def runCloud(self, data):
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
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.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
data["exec"] = "'bash'"
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
# data["cores"] = 4
data["options"] = ""
cmd = "exec/mcem2.r --steps {steps} --seed {seed} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
# cmd = "exec/mcem2.r --K.ce 1000 --K.em 100 --rho .01 --pcutoff .05"
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
job.put()
cloud_params = {
"job_id" : job.key().id(),
"job_type": "mcem2",
# "cores": data["cores"],
"paramstring": cmd,
"model_file": stringModel,
"model_data": {
"content": self.addWeightColumnIfNecessary(iFileData["data"]),
"extension": "txt"
},
"final_data": {
"content": self.addWeightColumnIfNecessary(jFileData["data"]),
"extension": "txt"
},
"key_prefix": self.user.user_id(),
"credentials": self.user_data.getCredentials(),
"bucketname": self.user_data.getBucketName()
}
# # execute cloud task
try:
service = backend.backendservice.backendservices(self.user_data)
cloud_result = service.submit_cloud_task(params=cloud_params)
if not cloud_result["success"]:
raise Exception(cloud_result["reason"])
job.cloudDatabaseID = cloud_result["db_id"]
job.resource = cloud_result['resource']
job.celeryPID = cloud_result["celery_pid"]
# job.pollProcessPID = int(cloud_result["poll_process_pid"])
# job.pid = handle.pid
job.put()
except Exception as e:
job.status='Failed'
job.delete(self)
raise
return job
def runMolns(self, data):
self.user_data.set_selected(2)
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir=basedir + 'output')
job = ParameterSweepJobWrapper()
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.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
job.output_stored = False
# # execute cloud task
try:
template_filename = 'parametersweep_template_{0}.py'.format(
data['modelType'])
logging.error(
"parametersweep.runMolns() template_filename={0}".format(
template_filename))
logging.error("*" * 80)
with open(os.path.join(path, template_filename), 'r') as f:
template = f.read()
templateData = {
"name": modelDb.name,
"modelType": modelDb.type,
"species": modelDb.species,
"parameters": modelDb.parameters,
"reactions": modelDb.reactions,
"speciesSelect": data['speciesSelect'],
"maxTime": data['maxTime'],
"increment": data['increment'],
"trajectories": data['trajectories'],
"seed": data['seed'],
"parameterA": data['parameterA'],
"minValueA": data['minValueA'],
"maxValueA": data['maxValueA'],
"stepsA": data['stepsA'],
"logA": data['logA'],
"parameterB": data['parameterB'],
"minValueB": data['minValueB'],
"maxValueB": data['maxValueB'],
"stepsB": data['stepsB'],
"logB": data['logB'],
"variableCount": data['variableCount'],
"isSpatial": modelDb.isSpatial,
"isLocal": False
}
if modelDb.isSpatial:
try:
meshWrapperDb = mesheditor.MeshWrapper.get_by_id(
modelDb.spatial["mesh_wrapper_id"])
except Exception as e:
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:
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
program = os.path.join(dataDir, 'program.py')
with open(program, 'w') as f:
jsonString = json.dumps(templateData, indent=4, sort_keys=True)
# We've got to double escape the strings here cause of how we're substituting the JSON data in a source file
jsonString = jsonString.replace('\\', '\\\\')
f.write(template.replace('___JSON_STRING___', jsonString))
molnsConfigDb = db.GqlQuery(
"SELECT * FROM MolnsConfigWrapper WHERE user_id = :1",
self.user.user_id()).get()
if not molnsConfigDb:
raise Exception("Molns not initialized")
config = molns.MOLNSConfig(config_dir=molnsConfigDb.folder)
result = molns.MOLNSExec.start_job(
['EC2_controller', "python {0}".format(program)], config)
job.resource = "molns"
job.molnsPID = result['id']
job.put()
except Exception as e:
job.status = 'Failed'
job.delete(self)
raise
return job
def runLocal(self, data):
'''
'''
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
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 = modelDb.name
job.resource = "local"
job.status = "Running"
# Convert model and write to file
model_file_file = tempfile.mktemp(prefix = 'modelFile', suffix = '.R', dir = dataDir)
mff = open(model_file_file, 'w')
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
mff.write(stringModel)
mff.close()
data["model_file_file"] = model_file_file
model_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
mdf = open(model_data_file, 'w')
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
mdf.write(self.addWeightColumnIfNecessary(jFileData["data"]))
mdf.close()
data["model_data_file"] = model_data_file
model_initial_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
midf = open(model_initial_data_file, 'w')
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
midf.write(self.addWeightColumnIfNecessary(iFileData["data"]))
midf.close()
data["model_initial_data_file"] = model_initial_data_file
data["exec"] = "\"bash&\""
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
try:
import multiprocessing
data["cores"] = multiprocessing.cpu_count()
except:
data["cores"] = 1
data["options"] = ""
data["path"] = path
cmd = "Rscript --vanilla {path}/../../stochoptim/exec/mcem2.r --model {model_file_file} --data {model_initial_data_file} --finalData {model_data_file} --steps {steps} --seed {seed} --cores {cores} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
exstring = '{0}/backend/wrapper.py {1}/stdout {1}/stderr {1}/return_code {2}'.format(basedir, dataDir, cmd)
handle = subprocess.Popen(exstring, shell=True, preexec_fn=os.setsid)
job.pid = handle.pid
job.put()
return job
def runStochKitLocal(self, params):
""" Submit a local StochKit job """
modelDb = StochKitModelWrapper.get_by_id(params["id"])
if not modelDb:
return {'status':False,
'msg':'Failed to retrive the model to simulate.'}
model = modelDb.createStochKitModel()
# Execute as concentration or population?
execType = params['execType'].lower()
if execType not in ["deterministic", "stochastic", "sensitivity"]:
raise Exception('exec_type must be deterministic, sensitivity, or stochastic. Found "{0}"'.format(execType))
if model.units.lower() == 'concentration' and execType.lower() == 'stochastic':
raise Exception('Concentration models cannot be executed stochastically')
# Assemble the argument list
args = ''
args += ' -t {0} '.format(params['time'])
num_output_points = int(float(params['time'])/float(params['increment']))
args += ' -i {0} '.format(num_output_points)
path = os.path.abspath(os.path.dirname(__file__))
