Merge pull request #219 from JuliaRobotics/master

Release 0.5.1

Author: GearsAD

Project.toml

@@ -1,6 +1,6 @@
 name = "DistributedFactorGraphs"
 uuid = "b5cc3c7e-6572-11e9-2517-99fb8daf2f04"
-version = "0.5.0"
+version = "0.5.1"
 
 [deps]
 Base64 = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
@@ -13,7 +13,6 @@ 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"
@@ -27,7 +26,6 @@ GraphPlot = "0.3.1, 0.4"
 Graphs = "0.10.2, 0.11, 1"
 JSON2 = "0.3.1"
 LightGraphs = "1.2, 1.3"
-MetaGraphs = "^0.6.3"
 Neo4j = "2"
 Reexport = "0.2, 0.3, 0.4, 0.5, 1"
 Requires = "0.5, 0.6, 0.7, 0.8, 0.9, 0.10, 1"

src/CloudGraphsDFG/services/CloudGraphsDFG.jl

@@ -42,6 +42,7 @@ So can make orderProperty = label or id.
 """
 function _getLabelsFromCyphonQuery(neo4jInstance::Neo4jInstance, matchCondition::String, orderProperty::String="")::Vector{Symbol}
     query = "match $matchCondition return distinct(node.label) $(orderProperty != "" ? "order by node.$orderProperty" : "")";
+    @debug "[Query] $query"
     result = _queryNeo4j(neo4jInstance, query)
     nodeIds = map(node -> node["row"][1], result.results[1]["data"])
     return Symbol.(nodeIds)

src/CloudGraphsDFG/services/CommonFunctions.jl

@@ -2,7 +2,6 @@ module DFGPlots
 
 using Colors
 using LightGraphs
-using MetaGraphs
 using GraphPlot
 using DocStringExtensions
 import GraphPlot: gplot
@@ -84,39 +83,6 @@ 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::DistributedFactorGraphs.MetaGraphsDFG, p::DFGPlotProps = DFGPlotProps())
-    @info "Deprecated, please use GraphsDFG or LightDFG."
-    nodesize = [has_prop(dfg.g,i,:factor) ?  p.nodesize.fac : p.nodesize.var for i=vertices(dfg.g)]
-    if p.drawlabels
-        nodelabel = [has_prop(dfg.g,i,:factor) ? "" : string(get_prop(dfg.g,i,:label)) for i=vertices(dfg.g)]
-    else
-        nodelabel = nothing
-    end
-    nodefillc = [has_prop(dfg.g,i,:factor) ? p.nodefillc.fac : p.nodefillc.var for i=vertices(dfg.g)]
-
-    gplot(dfg.g, nodelabel=nodelabel, nodesize=nodesize, nodefillc=nodefillc, layout=p.layout)
-
-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())
@@ -128,11 +94,6 @@ function dfgplot(dfg::AbstractDFG, p::DFGPlotProps = DFGPlotProps())
     dfgplot(ldfg, p)
 end
 
-function gplot(dfg::DistributedFactorGraphs.MetaGraphsDFG; keyargs...)
-    @info "Deprecated, please use GraphsDFG or LightDFG."
-    gplot(dfg.g; keyargs...)
-end
-
 function gplot(dfg::LightDFG; keyargs...)
     gplot(dfg.g; keyargs...)
 end

src/DFGPlots/DFGPlots.jl

@@ -21,6 +21,7 @@ export AbstractParams, NoSolverParams
 export DFGNode, DFGVariable, DFGFactor, AbstractDFGVariable, AbstractDFGFactor
 export InferenceType, PackedInferenceType, FunctorInferenceType, InferenceVariable, ConvolutionObject
 export FunctorSingleton, FunctorPairwise, FunctorPairwiseMinimize
+export getMaxPPE, getMeanPPE, getSuggestedPPE
 export label, timestamp, tags, estimates, estimate, data, softtype, solverData, getData, solverDataDict, setSolverData, internalId, smallData, bigData
 export DFGVariableSummary, DFGFactorSummary, AbstractDFGSummary
 
@@ -32,7 +33,8 @@ export getUserData, setUserData, getRobotData, setRobotData, getSessionData, set
 export pushUserData!, pushRobotData!, pushSessionData!, popUserData!, popRobotData!, popSessionData!
 
