Initial export from new PyNN version to NeuroML

.gitignore

@@ -32,3 +32,7 @@ NEST_SLI/*.gdf
 /PyNN/tests.log
 /PyNN/data/2024*
 /p0/*
+/NeuroML2/*.dat
+/PyNN/LEMS_Sim_Microcircuit*.xml
+/NeuroML2/*.spikes
+/NeuroML2/Microcircuit*.gv

NeuroML2/regenerate.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+set -ex
+
+cd ../PyNN
+python test_neuroml.py
+
+cp *.nml LEMS*ml ../NeuroML2

PyNN/network.py

@@ -52,7 +52,7 @@ def __init__(self, sim_dict, net_dict, stim_dict=None):
         self.data_path = sim_dict['data_path']
 
 
-    def setup_pyNN(self):
+    def setup_pyNN(self, extra_setup_params):
         """ Reset and configure the simulator.
 
         Where the simulator is NEST,
@@ -73,7 +73,8 @@ def setup_pyNN(self):
         self.sim.setup(timestep=self.sim_resolution,
                        threads=self.sim_dict['local_num_threads'],
                        grng_seed=grng_seed,
-                       rng_seeds=rng_seeds)
+                       rng_seeds=rng_seeds,
+                       **extra_setup_params)
         if self.sim.rank() == 0:
             print('Master seed: %i ' % master_seed)
             print('Number of total processes: %i' % N_tp)
@@ -230,7 +231,7 @@ def create_poisson(self):
             for i, target_pop in enumerate(self.pops):
                 poisson = self.sim.Population(target_pop.size,
                                               self.sim.SpikeSourcePoisson(rate=rate_ext[i]),
-                                              label="Input to {}".format(target_pop.label))
+                                              label="Input_to_{}".format(target_pop.label))
                 self.poisson.append(poisson)
 
     def create_dc_generator(self):
@@ -369,7 +370,7 @@ def connect_dc_generator(self):
             if self.stim_dict['dc_input']:
                 self.dc[i].inject_into(target_pop)
 
-    def setup(self):
+    def setup(self, extra_setup_params = {}):
         """ 
         Execute subfunctions of the network.
 
@@ -378,7 +379,7 @@ def setup(self):
         each other and with devices and input nodes.
 
         """
-        self.setup_pyNN()
+        self.setup_pyNN(extra_setup_params)
         self.create_populations()
         self.create_devices()
         self.create_thalamic_input()

PyNN/test.py

@@ -3,10 +3,7 @@
 PyNN microcircuit example
 ---------------------------
 
-Example file to run the microcircuit.
-
-Based on original PyNEST version by Hendrik Rothe, Hannah Bos, Sacha van Albada; May 2016
-Adapted for PyNN by Andrew Davison, December 2017
+Test file for the microcircuit.
 
 """
 
@@ -18,29 +15,46 @@
 from stimulus_params import stim_dict
 import os
 
-
-# Initialize the network and pass parameters to it.
-tic = time.time()
-
-net_dict['N_scaling'] = 0.1
-net_dict['to_record'] = ['spikes', 'v']
-sim_dict['data_path'] = os.path.join(os.getcwd(), 'results')
-
-
-net = network.Network(sim_dict, net_dict, stim_dict)
-toc = time.time() - tic
-print("Time to initialize the network: %.2f s" % toc)
-# Connect all nodes.
-tic = time.time()
-net.setup()
-toc = time.time() - tic
-print("Time to create the connections: %.2f s" % toc)
-# Simulate.
-tic = time.time()
-net.simulate()
-toc = time.time() - tic
-print("Time to simulate: %.2f s" % toc)
-tic = time.time()
-net.write_data()
-toc = time.time() - tic
-print("Time to write data: %.2f s" % toc)
+def setup(simulator='nest', N_scaling=0.1):
+    # Initialize the network and pass parameters to it.
+    tic = time.time()
+
+    net_dict['N_scaling'] = N_scaling
+
+    net_dict['to_record'] = ['spikes', 'v']
+    sim_dict['data_path'] = os.path.join(os.getcwd(), 'results')
+
+    sim_dict['simulator'] = simulator
+
+    net = network.Network(sim_dict, net_dict, stim_dict)
+    toc = time.time() - tic
+    print("Time to initialize the network: %.2f s" % toc)
+
+    # Connect all nodes.
+    tic = time.time()
+    extra_setup_params = {}
+    if simulator=='neuroml':
+        extra_setup_params['reference']='Microcircuit_%spcnt'%(str(N_scaling*100).replace('.','_'))
+
+    net.setup(extra_setup_params)
+    toc = time.time() - tic
+    print("Time to create the connections: %.2f s" % toc)
+    return net, net_dict, sim_dict
+
+
+def run(net):
+
+    # Simulate.
+    tic = time.time()
+    net.simulate()
+    toc = time.time() - tic
+    print("Time to simulate: %.2f s" % toc)
+    tic = time.time()
+    net.write_data()
+    toc = time.time() - tic
+    print("Time to write data: %.2f s" % toc)
+
+
+if __name__ == "__main__":
+    net, net_dict, sim_dict = setup(N_scaling=0.1)
+    run(net)

PyNN/test_neuroml.py

@@ -0,0 +1,35 @@
+# -*- coding: utf-8 -*-
+"""
+PyNN microcircuit example
+---------------------------
+
+Export to NeuroML of the microcircuit.
+
+"""
+
+import time
+import numpy as np
+import network
+from network_params import net_dict
+from sim_params import sim_dict
+from stimulus_params import stim_dict
+import os
+
+from test import setup
+
+def export(net):
+
+    # Export.
+    tic = time.time()
+    print("Exporting...")
+    net.simulate()
+    net.sim.end()
+    toc = time.time() - tic
+    print("Time to export: %.2f s" % toc)
+
+
+
+if __name__ == "__main__":
+    net, net_dict, sim_dict = setup(simulator='neuroml', 
+                N_scaling=0.002)
+    export(net)