def runCloud(self, data):
self.user_data.set_selected(1)
service = backendservices(self.user_data)
if not service.isOneOrMoreComputeNodesRunning():
raise Exception(
'No cloud computing resources found. (Have they been started?)'
)
# 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)
pymodel = self.construct_pyurdme_model(data)
#logging.info('DATA: {0}'.format(data))
#####
cloud_params = {
"job_type": "spatial",
"simulation_algorithm": data['algorithm'],
"simulation_realizations": data['realizations'],
"simulation_seed": data['seed'],
# "bucketname" : self.user_data.getBucketName(), #implys EC2, should be in backendservices
"paramstring": '',
}
logging.debug('cloud_params = {}'.format(pprint.pformat(cloud_params)))
cloud_params['document'] = pickle.dumps(pymodel)
#logging.debug('PYURDME: {0}'.format(cloud_params['document']))
# Send the task to the backend
cloud_result = service.submit_cloud_task(params=cloud_params)
if not cloud_result["success"]:
e = cloud_result["exception"]
raise Exception("Cloud execution failed: {0}".format(e))
celery_task_id = cloud_result["celery_pid"]
taskid = cloud_result["db_id"]
job = SpatialJobWrapper()
job.type = 'PyURDME Ensemble'
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 = None # This is where the data should be locally, when we get data from cloud, it must be put here
job.modelName = pymodel.name
job.resource = cloud_result['resource']
job.cloudDatabaseID = taskid
job.celeryPID = celery_task_id
job.status = "Running"
job.output_stored = "True"
job.put()
return job
def runCloud(self, data):
self.user_data.set_selected(1)
service = backendservices(self.user_data)
if not service.isOneOrMoreComputeNodesRunning():
raise Exception('No cloud computing resources found. (Have they been started?)')
# 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)
pymodel = self.construct_pyurdme_model(data)
#logging.info('DATA: {0}'.format(data))
#####
cloud_params = {
"job_type": "spatial",
"simulation_algorithm" : data['algorithm'],
"simulation_realizations" : data['realizations'],
"simulation_seed" : data['seed'],
# "bucketname" : self.user_data.getBucketName(), #implys EC2, should be in backendservices
"paramstring" : '',
}
logging.debug('cloud_params = {}'.format(pprint.pformat(cloud_params)))
cloud_params['document'] = pickle.dumps(pymodel)
#logging.debug('PYURDME: {0}'.format(cloud_params['document']))
# Send the task to the backend
cloud_result = service.submit_cloud_task(params=cloud_params)
if not cloud_result["success"]:
e = cloud_result["exception"]
raise Exception("Cloud execution failed: {0}".format(e))
celery_task_id = cloud_result["celery_pid"]
taskid = cloud_result["db_id"]
job = SpatialJobWrapper()
job.type = 'PyURDME Ensemble'
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 = None # This is where the data should be locally, when we get data from cloud, it must be put here
job.modelName = pymodel.name
job.resource = cloud_result['resource']
job.cloudDatabaseID = taskid
job.celeryPID = celery_task_id
job.status = "Running"
job.output_stored = "True"
job.put()
return job
