Merge branch 'master' into ci/github

Author: dehann

.travis.yml

@@ -2,20 +2,13 @@ language: julia
 sudo: required
 
 os:
-    - linux
+  - linux
 
 arch:
-    - amd64
+  - amd64
 
 services:
-    - neo4j
-
-julia:
-    - 1.5
-    - nightly
-
-env:
-    - IIF_TEST=false
+  - neo4j
 
 branches:
   only:
@@ -26,16 +19,37 @@ branches:
 
 jobs:
   include:
-    - julia: 1.4
+    - julia: 1.6
+      env:
+        - IIF_TEST=false
+        - DO_CGDFG_TESTS=false
+        - DFG_USE_CGDFG=false
+        - JULIA_PKG_SERVER=""
+    - julia: nightly
+      env:
+        - IIF_TEST=false
+        - DO_CGDFG_TESTS=false
+        - DFG_USE_CGDFG=false
+        - JULIA_PKG_SERVER=""
+    - julia: 1.6
       env:
         - IIF_TEST=true
+        - DO_CGDFG_TESTS=true
+        - DFG_USE_CGDFG=true
+        - JULIA_PKG_SERVER=""
       if: NOT branch =~ /(^v\d+\.\d+(\.\d+)?([-+]\S*)?$)|(^release.*$)/
     - arch: arm64
-      env: SKIP_CGDFG_TESTS=true
+      env: 
+        - IIF_TEST=false
+        - DO_CGDFG_TESTS=false
+        - DFG_USE_CGDFG=false
+        - JULIA_PKG_SERVER=""
       before_script:
     - stage: "Documentation"
-      julia: 1.4
+      julia: 1.6
       os: linux
+      env:
+        - JULIA_PKG_SERVER=""
       script:
         - julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
         - julia --project=docs/ docs/make.jl

LICENSE

@@ -1,4 +1,4 @@
-Copyright (c) 2017-2020 NavAbility
+Copyright (c) 2017-2021 NavAbility
 
 NOTICE: this license will be relaxed to be much more permissive soon.
 
@@ -18,13 +18,10 @@ Other general use or modification of the software beyond that of
 webservices or clouds (private or public) is permitted 
 according to terms defined by Apache 2.0 or other library specifc licenses.
 
-   Copyright 2017-2020 NavAbility
+   Copyright 2017-2021 NavAbility
 
-   Licensed under the Apache License, Version 2.0 (the "License");
+   Licensed under a Market Limited version of the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.
-   You may obtain a copy of the License at
-
-       http://www.apache.org/licenses/LICENSE-2.0
 
    Unless required by applicable law or agreed to in writing, software
    distributed under the License is distributed on an "AS IS" BASIS,

Project.toml

@@ -1,24 +1,25 @@
 name = "DistributedFactorGraphs"
 uuid = "b5cc3c7e-6572-11e9-2517-99fb8daf2f04"
-version = "0.11.3"
+version = "0.15.0"
 
 [deps]
 Base64 = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
 Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
-Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JSON2 = "2535ab7d-5cd8-5a07-80ac-9b1792aadce3"
 LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+ManifoldsBase = "3362f125-f0bb-47a3-aa74-596ffd7ef2fb"
 Neo4j = "d2adbeaf-5838-5367-8a2f-e46d570981db"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SHA = "ea8e919c-243c-51af-8825-aaa63cd721ce"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+TensorCast = "02d47bb6-7ce6-556a-be16-bb1710789e2b"
 TimeZones = "f269a46b-ccf7-5d73-abea-4c690281aa53"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 Unmarshal = "cbff2730-442d-58d7-89d1-8e530c41eb02"
@@ -27,22 +28,25 @@ Unmarshal = "cbff2730-442d-58d7-89d1-8e530c41eb02"
 Colors = "0.8, 0.9, 0.10, 0.11, 0.12"
 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"
-Graphs = "0.10.2, 0.11, 1"
 JSON = "0.21"
 JSON2 = "0.3.1"
 LightGraphs = "1.2, 1.3"
+ManifoldsBase = "0.11, 0.12"
 Neo4j = "2"
 Pkg = "1.4, 1.5"
 Reexport = "0.2, 0.3, 0.4, 0.5, 1"
-Requires = "0.5, 0.6, 0.7, 0.8, 0.9, 0.10, 1"
+Requires = "0.5, 1"
+TensorCast = "0.3.3, 0.4"
 TimeZones = "1.3.1"
 Unmarshal = "0.4"
-julia = "1.2"
+julia = "1.4"
 
