Merge pull request #95 from apdavison/300_pointneurons

Changes needed to run 300_pointneurons example with PyNN

examples/300_pointneurons/circuit_config.json

@@ -32,6 +32,7 @@
         "edge_types_file": "$NETWORK_DIR/external_internal_edge_types.csv"
       }
     ]
+  },
 
-  }
-}
+  "target_simulator": "NEST"
+}

examples/300_pointneurons/network/external_internal_edge_types.csv

@@ -1,3 +1,3 @@
 edge_type_id target_query source_query delay dynamics_params model_template
-100 ei=='e' * 2.0 ExcToExc.json static_synapse
-101 ei=='i' * 2.0 ExcToInh.json static_synapse
+100 ei=='e' * 2.0 ExcToExc.json nest:static_synapse
+101 ei=='i' * 2.0 ExcToInh.json nest:static_synapse

examples/300_pointneurons/network/internal_internal_edge_types.csv

@@ -1,5 +1,5 @@
 edge_type_id target_query source_query delay dynamics_params model_template
-100 ei=='e' ei=='e' 2.0 ExcToExc.json static_synapse
-101 ei=='i' ei=='e' 2.0 ExcToInh.json static_synapse
-102 ei=='e' ei=='i' 2.0 InhToExc.json static_synapse
-103 ei=='i' ei=='i' 2.0 InhToInh.json static_synapse
+100 ei=='e' ei=='e' 2.0 ExcToExc.json nest:static_synapse
+101 ei=='i' ei=='e' 2.0 ExcToInh.json nest:static_synapse
+102 ei=='e' ei=='i' 2.0 InhToExc.json nest:static_synapse
+103 ei=='i' ei=='i' 2.0 InhToInh.json nest:static_synapse

examples/300_pointneurons/node_sets.json

@@ -3,5 +3,8 @@
     "population": "external"
   },
 
-  "recorded_cells": [0, 80, 160, 240, 270]
+  "recorded_cells": {
+      "population": "internal",
+      "node_id": [0, 80, 160, 240, 270]
+  }
 }

examples/300_pointneurons/plot_potential.py

@@ -16,7 +16,7 @@
 from bmtk.utils.cell_vars import CellVarsFile
 
 
-def plot_vars(file_names, cell_var='v', gid_list=[]):
+def plot_vars(file_names, cell_var='v', gid_list=[], t_min=None, t_max=None):
     """Plots variable traces for a SONATA h5 file. If multiple spike files are specified will do a side-by-side
     comparsion for each gid.
 
@@ -29,11 +29,16 @@ def plot_vars(file_names, cell_var='v', gid_list=[]):
     assert(len(file_names) > 0)
 
     # Use bmtk to parse the cell-var files
-    cell_var_files = [CellVarsFile(fn) for fn in file_names]
+    cell_var_files = []
+    for fn in file_names:
+        try:
+            cell_var_files.append(CellVarsFile(fn, h5_root="/report/internal"))
+        except KeyError:
+            cell_var_files.append(CellVarsFile(fn))
 
     # get first spike file and properties
     cvf_base = cell_var_files[0]
-    xlim = [cvf_base.time_trace[0], cvf_base.time_trace[-1]]  # Use the same x-axis across all subplots
+    xlim = [t_min or cvf_base.time_trace[0], t_max or cvf_base.time_trace[-1]]  # Use the same x-axis across all subplots
     gid_list = cvf_base.gids if not gid_list else gid_list  # if gid_list is None just get all gids in first file
     n_cells = len(cvf_base.gids)
 
@@ -64,13 +69,19 @@ def plot_vars(file_names, cell_var='v', gid_list=[]):
                       action='callback',
                       callback=lambda option, opt, value, parser: setattr(parser.values, option.dest, [int(v) for v in value.split(',')]),
                       help='comma seperated list of gids to plot')
+    parser.add_option('--tmin', type=float, dest='t_min', default=None)
+    parser.add_option('--tmax', type=float, dest='t_max', default=None)
     options, args = parser.parse_args()
 
     if len(args) == 0:
         # If no file is specified see if there is a output/membrane_potential.h5 file to plot membrane voltage
         if not os.path.exists('output/membrane_potential.h5'):
             raise Exception('Please specifiy hdf5 file to read in arguments. Exiting!')
         else:
-            plot_vars('output/membrane_potential.h5', cell_var=options.cell_var)
+            plot_vars('output/membrane_potential.h5', cell_var=options.cell_var, t_min=options.t_min, t_max=options.t_max)
     else:
-        plot_vars(file_names=args, cell_var=options.cell_var, gid_list=options.gids)
+        plot_vars(file_names=args, cell_var=options.cell_var, gid_list=options.gids, t_min=options.t_min, t_max=options.t_max)
+    if len(args) == 1:
+        plt.savefig(args[0].replace(".h5", ".png"))
+    else:
+        plt.savefig("comparison_{}.png".format(options.cell_var))

examples/300_pointneurons/run_PyNN.py

@@ -0,0 +1,7 @@
+from pyNN.serialization import import_from_sonata, load_sonata_simulation_plan
+import pyNN.nest as sim
+
+simulation_plan = load_sonata_simulation_plan("simulation_config.json")
+simulation_plan.setup(sim)
+net = import_from_sonata("circuit_config.json", sim)
+simulation_plan.execute(net)