In [1]:

    

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import csv
plt.style.use('ggplot')


    

In [16]:

    

# create a CSV file by hand from 'lein test' output
perf_df = pd.read_csv("/users/rallen/Documents/Devel/clojure/iris/test.csv")
perf_df.head()


    

    
Out[16]:






  

    

      

      
date
      
logical cpu
      
jdk
      
clojure
      
type
      
parallelism
      
time (ms)
    
  
  

    

      
0
      
2016/01/20
      
8
      
1.8.0_72
      
1.6.0
      
512_cubes
      
1
      
9999.430526
    
    

      
1
      
2016/01/20
      
8
      
1.8.0_72
      
1.6.0
      
512_cubes
      
2
      
6112.124196
    
    

      
2
      
2016/01/20
      
8
      
1.8.0_72
      
1.6.0
      
512_cubes
      
3
      
4579.741014
    
    

      
3
      
2016/01/20
      
8
      
1.8.0_72
      
1.6.0
      
512_cubes
      
4
      
4390.740270
    
    

      
4
      
2016/01/20
      
8
      
1.8.0_72
      
1.6.0
      
512_cubes
      
6
      
3939.965605
    
  

In [21]:

    

def plot_em(sdfs):
    for i,k in enumerate(sorted(sdfs)):
        if i==0:
            ax=sdfs[k].plot(x="parallelism",y="time (ms)",
                            label=k,figsize=[16,8],marker='+',
                            title="Single Triangle")
            ax.set_xlabel("Parallelism")
            ax.set_ylabel("Render Time (ms)")
        else:
            sdfs[k].plot(x="parallelism",y="time (ms)",ax=ax,label=k,marker='+')
            
sf=perf_df[perf_df["type"]=="single_tri"] # select single tri
cu=perf_df[perf_df["type"]=="512_cubes"]  # select cubes


    

In [24]:

    

sdfs = {}
for v in ["1.6.0", "1.7.0", "1.8.0"]:
    sdfs[v]=sf[sf["clojure"]==v]
plot_em(sdfs)


    

In [25]:

    

sdfs = {}
for v in ["1.6.0", "1.7.0", "1.8.0"]:
    sdfs[v+" cubes"]=cu[cu["clojure"]==v]
plot_em(sdfs)


    

In [ ]: