Updated neuroml2 imports with error messages (#472)

* Fixed showmsg() bug in pybind11 based version.

The newer implementation of showmsg() shows the outgoing messages with
misdirected arrows. Fixed now.

* Added newer version of pybind11

* Swapped clocks for channel and compartment to fix  #467

* This actually fixes scheduling for channels and compartments #467

The previous commit only updated the docs. This one modifies the
actual tick assignments.
Now electrical compartments are scheduled on ticks 2 and 3 and
channels (all derived from ChanBase) on 4.

* Minor fix for compiler warning on loop var creating copy from const

* Removed CMake generated compile command.

the compile command file is generated by cmake in each build
environment and should not be part of the repo.

* Added error message at neuroml import error, corrected imports.

* Updated neuroml2 reader. Yet to debug Granule_98 model.

* Updated neuroml2 reader to handle spherical compartment for CaPool

Also created separate test script for Granule98 model.

* Fixed deprecated imp module use in rdesigneur.

- rdesigneur used imp module, now replaced by importlib.
- commented out debug logs from neuroml2 reader
- TODO: tests/support has files which conflict with tests/core. These
  seem to be old test code which may better be removed.

* Updated test script for Granule98 model

---------

Co-authored-by: HarshaRani <[email protected]>

Author: subhacom

python/moose/__init__.py

@@ -740,7 +740,7 @@ def doc(arg, paged=True):
 
     """
     text = _moose.__generatedoc__(arg)
-    if pydoc.page:
+    if pydoc.pager:
         pydoc.pager(text) 
     else:
         print(text)

python/moose/neuroml2/reader.py

@@ -13,16 +13,26 @@
 
 import os
 import math
+import logging
 import numpy as np
 import moose
 
-import logging
+
 logger_ = logging.getLogger('moose.nml2')
 
-import neuroml         as nml
-import pyneuroml.pynml as pynml
+
+nml_not_available_msg = ''
+
+try:
+    import neuroml as nml
+    import pyneuroml.pynml as pynml
+except ImportError as error:
+    raise ImportError(f'Could not import neuroml/pyneuroml. Please make sure you have pyneuroml installed (`pip install pyneuroml`)') from error
+    
+    
 from moose.neuroml2.units import SI
 
+
 def _write_flattened_nml( doc, outfile ):
     """_write_flattened_nml
     Concat all NML2 read by moose and generate one flattened NML file.
@@ -68,14 +78,15 @@ def _unique( ls ):
 
 def _isConcDep(ct):
     """_isConcDep
-    Check if componet is dependant on concentration. Most HHGates are
-    dependant on voltage.
+    Check if componet is dependent on concentration. Most HHGates are
+    dependent on voltage.
 
     :param ct: ComponentType
     :type ct: nml.ComponentType
 
     :return: True if Component is depenant on conc, False otherwise.
     """
+    # logger_.debug(f"{'#' * 10} EXTENDS {ct.extends}")
     if 'ConcDep' in ct.extends:
         return True
     return False
@@ -209,6 +220,7 @@ def read(self, filename, symmetric=True):
         self.importInputs(self.doc)
 
         for cell in self.doc.cells:
+            # logger_.debug(f"{'%' * 10} Creating cell prototype {cell}")
             self.createCellPrototype(cell, symmetric=symmetric)
 
         if len(self.doc.networks)>=1:
@@ -427,10 +439,15 @@ def copySpecies(self, species, compartment):
             raise RuntimeError(msg)
         pool_id = moose.copy(proto_pool, compartment, species.id)
         pool = moose.element(pool_id)
-        pool.B = pool.B / (np.pi * compartment.length * (
+        # print('&' * 10, compartment.path, compartment.length, compartment.diameter, pool.thick)
+        if compartment.length <= 0:
+            vol = 4 * np.pi * (0.5 * compartment.diameter**3 - (0.5 * compartment.diameter - pool.thick)**3) / 3
+        else:
+            vol = (np.pi * compartment.length * (
             0.5 * compartment.diameter + pool.thick) *
             (0.5 * compartment.diameter - pool.thick)
             )
+        pool.B = pool.B / vol
         return pool
 
     def importAxialResistance(self, nmlcell, intracellularProperties):
@@ -475,18 +492,20 @@ def calculateRateFn(self, ratefn, vmin, vmax, tablen=3000, vShift='0mV'):
             if ratefn.type != ct.name:
                 continue
 
