mixtures were excluded from list of serizalization & bug with extensi…

…ons fixed

bamt/networks/base.py

@@ -464,6 +464,8 @@ def save(self, bn_name, models_dir: str = "models_dir"):
         to_serialize = {}
         # separate logit and gaussian nodes from distributions to serialize bn's models
         for node_name in distributions.keys():
+            if "Mixture" in self[node_name].type:
+                continue
             if self[node_name].type.startswith("Gaussian"):
                 if not distributions[node_name]["regressor"]:
                     continue
@@ -491,7 +493,7 @@ def save(self, bn_name, models_dir: str = "models_dir"):
             "parameters": distributions,
             "weights": new_weights,
         }
-        return self._save_to_file(bn_name, outdict)
+        return self._save_to_file(f"{bn_name}.json", outdict)
 
     def load(self, input_dir: str, models_dir: str = "/"):
         """

tests/sendingRegressors.py

@@ -23,7 +23,7 @@
         "Permeability",
         "Depth",
     ]
-]
+].dropna()
 
 encoder = pp.LabelEncoder()
 discretizer = pp.KBinsDiscretizer(n_bins=5, encode="ordinal", strategy="quantile")
@@ -32,9 +32,9 @@
 
 discretized_data, est = p.apply(hack_data)
 
-bn = HybridBN()
+bn = HybridBN(has_logit=True)
 info = p.info
-#
+
 # with open(r"C:\Users\Roman\Desktop\mymodels\mynet.json") as f:
 #     net_data = json.load(f)
 
@@ -56,7 +56,7 @@
 
 bn.fit_parameters(hack_data)
 
-# bn.save("mynet.json")
+# bn.save("mynet")
 
 print(bn.sample(100).shape)
 bn.get_info(as_df=False)