Merge pull request #632 from JuliaRobotics/master

v0.6.3-rc1

.github/workflows/CompatHelper.yml

@@ -1,26 +1,16 @@
 name: CompatHelper
-
 on:
   schedule:
-    - cron: '20 00 * * *'
-  issues:
-    types: [opened, reopened]
-
+    - cron: '00 01 * * *'
+  workflow_dispatch:
 jobs:
   CompatHelper:
-    runs-on: ${{ matrix.os }}
-    strategy:
-      matrix:
-        julia-version: [1.2.0]
-        julia-arch: [x86]
-        os: [ubuntu-latest]
+    runs-on: ubuntu-latest
     steps:
-      - uses: julia-actions/setup-julia@latest
-        with:
-          version: ${{ matrix.julia-version }}
       - name: Pkg.add("CompatHelper")
         run: julia -e 'using Pkg; Pkg.add("CompatHelper")'
       - name: CompatHelper.main()
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          COMPATHELPER_PRIV: ${{ secrets.COMPATHELPER_PRIV }}  # optional
         run: julia -e 'using CompatHelper; CompatHelper.main()'

Project.toml

@@ -2,7 +2,7 @@ name = "Caesar"
 uuid = "62eebf14-49bc-5f46-9df9-f7b7ef379406"
 keywords = ["SLAM", "state-estimation", "mm-iSAM", "inference", "robotics", "ROS"]
 desc = "Non-Gaussian simultaneous localization and mapping"
-version = "0.6.2"
+version = "0.6.3"
 
 [deps]
 ApproxManifoldProducts = "9bbbb610-88a1-53cd-9763-118ce10c1f89"
@@ -44,15 +44,15 @@ YAML = "ddb6d928-2868-570f-bddf-ab3f9cf99eb6"
 ApproxManifoldProducts = "^0.1"
 Combinatorics = "^0.7, 0.8, 0.9, 1"
 CoordinateTransformations = "0.5, 0.6"
-DataStructures = "0.15, 0.16, 0.17, 0.18, 0.18, 0.19, 0.20"
+DataStructures = "0.16, 0.17, 0.18"
 DistributedFactorGraphs = "0.9, 0.10"
-Distributions = "0.18, 0.19, 0.20, 0.21, 0.22, 0.23"
+Distributions = "0.19, 0.20, 0.21, 0.22, 0.23, 0.24"
 DocStringExtensions = "0.7, 0.8, 0.9, 1"
-FFTW = "0.2.4, 0.3, 1"
+FFTW = "1"
 FileIO = "1"
 ImageCore = "0.7, 0.8, 0.9"
 ImageMagick = "0.7, 1.0, 1.1"
-IncrementalInference = "0.14.1, 0.15, 0.16"
+IncrementalInference = "0.15, 0.16, 0.17"
 JLD2 = "0.1, 0.2"
 JSON = "0.18, 0.19, 0.20, 0.21, 0.22, 0.23"
 JSON2 = "0.3, 0.4"
@@ -61,13 +61,13 @@ NLsolve = "3, 4"
 ProgressMeter = "0.9, 1"
 Reexport = "0.2"
 Requires = "0.5, 0.6, 0.7, 0.8, 0.9, 0.10, 1"
-RoME = "0.7.1, 0.8, 0.9"
-Rotations = "0.13, 1.0"
+RoME = "0.8, 0.9, 0.10"
+Rotations = "0.13, 1"
 TensorCast = "0.2, 0.3"
-TimeZones = "1.3.1"
-TransformUtils = "^0.2.2"
+TimeZones = "1.3.1, 1.4"
+TransformUtils = "0.2.2"
 Unmarshal = "0.2.1, 0.3, 0.4"
-YAML = "0.3"
+YAML = "0.3, 0.4"
 ZMQ = "1"
 julia = "1.4"
 

README.md

@@ -4,15 +4,6 @@
 
 A multimodal/non-Gaussian robotic toolkit for localization and mapping -- reducing the barrier of entry for sensor/data fusion tasks, including Simultaneous Localization and Mapping (SLAM).
 