-            logger_.info("Using %s to evaluate rate"%ct.name)
+            logger_.info(f"Using %s to evaluate rate"%ct.name)
             rate = []
             for v in tab:
-                # Note: MOOSE HHGate are either voltage of concentration
-                # dependant. Here we figure out if nml description of gate is
-                # concentration dependant or note.
+                # Note: MOOSE HHGate are voltage and/or concentration
+                # dependent. Here we figure out if nml description of gate is
+                # concentration dependent or not.
+                # logger_.debug(f"{'#' * 5} {_isConcDep(ct)}")
                 if _isConcDep(ct):
-                    # Concentration dependant. Concentration can't be negative.
+                    # Concentration dependent. Concentration can't be negative.
                     # Find a suitable CaConc from the /library. Currently on Ca
-                    # dependant channels are allowed.
+                    # dependent channels are allowed.
                     caConcName = _findCaConcVariableName()
-                    req_vars  = {caConcName:'%g'%max(0,v),'vShift':vShift,'temperature':self._getTemperature()}
+                    req_vars  = {'v': '0.0V', 'caConc':f'{max(1e-11,v):g}', caConcName:f'{max(1e-11,v):g}','vShift':vShift,'temperature':self._getTemperature()}
+                    # logger_.debug(f"{'A' * 30} {req_vars}")
                 else:
                     req_vars  = {'v':'%sV'%v,'vShift':vShift,'temperature':self._getTemperature()}
                 req_vars.update( self._variables )
@@ -669,6 +688,7 @@ def importInputs(self, doc):
             pg.firstWidth = SI(pg_nml.duration)
             pg.firstLevel = SI(pg_nml.amplitude)
             pg.secondDelay = 1e9
+            logger_.debug(f'{"$" * 10} Created input {epath}')
 
 
     def importIonChannels(self, doc, vmin=-150e-3, vmax=100e-3, vdivs=5000):
@@ -707,6 +727,6 @@ def createDecayingPoolConcentrationModel(self, concModel):
                       # shell and d is thickness - must divide by
                       # shell volume when copying
         self.proto_pools[concModel.id] = ca
-        self.nml_concs_to_moose[concModel.id] = ca
+        self.nml_conc_to_moose[concModel.id] = ca
         self.moose_to_nml[ca] = concModel
         logger_.debug('Created moose element: %s for nml conc %s' % (ca.path, concModel.id))

python/moose/neuroml2/test_granule98.py

@@ -0,0 +1,65 @@
+# test_granule98.py --- 
+# 
+# Filename: test_granule98.py
+# Description: 
+# Author: Subhasis Ray
+# Created: Mon Apr  8 21:41:22 2024 (+0530)
+# Last-Updated: Wed Apr 10 19:59:48 2024 (+0530)
+#           By: Subhasis Ray
+# 
+
+# Code:
+"""Test code for the Granule cell model
+
+"""
+import os
+import numpy as np
+# import unittest
+import logging
+
+
+LOGLEVEL = os.environ.get('LOGLEVEL', 'INFO')
+logging.basicConfig(level=LOGLEVEL)
+
+
+import moose
+from moose.neuroml2.reader import NML2Reader
+
+
+def run(nogui=True):
+    reader = NML2Reader()
+    filename = 'test_files/Granule_98/GranuleCell.net.nml'    
+    reader.read(filename)
+    soma = reader.getComp(reader.doc.networks[0].populations[0].id, 0, 0)
+    data = moose.Neutral('/data')
+    pg = reader.getInput('Gran_10pA')
+    inj = moose.Table(f'{data.path}/pulse')
+    moose.connect(inj, 'requestOut', pg, 'getOutputValue')
+    vm = moose.Table(f'{data.path}/Vm')
+    moose.connect(vm, 'requestOut', soma, 'getVm')
+    print('A' * 10, soma)
+
+    simtime = 300e-3
+    moose.reinit()
+    moose.start(simtime)
+    
+    t = np.arange(len(vm.vector)) * vm.dt
+    print('%' * 10, len(vm.vector), len(inj.vector))
+    results = np.array([t, vm.vector, inj.vector], dtype=[('time', float), ('Vm', float), ('Im', float)])
+    fname = 'Granule_98.npy'
+    np.save(fname, results)
+    print(f'Saved results in {fname}')
+    if not nogui:
+        import matplotlib.pyplot as plt
+        fig, axes = plt.subplots(nrows=2, sharex='all')
+        axes[0].plot(t, vm.vector, label='Vm')
+        axes[1].plot(t, inj.vector, label='Im')
+        plt.legend()
+        plt.show()
+        
+    
+run(nogui=False)
+
+
+# 
+# test_granule98.py ends here

