meme_em['niters'] = start.niters
meme_em['em_time'] = start.em_time
meme_em['cons'] = start.cons_after_em
meme_em['nsites'] = start.nsites
meme_em['sig'] = start.sig
logging.info(
'%s: cons0=%20s; nsites0=%3d; niters=%4d; elapsed=%7.1fs; per iteration=%6.2fs; cons=%20s; nsites0=%3d; sig=%e',
data_set, start.cons0, start.nsites0, start.niters, start.em_time, start.em_time /
start.niters, start.cons, start.nsites, start.sig
)
meme_em.append()
h5file.close() # Close (and flush) the HDF5 file
if '__main__' == __name__:
#
# parse options
#
parser = OptionParser()
test_data.add_options(parser)
stempy.add_options(parser)
options, args = parser.parse_args()
usage = 'USAGE: %s <options> <h5 file>' % sys.argv[0]
if len(args) != 1:
raise RuntimeError(usage)
if len(args) < 1:
raise RuntimeError(usage)
filename = args[0]
run(options)
def add_options(options):
stempy.add_options(options)
meme.add_options(options)
def time_per_iteration_per_base(timings):
return timings['duration'] / timings['niters'] / test_data.get_num_w_mers(timings['dataset'], len(timings['seed']))
if '__main__' == __name__:
def add_options(parser):
parser.add_option("-f", "--force", action="store_true",
help="Always run even if already have results.")
#
# parse options
#
options, args = stempy.parse_options(
lambda parser: (add_options(parser), stempy.add_options(
parser), test_data.add_options(parser))
)
if len(args) != 0:
raise RuntimeError('USAGE: %s <options>', sys.argv[0])
run(options)
#
# Slice and dice data
#
h5file = tables.openFile(filename)
timings_table = h5file.root.EtaStability.timings
nsite_values = list(set(row['nsites'] for row in timings_table))
nsite_values.sort()
time_per_iteration_per_base = [
map(suite_for_name, suite_names)
#
# Parse the options
#
from optparse import OptionParser
option_parser = OptionParser()
option_parser.add_option(
"--num-threads",
dest="num_threads",
default=3,
type='int',
help="Number of threads to run jobs on."
)
option_parser.add_option("--data-sets", action="append")
stem.add_options(option_parser)
meme.add_options(option_parser)
options = stem.parse_options(option_parser=option_parser)
stem.turn_on_google_profiling_if_asked_for(options)
# for each method and suite
for method_name in method_names:
for suite_name in suite_names:
suite = suite_for_name(suite_name)
method = method_for_name(method_name)
predictions_by_dataset = []
import cookbook.function_as_task as F
def do_work(task):
def add_options(option_parser):
stem.add_options(option_parser)
meme.add_options(option_parser)
