In [36]:

    

import pandas as pd
import numpy as np

import matplotlib.pyplot as plt
plt.style.use('ggplot')
%matplotlib inline


    

In [245]:

    

pdb_id = '1OPD'


    

In [246]:

    

rmsds = pd.read_csv(pdb_id + '.rmsd.csv', index_col=0)
rmsds[:3]


    

    
Out[246]:






  

    

      

      
fragment_size
      
group_count
      
max_templates
      
max_blast
      
matrix
      
rmsd
    
  
  

    

      
0
      
11
      
4
      
200
      
2000
      
PAM30
      
29.448881
    
    

      
1
      
5
      
8
      
50
      
500
      
BLOSUM62
      
24.286318
    
    

      
2
      
7
      
10
      
100
      
2000
      
BLOSUM62
      
27.771044
    
  

In [247]:

    

len(rmsds)


    

    
Out[247]:





288

In [298]:

    

ax = rmsds.hist(column='rmsd', figsize=(8,4))[0][0]
_ = ax.set(ylabel="Frequency", xlabel="RMSD", title="RMSD Histogram")


    

In [250]:

    

#fig = plt.figure(figsize=(10,6))
#ax = fig.add_subplot(1, 1, 1)
#rmsds.hist(column='rmsd', by='group_count', ax=ax)


    

In [251]:

    

def line_plot(df, column, title=None):
    fig = plt.figure(figsize=(12,5))
    ax = fig.add_subplot(1, 1, 1, xlabel="Experimento", ylabel="RMSD")
    for value in rmsds[column].unique():
        ax.plot(df[df[column] == value]['rmsd'], label=value)
    ax.legend()
    ax.set_title(title)
    fig.savefig(pdb_id + '.' + column + '.line.svg', format='svg')
    return ax


    

In [252]:

    

def scatter_plot(df, column, title):
    fig = plt.figure(figsize=(12,5))
    ax = fig.add_subplot(1, 1, 1, xticks=rmsds[column].unique())
    df.plot(column, "rmsd", ax=ax, kind='scatter')
    ax.set(title=title, xlabel=title, ylabel='RMSD')
    fig.savefig(pdb_id + '.' + column +  '.scatter.svg', format='svg')
    return ax


    

In [275]:

    

def box_plot(df, column, title):
    fig = plt.figure(figsize=(12,5))
    ax = fig.add_subplot(1, 1, 1, ylabel="RMSD", xlabel=title)
    df.boxplot('rmsd', column, ax=ax, showmeans=True)
    ax.set(title=title, xlabel=title, ylabel='RMSD')
    fig.suptitle('')
    fig.savefig(pdb_id + '.' + column +  '.boxplot.svg', format='svg')
    return ax


    

In [276]:

    

rmsds = rmsds.sort_values(by=['group_count', 'max_templates', 'max_blast', 'matrix', 'fragment_size'])
rmsds[:6]


    

    
Out[276]:






  

    

      

      
fragment_size
      
group_count
      
max_templates
      
max_blast
      
matrix
      
rmsd
    
  
  

    

      
116
      
5
      
4
      
50
      
500
      
BLOSUM62
      
33.556824
    
    

      
194
      
7
      
4
      
50
      
500
      
BLOSUM62
      
20.404449
    
    

      
104
      
9
      
4
      
50
      
500
      
BLOSUM62
      
26.297052
    
    

      
123
      
11
      
4
      
50
      
500
      
BLOSUM62
      
31.184532
    
    

      
28
      
5
      
4
      
50
      
500
      
PAM30
      
35.649433
    
    

      
4
      
7
      
4
      
50
      
500
      
PAM30
      
22.181728
    
  

In [299]:

    

line_plot(rmsds, 'fragment_size', "Fragment Size")


    

    
Out[299]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fce5dbdd8>






    

In [278]:

    

scatter_plot(rmsds, 'fragment_size', "Fragment Size")


    

    




/home/mchelem/dev/cref2/env/lib/python3.4/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):






    
Out[278]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd5ced4a8>






    

In [279]:

    

box_plot(rmsds, 'fragment_size', "Fragment Size")


