Merge branch 'master' into 23Q2/test/restore3alttests

Author: dehann

NEWS.md

@@ -1,4 +1,4 @@
-# Additional NEWS on IncrementalInference.jl Releases
+# NEWS on IncrementalInference.jl Releases
 
 Currently general maintenance and bug fix changes are mostly tracked via Github Integrations.  E.g. see Milestones along with Label filters to quickly find specific issues.
 - https://github.com/JuliaRobotics/IncrementalInference.jl/milestones?state=closed
@@ -13,8 +13,11 @@ The list below highlights breaking changes according to normal semver workflow -
 
 # Changes in v0.34
 
-- Start transition to Manopt.jl via Riemannian Levenberg Marquart.
+- Start transition to Manopt.jl via Riemannian Levenberg-Marquart.
 - Deprecate `AbstractRelativeRoots`.
+- Standardization improvements surrounding weakdeps code extensions. 
+- Code quality improvements along wiht refactoring and reorganizing of file names and locations.
+- Restoring `DERelative` factors, although further fixes necessary beyond anticipated patch release v0.34.1.
 
 # Changes in v0.33
 

Project.toml

@@ -2,7 +2,7 @@ name = "IncrementalInference"
 uuid = "904591bb-b899-562f-9e6f-b8df64c7d480"
 keywords = ["MM-iSAMv2", "Bayes tree", "junction tree", "Bayes network", "variable elimination", "graphical models", "SLAM", "inference", "sum-product", "belief-propagation"]
 desc = "Implements the Multimodal-iSAMv2 algorithm."
-version = "0.34.0"
+version = "0.34.1"
 
 [deps]
 ApproxManifoldProducts = "9bbbb610-88a1-53cd-9763-118ce10c1f89"
@@ -37,7 +37,6 @@ ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
-Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 SparseDiffTools = "47a9eef4-7e08-11e9-0b38-333d64bd3804"
 StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
@@ -50,25 +49,29 @@ TimeZones = "f269a46b-ccf7-5d73-abea-4c690281aa53"
 UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 
 [weakdeps]
+AMD = "14f7f29c-3bd6-536c-9a0b-7339e30b5a3e"
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
+Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 Gadfly = "c91e804a-d5a3-530f-b6f0-dfbca275c004"
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
 
 [extensions]
-DiffEqFactorExt = "DifferentialEquations"
-GadflyExt = "Gadfly"
-InteractiveUtilsExt = "InteractiveUtils"
-InterpolationsExt = "Interpolations"
+IncrInfrApproxMinDegreeExt = "AMD"
+IncrInfrDiffEqFactorExt = "DifferentialEquations"
+IncrInfrFluxFactorsExt = "Flux"
+IncrInfrGadflyExt = "Gadfly"
+IncrInfrInteractiveUtilsExt = "InteractiveUtils"
+IncrInfrInterpolationsExt = "Interpolations"
 
 [compat]
-ApproxManifoldProducts = "0.7"
+ApproxManifoldProducts = "0.7, 0.8"
 BSON = "0.2, 0.3"
 BlockArrays = "0.16"
 Combinatorics = "1.0"
 DataStructures = "0.16, 0.17, 0.18"
 DelimitedFiles = "1"
-DistributedFactorGraphs = "0.21, 0.22"
+DistributedFactorGraphs = "0.23"
 Distributions = "0.24, 0.25"
 DocStringExtensions = "0.8, 0.9"
 FileIO = "1"
@@ -88,17 +91,16 @@ PrecompileTools = "1"
 ProgressMeter = "1"
 RecursiveArrayTools = "2.31.1"
 Reexport = "1"
-Requires = "1"
 SparseDiffTools = "2"
 StaticArrays = "1"
 StatsBase = "0.32, 0.33, 0.34"
 StructTypes = "1"
 TensorCast = "0.3.3, 0.4"
 TimeZones = "1.3.1"
-julia = "1.8"
+julia = "1.9"
 
