In [1]:

    

%pylab inline
%config InlineBackend.figure_format = 'retina'


    

    




Populating the interactive namespace from numpy and matplotlib

In [27]:

    

import pandas as pd
import seaborn as sns
from ficus import FigureManager
from IPython.display import FileLink


    

In [44]:

    

meta_cols = ['full', 'tip', 'island', 'trivial']
data = pd.read_csv('petmar.kidney.nodemeta.csv')
del data['unknown']


    

In [45]:

    

with FigureManager(filename='petmar.kidney.n_unode_meta.png', ncols=2, figsize=(16,8), show=True) as (fig, ax_mat):
    data[meta_cols].plot(ax=ax_mat[0], title='Number of Unitig-Node Types', lw=4)
    ax_mat[0].set_xlabel('Read Number')
    
    data[meta_cols].divide(data['n_unodes'], axis=0).plot(ax=ax_mat[1], lw=4,
                                                          title='Proportion of Unitig-Node Types, petMar Kidney')
    ax_mat[1].set_xlabel('Read Number')
FileLink('petmar.kidney.n_unode_meta.png')


    

    













    
Out[45]:




petmar.kidney.n_unode_meta.png

In [39]:

    

with FigureManager(filename='petmar.kidney.n_unode_props.png', figsize=(16,12), show=True) as (fig, ax):
    data[meta_cols].divide(data['n_unodes'], axis=0).plot(ax=ax, lw=4,
                                                          title='Proportion of Unitig-Node Types, petMar Kidney')
    ax.set_xlabel('Read Number')
FileLink('petmar.kidney.n_unode_props.png')


    

    













    
Out[39]:




petmar.kidney.n_unode_props.png

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