Merge pull request #67 from JuliaRobotics/feature/LightGraphs

LightGraphs integration

Author: GearsAD

.travis.yml

@@ -28,6 +28,10 @@ matrix:
 #   - if [[ -a .git/shallow ]]; then git fetch --unshallow; fi
 #   - julia --check-bounds=yes -e 'using Pkg; Pkg.clone(pwd()); Pkg.build("DistributedFactorGraphs"); Pkg.test("DistributedFactorGraphs"; coverage=true)'
 
+# can be used if master of package is required
+# script:
+#     - julia --project --color=yes --check-bounds=yes -e 'using Pkg; Pkg.add(PackageSpec(name="MetaGraphs", rev="master")); Pkg.build(); Pkg.test(coverage=true)'
+
 after_success:
     - julia -e 'using Pkg; cd(Pkg.dir("DistributedFactorGraphs")); Pkg.add("Coverage"); using Coverage; Codecov.submit(process_folder()); Coveralls.submit(process_folder())'
 

Project.toml

@@ -9,7 +9,9 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 JSON2 = "2535ab7d-5cd8-5a07-80ac-9b1792aadce3"
+LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5"
 Neo4j = "d2adbeaf-5838-5367-8a2f-e46d570981db"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
@@ -21,6 +23,7 @@ Graphs = "≥ 0.10.3"
 Reexport = "≥ 0.2"
 Requires = "≥ 0.5"
 julia = "0.7, 1"
+MetaGraphs = "≥ 0.6.4"
 
 [extras]
 IncrementalInference = "904591bb-b899-562f-9e6f-b8df64c7d480"

src/DistributedFactorGraphs.jl

@@ -44,6 +44,9 @@ include("GraphsDFG/GraphsDFG.jl")
 # Include the FilesDFG API.
 include("FileDFG/FileDFG.jl")
 
+# Include the LightGraphs.jl (MetaGraphs.jl) API.
+include("LightGraphsDFG/LightGraphsDFG.jl")
+
 export saveDFG, loadDFG
 
 function __init__()
@@ -55,7 +58,7 @@ function __init__()
             Rows are all factors, columns are all variables, and each cell contains either nothing or the symbol of the relating factor.
             The first column is the factor headings.
             """
-            function getAdjacencyMatrixDataFrame(dfg::GraphsDFG)::Main.DataFrames.DataFrame
+            function getAdjacencyMatrixDataFrame(dfg::Union{GraphsDFG, LightGraphsDFG})::Main.DataFrames.DataFrame
                 varLabels = sort(map(v->v.label, getVariables(dfg)))
                 factLabels = sort(map(f->f.label, getFactors(dfg)))
                 adjDf = DataFrames.DataFrame(:Factor => Union{Missing, Symbol}[])

src/GraphsDFG/services/GraphsDFG.jl

@@ -195,7 +195,7 @@ end
     $(SIGNATURES)
 Delete a referenced DFGVariable from the DFG.
 """
-deleteVariable!(dfg::GraphsDFG, variable::DFGVariable)::DFGVariable = deleteVariable(dfg, variable.label)
+deleteVariable!(dfg::GraphsDFG, variable::DFGVariable)::DFGVariable = deleteVariable!(dfg, variable.label)
 
 """
     $(SIGNATURES)
@@ -224,7 +224,7 @@ List the DFGVariables in the DFG.
 Optionally specify a label regular expression to retrieves a subset of the variables.
 """
 function getVariables(dfg::GraphsDFG, regexFilter::Union{Nothing, Regex}=nothing; tags::Vector{Symbol}=Symbol[])::Vector{DFGVariable}
-    variables = map(v -> v.dfgNode, filter(n -> n.dfgNode isa DFGVariable, vertices(dfg.g)))
+    variables = map(v -> v.dfgNode, filter(n -> n.dfgNode isa DFGVariable, Graphs.vertices(dfg.g)))
     if regexFilter != nothing
         variables = filter(v -> occursin(regexFilter, String(v.label)), variables)
     end
@@ -269,7 +269,7 @@ List the DFGFactors in the DFG.
 Optionally specify a label regular expression to retrieves a subset of the factors.
 """
 function getFactors(dfg::GraphsDFG, regexFilter::Union{Nothing, Regex}=nothing)::Vector{DFGFactor}
-	factors = map(v -> v.dfgNode, filter(n -> n.dfgNode isa DFGFactor, vertices(dfg.g)))
+	factors = map(v -> v.dfgNode, filter(n -> n.dfgNode isa DFGFactor, Graphs.vertices(dfg.g)))
 	if regexFilter != nothing
 		factors = filter(f -> occursin(regexFilter, String(f.label)), factors)
 	end
@@ -304,7 +304,7 @@ end
 Checks if the graph is fully connected, returns true if so.
 """
 function isFullyConnected(dfg::GraphsDFG)::Bool
-    return length(connected_components(dfg.g)) == 1
+    return length(Graphs.connected_components(dfg.g)) == 1
 end
 