# Algorithm, SSA or Tau-leaping?
if params['execType'] != 'deterministic':
executable = "{0}/../../StochKit/{1}".format(path, params['algorithm'])
args += ' --realizations {0} '.format(params['realizations'])
args += ' --keep-trajectories '
if int(params['seed']) < 0:
random.seed()
params['seed'] = random.randint(0, 2147483647)
args += '--seed {0} '.format(params['seed'])
else:
executable = "{0}/../../ode/stochkit_ode.py".format(path)
# Columns need to be labeled for visulatization page to work.
args += ' --label'
cmd = executable + ' ' + args
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
# Wow, what a hack
if params['execType'] == 'deterministic' and model.units.lower() == 'population':
document = model.serialize()
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')
modelFileName = '{0}/{1}.xml'.format(dataDir, model.name)
fmodelHandle = open(modelFileName, 'w')
fmodelHandle.write(model.serialize())
fmodelHandle.close()
cmd += ' -m {0} --out-dir {1}/result'.format(modelFileName, dataDir)
logging.info("cmd =\n{}".format(cmd))
logging.debug('simulation.runLocal(): cmd={0}'.format(cmd))
logging.debug('*'*80)
logging.debug('*'*80)
#ode = "{0}/../../ode/stochkit_ode.py {1}".format(path, args)
exstring = '{0}/backend/wrapper.py {1}/stdout {1}/stderr {1}/return_code {2}'.format(basedir, dataDir, cmd)
logging.debug('simulation.runLocal(): exstring={0}'.format(exstring))
logging.debug('*'*80)
logging.debug('*'*80)
handle = subprocess.Popen(exstring.split(), preexec_fn=os.setsid)
# Create a wrapper to store the Job description in the datastore
job = StochKitJobWrapper()
job.resource = 'Local'
# 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 = handle.pid
# 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.outData = dataDir
job.stdout = '{0}/stdout'.format(dataDir)
job.stderr = '{0}/stderr'.format(dataDir)
job.status = 'Running'
job.put()
return job
def construct_pyurdme_model(self, data):
'''
'''
json_model_refs = ModelManager.getModel(self, data["id"]) # data["id"] is the model id of the selected model I think
stochkit_model_obj = StochKitModelWrapper.get_by_id(data["id"]).createStochKitModel()
#print 'json_model_refs["spatial"]["mesh_wrapper_id"]:', json_model_refs["spatial"]["mesh_wrapper_id"]
try:
meshWrapperDb = mesheditor.MeshWrapper.get_by_id(json_model_refs["spatial"]["mesh_wrapper_id"])
except Exception as e:
raise Exception("No Mesh file set. Choose one in the Mesh tab of the Model Editor")
try:
meshFileObj = fileserver.FileManager.getFile(self, meshWrapperDb.meshFileId)
mesh_filename = meshFileObj["storePath"]
except IOError as e:
#blowup here, need a mesh
#self.response.write(json.dumps({"status" : False,
# "msg" : "No Mesh file given"}))
#return
raise Exception("Mesh file inaccessible. Try another mesh")
#TODO: if we get advanced options, we don't need a mesh
reaction_subdomain_assigments = json_model_refs["spatial"]["reactions_subdomain_assignments"] #e.g. {'R1':[1,2,3]}
species_subdomain_assigments = json_model_refs["spatial"]["species_subdomain_assignments"] #e.g. {'S1':[1,2,3]}
species_diffusion_coefficients = json_model_refs["spatial"]["species_diffusion_coefficients"] #e.g. {'S1':0.5}
initial_conditions = json_model_refs["spatial"]["initial_conditions"] #e.g. { ic0 : { type : "place", species : "S0", x : 5.0, y : 10.0, z : 1.0, count : 5000 }, ic1 : { type : "scatter",species : "S0", subdomain : 1, count : 100 }, ic2 : { type : "distribute",species : "S0", subdomain : 2, count : 100 } }
for species in stochkit_model_obj.listOfSpecies:
if species not in species_diffusion_coefficients:
raise Exception("Species '{0}' does not have a diffusion coefficient set. Please do that in the Species tab of the Model Editor".format(species))
simulation_end_time = data['time']
simulation_time_increment = data['increment']
simulation_algorithm = data['algorithm'] # Don't trust this! I haven't implemented the algorithm selection for this yet
simulation_exec_type = data['execType'] # This should contain 'spatial' -- Not that you really need it, only spatial requests will be routed here
simulation_realizations = data['realizations']
simulation_seed = data['seed'] # If this is set to -1, it means choose a seed at random! (Whatever that means)
#### Construct the PyURDME object from the Stockkit model and mesh and other inputs
try:
# model
pymodel = pyurdme.URDMEModel(name=stochkit_model_obj.name)
# mesh
pymodel.mesh = pyurdme.URDMEMesh.read_dolfin_mesh(str(mesh_filename))
# timespan
pymodel.timespan(numpy.arange(0,simulation_end_time+simulation_time_increment, simulation_time_increment))
# subdomains
if len(meshWrapperDb.subdomains) > 0:
pymodel.set_subdomain_vector(numpy.array(meshWrapperDb.subdomains))
# species
for s in stochkit_model_obj.listOfSpecies:
pymodel.add_species(pyurdme.Species(name=s, diffusion_constant=float(species_diffusion_coefficients[s])))
# species subdomain restriction
for s, sd_list in species_subdomain_assigments.iteritems():
spec = pymodel.listOfSpecies[s]
pymodel.restrict(spec, sd_list)
# parameters
for p_name, p in stochkit_model_obj.listOfParameters.iteritems():
pymodel.add_parameter(pyurdme.Parameter(name=p_name, expression=p.expression))
