dev example of maniballtree

Project.toml

@@ -9,6 +9,7 @@ Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
 CoordinateTransformations = "150eb455-5306-5404-9cee-2592286d6298"
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
+Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 KernelDensityEstimate = "2472808a-b354-52ea-a80e-1658a3c6056d"
 LibGit2 = "76f85450-5226-5b5a-8eaa-529ad045b433"
 Libdl = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
@@ -18,11 +19,11 @@ Manifolds = "1cead3c2-87b3-11e9-0ccd-23c62b72b94e"
 ManifoldsBase = "3362f125-f0bb-47a3-aa74-596ffd7ef2fb"
 Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
 Mmap = "a63ad114-7e13-5084-954f-fe012c677804"
+NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
 NLsolve = "2774e3e8-f4cf-5e23-947b-6d7e65073b56"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 Rotations = "6038ab10-8711-5258-84ad-4b1120ba62dc"
@@ -42,21 +43,21 @@ Gadfly = "c91e804a-d5a3-530f-b6f0-dfbca275c004"
 ApproxManiProdGadflyExt = "Gadfly"
 
 [compat]
-CoordinateTransformations = "0.5, 0.6"
-DocStringExtensions = "0.7, 0.8, 0.9"
+CoordinateTransformations = "0.6"
+DocStringExtensions = "0.8, 0.9"
+Distances = "0.10.7"
 KernelDensityEstimate = "0.5.10"
 Manifolds = "0.8"
 ManifoldsBase = "0.13, 0.14"
 NLsolve = "3, 4"
 Optim = "1"
-RecursiveArrayTools = "2"
 Reexport = "0.2, 1.0"
 Requires = "0.5, 1"
 Rotations = "1"
 StaticArrays = "0.15, 1"
 TensorCast = "0.2, 0.3, 0.4"
 TransformUtils = "0.2.10"
-julia = "1.4"
+julia = "1.6"
 
 [extras]
 BSON = "fbb218c0-5317-5bc6-957e-2ee96dd4b1f0"

examples/ManiBallTree.jl

@@ -0,0 +1,41 @@
+
+
+# using Revise
+
+using Manifolds, NearestNeighbors, Distances, StaticArrays
+import Manifolds: ArrayPartition
+
+##
+
+Base.@kwdef struct DistSE2 <: Distances.Metric
+  M = SpecialEuclidean(2)
+end 
+# (d::DistSE2)(p,q) = Manifolds.ManifoldsBase.distance(d.M,p,q)
+(d::DistSE2)(p::ArrayPartition,q::ArrayPartition) = Manifolds.ManifoldsBase.distance(d.M,p,q)
+function (d::DistSE2)(p::ArrayPartition,q_::AbstractVector)
+  q = ArrayPartition(SA[q_[1],q_[2]], SMatrix{2,2}(q_[3],q_[4],q_[5],q_[6]))
+  Manifolds.ManifoldsBase.distance(d.M,p,q)
+end
+function (d::DistSE2)(p_::AbstractVector,q_::AbstractVector)
+  p = ArrayPartition(SA[p_[1],p_[2]], SMatrix{2,2}(p_[3],p_[4],p_[5],p_[6]))
+  q = ArrayPartition(SA[q_[1],q_[2]], SMatrix{2,2}(q_[3],q_[4],q_[5],q_[6]))
+  Manifolds.ManifoldsBase.distance(d.M,p,q)
+end
+
+# see https://github.com/SciML/RecursiveArrayTools.jl/pull/220
+Base.length(::Type{<:ArrayPartition{F,T}}) where {F,N,T <: NTuple{N,StaticArray}} = T.parameters .|> length |> sum
+
+##
+
+pts = [ArrayPartition(SA[randn(2)...], SMatrix{2,2}([1 0; 0 1.])) for _ in 1:10]
+dSE2 = DistSE2()
+
+##
+
+bt = NearestNeighbors.BallTree(pts, dSE2; leafsize=1)
+
+## How to get any node in the BallTree
+
+
+
+##

src/ApproxManifoldProducts.jl

@@ -9,8 +9,7 @@ import Rotations as _Rot
 
 import ManifoldsBase
 import ManifoldsBase: AbstractManifold
-using RecursiveArrayTools: ArrayPartition
-export ArrayPartition
+# using RecursiveArrayTools: ArrayPartition
 
 using Manifolds
 
@@ -26,11 +25,18 @@ using StaticArrays
 using Logging
 using Statistics
 
-import Random: rand
+import NearestNeighbors as NNR
+import Distances as DST
+
 
 import Base: *, isapprox, convert
 import LinearAlgebra: rotate!
 import Statistics: mean, std, cov, var
+import Random: rand
+
+import NearestNeighbors: TreeData, NNTree
+import Manifolds: ArrayPartition
+
 import KernelDensityEstimate: getPoints, getBW
 
 const MB = ManifoldsBase
@@ -41,6 +47,8 @@ const KDE = KernelDensityEstimate
 # TODO temporary for initial version of on-manifold products
 KDE.setForceEvalDirect!(true)
 
+export ArrayPartition
+
 # the exported API
 include("ExportAPI.jl")
 
@@ -54,6 +62,12 @@ include("Legacy.jl")
 include("services/ManifoldPartials.jl")
 include("Interface.jl")
 
+# Experimental ManifoldBallTreeBalanced
+include("services/TreeDataBalanced.jl")
+include("services/ManifoldTreeOps.jl")
+include("services/ManifoldHyperSpheres.jl")
+include("services/ManifoldBallTree.jl")
+
 # regular features
 include("CommonUtils.jl")
 include("services/ManifoldKernelDensity.jl")

src/Deprecated.jl

@@ -10,8 +10,6 @@
 # end
 
 
-@deprecate R(th::Real) _Rot.RotMatrix2(th).mat # = [[cos(th);-sin(th)]';[sin(th);cos(th)]'];
-@deprecate R(;x::Real=0.0,y::Real=0.0,z::Real=0.0) (M=SpecialOrthogonal(3);exp(M,identity_element(M),hat(M,Identity(M),[x,y,z]))) # convert(SO3, so3([x,y,z]))
 
 export calcCovarianceBasic
 # Returns the covariance (square), not deviation

src/Legacy.jl

@@ -48,7 +48,7 @@ function buildHybridManifoldCallbacks(manif::Tuple)
 end
 
 # FIXME TO BE REMOVED
-_MtoSymbol(::Euclidean{Tuple{1}}) = :Euclid
+_MtoSymbol(::Manifolds.Euclidean{Tuple{1}}) = :Euclid
 _MtoSymbol(::Circle) = :Circular
 Base.convert(::Type{<:Tuple}, M::ProductManifold) = _MtoSymbol.(M.manifolds)
 Base.convert(::Type{<:Tuple}, M::TranslationGroup) = tuple([:Euclid for i in 1:manifold_dimension(M)]...)