In [3]:

    

%load_ext autoreload
%autoreload 2

import os
import numpy as np
import pandas as pd

from browser import *


    

    




The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

In [4]:

    

exps = [
    'C100_DenseBest_F',
    'C100_DenseBest_Linear1_F',
    'C100_SparseBest_F',
    'C100_SparseBest_Linear1_F',
]

paths = [os.path.expanduser("~/nta/results/{}".format(e)) for e in exps]
df = load_many(paths)


    

In [5]:

    

df.shape


    

    
Out[5]:





(40, 62)

In [32]:

    

def mean_and_std(s):
    return "{:.4f} ± {:.4f}".format(s.mean(), s.std())

(df.groupby(['dataset', 'name'])
     .agg({'test_accuracy_max': [mean_and_std], 
           'mean_accuracy_max': [mean_and_std],
           'noise_accuracy_max': [mean_and_std]}))


    

    
Out[32]:







  

    

      

      

      
test_accuracy_max
      
mean_accuracy_max
      
noise_accuracy_max
    
    

      

      

      
mean_and_std
      
mean_and_std
      
mean_and_std
    
    

      
dataset
      
name
      

      

      

    
  
  

    

      
CIFAR100
      
C100_DenseBest_F
      
0.7257 ± 0.0023
      
0.4635 ± 0.0042
      
0.2190 ± 0.0078
    
    

      
C100_DenseBest_Linear1_F
      
0.7248 ± 0.0026
      
0.4568 ± 0.0049
      
0.2046 ± 0.0089
    
    

      
C100_SparseBest_F
      
0.6985 ± 0.0019
      
0.4645 ± 0.0031
      
0.2607 ± 0.0084
    
    

      
C100_SparseBest_Linear1_F
      
0.6964 ± 0.0029
      
0.4634 ± 0.0032
      
0.2676 ± 0.0119
    
  

In [33]:

    

(df.groupby(['dataset', 'name'])
     .agg({'test_accuracy_max': ['max','mean', 'std'], 
           'mean_accuracy_max': ['max', 'mean', 'std'],
           'noise_accuracy_max': ['max', 'mean', 'std']})
     .round(4))


    

    
Out[33]:







  

    

      

      

      
test_accuracy_max
      
mean_accuracy_max
      
noise_accuracy_max
    
    

      

      

      
max
      
mean
      
std
      
max
      
mean
      
std
      
max
      
mean
      
std
    
    

      
dataset
      
name
      

      

      

      

      

      

      

      

      

    
  
  

    

      
CIFAR100
      
C100_DenseBest_F
      
0.7296
      
0.7257
      
0.0023
      
0.4709
      
0.4635
      
0.0042
      
0.2371
      
0.2190
      
0.0078
    
    

      
C100_DenseBest_Linear1_F
      
0.7294
      
0.7248
      
0.0026
      
0.4642
      
0.4568
      
0.0049
      
0.2206
      
0.2046
      
0.0089
    
    

      
C100_SparseBest_F
      
0.7013
      
0.6985
      
0.0019
      
0.4682
      
0.4645
      
0.0031
      
0.2740
      
0.2607
      
0.0084
    
    

      
C100_SparseBest_Linear1_F
      
0.7020
      
0.6964
      
0.0029
      
0.4684
      
0.4634
      
0.0032
      
0.2830
      
0.2676
      
0.0119
    
  

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