python/moose/neuroml2/test_reader.py

@@ -7,9 +7,9 @@
 # Maintainer:
 # Created: Wed Jul 24 16:02:21 2013 (+0530)
 # Version:
-# Last-Updated: Sun Apr 17 16:13:01 2016 (-0400)
-#           By: subha
-#     Update #: 112
+# Last-Updated: Mon Apr  8 21:41:42 2024 (+0530)
+#           By: Subhasis Ray
+#     Update #: 125
 # URL:
 # Keywords:
 # Compatibility:
@@ -46,13 +46,18 @@
 
 # Code:
 
-from __future__ import print_function
+import os
 import unittest
 import numpy as np
+import logging
+
+
+LOGLEVEL = os.environ.get('LOGLEVEL', 'INFO')
+logging.basicConfig(level=LOGLEVEL)
+
+
 import moose
-import neuroml as nml
-from reader import NML2Reader
-import os
+from moose.neuroml2.reader import NML2Reader
 
 class TestFullCell(unittest.TestCase):
     def setUp(self):
@@ -125,24 +130,6 @@ def test_HHChannels(self):
         self.assertTrue(len(chans) < 3) # Only soma and dendrite2 have the channels
         self.assertAlmostEqual(soma_na.Gbar, 120e-2 * self.soma.diameter * self.soma.diameter * np.pi, places=6)
 
-'''
-Not yet working in NML2...
-
-class TestGran98(unittest.TestCase):
-    def setUp(self):
-        self.reader = NML2Reader()
-        self.lib = moose.Neutral('/library')
-        self.filename = 'test_files/Granule_98/Granule_98.nml'
-        self.reader.read(self.filename)
-        for ncell in self.reader.nml_to_moose:
-            if isinstance(ncell, nml.Cell):
-                self.ncell = ncell
-                break
-        self.mcell = moose.element(moose.wildcardFind('/##[ISA=Cell]')[0])
-
-    def test_CaPool(self):
-        pass
-'''
 
 if __name__ == '__main__':
     unittest.main()

python/moose/neuroml2/test_reader2.py

@@ -43,11 +43,19 @@
 # Code:
 
 from __future__ import print_function
+
+import os
 import unittest
+import logging
+
+
+LOGLEVEL = os.environ.get('LOGLEVEL', 'INFO')
+logging.basicConfig(level=LOGLEVEL)
+
+
 import moose
-from reader import NML2Reader
-import neuroml as nml
-import os
+from moose.neuroml2.reader import NML2Reader
+
 
 class TestPassiveCell(unittest.TestCase):
     def setUp(self):

python/rdesigneur/rdesigneur.py

@@ -16,10 +16,8 @@
 ## latter in the former, including mapping entities like calcium and
 ## channel conductances, between them.
 ##########################################################################
-from __future__ import print_function, absolute_import, division
 
-# FIXME: Deprecated since 3.4
-import imp
+import importlib
 import os
 import moose
 import numpy as np
@@ -323,14 +321,18 @@ def buildProtoFromFunction( self, func, protoName ):
             modulePath = os.path.realpath(os.path.join(*pathTokens[:-1]))
             moduleName = pathTokens[-1]
             funcName = func[modPos+1:bracePos]
-            moduleFile, pathName, description = imp.find_module(moduleName, [modulePath])
+            # moduleFile, pathName, description = imp.find_module(moduleName, [modulePath])
+            # `imp` has been deprecated and throws error in Python 3.12
+            spec = importlib.machinery.PathFinder().find_spec(moduleName, [modulePath])
             try:
-                module = imp.load_module(moduleName, moduleFile, pathName, description)
+                # module = imp.load_module(moduleName, moduleFile, pathName, description)
+                module = importlib.util.module_from_spec(spec)
                 funcObj = getattr(module, funcName)
                 funcObj(protoName)
                 return True
             finally:
-                moduleFile.close()
+              pass
+                # moduleFile.close()
             return False
         if not func[0:bracePos] in globals():
             raise BuildError( \