def eulerian_path(edge_dict):
'''Returns an Eulerian path from the given edges.'''
# Determine the unbalanced edges.
out_values = reduce(lambda a, b: a + b, edge_dict.values())
for node in set(out_values + edge_dict.keys()):
out_value = out_values.count(node)
if node in edge_dict:
in_value = len(edge_dict[node])
else:
in_value = 0
if in_value < out_value:
unbalanced_from = node
elif out_value < in_value:
unbalanced_to = node
# Add an edge connecting the unbalanced edges.
if unbalanced_from in edge_dict:
edge_dict[unbalanced_from].append(unbalanced_to)
else:
edge_dict[unbalanced_from] = [unbalanced_to]
# Get the Eulerian Cycle from the edges, including the unbalanced edge.
cycle = eulerian_cycle(edge_dict)
# Find the location of the unbalanced edge in the eulerian cycle.
divide_point = filter(
lambda i: cycle[i:i + 2] == [unbalanced_from, unbalanced_to],
xrange(len(cycle) - 1))[0]
# Remove the unbalanced edge, and shift appropriately, overlapping the head and tail.
return cycle[divide_point + 1:] + cycle[1:divide_point + 1]
def eulerian_path(edge_dict):
'''Returns an Eulerian path from the given edges.'''
# Determine the unbalanced edges.
out_values = reduce(lambda a,b: a+b, edge_dict.values())
for node in set(out_values+edge_dict.keys()):
out_value = out_values.count(node)
if node in edge_dict:
in_value = len(edge_dict[node])
else:
in_value = 0
if in_value < out_value:
unbalanced_from = node
elif out_value < in_value:
unbalanced_to = node
# Add an edge connecting the unbalanced edges.
if unbalanced_from in edge_dict:
edge_dict[unbalanced_from].append(unbalanced_to)
else:
edge_dict[unbalanced_from] = [unbalanced_to]
# Get the Eulerian Cycle from the edges, including the unbalanced edge.
cycle = eulerian_cycle(edge_dict)
# Find the location of the unbalanced edge in the eulerian cycle.
divide_point = filter(lambda i: cycle[i:i+2] == [unbalanced_from, unbalanced_to], xrange(len(cycle)-1))[0]
# Remove the unbalanced edge, and shift appropriately, overlapping the head and tail.
return cycle[divide_point+1:]+cycle[1:divide_point+1]
The course is run on Coursera and the assignments and textbook are hosted on Stepic
Problem Title: Universal String Problem
Assignment #: 05
Problem ID: C
URL: https://beta.stepic.org/Bioinformatics-Algorithms-2/From-Eulers-Theorem-to-an-Algorithm-for-Finding-Eulerian-Cycles-203/#step-8
'''
from Assignment_04E import eulerian_cycle
from itertools import product
# Read the input data.
with open('data/stepic_5c.txt') as input_data:
k = int(input_data.read().strip())
# Create the edges.
universal_dict = {}
for kmer in [''.join(item) for item in product('01', repeat=k)]:
if kmer[:-1] in universal_dict:
universal_dict[kmer[:-1]].append(kmer[1:])
else:
universal_dict[kmer[:-1]] = [kmer[1:]]
# Get the cycle, remove the repeated last entry for the associated path.
path = eulerian_cycle(universal_dict)
# Print and save the answer.
print ''.join([item[0] for item in path[:-1]])
with open('output/Assignment_05C.txt', 'w') as output_data:
output_data.write(''.join([item[0] for item in path[:-1]]))
