Use time for previous step column in examples

examples/agents_visualizations.jl

@@ -192,8 +192,8 @@ plot_layout = fig[:,end+1] = GridLayout()
 count_layout = plot_layout[1,1] = GridLayout()
 
 # collect tuples with x and y values for black and white daisys
-blacks = @lift(Point2f.($(abmobs.adf).step, $(abmobs.adf).count_black))
-whites = @lift(Point2f.($(abmobs.adf).step, $(abmobs.adf).count_white))
+blacks = @lift(Point2f.($(abmobs.adf).time, $(abmobs.adf).count_black))
+whites = @lift(Point2f.($(abmobs.adf).time, $(abmobs.adf).count_white))
 
 # create an axis to plot into and style it to our liking
 ax_counts = Axis(count_layout[1,1];

examples/measurements.jl

@@ -190,8 +190,8 @@ agent_df, model_df = run!(model, 1000; adata = adata, mdata = mdata)
 
 f = Figure(resolution = (600, 800))
 ax = f[1, 1] = Axis(f, ylabel = "Daisy count", title = "Daisyworld Analysis")
-lb = lines!(ax, agent_df.step, agent_df.count_black_daisies, linewidth = 2, color = :blue)
-lw = lines!(ax, agent_df.step, agent_df.count_white_daisies, linewidth = 2, color = :red)
+lb = lines!(ax, agent_df.time, agent_df.count_black_daisies, linewidth = 2, color = :blue)
+lw = lines!(ax, agent_df.time, agent_df.count_white_daisies, linewidth = 2, color = :red)
 leg = f[1, 1] = Legend(
         f,
         [lb, lw],
@@ -210,10 +210,10 @@ highband =
 lowband =
     Measurements.value.(agent_df[!, dataname(adata[3])]) -
     Measurements.uncertainty.(agent_df[!, dataname(adata[3])])
-band!(ax2, agent_df.step, lowband, highband, color = (:steelblue, 0.5))
+band!(ax2, agent_df.time, lowband, highband, color = (:steelblue, 0.5))
 lines!(
     ax2,
-    agent_df.step,
+    agent_df.time,
     Measurements.value.(agent_df[!, dataname(adata[3])]),
     linewidth = 2,
     color = :blue,
@@ -226,10 +226,10 @@ highband =
 lowband =
     Measurements.value.(model_df.solar_luminosity) -
     Measurements.uncertainty.(model_df.solar_luminosity)
-band!(ax3, agent_df.step, lowband, highband, color = (:steelblue, 0.5))
+band!(ax3, agent_df.time, lowband, highband, color = (:steelblue, 0.5))
 lines!(
     ax3,
-    agent_df.step,
+    agent_df.time,
     Measurements.value.(model_df.solar_luminosity),
     linewidth = 2,
     color = :blue,

examples/predator_prey.jl

@@ -242,9 +242,9 @@ adf, mdf = run!(sheepwolfgrass, steps; adata, mdata)
 function plot_population_timeseries(adf, mdf)
     figure = Figure(size = (600, 400))
     ax = figure[1, 1] = Axis(figure; xlabel = "Step", ylabel = "Population")
-    sheepl = lines!(ax, adf.step, adf.count_sheep, color = :cornsilk4)
-    wolfl = lines!(ax, adf.step, adf.count_wolf, color = RGBAf(0.2, 0.2, 0.3))
-    grassl = lines!(ax, mdf.step, mdf.count_grass, color = :green)
+    sheepl = lines!(ax, adf.time, adf.count_sheep, color = :cornsilk4)
+    wolfl = lines!(ax, adf.time, adf.count_wolf, color = RGBAf(0.2, 0.2, 0.3))
+    grassl = lines!(ax, mdf.time, mdf.count_grass, color = :green)
     figure[1, 2] = Legend(figure, [sheepl, wolfl, grassl], ["Sheep", "Wolves", "Grass"])
     figure
 end

examples/sir.jl

@@ -288,10 +288,10 @@ data[1:10, :]
 N = sum(model.Ns) # Total initial population
 fig = Figure(size = (600, 400))
 ax = fig[1, 1] = Axis(fig, xlabel = "steps", ylabel = "log10(count)")
-li = lines!(ax, data.step, log10.(data[:, dataname((:status, infected))]), color = :blue)
-lr = lines!(ax, data.step, log10.(data[:, dataname((:status, recovered))]), color = :red)
+li = lines!(ax, data.time, log10.(data[:, dataname((:status, infected))]), color = :blue)
+lr = lines!(ax, data.time, log10.(data[:, dataname((:status, recovered))]), color = :red)
 dead = log10.(N .- data[:, dataname((:status, length))])
-ld = lines!(ax, data.step, dead, color = :green)
+ld = lines!(ax, data.time, dead, color = :green)
 Legend(fig[1, 2], [li, lr, ld], ["infected", "recovered", "dead"])
 fig