def main(argv):
opts = docopt.docopt(__doc__, argv)
p = 0.01
if opts['-P'] is not None:
p = float(opts['-P'])
inp = opts['<input>']
out = opts['<output>']
with container(out, 'w') as z:
h = {}
with container(inp, 'r') as z0:
K = z0.meta['K']
z.meta = z0.meta.copy()
del z.meta['kmers']
del z.meta['counts']
xs = readKmersAndCounts(z0)
if opts['-D'] is None:
if opts['-S'] is not None:
S = long(opts['-S'])
random.seed(S)
writeKmersAndCounts(K, sampleR(p, xs, h), z)
else:
S = 0
if opts['-S'] is not None:
S = long(opts['-S'])
writeKmersAndCounts(K, sampleD(p, S, xs, h), z)
z.meta['hist'] = h
def test_rw_2():
K = 27
M = (1 << (2 * K)) - 1
N = 100000
random.seed(17)
xs = [random.randint(0, M) for i in xrange(N)]
nm = tmpfile()
with container.container(nm, 'w') as z:
w = vecs.writer64(z, "wibble")
for x in xs:
w.append(x)
with pytest.raises(KeyError):
with container.container(nm, 'r') as z:
ys = list(vecs.read64(z, 'wibble', N))
os.remove(nm)
def main(argv):
opts = docopt.docopt(__doc__, argv)
if opts['-X']:
K = 27
if opts['-K']:
K = int(opts['-K'])
buildIndex(K, opts['<input>'], opts['<alleles>'])
return
idx = index(opts['<alleles>'])
for inp in opts['<input>']:
with container(inp, 'r') as z:
K0 = z.meta['K']
if K0 != idx.K:
print >> sys.stderr, 'Input "%d" has different k to index' % (
inp, )
sys.exit(1)
xs = readKmers(z)
cs = [idx.lens[i] for i in xrange(len(idx.lens))]
for x in xs:
for j in idx[x]:
cs[j] -= 1
for j in xrange(len(idx.lens)):
assert cs[j] >= 0
if cs[j] == 0:
print '%s\t%d\t%s' % (inp, j, idx.names[j])
def test_merg2_0():
K = 27
M = (1 << (2 * K)) - 1
N = 100000
random.seed(17)
xs = [(random.randint(0, M), pois(10)) for i in xrange(N)]
xs.sort()
ys = [(random.randint(0, M), pois(10)) for i in xrange(N)]
ys.sort()
nm0 = tmpfile()
with container(nm0, 'w') as z:
writeKmersAndCounts(K, xs, z, 'xs')
writeKmersAndCounts(K, ys, z, 'ys')
nm1 = tmpfile()
h = {}
with container(nm0, 'r') as z0, container(nm1, 'w') as z:
merge2(z, K, readKmersAndCounts(z0, 'xs'),
readKmersAndCounts(z0, 'ys'), h, 'zs')
h = h.items()
h.sort()
ws = {}
for (x, c) in xs:
ws[x] = c + ws.get(x, 0)
for (y, c) in ys:
ws[y] = c + ws.get(y, 0)
ws = ws.items()
ws.sort()
with container(nm1, 'r') as z:
zs = list(readKmersAndCounts(z, 'zs'))
assert len(ws) == len(zs)
for i in xrange(len(ws)):
assert ws[i] == zs[i]
h1 = {}
for (_, c) in ws:
h1[c] = 1 + h1.get(c, 0)
h1 = h1.items()
h1.sort()
assert len(h) == len(h1)
for i in xrange(len(h)):
assert h[i] == h1[i]
def buildIndex(K, inputs, output):
"""
Create a new k-mer index. The FASTA files named in the list
`inputs` are read in and the `K` length k-mers and their reverse
complements are extracted and collated to create an index that
maps from k-mer to sequence number (numbering from 0). The
`names` member of the KmerIndex object can be used to retrieve
the name from the sequence number.
