def test_consume(self):
return # @CTB
kt = self.kt
# consume a test string, and verify that consume works.
s = "ATGAGAGACACAGGGAGAGACCCAATTAGAGAATTGGACC"
kt.consume(s)
kt2 = khmer.new_ktable(L)
for start in range(0, len(s) - L + 1):
word = s[start:start + L]
kt2.count(word)
for i in range(0, kt.n_entries()):
n = kt.get(i) # test 'consume_str' numbers
n3 = kt2.get(i) # and 'count' count.
assert n == n3
for i in range(0, kt.n_entries()):
kt.set(i, 1)
for i in range(0, kt.n_entries()):
assert (kt.get(i) == 1)
def test_consume(self):
return # @CTB
kt = self.kt
# consume a test string, and verify that consume works.
s = "ATGAGAGACACAGGGAGAGACCCAATTAGAGAATTGGACC"
kt.consume(s)
kt2 = khmer.new_ktable(L)
for start in range(0, len(s) - L + 1):
word = s[start:start + L]
kt2.count(word)
for i in range(0, kt.n_entries()):
n = kt.get(i) # test 'consume_str' numbers
n3 = kt2.get(i) # and 'count' count.
assert n == n3
for i in range(0, kt.n_entries()):
kt.set(i, 1)
for i in range(0, kt.n_entries()):
assert(kt.get(i) == 1)
def test_collision_2(self):
return # @CTB
kt = khmer.new_ktable(10)
GG = 'G' * 10 # forward_hash: 1048575
assert kt.forward_hash(GG) == 1048575
collision_1 = 'AACGGTCGGA' # forward_hash: 48572
assert kt.forward_hash(collision_1) == 48572
collision_2 = 'AACTTGTTAC' # forward_hash: 38738
assert kt.forward_hash(collision_2) == 38738
# note, hash(GG) % 1000003 == hash(collision_1)
# note, hash(GG) % 1009837 == hash(collision_2)
hi = self.hi
hi.consume(GG)
hi.consume(collision_2)
assert hi._kh1.get(GG) == 1
assert hi._kh2.get(GG) == 2
assert hi.get_min_count(GG) == 1
assert hi.get_max_count(GG) == 1
def test_complete_no_collision():
kh = khmer.new_hashtable(4, 4**4)
kt = khmer.new_ktable(4)
for i in range(0, kt.n_entries()):
s = kt.reverse_hash(i)
kh.count(s)
n_palindromes = 0
n_rc_filled = 0
n_fwd_filled = 0
for i in range(0, kt.n_entries()):
s = kt.reverse_hash(i)
if kh.get(s): # string hashing is rc aware
n_rc_filled += 1
if kh.get(s) == 1: # palindromes are singular
n_palindromes += 1
if kh.get(i): # int hashing is not rc aware
n_fwd_filled += 1
assert n_rc_filled == kt.n_entries(), n_rc_filled
assert n_palindromes == 16, n_palindromes # @CTB check this
assert n_fwd_filled == kt.n_entries() / 2 + n_palindromes / 2, \
n_fwd_filled
def enumerate_kmers(kmer_len):
"""
Return all kmers as strings.
"""
ktable = khmer.new_ktable(kmer_len)
kmers = [ktable.reverse_hash(n) \
for n in range(ktable.n_entries())]
return kmers
def enumerate_kmers(kmer_len):
"""
Return all kmers as strings.
