -- generate a random initial layout for the coarsest graph
+ self:computeInitialLayout(coarse_graph.graph, spring_length)
+
+ -- undo coarsening step by step, applying the force-based sub-algorithm
+ -- to every intermediate coarse graph as well as the original graph
+ while coarse_graph:getLevel() > 0 do
+ -- interpolate the previous coarse graph
+ coarse_graph:interpolate()
+
+ -- update the natural spring length so that, for the original graph,
+ -- it equals the natural spring dimension configured by the user
+ spring_length = spring_length * math.sqrt(4/7)
+
+ -- apply the force-based algorithm to improve the layout
+ self:computeForceLayout(coarse_graph.graph, spring_length)
+ end
+ else
+ -- generate a random initial layout for the coarsest graph
+ self:computeInitialLayout(coarse_graph.graph, spring_length)
+
+ -- apply the force-based algorithm to improve the layout
+ self:computeForceLayout(coarse_graph.graph, spring_length)
+ end
+end
+
+
+
+function SpringElectricalWalshaw2000:computeInitialLayout(graph, spring_length)
+ -- TODO how can supernodes and fixed nodes go hand in hand?
+ -- maybe fix the supernode if at least one of its subnodes is
+ -- fixated?
+
+ -- fixate all nodes that have a 'desired at' option. this will set the
+ -- node.fixed member to true and also set node.pos.x and node.pos.y
+ self:fixateNodes(graph)
+
+ if #graph.nodes == 2 then
+ if not (graph.nodes[1].fixed and graph.nodes[2].fixed) then
+ local fixed_index = graph.nodes[2].fixed and 2 or 1
+ local loose_index = graph.nodes[2].fixed and 1 or 2
+
+ if not graph.nodes[1].fixed and not graph.nodes[2].fixed then
+ -- both nodes can be moved, so we assume node 1 is fixed at (0,0)
+ graph.nodes[1].pos.x = 0
+ graph.nodes[1].pos.y = 0
+ end
+
+ -- position the loose node relative to the fixed node, with
+ -- the displacement (random direction) matching the spring length
+ local direction = Vector.new{x = math.random(1, 2), y = math.random(1, 2)}
+ local distance = 3 * spring_length * self.graph_density * math.sqrt(self.graph_size) / 2
+ local displacement = direction:normalized():timesScalar(distance)
+
+ graph.nodes[loose_index].pos = graph.nodes[fixed_index].pos:plus(displacement)
+ else
+ -- both nodes are fixed, initial layout may be far from optimal
+ end
+ else
+ -- function to filter out fixed nodes
+ local function nodeNotFixed(node) return not node.fixed end
+
+ -- use the random positioning technique
+ local function positioning_func(n)
+ local radius = 3 * spring_length * self.graph_density * math.sqrt(self.graph_size) / 2
+ return math.random(-radius, radius)
+ end
+
+ -- compute initial layout based on the random positioning technique
+ for _,node in ipairs(graph.nodes) do
+ if not node.fixed then
+ node.pos.x = positioning_func(1)
+ node.pos.y = positioning_func(2)
+ end
+ end
+ end
+end
+
+
+
+function SpringElectricalWalshaw2000:computeForceLayout(graph, spring_length)
+ -- global (=repulsive) force function
+ local function accurate_repulsive_force(distance, weight)
+ return - self.spring_constant * weight * math.pow(spring_length, self.repulsive_force_order + 1) / math.pow(distance, self.repulsive_force_order)
+ end
+
+ -- global (=repulsive, approximated) force function
+ local function approximated_repulsive_force(distance, mass)
+ return - mass * self.spring_constant * math.pow(spring_length, self.repulsive_force_order + 1) / math.pow(distance, self.repulsive_force_order)
+ end
+
+ -- local (spring) force function
+ local function attractive_force(distance, d, weight, charged, repulsive_force)