"""
seqs = []
for inp in inputs:
with openFile(inp) as f:
seqs += list(readFasta(f))
S = []
nms = []
lens = array.array('I', [])
for i in xrange(len(seqs)):
(nm, seq) = seqs[i]
nms.append(nm)
xs = list(kmers(K, seq, True))
xs.sort()
uniq(xs)
seqs[i] = [nm, xs]
lens.append(len(xs))
S += xs
S.sort()
uniq(S)
S = sparse(2*K, S)
T = array.array('I', [0 for i in xrange(S.count() + 1)])
for i in xrange(len(seqs)):
for x in seqs[i][1]:
r = S.rank(x)
T[r] += 1
t0 = 0
for i in xrange(len(T)):
t1 = t0 + T[i]
T[i] = t0
t0 = t1
T0 = [c for c in T]
U = array.array('H', [0 for i in xrange(t0)])
for i in xrange(len(seqs)):
for x in seqs[i][1]:
r = S.rank(x)
U[T0[r]] = i
T0[r] += 1
with container(output, 'w') as z:
writeKmers(K, S.xs, z)
n = write32(z, T, 'offsets')
z.meta['T'] = n
n = write16(z, U, 'postings')
z.meta['U'] = n
n = write32(z, lens, 'lens')
z.meta['lens'] = n
z.meta['names'] = nms
def index(fn):
"""
Load a k-mer index into memory and return the resulting KmerIndex
object.
"""
with container(fn, 'r') as z:
idx = KmerIndex(z)
return idx
def test_std_0():
K = 27
M = (1 << (2 * K)) - 1
N = 100000
random.seed(17)
xs = [(random.randint(0, M), pois(10)) for i in xrange(N)]
nm = tmpfile()
with container.container(nm, 'w') as z:
std.writeKmersAndCounts(K, xs, z, 'wibble')
with container.container(nm, 'r') as z:
ys = list(std.readKmersAndCounts(z, 'wibble'))
assert len(ys) == N
for i in xrange(N):
assert xs[i] == ys[i]
os.remove(nm)
def test_rw_1():
K = 27
M = (1 << (2 * K)) - 1
N = 100000
random.seed(17)
xs = [random.randint(0, M) for i in xrange(N)]
nm = tmpfile()
with container.container(nm, 'w') as z:
vecs.write64(z, xs, "wibble")
with container.container(nm, 'r') as z:
ys = list(vecs.read64(z, 'wibble', N))
assert len(ys) == N
for i in xrange(N):
assert xs[i] == ys[i]
os.remove(nm)
def main(argv):
opts = docopt.docopt(__doc__, argv)
for inp in opts['<input>']:
with container(inp, 'r') as z:
if 'hist' in z.meta:
h = z.meta['hist'].items()
h.sort()
for (f,c) in h:
print '%s\t%d\t%d' % (inp, f, c)
def main(argv):
opts = docopt.docopt(__doc__, argv)
with container(opts['<ref>'], 'r') as z:
K = z.meta['K']
xs = array.array('L', readKmers(z))
Z = len(xs)
with container(opts['<input>'], 'r') as z0:
K0 = z0.meta['K']
if K0 != K:
print >> sys.stderr, "mismatched K (%d)" % (K0, )
sys.exit(1)
with container(opts['<output>'], 'w') as z:
if 'counts' in z0.meta:
ys = readKmersAndCounts(z0)
writeKmersAndCounts(K, project2(xs, ys), z)
else:
ys = readKmers(z0)
writeKmers(K, project1(xs, ys), z)
def main(argv):
opts = docopt.docopt(__doc__, argv)
with container(opts['<ref>'], 'r') as z:
K = z.meta['K']
xs = readKmers(z)
if opts['-H'] is not None:
d = int(opts['-H'])
ref = hamming(K, d, xs)
elif opts['-L'] is not None:
d = int(opts['-L'])
ref = levenshtein(K, d, xs)
else:
ref = ksnp(K, xs)
xs = []
for ys in ref:
xs += ys
xs.sort()
with container(opts['<output>'], 'w') as z:
writeKmers(K, xs, z)
def main(argv):
opts = docopt.docopt(__doc__, argv)
inp = opts['<input>']
out = opts['<output>']
c = 0
if opts['-c'] is not None:
c = int(opts['-c'])
with container(inp, 'r') as z:
K = z.meta['K']
h = z.meta['hist']
if c == 0:
c = infer(K, h)
print >> sys.stderr, 'inferred cutoff:', c
xs = readKmersAndCounts(z)
with container(out, 'w') as w:
w.meta = z.meta.copy()
del w.meta['kmers']
del w.meta['counts']
writeKmersAndCounts(K, trim(xs, c), w)
def main(argv):
opts = docopt.docopt(__doc__, argv)
L0 = None
if opts['-l']:
L0 = int(opts['-l'])
for inp in opts['<input>']:
with container(inp, 'r') as z:
K = z.meta['K']
L = L0
if L is None:
L = 2*K
xs = array.array('L', readKmers(z))
S = sparse(2*K, xs)
seen = bitvec(S.count())
for i in xrange(S.count()):
if seen[i]:
continue
x = S.select(i)
xb = rc(K, x)
xp = succ(K, S, xb)
if xp == 1:
# x isn't the start of a contig
continue
pth = [x]
seen[i] = 1
xn = succ(K, S, x)
while len(xn) == 1:
if seen[xn[0]] == 1:
break
x = S.select(xn[0])
pth.append(x)
seen[xn[0]] = 1
xb = rc(K, x)
j = S.rank(xb)
seen[j] = 1
xn = succ(K, S, x)
if len(pth)+K-1 < L:
continue
s = [render(K, pth[0])]
for j in xrange(1, len(pth)):
s.append("ACGT"[pth[j]&3])
print '>contig_%d\n%s' % (i, ''.join(s))
def main(argv):
opts = docopt.docopt(__doc__, argv)
fns = opts['<input>']
Z = 1
if opts['-a']:
Z = len(fns)
p = None
if opts['-p'] is not None:
p = float(opts['-p'])
for i in xrange(Z):
with container(fns[i], 'r') as z0:
xK = z0.meta['K']
xs = array.array('L', readKmers(z0))
for j in xrange(i + 1, len(fns)):
with container(fns[j], 'r') as z1:
yK = z1.meta['K']
ys = array.array('L', readKmers(z1))
if xK != yK:
print >> sys.stderr, 'mismatched K:', fns[j]
sys.exit(1)
(isec, union, d) = jaccard(xs, ys)
if p is None:
print '%s\t%s\t%d\t%d\t%d\t%d\t%f' % (
fns[i], fns[j], len(xs), len(ys), isec, union, d)
else:
pv = logIx(p, isec + 1,
(union - isec) + 1) / math.log(10)
q05 = quantBeta(0.05, isec + 1, (union - isec) + 1)
q95 = quantBeta(0.95, isec + 1, (union - isec) + 1)
print '%s\t%s\t%d\t%d\t%d\t%d\t%f\t-%f\t+%f\t%f' % (
fns[i], fns[j], len(xs), len(ys), isec, union, d,
d - q05, q95 - d, pv)
sys.stdout.flush()
def main(argv):
opts = docopt.docopt(__doc__, argv)
nms = [str(i + 1) for i in xrange(len(probesMTB))]
probes = probesMTB
if opts['-p'] is not None:
nms = []
probes = []
bad = False
with open(opts['-p']) as f:
i = 0
ln = 0
for l in f:
ln += 1
if l[0] == '#':
