Merge pull request #2 from benedekrozemberczki/abc-test-suite

ABC Test suite

setup.py

@@ -37,13 +37,13 @@
 setup(
     name="shapley",
     packages=find_packages(),
-    version="1.0.2",
+    version="1.0.3",
     license="MIT",
     description="A general purpose library to quantify the value of classifiers in an ensemble.",
     author="Benedek Rozemberczki",
     author_email="[email protected]",
     url="https://github.com/benedekrozemberczki/shapley",
-    download_url="https://github.com/benedekrozemberczki/shapley/archive/v_10002.tar.gz",
+    download_url="https://github.com/benedekrozemberczki/shapley/archive/v_10003.tar.gz",
     keywords=keywords,
     install_requires=install_requires,
     setup_requires=setup_requires,

shapley/__init__.py

@@ -1,5 +1,6 @@
 from shapley.solvers import *
 from shapley.solution_concept import SolutionConcept
+from shapley.version import __version__  # noqa:F401,F403
 
 __all__ = [
     "shapley",

shapley/solution_concept.py

@@ -1,13 +1,35 @@
 """Solution Concept base class."""
 
+
 import numpy as np
+from abc import ABCMeta, abstractmethod
 
 
-class SolutionConcept(object):
+class SolutionConcept(metaclass=ABCMeta):
     """Solution Concept base class with constructor and public methods."""
 
-    def __init__(self):
-        """Creating a Solution Concept."""
+    @abstractmethod
+    def get_solution(self) -> np.ndarray:
+        r"""Returning the solution.
+
+        Return Types:
+            Phi (Numpy array): Approximate Shapley matrix of players in the game(s) with size :math:`n \times m`.
+        """
+        pass
+
+    @abstractmethod
+    def solve_game(self, W: np.ndarray, q: float):
+        r"""Solving the weigted voting game(s).
+
+        Args:
+            W (Numpy array): An :math:`n \times m` matrix of voting weights for the :math:`n` games with :math:`m` players.
+            q (float): Quota in the games.
+        """
+        pass
+
+    @abstractmethod
+    def setup(self, W: np.ndarray):
+        """Creating an empty Shapley value matrix and a player pool."""
         pass
 
     def _check_quota(self, q: float):

shapley/solvers/exact_enumeration.py

@@ -11,7 +11,7 @@ class ExactEnumeration(SolutionConcept):
     `"A Value for N-Person Games." <https://www.rand.org/pubs/papers/P0295.html>`_
     """
 
-    def _setup(self, W: np.ndarray):
+    def setup(self, W: np.ndarray):
         """Creating an empty Shapley value matrix and a player pool."""
         self._Phi = np.zeros(W.shape)
         self._indices = [i for i in range(W.shape[1])]
@@ -36,7 +36,7 @@ def solve_game(self, W: np.ndarray, q: float):
             q (float): Quota in the games.
         """
         self._check_quota(q)
-        self._setup(W)
+        self.setup(W)
         self._run_permutations(W, q)
         self._run_sanity_check(W, self._Phi)
         self._set_average_shapley()

shapley/solvers/expected_marginal_contributions.py

@@ -18,7 +18,7 @@ def create_integrand_vectors(player_count, q, w):
     :return b_s: Vector of upper integrand limits.
     """
     a_s = (q - w) / np.linspace(1, player_count - 1, player_count - 1)
-    b_s = (q - 10 ** -20) / np.linspace(1, player_count - 1, player_count - 1)
+    b_s = (q - 10**-20) / np.linspace(1, player_count - 1, player_count - 1)
     return a_s, b_s
 
 
@@ -42,10 +42,10 @@ class ExpectedMarginalContributions(SolutionConcept):
      <https://www.sciencedirect.com/science/article/pii/S0004370208000696>`_
     """
 
-    def __init__(self, epsilon: float = 10 ** -8):
+    def __init__(self, epsilon: float = 10**-8):
         self.epsilon = epsilon
 
-    def _setup(self, W: np.ndarray):
+    def setup(self, W: np.ndarray):
         """Creating an empty Shapley value matrix."""
         self._Phi = np.zeros(W.shape)
 
@@ -73,7 +73,7 @@ def solve_game(self, W: np.ndarray, q: float):
             q (float): Quota in the games.
         """
         self._check_quota(q)
-        self._setup(W)
+        self.setup(W)
         self._approximate(W, q)
         self._run_sanity_check(W, self._Phi)
         self._set_average_shapley()

shapley/solvers/multilinear_extension.py

@@ -12,7 +12,7 @@ class MultilinearExtension(SolutionConcept):
     `"Multilinear Extensions of Games."  <https://www.jstor.org/stable/2661445#metadata_info_tab_contents>`_
     """
 
-    def _setup(self, W: np.ndarray):
+    def setup(self, W: np.ndarray):
         """Creating an empty Shapley value matrix."""
         self._Phi = np.zeros(W.shape)
 
@@ -35,7 +35,7 @@ def solve_game(self, W: np.ndarray, q: float):
             q (float): Quota in the games.
         """
         self._check_quota(q)
-        self._setup(W)
+        self.setup(W)
         self._approximate(W, q)
         self._run_sanity_check(W, self._Phi)
         self._set_average_shapley()

shapley/solvers/permutation_sampler.py

@@ -20,7 +20,7 @@ class PermutationSampler(SolutionConcept):
     def __init__(self, permutations: int = 1000):
         self.permutations = permutations
 
-    def _setup(self, W: np.ndarray):
+    def setup(self, W: np.ndarray):
         """Creating an empty Shapley value matrix and a player pool."""
         self._Phi = np.zeros(W.shape)
         self._indices = [i for i in range(W.shape[1])]
@@ -43,7 +43,7 @@ def solve_game(self, W: np.ndarray, q: float):
             q (float): Quota in the games.
         """
         self._check_quota(q)
-        self._setup(W)
+        self.setup(W)
         self._run_permutations(W, q)
         self._run_sanity_check(W, self._Phi)
         self._set_average_shapley()

shapley/version.py

@@ -0,0 +1,3 @@
+"""Contains the version of ChemicalX."""
+
+__version__ = "1.0.3"