def createJob(handler, job, rename = None):
tryName = job["name"]
userID = None
if 'user_id' in job:
userID = job['user_id']
else:
userID = handler.user.user_id()
jobNames = [x.name for x in db.Query(StochKitJobWrapper).filter('user_id =', userID).run()]
if job["name"] in jobNames:
if not rename:
return None
else:
i = 1
tryName = '{0}_{1}'.format(job["name"], i)
while tryName in jobNames:
i = i + 1
tryName = '{0}_{1}'.format(job["name"], i)
if rename:
job["name"] = tryName
jobWrap = StochKitJobWrapper()
jobWrap.user_id = userID
jobWrap.name = job['name']
if 'seed' not in job:
job['seed'] = -1
jobWrap.modelName = job['modelName']
# This is probably not a good idea...
jobWrap.indata = json.dumps(dict([(k, job[k]) for k in ['type', 'final_time', 'increment', 'realizations', 'exec_type', 'units', 'epsilon', 'threshold', 'seed'] if k in job]))
if 'startTime' in job:
jobWrap.startTime = job['startTime']
if 'resource' in job:
jobWrap.resource = job['resource']
else:
jobWrap.resource = 'Local'
jobWrap.outData = job['output_location']
if 'output_url' in job:
jobWrap.outputURL = job['output_url']
jobWrap.stdout = job['stdout']
jobWrap.stderr = job['stderr']
if 'output_stored' in job:
jobWrap.output_stored = job['output_stored']
jobWrap.put()
return jobWrap.key().id()
def createJob(handler, job, rename = None):
tryName = job["name"]
userID = None
if 'user_id' in job:
userID = job['user_id']
else:
userID = handler.user.user_id()
jobNames = [x.name for x in db.Query(StochKitJobWrapper).filter('user_id =', userID).run()]
if job["name"] in jobNames:
if not rename:
return None
else:
i = 1
tryName = '{0}_{1}'.format(job["name"], i)
while tryName in jobNames:
i = i + 1
tryName = '{0}_{1}'.format(job["name"], i)
if rename:
job["name"] = tryName
jobWrap = StochKitJobWrapper()
jobWrap.user_id = userID
jobWrap.name = job['name']
if 'seed' not in job:
job['seed'] = -1
jobWrap.modelName = job['modelName']
# This is probably not a good idea...
jobWrap.indata = json.dumps(dict([(k, job[k]) for k in ['type', 'final_time', 'increment', 'realizations', 'exec_type', 'units', 'epsilon', 'rTol', 'aTol', 'mxSteps', 'threshold', 'seed'] if k in job]))
if 'startTime' in job:
jobWrap.startTime = job['startTime']
if 'resource' in job:
jobWrap.resource = job['resource'].lower()
else:
jobWrap.resource = 'local'
jobWrap.outData = job['output_location']
if 'output_url' in job:
jobWrap.outputURL = job['output_url']
jobWrap.stdout = job['stdout']
jobWrap.stderr = job['stderr']
if 'output_stored' in job:
jobWrap.output_stored = job['output_stored']
jobWrap.put()
return jobWrap.key().id()
def runCloud(self, params):
model = StochKitModelWrapper.get_by_id(params["id"]).createStochKitModel()
if not model:
raise Exception('Failed to retrive the model \'{0}\' to simulate'.format(params["id"]))
#the parameter dictionary to be passed to the backend
param = {}
# Execute as concentration or population?
exec_type = params['execType'].lower()
if exec_type not in ["deterministic", "stochastic"]:
raise Exception('exec_type must be concentration or population. Found \'{0}\''.format(exec_type))
if model.units.lower() == 'concentration' and exec_type.lower() == 'stochastic':
raise Exception('Concentration models cannot be executed Stochastically' )
executable = exec_type.lower()
document = model.serialize()
# Wow, what a hack
if executable == 'deterministic' and model.units.lower() == 'population':
model = StochMLDocument.fromString(document).toModel(model.name)
for reactionN in model.getAllReactions():
reaction = model.getAllReactions()[reactionN]
if reaction.massaction:
if len(reaction.reactants) == 1 and reaction.reactants.values()[0] == 2:
reaction.marate.setExpression(reaction.marate.expression + ' / 2')
document = model.serialize()
params['document']=str(document)
filepath = ""
params['file'] = filepath
ensemblename = params['jobName']
stime = params['time']
realizations = params['realizations']
increment = params['increment']
if int(params['seed']) < 0:
random.seed()
params['seed'] = random.randint(0, 2147483647)
seed = params['seed']
# Assemble the argument list
args = ''
args+=' -t '
args+=str(stime)
num_output_points = str(int(float(stime)/float(increment)))
args+=' -i ' + str(num_output_points)
path = os.path.dirname(__file__)
# Algorithm, SSA or Tau-leaping?
if executable != 'deterministic':
params['job_type'] = 'stochkit'
executable = params['algorithm']
args+=' --realizations '
args+=str(realizations)