"""
ktable = khmer.new_ktable(kmer_len)
kmers = [ktable.reverse_hash(n) \
for n in range(ktable.n_entries())]
return kmers
def process_file(filename, HT_SIZE_array):
N_HT = 4
K = 12
list_average_miscount = []
list_average_miscount_perc = []
list_fp_miscount0 = []
print filename
for HT_SIZE in HT_SIZE_array:
print HT_SIZE
ht = khmer.new_counting_hash(K, HT_SIZE, N_HT)
ht.consume_fasta(filename)
ktable = khmer.new_ktable(K)
f = screed.open(filename)
for record in f:
sequence = record['sequence']
ktable.consume(sequence)
list_miscount = []
list_miscount_perc = []
total_kmer = 0 # total number of unique k-mers
miscount0 = 0
for i in range(0, ktable.n_entries()):
n = ktable.get(i)
if n:
total_kmer = total_kmer + 1
kmer2 = ktable.reverse_hash(i)
miscount = ht.get(kmer2) - ktable.get(kmer2) ######
# if ht.get(kmer2)<ktable.get(kmer2):
# print kmer2,ht.get(kmer2),ktable.get(kmer2)
miscount_perc = miscount / ktable.get(kmer2)
list_miscount.append(miscount)
list_miscount_perc.append(miscount_perc)
if miscount > 0:
miscount0 = miscount0 + 1
average_miscount = float(sum(list_miscount)) / len(list_miscount)
list_average_miscount.append(average_miscount)
average_miscount_perc = float(
sum(list_miscount_perc)) / len(list_miscount_perc)
list_average_miscount_perc.append(average_miscount_perc)
fp_miscount0 = float(miscount0) / total_kmer
list_fp_miscount0.append(fp_miscount0)
to_return = [
list_average_miscount, list_fp_miscount0, total_kmer,
list_average_miscount_perc
]
return to_return
def count_kmers_and_reads(in_fastq, kmer_size):
ktable = khmer.new_ktable(kmer_size)
read_count = collections.defaultdict(int)
with open(in_fastq) as in_handle:
i = 0
for (_, seq, _) in FastqGeneralIterator(in_handle):
i += 1
#if i > 1e5: break
if seq.find("N") == -1:
ktable.consume(seq)
read_count[seq] += 1
return ktable, dict(read_count)
def count_kmers_and_reads(in_fastq, kmer_size):
ktable = khmer.new_ktable(kmer_size)
read_count = collections.defaultdict(int)
with open(in_fastq) as in_handle:
i = 0
for (_, seq, _) in FastqGeneralIterator(in_handle):
i += 1
#if i > 1e5: break
if seq.find("N") == -1:
ktable.consume(seq)
read_count[seq] += 1
return ktable, dict(read_count)
def process_file(filename,HT_SIZE_array):
N_HT = 4
K = 12
list_average_miscount = []
list_average_miscount_perc = []
list_fp_miscount0 = []
print filename
for HT_SIZE in HT_SIZE_array:
print HT_SIZE
ht = khmer.new_counting_hash(K, HT_SIZE, N_HT)
ht.consume_fasta(filename)
ktable = khmer.new_ktable(K)
for n, record in enumerate(fasta_iter(open(filename))):
sequence = record['sequence']
# ktable.consume(sequence)
seq_len = len(sequence)
for n in range(0,seq_len+1-K):
kmer = sequence[n:n+K]
ktable.count(kmer)
list_miscount = []
list_miscount_perc = []
total_kmer = 0 # total number of unique k-mers
miscount0 = 0
for i in range(0, ktable.n_entries()):
n = ktable.get(i)
if n:
total_kmer = total_kmer + 1
kmer2 = ktable.reverse_hash(i)
miscount = ht.get(kmer2) - ktable.get(kmer2)######
miscount_perc = miscount/ktable.get(kmer2)
list_miscount.append(miscount)
list_miscount_perc.append(miscount_perc)
if miscount > 0:
miscount0 = miscount0 + 1
average_miscount = float(sum(list_miscount))/len(list_miscount)
list_average_miscount.append(average_miscount)
average_miscount_perc = float(sum(list_miscount_perc))/len(list_miscount_perc)
list_average_miscount_perc.append(average_miscount_perc)