+ -- for charged nodes, never subtract the repulsive force; we want ALL other
+ -- nodes to be attracted more / repulsed less (not just non-adjacent ones),
+ -- depending on the charge of course
+ if charged then
+ return (distance - spring_length) / d - accurate_repulsive_force(distance, weight)
+ else
+ return (distance - spring_length) / d - (repulsive_force or 0)
+ end
+ end
+
+ -- define the Barnes-Hut opening criterion
+ function barnes_hut_criterion(cell, particle)
+ local distance = particle.pos:minus(cell.center_of_mass):norm()
+ return cell.width / distance <= 1.2
+ end
+
+ -- fixate all nodes that have a 'desired at' option. this will set the
+ -- node.fixed member to true and also set node.pos.x and node.pos.y
+ self:fixateNodes(graph)
+
+ -- adjust the initial step length automatically if desired by the user
+ local step_length = self.initial_step_length == 0 and spring_length or self.initial_step_length
+
+ -- convergence criteria
+ local converged = false
+ local i = 0
+
+ while not converged and i < self.iterations do
+
+ -- assume that we are converging
+ converged = true
+ i = i + 1
+
+ -- build the quadtree for approximating repulsive forces, if desired
+ local quadtree = nil
+ if self.approximate_repulsive_forces then
+ quadtree = self:buildQuadtree(graph)
+ end
+
+ local function nodeNotFixed(node) return not node.fixed end
+
+ -- iterate over all nodes
+ for _,v in ipairs(graph.nodes) do
+ if not v.fixed then
+ -- vector for the displacement of v
+ local d = Vector.new(2)
+
+ -- repulsive force induced by other nodes
+ local repulsive_forces = {}
+
+ -- compute repulsive forces
+ if self.approximate_repulsive_forces then
+ -- determine the cells that have an repulsive influence on v
+ local cells = quadtree:findInteractionCells(v, barnes_hut_criterion)
+
+ -- compute the repulsive force between these cells and v
+ for _,cell in ipairs(cells) do
+ -- check if the cell is a leaf
+ if #cell.subcells == 0 then
+ -- compute the forces between the node and all particles in the cell
+ for _,particle in ipairs(cell.particles) do
+ -- build a table that contains the particle plus all its subparticles
+ -- (particles at the same position)
+ local real_particles = lib.copy(particle.subparticles)
+ table.insert(real_particles, particle)
+
+ for _,real_particle in ipairs(real_particles) do
+ local delta = real_particle.pos:minus(v.pos)
+
+ -- enforce a small virtual distance if the node and the cell's
+ -- center of mass are located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the repulsive force vector
+ local repulsive_force = approximated_repulsive_force(delta:norm(), real_particle.mass)
+ local force = delta:normalized():timesScalar(repulsive_force)
+
+ -- remember the repulsive force for the particle so that we can
+ -- subtract it later when computing the attractive forces with
+ -- adjacent nodes
+ repulsive_forces[real_particle.node] = repulsive_force
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+ end
+ else
+ -- compute the distance between the node and the cell's center of mass
+ local delta = cell.center_of_mass:minus(v.pos)
+
+ -- enforce a small virtual distance if the node and the cell's
+ -- center of mass are located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the repulsive force vector
+ local repulsive_force = approximated_repulsive_force(delta:norm(), cell.mass)
+ local force = delta:normalized():timesScalar(repulsive_force)
+
+ -- TODO for each neighbour of v, check if it is in this cell.
