fix wrong export and deprecate

Author: dehann

NEWS.md

@@ -23,6 +23,7 @@ The list below highlights major breaking changes, and please note that significa
 - Deprecate use of `getParametricMeasurement` and use `getMeasurementParametric` instead, and add `<:AbstractManifold` to API.
 - Deprecate use of `solveBinaryFactorParameteric`, instead use `solveFactorParameteric`.
 - Deprecating `approxConvBinary`, use `approxConvBelief` instead.
+- Deprecating `accumulateFactorChain`, use `approxConvBelief` instead.
 
 
 # Major changes in v0.24

src/Deprecated.jl

@@ -26,6 +26,49 @@ end
 ##==============================================================================
 
 
+# """
+#     $SIGNATURES
+
+# Calculate both measured and predicted relative variable values, starting with `from` at zeros up to `to::Symbol`.
+
+# Notes
+# - assume single variable separators only.
+
+# DevNotes
+# - TODO better consolidate with [`approxConvBelief`](@ref) which can now also work with factor chains.
+# """
+# function accumulateFactorChain( dfg::AbstractDFG,
+#                                 from::Symbol,
+#                                 to::Symbol,
+#                                 fsyms::Vector{Symbol}=findFactorsBetweenNaive(dfg, from, to);
+#                                 initval=zeros(size(getVal(dfg, from))))
+
+#   # get associated variables
+#   svars = union(ls.(dfg, fsyms)...)
+
+#   # use subgraph copys to do calculations
+#   tfg_meas = buildSubgraph(dfg, [svars;fsyms])
+#   tfg_pred = buildSubgraph(dfg, [svars;fsyms])
+
+#   # drive variable values manually to ensure no additional stochastics are introduced.
+#   nextvar = from
+#   initManual!(tfg_meas, nextvar, initval)
+#   initManual!(tfg_pred, nextvar, initval)
+
+#   # nextfct = fsyms[1] # for debugging
+#   for nextfct in fsyms
+#     nextvars = setdiff(ls(tfg_meas,nextfct),[nextvar])
+#     @assert length(nextvars) == 1 "accumulateFactorChain requires each factor pair to separated by a single variable"
+#     nextvar = nextvars[1]
+#     meas, pred = approxDeconv(dfg, nextfct) # solveFactorMeasurements
+#     pts_meas = approxConv(tfg_meas, nextfct, nextvar, (meas,ones(Int,100),collect(1:100)))
+#     pts_pred = approxConv(tfg_pred, nextfct, nextvar, (pred,ones(Int,100),collect(1:100)))
+#     initManual!(tfg_meas, nextvar, pts_meas)
+#     initManual!(tfg_pred, nextvar, pts_pred)
+#   end
+#   return getVal(tfg_meas,nextvar), getVal(tfg_pred,nextvar)
+# end
+
 
 # # TODO should this be consolidated with regular approxConv?
 # # TODO, perhaps pass Xi::Vector{DFGVariable} instead?

src/IncrementalInference.jl

@@ -392,8 +392,7 @@ export *,
   getPointType, 
   getPointIdentity,
   setVariableRefence!,
-  reshapeVec2Mat,
-  accumulateFactorChain
+  reshapeVec2Mat
 
 # more optional exports
 export HeatmapDensityRegular

src/ODE/DERelative.jl

@@ -5,7 +5,7 @@ using .DifferentialEquations
 
 import .DifferentialEquations: solve
 
-import IncrementalInference: getSample
+import IncrementalInference: getSample, getManifold
 
 export DERelative
 
@@ -38,6 +38,7 @@ struct DERelative{T <:InferenceVariable, P, D} <: AbstractRelativeRoots
   specialSampler::Function
 end
 
+getManifold(de::DERelative{T}) where T = getManifold(de.domain)
 
 """
 $SIGNATURES

src/TetherUtils.jl

@@ -2,7 +2,7 @@
 
 export cont2disc
 export rebaseFactorVariable!
-export getFactorMean
+export accumulateFactorMeans
 export solveFactorParameteric
 
 """

src/services/ApproxConv.jl

@@ -1,6 +1,6 @@
 
 export calcFactorResidual
-export accumulateFactorChain
+
 
 
 function approxConvBelief(dfg::AbstractDFG,
@@ -299,48 +299,5 @@ end
 
 
 
-"""
-    $SIGNATURES
-
-Calculate both measured and predicted relative variable values, starting with `from` at zeros up to `to::Symbol`.
-
-Notes
-- assume single variable separators only.
-
-DevNotes
-- TODO better consolidate with [`approxConvBelief`](@ref) which can now also work with factor chains.
-"""
-function accumulateFactorChain( dfg::AbstractDFG,
-                                from::Symbol,
-                                to::Symbol,
-                                fsyms::Vector{Symbol}=findFactorsBetweenNaive(dfg, from, to);
-                                initval=zeros(size(getVal(dfg, from))))
-
-  # get associated variables
-  svars = union(ls.(dfg, fsyms)...)
-
-  # use subgraph copys to do calculations
-  tfg_meas = buildSubgraph(dfg, [svars;fsyms])
-  tfg_pred = buildSubgraph(dfg, [svars;fsyms])
-
-  # drive variable values manually to ensure no additional stochastics are introduced.
-  nextvar = from
-  initManual!(tfg_meas, nextvar, initval)
-  initManual!(tfg_pred, nextvar, initval)
-
-  # nextfct = fsyms[1] # for debugging
-  for nextfct in fsyms
-    nextvars = setdiff(ls(tfg_meas,nextfct),[nextvar])
-    @assert length(nextvars) == 1 "accumulateFactorChain requires each factor pair to separated by a single variable"
-    nextvar = nextvars[1]
-    meas, pred = approxDeconv(dfg, nextfct) # solveFactorMeasurements
-    pts_meas = approxConv(tfg_meas, nextfct, nextvar, (meas,ones(Int,100),collect(1:100)))
-    pts_pred = approxConv(tfg_pred, nextfct, nextvar, (pred,ones(Int,100),collect(1:100)))
-    initManual!(tfg_meas, nextvar, pts_meas)
-    initManual!(tfg_pred, nextvar, pts_pred)
-  end
-  return getVal(tfg_meas,nextvar), getVal(tfg_pred,nextvar)
-end
-
 
 #