Setting a property tag for a population of type population (not populationlist) causes jlems to throw an error

[sanjayankur31]

Python script:

#!/usr/bin/env python3
"""
Create a simple network with two populations.
"""

import random
import numpy as np

from neuroml.utils import component_factory
from pyneuroml import pynml
from pyneuroml.lems import LEMSSimulation
import neuroml.writers as writers


nml_doc = component_factory("NeuroMLDocument", id="IzNet")
iz0 = nml_doc.add(
    "Izhikevich2007Cell",
    id="iz2007RS0",
    v0="-60mV",
    C="100pF",
    k="0.7nS_per_mV",
    vr="-60mV",
    vt="-40mV",
    vpeak="35mV",
    a="0.03per_ms",
    b="-2nS",
    c="-50.0mV",
    d="100pA",
)

# Inspect the component, also show all members:
iz0.info(True)

# Create a component of type ExpOneSynapse, and add it to the document
syn0 = nml_doc.add(
    "ExpOneSynapse", id="syn0", gbase="65nS", erev="0mV", tau_decay="3ms"
)
# Check what we have so far:
nml_doc.info(True)
# Also try:
print(nml_doc.summary())

# create the network: turned of validation because we will add populations next
net = nml_doc.add("Network", id="IzNet", validate=False)

# create the first population
size0 = 5
pop0 = component_factory("Population", id="IzPop0", component=iz0.id, size=size0)
# Set optional color property. Note: used later when generating plots
pop0.add("Property", tag="color", value="0 0 .8")
net.add(pop0)

# create the second population
size1 = 5
pop1 = component_factory("Population", id="IzPop1", component=iz0.id, size=size1)
pop1.add("Property", tag="color", value=".8 0 0")
net.add(pop1)

# network should be valid now that it contains populations
net.validate()

# create a projection from one population to another
proj = net.add(
    "Projection",
    id="proj",
    presynaptic_population=pop0.id,
    postsynaptic_population=pop1.id,
    synapse=syn0.id,
)

# We do two things in the loop:
# - add pulse generator inputs to population 1 to make neurons spike
# - create synapses between the two populations with a particular probability
random.seed(123)
prob_connection = 0.8
count = 0
for pre in range(0, size0):
    # pulse generator as explicit stimulus
    pg = nml_doc.add(
        "PulseGenerator",
        id="pg_%i" % pre,
        delay="0ms",
        duration="10000ms",
        amplitude="%f nA" % (0.1 + 0.1 * random.random()),
    )

    exp_input = net.add(
        "ExplicitInput", target="%s[%i]" % (pop0.id, pre), input=pg.id
    )

    # synapses between populations
    for post in range(0, size1):
        if random.random() <= prob_connection:
            syn = proj.add(
                "Connection",
                id=count,
                pre_cell_id="../%s[%i]" % (pop0.id, pre),
                post_cell_id="../%s[%i]" % (pop1.id, post),
            )
            count += 1

nml_doc.info(True)
print(nml_doc.summary())

# write model to file and validate
nml_file = "izhikevich2007_network.nml"
writers.NeuroMLWriter.write(nml_doc, nml_file)

print("Written network file to: " + nml_file)
pynml.validate_neuroml2(nml_file)

# Create simulation, and record data
simulation_id = "example_izhikevich2007network_sim"
simulation = LEMSSimulation(
    sim_id=simulation_id, duration=1000, dt=0.1, simulation_seed=123
)
simulation.assign_simulation_target(net.id)
simulation.include_neuroml2_file(nml_file)

simulation.create_event_output_file(
    "pop0", "%s.0.spikes.dat" % simulation_id, format="ID_TIME"
)
for pre in range(0, size0):
    simulation.add_selection_to_event_output_file(
        "pop0", pre, "IzPop0[{}]".format(pre), "spike"
    )

simulation.create_event_output_file(
    "pop1", "%s.1.spikes.dat" % simulation_id, format="ID_TIME"
)
for pre in range(0, size1):
    simulation.add_selection_to_event_output_file(
        "pop1", pre, "IzPop1[{}]".format(pre), "spike"
    )

lems_simulation_file = simulation.save_to_file()

# Run the simulation
pynml.run_lems_with_jneuroml(
    lems_simulation_file, max_memory="2G", nogui=True, plot=False
)

# Load the data from the file and plot the spike times
# using the pynml generate_plot utility function.
data_array_0 = np.loadtxt("%s.0.spikes.dat" % simulation_id)
data_array_1 = np.loadtxt("%s.1.spikes.dat" % simulation_id)
times_0 = data_array_0[:, 1]
times_1 = data_array_1[:, 1]
ids_0 = data_array_0[:, 0]
ids_1 = [id + size0 for id in data_array_1[:, 0]]
pynml.generate_plot(
    [times_0, times_1],
    [ids_0, ids_1],
    "Spike times",
    show_plot_already=False,
    save_figure_to="%s-spikes.png" % simulation_id,
    xaxis="time (s)",
    yaxis="cell ID",
    colors=["b", "r"],
    linewidths=["0", "0"],
    markers=[".", "."],
)

