def test_dagman_job_order(tmpdir):
# Test to check that the order in which Jobs are added to a Dagman doesn't
# change the Dagman submit file that is built. See issue #57.
submit_dir = str(tmpdir.mkdir('submit'))
dag_submit_lines = []
for order_idx in range(2):
dagman = Dagman('testdagman', submit=submit_dir)
job_child = Job('childjob', example_script, submit=submit_dir)
job_child.add_arg('--length 200', name='200jobname')
job_child.add_arg('--length 400', retry=3)
job_parent = Job('parentjob', example_script, submit=submit_dir)
job_parent.add_arg('--length 100')
job_parent.add_child(job_child)
if order_idx == 0:
# Add job_parent to dagman first
dagman.add_job(job_parent)
dagman.add_job(job_child)
else:
# Add job_child to dagman first
dagman.add_job(job_child)
dagman.add_job(job_parent)
dagman.build(fancyname=False)
# Append submit file lines to dag_submit_lines
with open(dagman.submit_file, 'r') as dag_submit_file:
dag_submit_lines.append(dag_submit_file.readlines())
# Test that the same lines occur in the Dagman submit file for
# adding the parent/child jobs in either order
assert Counter(dag_submit_lines[0]) == Counter(dag_submit_lines[1])
def test_job_arg_name_files(tmpdir, fancyname):
# Test to check that when a named argument is added to a Job, and the Job
# is built with fancyname=True, the Job submit file and the
# error/log/output files for the argument start with the same index.
# E.g. job_(date)_01.submit, job_(date)_01.error, etc.
# Regression test for issue #47
submit_dir = str(tmpdir.mkdir('submit'))
job = Job('testjob', example_script, submit=submit_dir)
job.add_arg('arg', name='argname')
dagman = Dagman('exampledagman', submit=submit_dir)
dagman.add_job(job)
dagman.build(fancyname=fancyname)
with open(dagman.submit_file, 'r') as dagman_submit_file:
dagman_submit_lines = dagman_submit_file.readlines()
# Get root of the dagman submit file (submit file basename w/o .submit)
submit_file_line = dagman_submit_lines[0]
submit_file_basename = submit_file_line.split(os.sep)[-1].rstrip()
submit_file_root = os.path.splitext(submit_file_basename)[0]
# Get job_name variable (used to built error/log/output file basenames)
jobname_line = dagman_submit_lines[2]
jobname = jobname_line.split('"')[-2]
other_file_root = '_'.join(jobname.split('_')[:-1])
assert submit_file_root == other_file_root
def test_dagman_subdag_build(tmpdir):
submit_dir = str(tmpdir.join('submit'))
extra_lines = ['first extra line', 'second extra line']
dagman = Dagman('dagman', submit=submit_dir, extra_lines=extra_lines)
subdag = Dagman('subdag_1', submit=submit_dir, extra_lines=extra_lines)
dagman.add_subdag(subdag)
dagman.build()
with open(dagman.submit_file, 'r') as f:
assert set(extra_lines) <= set(line.rstrip('\n') for line in f)
with open(dagman.submit_file, 'r') as f:
assert set(extra_lines) <= set(line.rstrip('\n') for line in f)
def test_dagman_env_variable_dir(tmpdir, monkeypatch):
# Set pycondor environment variable
submit_dir = str(tmpdir.mkdir('submit'))
monkeypatch.setenv('PYCONDOR_SUBMIT_DIR', submit_dir)
dagman = Dagman('testdagman')
job = Job('jobname', example_script)
dagman.add_job(job)
dagman.build()
submit_path = os.path.dirname(dagman.submit_file)
assert submit_dir == submit_path
def test_dagman_has_bad_node_names(tmpdir):
submit_dir = str(tmpdir.mkdir('submit'))
# Test all combinations
jobs_names = ['testjob', 'testjob.', 'testjob', 'testjob+']
arg_names = ['argname', 'argname', 'argname+', 'argname.']
