fonsp/custom_plots_pop.jl

## custom_plots_pop.jl

using Plots
using ClimateMARGO
using LaTeXStrings
using Colors

# Helpers

function pl_percent_formatter(y)
	"$(Integer(round(y*100)))%"
end

function pl_plot_refline!(x, y)
	plot!(x, y, color="rgba(0,0,0,.5)", label=nothing, linestyle=:dash)
end


function pl_fill_between!(x, y1, y2; kwargs...)
	plot!(x, y1, fillrange=[y2, y1]; kwargs...)
end

function pl_fill_past!(model, ylim)
    is_past = (model.domain .<= model.present_year)
    pl_fill_between!(
        model.domain[is_past],
        ones(size(model.domain[is_past])) * ylim[1] * 2.,
        ones(size(model.domain[is_past])) * ylim[2] * 2.,
        facecolor = "b", alpha = 0.1,
		ylim=ylim,
		label=nothing,
    )
end

function pl_finish_years_plot!(model::ClimateModel; when=missing, ylim=nothing, refline=nothing)
	plot!(
		xlabel="year",
		ylim=ylim,
		grid=true,
		xlim=(model.domain[1], 2200.),
		xticks=model.domain[1]:40.:2200.,
    )
	if refline !== nothing
		t = if when === missing
			model.domain
		else
			model.domain[when]
		end
		pl_plot_refline!(t, fill(refline, size(t)))
	end
	if ylim !== nothing
		pl_fill_past!(model, ylim)
	end
	return plot!()
end

# Model plots

function pl_plot_emissions(model::ClimateModel)
    data = [
        effective_baseline_emissions(model),
        effective_emissions(model),
	]
    labels = [L"$rq$ (no-policy baseline)" L"$rq(1-M) - q_{0}R$ (controlled)"]
	limit = maximum(effective_baseline_emissions(model))
	ylim = 1.1 .* (-limit, limit)
    plot(
        model.domain,
        data,
		title="Effective emissions",
		ylabel=L"effective CO$_{2e}$ emissions [ppm / yr]",
        label=labels,
    )
	pl_finish_years_plot!(model, ylim=ylim, refline=0.0)
end

function pl_plot_concentrations(model::ClimateModel)
	data = [
		CO₂_baseline(model),
        CO₂(model),
	]
    labels = [L"$c$ (no-policy baseline)" L"$c_{M,R}$ (controlled)"]
	limit = maximum(CO₂_baseline(model))
	ylim = 1.1 .* (0, limit)
    plot(
        model.domain,
        data,
		title="Concentrations",
		ylabel=L"CO$_{2e}$ concentration [ppm]",
        label=labels,
    )
	pl_finish_years_plot!(model, ylim=ylim)
end

function pl_plot_temperatures(model::ClimateModel; hide_baseline=false)
	if !hide_baseline
		plot(model.domain, δT_baseline(model), color=1, label=L"$T$ (no-policy baseline)")
	else
		plot()
	end

	data = [
		δT_no_geoeng(model),
        δT(model),
		δT(model).*sqrt.(1. .- model.controls.adapt),
	]
    labels = [L"$T_{M,R}$ (controlled with $G=0$)" L"$T_{M,R,G}$ (controlled)" L"$T_{M,R,G,A}$ (adapted)"]
	colors = [2 4 3]
	limit = maximum(δT_baseline(model))
	ylim = 1.1 .* (0, limit)
    plot!(
        model.domain,
        data,
		title="Temparature change since 1850",
		ylabel=L"temperature anomaly [$^{\circ}$C]",
        label=labels,
		color=colors,
    )
	pl_finish_years_plot!(model, ylim=ylim, refline=2.0)
end

function pl_plot_controls(model::ClimateModel)

	data = [
		model.controls.mitigate,
        model.controls.remove,
		model.controls.adapt,
		model.controls.geoeng,
	]
	labels = ["Mitigation" "CO₂ Removal" "Adaptation" "Geoengineering"]
    # labels = [L"$M$ (emissions mitigation)" L"$R$ (carbon dioxide removal)" L"$A$ (adaptation)" L"$G$ (solar geoengineering)"]
    plot(
        model.domain,
        data,
		title="Optimized control deployments",
		yformatter=pl_percent_formatter,
		label=labels,
		width=3,
    )

