Merge pull request #708 from JuliaRobotics/master

Release v0.11.1

Author: GearsAD

src/CloudGraphsDFG/services/CloudGraphsDFG.jl

@@ -535,9 +535,9 @@ function _unpackPPE(dfg::G, packedPPE::Dict{String, Any})::AbstractPointParametr
         packedPPE["lastUpdatedTimestamp"] = packedPPE["lastUpdatedTimestamp"][1:end-1]
     end
 
-    !haskey(packedPPE, "_type") && error("Cannot find type key '$TYPEKEY' in packed PPE data")
+    !haskey(packedPPE, "_type") && error("Cannot find type key '_type' in packed PPE data")
     type = pop!(packedPPE, "_type")
-    (type == nothing || type == "") && error("Cannot deserialize PPE, type key is empty")
+    (type === nothing || type == "") && error("Cannot deserialize PPE, type key is empty")
     ppe = Unmarshal.unmarshal(
             DistributedFactorGraphs.getTypeFromSerializationModule(dfg, Symbol(type)),
             packedPPE)
@@ -555,6 +555,9 @@ end
 
 function _generateAdditionalProperties(variableType::ST, ppe::P)::Dict{String, String} where {P <: AbstractPointParametricEst, ST <: InferenceVariable}
     addProps = Dict{String, String}()
+    # Save in the type for PPEs
+    addProps["_type"]="\"$(typeof(ppe))\""
+
     # Try get the projectCartesian function for this variableType
     projectCartesianFunc = nothing
     if isdefined(Main, :projectCartesian)

src/CloudGraphsDFG/services/CommonFunctions.jl

@@ -204,10 +204,10 @@ function _structToNeo4jProps(inst::Union{User, Robot, Session, PVND, N, APPE, AB
         write(io, "$cypherNodeName.$k= $v,")
     end
     # Write in the version and node type
-    write(io, "$cypherNodeName._version=\"$(_getDFGVersion())\",")
-    write(io, "$cypherNodeName._type=\"$(typeof(inst))\"")
+    write(io, "$cypherNodeName._version=\"$(_getDFGVersion())\"")
     # Ref String(): "When possible, the memory of v will be used without copying when the String object is created.
-    # This is guaranteed to be the case for byte vectors returned by take!" # Apparent replacement for takebuf_string()
+    # This is guaranteed to be the case for byte vectors returned by take!" 
+    # Apparent replacement for takebuf_string()
     return String(take!(io))
 end
 

test/CGStructureTests.jl

@@ -59,8 +59,8 @@ v1 = addVariable!(dfg, :a, ContinuousScalar, tags = [:POSE])
 v2 = addVariable!(dfg, :b, ContinuousScalar, tags = [:POSE])
 v3 = addVariable!(dfg, :c, ContinuousScalar, tags = [:LANDMARK])
 addFactor!(dfg, [:a], Prior(Normal(0,1)))
-f1 = addFactor!(dfg, [:a; :b], LinearConditional(Normal(50.0,2.0)) )
-f2 = addFactor!(dfg, [:b; :c], LinearConditional(Normal(50.0,2.0)) )
+f1 = addFactor!(dfg, [:a; :b], LinearRelative(Normal(50.0,2.0)) )
+f2 = addFactor!(dfg, [:b; :c], LinearRelative(Normal(50.0,2.0)) )
 
 sessions = lsSessions(dfg)
 @test map(s -> s.id, sessions) == [session.id]

test/data/0_11_0.tar.gz

@@ -37,14 +37,14 @@ using Test
         updateVariable!.(dfg, verts)
 
 
-        facts = map(n -> addFactor!(dfg, [verts[n], verts[n+1]], LinearConditional(Normal(50.0,2.0))), 1:(numNodes-1))
+        facts = map(n -> addFactor!(dfg, [verts[n], verts[n+1]], LinearRelative(Normal(50.0,2.0))), 1:(numNodes-1))
         map(f -> setSolvable!(f, Int(round(rand()))), facts)
         map(f -> f.solverData.eliminated = rand() > 0.5, facts)
         map(f -> f.solverData.potentialused = rand() > 0.5, facts)
         updateFactor!.(dfg, facts)
 
         #test multihypo
-        addFactor!(dfg, [:x1, :x2, :x3], LinearConditional(Normal(50.0,2.0)), multihypo = [1, 0.3, 0.7])
+        addFactor!(dfg, [:x1, :x2, :x3], LinearRelative(Normal(50.0,2.0)), multihypo = [1, 0.3, 0.7])
 
         # Save and load the graph to test.
         saveDFG(filename, dfg)
@@ -85,7 +85,7 @@ end
 
 @testset "FileDFG Regression Tests" begin
     @info "If any of these tests fail, we have breaking changes"
-    for file in readdir(joinpath(@__DIR__, "data"))
+    for file in filter(f -> endswith(f, ".tar.gz"), readdir(joinpath(@__DIR__, "data")))
         loadFile = joinpath(@__DIR__, "data", file)
         global dfg
         dfgCopy = DistributedFactorGraphs._getDuplicatedEmptyDFG(dfg)

test/data/0_10_0.tar.gz renamed to test/data/archive/0_10_0.tar.gz

@@ -15,7 +15,7 @@ using Test
     @test compareFactor(f1,f1)
 
     v2 = addVariable!(fg, :x1, ContinuousScalar)
-    f2 = addFactor!(fg, [:x0;:x1], LinearConditional(Normal(2.0, 0.1)))
+    f2 = addFactor!(fg, [:x0;:x1], LinearRelative(Normal(2.0, 0.1)))
 
     fg2 = deepcopy(fg)
 