 [extras]
 GraphPlot = "a2cc645c-3eea-5389-862e-a155d0052231"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+Manifolds = "1cead3c2-87b3-11e9-0ccd-23c62b72b94e"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test", "GraphPlot", "Pkg"]
+test = ["Test", "GraphPlot", "LinearAlgebra", "Manifolds", "Pkg"]

README.md

@@ -2,11 +2,19 @@
 
 Click on badges to follow links:
 
-Release v0.9 | Release v0.10 | Dev | Coverage | Documentation |
+Release v0.13 | Release v0.14 | Dev | Coverage | Documentation |
 ---------|---------|-----|------------|------------|
-[![Build Status](https://api.travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=release/v0.9)](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl) | [![Build Status](https://api.travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=release/v0.10)](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl) |  [![Build Status](https://api.travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=master)](https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl) <br> [![Average time to resolve an issue](https://isitmaintained.com/badge/resolution/JuliaRobotics/DistributedFactorGraphs.jl.svg)](https://github.com/JuliaRobotics/DistributedFactorGraphs.jl/issues) | [![Codecov Status](https://codecov.io/gh/JuliaRobotics/DistributedFactorGraphs.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/JuliaRobotics/DistributedFactorGraphs.jl) <br> [![Percentage of issues still open](https://isitmaintained.com/badge/open/JuliaRobotics/DistributedFactorGraphs.jl.svg)](https://github.com/JuliaRobotics/DistributedFactorGraphs.jl/issues) | [![docs](https://img.shields.io/badge/DFGDocs-latest-blue.svg)](http://juliarobotics.github.io/DistributedFactorGraphs.jl/latest/) <br> [![docs](https://img.shields.io/badge/CaesarDocs-latest-blue.svg)](http://juliarobotics.github.io/Caesar.jl/latest/)
+[![Build Status][dfg-build-v0.13]][dfg-build-url] | [![Build Status][dfg-build-v0.14]][dfg-build-url] | [![Build Status][dfg-build-img]][dfg-build-url] <br> [![Average time to resolve an issue](https://isitmaintained.com/badge/resolution/JuliaRobotics/DistributedFactorGraphs.jl.svg)](https://github.com/JuliaRobotics/DistributedFactorGraphs.jl/issues) | [![codecov.io][dfg-cov-img]][dfg-cov-url] <br> [![Percentage of issues still open](https://isitmaintained.com/badge/open/JuliaRobotics/DistributedFactorGraphs.jl.svg)](https://github.com/JuliaRobotics/DistributedFactorGraphs.jl/issues) | [![docs](https://img.shields.io/badge/DFGDocs-latest-blue.svg)](http://juliarobotics.github.io/DistributedFactorGraphs.jl/latest/) <br> [![docs](https://img.shields.io/badge/CaesarDocs-latest-blue.svg)](http://juliarobotics.github.io/Caesar.jl/latest/)
 
