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Commit fb12a137 authored by Stephan Hilb's avatar Stephan Hilb
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finalize primal-dual comparison experiment

parent 370069e3
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scripts/run_experiments.jl
+ 72
− 49
View file @ fb12a137
......@@ -410,6 +410,9 @@ function estimate!(ctx::L1L2TVContext)
nablau = nabla(ctx.u), w, nablaw = nabla(w), ctx.tdata)
end
estimate_error(st::L1L2TVContext) =
sqrt(sum(st.est.data) / area(st.mesh))
# minimal Dörfler marking
function mark(ctx::L1L2TVContext; theta=0.5)
n = ncells(ctx.mesh)
......@@ -529,113 +532,132 @@ function denoise(img; name, params...)
end
function denoise_pd(ctx, img; df=nothing, name, algorithm, params_...)
function denoise_pd(st, img; df=nothing, name, algorithm, params_...)
params = NamedTuple(params_)
m = 1
img = from_img(img) # coord flip
mesh = init_grid(img; type=:vertex)
mesh = init_grid(img)
#mesh = init_grid(img, 5, 5)
T(tdata, u) = u
S(u, nablau) = u
ctx = L1L2TVContext(name, mesh, m;
st = L1L2TVContext(name, mesh, m;
T, tdata = nothing, S,
params.alpha1, params.alpha2, params.lambda, params.beta,
params.gamma1, params.gamma2)
# semi-implicit primal dual parameters
gamma = ctx.alpha2 + ctx.beta # T = I, S = I
gamma /= 100 # kind of arbitrary?
mu = st.alpha2 + st.beta # T = I, S = I
#mu /= 100 # kind of arbitrary?
tau = 1e-1
L = 100
sigma = inv(tau * L^2)
theta = 1.
#project_img!(ctx.g, img)
interpolate!(ctx.g, x -> interpolate_bilinear(img, x))
ctx.u.data .= ctx.g.data
#project_img!(st.g, img)
interpolate!(st.g, x -> interpolate_bilinear(img, x))
st.u.data .= st.g.data
save_denoise(ctx, i) =
output(ctx, "output/$(ctx.name)_$(lpad(i, 5, '0')).vtu",
ctx.g, ctx.u, ctx.p1, ctx.p2)
save_denoise(st, i) =
output(st, "output/$(st.name)_$(lpad(i, 5, '0')).vtu",
st.g, st.u, st.p1, st.p2)
log!(x::Nothing; kwargs...) = x
function log!(df::DataFrame; k, norm_step, norm_residual)
push!(df, (;
k,
primal_energy = primal_energy(ctx),
norm_step,
norm_residual))
println(NamedTuple(last(df)))
function log!(df::DataFrame; kwargs...)
row = NamedTuple(kwargs)
push!(df, row)
#println(df)
println(row)
end
#pvd = paraview_collection("output/$(ctx.name).pvd")
#pvd[0] = save_denoise(ctx, 0)
#pvd = paraview_collection("output/$(st.name).pvd")
#pvd[0] = save_denoise(st, 0)
k = 0
println("primal energy: $(primal_energy(ctx))")
println("primal energy: $(primal_energy(st))")
while true
k += 1
if algorithm == :pd1
# no step size control
step_pd2!(ctx; sigma, tau, theta)
step_pd2!(st; sigma, tau, theta)
elseif algorithm == :pd2
theta = 1 / sqrt(1 + 2 * gamma * tau)
theta = 1 / sqrt(1 + 2 * mu * tau)
tau *= theta
sigma /= theta
step_pd2!(ctx; sigma, tau, theta)
step_pd2!(st; sigma, tau, theta)
elseif algorithm == :newton
step!(ctx)
step!(st)
end
#pvd[k] = save_denoise(ctx, k)
#pvd[k] = save_denoise(st, k)
domain_factor = 1 / sqrt(area(mesh))
norm_step_ = norm_step(ctx) * domain_factor
norm_residual_ = norm_residual(ctx) * domain_factor
norm_step_ = norm_step(st) * domain_factor
#estimate!(st)
log!(df; k, norm_step = norm_step_, norm_residual = norm_residual_)
log!(df; k,
norm_step = norm_step_,
#est = estimate_error(st),
primal_energy = primal_energy(st))
#norm_residual_ < params.tol && norm_step_ < params.tol && break
haskey(params, :tol) && norm_step_ < params.tol && break
haskey(params, :max_iters) && k >= params.max_iters && break
end
#pvd[1] = save_denoise(ctx, 1)
#pvd[1] = save_denoise(st, 1)
#vtk_save(pvd)
return ctx
return st
end
function experiment_pd_comparison(ctx)
img = loadimg(joinpath(ctx.indir, "input.png"))
img = from_img(img) # coord flip
#img = [0. 0.; 1. 0.]
