Added coveralls to GitHub action workflow

.github/workflows/main.yml

@@ -29,7 +29,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.11", "3.12", "3.13"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
       fail-fast: false
     defaults:
       run:
@@ -49,12 +49,12 @@ jobs:
       - name: Check typing
         run: uv run pyright
 
-
-      - name: Upload coverage reports to Codecov with GitHub Action on Python 3.11
-        uses: codecov/codecov-action@v4
-        if: ${{ matrix.python-version == '3.11' }}
+      - name: Upload coeverage reports to Coveralls
+        uses: coverallsapp/github-action@v2
+        with:
+          path-to-lcov: coverage.xml
         env:
-          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+          COVERALLS_REPO_TOKEN: ${{ secrets.COVERALLS_REPO_TOKEN }}
 
   check-docs:
     runs-on: ubuntu-latest

README.md

@@ -2,7 +2,7 @@
 
 [![Release](https://img.shields.io/github/v/release/automl/HyperSHAP)](https://img.shields.io/github/v/release/automl/hypershap)
 [![Build status](https://img.shields.io/github/actions/workflow/status/automl/hypershap/main.yml?branch=main)](https://github.com/automl/hypershap/actions/workflows/main.yml?query=branch%3Amain)
-[![codecov](https://codecov.io/gh/automl/hypershap/branch/main/graph/badge.svg)](https://codecov.io/gh/automl/hypershap)
+[![Coverage Status](https://coveralls.io/repos/github/automl/HyperSHAP/badge.svg?branch=dev)](https://coveralls.io/github/automl/HyperSHAP?branch=dev)
 [![Commit activity](https://img.shields.io/github/commit-activity/m/automl/hypershap)](https://img.shields.io/github/commit-activity/m/automl/hypershap)
 [![License](https://img.shields.io/github/license/automl/hypershap)](https://img.shields.io/github/license/automl/hypershap)
 

pyproject.toml

@@ -5,22 +5,23 @@ description = "HyperSHAP is a post-hoc explanation method for hyperparameter opt
 authors = [{ name = "Marcel Wever", email = "m.wever@ai.uni-hannover.de" }]
 readme = "README.md"
 keywords = ['python']
-requires-python = ">=3.11,<4.0"
+requires-python = ">=3.10,<4.0"
 classifiers = [
     "Intended Audience :: Developers",
     "Programming Language :: Python",
     "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: 3.13",
     "Topic :: Software Development :: Libraries :: Python Modules",
 ]
 dependencies = [
     "shapiq>=1.2.3",
-    "numpy>=2.3.2",
+    "numpy>=2.2.6",
     "scikit-learn>=1.7.1",
     "matplotlib>=3.10.5",
-    "networkx>=3.5"
+    "networkx>=3.4.2",
 ]
 
 [project.urls]

src/hypershap/games/ablation.py

@@ -81,8 +81,8 @@ def evaluate_single_coalition(self, coalition: np.ndarray) -> float:
         res = self._get_explanation_task().surrogate_model.evaluate(blend)
 
         # validate that we do not get a list of floats by accident
-        if isinstance(res, list):
-            raise TypeError
+        if isinstance(res, list):  # pragma: no cover
+            raise TypeError  # pragma: no cover
 
         return res
 
@@ -98,4 +98,5 @@ def _get_explanation_task(self) -> AblationExplanationTask:
         """
         if isinstance(self.explanation_task, AblationExplanationTask):
             return self.explanation_task
-        raise ValueError
+
+        raise ValueError  # pragma: no cover

src/hypershap/games/optimizerbias.py

@@ -83,7 +83,7 @@ def __init__(
     def _get_explanation_task(self) -> OptimizerBiasExplanationTask:
         if isinstance(self.explanation_task, OptimizerBiasExplanationTask):
             return self.explanation_task
-        raise ValueError
+        raise ValueError  # pragma: no cover
 
     def evaluate_single_coalition(self, coalition: np.ndarray) -> float:
         """Evaluate a single coalition by comparing against an optimizer ensemble.

src/hypershap/hypershap.py

@@ -301,12 +301,18 @@ def optimizer_bias(
         og = OptimizerBiasGame(explanation_task=optimizer_bias_task, n_workers=self.n_workers, verbose=self.verbose)
         return self.__get_interaction_values(game=og, index=index, order=order)
 
-    def plot_si_graph(self, interaction_values: InteractionValues | None = None, save_path: str | None = None) -> None:
+    def plot_si_graph(
+        self,
+        interaction_values: InteractionValues | None = None,
+        save_path: str | None = None,
+        no_show: bool | None = None,
+    ) -> None:
         """Plot the SHAP interaction values as a graph.
 
