In [25]:

    

Pkg.add("DataFrames")
Pkg.add("Gadfly")


    

    




INFO: Nothing to be done
INFO: METADATA is out-of-date — you may not have the latest version of DataFrames
INFO: Use `Pkg.update()` to get the latest versions of your packages
INFO: Nothing to be done
INFO: METADATA is out-of-date — you may not have the latest version of Gadfly
INFO: Use `Pkg.update()` to get the latest versions of your packages

In [2]:

    

cd("/Users/utensil/experiments")


    

In [4]:

    

run(`git clone https://github.com/JuliaLang/julia.git`)


    

    




Cloning into 'julia'...

In [3]:

    

cd("julia/test/perf/micro")


    

In [4]:

    

run(pipeline(`python perf.py`, stdout="py.csv"))


    

In [5]:

    

run(pipeline(`julia perf.jl`, stdout="jl.csv"))


    

In [6]:

    

run(pipeline(`r --vanilla --slave -f perf.R`, stdout="r.csv"))


    

    




载入需要的程辑包：compiler

In [7]:

    

run(pipeline(`cat py.csv r.csv`, stdout="benchmarks.csv"))


    

In [8]:

    

using DataFrames
using Gadfly


    

In [10]:

    

jl_data = readtable("jl.csv", header=false, names=[:language, :benchmark, :min, :max, :mean_time, :std])


    

    
Out[10]:




language
benchmark
min
max
mean_time
std
1
julia
fib
0.056615
12.929825
0.06721
0.095576
2
julia
parse_int
0.184276
14.152507
0.240393
0.233401
3
julia
mandel
0.207146
15.422047
0.254343
0.232392
4
julia
quicksort
0.37266
4.646582
0.442788
0.085605
5
julia
pi_sum
23.337202
40.237361
26.38479
2.331499
6
julia
rand_mat_stat
20.954935
58.0542
24.982474
5.086046
7
julia
rand_mat_mul
36.421051
49.189161
39.883087
3.066839
8
julia
printfd
25.061242
34.104159
27.590273
1.608627

In [18]:

    

benchmarks = readtable("benchmarks.csv", header=false, names=[:language, :benchmark, :mean_time])


    

    
Out[18]:




language
benchmark
mean_time
1
python
fib
2.87795066833
2
python
parse_int
2.0809173584
3
python
mandel
3.95393371582
4
python
quicksort
14.358997345
5
python
pi_sum
652.050018311
6
python
rand_mat_stat
125.365018845
7
python
rand_mat_mul
66.064119339
8
r
fib
16.0
9
r
parse_int
4.0
10
r
quicksort
93.0
11
r
mandel
12.0
12
r
pi_sum
332.0
13
r
rand_mat_stat
86.0
14
r
rand_mat_mul
137.0

In [19]:

    

jl_benchmarks = jl_data[:, [:language, :benchmark, :mean_time]]


    

    
Out[19]:




language
benchmark
mean_time
1
julia
fib
0.06721
2
julia
parse_int
0.240393
3
julia
mandel
0.254343
4
julia
quicksort
0.442788
5
julia
pi_sum
26.38479
6
julia
rand_mat_stat
24.982474
7
julia
rand_mat_mul
39.883087
8
julia
printfd
27.590273

In [20]:

    

benchmarks = [benchmarks; jl_benchmarks]


    

    
Out[20]:




language
benchmark
mean_time
1
python
fib
2.87795066833
2
python
parse_int
2.0809173584
3
python
mandel
3.95393371582
4
python
quicksort
14.358997345
5
python
pi_sum
652.050018311
6
python
rand_mat_stat
125.365018845
7
python
rand_mat_mul
66.064119339
8
r
fib
16.0
9
r
parse_int
4.0
10
r
quicksort
93.0
11
r
mandel
12.0
12
r
pi_sum
332.0
13
r
rand_mat_stat
86.0
14
r
rand_mat_mul
137.0
15
julia
fib
0.06721
16
julia
parse_int
0.240393
17
julia
mandel
0.254343
18
julia
quicksort
0.442788
19
julia
pi_sum
26.38479
20
julia
rand_mat_stat
24.982474
21
julia
rand_mat_mul
39.883087
22
julia
printfd
27.590273

In [21]:

    

p = plot(benchmarks,
    x = :language,
    y = :mean_time,
    color = :benchmark,
    Scale.y_log10,
    Guide.ylabel(nothing),
    Guide.xlabel(nothing),
    Theme(
        default_point_size = 1mm,
        guide_title_position = :left,
        colorkey_swatch_shape = :circle,
        minor_label_font = "Georgia",
        major_label_font = "Georgia",
    ),
)
draw(SVG(8inch,8inch/golden), p)


    

In [23]:

    

p = plot(benchmarks,
    x = :language,
    y = :mean_time,
    color = :benchmark,
    Scale.y_continuous,
    Guide.ylabel(nothing),
    Guide.xlabel(nothing),
    Theme(
        default_point_size = 1mm,
        guide_title_position = :left,
        colorkey_swatch_shape = :circle,
        minor_label_font = "Georgia",
        major_label_font = "Georgia",
    ),
)
draw(SVG(8inch,8inch/golden), p)


    

In [ ]: