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automl · Sep 8, 2023 · aded257 · aded257
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commit aded257
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Showing 3 changed files with 15 additions and 28 deletions.
diff --git a/deepcave/config.py b/deepcave/config.py
@@ -49,7 +49,9 @@ def PLUGINS(self) -> Dict[str, List["Plugin"]]:
         from deepcave.plugins.budget.budget_correlation import BudgetCorrelation
         from deepcave.plugins.hyperparameter.importances import Importances
         from deepcave.plugins.hyperparameter.pdp import PartialDependencies
-        from deepcave.plugins.hyperparameter.symbolic_explanations import SymbolicExplanations
+        from deepcave.plugins.hyperparameter.symbolic_explanations import (
+            SymbolicExplanations,
+        )
         from deepcave.plugins.objective.configuration_cube import ConfigurationCube
         from deepcave.plugins.objective.cost_over_time import CostOverTime
         from deepcave.plugins.objective.parallel_coordinates import ParallelCoordinates

diff --git a/deepcave/plugins/hyperparameter/symbolic_explanations.py b/deepcave/plugins/hyperparameter/symbolic_explanations.py
@@ -2,16 +2,16 @@
 import numpy as np
 import plotly.graph_objs as go
 from dash import dcc, html
-from pyPDP.algorithms.pdp import PDP
 from gplearn.genetic import SymbolicRegressor
+from pyPDP.algorithms.pdp import PDP
 
 from deepcave import config
 from deepcave.evaluators.epm.random_forest_surrogate import RandomForestSurrogate
 from deepcave.plugins.static import StaticPlugin
 from deepcave.runs import Status
 from deepcave.utils.layout import get_checklist_options, get_select_options, help_button
 from deepcave.utils.styled_plotty import get_color, get_hyperparameter_ticks, save_image
-from deepcave.utils.symbolic_regression import get_function_set, convert_symb
+from deepcave.utils.symbolic_regression import convert_symb, get_function_set
 
 GRID_POINTS_PER_AXIS = 20
 SAMPLES_PER_HP = 10
@@ -24,7 +24,7 @@ class SymbolicExplanations(StaticPlugin):
     id = "symbolic_explanations"
     name = "Symbolic Explanations"
     icon = "fas fa-subscript"
-    help = "docs/plugins/partial_dependencies.rst" # TODO
+    help = "docs/plugins/partial_dependencies.rst"  # TODO
     activate_run_selection = True
 
     @staticmethod
@@ -129,8 +129,8 @@ def get_filter_layout(register):
 
     def load_inputs(self):
         return {
-            #"show_confidence": {"options": get_select_options(binary=True), "value": "true"},
-            #"show_ice": {"options": get_select_options(binary=True), "value": "true"},
+            # "show_confidence": {"options": get_select_options(binary=True), "value": "true"},
+            # "show_ice": {"options": get_select_options(binary=True), "value": "true"},
         }
 
     def load_dependency_inputs(self, run, previous_inputs, inputs):
@@ -234,11 +234,7 @@ def process(run, inputs):
 
         y_symbolic = symb_model.predict(x).tolist()
 
-        return {
-            "x": x,
-            "y": y_symbolic,
-            "expr": str(conv_expr)
-        }
+        return {"x": x, "y": y_symbolic, "expr": str(conv_expr)}
 
     @staticmethod
     def get_output_layout(register):
@@ -313,7 +309,7 @@ def load_outputs(run, inputs, outputs):
                     xaxis=dict(tickvals=x_tickvals, ticktext=x_ticktext, title=hp1_name),
                     yaxis=dict(tickvals=y_tickvals, ticktext=y_ticktext, title=hp2_name),
                     margin=config.FIGURE_MARGIN,
-                    title=expr
+                    title=expr,
                 )
             )
 

diff --git a/deepcave/utils/symbolic_regression.py b/deepcave/utils/symbolic_regression.py
@@ -1,5 +1,5 @@
-import sympy
 import numpy as np
+import sympy
 from gplearn import functions
 from gplearn.functions import make_function
 
@@ -14,21 +14,11 @@ def exp(x):
 def get_function_set():
     exp_func = make_function(function=exp, arity=1, name="exp")
 
-    function_set = [
-        "add",
-        "sub",
-        "mul",
-        "div",
-        "sqrt",
-        "log",
-        "sin",
-        "cos",
-        "abs",
-        exp_func
-    ]
+    function_set = ["add", "sub", "mul", "div", "sqrt", "log", "sin", "cos", "abs", exp_func]
 
     return function_set
 
+
 def convert_symb(symb, n_dim: int = None, n_decimals: int = None) -> sympy.core.expr:
     """
     Convert a fitted symbolic regression to a simplified and potentially rounded mathematical expression.
@@ -68,14 +58,13 @@ def convert_symb(symb, n_dim: int = None, n_decimals: int = None) -> sympy.core.
 
     symb_str = str(symb._program)
 
-
     converter = {
         "sub": lambda x, y: x - y,
         "div": lambda x, y: x / y,
         "mul": lambda x, y: x * y,
         "add": lambda x, y: x + y,
         "neg": lambda x: -x,
-        "pow": lambda x, y: x**y
+        "pow": lambda x, y: x**y,
     }
 
     if symb._program.length_ > 300:
@@ -99,4 +88,4 @@ def convert_symb(symb, n_dim: int = None, n_decimals: int = None) -> sympy.core.
             if isinstance(a, sympy.core.numbers.Float):
                 symb_simpl = symb_simpl.subs(a, round(a, n_decimals))
 
-    return symb_simpl
+    return symb_simpl