PR: list recordables

.github/workflows/ci.yml

@@ -43,13 +43,15 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install -r requirements-dev.txt
+        pip install pytest
         pip install .
 
-    - name: Lint with flake8
-      run: |
-        pip install flake8
-        flake8 . --count --exit-zero --show-source --max-line-length=127 --statistics
     - name: Run tests
       run: |
+        pytest .
         pynml -h
         ./test-ghactions.sh
+    - name: Lint with flake8
+      run: |
+        pip install flake8
+        flake8 . --count --exit-zero --show-source --max-line-length=127 --statistics

pyneuroml/__init__.py

@@ -7,9 +7,9 @@
 # Define a logger for the package
 logging.basicConfig(format="pyNeuroML >>> %(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.WARN)
 logger = logging.getLogger(__name__)
-logger.setLevel(logging.WARN)
+logger.setLevel(logging.INFO)
 ch = logging.StreamHandler()
-ch.setLevel(logging.DEBUG)
+ch.setLevel(logging.INFO)
 formatter = logging.Formatter('pyNeuroML >>> %(name)s - %(levelname)s - %(message)s')
 ch.setFormatter(formatter)
 logger.addHandler(ch)

pyneuroml/pynml.py

@@ -13,6 +13,7 @@
 from __future__ import print_function
 from __future__ import unicode_literals
 import os
+import shutil
 import sys
 import subprocess
 import math
@@ -25,6 +26,7 @@
 from lxml import etree
 import pprint
 import logging
+import tempfile
 
 try:
     import typing
@@ -33,6 +35,7 @@
 
 import matplotlib
 import lems.model.model as lems_model
+from lems.model.fundamental import Include
 from lems.parser.LEMS import LEMSFileParser
 
 from pyneuroml import __version__
@@ -51,6 +54,7 @@
 lems_model_with_units = None
 
 logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
 
 
 def parse_arguments():
@@ -317,6 +321,129 @@ def get_lems_model_with_units():
     return lems_model_with_units
 
 
+def extract_lems_definition_files(path=None):
+    # type: (typing.Union[str, None, tempfile.TemporaryDirectory[typing.Any]]) -> str
+    """Extract the NeuroML2 LEMS definition files to a directory and return its path.
+
+    This function can be used by other LEMS related functions that need to
+    include the NeuroML2 LEMS definitions.
+
+    If a path is provided, the folder is created relative to the current
+    working directory.
+
+    If no path is provided, for repeated usage for example, the files are
+    extracted to a temporary directory using Python's
+    `tempfile.mkdtemp
+    <https://docs.python.org/3/library/tempfile.html>`__ function.
+
+    Note: in both cases, it is the user's responsibility to remove the created
+    directory when it is no longer required, for example using.  the
+    `shutil.rmtree()` Python function.
+
+    :param path: path of directory relative to current working directory to extract to, or None
+    :type path: str or None
+    :returns: directory path
+    """
+    jar_path = get_path_to_jnml_jar()
+    logger.debug("Loading standard NeuroML2 dimension/unit definitions from %s" % jar_path)
+    jar = zipfile.ZipFile(jar_path, 'r')
+    namelist = [x for x in jar.namelist() if ".xml" in x and "NeuroML2CoreTypes" in x]
+    logger.debug("NeuroML LEMS definition files in jar are: {}".format(namelist))
+
+    # If a string is provided, ensure that it is relative to cwd
+    if path and isinstance(path, str) and len(path) > 0:
+        path = "./" + path
+        try:
+            os.makedirs(path)
+        except FileExistsError:
+            logger.warn("{} already exists. Any NeuroML LEMS files in it will be overwritten".format(path))
+        except OSError as err:
+            logger.critical(err)
+            sys.exit(-1)
+    else:
+        path = tempfile.mkdtemp()
+
+    logger.debug("Created directory: " + path)
+    jar.extractall(path, namelist)
+    path = path + "/NeuroML2CoreTypes/"
+    logger.info("NeuroML LEMS definition files extracted to: {}".format(path))
+    return path
+
+
+def list_exposures(nml_doc_fn, substring=None):
+    # type: (str, str) -> typing.Union[typing.Dict[lems_model.component.Component, typing.List[lems_model.component.Exposure]], None]
+    """List exposures in a NeuroML model document file.
+
+    This wraps around `lems.model.list_exposures` to list the exposures in a
+    NeuroML2 model. The only difference between the two is that the
+    `lems.model.list_exposures` function is not aware of the NeuroML2 component
+    types (since it's for any LEMS models in general), but this one is.
+
+    :param nml_doc_fn: NeuroML2 file to list exposures for
+    :type nml_doc: str
+    :param substring: substring to match for in component names
+    :type substring: str
+    :returns: dictionary of components and their exposures.
+
+    The returned dictionary is of the form:
+
+    ..
+        {
+            "component": ["exp1", "exp2"]
+        }
+
+    """
+    return get_standalone_lems_model(nml_doc_fn).list_exposures(substring)
+
+
+def list_recording_paths(nml_doc_fn, substring):
+    # type: (str, str) -> typing.List[str]
+    """List the recording path strings for exposures.
+
+    This wraps around `lems.model.list_recording_paths` to list the recording
+    paths in the given NeuroML2 model. The only difference between the two is
+    that the `lems.model.list_recording_paths` function is not aware of the
+    NeuroML2 component types (since it's for any LEMS models in general), but
+    this one is.
+
+    :param nml_doc_fn: NeuroML2 file to list recording paths for
+    :type nml_doc: str
+    :param substring: substring to match component ids against
+    :type substring: str
+    :returns: list of recording paths
+
+    """
+    return get_standalone_lems_model(nml_doc_fn).list_recording_paths(substring)
+
+
+def get_standalone_lems_model(nml_doc_fn):
+    # type: (str) -> lems_model.Model
+    """Get the complete, expanded LEMS model.
+
+    This function takes a NeuroML2 file, includes all the NeuroML2 LEMS
+    definitions in it and generates the complete, standalone LEMS model.
+
+    :param nml_doc_fn: name of NeuroML file to expand
+    :type nml_doc_fn: str
+    :returns: complete LEMS model
+    """
+    new_lems_model = lems_model.Model(include_includes=True,
+                                      fail_on_missing_includes=True)
+    if logger.level < logging.INFO:
+        new_lems_model.debug = True
+    else:
+        new_lems_model.debug = False
+    neuroml2_defs_dir = extract_lems_definition_files()
+    filelist = os.listdir(neuroml2_defs_dir)
+    # Remove the temporary directory
+    for nml_lems_f in filelist:
+        new_lems_model.include_file(neuroml2_defs_dir + nml_lems_f,
+                                    [neuroml2_defs_dir])
+    new_lems_model.include_file(nml_doc_fn, [""])
+    shutil.rmtree(neuroml2_defs_dir[:-1 * len("NeuroML2CoreTypes/")])
+    return new_lems_model
+
+
 def split_nml2_quantity(nml2_quantity):
     # type: (str) -> typing.Tuple[float, str]
     """Split a NeuroML 2 quantity into its magnitude and units
@@ -340,7 +467,7 @@ def split_nml2_quantity(nml2_quantity):
 
