SSN implementation in BMTK

bmtk/analyzer/firing_rates.py

@@ -23,6 +23,10 @@
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
+from pathlib import Path
+import h5py
+
+from bmtk.utils.sonata.config import SonataConfig
 
 
 def convert_rates(rates_file):
@@ -87,3 +91,83 @@ def plot_rates_popnet(cell_models_file, rates_file, model_keys=None, save_as=Non
 
     if show_plot:
         plt.show()
+
+
+def plot_rates(config_file=None, rates_files=None, population=None, times=None, label_column='node_id', title=None, show=True,
+                save_as=None, group_by=None, group_excludes=None,
+                nodes_file=None, node_types_file=None, plt_style=None):
+
+    def is_hdf5(file_path):
+        try:
+            h5py.File(file_path, 'r')
+            return True
+        except Exception:
+            return False
+
+    def is_csv(file_path):
+        try:
+            pd.read_csv(file_path)
+            return True
+        except Exception:
+            return False
+
+
+    sonata_config = SonataConfig.from_json(config_file) if config_file else None
+
+    rates_paths = set()
+    if isinstance(rates_files, (list, tuple, pd.Series)):
+        rates_paths.update([Path(rf).absolute() for rf in rates_files])
+    elif rates_files is not None:
+        rates_paths.add(Path(rates_files))
+
+    if sonata_config is not None:
+        for k in ['rates_file', 'rates_file_csv', 'rates_file_h5']:
+            if k in sonata_config.output:
+                rates_paths.add(Path(sonata_config.get('output', {}).get('output_dir', '.')) / Path(sonata_config.output[k]))
+                break
+
+    fig, ax = plt.subplots(1, 1)
+    for rpath in rates_paths:
+        if is_csv(rpath):
+            rates_df = pd.read_csv(rpath, sep=' ')
+            for (population, node_id), subdf in rates_df.groupby(['population', 'node_id']):
+                times = subdf['timestamps'].values
+                frs = subdf['firing_rates'].values
+
+                if label_column == 'population':
+                    label = population
+                elif label_column == 'node_id':
+                    label = node_id
+                elif label_column in subdf.columns:
+                    label = subdf[label_column].iloc[0]
+                else:
+                    label = ''
+
+                ax.plot(times, frs, label=label)
+
+        elif is_hdf5(rpath):
+            with h5py.File(rpath, 'r') as h5:
+                for population, popgrp in h5['/rates'].items():
+                    times = popgrp['mapping/time'][()]
+                    node_ids = popgrp['mapping/node_ids'][()]
+
+                    if label_column == 'population':
+                        labels = [population]*len(node_ids)
+                    elif label_column == 'node_id':
+                        labels = node_ids
+                    elif label_column in popgrp['mapping']:
+                        labels = popgrp['mapping'][label_column][()].astype(str)
+                    else:
+                        labels = ['']*len(node_ids)
+
+                    for idx, node_id in enumerate(node_ids):
+                        frs = popgrp['data'][:, idx]
+                        ax.plot(times, frs, label=labels[idx])
+
+
+    ax.legend()
+    ax.set_ylabel('firing rates (Hz)')
+    ax.set_xlabel('times (ms)')
+
+    if show:
+        plt.show()

bmtk/simulator/core/node_sets.py

@@ -57,6 +57,9 @@ def fetch_nodes(self):
             for node in pop.filter(self._filter):
                 yield node
 
+    def __len__(self) -> int:
+        return len(self.node_ids)
+
 
 class NodeSetAll(NodeSet):
     def __init__(self, network):

bmtk/simulator/core/sonata_reader/node_adaptor.py

@@ -145,7 +145,7 @@ def preprocess_node_types(network, node_population):
                     params_dir = network.get_component('point_neuron_models_dir')
                 elif model_type == 'point_soma':
                     params_dir = network.get_component('point_neuron_models_dir')
-                elif model_type == 'population':
+                elif model_type in ['population', 'rate_population']:
                     params_dir = network.get_component('population_models_dir')
                 elif model_type == 'lgnmodel' or model_type == 'virtual':
                     params_dir = network.get_component('filter_models_dir')

