def test_get_primes():
primes = khmer.get_n_primes_near_x(7, 20)
assert primes == [19, 17, 13, 11, 7, 5, 3]
primes_not_float = khmer.get_n_primes_near_x(7, 20.)
assert primes_not_float == [19, 17, 13, 11, 7, 5, 3]
assert all(isinstance(p, int) for p in primes_not_float)
def test_get_primes():
primes = khmer.get_n_primes_near_x(7, 20)
assert primes == [19, 17, 13, 11, 7, 5, 3]
primes_not_float = khmer.get_n_primes_near_x(7, 20.)
assert primes_not_float == [19, 17, 13, 11, 7, 5, 3]
assert all(isinstance(p, int) for p in primes_not_float)
def test_get_primes_fal():
try:
primes = khmer.get_n_primes_near_x(5, 5)
assert 0, "previous statement should fail"
except AssertionError:
raise
except Exception as err:
assert "unable to find 5 prime numbers < 5" in str(err)
def test_save_load_large(ctfile):
inpath = utils.get_test_data('random-20-a.fa')
savepath = utils.get_temp_filename(ctfile)
sizes = khmer.get_n_primes_near_x(1, 2**31 + 1000)
orig = khmer._Countgraph(12, sizes)
orig.consume_seqfile(inpath)
orig.save(savepath)
loaded = khmer.load_countgraph(savepath)
orig_count = orig.n_occupied()
loaded_count = loaded.n_occupied()
assert orig_count == 3966, orig_count
assert loaded_count == orig_count, loaded_count
def do_test(ctfile):
inpath = utils.get_test_data('random-20-a.fa')
savepath = utils.get_temp_filename(ctfile)
sizes = khmer.get_n_primes_near_x(1, 2 ** 31 + 1000)
orig = khmer._Countgraph(12, sizes)
orig.consume_fasta(inpath)
orig.save(savepath)
loaded = khmer.load_countgraph(savepath)
orig_count = orig.n_occupied()
loaded_count = loaded.n_occupied()
assert orig_count == 3966, orig_count
assert loaded_count == orig_count, loaded_count
def test_load_truncated():
inpath = utils.get_test_data('random-20-a.fa')
savepath = utils.get_temp_filename('save.ht')
truncpath = utils.get_temp_filename('trunc.ht')
sizes = khmer.get_n_primes_near_x(3, 200)
hi = khmer._Countgraph(12, sizes)
hi.consume_seqfile(inpath)
hi.save(savepath)
data = open(savepath, 'rb').read()
for i in range(len(data)):
fp = open(truncpath, 'wb')
fp.write(data[:i])
fp.close()
try:
khmer.load_countgraph(truncpath)
assert 0, "this should not be reached!"
except OSError as err:
print(str(err))
def test_load_truncated():
inpath = utils.get_test_data('random-20-a.fa')
savepath = utils.get_temp_filename('save.ht')
truncpath = utils.get_temp_filename('trunc.ht')
sizes = khmer.get_n_primes_near_x(3, 200)
hi = khmer._Countgraph(12, sizes)
hi.consume_fasta(inpath)
hi.save(savepath)
data = open(savepath, 'rb').read()
for i in range(len(data)):
fp = open(truncpath, 'wb')
fp.write(data[:i])
fp.close()
try:
khmer.load_countgraph(truncpath)
assert 0, "this should not be reached!"
except OSError as err:
print(str(err))
def test_get_primes():
primes = khmer.get_n_primes_near_x(7, 20)
assert primes == [19, 17, 13, 11, 7, 5, 3]
def test_get_primes_fal():
try:
khmer.get_n_primes_near_x(5, 5)
assert 0, "previous statement should fail"
except RuntimeError as err:
assert "unable to find 5 prime numbers < 5" in str(err)
def test_get_primes_fal():
try:
khmer.get_n_primes_near_x(5, 5)
assert 0, "previous statement should fail"
except RuntimeError as err:
assert "unable to find 5 prime numbers < 5" in str(err)
def test_init_with_primes(sketchtype):
primes = khmer.get_n_primes_near_x(4, random.randint(1000, 2000))
sketch = sketchtype(31, 1, 1, primes=primes)
assert sketch.hashsizes() == primes
def test_get_primes():
primes = khmer.get_n_primes_near_x(7, 20)
assert primes == [19, 17, 13, 11, 7, 5, 3]
def main(filename):
global ht
n = 5
basename = os.path.basename(filename)
fd = open("log.txt", "w")
primes = []
below = khmer.get_n_primes_near_x(N_HT * n, HASHTABLE_SIZE)
above = khmer.get_n_primes_above_x(N_HT * n, HASHTABLE_SIZE)
primes = below + above
random.shuffle(primes)
for run in range(n):
print primes[run * N_HT:run * N_HT + N_HT]
ht = khmer._new_hashbits(K, primes[run * N_HT:run * N_HT + N_HT])
#ht = khmer.new_hashbits(K, HASHTABLE_SIZE, N_HT)
# populate the hash table and tag set
if not load_ht:
ht.consume_fasta_and_tag(filename)
# save to a file (optional)
if save_ht:
ht.save(basename + '.ht')
ht.save_tagset(basename + '.tagset')
# calculate the hashtable occupancy
print '---'
print 'hashtable occupancy:', ht.n_occupied() / float(
HASHTABLE_SIZE)
print '---'
else:
ht.load(basename + '.ht')
ht.load_tagset(basename + '.tagset')
