Merge pull request #318 from ModECI/nml_examples

Updates to NeuroML examples

.github/workflows/ci.yml

@@ -35,19 +35,17 @@ jobs:
       with:
         python-version: ${{ matrix.python-version }}
 
-    # Rely on latest release of modelspec...
+    # Rely on version of modelspec from PyPI as set by setup.cfg...
     #- name: Install modelspec
     #  run: python -m pip install git+https://github.com/ModECI/modelspec.git@main
 
+    # Rely on version of NeuroMLlite from PyPI as set by setup.py...
     # - name: Install NeuroMLlite
     #   run: python -m pip install NeuroMLlite>=0.5.0
 
-    - name: Install GPy (py3.9)
-      if: ${{ matrix.python-version == '3.9' }}
-      run: python -m pip install git+https://github.com/SheffieldML/GPy.git@devel
-
-    - name: Install specific PsyNeuLink branch
-      run: python -m pip install git+https://github.com/ModECI/PsyNeuLink@devel
+    # Rely on version of PsyNeuLink from PyPI as set by setup.py...
+    #- name: Install specific PsyNeuLink branch
+    #  run: python -m pip install git+https://github.com/ModECI/PsyNeuLink@devel
 
     - name: Install core package
       run: python -m pip install .[dev]

.gitignore

@@ -252,13 +252,10 @@ Thumbs.db #thumbnail cache on Windows
 /examples/NeuroML/Izh.png
 /examples/NeuroML/Izh_multi
 /examples/NeuroML/Izh_multi.png
-/examples/NeuroML/Izh_run.png
 /examples/NeuroML/IzhikevichTest.mdf.json
 /examples/NeuroML/IzhikevichTest.net.nml
-/examples/NeuroML/IzhikevichTest.nmllite.yaml
 /examples/NeuroML/LEMS_SimIzhikevichTest.xml
 /examples/NeuroML/SimIzhikevichTest.json
-/examples/NeuroML/SimIzhikevichTest.yaml
 /examples/AB
 /examples/AB.png
 /examples/states
@@ -272,3 +269,10 @@ Thumbs.db #thumbnail cache on Windows
 /examples/MDF/params_funcs_example_3
 /examples/MDF/params_funcs_example_3.png
 /examples/MDF/params_funcs_example.png
+/examples/NeuroML/LEMS_SimFN_nrn.py
+/examples/MDF/RNN/*.gv.png
+/examples/MDF/RNN/*.dat
+/examples/MDF/RNN/LEMS_Simiaf_example.xml
+/examples/MDF/RNN/iaf_example.net.nml
+/examples/MDF/RNN/iaf_example__lems.xml
+/examples/MDF/RNN/iaf_example_lems_definitions.xml

examples/MDF/RNN/IAFs.json

@@ -7,7 +7,7 @@
                 "nodes": {
                     "input_node": {
                         "parameters": {
-                            "t": {
+                            "time": {
                                 "default_initial_value": 0,
                                 "time_derivative": "1"
                             },
@@ -25,12 +25,12 @@
                                 "conditions": [
                                     {
                                         "id": "on",
-                                        "test": "t > start and t < start + duration",
+                                        "test": "time > start and time < start + duration",
                                         "value": "amplitude"
                                     },
                                     {
                                         "id": "off",
-                                        "test": "t > start + duration",
+                                        "test": "time > start + duration",
                                         "value": 0
                                     }
                                 ]
@@ -39,9 +39,6 @@
                         "output_ports": {
                             "out_port": {
                                 "value": "level"
-                            },
-                            "t_out_port": {
-                                "value": "t"
                             }
                         }
                     },

