DFG[Variable/Factor] -> [Variable/Factor]Compute

Author: Affie

IncrementalInference/ext/IncrInfrDiffEqFactorExt.jl

@@ -51,7 +51,7 @@ DevNotes
 - TODO does not handle timezone crossing properly yet.
 """
 function _calcTimespan(
-  Xi::AbstractVector{<:DFGVariable}
+  Xi::AbstractVector{<:VariableCompute}
 )
   #
   tsmps = getTimestamp.(Xi[1:2]) .|> DateTime .|> datetime2unix
@@ -60,13 +60,13 @@ function _calcTimespan(
 end
 # Notes
 # - Can change numerical data return type using an additional first argument, `_calcTimespan(Float32, Xi)`.
-# _calcTimespan(Xi::AbstractVector{<:DFGVariable}) = _calcTimespan(Float64, Xi)
+# _calcTimespan(Xi::AbstractVector{<:VariableCompute}) = _calcTimespan(Float64, Xi)
 
 # performance helper function, FIXME not compatible with all multihypo cases
 _maketuplebeyond2args = (w1 = nothing, w2 = nothing, w3_...) -> (w3_...,)
 
 function DERelative(
-  Xi::AbstractVector{<:DFGVariable},
+  Xi::AbstractVector{<:VariableCompute},
   domain::Type{<:VariableStateType},
   f::Function,
   data = () -> ();
@@ -97,7 +97,7 @@ function DERelative(
   domain::Type{<:VariableStateType},
   f::Function,
   data = () -> ();
-  Xi::AbstractArray{<:DFGVariable} = getVariable.(dfg, labels),
+  Xi::AbstractArray{<:VariableCompute} = getVariable.(dfg, labels),
   dt::Real = 1,
   state1::AbstractVector{<:Real} = allocate(getPointIdentity(domain)), #zeros(getDimension(domain)),
   state0::AbstractVector{<:Real} = allocate(getPointIdentity(domain)), #zeros(getDimension(domain)),

IncrementalInference/src/ExportAPI.jl

@@ -29,9 +29,9 @@ export AbstractDFG,
   addData!,
   addBlob!,
   getData,
-  DFGVariable,
+  VariableCompute,
   DFGVariableSummary,
-  DFGFactor,
+  FactorCompute,
   DFGFactorSummary,
   deleteVariableSolverData!
 # listDataBlobs  # ERROR: LightDFG{} doesn't override 'listDataBlobs'.

IncrementalInference/src/IncrementalInference.jl

@@ -73,7 +73,6 @@ import DistributedFactorGraphs: compare
 import DistributedFactorGraphs: rebuildFactorCache!
 import DistributedFactorGraphs: getDimension, getManifold, getPointType, getPointIdentity
 import DistributedFactorGraphs: getPPE, getPPEDict
-import DistributedFactorGraphs: getFactorOperationalMemoryType
 import DistributedFactorGraphs: getPoint, getCoordinates
 import DistributedFactorGraphs: getVariableType
 import DistributedFactorGraphs: AbstractPointParametricEst, loadDFG

IncrementalInference/src/Serialization/services/DispatchPackedConversions.jl

@@ -94,8 +94,8 @@ Dev Notes:
 - TODO: needs testing
 """
 function DFG.rebuildFactorCache!(
-  dfg::AbstractDFG{SolverParams},
-  factor::DFGFactor,
+  dfg::AbstractDFG,
+  factor::FactorCompute,
   neighbors = map(vId -> getVariable(dfg, vId), listNeighbors(dfg, factor));
   _blockRecursionGradients::Bool=false
 )

IncrementalInference/src/entities/BeliefTypes.jl

@@ -86,7 +86,7 @@ function TreeBelief(vnd::VariableNodeData, solvDim::Real = 0)
   )
 end
 
-function TreeBelief(vari::DFGVariable, solveKey::Symbol = :default; solvableDim::Real = 0)
+function TreeBelief(vari::VariableCompute, solveKey::Symbol = :default; solvableDim::Real = 0)
   return TreeBelief(getVariableState(vari, solveKey), solvableDim)
 end
 #

IncrementalInference/src/entities/CalcFactor.jl

@@ -54,7 +54,7 @@ struct CalcFactorNormSq{
   ## TODO Consolidation WIP with FactorMetadata
   # full list of variables connected to the factor
   # TODO make sure this list is of the active hypo only
-  fullvariables::VT # Vector{<:DFGVariable} # FIXME change to tuple for better type stability
+  fullvariables::VT # Vector{<:VariableCompute} # FIXME change to tuple for better type stability
   # which index is being solved for?
   solvefor::Int
   manifold::M

IncrementalInference/src/entities/FactorGradients.jl

@@ -59,7 +59,7 @@ Related
 [`calcFactorResidualTemporary`](@ref), [`_buildGraphByFactorAndTypes`](@ref)
 """
 mutable struct FactorGradientsCached!{F <: AbstractRelative, S, M, P, G, L}
-  dfgfct::DFGFactor{F}
+  dfgfct::FactorCompute{F}
   # cached jacobian matrix of gradients
   cached_gradients::Matrix{Float64}
   # likely <:AbstractVector, while CalcFactor residuals are vectors in Rn but could change to Tangent vectors

IncrementalInference/src/parametric/services/ConsolidateParametricRelatives.jl

@@ -20,7 +20,7 @@ Related: [`getMeasurementParametric`](@ref), [`approxConvBelief`](@ref), [`Mutab
 """
 function solveFactorParametric(
   dfg::AbstractDFG,
-  fct::DFGFactor,
+  fct::FactorCompute,
   # currval::P1,
   srcsym_vals::AbstractVector{Pair{Symbol, P}},
   trgsym::Symbol;
@@ -44,7 +44,7 @@ function solveFactorParametric(
   measT = [mea_]
 
   # get variable points
-  function _getParametric(vari::DFGVariable, key = :default)
+  function _getParametric(vari::VariableCompute, key = :default)
     # hasp = haskey(getPPEDict(vari), key)
     # FIXME use PPE via Manifold points currently in coordinates
     # hasp ? getPPE(vari, key).suggested : calcMean(getBelief(vari, key))

IncrementalInference/src/parametric/services/ParametricCSMFunctions.jl

@@ -12,7 +12,7 @@ function solveUp_ParametricStateMachine(csmc::CliqStateMachineContainer)
   # csmc.drawtree ? drawTree(csmc.tree, show=false, filepath=joinpath(getSolverParams(csmc.dfg).logpath,"bt.pdf")) : nothing
 
   #TODO maybe change to symbols
-  msgfcts = DFGFactor[]
+  msgfcts = FactorCompute[]
   # LITTLE WEIRD get previously set up msgs (stored in this clique)
   # FIXME, fetch message buffered in channels
   # see #855

IncrementalInference/src/parametric/services/ParametricManopt.jl

@@ -18,7 +18,7 @@ end
 
 function CalcFactorResidual(
   fg, 
-  fct::DFGFactor, 
+  fct::FactorCompute, 
   varIntLabel
 )
   fac_func = getFactorType(fct)
@@ -520,7 +520,7 @@ end
 
 function autoinitParametric!(
   dfg::AbstractDFG,
-  xi::DFGVariable;
+  xi::VariableCompute;
   solveKey = :parametric,
   reinit::Bool = false,
   perturb_point::Bool=false,