def bcalm(input_filename, output_filename, k, m):
input_file = open(input_filename)
simple_buckets = False
if simple_buckets:
minimizers = sorted(list(set(map(lambda s: minimizer("".join(s), m), product("acgt", repeat=m)))))
buckets = Buckets(minimizers, output_filename)
else:
m *= 2
minimizers = sorted(list(set(map(lambda s: minimizer("".join(s), m), product("acgt", repeat=m)))))
buckets = Superbuckets(minimizers, output_filename)
precompute_hashes(m)
# partition k-mers
for line in input_file:
kmer = line.strip()[:-1]
bucket_minimizer = minimizer(kmer, m)
buckets.put(kmer, bucket_minimizer)
buckets.flush()
buckets.stats()
# process each bucket in minimizer order
for bucket_file, bucket_minimizer in buckets.iterate():
G = Graph(k)
buckets.flush()
G.importg(bucket_file)
G.debruijn()
G.compress(bucket_minimizer, m)
for node in G.nodes.values():
if use_tags:
node = untag(node)
min = minbutbiggerthan(node[: k - 1], node[-(k - 1) :], bucket_minimizer, m)
buckets.put(node, min)
def output(self, file):
with open(file,'w') as f:
for n in self.nodes:
node = self.nodes[n]
if use_tags:
node = untag(node)
f.write("%s;\n" % self.nodes[n])