Merge pull request #101 from icecube/pprint_config

Pprint config
icecube · Jan 12, 2024 · 05969ba · 05969ba
2 parents b80db23 + a3056fa
commit 05969ba
Showing 1 changed file with 10 additions and 0 deletions.
diff --git a/python/asteria/simulation.py b/python/asteria/simulation.py
@@ -30,9 +30,17 @@ class Simulation:
     def __init__(self, config=None, *, model=None, distance=10 * u.kpc, res_dt=2 * u.ms, flavors=None, hierarchy=None,
                  interactions=Interactions, mixing_scheme=None, mixing_angle=None, E=None, Emin=None, Emax=None,
                  dE=None, t=None, tmin=None, tmax=None, dt=None, geomfile=None, effvolfile=None):
+        self.metadata = {key: str(val) for key, val in locals().items() if
+                         val is not None and
+                         key not in ['self', 'E', 't']}
+        self.metadata.update({'interactions': ', '.join([item.name for item in interactions])})
+
         self.param = {}
         if model and not config:
 
+            self.metadata.update({'model': {'name': model['name'],
+                                            'param': '; '.join([f"{key}, {val}" for key, val in model['param'].items()])}
+                                })
             if not E and None in (Emin, Emax, dE):
                 raise ValueError("Missing or incomplete energy range definition. Use argument `E` or "
                                  "arguments `Emin`, `Emax`, `dE")
@@ -43,6 +51,7 @@ def __init__(self, config=None, *, model=None, distance=10 * u.kpc, res_dt=2 * u
                 E = np.arange(_Emin, _Emax + _dE, _dE) * u.MeV
             elif not E:
                 E = np.arange(0, 100, 1) * u.MeV
+                self.metadata.update({'Emin': 0 * u.MeV, 'Emax': 100 * u.MeV, 'dE': 1 * u.ms})
 
             if not t and None in (tmin, tmax, dt):
                 raise ValueError("Missing or incomplete energy range definition. Use argument `t` or "
@@ -58,6 +67,7 @@ def __init__(self, config=None, *, model=None, distance=10 * u.kpc, res_dt=2 * u
             else:
                 t = np.arange(-1, 1, 0.001) * u.s
                 _dt = 1 * u.ms
+                self.metadata.update({'tmin': -1 * u.s, 'tmax': 1 * u.s, 'dt': 1 * u.ms})
 
             self.source = Source(model['name'], model['param'])
             self.distance = distance