Plotting utility function

Project.toml

@@ -12,8 +12,10 @@ JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MAT = "23992714-dd62-5051-b70f-ba57cb901cac"
 MutableNamedTuples = "af6c499f-54b4-48cc-bbd2-094bba7533c7"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
+StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]

examples/basic_example.jl

@@ -3,7 +3,7 @@
 # We start by importing the BeforeIT library and other useful libraries.
 
 import BeforeIT as Bit
-using FileIO, Plots, StatsPlots
+using FileIO, Plots
 
 
 # We then initialise the model loading some precomputed set of parameters and by specifying a number of epochs.
@@ -43,18 +43,12 @@ end
 
 # We can then plot any time series stored in the data tracker, for example
 
-p1 = plot(data.real_gdp, title = "gdp", titlefont = 10)
-p2 = plot(data.real_household_consumption, title = "household cons.", titlefont = 10)
-p3 = plot(data.real_government_consumption, title = "gov. cons.", titlefont = 10)
-p4 = plot(data.real_capitalformation, title = "capital form.", titlefont = 10)
-p5 = plot(data.real_exports, title = "exports", titlefont = 10)
-p6 = plot(data.real_imports, title = "imports", titlefont = 10)
-p7 = plot(data.wages, title = "wages", titlefont = 10)
-p8 = plot(data.euribor, title = "euribor", titlefont = 10)
-p9 = plot(data.nominal_gdp ./ data.real_gdp, title = "gdp deflator", titlefont = 10)
+plot(data.real_gdp, title = "gdp", titlefont = 10)
 
+# Or we can plot multiple time series at once using the function `plot_data`
 
-plot(p1, p2, p3, p4, p5, p6, p7, p8, p9, layout = (3, 3), legend = false)
+ps = Bit.plot_data(data, quantities = [:real_gdp, :real_household_consumption, :real_government_consumption, :real_capitalformation, :real_exports, :real_imports, :wages, :euribor, :gdp_deflator])
+plot(ps..., layout = (3, 3))
 
 # To run multiple monte-carlo repetitions in parallel we can use
 
@@ -69,38 +63,8 @@ Threads.nthreads()
 # To activate Julia with a specific number of threads, say 8, you can use the command
 # `julia -t 8` in the terminal.
 
-# We can then plot the results of the monte-carlo repetitions.
-# Since we are saving the initial data point, we effectively have T+1 data points in our time series.
-
-Te = T + 1
-
-p1 = errorline(1:Te, data_vector.real_gdp, errorstyle = :ribbon, title = "gdp", titlefont = 10)
-p2 = errorline(
-    1:Te,
-    data_vector.real_household_consumption,
-    errorstyle = :ribbon,
-    title = "household cons.",
-    titlefont = 10,
-)
-p3 =
-    errorline(1:Te, data_vector.real_government_consumption, errorstyle = :ribbon, title = "gov. cons.", titlefont = 10)
-p4 = errorline(1:Te, data_vector.real_capitalformation, errorstyle = :ribbon, title = "capital form.", titlefont = 10)
-p5 = errorline(1:Te, data_vector.real_exports, errorstyle = :ribbon, title = "exports", titlefont = 10)
-p6 = errorline(1:Te, data_vector.real_imports, errorstyle = :ribbon, title = "imports", titlefont = 10)
-p7 = errorline(1:Te, data_vector.wages, errorstyle = :ribbon, title = "wages", titlefont = 10)
-p8 = errorline(1:Te, data_vector.euribor, errorstyle = :ribbon, title = "euribor", titlefont = 10)
-p9 = errorline(
-    1:Te,
-    data_vector.nominal_gdp ./ data.real_gdp,
-    errorstyle = :ribbon,
-    title = "gdp deflator",
-    titlefont = 10,
-)
-plot(p1, p2, p3, p4, p5, p6, p7, p8, p9, layout = (3, 3), legend = false)
-
-plot(p1, p4, p5, p3, p8, p9, layout = (3, 2), legend = false, size = (400, 600), dpi = 300, left_margin = 3Plots.mm) 
-
-plot(p1, p4, p5, p3, p8, p9, layout = (2, 3), legend = false, size = (600, 400), dpi = 300)#, left_margin = 3Plots.mm) 
-
-
-savefig("output.png")
+# We can then plot the results of the monte-carlo repetitions using the function `plot_data_vector`
+
+ps = Bit.plot_data_vector(data_vector)
+plot(ps..., layout = (3, 3))
+

src/BeforeIT.jl

@@ -46,6 +46,7 @@ include("utils/epsilon.jl")
 include("utils/positive.jl")
 include("utils/toannual.jl")
 include("utils/get_predictions_from_sims.jl")
+include("utils/plot_data_vector.jl")
 
 # calibration
 include("utils/calibration.jl")

src/utils/plot_data_vector.jl

@@ -0,0 +1,44 @@
+using Plots, StatsPlots
+
+const default_quantities = [:real_gdp, :real_household_consumption, :real_government_consumption, :real_capitalformation, :real_exports, :real_imports, :wages, :euribor, :gdp_deflator]
+
+# define a table that maps the quantities to concise names
+const quantity_titles = Dict(
+	:real_gdp => "gdp",
+	:real_household_consumption => "household cons.",
+	:real_government_consumption => "gov. cons.",
+	:real_capitalformation => "capital form.",
+	:real_exports => "exports",
+	:real_imports => "imports",
+	:gdp_deflator => "gdp deflator",
+)
+
+function plot_data_vector(data_vector::Vector{Data}; titlefont = 9, quantities = default_quantities)	
+	Te = length(data_vector[1].wages)	
+	ps = []
+
+	for q in quantities
+		# define title via the table only if the entry exists
+		title = haskey(quantity_titles, q) ? quantity_titles[q] : string(q)
+		if q == :gdp_deflator
+			push!(ps, errorline(1:Te, data_vector.nominal_gdp ./ data_vector.real_gdp, errorstyle = :ribbon, title = title, titlefont = titlefont, legend = false))
+		else
+			push!(ps, errorline(1:Te, getproperty(data_vector, q), errorstyle = :ribbon, title = title, titlefont = titlefont, legend = false))
+		end
+	end
+	return ps
+end
+
+function plot_data(data::Data; titlefont = 9, quantities = default_quantities)
+	ps = []
+	for q in quantities
+		title = haskey(quantity_titles, q) ? quantity_titles[q] : string(q)
+		if q == :gdp_deflator
+			push!(ps, plot(data.nominal_gdp ./ data.real_gdp, title = title, titlefont = titlefont, legend = false))
+		else
+			push!(ps, plot(getproperty(data, q), title = title, titlefont = titlefont, legend = false))
+		end
+	end
+	return ps
+end
+