has_bad_node_names = [False, True, True, True]
for job_name, arg_name, bad_node_names in zip(jobs_names, arg_names,
has_bad_node_names):
job = Job(job_name, example_script, submit=submit_dir)
job.add_arg('arg', name=arg_name)
dagman = Dagman('testdagman', submit=submit_dir)
dagman.add_job(job)
dagman.build()
assert dagman._has_bad_node_names == bad_node_names
def generate_dag(times,
flags=[],
tag='gwdetchar-omega-batch',
submit=False,
outdir=os.getcwd(),
universe='vanilla',
condor_commands=get_condor_arguments()):
"""Construct a Directed Acyclic Graph (DAG) for a batch of omega scans
Parameters
----------
times : `list` of `float`
list of GPS times to scan
flags : `list` of `str`, optional
a list of command line flags to run for each job, defaults to an
empty list
tag : `str`, optional
a helpful string to use to name the DAG,
default: `'gwdetchar-omega-batch'`
submit : `bool`, optional
submit the DAG to condor, default: `False`
outdir : `str`, optional
the output directory in which to store files, will result in
sub-directories called `'condor'` and `'log'`, default: `os.getcwd`
universe : `str`, optional
condor universe to run in, default: `'vanilla'`
condor_commands : `list` of `str`, optional
list of condor settings to process with, defaults to the output of
`get_condor_arguments`
Returns
-------
dagman : `~pycondor.Dagman`
the fully built DAG object
"""
logdir = os.path.join(outdir, 'logs')
subdir = os.path.join(outdir, 'condor')
executable = find_executable('gwdetchar-omega')
# create DAG and jobs
dagman = Dagman(name=tag, submit=subdir)
job = Job(dag=dagman,
name=os.path.basename(executable),
executable=executable,
universe=universe,
submit=subdir,
error=logdir,
output=logdir,
getenv=True,
request_memory=4096 if universe != "local" else None,
extra_lines=condor_commands)
# make a node in the workflow for each event time
for t in times:
cmd = " ".join([str(t)] +
["--output-directory",
os.path.join(outdir, str(t))] + flags)
job.add_arg(cmd, name=str(t).replace(".", "_"))
# write and submit the DAG
dagman.build(fancyname=False)
print("Workflow generated for {} times".format(len(times)))
if submit:
dagman.submit_dag(submit_options="-force")
print("Submitted to condor, check status via:\n\n"
"$ condor_q {}".format(getuser()))
else:
print(
"Submit to condor via:\n\n"
"$ condor_submit_dag {0.submit_file}".format(dagman), )
return dagman
def generate_dag(times, flags=[], tag='gwdetchar-omega-batch',
submit=False, outdir=os.getcwd(), universe='vanilla',
condor_commands=get_condor_arguments()):
"""Construct a Directed Acyclic Graph (DAG) for a batch of omega scans
Parameters
----------
times : `list` of `float`
list of GPS times to scan
flags : `list` of `str`, optional
a list of command line flags to run for each job, defaults to an
empty list
tag : `str`, optional
a helpful string to use to name the DAG,
default: `'gwdetchar-omega-batch'`
submit : `bool`, optional
submit the DAG to condor, default: `False`
outdir : `str`, optional
the output directory in which to store files, will result in
sub-directories called `'condor'` and `'log'`, default: `os.getcwd`
universe : `str`, optional
condor universe to run in, default: `'vanilla'`
condor_commands : `list` of `str`, optional
list of condor settings to process with, defaults to the output of
`get_condor_arguments`
Returns
-------
dagman : `~pycondor.Dagman`
the fully built DAG object
"""
logdir = os.path.join(outdir, 'logs')
subdir = os.path.join(outdir, 'condor')
executable = find_executable('gwdetchar-omega')
# create DAG and jobs
dagman = Dagman(name=tag, submit=subdir)
job = Job(
dag=dagman,
name=os.path.basename(executable),
executable=executable,
universe=universe,
submit=subdir,
error=logdir,
output=logdir,
getenv=True,
request_memory=4096 if universe != "local" else None,
extra_lines=condor_commands
)
# make a node in the workflow for each event time
for t in times:
cmd = " ".join([str(t)] + [
"--output-directory", os.path.join(outdir, str(t))] + flags)
job.add_arg(cmd, name=str(t).replace(".", "_"))
# write and submit the DAG
dagman.build(fancyname=False)
print("Workflow generated for {} times".format(len(times)))
if submit:
dagman.submit_dag(submit_options="-force")
print(
"Submitted to condor, check status via:\n\n"
"$ condor_q {}".format(getuser())
)
else:
print(
"Submit to condor via:\n\n"
"$ condor_submit_dag {0.submit_file}".format(dagman),
)
return dagman
def main():
parser = argparse.ArgumentParser(
description="Compute pair-wise overlap of a batch of skymaps")
parser.add_argument(
"--skymap",
metavar="PATH",
action="append",
help="A list of paths pointing to the probability skymaps")
parser.add_argument("--accounting-tag",
type=str,
default="ligo.dev.o3.cbc.lensing.multi",
help="Accounting tag")
parser.add_argument("--slurm",
action="store_true",
help="Run on a condor+slurm cluster")
parser.add_argument("--plot",
action="store_true",
help="Visualize the skymaps")
parser.add_argument("--verbose",
action="store_true",
help="Be very verbose")
args = parser.parse_args()
compute_overlap_job_name = "compute_overlap"
pairwise_overlap_out_str = "{prefix_1}_{prefix_2}_overlap.dat"
# Directories for HTCondor
try:
os.makedirs(compute_overlap_job_name)
except:
pass
error = os.path.abspath("logs")
output = os.path.abspath("logs")
log = os.path.abspath("logs")
submit = os.path.abspath("")
# Create a DAG (but actually each node is independent of each other)
dag = Dagman(
name="dag_compute_overlap_from_skymaps",
submit=submit,
)
universe = "vanilla"
extra_lines = ["accounting_group = {}".format(args.accounting_tag)]
if args.slurm:
universe = "grid"
extra_lines.append("grid_resource = batch slurm")
# Compute overlap
if len(args.skymap) >= 2:
# At least two skymaps, now we can compute the pairwise overlap
compute_overlap_job = Job(
name="job_" + compute_overlap_job_name,
executable=shutil.which("compute_overlap"),
universe=universe,
error=error,
output=output,
log=log,
dag=dag,
extra_lines=extra_lines,
)
for skymap_1, skymap_2 in list(itertools.combinations(args.skymap, 2)):
prefix_1 = get_filename_prefix(skymap_1)
prefix_2 = get_filename_prefix(skymap_2)
argument_str = ""
if args.verbose:
argument_str += " --verbose"
if args.plot:
argument_str += " --plot"
argument_str += " --skymap " + os.path.abspath(skymap_1) + " --skymap " + os.path.abspath(skymap_2) + \
" --output " + os.path.abspath(os.path.join(compute_overlap_job_name, pairwise_overlap_out_str.format(prefix_1=prefix_1, prefix_2=prefix_2)))
compute_overlap_job.add_arg(argument_str, retry=3)
dag.build(fancyname=False)
