def set(self, value, calc_output=True):
ActivityNode.set(self, value, calc_output=False)
if self.mode == 'spike':
if value is None:
self._set_current = None
else:
c = self.array_to_current(self._set_array) + self.Jbias
self._set_current = c
if calc_output: self._calc_output()
def set(self,value,calc_output=True):
ActivityNode.set(self,value,calc_output=False)
if self.mode=='spike':
if value is None:
self._set_current=None
else:
c=self.array_to_current(self._set_array)+self.Jbias
self._set_current=c
if calc_output: self._calc_output()
def _calc_output(self):
if self.mode != 'spike': return ActivityNode._calc_output(self)
if self._set_current is not None:
curr = self._set_current
else:
curr = self.array_to_current(self.accumulator.value()) + self.Jbias
if self.current_noise is not None:
curr = self.add_current_noise(curr)
self._output = self.calc_spikes(curr)
def _calc_output(self):
if self.mode!='spike': return ActivityNode._calc_output(self)
if self._set_current is not None:
curr=self._set_current
else:
curr=self.array_to_current(self.accumulator.value())+self.Jbias
if self.current_noise is not None:
curr=self.add_current_noise(curr)
self._output=self.calc_spikes(curr)
def _calc_output(self):
if self.mode != 'spike': return ActivityNode._calc_output(self)
if self._set_current is not None:
curr = self._set_current
elif self._input is not None:
curr = self._input
else:
curr = numpy.zeros(self.neurons)
if self.current_noise is not None:
curr = self.add_current_noise(curr)
self._output = self.calc_spikes(curr)
def array(self):
if self._array is None:
if self.mode != 'spike': return ActivityNode.array(self)
self._array = self.activity_to_array(self._output / self.dt)
return self._array
def array(self):
if self._array is None:
if self.mode!='spike': return ActivityNode.array(self)
self._array=self.activity_to_array(self._output/self.dt)
return self._array
def array(self):
if self._array is None:
if self.mode != 'spike': return ActivityNode.array(self)
self._array = self.activity_to_array(
numpy.where(self._output >= 0, 1.0 / self.dt, 0))
return self._array
def _clear_inputs(self):
if self.mode != 'spike': return ActivityNode._clear_inputs(self)
if self._input is None: self._input = numpy.zeros(self.neurons)
self._input[:] = self.Jbias
def set(self, value, calc_output=True):
ActivityNode.set(self, value, calc_output=False)
if self.mode == 'spike':
c = self.array_to_current(self._set_array) + self.Jbias
self._set_current = c
