Merge pull request #1810 from JuliaRobotics/master

release v0.35.2-rc1

.github/workflows/ci.yml

@@ -16,7 +16,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.9'
+          - '1.10'
         os:
           - ubuntu-latest
         arch:
@@ -54,7 +54,7 @@ jobs:
         arch: 
           - x64
         version:
-          - '~1.10.0-0'
+          - '1.10'
         group:
           - 'basic_functional_group'
     steps:
@@ -96,7 +96,7 @@ jobs:
         arch: 
           - x64
         version:
-          - '~1.10.0-0'
+          - '1.10'
         group:
           - 'test_cases_group'
     steps:
@@ -139,7 +139,7 @@ jobs:
         os:
           - ubuntu-latest
         version:
-          - '1.9'
+          - '1.10'
         arch:
           - x64
         group:

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 = "0.35.1"
+version = "0.35.2"
 
 [deps]
 ApproxManifoldProducts = "9bbbb610-88a1-53cd-9763-118ce10c1f89"
@@ -87,7 +87,7 @@ Optim = "1"
 OrderedCollections = "1"
 PrecompileTools = "1"
 ProgressMeter = "1"
-RecursiveArrayTools = "2.31.1"
+RecursiveArrayTools = "2.31.1, 3"
 Reexport = "1"
 SparseDiffTools = "2"
 StaticArrays = "1"

ext/HeatmapSampler.jl

@@ -124,12 +124,12 @@ function sampleHeatmap(
   roi::AbstractMatrix{<:Real},
   x_grid::AbstractVector{<:Real},
   y_grid::AbstractVector{<:Real},
-  thres::Real = 0,
+  thres::Real = 1e-14,
 )
   #
 
   # mask the region of interest above the sampling threshold value
-  mask = thres .<= roi
+  mask = thres .< roi
 
   idx2d = findall(mask)  # 2D indices
   pos = (v -> [x_grid[v[1]], y_grid[v[2]]]).(idx2d)
@@ -235,21 +235,7 @@ function LevelSetGridNormal(
   N::Int = 10000,
 )
   #
-
-  # select the support from raw data
-  roi = data .- level
-  # make Gaussian
-  roi .^= 2
-  roi .*= 0.5 / (sigma^2)
-  roi .-= sigma_scale^2
-  roi .*= -1
-  # truncate sigma_scale*sigma below zero
-  #   h = heatmap;  z = measurement
-  #   l = 1/2 (h-z/σ)^2
-  #   masked_roi = 0 .< κ^2 - l
-
   hgd = HeatmapGridDensity(data, domain, hint_callback, bw_factor; N = N)
-
   return LevelSetGridNormal(level, sigma, float(sigma_scale), hgd)
 end