examples/MDF/RNN/IAFs.nmllite.json

@@ -0,0 +1,53 @@
+{
+    "iaf_example": {
+        "version": "NeuroMLlite v0.5.2",
+        "notes": "NeuroMLlite export of MDF graph: iaf_example",
+        "cells": {
+            "input_node__instance": {
+                "lems_source_file": "iaf_example_lems_definitions.xml"
+            },
+            "iaf_node__instance": {
+                "lems_source_file": "iaf_example_lems_definitions.xml"
+            }
+        },
+        "synapses": {
+            "rsDL": {
+                "lems_source_file": "iaf_example_lems_definitions.xml"
+            },
+            "silentSyn_proj_input_edge": {
+                "lems_source_file": "iaf_example_lems_definitions.xml"
+            }
+        },
+        "populations": {
+            "input_node": {
+                "size": 1,
+                "component": "input_node__instance",
+                "properties": {
+                    "color": "0.2 0.2 0.2",
+                    "radius": 3
+                }
+            },
+            "iaf_node": {
+                "size": 1,
+                "component": "iaf_node__instance",
+                "properties": {
+                    "color": "0.2 0.2 0.2",
+                    "radius": 3
+                }
+            }
+        },
+        "projections": {
+            "proj_input_edge": {
+                "presynaptic": "input_node",
+                "postsynaptic": "iaf_node",
+                "synapse": "rsDL",
+                "pre_synapse": "silentSyn_proj_input_edge",
+                "type": "continuousProjection",
+                "weight": 1,
+                "random_connectivity": {
+                    "probability": 1
+                }
+            }
+        }
+    }
+}

examples/MDF/RNN/IAFs.yaml

@@ -6,7 +6,7 @@ IAFs:
             nodes:
                 input_node:
                     parameters:
-                        t:
+                        time:
                             default_initial_value: 0
                             time_derivative: '1'
                         start:
@@ -19,16 +19,14 @@ IAFs:
                             value: 0
                             conditions:
                             -   id: 'on'
-                                test: t > start and t < start + duration
+                                test: time > start and time < start + duration
                                 value: amplitude
                             -   id: 'off'
-                                test: t > start + duration
+                                test: time > start + duration
                                 value: 0
                     output_ports:
                         out_port:
                             value: level
-                        t_out_port:
-                            value: t
                 iaf_node:
                     input_ports:
                         input: {}

examples/MDF/RNN/Simiaf_example.json

@@ -0,0 +1,24 @@
+{
+    "Simiaf_example": {
+        "version": "NeuroMLlite v0.5.2",
+        "network": "IAFs.nmllite.json",
+        "duration": 100000.0,
+        "dt": 10.0,
+        "seed": 123,
+        "record_variables": {
+            "time": {
+                "input_node": 0
+            },
+            "out_port": {
+                "input_node": 0,
+                "iaf_node": 0
+            },
+            "input": {
+                "iaf_node": 0
+            },
+            "v": {
+                "iaf_node": 0
+            }
+        }
+    }
+}

examples/MDF/RNN/generate_iaf.py

@@ -14,7 +14,7 @@ def main():
     ## Counter node
     input_node = Node(id="input_node")
 
-    t_param = Parameter(id="t", default_initial_value=0, time_derivative="1")
+    t_param = Parameter(id="time", default_initial_value=0, time_derivative="1")
     input_node.parameters.append(t_param)
 
     start = Parameter(id="start", value=20)
@@ -30,20 +30,20 @@ def main():
 
     level.conditions.append(
         ParameterCondition(
-            id="on", test="t > start and t < start + duration", value=amp.id
+            id="on", test="time > start and time < start + duration", value=amp.id
         )
     )
     level.conditions.append(
-        ParameterCondition(id="off", test="t > start + duration", value=0)
+        ParameterCondition(id="off", test="time > start + duration", value=0)
     )
 
     input_node.parameters.append(level)
 
     op1 = OutputPort(id="out_port", value=level.id)
     input_node.output_ports.append(op1)
 
-    op2 = OutputPort(id="t_out_port", value=t_param.id)
-    input_node.output_ports.append(op2)
+    # op2 = OutputPort(id="t_out_port", value=t_param.id)
+    # input_node.output_ports.append(op2)
 
     mod_graph.nodes.append(input_node)
 
