def test_writing(self):
networks_table, networks = read_networks(path.join(TEST_DIR, 'network_random'))
tmp_dir = path.join(TEST_DIR, 'tmp')
makedirs(tmp_dir, exist_ok=True)
write_networks(tmp_dir, networks_table, networks)
_networks_table, _networks = read_networks(tmp_dir)
self.assertTrue(networks_table.equals(_networks_table))
guid = networks_table['GUID'][0]
self.assertTrue(networks[guid]['node_table'].equals(_networks[guid]['node_table']))
self.assertTrue(networks[guid]['edge_table'].equals(_networks[guid]['edge_table']))
rmtree(tmp_dir)
def test_create_networkx_graph(self):
networks_table, networks = read_networks(path.join(TEST_DIR, 'network_random'))
graphs = nx.from_perseus(networks_table, networks)
self.assertEqual(3, len(graphs))
for i, G in enumerate(graphs):
self.assertEqual(150, G.number_of_edges(), G.graph['Name'])
self.assertEqual(100, G.number_of_nodes())
def test_reading_single_network(self):
networks_table, networks = read_networks(path.join(TEST_DIR, 'network_random'))
self.assertEqual(3, networks_table.shape[0])
self.assertEqual(3, len(networks))
for guid, name in networks_table[['GUID', 'Name']].values:
network = networks[guid]
self.assertEqual(name, network['name'])
node_table = network['node_table']
self.assertEqual(100, node_table.shape[0])
edge_table = network['edge_table']
self.assertEqual(150, edge_table.shape[0])
def test_networkx_graph_roundtrip(self):
networks_table, networks = read_networks(path.join(TEST_DIR, 'network_random'))
graphs = nx.from_perseus(networks_table, networks)
_networks_table, _networks = nx.to_perseus(graphs)
self.assertTrue(networks_table.sort_index(axis=1).equals(_networks_table.sort_index(axis=1)))
for guid in networks_table['GUID']:
node_table = networks[guid]['node_table'].sort_values('Node').reset_index(drop=True)
_node_table = _networks[guid]['node_table'].sort_values('Node').reset_index(drop=True)
edge_table = networks[guid]['edge_table'].sort_values(['Source','Target']).reset_index(drop=True)
_edge_table = _networks[guid]['edge_table'].sort_values(['Source', 'Target']).reset_index(drop=True)
self.assertTrue(node_table.equals(_node_table))
self.assertTrue(edge_table.equals(_edge_table))
#source https://github.com/jdrudolph/perseuspy
import sys
from perseuspy import pd
from perseuspy.parameters import *
_, paramfile, infile, outfile = sys.argv # read arguments from the command line
parameters = parse_parameters(paramfile) # parse the parameters file
df = pd.read_perseus(infile) # read the input matrix into a pandas.DataFrame
some_value = doubleParam(parameters, 'some value') # extract a parameter value
df2 = some_value / df.drop('Name', 1)
df2.to_perseus(outfile) # write pandas.DataFrame in Perseus txt format
import sys
from perseuspy import nx, pd, read_networks, write_networks
_, paramfile, infolder, outfolder = sys.argv # read arguments from the command line
networks_table, networks = read_networks(infolder) # networks in tabular form
graphs = nx.from_perseus(networks_table, networks) # graphs as networkx objects
_networks_table, _networks = nx.to_perseus(graphs) # convert back into tabular form
write_networks(tmp_dir, networks_table, networks) # write to folder
import pandas as pd
data = pd.read_table("C:/Users/animeshs/OneDrive - NTNU/OneDrive - NTNU/Jimita/txt48/proteinGroups.txt",sep='\t', index_col=0, header=0, lineterminator='\n')
data.head()
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
dataLFQlog2=np.log2(dataLFQ+1)
dataLFQlog2.hist()
label = pd.read_table("C:/Users/animeshs/OneDrive - NTNU/OneDrive - NTNU/Jimita/txt48/Groups.txt",sep='\t', index_col=0, header=0, lineterminator='\n')