 
+[dfg-build-v0.13]: https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=release/v0.13
+[dfg-build-v0.14]: https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=release/v0.14
+
+[dfg-cov-img]: https://codecov.io/github/JuliaRobotics/DistributedFactorGraphs.jl/coverage.svg?branch=master
+[dfg-cov-url]: https://codecov.io/github/JuliaRobotics/DistributedFactorGraphs.jl?branch=master
+[dfg-build-img]: https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=master
+[dfg-build-url]: https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl
+
 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
 * Implementations of the API for in-memory and database-driven operation
@@ -42,7 +50,7 @@ dfg = initfg()
 # add 2 ContinuousScalar variable types to the new factor graph
 addVariable!(dfg, :a, ContinuousScalar)
 addVariable!(dfg, :b, ContinuousScalar)
-# add a LinearConditional factor
-addFactor!(dfg, [:a, :b], LinearConditional(Normal(10.0,1.0)))
+# add a LinearRelative factor
+addFactor!(dfg, [:a, :b], LinearRelative(Normal(10.0,1.0)))
 ```
 

src/DataBlobs/services/AbstractDataEntries.jl

@@ -29,7 +29,7 @@ buildSourceString(dfg::AbstractDFG, label::Symbol) =
 Get data entry
 """
 function getDataEntry(var::AbstractDFGVariable, key::Symbol)
-    !hasDataEntry(var, key) && error("Data entry $(key) does not exist in variable")
+    !hasDataEntry(var, key) && error("Data entry $(key) does not exist in variable $(getLabel(var))")
     return var.dataDict[key]
 end
 
@@ -42,7 +42,7 @@ end
 Add Data Entry to a DFG variable
 """
 function addDataEntry!(var::AbstractDFGVariable, bde::AbstractDataEntry)
-    haskey(var.dataDict, bde.label) && error("Data entry $(bde.label) already exists in variable")
+    haskey(var.dataDict, bde.label) && error("Data entry $(bde.label) already exists in variable $(getLabel(var))")
     var.dataDict[bde.label] = bde
     return bde
 end
@@ -66,7 +66,7 @@ DevNote
 - DF, unclear if `update` verb is applicable in this case, see #404
 """
 function updateDataEntry!(var::AbstractDFGVariable,  bde::AbstractDataEntry)
-    !haskey(var.dataDict, bde.label) && (@warn "$(bde.label) does not exist in variable, adding")
+    !haskey(var.dataDict, bde.label) && (@warn "$(bde.label) does not exist in variable $(getLabel(var)), adding")
     var.dataDict[bde.label] = bde
     return bde
 end

src/Deprecated.jl

@@ -135,8 +135,9 @@ end
 ## Deprecated in v0.11 Remove in the v0.12 cycle
 ##==============================================================================
 
-export AbstractRelativeFactor, AbstractRelativeFactorMinimize
-
+# @warn("BREAKING CHANGE coming to DistributedFactorGraphs v0.12: deprecating AbstractRelativeFactor, use AbstractRelativeRoots instead")
+# @warn("BREAKING CHANGE coming to DistributedFactorGraphs v0.12: deprecating AbstractRelativeFactorMinimize, use AbstractRelativeMinimize instead")
+# export AbstractRelativeFactor, AbstractRelativeFactorMinimize
 const AbstractRelativeFactor = AbstractRelativeRoots
 const AbstractRelativeFactorMinimize = AbstractRelativeMinimize
 

src/DistributedFactorGraphs.jl

@@ -28,6 +28,12 @@ using LinearAlgebra
 using SparseArrays
 using UUIDs
 using Pkg
+using TensorCast
+
+# used for @defVariable
+import ManifoldsBase
+import ManifoldsBase: AbstractManifold, manifold_dimension
+export AbstractManifold, manifold_dimension
 
 import Base: getindex
 
@@ -130,7 +136,10 @@ export getSolverData
 export getVariableType
 
 # VariableType functions
-export getDimension, getManifolds
+export getDimension, getManifold, getPointType
+export getPointIdentity, getPoint, getCoordinates
+
+export getManifolds # TODO Deprecate?
 
 # Small Data CRUD
 export SmallDataTypes, getSmallData, addSmallData!, updateSmallData!, deleteSmallData!, listSmallData, emptySmallData!
@@ -175,7 +184,7 @@ export VariableNodeData, PackedVariableNodeData
 
 export packVariableNodeData, unpackVariableNodeData
 
-export getSolvedCount, isSolved, setSolvedCount!, isInitialized
+export getSolvedCount, isSolved, setSolvedCount!, isInitialized, isMarginalized, setMarginalized!
 
 export getNeighborhood, getNeighbors, _getDuplicatedEmptyDFG
 export findFactorsBetweenNaive
@@ -315,9 +324,6 @@ if get(ENV, "DFG_USE_CGDFG", "") == "true"
 end
 
 function __init__()
-    @warn("BREAKING CHANGE coming to DistributedFactorGraphs v0.12: deprecating AbstractRelativeFactor, use AbstractRelativeRoots instead")
-    @warn("BREAKING CHANGE coming to DistributedFactorGraphs v0.12: deprecating AbstractRelativeFactorMinimize, use AbstractRelativeMinimize instead")
-
     @require GraphPlot = "a2cc645c-3eea-5389-862e-a155d0052231" begin
         @info "DistributedFactorGraphs.jl is adding tools using GraphPlot.jl"
         include("DFGPlots/DFGPlots.jl")

src/LightDFG/services/LightDFG.jl

@@ -438,11 +438,11 @@ function findShortestPathDijkstra(  dfg::LightDFG,
