Lint fix

Author: Jaquier Aurélien Tristan

bluepyopt/neuroml/biophys.py

@@ -25,7 +25,8 @@
 
 ignore_params = ["cm", "Ra", "ena", "ek"]
 
-# Due to the use of 1e-4 in BREAKPOINT in StochKv.mod: ik = 1e-4 * gk * (v - ek)
+# Due to the use of 1e-4 in BREAKPOINT in StochKv.mod:
+# ik = 1e-4 * gk * (v - ek)
 density_scales = {"StochKv": 1e-4}
 
 channel_substitutes = {"StochKv": "StochKv_deterministic"}
@@ -95,8 +96,10 @@ def adapt_CaDynamics_nml(
         channel_dir (str): repo in which to copy the channel files
     """
     place_after = (
-        '    <concentrationModel id="CaDynamics_E2_NML2" type="concentrationModelHayEtAl" '
-        'minCai="1e-4 mM" decay="80 ms" depth="0.1 um" gamma="0.05" ion="ca"/>\n'
+        '    <concentrationModel id="CaDynamics_E2_NML2" '
+        'type="concentrationModelHayEtAl" '
+        'minCai="1e-4 mM" decay="80 ms" depth="0.1 um" '
+        'gamma="0.05" ion="ca"/>\n'
     )
     cadyn_filename = "baseCaDynamics_E2_NML2.nml"
     new_cadyn_filename = "CaDynamics_E2_NML2.nml"
@@ -112,7 +115,7 @@ def adapt_CaDynamics_nml(
             f'gamma="{value_dict["gamma"]}" '
             f'decay="{value_dict["decay"]} ms" depth="0.1 um"/>\n'
         )
-        if not new_concentration in lines:
+        if new_concentration not in lines:
             idx = lines.index(place_after) + 2  # 2 to account for blank line
             lines.insert(idx, f"{new_concentration}\n")
 
@@ -136,7 +139,9 @@ def get_channel_from_param_name(param_name):
     elif len(split_name) == 2:
         channel = split_name[1]
     else:
-        raise Exception(f"Could not extract channel from parameter name {param_name}")
+        raise Exception(
+            f"Could not extract channel from parameter name {param_name}"
+        )
 
     return channel
 
@@ -152,7 +157,8 @@ def format_dist_fun(raw_expr, value, dist_param_names):
     """
     if dist_param_names is not None:
         raise NotImplementedError(
-            "Functions that depend on other parameters, like decay function, are not implemented yet."
+            "Functions that depend on other parameters, "
+            "like decay function, are not implemented yet."
         )
     new_expr = raw_expr.format(distance="p", value=value)
     if "math" in new_expr:
@@ -224,8 +230,10 @@ def get_arguments(
         parameter_name (str): name of the parameter (e.g. e_pas)
         section_list (str): name of the location of the parameter (e.g. axonal)
         channel (str): ion channel (e.g. StochKv)
-        channel_name (str): ion channel name used in the neuroML channel file (e.g. StochKv_deterministic)
-        variable_parameters (list of neuroml.VariableParameter): parameters for non-uniform distributions
+        channel_name (str): ion channel name used in the neuroML channel file
+            (e.g. StochKv_deterministic)
+        variable_parameters (list of neuroml.VariableParameter):
+            parameters for non-uniform distributions
         cond_density (str): conductance density
         release_params (dict): optimized parameters
     """
@@ -240,7 +248,6 @@ def get_arguments(
         erev = None
         channel_class = "ChannelDensityNernst"
     elif erev == "pas":
-        # do all pas have the same section_list? e.g. does it happen to have g_pas.all and e_pas.somatic?
         erev = params[f"e_pas.{section_list}"].value
         if erev is None:
             # non frozen parameter
@@ -338,7 +345,8 @@ def get_density(
         cell (ephys.CellModel)
         parameter (ephys.parameters)
         section_list (str): location
-        included_channels (list): list of channels already included in the nml file
+        included_channels (list): list of channels already included
+            in the nml file
         skip_non_uniform (bool): True to skip non uniform distributions
         release_params (dict): optimized parameters
         skip_channels_copy (bool): True to skip the copy pasting
@@ -397,7 +405,9 @@ def get_specific_capacitance(capacitance_overwrites):
             capacitance = default_capacitances[section_list]
 
         specific_capacitances.append(
-            neuroml.SpecificCapacitance(value=capacitance, segment_groups=section_list)
+            neuroml.SpecificCapacitance(
+                value=capacitance, segment_groups=section_list
+            )
         )
 
     return specific_capacitances
@@ -426,7 +436,7 @@ def get_biophys(
     included_channels = []
     channel_densities = []
     channel_density_nernsts = []
-    channel_density_non_uniform_nernsts = []
+    channel_density_non_unif_nernsts = []
     channel_density_non_uniforms = []
     species = []
 
@@ -460,8 +470,12 @@ def get_biophys(
                         # add density to list of densities
                         if channel_class == "ChannelDensityNernst":
                             channel_density_nernsts.append(density)
-                        elif channel_class == "ChannelDensityNernstNonUniform":
-                            channel_density_non_uniform_nernsts.append(density)
+                        elif (
+                            channel_class == "ChannelDensityNernstNonUniform"
+                        ):
+                            channel_density_non_unif_nernsts.append(
+                                density
+                            )
                         elif channel_class == "ChannelDensityNonUniform":
                             channel_density_non_uniforms.append(density)
                         else:
@@ -474,7 +488,7 @@ def get_biophys(
                         # non frozen parameter
                         value = release_params[parameter.name]
 