	pl_finish_years_plot!(model, ylim=(0., 1.))
end

function pl_plot_benefits(model::ClimateModel; discounted=true)
	discount = if discounted
		discounting(model)
	else
		1.0
	end

	when = (model.domain .> model.present_year)
    benefits = (damage_cost_baseline(model) - damage_cost(model))

	t = model.domain[when]

	plot()
	pl_fill_between!(
		t,
		zeros(size(t)),
		((benefits - control_cost(model)) .* discount)[when],
		fillcolor = "rgba(0,0,0,.15)",
		label=nothing
	)

	data = [
        (benefits .* discount)[when],
		(- control_cost(model) .* discount)[when],
		((benefits - control_cost(model)) .* discount)[when],
	]
    labels = [L"$T_{M,R}$ (controlled with $G=0$)" L"$T_{M,R,G}$ (controlled)" L"$T_{M,R,G,A}$ (adapted)"]
	colors = [2 4 3]
    plot!(
        model.domain[when],
        data,
		title="Cost-benefit analysis",
		ylabel=L"discounted costs and benefits [10$^{12}$ \$ / year]",
        label=labels,
		color=colors,
    )
	pl_finish_years_plot!(model, when=when, refline=0.0)
end

function pl_plot_damages(model::ClimateModel; discounted=false, normalized=false)
	discount = if discounted
		deepcopy(discounting(model))
	else
		1.0
	end
    E = if normalized
		deepcopy(model.economics.GWP)/100.
	else
		1.0
	end

	when = (model.domain .> model.present_year)

	t = model.domain[when]

	plot()
	pl_fill_between!(
		t,
		zeros(size(t)),
		(control_cost(model) .* discount ./ E)[when],
		fillcolor = 4,
		#alpha=.2,
		label=nothing
	)

	data = [
        (damage_cost_baseline(model) .* discount ./ E)[when],
		(net_cost(model) .* discount ./ E)[when],
		(damage_cost(model) .* discount ./ E)[when],
		(control_cost(model) .* discount ./ E)[when],
	]
    labels = ["uncontrolled damages" "net costs (controlled damages + controls)" "controlled damages" "cost of controls"]
	colors = [1 :black 2 4]
    plot!(
        model.domain[when],
        data,
		title="Costs of avoiding a damage threshold",
		ylabel=L"discounted costs [10$^{12}$ \$ / year]",
        label=labels,
		color=colors,
    )
	plot!(
		t,
		(model.economics.β .* (model.economics.GWP ./ E) .* (2.0^2).*ones(size(model.domain)))[when],
		color="rgba(0,0,0,.5)",
		label=L"damage threshold at 2$^{\circ}$ C with $A=0$",
		linestyle=:dash
	)
	pl_finish_years_plot!(model)
end

# State plot

function pl_plot_state(model::ClimateModel; plot_legends=true)
	plot(
		pl_plot_emissions(model),
		pl_plot_concentrations(model),
		pl_plot_temperatures(model),
		pl_plot_controls(model),
		pl_plot_benefits(model),
		pl_plot_damages(model),
    	layout=(2,3),
		size=(1300,800)
    )
end

## margo_interactive_1.jl
### A Pluto.jl notebook ###
# v0.9.7

using Markdown
macro bind(def, element)
    quote
        local el = $(esc(element))
        global $(esc(def)) = Core.applicable(Base.peek, el) ? Base.peek(el) : missing
        el
    end
end

# ╔═╡ 85d394a6-ab2e-11ea-162a-bf287f53a2b9
begin
	cd("/mnt/c/dev/julia/margo_tests/")
	import Pkg
	Pkg.activate(".")
	using ClimateMARGO
	import Plots
	import PlutoUI
	Plots.gr()
end

