def test_ecl_defaults_methods(self):
try:
import ert.ecl.ecl_local as ecl_local
self.assertEqual(EclDefault.ecl_cmd(), ecl_local.ecl_cmd)
self.assertEqual(EclDefault.ecl_version(), ecl_local.ecl_version)
self.assertEqual(EclDefault.lsf_resource_request(), ecl_local.lsf_resource_request)
self.assertEqual(EclDefault.driver_type(), ecl_local.driver_type)
self.assertEqual(EclDefault.driver_options(), ecl_local.driver_options)
except ImportError:
self.fail("Unable to import ecl_local.py")
def test_ecl_defaults_methods(self):
if (has_ecl_local()):
try:
import ert.ecl.ecl_local as ecl_local
if hasattr(ecl_local, 'ecl_cmd'):
self.assertEqual(EclDefault.ecl_cmd(), ecl_local.ecl_cmd)
else:
with self.assertRaises(NotImplementedError):
EclDefault.ecl_cmd()
if hasattr(ecl_local, 'ecl_version'):
self.assertEqual(EclDefault.ecl_version(),
ecl_local.ecl_version)
else:
with self.assertRaises(NotImplementedError):
EclDefault.ecl_version()
if hasattr(ecl_local, 'lsf_resource_request'):
self.assertEqual(EclDefault.lsf_resource_request(),
ecl_local.lsf_resource_request)
else:
with self.assertRaises(NotImplementedError):
EclDefault.lsf_resource_request()
if hasattr(ecl_local, 'driver_type'):
self.assertEqual(EclDefault.driver_type(),
ecl_local.driver_type)
else:
with self.assertRaises(NotImplementedError):
EclDefault.driver_type()
if hasattr(ecl_local, 'driver_options'):
self.assertEqual(EclDefault.driver_options(),
ecl_local.driver_options)
else:
with self.assertRaises(NotImplementedError):
EclDefault.driver_options()
except ImportError:
self.fail("Unable to import ecl_local.py")
else:
with self.assertRaises(NotImplementedError):
EclDefault.ecl_cmd()
EclDefault.ecl_version()
EclDefault.lsf_resource_request()
EclDefault.driver_type()
EclDefault.driver_options()
def run(self,
ecl_cmd=None,
ecl_version=None,
driver=None,
driver_type=None,
driver_options=None,
blocking=False):
"""
Will start an ECLIPSE simulation of the current case.
The method has a long and nasty argument list, but all
arguments have sensible defaults, and you probably do not need
to enter any at all. The arguments are as follows:
ecl_cmd: The command used to run ECLIPSE. This will
typically be a script of some kind. The command will be
called with three commandline arguments: version datafile
num_cpu
ecl_version: The eclipse version you want to use, this
should be a string of the type "2010.2".
driver: This should be an instance of Driver() from
ert.job_queue.driver. If driver is None the method will
create a new driver instance.
driver_type: If the driver is none the method will create a
new driver instance, it will create a driver of this type
(i.e. LOCAL, LSF or RSH).
driver_options: When creating a new driver, these options
will be used.
blocking: If blocking is True the method will not return
before the simulation is complete, otherwise the method
will return immediately. If blocking is False the ECLIPSE
simulation will continue even if the python script
exits.
Observe that there are some dependencies between the arguments:
* If both driver and driver_type are present the existing
driver instance will be used, and the driver_type argument
will be ignored.
* The driver_options argument will only be used when
creating a new driver instance, and will not be used to
modify an existing driver instance.
This method will immediately start/submit an ECLIPSE
simulation of the current case. If you have many simulations
you might want use an EclQueue() and the submit() method instead, in
particular if you are running locally.
"""
import ert.job_queue.driver as queue_driver
num_cpu = EclUtil.get_num_cpu(self.datafile)
argv = [ecl_version, self.datafile, num_cpu]
if ecl_cmd is None:
ecl_cmd = EclDefault.ecl_cmd()
if driver_type is None:
driver_type = EclDefault.driver_type()
if ecl_version is None:
ecl_version = EclDefault.ecl_version()
if driver is None:
if driver_options is None:
driver_options = EclDefault.driver_options()[driver_type]
driver = queue_driver.Driver(driver_type,
max_running=0,
options=driver_options)
job = driver.submit(self.base,
ecl_cmd,
self.path,
argv,
blocking=blocking)
return job
def run( self ,
ecl_cmd = None,
ecl_version = None,
driver = None ,
driver_type = None,
driver_options = None,
blocking = False ):
"""
Will start an ECLIPSE simulation of the current case.
The method has a long and nasty argument list, but all
arguments have sensible defaults, and you probably do not need
to enter any at all. The arguments are as follows:
ecl_cmd: The command used to run ECLIPSE. This will
typically be a script of some kind. The command will be
called with three commandline arguments: version datafile
num_cpu
ecl_version: The eclipse version you want to use, this
should be a string of the type "2010.2".
driver: This should be an instance of Driver() from
ert.job_queue.driver. If driver is None the method will
create a new driver instance.
driver_type: If the driver is none the method will create a
new driver instance, it will create a driver of this type
(i.e. LOCAL, LSF or RSH).
driver_options: When creating a new driver, these options
will be used.
blocking: If blocking is True the method will not return
before the simulation is complete, otherwise the method
will return immediately. If blocking is False the ECLIPSE
simulation will continue even if the python script
exits.
