schwefel class

src/schwefel.py

@@ -0,0 +1,32 @@
+import numpy as np
+
+class SchwefelProblem:
+    def __init__(self, n_var=1, noise_level=0.01):
+        """
+        y = f(x) + eps
+        """
+        self.noise_level = noise_level
+        self.n_var = n_var  # Number of variables/dimensions
+        self.bounds = np.array([[-500] * self.n_var, [500] * self.n_var])
+
+    def _schwefel_individual(self, x):
+        return x * np.sin(np.sqrt(np.abs(x)))
+
+    def f(self, x):
+        return 418.9829 * self.n_var - np.sum(self._schwefel_individual(x), axis=1) 
+
+    def eps(self, x):
+        # Assuming the noise is independent of x for simplicity
+        return np.random.normal(0, self.noise_level, x.shape[0])
+
+    def y(self, x):
+        return self.f(x) + self.eps(x)
+
+# Test code if this file is the main program being run
+if __name__ == "__main__":
+    # Create a SchwefelProblem instance with 3 variables/dimensions
+    schwefel = SchwefelProblem(n_var=3, noise_level=1.)
+    x_test = np.array([[420, 420, 420], [420, 420, 420]])  # Example input vector
+    print("Objective function value (f):", schwefel.f(x_test))
+    print("Noisy objective function value (y):", schwefel.y(x_test))
+