# ╔═╡ ad4c245a-ab2e-11ea-315d-7bd757b9d9a6
include("./custom_plots_pop.jl")

# ╔═╡ 7b158352-ab43-11ea-06bf-070326039159
t = 2020.0:20:2200.0

# ╔═╡ b6292bb6-ab2e-11ea-3763-734fa0bcc219
begin
	model_initial = ClimateModel(; t=collect(t), dt=step(t))
end

# ╔═╡ 5bd5d6be-ab33-11ea-19e4-cfa028000899
md"# Maximum temperature"

# ╔═╡ d71ce3a0-ab31-11ea-2c25-51b58f110211
md"##### `0.0 °C` $(@bind T_max PlutoUI.Slider(0.0 : 0.01 : 4.0; default=4.0)) `4.0 °C` "

# ╔═╡ 48169fe0-ab48-11ea-18e6-37d29e7f279b
md"## Results"

# ╔═╡ 4b9298ac-ab4a-11ea-050e-2d26ce07187f
@bind show_damages html"<input type='checkbox' id='show-damage'><label for='show-damage'> Show economic damage</label>"

# ╔═╡ 06339a5c-ab38-11ea-07ff-1f724147d164
@bind reset PlutoUI.Button("Reset graph")

# ╔═╡ f84c8ec6-ab34-11ea-0b6e-67ff6c00c45e
md"## Appendix"

# ╔═╡ d0df7460-ab2e-11ea-2d5f-adb730df9082
model = begin
	optimize_controls!(model_initial; temp_goal=T_max)
	model_initial
end

# ╔═╡ 4fd40bba-ab33-11ea-1112-c503ffda1799
"""
<blockquote><p style="font-size: 1.3rem">Temperature limit of <b>$(T_max) °C</b> can be achieved for <b>$(round(discounted_total_control_cost(model); sigdigits=3)) trillion USD</b>.</p></blockquote>
"""|> HTML

# ╔═╡ fc8aa7e0-ab2e-11ea-100b-b3e79670d056
pl_plot_controls(model)

# ╔═╡ c4159248-ab36-11ea-0304-efb66384670e
begin
	reset # reactive reference
	explored = (Number[], Number[], Number[])
end;

# ╔═╡ e71f4126-ab36-11ea-19bf-db353b290d68
explored_current = (
	push!(explored[1], T_max),
	push!(explored[2], discounted_total_control_cost(model)),
	push!(explored[3], discounted_total_damage_cost(model)),
);

# ╔═╡ a8db7eae-ab48-11ea-2678-eb14348b2172
r = [1 2 3] |> typeof

# ╔═╡ d0c275a8-ab48-11ea-0739-8d4049d5bdd8
[1:3 1:3]

# ╔═╡ 5eace9d4-ab49-11ea-23dc-2bdb9ce7cc46
(
	1,
	2
	)

# ╔═╡ 69aa4df2-ab4b-11ea-388b-679feb1c3627
function results_text(short)
	if short
		md"Try changing the goal temperature above!"
	else
		md"A **higher goal temperature** can be achieved at a **lower cost**. "
	end
end

# ╔═╡ f162108c-ab4a-11ea-192a-db8fe908fe3b
results_text(length(explored_current[1]) < 10)

# ╔═╡ 8d84c28e-ab4b-11ea-3d37-87665a18b296
function explored_graph(explored_current, show_damages, T_max)
	begin
	cost_lim = show_damages ? 1600.0 : 400.0
	data = if show_damages
		[explored_current[2] explored_current[3]]
	else
		explored_current[2]
	end
	labels = show_damages ? ["Control cost" "Economic damage"] : "Control cost"

	Plots.scatter(
		explored_current[1],
		data,
		xlabel="Maximum temperature",
		ylabel="Costs [trillion USD]",
		xlims=(0.0, 4.0),
		ylims=(0.0, cost_lim),
		label=labels
	)
	pl_fill_between!([0.0, 2.0], [0.0, 0.0], [cost_lim, cost_lim]; color="rgba(30,30,255,.05)", label="Paris agreement")
	Plots.vline!([T_max]; width=3, color="rgba(0,0,0,.3)", label="Selected goal")
end
end