bmtk/simulator/popnet/__init__.py

@@ -20,6 +20,47 @@
 # 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.
 #
-from .popnetwork import PopNetwork
-from .popsimulator import PopSimulator
+from six import string_types
+
+from bmtk.simulator.core.simulation_config import SimulationConfig
+from bmtk.simulator.core.io_tools import io
 from .config import Config
+from .ssn import inputs_generator, init_function, activation_function
+
+
+class PopNetwork:
+    @staticmethod
+    def from_config(conf, **properties):
+        if isinstance(conf, SimulationConfig):
+            config = conf
+        else:
+            try:
+                config = SimulationConfig.load(conf)
+            except Exception as e:
+                io.log_exception('Could not convert {} (type "{}") to json.'.format(conf, type(conf)))
+
+        if config.target_simulator is None:
+            io.log_debug('Unspecified PopNet "target_simulator", defaulting to SSN (Options: SSN, DiPDE)')
+        elif config.target_simulator.lower() == 'dipde':
+            from .dipde import PopNetwork
+            return PopNetwork.from_config(config, **properties)
+        elif config.target_simulator.lower() == 'ssn':
+            from .ssn import PopNetwork
+            return PopNetwork.from_config(config, **properties)
+        else:
+            io.log_exception(f'Unrecognized PopNet target_simulator "{config.target_simulator}')
+
+
+class PopSimulator:
+    @staticmethod
+    def from_config(configure, network, **properties):
+        if network.target_simulator is None:
+            io.log_debug('Unspecified PopNet "target_simulator", defaulting to SSN (Options: SSN, DiPDE)')
+        elif network.target_simulator.lower() == 'dipde':
+            from .dipde import PopSimulator
+            return PopSimulator.from_config(configure, network, **properties)
+        elif network.target_simulator.lower() == 'ssn':
+            from .ssn import PopSimulator
+            return PopSimulator.from_config(configure, network, **properties)
+        else:
+            io.log_exception(f'Unrecognized PopNet target_simulator "{config.target_simulator}')

bmtk/simulator/popnet/config.py

@@ -30,4 +30,4 @@ def from_json(config_file, validate=False):
 
 
 class Config(SimulationConfig):
-    pass
+    pass

bmtk/simulator/popnet/dipde/__init__.py

@@ -0,0 +1,25 @@
+# Copyright 2017. 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.
+#
+from .popnetwork import PopNetwork
+from .popsimulator import PopSimulator
+from ..config import Config

bmtk/simulator/popnet/popnetwork.py → bmtk/simulator/popnet/dipde/popnetwork.py

@@ -25,8 +25,8 @@
 import numpy as np
 
 from bmtk.simulator.core.simulator_network import SimNetwork
-from bmtk.simulator.popnet import utils as poputils
-from bmtk.simulator.popnet.sonata_adaptors import PopEdgeAdaptor
+from bmtk.simulator.popnet.dipde import utils as poputils
+from bmtk.simulator.popnet.dipde.sonata_adaptors import PopEdgeAdaptor
 
 from dipde.internals.internalpopulation import InternalPopulation
 from dipde.internals.externalpopulation import ExternalPopulation
@@ -162,6 +162,10 @@ def __init__(self, group_by='node_type_id', **properties):
         self._external_connections = {}
         self._all_connections = []
 
+    @property
+    def target_simulator(self):
+        return 'DiPDE'
+
     @property
     def populations(self):
         return self._all_populations

bmtk/simulator/popnet/popsimulator.py → bmtk/simulator/popnet/dipde/popsimulator.py

@@ -30,13 +30,21 @@
 import dipde
 
 from bmtk.simulator.core.simulator import Simulator
-from . import config as cfg
+# from bmtk. import config as cfg
+from bmtk.simulator.core.simulation_config import SimulationConfig
+from bmtk.simulator.core.io_tools import io
 from . import utils as poputils
 import bmtk.simulator.utils.simulation_inputs as inputs
 from bmtk.utils.reports.spike_trains import SpikeTrains
 from bmtk.utils.io import firing_rates
 
 
+def from_json(config_file, validate=False):
+    conf_dict = SimulationConfig.from_json(config_file)
+    conf_dict.io = io
+    return conf_dict
+
+
 class PopSimulator(Simulator):
     def __init__(self, graph, dt=0.0001, tstop=0.0, overwrite=True):
         self._graph = graph

bmtk/simulator/popnet/ssn/__init__.py

@@ -0,0 +1,28 @@
+# Copyright 2025. 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.
+#
+from .popnetwork import PopNetwork
+from .popsimulator import PopSimulator
+from .pyfunction_cache import inputs_generator, init_function, activation_function, add_activation_function
+
+from bmtk.simulator.core.simulation_config import SimulationConfig as Config
+# from .config import Config