@@ -118,7 +118,7 @@ def main():
                 eg.evaluate(time_increment=dt)
 
             i.append(eg.enodes["input_node"].evaluable_outputs["out_port"].curr_value)
-            t.append(eg.enodes["input_node"].evaluable_outputs["t_out_port"].curr_value)
+            t.append(eg.enodes["input_node"].evaluable_parameters["time"].curr_value)
             s.append(eg.enodes["iaf_node"].evaluable_outputs["out_port"].curr_value)
             t_ext += dt
 
@@ -144,6 +144,17 @@ def main():
             only_warn_on_fail=True,  # Makes sure test of this doesn't fail on Windows on GitHub Actions
         )
 
+    if "-neuroml" in sys.argv:
+        from modeci_mdf.interfaces.neuroml.exporter import mdf_to_neuroml
+
+        net, sim = mdf_to_neuroml(
+            mod_graph, save_to="%s.nmllite.json" % mod.id, run_duration_sec=100
+        )
+
+        from neuromllite.NetworkGenerator import generate_and_run
+
+        generate_and_run(sim, simulator="jNeuroML")
+
     return mod_graph
 
 

examples/MDF/RNN/regenerate.sh

@@ -6,3 +6,5 @@ python generate_rnn.py -run -nogui
 
 python generate_iaf.py -graph
 python generate_iaf.py -run -nogui
+python generate_iaf.py -neuroml
+pynml LEMS_Simiaf_example.xml -lems-graph

examples/NeuroML/ABCD.json

@@ -1,6 +1,6 @@
 {
     "ABCD": {
-        "version": "NeuroMLlite v0.5.1",
+        "version": "NeuroMLlite v0.5.2",
         "notes": "Example of a simplified network",
         "parameters": {
             "A_initial": 0.1,

examples/NeuroML/ABCD.net.nml

@@ -1,5 +1,5 @@
-<neuroml xmlns="http://www.neuroml.org/schema/neuroml2"  xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2.2.xsd" id="ABCD">
-    <notes>Generated by NeuroMLlite v0.5.1
+<neuroml xmlns="http://www.neuroml.org/schema/neuroml2"  xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2.3.xsd" id="ABCD">
+    <notes>Generated by NeuroMLlite v0.5.2
     Generated network: ABCD
     Generation seed: 1234
     NeuroMLlite parameters:

examples/NeuroML/FN.json

@@ -1,6 +1,6 @@
 {
     "FN": {
-        "version": "NeuroMLlite v0.5.1",
+        "version": "NeuroMLlite v0.5.2",
         "notes": "FitzHugh Nagumo cell model - originally specified in NeuroML/LEMS",
         "parameters": {
             "initial_w": 0.0,

