Merge pull request #112 from NiklasMelton/consistency-fixes

improve consistency across modules

artlib/common/BaseART.py

@@ -88,7 +88,7 @@ def set_params(self, **params):
         for key, value in params.items():
             key, delim, sub_key = key.partition("__")
             if key not in valid_params:
-                local_valid_params = List(valid_params.keys())
+                local_valid_params = list(valid_params.keys())
                 raise ValueError(
                     f"Invalid parameter {key!r} for estimator {self}. "
                     f"Valid parameters are: {local_valid_params!r}."
@@ -219,7 +219,7 @@ def match_criterion(
         w: np.ndarray,
         params: Dict,
         cache: Optional[Dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters

artlib/elementary/ART1.py

@@ -7,7 +7,7 @@
 # Processing, 37, 54 – 115. doi:10. 1016/S0734-189X(87)80014-2.
 
 import numpy as np
-from typing import Optional, List, Tuple, Union, Dict
+from typing import Optional, List, Tuple, Dict
 from artlib.common.BaseART import BaseART
 from artlib.common.utils import l1norm
 
@@ -108,7 +108,7 @@ def match_criterion(
         w: np.ndarray,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters

artlib/elementary/BayesianART.py

@@ -127,7 +127,7 @@ def match_criterion(
         w: np.ndarray,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters

artlib/elementary/EllipsoidART.py

@@ -10,7 +10,7 @@
 # International Society for Optics and Photonics. doi:10.1117/12.421180.
 
 import numpy as np
-from typing import Optional, List, Tuple, Union, Dict
+from typing import Optional, List, Tuple, Dict
 from matplotlib.axes import Axes
 from artlib.common.BaseART import BaseART
 from artlib.common.utils import l2norm2, IndexableOrKeyable
@@ -166,7 +166,7 @@ def match_criterion(
         w: np.ndarray,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters

artlib/elementary/FuzzyART.py

@@ -5,7 +5,7 @@
 # Neural Networks, 4, 759 – 771. doi:10.1016/0893-6080(91)90056-B.
 
 import numpy as np
-from typing import Optional, Iterable, List, Tuple, Union, Dict
+from typing import Optional, Iterable, List, Tuple, Dict
 from matplotlib.axes import Axes
 from artlib.common.BaseART import BaseART
 from artlib.common.utils import (
@@ -206,7 +206,7 @@ def match_criterion(
         w: np.ndarray,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters

artlib/elementary/GaussianART.py

@@ -5,7 +5,7 @@
 # Neural Networks, 9, 881 – 897. doi:10.1016/0893-6080(95)00115-8.
 
 import numpy as np
-from typing import Optional, Iterable, List, Tuple, Union, Dict
+from typing import Optional, Iterable, List, Tuple, Dict
 from matplotlib.axes import Axes
 from artlib.common.BaseART import BaseART
 from artlib.common.visualization import plot_gaussian_contours_fading
@@ -109,7 +109,7 @@ def match_criterion(
         w: np.ndarray,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters

artlib/elementary/QuadraticNeuronART.py

@@ -8,7 +8,7 @@
 # Pattern Recognition, 38, 1887 – 1901. doi:10.1016/j.patcog.2005.04.010.
 
 import numpy as np
-from typing import Optional, Iterable, List, Tuple, Union, Dict
+from typing import Optional, Iterable, List, Tuple, Dict
 from matplotlib.axes import Axes
 from artlib.common.BaseART import BaseART
 from artlib.common.utils import l2norm2
@@ -133,7 +133,7 @@ def match_criterion(
         w: np.ndarray,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters

artlib/experimental/ConvexHullART.py

@@ -271,7 +271,7 @@ def match_criterion(
         w: HullTypes,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """
         Get the match criterion of the cluster.
 

artlib/experimental/SeqART.py

@@ -234,7 +234,7 @@ def category_choice(
 
     def match_criterion(
         self, i: str, w: str, params: dict, cache: Optional[dict] = None
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """
         Get the match criterion of the cluster.
 

artlib/fusion/FusionART.py

@@ -289,7 +289,7 @@ def match_criterion(
         params: Dict,
         cache: Optional[Dict] = None,
         skip_channels: List[int] = [],
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion for the cluster.
 
         Parameters
@@ -308,7 +308,7 @@ def match_criterion(
         Returns
         -------
         tuple
-            List of match criteria for each channel and the updated cache.
+            max match_criterion across channels and the updated cache.
 
         """
         if cache is None:
@@ -322,12 +322,12 @@ def match_criterion(
                     cache[k],
                 )
                 if k not in skip_channels
-                else (np.inf, {"match_criterion": np.inf})
+                else (np.nan, {"match_criterion": np.inf})
                 for k in range(self.n)
             ]
         )
         cache = {k: cache_k for k, cache_k in enumerate(caches)}
-        return M, cache
+        return np.nanmax(M), cache
 
     def match_criterion_bin(
         self,

artlib/topological/TopoART.py

@@ -192,7 +192,7 @@ def match_criterion(
         w: np.ndarray,
         params: dict,
         cache: Optional[dict] = None,
-    ) -> Tuple[Union[float, List[float]], Optional[Dict]]:
+    ) -> Tuple[float, Optional[Dict]]:
         """Get the match criterion of the cluster.
 
         Parameters