--- a
+++ b/cmaes/test_problems.py
@@ -0,0 +1,82 @@
+# Copyright (c) 2015, Disney Research
+# All rights reserved.
+#
+# Author(s): Sehoon Ha <sehoon.ha@disneyresearch.com>
+# Disney Research Robotics Group
+
+
+import numpy as np
+
+
+class QuadProb(object):
+    def __init__(self, x=None):
+        self.dim = 4
+        self.x = np.array([0.5, 0.7, -0.5, 1.0])
+        if x is not None:
+            self.dim = len(x)
+            self.x = x
+
+    def f(self, x):
+        diff = x - self.x
+        return 0.5 * np.linalg.norm(diff) ** 2
+
+
+class Rosen(object):
+    def __init__(self):
+        self.dim = 10
+
+    def f(self, x):
+        import scipy.optimize
+        return scipy.optimize.rosen(x)
+
+    def bounds(self):
+        return [(-0.5, 0.5)] * self.dim
+
+    def on_eval_f(self, solver):
+        counter = solver.eval_counter
+        value = solver.last_f
+        # if counter % 10 == 0:
+        #     solver.plot_convergence()
+
+
+class ConstrainedQuadProb(object):
+    def __init__(self, x=None):
+        self.dim = 4
+        self.x = x if x is not None else np.array([0.5, 0.7, -0.5, 1.0])
+
+    def f(self, x):
+        diff = x - self.x
+        return 0.5 * np.linalg.norm(diff) ** 2
+
+    def num_eq_constraints(self):
+        return 2
+
+    def c_eq(self, x, index):
+        if index == 0:
+            return x[0] + x[1] - 1.0
+        elif index == 1:
+            return x[1] + x[2] - 1.0
+
+    def c_eq_jac(self, x, index):
+        """ (optional) """
+        if index == 0:
+            return np.array([1.0, 1.0, 0.0, 0.0])
+        elif index == 1:
+            return np.array([0.0, 1.0, 1.0, 0.0])
+
+    def num_ineq_constraints(self):
+        return 1
+
+    def c_ineq(self, x, index):
+        if index == 0:
+            return x[3] - 1.2
+
+
+if __name__ == '__main__':
+    print('test optimization problems')
+    prob = QuadProb(np.array([0.5, -0.3, 0.9]))
+    print('prob.dim = %d' % (prob.dim))
+    from optimization.solver_cma import CMASolver as Solver
+    solver = Solver(prob)
+    res = solver.solve()
+    print(res)