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,
)