algparams = (
alpha1=0., alpha2=30., lambda=1., beta=0.,
gamma1=1e-3, gamma2=1e-3,
tol = 1e-6, max_iters = 50,
gamma1=1e-2, gamma2=1e-3,
tol = 1e-10,
max_iters = 10000,
)
df1 = DataFrame()
df2 = DataFrame()
df3 = DataFrame()
denoise_pd(ctx, img; name="test", algorithm=:pd1, df = df1, algparams...);
denoise_pd(ctx, img; name="test", algorithm=:pd2, df = df2, algparams...);
denoise_pd(ctx, img; name="test", algorithm=:newton, df = df3, algparams...);
st1 = denoise_pd(ctx, img; name="test",
algorithm=:pd1, df = df1, algparams...);
st2 = denoise_pd(ctx, img; name="test",
algorithm=:pd2, df = df2, algparams...);
st3 = denoise_pd(ctx, img; name="test",
algorithm=:newton, df = df3, algparams...);
energy_min = min(minimum(df1.primal_energy), minimum(df2.primal_energy),
minimum(df3.primal_energy))
#df1.primal_energy .-= energy_min
#df2.primal_energy .-= energy_min
#df3.primal_energy .-= energy_min
CSV.write(joinpath(ctx.outdir, "semiimplicit.csv"), logfilter(df1))
CSV.write(joinpath(ctx.outdir, "semiimplicit-accelerated.csv"), logfilter(df2))
CSV.write(joinpath(ctx.outdir, "newton.csv"), logfilter(df3))
df1[!, :energy_min] .= energy_min
df2[!, :energy_min] .= energy_min
df3[!, :energy_min] .= energy_min
CSV.write(joinpath(ctx.outdir, "semi-implicit.csv"),
logfilter(df1))
CSV.write(joinpath(ctx.outdir, "semi-implicit-accelerated.csv"),
logfilter(df2))
CSV.write(joinpath(ctx.outdir, "newton.csv"),
logfilter(df3))
saveimg(joinpath(ctx.outdir, "input.png"),
img)
saveimg(joinpath(ctx.outdir, "semi-implicit.png"),
to_img(sample(st1.u)))
saveimg(joinpath(ctx.outdir, "semi-implicit-accelerated.png"),
to_img(sample(st2.u)))
saveimg(joinpath(ctx.outdir, "newton.png"),
to_img(sample(st3.u)))
savedata(joinpath(ctx.outdir, "data.tex");
energy_min, algparams...)
end
function denoise_approximation(ctx)
......@@ -662,7 +684,8 @@ function denoise_approximation(ctx)
function log!(df::DataFrame; kwargs...)
row = NamedTuple(kwargs)
push!(df, row)
println(row)
println(df)
#println(row)
end
pvd_path = joinpath(ctx.outdir, "$(ctx.params.name).pvd")
......@@ -716,9 +739,9 @@ function experiment_approximation(ctx)
denoise_approximation(Util.Context(ctx; name = "test", df,
img, mesh,
#alpha1 = 0., alpha2 = 30., lambda = 1., beta = 0.,
alpha1 = 0.5, alpha2 = 0., lambda = 0., beta = 1.,
gamma1 = 1e-5, gamma2 = 1e-3,
alpha1 = 0., alpha2 = 30., lambda = 1., beta = 0.,
#alpha1 = 0.5, alpha2 = 0., lambda = 0., beta = 1.,
gamma1 = 1e-5, gamma2 = 1e-5,
tol = 1e-10, adaptive = true,
))
end
......
scripts/util.jl
+ 5
− 6
View file @ fb12a137
......@@ -44,13 +44,12 @@ end
# LaTeX Data Output
# TODO: don't depend on ctx.path and use filename only
savedata(ctx::Context, filename; data...) =
open(joinpath(ctx.outdir, filename); write=true) do io
_savedata(io, ctx.path; data...)
savedata(filename; data...) =
open(filename; write=true) do io
_savedata(io; data...)
end
function _savedata(io, path; data...)
function _savedata(io; data...)
isvalidname(x) = contains(string(x), r"^[^/\\]+$")
# define tex command to access data
......@@ -67,7 +66,7 @@ function _savedata(io, path; data...)
# actual data encoded as tex-commands
write(io, "\\expandafter\\def")
write(io, "\\csname $(texcmd)/$(path)/$(key)\\endcsname{")
write(io, "\\csname $(texcmd)/\\DataPrefix/$(key)\\endcsname{")
show(io, MIME("text/latex"), value)
write(io, "}\n")
end
......
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