#!/usr/bin/env python

import matplotlib.pyplot as plt
import nest
import numpy as np
import os

from pynestml.frontend.pynestml_frontend import generate_nest_target

neuron_model = "aeif_cond_alpha"
codegen_opts = {"neuron_synapse_pairs": [{"neuron": "aeif_cond_alpha",
                                         "synapse": "dopamine_synapse", 
                                         # "post_ports": post_ports,
                                         "vt_ports": "dopa_spikes"}],
                "gap_junctions": {"enable": True,
                                  "gap_current_port": "I_stim",
                                  "membrane_potential_variable": "V_m"}}

files = [os.path.join("models", "neurons", neuron_model + ".nestml")]
input_path = ["/opt/miniconda3/envs/pd_nestml/models/neurons/aeif_cond_alpha.nestml",
              "/opt/miniconda3/envs/pd_nestml/models/synapses/dopamine_synapse_NEW.nestml"] 

generate_nest_target(input_path=input_path,
                     target_path="/opt/miniconda3/envs/pd_nestml/models/gap-dopamod-component-new",
                     logging_level="DEBUG",
                     module_name="nestml_gap_dopa_module", 
                     suffix="_nestml",
                     codegen_opts=codegen_opts)