section in config are allowed but optional

src/scgenerator/io.py

@@ -88,6 +88,11 @@ def load_toml(path: os.PathLike):
     path = conform_toml_path(path)
     with open(path, mode="r") as file:
         dico = toml.load(file)
+    dico.setdefault("variable", {})
+    for key in {"simulation", "fiber", "gas", "pulse"} & dico.keys():
+        section = dico.pop(key, {})
+        dico["variable"].update(section.pop("variable", {}))
+        dico.update(section)
     return dico
 
 

src/scgenerator/physics/simulate.py

@@ -424,7 +424,6 @@ class Simulations:
         io.save_parameters(self.param_seq.config, self.sim_dir, file_name="initial_config.toml")
 
         self.sim_jobs_per_node = 1
-        self.max_concurrent_jobs = np.inf
 
     @property
     def finished_and_complete(self):
@@ -434,9 +433,6 @@ class Simulations:
         except IncompleteDataFolderError:
             return False
 
-    def limit_concurrent_jobs(self, max_concurrent_jobs):
-        self.max_concurrent_jobs = max_concurrent_jobs
-
     def update(self, param_seq: initialize.ParamSequence):
         self.param_seq = param_seq
 
@@ -656,8 +652,7 @@ class RaySimulations(Simulations, priority=2):
     def sim_jobs_total(self):
         if self.param_seq.config.worker_num is not None:
             return self.param_seq.config.worker_num
-        tot_cpus = sum([node.get("Resources", {}).get("CPU", 0) for node in ray.nodes()])
-        tot_cpus = min(tot_cpus, self.max_concurrent_jobs)
+        tot_cpus = ray.cluster_resources().get("CPU", 1)
         return int(min(self.param_seq.num_sim, tot_cpus))