         dfg
     end
 
-    # LightDFG internally uses Integers 
-    if !haskey(dfg_.g.labels, from) || !haskey(dfg_.g.labels, from)
+    if !exists(dfg_, from) || !exists(dfg_, to)
         # assume filters excluded either `to` or `from` and hence no shortest path
         return Symbol[]
     end
+    # LightDFG internally uses Integers 
     frI = dfg_.g.labels[from]
     toI = dfg_.g.labels[to]
 

src/entities/DFGFactor.jl

@@ -4,9 +4,10 @@
 
 # TODO consider changing this to AbstractFactor
 abstract type AbstractFactor end
-const FunctorInferenceType = AbstractFactor
 abstract type AbstractPackedFactor end
-const PackedInferenceType = AbstractPackedFactor
+
+const FunctorInferenceType = AbstractFactor       # will eventually deprecate
+const PackedInferenceType = AbstractPackedFactor  # will eventually deprecate
 
 abstract type AbstractPrior <: AbstractFactor end
 abstract type AbstractRelative <: AbstractFactor end
@@ -15,8 +16,8 @@ abstract type AbstractRelativeMinimize <: AbstractRelative end
 
 # NOTE DF, Convolution is IIF idea, but DFG should know about "FactorOperationalMemory"
 # DF, IIF.CommonConvWrapper <: FactorOperationalMemory #
-# TODO resolve whether `<: Function` is really needed here
-abstract type FactorOperationalMemory <: Function end
+# NOTE was `<: Function` as unnecessary
+abstract type FactorOperationalMemory end   # <: Function
 # TODO to be removed from DFG,
 # we can add to IIF or have IIF.CommonConvWrapper <: FactorOperationalMemory directly
 # abstract type ConvolutionObject <: FactorOperationalMemory end
@@ -46,36 +47,40 @@ mutable struct GenericFunctionNodeData{T<:Union{PackedInferenceType, FunctorInfe
     certainhypo::Vector{Int}
     nullhypo::Float64
     solveInProgress::Int
-
+    inflation::Float64
+    # inner constructor needed for dual use
+    # GenericFunctionNodeData{T}(x1::Bool,x2::Bool,x3,x4::T,args...) where T = new{T}(x1,x2,x3,x4,args...)
     # TODO deprecate all these inner constructors at end of DFG v0.9.x (was added for GFND.nullhypo::Float64 breaking change)
-    GenericFunctionNodeData{T}(el,po,ed,fn,mu::Vector{<:Real},ce::Vector{Int},so::Int) where T = new{T}(el,po,ed,fn,mu,ce,0.0,so)
-    GenericFunctionNodeData{T}(el,po,ed,fn,mu::Vector{<:Real},ce::Vector{Int},nu::Real,so::Int) where T = new{T}(el,po,ed,fn,mu,ce,nu,so)
+    # GenericFunctionNodeData{T}(el,po,ed,fn,mu::Vector{<:Real},ce::Vector{Int},so::Int) where T = 
+    #                            new{T}(el,po,ed,fn,mu,ce,0.0,so)
+    # GenericFunctionNodeData{T}(el,po,ed,fn,mu::Vector{<:Real},ce::Vector{Int},nu::Real,so::Int,infl::Real) where T = new{T}(el,po,ed,fn,mu,ce,nu,so,infl)
 end
 
 ## Constructors
 
 GenericFunctionNodeData{T}() where T =
-    GenericFunctionNodeData{T}(false, false, Int[], T(), Float64[], Int[], 0, 0)
-
-function GenericFunctionNodeData(eliminated::Bool,
-                                 potentialused::Bool,
-                                 edgeIDs::Vector{Int},
-                                 fnc::T,
-                                 multihypo::Vector{<:Real}=Float64[],
-                                 certainhypo::Vector{Int}=Int[],
-                                 nullhypo::Real=0,
-                                 solveInP::Int=0) where T
-    return GenericFunctionNodeData{T}(eliminated, potentialused, edgeIDs, fnc, multihypo, certainhypo, nullhypo, solveInP)
+    GenericFunctionNodeData(false, false, Int[], T())
+
+function GenericFunctionNodeData(   eliminated::Bool,
+                                    potentialused::Bool,
+                                    edgeIDs::Vector{Int},
+                                    fnc::T,
+                                    multihypo::Vector{<:Real}=Float64[],
+                                    certainhypo::Vector{Int}=Int[],
+                                    nullhypo::Real=0,
+                                    solveInP::Int=0,
+                                    inflation::Real=0.0 ) where T
+    return GenericFunctionNodeData{T}(eliminated, potentialused, edgeIDs, fnc, multihypo, certainhypo, nullhypo, solveInP, inflation)
 end
 
 
 ##------------------------------------------------------------------------------
 ## PackedFunctionNodeData and FunctionNodeData
 
-const PackedFunctionNodeData{T} = GenericFunctionNodeData{T} where T <: PackedInferenceType
+const PackedFunctionNodeData{T} = GenericFunctionNodeData{T} where T <: AbstractPackedFactor
 PackedFunctionNodeData(args...) = PackedFunctionNodeData{typeof(args[4])}(args...)
 
-const FunctionNodeData{T} = GenericFunctionNodeData{T} where T <: Union{FunctorInferenceType, FactorOperationalMemory}
+const FunctionNodeData{T} = GenericFunctionNodeData{T} where T <: Union{AbstractFactor, FactorOperationalMemory}
 FunctionNodeData(args...) = FunctionNodeData{typeof(args[4])}(args...)