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dynsasFailExample.jl
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dynsasFailExample.jl
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# using Distributed
# addprocs(5)
using Caesar, RoME
using RoMEPlotting, Gadfly, KernelDensityEstimatePlotting, Cairo, Fontconfig
using KernelDensityEstimate
using IncrementalInference
using DocStringExtensions
using DelimitedFiles, JLD, DistributedFactorGraphs
include(joinpath(@__DIR__,"slamUtils.jl"))
include(joinpath(@__DIR__,"plotSASUtils.jl"))
include(joinpath(@__DIR__,"expDataUtils.jl"))
function main(expID::String, datastart::Int, dataend::Int, fgap::Int, gps_gap::Int; saswindow::Int=8, trialID::Int=1)
## Default parameters
println("Start Script\n")
sas_gap = saswindow+fgap;
tstart = 1_000_000;
element = 2
totalposes = dataend-datastart;
datawindow = collect(datastart:dataend);
allpaths = getPaths(expID,"dynsas", currloc = "local", trialID = trialID);
scriptHeader = joinpath(allpaths[3],expID*"_fgap$(fgap)_gpsgap$(gps_gap)_swind$(saswindow)_f$(datastart)t$(dataend)_")
poses = Dict{Int,Array}();
nav = Dict{Int,Array}();
errorinds = [];
allsasframes = Dict{Int,Array}();
igt = loadGT(datawindow,expID,allpaths);
posData = loadNav(datawindow,allpaths)
dposData = deepcopy(posData)
i=1
while i+gps_gap < size(dposData,1)
cumulativeDrift!(@view(dposData[i:i+gps_gap-1,:]),[0.0;0],[0.2,0.2])
i+=gps_gap
if i+gps_gap > size(dposData,1)
cumulativeDrift!(@view(dposData[i-gps_gap:end,:]),[0.0;0],[0.2,0.2])
end
end
# posPl = Gadfly.plot(layer(x=posData[:,1],y=posData[:,2], Geom.path, Theme(default_color=colorant"green")), layer(x=dposData[:,1],y=dposData[:,2],Geom.path)); posPl |> PDF(scriptHeader*"posGT.pdf")
chirpFile = joinpath(ENV["HOME"],"data","sas","chirp250.txt");
cfgFile = joinpath(ENV["HOME"],"data","sas","SAS2D.yaml")
cfgd=loadConfigFile(cfgFile)
fg = initfg();
beacon = :l1
addVariable!(fg, beacon, Point2 )
tree = emptyBayesTree();
pose_counter = 1
sas_counter = 1
sas_gap_counter = 0;
while pose_counter < totalposes-2
current_symbol = Symbol("x$pose_counter")
addVariable!(fg, current_symbol, DynPoint2(ut=tstart))
println("Adding Variable x$pose_counter")
sas_gap_counter += 1
tstart += 1_000_000
#Interpolate velocity from GPS ground truth every gps_gap poses
if pose_counter == 1 || mod(pose_counter,gps_gap) == 0
xdotp = posData[pose_counter+1,1] - posData[pose_counter,1];
ydotp = posData[pose_counter+1,2] - posData[pose_counter,2];
dpμ = [posData[pose_counter,1];posData[pose_counter,2];xdotp;ydotp];
dpσ = Matrix(Diagonal([0.1;0.1;0.2;0.2].^2))
pp = DynPoint2VelocityPrior(MvNormal(dpμ,dpσ))
addFactor!(fg, [current_symbol;], pp, autoinit=false)
# initManual!(fg,current_symbol,kde!(rand(MvNormal(dpμ,dpσ),100)))
end
#odo factors
if pose_counter > 1
xdotp = dposData[pose_counter-1,1] - dposData[pose_counter,1];
ydotp = dposData[pose_counter-1,2] - dposData[pose_counter,2];
xdotf = dposData[pose_counter+1,1] - dposData[pose_counter,1];
