Merge branch 'master' into fix/3Q19/56

Author: Affie

Project.toml

@@ -7,12 +7,12 @@ Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
+GraphPlot = "a2cc645c-3eea-5389-862e-a155d0052231"
 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"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
@@ -28,6 +28,8 @@ julia = "0.7, 1"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+GraphPlot = "a2cc645c-3eea-5389-862e-a155d0052231"
+Neo4j = "d2adbeaf-5838-5367-8a2f-e46d570981db"
 
 [targets]
-test = ["Test"]
+test = ["Test", "GraphPlot", "Neo4j"]

docs/src/func_ref.md

@@ -58,8 +58,15 @@ getSubgraphAroundNode
 getSubgraph
 ```
 
-### Visualization
+### Summaries
+```@docs
+getSummary
+getSummaryGraph
+```
+
+### Visualization and Plotting
 ```@docs
 toDot
 toDotFile
+dfgplot
 ```

src/CloudGraphsDFG/services/CloudGraphsDFG.jl

@@ -789,11 +789,11 @@ end
 
 function getAdjacencyMatrixSparse(dfg::CloudGraphsDFG)::Tuple{SparseMatrixCSC, Vector{Symbol}, Vector{Symbol}}
     varLabels = getVariableIds(dfg)
-    factLabels = sort(getFactorIds(dfg))
-    vDict = Dict(varLabels .=> [1:length(varLabels)...].+1)
-    fDict = Dict(factLabels .=> [1:length(factLabels)...].+1)
+    factLabels = getFactorIds(dfg)
+    vDict = Dict(varLabels .=> [1:length(varLabels)...])
+    fDict = Dict(factLabels .=> [1:length(factLabels)...])
 
-    adjMat = spzeros(Int, length(factLabels)+1, length(varLabels)+1)
+    adjMat = spzeros(Int, length(factLabels), length(varLabels))
 
     # Now ask for all relationships for this session graph
     loadtx = transaction(dfg.neo4jInstance.connection)

src/Common.jl

@@ -1,4 +1,5 @@
-export sortVarNested
+
+export sortVarNested, sortDFG
 export isPrior, lsfPriors
 export getVariableType, getSofttype
 export getFactorType, getfnctype
@@ -88,6 +89,24 @@ function sortVarNested(vars::Vector{Symbol})::Vector{Symbol}
 	return retvars
 end
 
+"""
+    $SIGNATURES
+
+Sort variable (factor) lists in a meaningful way, for example `[:april;:x1_3;:x1_6;]`
+
+Notes
+- Not fool proof, but does better than native sort.
+
+Example
+
+`sortDFG(ls(dfg))`
+
+Related
+
+ls, lsf
+"""
+sortDFG(vars::Vector{Symbol})::Vector{Symbol} = sortVarNested(vars)
+
 """
     $SIGNATURES
 

src/DFGPlots/DFGPlots.jl

@@ -4,6 +4,7 @@ using Colors
 using LightGraphs
 using MetaGraphs
 using GraphPlot
+using DocStringExtensions
 import GraphPlot: gplot
 
 using ...DistributedFactorGraphs
@@ -28,6 +29,26 @@ DFGPlotProps() = DFGPlotProps(  (var=colorant"seagreen", fac=colorant"cyan3"),
                                 true)
 
 
+
+"""
+    $(SIGNATURES)
+Plots the structure of the factor graph. GraphPlot must be imported before DistributedFactoGraphs for these functions to be available.
+Returns the plot context.
+
+E.g.
+```
+using GraphPlot
+using DistributedFactorGraphs, DistributedFactorGraphs.DFGPlots
+# ... Make graph...
+# Using GraphViz plotting
+dfgplot(fg)
+# Save to PDFG
+using Compose
+draw(PDF("/tmp/graph.pdf", 16cm, 16cm), dfgplot(fg))
+```
+
+More information at [GraphPlot.jl](https://github.com/JuliaGraphs/GraphPlot.jl)
+"""
 function dfgplot(dfg::LightDFG, p::DFGPlotProps = DFGPlotProps())
 
     nodetypes = [haskey(dfg.g.variables, s) for s in dfg.g.labels]
@@ -46,6 +67,25 @@ function dfgplot(dfg::LightDFG, p::DFGPlotProps = DFGPlotProps())
 
 end
 
+"""
+    $(SIGNATURES)
+Plots the structure of the factor graph. GraphPlot must be imported before DistributedFactoGraphs for these functions to be available.
+Returns the plot context.
+
+E.g.
+```
+using GraphPlot
+using DistributedFactorGraphs, DistributedFactorGraphs.DFGPlots
+# ... Make graph...
+# Using GraphViz plotting
+dfgplot(fg)
+# Save to PDFG
+using Compose
+draw(PDF("/tmp/graph.pdf", 16cm, 16cm), dfgplot(fg))
+```
+
+More information at [GraphPlot.jl](https://github.com/JuliaGraphs/GraphPlot.jl)
+"""
 function dfgplot(dfg::MetaGraphsDFG, p::DFGPlotProps = DFGPlotProps())
 
