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