v0.4.18-rc1

Project.toml

@@ -1,7 +1,7 @@
 name = "ApproxManifoldProducts"
 uuid = "9bbbb610-88a1-53cd-9763-118ce10c1f89"
 keywords = ["MM-iSAMv2", "SLAM", "inference", "sum-product", "belief-propagation", "nonparametric", "manifolds", "functional"]
-version = "0.4.17"
+version = "0.4.18"
 
 [deps]
 Base64 = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
@@ -37,7 +37,7 @@ Unicode = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
 CoordinateTransformations = "0.5, 0.6"
 DocStringExtensions = "0.7, 0.8, 0.9"
 KernelDensityEstimate = "0.5.9"
-Manifolds = "0.6"
+Manifolds = "0.6, 0.7"
 ManifoldsBase = "0.11, 0.12"
 NLsolve = "3, 4"
 Optim = "1"

README.md

@@ -1,6 +1,6 @@
 # ApproxManifoldProducts.jl
 
-[![Build Status](https://travis-ci.org/JuliaRobotics/ApproxManifoldProducts.jl.svg?branch=master)](https://travis-ci.org/JuliaRobotics/ApproxManifoldProducts.jl)
+[![CI](https://github.com/JuliaRobotics/ApproxManifoldProducts.jl/actions/workflows/ci.yml/badge.svg)](https://github.com/JuliaRobotics/ApproxManifoldProducts.jl/actions/workflows/ci.yml)
 [![codecov.io](https://codecov.io/github/JuliaRobotics/ApproxManifoldProducts.jl/coverage.svg?branch=master)](https://codecov.io/github/JuliaRobotics/ApproxManifoldProducts.jl?branch=master)
 
 

src/KernelHilbertEmbeddings.jl

@@ -5,7 +5,11 @@ export
   mmd!,  # KED
   mmd
 
+"""
+    $SIGNATURES
 
+Normal kernel used for Hilbert space embeddings.
+"""
 ker(M::MB.AbstractManifold, p, q, sigma::Real=0.001) = exp( -sigma*(distance(M, p, q)^2) )
 
 """
@@ -17,37 +21,47 @@ Notes:
 - This is the in-place version (well more in-place than mmd)
 
 DevNotes:
-- TODO make work for different sizes N,M
 - TODO dont assume equally weighted particles
+- TODO profile SIMD vs SLEEF
+- TODO optimize memory
+- TODO make multithreaded
 
-Related
-
-mmd, ker
+See also: [`mmd`](@ref), [`ker`](@ref)
 """
 function mmd!(MF::MB.AbstractManifold,
               val::AbstractVector{<:Real},
               a::AbstractVector,
               b::AbstractVector,
-              N::Int=length(a), M::Int=length(b); 
+              N::Integer=length(a), M::Integer=length(b); 
               bw::AbstractVector{<:Real}=[0.001;] )
   #
   # TODO allow unequal data too
-  @assert N == M "mmd! currently requires input vectors be the same length"
-  val[1] = 0.0
+  _N = 1.0/N
+  _M = 1.0/M
+  _val1 = 0.0
+  _val2 = 0.0
+  _val3 = 0.0
   @inbounds @fastmath for i in 1:N
     @simd for j in 1:M
-      val[1] -= ker(MF, a[i], b[j], bw[1])
+      _val1 -= ker(MF, a[i], b[j], bw[1])
     end
   end
-  val .*= 2.0
+  _val1 *= 2.0*_N*_M
   @inbounds @fastmath for i in 1:N
+    @simd for j in 1:N
+      _val2 += ker(MF, a[i], a[j], bw[1])
+    end
+  end
+  _val2 *= (_N*_N)
+  @inbounds @fastmath for i in 1:M
     @simd for j in 1:M
-      val[1] += ker(MF, a[i], a[j], bw[1])
-      val[1] += ker(MF, b[i], b[j], bw[1])
+      _val3 += ker(MF, b[i], b[j], bw[1])
     end
   end
-  val ./= N
-  val ./= M
+  _val3 *= (_M*_M)
+
+  # accumulate all terms
+  val[1] = _val1 + _val2 + _val3
   return val
 end
 

src/services/ManifoldKernelDensity.jl

@@ -243,11 +243,20 @@ function Base.show(io::IO, mkd::ManifoldKernelDensity{M,B,L,P}) where {M,B,L,P}
   pvec = isPartial(mkd) ? mkd._partial : collect(1:length(bw))
   println(io, "  bws:   ", getBandwidth(mkd, true) .|> x->round(x,digits=4))
   println(io, "  ipc:   ", getInfoPerCoord(mkd, true) .|> x->round(x,digits=4))
+  print(io, "   mean: ")
   try
     # mn = mean(mkd.manifold, getPoints(mkd, false))
     mn = mean(mkd)
-    println(io, "   mean: ", round.(mn',digits=4))
+    if mn isa ProductRepr
+      println(io)
+      for prt in mn.parts
+        println(io, "         ", round.(prt,digits=4))
+      end
+    else
+      println(io, round.(mn',digits=4))
+    end
   catch
+    println(io, "----")
   end
   println(io, ")")
   nothing