def read_lgn(filepath):
edges_in_lgn = []
with open(filepath) as lgn_file:
lgn_reader = csv.reader(lgn_file)
lgn_reader.next() # skip the header row
edges_in_lgn = []
for row in lgn_reader:
gene_1, gene_2 = helper.swap(row[0], row[1])
edges_in_lgn.append([gene_1, gene_2])
genes_in_lgn = helper.genes_from_edges(edges_in_lgn)
return genes_in_lgn, edges_in_lgn
def __connection_in_extra_genes_step_0(self, block):
"""
calculate c[0]: whether or not this 'extra gene' appear in a specific block
"""
control = dict()
max_length = len(self.genes_in_lgn) + 2
genes_in_block = helper.genes_from_edges(block)
extra_genes = set(genes_in_block) - set(self.genes_in_lgn)
""" since we do not care how many time extra genes appear in block
we ONLY pay attention to whether it appears or not
"""
for gene in extra_genes:
control[gene] = [0] * max_length
control[gene][0] = 1
# number of times it's connected with the LGN - c[1]
# number of times it's connected with the subLGN - c[2]
# will be calculated later
return control
import os
import csv
import pdb
import logging
import helper
def read_lgn(filepath):
edges_in_lgn = []
with open(filepath) as lgn_file:
lgn_reader = csv.reader(lgn_file, delimiter=';')
lgn_reader.next() # skip the header row
edges_in_lgn = []
for row in lgn_reader:
try:
gene_1, gene_2 = helper.swap(row[0], row[1])
edges_in_lgn.append([gene_1, gene_2])
except IndexError, e:
logging.warning("%s is not in the correct format" % row)
pass
genes_in_lgn = helper.genes_from_edges(edges_in_lgn)
return genes_in_lgn, edges_in_lgn