# ╔═╡ cdee4292-ab36-11ea-004a-d1051fca11ec
explored_graph(explored_current, show_damages, T_max)

# ╔═╡ Cell order:
# ╠═85d394a6-ab2e-11ea-162a-bf287f53a2b9
# ╠═ad4c245a-ab2e-11ea-315d-7bd757b9d9a6
# ╠═7b158352-ab43-11ea-06bf-070326039159
# ╠═b6292bb6-ab2e-11ea-3763-734fa0bcc219
# ╟─5bd5d6be-ab33-11ea-19e4-cfa028000899
# ╟─d71ce3a0-ab31-11ea-2c25-51b58f110211
# ╟─4fd40bba-ab33-11ea-1112-c503ffda1799
# ╟─fc8aa7e0-ab2e-11ea-100b-b3e79670d056
# ╟─48169fe0-ab48-11ea-18e6-37d29e7f279b
# ╟─f162108c-ab4a-11ea-192a-db8fe908fe3b
# ╟─cdee4292-ab36-11ea-004a-d1051fca11ec
# ╟─4b9298ac-ab4a-11ea-050e-2d26ce07187f
# ╟─06339a5c-ab38-11ea-07ff-1f724147d164
# ╟─f84c8ec6-ab34-11ea-0b6e-67ff6c00c45e
# ╠═d0df7460-ab2e-11ea-2d5f-adb730df9082
# ╠═c4159248-ab36-11ea-0304-efb66384670e
# ╠═e71f4126-ab36-11ea-19bf-db353b290d68
# ╠═a8db7eae-ab48-11ea-2678-eb14348b2172
# ╠═d0c275a8-ab48-11ea-0739-8d4049d5bdd8
# ╠═5eace9d4-ab49-11ea-23dc-2bdb9ce7cc46
# ╠═69aa4df2-ab4b-11ea-388b-679feb1c3627
# ╠═8d84c28e-ab4b-11ea-3d37-87665a18b296

	using Plots
	using ClimateMARGO
	using LaTeXStrings
	using Colors

	# Helpers

	function pl_percent_formatter(y)
	"$(Integer(round(y*100)))%"
	end

	function pl_plot_refline!(x, y)
	plot!(x, y, color="rgba(0,0,0,.5)", label=nothing, linestyle=:dash)
	end


	function pl_fill_between!(x, y1, y2; kwargs...)
	plot!(x, y1, fillrange=[y2, y1]; kwargs...)
	end

	function pl_fill_past!(model, ylim)
	is_past = (model.domain .<= model.present_year)
	pl_fill_between!(
	model.domain[is_past],
	ones(size(model.domain[is_past])) * ylim[1] * 2.,
	ones(size(model.domain[is_past])) * ylim[2] * 2.,
	facecolor = "b", alpha = 0.1,
	ylim=ylim,
	label=nothing,
	)
	end

	function pl_finish_years_plot!(model::ClimateModel; when=missing, ylim=nothing, refline=nothing)
	plot!(
	xlabel="year",
	ylim=ylim,
	grid=true,
	xlim=(model.domain[1], 2200.),
	xticks=model.domain[1]:40.:2200.,
	)
	if refline !== nothing
	t = if when === missing
	model.domain
	else
	model.domain[when]
	end
	pl_plot_refline!(t, fill(refline, size(t)))
	end
	if ylim !== nothing
	pl_fill_past!(model, ylim)
	end
	return plot!()
	end

	# Model plots

	function pl_plot_emissions(model::ClimateModel)
	data = [
	effective_baseline_emissions(model),
	effective_emissions(model),
	]
	labels = [L"$rq$ (no-policy baseline)" L"$rq(1-M) - q_{0}R$ (controlled)"]
	limit = maximum(effective_baseline_emissions(model))
	ylim = 1.1 .* (-limit, limit)
	plot(
	model.domain,
	data,
	title="Effective emissions",
	ylabel=L"effective CO$_{2e}$ emissions [ppm / yr]",
	label=labels,
	)
	pl_finish_years_plot!(model, ylim=ylim, refline=0.0)
	end

