before lecture 10

notebooks/failure_prob.jl

@@ -441,7 +441,14 @@ end;
 
 # ╔═╡ 7b37a30e-fec7-4854-a48e-b9eb036758e1
 begin
-	pl1, _ = plot_samples(τs_is_fit, Normal(dist_fit.μ, dist_fit.σ), ws=ws_fit, color=thepurple, ymax=1.5, failure_dist=true)
+	# pl1, _ = plot_samples(τs_is_fit, Normal(dist_fit.μ, dist_fit.σ), ws=ws_fit, color=thepurple, ymax=1.5, failure_dist=true)
+	pl1 = plot(xlims=(-4, 4), ylims=(0, 1.5), grid=false, bg="transparent", background_color_inside=:black, fg="white", yticks=false, xticks=false, alpha=0.6, legend=false)
+	plot!(pl1, rectangle(abs(-4 - γ), 1.5, -4, 0), color=thered, alpha=0.3)
+	plot!(pl1, x->pdf(Truncated(Normal(), -Inf, γ), x), -4, 4, lw=1.5, color=:indianred1)
+	plot!(pl1, x->pdf(Normal(), x), -4, 4, color=:gray, lw=2)
+	plot!(pl1, x->pdf(Normal(dist_fit.μ, dist_fit.σ), x), -4, 4, color=thepurple, lw=2)
+	scatter!(pl1, 𝐬[5:end], 0.02 * ones(length(𝐬)-5), markercolor=thered, markerstrokecolor=:indianred1, ms=4, msw=2, alpha=0.25)
+
 	pll = plot(size=(650, 350))
 	plot_estimation_error!(pll, hists_mc, :white, ns=140, label="Direct Estimation")
 	plot_estimation_error!(pll, hists_is_fit, thepurple, ns=140, label="Fit Proposal")
@@ -593,7 +600,7 @@ begin
 		ysfail = [0.02 for s in 𝐬fail] #[pdf(dist, s) for s in 𝐬fail]
 		inds_fail = findall(𝐬 .< γ2)
 		# ws_fail = max.(min.(ws[inds_fail], 4), 0.1)
-		ws_fail = pdf.(Normal(), 𝐬fail) / pdf.(dist, 𝐬fail)
+		ws_fail = pdf.(Normal(), 𝐬fail) ./ pdf.(dist, 𝐬fail)
 		𝐬succ= filter(x->x>γ2, 𝐬)
 		yssucc = [0.02 for s in 𝐬succ] #[pdf(dist, s) for s in 𝐬succ]
 		inds_succ = findall(𝐬 .> γ2)