fp_miscount0 = float(miscount0)/total_kmer
list_fp_miscount0.append(fp_miscount0)
to_return = [list_average_miscount,list_fp_miscount0,total_kmer,list_average_miscount_perc]
return to_return
def load_fastx_into_ktable(fastx_fname, kmer_len):
t1 = time.time()
ktable = khmer.new_ktable(kmer_len)
# Load up the FASTA into ktable
for fastx_entry in fastx_utils.get_fastx_entries(fastx_fname):
fastx_name, fastx_seq = fastx_entry
# Skip very short sequences
if len(fastx_seq) < kmer_len:
continue
ktable.consume(fastx_seq)
t2 = time.time()
print "Loading up of seqs into ktable took %.2f seconds." %(t2 - t1)
return ktable
def load_fastx_into_ktable(fastx_fname, kmer_len):
t1 = time.time()
ktable = khmer.new_ktable(kmer_len)
# Load up the FASTA into ktable
for fastx_entry in fastx_utils.get_fastx_entries(fastx_fname):
fastx_name, fastx_seq = fastx_entry
# Skip very short sequences
if len(fastx_seq) < kmer_len:
continue
ktable.consume(fastx_seq)
t2 = time.time()
print "Loading up of seqs into ktable took %.2f seconds." % (t2 - t1)
return ktable
def test_update(self):
kt = self.kt
# intersection
for i in range(0, 4**L / 4):
kt.set(i * 4, 1)
kt2 = khmer.new_ktable(L)
for i in range(0, 4**L / 5):
kt2.set(i * 5, 1)
kt.update(kt2)
for i in range(0, 4**L):
if kt.get(i):
assert i % 4 == 0 or i % 5 == 0
def test_update(self):
kt = self.kt
# intersection
for i in range(0, 4 ** L / 4):
kt.set(i * 4, 1)
kt2 = khmer.new_ktable(L)
for i in range(0, 4 ** L / 5):
kt2.set(i * 5, 1)
kt.update(kt2)
for i in range(0, 4 ** L):
if kt.get(i):
assert i % 4 == 0 or i % 5 == 0
def calc_tetra(seqs):
ktable = khmer.new_ktable(4)
for seq in seqs:
ktable.consume(str(seq.seq))
tetramers = {}
for a in ['A', 'C', 'G', 'T']:
for b in ['A', 'C', 'G', 'T']:
for c in ['A', 'C', 'G', 'T']:
for d in ['A', 'C', 'G', 'T']:
tetramers[a+b+c+d] = 0
for t in tetramers.keys():
tetramers[t] = int(ktable.get(t))
print tetramers
def main(inp_name, outp_name, min_seq_len):
outfp = open(outp_name, 'w')
min_seq_len = int(min_seq_len)
for record in screed.open(inp_name):
if len(record.sequence) < min_seq_len:
continue
kt = khmer.new_ktable(KSIZE)
kt.consume(record.sequence)
x = []
for i in range(4**KSIZE):
x.append("%s" % (kt.get(i), ))
vector = " ".join(x)
print >> outfp, "%s %s" % (record.name.split('\t')[0], vector)
def main(inp_name, outp_name, min_seq_len):
outfp = open(outp_name, 'w')
min_seq_len = int(min_seq_len)
for record in screed.open(inp_name):
if len(record.sequence) < min_seq_len:
continue
kt = khmer.new_ktable(KSIZE)
kt.consume(record.sequence)
x = []
for i in range(4**KSIZE):
x.append("%s" % (kt.get(i),))
vector = " ".join(x)
print >>outfp, "%s %s" % (record.name.split('\t')[0], vector)
def test_intersection(self):
kt = self.kt
# intersection
for i in range(0, 4 ** L / 4):
kt.set(i * 4, 1)
kt2 = khmer.new_ktable(L)
for i in range(0, 4 ** L / 5):
kt2.set(i * 5, 1)
kt3 = kt.intersect(kt2)
assert kt3.get(20) == 2
for i in range(0, 4 ** L):
if kt3.get(i):
assert i % 4 == 0
assert i % 5 == 0
def test_intersection(self):
kt = self.kt
# intersection
for i in range(0, 4**L / 4):
kt.set(i * 4, 1)
kt2 = khmer.new_ktable(L)
for i in range(0, 4**L / 5):
kt2.set(i * 5, 1)
kt3 = kt.intersect(kt2)
assert kt3.get(20) == 2
for i in range(0, 4**L):
if kt3.get(i):
assert i % 4 == 0
assert i % 5 == 0
def test_complete_4_collision():
kh = khmer.new_hashtable(4, 4**4 / 4)
kt = khmer.new_ktable(4)