 # Services/AbstractDFG Exports
-export hasFactor, hasVariable, isInitialized, getFactorFunction, isVariable, isFactor
+export isInitialized, getFactorFunction, isVariable, isFactor
+export isSolvable, isSolveInProgress
 export mergeUpdateVariableSolverData!, mergeUpdateGraphSolverData!
 
 # Solver (IIF) Exports
@@ -85,9 +87,6 @@ include("GraphsDFG/GraphsDFG.jl")
 # Include the FilesDFG API.
 include("FileDFG/FileDFG.jl")
 
-# Include the LightGraphs.jl (MetaGraphs.jl) API.
-include("MetaGraphsDFG/MetaGraphsDFG.jl")
-
 include("SymbolDFG/SymbolDFG.jl")
 using .SymbolDFGs
 

src/DistributedFactorGraphs.jl

@@ -235,11 +235,20 @@ end
 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, Graphs.vertices(dfg.g)))
+function getVariables(dfg::GraphsDFG,
+                      regexFilter::Union{Nothing, Regex}=nothing;
+                      tags::Vector{Symbol}=Symbol[],
+                      solvable::Int=0)::Vector{DFGVariable}
+    #
+    variables = map(v -> v.dfgNode, filter(n -> (n.dfgNode isa DFGVariable) && (solvable != 0 ? solvable <= isSolvable(n.dfgNode) : true), Graphs.vertices(dfg.g)))
+    # filter on solvable
+
+    # filter on regex
     if regexFilter != nothing
         variables = filter(v -> occursin(regexFilter, String(v.label)), variables)
     end
+
+    # filter on tags
 	if length(tags) > 0
         mask = map(v -> length(intersect(v.tags, tags)) > 0, variables )
         return variables[mask]
@@ -252,8 +261,9 @@ end
 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, Graphs.vertices(dfg.g)))
+function getFactors(dfg::GraphsDFG, regexFilter::Union{Nothing, Regex}=nothing; solvable::Int=0)::Vector{DFGFactor}
+	factors = map(v -> v.dfgNode, filter(n -> (n.dfgNode isa DFGFactor) && (solvable != 0 ? solvable <= isSolvable(n.dfgNode) : true), Graphs.vertices(dfg.g)))
+
 	if regexFilter != nothing
 		factors = filter(f -> occursin(regexFilter, String(f.label)), factors)
 	end
@@ -272,15 +282,14 @@ end
     $(SIGNATURES)
 Retrieve a list of labels of the immediate neighbors around a given variable or factor.
 """
-function getNeighbors(dfg::GraphsDFG, node::T; ready::Union{Nothing, Int}=nothing, backendset::Union{Nothing, Int}=nothing)::Vector{Symbol}  where T <: DFGNode
+function getNeighbors(dfg::GraphsDFG, node::T; solvable::Int=0)::Vector{Symbol}  where T <: DFGNode
     if !haskey(dfg.labelDict, node.label)
         error("Variable/factor with label '$(node.label)' does not exist in the factor graph")
     end
     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.dfgNode.ready == ready, neighbors) : neighbors
-    neighbors = backendset != nothing ? filter(v -> v.dfgNode.backendset == backendset, neighbors) : neighbors
+	neighbors = solvable != 0 ? filter(v -> solvable <= isSolvable(v.dfgNode), neighbors) : neighbors
     # Variable sorting (order is important)
     if node isa DFGFactor
         order = intersect(node._variableOrderSymbols, map(v->v.dfgNode.label, neighbors))
@@ -293,15 +302,14 @@ end
     $(SIGNATURES)
 Retrieve a list of labels of the immediate neighbors around a given variable or factor specified by its label.
 """
-function getNeighbors(dfg::GraphsDFG, label::Symbol; ready::Union{Nothing, Int}=nothing, backendset::Union{Nothing, Int}=nothing)::Vector{Symbol}  where T <: DFGNode
+function getNeighbors(dfg::GraphsDFG, label::Symbol; solvable::Int=0)::Vector{Symbol}  where T <: DFGNode
     if !haskey(dfg.labelDict, label)
         error("Variable/factor with label '$(label)' does not exist in the factor graph")
     end
     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.dfgNode.ready == ready, neighbors) : neighbors
-    neighbors = backendset != nothing ? filter(v -> v.dfgNode.backendset == backendset, neighbors) : neighbors
+    neighbors = solvable != 0 ? filter(v -> isSolvable(v.dfgNode) >= solvable, neighbors) : neighbors
     # Variable sorting when using a factor (function order is important)
     if vert.dfgNode isa DFGFactor
         vert.dfgNode._variableOrderSymbols
@@ -312,49 +320,14 @@ function getNeighbors(dfg::GraphsDFG, label::Symbol; ready::Union{Nothing, Int}=
     return map(n -> n.dfgNode.label, neighbors)
 end
 