# reactions
for r_name, r in stochkit_model_obj.listOfReactions.iteritems():
if r.massaction:
pymodel.add_reaction(pyurdme.Reaction(name=r_name, reactants=r.reactants, products=r.products, rate=r.marate, massaction=True))
else:
pymodel.add_reaction(pyurdme.Reaction(name=r_name, reactants=r.reactants, products=r.products, propensity_function=r.propensity_function))
# reaction subdomain restrictions
for r in reaction_subdomain_assigments:
pymodel.listOfReactions[r].restrict_to = reaction_subdomain_assigments[r]
# Initial Conditions
# initial_conditions = json_model_refs["spatial"]["initial_conditions"] #e.g. { ic0 : { type : "place", species : "S0", x : 5.0, y : 10.0, z : 1.0, count : 5000 }, ic1 : { type : "scatter",species : "S0", subdomain : 1, count : 100 }, ic2 : { type : "distribute",species : "S0", subdomain : 2, count : 100 } }
for ic in initial_conditions:
spec = pymodel.listOfSpecies[ic['species']]
if ic['type'] == "place":
pymodel.set_initial_condition_place_near({spec:int(ic['count'])}, point=[float(ic['x']),float(ic['y']),float(ic['z'])])
elif ic['type'] == "scatter":
pymodel.set_initial_condition_scatter({spec:int(ic['count'])},subdomains=[int(ic['subdomain'])])
elif ic['type'] == "distribute":
pymodel.set_initial_condition_distribute_uniformly({spec:int(ic['count'])},subdomains=[int(ic['subdomain'])])
else:
#self.response.write(json.dumps({"status" : False,
# "msg" : "Unknown initial condition type {0}".format(ic['type'])}))
#return
raise Exception("Unknown initial condition type {0}".format(ic['type']))
except Exception as e:
raise Exception("Error while assembling the model: {0}".format(e))
return pymodel
def construct_pyurdme_model(self, data):
'''
'''
json_model_refs = ModelManager.getModel(
self, int(data["id"])
) # data["id"] is the model id of the selected model I think
stochkit_model_obj = StochKitModelWrapper.get_by_id(int(
data["id"])).createStochKitModel()
#print 'json_model_refs["spatial"]["mesh_wrapper_id"]:', json_model_refs["spatial"]["mesh_wrapper_id"]
try:
meshWrapperDb = mesheditor.MeshWrapper.get_by_id(
json_model_refs["spatial"]["mesh_wrapper_id"])
except Exception as e:
raise Exception(
"No Mesh file set. Choose one in the Mesh tab of the Model Editor"
)
try:
meshFileObj = fileserver.FileManager.getFile(
self, meshWrapperDb.meshFileId)
mesh_filename = meshFileObj["storePath"]
except IOError as e:
#blowup here, need a mesh
#self.response.write(json.dumps({"status" : False,
# "msg" : "No Mesh file given"}))
#return
raise Exception("Mesh file inaccessible. Try another mesh")
#TODO: if we get advanced options, we don't need a mesh
reaction_subdomain_assigments = json_model_refs["spatial"][
"reactions_subdomain_assignments"] #e.g. {'R1':[1,2,3]}
species_subdomain_assigments = json_model_refs["spatial"][
"species_subdomain_assignments"] #e.g. {'S1':[1,2,3]}
species_diffusion_coefficients = json_model_refs["spatial"][
"species_diffusion_coefficients"] #e.g. {'S1':0.5}
initial_conditions = json_model_refs["spatial"][
"initial_conditions"] #e.g. { ic0 : { type : "place", species : "S0", x : 5.0, y : 10.0, z : 1.0, count : 5000 }, ic1 : { type : "scatter",species : "S0", subdomain : 1, count : 100 }, ic2 : { type : "distribute",species : "S0", subdomain : 2, count : 100 } }
for species in stochkit_model_obj.listOfSpecies:
if species not in species_diffusion_coefficients:
raise Exception(
"Species '{0}' does not have a diffusion coefficient set. Please do that in the Species tab of the Model Editor"
.format(species))
simulation_end_time = data['time']
simulation_time_increment = data['increment']
simulation_algorithm = data[
'algorithm'] # Don't trust this! I haven't implemented the algorithm selection for this yet
simulation_exec_type = data[
'execType'] # This should contain 'spatial' -- Not that you really need it, only spatial requests will be routed here
simulation_realizations = data['realizations']
simulation_seed = data[
'seed'] # If this is set to -1, it means choose a seed at random! (Whatever that means)
#### Construct the PyURDME object from the Stockkit model and mesh and other inputs
try:
# model
pymodel = pyurdme.URDMEModel(name=stochkit_model_obj.name)
# mesh
pymodel.mesh = pyurdme.URDMEMesh.read_dolfin_mesh(
str(mesh_filename))
# timespan
pymodel.timespan(
numpy.arange(0,
simulation_end_time + simulation_time_increment,
simulation_time_increment))
# subdomains
if len(meshWrapperDb.subdomains) > 0:
pymodel.set_subdomain_vector(
numpy.array(meshWrapperDb.subdomains))
# species
for s in stochkit_model_obj.listOfSpecies:
pymodel.add_species(
pyurdme.Species(name=s,
diffusion_constant=float(
species_diffusion_coefficients[s])))
# species subdomain restriction
for s, sd_list in species_subdomain_assigments.iteritems():
spec = pymodel.listOfSpecies[s]
pymodel.restrict(spec, sd_list)
# parameters
for p_name, p in stochkit_model_obj.listOfParameters.iteritems():
pymodel.add_parameter(
pyurdme.Parameter(name=p_name, expression=p.expression))
# reactions
for r_name, r in stochkit_model_obj.listOfReactions.iteritems():
if r.massaction:
pymodel.add_reaction(
pyurdme.Reaction(name=r_name,
reactants=r.reactants,
products=r.products,
rate=r.marate,
massaction=True))
else:
