Merge pull request #6 from javidahmed64592/add-matrix-mutation-method

Add method to mutate matrix

neural_network/math/matrix.py

@@ -201,3 +201,22 @@ def average_matrix(matrix: Matrix, other_matrix: Matrix) -> Matrix:
         """
         new_matrix = np.average([matrix.data, other_matrix.data], axis=0)
         return Matrix.from_array(new_matrix)
+
+    @staticmethod
+    def mutated_matrix(matrix: Matrix, mutation_rate: float, random_range: List[float]) -> Matrix:
+        """
+        Mutate Matrix with a mutation rate.
+
+        Parameters:
+            matrix (Matrix): Matrix to use for average
+            mutation_rate (float): Probability for mutation
+            random_range (List[float]): Range for random number
+
+        Returns:
+            new_matrix (Matrix): Mutated Matrix
+        """
+        _mutation_matrix = np.random.uniform(low=0, high=1, size=matrix.shape)
+        new_matrix = np.where(
+            _mutation_matrix < mutation_rate, np.random.uniform(low=random_range[0], high=random_range[1]), matrix.data
+        )
+        return Matrix.from_array(new_matrix)

setup.py

@@ -1,6 +1,6 @@
 from setuptools import find_packages, setup  # type: ignore
 
-__version__ = "1.1.0"
+__version__ = "1.2.0"
 
 setup(
     name="neural_network",

tests/math/test_matrix.py

@@ -130,3 +130,16 @@ def test_given_two_matrices_when_calculating_average_matrix_then_check_new_matri
         expected_vals = np.array([[0, 1.5], [3, -1], [2.5, 3]])
         actual_vals = new_matrix.data
         assert np.all(actual_vals == expected_vals)
+
+    def test_given_matrix_when_mutating_then_check_new_matrix_with_same_shape_returned(self):
+        array_1 = np.array([[1, 2], [4, 3], [2, 4]])
+        mutation_rate = 0.5
+        random_range = [1.0, 4.0]
+
+        matrix_1 = Matrix.from_array(array_1)
+        new_matrix = Matrix.mutated_matrix(matrix_1, mutation_rate, random_range)
+
+        expected_shape = matrix_1.shape
+        actual_shape = new_matrix.shape
+        assert np.all(actual_shape == expected_shape)
+        assert not np.all(matrix_1.data == new_matrix.data)