def setup(self):
self.metric = metrics.Dihedral()
self.pdb_fn = os.path.join(fixtures_dir(), 'native.pdb')
self.trj_fn = os.path.join(fixtures_dir(), 'trj0.lh5')
self.project = Project({'traj_lengths': [501], 'traj_paths': [self.trj_fn],
'conf_filename': self.pdb_fn, 'traj_converted_from': [None],
'traj_errors': [None]})
self.vtraj = partition(self.project, chunk_size=501)[0]
def setup(self):
self.metric = metrics.Dihedral()
self.pdb_fn = os.path.join(fixtures_dir(), 'native.pdb')
self.trj_fn = os.path.join(fixtures_dir(), 'trj0.lh5')
self.project = Project({'NumTrajs': 1, 'TrajLengths': [501], 'TrajFileBaseName': 'trj', 'TrajFileType': '.lh5',
'ConfFilename': self.pdb_fn,
'TrajFilePath': fixtures_dir()})
self.vtraj = partition(self.project, chunk_size=501)[0]
def test_partition_1():
project = Project([2, 1, 10], 3)
chunk_size = 4
got = partition(project, chunk_size)
correct = [[(0, 0, 2), (1, 0, 1), (2, 0, 1)], [(2, 1, 5)], [(2, 5, 9)],
[(2, 9, 10)]]
assert [e.canonical() for e in got] == correct
assert sum(len(e) for e in got) == sum(project.traj_lengths)
def test_partition_0():
project = {'TrajLengths': [2, 5]}
chunk_size = 3
got = partition(project, chunk_size)
correct = [[(0, 0, 2), (1, 0, 1)], [(1, 1, 4)], [(1, 4, 5)]]
assert [e.canonical() for e in got] == correct
assert sum(len(e) for e in got) == sum(project['TrajLengths'])
def test_partition_0():
project = Project([2, 5], 2)
chunk_size = 3
got = partition(project, chunk_size)
correct = [[(0, 0, 2), (1, 0, 1)], [(1, 1, 4)], [(1, 4, 5)]]
assert [e.canonical() for e in got] == correct
assert sum(len(e) for e in got) == sum(project.traj_lengths)
def test_partition_1():
project = {'TrajLengths': [2,1,10]}
chunk_size = 4
got = partition(project, chunk_size)
correct = [[(0,0,2), (1,0,1), (2,0,1)],
[(2,1,5)],
[(2,5,9)],
[(2,9,10)]]
assert [e.canonical() for e in got] == correct
assert sum(len(e) for e in got) == sum(project['TrajLengths'])
def setup(self):
self.metric = metrics.Dihedral()
self.pdb_fn = os.path.join(fixtures_dir(), 'native.pdb')
self.trj_fn = os.path.join(fixtures_dir(), 'trj0.lh5')
self.project = Project({
'NumTrajs': 1,
'TrajLengths': [501],
'TrajFileBaseName': 'trj',
'TrajFileType': '.lh5',
'ConfFilename': self.pdb_fn,
'TrajFilePath': fixtures_dir()
})
self.vtraj = partition(self.project, chunk_size=501)[0]
def test_2(self):
# reset the global
remote.PREPARED=False
# get a smaller vtraj, and just assign it to only the pDB
vtraj = partition(self.project, chunk_size=10)[1]
a,d,vtraj = assign(vtraj, self.pdb_fn, self.metric)
# these are the right RMSD distances
correct_d = np.array([ 0.26932446, 0.53129266, 0.64795935, 1.56435365, 1.05962805,
0.60572095, 0.47062515, 0.5758602 , 0.24565975, 0.69161412], dtype=np.float32)
npt.assert_array_almost_equal(d, correct_d)
npt.assert_array_equal(a, np.zeros(10))
def test_partition_0():
project = Project([2,5], 2)
chunk_size = 3
got = partition(project, chunk_size)
correct = [[(0, 0, 2), (1, 0, 1)],
[(1, 1, 4)],
[(1, 4,5)]]
assert [e.canonical() for e in got] == correct
assert sum(len(e) for e in got) == sum(project.traj_lengths)
def test_partition_0():
project = {'TrajLengths': [2,5]}
chunk_size = 3
got = partition(project, chunk_size)
correct = [[(0, 0, 2), (1, 0, 1)],
[(1, 1, 4)],
[(1, 4,5)]]
assert [e.canonical() for e in got] == correct
assert sum(len(e) for e in got) == sum(project['TrajLengths'])
def test_partition_3():
project = {'TrajLengths': [1, 0]}
chunk_size = 1
partition(project, chunk_size)
def test_partition_2():
project = Project([1,1,-1], 3)