     nodesize = [has_prop(dfg.g,i,:factor) ?  p.nodesize.fac : p.nodesize.var for i=vertices(dfg.g)]
@@ -60,14 +100,32 @@ function dfgplot(dfg::MetaGraphsDFG, p::DFGPlotProps = DFGPlotProps())
 
 end
 
+"""
+    $(SIGNATURES)
+Plots the structure of the factor graph. GraphPlot must be imported before DistributedFactoGraphs for these functions to be available.
+Returns the plot context.
+
+E.g.
+```
+using GraphPlot
+using DistributedFactorGraphs, DistributedFactorGraphs.DFGPlots
+# ... Make graph...
+# Using GraphViz plotting
+dfgplot(fg)
+# Save to PDFG
+using Compose
+draw(PDF("/tmp/graph.pdf", 16cm, 16cm), dfgplot(fg))
+```
+
+More information at [GraphPlot.jl](https://github.com/JuliaGraphs/GraphPlot.jl)
+"""
 function dfgplot(dfg::AbstractDFG, p::DFGPlotProps = DFGPlotProps())
     # TODO implement convert functions
     @warn "TODO Implement convert"
     ldfg = MetaGraphsDFG{AbstractParams}()
     DistributedFactorGraphs._copyIntoGraph!(dfg, ldfg, union(getVariableIds(dfg), getFactorIds(dfg)), true)
 
     dfgplot(ldfg, p)
-
 end
 
 function gplot(dfg::MetaGraphsDFG; keyargs...)

src/DistributedFactorGraphs.jl

@@ -11,23 +11,18 @@ using LinearAlgebra
 using SparseArrays
 
 # Entities
-include("entities/AbstractTypes.jl")
+include("entities/AbstractDFG.jl")
 include("entities/DFGFactor.jl")
 include("entities/DFGVariable.jl")
+include("entities/AbstractDFGSummary.jl")
 
 export AbstractDFG
 export AbstractParams, NoSolverParams
-export DFGNode
-
-export DFGFactor
+export DFGNode, DFGVariable, DFGFactor
 export InferenceType, PackedInferenceType, FunctorInferenceType, InferenceVariable, ConvolutionObject
-
 export FunctorSingleton, FunctorPairwise, FunctorPairwiseMinimize
-
-export DFGVariable
-export label, timestamp, tags, estimates, estimate, solverData, getData, solverDataDict, internalId, smallData, bigData
-export setSolverData
-export label, data, id
+export label, timestamp, tags, estimates, estimate, data, solverData, getData, solverDataDict, setSolverData, internalId, smallData, bigData
+export DFGVariableSummary, DFGFactorSummary, AbstractDFGSummary
 
 # Services/AbstractDFG Exports
 export hasFactor, hasVariable, isInitialized, getFactorFunction, isVariable, isFactor
@@ -42,9 +37,16 @@ export pack, unpack
 #Interfaces
 export getAdjacencyMatrixSparse
 
+# File import and export
+export saveDFG, loadDFG
+
+# Summary functions
+export getSummary, getSummaryGraph
+
 # Common includes
 include("services/AbstractDFG.jl")
 include("services/DFGVariable.jl")
+include("services/DFGFactor.jl")
 
 # Include the Graphs.jl API.
 include("GraphsDFG/GraphsDFG.jl")
@@ -61,8 +63,6 @@ include("SymbolDFG/SymbolDFG.jl")
 include("LightDFG/LightDFG.jl")
 @reexport using .LightDFGs
 
-export saveDFG, loadDFG
-
 function __init__()
     @require Neo4j="d2adbeaf-5838-5367-8a2f-e46d570981db" begin
         # Include the Cloudgraphs API

src/GraphsDFG/services/GraphsDFG.jl

@@ -366,68 +366,10 @@ function getSubgraphAroundNode(dfg::GraphsDFG{P}, node::T, distance::Int64=1, in
     return addToDFG
 end
 
-"""
-    $(SIGNATURES)
-Get an adjacency matrix for the DFG, returned as a Matrix{Union{Nothing, Symbol}}.
-Rows are all factors, columns are all variables, and each cell contains either nothing or the symbol of the relating factor.
-The first row and first column are factor and variable headings respectively.
-"""
-function getAdjacencyMatrix(dfg::GraphsDFG)::Matrix{Union{Nothing, Symbol}}
-    varLabels = sort(map(v->v.label, getVariables(dfg)))
-    factLabels = sort(map(f->f.label, getFactors(dfg)))
-    vDict = Dict(varLabels .=> [1:length(varLabels)...].+1)
-
-    adjMat = Matrix{Union{Nothing, Symbol}}(nothing, length(factLabels)+1, length(varLabels)+1)
-    # Set row/col headings
-    adjMat[2:end, 1] = factLabels
-    adjMat[1, 2:end] = varLabels
-    for (fIndex, factLabel) in enumerate(factLabels)
