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mv summary function to scripts & replot according to HY's comment
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@szcf-weiya
szcf-weiya committed Jan 4, 2024
1 parent 71653be commit 6433636
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74 changes: 74 additions & 0 deletions scripts/summary_monotest.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -156,4 +156,78 @@ function summary_res4x3_3()
#
res2 = deserialize("../res/mono_test/res_mono_test_ghosal.sil")
μ2 = mean(res2) # 3x4x5
end

# summary experiment results
function summary_mono_test(resfile::String, task = "typeI_error")
texname = resfile[1:end-4] * ".tex"
res0 = deserialize(resfile)
res = [x .< 0.05 for x in res0]
methods_fullname = ["\\textcite{wangTestingMonotonicityConvexity2011}",
"\\textcite{ghosalTestingMonotonicityRegression2000}",
"\\textcite{bowmanTestingMonotonicityRegression1998}",
"MDCS",
"MDSS"]
methods = ["Wang and Meyer (2011)", "Ghosal et al. (2000)", "Bowman et al. (2000)",
"MDCS",
"MDSS"
]
nmethod = length(methods)
μ = mean(res)
@assert size(μ, 4) == nmethod
A = Array{Matrix, 1}(undef, nmethod)
name_σs = ["\$\\sigma = 0.001\$", "\$\\sigma = 0.01\$", "\$\\sigma = 0.1\$"]
if task == "typeI_error"
name_curves = ["\$x\$", "\$x^3\$", "\$x^{1/3}\$", "\$e^x\$", "\$1/(1+e^{-x})\$"]
elseif task == "bowman"
name_curves = "a = " .* string.([0,0.15,0.25,0.45])
elseif task == "ghosal"
name_curves = "m" .* string.(1:4)
end
for i in 1:nmethod
if task == "bowman"
A[i] = hcat([μ[:, :, j, i] for j = 1:3]...)
else
A[i] = hcat([μ[:, j, :, i]' for j = 1:3]...)
end
end
print2tex(A, methods_fullname, name_σs,
subcolnames=["n = 50", "100", "200"],
subrownames = name_curves,
colnames_of_rownames = ["Methods", "Curves"],
file = texname, format="raw")
# if task == "typeI_error"
# mkpath(resfile[1:end-4])
# for i = 1:3
# for j = 1:3
# for k = 1:5
# plot([histogram([x[i, j, k, ℓ] for x in res0], xlims = (0, 1.1), bins = 0:0.05:1.1, normalize = :probability, legend = false, title = methods[ℓ], margin=5Plots.mm) for ℓ = 1:5]..., layout = (1, 5), size = (2000, 400))
# savefig(joinpath(resfile[1:end-4], "pval_$i$j$k.pdf"))
# end
# end
# end
# end
end

function qqplot_mono_test(resfile::String)
res0 = deserialize(resfile)
for i = 1:3
for j = 1:3
for k = 1:5
fig = plot(xlab = "Uniform[0, 1] Quantiles", ylab = "Sample Quantiles", xlim = (0, 1), ylim = (0, 1))
ms = [:star5, :x, :+, :circle, :rect]
u = rand(Uniform(), 100)
methods = ["Wang and Meyer (2011)", "Ghosal et al. (2000)", "Bowman et al. (2000)", "MDCS", "MDSS"]
qu = quantile(u, 0:0.01:1.0)
for ℓ = 1:5
a = [x[i, j, k, ℓ] for x in res0]
# qqplot!(fig, u, a, markershape = ms[ℓ], label = methods[ℓ])
qa = quantile(a, 0:0.01:1.0)
plot!(fig, qu, qa, markershape = ms[ℓ], label = methods[ℓ])
end
Plots.abline!(fig, 1, 0, label = "", ls = :dash)
savefig(joinpath(resfile[1:end-4], "qqplot_$i$j$k.pdf"))
end
end
end
end
58 changes: 5 additions & 53 deletions src/mono_test.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -65,13 +65,13 @@ function gen_data_ghosal(; n = 100, σ = 0.1, plt = false)
m4 = m40 + randn(n) * σ
if plt
ind = sortperm(xs)
p1 = plot(xs[ind], m10[ind], legend = false)
p1 = plot(xs[ind], m10[ind], legend = false, title = L"m_1")
scatter!(p1, xs, m1)
p2 = plot(xs[ind], m20[ind], legend = false)
p2 = plot(xs[ind], m20[ind], legend = false, title = L"m_2")
scatter!(p2, xs, m2)
p3 = plot(xs[ind], m30[ind], legend = false)
p3 = plot(xs[ind], m30[ind], legend = false, title = L"m_3")
scatter!(p3, xs, m3)
p4 = plot(xs[ind], m40[ind], legend = false)
p4 = plot(xs[ind], m40[ind], legend = false, title = L"m_4")
scatter!(p4, xs, m4)
return [p1, p2, p3, p4]
else
Expand Down Expand Up @@ -553,52 +553,4 @@ function mono_test(x::AbstractVector{T}, y::AbstractVector{T}) where T <: Real
pval = 1 - cdf(Chisq(res.workspace.J), tobs)
# println("pval = $pval, tobs = $tobs, critical = $(quantile(Chisq(J), 0.95))")
return pval < 0.05
end

# summary experiment results
function summary_mono_test(resfile::String, task = "typeI_error")
texname = resfile[1:end-4] * ".tex"
res0 = deserialize(resfile)
res = [x .< 0.05 for x in res0]
methods = ["Meyer", "Ghosal", "Bowman",
# "MD (CS) sup", "MD (CS) min", "MD (CS) 1se",
"MDCS",
"MDSS"
# "MD (SS) sup", "MD (SS) min", "MD (SS) 1se"
]
nmethod = length(methods)
μ = mean(res)
@assert size(μ, 4) == nmethod
A = Array{Matrix, 1}(undef, nmethod)
name_σs = ["\$\\sigma = 0.001\$", "\$\\sigma = 0.01\$", "\$\\sigma = 0.1\$"]
if task == "typeI_error"
name_curves = ["\$x\$", "\$x^3\$", "\$x^{1/3}\$", "\$e^x\$", "\$1/(1+e^{-x})\$"]
elseif task == "bowman"
name_curves = "a = " .* string.([0,0.15,0.25,0.45])
elseif task == "ghosal"
name_curves = "m" .* string.(1:4)
end
for i in 1:nmethod
if task == "bowman"
A[i] = hcat([μ[:, :, j, i] for j = 1:3]...)
else
A[i] = hcat([μ[:, j, :, i]' for j = 1:3]...)
end
end
print2tex(A, methods, name_σs,
subcolnames=["n = 50", "100", "200"],
subrownames = name_curves,
colnames_of_rownames = ["Methods", "Curves"],
file = texname, format="raw")
if task == "typeI_error"
mkpath(resfile[1:end-4])
for i = 1:3
for j = 1:3
for k = 1:5
plot([histogram([x[i, j, k, ℓ] for x in res0], xlims = (0, 1.1), bins = 0:0.05:1.1, normalize = :probability, legend = false, title = methods[ℓ], margin=5Plots.mm) for ℓ = 1:5]..., layout = (1, 5), size = (2000, 400))
savefig(joinpath(resfile[1:end-4], "pval_$i$j$k.pdf"))
end
end
end
end
end
end

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