-# NOTICE Gadfly#master
-
-Note current installation requires the latest Gadfly to overcome a Type Piracy problem that occurred in ImageCore.jl.  The following installation will fix the recent (but transient) Pkg compat problems:
-```julia
-julia> ] # to activate package manager
-(@v1.5) pkg> add Gadfly#master
-(@v1.5) pkg> add IncrementalInference RoME Caesar
-```
-
 # Weblink Info
 
 Click on the badges to follow web url links:
@@ -39,7 +30,6 @@ Code changes are currently tracked via Github's integrated Milestone/Issues/PR s
 | [TransformUtils.jl][tf-url] | [![][tf-stable]][tf-releases] | [![Build Status][tf-build-img]][tf-build-url] | [![codecov.io][tf-cov-img]][tf-cov-url] | -- |
 | [LightGraphs.jl][lgraphs-url] | [![][lgjl-stable]][lgjl-releases] | [![Build Status][lgraphs-build-img]][lgraphs-build-url] | [![codecov.io][lgraphs-cov-img]][lgraphs-cov-url] | n/a |
 | [~~Graphs.jl~~][graphs-url] | [![][gjl-stable]][gjl-releases] | [![Build Status][graphs-build-img]][graphs-build-url] | [![codecov.io][graphs-cov-img]][graphs-cov-url] | n/a |
-| [~~CloudGraphs.jl~~][cloudgraphs-url] | ![][cg-stable] | [![Build Status][cloudgraphs-build-img]][cloudgraphs-build-url] | [![codecov.io][cloudgraphs-cov-img]][cloudgraphs-cov-url] | [![][mst-shield2]][dfg-milestones] |
 
 # Contributors
 
@@ -75,9 +65,9 @@ This project adheres to the [JuliaRobotics code of conduct](https://github.com/J
 [cov-img]: https://codecov.io/github/JuliaRobotics/Caesar.jl/coverage.svg?branch=master
 [cov-url]: https://codecov.io/github/JuliaRobotics/Caesar.jl?branch=master
 [build-img]: https://travis-ci.org/JuliaRobotics/Caesar.jl.svg?branch=master
-[build-tag]: https://travis-ci.org/JuliaRobotics/Caesar.jl.svg?branch=release/v0.5
+[build-tag]: https://travis-ci.org/JuliaRobotics/Caesar.jl.svg?branch=release/v0.6
 [build-url]: https://travis-ci.org/JuliaRobotics/Caesar.jl
-[caesar-stable]: https://img.shields.io/badge/2020Q3-v0.6.x-green.svg
+[caesar-stable]: https://img.shields.io/badge/2020Q4-v0.6.x-green.svg
 [caesar-slack-badge]: https://img.shields.io/badge/Caesarjl-Slack-green.svg?style=popout
 [caesar-slack]: https://caesarjl.slack.com
 [caesar-milestones]: https://github.com/JuliaRobotics/Caesar.jl/milestones
@@ -87,19 +77,19 @@ This project adheres to the [JuliaRobotics code of conduct](https://github.com/J
 [r-cov-img]: https://codecov.io/github/JuliaRobotics/RoME.jl/coverage.svg?branch=master
 [r-cov-url]: https://codecov.io/github/JuliaRobotics/RoME.jl?branch=master
 [r-build-img]: https://travis-ci.org/JuliaRobotics/RoME.jl.svg?branch=master
-[r-build-v05]: https://travis-ci.org/JuliaRobotics/RoME.jl.svg?branch=release%2Fv0.5
+[r-build-v05]: https://travis-ci.org/JuliaRobotics/RoME.jl.svg?branch=release%2Fv0.9
 [r-build-url]: https://travis-ci.org/JuliaRobotics/RoME.jl
-[r-stable]: https://img.shields.io/badge/2020Q3-v0.9.x-green.svg
+[r-stable]: https://img.shields.io/badge/2020Q4-v0.9.x-green.svg
 [r-milestones]: https://github.com/JuliaRobotics/RoME.jl/milestones
 [r-releases]: https://github.com/JuliaRobotics/RoME.jl/releases
 
