def main(args):
bench = 'arbtkf91-bench'
data_path = os.path.realpath(args.bench_data)
samples = args.samples
model_params = {
"pa" : rat(27, 100),
"pc" : rat(24, 100),
"pg" : rat(26, 100),
"pt" : rat(23, 100),
"lambda" : rat(1, 1),
"mu" : rat(2, 1),
"tau" : rat(1, 10)}
for name, fin in data_source.gen_files(data_path):
print(name)
total_ticks = 0
for a, b in data_source.gen_sequence_pairs(fin):
d = dict(
precision=args.precision,
rtol=0.0,
samples=samples,
parameters=model_params,
sequence_a=a,
sequence_b=b)
elapsed = bench_pair(bench, d)
print(len(a), len(b), elapsed)
total_ticks += sum(elapsed)
print(total_ticks / samples)
print()
def main(args):
align = os.path.realpath(args.exe)
data_path = os.path.realpath(args.bench_data)
for name, fin in gen_files(data_path):
ncanon = 0
nopt = 0
k = 0
for a, b in gen_sequence_pairs(fin, force_acgt=True):
out, err = align_pair(align, a, b)
lines = [x.strip() for x in out.splitlines()]
nlines = len(lines)
found = False
for i in range(nlines):
if lines[i] == 'log_caching_round_up':
a_aln = lines[i+1]
b_aln = lines[i+2]
found = True
break
if not found:
raise Exception('failed to understand the output')
js = check_pair(a_aln, b_aln)
if js['alignment_is_canonical']:
ncanon += 1
if js['alignment_is_optimal']:
nopt += 1
k += 1
print(name)
print('total number of alignments:', k)
print('number of optimal alignments:', nopt)
print('number that are also canonical:', ncanon)
print()
def main(args):
align = os.path.realpath(args.exe)
data_path = os.path.realpath(args.bench_data)
for name, fin in gen_files(data_path):
ncanon = 0
nopt = 0
k = 0
for a, b in gen_sequence_pairs(fin, force_acgt=True):
out, err = align_pair(align, a, b)
# print(out)
# print(err)
lines = [x.strip() for x in out.splitlines()]
a_aln = lines[2]
b_aln = lines[3]
js = check_pair(a_aln, b_aln)
if js["alignment_is_canonical"]:
ncanon += 1
if js["alignment_is_optimal"]:
nopt += 1
k += 1
print(name)
print("total number of alignments:", k)
print("number of optimal alignments:", nopt)
print("number that are also canonical:", ncanon)
print()
def main(args):
data_path = os.path.realpath(args.bench_data)
model_params = {
"pa" : rat(27, 100),
"pc" : rat(24, 100),
"pg" : rat(26, 100),
"pt" : rat(23, 100),
"lambda" : rat(1, 1),
"mu" : rat(2, 1),
"tau" : rat(1, 10)}
for name, fin in gen_files(data_path):
print(name)
print('precision={} rtol={}'.format(args.precision, args.rtol))
sequence_pairs = list(gen_sequence_pairs(fin, force_acgt=True))
ncanon = 0
nopt = 0
k = 0
for a, b in sequence_pairs:
j_in = dict(
parameters=model_params,
rtol=args.rtol,
precision=args.precision,
sequence_a=a,
sequence_b=b)
d = runjson([align], j_in)
j_in = dict(
parameters=model_params,
sequence_a=d['sequence_a'],
sequence_b=d['sequence_b'])
d = runjson([check], j_in)
if d['alignment_is_canonical']:
ncanon += 1
if d['alignment_is_optimal']:
nopt += 1
k += 1
print('total number of alignments:', k)
print('number of optimal alignments:', nopt)
print('number that are also canonical:', ncanon)
print()
