[DOC] added type hints to 'classification->convolution_based' module (#…

…2494)

* added type hints to classification->convolution_based

* Automatic `pre-commit` fixes

aeon/classification/convolution_based/_arsenal.py

@@ -130,15 +130,15 @@ class Arsenal(BaseClassifier):
 
     def __init__(
         self,
-        n_kernels=2000,
-        n_estimators=25,
-        rocket_transform="rocket",
-        max_dilations_per_kernel=32,
-        n_features_per_kernel=4,
-        time_limit_in_minutes=0.0,
-        contract_max_n_estimators=100,
+        n_kernels: int = 2000,
+        n_estimators: int = 25,
+        rocket_transform: str = "rocket",
+        max_dilations_per_kernel: int = 32,
+        n_features_per_kernel: int = 4,
+        time_limit_in_minutes: float = 0.0,
+        contract_max_n_estimators: int = 100,
         class_weight=None,
-        n_jobs=1,
+        n_jobs: int = 1,
         random_state=None,
     ):
         self.n_kernels = n_kernels

aeon/classification/convolution_based/_hydra.py

@@ -96,7 +96,12 @@ class HydraClassifier(BaseClassifier):
     }
 
     def __init__(
-        self, n_kernels=8, n_groups=64, class_weight=None, n_jobs=1, random_state=None
+        self,
+        n_kernels: int = 8,
+        n_groups: int = 64,
+        class_weight=None,
+        n_jobs: int = 1,
+        random_state=None,
     ):
         self.n_kernels = n_kernels
         self.n_groups = n_groups

aeon/classification/convolution_based/_minirocket.py

@@ -89,11 +89,11 @@ class MiniRocketClassifier(BaseClassifier):
 
     def __init__(
         self,
-        n_kernels=10000,
-        max_dilations_per_kernel=32,
+        n_kernels: int = 10000,
+        max_dilations_per_kernel: int = 32,
         estimator=None,
         class_weight=None,
-        n_jobs=1,
+        n_jobs: int = 1,
         random_state=None,
     ):
         self.n_kernels = n_kernels

aeon/classification/convolution_based/_mr_hydra.py

@@ -89,7 +89,12 @@ class MultiRocketHydraClassifier(BaseClassifier):
     }
 
     def __init__(
-        self, n_kernels=8, n_groups=64, class_weight=None, n_jobs=1, random_state=None
+        self,
+        n_kernels: int = 8,
+        n_groups: int = 64,
+        class_weight=None,
+        n_jobs: int = 1,
+        random_state=None,
     ):
         self.n_kernels = n_kernels
         self.n_groups = n_groups

aeon/classification/convolution_based/_multirocket.py

@@ -90,12 +90,12 @@ class MultiRocketClassifier(BaseClassifier):
 
     def __init__(
         self,
-        n_kernels=10000,
-        max_dilations_per_kernel=32,
-        n_features_per_kernel=4,
+        n_kernels: int = 10000,
+        max_dilations_per_kernel: int = 32,
+        n_features_per_kernel: int = 4,
         estimator=None,
         class_weight=None,
-        n_jobs=1,
+        n_jobs: int = 1,
         random_state=None,
     ):
         self.n_kernels = n_kernels

aeon/classification/convolution_based/_rocket.py

@@ -93,10 +93,10 @@ class RocketClassifier(BaseClassifier):
 
     def __init__(
         self,
-        n_kernels=10000,
+        n_kernels: int = 10000,
         estimator=None,
         class_weight=None,
-        n_jobs=1,
+        n_jobs: int = 1,
         random_state=None,
     ):
         self.n_kernels = n_kernels