66268ffdc847e64216114871bd4169ad7872966a,snntoolbox/simulation/target_simulators/pyNN_target_sim.py,SNN,simulate,#SNN#,134

Before Change

            raise NotImplementedError
        else:
            constant_input_currents = kwargs[str("x_b_l")].flatten()
            try:
                for neuron_idx, neuron in enumerate(self.layers[0]):
                    // TODO: Implement constant input currents.
                    neuron.current = constant_input_currents[neuron_idx]
            except AttributeError:
                raise NotImplementedError

        self.sim.run(self._duration - self._dt)

        output_b_l_t = self.get_recorded_vars(self.layers)

After Change

        if self.data_format == "channels_last" and data.ndim == 4:
            data = np.moveaxis(data, 3, 1)

        x_flat = np.ravel(data)
        if self._poisson_input:
            self.layers[0].set(rate=list(x_flat / self.rescale_fac * 1000))
        elif self._dataset_format == "aedat":
            raise NotImplementedError
        else:
            spike_times = \
                [np.linspace(0, self._duration, self._duration * amplitude)
                 for amplitude in x_flat]
            self.layers[0].set(spike_times=spike_times)

        self.sim.run(self._duration - self._dt,

Instances