-        factVars = getNeighbors(dfg, getFactor(dfg, factLabel))
-        map(vLabel -> adjMat[fIndex+1,vDict[vLabel]] = factLabel, factVars)
-    end
-    return adjMat
-end
-
-function getAdjacencyMatrixSparse(dfg::GraphsDFG)::Tuple{LightGraphs.SparseMatrixCSC, Vector{Symbol}, Vector{Symbol}}
-	varLabels = map(v->v.label, getVariables(dfg))
-	factLabels = map(f->f.label, getFactors(dfg))
-
-	vDict = Dict(varLabels .=> [1:length(varLabels)...])
-
-	adjMat = spzeros(Int, length(factLabels), length(varLabels))
-
-	for (fIndex, factLabel) in enumerate(factLabels)
-		factVars = getNeighbors(dfg, getFactor(dfg, factLabel))
-	    map(vLabel -> adjMat[fIndex,vDict[vLabel]] = 1, factVars)
-	end
-	return adjMat, varLabels, factLabels
-end
-
 """
     $(SIGNATURES)
 Produces a dot-format of the graph for visualization.
 """
 function toDot(dfg::GraphsDFG)::String
-    m = PipeBuffer()
-    write(m,Graphs.to_dot(dfg.g))
-    data = take!(m)
-    close(m)
-    return String(data)
-end
-
-"""
-    $(SIGNATURES)
-Produces a dot file of the graph for visualization.
-Download XDot to see the data
-
-Note
-- Default location "/tmp/dfg.dot" -- MIGHT BE REMOVED
-- Can be viewed with the `xdot` system application.
-- Based on graphviz.org
-"""
-function toDotFile(dfg::GraphsDFG, fileName::String="/tmp/dfg.dot")::Nothing
-    open(fileName, "w") do fid
-        write(fid,Graphs.to_dot(dfg.g))
-    end
-    return nothing
+	return Graphs.to_dot(dfg.g)
 end

src/LightDFG/FactorGraphs/FactorGraphs.jl

@@ -31,19 +31,22 @@ export
     filter_vertices,
     reverse
 
-import DistributedFactorGraphs: DFGNode
-const AbstractNodeType = DFGNode
+# import DistributedFactorGraphs: DFGNode
+# const AbstractNodeType = DFGNode
+import DistributedFactorGraphs: AbstractDFGVariable, AbstractDFGFactor
+const AbstractVariableType = AbstractDFGVariable
+const AbstractFactorType = AbstractDFGFactor
 
 include("BiMaps.jl")
 
-struct FactorGraph{T <: Integer,V <: AbstractNodeType, F <: AbstractNodeType} <: AbstractGraph{T}
+struct FactorGraph{T <: Integer,V <: AbstractVariableType, F <: AbstractFactorType} <: AbstractGraph{T}
     graph::SimpleGraph{T}
     labels::BiDictMap{T}
     variables::Dict{Symbol,V}
     factors::Dict{Symbol,F}
 end
 
-function FactorGraph{T, V, F}(nv::Int=100, nf::Int=100) where {T <: Integer, V <: AbstractNodeType, F <: AbstractNodeType}
+function FactorGraph{T, V, F}(nv::Int=100, nf::Int=100) where {T <: Integer, V <: AbstractVariableType, F <: AbstractFactorType}
     fadjlist = Vector{Vector{T}}()
         sizehint!(fadjlist, nv + nf)
     g = SimpleGraph{T}(0, fadjlist)
@@ -55,10 +58,10 @@ function FactorGraph{T, V, F}(nv::Int=100, nf::Int=100) where {T <: Integer, V <
     return FactorGraph{T, V, F}(g, labels, variables, factors)
 end
 
-# fg = FactorGraph{Int, AbstractNodeType, AbstractNodeType}()
+# fg = FactorGraph{Int, AbstractVariableType, AbstractFactorType}()
 
-FactorGraph() = FactorGraph{Int, AbstractNodeType, AbstractNodeType}()
-FactorGraph{V,F}() where {V <: AbstractNodeType, F <: AbstractNodeType} = FactorGraph{Int, V, F}()
+FactorGraph() = FactorGraph{Int, AbstractVariableType, AbstractFactorType}()
+FactorGraph{V,F}() where {V <: AbstractVariableType, F <: AbstractFactorType} = FactorGraph{Int, V, F}()
 
 
 function show(io::IO, g::FactorGraph)

src/LightDFG/LightDFG.jl

@@ -3,9 +3,9 @@ module LightDFGs
 using LightGraphs
 using DocStringExtensions
 
-import ...DistributedFactorGraphs: AbstractDFG, DFGNode, AbstractParams, NoSolverParams, DFGVariable, DFGFactor
+import ...DistributedFactorGraphs: AbstractDFG, DFGNode, AbstractDFGVariable, AbstractDFGFactor, AbstractDFGSummary, AbstractParams, NoSolverParams, DFGVariable, DFGFactor
 
-# import DFG functions to exstend
+# import DFG functions to extend
 import ...DistributedFactorGraphs:  setSolverParams,
                                     getInnerGraph,
                                     getFactor,