 [iif-cov-img]: https://codecov.io/github/JuliaRobotics/IncrementalInference.jl/coverage.svg?branch=master
 [iif-cov-url]: https://codecov.io/github/JuliaRobotics/IncrementalInference.jl?branch=master
 [iif-build-img]: https://travis-ci.org/JuliaRobotics/IncrementalInference.jl.svg?branch=master
-[iif-build-v08]: https://travis-ci.org/JuliaRobotics/IncrementalInference.jl.svg?branch=release/v0.8
+[iif-build-v016]: https://travis-ci.org/JuliaRobotics/IncrementalInference.jl.svg?branch=release/v0.16
 [iif-build-url]: https://travis-ci.org/JuliaRobotics/IncrementalInference.jl
 [iif-url]: http://www.github.com/JuliaRobotics/IncrementalInference.jl
-[iif-stable]: https://img.shields.io/badge/2020Q3-v0.15.x-green.svg
+[iif-stable]: https://img.shields.io/badge/2020Q4-v0.16.x-green.svg
 [iif-milestones]: https://github.com/JuliaRobotics/IncrementalInference.jl/milestones
 [iif-releases]: https://github.com/JuliaRobotics/IncrementalInference.jl/releases
 
@@ -149,7 +139,7 @@ This project adheres to the [JuliaRobotics code of conduct](https://github.com/J
 [dfg-build-img]: https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl.svg?branch=master
 [dfg-build-url]: https://travis-ci.org/JuliaRobotics/DistributedFactorGraphs.jl
 [dfg-url]: http://www.github.com/JuliaRobotics/DistributedFactorGraphs.jl
-[dfg-stable]: https://img.shields.io/badge/2020Q3-v0.10.x-green.svg
+[dfg-stable]: https://img.shields.io/badge/2020Q4-v0.10.x-green.svg
 [dfg-milestones]: https://github.com/JuliaRobotics/DistributedFactorGraphs.jl/milestones
 [dfg-releases]: https://github.com/JuliaRobotics/DistributedFactorGraphs.jl/releases
 
@@ -171,18 +161,11 @@ This project adheres to the [JuliaRobotics code of conduct](https://github.com/J
 [fsm-milestones]: https://github.com/JuliaRobotics/FunctionalStateMachine.jl/milestones
 [fsm-releases]: https://github.com/JuliaRobotics/FunctionalStateMachine.jl/releases
 
-[cloudgraphs-cov-img]: https://codecov.io/github/GearsAD/CloudGraphs.jl/coverage.svg?branch=master
-[cloudgraphs-cov-url]: https://codecov.io/github/GearsAD/CloudGraphs.jl?branch=master
-[cloudgraphs-build-img]: https://travis-ci.org/GearsAD/CloudGraphs.jl.svg?branch=master
-[cloudgraphs-build-url]: https://travis-ci.org/GearsAD/CloudGraphs.jl
-[cloudgraphs-url]: http://www.github.com/GearsAD/CloudGraphs.jl
-[cg-stable]: https://img.shields.io/badge/2019Q3-WIP-yellowgreen.svg
-
 [rp-url]: http://www.github.com/JuliaRobotics/RoMEPlotting.jl
 [rp-cov-img]: https://codecov.io/github/JuliaRobotics/RoMEPlotting.jl/coverage.svg?branch=master
 [rp-cov-url]: https://codecov.io/github/JuliaRobotics/RoMEPlotting.jl?branch=master
 [rp-build-img]: https://travis-ci.org/JuliaRobotics/RoMEPlotting.jl.svg?branch=master
 [rp-build-url]: https://travis-ci.org/JuliaRobotics/RoMEPlotting.jl
-[rp-stable]: https://img.shields.io/badge/2020Q3-v0.4.x-green.svg
+[rp-stable]: https://img.shields.io/badge/2020Q4-v0.4.x-green.svg
 [rp-milestones]: https://github.com/JuliaRobotics/RoMEPlotting.jl/milestones
 [rp-releases]: https://github.com/JuliaRobotics/RoMEPlotting.jl/releases

docs/src/concepts/available_varfacs.md

@@ -57,7 +57,6 @@ Defaults in IncrementalInference.jl:
 ```@docs
 Prior
 PartialPrior
-MixturePrior
 ```
 