 #Alias
@@ -326,8 +326,8 @@ function getNeighbors(dfg::GraphsDFG, node::T; ready::Union{Nothing, Int}=nothin
     vert = dfg.g.vertices[dfg.labelDict[node.label]]
     neighbors = in_neighbors(vert, dfg.g) #Don't use out_neighbors! It enforces directiveness even if we don't want it
     # Additional filtering
-    neighbors = ready != nothing ? filter(v -> v.ready == ready, neighbors) : neighbors
-    neighbors = backendset != nothing ? filter(v -> v.backendset == backendset, neighbors) : neighbors
+    neighbors = ready != nothing ? filter(v -> v.dfgNode.ready == ready, neighbors) : neighbors
+    neighbors = backendset != nothing ? filter(v -> v.dfgNode.backendset == backendset, neighbors) : neighbors
     # Variable sorting (order is important)
     if node isa DFGFactor
         order = intersect(node._variableOrderSymbols, map(v->v.dfgNode.label, neighbors))
@@ -347,8 +347,8 @@ function getNeighbors(dfg::GraphsDFG, label::Symbol; ready::Union{Nothing, Int}=
     vert = dfg.g.vertices[dfg.labelDict[label]]
     neighbors = in_neighbors(vert, dfg.g) #Don't use out_neighbors! It enforces directiveness even if we don't want it
     # Additional filtering
-    neighbors = ready != nothing ? filter(v -> v.ready == ready, neighbors) : neighbors
-    neighbors = backendset != nothing ? filter(v -> v.backendset == backendset, neighbors) : neighbors
+    neighbors = ready != nothing ? filter(v -> v.dfgNode.ready == ready, neighbors) : neighbors
+    neighbors = backendset != nothing ? filter(v -> v.dfgNode.backendset == backendset, neighbors) : neighbors
     # Variable sorting when using a factor (function order is important)
     if vert.dfgNode isa DFGFactor
         vert.dfgNode._variableOrderSymbols
@@ -451,7 +451,7 @@ Get a deep subgraph copy from the DFG given a list of variables and factors.
 Optionally provide an existing subgraph addToDFG, the extracted nodes will be copied into this graph. By default a new subgraph will be created.
 Note: By default orphaned factors (where the subgraph does not contain all the related variables) are not returned. Set includeOrphanFactors to return the orphans irrespective of whether the subgraph contains all the variables.
 """
-function getSubgraph(dfg::GraphsDFG, variableFactorLabels::Vector{Symbol}, includeOrphanFactors::Bool=false, addToDFG::GraphsDFG=GraphsDFG())::GraphsDFG
+function getSubgraph(dfg::GraphsDFG, variableFactorLabels::Vector{Symbol}, includeOrphanFactors::Bool=false, addToDFG::GraphsDFG=GraphsDFG{AbstractParams}())::GraphsDFG
     for label in variableFactorLabels
         if !haskey(dfg.labelDict, label)
             error("Variable/factor with label '$(label)' does not exist in the factor graph")

src/LightGraphsDFG/LightGraphsDFG.jl

@@ -0,0 +1,25 @@
+using LightGraphs
+using MetaGraphs
+
+# Imports
+include("entities/LightGraphsDFG.jl")
+include("services/LightGraphsDFG.jl")
+
+# Exports
+export LightGraphsDFG
+export exists
+export getLabelDict, getDescription, setDescription, getInnerGraph, getAddHistory, getSolverParams, setSolverParams
+#
+export getAddHistory, getDescription, getLabelDict
+export addVariable!, addFactor!
+export ls, lsf, getVariables, getFactors, getVariableIds, getFactorIds
+export getVariable, getFactor
+export updateVariable!, updateFactor!
+export deleteVariable!, deleteFactor!
+export getAdjacencyMatrix
+export getAdjacencyMatrixDataFrame
+export getNeighbors
+export getSubgraphAroundNode
+export getSubgraph
+export isFullyConnected, hasOrphans
+export toDot, toDotFile

src/LightGraphsDFG/entities/LightGraphsDFG.jl

@@ -0,0 +1,55 @@
+# Starting of with Graph.jl implementation. There are a lot of overlap with metagraphs and some data can be moved there.
+"""
+$(TYPEDEF)
+Encapsulation structure for a DFGNode (Variable or Factor) in LightGraphs.jl graph.
+"""
+mutable struct LightGraphsNode
+    index::Int
+    dfgNode::DFGNode
+end
+
+const LFGType = MetaGraph{Int64,Float64}
+
+mutable struct LightGraphsDFG{T <: AbstractParams} <: AbstractDFG
+    g::LFGType
+    description::String
+    userId::String
+    robotId::String
+    sessionId::String
+    #NOTE Removed nodeCounter
+    # nodeCounter::Int64
+    #NOTE using matagraphs labels
+    # labelDict::Dict{Symbol, Int64}
+    addHistory::Vector{Symbol} #TODO: Discuss more - is this an audit trail?
+    solverParams::T # Solver parameters
+end
+
+#TODO? do we not want props such as userId, robotId, sessionId, etc...
+function LightGraphsDFG{T}(g::LFGType=MetaGraph();
+                           description::String="LightGraphs.jl implementation",
+                           userId::String="User ID",
+                           robotId::String="Robot ID",
+                           sessionId::String="Session ID",
+                           params::T=NoSolverParams()) where T <: AbstractParams
+    set_prop!(g, :description, description)
+    set_prop!(g, :userId, userId)
+    set_prop!(g, :robotId, robotId)
+    set_prop!(g, :sessionId, sessionId)
+    set_indexing_prop!(g, :label)
+    LightGraphsDFG{T}(g, description, userId, robotId, sessionId, Symbol[], params)
+end
+
+Base.propertynames(x::LightGraphsDFG, private::Bool=false) =
+    (:g, :description, :userId, :robotId, :sessionId, :nodeCounter, :labelDict, :addHistory, :solverParams)
+        # (private ? fieldnames(typeof(x)) : ())...)
+
+Base.getproperty(x::LightGraphsDFG,f::Symbol) = begin
+    if f == :nodeCounter
+        nv(x.g)
+    elseif f == :labelDict
+        @warn "Read only! using internal labelDict"
+        x.g.metaindex[:label]
+    else
+        getfield(x,f)
+    end
+end