def test_init_jugspace(tmpdir):
jugdir = tmpdir
gridjug.grid_jug(
jugfile=PRIMES_JUGFILE,
jugdir=jugdir.strpath,
local=True,
)
jug.init(jugfile=PRIMES_JUGFILE, jugdir=jugdir.strpath)
def _status_nocache(options):
store, _ = jug.init(options.jugfile, options.jugdir)
Task.store = memoize_store(store, list_base=True)
tasks_waiting = defaultdict(int)
tasks_ready = defaultdict(int)
tasks_running = defaultdict(int)
tasks_failed = defaultdict(int)
tasks_finished = defaultdict(int)
for t in task.alltasks:
if t.can_load():
tasks_finished[t.name] += 1
elif t.can_run():
if t.is_locked():
if t.is_failed():
tasks_failed[t.name] += 1
else:
tasks_running[t.name] += 1
else:
tasks_ready[t.name] += 1
else:
tasks_waiting[t.name] += 1
_print_status(options, tasks_waiting, tasks_ready, tasks_running,
tasks_failed, tasks_finished)
return sum(tasks_finished.values())
def test_nld_failing_keep_going(jugdir):
gridjug.grid_jug(jugfile=FAILING_JUGFILE,
jugdir=jugdir,
keep_going=True,
**NLD_GRIDMAP_PARAMS)
_, jugspace = jug.init(jugfile=FAILING_JUGFILE, jugdir=jugdir)
for n, task in zip(range(2, 11), jugspace['primes10']):
assert task.can_load() == (n != 6)
def test_nld_access_results(jugdir):
gridjug.grid_jug(jugfile=PRIMES_JUGFILE,
jugdir=jugdir,
**NLD_GRIDMAP_PARAMS)
_, jugspace = jug.init(jugfile=PRIMES_JUGFILE, jugdir=jugdir)
assert jug.value(jugspace['primes10']) == [
True, True, False, True, False, True, False, False, False
]
def test_failing_keep_going(tmpdir):
jugdir = tmpdir
gridjug.grid_jug(
jugfile=FAILING_JUGFILE,
jugdir=jugdir.strpath,
local=True,
keep_going=True,
)
_, jugspace = jug.init(jugfile=FAILING_JUGFILE, jugdir=jugdir.strpath)
for n, task in zip(range(2, 11), jugspace['primes10']):
assert task.can_load() == (n != 6)
def test_access_results(tmpdir):
jugdir = tmpdir
gridjug.grid_jug(
jugfile=PRIMES_JUGFILE,
jugdir=jugdir.strpath,
local=True,
)
_, jugspace = jug.init(jugfile=PRIMES_JUGFILE, jugdir=jugdir.strpath)
assert jug.value(jugspace['primes10']) == [
True, True, False, True, False, True, False, False, False
]
def load_jugfile(options):
store, _ = jug.init(options.jugfile, options.jugdir)
h2idx = {}
ht = []
deps = {}
for i, t in enumerate(task.alltasks):
deps[i] = [h2idx[d.hash() if isinstance(d, Task) else d._base_hash()]
for d in t.dependencies()]
hash = t.hash()
ht.append((i, t.name, hash, unknown))
h2idx[hash] = i
rdeps = defaultdict(list)
for k, v in deps.items():
for rv in v:
rdeps[rv].append(k)
return store, ht, deps, dict(rdeps)
import jug
jug.init('jugfile', 'jugdata')
import jugfile
results = jug.task.value(jugfile.fullresults)
for p, t in results:
print "%s\n\n Password was '%s'" % (t, p)
import jug
import jug.task
jug.init('eval_electro_jug.py', 'eval_electro_jug.jugdata')
import eval_electro_jug
results = jug.task.value(eval_electro_jug.results)
# Now use these results
import numpy as np
RESULTS_FROM_JUG = 'results_from_jug.txt'
# Stitch the results back together:
top_k_accs, result_lines = zip(*results)
acc_storage = np.stack(top_k_accs)
# We now compute the path level average accuracies and print these out.
top_k_accs = np.mean((np.cumsum(acc_storage, axis=1) > 0.5).astype(np.float64),
axis=0)
for k, k_acc in enumerate(top_k_accs, start=1):
print(f"The top-{k} accuracy is {k_acc}")
# Finally we store the reaction paths in a text file.
with open(RESULTS_FROM_JUG, 'w') as fo:
fo.writelines('\n'.join(result_lines))
def main():
jug.init('jug_demo.py', 'redis://127.0.0.1/')
import jug_demo
print "Merged counts", jug.task.value(jug_demo.merged_counts)
def test_nld_init_jugspace(jugdir):
gridjug.grid_jug(jugfile=PRIMES_JUGFILE,
jugdir=jugdir,
**NLD_GRIDMAP_PARAMS)
jug.init(jugfile=PRIMES_JUGFILE, jugdir=jugdir)
'''
Created on Jul 22, 2015
@author: linzhang
'''
import jug
jug.init('foldx_montecarlo_jug_v2.py', 'foldx_montecarlo_jug_v2.jugdata')
import foldx_montecarlo_jug_v2
count = 0
total = 0
for i in jug.task.value(foldx_montecarlo_jug_v2.rand):
if i >= jug.task.value(foldx_montecarlo_jug_v2.obs):
count += 1
total += i
r_value = count / float(len(foldx_montecarlo_jug_v2.rand))
print jug.task.value(foldx_montecarlo_jug_v2.obs)
print jug.task.value(len(foldx_montecarlo_jug_v2.rand))
print total
print total / len(foldx_montecarlo_jug_v2.rand)
print "r_value: " + str(r_value)
import jug
import jug.task
jug.init('jugfile.py', 'jugfile.jugdata')
import jugfile
results = jug.task.value(jugfile.results)
with open('MPs.txt') as f:
for mp, r in zip(f, results):
mp = mp.strip()
print(mp, ": ", " ".join(r[:8]))
