def setUp(self): """Sets up test fixtures""" self.optimizer = LocalBestPSO self.n_particles = 40 self.dimensions = 20 self.options = { 'c1': [1, 2, 3], 'c2': [1, 2, 3], 'k': [5, 10, 15], 'w': [0.9, 0.7, 0.4], 'p': [1] } self.mini_options = {'c1': [1, 2], 'c2': 6, 'k': 5, 'w': 0.9, 'p': 0} self.bounds = (np.array([-5, -5]), np.array([5, 5])) self.iters = 10 self.objective_func = sphere_func self.g = GridSearch(self.optimizer, self.n_particles, self.dimensions, self.options, self.objective_func, self.iters, bounds=None, velocity_clamp=None) self.g_mini = GridSearch(self.optimizer, self.n_particles, self.dimensions, self.mini_options, self.objective_func, self.iters, bounds=None, velocity_clamp=None)
def grid_mini(): """Returns a GridSearch instance with a smaller search-space""" options = {'c1': [1, 2], 'c2': 6, 'k': 5, 'w': 0.9, 'p': 0} return GridSearch(LocalBestPSO, n_particles=40, dimensions=20, options=options, objective_func=sphere_func, iters=10, bounds=None)
def grid_mini(): """Returns a GridSearch instance with a smaller search-space""" options = {"c1": [1, 2], "c2": 6, "k": 5, "w": 0.9, "p": 0} return GridSearch( LocalBestPSO, n_particles=40, dimensions=20, options=options, objective_func=sphere_func, iters=10, bounds=None, )
def test_optimizer_type_fail(self): """Tests that :code:`optimizer` of type :code:`string` raises :code:`TypeError`""" bad_optimizer = 'LocalBestPSO' # a string instead of a class object with self.assertRaises(TypeError): g = GridSearch(bad_optimizer, self.n_particles, self.dimensions, self.options, self.objective_func, self.iters, bounds=None, velocity_clamp=None)
def grid(): """Returns a GridSearch instance""" options = { 'c1': [1, 2, 3], 'c2': [1, 2, 3], 'k': [5, 10, 15], 'w': [0.9, 0.7, 0.4], 'p': [1] } return GridSearch(LocalBestPSO, n_particles=40, dimensions=20, options=options, objective_func=sphere_func, iters=10, bounds=None)
def grid(): """Returns a GridSearch instance""" options = { "c1": [1, 2, 3], "c2": [1, 2, 3], "k": [5, 10, 15], "w": [0.9, 0.7, 0.4], "p": [1], } return GridSearch( LocalBestPSO, n_particles=40, dimensions=20, options=options, objective_func=sphere_func, iters=10, bounds=None, )