continue
i += 1
t = l.split()
if len(t) == 1:
nms.append(str(i))
probes.append(probe(t[0]))
elif len(t) == 2:
nms.append(t[0])
probes.append(probe(t[1]))
else:
bad = True
print >> sys.stderr, '%s line %d, badly formatted.' % (
opts['-p'], i)
if bad:
sys.exit(1)
for inp in opts['<input>']:
with container(inp, 'r') as z:
K = z.meta['K']
xs = readKmers(z)
xs = sparse(2 * K, array.array('L', xs))
res = []
for i in xrange(len(probes)):
if findProbe(probes[i], K, xs):
res.append('1')
else:
res.append('0')
if opts['-l']:
for i in xrange(len(nms)):
print '%s\t%s\t%s' % (inp, nms[i], res[i])
else:
print inp + '\t' + ''.join(res)
def main(argv):
opts = docopt.docopt(__doc__, argv)
inp = opts['<input>']
with container(inp, 'r') as z:
K = z.meta['K']
if 'kmers' not in z.meta:
print >> sys.stderr, 'cannot dump "%s" as it contains no k-mers' % (
inp, )
return
if 'counts' in z.meta:
xs = readKmersAndCounts(z)
for (x, c) in xs:
print '%s\t%d' % (render(K, x), c)
else:
xs = readKmers(z)
for x in xs:
print render(K, x)
def main(argv):
opts = docopt.docopt(__doc__, argv)
K = None
out = opts['<output>']
px = list(pairs(opts['<input>']))
if len(px) == 1:
with container(out, 'w') as z:
h = {}
acgt = [0, 0, 0, 0]
ix = px[0]
if len(ix) == 1:
with container(ix[0], 'r') as z0:
K = z0.meta['K']
xs = readKmersAndCounts(z0)
zs = hist(xs, h, acgt)
writeKmersAndCounts(K, xs, z)
else:
with container(ix[0], 'r') as z0:
K = z0.meta['K']
xs = readKmersAndCounts(z0)
with container(ix[1], 'r') as z1:
K1 = z1.meta['K']
if K1 != K:
print >> sys.stderr, "mismatched K"
sys.exit(1)
ys = readKmersAndCounts(z1)
zs = hist(merge(xs, ys), h, acgt)
writeKmersAndCounts(K, zs, z)
n = float(sum(acgt))
acgt = [c/n for c in acgt]
z.meta['hist'] = h
z.meta['acgt'] = acgt
return
tmps = []
tmpnm = tmpfile('.pmc')
with container(tmpnm, 'w') as z:
for ix in px:
if len(ix) == 1:
nm = 'tmp-' + str(len(tmps))
tmps.append(nm)
with container(ix[0], 'r') as z0:
if K is None:
K = z0.meta['K']
else:
K0 = z0.meta['K']
if K0 != K:
print >> sys.stderr, "mismatched K"
sys.exit(1)
xs = readKmersAndCounts(z0)
writeKmersAndCounts(K, xs, z, nm)
else:
nm = 'tmp-' + str(len(tmps))
tmps.append(nm)
with container(ix[0], 'r') as z0:
if K is None:
K = z0.meta['K']
else:
K0 = z0.meta['K']
if K0 != K:
print >> sys.stderr, "mismatched K"
sys.exit(1)
xs = readKmersAndCounts(z0)
with container(ix[1], 'r') as z1:
K1 = z1.meta['K']
if K1 != K:
print >> sys.stderr, "mismatched K"
sys.exit(1)
ys = readKmersAndCounts(z1)
writeKmersAndCounts(K, merge(xs, ys), z, nm)
assert K is not None
with container(out, 'w') as z:
h = {}
acgt = [0, 0, 0, 0]
with container(tmpnm, 'r') as z0:
zs = None
for fn in tmps:
