def run(self):
np = 2
try:
inform("Running file %s with %s" %
(trim_path(self.modelpath), JNeuroMLNetPyNEEngine.name),
indent=1)
from omv.engines.jneuroml import JNeuroMLEngine
jnml = JNeuroMLEngine.get_executable()
self.stdout = check_output([
jnml, self.modelpath, '-netpyne', '-nogui', '-run', '-np',
'%s' % np
],
cwd=os.path.dirname(self.modelpath),
env=JNeuroMLEngine.get_environment())
inform("Success with running ",
JNeuroMLNetPyNEEngine.name,
indent=1)
self.returncode = 0
except sp.CalledProcessError as err:
inform("Error with ", JNeuroMLNetPyNEEngine.name, indent=1)
self.returncode = err.returncode
self.stdout = err.output
raise EngineExecutionError
def run(self):
try:
path_s = resolve_paths(self.modelpath)
from omv.engines.jneuroml import JNeuroMLEngine
jnml = JNeuroMLEngine.get_executable()
cmds = [jnml, '-validatev1']
for p in path_s:
cmds.append(p)
inform("Running with %s, using %s..." %
(JNeuroMLValidateV1Engine.name, cmds),
indent=1)
self.stdout = sp.check_output(cmds,
cwd=os.path.dirname(self.modelpath),
env=JNeuroMLEngine.get_environment())
inform("Success with running ",
JNeuroMLValidateV1Engine.name,
indent=1,
verbosity=1)
self.returncode = 0
except sp.CalledProcessError as err:
self.returncode = err.returncode
self.stdout = err.output
raise EngineExecutionError
def run(self):
try:
inform("Running file %s with %s" % (trim_path(self.modelpath), JNeuroMLBrianEngine.name), indent=1)
from omv.engines.jneuroml import JNeuroMLEngine
jnml = JNeuroMLEngine.get_executable()
self.stdout = check_output([jnml, self.modelpath, '-brian'], cwd=os.path.dirname(self.modelpath),env=JNeuroMLEngine.get_environment())
self.stdout += check_output(['python', self.modelpath.replace('.xml', '_brian.py'), '-nogui'], cwd=os.path.dirname(self.modelpath))
inform("Success with running ", JNeuroMLBrianEngine.name, indent=1)
self.returncode = 0
except sp.CalledProcessError as err:
inform("Error with ", JNeuroMLBrianEngine.name, indent=1)
self.returncode = err.returncode
self.stdout = err.output
raise EngineExecutionError
def run_using_jnmlnrn_env(engine, modelpath, args):
try:
env = JNeuroMLNRNEngine.get_jnmlnrnenv()
inform("Running file %s with %s, env: %s" %
(trim_path(modelpath), engine, env),
indent=1)
from omv.engines.jneuroml import JNeuroMLEngine
jnml = JNeuroMLEngine.get_executable()
cmds = [jnml, modelpath]
cmds.extend(args)
stdout = check_output(cmds,
cwd=os.path.dirname(modelpath),
env=env)
inform("Success with running ", engine, indent=1)
returncode = 0
return stdout, returncode
except sp.CalledProcessError as err:
inform("Error with ", engine, indent=1)
returncode = err.returncode
stdout = err.output
return stdout, returncode