remove input type

SimonBlanke · Dec 31, 2023 · 0bf4b93 · 0bf4b93
1 parent 5659988
commit 0bf4b93
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Showing 4 changed files with 20 additions and 11 deletions.
diff --git a/surfaces/machine_learning_functions/base_machine_learning_function.py b/surfaces/machine_learning_functions/base_machine_learning_function.py
@@ -13,8 +13,8 @@
 
 
 class MachineLearningFunction(BaseTestFunction):
-    def __init__(self, input_type="dictionary"):
-        super().__init__(input_type)
+    def __init__(self):
+        super().__init__()
 
         self.objective_function.__func__.__name__ = self.__name__
 

diff --git a/surfaces/machine_learning_functions/tabular_classifiers.py b/surfaces/machine_learning_functions/tabular_classifiers.py
@@ -13,7 +13,10 @@ class KNeighborsClassifierFunction(MachineLearningFunction):
     __name__ = "k_neighbors_classifier"
 
     def __init__(self, input_type="dictionary", sleep=0):
-        super().__init__(input_type, sleep)
+        super().__init__()
+
+        self.input_type = input_type
+        self.sleep = sleep
 
         self.search_space = {
             "n_neighbors": list(np.arange(3, 150)),

diff --git a/surfaces/machine_learning_functions/tabular_regressors.py b/surfaces/machine_learning_functions/tabular_regressors.py
@@ -14,7 +14,10 @@ class KNeighborsRegressorFunction(MachineLearningFunction):
     __name__ = "k_neighbors_regressor"
 
     def __init__(self, input_type="dictionary", sleep=0):
-        super().__init__(input_type, sleep)
+        super().__init__()
+
+        self.input_type = input_type
+        self.sleep = sleep
 
         self.search_space = {
             "n_neighbors": list(np.arange(3, 150)),
@@ -37,7 +40,10 @@ class GradientBoostingRegressorFunction(MachineLearningFunction):
     __name__ = "gradient_boosting_regressor"
 
     def __init__(self, input_type="dictionary", sleep=0):
-        super().__init__(input_type, sleep)
+        super().__init__()
+
+        self.input_type = input_type
+        self.sleep = sleep
 
         self.search_space = {
             "n_estimators": list(np.arange(5, 150)),

diff --git a/surfaces/mathematical_functions/_base_objective_function.py b/surfaces/mathematical_functions/_base_objective_function.py
@@ -28,35 +28,35 @@ def __init__(self, metric="score", input_type="dictionary", sleep=0):
         self.input_type = input_type
         self.sleep = sleep
 
-    def search_space(self, min=-5, max=5, step=0.1, value_typ="array"):
+    def search_space(self, min=-5, max=5, step=0.1, value_types="array"):
         search_space_ = {}
 
         for dim in range(self.n_dim):
             dim_str = "x" + str(dim)
 
             values = np.arange(min, max, step)
-            if value_typ == "list":
+            if value_types == "list":
                 values = list(values)
             search_space_[dim_str] = values
 
         return search_space_
 
     def collect_data(self, if_exists="append"):
-        self.search_space = self.search_space(value_typ="list")
+        self.search_space = self.search_space(value_types="list")
 
-        para_names = list(self.search_space().keys())
+        para_names = list(self.search_space.keys())
         search_data_cols = para_names + ["score"]
         search_data = pd.DataFrame([], columns=search_data_cols)
         search_data_length = 0
 
-        dim_sizes_list = [len(array) for array in self.search_space().values()]
+        dim_sizes_list = [len(array) for array in self.search_space.values()]
         search_space_size = reduce((lambda x, y: x * y), dim_sizes_list)
 
         while search_data_length < search_space_size:
             hyper = Hyperactive(verbosity=["progress_bar"])
             hyper.add_search(
                 self.objective_function_dict,
-                self.search_space(value_typ="list"),
+                self.search_space,
                 initialize={},
                 n_iter=search_space_size,
                 optimizer=GridSearchOptimizer(direction="orthogonal"),