Move some deprecated code and update some deprecated DFG functions: (#1881)

* Move some deprecated code and update some deprecated DFG functions:
AbstractRelative, AbstractFactor, AbstractPrior, VariableNodeData, AbstractPackedFactor, VariableNodeData, @defVariable,

Author: Affie

IncrementalInference/ext/IncrInfrDiffEqFactorExt.jl

@@ -158,7 +158,7 @@ function _solveFactorODE!(
   return sol
 end
 
-# # # output for AbstractRelative is tangents (but currently we working in coordinates for integration with DiffEqs)
+# # # output for AbstractRelativeObservation is tangents (but currently we working in coordinates for integration with DiffEqs)
 # # # FIXME, how to consolidate DERelative with parametric solve which currently only goes through getMeasurementParametric
 # function getSample(cf::CalcFactor{<:DERelative})
 #   #

IncrementalInference/ext/IncrInfrFluxFactorsExt.jl

@@ -138,7 +138,7 @@ Related
 Mixture, FluxModelsDistribution
 """
 function MixtureFluxModels(
-  F_::AbstractFactor,
+  F_::AbstractObservation,
   nnModels::Vector{P},
   inDim::NTuple{ID, Int},
   data::D,
@@ -174,7 +174,7 @@ function MixtureFluxModels(
   return Mixture(F_, ntup, diversity)
 end
 
-function MixtureFluxModels(::Type{F}, w...; kw...) where {F <: AbstractFactor}
+function MixtureFluxModels(::Type{F}, w...; kw...) where {F <: AbstractObservation}
   return MixtureFluxModels(F(LinearAlgebra.I), w...; kw...)
 end
 

IncrementalInference/ext/IncrInfrInteractiveUtilsExt.jl

@@ -4,7 +4,7 @@ module IncrInfrInteractiveUtilsExt
 
 using InteractiveUtils
 using DocStringExtensions
-using IncrementalInference: StateType, AbstractPrior, RelativeObservation
+using IncrementalInference: StateType, AbstractPriorObservation, RelativeObservation
 # using IncrementalInference: getCurrentWorkspaceFactors, getCurrentWorkspaceVariables, listTypeTree
 import IncrementalInference: getCurrentWorkspaceFactors, getCurrentWorkspaceVariables, listTypeTree
 
@@ -18,7 +18,7 @@ Return all factors currently registered in the workspace.
 """
 function getCurrentWorkspaceFactors()
   return [
-    InteractiveUtils.subtypes(AbstractPrior)...,
+    InteractiveUtils.subtypes(AbstractPriorObservation)...,
     InteractiveUtils.subtypes(RelativeObservation)...,
   ]
 end

IncrementalInference/src/Deprecated.jl

@@ -50,6 +50,107 @@ function addBayesNetVerts!(dfg::AbstractDFG, elimOrder::Array{Symbol, 1})
   end
 end
 