 Some of the most common priors (unary factors) in Caesar.jl/RoME.jl include:
@@ -73,8 +72,7 @@ PriorPose3
 
 Defaults in IncrementalInference.jl:
 ```@docs
-LinearConditional
-MixtureLinearConditional
+LinearRelative
 ```
 
 Existing n-ary factors in Caesar.jl/RoME.jl/IIF.jl include:

docs/src/concepts/building_graphs.md

@@ -80,6 +80,20 @@ for i in 1:10
 end
 ```
 
+#### [OPTIONAL] Understanding Internal Factor Naming Convention
+
+The factor name used by Caesar is automatically generated from 
+```julia
+addFactor!(fg, [:x0; :x1],...)
+```
+will create a factor with name `:x0x1f1`
+
+When you were to add a another factor betweem `:x0`, `:x1`:
+```julia
+addFactor!(fg, [:x0; :x1],...)
+```
+will create a second factor with the name `:x0x1f2`.
+
 ### When to Instantiate Poses (i.e. new Variables in Factor Graph)
 
 Consider a robot traversing some area while exploring, localizing, and wanting to find strong loop-closure features for consistent mapping.  The creation of new poses and landmark variables is a trade-off in computational complexity and marginalization errors made during factor graph construction.  Common triggers for new poses are:

docs/src/examples/basic_continuousscalar.md

@@ -95,18 +95,18 @@ By forcing the initialization of `:x1` and plotting its belief estimate,
 ensureAllInitialized!(fg)
 plotKDE(fg, [:x0, :x1])
 ```
-the predicted influence of the `P(Z| X1 - X0) = LinearConditional(Normal(10, 1))` is shown by the red trace.
+the predicted influence of the `P(Z| X1 - X0) = LinearRelative(Normal(10, 1))` is shown by the red trace.
 ```@raw html
 <p align="center">
 <img src="https://raw.githubusercontent.com/JuliaRobotics/Caesar.jl/master/docs/src/assets/tutorials/ContinuousScalar/plx01.png" width="360" border="0" />
 </p>
 ```
 The red trace (predicted belief of `:x1`) is noting more than the approximated convolution of the current marginal belief of `:x0` with the conditional belief described by `P(Z | X1 - X0)`.
 
-Another `ContinuousScalar` variable `:x2` is 'connected' to `:x1` through a more complicated `MixtureLinearConditional` likelihood function.
+Another `ContinuousScalar` variable `:x2` is 'connected' to `:x1` through a more complicated `MixtureRelative` likelihood function.
 ```julia
 addVariable!(fg, :x2, ContinuousScalar)
-mmo = MixtureLinearConditional([Rayleigh(3); Uniform(30,55)], Categorical([0.4; 0.6]))
+mmo = MixtureRelative(LinearRelative, (hypo1=Rayleigh(3), hypo2=Uniform(30,55)), [0.4; 0.6])
 addFactor!(fg, [:x1, :x2], mmo)
 ```
 ```@raw html

docs/src/faq.md

@@ -10,7 +10,7 @@ The [non-Gaussian/multimodal section in the docs](https://juliarobotics.org/Caes
 
 ## Why Julia
 The [JuliaLang](https://julialang.org/) and ([JuliaPro](https://juliacomputing.com/)) is an open-source Just-In-Time (JIT) & optionally precompiled, strongly-typed, and high-performance programming language.
-The algorithmic code is implemented in Julia for many reasons, such as agile development, high level syntax, performance, type safety, multiple dispatch replacement for [object oriented](https://invenia.github.io/blog/2019/10/30/julialang-features-part-1/), parallel computing, dynamic development, cross compilable (with gcc and clang) and foundational cross-platform ([LLVM](http:///www.llvm.org)) technologies.  
+The algorithmic code is implemented in Julia for many reasons, such as agile development, high level syntax, performance, type safety, multiple dispatch replacement for [object oriented](https://invenia.github.io/blog/2019/10/30/julialang-features-part-1/) which exhibits [several emergent properties](https://invenia.github.io/blog/2019/11/06/julialang-features-part-2/), parallel computing, dynamic development, cross compilable (with gcc and clang) and foundational cross-platform ([LLVM](http:///www.llvm.org)) technologies.  
 See [JuliaCon2018 highlights video](https://www.youtube.com/watch?v=baR02tlea5Y).  Julia can be thought of as either {C+, Mex (done right), [or as a modern Fortran replacement](https://arstechnica.com/science/2020/10/the-unreasonable-effectiveness-of-the-julia-programming-language/)}.
 
 ### Current Julia version?

docs/src/func_ref.md

@@ -170,7 +170,7 @@ updateFGBT!
 updateTreeCliquesAsMarginalizedFromVars!
 upGibbsCliqueDensity
 upMsg
-wipeBuildNewTree!
+resetBuildTree!
 writeGraphPdf
 resetVariableAllInitializations!
 ```