chunk_size = 1
partition(project, chunk_size)
def setup(self):
self.d = tempfile.mkdtemp()
project = {'TrajLengths': [9, 10], 'NumTrajs': 2}
self.vtrajs = partition(project, 3)
self.fa, self.fd = setup_containers(self.d, project, self.vtrajs)
def test_partition_4():
project = {'TrajLengths': [1]}
chunk_size = 11
got = partition(project, chunk_size)
correct = [[(0, 0, 1)]]
assert [e.canonical() for e in got] == correct
def test_partition_3():
project = {'TrajLengths': [1, 0]}
chunk_size = 1
partition(project, chunk_size)
def test_partition_3():
project = Project([1,1.5,1], 3)
chunk_size = 1
partition(project, chunk_size)
def test_partition_4():
project = Project([1], 1)
chunk_size = 11
got = partition(project, chunk_size)
correct = [[(0, 0, 1)]]
assert [e.canonical() for e in got] == correct
def test_partition_3():
project = Project([1, 1.5, 1], 3)
chunk_size = 1
partition(project, chunk_size)
def test_partition_3():
project = Project([1,0], 2)
chunk_size = 1
partition(project, chunk_size)
def test_partition_4():
project = Project([1], 1)
chunk_size = 11
got = partition(project, chunk_size)
correct = [[(0,0,1)]]
assert [e.canonical() for e in got] == correct
def setup(self):
self.d = tempfile.mkdtemp()
project = Project([9,10], 2)
self.vtrajs = partition(project, 3)
self.fa, self.fd = setup_containers(self.d, project, self.vtrajs)
def main(args, metric, logger):
project = Project.load_from(args.project)
if not os.path.exists(args.generators):
raise IOError("Could not open generators")
generators = os.path.abspath(args.generators)
output_dir = os.path.abspath(args.output_dir)
# connect to the workers
try:
json_file = client_json_file(args.profile, args.cluster_id)
client = parallel.Client(json_file, timeout=2)
except parallel.error.TimeoutError as exception:
msg = "\nparallel.error.TimeoutError: " + str(exception)
msg += "\n\nPerhaps you didn't start a controller?\n"
msg += "(hint, use ipcluster start)"
print >> sys.stderr, msg
sys.exit(1)
lview = client.load_balanced_view()
# partition the frames into a bunch of vtrajs
all_vtrajs = local.partition(project, args.chunk_size)
# initialze the containers to save to disk
f_assignments, f_distances = local.setup_containers(output_dir, project, all_vtrajs)
# get the chunks that have not been computed yet
valid_indices = np.where(f_assignments.root.completed_vtrajs[:] == False)[0]
remaining_vtrajs = np.array(all_vtrajs)[valid_indices].tolist()
logger.info("%d/%d jobs remaining", len(remaining_vtrajs), len(all_vtrajs))
# send the workers the files they need to get started
# dview.apply_sync(remote.load_gens, generators, project['ConfFilename'],
# metric)
# get the workers going
n_jobs = len(remaining_vtrajs)
amr = lview.map(remote.assign, remaining_vtrajs, [generators] * n_jobs, [metric] * n_jobs, chunksize=1)
pending = set(amr.msg_ids)
while pending:
client.wait(pending, 1e-3)
# finished is the set of msg_ids that are complete
finished = pending.difference(client.outstanding)
# update pending to exclude those that just finished
pending = pending.difference(finished)
for msg_id in finished:
# we know these are done, so don't worry about blocking
async = client.get_result(msg_id)
try:
assignments, distances, chunk = async.result[0]
except RemoteError as e:
print "Remote Error:"
e.print_traceback()
raise
vtraj_id = local.save(f_assignments, f_distances, assignments, distances, chunk)
log_status(logger, len(pending), n_jobs, vtraj_id, async)
f_assignments.close()
f_distances.close()
logger.info("All done, exiting.")