+## packing converters-----------------------------------------------------------
+# heavy use of multiple dispatch for converting between packed and original data types during DB usage
+
+function convert(
+  ::Type{DFG.PackedFunctionNodeData{P}},
+  d::DFG.FunctionNodeData{T},
+) where {P <: AbstractPackedObservation, T <: FactorCache}
+  error("TODO remove. PackedFunctionNodeData is obsolete")
+  return DFG.PackedFunctionNodeData(
+    d.eliminated,
+    d.potentialused,
+    d.edgeIDs,
+    convert(P, _getCCW(d).usrfnc!),
+    d.multihypo,
+    _getCCW(d).hyporecipe.certainhypo,
+    d.nullhypo,
+    d.solveInProgress,
+    d.inflation,
+  )  # extract two values from ccw for storage -- ccw thrown away
+end
+
+## unpack converters------------------------------------------------------------
+# see #1424
+#TODO Consolidate: this looks alot like `getDefaultFactorData`
+function DFG.reconstFactorData(
+  dfg::AbstractDFG,
+  varOrder::AbstractVector{Symbol},
+  ::Type{<:DFG.GenericFunctionNodeData{<:CommonConvWrapper{F}}},
+  packed::DFG.GenericFunctionNodeData{<:AbstractPackedObservation},
+) where {F <: AbstractObservation}
+
+  error("TODO remove. Obsolete: use `DFG.rebuildFactorCache!` and getDefaultFactorData instead.")
+  #
+  # TODO store threadmodel=MutliThreaded,SingleThreaded in persistence layer
+  usrfnc = convert(F, packed.fnc)
+  multihypo, nullhypo = parseusermultihypo(packed.multihypo, packed.nullhypo)
+
+  # IIF #1424
+  vars = map(f -> getVariable(dfg, f), varOrder)
+  userCache = preambleCache(dfg, vars, usrfnc)
+
+  # TODO -- improve _createCCW for hypotheses and certainhypo field recovery when deserializing
+  # reconstitute from stored data
+  # FIXME, add threadmodel=threadmodel
+  # FIXME https://github.com/JuliaRobotics/DistributedFactorGraphs.jl/issues/590#issuecomment-776838053
+  # FIXME dont know what manifolds to use in ccw
+  ccw = _createCCW(
+    vars,
+    usrfnc;
+    multihypo,
+    nullhypo,
+    certainhypo = packed.certainhypo,
+    inflation = packed.inflation,
+    userCache,
+    attemptGradients = getSolverParams(dfg).attemptGradients,
+    # Block recursion if NoSolverParams or if set to not attempt gradients.
+    _blockRecursion=
+      getSolverParams(dfg) isa NoSolverParams || 
+      !getSolverParams(dfg).attemptGradients,
+  )
+  #
+
+  # CommonConvWrapper{typeof(usrfnc)}
+  ret = DFG.FunctionNodeData{typeof(ccw)}(
+    packed.eliminated,
+    packed.potentialused,
+    packed.edgeIDs,
+    ccw,
+    packed.multihypo,
+    packed.certainhypo,
+    packed.nullhypo,
+    packed.solveInProgress,
+    packed.inflation,
+  )
+  #
+  return ret
+end
+
+function _getDimensionsPartial(data::DFG.GenericFunctionNodeData)
+  Base.depwarn(
+    "_getDimensionsPartial(data::GenericFunctionNodeData) is deprecated, use solvercache <: FactorCache instead",
+    :_getDimensionsPartial,
+  ) 
+  return _getCCW(data) |> _getDimensionsPartial
+end
+
+"""
+    $SIGNATURES
+Get the CommonConvWrapper for this factor.
+"""
+function _getCCW(gfnd::DFG.GenericFunctionNodeData)
+  error("_getCCW(gfnd::DFG.GenericFunctionNodeData) is deprecated, use DFG.getCache instead.")
+end
+
+_getZDim(fcd::DFG.GenericFunctionNodeData) = _getCCW(fcd) |> _getZDim
+DFG.getDimension(fct::DFG.GenericFunctionNodeData) = _getZDim(fct)
+
+function resetData!(vdata::DFG.FunctionNodeData)
+  error("resetData!(vdata::FunctionNodeData) is deprecated, use resetData!(state::FactorState) instead")
+end
+
 ## ================================================================================================
 ## ================================================================================================
 

IncrementalInference/src/ExportAPI.jl

@@ -36,8 +36,8 @@ export AbstractDFG,
 # listDataBlobs  # ERROR: LightDFG{} doesn't override 'listDataBlobs'.
 