# We keep all the trajectories by default. The user can select to only store means and variance
# through the advanced options.
if not "only-moments" in params:
args+=' --keep-trajectories'
if "keep-histograms" in params:
args+=' --keep-histograms'
args+=' --seed '
args+=str(seed)
else:
params['job_type'] = 'stochkit_ode'
executable = "stochkit_ode.py"
# Columns need to be labeled for visulatization page to work.
args += ' --label'
cmd = executable+' '+args
params['paramstring'] = cmd
bucketname = self.user_data.getBucketName()
params['bucketname'] = bucketname
params['user_id'] = self.user.user_id()
# Call backendservices and execute StochKit
service = backendservices(self.user_data)
cloud_result = service.submit_cloud_task(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"]
# Create a StochKitJob instance
job = StochKitJobWrapper()
job.resource = cloud_result['resource']
# stochkit_job.uuid = res['uuid']
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = params['jobName']
job.modelName = model.name
#job.pid = taskid
job.celeryPID = celery_task_id
job.cloudDatabaseID = taskid
# Create a StochKitJob instance
job.indata = json.dumps({ "type" : 'StochKit2 Ensemble',
"final_time" : params['time'],
"realizations" : params['realizations'],
"increment" : params['increment'],
"seed" : params['seed'],
"exec_type" : params['execType'],
"units" : model.units.lower(),
"epsilon" : params['epsilon'],
"threshold" : params['threshold'] })
job.output_stored = 'True'
job.outData = None
#job.stdout = '{0}/stdout'.format(dataDir)
#job.stderr = '{0}/stderr'.format(dataDir)
job.status = 'Running'
job.put()
return job
def runCloud(self, params):
model = StochKitModelWrapper.get_by_id(
params["id"]).createStochKitModel()
if not model:
raise Exception(
'Failed to retrive the model \'{0}\' to simulate'.format(
params["id"]))
#the parameter dictionary to be passed to the backend
param = {}
# Execute as concentration or population?
exec_type = params['execType'].lower()
if exec_type not in ["deterministic", "stochastic"]:
raise Exception(
'exec_type must be concentration or population. Found \'{0}\''.
format(exec_type))
if model.units.lower() == 'concentration' and exec_type.lower(
) == 'stochastic':
raise Exception(
'Concentration models cannot be executed Stochastically')
executable = exec_type.lower()
document = model.serialize()
# Wow, what a hack
if executable == 'deterministic' and model.units.lower(
) == 'population':
model = StochMLDocument.fromString(document).toModel(model.name)
for reactionN in model.getAllReactions():
reaction = model.getAllReactions()[reactionN]
if reaction.massaction:
if len(reaction.reactants
) == 1 and reaction.reactants.values()[0] == 2:
reaction.marate.setExpression(
reaction.marate.expression + ' / 2')
document = model.serialize()
params['document'] = str(document)
filepath = ""
params['file'] = filepath
ensemblename = params['jobName']
stime = params['time']
realizations = params['realizations']
increment = params['increment']
if int(params['seed']) < 0:
random.seed()
params['seed'] = random.randint(0, 2147483647)
seed = params['seed']
# Assemble the argument list
args = ''
args += ' -t '
args += str(stime)
num_output_points = str(int(float(stime) / float(increment)))
args += ' -i ' + str(num_output_points)
path = os.path.dirname(__file__)
# Algorithm, SSA or Tau-leaping?
if executable != 'deterministic':
params['job_type'] = 'stochkit'
executable = params['algorithm']
args += ' --realizations '
args += str(realizations)
# We keep all the trajectories by default. The user can select to only store means and variance
# through the advanced options.
if not "only-moments" in params:
args += ' --keep-trajectories'
if "keep-histograms" in params:
args += ' --keep-histograms'
args += ' --seed '
args += str(seed)
else:
params['job_type'] = 'stochkit_ode'
executable = "stochkit_ode.py"
# Columns need to be labeled for visulatization page to work.
args += ' --label'
cmd = executable + ' ' + args
params['paramstring'] = cmd
bucketname = self.user_data.getBucketName()
params['bucketname'] = bucketname
params['user_id'] = self.user.user_id()
# Call backendservices and execute StochKit
service = backendservices(self.user_data)
cloud_result = service.submit_cloud_task(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"]
# Create a StochKitJob instance
job = StochKitJobWrapper()
job.resource = cloud_result['resource']
# stochkit_job.uuid = res['uuid']
job.user_id = self.user.user_id()
job.startTime = time.strftime("%Y-%m-%d-%H-%M-%S")
job.name = params['jobName']
job.modelName = model.name
#job.pid = taskid
job.celeryPID = celery_task_id
job.cloudDatabaseID = taskid
# Create a StochKitJob instance
job.indata = json.dumps({
"type": 'StochKit2 Ensemble',
"final_time": params['time'],
"realizations": params['realizations'],
"increment": params['increment'],
"seed": params['seed'],
"exec_type": params['execType'],
"units": model.units.lower(),
"epsilon": params['epsilon'],
"rTol": params['rTol'],
"aTol": params['aTol'],
"mxSteps": params['mxSteps'],
"threshold": params['threshold']
})
job.output_stored = 'True'
job.outData = None
#job.stdout = '{0}/stdout'.format(dataDir)
#job.stderr = '{0}/stderr'.format(dataDir)
job.status = 'Running'
job.put()
return job
def runQsub(self, data, cluster_info):
from db_models.parameter_sweep_job import ParameterSweepJobWrapper
from modeleditor import StochKitModelWrapper
import parametersweep_qsub
logging.error("*" * 80)
logging.error("simulate.runQsub() modelType={0}".format(data['execType']))
logging.error("*" * 80)
modelDb = StochKitModelWrapper.get_by_id(int(data["id"]))
