Merge pull request #641 from JuliaRobotics/hotfix/1Q20/specSampXi

special sampler with full DFGVariable not VND
JuliaRobotics · Mar 14, 2020 · d6ab7fb · d6ab7fb
2 parents fb7be6d + 8f772fd
commit d6ab7fb
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Showing 3 changed files with 7 additions and 6 deletions.
diff --git a/src/ApproxConv.jl b/src/ApproxConv.jl
@@ -84,7 +84,7 @@ function prepareCommonConvWrapper!(ccwl::CommonConvWrapper{T},
   # get factor metadata -- TODO, populate
   fmd = FactorMetadata()
   #  get variable node data
-  vnds = (x->getSolverData(x)).(Xi)
+  vnds = Xi # (x->getSolverData(x)).(Xi)
   freshSamples!(ccwl, maxlen, fmd, vnds...)
   # ccwl.measurement = getSample(ccwl.usrfnc!, maxlen) # ccwl.samplerfnc
   if ccwl.specialzDim
@@ -256,7 +256,7 @@ function evalPotentialSpecific(Xi::Vector{DFGVariable},
   nn = (N <= 0 ? size(getVal(Xi[1]),2) : N)
   # ccwl.measurement = 0 < size(measurement[1],1) ? measurement : getSample(ccwl.usrfnc!, nn)
   # ccwl.measurement = freshSamples(ccwl.usrfnc!, nn) # TODO make in-place
-  vnds = (x->getSolverData(x)).(Xi)
+  vnds = Xi # (x->getSolverData(x)).(Xi)
   freshSamples!(ccwl, nn, FactorMetadata(), vnds...) # in-place version
   if !ccwl.partial
     return ccwl.measurement[1]
@@ -287,7 +287,7 @@ function evalPotentialSpecific(Xi::Vector{DFGVariable},
   var = Statistics.var(val, dims=2) .+ 1e-3
 
   # prep in case special samplers used
-  vnds = (x->getSolverData(x)).(Xi)
+  vnds = Xi # (x->getSolverData(x)).(Xi)
   # determine amount share of null hypothesis particles
   freshSamples!(ccwl, N, FactorMetadata(), vnds...)
   # ccwl.measurement = getSample(ccwl.usrfnc!, N)
@@ -382,7 +382,7 @@ function approxConvBinary(arr::Array{Float64,2},
                           varidx::Int=2,
                           N::Int=size(arr,2),
                           fmd::FactorMetadata=FactorMetadata(),
-                          vnds=VariableNodeData[] )
+                          vnds=DFGVariable[] )
   #
   # N = N == 0 ? size(arr,2) : N
   pts = zeros(outdims,N);

diff --git a/src/FactorGraph.jl b/src/FactorGraph.jl
@@ -587,7 +587,7 @@ end
 function calcZDim(usrfnc::T, Xi::Vector{<:DFGVariable})::Int where {T <: FunctorInferenceType}
   # zdim = T != GenericMarginal ? size(getSample(usrfnc, 2)[1],1) : 0
   zdim = if T != GenericMarginal
-    vnds = (x->getSolverData(x)).(Xi)
+    vnds = Xi # (x->getSolverData(x)).(Xi)
     smpls = freshSamples(usrfnc, 2, FactorMetadata(), vnds...)[1]
     size(smpls,1)
   else

diff --git a/src/SolverUtilities.jl b/src/SolverUtilities.jl
@@ -101,6 +101,7 @@ function (ccw::CommonConvWrapper)(x::Vector{Float64})
     ccw.params[ccw.varidx][ccw.cpt[Threads.threadid()].p, ccw.cpt[Threads.threadid()].particleidx] .= x #ccw.Y
   end
   # evaulate the user provided residual function with constructed set of parameters
+  @show typeof(ccw.usrfnc!)
   ccw.usrfnc!(ccw.cpt[Threads.threadid()].res,
               ccw.cpt[Threads.threadid()].factormetadata,
               ccw.cpt[Threads.threadid()].particleidx,
@@ -345,13 +346,13 @@ function solveFactorMeasurements(dfg::AbstractDFG,
   # varsyms = fcto._variableOrderSymbols
   VV = (v->getVariable(dfg, v)).(varsyms)
   vars = map(x->getPoints(getKDE(x)), VV) # varsyms
-  vnds = (v->getSolverData(v)).(VV)
   fcttype = getFactorType(fcto)
   zDim = getSolverData(fcto).fnc.zDim
 
   N = size(vars[1])[2]
   res = zeros(zDim)
   ud = FactorMetadata()
+  vnds = VV # (v->getSolverData(v)).(VV)
   meas = freshSamples(fcttype, N, ud, vnds)
   # meas = getSample(fcttype, N)
   meas0 = deepcopy(meas[1])