Merge pull request #25 from JuliaRobotics/feature/addstringconversions

adding new string conversion for easier downstream use
JuliaRobotics · Jul 17, 2018 · f20761c · f20761c
2 parents 9e27e18 + 120ac8f
commit f20761c
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diff --git a/src/DualTree01.jl b/src/DualTree01.jl
@@ -1,43 +1,36 @@
 
+function string(d::KernelDensityEstimate.BallTreeDensity)
+  # TODO only supports single bandwidth per dimension at this point
+  pts = getPoints(d)
+  return "KDE:$(size(pts,2)):$(getBW(d)[:,1]):$(pts)"
+end
+
+function parsestringvector(str::AS; dlim=',') where {AS <: AbstractString}
+  sstr = split(split(strip(str),'[')[end],']')[1]
+  ssstr = strip.(split(sstr,dlim))
+  parse.(Float64, ssstr)
+end
+
+function convert(::Type{BallTreeDensity}, str::AS) where {AS <: AbstractString}
+  @assert ismatch(r"KDE:", str)
+  sstr = strip.(split(str, ':'))
+  N = parse(Int, sstr[2])
+  bw = parsestringvector(sstr[3])
+  dims = length(bw)
+  ptrowstrs = split(sstr[4],';')
+  @assert dims == length(ptrowstrs)
+  pts = zeros(dims, N)
+  for i in 1:dims
+    pts[i,:] = parsestringvector(ptrowstrs[i], dlim=' ')
+  end
+  kde!(pts, bw)
+end
+# psubs = split(psubs, '[')[end]
+# psubsub = split(psubs, ']')[1]
+# pw = split(psubsub, ',')
+
+
 
-# function OLDminDistGauss(bd::BallTreeDensity, dRoot::Int, atTree::BallTreeDensity, aRoot::Int)
-#   #@show "minDistGauss",  dRoot, aRoot
-#   atCenter = center(atTree, aRoot)
-#   densCenter = center(bd, dRoot)
-#   bw = bwMax(bd, dRoot)
-#   result = 0.0
-#   tmp = 0.0
-#   for (k=1:Ndim(atTree))
-#     tmp = abs( atCenter[k] - densCenter[k] )
-#     tmp -= (rangeB(atTree, aRoot))[k] + (rangeB(bd, dRoot))[k];
-#     tmp = (tmp > 0) ? tmp : 0.0
-#     if ( bwUniform(bd) )
-#       result -= (tmp*tmp)/bw[k]
-#     else
-#       result -= (tmp*tmp)/bw[k] + log(bwMin(bd, dRoot)[k]) end
-#   end
-#   result = exp(result/2.0)
-#   return result
-# end
-#
-# function OLDmaxDistGauss(bd::BallTreeDensity, dRoot::Int, atTree::BallTreeDensity, aRoot::Int)
-#   atCenter = center(atTree, aRoot)
-#   densCenter = center(bd, dRoot)
-#   bw = bwMin(bd, dRoot)
-#   tmp = 0.0
-#   result = 0.0
-#   for k in 1:Ndim(atTree.bt)
-#     tmp = abs( atCenter[k] - densCenter[k] )
-#     tmp+= rangeB(atTree, aRoot)[k] + rangeB(bd, dRoot)[k]
-#     if ( bwUniform(bd) )
-#         result -= (tmp*tmp)/bw[k]
-#     else
-#         result -= (tmp*tmp)/bw[k] + log(bwMax(bd, Root)[k])
-#     end
-#   end
-#   result = exp(result/2.0);
-#   return result
-# end
 
 function minDistGauss!(restmp::Array{Float64, 1}, bd::BallTreeDensity, dRoot::Int, atTree::BallTreeDensity, aRoot::Int)
   #@show "minDistGauss",  dRoot, aRoot

diff --git a/src/KernelDensityEstimate.jl b/src/KernelDensityEstimate.jl
@@ -6,9 +6,14 @@ module KernelDensityEstimate
 using Distributions, Compat
 
 import Distributions: sample
-import Base: promote_rule, *, rand
+import Base: promote_rule, *, rand, string, convert
 
 export
+    # override Base
+    string,
+    convert,
+
+    # new stuff
     MixtureDensity,
     kde!,
     getPoints,

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -1,43 +1,6 @@
 using KernelDensityEstimate
 using Base.Test
-# include("BallTree01.jl")
-# include("BallTreeDensity01.jl")
-# include("KDE01.jl")
-# include("DualTree01.jl")
-
-# type BallTree
-#   dims::Int                     # dimension of data
-#   num_points::Int               # of points
-#   centers::Array{Float64,1}       # ball centers, dims numbers per ball
-#   ranges::Array{Float64,1}        # bounding box ranges, dims per ball, dist from center to one side
-#   weights::Array{Float64,1}       # total weight in each ball
-#
-#   left_child::Array{Int,1}
-#   right_child::Array{Int,1}     # left, right children; no parent indices
-#   lowest_leaf::Array{Int,1}
-#   highest_leaf::Array{Int,1}    # lower & upper leaf indices for each ball
-#   permutation::Array{Int,1}     # point's position in the original data
-#
-#   next::Int                     # internal var for placing the non-leaf nodes
-#
-#   swapHandle::Function
-#   calcStatsHandle::Function
-#   data
-# end
-# type BallTreeDensity
-#   bt::BallTree
-#
-#   KernelType
-#   multibandwidth::Int               # flag: is bandwidth uniform?
-#
-#   means::Array{Float64,1}                  # Weighted mean of points from this level down
-#   bandwidth::Array{Float64,1}              # Variance or other multiscale bandwidth
-#   bandwidthMin::Array{Float64,1}
-#   bandwidthMax::Array{Float64,1}           # Bounds on BW in non-uniform case
-#
-#   calcStatsHandle::Function
-#   swapHandle::Function
-# end
+
 
 # parse the output from matlab process
 function parseMatPrintKDE(filename::String)
@@ -267,3 +230,16 @@ end
 @test integralAppxUnitTests()
 
 @test testRand()
+
+
+
+@testset "test string and back conversion" begin
+
+p = kde!(randn(2,3))
+ps = string(p)
+pp = convert(BallTreeDensity, ps)
+
+@test norm(getPoints(pp)-getPoints(p)) < 1e-5
+@test norm(getBW(pp)-getBW(p)) < 1e-5
+
+end