-                    if not model in concentrationModels:
+                    if model not in concentrationModels:
                         concentrationModels[model] = {}
                     concentrationModels[model]["gamma"] = value
 
@@ -493,15 +507,17 @@ def get_biophys(
 
                     channel_nml2_file = "CaDynamics_E2_NML2.nml"
                     add_nml_channel_to_nml_cell_file(
-                        cell_doc, included_channels, channel_nml2_file=channel_nml2_file
+                        cell_doc,
+                        included_channels,
+                        channel_nml2_file=channel_nml2_file,
                     )
 
                     value = parameter.value
                     if value is None:
                         # non frozen parameter
                         value = release_params[parameter.name]
 
-                    if not model in concentrationModels:
+                    if model not in concentrationModels:
                         concentrationModels[model] = {}
                     concentrationModels[model]["decay"] = value
 
@@ -524,15 +540,17 @@ def get_biophys(
     membrane_properties = neuroml.MembraneProperties(
         channel_densities=channel_densities,
         channel_density_nernsts=channel_density_nernsts,
-        channel_density_non_uniform_nernsts=channel_density_non_uniform_nernsts,
+        channel_density_non_uniform_nernsts=channel_density_non_unif_nernsts,
         channel_density_non_uniforms=channel_density_non_uniforms,
         specific_capacitances=specific_capacitances,
         init_memb_potentials=init_memb_potentials,
     )
 
     # Intracellular Properties
     Ra = cell.params["Ra.all"].value
-    resistivities = [neuroml.Resistivity(value=f"{Ra} ohm_cm", segment_groups="all")]
+    resistivities = [
+        neuroml.Resistivity(value=f"{Ra} ohm_cm", segment_groups="all")
+    ]
 
     intracellular_properties = neuroml.IntracellularProperties(
         resistivities=resistivities,

bluepyopt/neuroml/cell.py

@@ -31,7 +31,8 @@ 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
+        nml_mech_files (list): paths to the nml files
+            containing the mechanisms
         bpo_cell
         release_params (dict): the optimized parameters
         skip_channels_copy (bool): True to skip the copy pasting
@@ -45,11 +46,13 @@ def create_neuroml_cell(bpo_cell, release_params, skip_channels_copy=False):
     network_filename = f"{bpo_cell.name}.net.nml"
 
     # Morphology
-    logger.info("This will create a cell hoc file in order to create a cell nml file")
+    logger.info(
+        "This will create a cell hoc file in order to create a cell nml file"
+    )
     create_morph_nml(bpo_cell, network_filename, release_params)
 
     # change the network temperature.
-    # For some reason, the pyneurom.export_to_neuroml2 sets it automatically to 6C.
+    # because the pyneurom.export_to_neuroml2 sets it automatically to 6C.
     network_doc = pynml.read_neuroml2_file(network_filename)
     network = network_doc.networks[0]
     network.temperature = f"{bpo_cell.params['celsius'].value} degC"

bluepyopt/neuroml/morphology.py

@@ -32,19 +32,21 @@ def create_loadcell_hoc(
     morph_path = Path(morphology_path)
     morph_dir = morph_path.parent
     morph_file = morph_path.name
+    cell_cmd = '"cell = new %s(\\"%s\\", \\"%s\\")"'
+    cell = f'{cell_cmd}, "{cell_name}", "{morph_dir}", "{morph_file}"'
     loadcell_hoc = f"""
         load_file("nrngui.hoc")
         load_file("import3d.hoc")
         load_file("{hoc_filename}")
 
         // ================== constants ==================
         v_init={v_init}
-        //=================== creating cell object ===========================
+        // ================== creating cell object ==================
         objref cell
 
         proc create_cell() {{ localobj cellstring
             cellstring = new String()
-            sprint(cellstring.s, "cell = new %s(\\"%s\\", \\"%s\\")", "{cell_name}", "{morph_dir}", "{morph_file}")
+            sprint(cellstring.s, {cell})
             execute(cellstring.s)
         }}
         create_cell(0)
@@ -76,12 +78,14 @@ def create_morph_nml(bpo_cell, network_filename, release_params):
 
     if not os.path.isdir("x86_64"):
         logger.warning(
-            "It seems you have not compiled the mechanisms. This program will likely fail."
+            "It seems you have not compiled the mechanisms. "
+            "This program will likely fail."
         )
 
     # isolate the export_to_neuroml to a subprocess
     # so that the cell remain non-instantiated in the main process
-    # that way, using this function will not prevent us to run the cell with bluepyopt
+    # that way, using this function will not prevent us to run the cell
+    # with bluepyopt
     with pebble.ProcessPool(max_workers=1, max_tasks=1) as pool:
         tasks = pool.schedule(
             export_to_neuroml2,
@@ -128,10 +132,14 @@ def add_segment_groups(cell):
             )
 
     cell.morphology.segment_groups.append(
-        neuroml.SegmentGroup(id="soma_group", includes=[neuroml.Include("somatic")])
+        neuroml.SegmentGroup(
+            id="soma_group", includes=[neuroml.Include("somatic")]
+        )
     )
     cell.morphology.segment_groups.append(
-        neuroml.SegmentGroup(id="axon_group", includes=[neuroml.Include("axonal")])
+        neuroml.SegmentGroup(
+            id="axon_group", includes=[neuroml.Include("axonal")]
+        )
     )
     cell.morphology.segment_groups.append(
         neuroml.SegmentGroup(