+ -- if this is the case, compute the quadtree force for the mass
+ -- 'node.weight / cell.mass' and remember this as the repulsive
+ -- force of the neighbour; (it is not necessarily at
+ -- the center of mass of the cell, so the result is only an
+ -- approximation of the real repulsive force generated by the
+ -- neighbour)
+
+ -- move te node v accordingly
+ d = d:plus(force)
+ end
+ end
+ else
+ for _,u in ipairs(graph.nodes) do
+ if u.name ~= v.name then
+ -- compute the distance between u and v
+ local delta = u.pos:minus(v.pos)
+
+ -- enforce a small virtual distance if the nodes are
+ -- located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the repulsive force vector
+ local repulsive_force = accurate_repulsive_force(delta:norm(), u.weight)
+ local force = delta:normalized():timesScalar(repulsive_force)
+
+ -- remember the repulsive force so we can later subtract them
+ -- when computing the attractive forces
+ repulsive_forces[u] = repulsive_force
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+ end
+ end
+
+ -- compute attractive forces between v and its neighbours
+ for _,edge in ipairs(v.edges) do
+ local u = edge:getNeighbour(v)
+
+ -- compute the distance between u and v
+ local delta = u.pos:minus(v.pos)
+
+ -- enforce a small virtual distance if the nodes are
+ -- located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ -- compute the spring force between them
+ local attr_force = attractive_force(delta:norm(), #v.edges, u.weight, u.charged, repulsive_forces[u])
+ local force = delta:normalized():timesScalar(attr_force)
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+
+ -- remember the previous position of v
+ old_position = v.pos:copy()
+
+ if d:norm() > 0 then
+ -- reposition v according to the force vector and the current temperature
+ v.pos = v.pos:plus(d:normalized():timesScalar(math.min(step_length, d:norm())))
+ end
+
+ -- we need to improve the system energy as long as any of
+ -- the node movements is large enough to assume we're far
+ -- away from the minimum system energy
+ if v.pos:minus(old_position):norm() > spring_length * self.convergence_tolerance then
+ converged = false
+ end
+ end
+ end
+
+ -- update the step length using the conservative cooling scheme
+ step_length = self.cooling_factor * step_length
+ end
+end
+
+
+
+-- Fixes nodes at their specified positions.
+--
+function SpringElectricalWalshaw2000:fixateNodes(graph)
+ local number_of_fixed_nodes = 0
+
+ for _,node in ipairs(graph.nodes) do
+ -- read the 'desired at' option of the node
+ local coordinate = node:getOption('desired at')
+
+ if coordinate then
+ -- parse the coordinate
+ node.pos.x = coordinate.x
+ node.pos.y = coordinate.y
+
+ -- mark the node as fixed
+ node.fixed = true
+
+ number_of_fixed_nodes = number_of_fixed_nodes + 1
+ end
+ end
+ if number_of_fixed_nodes > 1 then
+ self.growth_direction = "fixed" -- do not grow, orientation is now fixed
+ end
+end
+
+
+
+function SpringElectricalWalshaw2000:buildQuadtree(graph)
+ -- compute the minimum x and y coordinates of all nodes
+ local min_pos = graph.nodes[1].pos
+ for _,node in ipairs(graph.nodes) do
+ min_pos = Vector.new(2, function (n) return math.min(min_pos[n], node.pos[n]) end)
+ end
+
+ -- compute maximum x and y coordinates of all nodes
+ local max_pos = graph.nodes[1].pos
+ for _,node in ipairs(graph.nodes) do
+ max_pos = Vector.new(2, function (n) return math.max(max_pos[n], node.pos[n]) end)
+ end
+
+ -- make sure the maximum position is at least a tiny bit
+ -- larger than the minimum position
+ if min_pos:equals(max_pos) then
+ max_pos = max_pos:plus(Vector.new(2, function (n)
+ return 0.1 + math.random() * 0.1
+ end))
+ end
+
+ -- make sure to make the quadtree area slightly larger than required
+ -- in theory; for some reason Lua will otherwise think that nodes with
+ -- min/max x/y coordinates are outside the box... weird? yes.
+ min_pos = min_pos:minusScalar(1)
+ max_pos = max_pos:plusScalar(1)
+
+ -- create the quadtree
+ quadtree = QuadTree.new(min_pos.x, min_pos.y,
+ max_pos.x - min_pos.x,
+ max_pos.y - min_pos.y)
+
+ -- insert nodes into the quadtree
+ for _,node in ipairs(graph.nodes) do
+ local particle = QuadTree.Particle.new(node.pos, node.weight)
+ particle.node = node
+ quadtree:insert(particle)
+ end
+
+ return quadtree
+end
+
+
+
+-- done
+
+return SpringElectricalWalshaw2000 \ No newline at end of file
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringHu2006.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringHu2006.lua
new file mode 100644
index 00000000000..35dc21008fb
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringHu2006.lua
@@ -0,0 +1,387 @@
+-- Copyright 2011 by Jannis Pohlmann
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed and/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringHu2006.lua,v 1.1 2012/11/27 17:24:25 tantau Exp $
+
+
+
+local SpringHu2006 = {}
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+
+
+---
+
+declare {
+ key = "spring Hu 2006 layout",
+ algorithm = SpringHu2006,
+
+ preconditions = {
+ connected = true,
+ loop_free = true,
+ simple = true,
+ },
+
+ old_graph_model = true,
+
+ summary = [["
+ Implementation of a spring graph drawing algorithm based on
+ a paper by Hu.