	function pl_plot_concentrations(model::ClimateModel)
	data = [
	CO₂_baseline(model),
	CO₂(model),
	]
	labels = [L"$c$ (no-policy baseline)" L"$c_{M,R}$ (controlled)"]
	limit = maximum(CO₂_baseline(model))
	ylim = 1.1 .* (0, limit)
	plot(
	model.domain,
	data,
	title="Concentrations",
	ylabel=L"CO$_{2e}$ concentration [ppm]",
	label=labels,
	)
	pl_finish_years_plot!(model, ylim=ylim)
	end

	function pl_plot_temperatures(model::ClimateModel; hide_baseline=false)
	if !hide_baseline
	plot(model.domain, δT_baseline(model), color=1, label=L"$T$ (no-policy baseline)")
	else
	plot()
	end

	data = [
	δT_no_geoeng(model),
	δT(model),
	δT(model).*sqrt.(1. .- model.controls.adapt),
	]
	labels = [L"$T_{M,R}$ (controlled with $G=0$)" L"$T_{M,R,G}$ (controlled)" L"$T_{M,R,G,A}$ (adapted)"]
	colors = [2 4 3]
	limit = maximum(δT_baseline(model))
	ylim = 1.1 .* (0, limit)
	plot!(
	model.domain,
	data,
	title="Temparature change since 1850",
	ylabel=L"temperature anomaly [$^{\circ}$C]",
	label=labels,
	color=colors,
	)
	pl_finish_years_plot!(model, ylim=ylim, refline=2.0)
	end

	function pl_plot_controls(model::ClimateModel)

	data = [
	model.controls.mitigate,
	model.controls.remove,
	model.controls.adapt,
	model.controls.geoeng,
	]
	labels = ["Mitigation" "CO₂ Removal" "Adaptation" "Geoengineering"]
	# labels = [L"$M$ (emissions mitigation)" L"$R$ (carbon dioxide removal)" L"$A$ (adaptation)" L"$G$ (solar geoengineering)"]
	plot(
	model.domain,
	data,
	title="Optimized control deployments",
	yformatter=pl_percent_formatter,
	label=labels,
	width=3,
	)

	pl_finish_years_plot!(model, ylim=(0., 1.))
	end

	function pl_plot_benefits(model::ClimateModel; discounted=true)
	discount = if discounted
	discounting(model)
	else
	1.0
	end

	when = (model.domain .> model.present_year)
	benefits = (damage_cost_baseline(model) - damage_cost(model))

	t = model.domain[when]

	plot()
	pl_fill_between!(
	t,
	zeros(size(t)),
	((benefits - control_cost(model)) .* discount)[when],
	fillcolor = "rgba(0,0,0,.15)",
	label=nothing
	)

	data = [
	(benefits .* discount)[when],
	(- control_cost(model) .* discount)[when],
	((benefits - control_cost(model)) .* discount)[when],
	]
	labels = [L"$T_{M,R}$ (controlled with $G=0$)" L"$T_{M,R,G}$ (controlled)" L"$T_{M,R,G,A}$ (adapted)"]
	colors = [2 4 3]
	plot!(
	model.domain[when],
	data,
	title="Cost-benefit analysis",
	ylabel=L"discounted costs and benefits [10$^{12}$ \$ / year]",
	label=labels,
	color=colors,
	)
	pl_finish_years_plot!(model, when=when, refline=0.0)
	end

	function pl_plot_damages(model::ClimateModel; discounted=false, normalized=false)
	discount = if discounted
	deepcopy(discounting(model))
	else
	1.0
	end
	E = if normalized
	deepcopy(model.economics.GWP)/100.
	else
	1.0
	end

	when = (model.domain .> model.present_year)

	t = model.domain[when]

	plot()
	pl_fill_between!(
	t,
	zeros(size(t)),
	(control_cost(model) .* discount ./ E)[when],
	fillcolor = 4,
	#alpha=.2,
	label=nothing
	)