xs = readKmersAndCounts(z0, fn)
if zs is None:
zs = xs
else:
zs = merge(zs, xs)
zs = hist(zs, h, acgt)
writeKmersAndCounts(K, zs, z)
n = float(sum(acgt))
acgt = [c/n for c in acgt]
z.meta['hist'] = h
z.meta['acgt'] = acgt
os.remove(tmpnm)
def main(argv):
opts = docopt.docopt(__doc__, argv)
if opts['-X']:
K = 27
S = []
N = 0
qacgt = [0, 0, 0, 0]
for fn in opts['<input>']:
with open(fn) as f:
for (nm, seq) in readFasta(f):
if len(seq) < K:
continue
for (x,p) in kmersWithPos(K, seq, True):
S.append(x)
qacgt[x&3] += 1
N += 1
S.sort()
qacgt = [float(c)/float(N) for c in qacgt]
S = sparse(2*K, array.array('L', uniq(S)))
lens = array.array('I', [])
nms = []
seqs = []
n = 0
tmp = [[] for i in xrange(S.count())]
for fn in opts['<input>']:
with open(fn) as f:
for (nm, seq) in readFasta(f):
if len(seq) < K:
print >> sys.stderr, "warning: `%s' skipped" % (nm,)
continue
nms.append(nm)
seqs.append(seq)
lens.append(len(seq))
for (x,p) in kmersWithPos(K, seq, True):
r = S.rank(x)
tmp[r].append((n, p))
n += 1
T = array.array('I', [])
U = array.array('I', [])
V = array.array('i', [])
t = 0
for nps in tmp:
T.append(t)
t += len(nps)
for (n, p) in nps:
U.append(n)
V.append(p)
T.append(t)
del tmp
gfn = opts['<genes>']
with container(gfn, 'w') as z:
z.meta['K'] = K
z.meta['S'] = S.count()
write64(z, S.xs, 'S')
z.meta['T'] = len(T)
write64(z, T, 'T')
z.meta['U'] = len(U)
write32(z, U, 'U')
z.meta['V'] = len(V)
write32s(z, V, 'V')
z.meta['lens'] = lens
z.meta['qacgt'] = qacgt
z.meta['nms'] = nms
z.meta['seqs'] = seqs
return
print >> sys.stderr, "loading..."
gfn = opts['<genes>']
with container(gfn, 'r') as z:
K = z.meta['K']
S = array.array('L', read64(z, 'S', z.meta['S']))
S = sparse(2*K, S)
T = array.array('L', read64(z, 'T', z.meta['T']))
U = array.array('I', read32(z, 'U', z.meta['U']))
V = array.array('i', read32s(z, 'V', z.meta['V']))
lens = z.meta['lens']
qacgt = z.meta['qacgt']
nms = z.meta['nms']
seqs = z.meta['seqs']
print >> sys.stderr, "done."
for fn in opts['<input>']:
L = array.array('B', [0 for i in xrange(S.count())])
Y = array.array('L', [0 for i in xrange(S.count())])
with container(fn, 'r') as z:
sacgt = z.meta['acgt']
xs = readKmers(z)
X = array.array('L', xs)
M = len(X)
resolveAll(K, S, L, Y, X)
X = sparse(2*K, X)
g = sum([qp*sp for (qp, sp) in zip(qacgt, sacgt)])
print >> sys.stderr, "g =", g
nm = [null(g, M, j) for j in range(0, K+1)]
# counts for computing distribution of prefix lengths
cnt = [[0 for j in xrange(K+1)] for i in xrange(len(nms))]
# the k-mers that we pulled by lcp from the sample
# for each position of each query.
P = [array.array('L', [0 for j in xrange(lens[i] - K + 1)]) for i in xrange(len(lens))]
