Fix identity to identity_element for Manifolds 0.6

Project.toml

@@ -37,7 +37,7 @@ Unicode = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
 CoordinateTransformations = "0.5, 0.6, 0.8, 0.9"
 DocStringExtensions = "0.7, 0.8, 0.9"
 KernelDensityEstimate = "0.5.6"
-Manifolds = "0.5, 0.6"
+Manifolds = "0.6"
 ManifoldsBase = "0.11, 0.12"
 NLsolve = "3, 4"
 Optim = "0.16, 0.17, 0.18, 0.19, 0.20, 0.21, 0.22, 0.23, 1"

src/API.jl

@@ -38,7 +38,7 @@ function manifoldProduct( ff::AbstractVector{<:ManifoldKernelDensity},
                           ndims::Int=maximum(Ndim.(ff)),
                           N::Int = maximum(Npts.(ff)),
                           u0 = getPoints(ff[1], false)[1],
-                          oldPoints::AbstractVector{P}= [identity(mani, u0) for i in 1:N],
+                          oldPoints::AbstractVector{P}= [identity_element(mani, u0) for i in 1:N],
                           addEntropy::Bool=true,
                           recordLabels::Bool=false,
                           selectedLabels::Vector{Vector{Int}}=Vector{Vector{Int}}(),

src/Interface.jl

@@ -7,9 +7,9 @@ export makeCoordsFromPoint, makePointFromCoords, getNumberCoords
 export identity
 export replace
 
-# Deprecate in favor of TranslationGroup instead
-ManifoldsBase.identity(::Euclidean{Tuple{N}}, val::AbstractVector{T}) where {N, T <: Number} = zeros(T, N)
-ManifoldsBase.identity(::Circle, val::AbstractVector{T}) where {T <: Real} = zeros(T, 1)
+# Deprecate in favor of TranslationGroup instead, also type piracy
+Manifolds.identity_element(::Euclidean{Tuple{N}}, val::AbstractVector{T}) where {N, T <: Number} = zeros(T, N)
+Manifolds.identity_element(::Circle, val::AbstractVector{T}) where {T <: Real} = zeros(T, 1)
 
 """
     $SIGNATURES
@@ -23,15 +23,15 @@ Notes
 makePointFromCoords(M::MB.AbstractManifold,
                     coords::AbstractVector{<:Real},
                     u0=zeros(manifold_dimension(M)),
-                    ϵ=identity(M,u0),
+                    ϵ=identity_element(M,u0),
                     retraction_method::AbstractRetractionMethod=ExponentialRetraction()  ) = retract(M, ϵ, hat(M, ϵ, coords), retraction_method)
 #
 
 function makeCoordsFromPoint( M::MB.AbstractManifold,
                               pt::P ) where P
   #
   # only works for manifold which have an identity (eg groups)
-  ϵ = identity(M, pt)
+  ϵ = identity_element(M, pt)
   vee(M, ϵ, log(M, ϵ, pt))
 end
 
@@ -57,7 +57,7 @@ end
 
 function _pointsToMatrixCoords(M::MB.AbstractManifold, pts::AbstractVector{P}) where P
   mat = zeros(manifold_dimension(M), length(pts))
-  ϵ = identity(M, pts[1])
+  ϵ = identity_element(M, pts[1])
   for (j,pt) in enumerate(pts)
     mat[:,j] = vee(M, ϵ, log(M, ϵ, pt))
   end

src/services/ManifoldKernelDensity.jl

@@ -51,7 +51,7 @@ function ManifoldKernelDensity( M::MB.AbstractManifold,
   #
   # FIXME obsolete
   arr = Matrix{Float64}(undef, dims, length(vecP))
-  ϵ = identity(M, vecP[1])
+  ϵ = identity_element(M, vecP[1])
 
   for j in 1:length(vecP)
     arr[:,j] = vee(M, ϵ, log(M, ϵ, vecP[j]))

src/services/ManifoldPartials.jl

@@ -137,7 +137,7 @@ M_x, _ = getManifoldPartial(M,[1;])
 u0 = ProductRepr([0.0;0],[1 0; 0 1.0])
 
 # known coordinates are [x,y,θ], eg
-#   vee(M,identity(M,u0),log(M,identity(M,u0),u0))
+#   vee(M,identity_element(M,u0),log(M,identity_element(M,u0),u0))
 #   [0;0;0] in this example
 
 # make another new partial of only the rotation component

test/basic_se3.jl

@@ -19,7 +19,7 @@ using Test
 
 M = SpecialEuclidean(3)
 u0 = ProductRepr(zeros(3),[1 0 0; 0 1 0; 0 0 1.0])
-ϵ = identity(M, u0)
+ϵ = identity_element(M, u0)
 N = 50
 
 pts1 = [exp(M, ϵ, hat(M, ϵ, [0.5*randn(3);0.1*randn(3)])) for i in 1:N]

test/testBasicManiProduct.jl

@@ -38,7 +38,7 @@ pts = AMP._pointsToMatrixCoords(P12.manifold, pts_)
 
 M = SpecialEuclidean(2)
 u0 = ProductRepr(zeros(2),[1 0; 0 1.0])
-ϵ = identity(M, u0)
+ϵ = identity_element(M, u0)
 
 pts1 = [exp(M, ϵ, hat(M, ϵ, [0.05*randn(2);0.75*randn()])) for i in 1:N]
 pts2 = [exp(M, ϵ, hat(M, ϵ, [0.05*randn(2);0.75*randn()])) for i in 1:N]

test/testManiProductBigSmall.jl

@@ -14,7 +14,7 @@ using TensorCast
 M = SpecialEuclidean(2)
 N = 100
 u0 = ProductRepr([0;0.0],[1 0; 0 1.0])
-ϵ = identity(M, u0)
+ϵ = identity_element(M, u0)
 
 X1 = [exp(M, ϵ, hat(M, ϵ, randn(3))) for i in 1:N]
 X2 = [exp(M, ϵ, hat(M, ϵ, 0.1.*randn(3))) for i in 1:N]