release v0.27.4-rc1

Project.toml

@@ -2,7 +2,7 @@ name = "IncrementalInference"
 uuid = "904591bb-b899-562f-9e6f-b8df64c7d480"
 keywords = ["MM-iSAMv2", "Bayes tree", "junction tree", "Bayes network", "variable elimination", "graphical models", "SLAM", "inference", "sum-product", "belief-propagation"]
 desc = "Implements the Multimodal-iSAMv2 algorithm."
-version = "0.27.3"
+version = "0.27.4"
 
 [deps]
 ApproxManifoldProducts = "9bbbb610-88a1-53cd-9763-118ce10c1f89"

src/ExportAPI.jl

@@ -295,6 +295,19 @@ export
   setVariableRefence!,
   reshapeVec2Mat
 
+
+export incrSuffix
+
+export calcPPE, calcVariablePPE
+export setPPE!, setVariablePosteriorEstimates!
+export getPPEDict
+export getPPESuggested, getPPEMean, getPPEMax
+export getPPESuggestedAll
+export loadDFG
+export findVariablesNear, defaultFixedLagOnTree!
+export fetchDataJSON
+
+
 export Position, Position1, Position2, Position3, Position4
 export ContinuousScalar, ContinuousEuclid # TODO figure out if this will be deprecated, Caesar.jl #807
 export Circular, Circle

src/FGOSUtils.jl

@@ -2,18 +2,8 @@
 #  IIF methods should direclty detect extended types from user import
 # of convert in their namespace
 
-import DistributedFactorGraphs: AbstractPointParametricEst, loadDFG
-import DistributedFactorGraphs: getFactorType
-
-export incrSuffix
-export calcPPE, calcVariablePPE
-export setPPE!, setVariablePosteriorEstimates!
-export getPPESuggestedAll, findVariablesNear, defaultFixedLagOnTree!
-export loadDFG
-export fetchDataJSON
-
-
 
+# FIXME, upgrade to AMP instead
 KDE.getPoints(dfg::AbstractDFG, lbl::Symbol) = getBelief(dfg, lbl) |> getPoints
 
 clampStringLength(st::AbstractString, len::Int=5) = st[1:minimum([len; length(st)])]

src/Factors/Mixture.jl

@@ -12,15 +12,19 @@ A `Mixture` object for use with either a `<: AbstractPrior` or `<: AbstractRelat
 Notes
 - The internal data representation is a `::NamedTuple`, which allows total type-stability for all component types.
 - Various construction helpers can accept a variety of inputs, including `<: AbstractArray` and `Tuple`.
+- `N` is the number of components used to make the mixture, so two bumps from two Normal components means `N=2`.
 
 DevNotes
+- FIXME swap API order so Mixture of distibutions works like a distribtion, see Caesar.jl #808
+  - Should not have field mechanics.
 - TODO on sampling see #1099 and #1094 and #1069 
 
+
 Example
 ```juila
 # prior factor
-msp = Mixture(PriorSphere1, 
-              [model=Normal(0,0.1), Uniform(-pi/1,pi/2)],
+msp = Mixture(Prior, 
+              [Normal(0,0.1), Uniform(-pi/1,pi/2)],
               [0.5;0.5])
 
 addFactor!(fg, [:head], msp, tags=[:MAGNETOMETER;])
@@ -34,9 +38,11 @@ addFactor!(fg, [:x0;:x1], mlr)
 ```
 """
 struct Mixture{N, F<:AbstractFactor, S, T<:Tuple} <: AbstractFactor
+  """ factor mechanics """
   mechanics::F
   components::NamedTuple{S,T}
   diversity::Distributions.Categorical
+  """ dimension of factor, so range measurement would be dims=1 """
   dims::Int
   labels::Vector{Int}
 end

src/IncrementalInference.jl

@@ -76,7 +76,8 @@ import DistributedFactorGraphs: getPPE, getPPEDict
 import DistributedFactorGraphs: getFactorOperationalMemoryType
 import DistributedFactorGraphs: getPoint, getCoordinates
 import DistributedFactorGraphs: getVariableType
-
+import DistributedFactorGraphs: AbstractPointParametricEst, loadDFG
+import DistributedFactorGraphs: getFactorType
 
 # will be deprecated in IIF
 import DistributedFactorGraphs: isSolvable