pymodel.add_reaction(
pyurdme.Reaction(
name=r_name,
reactants=r.reactants,
products=r.products,
propensity_function=r.propensity_function))
# reaction subdomain restrictions
for r in reaction_subdomain_assigments:
pymodel.listOfReactions[
r].restrict_to = reaction_subdomain_assigments[r]
# Initial Conditions
# initial_conditions = json_model_refs["spatial"]["initial_conditions"] #e.g. { ic0 : { type : "place", species : "S0", x : 5.0, y : 10.0, z : 1.0, count : 5000 }, ic1 : { type : "scatter",species : "S0", subdomain : 1, count : 100 }, ic2 : { type : "distribute",species : "S0", subdomain : 2, count : 100 } }
for ic in initial_conditions:
spec = pymodel.listOfSpecies[ic['species']]
if ic['type'] == "place":
pymodel.set_initial_condition_place_near(
{spec: int(ic['count'])},
point=[float(ic['x']),
float(ic['y']),
float(ic['z'])])
elif ic['type'] == "scatter":
pymodel.set_initial_condition_scatter(
{spec: int(ic['count'])},
subdomains=[int(ic['subdomain'])])
elif ic['type'] == "distribute":
pymodel.set_initial_condition_distribute_uniformly(
{spec: int(ic['count'])},
subdomains=[int(ic['subdomain'])])
else:
#self.response.write(json.dumps({"status" : False,
# "msg" : "Unknown initial condition type {0}".format(ic['type'])}))
#return
raise Exception(
"Unknown initial condition type {0}".format(
ic['type']))
except Exception as e:
raise Exception("Error while assembling the model: {0}".format(e))
return pymodel
def runMolns(self, params):
""" Submit a remote molns StochKit job """
modelDb = StochKitModelWrapper.get_by_id(params["id"])
sys.stderr.write("*"*80 + "\n")
sys.stderr.write("*"*80 + "\n")
sys.stderr.write("runMolns\n")
logging.info('runMolns')
sys.stderr.write("*"*80 + "\n")
sys.stderr.write("*"*80 + "\n")
if not modelDb:
return {'status':False,
'msg':'Failed to retrive the model to simulate.'}
model = modelDb.createStochKitModel()
# Execute as concentration or population?
execType = params['execType'].lower()
if execType not in ["deterministic", "stochastic", "sensitivity"]:
raise Exception('exec_type must be deterministic, sensitivity, or stochastic. Found "{0}"'.format(execType))
if model.units.lower() == 'concentration' and execType.lower() == 'stochastic':
raise Exception('Concentration models cannot be executed stochastically')
# Assemble the argument list
args = ''
args += ' -t {0} '.format(params['time'])
num_output_points = int(float(params['time'])/float(params['increment']))
args += ' -i {0} '.format(num_output_points)
path = os.path.abspath(os.path.dirname(__file__))
# Algorithm, SSA or Tau-leaping?
if params['execType'] != 'deterministic':
executable = "/usr/local/StochKit/{0}".format(params['algorithm'])
args += ' --realizations {0} '.format(params['realizations'])
args += ' --keep-trajectories '
if int(params['seed']) < 0:
random.seed()
params['seed'] = random.randint(0, 2147483647)
args += '--seed {0} '.format(params['seed'])
else:
executable = "/usr/local/ode-1.0.2/stochkit_ode.py"
# Columns need to be labeled for visulatization page to work.
args += ' --label'
cmd = executable + ' ' + args
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
# Wow, what a hack
if params['execType'] == 'deterministic' and model.units.lower() == 'population':
document = model.serialize()
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')
modelFileName = '{0}/{1}.xml'.format(dataDir, model.name)
with open(modelFileName, 'w') as fmodelHandle:
fmodelHandle.write(model.serialize())
cmd += ' -m {0} --out-dir ./result'.format(os.path.basename(modelFileName))
sys.stderr.write('*'*80+"\n")
logging.error("cmd =\n{}".format(cmd))
sys.stderr.write('simulation.runMolns(): cmd={0}\n'.format(cmd))
with tempfile.NamedTemporaryFile() as exec_file:
exec_file.write(cmd+"\n")
exec_file.write("tar -czf result.tar.gz result")
exec_file.flush()
controllerName = 'EC2_controller' #TODO: look this up
exec_str = "bash {0} {1}".format(exec_file.name, modelFileName)
sys.stderr.write("result = molns.MOLNSExec.start_job(['{0}', '{1}])".format(controllerName, exec_str))
sys.stderr.write('*'*80+"\n")
molnsConfigDb = db.GqlQuery("SELECT * FROM MolnsConfigWrapper WHERE user_id = :1", self.user.user_id()).get()
if not molnsConfigDb:
raise Exception("Molns not initialized")
config = molns.MOLNSConfig(config_dir=molnsConfigDb.folder)
result = molns.MOLNSExec.start_job([controllerName, exec_str], config)
sys.stderr.write('result = {0}'.format(result))
sys.stderr.write('*'*80+"\n")
# Create a wrapper to store the Job description in the datastore
# Create a StochKitJob instance
job = StochKitJobWrapper()
job.resource = 'Molns'
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 = None
job.pid = result['id']
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.outData = dataDir
job.status = 'Running'
job.put()
return job
def runMolns(self, params):
""" Submit a remote molns StochKit job """
modelDb = StochKitModelWrapper.get_by_id(params["id"])
sys.stderr.write("*" * 80 + "\n")
sys.stderr.write("*" * 80 + "\n")
sys.stderr.write("runMolns\n")
logging.info('runMolns')
sys.stderr.write("*" * 80 + "\n")
sys.stderr.write("*" * 80 + "\n")
if not modelDb:
return {
'status': False,
'msg': 'Failed to retrive the model to simulate.'