 [extras]
-Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
+AMD = "14f7f29c-3bd6-536c-9a0b-7339e30b5a3e"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 LineSearches = "d3d80556-e9d4-5f37-9878-2ab0fcc64255"
 Manopt = "0fc0a36d-df90-57f3-8f93-d78a9fc72bb5"
@@ -108,4 +110,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["DifferentialEquations", "Flux", "Graphs", "Manopt", "InteractiveUtils", "Interpolations", "LineSearches", "Pkg", "Rotations", "Test", "Zygote"]
+test = ["AMD", "DifferentialEquations", "Flux", "Graphs", "Manopt", "InteractiveUtils", "Interpolations", "LineSearches", "Pkg", "Rotations", "Test", "Zygote"]

src/services/ccolamd.jl attic/src/ccolamd.jl

@@ -2,9 +2,6 @@
 
 # @info "IncrementalInference is adding Flux/BSON serialization functionality."
 
-using Base64
-
-import Base: convert
 
 function _serializeFluxModelBase64(model::Flux.Chain)
   io = IOBuffer()

src/Serialization/services/FluxModelsSerialization.jl ext/FluxModelsSerialization.jl

@@ -1,5 +1,110 @@
 # heatmap sampler (experimental)
 
+
+(hmd::HeatmapGridDensity)(w...; kw...) = hmd.densityFnc(w...; kw...)
+
+function sampleTangent(M::AbstractManifold, hms::HeatmapGridDensity)
+  return sampleTangent(M, hms.densityFnc)
+end
+
+function Base.show(io::IO, x::HeatmapGridDensity{T, H, B}) where {T, H, B}
+  printstyled(io, "HeatmapGridDensity{"; bold = true, color = :blue)
+  println(io)
+  printstyled(io, "    T"; color = :magenta, bold = true)
+  println(io, "      = ", T)
+  printstyled(io, "    H"; color = :magenta, bold = true)
+  println(io, "`int  = ", H)
+  printstyled(io, "    B"; color = :magenta, bold = true)
+  println(io, "      = ", B)
+  printstyled(io, " }"; color = :blue, bold = true)
+  println(io, "(")
+  println(io, "  data:       ", size(x.data))
+  println(
+    io,
+    "    min/max:    ",
+    round(minimum(x.data); digits = 5),
+    " / ",
+    round(maximum(x.data); digits = 5),
+  )
+  println(io, "  domain:     ", size(x.domain[1]), ", ", size(x.domain[2]))
+  println(
+    io,
+    "    min/max:    ",
+    round(minimum(x.domain[1]); digits = 5),
+    " / ",
+    round(maximum(x.domain[1]); digits = 5),
+  )
+  println(
+    io,
+    "    min/max:    ",
+    round(minimum(x.domain[2]); digits = 5),
+    " / ",
+    round(maximum(x.domain[2]); digits = 5),
+  )
+  println(io, "  bw_factor:  ", x.bw_factor)
+  print(io, "  ")
+  show(io, x.densityFnc)
+  return nothing
+end
+
+Base.show(io::IO, ::MIME"text/plain", x::HeatmapGridDensity) = show(io, x)
+Base.show(io::IO, ::MIME"application/prs.juno.inline", x::HeatmapGridDensity) = show(io, x)
+
+"""
+    $SIGNATURES
+
+Internal function for updating HGD.  
+  
+Notes
+- Likely to be used for [unstashing packed factors](@ref section_stash_unstash) via [`preambleCache`](@ref).
+- Counterpart to `AMP._update!` function for stashing of either MKD or HGD.
+"""
+function _update!(
+  dst::HeatmapGridDensity{T, H, B},
+  src::HeatmapGridDensity{T, H, B},
+) where {T, H, B}
+  @assert size(dst.data) == size(src.data) "Updating HeatmapDensityGrid can only be done for data of the same size"
+  dst.data .= src.data
+  if !isapprox(dst.domain[1], src.domain[1])
+    dst.domain[1] .= src.domain[1]
+  end
+  if !isapprox(dst.domain[2], src.domain[2])
+    dst.domain[2] .= src.domain[2]
+  end
+  AMP._update!(dst.densityFnc, src.densityFnc)
+  return dst
+end
+
+
+##
+
+(lsg::LevelSetGridNormal)(w...; kw...) = lsg.densityFnc(w...; kw...)
+
+function sampleTangent(M::AbstractManifold, lsg::LevelSetGridNormal)
+  return sampleTangent(M, lsg.heatmap.densityFnc)
+end
+
+function Base.show(io::IO, x::LevelSetGridNormal{T, H}) where {T, H}
+  printstyled(io, "LevelSetGridNormal{"; bold = true, color = :blue)
+  println(io)
+  printstyled(io, "    T"; color = :magenta, bold = true)
+  println(io, "      = ", T)
+  printstyled(io, "    H"; color = :magenta, bold = true)
+  println(io, "`int  = ", H)
+  printstyled(io, " }"; color = :blue, bold = true)
+  println(io, "(")
+  println(io, "  level:      ", x.level)
+  println(io, "  sigma:      ", x.sigma)
+  println(io, "  sig.scale:  ", x.sigma_scale)
+  println(io, "  heatmap:    ")
+  show(io, x.heatmap)
+  return nothing
+end
+
+Base.show(io::IO, ::MIME"text/plain", x::LevelSetGridNormal) = show(io, x)
+Base.show(io::IO, ::MIME"application/prs.juno.inline", x::LevelSetGridNormal) = show(io, x)
+
+
 ##
 
