Merge pull request #440 from AurelienJaquier/nml-smallfixes

neuroml small improvements

Author: AurelienJaquier

bluepyopt/neuroml/biophys.py

@@ -192,15 +192,15 @@ def add_nml_channel_to_nml_cell_file(
         channel_nml2_file = f"{channel_name}.channel.nml"
 
     if channel_nml2_file not in included_channels:
-        nml_mech_dir = get_nml_mech_dir()
         channel_new_path = Path(channel_dir) / channel_nml2_file
         cell_doc.includes.append(neuroml.IncludeType(href=channel_new_path))
 
         # for some reason, pynml cannot accept absolute paths in IncludeType,
         # so copy paste files in current directory for the simulation to work
         if not skip_channels_copy:
             Path(channel_dir).mkdir(exist_ok=True)
-            channel_path = Path(nml_mech_dir) / channel_nml2_file
+            nml_mech_dir = Path(get_nml_mech_dir())
+            channel_path = nml_mech_dir / channel_nml2_file
             if channel_path.is_file():
                 shutil.copy(channel_path, channel_new_path)
 
@@ -336,7 +336,7 @@ def get_density(
 
     Arguments:
         cell_doc (NeuroMLDocument): nml document of the cell model
-        cell (ephys.CellModel)
+        cell (ephys.CellModel): bluepyopt cell
         parameter (ephys.parameters)
         section_list (str): location
         included_channels (list): list of channels already included
@@ -417,10 +417,10 @@ def get_biophys(
     """Get biophys in neuroml format.
 
     Arguments:
-        cell (ephys.CellModel)
+        cell (ephys.CellModel): bluepyopt cell
         cell_doc (NeuroMLDocument): nml document of the cell model
-        skip_non_uniform (bool): True to skip non uniform distributions
         release_params (dict): optimized parameters
+        skip_non_uniform (bool): True to skip non uniform distributions
         skip_channels_copy (bool): True to skip the copy pasting
             of the neuroml channel files
     """

bluepyopt/neuroml/cell.py

@@ -31,9 +31,7 @@ def create_neuroml_cell(bpo_cell, release_params, skip_channels_copy=False):
     """Create the cell.
 
     Arguments:
-        nml_mech_files (list): paths to the nml files
-            containing the mechanisms
-        bpo_cell
+        bpo_cell (ephys.CellModel): bluepyopt cell
         release_params (dict): the optimized parameters
         skip_channels_copy (bool): True to skip the copy pasting
             of the neuroml channel files

bluepyopt/neuroml/morphology.py

@@ -28,7 +28,15 @@
 def create_loadcell_hoc(
     loadcell_hoc_filename, hoc_filename, morphology_path, v_init, cell_name
 ):
-    """Create a hoc file able to load the cell."""
+    """Create a hoc file able to load the cell.
+
+    Arguments:
+        loadcell_hoc_filename (str): path to the loadcell hoc file to output
+        hoc_filename (str): file name of the cell hoc file
+        morphology_path (str): path to the morphology file
+        v_init (float): inital voltage in mV
+        cell_name (str): cell name
+    """
     morph_path = Path(morphology_path)
     morph_dir = morph_path.parent
     morph_file = morph_path.name
@@ -56,7 +64,13 @@ def create_loadcell_hoc(
 
 
 def create_morph_nml(bpo_cell, network_filename, release_params):
-    """Create cell hoc file, then cell nml file."""
+    """Create cell hoc file, then cell nml file.
+
+    Arguments:
+        bpo_cell (ephys.CellModel): bluepyopt cell
+        network_filename (str): name of the neuroml network file
+        release_params (dict): name and values of optimised parameters
+    """
     import pebble
 
     hoc_filename = f"{bpo_cell.name}.hoc"

examples/neuroml/neuroml.ipynb

@@ -29,13 +29,15 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "id": "63d69fd0-dd92-424b-b38a-be50f03e3dd7",
    "metadata": {},
    "source": [
     "Note that the bluepyopt neuroml module cannot yet handle:\n",
     "- non uniform parameter\n",
-    "- axon replacement"
+    "- axon replacement\n",
+    "- stochasticity"
    ]
   },
   {