# TODO: Ben needs to fix the following code to work directly with StochKitModelWrappers
# model = StochKitModelWrapper.get_by_id(params["id"]).createStochKitModel()
#
# if not model:
# raise Exception('Failed to retrive the model \'{0}\' to simulate'.format(params["id"]))
#
# # Execute as concentration or population?
# exec_type = params['execType'].lower()
#
# if exec_type not in ["deterministic", "stochastic"]:
# raise Exception('exec_type must be concentration or population. Found \'{0}\''.format(exec_type))
#
# if model.units.lower() == 'concentration' and exec_type.lower() == 'stochastic':
# raise Exception('Concentration models cannot be executed Stochastically' )
#
# document = model.serialize()
#
# # Wow, what a hack
#
# if executable == 'deterministic' and model.units.lower() == 'population':
# model = StochMLDocument.fromString(document).toModel(model.name)
#
# for reactionN in model.getAllReactions():
# reaction = model.getAllReactions()[reactionN]
# if reaction.massaction:
# if len(reaction.reactants) == 1 and reaction.reactants.values()[0] == 2:
# reaction.marate.setExpression(reaction.marate.expression + ' / 2')
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir=basedir + 'output')
job = StochKitJobWrapper()
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.indata = json.dumps({ "type" : 'StochKit2 Ensemble',
"final_time" : data['time'],
"realizations" : data['realizations'],
"increment" : data['increment'],
"seed" : data['seed'],
"exec_type" : data['execType'],
"units" : modelDb.units.lower(),
"epsilon" : data['epsilon'],
"rTol" : data['rTol'],
"aTol" : data['aTol'],
"mxSteps" : data['mxSteps'],
"threshold" : data['threshold'] })
job.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
job.output_stored = "False"
job.is_simulation = True
job.resource = "qsub"
try:
templateData = {
"name": modelDb.name,
"modelType": modelDb.type,
"species": modelDb.species,
"parameters": modelDb.parameters,
"reactions": modelDb.reactions,
# "speciesSelect": data['speciesSelect'],
"speciesSelect": data['selections'],
# "maxTime": data['maxTime'],
"maxTime": data['time'],
"increment": data['increment'],
# "trajectories": data['trajectories'],
"trajectories": data['realizations'],
"seed": data['seed'],
"isSpatial": modelDb.isSpatial,
"isLocal": True
}
if modelDb.isSpatial:
try:
meshWrapperDb = mesheditor.MeshWrapper.get_by_id(modelDb.spatial["mesh_wrapper_id"])
except Exception as e:
logging.exception(e)
logging.error("No Mesh file set. Choose one in the Mesh tab of the Model Editor")
raise Exception("No Mesh file set. Choose one in the Mesh tab of the Model Editor")
try:
meshFileObj = fileserver.FileManager.getFile(self, meshWrapperDb.meshFileId, noFile=False)
templateData["mesh"] = meshFileObj["data"]
except IOError as e:
logging.exception(e)
logging.error("Mesh file inaccessible. Try another mesh")
raise Exception("Mesh file inaccessible. Try another mesh")
templateData['reaction_subdomain_assignments'] = modelDb.spatial["reactions_subdomain_assignments"]
templateData['species_subdomain_assignments'] = modelDb.spatial["species_subdomain_assignments"]
templateData['species_diffusion_coefficients'] = modelDb.spatial["species_diffusion_coefficients"]
templateData['initial_conditions'] = modelDb.spatial["initial_conditions"]
templateData['subdomains'] = meshWrapperDb.subdomains
if data['execType'] == "stochastic":
job.qsubHandle = pickle.dumps(parametersweep_qsub.stochastic(templateData, cluster_info,
not_full_parameter_sweep=True))
elif data['execType'] == "deterministic":
job.qsubHandle = pickle.dumps(parametersweep_qsub.deterministic(templateData, cluster_info,
not_full_parameter_sweep=True))
elif data['execType'] == "spatial":
job.qsubHandle = pickle.dumps(parametersweep_qsub.spatial(templateData, cluster_info,
not_full_parameter_sweep=True))
else:
raise Exception("Trying to runQsub on unsupported modelType {0}".format(data['modelType']))
job.put()
except Exception as e:
exc_info = sys.exc_info()
logging.exception(e)
job.status = 'Failed'
try:
job.delete(self)
except Exception as e:
pass
raise exc_info[1], None, exc_info[2]
return job
