Thanks to visit codestin.com
Credit goes to github.com

Skip to content

Commit 35dc87d

Browse files
LC-LinkousLC-Linkous
committed
post integration debug update
1 parent 4c36bea commit 35dc87d

File tree

4 files changed

+33
-89
lines changed

4 files changed

+33
-89
lines changed

‎src/chicken_swarm.py‎

Lines changed: 12 additions & 31 deletions
Original file line numberDiff line numberDiff line change
@@ -3,37 +3,33 @@
33
##--------------------------------------------------------------------\
44
# chicken_swarm_python
55
# './chicken_swarm_python/src/chicken_swarm.py'
6-
# A basic chicken swarm optimization class. This class follows the same
7-
# format as pso_python and pso_basic to make them interchangeable
8-
# in function calls.
9-
#
6+
# A basic chicken swarm optimization class.
107
#
118
# Author(s): Lauren Linkous, Jonathan Lundquist
12-
# Last update: June 14, 2024
9+
# Last update: August 18, 2024
1310
##--------------------------------------------------------------------\
1411

1512

1613
import numpy as np
1714
from numpy.random import Generator, MT19937
1815
import sys
19-
import time
2016
np.seterr(all='raise')
2117

2218

2319
class swarm:
2420
# arguments should take form:
25-
# swarm(int,
26-
# [[float, float, ...]], [[float, float, ...]], [[float, ...]],
21+
# swarm(int, [[float, float, ...]], [[float, float, ...]],
2722
# int, [[float, ...]],
28-
# float, int, int, func, func,
23+
# float, int, int,
24+
# func, func,
2925
# int, int, int, int, int,
30-
# obj, bool)
26+
# class obj, bool)
3127
# int boundary 1 = random, 2 = reflecting
3228
# 3 = absorbing, 4 = invisible
33-
def __init__(self, NO_OF_PARTICLES,
34-
lbound, ubound,
29+
def __init__(self, NO_OF_PARTICLES, lbound, ubound,
3530
output_size, targets,
36-
E_TOL, maxit, boundary, obj_func, constr_func,
31+
E_TOL, maxit, boundary,
32+
obj_func, constr_func,
3733
RN=3, HN=12, MN=8, CN=15, G = 150,
3834
parent=None, detailedWarnings=False):
3935

@@ -219,8 +215,6 @@ def __init__(self, NO_OF_PARTICLES,
219215
self.Flist : List to store fitness values.
220216
self.Fvals : List to store fitness values.
221217
self.Mlast : Last location of particle
222-
self.InitDeviation : Initial deviation of particles.
223-
self.delta_t : static time modulation. retained for comparison to original repo. and swarm export
224218
'''
225219

226220
self.output_size = output_size
@@ -242,7 +236,6 @@ def __init__(self, NO_OF_PARTICLES,
242236
self.Flist = []
243237
self.Fvals = []
244238
self.Mlast = 1*self.ubound
245-
self.InitDeviation = self.absolute_mean_deviation_of_particles()
246239

247240

248241
self.error_message_generator("swarm successfully initialized")
@@ -462,25 +455,14 @@ def check_bounds(self, particle):
462455
return update
463456

464457

465-
def validate_obj_function(self, particle):
466-
# checks the the objective function resolves with the current particle.
467-
# It is possible (and likely) that obj funcs without proper error handling
468-
# will throw over/underflow errors.
469-
# e.g.: numpy does not support float128()
470-
newFVals, noError = self.obj_func(particle, self.output_size)
471-
if noError == False:
472-
#print("!!!!")
473-
pass
474-
return noError
475-
476458
def random_bound(self, particle):
477459
# If particle is out of bounds, bring the particle back in bounds
478460
# The first condition checks if constraints are met,
479461
# and the second determins if the values are to large (positive or negitive)
480462
# and may cause a buffer overflow with large exponents (a bug that was found experimentally)
481-
update = self.check_bounds(particle) or not self.constr_func(self.M[particle]) or not self.validate_obj_function(np.hstack(self.M[self.current_particle]))
463+
update = self.check_bounds(particle) or not self.constr_func(self.M[particle])
482464
if update > 0:
483-
while(self.check_bounds(particle)>0) or (self.constr_func(self.M[particle])==False) or (self.validate_obj_function(self.M[particle])==False):
465+
while(self.check_bounds(particle)>0) or (self.constr_func(self.M[particle])==False):
484466
variation = self.ubound-self.lbound
485467
self.M[particle] = \
486468
np.squeeze(self.rng.random() *
@@ -507,7 +489,7 @@ def absorbing_bound(self, particle):
507489
self.random_bound(particle)
508490

