def _set_cython_attribute(self, attribute, value):
"""
Sets the value of the given attribute for all neurons in the population,
as a Numpy array having the same geometry as the population if it is local.
:param attribute: should be a string representing the variables's name.
:param value: a value or Numpy array of the right size.
"""
try:
ctype = self._get_attribute_cpp_type(attribute)
if attribute in self.neuron_type.description['local']:
if isinstance(value, np.ndarray):
self.cyInstance.set_local_attribute_all(
attribute, value.reshape(self.size), ctype)
elif isinstance(value, list):
self.cyInstance.set_local_attribute_all(
attribute,
np.array(value).reshape(self.size), ctype)
else:
self.cyInstance.set_local_attribute_all(
attribute, value * np.ones(self.size), ctype)
else:
self.cyInstance.set_global_attribute(attribute, value, ctype)
except Exception as e:
Global._debug(e)
err_msg = """Population.set(): either the variable '%(attr)s' does not exist in the population '%(pop)s', or the provided array does not have the right size."""
Global._error(err_msg % {'attr': attribute, 'pop': self.name})
def _set_cython_attribute(self, attribute, value):
"""
Sets the value of the given attribute for all neurons in the population,
as a NumPy array having the same geometry as the population if it is local.
*Parameter:*
* **attribute**: should be a string representing the variables's name.
* **value**: a value or Numpy array of the right size.
"""
try:
if attribute in self.neuron_type.description['local']:
if isinstance(value, np.ndarray):
getattr(self.cyInstance, 'set_'+attribute)(value.reshape(self.size))
elif isinstance(value, list):
getattr(self.cyInstance, 'set_'+attribute)(np.array(value).reshape(self.size))
else:
getattr(self.cyInstance, 'set_'+attribute)(value * np.ones( self.size ))
else:
getattr(self.cyInstance, 'set_'+attribute)(value)
except Exception as e:
Global._debug(e)
err_msg = """Population.set(): either the variable '%(attr)s' does not exist in the population '%(pop)s', or the provided array does not have the right size."""
Global._error(err_msg % { 'attr': attribute, 'pop': self.name } )
def add_network(self, py_instance):
"""
Adds an empty structure for a new network and returns the new network ID.
"""
new_dict = {
'populations': [],
'projections': [],
'monitors': [],
'extensions': [],
'instance': None,
'compiled': False,
'directory': None
}
found = -1
# scan for slots which were freed before
for i, entry in enumerate(self._network):
if entry == None and self._py_instances[i] == None:
found = i
break
# dependent on the scan append at the end
# or fill free slot
if found == -1:
new_id = len(self._network)
self._network.append(new_dict)
self._py_instances.append(py_instance)
else:
new_id = found
self._network[new_id] = new_dict
self._py_instances[new_id] = py_instance
Global._debug("Added network", new_id)
return new_id
def _set_cython_attribute(self, attribute, value):
"""
Sets the value of the given attribute for all neurons in the population,
as a NumPy array having the same geometry as the population if it is local.
Parameter:
* *attribute*: should be a string representing the variables's name.
* *value*: a value or Numpy array of the right size.
"""
try:
if attribute in self.neuron_type.description['local']:
if isinstance(value, np.ndarray):
getattr(self.cyInstance,
'set_' + attribute)(value.reshape(self.size))
elif isinstance(value, list):
getattr(self.cyInstance, 'set_' + attribute)(
np.array(value).reshape(self.size))
else:
getattr(self.cyInstance,
'set_' + attribute)(value * np.ones(self.size))
else:
getattr(self.cyInstance, 'set_' + attribute)(value)
except Exception as e:
Global._debug(e)
err_msg = """either the variable '%(attr)s' does not exist in the population '%(pop)s', or the provided array does not have the right size."""
Global._error(err_msg % {'attr': attribute, 'pop': self.name})
def _remove_network(self, py_instance):
"""
Remove the given network from the list of compilable/instantiable networks.
It is important to invalidate only the slot. If del is called on the dictionary
entry then this will lead to a removal of the space and therefore all succesequent
networks would be assigned wrong.
This function will be called from the Network.__del__() method, after destruction
of the attached objects.
"""
Global._debug("Remove network", py_instance)
net_id = -1
for net_id, inst in enumerate(self._py_instances):
if inst == py_instance:
self._network[net_id] = None
self._py_instances[net_id] = None
