In [10]:

    

%matplotlib inline
import pandas as pd
from matplotlib.ticker import ScalarFormatter, FormatStrFormatter
import matplotlib
matplotlib.rcParams['figure.figsize'] = (11.0, 7.0)
import matplotlib.pyplot as plt
import re
import numpy as np
from  matplotlib.ticker import FuncFormatter
import glob
import os


    

In [11]:

    

dfs = []
for path in glob.glob('results/*.log'):
    fn = os.path.basename(path)
    parts = fn.split(".")
    size = int(parts[1])
    omap_max_size = parts[2]
    tmp = pd.read_csv(path, names=('iops',))
    tmp["size"] = size
    tmp["omap_max_size"] = omap_max_size
    dfs.append(tmp)
df = pd.concat(dfs)
#df[df["size"] > 32000]


    

In [12]:

    

df.groupby(['size', 'omap_max_size']).mean().unstack(-1).plot.bar(legend=True)


    

    
Out[12]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f63e1bc88d0>






    

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