# the length of the lcp for each position of each query.
Q = [array.array('B', [0 for j in xrange(lens[i] - K + 1)]) for i in xrange(len(lens))]
for i in xrange(S.count()):
for j in xrange(T[i], T[i+1]):
n = U[j]
p = V[j]
y = Y[i]
l = L[i]
cnt[n][l] += 1
if p > 0:
p -= 1
else:
p = -(p + 1)
y = rc(K, y)
if l > Q[n][p]:
Q[n][p] = l
P[n][p] = y
for i in xrange(len(nms)):
# iterate over the queries
qc = math.log(K*0.05/float(lens[i] - K + 1)/2)
# Link up "de Bruijn" sequences
m = (1 << (2*K - 2)) - 1
py = 0
u = unionfind()
for j in xrange(lens[i] - K + 1):
x = P[i][j]
y = x >> 2
if j > 0:
d = ham(py, y)
if d == 0:
u.union(j-1, j)
py = x & m
# Gather up the de Bruin fragments
udx = {}
for j in xrange(lens[i] - K + 1):
v = u.find(j)
if v not in udx:
udx[v] = []
udx[v].append(j)
# Index the left hand k-mers
idxLhs = {}
kx = []
for (jx, js) in udx.iteritems():
q = 0
for j in js:
q += math.log1p(-nm[Q[i][j]])
if q > math.log(0.05/len(js)):
continue
kx.append((-len(js), jx))
idxLhs[P[i][js[0]]] = jx
kx.sort()
# Attempt to link up fragments
links = {}
for (_, jx) in kx:
jR = udx[jx][-1]
if jR == lens[i] - K + 1:
continue
x = P[i][jR]
xs = []
lnk = None
for k in xrange(100):
ys = succ(K, X, x)
if len(ys) != 1:
break
x = ys[0]
if x in idxLhs:
lnk = idxLhs[x]
break
xs.append(x)
if lnk is not None:
links[jx] = xs
u.union(jx, lnk)
# Gather up the linked fragments
vdx = {}
for j in [jx for (_, jx) in kx]:
v = u.find(j)
if v not in vdx:
vdx[v] = []
vdx[v].append(j)
res = []
for (jxx, jxs) in vdx.iteritems():
# Order the gragments by start position
fs = [(udx[jx][0], jx) for jx in jxs]
fs.sort()
sxs = []
for fj in xrange(len(fs)):
(_, jx) = fs[fj]
beg = udx[jx][0]
end = udx[jx][-1] + 1
if fj == 0:
for j in xrange(beg):
sxs.append((0, 0))
xs = links.get(jx, None)
for j in xrange(beg, end):
x = P[i][j]
l = Q[i][j]
sxs.append((x, l))
if xs:
for x in xs:
sxs.append((x, 27))
else:
if fj < len(fs) - 1:
nxt = fs[fj+1][0]
else:
nxt = lens[i] - K + 1
for j in xrange(end, nxt):
sxs.append((0, 0))
seq = [[0, 0, 0, 0] for j in xrange(len(sxs) + K - 1)]
for j in xrange(len(sxs)):
(x, l) = sxs[j]
p = math.log1p(-nm[l])
for k in xrange(K):
seq[j + K - k - 1][x&3] += p
x >>= 2
ax = []
p = None
inf = False
for j in xrange(len(seq)):
b = 0
for k in xrange(4):
if seq[j][k] < qc:
b |= 1 << k
ax.append(fasta(b))
ssj = sum(seq[j])
if p is None:
p = ssj
else:
p = logAdd(p, ssj)
if ssj > -1e-300:
inf = True
dst = counts2cdf(cnt[i])
(_, kd) = ksDistance2(dst, nm)
df = math.ceil(len(seq)/float(K))
if inf:
q = 1e300
pv = 0.0
else:
q = 2*math.exp(p)
pv = chi2(df, q)
res.append((pv, q, kd, ''.join(ax)))
if len(res) == 0:
continue
res.sort()
if res[0][0] < -2:
#ed = lev(seqs[i], res[0][2])
ed = 0