 
 def get_value_in_si(nml2_quantity):
-    # type: (str) -> float
+    # type: (str) -> typing.Union[float, None]
     """Get value of a NeuroML2 quantity in SI units
 
     :param nml2_quantity: NeuroML2 quantity to convert

tests/izhikevich_test_file.nml

@@ -0,0 +1,9 @@
+<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="IzhSingleNeuron">
+    <izhikevich2007Cell id="izh2007RS0" C="100pF" v0="-60mV" k="0.7nS_per_mV" vr="-60mV" vt="-40mV" vpeak="35mV" a="0.03per_ms" b="-2nS" c="-50.0mV" d="100pA"/>
+    <pulseGenerator id="pulseGen_0" delay="0ms" duration="1000ms" amplitude="0.07 nA"/>
+    <network id="IzhNet">
+        <population id="IzhPop0" component="izh2007RS0" size="1"/>
+        <explicitInput target="IzhPop0[0]" input="pulseGen_0"/>
+    </network>
+</neuroml>
+

tests/test_pynml.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+"""
+Unit tests for pynml.py
+
+File: test/test_pynml.py
+
+Copyright 2021 NeuroML contributors
+Author: Ankur Sinha <sanjay DOT ankur AT gmail DOT com>
+"""
+
+import unittest
+import os
+import shutil
+import logging
+
+from pyneuroml.pynml import (extract_lems_definition_files, list_exposures,
+                             list_recording_paths)
+
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+
+
+class TestJarUtils(unittest.TestCase):
+
+    """Test jNeuroML jar related functions"""
+
+    def test_lems_def_files_extraction(self):
+        """Test extraction of NeuroML2 LEMS files from jar."""
+        filelist = ["Cells.xml",
+                    "Channels.xml",
+                    "Inputs.xml",
+                    "Networks.xml",
+                    "NeuroML2CoreTypes.xml",
+                    "NeuroMLCoreCompTypes.xml",
+                    "NeuroMLCoreDimensions.xml",
+                    "PyNN.xml",
+                    "Simulation.xml",
+                    "Synapses.xml"]
+
+        extraction_dir = extract_lems_definition_files()
+        newfilelist = os.listdir(extraction_dir)
+        shutil.rmtree(extraction_dir[:-1 * len("NeuroML2CoreTypes/")])
+        assert(sorted(filelist) == sorted(newfilelist))
+
+
+class TestHelperUtils(unittest.TestCase):
+
+    """Test helper utilities."""
+
+    def test_exposure_listing(self):
+        """Test listing of exposures in NeuroML documents."""
+        exps = list_exposures("tests/izhikevich_test_file.nml", "iz")
+        ctypes = {}
+        for key, val in exps.items():
+            ctypes[key.type] = val
+
+        self.assertTrue("izhikevich2007Cell" in ctypes.keys())
+        expnames = []
+        for exp in ctypes["izhikevich2007Cell"]:
+            expnames.append(exp.name)
+        # https://docs.neuroml.org/Userdocs/Schemas/Cells.html#schema-izhikevich2007cell
+        self.assertTrue("u" in expnames)
+        self.assertTrue("v" in expnames)
+        self.assertTrue("iMemb" in expnames)
+        self.assertTrue("iSyn" in expnames)
+
+    def test_recording_path_listing(self):
+        """Test listing of recording paths in NeuroML documents."""
+        paths = list_recording_paths("tests/izhikevich_test_file.nml", "iz")
+        self.assertTrue("izh2007RS0/u" in paths)
+        self.assertTrue("izh2007RS0/v" in paths)
+
+
+if __name__ == "__main__":
+    unittest.main()