+ "]],
+ documentation = [["
+ \begin{itemize}
+ \item
+ Y. Hu.
+ \newblock Efficient, high-quality force-directed graph drawing.
+ \newblock \emph{The Mathematica Journal}, 2006.
+ \end{itemize}
+
+ There are some modifications compared to the original algorithm,
+ see the Diploma thesis of Pohlmann for details.
+ "]]
+}
+
+
+-- Imports
+
+local PathLengths = require "pgf.gd.lib.PathLengths"
+local Vector = require "pgf.gd.deprecated.Vector"
+
+local CoarseGraph = require "pgf.gd.force.CoarseGraph"
+
+local lib = require("pgf.gd.lib")
+
+
+
+
+
+function SpringHu2006:run()
+
+ -- Setup some parameters
+ local options = self.digraph.options
+
+ self.iterations = options['iterations']
+ self.cooling_factor = options['cooling factor']
+ self.initial_step_length = options['initial step length']
+ self.convergence_tolerance = options['convergence tolerance']
+
+ self.natural_spring_length = options['node distance']
+
+ self.coarsen = options['coarsen']
+ self.downsize_ratio = options['downsize ratio']
+ self.minimum_graph_size = options['minimum coarsening size']
+
+
+ -- Setup
+
+ self.downsize_ratio = math.max(0, math.min(1, tonumber(self.downsize_ratio)))
+
+ self.graph_size = #self.graph.nodes
+ self.graph_density = (2 * #self.graph.edges) / (#self.graph.nodes * (#self.graph.nodes - 1))
+
+ -- validate input parameters
+ assert(self.iterations >= 0, 'iterations (value: ' .. self.iterations .. ') need to be greater than 0')
+ assert(self.cooling_factor >= 0 and self.cooling_factor <= 1, 'the cooling factor (value: ' .. self.cooling_factor .. ') needs to be between 0 and 1')
+ assert(self.initial_step_length >= 0, 'the initial step length (value: ' .. self.initial_step_length .. ') needs to be greater than or equal to 0')
+ assert(self.convergence_tolerance >= 0, 'the convergence tolerance (value: ' .. self.convergence_tolerance .. ') needs to be greater than or equal to 0')
+ assert(self.natural_spring_length >= 0, 'the natural spring dimension (value: ' .. self.natural_spring_length .. ') needs to be greater than or equal to 0')
+ assert(self.downsize_ratio >= 0 and self.downsize_ratio <= 1, 'the downsize ratio (value: ' .. self.downsize_ratio .. ') needs to be between 0 and 1')
+ assert(self.minimum_graph_size >= 2, 'the minimum coarsening size of coarse graphs (value: ' .. self.minimum_graph_size .. ') needs to be greater than or equal to 2')
+
+ -- initialize node weights
+ for _,node in ipairs(self.graph.nodes) do
+ node.weight = 1
+ end
+
+ -- initialize edge weights
+ for _,edge in ipairs(self.graph.edges) do
+ edge.weight = 1
+ end
+
+
+ -- initialize the coarse graph data structure. note that the algorithm
+ -- is the same regardless whether coarsening is used, except that the
+ -- number of coarsening steps without coarsening is 0
+ local coarse_graph = CoarseGraph.new(self.graph)
+
+ -- check if the multilevel approach should be used
+ if self.coarsen then
+ -- coarsen the graph repeatedly until only minimum_graph_size nodes
+ -- are left or until the size of the coarse graph was not reduced by