}
model = modelDb.createStochKitModel()
# Execute as concentration or population?
execType = params['execType'].lower()
if execType not in ["deterministic", "stochastic", "sensitivity"]:
raise Exception(
'exec_type must be deterministic, sensitivity, or stochastic. Found "{0}"'
.format(execType))
if model.units.lower() == 'concentration' and execType.lower(
) == 'stochastic':
raise Exception(
'Concentration models cannot be executed stochastically')
# Assemble the argument list
args = ''
args += ' -t {0} '.format(params['time'])
num_output_points = int(
float(params['time']) / float(params['increment']))
args += ' -i {0} '.format(num_output_points)
path = os.path.abspath(os.path.dirname(__file__))
# Algorithm, SSA or Tau-leaping?
if params['execType'] != 'deterministic':
executable = "/usr/local/StochKit/{0}".format(params['algorithm'])
args += ' --realizations {0} '.format(params['realizations'])
args += ' --keep-trajectories '
if int(params['seed']) < 0:
random.seed()
params['seed'] = random.randint(0, 2147483647)
args += '--seed {0} '.format(params['seed'])
else:
executable = "/usr/local/ode-1.0.2/stochkit_ode.py"
# Columns need to be labeled for visulatization page to work.
args += ' --label'
cmd = executable + ' ' + args
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir=basedir + 'output')
# Wow, what a hack
if params['execType'] == 'deterministic' and model.units.lower(
) == 'population':
document = model.serialize()
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')
modelFileName = '{0}/{1}.xml'.format(dataDir, model.name)
with open(modelFileName, 'w') as fmodelHandle:
fmodelHandle.write(model.serialize())
cmd += ' -m {0} --out-dir ./result'.format(
os.path.basename(modelFileName))
sys.stderr.write('*' * 80 + "\n")
logging.error("cmd =\n{}".format(cmd))
sys.stderr.write('simulation.runMolns(): cmd={0}\n'.format(cmd))
with tempfile.NamedTemporaryFile() as exec_file:
exec_file.write(cmd + "\n")
exec_file.write("tar -czf result.tar.gz result")
exec_file.flush()
controllerName = 'EC2_controller' #TODO: look this up
exec_str = "bash {0} {1}".format(exec_file.name, modelFileName)
sys.stderr.write(
"result = molns.MOLNSExec.start_job(['{0}', '{1}])".format(
controllerName, exec_str))
sys.stderr.write('*' * 80 + "\n")
molnsConfigDb = db.GqlQuery(
"SELECT * FROM MolnsConfigWrapper WHERE user_id = :1",
self.user.user_id()).get()
if not molnsConfigDb:
raise Exception("Molns not initialized")
config = molns.MOLNSConfig(config_dir=molnsConfigDb.folder)
result = molns.MOLNSExec.start_job([controllerName, exec_str],
config)
sys.stderr.write('result = {0}'.format(result))
sys.stderr.write('*' * 80 + "\n")
# Create a wrapper to store the Job description in the datastore
# Create a StochKitJob instance
job = StochKitJobWrapper()
job.resource = 'Molns'
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 = None
job.pid = result['id']
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.outData = 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):
logging.error("*"*80)
logging.error("parametersweep.runQsub() modelType={0}".format(data['modelType']))
logging.error("*"*80)
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = ParameterSweepJobWrapper()
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.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
job.output_stored = False
try:
templateData = {
"name" : modelDb.name,
"modelType" : modelDb.type,
"species" : modelDb.species,
"parameters" : modelDb.parameters,
"reactions" : modelDb.reactions,
"speciesSelect" : data['speciesSelect'],
"maxTime" : data['maxTime'],
"increment" : data['increment'],
"trajectories" : data['trajectories'],
"seed" : data['seed'],
"parameterA" : data['parameterA'],
"minValueA" : data['minValueA'],
"maxValueA" : data['maxValueA'],
"stepsA" : data['stepsA'],
"logA" : data['logA'],
"parameterB" : data['parameterB'],
"minValueB" : data['minValueB'],
"maxValueB" : data['maxValueB'],
"stepsB" : data['stepsB'],
"logB" : data['logB'],
"variableCount" : data['variableCount'],
"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['modelType'] == "stochastic":
job.qsubHandle = pickle.dumps(parametersweep_qsub.stochastic(templateData, cluster_info))
elif data['modelType'] == "deterministic":
job.qsubHandle = pickle.dumps(parametersweep_qsub.deterministic(templateData, cluster_info))
elif data['modelType'] == "spatial":
job.qsubHandle = pickle.dumps(parametersweep_qsub.spatial(templateData, cluster_info))
else:
raise Exception("Trying to runQsub on unsupported modelType {0}".format(data['modelType']))
job.resource = "qsub"
job.put()
except Exception as e:
logging.exception(e)
job.status='Failed'
job.delete(self)
raise
return job
def runMolns(self, data):
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = ParameterSweepJobWrapper()
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.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
job.output_stored = False
# # execute cloud task
try:
with open(os.path.join(path, 'parametersweep_template.py'), 'r') as f:
template = f.read()
templateData = {
"name" : modelDb.name,
"modelType" : modelDb.type,
"species" : modelDb.species,
"parameters" : modelDb.parameters,
"reactions" : modelDb.reactions,
"speciesSelect" : data['speciesSelect'],
"maxTime" : data['maxTime'],
"increment" : data['increment'],
"trajectories" : data['trajectories'],
"seed" : data['seed'],
"parameterA" : data['parameterA'],
"minValueA" : data['minValueA'],
"maxValueA" : data['maxValueA'],
"stepsA" : data['stepsA'],
"logA" : data['logA'],