bmtk/simulator/popnet/ssn/default_setters/__init__.py

@@ -0,0 +1 @@
+from . import activation_functions

bmtk/simulator/popnet/ssn/default_setters/activation_functions.py

@@ -0,0 +1,22 @@
+from bmtk.simulator.popnet.ssn.pyfunction_cache import add_activation_function
+
+try:
+    from numba import njit
+
+except ImportError as ie:
+    from bmtk.simulator.popnet.ssn.utils import empty_decorator
+    njit = empty_decorator
+
+
+@njit
+def relu2(array):
+    # if the element is negative, set it to zero using loop
+    # destructive method (alters the original array), but faster than the above one.
+    for i in range(len(array)):
+        if array[i] < 0:
+            array[i] = 0
+    return array
+
+
+add_activation_function(relu2, name='default', overwrite=False)
+add_activation_function(relu2, overwrite=False)

bmtk/simulator/popnet/ssn/modules/__init__.py

@@ -0,0 +1,3 @@
+from .initial_states import InitStatesMod
+from .rates_recorder import RatesRecorderMod
+from .external_inputs import ExternalRatesMod

bmtk/simulator/popnet/ssn/modules/external_inputs.py

@@ -0,0 +1,87 @@
+import numpy as np
+import pandas as pd
+import h5py
+
+from ..pyfunction_cache import py_modules
+from .sim_module import SimulatorMod
+
+
+class ExternalRatesMod(SimulatorMod):
+    def __init__(self, name, input_type, module, **kwargs):
+        self._name = name
+        self._input_type = input_type
+        self._module = module
+        self._params = kwargs
+
+    def initialize(self, sim):
+        if self._module == 'npy':
+            npy_path = self._params['file']
+            inputs_arr = np.load(npy_path)
+
+            if sim.tstop is None:
+                # TODO: WARNING THAT TSTOP IS BEING SET BY INPUT
+                sim.tstop = len(inputs_arr)*sim.dt
+
+            if sim.nsteps < len(inputs_arr):
+                # TODO: WARN THAT input is being cut
+                inputs_arr = inputs_arr[:sim.nsteps]
+
+            elif sim.nsteps > len(inputs_arr):
+                # GIVE WARNING
+                inputs_arr = np.append(inputs_arr, np.zeros(sim.nsteps - len(inputs_arr)))
+
+            node_set = sim.network.get_node_set(self._params.get('node_set', 'all'))
+
+            for node in node_set.fetch_nodes():
+                ssn_node = sim.network.get_node(node.population_name, node.node_id)
+                ssn_node.external_inputs = inputs_arr.flatten()
+
+
+        elif self._module == 'function':
+            fnc_name = self._params['inputs_generator']
+            generator_fnc = py_modules.user_function(fnc_name)
+
+            node_set = sim.network.get_node_set(self._params.get('node_set', 'all'))
+            for node in node_set.fetch_nodes():
+                ssn_node = sim.network.get_node(node.population_name, node.node_id)
+                external_inputs = generator_fnc(ssn_node, sim)
+                ssn_node.external_inputs = external_inputs
+
+                if sim.tstop is None:
+                    # TODO: WARNING THAT TSTOP IS BEING SET BY INPUT
+                    sim.tstop = len(external_inputs)*sim.dt
+
+        elif self._module == 'csv':
+            # TODO: Check Timestamps match, line up if needed
+            rates_df = pd.read_csv(self._params['file'], sep=self._params.get('sep', ' '))
+            node_set = sim.network.get_node_set(self._params.get('node_set', 'all'))
+            for node in node_set.fetch_nodes():
+                ssn_node = sim.network.get_node(node.population_name, node.node_id)
+
+                # TODO: Check that node exists in file
+                inputs = rates_df[(rates_df['node_id'] == ssn_node.node_id) & (rates_df['population'] == ssn_node.population)]['firing_rates']
+                if len(inputs) > 0:
+                    ssn_node.external_inputs = inputs
+
+                    if sim.tstop is None:
+                        # TODO: WARNING THAT TSTOP IS BEING SET BY INPUT
+                        sim.tstop = len(inputs)*sim.dt
+
+        elif self._module in ['h5', 'sonata']:
+            with h5py.File(self._params['file'], 'r') as h5:
+                ratesgrp = h5['/rates']
+                node_set = sim.network.get_node_set(self._params.get('node_set', 'all'))
+                for node in node_set.fetch_nodes():
+                    ssn_node = sim.network.get_node(node.population_name, node.node_id)
+
+                    node_id_map = ratesgrp[f'{ssn_node.population}/mapping/node_ids'][()]
+                    idx = np.argwhere(node_id_map == ssn_node.node_id)[0][0]
+                    inputs = ratesgrp[f'{ssn_node.population}/data'][:, idx]
+
+                    ssn_node.external_inputs = inputs
+
+                    if sim.tstop is None:
+                        # TODO: WARNING THAT TSTOP IS BEING SET BY INPUT
+                        sim.tstop = len(inputs)*sim.dt
+        else:
+            raise ValueError('Unknown module')