levels management

Author: bartzbeielstein

pyproject.toml

@@ -7,7 +7,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "spotPython"
-version = "0.0.14"
+version = "0.0.15"
 authors = [
   { name="T. Bartz-Beielstein", email="tbb@bartzundbartz.de" }
 ]

src/spotPython/hyperparameters/levels.py

@@ -0,0 +1,22 @@
+def modify_hyper_parameter_levels(fun_control, hyperparameter, levels):
+    """
+
+    Args:
+        fun_control (dict): fun_control dictionary
+        hyperparameter (str): hyperparameter name
+        levels (list): list of levels
+
+    Returns:
+        fun_control (dict): updated fun_control
+    Example:
+        >>> fun_control = {}
+            core_model  = HoeffdingTreeRegressor
+            fun_control.update({"core_model": core_model})
+            fun_control.update({"core_model_hyper_dict": river_hyper_dict[core_model.__name__]})
+            levels = ["mean", "model"]
+            fun_control = modify_hyper_parameter_levels(fun_control, "leaf_prediction", levels)
+    """
+    fun_control["core_model_hyper_dict"][hyperparameter].update({"levels": levels})
+    fun_control["core_model_hyper_dict"][hyperparameter].update({"lower": 0})
+    fun_control["core_model_hyper_dict"][hyperparameter].update({"upper": len(levels) - 1})
+    return fun_control

src/spotPython/spot/spot.py

@@ -18,7 +18,7 @@
 from numpy import ravel
 from numpy import array
 from numpy import append
-from spotPython.utils.compare import selectNew
+from spotPython.utils.compare import selectNew, find_equal_in_lists
 from spotPython.utils.aggregate import aggregate_mean_var
 from spotPython.utils.repair import remove_nan
 from spotPython.budget.ocba import get_ocba_X
@@ -251,7 +251,7 @@ def __init__(
     def to_red_dim(self):
         self.all_lower = self.lower
         self.all_upper = self.upper
-        self.ident = (self.upper - self.lower) == 0
+        self.ident = find_equal_in_lists(a=self.lower, b=self.upper)
         self.lower = self.lower[~self.ident]
         self.upper = self.upper[~self.ident]
         self.red_dim = self.ident.any()

src/spotPython/utils/compare.py

@@ -18,3 +18,27 @@ def selectNew(A, X, tolerance=0):
         B = np.abs(A - X[i, :])
         ind = ind + np.all(B <= tolerance, axis=1)
     return A[~ind], ~ind
+
+
+def find_equal_in_lists(a, b):
+    """Find equal values in two lists.
+
+    Args:
+        a (list): list with a values
+        b (list): list with b values
+
+    Returns:
+        list: list with 1 if equal, otherwise 0
+    Example:
+        >>> a = [1, 2, 3, 4, 5]
+        >>> b = [1, 2, 3, 4, 5]
+        >>> find_equal_in_lists(a, b)
+        [1, 1, 1, 1, 1]
+    """
+    equal = []
+    for i in range(len(a)):
+        if a[i] == b[i]:
+            equal.append(1)
+        else:
+            equal.append(0)
+    return equal