Merge branch 'master' of https://github.com/JuliaRobotics/DistributedFactorGraphs.jl into 4Q19/feature/needsahome

Author: GearsAD

Project.toml

@@ -21,7 +21,7 @@ SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 [compat]
 Colors = "0.8, 0.9, 0.10, 0.11"
 Distributions = "0.18, 0.19, 0.20, 0.21, 0.22, 0.23, 0.24, 0.25, 1"
-DocStringExtensions = "0.8, 0.9, 0.10, 1"
+DocStringExtensions = "0.7, 0.8, 0.9, 0.10, 1"
 GraphPlot = "0.3.1, 0.4"
 Graphs = "0.10.2, 0.11, 1"
 JSON2 = "0.3.1"

README.md

@@ -1,9 +1,8 @@
 # DistributedFactorGraphs.jl
 
-[![Build Status](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=master)](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl)
-[![Codecov Status](https://codecov.io/gh/JuliaRobotics/DistributedFactorGraphs.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaRobotics/DistributedFactorGraphs.jl)
-[![Coverage Status](https://img.shields.io/coveralls/JuliaRobotics/DistributedFactorGraphs.jl.svg)](https://coveralls.io/r/JuliaRobotics/DistributedFactorGraphs.jl?branch=master)
-[![docs](https://img.shields.io/badge/docs-latest-blue.svg)](http://juliarobotics.github.io/DistributedFactorGraphs.jl/latest/)
+Release | Dev | Coverage | Docs
+---------|-----|----------|------
+[![Build Status](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=release/v0.5)](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl) |  [![Build Status](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=master)](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl) | [![Codecov Status](https://codecov.io/gh/JuliaRobotics/DistributedFactorGraphs.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaRobotics/DistributedFactorGraphs.jl) [![Coverage Status](https://img.shields.io/coveralls/JuliaRobotics/DistributedFactorGraphs.jl.svg)](https://coveralls.io/r/JuliaRobotics/DistributedFactorGraphs.jl?branch=master) | [![docs](https://img.shields.io/badge/docs-latest-blue.svg)](http://juliarobotics.github.io/DistributedFactorGraphs.jl/latest/)
 
 DistributedFactorGraphs.jl provides a flexible factor graph API for use in the [Caesar.jl](https://github.com/JuliaRobotics/Caesar.jl) ecosystem. The package supplies:
 * A standardized API for interacting with factor graphs

test/CGStructureTests.jl

@@ -1,10 +1,10 @@
-dfg = CloudGraphsDFG{NoSolverParams}("localhost", 7474, "neo4j", "test",
+dfg = CloudGraphsDFG{SolverParams}("localhost", 7474, "neo4j", "test",
                             "testUser", "testRobot", "testSession",
                             nothing,
                             nothing,
                             IncrementalInference.decodePackedType,
                             IncrementalInference.rebuildFactorMetadata!,
-                            solverParams=NoSolverParams())
+                            solverParams=SolverParams())
 
 # Nuke the user
 clearUser!!(dfg)
@@ -61,37 +61,15 @@ setSessionData(dfg, session.data)
 v1 = addVariable!(dfg, :a, ContinuousScalar, labels = [:POSE])
 v2 = addVariable!(dfg, :b, ContinuousScalar, labels = [:POSE])
 v3 = addVariable!(dfg, :c, ContinuousScalar, labels = [: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)) )
 
 sessions = lsSessions(dfg)
 @test map(s -> s.id, sessions) == [session.id]
 
-# Pull and solve this graph
 dfgLocal = GraphsDFG{SolverParams}(params=SolverParams())
 DistributedFactorGraphs.getSubgraph(dfg, union(ls(dfg), lsf(dfg)), true, dfgLocal)
-
 # Confirm that with sentinels we still have the same graph (doesn't pull in the sentinels)
 @test symdiff(ls(dfgLocal), ls(dfg)) == []
 @test symdiff(lsf(dfgLocal), lsf(dfg)) == []
-
-# Solve it
-tree, smtasks = solveTree!(dfgLocal)
-
-
-# Make sure we can copy and solve normal orphaned sessions.
-dfgOrphaned = deepcopy(dfg)
-dfgOrphaned.sessionId = "doesntexist"
-# Don't create a session
-# Add some nodes.
-v1 = addVariable!(dfgOrphaned, :a, ContinuousScalar, labels = [:POSE])
-v2 = addVariable!(dfgOrphaned, :b, ContinuousScalar, labels = [:POSE])
-v3 = addVariable!(dfgOrphaned, :c, ContinuousScalar, labels = [:LANDMARK])
-f1 = addFactor!(dfgOrphaned, [:a; :b], LinearConditional(Normal(50.0,2.0)) )
-f2 = addFactor!(dfgOrphaned, [:b; :c], LinearConditional(Normal(50.0,2.0)) )
-# Solve it
-dfgLocal = GraphsDFG{SolverParams}(params=SolverParams())
-DistributedFactorGraphs.getSubgraph(dfgOrphaned, union(ls(dfgOrphaned), lsf(dfgOrphaned)), true, dfgLocal)
-tree, smtasks = solveTree!(dfgLocal)
-
-# If this passes without errors and we solve the graph, then all good.

test/runtests.jl

@@ -61,7 +61,6 @@ end
 
 if get(ENV, "IIF_TEST", "") == "true"
 
-    Pkg.add("IncrementalInference")
     # Switch to our upstream test branch.
     Pkg.add(PackageSpec(name="IncrementalInference", rev="upstream/dfg_integration_test"))
     @info "------------------------------------------------------------------------"
@@ -100,6 +99,19 @@ if get(ENV, "IIF_TEST", "") == "true"
         # Run the CGStructure tests
         include("CGStructureTests.jl")
     end
+
+    # Simple graph solving test
+    @testset "Simple graph solving test" begin
+        # This is just to validate we're not going to blow up downstream.
+        apis = [
+            GraphsDFG{SolverParams}(params=SolverParams()),
+            LightDFG{SolverParams}(params=SolverParams())]
+        for api in apis
+            @info "Running simple solver test: $(typeof(api))"
+            global dfg = deepcopy(api)
+            include("solveTest.jl")
+        end
+    end
 else
     @warn "Skipping IncrementalInference driver tests"
 end

test/solveTest.jl

@@ -0,0 +1,10 @@
+# Add some nodes.
+v1 = addVariable!(dfg, :a, ContinuousScalar, labels = [:POSE])
+addFactor!(dfg, [:a], Prior(Normal(0,1)))
+v2 = addVariable!(dfg, :b, ContinuousScalar, labels = [:POSE])
+v3 = addVariable!(dfg, :c, ContinuousScalar, labels = [:LANDMARK])
+f1 = addFactor!(dfg, [:a; :b], LinearConditional(Normal(50.0,2.0)) )
+f2 = addFactor!(dfg, [:b; :c], LinearConditional(Normal(50.0,2.0)) )
+
+# Solve it
+tree, smtasks = solveTree!(dfg)