@@ -56,7 +56,7 @@ using Test
     # fg2 has been solved, so it should fail on the estimate dictionary
     @test !compareSimilarVariables(fg, fg2, skipsamples=true, skip=Symbol[:initialized;:inferdim])
 
-    tree = wipeBuildNewTree!(fg2)
+    tree = resetBuildTree!(fg2)
 
     @test compareSimilarFactors(fg, fg2, skipsamples=true, skipcompute=true)
 
@@ -77,13 +77,13 @@ end
     addFactor!(fg, [:x0;], Prior(Normal()))
 
     addVariable!(fg, :x1, ContinuousScalar)
-    addFactor!(fg, [:x0;:x1], LinearConditional(Normal(2.0, 0.1)))
+    addFactor!(fg, [:x0;:x1], LinearRelative(Normal(2.0, 0.1)))
 
     addVariable!(fg, :x2, ContinuousScalar)
-    addFactor!(fg, [:x1;:x2], LinearConditional(Normal(4.0, 0.1)))
+    addFactor!(fg, [:x1;:x2], LinearRelative(Normal(4.0, 0.1)))
 
     addVariable!(fg, :l1, ContinuousScalar)
-    addFactor!(fg, [:x1;:l1], LinearConditional(Rayleigh()))
+    addFactor!(fg, [:x1;:l1], LinearRelative(Rayleigh()))
 
     sfg = buildSubgraph(LightDFG, fg, [:x0;:x1])
 

test/fileDFGTests.jl

@@ -12,7 +12,7 @@ end
     # Use IIF to add the variables and factors
     v1 = addVariable!(dfg, :a, ContinuousScalar, tags = [:POSE], solvable=0)
     v2 = addVariable!(dfg, :b, ContinuousScalar, tags = [:LANDMARK], solvable=1)
-    f1 = addFactor!(dfg, [:a; :b], LinearConditional(Normal(50.0,2.0)), solvable=0)
+    f1 = addFactor!(dfg, [:a; :b], LinearRelative(Normal(50.0,2.0)), solvable=0)
 
     @show dfg
     @show f1
@@ -50,8 +50,8 @@ end
     v1 = deepcopy(addVariable!(iiffg, :a, ContinuousScalar))
     v2 = deepcopy(addVariable!(iiffg, :b, ContinuousScalar))
     v3 = deepcopy(addVariable!(iiffg, :c, ContinuousScalar))
-    f1 = deepcopy(addFactor!(iiffg, [:a; :b], LinearConditional(Normal(50.0,2.0)) ))
-    f2 = deepcopy(addFactor!(iiffg, [:b; :c], LinearConditional(Normal(10.0,1.0)) ))
+    f1 = deepcopy(addFactor!(iiffg, [:a; :b], LinearRelative(Normal(50.0,2.0)) ))
+    f2 = deepcopy(addFactor!(iiffg, [:b; :c], LinearRelative(Normal(10.0,1.0)) ))
 
     # Add it to the new graph.
     @test addVariable!(dfg2, v1) == v1
@@ -141,9 +141,9 @@ end
     #FIXME don't know what it is supposed to do
     @test_broken lsfTypes(dfg)
 
-    @test ls(dfg, LinearConditional) == [:abf1]
-    @test lsf(dfg, LinearConditional) == [:abf1]
-    @test lsfWho(dfg, :LinearConditional) == [:abf1]
+    @test ls(dfg, LinearRelative) == [:abf1]
+    @test lsf(dfg, LinearRelative) == [:abf1]
+    @test lsfWho(dfg, :LinearRelative) == [:abf1]
 
     @test getVariableType(v1) isa ContinuousScalar
     @test getVariableType(dfg,:a) isa ContinuousScalar
@@ -397,7 +397,7 @@ updateVariable!(dfg, verts[7])
 updateVariable!(dfg, verts[8])
 
 facts = map(n ->
-    addFactor!(dfg, [verts[n], verts[n+1]], LinearConditional(Normal(50.0,2.0)),solvable=0), 1:(numNodes-1))
+    addFactor!(dfg, [verts[n], verts[n+1]], LinearRelative(Normal(50.0,2.0)),solvable=0), 1:(numNodes-1))
 
 @testset "Getting Neighbors" begin
     global dfg,verts

test/iifCompareTests.jl

@@ -7,6 +7,7 @@ using Pkg
 using Dates
 using TimeZones
 using SHA
+using UUIDs
 
 ## To run the IIF tests, you need a local Neo4j with user/pass neo4j:test
 # To run a Docker image

test/iifInterfaceTests.jl

@@ -4,8 +4,8 @@ v1 = addVariable!(dfg, :a, ContinuousScalar, tags = [:POSE])
 addFactor!(dfg, [:a], Prior(Normal(0,1)))
 v2 = addVariable!(dfg, :b, ContinuousScalar, tags = [:POSE])
 v3 = addVariable!(dfg, :c, ContinuousScalar, tags = [:LANDMARK])
-f1 = addFactor!(dfg, [:a; :b], LinearConditional(Normal(50.0,2.0)) )
-f2 = addFactor!(dfg, [:b; :c], LinearConditional(Normal(50.0,2.0)) )
+f1 = addFactor!(dfg, [:a; :b], LinearRelative(Normal(50.0,2.0)) )
+f2 = addFactor!(dfg, [:b; :c], LinearRelative(Normal(50.0,2.0)) )
 
 # Solve it
 tree, smtasks = solveTree!(dfg)

test/runtests.jl

@@ -1,7 +1,6 @@
 using DistributedFactorGraphs
 using Test
 using Dates
-using UUIDs
 
 import Base: convert