refactro to ccw.hyporecipe

Author: dehann

src/Deprecated.jl

@@ -256,6 +256,15 @@ function Base.getproperty(ccw::CommonConvWrapper, f::Symbol)
   elseif f == :vartypes
     @warn "CommonConvWrapper.vartypes is deprecated, use typeof.(getVariableType.(ccw.fullvariables) instead" maxlog=3
     return typeof.(getVariableType.(ccw.fullvariables))
+  elseif f == :hypotheses
+    @warn "CommonConvWrapper.hypotheses is now under ccw.hyporecipe.hypotheses" maxlog=5
+    return ccw.hyporecipe.hypotheses
+  elseif f == :certainhypo
+    @warn "CommonConvWrapper.certainhypo is now under ccw.hyporecipe.certainhypo" maxlog=5
+    return ccw.hyporecipe.certainhypo
+  elseif f == :activehypo
+    @warn "CommonConvWrapper.activehypo is now under ccw.hyporecipe.activehypo" maxlog=5
+    return ccw.hyporecipe.activehypo
   else
     return getfield(ccw, f)
   end

src/IncrementalInference.jl

@@ -125,6 +125,7 @@ include("ManifoldsExtentions.jl")
 # regular
 include("entities/SolverParams.jl")
 
+include("entities/HypoRecipe.jl")
 include("entities/FactorOperationalMemory.jl")
 
 include("Factors/GenericMarginal.jl")

src/entities/FactorOperationalMemory.jl

@@ -63,6 +63,8 @@ $(TYPEDEF)
 """
 struct MultiThreaded <: _AbstractThreadModel end
 
+
+
 """
 $(TYPEDEF)
 
@@ -86,8 +88,7 @@ Base.@kwdef struct CommonConvWrapper{
   TP <: Tuple, 
   CT,
   AM <: AbstractManifold,
-  HP <: Union{Nothing, <:Distributions.Categorical{Float64, Vector{Float64}}},
-  CH <: Union{Nothing, Vector{Int}},
+  HR <: HypoRecipeCompute,
   MT, 
   G
 } <: FactorOperationalMemory
@@ -114,13 +115,8 @@ Base.@kwdef struct CommonConvWrapper{
   nullhypo::Float64 = 0.0
   """ inflationSpread particular to this factor (by how much to dispurse the belief initial values before numerical optimization is run).  Analogous to stochastic search """
   inflation::Float64 = SolverParams().inflation
-  # multihypo specific field containers for recipe of hypotheses to compute
-  """ multi hypothesis settings #NOTE no need for a parameter as type is known from `parseusermultihypo` """
-  hypotheses::HP = nothing
-  """ categorical to select which hypothesis is being considered during convolution operation """
-  certainhypo::CH = nothing
-  """ subsection indices to select which params should be used for this hypothesis evaluation """
-  activehypo::Vector{Int} = collect(1:length(varValsAll))
+  """ multihypo specific field containers for recipe of hypotheses to compute """
+  hyporecipe::HR = HypoRecipeCompute(;activehypo=collect(1:length(varValsAll)))
   # buffers and indices to point numerical computations to specific memory locations
   """ user defined measurement values for each approxConv operation
       FIXME make type stable, JT should now be type stable if rest works.

src/entities/HypoRecipe.jl

@@ -0,0 +1,21 @@
+
+
+
+Base.@kwdef struct HypoRecipe
+  certainidx::Vector{Int}
+  allelements::Vector{Vector{Int}}
+  activehypo::Vector{Tuple{Int,Vector{Int}}}
+  mhidx::Vector{Int}
+end
+
+Base.@kwdef struct HypoRecipeCompute{
+  HP <: Union{Nothing, <:Distributions.Categorical{Float64, <:AbstractVector{Float64}}},
+  CH <: Union{Nothing, <:AbstractVector{<:Integer}},
+}
+  """ multi hypothesis settings #NOTE no need for a parameter as type is known from `parseusermultihypo` """
+  hypotheses::HP = nothing
+  """ categorical to select which hypothesis is being considered during convolution operation """
+  certainhypo::CH = nothing
+  """ subsection indices to select which params should be used for this hypothesis evaluation """
+  activehypo::Vector{Int} = Int[]
+end

src/services/CalcFactor.jl

@@ -436,8 +436,10 @@ function _createCCW(
     partial,
     nullhypo = float(nullhypo),
     inflation = float(inflation),
-    hypotheses = multihypo,
-    certainhypo,
+    hyporecipe = HypoRecipeCompute(;
+      hypotheses = multihypo,
+      certainhypo,
+    ),
     measurement,
     _gradients,
   )

src/services/ExplicitDiscreteMarginalizations.jl

@@ -23,12 +23,7 @@ function getHypothesesVectors(
   return (allmhp, certainidx, uncertnidx)
 end
 
-Base.@kwdef struct HypoRecipe
-  certainidx::Vector{Int}
-  allelements::Vector{Vector{Int}}
-  activehypo::Vector{Tuple{Int,Vector{Int}}}
-  mhidx::Vector{Int}
-end
+
 
 """
     $(SIGNATURES)

src/services/FactorGraph.jl

@@ -725,7 +725,7 @@ function getDefaultFactorData(
 
   # allocate temporary state for convolutional operations (not stored)
   userCache = preambleCache(dfg, Xi, usrfnc)
-  ccw = _createCCW(
+  ccwl = _createCCW(
     Xi,
     usrfnc;
     multihypo = mhcat,
@@ -737,11 +737,11 @@ function getDefaultFactorData(
   )
 
   # and the factor data itself
-  return FunctionNodeData{typeof(ccw)}(
+  return FunctionNodeData{typeof(ccwl)}(
     eliminated,
     potentialused,
     edgeIDs,
-    ccw,
+    ccwl,
     multihypo,
     ccw.certainhypo,
     nullhypo,

src/services/NumericalCalculations.jl

@@ -349,7 +349,7 @@ function _buildCalcFactorLambdaSample(
   # DevNotes, also see new `hyporecipe` approach (towards consolidation CCW CPT FMd CF...)
 
   # build a view to the decision variable memory
-  varValsHypo = ccwl.varValsAll[ccwl.activehypo]
+  varValsHypo = ccwl.varValsAll[ccwl.hyporecipe.activehypo]
   # tup = tuple(varParams...)
   # nms = keys(ccwl.varValsAll)[cpt_.activehypo]
   # varValsHypo = NamedTuple{nms,typeof(tup)}(tup)
@@ -364,7 +364,7 @@ function _buildCalcFactorLambdaSample(
   #                         fmd_.cachedata  )
   #
   # get the operational CalcFactor object
-  cf = _buildCalcFactor(ccwl, smpid, varValsHypo, ccwl.activehypo)
+  cf = _buildCalcFactor(ccwl, smpid, varValsHypo, ccwl.hyporecipe.activehypo)
   # new dev work on CalcFactor
   # cf = CalcFactor(ccwl.usrfnc!, _fmd_, smpid, 
   #                 varValsHypo)