wrote standalone tester for optimizer

rosplane_tuning/src/autotune/optimizer_tester.py

@@ -0,0 +1,36 @@
+from optimizer import Optimizer
+import numpy as np
+
+
+# Function to test the optimizer with
+def function(x):
+    # Matyas function
+    return 0.26 * (x[0] ** 2 + x[1] ** 2) - 0.48 * x[0] * x[1]
+
+
+# Initialize optimizer
+points = np.array([[1, 2]])  # Initial point
+optimization_params = {'u1': 1e-4,
+                       'u2': 0.5,
+                       'sigma': 1.5,
+                       'alpha': 1.0,
+                       'tau': 1e-3}
+optimizer = Optimizer(points[0], optimization_params)
+
+
+while not optimizer.optimization_terminated():
+    # Print status
+    print(optimizer.get_optimiztion_status())
+
+    # Calculate error for current points
+    error = []
+    for point in points:
+        error.append(function(point))
+    error = np.array(error)
+
+    # Pass points to optimizer
+    points = optimizer.get_next_parameter_set(error)
+
+
+print('Optimization terminated with status: {}'.format(optimizer.get_optimiztion_status()))
+