"parameterB" : data['parameterB'],
"minValueB" : data['minValueB'],
"maxValueB" : data['maxValueB'],
"stepsB" : data['stepsB'],
"logB" : data['logB'],
"variableCount" : data['variableCount'],
"isSpatial" : modelDb.isSpatial,
"isLocal" : False
}
if modelDb.isSpatial:
try:
meshWrapperDb = mesheditor.MeshWrapper.get_by_id(modelDb.spatial["mesh_wrapper_id"])
except Exception as e:
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:
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
program = os.path.join(dataDir, 'program.py')
with open(program, 'w') as f:
jsonString = json.dumps(templateData, indent = 4, sort_keys = True)
# We've got to double escape the strings here cause of how we're substituting the JSON data in a source file
jsonString = jsonString.replace('\\', '\\\\')
f.write(template.replace('___JSON_STRING___', jsonString))
molnsConfigDb = db.GqlQuery("SELECT * FROM MolnsConfigWrapper WHERE user_id = :1", self.user.user_id()).get()
if not molnsConfigDb:
raise Exception("Molns not initialized")
config = molns.MOLNSConfig(config_dir=molnsConfigDb.folder)
result = molns.MOLNSExec.start_job(['EC2_controller', "python {0}".format(program)], config)
job.resource = "molns"
job.molnsPID = result['id']
job.put()
except Exception as e:
job.status='Failed'
job.delete(self)
raise
return job
def runLocal(self, data):
self.user_data.set_selected(0)
logging.error("*"*80)
logging.error("parametersweep.runLocal() modelType={0}".format(data['modelType']))
logging.error("*"*80)
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = ParameterSweepJobWrapper()
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.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
job.output_stored = False
# # execute local task
try:
template_filename = 'parametersweep_template_{0}.py'.format(data['modelType'])
logging.error("parametersweep.runLocal() template_filename={0}".format(template_filename))
logging.error("*"*80)
with open(os.path.join(path,template_filename ), 'r') as f:
template = f.read()
templateData = {
"name" : modelDb.name,
"modelType" : modelDb.type,
"species" : modelDb.species,
"parameters" : modelDb.parameters,
"reactions" : modelDb.reactions,
"speciesSelect" : data['speciesSelect'],
"maxTime" : data['maxTime'],
"increment" : data['increment'],
"trajectories" : data['trajectories'],
"seed" : data['seed'],
"parameterA" : data['parameterA'],
"minValueA" : data['minValueA'],
"maxValueA" : data['maxValueA'],
"stepsA" : data['stepsA'],
"logA" : data['logA'],
"parameterB" : data['parameterB'],
"minValueB" : data['minValueB'],
"maxValueB" : data['maxValueB'],
"stepsB" : data['stepsB'],
"logB" : data['logB'],
"variableCount" : data['variableCount'],
"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
program = os.path.join(dataDir, 'stochss_parametersweep_program.py')
with open(program, 'w') as f:
jsonString = json.dumps(templateData, indent = 4, sort_keys = True)
# We've got to double escape the strings here cause of how we're substituting the JSON data in a source file
jsonString = jsonString.replace('\\', '\\\\')
f.write(template.replace('___JSON_STRING___', jsonString))
#? molnsConfigDb = db.GqlQuery("SELECT * FROM MolnsConfigWrapper WHERE user_id = :1", self.user.user_id()).get()
#? if not molnsConfigDb:
#? raise Exception("Molns not initialized")
#?
#? config = molns.MOLNSConfig(config_dir=molnsConfigDb.folder)
#? result = molns.MOLNSExec.start_job(['EC2_controller', "python {0}".format(program)], config)
cmd = "python {0}".format(program)
logging.info('parametersweep.runLocal(): cmd={0}'.format(cmd))
logging.info('*'*80)
exstring = '{0}/backend/wrapper.py {1}/stdout {1}/stderr {1}/return_code {2}'.format(basedir, dataDir, cmd)
logging.info('parametersweep.runLocal(): exstring={0}'.format(exstring))
logging.info('*'*80)
handle = subprocess.Popen(exstring.split(), preexec_fn=os.setsid)
job.pid = handle.pid
logging.info("parametersweep.runLocal() job started pid={0}".format(job.pid))
logging.info('*'*80)
job.resource = "local"
job.put()
except Exception as e:
logging.exception(e)
job.status='Failed'
job.delete(self)
raise
return job
def runStochKitLocal(self, params):
""" Submit a local StochKit job """
try:
model = StochKitModelWrapper.get_by_id(params["id"])
if not model:
return {"status": False, "msg": "Failed to retrive the model to simulate."}
model = model.model
# Execute as concentration or population?
execType = params["execType"]
if not (execType == "deterministic" or execType == "stochastic" or execType == "sensitivity"):
result = {
"status": False,
"msg": "exec_type must be deterministic, sensitivity, or stochastic. Try refreshing page, or e-mail developers",
}
return result
if model.units.lower() == "concentration" and execType.lower() == "stochastic":
result = {
"status": False,
"msg": "GUI Error: Concentration models cannot be executed Stochastically. Try leaving and returning to this page",
}
return result
executable = execType.lower()
# Assemble the argument list
args = ""
args += " -t {0} ".format(params["time"])
num_output_points = int(float(params["time"]) / float(params["increment"]))
args += " -i {0} ".format(num_output_points)
path = os.path.abspath(os.path.dirname(__file__))
# Algorithm, SSA or Tau-leaping?
if params["execType"] != "deterministic":
executable = "{0}/../../StochKit/{1}".format(path, params["algorithm"])
args += " --realizations {0} ".format(params["realizations"])
args += " --keep-trajectories --seed {0} ".format(params["seed"])
else:
executable = "{0}/../../ode/stochkit_ode.py".format(path)