Observe that there are some dependencies between the arguments:
* If both driver and driver_type are present the existing
driver instance will be used, and the driver_type argument
will be ignored.
* The driver_options argument will only be used when
creating a new driver instance, and will not be used to
modify an existing driver instance.
This method will immediately start/submit an ECLIPSE
simulation of the current case. If you have many simulations
you might want use an EclQueue() and the submit() method instead, in
particular if you are running locally.
"""
import ert.job_queue.driver as queue_driver
num_cpu = EclUtil.get_num_cpu( self.datafile )
argv = [ecl_version , self.datafile , num_cpu]
if ecl_cmd is None:
ecl_cmd = EclDefault.ecl_cmd()
if driver_type is None:
driver_type = EclDefault.driver_type()
if ecl_version is None:
ecl_version = EclDefault.ecl_version()
if driver is None:
if driver_options is None:
driver_options = EclDefault.driver_options()[ driver_type ]
driver = queue_driver.Driver( driver_type , max_running = 0 , options = driver_options )
job = driver.submit( self.base , ecl_cmd , self.path , argv , blocking = blocking)
return job
def __init__(self,
driver=None,
driver_type=None,
driver_options=None,
ecl_version=None,
ecl_cmd=None,
max_running=0,
size=0):
"""
Create a new queue instance to manage ECLIPSE simulations.
The constructor will create a new EclQueue instance which can
be used to manage ECLIPSE simulations. All the ECLIPSE
simulations managed by this queue instance will be 'of the
same type', i.e. they will run the same ECLIPSE version using
the same command to run ECLIPSE.
The queue starts running (i.e. managing jobs) as soon as it is
created. Subsequently the user must add jobs to run using the
submit() method, or alternatively the submit() method of an
EclCase instance.
The queue will run in a separate thread, and there is nothing
preventing your script from finishing (i.e. exit) even though
the queue thread is still running; in that case the jobs which
are still waiting in the queue will not be started[1]. To
protect against this premature exit you must use on of the
methods:
- queue.block_waiting()
- queue.block()
- while queue.running:
.....
All simulations which have been started by the queue instance
will continue running even if the queue itself goes out of
scope and the script exits.
There are many arguments to the constructor, all of them are
optional with sensible default values. There are essentially
three groups of arguments:
Driver related arguments
------------------------
driver: This should be an instance of Driver (or one of the
descendants LSFDriver, LocalDriver, or ...) from the
ert.job_queue.driver module. If the driver is None the
queue will instanstiate a driver itself.
driver_type: If the driver is None the queue needs to
instantiate a private driver. It will then instantiate a
driver of the type given by driver_type.
driver_options: If the queue needs to instantiate a private
driver it will pass the options given by the
driver_options argument to the driver constructor.
There is some dependance between the driver related arguments;
if a @driver argument is passed the @driver_type and
@driver_options arguments are not considered.
ECLIPSE related arguments
-------------------------
ecl_version: The ECLIPSE version used when simulating. This
should be a string of the type "2009.1".
ecl_cmd: The path to the executable used to invoke
ECLIPSE. The executable will be invoked with commandline
arguments:
version data_file num_cpu
And this executable is responsible for then starting the
real ECLIPSE binary.
Other arguments
---------------
max_running: The maximum number of jobs the queue can run
concurrently. The default value max_running=0 means that
the queue can start an unlimited number of jobs; in the
case of e.g. LSF the default value can be sensible,
otherwise you should probably set a value.
size: This is the total number of simulations we want to run
with the queue; this is further documented in the
ert.job_queue.queue.JobQueue class.