examples/NeuroML/FN.mdf.json

@@ -51,7 +51,7 @@
                             "time_constant_w": {
                                 "value": 12.5
                             },
-                            "threshold": {
+                            "threshold_exc": {
                                 "value": -1.0
                             },
                             "mode": {
@@ -68,7 +68,7 @@
                             },
                             "V": {
                                 "default_initial_value": "initial_v",
-                                "time_derivative": "(a_v*V*V*V + (1+threshold)*b_v*V*V + (-1*threshold)*c_v*V + d_v + e_v*W + f_v*Iext + INPUT) / (time_constant_v*MSEC)"
+                                "time_derivative": "(a_v*V*V*V + (1+threshold_exc)*b_v*V*V + (-1*threshold_exc)*c_v*V + d_v + e_v*W + f_v*Iext + INPUT) / (time_constant_v*MSEC)"
                             },
                             "W": {
                                 "default_initial_value": "initial_w",
@@ -86,7 +86,7 @@
                                 "value": "W"
                             }
                         },
-                        "notes": "Cell: [Cell(notes=None, id='fn', parameters={'initial_w': 'initial_w', 'initial_v': 'initial_v', 'a_v': 'a_v', 'b_v': 'b_v', 'c_v': 'c_v', 'd_v': 'd_v', 'e_v': 'e_v', 'f_v': 'f_v', 'time_constant_v': 'time_constant_v', 'a_w': 'a_w', 'b_w': 'b_w', 'c_w': 'c_w', 'time_constant_w': 'time_constant_w', 'threshold': 'threshold', 'mode': 'mode', 'uncorrelated_activity': 'uncorrelated_activity', 'Iext': 'Iext'}, neuroml2_source_file=None, lems_source_file='FN_Definitions.xml', neuroml2_cell=None, pynn_cell=None, arbor_cell=None, bindsnet_node=None)] is defined in FN_Definitions.xml and in Lems is: Component, id: fn, type: fnCell,\n   parameters: {'initial_w': '0.0', 'initial_v': '-1', 'a_v': '-0.3333333333333333', 'b_v': '0.0', 'c_v': '1.0', 'd_v': '1', 'e_v': '-1.0', 'f_v': '1.0', 'time_constant_v': '1.0', 'a_w': '1.0', 'b_w': '-0.8', 'c_w': '0.7', 'time_constant_w': '12.5', 'threshold': '-1.0', 'mode': '1.0', 'uncorrelated_activity': '0.0', 'Iext': '0'}\n   parent: None\n"
+                        "notes": "Cell: [Cell(notes=None, id='fn', parameters={'initial_w': 'initial_w', 'initial_v': 'initial_v', 'a_v': 'a_v', 'b_v': 'b_v', 'c_v': 'c_v', 'd_v': 'd_v', 'e_v': 'e_v', 'f_v': 'f_v', 'time_constant_v': 'time_constant_v', 'a_w': 'a_w', 'b_w': 'b_w', 'c_w': 'c_w', 'time_constant_w': 'time_constant_w', 'threshold': 'threshold', 'mode': 'mode', 'uncorrelated_activity': 'uncorrelated_activity', 'Iext': 'Iext'}, neuroml2_source_file=None, lems_source_file='FN_Definitions.xml', neuroml2_cell=None, pynn_cell=None, arbor_cell=None, bindsnet_node=None)] is defined in FN_Definitions.xml and in Lems is: Component, id: fn, type: fnCell,\n   parameters: {'initial_w': '0.0', 'initial_v': '-1', 'a_v': '-0.3333333333333333', 'b_v': '0.0', 'c_v': '1.0', 'd_v': '1', 'e_v': '-1.0', 'f_v': '1.0', 'time_constant_v': '1.0', 'a_w': '1.0', 'b_w': '-0.8', 'c_w': '0.7', 'time_constant_w': '12.5', 'threshold_exc': '-1.0', 'mode': '1.0', 'uncorrelated_activity': '0.0', 'Iext': '0'}\n   parent: None\n"
                     }
                 },
                 "edges": {}

examples/NeuroML/FN.mdf.yaml

@@ -36,7 +36,7 @@ FN:
                             value: 0.7
                         time_constant_w:
                             value: 12.5
-                        threshold:
+                        threshold_exc:
                             value: -1.0
                         mode:
                             value: 1.0
@@ -48,9 +48,9 @@ FN:
                             value: 0.001
                         V:
                             default_initial_value: initial_v
-                            time_derivative: (a_v*V*V*V + (1+threshold)*b_v*V*V +
-                                (-1*threshold)*c_v*V + d_v + e_v*W + f_v*Iext + INPUT)
-                                / (time_constant_v*MSEC)
+                            time_derivative: (a_v*V*V*V + (1+threshold_exc)*b_v*V*V
+                                + (-1*threshold_exc)*c_v*V + d_v + e_v*W + f_v*Iext
+                                + INPUT) / (time_constant_v*MSEC)
                         W:
                             default_initial_value: initial_w
                             time_derivative: (mode*a_w*V + b_w*W + c_w + (1-mode)*uncorrelated_activity)
@@ -76,7 +76,7 @@ FN:
                         \ 'initial_v': '-1', 'a_v': '-0.3333333333333333', 'b_v':\
                         \ '0.0', 'c_v': '1.0', 'd_v': '1', 'e_v': '-1.0', 'f_v': '1.0',\
                         \ 'time_constant_v': '1.0', 'a_w': '1.0', 'b_w': '-0.8', 'c_w':\
-                        \ '0.7', 'time_constant_w': '12.5', 'threshold': '-1.0', 'mode':\
-                        \ '1.0', 'uncorrelated_activity': '0.0', 'Iext': '0'}\n  \
-                        \ parent: None\n"
+                        \ '0.7', 'time_constant_w': '12.5', 'threshold_exc': '-1.0',\
+                        \ 'mode': '1.0', 'uncorrelated_activity': '0.0', 'Iext': '0'}\n\
+                        \   parent: None\n"
             edges: {}