# Columns need to be labeled for visulatization page to work.
args += " --label"
cmd = executable + " " + args
basedir = path + "/../"
dataDir = tempfile.mkdtemp(dir=basedir + "output")
# Wow, what a hack
if executable == "deterministic" and model.units.lower() == "population":
document = model.serialize()
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")
modelFileName = "{0}/{1}.xml".format(dataDir, model.name)
fmodelHandle = open(modelFileName, "w")
fmodelHandle.write(model.serialize())
fmodelHandle.close()
cmd += " -m {0} --out-dir {1}/result".format(modelFileName, dataDir)
print cmd
# ode = "{0}/../../ode/stochkit_ode.py {1}".format(path, args)
exstring = "{0}/backend/wrapper.sh {1}/stdout {1}/stderr {2}".format(basedir, dataDir, cmd)
handle = subprocess.Popen(exstring.split())
# Create a StochKitJob instance
stochkit_job = StochKitJob(
name=params["jobName"],
final_time=params["time"],
realizations=params["realizations"],
increment=params["increment"],
seed=params["seed"],
exec_type=params["execType"],
units=model.units.lower(),
)
stochkit_job.resource = "Local"
stochkit_job.type = "StochKit2 Ensemble"
stochkit_job.pid = handle.pid
stochkit_job.output_location = dataDir
# stochkit_job.uuid = res['uuid']
stochkit_job.status = "Running"
stochkit_job.stdout = "{0}/stdout".format(dataDir)
stochkit_job.stderr = "{0}/stderr".format(dataDir)
# Create a wrapper to store the Job description in the datastore
stochkit_job_db = StochKitJobWrapper()
stochkit_job_db.user_id = self.user.user_id()
stochkit_job_db.startDate = time.strftime("%Y-%m-%d-%H-%M-%S")
stochkit_job_db.name = stochkit_job.name
stochkit_job_db.stochkit_job = stochkit_job
stochkit_job_db.stdout = stochkit_job.stdout
stochkit_job_db.stderr = stochkit_job.stderr
stochkit_job_db.put()
result = {"status": True, "msg": "Job submitted sucessfully"}
except None: # Exception,e:
raise e
# result = {'status':False,'msg':'Local execution failed: '+str(e)}
return result
def runCloud(self, params):
try:
model = StochKitModelWrapper.get_by_id(params["id"]).model
if not model:
return {"status": False, "msg": "Failed to retrive the model to simulate."}
db_credentials = self.user_data.getCredentials()
# Set the environmental variables
os.environ["AWS_ACCESS_KEY_ID"] = db_credentials["EC2_ACCESS_KEY"]
os.environ["AWS_SECRET_ACCESS_KEY"] = db_credentials["EC2_SECRET_KEY"]
if os.environ["AWS_ACCESS_KEY_ID"] == "":
result = {"status": False, "msg": "Access Key not set. Check : Settings > Cloud Computing"}
return result
if os.environ["AWS_SECRET_ACCESS_KEY"] == "":
result = {"status": False, "msg": "Secret Key not set. Check : Settings > Cloud Computing"}
return result
# the parameter dictionary to be passed to the backend
param = {}
# Execute as concentration or population?
exec_type = params["execType"]
if not (exec_type == "deterministic" or exec_type == "stochastic"):
result = {
"status": False,
"msg": "exec_type must be concentration or population. Try refreshing page, or e-mail developers",
}
return result
if model.units.lower() == "concentration" and exec_type.lower() == "stochastic":
result = {
"status": False,
"msg": "GUI Error: Concentration models cannot be executed Stochastically. Try leaving and returning to this page",
}
return result
executable = exec_type.lower()
document = model.serialize()
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"]
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"
print executable
# 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
# Call backendservices and execute StochKit
service = backendservices()
celery_task_id, taskid = service.executeTask(params)
if celery_task_id == None:
result = {"status": False, "msg": "Cloud execution failed. "}
return result
# Create a StochKitJob instance
stochkit_job = StochKitJob(
name=ensemblename,
final_time=stime,
realizations=realizations,
increment=increment,
seed=seed,
exec_type=exec_type,
units=model.units.lower(),
)
stochkit_job.resource = "Cloud"
stochkit_job.type = "StochKit2 Ensemble"
# The jobs pid is the DB/S3 ID.
stochkit_job.pid = taskid
# The celery_pid is the Celery Task ID.
stochkit_job.celery_pid = celery_task_id
stochkit_job.status = "Running"
stochkit_job.output_location = None
# stochkit_job.output_location = 'output/%s' % taskid
# stochkit_job.stdout = stochkit_job.output_location + '/stdout.log'
# stochkit_job.stderr = stochkit_job.output_location + '/stderr.log'
# Create a wrapper to store the Job description in the datastore
stochkit_job_db = StochKitJobWrapper()
stochkit_job_db.startDate = time.strftime("%Y-%m-%d-%H-%M-%S")
stochkit_job_db.user_id = self.user.user_id()
stochkit_job_db.name = stochkit_job.name
stochkit_job_db.stochkit_job = stochkit_job
stochkit_job_db.put()
result = {"status": True, "msg": "Job submitted sucessfully."}
except Exception, e:
result = {"status": False, "msg": "Cloud execution failed: " + str(e)}
def runLocal(self, data):
'''
'''
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
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 = modelDb.name
job.resource = "local"
job.status = "Running"
# Convert model and write to file
model_file_file = tempfile.mktemp(prefix = 'modelFile', suffix = '.R', dir = dataDir)
mff = open(model_file_file, 'w')
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
mff.write(stringModel)
mff.close()
data["model_file_file"] = model_file_file
model_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
mdf = open(model_data_file, 'w')
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
mdf.write(self.addWeightColumnIfNecessary(jFileData["data"]))
mdf.close()
data["model_data_file"] = model_data_file
model_initial_data_file = tempfile.mktemp(prefix = 'dataFile', suffix = '.txt', dir = dataDir)
midf = open(model_initial_data_file, 'w')
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
midf.write(self.addWeightColumnIfNecessary(iFileData["data"]))
midf.close()
data["model_initial_data_file"] = model_initial_data_file
data["exec"] = "\"bash&\""
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
try:
import multiprocessing
data["cores"] = multiprocessing.cpu_count()
except:
data["cores"] = 1
data["options"] = ""
data["path"] = path
cmd = "Rscript --vanilla {path}/../../stochoptim/exec/mcem2.r --model {model_file_file} --data {model_initial_data_file} --finalData {model_data_file} --steps {steps} --seed {seed} --cores {cores} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
exstring = '{0}/backend/wrapper.py {1}/stdout {1}/stderr {1}/return_code {2}'.format(basedir, dataDir, cmd)
handle = subprocess.Popen(exstring, shell=True, preexec_fn=os.setsid)
job.pid = handle.pid
job.put()
return job
def runStochKitLocal(self, params):
""" Submit a local StochKit job """
modelDb = StochKitModelWrapper.get_by_id(params["id"])
if not modelDb:
return {
'status': False,
'msg': 'Failed to retrive the model to simulate.'