# did we just want to load the ht/tagset?
if stop_after_n_subsets == 0:
sys.exit(0)
#stop_tags = pickle.load(open(sys.argv[2]))
#for stop_tag in stop_tags:
# ht.add_stop_tag(stop_tag)
# divide the tags up into subsets
divvy = ht.divide_tags_into_subsets(SUBSET_SIZE)
n_subsets = len(divvy)
divvy.append(0)
# build a queue of tasks:
worker_q = Queue.Queue()
for i in range(0, n_subsets):
if stop_after_n_subsets is not None and i >= stop_after_n_subsets:
break
start = divvy[i]
end = divvy[i + 1]
worker_q.put((ht, i, start, end))
open('%s.info' % basename,
'w').write('%d subsets total\n' % (n_subsets))
threads = []
for th in range(N_THREADS):
t = threading.Thread(target=worker, args=(worker_q, basename))
threads.append(t)
t.start()
# wait for threads
for t in threads:
t.join()
###
del ht
gc.collect()
# create a new, empty ht object for merging; K matters, but not
# hashtable size.
ht = khmer.new_hashbits(K, 1, 1)
# load & merge all pmap files
for i in range(0, n_subsets):
pmap_file = basename + '.subset.%d.pmap' % (i, )
ht.merge_subset_from_disk(pmap_file)
# save merged partitionmap
if save_merged_pmap:
ht.save_partitionmap(basename + '.pmap.merged')
if remove_orig_pmap:
for i in range(0, n_subsets):
pmap_file = basename + '.subset.%d.pmap' % (i, )
os.unlink(pmap_file)
# output partitions!
n_partitions = ht.output_partitions(filename, basename + '.part')
(n_partitions, n_singletons) = ht.count_partitions()
print n_partitions
fd.write(str(n_partitions) + "\n")
#print os.listdir(os.getcwd())
for file in glob.glob(os.getcwd() + "/*pmap*"):
os.remove(file)
for file in glob.glob(os.getcwd() + "/*.info"):
os.remove(file)
for file in glob.glob(os.getcwd() + "/*.part"):
os.remove(file)
fd.close()
def main(filename):
global ht
n = 5
basename = os.path.basename(filename)
fd = open("log.txt", "w")
primes = []
below = khmer.get_n_primes_near_x(N_HT * n, HASHTABLE_SIZE)
above = khmer.get_n_primes_above_x(N_HT * n, HASHTABLE_SIZE)
primes = below + above
random.shuffle(primes)
for run in range(n):
print primes[run*N_HT:run*N_HT+N_HT]
ht = khmer._new_hashbits(K, primes[run*N_HT:run*N_HT+N_HT])
#ht = khmer.new_hashbits(K, HASHTABLE_SIZE, N_HT)
# populate the hash table and tag set
if not load_ht:
ht.consume_fasta_and_tag(filename)
# save to a file (optional)
if save_ht:
ht.save(basename + '.ht')
ht.save_tagset(basename + '.tagset')
# calculate the hashtable occupancy
print '---'
print 'hashtable occupancy:', ht.n_occupied() / float(HASHTABLE_SIZE)
print '---'
else:
ht.load(basename + '.ht')
ht.load_tagset(basename + '.tagset')
# did we just want to load the ht/tagset?
if stop_after_n_subsets == 0:
sys.exit(0)
#stop_tags = pickle.load(open(sys.argv[2]))
#for stop_tag in stop_tags:
# ht.add_stop_tag(stop_tag)
# divide the tags up into subsets
divvy = ht.divide_tags_into_subsets(SUBSET_SIZE)
n_subsets = len(divvy)
divvy.append(0)
# build a queue of tasks:
worker_q = Queue.Queue()
for i in range(0, n_subsets):
if stop_after_n_subsets is not None and i >= stop_after_n_subsets:
break
start = divvy[i]
end = divvy[i+1]
worker_q.put((ht, i, start, end))
open('%s.info' % basename, 'w').write('%d subsets total\n' % (n_subsets))
threads = []
for th in range(N_THREADS):
t = threading.Thread(target=worker, args=(worker_q, basename))
threads.append(t)
t.start()
# wait for threads
for t in threads:
t.join()
###
del ht
gc.collect()
# create a new, empty ht object for merging; K matters, but not
# hashtable size.
ht = khmer.new_hashbits(K, 1, 1)
# load & merge all pmap files
for i in range(0, n_subsets):
pmap_file = basename + '.subset.%d.pmap' % (i,)
ht.merge_subset_from_disk(pmap_file)
# save merged partitionmap
if save_merged_pmap:
ht.save_partitionmap(basename + '.pmap.merged')
if remove_orig_pmap:
for i in range(0, n_subsets):
pmap_file = basename + '.subset.%d.pmap' % (i,)
os.unlink(pmap_file)
# output partitions!
n_partitions = ht.output_partitions(filename, basename + '.part')
(n_partitions, n_singletons) = ht.count_partitions()
print n_partitions
fd.write(str(n_partitions) + "\n")
#print os.listdir(os.getcwd())
for file in glob.glob(os.getcwd() + "/*pmap*"):
os.remove(file)
for file in glob.glob(os.getcwd() + "/*.info"):
os.remove(file)
for file in glob.glob(os.getcwd() + "/*.part"):
os.remove(file)
fd.close()
def test_init_with_primes(sketchtype):
primes = khmer.get_n_primes_near_x(4, random.randint(1000, 2000))
sketch = sketchtype(31, 1, 1, primes=primes)
assert sketch.hashsizes() == primes