	data = [
	(damage_cost_baseline(model) .* discount ./ E)[when],
	(net_cost(model) .* discount ./ E)[when],
	(damage_cost(model) .* discount ./ E)[when],
	(control_cost(model) .* discount ./ E)[when],
	]
	labels = ["uncontrolled damages" "net costs (controlled damages + controls)" "controlled damages" "cost of controls"]
	colors = [1 :black 2 4]
	plot!(
	model.domain[when],
	data,
	title="Costs of avoiding a damage threshold",
	ylabel=L"discounted costs [10$^{12}$ \$ / year]",
	label=labels,
	color=colors,
	)
	plot!(
	t,
	(model.economics.β .* (model.economics.GWP ./ E) .* (2.0^2).*ones(size(model.domain)))[when],
	color="rgba(0,0,0,.5)",
	label=L"damage threshold at 2$^{\circ}$ C with $A=0$",
	linestyle=:dash
	)
	pl_finish_years_plot!(model)
	end

	# State plot

	function pl_plot_state(model::ClimateModel; plot_legends=true)
	plot(
	pl_plot_emissions(model),
	pl_plot_concentrations(model),
	pl_plot_temperatures(model),
	pl_plot_controls(model),
	pl_plot_benefits(model),
	pl_plot_damages(model),
	layout=(2,3),
	size=(1300,800)
	)
	end
	### A Pluto.jl notebook ###
	# v0.9.7

	using Markdown
	macro bind(def, element)
	quote
	local el = $(esc(element))
	global $(esc(def)) = Core.applicable(Base.peek, el) ? Base.peek(el) : missing
	el
	end
	end

	# ╔═╡ 85d394a6-ab2e-11ea-162a-bf287f53a2b9
	begin
	cd("/mnt/c/dev/julia/margo_tests/")
	import Pkg
	Pkg.activate(".")
	using ClimateMARGO
	import Plots
	import PlutoUI
	Plots.gr()
	end

	# ╔═╡ ad4c245a-ab2e-11ea-315d-7bd757b9d9a6
	include("./custom_plots_pop.jl")

	# ╔═╡ 7b158352-ab43-11ea-06bf-070326039159
	t = 2020.0:20:2200.0

	# ╔═╡ b6292bb6-ab2e-11ea-3763-734fa0bcc219
	begin
	model_initial = ClimateModel(; t=collect(t), dt=step(t))
	end

	# ╔═╡ 5bd5d6be-ab33-11ea-19e4-cfa028000899
	md"# Maximum temperature"

	# ╔═╡ d71ce3a0-ab31-11ea-2c25-51b58f110211
	md"##### `0.0 °C` $(@bind T_max PlutoUI.Slider(0.0 : 0.01 : 4.0; default=4.0)) `4.0 °C` "

	# ╔═╡ 48169fe0-ab48-11ea-18e6-37d29e7f279b
	md"## Results"

	# ╔═╡ 4b9298ac-ab4a-11ea-050e-2d26ce07187f
	@bind show_damages html"<input type='checkbox' id='show-damage'><label for='show-damage'> Show economic damage</label>"

	# ╔═╡ 06339a5c-ab38-11ea-07ff-1f724147d164
	@bind reset PlutoUI.Button("Reset graph")

	# ╔═╡ f84c8ec6-ab34-11ea-0b6e-67ff6c00c45e
	md"## Appendix"

	# ╔═╡ d0df7460-ab2e-11ea-2d5f-adb730df9082
	model = begin
	optimize_controls!(model_initial; temp_goal=T_max)
	model_initial
	end

	# ╔═╡ 4fd40bba-ab33-11ea-1112-c503ffda1799
	"""
	<blockquote><p style="font-size: 1.3rem">Temperature limit of <b>$(T_max) °C</b> can be achieved for <b>$(round(discounted_total_control_cost(model); sigdigits=3)) trillion USD</b>.</p></blockquote>
	"""\|> HTML

	# ╔═╡ fc8aa7e0-ab2e-11ea-100b-b3e79670d056
	pl_plot_controls(model)

	# ╔═╡ c4159248-ab36-11ea-0304-efb66384670e
	begin
	reset # reactive reference
	explored = (Number[], Number[], Number[])
	end;

