for result in results.get_ids():
res = results[result]
for tog in toggles:
if '' == res.single_args[tog]:
file_output += '1,'
else:
file_output += '0,'
file_output += "%s,%d,%f\n" % _get_file_size_time_bdg(res)
write_file(domain + '-results.csv', file_output)
######################################
opts, flags = get_opts()
did_something = False
if '-domain' in opts:
all_domains = [opts['-domain']]
if 'size_time' in flags:
did_something = True
if not os.path.isdir('size_time_results'):
os.system('mkdir size_time_results')
for dom in all_domains:
test_size_time(dom)
os.system('mv results-* size_time_results')
import os
from krrt.utils import fileio, run_experiment, get_opts, get_value, write_file
domain = get_opts()[0]['-domain']
problems = fileio.read_file("%s/pmap" % domain)
domprobs = [
"../%s/domain.pddl ../%s/%s OUT --jic-limit 10" % (domain, domain, prob)
for prob in problems
]
results = run_experiment(
base_directory=".",
base_command='./../../src/plan-prp',
single_arguments={'domprob': domprobs},
time_limit=1800, # 15minute time limit (900 seconds)
memory_limit=1000, # 1gig memory limit (1000 megs)
results_dir="%s/results" % domain,
progress_file=None, # Print the progress to stdout
processors=6, # You've got 8 cores, right?
sandbox='fd_out',
clean_sandbox=False)
good_results = results.filter(lambda result: not result.timed_out)
good_results = [good_results[i] for i in good_results.get_ids()]
print "Coverage: %d / %d" % (len(good_results), len(domprobs))
try:
data = ['runtime(s),size(nodes)'] + [
"%f,%d" %
f, (ax1) = pylab.subplots(1)
SYMBOLS = ['s', 'x', 'o', '^', '>', 'v', '<', 'd', 'p', 'h', '8']
COLOURS = ['b','g','k','m']
LINES = ['-', '--', '-.', ':']
handle = ax1.plot(xs, data, c='b', ls='-')
ax1.set_title(title)
if logplot:
ax1.set_yscale('log')
pylab.show()
if '-csv' in get_opts()[0]:
data = [line.split(',') for line in read_file(get_opts()[0]['-csv'])[1:]]
times = [float(i[0]) for i in data]
sizes = [float(i[1]) for i in data]
print "Mean time: %f" % (sum(times) / len(times))
print "Mean size: %f" % (sum(sizes) / len(sizes))
elif '-size' in get_opts()[0]:
dom = get_opts()[0]['-size']
fname = "%s.csv" % dom
data = [line.split(',') for line in read_file(fname)[1:]]
times = sorted([float(i[0]) for i in data])
sizes = sorted([float(i[1]) for i in data])
xs = [i+1 for i in range(len(data))]
if disable_x_tics:
ax.xaxis.set_major_formatter(pylab.NullFormatter())
pylab.show()
def create_time_profile(times):
x = sorted(times)
y = [i + 1 for i in range(len(times))]
return (x, y)
if __name__ == '__main__':
from krrt.utils import get_opts
import os
myargs, flags = get_opts()
if '-csv' not in myargs:
print("Error: Must include a path to the csv file:")
print(USAGE_STRING)
os._exit(1)
title = None
if '-title' in myargs:
title = myargs['-title']
xlabel = ""
if '-xlabel' in myargs:
xlabel = myargs['-xlabel']
ylabel = ""
from krrt.utils import get_opts, write_file
(options, _) = get_opts()
prob = options['-prob']
peeps = int(options['-peeps'])
out = """(define (domain zenotravel)
(:requirements :typing :non-deterministic)
(:types aircraft person city flevel - object)\n"""
out += " (:constants %s - person)\n" % (' '.join(
["p%d" % i for i in range(peeps)]))
out += """ (:predicates (at-person ?p - person ?c - city)
(at-aircraft ?a - aircraft ?c - city)
(boarding ?p - person ?a - aircraft)
(not-boarding ?p - person)
(in ?p - person ?a - aircraft)
(debarking ?p - person ?a - aircraft)
(not-debarking ?p - person)
(fuel-level ?a - aircraft ?l - flevel)
(next ?l1 ?l2 - flevel)
(flying ?a - aircraft ?c - city)
(zooming ?a - aircraft ?c - city)
(refueling ?a - aircraft)
(not-refueling ?a - aircraft)
)
(:action start-boarding
:parameters (?p - person ?a - aircraft ?c - city)
:precondition (and (at-person ?p ?c) (at-aircraft ?a ?c))
:effect (and (not (at-person ?p ?c)) (not (not-boarding ?p)) (boarding ?p ?a))