def create_swarm(n_particles, dimensions, options, bounds, discrete_index):
position=generate_position(n_particles, dimensions, bounds, discrete_index)
velocity=generate_velocity(n_particles, dimensions,bounds, discrete_index)
swarm= Swarm(position, velocity, options=options)
swarm.discrete_index=discrete_index
return swarm
def swarm():
"""A contrived instance of the Swarm class at a certain timestep"""
# fmt: off
attrs_at_t = {
"position":
np.array([[9.95838686e-01, 5.87433429e-04, 6.49113772e-03],
[1.00559609e+00, 3.96477697e-02, 7.67205397e-01],
[2.87990950e-01, -3.64932609e-02, 1.89750725e-02],
[1.11646877e+00, 3.12037361e-03, 1.97885369e-01],
[8.96117216e-01, -9.79602053e-03, -1.66139336e-01],
[9.90423669e-01, 1.99307974e-03, -1.23386797e-02],
[2.06800701e-01, -1.67869387e-02, 1.14268810e-01],
[4.21786494e-01, 2.58755510e-02, 6.62254843e-01],
[9.90350831e-01, 3.81575154e-03, 8.80833545e-01],
[9.94353749e-01, -4.85086205e-02, 9.85313500e-03]]),
"velocity":
np.array([[2.09076818e-02, 2.04936403e-03, 1.06761248e-02],
[1.64940497e-03, 5.67924469e-03, 9.74902301e-02],
[1.50445516e-01, 9.11699158e-03, 1.51474794e-02],
[2.94238740e-01, 5.71545680e-04, 1.54122294e-02],
[4.10430034e-02, 6.51847479e-04, 6.25109226e-02],
[6.71076116e-06, 1.89615516e-04, 4.65023770e-03],
[4.76081378e-02, 4.24416089e-03, 7.11856172e-02],
[1.33832808e-01, 1.81818698e-02, 1.16947941e-01],
[1.22849955e-03, 1.55685312e-03, 1.67819003e-02],
[5.60617396e-03, 4.31819608e-02, 2.52217220e-02]]),
"current_cost":
np.array([
1.07818462, 5.5647911, 19.6046078, 14.05300016, 3.72597614,
1.01169386, 16.51846203, 32.72262829, 3.80274901, 1.05237138
]),
"pbest_cost":
np.array([
1.00362006, 2.39151041, 2.55208424, 5.00176207, 1.04510827,
1.00025284, 6.31216654, 2.53873121, 2.00530884, 1.05237138
]),
"pbest_pos":
np.array([[9.98033031e-01, 4.97392619e-03, 3.07726256e-03],
[1.00665809e+00, 4.22504014e-02, 9.84334657e-01],
[1.12159389e-02, 1.11429739e-01, 2.86388193e-02],
[1.64059236e-01, 6.85791237e-03, -2.32137604e-02],
[9.93740665e-01, -6.16501403e-03, -1.46096578e-02],
[9.90438476e-01, 2.50379538e-03, 1.87405987e-05],
[1.12301876e-01, 1.77099784e-03, 1.45382457e-01],
[4.41204876e-02, 4.84059652e-02, 1.05454822e+00],
[9.89348409e-01, -1.31692358e-03, 9.88291764e-01],
[9.99959923e-01, -5.32665972e-03, -1.53685870e-02]]),
"best_cost":
1.0002528364353296,
"best_pos":
np.array([9.90438476e-01, 2.50379538e-03, 1.87405987e-05]),
"options": {
'c1': 0.5,
'c2': 0.3,
'w': 0.9
},
}
# fmt: on
return Swarm(**attrs_at_t)
def swarm():
"""A contrived instance of the Swarm class at a certain timestep"""
attrs_at_t = {
"position": np.array([[5, 5, 5], [3, 3, 3], [1, 1, 1]]),
"velocity": np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]]),
"current_cost": np.array([2, 2, 2]),
"pbest_cost": np.array([1, 2, 3]),
"pbest_pos": np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
"best_cost": 1,
"best_pos": np.array([1, 1, 1]),
"options": {
"c1": 0.5,
"c2": 1,
"w": 2
},
}
return Swarm(**attrs_at_t)
def swarm():
"""A contrived instance of the Swarm class at a certain timestep"""
attrs_at_t = {
'position': np.array([[5, 5, 5], [3, 3, 3], [1, 1, 1]]),
'velocity': np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]]),
'current_cost': np.array([2, 2, 2]),
'pbest_cost': np.array([1, 2, 3]),
'pbest_pos': np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
'best_cost': 1,
'best_pos': np.array([1, 1, 1]),
'options': {
'c1': 0.5,
'c2': 1,
'w': 2
}
}
return Swarm(**attrs_at_t)