Figure - usALEX 5 dsDNA samples FRET

In [1]:

    

from __future__ import division
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
from cycler import cycler
%matplotlib inline
%config InlineBackend.figure_format='retina'  # for hi-dpi displays
sns.set_style('whitegrid')

palette = ('Paired', 10)
sns.palplot(sns.color_palette(*palette))
sns.set_palette(*palette)


    

In [2]:

    

data_file = 'results/usALEX-5samples-E-all-methods.csv'


    

In [3]:

    

E = pd.read_csv(data_file, index_col=0)
E.round(2)


    

    
Out[3]:






  

    

      

      
E KDE
      
E Gauss
      
PR KDE
      
PR Gauss
      
SNA E mean
      
SNA E max
    
  
  

    

      
7d
      
92.90
      
92.43
      
92.87
      
92.22
      
91.25
      
93.51
    
    

      
12d
      
73.98
      
72.70
      
72.77
      
72.56
      
72.50
      
73.60
    
    

      
17d
      
42.68
      
42.26
      
43.14
      
41.98
      
42.25
      
41.81
    
    

      
22d
      
17.74
      
18.11
      
17.62
      
18.25
      
18.50
      
17.98
    
    

      
27d
      
8.26
      
8.40
      
7.81
      
7.85
      
8.00
      
8.00
    
  

In [4]:

    

import matplotlib
matplotlib.rcParams['svg.fonttype'] = 'none'


    

In [5]:

    

o = E.plot.bar(table=np.round(E, 1).T, linewidth=0)
plt.ylabel('FRET (%)')
plt.gca().xaxis.set_visible(False)
#plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0., frameon=True);
leg = plt.legend(bbox_to_anchor=(1.02, 1), frameon=True, borderpad=1);
leg.get_frame().set_edgecolor('white')
ax = plt.gca()
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

table = o.get_children()[-3]
table_props = table.properties()
table_cells = table_props['child_artists']
for cell in table_cells:
    cell.set_linewidth(0)
plt.savefig('figures/5dsDNA FRET usALEX.svg', dpi=300, bbox_inches='tight')


    

In [6]: