def test_get_gbest_toroidal():
"""
swarm.get_best tests.
"""
# Attempted output
output = np.array([[-0.4848329, 1.111317]], dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[:] = 1.0
swarm.misfit[5] = 0.0
# Testing get_gbest for topology: toroidal
np.testing.assert_equal(
swarm.get_gbest(topology='toroidal', indv=8, ndim=3), output)
def test_init_particles():
"""
swarm.init_particles test.
"""
# Attempted output
output = np.array([[[-0.49786797, 1.321947], [-2.9993138, -1.1860045],
[-2.1194646, -2.4459684]],
[[-1.8824388, -0.9266356], [-0.61939514, 0.23290041],
[-0.4848329, 1.111317]]],
dtype=np.float32)
# Initialize the random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_multi_line.txt')
# Initialize particles
swarm.init_particles(2)
# Testing particle initializations
np.testing.assert_equal(swarm.current, output)
def test_init_pspace_multi_line():
"""
swarm.init_pspace test for multipoints search.
"""
# Attempted output
output = np.zeros((3, 2, 3), dtype=np.float32)
output = np.array([[[-3.0, 3.0, 0.6], [-3.0, 3.0, 0.6]],
[[-3.0, 3.0, 0.6], [-3.0, 3.0, 0.6]],
[[-3.0, 3.0, 0.6], [-3.0, 3.0, 0.6]]],
dtype=np.float32)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_multi_line.txt')
# Testing the parameter space initialization
np.testing.assert_equal(swarm.pspace, output)
def test_update_constriction_toroidal():
"""
swarm.update with constriction and toroidal topology options.
"""
# Attempted output
output = np.array(
[[[-0.97847301, 0.72194695]], [[-2.39931393, -1.78600454]],
[[-2.11946464, -2.44596839]], [[-1.28243876, -0.3266356]],
[[-0.55587643, 0.8329004]], [[-1.08483291, 0.51131701]],
[[-2.37328649, 1.66870463]], [[-2.83567452, 1.02280509]],
[[-1.09617114, -0.24786106]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=1, topology='toroidal', ndim=3)
np.testing.assert_equal(swarm.current, output)
def test_update_weight_ring():
"""
swarm.update with inertia weight and ring topology options.
"""
# Attempted output
output = np.array(
[[[-1.09786797, 0.72194695]], [[-2.39931393, -1.78600454]],
[[-2.11946464, -2.44596839]], [[-2.08705616, -1.52663565]],
[[-0.53235936, 0.8329004]], [[-0.48483291, 1.11131704]],
[[-1.17328644, 1.66870463]], [[-2.83567452, 1.02280509]],
[[-1.09617114, 0.7172299]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=0, topology='ring')
np.testing.assert_equal(swarm.current, output)
def test_fiupdate_weight_toroidal():
"""
swarm.fiupdate with inertia weight and toroidal topology options.
"""
# Attempted output
output = np.array([[[-1.097868, 0.72194695]], [[-2.399314, -0.5860045]],
[[-1.5194646, -1.8459684]], [[-1.2824388, -0.3266356]],
[[-1.2193952, 0.16728637]], [[-1.0848329, 0.511317]],
[[-1.1732864, 1.6687046]], [[-2.2356744, 0.42280507]],
[[-1.0961711, 0.952139]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.fiupdate(control=0, topology='toroidal', ndim=3)
np.testing.assert_equal(swarm.current, output)
def test_update_weight_full_pupd():
"""
swarm.update with inertia weight and full topology options.
"""
# Attempted output
output = np.array([[[-1.097868, 0.72194695]], [[-2.9993138, -1.1860045]],
[[-2.1194646, -2.4459684]], [[-1.8824388, -0.9266356]],
[[-1.1416478, -0.30718902]], [[-1.0848329, 0.511317]],
[[-1.7732865, 2.2687047]], [[-2.8356745, 1.0228051]],
[[-1.0961711, -0.24786106]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=0, topology='full', pupd=0.5)
np.testing.assert_equal(swarm.current, output)
def test_update_constriction_toroidal():
"""
swarm.update with constriction and toroidal topology options.
"""
# Attempted output
output = np.array([[[-1.097868, 0.72194695]], [[-2.399314, -1.2596235]],
[[-2.1194646, -2.4459684]], [[-1.2824388, -0.3266356]],
[[-0.4203204, 0.60145724]], [[-1.0848329, 0.511317]],
[[-1.8040688, 1.8742346]], [[-2.8356745, 1.0228051]],
[[-0.74469984, -0.24786106]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=1, topology='toroidal', ndim=3)
np.testing.assert_equal(swarm.current, output)
def test_update_constriction_ring():
"""
swarm.update with constriction and ring topology options.
"""
# Attempted output
output = np.array([[[-1.097868, 0.72194695]], [[-2.399314, -1.2596235]],
[[-2.1194646, -2.4459684]], [[-1.9943244, -1.5266356]],
[[-0.4203204, 0.60145724]], [[-0.4848329, 1.111317]],
[[-1.7359539, 1.9022588]], [[-2.8356745, 1.0228051]],
[[-0.8543527, 0.952139]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=1, topology='ring')
np.testing.assert_equal(swarm.current, output)
def test_update_constriction_full():
"""
swarm.update with constriction and full topology options.
"""
# Attempted output
output = np.array([[[-1.097868, 0.72194695]], [[-2.399314, -1.2596235]],
[[-2.1194646, -2.4459684]], [[-1.9943244, -1.5266356]],
[[-1.2193952, -0.3670996]], [[-1.0848329, 0.511317]],
[[-1.7833169, 1.6687046]], [[-2.7784958, 0.42280507]],
[[-0.74469984, -0.24786106]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=1, topology='full')
np.testing.assert_equal(swarm.current, output)
def test_update_weight_ring():
"""
swarm.update with inertia weight and ring topology options.
"""
# Attempted output
output = np.array([[[-1.097868, 0.72194695]], [[-2.399314, -1.2868801]],
[[-2.1194646, -2.4459684]], [[-2.0357487, -1.5266356]],
[[-0.34661528, 0.7379111]], [[-0.4848329, 1.111317]],
[[-1.722132, 1.7665863]], [[-2.8356745, 1.0228051]],
[[-0.98696524, 0.952139]]],
dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00
swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01
swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53
swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64
swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=0, topology='ring')
np.testing.assert_equal(swarm.current, output)
def test_update_weight_toroidal():
"""
swarm.update with inertia weight and toroidal topology options.
"""
# Attempted output
output = np.array([
[[-1.097868, 0.72194695]],
[[-2.399314, -1.2868801 ]],
[[-2.1194646, -2.4459684 ]],
[[-1.2824388, -0.3266356 ]],
[[-0.34661528, 0.7379111 ]],
[[-1.0848329, 0.511317 ]],
[[-1.8154657, 1.7281866 ]],
[[-2.8356745, 1.0228051 ]],
[[-0.83671474, -0.24786106]]], dtype=np.float32)
# Initialize random number generator
np.random.seed(1)
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Initialize particles
swarm.init_particles(9)
# Fake evaluation
swarm.history[:, :, :] = swarm.current[:, :, :]
swarm.misfit[0] = 1.00; swarm.misfit[1] = 0.28
swarm.misfit[2] = 0.01; swarm.misfit[3] = 0.72
swarm.misfit[4] = 0.53; swarm.misfit[5] = 0.02
swarm.misfit[6] = 0.64; swarm.misfit[7] = 0.21
swarm.misfit[8] = 0.98
# Testing update method
swarm.update(control=0, topology='toroidal', ndim=3)
np.testing.assert_equal(swarm.current, output)
def test_init_pspace_one_line():
"""
swarm.init_pspace test for one point search.
"""
# Attempted output
output = np.zeros((1, 2, 3), dtype=np.float32)
output[0, 0, 0] = -3.0
output[0, 0, 1] = 3.0
output[0, 0, 2] = 0.6
output[0, 1, 0] = -3.0
output[0, 1, 1] = 3.0
output[0, 1, 2] = 0.6
# Initialize the swarm class
swarm = Swarm()
# Initialize the parameter space
swarm.init_pspace('data/pspace_one_line.txt')
# Testing the parameter space initialization
np.testing.assert_equal(swarm.pspace, output)