ydotf = dposData[pose_counter+1,2] - dposData[pose_counter,2];
dpμ = [xdotp;ydotp;xdotf-xdotp;xdotf-xdotp];
dpσ = Matrix(Diagonal([0.2;0.2;0.2;0.2].^2))
vp = VelPoint2VelPoint2(MvNormal(dpμ,dpσ))
addFactor!(fg, [Symbol("x$(pose_counter-1)");current_symbol], vp, autoinit=false)
# initManual!(fg,current_symbol,kde!(rand(MvNormal(dpμ,dpσ),100)))
end
if sas_gap_counter >= sas_gap
println("Trying to add SAS at pose: $pose_counter")
navframes = collect(pose_counter-saswindow+1:1:pose_counter)
navtemp = posData[navframes,:];
navchecked, errorind = sanitycheck_nav(navtemp);
push!(errorinds,errorind);
if navchecked
poses[sas_counter] = [Symbol("x$i") for i in pose_counter-saswindow+1:pose_counter]
currentstart = datastart+pose_counter-saswindow
println("Adding SAS at dataframe: $currentstart")
sasframes = collect(currentstart:1:currentstart+saswindow-1);
allsasframes[sas_counter] = sasframes;
waveformData = importdata_waveforms(sasframes,element,datadir=allpaths[1]);
sas2d = prepareSAS2DFactor(saswindow, waveformData, rangemodel=:Correlator,cfgd=cfgd, chirpFile=chirpFile)
addFactor!(fg, [beacon;poses[sas_counter]], sas2d, autoinit=false)
getSolverParams(fg).drawtree = false
getSolverParams(fg).showtree = false
if sas_counter > 1
tree = solveTree!(fg,tree)
else
tree = solveTree!(fg)
end
writeGraphPdf(fg,viewerapp="", engine="neato", filepath=scriptHeader*"fg.pdf")
drawTree(tree, filepath=scriptHeader*"bt.pdf")
plotSASDefault(fg,expID, posData,igt,datadir=allpaths[1],savedir=scriptHeader*"$sas_counter.pdf")
if expID == "dock"
l1fit = getKDEMean(getBelief(getVariable(fg,:l1)))
meanerror = sqrt((igt[1]-l1fit[1])^2+(igt[2]-l1fit[2])^2)
l1max = getKDEMax(getBelief(getVariable(fg,:l1)))
maxerror = sqrt((igt[1]-l1max[1])^2+(igt[2]-l1max[2])^2)
mykde = getBelief(getVariable(fg,:l1))
mynorm = kde!(rand(fit(MvNormal,getVal(fg,:l1)),200))
kld = min(abs(KernelDensityEstimate.kld(mynorm,mykde)),abs(KernelDensityEstimate.kld(mykde,mynorm)))
elseif expID == "drift"
l1fit = getKDEMean(getBelief(getVariable(fg,:l1)))
meanerror = sqrt((mean(igt[:,1])-l1fit[1])^2+(mean(igt[:,2])-l1fit[2])^2)
l1max = getKDEMax(getBelief(getVariable(fg,:l1)))
maxerror = sqrt((mean(igt[:,1])-l1max[1])^2+(mean(igt[:,2])-l1max[2])^2)
mykde = getBelief(getVariable(fg,:l1))
mynorm = kde!(rand(fit(MvNormal,getVal(fg,:l1)),200))
kld = min(abs(KernelDensityEstimate.kld(mynorm,mykde)),abs(KernelDensityEstimate.kld(mykde,mynorm)))
end
jldname2 = scriptHeader * "solve_$(sas_counter).jld"
JLD.save(jldname2,"beacon",getVal(fg,:l1),"posData",posData,"dposData", dposData,"gps_gap", gps_gap, "poses",poses,"sasframes", allsasframes, "l1fit",l1fit, "meanerror",meanerror,"l1max",l1max,"maxerror",maxerror,"kld",kld)
saveDFG(fg,scriptHeader * "fg$(sas_counter)")
sas_counter +=1
sas_gap_counter = 0
end
end
pose_counter+=1
println("Trying next Variable: $pose_counter")
println("Trying next SAS: $sas_counter")
end
return fg
end
fg = main("drift",1550,1580,1,19,trialID=1)