+ -- at least the downsize ratio configured by the user
+ while coarse_graph:getSize() > self.minimum_graph_size
+ and coarse_graph:getRatio() <= (1 - self.downsize_ratio)
+ do
+ coarse_graph:coarsen()
+ end
+ end
+
+ if self.coarsen then
+ -- use the natural spring length as the initial natural spring length
+ local spring_length = self.natural_spring_length
+
+ -- compute a random initial layout for the coarsest graph
+ self:computeInitialLayout(coarse_graph.graph, spring_length)
+
+ -- set the spring length to the average edge length of the initial layout
+ spring_length = 0
+ for _,edge in ipairs(coarse_graph.graph.edges) do
+ spring_length = spring_length + edge.nodes[1].pos:minus(edge.nodes[2].pos):norm()
+ end
+ spring_length = spring_length / #coarse_graph.graph.edges
+
+ -- additionally improve the layout with the force-based algorithm
+ -- if there are more than two nodes in the coarsest graph
+ if coarse_graph:getSize() > 2 then
+ self:computeForceLayout(coarse_graph.graph, spring_length, SpringHu2006.adaptive_step_update)
+ end
+
+ -- undo coarsening step by step, applying the force-based sub-algorithm
+ -- to every intermediate coarse graph as well as the original graph
+ while coarse_graph:getLevel() > 0 do
+ -- compute the diameter of the parent coarse graph
+ local parent_diameter = PathLengths.pseudoDiameter(coarse_graph.graph)
+
+ -- interpolate the previous coarse graph from its parent
+ coarse_graph:interpolate()
+
+ -- compute the diameter of the current coarse graph
+ local current_diameter = PathLengths.pseudoDiameter(coarse_graph.graph)
+
+ -- scale node positions by the quotient of the pseudo diameters
+ for _,node in ipairs(coarse_graph.graph) do
+ node.pos:update(function (n, value)
+ return value * (current_diameter / parent_diameter)
+ end)
+ end
+
+ -- compute forces in the graph
+ self:computeForceLayout(coarse_graph.graph, spring_length, SpringHu2006.conservative_step_update)
+ end
+ else
+ -- compute a random initial layout for the coarsest graph
+ self:computeInitialLayout(coarse_graph.graph, self.natural_spring_length)
+
+ -- set the spring length to the average edge length of the initial layout
+ spring_length = 0
+ for _,edge in ipairs(coarse_graph.graph.edges) do
+ spring_length = spring_length + edge.nodes[1].pos:minus(edge.nodes[2].pos):norm()
+ end
+ spring_length = spring_length / #coarse_graph.graph.edges
+
+ -- improve the layout with the force-based algorithm
+ self:computeForceLayout(coarse_graph.graph, spring_length, SpringHu2006.adaptive_step_update)
+ end
+
+ local avg_spring_length = 0
+ for _,edge in ipairs(self.graph.edges) do
+ avg_spring_length = avg_spring_length + edge.nodes[1].pos:minus(edge.nodes[2].pos):norm()
+ end
+ avg_spring_length = avg_spring_length / #self.graph.edges
+end
+
+
+
+function SpringHu2006:computeInitialLayout(graph, spring_length)
+ -- TODO how can supernodes and fixed nodes go hand in hand?
+ -- maybe fix the supernode if at least one of its subnodes is
+ -- fixated?
