Enh for JSON path handling

Signed-off-by: samadpls <[email protected]>

hnn_core/batch_simulate.py

@@ -5,6 +5,7 @@
 #          Ryan Thorpe <[email protected]>
 #          Mainak Jas <[email protected]>
 
+import json
 import numpy as np
 import os
 from joblib import Parallel, delayed, parallel_config
@@ -13,6 +14,7 @@
 from .externals.mne import _validate_type, _check_option
 from .dipole import simulate_dipole
 from .network_models import jones_2009_model
+from .hnn_io import dict_to_network
 
 
 class BatchSimulate(object):
@@ -24,7 +26,7 @@ def __init__(self, set_params, net=jones_2009_model(), tstop=170,
                  save_dpl=True, save_spiking=False,
                  save_lfp=False, save_voltages=False,
                  save_currents=False, save_calcium=False,
-                 clear_cache=False):
+                 clear_cache=False, net_json=None):
         """Initialize the BatchSimulate class.
 
         Parameters
@@ -100,6 +102,9 @@ def __init__(self, set_params, net=jones_2009_model(), tstop=170,
         clear_cache : bool, optional
             Whether to clear the results cache after saving each batch.
             Default is False.
+        net_json : str, optional
+            The path to a JSON file to create the network model. If provided,
+            this will override the `net` parameter. Default is None.
         Notes
         -----
         When `save_output=True`, the saved files will appear as
@@ -127,6 +132,8 @@ def __init__(self, set_params, net=jones_2009_model(), tstop=170,
         _validate_type(save_currents, types=(bool,), item_name='save_currents')
         _validate_type(save_calcium, types=(bool,), item_name='save_calcium')
         _validate_type(clear_cache, types=(bool,), item_name='clear_cache')
+        _validate_type(net_json, types=('path-like', None),
+                       item_name='net_json')
 
         if set_params is not None and not callable(set_params):
             raise TypeError("set_params must be a callable function")
@@ -154,6 +161,7 @@ def __init__(self, set_params, net=jones_2009_model(), tstop=170,
         self.save_currents = save_currents
         self.save_calcium = save_calcium
         self.clear_cache = clear_cache
+        self.net_json = net_json
 
     def run(self, param_grid, return_output=True,
             combinations=True, n_jobs=1, backend='loky',
@@ -295,7 +303,14 @@ def _run_single_sim(self, param_values):
             - `param_values`: The parameter values used for the simulation.
         """
 
-        net = self.net.copy()
+        if isinstance(self.net_json, str):
+            with open(self.net_json, 'r') as file:
+                net_data = json.load(file)
+            net = dict_to_network(net_data)
+        else:
+            net = self.net
+        net = net.copy()
+
         self.set_params(param_values, net)
 
         results = {'net': net, 'param_values': param_values}

hnn_core/tests/test_batch_simulate.py

@@ -3,13 +3,17 @@
 #          Ryan Thorpe <[email protected]>
 #          Mainak Jas <[email protected]>
 
+from pathlib import Path
 import pytest
 import numpy as np
 import os
 
 from hnn_core.batch_simulate import BatchSimulate
 from hnn_core import jones_2009_model
 
+hnn_core_root = Path(__file__).parents[1]
+assets_path = Path(hnn_core_root, 'tests', 'assets')
+
 
 @pytest.fixture
 def batch_simulate_instance(tmp_path):
@@ -33,9 +37,9 @@ def set_params(param_values, net):
                              weights_ampa=weights_ampa,
                              synaptic_delays=synaptic_delays)
 
-    net = jones_2009_model()
+    net = jones_2009_model(mesh_shape=(3, 3))
     return BatchSimulate(net=net, set_params=set_params,
-                         tstop=1.,
+                         tstop=10,
                          save_folder=tmp_path,
                          batch_size=3)
 
@@ -75,6 +79,9 @@ def test_parameter_validation():
     with pytest.raises(TypeError, match="net must be"):
         BatchSimulate(net="invalid_network", set_params=lambda x: x)
 
+    with pytest.raises(TypeError, match="net_json must be"):
+        BatchSimulate(net_json=123, set_params=lambda x: x)
+
 
 def test_generate_param_combinations(batch_simulate_instance, param_grid):
     """Test generating parameter combinations."""
@@ -104,6 +111,21 @@ def test_run_single_sim(batch_simulate_instance):
     assert isinstance(result['net'], type(batch_simulate_instance.net))
 
 
+def test_net_json_loading(param_grid):
+    """Test loading the network from a JSON file."""
+    json_path = assets_path / 'jones2009_3x3_drives.json'
+
+    batch_simulate = BatchSimulate(net_json=str(json_path),
+                                   set_params=lambda x, y: x,
+                                   tstop=70)
+
+    result = batch_simulate._run_single_sim(param_grid)
+    assert isinstance(result, dict)
+    assert 'net' in result
+    assert 'param_values' in result
+    assert 'dpl' in result
+
+
 def test_simulate_batch(batch_simulate_instance, param_grid):
     """Test simulating a batch of parameter sets."""
     param_combinations = batch_simulate_instance._generate_param_combinations(