examples/NeuroML/FN.net.nml

@@ -1,5 +1,5 @@
-<neuroml xmlns="http://www.neuroml.org/schema/neuroml2"  xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2.2.xsd" id="FN">
-    <notes>Generated by NeuroMLlite v0.5.1
+<neuroml xmlns="http://www.neuroml.org/schema/neuroml2"  xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.neuroml.org/schema/neuroml2 https://raw.github.com/NeuroML/NeuroML2/development/Schemas/NeuroML2/NeuroML_v2.3.xsd" id="FN">
+    <notes>Generated by NeuroMLlite v0.5.2
     Generated network: FN
     Generation seed: 1234
     NeuroMLlite parameters:

examples/NeuroML/FN_Definitions.xml

@@ -16,7 +16,7 @@
         <Parameter name="b_w" dimension="none"/>
         <Parameter name="c_w" dimension="none"/>
         <Parameter name="time_constant_w" dimension="none"/>
-        <Parameter name="threshold" dimension="none"/>
+        <Parameter name="threshold_exc" dimension="none" description="Note: renamed temporarily from threshold to allow testing in NEURON, where threshold is reserved word"/>
         <Parameter name="mode" dimension="none"/>
         <Parameter name="uncorrelated_activity" dimension="none"/>
         <!-- Initial Conditions -->
@@ -46,7 +46,7 @@
 
             <DerivedVariable name="INPUT" dimension="none" exposure="INPUT" select="synapses[*]/I" reduce="add" />
 
-            <TimeDerivative variable="V" value="(a_v*V*V*V + (1+threshold)*b_v*V*V + (-1*threshold)*c_v*V + d_v + e_v*W + f_v*Iext + INPUT) / (time_constant_v*MSEC)"/>
+            <TimeDerivative variable="V" value="(a_v*V*V*V + (1+threshold_exc)*b_v*V*V + (-1*threshold_exc)*c_v*V + d_v + e_v*W + f_v*Iext + INPUT) / (time_constant_v*MSEC)"/>
             <TimeDerivative variable="W" value="(mode*a_w*V + b_w*W + c_w + (1-mode)*uncorrelated_activity) / (time_constant_w*MSEC)"/>
 
             <OnStart>
@@ -64,14 +64,14 @@
     <fnCell id="fn0" initial_w="-0.62" initial_v="-1.2" a_v="-0.3333333333333333" b_v="0.0"
             c_v="1.0" d_v="0" e_v="-1.0" f_v="1.0"
             time_constant_v="1.0" a_w="1.0" b_w="-0.8" c_w="0.7"
-            time_constant_w="12.5" threshold="-1.0"
+            time_constant_w="12.5" threshold_exc="-1.0"
             mode="1.0" uncorrelated_activity="0.0"
             Iext="0" />
 
     <fnCell id="fn" initial_w="0.0" initial_v="-1" a_v="-0.3333333333333333" b_v="0.0"
             c_v="1.0" d_v="1" e_v="-1.0" f_v="1.0"
             time_constant_v="1.0" a_w="1.0" b_w="-0.8" c_w="0.7"
-            time_constant_w="12.5" threshold="-1.0"
+            time_constant_w="12.5" threshold_exc="-1.0"
             mode="1.0" uncorrelated_activity="0.0"
             Iext="0" />