+
+ -- fixate all nodes that have a 'desired at' option. this will set the
+ -- node.fixed member to true and also set node.pos.x and node.pos.y
+ self:fixateNodes(graph)
+
+ if #graph.nodes == 2 then
+ if not (graph.nodes[1].fixed and graph.nodes[2].fixed) then
+ local fixed_index = graph.nodes[2].fixed and 2 or 1
+ local loose_index = graph.nodes[2].fixed and 1 or 2
+
+ if not graph.nodes[1].fixed and not graph.nodes[2].fixed then
+ -- both nodes can be moved, so we assume node 1 is fixed at (0,0)
+ graph.nodes[1].pos.x = 0
+ graph.nodes[1].pos.y = 0
+ end
+
+ -- position the loose node relative to the fixed node, with
+ -- the displacement (random direction) matching the spring length
+ local direction = Vector.new{x = math.random(1, spring_length), y = math.random(1, spring_length)}
+ local distance = 1.8 * spring_length * self.graph_density * math.sqrt(self.graph_size) / 2
+ local displacement = direction:normalized():timesScalar(distance)
+
+ graph.nodes[loose_index].pos = graph.nodes[fixed_index].pos:plus(displacement)
+ else
+ -- both nodes are fixed, initial layout may be far from optimal
+ end
+ else
+ -- use a random positioning technique
+ local function positioning_func(n)
+ local radius = 2 * spring_length * self.graph_density * math.sqrt(self.graph_size) / 2
+ return math.random(-radius, radius)
+ end
+
+ -- compute initial layout based on the random positioning technique
+ for _,node in ipairs(graph.nodes) do
+ if not node.fixed then
+ node.pos.x = positioning_func(1)
+ node.pos.y = positioning_func(2)
+ end
+ end
+ end
+end
+
+
+
+function SpringHu2006:computeForceLayout(graph, spring_length, step_update_func)
+ -- global (=repulsive) force function
+ function repulsive_force(distance, graph_distance, weight)
+ --return (1/4) * (1/math.pow(graph_distance, 2)) * (distance - (spring_length * graph_distance))
+ return (distance - (spring_length * graph_distance))
+ end
+
+ -- fixate all nodes that have a 'desired at' option. this will set the
+ -- node.fixed member to true and also set node.pos.x and node.pos.y
+ self:fixateNodes(graph)
+
+ -- adjust the initial step length automatically if desired by the user
+ local step_length = self.initial_step_length == 0 and spring_length or self.initial_step_length
+
+ -- convergence criteria etc.
+ local converged = false
+ local energy = math.huge
+ local iteration = 0
+ local progress = 0
+
+ -- compute graph distance between all pairs of nodes
+ local distances = PathLengths.floydWarshall(graph)
+
+ while not converged and iteration < self.iterations do
+ -- remember old node positions
+ local old_positions = lib.map(graph.nodes, function (node) return node.pos:copy(), node end)
+
+ -- remember the old system energy and reset it for the current iteration
+ local old_energy = energy
+ energy = 0
+
+ for _,v in ipairs(graph.nodes) do
+ if not v.fixed then
+ -- vector for the displacement of v
+ local d = Vector.new(2)
+
+ for _,u in ipairs(graph.nodes) do
+ if v ~= u then
+ -- compute the distance between u and v
+ local delta = u.pos:minus(v.pos)
+
+ -- enforce a small virtual distance if the nodes are
+ -- located at (almost) the same position
+ if delta:norm() < 0.1 then
+ delta:update(function (n, value) return 0.1 + math.random() * 0.1 end)
+ end
+
+ local graph_distance = (distances[u] and distances[u][v]) and distances[u][v] or #graph.nodes + 1
+
+ -- compute the repulsive force vector
+ local force = repulsive_force(delta:norm(), graph_distance, v.weight)
+ local force = delta:normalized():timesScalar(force)
+
+ -- move the node v accordingly
+ d = d:plus(force)
+ end
+ end
+
+ -- really move the node now
+ -- TODO note how all nodes are moved by the same amount (step_length)
+ -- while Walshaw multiplies the normalized force with min(step_length,
+ -- d:norm()). could that improve this algorithm even further?
+ v.pos = v.pos:plus(d:normalized():timesScalar(step_length))
+
+ -- update the energy function
+ energy = energy + math.pow(d:norm(), 2)
+ end
+ end
+
+ -- update the step length and progress counter
+ step_length, progress = step_update_func(step_length, self.cooling_factor, energy, old_energy, progress)
+
+ -- compute the maximum node movement in this iteration
+ local max_movement = 0
+ for _,x in ipairs(graph.nodes) do
+ local delta = x.pos:minus(old_positions[x])
+ max_movement = math.max(delta:norm(), max_movement)
+ end
+
+ -- the algorithm will converge if the maximum movement is below a
+ -- threshold depending on the spring length and the convergence
+ -- tolerance
+ if max_movement < spring_length * self.convergence_tolerance then
+ converged = true
+ end
+
+ -- increment the iteration counter
+ iteration = iteration + 1
+ end
+end
+
+
+
+-- Fixes nodes at their specified positions.
