Merge pull request #82 from NeuroML/experimental

Fix for python 3.13

Author: pgleeson

.github/workflows/ci.yml

@@ -13,7 +13,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
     env:
       JNML_HOME: "/home/runner/work/NeuroMLlite/NeuroMLlite/jNeuroML"
       HDF5_DISABLE_VERSION_CHECK: 1

examples/Example6.py

@@ -111,25 +111,24 @@ def generate(ref="Example6_PyNN", add_inputs=True):
             pop_id = "%s_%s" % (l, t)
             pops.append(pop_id)
             ref = "l%s%s" % (l[1:], t.lower())
-            exec(
-                ref
-                + " = Population(id=pop_id, size='int(%s*N_scaling)'%N_full[l][t], component=cell.id, properties={'color':color, 'type':t})"
-            )
-            exec("%s.random_layout = RandomLayout(region = r.id)" % ref)
-            exec("net.populations.append(%s)" % ref)
-            exec("pop_dict['%s'] = %s" % (pop_id, ref))
+            d = {}
+            d[ref] = Population(id=pop_id, size='int(%s*N_scaling)'%N_full[l][t], component=cell.id, properties={'color':color, 'type':t})
+
+            # Instead of exec, set the attribute directly using locals()
+            d[ref].random_layout = RandomLayout(region=r.id)
+            net.populations.append(d[ref])
+            pop_dict['%s'% (pop_id)] = d[ref]
 
             if add_inputs:
                 color = ".8 .8 .8"
                 input_id = "%s_%s_input" % (l, t)
                 input_pops.append(input_id)
                 input_ref = "l%s%s_i" % (l[1:], t.lower())
-                exec(
-                    input_ref
-                    + " = Population(id=input_id, size='int(%s*N_scaling)'%N_full[l][t], component=input_cell.id, properties={'color':color})"
-                )
-                exec("%s.random_layout = RandomLayout(region = r.id)" % input_ref)
-                exec("net.populations.append(%s)" % input_ref)
+                ir = {}
+                ir[input_ref] = Population(id=input_id, size='int(%s*N_scaling)'%N_full[l][t], component=input_cell.id, properties={'color':color})
+                
+                ir[input_ref].random_layout = RandomLayout(region = r.id)
+                net.populations.append(ir[input_ref])
 
         # l23i = Population(id='L23_I', size=int(100*scale), component=cell.id, properties={'color':})
         # l23ei = Population(id='L23_E_input', size=int(100*scale), component=input_cell.id)

examples/LEMS_SimExample3.xml

@@ -2,7 +2,7 @@
 
     <!-- 
 
-        This LEMS file has been automatically generated using PyNeuroML v1.3.17 (libNeuroML v0.6.6)
+        This LEMS file has been automatically generated using PyNeuroML v1.3.18 (libNeuroML v0.6.7)
 
      -->
 

examples/LEMS_SimExample4.xml

@@ -2,7 +2,7 @@
 
     <!-- 
 
-        This LEMS file has been automatically generated using PyNeuroML v1.3.17 (libNeuroML v0.6.6)
+        This LEMS file has been automatically generated using PyNeuroML v1.3.18 (libNeuroML v0.6.7)
 
      -->