Add Timings per Phreeqc

eval_phreeqc_per_it.jl

@@ -0,0 +1,55 @@
+using CSV, DataFrames, Statistics, Base.cumsum
+
+function read_csvs(csv_files)
+        full_vec = []
+        for file in csv_files
+                vec = (CSV.File(file; header=false)|>Tables.matrix)[1, 1:end-1]
+                push!(full_vec, vec)
+        end
+
+        return hcat(full_vec...)
+end
+
+input_dir = "per_phreeqc/"
+csv_files = readdir(input_dir, join=true)
+csv_files = filter(x -> occursin(r"worker_timings_\d+.csv", x), csv_files)
+
+mat = read_csvs(csv_files)
+
+# calculate the mean of each row
+mean_vec = vec(mean(mat; dims=2))
+
+mean_intervalls = collect(0:1000:5000)
+
+# calculate the mean of each intervall
+mean_cummulative = [mean(@view mean_vec[mean_intervalls[i]+1:mean_intervalls[i+1]])
+                    for i in 1:length(mean_intervalls)-1] .* 1e3
+
+using Plots
+
+p = plot(mean_vec .* 1e3,
+        xlabel="Iteration",
+        ylabel="Runimte [ms]",
+        xguidefontsize=8,
+        yguidefontsize=8,
+        xtickfontsize=6,
+        ytickfontsize=6,
+        legend=false,
+        formatter=:plain,
+        yminorgrid=true,
+        ylimits=(0, 16),
+        yticks=collect(0:2:16),
+        yminorticks=4,
+        linecolor=:black,
+)
+
+for i in 1:length(mean_intervalls)-1
+        plot!(p, [mean_intervalls[i]; mean_intervalls[i+1]], [mean_cummulative[i]; mean_cummulative[i]],
+                linecolor=:red,
+                linewidth=1,
+        )
+end
+
+display(p)
+
+savefig(p, "phreeeqc_per_iteration_barite.pdf")