Use example
-----------
import ert.ecl.ecl as ecl
import ert.job_queue.driver as driver
queue = ecl.EclQueue( driver_type = driver.LOCAL , max_running = 4 , size = 100)
data_file_fmt = "/path/to/ECLIPSE/sim%d/ECL.DATA"
for i in range(100):
queue.submit( data_file_fmt % i )
queue.block()
[1]: It should be possible with a fork based solution to let
the queue stay alive and continue managing jobs even
after the main thread has exited - not yet :-(
"""
if ecl_cmd is None:
ecl_cmd = EclDefault.ecl_cmd()
if driver_type is None:
driver_type = EclDefault.driver_type()
if ecl_version is None:
ecl_version = EclDefault.ecl_version()
self.ecl_version = ecl_version
self.ecl_cmd = ecl_cmd
if driver is None:
if driver_options is None:
driver_options = EclDefault.driver_options()[driver_type]
driver = Driver(driver_type,
max_running=max_running,
options=driver_options)
super(EclQueue, self).__init__(driver, size=size)
def test_ecl_defaults_methods(self):
if (has_ecl_local()):
try:
import ert.ecl.ecl_local as ecl_local
if hasattr(ecl_local, 'ecl_cmd'):
self.assertEqual(EclDefault.ecl_cmd(), ecl_local.ecl_cmd)
else:
with self.assertRaises(NotImplementedError):
EclDefault.ecl_cmd()
if hasattr(ecl_local, 'ecl_version'):
self.assertEqual(EclDefault.ecl_version(), ecl_local.ecl_version)
else:
with self.assertRaises(NotImplementedError):
EclDefault.ecl_version()
if hasattr(ecl_local, 'lsf_resource_request'):
self.assertEqual(EclDefault.lsf_resource_request(), ecl_local.lsf_resource_request)
else:
with self.assertRaises(NotImplementedError):
EclDefault.lsf_resource_request()
if hasattr(ecl_local, 'driver_type'):
self.assertEqual(EclDefault.driver_type(), ecl_local.driver_type)
else:
with self.assertRaises(NotImplementedError):
EclDefault.driver_type()
if hasattr(ecl_local, 'driver_options'):
self.assertEqual(EclDefault.driver_options(), ecl_local.driver_options)
else:
with self.assertRaises(NotImplementedError):
EclDefault.driver_options()
except ImportError:
self.fail("Unable to import ecl_local.py")
else:
with self.assertRaises(NotImplementedError):
EclDefault.ecl_cmd()
EclDefault.ecl_version()
EclDefault.lsf_resource_request()
EclDefault.driver_type()
EclDefault.driver_options()
def __init__(self,
driver=None,
driver_type=None,
driver_options=None,
ecl_version=None,
ecl_cmd=None,
max_running=0,
size=0):
"""
Create a new queue instance to manage ECLIPSE simulations.
The constructor will create a new EclQueue instance which can
be used to manage ECLIPSE simulations. All the ECLIPSE
simulations managed by this queue instance will be 'of the
same type', i.e. they will run the same ECLIPSE version using
the same command to run ECLIPSE.
The queue starts running (i.e. managing jobs) as soon as it is
created. Subsequently the user must add jobs to run using the
submit() method, or alternatively the submit() method of an
EclCase instance.
The queue will run in a separate thread, and there is nothing
preventing your script from finishing (i.e. exit) even though
the queue thread is still running; in that case the jobs which
are still waiting in the queue will not be started[1]. To
protect against this premature exit you must use on of the
methods:
- queue.block_waiting()
- queue.block()
- while queue.running:
.....
All simulations which have been started by the queue instance
will continue running even if the queue itself goes out of
scope and the script exits.
There are many arguments to the constructor, all of them are
optional with sensible default values. There are essentially
three groups of arguments:
Driver related arguments
------------------------
driver: This should be an instance of Driver (or one of the
descendants LSFDriver, LocalDriver, or ...) from the
ert.job_queue.driver module. If the driver is None the
queue will instanstiate a driver itself.
driver_type: If the driver is None the queue needs to
instantiate a private driver. It will then instantiate a
driver of the type given by driver_type.
driver_options: If the queue needs to instantiate a private
driver it will pass the options given by the
driver_options argument to the driver constructor.
There is some dependance between the driver related arguments;
if a @driver argument is passed the @driver_type and
@driver_options arguments are not considered.
ECLIPSE related arguments
-------------------------
ecl_version: The ECLIPSE version used when simulating. This
should be a string of the type "2009.1".
ecl_cmd: The path to the executable used to invoke
ECLIPSE. The executable will be invoked with commandline
arguments:
version data_file num_cpu
And this executable is responsible for then starting the
real ECLIPSE binary.
Other arguments
---------------
max_running: The maximum number of jobs the queue can run
concurrently. The default value max_running=0 means that
the queue can start an unlimited number of jobs; in the
case of e.g. LSF the default value can be sensible,
otherwise you should probably set a value.
size: This is the total number of simulations we want to run
with the queue; this is further documented in the
ert.job_queue.queue.JobQueue class.
Use example
-----------
import ert.ecl.ecl as ecl
import ert.job_queue.driver as driver
queue = ecl.EclQueue( driver_type = driver.LOCAL , max_running = 4 , size = 100)
data_file_fmt = "/path/to/ECLIPSE/sim%d/ECL.DATA"
for i in range(100):
queue.submit( data_file_fmt % i )
queue.block()
[1]: It should be possible with a fork based solution to let
the queue stay alive and continue managing jobs even
after the main thread has exited - not yet :-(
"""
if ecl_cmd is None:
ecl_cmd = EclDefault.ecl_cmd()
if driver_type is None:
driver_type = EclDefault.driver_type()
if ecl_version is None:
ecl_version = EclDefault.ecl_version()
self.ecl_version = ecl_version
self.ecl_cmd = ecl_cmd
if driver is None:
if driver_options is None:
driver_options = EclDefault.driver_options()[driver_type]
driver = Driver(driver_type, max_running=max_running, options=driver_options)
super(EclQueue, self).__init__(driver, size=size)