def before_run(self, run_namespace=None, level=0):
# execute code to initalize the spike queue
if self._initialise_queue_codeobj is None:
self._initialise_queue_codeobj = create_runner_codeobj(
self,
'', # no code,
'synapses_initialise_queue',
name=self.name + '_initialise_queue',
check_units=False,
additional_variables=self.variables,
run_namespace=run_namespace,
level=level + 1)
self._initialise_queue_codeobj()
CodeRunner.before_run(self, run_namespace, level=level + 1)
# we insert rather than replace because CodeRunner puts a CodeObject in updaters already
if self._pushspikes_codeobj is None:
self._pushspikes_codeobj = create_runner_codeobj(
self,
'', # no code
'synapses_push_spikes',
name=self.name + '_push_spikes',
check_units=False,
additional_variables=self.variables,
run_namespace=run_namespace,
level=level + 1)
self._code_objects.insert(0, weakref.proxy(self._pushspikes_codeobj))
def before_run(self, run_namespace):
# execute code to initalize the data structures
if self._prepare_codeobj is None:
self._prepare_codeobj = create_runner_codeobj(self.group,
'', # no code,
'spatialneuron_prepare',
name=self.name+'_spatialneuron_prepare',
check_units=False,
additional_variables=self.variables,
run_namespace=run_namespace)
self._prepare_codeobj()
# Raise a warning if the slow pure numpy version is used
# For simplicity, we check which CodeObject class the _prepare_codeobj
# is using, this will be the same as the main state updater
from brian2.codegen.runtime.numpy_rt.numpy_rt import NumpyCodeObject
if isinstance(self._prepare_codeobj, NumpyCodeObject):
# If numpy is used, raise a warning if scipy is not present
try:
import scipy
except ImportError:
logger.info(('SpatialNeuron will use numpy to do the numerical '
'integration -- this will be very slow. Either '
'switch to a different code generation target '
'(e.g. weave or cython) or install scipy.'),
once=True)
CodeRunner.before_run(self, run_namespace)
def before_run(self, run_namespace=None, level=0):
# execute code to initalize the data structures
if self._prepare_codeobj is None:
self._prepare_codeobj = create_runner_codeobj(
self.group,
'', # no code,
'spatialneuron_prepare',
name=self.name + '_spatialneuron_prepare',
check_units=False,
additional_variables=self.variables,
run_namespace=run_namespace,
level=level + 1)
self._prepare_codeobj()
# Raise a warning if the slow pure numpy version is used
# For simplicity, we check which CodeObject class the _prepare_codeobj
# is using, this will be the same as the main state updater
from brian2.codegen.runtime.numpy_rt.numpy_rt import NumpyCodeObject
if isinstance(self._prepare_codeobj, NumpyCodeObject):
# If numpy is used, raise a warning if scipy is not present
try:
import scipy
except ImportError:
logger.warn(
('SpatialNeuron will use numpy to do the numerical '
'integration -- this will be very slow. Either '
'switch to a different code generation target '
'(e.g. weave or cython) or install scipy.'),
once=True)
CodeRunner.before_run(self, run_namespace, level=level + 1)
def before_run(self, run_namespace=None, level=0):
# execute code to initalize the spike queue
if self._initialise_queue_codeobj is None:
self._initialise_queue_codeobj = create_runner_codeobj(self,
'', # no code,
'synapses_initialise_queue',
name=self.name+'_initialise_queue',
check_units=False,
additional_variables=self.variables,
run_namespace=run_namespace,
level=level+1)
self._initialise_queue_codeobj()
CodeRunner.before_run(self, run_namespace, level=level+1)
# we insert rather than replace because CodeRunner puts a CodeObject in updaters already
if self._pushspikes_codeobj is None:
self._pushspikes_codeobj = create_runner_codeobj(self,
'', # no code
'synapses_push_spikes',
name=self.name+'_push_spikes',
check_units=False,
additional_variables=self.variables,
run_namespace=run_namespace,
level=level+1)
self._code_objects.insert(0, weakref.proxy(self._pushspikes_codeobj))
def before_run(self, run_namespace=None, level=0):
if self._group.dt != self._stored_dt:
raise NotImplementedError('The dt used for simulating %s changed '
'after the PoissonInput source was '
'created.' % self.group.name)
CodeRunner.before_run(self, run_namespace=run_namespace,
level=level+1)
def before_run(self, run_namespace):
if self._group.dt_ != self._stored_dt:
raise NotImplementedError(
f"The dt used for simulating {self.group.name} "
f"changed after the PoissonInput source was "
f"created.")
CodeRunner.before_run(self, run_namespace=run_namespace)
def before_run(self, run_namespace=None, level=0):
# execute code to initalize the data structures
if self._prepare_codeobj is None:
self._prepare_codeobj = create_runner_codeobj(self.group,
'', # no code,
'spatialneuron_prepare',
name=self.name+'_spatialneuron_prepare',
check_units=False,
additional_variables=self.variables,
run_namespace=run_namespace,
level=level+1)
self._prepare_codeobj()
CodeRunner.before_run(self, run_namespace, level=level + 1)
def before_run(self, run_namespace=None, level=0):
if not self._isprepared: # this is done only once even if there are multiple runs
self.prepare()
self._isprepared = True
CodeRunner.before_run(self, run_namespace, level=level + 1)
def before_run(self, run_namespace=None, level=0):
if not self._isprepared: # this is done only once even if there are multiple runs
self.prepare()
self._isprepared = True
CodeRunner.before_run(self, run_namespace, level=level + 1)