509491
def invisible_bound(self, particle):
510-
update = self.check_bounds(particle) or not self.constr_func(self.M[particle]) or not self.validate_obj_function(self.M[particle])
492+
update = self.check_bounds(particle) or not self.constr_func(self.M[particle])
511493
if update > 0:
512494
self.Active[particle] = 0
513495
else:
@@ -618,7 +600,6 @@ def export_swarm(self):
618600
'maxit': self.maxit,
619601
'E_TOL': self.E_TOL,
620602
'iter': self.iter,
621-
'delta_t': self.delta_t,
622603
'current_particle': self.current_particle,
623604
'number_of_particles': self.number_of_particles,
624605
'allow_update': self.allow_update,

‎src/main_test.py‎

Lines changed: 2 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -10,7 +10,7 @@
1010
# for integration in the AntennaCAT GUI.
1111
#
1212
# Author(s): Lauren Linkous, Jonathan Lundquist
13-
# Last update: June 14, 2024
13+
# Last update: August 18, 2024
1414
##--------------------------------------------------------------------\
1515

1616

@@ -31,7 +31,6 @@
3131
# 3 = absorbing, 4 = invisible
3232

3333

34-
3534
# Objective function dependent variables
3635
LB = func_configs.LB # Lower boundaries, [[0.21, 0, 0.1]]
3736
UB = func_configs.UB # Upper boundaries, [[1, 1, 0.5]]
@@ -43,8 +42,7 @@
4342
func_F = func_configs.OBJECTIVE_FUNC # objective function
4443
constr_F = func_configs.CONSTR_FUNC # constraint function
4544

46-
47-
45+
4846
# chicken swarm specific
4947
RN = 10 # Total number of roosters
5048
HN = 20 # Total number of hens
@@ -81,11 +79,6 @@
8179
# when it is allowed to update and return
8280
# control to optimizer
8381

84-
# for some objective functions, the function
85-
# might not evaluate correctly (e.g., under/overflow)
86-
# so when that happens, the function is not evaluated
87-
# and the 'step' fucntion will re-gen values and try again
88-
8982
mySwarm.call_objective(allow_update)
9083
iter, eval = mySwarm.get_convergence_data()
9184
if (eval < best_eval) and (eval != 0):

‎src/main_test_details.py‎

Lines changed: 1 addition & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -10,7 +10,7 @@
1010
# for integration in the AntennaCAT GUI.
1111
#
1212
# Author(s): Lauren Linkous, Jonathan Lundquist
13-
# Last update: June 14, 2024
13+
# Last update: August 18, 2024
1414
##--------------------------------------------------------------------\
1515

1616

@@ -55,15 +55,6 @@ def __init__(self):
5555
G = 70 # Reorganize groups every G steps
5656
NO_OF_PARTICLES = RN + HN + MN + CN # Number of particles in swarm
5757

58-
# swarm setup
59-
parent = self # Optional parent class for swarm
60-
# (Used for passing debug messages or
61-
# other information that will appear
62-
# in GUI panels)
63-
64-
detailedWarnings = False # Optional boolean for detailed feedback
65-
66-
6758
# Swarm vars
6859
self.best_eval = 1 # Starting eval value
6960

@@ -99,12 +90,6 @@ def debug_message_printout(self, txt):
9990
print(msg)
10091

10192

102-
def record_params(self):
103-
# this function is called from particle_swarm.py to trigger a write to a log file
104-
# running in the AntennaCAT GUI to record the parameter iteration that caused an error
105-
pass
106-
107-
10893
def run(self):
10994

11095
# instantiation of particle swarm optimizer

‎src/main_test_graph.py‎

Lines changed: 18 additions & 33 deletions
Original file line numberDiff line numberDiff line change
@@ -12,7 +12,7 @@
1212
# matplotlib plot of particle location
1313
#
1414
# Author(s): Lauren Linkous, Jonathan Lundquist
15-
# Last update: June 14, 2024
15+
# Last update: August 18, 2024
1616
##--------------------------------------------------------------------\
1717

1818

@@ -27,7 +27,6 @@
2727
#import lundquist_3_var.configs_F as func_configs # multi objective function
2828