+--
+function SpringHu2006:fixateNodes(graph)
+ local number_of_fixed_nodes = 0
+
+ for _,node in ipairs(graph.nodes) do
+ -- read the 'desired at' option of the node
+ local coordinate = node:getOption('desired at')
+
+ if coordinate then
+ -- apply the coordinate
+ node.pos.x = coordinate.x
+ node.pos.y = coordinate.y
+
+ -- mark the node as fixed
+ node.fixed = true
+
+ number_of_fixed_nodes = number_of_fixed_nodes + 1
+ end
+ end
+ if number_of_fixed_nodes > 1 then
+ self.growth_direction = "fixed" -- do not grow, orientation is now fixed
+ end
+end
+
+
+
+function SpringHu2006.conservative_step_update(step, cooling_factor)
+ return cooling_factor * step, nil
+end
+
+
+
+function SpringHu2006.adaptive_step_update(step, cooling_factor, energy, old_energy, progress)
+ if energy < old_energy then
+ progress = progress + 1
+ if progress >= 5 then
+ progress = 0
+ step = step / cooling_factor
+ end
+ else
+ progress = 0
+ step = cooling_factor * step
+ end
+ return step, progress
+end
+
+
+-- done
+
+return SpringHu2006 \ No newline at end of file
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringLayouts.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringLayouts.lua
new file mode 100644
index 00000000000..ab0126d7fcd
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringLayouts.lua
@@ -0,0 +1,36 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/SpringLayouts.lua,v 1.4 2013/05/23 20:01:27 tantau Exp $
+
+
+-- Imports
+local declare = require("pgf.gd.interface.InterfaceToAlgorithms").declare
+
+
+---
+-- @section subsection {Spring Layouts}
+--
+-- @end
+
+
+
+---
+
+declare {
+ key = "spring layout",
+ use = {
+ { key = "spring Hu 2006 layout" },
+ },
+
+ summary = [["
+ This key selects Hu's 2006 spring layout with appropriate settings
+ for some parameters.
+ "]]
+ }
diff --git a/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/library.lua b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/library.lua
new file mode 100644
index 00000000000..af3a1a62c27
--- /dev/null
+++ b/Master/texmf-dist/tex/generic/pgf/graphdrawing/lua/pgf/gd/force/library.lua
@@ -0,0 +1,126 @@
+-- Copyright 2012 by Till Tantau
+--
+-- This file may be distributed an/or modified
+--
+-- 1. under the LaTeX Project Public License and/or
+-- 2. under the GNU Public License
+--
+-- See the file doc/generic/pgf/licenses/LICENSE for more information
+
+-- @release $Header: /cvsroot/pgf/pgf/generic/pgf/graphdrawing/lua/pgf/gd/force/library.lua,v 1.4 2013/05/23 20:01:27 tantau Exp $
+
+
+
+---
+-- Nature creates beautiful graph layouts all the time. Consider a
+-- spider's web: Nodes are connected by edges in a visually most pleasing
+-- manner (if you ignore the spider in the middle). The layout of a
+-- spider's web is created just by the physical forces exerted by the
+-- threads. The idea behind force-based graph drawing algorithms is to
+-- mimic nature: We treat edges as threads that exert forces and simulate
+-- into which configuration the whole graph is ``pulled'' by these
+-- forces.
+--
+-- When you start thinking about for a moment, it turns out that there
+-- are endless variations of the force model. All of these models have
+-- the following in common, however:
+-- \begin{itemize}
+-- \item ``Forces'' pull and push at the nodes in different
+-- directions.
+-- \item The effect of these forces is simulated by iteratively moving
+-- all the nodes simultaneously a little in the direction of the forces
+-- and by then recalculating the forces.
