From ec430751aaa767c54cf59a53b9d224b9c83dfe01 Mon Sep 17 00:00:00 2001
From: Stephan Hilb <stephan@ecshi.net>
Date: Mon, 21 Feb 2022 22:54:37 +0100
Subject: [PATCH] tweak synthetic experiments
---
scripts/run.jl | 21 +++++++++++++++++++++
scripts/run_experiments.jl | 24 ++++++++++++++++--------
2 files changed, 37 insertions(+), 8 deletions(-)
diff --git a/scripts/run.jl b/scripts/run.jl
index 1166883..682065e 100644
--- a/scripts/run.jl
+++ b/scripts/run.jl
@@ -5,5 +5,26 @@ const outpath = "/home/stev47/stuff/phd/data"
ctx = Util.Context(datapath, outpath)
+# convergence
+
+# algorithm comparison
ctx(experiment_convergence_rate, "fem/convergence/rate")
+# L1 convergence, difference in algorithm
+
+# L1 non-convergence / oscillations
+
+
+# adaptivity
+
+# residual estimator, discrete g, good
+# pd est, L2-TV, discrete g, good?
+# pd est, zero
+# pd est, L1-TV, bad
+
+
+# applications
+
+# denoising
+# adaptive
+# optical flow
ctx(experiment_optflow_middlebury_all, "fem/optflow/middlebury")
diff --git a/scripts/run_experiments.jl b/scripts/run_experiments.jl
index cbae523..da08a90 100644
--- a/scripts/run_experiments.jl
+++ b/scripts/run_experiments.jl
@@ -857,12 +857,12 @@ function denoise_pd(ctx)
# semi-implicit primal dual parameters
mu = st.alpha2 + st.beta # T = I, S = I
- #mu /= 100 # kind of arbitrary?
+ mu /= 100 # kind of arbitrary?
tau = 1e-1
- L = 100
+ L = norm_gradient(mesh)
sigma = inv(tau * L^2)
- theta = 1.
+ theta = NaN # initialized later
#project_l2_lagrange!(st.g, ctx.params.g_arr)
interpolate!(st.g, x -> evaluate_bilinear(ctx.params.g_arr, x))
@@ -909,6 +909,7 @@ function denoise_pd(ctx)
log!(ctx.params.df; k,
norm_step = norm_step_,
+ norm_residual = norm_residual(st),
#est = estimate_error(st),
primal_energy = primal_energy(st))
@@ -978,7 +979,7 @@ function experiment_convergence_difference(ctx)
algparams = (
init_zero = true,
alpha1 = 0.5, alpha2 = 0., lambda = 0., beta = 1.,
- gamma1 = 1e-10, gamma2 = 1e-10,
+ gamma1 = 1e-7, gamma2 = 1e-7,
tol = 1e-10,
max_iters = 10000,
)
@@ -990,12 +991,16 @@ function experiment_convergence_difference(ctx)
st2 = denoise_pd(Util.Context(algctx; algorithm = :newton, df = df2));
p1 = plot(df1.k, df1.norm_step; axis = :log)
p2 = plot(df2.k, df2.norm_step; axis = :log)
- p3 = plot(df1.k, df1.primal_energy; xaxis = :log)
- p4 = plot(df2.k, df2.primal_energy; xaxis = :log)
+ p3 = plot(df1.k, df1.norm_residual; axis = :log)
+ p4 = plot(df2.k, df2.norm_residual; axis = :log)
display(plot(p1, p2, p3, p4; layout = @layout[a b; c d]))
display(st1.u.data)
+ display(norm_residual(st1))
+ display(primal_energy(st1))
display(st2.u.data)
+ display(norm_residual(st2))
+ display(primal_energy(st2))
return
end
@@ -1005,11 +1010,12 @@ function experiment_convergence_oscillations(ctx)
mesh = init_grid(g_arr;)
algparams = (
+ #init_zero = true,
#alpha1 = 0., alpha2 = 30., lambda = 1., beta = 0.,
#alpha1 = 0.5, alpha2 = 0., lambda = 0., beta = 1.,
- alpha1 = 1., alpha2 = 0., lambda = 0., beta = 1., # oscillating
+ alpha1 = 0.5, alpha2 = 0., lambda = 1., beta = 1., # oscillating
# DP0 for p1 has less oscillations
- gamma1 = 1e-5, gamma2 = 1e-5,
+ gamma1 = 1e-7, gamma2 = 1e-7,
tol = 1e-10,
max_iters = 10000,
)
@@ -1026,7 +1032,9 @@ function experiment_convergence_oscillations(ctx)
display(plot(p1, p2, p3, p4; layout = @layout[a b; c d]))
display(st1.u.data)
+ display(primal_energy(st1))
display(st2.u.data)
+ display(primal_energy(st2))
return
end
--
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