In [1]:

    

import pandas as pd
import numpy as np

from matplotlib import pyplot as plt
%matplotlib inline


    

In [83]:

    

bench_df = pd.read_csv('cross_cov_benchmark.csv',
                       index_col = False,
                       header = False, 
                       names = ['dims', 'samples', 'partitions', 'max_lag', 'avg_time'])

bench_df = bench_df[bench_df['partitions'] > 1]


    

In [84]:

    

bench_df.plot('dims', 'avg_time', kind = 'scatter')


    

    
Out[84]:





<matplotlib.axes._subplots.AxesSubplot at 0x10a917490>






    

In [85]:

    

bench_df[(bench_df['partitions'] > 1.0) 
         & (bench_df['max_lag'] > 3)].plot('max_lag', 'avg_time', kind = 'scatter', c = 'partitions', cmap = 'winter', lw = 0)


    

    
Out[85]:





<matplotlib.axes._subplots.AxesSubplot at 0x10a9299d0>






    

In [98]:

    

plt.scatter(bench_df['max_lag'].values, 
            bench_df['avg_time'].values, 
            s = bench_df['samples'].values / 1e4, 
            c = bench_df['partitions'].values,
            cmap = 'winter',
            lw = 0,
            alpha = 0.4)
plt.xlabel('maximum lag')
plt.ylabel('100 averaged computational time in ms')
plt.title('Cross-covariance benchmark')


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-98-ddcff306d689> in <module>()
      8 plt.xlabel('maximum lag')
      9 plt.ylabel('100 averaged computational time in ms')
---> 10 plt.colormap()
     11 plt.title('Cross-covariance benchmark')

AttributeError: 'module' object has no attribute 'colormap'





    

In [93]:

    

plt.scatter(np.log10(bench_df['samples'].values), 
            bench_df['avg_time'].values, 
            s = bench_df['max_lag'].values * 2, 
            c = bench_df['partitions'].values,
            cmap = 'winter',
            lw = 0,
            alpha = 0.4)


    

    
Out[93]:





<matplotlib.collections.PathCollection at 0x10b43ba10>






    

In [94]:

    

plt.scatter(bench_df['dims'].values, 
            bench_df['avg_time'].values, 
            s = bench_df['max_lag'].values * 2, 
            c = bench_df['partitions'].values,
            cmap = 'winter',
            lw = 0,
            alpha = 0.4)


    

    
Out[94]:





<matplotlib.collections.PathCollection at 0x10b5bb9d0>






    

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