 # Inference types
-export AbstractPackedFactor, AbstractFactor
-export AbstractPrior, AbstractRelative
+export AbstractPackedObservation, AbstractObservation
+export AbstractPriorObservation, AbstractRelativeObservation
 export AbstractRelativeMinimize, AbstractManifoldMinimize
 
 # not sure if this is necessary
@@ -116,8 +116,6 @@ export CSMHistory,
   getTags,
 
   # using either dictionary or cloudgraphs
-  FunctionNodeData,
-  PackedFunctionNodeData, # moved to DFG
   normalfromstring,
   categoricalfromstring,
   # extractdistribution,

IncrementalInference/src/Factors/EuclidDistance.jl

@@ -28,7 +28,7 @@ getDimension(::InstanceType{<:EuclidDistance}) = 1
 $(TYPEDEF)
 Serialization type for `EuclidDistance` binary factor.
 """
-Base.@kwdef mutable struct PackedEuclidDistance <: AbstractPackedFactor
+Base.@kwdef mutable struct PackedEuclidDistance <: AbstractPackedObservation
   _type::String
   Z::PackedBelief
 end

IncrementalInference/src/Factors/GenericFunctions.jl

@@ -153,7 +153,7 @@ export ManifoldPrior, PackedManifoldPrior
 # `p` is a point on manifold `M`
 # `Z` is a measurement at the tangent space of `p` on manifold `M` 
 struct ManifoldPrior{M <: AbstractManifold, T <: SamplableBelief, P, B <: AbstractBasis} <:
-       AbstractPrior
+       AbstractPriorObservation
   M::M
   p::P #NOTE This is a fixed point from where the measurement `Z` is made in coordinates on tangent TpM
   Z::T
@@ -226,14 +226,14 @@ function mahalanobus_distance2(M, X, inv_Σ)
   return Xc' * inv_Σ * Xc
 end
 
-Base.@kwdef mutable struct PackedManifoldPrior <: AbstractPackedFactor
+Base.@kwdef mutable struct PackedManifoldPrior <: AbstractPackedObservation
   varType::String
   p::Vector{Float64}  #NOTE This is a fixed point from where the measurement `Z` likely stored as a coordinate
   Z::PackedBelief
 end
 
 function convert(
-  ::Union{Type{<:AbstractPackedFactor}, Type{<:PackedManifoldPrior}},
+  ::Union{Type{<:AbstractPackedObservation}, Type{<:PackedManifoldPrior}},
   obj::ManifoldPrior,
 )
   #
@@ -249,7 +249,7 @@ function convert(
 end
 
 function convert(
-  ::Union{Type{<:AbstractFactor}, Type{<:ManifoldPrior}},
+  ::Union{Type{<:AbstractObservation}, Type{<:ManifoldPrior}},
   obj::PackedManifoldPrior,
 )
   #
@@ -286,7 +286,7 @@ function samplePointPartial(
 end
 
 struct ManifoldPriorPartial{M <: AbstractManifold, T <: SamplableBelief, P <: Tuple} <:
-       AbstractPrior
+       AbstractPriorObservation
   M::M
   Z::T
   partial::P

IncrementalInference/src/Factors/GenericMarginal.jl

@@ -15,7 +15,7 @@ getManifold(::GenericMarginal) = LieGroups.TranslationGroup(1)
 
 getSample(::CalcFactor{<:GenericMarginal}) = [0]
 
-Base.@kwdef mutable struct PackedGenericMarginal <: AbstractPackedFactor
+Base.@kwdef mutable struct PackedGenericMarginal <: AbstractPackedObservation
   Zij::Array{Float64, 1}
   Cov::Array{Float64, 1}
   W::Array{Float64, 1}

IncrementalInference/src/Factors/LinearRelative.jl

@@ -59,7 +59,7 @@ end
 $(TYPEDEF)
 Serialization type for `LinearRelative` binary factor.
 """
-Base.@kwdef mutable struct PackedLinearRelative <: AbstractPackedFactor
+Base.@kwdef mutable struct PackedLinearRelative <: AbstractPackedObservation
   Z::PackedBelief
 end
 function convert(::Type{PackedLinearRelative}, d::LinearRelative)

IncrementalInference/src/Factors/MetaPrior.jl

@@ -1,6 +1,6 @@
 # Meta prior brings additional information not necessarily numerical prior
 
-Base.@kwdef struct MetaPrior{T} <: AbstractPrior
+Base.@kwdef struct MetaPrior{T} <: AbstractPriorObservation
   data::T
   partial::Vector{Int} = Int[]
 end