add test script

hnn_core/viz.py

@@ -555,53 +555,6 @@ def plot_cells(net, ax=None, show=True):
     for cell_name in net.cell_types:
         if cell_name not in cell_names:
             cell_names.append(cell_name)
-#     import hnn_core
-# from hnn_core import  jones_2009_model, simulate_dipole
-# import matplotlib as plt
-
-# net = jones_2009_model(add_drives_from_params= True)
-# params = hnn_core.read_params('/home/mohamed/Desktop/PhD Thesis/auditory_evoked_simulation/HNN-AEF-main/HNN_Parameters/L_Contra.param')
-
-# def martinotti(n_cells):
-#     from hnn_core.cell import Section, Cell
-
-#     cell_name = 'martinotti'
-#     pos = [(5, 5, 5)] * n_cells
-#     # pos = net.pos_dict['L5_basket'].copy()
-
-#     end_pts = [[0, 0, 0], [0, 0, 39.]]
-#     soma = Section(L=39., diam=20., cm=0.85,
-#         Ra=200., end_pts=end_pts)
-#     soma.syns = ['gabaa', 'nmda']
-
-#     synapses = {
-#         'gabaa': {
-#             'e': -80,
-#             'tau1': 0.5,
-#             'tau2': 5.
-#         },
-#         'nmda': {
-#             'e': 0,
-#             'tau1': 1.,
-#             'tau2': 20.
-#         }
-#     }
-#     sect_loc = ['proximal']
-
-#     return Cell(cell_name, pos,
-#             sections=soma,
-#             synapses=synapses,
-#             topology=None,
-#             sect_loc=sect_loc,
-#             gid=0)
-
-# net.plot_cells()
-# net._add_cell_type('L5_martinotti', pos='L5_basket' ,cell_template = None)
-
-# simulate_dipole(net, tstop = 100, record_vsec= 'all')
-
-# net.add_connection(src_gids='L5_martinotti', target_gids='L5_pyramidal', loc='apical_tuft', receptor='gabaa', weight= 0.025 , delay=1.0 ,lamtha=70.0 , allow_autapses= False, probability=1)
-
 
     colors= dict()
     markers= dict()

test_script.py

@@ -0,0 +1,66 @@
+import hnn_core
+from hnn_core import  jones_2009_model, simulate_dipole, Network
+import numpy as np
+import matplotlib as plt
+
+params = hnn_core.read_params('/home/mohamed/Desktop/PhD Thesis/auditory_evoked_simulation/HNN-AEF-main/HNN_Parameters/L_Contra.param')
+net = jones_2009_model()
+
+
+def martinotti_template():
+    from hnn_core.cell import Section, Cell
+
+    cell_name = 'martinotti'
+    pos = (5, 5, 5)
+    # pos = net.pos_dict['L5_basket'].copy()
+
+    end_pts = [[0, 0, 0], [0, 0, 39.]]
+    sections = {'soma': Section(L=39., diam=20., cm=0.85,
+        Ra=200., end_pts=end_pts)}
+    sections['soma'].syns = ['gabaa', 'nmda']
+
+    synapses = {
+        'gabaa': {
+            'e': -80,
+            'tau1': 0.5,
+            'tau2': 5.
+        },
+        'nmda': {
+            'e': 0,
+            'tau1': 1.,
+            'tau2': 20.
+        }
+    }
+    sect_loc = dict(proximal=['soma'], distal=['soma'])
+
+    return Cell(cell_name, pos,
+            sections=sections,
+            synapses=synapses,
+            topology=None,
+            sect_loc=sect_loc,
+            gid=None)
+
+x1= np.linspace(0, 7, 7)
+y1= np.linspace(0, 5, 5)
+xv, yv = np.meshgrid(x1, y1)
+pos = list()
+for (x, y) in zip(xv.ravel(), yv.ravel()):
+    pos.append((x, y, 0.))
+
+# net._add_cell_type('L5_martinotti', pos= pos, cell_template=martinotti_template())
+# net.plot_cells()
+
+weights_nmda_d1 = {'L2_basket': 0.019482, 'L2_pyramidal': 0.004317,
+                   'L5_pyramidal': 0.080074}
+synaptic_delays_d1 = {'L2_basket': 0.1, 'L2_pyramidal': 0.1,
+                      'L5_pyramidal': 0.1}
+net.add_evoked_drive(
+    'evdist1', mu=63.53, sigma=3.85, numspikes=1, weights_ampa=None,
+    weights_nmda=weights_nmda_d1, location='distal',
+    synaptic_delays=synaptic_delays_d1, event_seed=4)
+
+simulate_dipole(net, tstop = 100, record_vsec=False)
+
+# net.add_connection(src_gids='L5_martinotti', target_gids='L5_pyramidal', loc='apical_tuft', receptor='gabaa', weight= 0.025 , delay=1.0 ,lamtha=70.0 , allow_autapses= False, probability=1)
+
+