Output (failure):

pyNeuroML >>> INFO - Loading NeuroML2 file: /home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/source/Userdocs/NML2_examples/izhikevich2007_network.nml
pyNeuroML >>> INFO - Loading LEMS file: LEMS_example_izhikevich2007network_sim.xml and running with jNeuroML
pyNeuroML >>> INFO - Executing: (java -Xmx2G  -Djava.awt.headless=true -jar  "/home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/.venv/lib/python3.10/site-packages/pyneuroml/lib/jNeuroML-0.12.0-jar-with-dependencies.jar"  "LEMS_example_izhikevich2007network_sim.xml"  -nogui -I '') in directory: .
pyNeuroML >>> CRITICAL - *** Problem running command:
       Command 'java -Xmx2G  -Djava.awt.headless=true -jar  "/home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/.venv/lib/python3.10/site-packages/pyneuroml/lib/jNeuroML-0.12.0-jar-with-dependencies.jar"  "LEMS_example_izhikevich2007network_sim.xml"  -nogui -I ''' returned non-zero exit status 1.
pyNeuroML >>> CRITICAL -  jNeuroML >>   jNeuroML v0.12.0
 jNeuroML >>  Loading: /home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/source/Userdocs/NML2_examples/LEMS_example_izhikevich2007network_sim.xml with jLEMS, NO GUI mode...
 jNeuroML >>  org.lemsml.jlems.core.run.ConnectionError: Can't get predicate [0] from IzPop0[population], original path: ../IzPop0[0]
 jNeuroML >>  component has singeMI=false
 jNeuroML >>    at org.lemsml.jlems.core.sim.RunnableAccessor.getRelativeStateInstance(RunnableAccessor.java:140)
 jNeuroML >>    at org.lemsml.jlems.core.run.WithBuilder.postBuild(WithBuilder.java:37)
 jNeuroML >>    at org.lemsml.jlems.core.run.Builder.postBuild(Builder.java:25)
 jNeuroML >>    at org.lemsml.jlems.core.run.StateType.build(StateType.java:340)
 jNeuroML >>    at org.lemsml.jlems.core.run.StateInstance.checkBuilt(StateInstance.java:1187)
 jNeuroML >>    at org.lemsml.jlems.core.run.StateInstance.checkBuilt(StateInstance.java:1199)
 jNeuroML >>    at org.lemsml.jlems.core.run.StateInstance.checkBuilt(StateInstance.java:1199)
 jNeuroML >>    at org.lemsml.jlems.core.type.Lems.build(Lems.java:359)
 jNeuroML >>    at org.lemsml.jlems.core.sim.Sim.run(Sim.java:232)
 jNeuroML >>    at org.lemsml.jlems.core.sim.Sim.run(Sim.java:154)
 jNeuroML >>    at org.lemsml.jlems.core.sim.Sim.run(Sim.java:145)
 jNeuroML >>    at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:527)
 jNeuroML >>    at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)
 jNeuroML >>    at org.neuroml.JNeuroML.main(JNeuroML.java:606)
 jNeuroML >>  INFO Oct 19,2022 13:17  (INFO) Loading LEMS file from: /home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/source/Userdocs/NML2_examples/LEMS_example_izhikevich2007network_sim.xml
 jNeuroML >>  INFO Oct 19,2022 13:17  (INFO) Reading from: /home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/source/Userdocs/NML2_examples/LEMS_example_izhikevich2007network_sim.xml
 jNeuroML >>
pyNeuroML >>> ERROR - execute_command_in_dir returned with output:  jNeuroML v0.12.0
Loading: /home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/source/Userdocs/NML2_examples/LEMS_example_izhikevich2007network_sim.xml with jLEMS, NO GUI mode...
org.lemsml.jlems.core.run.ConnectionError: Can't get predicate [0] from IzPop0[population], original path: ../IzPop0[0]
component has singeMI=false
        at org.lemsml.jlems.core.sim.RunnableAccessor.getRelativeStateInstance(RunnableAccessor.java:140)
        at org.lemsml.jlems.core.run.WithBuilder.postBuild(WithBuilder.java:37)
        at org.lemsml.jlems.core.run.Builder.postBuild(Builder.java:25)
        at org.lemsml.jlems.core.run.StateType.build(StateType.java:340)
        at org.lemsml.jlems.core.run.StateInstance.checkBuilt(StateInstance.java:1187)
        at org.lemsml.jlems.core.run.StateInstance.checkBuilt(StateInstance.java:1199)
        at org.lemsml.jlems.core.run.StateInstance.checkBuilt(StateInstance.java:1199)
        at org.lemsml.jlems.core.type.Lems.build(Lems.java:359)
        at org.lemsml.jlems.core.sim.Sim.run(Sim.java:232)
        at org.lemsml.jlems.core.sim.Sim.run(Sim.java:154)
        at org.lemsml.jlems.core.sim.Sim.run(Sim.java:145)
        at org.neuroml.export.utils.Utils.loadLemsFile(Utils.java:527)
        at org.neuroml.export.utils.Utils.runLemsFile(Utils.java:493)
        at org.neuroml.JNeuroML.main(JNeuroML.java:606)
INFO Oct 19,2022 13:17  (INFO) Loading LEMS file from: /home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/source/Userdocs/NML2_examples/LEMS_example_izhikevich2007network_sim.xml
INFO Oct 19,2022 13:17  (INFO) Reading from: /home/asinha/Documents/02_Code/00_mine/NeuroML/documentation/source/Userdocs/NML2_examples/LEMS_example_izhikevich2007network_sim.xml

It runs fine if one uses the NEURON simulation backend. To make it run in jneuroml/jlems, one needs to remove the property tag for the two populations.

Analysis (short!)

This is where the error message is generated:

https://github.com/LEMS/jLEMS/blob/master/src/main/java/org/lemsml/jlems/core/sim/RunnableAccessor.java#L139

The addition of the property tag to the population makes seems to set singleAMI to false. I think this is being his is being set here in countMIs on the basis of the size of multiA:

https://github.com/LEMS/jLEMS/blob/master/src/main/java/org/lemsml/jlems/core/run/StateInstance.java#L788