         Args:
             interaction_values (InteractionValues | None, optional): The interaction values to plot. Defaults to None.
             save_path (str | None, optional): The path to save the plot. Defaults to None.
+            no_show (bool | None, optional): Do not show the plot if set to true. Defaults to None.
 
         """
         if interaction_values is None and self.last_interaction_values is None:
@@ -315,8 +321,8 @@ def plot_si_graph(self, interaction_values: InteractionValues | None = None, sav
         # if given interaction values use those, else use cached interaction values
         iv = interaction_values if interaction_values is not None else self.last_interaction_values
 
-        if not isinstance(iv, InteractionValues):
-            raise TypeError
+        if not isinstance(iv, InteractionValues):  # pragma: no cover
+            raise TypeError  # pragma: no cover
 
         hyperparameter_names = self.explanation_task.get_hyperparameter_names()
 
@@ -342,14 +348,21 @@ def get_circular_layout(n_players: int) -> dict:
             plt.savefig(save_path)
             logger.info("Saved SI graph to %s", save_path)
 
-        plt.show()
+        if no_show is None or not no_show:  # pragma: no cover
+            plt.show()  # pragma: no cover
 
-    def plot_upset(self, interaction_values: InteractionValues | None = None, save_path: str | None = None) -> None:
+    def plot_upset(
+        self,
+        interaction_values: InteractionValues | None = None,
+        save_path: str | None = None,
+        no_show: bool | None = None,
+    ) -> None:
         """Plot the SHAP interaction values as an upset plot graph.
 
         Args:
             interaction_values (InteractionValues | None, optional): The interaction values to plot. Defaults to None.
             save_path (str | None, optional): The path to save the plot. Defaults to None.
+            no_show (bool | None, optional): Do not show the plot if set to true. Defaults to None.
 
         """
         if interaction_values is None and self.last_interaction_values is None:
@@ -358,15 +371,15 @@ def plot_upset(self, interaction_values: InteractionValues | None = None, save_p
         # if given interaction values use those, else use cached interaction values
         iv = interaction_values if interaction_values is not None else self.last_interaction_values
 
-        if not isinstance(iv, InteractionValues):
-            raise TypeError
+        if not isinstance(iv, InteractionValues):  # pragma: no cover
+            raise TypeError  # pragma: no cover
 
         hyperparameter_names = self.explanation_task.get_hyperparameter_names()
 
         fig = iv.plot_upset(feature_names=hyperparameter_names, show=False)
 
-        if fig is None:
-            raise TypeError
+        if fig is None:  # pragma: no cover
+            raise TypeError  # pragma: no cover
 
         ax = fig.get_axes()[0]
         ax.set_ylabel("Performance Gain")
@@ -379,14 +392,21 @@ def plot_upset(self, interaction_values: InteractionValues | None = None, save_p
         if save_path is not None:
             plt.savefig(save_path)
 
-        plt.show()
+        if no_show is None or not no_show:  # pragma: no cover
+            plt.show()  # pragma: no cover
 
-    def plot_force(self, interaction_values: InteractionValues | None = None, save_path: str | None = None) -> None:
+    def plot_force(
+        self,
+        interaction_values: InteractionValues | None = None,
+        save_path: str | None = None,
+        no_show: bool | None = None,
+    ) -> None:
         """Plot the SHAP interaction values as a forceplot graph.
 
         Args:
             interaction_values: Interaction values to plot. Defaults to None.
             save_path: The path to save the plot. Defaults to None.
+            no_show (bool | None, optional): Do not show the plot if set to true. Defaults to None.
 
         """
         if interaction_values is None and self.last_interaction_values is None:
@@ -395,8 +415,8 @@ def plot_force(self, interaction_values: InteractionValues | None = None, save_p
         # if given interaction values use those, else use cached interaction values
         iv = interaction_values if interaction_values is not None else self.last_interaction_values
 
-        if not isinstance(iv, InteractionValues):
-            raise TypeError
+        if not isinstance(iv, InteractionValues):  # pragma: no cover
+            raise TypeError  # pragma: no cover
 
         hyperparameter_names = self.explanation_task.get_hyperparameter_names()
 
@@ -406,4 +426,5 @@ def plot_force(self, interaction_values: InteractionValues | None = None, save_p
         if save_path is not None:
             plt.savefig(save_path)
 
-        plt.show()
+        if no_show is None or not no_show:  # pragma: no cover
+            plt.show()  # pragma: no cover

src/hypershap/surrogate_model.py

@@ -106,8 +106,8 @@ def evaluate_config(self, config: Configuration) -> float:
 
