ALLEN INSTITUTE

# Source code for bmtk.simulator.pointnet.modules.spikes_inputs

    # Copyright 2023. Allen Institute. All rights reserved
    #
    # Redistribution and use in source and binary forms, with or without modification, are permitted provided that the
    # following conditions are met:
    #
    # 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following
    # disclaimer.
    #
    # 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following
    # disclaimer in the documentation and/or other materials provided with the distribution.
    #
    # 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote
    # products derived from this software without specific prior written permission.
    #
    # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
    # INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
    # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
    # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
    # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
    # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
    # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
    #
    import os
    from bmtk.simulator.pointnet.modules.sim_module import SimulatorMod
    from bmtk.simulator.pointnet.io_tools import io
    from bmtk.utils.reports.spike_trains import SpikeTrains
    from bmtk.simulator.pointnet.pyfunction_cache import py_modules

    class SpikesInputsMod(SimulatorMod):
        def __init__(self, name, input_type, module, **kwargs):
            self._name = name
            self._input_type = input_type
            self._module = module
            self._params = kwargs
            self._spike_trains = None

        def initialize(self, sim):
            io.log_info('Build virtual cell stimulations for {}'.format(self._name))

            node_set = sim.net.get_node_set(self._params['node_set'])

            if self._module == 'function':
                if 'spikes_function' not in self._params:
                    io.log_exception('missing parameter "spikes_function" for input {self._name}, module {self._module}')
                spikes_generator = self._params['spikes_function']
                if spikes_generator not in py_modules.spikes_generators:
                    io.log_exception(f'Could not find @spikes_generator function "{spikes_generator}" required for {self._name} inputs.')
                spikes_func = py_modules.spikes_generator(name=spikes_generator)

                self._spike_trains = SpikeTrains(cache_to_disk=False)
                for node in node_set.fetch_nodes():
                    timestamps = spikes_func(node, sim)
                    self._spike_trains.add_spikes(
                        node_ids=node.node_id,
                        timestamps=timestamps,
                        population=node.population_name
                    )
            else:
                self._spike_trains = SpikeTrains.load(
                    path=self._params['input_file'],
                    file_type=self._module,
                    **self._params
                )

            sim.net.add_spike_trains(self._spike_trains, node_set, sim.get_spike_generator_params())