Merge pull request #262 from NeuroML/feat/sim-meta

Expose `meta` in LEMSSimulation

pyneuroml/lems/LEMSSimulation.py

@@ -34,11 +34,12 @@ def __init__(
         sim_id: str,
         duration: float,
         dt: float,
-        target: str = None,
+        target: typing.Optional[str] = None,
         comment: str = "\n\n        This LEMS file has been automatically generated using PyNeuroML v%s (libNeuroML v%s)\n\n    "
         % (pynml_ver, libnml_ver),
         lems_file_generate_seed: typing.Any = None,
         simulation_seed: int = 12345,
+        meta: typing.Optional[typing.Dict[str, str]] = None,
     ) -> None:
         """Init a new LEMSSimulation object.
 
@@ -62,6 +63,18 @@ def __init__(
         :type lems_file_generate_seed:
         :param simulation_seed: simulation seed to set to
         :type simulation_seed: int
+        :param meta: dictionary to set Meta options.
+
+            Currently, only supported for the Neuron simulator to use the CVODE
+            solver. A dict needs to be passed:
+            {
+                "for": "neuron",
+                "method": "cvode",
+                "abs_tolerance" = "0.001",
+                "rel_tolerance": "0.001"
+            }
+
+        :type meta: dict
         """
 
         self.lems_info["sim_id"] = sim_id
@@ -75,6 +88,7 @@ def __init__(
         self.lems_info["displays"] = []
         self.lems_info["output_files"] = []
         self.lems_info["event_output_files"] = []
+        self.lems_info["meta"] = meta
 
         if target:
             self.lems_info["target"] = target
@@ -251,7 +265,7 @@ def add_line_to_display(
         line_id: str,
         quantity: str,
         scale: str = "1",
-        color: str = None,
+        color: typing.Optional[str] = None,
         timeScale: str = "1ms",
     ) -> None:
         """Add a new line to the display
@@ -364,12 +378,13 @@ def to_xml(self) -> str:
             templ = airspeed.Template(f.read())
         return templ.merge(self.lems_info)
 
-    def save_to_file(self, file_name: str = None):
+    def save_to_file(self, file_name: typing.Optional[str] = None):
         """Save LEMSSimulation to a file.
 
         :param file_name: name of file to store to.
             `LEMS_<some id string>.xml` is the suggested format. Leave empty
-            to use `LEMS_<sim_id>.xml` :type file_name: str
+            to use `LEMS_<sim_id>.xml`
+        :type file_name: str
         :returns: name of file
         :rtype: str
         """

pyneuroml/lems/LEMS_TEMPLATE.xml

@@ -1,49 +1,51 @@
 <Lems>
-    
+
 #if ($comment)##
     <!-- ${comment} -->
-    
-#end## 
+
+#end##
     <!-- Specify which component to run -->
     <Target component="${sim_id}"${report}/>
 
     <!-- Include core NeuroML2 ComponentType definitions -->
     <Include file="Cells.xml"/>
     <Include file="Networks.xml"/>
     <Include file="Simulation.xml"/>
-    
+
 #foreach ($include_file in $include_files)##
     <Include file="${include_file}"/>
-#end##     
-   
+#end##
+
 #set( $start = -0.1 * $duration )
 #set( $end = 1.1 * $duration )
     <Simulation id="${sim_id}" length="${duration}ms" step="${dt}ms" target="${target}" seed="${seed}">  <!-- Note seed: ensures same random numbers used every run -->
-
+#if ($meta)##
+        <Meta for="${meta.for}" method="${meta.method}" abs_tolerance="${meta.abs_tolerance}" rel_tolerance="${meta.rel_tolerance}"/>
+#end##
 #foreach ($display in $displays)##
         <Display id="${display.id}" title="${display.title}" timeScale="${display.time_scale}" xmin="$start" xmax="$end" ymin="${display.ymin}" ymax="${display.ymax}">
 #foreach ($line in $display.lines)##
             <Line id="${line.id}" quantity="${line.quantity}" scale="${line.scale}" color="${line.color}" timeScale="${line.time_scale}"/>
-#end## 
+#end##
         </Display>
-        
-#end## 
+
+#end##
 #foreach ($output_file in $output_files)##
         <OutputFile id="${output_file.id}" fileName="${output_file.file_name}">
 #foreach ($column in $output_file.columns)##
-            <OutputColumn id="${column.id}" quantity="${column.quantity}"/> 
-#end## 
+            <OutputColumn id="${column.id}" quantity="${column.quantity}"/>
+#end##
         </OutputFile>
-        
-#end## 
+
+#end##
 #foreach ($event_output_file in $event_output_files)##
         <EventOutputFile id="${event_output_file.id}" fileName="${event_output_file.file_name}" format="${event_output_file.format}">
 #foreach ($selection in $event_output_file.selections)##
-            <EventSelection id="${selection.id}" select="${selection.select}" eventPort="${selection.event_port}"/> 
-#end## 
+            <EventSelection id="${selection.id}" select="${selection.select}" eventPort="${selection.event_port}"/>
+#end##
         </EventOutputFile>
-        
-#end## 
+
+#end##
     </Simulation>
 
 </Lems>

tests/lems/test_lemssimulation.py

@@ -0,0 +1,73 @@
+#!/usr/bin/env python3
+"""
+Test the LEMSSimulation class
+
+File: tests/lems/test_lemssimulation.py
+
+Copyright 2023 NeuroML contributors
+Author: Ankur Sinha <sanjay DOT ankur AT gmail DOT com>
+"""
+
+import logging
+import pathlib as pl
+import unittest
+
+import pytest
+from pyneuroml.lems import LEMSSimulation
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+
+
+class TestLEMSSimulation(unittest.TestCase):
+
+    """Test the LEMSSimulation class"""
+
+    def test_lemssimulation_meta(self):
+        """Test the LEMSSimulation class."""
+        # Create a simulation instance of the model
+        simulation_id = "tests-sim"
+        simulation = LEMSSimulation(
+            sim_id=simulation_id,
+            duration=1000,
+            dt=0.1,
+            simulation_seed=123,
+            meta={
+                "for": "neuron",
+                "method": "cvode",
+                "abs_tolerance": "0.0001",
+                "rel_tolerance": "0.0004",
+            },
+        )
+        simulation.assign_simulation_target("some_network")
+        # Save the simulation to a file
+        lems_simulation_file = simulation.save_to_file()
+
+        expected_string = '<Meta for="neuron" method="cvode" abs_tolerance="0.0001" rel_tolerance="0.0004"/>'
+
+        with open(lems_simulation_file, "r") as f:
+            self.assertIn(expected_string, f.read())
+
+        pl.Path(lems_simulation_file).unlink()
+
+    @pytest.mark.xfail
+    def test_lemssimulation_meta_should_fail(self):
+        """Test without meta to ensure it's not always added"""
+        # Create a simulation instance of the model
+        simulation_id = "tests-sim-failure"
+        simulation = LEMSSimulation(
+            sim_id=simulation_id,
+            duration=1000,
+            dt=0.1,
+            simulation_seed=123,
+        )
+        simulation.assign_simulation_target("some_network")
+        # Save the simulation to a file
+        lems_simulation_file = simulation.save_to_file()
+
+        expected_string = '<Meta for="neuron" method="cvode" abs_tolerance="0.0001" rel_tolerance="0.0004"/>'
+
+        with open(lems_simulation_file, "r") as f:
+            self.assertIn(expected_string, f.read())
+
+        pl.Path(lems_simulation_file).unlink()