use DFG.@packed macro and update addVariable!

IncrementalInference/Project.toml

@@ -48,6 +48,7 @@ StructTypes = "856f2bd8-1eba-4b0a-8007-ebc267875bd4"
 SuiteSparse = "4607b0f0-06f3-5cda-b6b1-a6196a1729e9"
 TensorCast = "02d47bb6-7ce6-556a-be16-bb1710789e2b"
 TimeZones = "f269a46b-ccf7-5d73-abea-4c690281aa53"
+TimesDates = "bdfc003b-8df8-5c39-adcd-3a9087f5df4a"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
 [weakdeps]
@@ -108,6 +109,7 @@ StatsBase = "0.32, 0.33, 0.34"
 StructTypes = "1"
 TensorCast = "0.3.3, 0.4"
 TimeZones = "1.3.1"
+TimesDates = "0.3.3"
 julia = "1.10"
 
 [extras]

IncrementalInference/src/ExportAPI.jl

@@ -24,12 +24,12 @@ export AbstractDFG,
   diagm,
   listBlobEntries,
   FolderStore,
-  addBlobStore!,
+  addBlobstore!,
   addData!,
   addBlob!,
   getData,
   VariableCompute,
-  DFGVariableSummary,
+  VariableSummary,
   FactorCompute,
   DFGFactorSummary,
   deleteVariableSolverData!

IncrementalInference/src/Factors/LinearRelative.jl

@@ -11,7 +11,7 @@ X_2 = X_1 + η_Z
 ```
 """
 DFG.@tags struct LinearRelative{N, T <: SamplableBelief} <: RelativeObservation 
-  Z::T & (lower = DFG.Packed, choosetype = DFG.resolvePackedType)
+  Z::T & DFG.@packed
 end
 
 # need several helper constructors since the dimension over which LinearRelative will be used is unknown at this point

IncrementalInference/src/Factors/Mixture.jl

@@ -56,7 +56,7 @@ end
 
 DFG.@tags struct PackedMixture
   components::NamedTuple & (choosetype = obj->NamedTuple{Tuple(Symbol.(keys(obj))), Tuple{DFG.resolveType.(values(obj))...}}, )
-  prior & (lower = DFG.Packed, choosetype = DFG.resolvePackedType)
+  prior & DFG.@packed
 end
 
 function DFG.pack(m::Mixture)

IncrementalInference/src/Factors/PartialPriorPassThrough.jl

@@ -6,7 +6,7 @@ DFG.@tags struct PartialPriorPassThrough{
   B <: Union{<:HeatmapGridDensity, <:LevelSetGridNormal},
   T <: Tuple,
 } <: AbstractPriorObservation
-  Z::B & (lower = DFG.Packed, choosetype = DFG.resolvePackedType)
+  Z::B & DFG.@packed
   partial::T & (choosetype = x->NTuple{length(x), Int},)
 end
 

IncrementalInference/src/IncrementalInference.jl

@@ -79,6 +79,9 @@ using Dates,
   UUIDs,
   TensorCast
 
+using TimesDates: TimeDateZone
+using TimeZones: ZonedDateTime
+
 using StructTypes
 
 using StaticArrays

IncrementalInference/src/services/FactorGraph.jl

@@ -566,61 +566,67 @@ fg = initfg()
 addVariable!(fg, :x0, Pose2)
 ```
 """
-function addVariable!(
+function DFG.addVariable!(
   dfg::AbstractDFG,
   label::Symbol,
-  varTypeU::Union{T, Type{T}};
-  N::Int = getSolverParams(dfg).N,
+  statetype::Union{T, Type{T}};
+  tags::Union{Set{Symbol}, Vector{Symbol}} = Set{Symbol}(),
+  timestamp::Union{TimeDateZone, ZonedDateTime}  = DFG.now_tdz(),
   solvable::Int = 1,
-  timestamp::Union{DateTime, ZonedDateTime} = now(localzone()),
-  nanosecondtime = nothing,
-  # dontmargin::Bool = false,
-  tags::Vector{Symbol} = Symbol[],
-  smalldata = Dict{Symbol, DFG.MetadataTypes}(),
+  # IIF extras
+  N::Int = getSolverParams(dfg).N,
   checkduplicates::Bool = true,
+  # dontmargin::Bool = false,
   initsolvekeys::Vector{Symbol} = getSolverParams(dfg).algorithms,
+
+  #deprecated v0.37
+  smalldata = nothing,
+  nanosecondtime = nothing,
+
+  # default DFG
+  bloblets = DFG.Bloblets(),
+  blobentries = DFG.Blobentries(),
+  kwargs...,  
 ) where {T <: StateType}
 
   if !isnothing(nanosecondtime)
-    Base.depwarn(
-      "nanosecondtime kwarg is deprecated, use `timestamp` instead",
-      :addVariable!,
-    )
+    error("nanosecondtime kwarg is deprecated, use `timestamp` instead")
   end
 
-  varType = _variableType(varTypeU)
-
-  _zonedtime(s::DateTime) = ZonedDateTime(s, localzone())
-  _zonedtime(s::ZonedDateTime) = s 
+  if !isnothing(smalldata)
+    error("smalldata kwarg is deprecated, use `bloblets` instead")
+  end
 
-  union!(tags, [:VARIABLE])
-  v = VariableCompute(
+  tags = union(Set(tags), [:VARIABLE])
+  v = VariableDFG(
     label,
-    varType;
-    tags = Set(tags),
-    bloblets = smalldata,
-    solvable = solvable,
-    timestamp = _zonedtime(timestamp),
+    statetype;
+    tags,
+    bloblets,
+    blobentries,
+    solvable,
+    timestamp,
+    kwargs...,
   )
 
   (:default in initsolvekeys) && setDefaultNodeData!(
     v,
     0,
     N;
     initialized = false,
-    varType = varType,
+    varType = T(),
     # dontmargin = dontmargin,
   ) # dodims
 
   (:parametric in initsolvekeys) &&
     setDefaultNodeDataParametric!(
       v,
-      varType;
+      T();
       initialized = false,
       # dontmargin = dontmargin
     )
 
-  return DFG.addVariable!(dfg, v)
+  return addVariable!(dfg, v)
 end
 
 function parseusermultihypo(multihypo::Nothing, nullhypo::Float64)

IncrementalInference/src/services/SolverUtilities.jl

@@ -198,7 +198,7 @@ end
 Check if a variable might already be located at the test location, by means of a (default) `refKey=:simulated` PPE stored in the existing variables.
 
 Notes
-- Checks, using provided `factor` from `srcLabel` in `fg` to an assumed `dest` variable whcih may or may not yet exist.
+- Checks, using provided `factor` from `srcLabel` in `fg` to an assumed `dest` variable which may or may not yet exist.
 - This function was written to aid in building simulation code, 
   - it's use in real world usage may have unexpected behaviour -- hence not exported.
 - Return `::Tuple{Bool, Vector{Float64}, Symbol}`, eg. already exists `(true, [refVal], :l17)`, or if a refernce variable does not yet `(false, [refVal], :l28)`.

IncrementalInferenceTypes/src/factors/LinearRelative.jl

@@ -9,7 +9,7 @@ X_2 = X_1 + η_Z
 ```
 """
 # @tags struct LinearRelative{T} <: RelativeObservation
-#   Z::T & (lower = DFG.Packed, choosetype = DFG.resolvePackedType)
+#   Z::T & DFG.@packed
 # end
 
 #TODO