file_uniprot = open('uniprot_whole.csv', 'r')
file_hmm = open('out.txt', 'r')
file_out = open('outfile.txt', 'w')
parsed = []
for line in file_uniprot:
parsed.append(line.split(',')[0])
for line in file_hmm:
out = line.split()[0].split('|')[1]
if out in parsed:
file_out.write('YES:' + line)
else:
file_out.write('NO:' + line)
file_uniprot.close()
file_hmm.close()
file_out.close()
file_in = open('outfile.txt', 'r')
summ_yes = 0
summ_no = 0
lines = 0
for line in file_in:
lines +=1
if 'YES' in line:
summ +=1
else:
summ_no +=1
print('summ_yes=', summ_yes)
print('summ_no=', summ_no)
print('lines=', lines)
file_in.close()
file_in = open('outfile.txt', 'r')
file_out = open('done.txt', 'w')
counter_yes = 0
counter_no = 78409
total_sum_up = 0
total_sum_down = 79050
file_out.write('Weight' + '\t' + 'Sensitivity' + '\t' + 'Specificity'+ '\n')
for line in file_in:
total_sum_up +=1
total_sum_down = total_sum_down - 1
if 'YES' in line:
counter_yes +=1
else:
counter_no = counter_no - 1
sens = counter_yes/total_sum_up
spec = counter_no/total_sum_down
file_out.write(str(line.split()[-2]) + '\t' + str(sens) + '\t' + str(spec) + '\n')
file_in.close()
file_out.close()
import matplotlib as mpl
import seaborn as sns
import pandas as pd
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
import plotly
import plotly.graph_objs as go
init_notebook_mode(connected=True)
sns.set()
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
dataset = pd.read_csv('done.txt', delimiter='\t')
dataset.head()
trace0 = go.Scatter(
x=dataset['Weight'],
y=dataset['Sensitivity'],
name='Sensitivity'
)
trace1 = go.Scatter(
x=dataset['Weight'],
y=dataset['Specificity'],
name='Specificity'
)
data = [trace0, trace1]
layout = {'title': 'ROS graph'}
fig = go.Figure(data=data, layout=layout)
iplot(fig, show_link=False)
plotly.offline.plot(fig, filename='graph.html', show_link=False);