+-- \item The iteration is stopped either after a certain number of
+-- iterations or when a \emph{global energy minimum} is reached (a very
+-- scientific way of saying that nothing happens anymore).
+-- \end{itemize}
+--
+-- The main difference between the different force-based approaches is
+-- how the forces are determined. Here are some ideas what could cause a
+-- force to be exerted between two nodes (and there are more):
+-- \begin{itemize}
+-- \item If the nodes are connected by an edge, one can treat the edge as
+-- a ``spring'' that has a ``natural spring dimension.'' If the nodes
+-- are nearer than the spring dimension, they are push apart; if they
+-- are farther aways than the spring dimension, they are pulled
+-- together.
+-- \item If two nodes are connected by a path of a certain length, the
+-- nodes may ``wish to be at a distance proportional to the path
+-- length''. If they are nearer, they are pushed apart; if they are
+-- farther, they are pulled together. (This is obviously a
+-- generalization of the previous idea.)
+-- \item There may be a general force field that pushes nodes apart (an
+-- electrical field), so that nodes do not tend to ``cluster''.
+-- \item There may be a general force field that pulls nodes together (a
+-- gravitational field), so that nodes are not too loosely scattered.
+-- \item There may be highly nonlinear forces depending on the distance of
+-- nodes, so that nodes very near to each get pushed apart strongly,
+-- but the effect wears of rapidly at a distance. (Such forces are
+-- known as strong nuclear forces.)
+-- \item There rotational forces caused by the angles between the edges
+-- leaving a node. Such forces try to create a \emph{perfect angular
+-- resolution} (a very scientific way of saying that all angles
+-- at a node are equal).
+-- \end{itemize}
+--
+-- Force-based algorithms combine one or more of the above ideas into a
+-- single algorithm that uses ``good'' formulas for computing the
+-- forces.
+--
+-- Currently, three algorithms are implemented in this library, two of
+-- which are from the first of the following paper, while the third is
+-- from the third paper:
+--
+-- \begin{itemize}
+-- \item
+-- Y. Hu.
+-- \newblock Efficient, high-quality force-directed graph drawing.
+-- \newblock \emph{The Mathematica Journal}, 2006.
+-- \item
+-- C. Walshaw.
+-- \newblock A multilevel algorithm for force-directed graph
+-- drawing.
+-- \newblock In J. Marks, editor, \emph{Graph Drawing}, Lecture Notes in
+-- Computer Science, 1984:31--55, 2001.
+-- \end{itemize}
+--
+-- Our implementation is described in detail in the following
+-- diploma thesis:
+--
+-- \begin{itemize}
+-- \item
+-- Jannis Pohlmann,
+-- \newblock \emph{Configurable Graph Drawing Algorithms
+-- for the \tikzname\ Graphics Description Language,}
+-- \newblock Diploma Thesis,
+-- \newblock Institute of Theoretical Computer Science, Univerist\"at
+-- zu L\"ubeck, 2011.\\[.5em]
+-- \newblock Online at
+-- \url{http://www.tcs.uni-luebeck.de/downloads/papers/2011/}\\ \url{2011-configurable-graph-drawing-algorithms-jannis-pohlmann.pdf}
+-- \end{itemize}
+--
+-- In the future, I hope that most, if not all, of the force-based
+-- algorithms become ``just configuration options'' of a general
+-- force-based algorithm similar to the way the modular Sugiyama method
+-- is implemented in the |layered| graph drawing library.
+--
+-- @library
+
+local force -- Library name
+
+-- Load declarations from:
+require "pgf.gd.force.Control"
+require "pgf.gd.force.ControlStart"
+require "pgf.gd.force.ControlIteration"
+require "pgf.gd.force.ControlSprings"
+require "pgf.gd.force.ControlElectric"
+require "pgf.gd.force.ControlCoarsening"
+
+require "pgf.gd.force.SpringLayouts"
+require "pgf.gd.force.SpringElectricalLayouts"
+
+-- Load algorithms from:
+require "pgf.gd.force.SpringHu2006"
+require "pgf.gd.force.SpringElectricalHu2006"
+require "pgf.gd.force.SpringElectricalWalshaw2000"
+