def runLocal(self, data):
''' Run a PyURDME run using local compute recources. '''
self.user_data.set_selected(0)
#####
pymodel = self.construct_pyurdme_model(data)
#####
simulation_algorithm = data[
'algorithm'] # Don't trust this! I haven't implemented the algorithm selection for this yet
simulation_realizations = data['realizations']
# If the seed is negative, this means choose a seed >= 0 randomly
if int(data['seed']) < 0:
random.seed()
data['seed'] = random.randint(0, 2147483647)
simulation_seed = data['seed']
#####
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir=basedir + 'output')
job = SpatialJobWrapper()
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = data["jobName"]
job.indata = json.dumps(data)
job.outData = dataDir
job.modelName = pymodel.name
job.resource = "local"
job.status = "Running"
model_file_pkl = "{0}/model_file.pkl".format(dataDir)
result_dir = "{0}/results/".format(dataDir)
os.makedirs(result_dir)
# searilize the model and write it to a file in the data dir
with open(model_file_pkl, 'w') as fd:
pickle.dump(pymodel, fd)
cmd = "{0}/../../pyurdme/pyurdme_wrapper.py {1} {2} {3} {4} {5}".format(
path, model_file_pkl, result_dir, simulation_algorithm,
simulation_realizations, simulation_seed)
logging.info("cmd =\n{}".format(cmd))
exstring = '{0}/backend/wrapper.py {1}/stdout.log {1}/stderr.log {1}/return_code {2}'.format(
basedir, dataDir, cmd)
handle = subprocess.Popen(exstring, shell=True, preexec_fn=os.setsid)
job.pid = int(handle.pid)
job.put()
return job
def runLocal(self, data):
''' Run a PyURDME run using local compute recources. '''
self.user_data.set_selected(0)
#####
pymodel = self.construct_pyurdme_model(data)
#####
simulation_algorithm = data['algorithm'] # Don't trust this! I haven't implemented the algorithm selection for this yet
simulation_realizations = data['realizations']
# If the seed is negative, this means choose a seed >= 0 randomly
if int(data['seed']) < 0:
random.seed()
data['seed'] = random.randint(0, 2147483647)
simulation_seed = data['seed']
#####
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = SpatialJobWrapper()
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = data["jobName"]
job.indata = json.dumps(data)
job.outData = dataDir
job.modelName = pymodel.name
job.resource = "local"
job.status = "Running"
model_file_pkl = "{0}/model_file.pkl".format(dataDir)
result_dir = "{0}/results/".format(dataDir)
os.makedirs(result_dir)
# searilize the model and write it to a file in the data dir
with open(model_file_pkl, 'w') as fd:
pickle.dump(pymodel, fd)
cmd = "{0}/../../pyurdme/pyurdme_wrapper.py {1} {2} {3} {4} {5}".format(path, model_file_pkl, result_dir, simulation_algorithm, simulation_realizations, simulation_seed)
logging.info("cmd =\n{}".format(cmd))
exstring = '{0}/backend/wrapper.py {1}/stdout.log {1}/stderr.log {1}/return_code {2}'.format(basedir, dataDir, cmd)
handle = subprocess.Popen(exstring, shell=True, preexec_fn=os.setsid)
job.pid = int(handle.pid)
job.put()
return job
