def run(parser, args):
# TODO: Move logging config to separate configuration file
# TODO: use setup_logger here instead?
# set up logging to file for DEBUG messages and above
logging.basicConfig(
level=logging.DEBUG,
# TODO: args.log_format
format="%(levelname)s %(asctime)s %(name)s %(message)s",
filename=args.log_file,
filemode="w",
)
# define a Handler that writes INFO messages or higher to the sys.stderr
console = logging.StreamHandler()
console.setLevel(logging.INFO)
# set a format which is simpler for console use
formatter = logging.Formatter(args.log_format)
console.setFormatter(formatter)
# add the handler to the root logger
logging.getLogger("").addHandler(console)
# Start by logging sys.argv and the parameters used
logger = logging.getLogger("Manager")
# logger = setup_logger(__name__, args.log_format, log_file=args.log_file, level=logging.INFO)
logger.info(" ".join(sys.argv))
print_args(args, logger=logger)
read_until_client = read_until.ReadUntilClient(
mk_host=args.host,
mk_port=args.port,
device=args.device,
# one_chunk=args.one_chunk,
filter_strands=True,
# TODO: test cache_type by passing a function here
cache_type=args.read_cache,
cache_size=args.cache_size,
)
analysis_worker = functools.partial(
simple_analysis,
client=read_until_client,
batch_size=args.batch_size,
throttle=args.throttle,
unblock_duration=args.unblock_duration,
)
results = run_workflow(
client=read_until_client,
partial_analysis_func=analysis_worker,
n_workers=args.workers,
run_time=args.run_time,
runner_kwargs={
# "min_chunk_size": args.min_chunk_size,
"first_channel": args.channels[0],
"last_channel": args.channels[-1],
},
)
def main():
extra_args = (
(
"--toml",
dict(
metavar="TOML",
required=True,
help="TOML file specifying experimental parameters",
),
),
("--paf-log", dict(
help="PAF log",
default="paflog.log",
)),
("--chunk-log", dict(
help="Chunk log",
default="chunk_log.log",
)),
)
parser, args = get_parser(extra_args=extra_args, file=__file__)
# set up logging to file for DEBUG messages and above
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s %(name)s %(message)s",
filename=args.log_file,
filemode="w",
)
# define a Handler that writes INFO messages or higher to the sys.stderr
console = logging.StreamHandler()
console.setLevel(logging.INFO)
# set a format which is simpler for console use
formatter = logging.Formatter(args.log_format)
console.setFormatter(formatter)
# add the handler to the root logger
logging.getLogger("").addHandler(console)
# Start by logging sys.argv and the parameters used
logger = logging.getLogger("Manager")
logger.info(" ".join(sys.argv))
print_args(args, logger=logger)
# Setup chunk and paf logs
chunk_logger = setup_logger("DEC", log_file=args.chunk_log)
paf_logger = setup_logger("PAF", log_file=args.paf_log)
# Parse configuration TOML
# TODO: num_channels is not configurable here, should be inferred from client
run_info, conditions, reference, caller_kwargs = get_run_info(
args.toml, num_channels=512)
live_toml = Path("{}_live".format(args.toml))
# Load Minimap2 index
logger.info("Initialising minimap2 mapper")
mapper = CustomMapper(reference)
logger.info("Mapper initialised")
read_until_client = read_until.ReadUntilClient(
mk_host=args.host,
mk_port=args.port,
device=args.device,
# one_chunk=args.one_chunk,
filter_strands=True,
# TODO: test cache_type by passing a function here
cache_type=args.read_cache,
cache_size=args.cache_size,
)
send_message(
read_until_client.connection,
"Read Until is controlling sequencing on this device. You use it at your own risk.",
Severity.WARN,
)
for message, sev in describe_experiment(conditions, mapper):
logger.info(message)
send_message(
read_until_client.connection,
message,
sev,
)
"""
This experiment has N regions on the flowcell.
using reference: /path/to/ref.mmi
Region i:NAME (control=bool) has X targets of which Y are found in the reference.
reads will be unblocked when [u,v], sequenced when [w,x] and polled for more data when [y,z].
"""
# FIXME: currently flowcell size is not included, this should be pulled from
# the read_until_client
analysis_worker = functools.partial(
simple_analysis,
read_until_client,
unblock_duration=args.unblock_duration,
throttle=args.throttle,
batch_size=args.batch_size,
cl=chunk_logger,
pf=paf_logger,
live_toml_path=live_toml,
dry_run=args.dry_run,
run_info=run_info,
conditions=conditions,
mapper=mapper,
caller_kwargs=caller_kwargs,
)
results = run_workflow(
read_until_client,
analysis_worker,
args.workers,
args.run_time,
runner_kwargs={
# "min_chunk_size": args.min_chunk_size,
"first_channel": min(args.channels),
"last_channel": max(args.channels),
},
)
# No results returned
send_message(
read_until_client.connection,
"Read Until is disconnected from this device. Sequencing will proceed normally.",
Severity.WARN,
)
def main():
extra_args = (
(
"--toml",
dict(
metavar="TOML",
required=True,
help="TOML file specifying experimental parameters",
),
),
(
"--chunk-log",
dict(
help="Chunk log",
default="chunk_log.log",
)
),
)
parser, args = get_parser(extra_args=extra_args, file=__file__)
# TODO: Move logging config to separate configuration file
# set up logging to file for DEBUG messages and above
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s %(name)s %(message)s",
filename=args.log_file,
filemode="w",
)
# define a Handler that writes INFO messages or higher to the sys.stderr
console = logging.StreamHandler()
console.setLevel(logging.INFO)
# set a format which is simpler for console use
formatter = logging.Formatter(args.log_format)
console.setFormatter(formatter)
# add the handler to the root logger
logging.getLogger("").addHandler(console)
# Start by logging sys.argv and the parameters used
logger = logging.getLogger("Manager")
logger.info(" ".join(sys.argv))
print_args(args, logger=logger)
read_until_client = read_until.ReadUntilClient(
mk_host=args.host,
mk_port=args.port,
device=args.device,
# one_chunk=args.one_chunk,
filter_strands=True,
# TODO: test cache_type by passing a function here
cache_type=args.read_cache,
cache_size=args.cache_size,
)
# FIXME: currently flowcell size is not included, this should be pulled from
# the read_until_client
analysis_worker = functools.partial(
simple_analysis,
read_until_client,
unblock_duration=args.unblock_duration,
throttle=args.throttle,
batch_size=args.batch_size,
chunk_log=args.chunk_log,
toml_path=args.toml,
dry_run=args.dry_run,
)
results = run_workflow(
read_until_client,
analysis_worker,
args.workers,
args.run_time,
runner_kwargs={
# "min_chunk_size": args.min_chunk_size,
"first_channel": min(args.channels),
"last_channel": max(args.channels),
},
)