         """
         res = self.evaluate(np.array(config.get_array()))
-        if not isinstance(res, float):
-            raise TypeError
+        if not isinstance(res, float):  # pragma: no cover
+            raise TypeError  # pragma: no cover
         return res
 
     def evaluate_config_batch(self, config_batch: list[Configuration]) -> list[float]:
@@ -121,8 +121,8 @@ def evaluate_config_batch(self, config_batch: list[Configuration]) -> list[float
 
         """
         res = self.evaluate(np.array([config.get_array() for config in config_batch]))
-        if not isinstance(res, list):
-            raise TypeError
+        if not isinstance(res, list):  # pragma: no cover
+            raise TypeError  # pragma: no cover
         return res
 
     @abstractmethod
@@ -163,8 +163,8 @@ def evaluate_config(self, config: Configuration) -> float:
 
         """
         res = self.evaluate(config.get_array())
-        if not isinstance(res, float):
-            raise TypeError
+        if not isinstance(res, float):  # pragma: no cover
+            raise TypeError  # pragma: no cover
         return res
 
     def evaluate_config_batch(self, config_batch: list[Configuration]) -> list[float]:
@@ -178,8 +178,8 @@ def evaluate_config_batch(self, config_batch: list[Configuration]) -> list[float
 
         """
         res = self.evaluate(np.array([config.get_array() for config in config_batch]))
-        if not isinstance(res, list):
-            raise TypeError
+        if not isinstance(res, list):  # pragma: no cover
+            raise TypeError  # pragma: no cover
         return res
 
     def evaluate(self, config_array: np.ndarray) -> float | list[float]:

tests/__init__.py

@@ -0,0 +1 @@
+"""Tests for the HyperSHAP module."""

tests/conftest.py

@@ -0,0 +1,7 @@
+"""Conftest with all pytest plugins for HyperSHAP."""
+
+from __future__ import annotations
+
+pytest_plugins = [
+    "tests.fixtures.simple_setup",
+]

tests/fixtures/__init__.py

@@ -0,0 +1 @@
+"""Fixtures for the HyperSHAP tests."""

tests/fixtures/simple_setup.py

@@ -0,0 +1,72 @@
+"""The module contains simple setup fixtures for more convenient testing."""
+
+from __future__ import annotations
+
+import pytest
+from ConfigSpace import Configuration, ConfigurationSpace, UniformFloatHyperparameter
+
+from hypershap import ExplanationTask
+
+
+@pytest.fixture(scope="session")
+def simple_config_space() -> ConfigurationSpace:
+    """Return a simple config space for testing."""
+    config_space = ConfigurationSpace()
+    config_space.add(UniformFloatHyperparameter("a", 0, 1, 0))
+    config_space.add(UniformFloatHyperparameter("b", 0, 1, 0))
+    return config_space
+
+
+class SimpleBlackboxFunction:
+    """A very simple black box function for testing."""
+
+    def __init__(self, a_coeff: float, b_coeff: float) -> None:
+        """Initialize the simple black box function.
+
+        Args:
+            a_coeff: Coefficient for hyperparameter a.
+            b_coeff: Coefficient for hyperparameter b.
+
+        """
+        self.a_coeff = a_coeff
+        self.b_coeff = b_coeff
+
+    def evaluate(self, x: Configuration) -> float:
+        """Evaluate the value of a configuration.
+
+        Args:
+            x: The configuration to be evaluated.
+
+        Returns: The value of the configuration.
+
+        """
+        return self.value(x["a"], x["b"])
+
+    def value(self, a: float, b: float) -> float:
+        """Evaluate the value of a configuration.
+
+        Args:
+            a: The value for hyperparameter a.
+            b: The value for hyperparameter b.
+
+        """
+        return self.a_coeff * a + self.b_coeff * b
+
+
+@pytest.fixture(scope="session")
+def simple_blackbox_function() -> SimpleBlackboxFunction:
+    """Return a simple blackbox function for testing.
+
+    Returns: The simple blackbox function.
+
+    """
+    return SimpleBlackboxFunction(0.7, 2.0)
+
+
+@pytest.fixture(scope="session")
+def simple_base_et(
+    simple_config_space: ConfigurationSpace,
+    simple_blackbox_function: SimpleBlackboxFunction,
+) -> ExplanationTask:
+    """Return a base explanation task for the simple setup."""
+    return ExplanationTask.from_function(simple_config_space, simple_blackbox_function.evaluate)

tests/test_ablation_game.py

@@ -70,3 +70,6 @@ def evaluate(self, config: np.ndarray) -> float:
         surrogate_model.last_queried_config,
         "Mismatch between expected config and actual config",
     )
+
+    game_hp_names = ablation_game.get_hyperparameter_names()
+    assert game_hp_names == ["a", "b", "c"], "Hyperparameter names mismatch"