 getManifold(hgd::HeatmapGridDensity) = getManifold(hgd.densityFnc)

ext/HeatmapSampler.jl

@@ -0,0 +1,100 @@
+module IncrInfrApproxMinDegreeExt
+
+using AMD
+import IncrementalInference: _ccolamd, _ccolamd!
+
+# elseif ordering == :ccolamd
+#   cons = zeros(SuiteSparse_long, length(adjMat.colptr) - 1)
+#   cons[findall(x -> x in constraints, permuteds)] .= 1
+#   p = Ccolamd.ccolamd(adjMat, cons)
+#   @warn "Ccolamd is experimental in IIF at this point in time."
+
+const KNOBS = 20
+const STATS = 20
+
+
+
+function _ccolamd!(
+  n_row, #SuiteSparse_long,
+  A::AbstractVector{T}, # SuiteSparse_long},
+  p::AbstractVector, # SuiteSparse_long},
+  knobs::Union{Ptr{Nothing}, Vector{Float64}},
+  stats::AbstractVector, #{SuiteSparse_long},
+  cmember::Union{Ptr{Nothing}, <:AbstractVector}, #{SuiteSparse_long}},
+) where T
+  n_col = length(p) - 1
+
+  if length(stats) != STATS
+    error("stats must hcae length $STATS")
+  end
+  if isa(cmember, Vector) && length(cmember) != n_col
+    error("cmember must have length $n_col")
+  end
+
+  Alen = AMD.ccolamd_l_recommended(length(A), n_row, n_col)
+  resize!(A, Alen)
+
+  for i in eachindex(A)
+    A[i] -= 1
+  end
+  for i in eachindex(p)
+    p[i] -= 1
+  end
+  err = AMD.ccolamd_l( # ccolamd_l
+    n_row,
+    n_col,
+    Alen,
+    A,
+    p,
+    knobs,
+    stats,
+    cmember
+  )
+
+  if err == 0
+    AMD.ccolamd_l_report(stats)
+    error("call to ccolamd return with error code $(stats[4])")
+  end
+
+  for i in eachindex(p)
+    p[i] += 1
+  end
+
+  pop!(p) # remove last zero from pivoting vector
+  return p
+end
+
+function _ccolamd!(
+  n_row,
+  A::AbstractVector{T1}, #SuiteSparse_long},
+  p::AbstractVector{<:Real}, # {SuiteSparse_long},
+  cmember::Union{Ptr{Nothing}, <:AbstractVector{T}}, # SuiteSparse_long
+) where {T1<:Real, T}
+  n_col = length(p) - 1
+
+  if length(cmember) != n_col
+    error("cmember must have length $n_col")
+  end
+
+  Alen = AMD.ccolamd_l_recommended(length(A), n_row, n_col)
+  resize!(A, Alen)
+  stats = zeros(T1, STATS)
+  return _ccolamd!(n_row, A, p, C_NULL, stats, cmember)
+end
+
+# function _ccolamd!(
+#   n_row,
+#   A::AbstractVector{T}, # ::Vector{SuiteSparse_long},
+#   p::AbstractVector, # ::Vector{SuiteSparse_long},
+#   constraints = zeros(T,length(p) - 1), # SuiteSparse_long, 
+# ) where T
+#   n_col = length(p) - 1
+#   return _ccolamd!(n_row, A, p, constraints)
+# end
+
+_ccolamd(n_row,A,p,constraints) = _ccolamd!(n_row, copy(A), copy(p), constraints)
+_ccolamd(biadjMat, constraints) = _ccolamd(size(biadjMat, 1), biadjMat.rowval, biadjMat.colptr, constraints)
+
+
+
+end