for i in range(0, kt.n_entries()):
s = kt.reverse_hash(i)
kh.count(s)
n_rc_filled = 0
n_fwd_filled = 0
for i in range(0, 64):
s = kt.reverse_hash(i)
if kh.get(s): # string hashing is rc aware
n_rc_filled += 1
if kh.get(i): # int hashing is not rc aware
n_fwd_filled += 1
assert n_rc_filled == 64, n_rc_filled
def test_collision_2(self):
kt = khmer.new_ktable(12)
GG = 'G' * 12 # forward_hash: 11184810
assert khmer.forward_hash(GG, 12) == 11184810
collision_1 = 'AAACGTATGACT'
assert khmer.forward_hash(collision_1, 12) == 184777L
collision_2 = 'AAATACCGAGCG'
assert khmer.forward_hash(collision_2, 12) == 76603L
# hash(GG) % 1000003 == hash(collision_1)
# hash(GG) % 1009837 == hash(collision_2)
hi = self.hi
hi.consume(GG)
hi.consume(collision_2)
assert hi.get(GG) == 1
def test_collision_2(self):
kt = khmer.new_ktable(12)
GG = 'G' * 12 # forward_hash: 11184810
assert khmer.forward_hash(GG, 12) == 11184810
collision_1 = 'AAACGTATGACT'
assert khmer.forward_hash(collision_1, 12) == 184777L
collision_2 = 'AAATACCGAGCG'
assert khmer.forward_hash(collision_2, 12) == 76603L
# hash(GG) % 1000003 == hash(collision_1)
# hash(GG) % 1009837 == hash(collision_2)
hi = self.hi
hi.consume(GG)
hi.consume(collision_2)
assert hi.get(GG) == 1
def makeKmerArray(screedb,ksize,normalize):
"""
This takes a screedb file and a k-mer size in inputs,
and print the ktable.
"""
ktable = khmer.new_ktable(ksize)
knames=[]
print str(ksize) + "-mer" + sep,
for i in range(0, ktable.n_entries()):
knames.append(ktable.reverse_hash(i))
print sep.join(knames)
if norm:
for record in screedb.itervalues():
tot=float()
kmers=[]
ktable.clear()
ktable.consume(str(record.sequence))
print record.name,
for i in range(0, ktable.n_entries()):
kmers.append(ktable.get(i))
tot=tot+ktable.get(i)
#print kmers
kmersNorm = [float(x)/tot for x in kmers]
#print kmersNorm
for ele in kmersNorm:
sys.stdout.write(sep + '%f' % (ele))
print
else:
for record in screedb.itervalues():
ktable.clear()
ktable.consume(str(record.sequence))
sys.stdout.write(record.name)
for i in range(0, ktable.n_entries()):
sys.stdout.write(sep + str(ktable.get(i)))
print
def makeKmerArray(screedb, ksize, normalize):
"""
This takes a screedb file and a k-mer size in inputs,
and print the ktable.
"""
ktable = khmer.new_ktable(ksize)
knames = []
print str(ksize) + "-mer" + sep,
for i in range(0, ktable.n_entries()):
knames.append(ktable.reverse_hash(i))
print sep.join(knames)
if norm:
for record in screedb.itervalues():
tot = float()
kmers = []
ktable.clear()
ktable.consume(str(record.sequence))
print record.name,
for i in range(0, ktable.n_entries()):
kmers.append(ktable.get(i))
tot = tot + ktable.get(i)
#print kmers
kmersNorm = [float(x) / tot for x in kmers]
#print kmersNorm
for ele in kmersNorm:
sys.stdout.write(sep + '%f' % (ele))
print
else:
for record in screedb.itervalues():
ktable.clear()
ktable.consume(str(record.sequence))
sys.stdout.write(record.name)
for i in range(0, ktable.n_entries()):
sys.stdout.write(sep + str(ktable.get(i)))
print
K = 12 # size of K
N = 25000 # 1/4 the size of the genome
P_ERROR = .01 # per-base probability of error
###
# construct a random genome
genome = "A"*N + "C"*N + "G"*N + "T"*N
genome = list(genome)
random.shuffle(genome)
genome = "".join(genome)
###
# count the number of unique k-mers
kt = khmer.new_ktable(K)
kt.consume(genome)
total = 0
for i in range(0, 4**K):
if kt.get(i):