}
model = modelDb.createStochKitModel()
# Execute as concentration or population?
execType = params['execType'].lower()
if execType not in ["deterministic", "stochastic", "sensitivity"]:
raise Exception(
'exec_type must be deterministic, sensitivity, or stochastic. Found "{0}"'
.format(execType))
if model.units.lower() == 'concentration' and execType.lower(
) == 'stochastic':
raise Exception(
'Concentration models cannot be executed stochastically')
# Assemble the argument list
args = ''
args += ' -t {0} '.format(params['time'])
num_output_points = int(
float(params['time']) / float(params['increment']))
args += ' -i {0} '.format(num_output_points)
path = os.path.abspath(os.path.dirname(__file__))
# Algorithm, SSA or Tau-leaping?
if params['execType'] != 'deterministic':
executable = "{0}/../../StochKit/{1}".format(
path, params['algorithm'])
args += ' --realizations {0} '.format(params['realizations'])
args += ' --keep-trajectories '
if int(params['seed']) < 0:
random.seed()
params['seed'] = random.randint(0, 2147483647)
args += '--seed {0} '.format(params['seed'])
else:
executable = "{0}/../../ode/stochkit_ode.py".format(path)
# Columns need to be labeled for visulatization page to work.
args += ' --label'
cmd = executable + ' ' + args
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir=basedir + 'output')
# Wow, what a hack
if params['execType'] == 'deterministic' and model.units.lower(
) == 'population':
document = model.serialize()
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')
modelFileName = '{0}/{1}.xml'.format(dataDir, model.name)
fmodelHandle = open(modelFileName, 'w')
fmodelHandle.write(model.serialize())
fmodelHandle.close()
cmd += ' -m {0} --out-dir {1}/result'.format(modelFileName, dataDir)
if params['execType'] == 'deterministic':
cmd += ' -r {0} -a {1} --mxsteps {2}'.format(
params['rTol'], params['aTol'], params['mxSteps'])
logging.info("cmd =\n{}".format(cmd))
logging.debug('simulation.runLocal(): cmd={0}'.format(cmd))
logging.debug('*' * 80)
logging.debug('*' * 80)
#ode = "{0}/../../ode/stochkit_ode.py {1}".format(path, args)
exstring = '{0}/backend/wrapper.py {1}/stdout {1}/stderr {1}/return_code {2}'.format(
basedir, dataDir, cmd)
logging.debug('simulation.runLocal(): exstring={0}'.format(exstring))
logging.debug('*' * 80)
logging.debug('*' * 80)
handle = subprocess.Popen(exstring.split(), preexec_fn=os.setsid)
# Create a wrapper to store the Job description in the datastore
job = StochKitJobWrapper()
job.resource = 'local'
# 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 = handle.pid
# 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.outData = dataDir
job.stdout = '{0}/stdout'.format(dataDir)
job.stderr = '{0}/stderr'.format(dataDir)
job.status = 'Running'
job.put()
return job
def runCloud(self, data):
modelDb = StochKitModelWrapper.get_by_id(data["modelID"])
berniemodel = StochOptimModel()
success, msgs = berniemodel.fromStochKitModel(modelDb.createStochKitModel())
if not success:
raise Exception(msgs)
path = os.path.abspath(os.path.dirname(__file__))
basedir = path + '/../'
dataDir = tempfile.mkdtemp(dir = basedir + 'output')
job = StochOptimJobWrapper()
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.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
data["exec"] = "'bash'"
data["steps"] = ("C" if data["crossEntropyStep"] else "") + ("E" if data["emStep"] else "") + ("U" if data["uncertaintyStep"] else "")
# data["cores"] = 4
data["options"] = ""
cmd = "exec/mcem2.r --steps {steps} --seed {seed} --K.ce {Kce} --K.em {Kem} --K.lik {Klik} --K.cov {Kcov} --rho {rho} --perturb {perturb} --alpha {alpha} --beta {beta} --gamma {gamma} --k {k} --pcutoff {pcutoff} --qcutoff {qcutoff} --numIter {numIter} --numConverge {numConverge} --command {exec}".format(**data)
# cmd = "exec/mcem2.r --K.ce 1000 --K.em 100 --rho .01 --pcutoff .05"
stringModel, nameToIndex = berniemodel.serialize(data["activate"], True)
job.nameToIndex = json.dumps(nameToIndex)
jFileData = fileserver.FileManager.getFile(self, data["trajectoriesID"], noFile = False)
iFileData = fileserver.FileManager.getFile(self, data["initialDataID"], noFile = False)
job.put()
cloud_params = {
"job_id" : job.key().id(),
"job_type": "mcem2",
# "cores": data["cores"],
"paramstring": cmd,
"model_file": stringModel,
"model_data": {
"content": self.addWeightColumnIfNecessary(iFileData["data"]),
"extension": "txt"
},
"final_data": {
"content": self.addWeightColumnIfNecessary(jFileData["data"]),
"extension": "txt"
},
"key_prefix": self.user.user_id(),
"credentials": self.user_data.getCredentials(),
"bucketname": self.user_data.getBucketName()
}
# # execute cloud task
try:
service = backend.backendservice.backendservices(self.user_data)
cloud_result = service.submit_cloud_task(params=cloud_params)
if not cloud_result["success"]:
raise Exception(cloud_result["reason"])
job.cloudDatabaseID = cloud_result["db_id"]
job.resource = cloud_result['resource']
job.celeryPID = cloud_result["celery_pid"]
# job.pollProcessPID = int(cloud_result["poll_process_pid"])
# job.pid = handle.pid
job.put()
except Exception as e:
job.status='Failed'
job.delete(self)
raise
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'],
"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):
logging.error("*" * 80)
logging.error("simulate.runQsub() modelType={0}".format(
data['execType']))
logging.error("*" * 80)
modelDb = StochKitModelWrapper.get_by_id(int(data["id"]))
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.modelName = modelDb.name
job.outData = dataDir
job.status = "Pending"
job.output_stored = "False"
job.is_spatial = True
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.resource = "qsub"
job.put()
except Exception as e:
logging.exception(e)
job.status = 'Failed'
#job.delete(self)
raise
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