    

    
Out[279]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd5c8b358>






    

In [280]:

    

rmsds = rmsds.sort_values(by=['fragment_size', 'matrix', 'max_blast', 'max_templates', 'group_count'])
rmsds[:6]


    

    
Out[280]:






  

    

      

      
fragment_size
      
group_count
      
max_templates
      
max_blast
      
matrix
      
rmsd
    
  
  

    

      
116
      
5
      
4
      
50
      
500
      
BLOSUM62
      
33.556824
    
    

      
212
      
5
      
6
      
50
      
500
      
BLOSUM62
      
34.630268
    
    

      
1
      
5
      
8
      
50
      
500
      
BLOSUM62
      
24.286318
    
    

      
167
      
5
      
10
      
50
      
500
      
BLOSUM62
      
26.546434
    
    

      
276
      
5
      
4
      
100
      
500
      
BLOSUM62
      
27.109640
    
    

      
208
      
5
      
6
      
100
      
500
      
BLOSUM62
      
25.765680
    
  

In [281]:

    

line_plot(rmsds, 'group_count', "Number of Groups")


    

    
Out[281]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd5e7b6d8>






    

In [282]:

    

box_plot(rmsds, 'group_count', "Number of Groups")


    

    
Out[282]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd5f2f780>






    

In [283]:

    

rmsds = rmsds.sort_values(by=['fragment_size', 'group_count', 'max_blast', 'matrix', 'max_templates'])
rmsds[:6]


    

    
Out[283]:






  

    

      

      
fragment_size
      
group_count
      
max_templates
      
max_blast
      
matrix
      
rmsd
    
  
  

    

      
116
      
5
      
4
      
50
      
500
      
BLOSUM62
      
33.556824
    
    

      
276
      
5
      
4
      
100
      
500
      
BLOSUM62
      
27.109640
    
    

      
10
      
5
      
4
      
200
      
500
      
BLOSUM62
      
33.810535
    
    

      
28
      
5
      
4
      
50
      
500
      
PAM30
      
35.649433
    
    

      
58
      
5
      
4
      
100
      
500
      
PAM30
      
16.302038
    
    

      
96
      
5
      
4
      
200
      
500
      
PAM30
      
22.605623
    
  

In [284]:

    

line_plot(rmsds, 'max_templates', "Number of Templates")


    

    
Out[284]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd6d16978>






    

In [285]:

    

box_plot(rmsds, 'max_templates', "Number of Templates")


    

    
Out[285]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd6f4eef0>






    

In [286]:

    

rmsds = rmsds.sort_values(by=['fragment_size', 'group_count', 'max_templates', 'max_blast', 'matrix'])
rmsds[:4]


    

    
Out[286]:






  

    

      

      
fragment_size
      
group_count
      
max_templates
      
max_blast
      
matrix
      
rmsd
    
  
  

    

      
116
      
5
      
4
      
50
      
500
      
BLOSUM62
      
33.556824
    
    

      
28
      
5
      
4
      
50
      
500
      
PAM30
      
35.649433
    
    

      
130
      
5
      
4
      
50
      
1000
      
BLOSUM62
      
33.556824
    
    

      
202
      
5
      
4
      
50
      
1000
      
PAM30
      
35.649433
    
  

In [287]:

    

line_plot(rmsds, 'matrix', "Substitution Matrix")


    

    
Out[287]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd6f55d68>






    

In [288]:

    

box_plot(rmsds, 'matrix', "Substitution Matrix")


    

    
Out[288]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f7fd732cac8>






    

In [302]:

    

from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm

fig = plt.figure(figsize=(12,8))
ax = fig.add_subplot(111, projection='3d', xlabel="Fragment Size", ylabel="Number of Groups", zlabel="RMSD")
surf = ax.plot_trisurf(rmsds['fragment_size'], rmsds['group_count'], rmsds['rmsd'], cmap=cm.Blues)
fig.colorbar(surf)


    

    




/home/mchelem/dev/cref2/env/lib/python3.4/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):






    
Out[302]:





<matplotlib.colorbar.Colorbar at 0x7f7fce311780>