Create distributions for axon according to https://bbpcode.epfl.ch/co…

…de/\#/c/52107

Change-Id: I33b12698a15a84444038c00b8d502dc33192e219

doc/source/conf.py

@@ -134,7 +134,7 @@
 }
 
 
-# pylint: disable=unused-argument
+# pylint: disable=unused-argument,protected-access
 def maybe_skip_member(app, what, name, obj, skip, options):
     """Skip and update documented objects."""
     skip = None

requirements.pip

@@ -21,7 +21,7 @@ PyYAML
 region_grower>=0.1.10
 scipy
 seaborn
-tns>=2.2.7,<2.3
+tns>=2.3.0
 tmd
 tqdm
 voxcell>=3

setup.py

@@ -20,7 +20,7 @@
     "bluepyefe",
     "bluepyopt",
     "bluepymm",
-    "diameter_synthesis>=0.1.7",
+    "diameter_synthesis>=0.1.8",
     "gitpython",
     "jinja2",
     "joblib",
@@ -35,7 +35,7 @@
     "pandas",
     "placement_algorithm>=2.1.2",
     "PyYAML",
-    "region_grower==0.1.11",
+    "region_grower>=0.1.11,<0.2",
     "scipy",
     "seaborn",
     "tns>=2.3.3",

src/synthesis_workflow/synthesis.py

@@ -37,9 +37,9 @@
 def get_neurite_types(morphs_df, mtypes):
     """Get the neurite types to consider for PC or IN cells."""
     return {
-        mtype: ["basal"]
+        mtype: ["basal", "axon"]
         if morphs_df.loc[morphs_df.mtype == mtype, "morph_class"].tolist()[0] == "IN"
-        else ["basal", "apical"]
+        else ["basal", "apical", "axon"]
         for mtype in mtypes
     }
 
@@ -335,6 +335,8 @@ def run_synthesize_morphologies(kwargs, nb_jobs=-1, debug_scales_path=None):
             "scaling-jitter-std",
             "rotational-jitter-std",
             "no-mpi",
+            "out-apical-NRN-sections",
+            "out-apical-sections",
         ]
     ]
 
@@ -352,6 +354,8 @@ def run_synthesize_morphologies(kwargs, nb_jobs=-1, debug_scales_path=None):
         "scaling_jitter_std": None,
         "rotational_jitter_std": None,
         "seed": 0,
+        "out-apical-NRN-sections": None,
+        "out-apical-sections": None,
     }
 
     if kwargs.pop("apply_jitter", False):

src/synthesis_workflow/tools.py

@@ -343,6 +343,8 @@ def run_master(
                 handlers.add(i)
 
         # shuffle ids to speed up computation with uneven cell complexities
+        if hasattr(args, "seed"):
+            np.random.seed(args.seed)
         task_ids = np.random.permutation(master.task_ids)
 
         # Run the worker