docs/src/principles/approxConvDensities.md

@@ -68,7 +68,7 @@ The [IncrementalInference.jl](http://www.github.com/JuliaRobotics/IncrementalInf
 
     Note in a factor graph sense, the flow of time is captured in the structure of the graph and a requirement of the IncrementalInference system is that factors can be resolved towards any variable, given current estimates on all other variables connected to that factor.  Furthermore, this forwards or backwards resolving/convolution through a factor should adhere to the Kolmogorov Criterion of reversibility to ensure that detailed balance is maintained in the overall marginal posterior solutions.
 
-The IncrementalInference (IIF) package provides a few generic conditional likelihood functions such as `LinearConditional` or `MixtureLinearConditional` which we will use in this illustration.  
+The IncrementalInference (IIF) package provides a few generic conditional likelihood functions such as `LinearRelative` or `MixtureRelative` which we will use in this illustration.  
 
 !!! note
 

examples/dev/devCSMHexDelayMatrix.jl

@@ -45,7 +45,7 @@ allCSMFunctions = [
   slowOnPrntAsChildrNeedDwn_StateMachine,
   towardUpOrDwnSolve_StateMachine,
   canCliqMargSkipUpSolve_StateMachine,
-  attemptDownInit_StateMachine,
+  tryDwnInitCliq_StateMachine,
   rmMsgLikelihoodsAfterDwn_StateMachine,
   blockSiblingStatus_StateMachine,
   slowIfChildrenNotUpSolved_StateMachine,
@@ -56,7 +56,6 @@ allCSMFunctions = [
   doAllSiblingsNeedDwn_StateMachine,
   maybeNeedDwnMsg_StateMachine,
   determineCliqNeedDownMsg_StateMachine,
-  doAnyChildrenNeedDwn_StateMachine,
   decideUpMsgOrInit_StateMachine,
   doesParentNeedDwn_StateMachine,
   attemptCliqInitUp_StateMachine,

examples/marine/auv/Sandshark/dev/Sandshark_AutoinitFailCase.jl

@@ -224,8 +224,8 @@ fetchCliqSolvableDims(getClique(tree, :x0))
 prnt = getClique(tree, :x1)
 getCliqSiblingsPriorityInitOrder(tree, prnt)
 
-getData(getClique(tree, :x0)).solvableDims
+# getData(getClique(tree, :x0)).solvableDims
 
-fetch(getData(getClique(tree, :x0)).solvableDims)
+# fetch(getData(getClique(tree, :x0)).solvableDims)
 
 #

examples/wheeled/racecar/LoadPyNNTxt.jl

@@ -16,9 +16,9 @@ end
 
 
 # convenience function to load specific model format from tensorflow
-function loadPose2OdoNNModelIntoFlux(dest::AbstractString)
+function loadPose2OdoNNModelIntoFlux(dest::AbstractString; pad::Bool=false)
   weights = loadPyNNTxt(dest::AbstractString)
-  buildPose2OdoNN_01_FromWeights(weights)
+  buildPose2OdoNN_01_FromWeights(weights, pad=pad)
 end