total += 1
print >> sys.stderr, "%d unique k-mers in genome" % total
###
# go through, sample with replacement and mutation, and calculate
# number of novel k-mers picked as a function of sampling.
kt = khmer.new_ktable(K)
def setup(self):
# make a new ktable.
self.kt = khmer.new_ktable(L)
return round(estimate)
def _bitscan(self, x, m):
v = 1
while v<=m and not x&0x80000000:
v+=1
x<<=1
return v
if __name__ == '__main__':
k=12
kt=khmer.new_ktable(k)
alphabet={0:'A',1:'T',2:'G',3:'C'}
given_string=''
for i in range(1000):
given_string+=alphabet[random.randint(0,3)]
n=kt.consume(given_string)
H = HyperLogLog(8)
for i in range(n):
H.add(given_string[i:i+k],k)
from threading import Thread
import time
import khmer
class ConsumeThread(Thread):
def __init__(self, wordsize, genome):
self.wordsize = wordsize
self.genome = genome
Thread.__init__(self)
def run(self):
self.kt = khmer.consume_genome(self.wordsize, self.genome)
genome = open('/tmp/all2.dna').read()
nthreads = 2
length = len(genome)
genome1 = genome[:length/2]
genome2 = genome[length/2:]
t1 = ConsumeThread(5, genome1)
t2 = ConsumeThread(5, genome2)
t1.start()
t2.start()
t1.join()
t2.join()
master_kt = khmer.new_ktable(5)
master_kt.update(t1.kt)
master_kt.update(t2.kt)
def setup(self):
# make a new ktable.
self.kt = khmer.new_ktable(L)
ht = khmer.new_counting_hash(K, HT_SIZE, N_HT)
unique_kmer = []
for n, record in enumerate(fasta_iter(open(filename))):
sequence = record['sequence']
seq_len = len(sequence)
for n in range(0,seq_len+1-K):
kmer = sequence[n:n+K]
if (not ht.get(kmer)):
unique_kmer.append(kmer)
ht.count(kmer)
#for kmer2 in unique_kmer:
# print kmer2,ht.get(kmer2)
ktable = khmer.new_ktable(K)
for n, record in enumerate(fasta_iter(open(filename))):
sequence = record['sequence']
seq_len = len(sequence)
for n in range(0,seq_len+1-K):
kmer = sequence[n:n+K]
ktable.count(kmer)
false = 0
all_n = 1
for kmer2 in unique_kmer:
if ht.get(kmer2) != ktable.get(kmer2):
false = false+1
all_n = all_n +1
fp = false*100.0/all_n
import sys
sys.path.insert(0, 'build/lib.linux-i686-2.3/')
import khmer
ktable = khmer.new_ktable(6)
ktable.consume("ATGAGAGACACAGGGAGAGACCCAATTAGAGAATTGGACC")
for i in range(0, ktable.n_entries()):
n = ktable.get(i)
if n:
print ktable.reverse_hash(i), "is present", n, "time(s)."
import khmer
class ConsumeThread(Thread):
def __init__(self, wordsize, genome):
self.wordsize = wordsize
self.genome = genome
Thread.__init__(self)
def run(self):
self.kt = khmer.consume_genome(self.wordsize, self.genome)
genome = open('/tmp/all2.dna').read()
nthreads = 2
length = len(genome)
genome1 = genome[:length / 2]
genome2 = genome[length / 2:]
t1 = ConsumeThread(5, genome1)
t2 = ConsumeThread(5, genome2)
t1.start()
t2.start()
t1.join()
t2.join()
master_kt = khmer.new_ktable(5)
master_kt.update(t1.kt)
master_kt.update(t2.kt)