pv = res[0][0]/math.log(10)
c2 = res[0][1]
kd = res[0][2]
a = res[0][3]
print '%d\t%d\t%d\t%g\t%g\t%g\t%s\t%s' % (i, lens[i], len(a), kd, c2, pv, nms[i], a)
sys.stdout.flush()
def main(argv):
opts = docopt.docopt(__doc__, argv)
K = int(opts['<k>'])
out = opts['<output>']
Z = 1024 * 1024 * 32
if opts['-m'] is not None:
Z = 1024 * 1024 * int(opts['-m'])
buf = KmerAccumulator()
n = 0
tmps = []
acgt = [0, 0, 0, 0]
m = 0
d = None
if opts['-D'] is not None:
d = float(opts['-D'])
S = 0
if opts['-S'] is not None:
S = int(opts['-S'])
cacheYes = set([])
cacheNo = set([])
tmpnm = tmpfile('.pmc')
with container(tmpnm, 'w') as z:
pass
PN = 1024 * 1024
nr = 0
t0 = time.time()
for fn in opts['<input>']:
for rds in mkParser(fn):
for (nm, seq) in rds:
nr += 1
if nr & (PN - 1) == 0:
t1 = time.time()
print >> sys.stderr, 'reads processed:', nr, (PN) / (
t1 - t0), 'reads/second'
t0 = t1
#buf.stat()
xs = kmersList(K, seq, True)
if d is None:
buf.addList(xs)
for x in xs:
acgt[x & 3] += 1
m += 1
n += 1
else:
for x in xs:
if x in cacheNo:
continue
if x not in cacheYes:
if not sub(S, d, x):
cacheNo.add(x)
continue
cacheYes.add(x)
buf.add(x)
acgt[x & 3] += 1
m += 1
n += 1
if len(cacheYes) > 1000000:
cacheYes = set([])
if len(cacheNo) > 1000000:
cacheNo = set([])
if 8 * n >= Z:
fn = 'tmps-%d' % (len(tmps), )
#print >> sys.stderr, "writing " + fn + "\t" + tmpnm
tmps.append(fn)
with container(tmpnm, 'a') as z:
writeKmersAndCounts(K, mkPairs(buf.kmers()), z, fn)
buf.clear()
n = 0
t1 = time.time()
print >> sys.stderr, 'reads processed:', nr, (nr % PN) / (
t1 - t0), 'reads/second'
if len(tmps) and len(buf):
fn = 'tmps-%d' % (len(tmps), )
#print >> sys.stderr, "writing " + fn + "\t" + tmpnm
tmps.append(fn)
with container(tmpnm, 'a') as z:
writeKmersAndCounts(K, mkPairs(buf.kmers()), z, fn)
buf = []
while len(tmps) > 2:
tmpnm2 = tmpfile('.pmc')
tmps2 = []
with container(tmpnm, 'r') as z0, container(tmpnm2, 'w') as z:
ps = pairs(tmps)
for p in ps:
fn = 'tmps-%d' % (len(tmps2), )
tmps2.append(fn)
if len(p) == 1:
writeKmersAndCounts(K, readKmersAndCounts(z0, p[0]), z, fn)
continue
h = {}
merge2(z, K, readKmersAndCounts(z0, p[0]),
readKmersAndCounts(z0, p[1]), h, fn)
os.remove(tmpnm)
tmpnm = tmpnm2
tmps = tmps2
with container(out, 'w') as z:
h = {}
if len(tmps) == 0:
zs = hist(mkPairs(buf.kmers()), h)
writeKmersAndCounts(K, zs, z)
elif len(tmps) == 1:
with container(tmpnm, 'r') as z0:
writeKmersAndCounts(K, hist(readKmersAndCounts(z0, tmps[0]),
h), z)
else:
assert len(tmps) == 2
with container(tmpnm, 'r') as z0:
merge2(z, K, readKmersAndCounts(z0, tmps[0]),
readKmersAndCounts(z0, tmps[1]), h)
n = float(sum(acgt))
acgt = [c / n for c in acgt]
z.meta['hist'] = h
z.meta['acgt'] = acgt
z.meta['reads'] = nr