	# ╔═╡ e71f4126-ab36-11ea-19bf-db353b290d68
	explored_current = (
	push!(explored[1], T_max),
	push!(explored[2], discounted_total_control_cost(model)),
	push!(explored[3], discounted_total_damage_cost(model)),
	);

	# ╔═╡ a8db7eae-ab48-11ea-2678-eb14348b2172
	r = [1 2 3] \|> typeof

	# ╔═╡ d0c275a8-ab48-11ea-0739-8d4049d5bdd8
	[1:3 1:3]

	# ╔═╡ 5eace9d4-ab49-11ea-23dc-2bdb9ce7cc46
	(
	1,
	2
	)

	# ╔═╡ 69aa4df2-ab4b-11ea-388b-679feb1c3627
	function results_text(short)
	if short
	md"Try changing the goal temperature above!"
	else
	md"A higher goal temperature can be achieved at a lower cost. "
	end
	end

	# ╔═╡ f162108c-ab4a-11ea-192a-db8fe908fe3b
	results_text(length(explored_current[1]) < 10)

	# ╔═╡ 8d84c28e-ab4b-11ea-3d37-87665a18b296
	function explored_graph(explored_current, show_damages, T_max)
	begin
	cost_lim = show_damages ? 1600.0 : 400.0
	data = if show_damages
	[explored_current[2] explored_current[3]]
	else
	explored_current[2]
	end
	labels = show_damages ? ["Control cost" "Economic damage"] : "Control cost"

	Plots.scatter(
	explored_current[1],
	data,
	xlabel="Maximum temperature",
	ylabel="Costs [trillion USD]",
	xlims=(0.0, 4.0),
	ylims=(0.0, cost_lim),
	label=labels
	)
	pl_fill_between!([0.0, 2.0], [0.0, 0.0], [cost_lim, cost_lim]; color="rgba(30,30,255,.05)", label="Paris agreement")
	Plots.vline!([T_max]; width=3, color="rgba(0,0,0,.3)", label="Selected goal")
	end
	end

	# ╔═╡ cdee4292-ab36-11ea-004a-d1051fca11ec
	explored_graph(explored_current, show_damages, T_max)

	# ╔═╡ Cell order:
	# ╠═85d394a6-ab2e-11ea-162a-bf287f53a2b9
	# ╠═ad4c245a-ab2e-11ea-315d-7bd757b9d9a6
	# ╠═7b158352-ab43-11ea-06bf-070326039159
	# ╠═b6292bb6-ab2e-11ea-3763-734fa0bcc219
	# ╟─5bd5d6be-ab33-11ea-19e4-cfa028000899
	# ╟─d71ce3a0-ab31-11ea-2c25-51b58f110211
	# ╟─4fd40bba-ab33-11ea-1112-c503ffda1799
	# ╟─fc8aa7e0-ab2e-11ea-100b-b3e79670d056
	# ╟─48169fe0-ab48-11ea-18e6-37d29e7f279b
	# ╟─f162108c-ab4a-11ea-192a-db8fe908fe3b
	# ╟─cdee4292-ab36-11ea-004a-d1051fca11ec
	# ╟─4b9298ac-ab4a-11ea-050e-2d26ce07187f
	# ╟─06339a5c-ab38-11ea-07ff-1f724147d164
	# ╟─f84c8ec6-ab34-11ea-0b6e-67ff6c00c45e
	# ╠═d0df7460-ab2e-11ea-2d5f-adb730df9082
	# ╠═c4159248-ab36-11ea-0304-efb66384670e
	# ╠═e71f4126-ab36-11ea-19bf-db353b290d68
	# ╠═a8db7eae-ab48-11ea-2678-eb14348b2172
	# ╠═d0c275a8-ab48-11ea-0739-8d4049d5bdd8
	# ╠═5eace9d4-ab49-11ea-23dc-2bdb9ce7cc46
	# ╠═69aa4df2-ab4b-11ea-388b-679feb1c3627
	# ╠═8d84c28e-ab4b-11ea-3d37-87665a18b296