Make a julia package

Project.toml

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+name = "Microbenchmarks"
+uuid = "d04c57ce-49d5-44bb-b39e-e10e2075fbb8"
+authors = ["Viral B. Shah <[email protected]>"]
+version = "0.1.0"
+
+[deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Gadfly = "c91e804a-d5a3-530f-b6f0-dfbca275c004"
+StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
+
+[compat]
+CSV = "0.10.15"
+DataFrames = "1.7.0"
+Gadfly = "1.4.1"
+StatsBase = "0.34.5"

src/Microbenchmarks.jl

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+module Microbenchmarks
+
+using DataFrames, CSV, StatsBase
+
+function read_bench(benchfile::String)
+    # Load benchmark data from file
+    benchmarks = CSV.read(benchfile, DataFrame; header=["language", "benchmark", "time"])
+
+    # Capitalize and decorate language names from datafile
+    dict = Dict("c"=>"C", "julia"=>"Julia", "lua"=>"LuaJIT", "fortran"=>"Fortran", "java"=>"Java",
+                "javascript"=>"JavaScript", "matlab"=>"Matlab", "mathematica"=>"Mathematica",
+                "python"=>"Python", "octave"=>"Octave", "r"=>"R", "rust"=>"Rust", "go"=>"Go");
+    benchmarks[!,:language] = [dict[lang] for lang in benchmarks[!,:language]]
+
+    # Normalize benchmark times by C times
+    ctime = benchmarks[benchmarks[!,:language] .== "C", :]
+    benchmarks = innerjoin(benchmarks, ctime, on=:benchmark, makeunique=true)
+    select!(benchmarks, Not([:language_1]))
+    rename!(benchmarks, :time_1 =>:ctime)
+    benchmarks[!,:normtime] = benchmarks[!,:time] ./ benchmarks[!,:ctime];
+
+    # Compute the geometric mean for each language
+    langs = [];
+    means = [];
+    priorities = [];
+    for lang in unique(benchmarks[!,:language])
+        data = benchmarks[benchmarks[!,:language].== lang, :]
+        gmean = geomean(data[!,:normtime])
+        push!(langs, lang)
+        push!(means, gmean)
+        if (lang == "C")
+            push!(priorities, 1)
+        elseif (lang == "Julia")
+            push!(priorities, 2)
+        else
+            push!(priorities, 3)
+        end
+    end
+
+    # Add the geometric means back into the benchmarks dataframe
+    langmean = DataFrame(language=langs, geomean = means, priority = priorities)
+    benchmarks = innerjoin(benchmarks, langmean, on=:language)
+
+    # Put C first, Julia second, and sort the rest by geometric mean
+    sort!(benchmarks, [:priority, :geomean]);
+    sort!(langmean,   [:priority, :geomean]);
+
+    return benchmarks
+end
+
+benchmarks = read_bench("benchmarks.csv")
+
+#=
+p = plot(benchmarks,
+         x = :language,
+         y = :normtime,
+         color = :benchmark,
+         Scale.y_log10,
+         Guide.ylabel(nothing),
+         Guide.xlabel(nothing),
+         Coord.Cartesian(ymin=-0.5),
+         Theme(
+             guide_title_position = :left,
+             colorkey_swatch_shape = :circle,
+             minor_label_font = "Georgia",
+             major_label_font = "Georgia"
+         ),
+         )
+
+golden = MathConstants.golden
+#draw(SVG(8inch,8inch/golden), p)
+draw(SVG("benchmarks.svg", 10inch, 10inch/golden), p)
+=#
+
+end #module