def test_partition_2():
project = Project([1, 1, -1], 3)
chunk_size = 1
partition(project, chunk_size)
def test_partition_4():
project = {'TrajLengths': [1]}
chunk_size = 11
got = partition(project, chunk_size)
correct = [[(0,0,1)]]
assert [e.canonical() for e in got] == correct
def test_partition_3():
project = Project([1, 0], 2)
chunk_size = 1
partition(project, chunk_size)
def setup(self):
self.d = tempfile.mkdtemp()
project = {'TrajLengths': [9,10], 'NumTrajs':2}
self.vtrajs = partition(project, 3)
self.fa, self.fd = setup_containers(self.d, project, self.vtrajs)
def setup(self):
self.d = tempfile.mkdtemp()
project = Project([9, 10], 2)
self.vtrajs = partition(project, 3)
self.fa, self.fd = setup_containers(self.d, project, self.vtrajs)
def main(args, metric, logger):
project = Project.load_from_hdf(args.project)
if not os.path.exists(args.generators):
raise IOError('Could not open generators')
generators = os.path.abspath(args.generators)
output_dir = os.path.abspath(args.output_dir)
# connect to the workers
try:
json_file = client_json_file(args.profile, args.cluster_id)
client = parallel.Client(json_file, timeout=2)
except parallel.error.TimeoutError as exception:
msg = '\nparallel.error.TimeoutError: ' + str(exception)
msg += "\n\nPerhaps you didn't start a controller?\n"
msg += "(hint, use ipcluster start)"
print >> sys.stderr, msg
sys.exit(1)
lview = client.load_balanced_view()
# partition the frames into a bunch of vtrajs
all_vtrajs = local.partition(project, args.chunk_size)
# initialze the containers to save to disk
f_assignments, f_distances = local.setup_containers(
output_dir, project, all_vtrajs)
# get the chunks that have not been computed yet
valid_indices = np.where(
f_assignments.root.completed_vtrajs[:] == False)[0]
remaining_vtrajs = np.array(all_vtrajs)[valid_indices].tolist()
logger.info('%d/%d jobs remaining', len(remaining_vtrajs), len(all_vtrajs))
# send the workers the files they need to get started
# dview.apply_sync(remote.load_gens, generators, project['ConfFilename'],
# metric)
# get the workers going
n_jobs = len(remaining_vtrajs)
amr = lview.map(remote.assign,
remaining_vtrajs, [generators] * n_jobs, [metric] * n_jobs,
chunksize=1)
pending = set(amr.msg_ids)
while pending:
client.wait(pending, 1e-3)
# finished is the set of msg_ids that are complete
finished = pending.difference(client.outstanding)
# update pending to exclude those that just finished
pending = pending.difference(finished)
for msg_id in finished:
# we know these are done, so don't worry about blocking
async = client.get_result(msg_id)
assignments, distances, chunk = async .result[0]
vtraj_id = local.save(f_assignments, f_distances, assignments,
distances, chunk)
log_status(logger, len(pending), n_jobs, vtraj_id, async)
f_assignments.close()
f_distances.close()
logger.info('All done, exiting.')