-# function _copyIntoGraph!(sourceDFG::GraphsDFG, destDFG::GraphsDFG, variableFactorLabels::Vector{Symbol}, includeOrphanFactors::Bool=false)::Nothing
-#     # Split into variables and factors
-#     verts = map(id -> sourceDFG.g.vertices[sourceDFG.labelDict[id]], variableFactorLabels)
-#     sourceVariables = filter(n -> n.dfgNode isa DFGVariable, verts)
-#     sourceFactors = filter(n -> n.dfgNode isa DFGFactor, verts)
-#
-#     # Now we have to add all variables first,
-#     for variable in sourceVariables
-#         if !haskey(destDFG.labelDict, variable.dfgNode.label)
-#             addVariable!(destDFG, deepcopy(variable.dfgNode))
-#         end
-#     end
-#     # And then all factors to the destDFG.
-#     for factor in sourceFactors
-#         if !haskey(destDFG.labelDict, factor.dfgNode.label)
-#             # Get the original factor variables (we need them to create it)
-#             neighVarIds = getNeighbors(sourceDFG, factor.dfgNode.label) #OLD: in_neighbors(factor, sourceDFG.g)
-#             # Find the labels and associated neighVarIds in our new subgraph
-#             factVariables = DFGVariable[]
-#             for neighVarId in neighVarIds
-#                 if haskey(destDFG.labelDict, neighVarId)
-#                     push!(factVariables, getVariable(destDFG, neighVarId))
-#                     #otherwise ignore
-#                 end
-#             end
-#
-#             # Only if we have all of them should we add it (otherwise strange things may happen on evaluation)
-#             if includeOrphanFactors || length(factVariables) == length(neighVarIds)
-#                 addFactor!(destDFG, factVariables, deepcopy(factor.dfgNode))
-#             end
-#         end
-#     end
-#     return nothing
-# end
-
 """
     $(SIGNATURES)
 Retrieve a deep subgraph copy around a given variable or factor.
 Optionally provide a distance to specify the number of edges should be followed.
 Optionally provide an existing subgraph addToDFG, the extracted nodes will be copied into this graph. By default a new subgraph will be created.
 Note: By default orphaned factors (where the subgraph does not contain all the related variables) are not returned. Set includeOrphanFactors to return the orphans irrespective of whether the subgraph contains all the variables.
 """
-function getSubgraphAroundNode(dfg::GraphsDFG{P}, node::T, distance::Int64=1, includeOrphanFactors::Bool=false, addToDFG::GraphsDFG=GraphsDFG{P}())::GraphsDFG where {P <: AbstractParams, T <: DFGNode}
+function getSubgraphAroundNode(dfg::GraphsDFG{P}, node::T, distance::Int64=1, includeOrphanFactors::Bool=false, addToDFG::GraphsDFG=GraphsDFG{P}(); solvable::Int=0)::GraphsDFG where {P <: AbstractParams, T <: DFGNode}
     if !haskey(dfg.labelDict, node.label)
         error("Variable/factor with label '$(node.label)' does not exist in the factor graph")
     end
@@ -368,7 +341,7 @@ function getSubgraphAroundNode(dfg::GraphsDFG{P}, node::T, distance::Int64=1, in
         for (key, node) in curList
             neighbors = in_neighbors(node, dfg.g) #Don't use out_neighbors! It enforces directiveness even if we don't want it
             for neighbor in neighbors
-                if !haskey(neighborList, neighbor.dfgNode.label)
+                if !haskey(neighborList, neighbor.dfgNode.label) && (isSolvable(neighbor.dfgNode) >= solvable)
                     push!(neighborList, neighbor.dfgNode.label => neighbor)
                     push!(newNeighbors, neighbor.dfgNode.label => neighbor)
                 end