2929

30-
3130
class TestGraph():
3231
def __init__(self):
3332

@@ -40,7 +39,6 @@ def __init__(self):
4039
# 3 = absorbing, 4 = invisible
4140

4241

43-
4442
# Objective function dependent variables
4543
LB = func_configs.LB # Lower boundaries, [[0.21, 0, 0.1]]
4644
UB = func_configs.UB # Upper boundaries, [[1, 1, 0.5]]
@@ -52,8 +50,7 @@ def __init__(self):
5250
func_F = func_configs.OBJECTIVE_FUNC # objective function
5351
constr_F = func_configs.CONSTR_FUNC # constraint function
5452

55-
56-
53+
5754
# chicken swarm specific
5855
RN = 10 # Total number of roosters
5956
HN = 20 # Total number of hens
@@ -62,15 +59,6 @@ def __init__(self):
6259
G = 70 # Reorganize groups every G steps
6360
NO_OF_PARTICLES = RN + HN + MN + CN # Number of particles in swarm
6461

65-
# swarm setup
66-
parent = self # Optional parent class for swarm
67-
# (Used for passing debug messages or
68-
# other information that will appear
69-
# in GUI panels)
70-
71-
detailedWarnings = False # Optional boolean for detailed feedback
72-
73-
7462
# Swarm vars
7563
self.best_eval = 1 # Starting eval value
7664

@@ -89,7 +77,6 @@ def __init__(self):
8977

9078

9179

92-
9380
self.mySwarm = swarm(NO_OF_PARTICLES, LB, UB,
9481
OUT_VARS, TARGETS,
9582
E_TOL, MAXIT, BOUNDARY, func_F, constr_F,
@@ -103,16 +90,16 @@ def __init__(self):
10390
# position
10491
self.ax1 = self.fig.add_subplot(121, projection='3d')
10592
self.ax1.set_title("Particle Location, Iteration: " + str(self.ctr))
106-
self.ax1.set_xlabel('X')
107-
self.ax1.set_ylabel('Y')
108-
self.ax1.set_zlabel('Z')
93+
self.ax1.set_xlabel('x_1')
94+
self.ax1.set_ylabel('x_2')
95+
self.ax1.set_zlabel('x_3')
10996
self.scatter1 = None
11097
# fitness
11198
self.ax2 = self.fig.add_subplot(122, projection='3d')
11299
self.ax2.set_title("Fitness Relation to Target")
113-
self.ax2.set_xlabel('X')
114-
self.ax2.set_ylabel('Y')
115-
self.ax2.set_zlabel('Z')
100+
self.ax2.set_xlabel('x_1')
101+
self.ax2.set_ylabel('x_2')
102+
self.ax2.set_zlabel('x_3')
116103
self.scatter2 = None
117104

118105
def debug_message_printout(self, txt):
@@ -124,12 +111,6 @@ def debug_message_printout(self, txt):
124111
print(msg)
125112

126113

127-
def record_params(self):
128-
# this function is called from particle_swarm.py to trigger a write to a log file
129-
# running in the AntennaCAT GUI to record the parameter iteration that caused an error
130-
pass
131-
132-
133114
def update_plot(self, x_coords, y_coords, targets, showTarget=True, clearAx=True):
134115

135116
# check if any points. first call might not have anythign set yet.
@@ -147,12 +128,14 @@ def update_plot(self, x_coords, y_coords, targets, showTarget=True, clearAx=True
147128
self.ax1.set_title("Search Locations, Iteration: " + str(self.ctr))
148129
self.ax1.set_xlabel("$x_1$")
149130
self.ax1.set_ylabel("filler coords")
131+
self.ax1.set_zlabel("filler coords")
150132
self.scatter = self.ax1.scatter(x_coords, x_plot_coords, edgecolors='b')
151133

152134
elif np.shape(x_coords)[1] == 2: #2-dim func
153135
self.ax1.set_title("Search Locations, Iteration: " + str(self.ctr))
154136
self.ax1.set_xlabel("$x_1$")
155137
self.ax1.set_ylabel("$x_2$")
138+
self.ax1.set_zlabel("filler coords")
156139
self.scatter = self.ax1.scatter(x_coords[:,0], x_coords[:,1], edgecolors='b')
157140

158141
elif np.shape(x_coords)[1] == 3: #3-dim func
@@ -167,21 +150,23 @@ def update_plot(self, x_coords, y_coords, targets, showTarget=True, clearAx=True
167150
if np.shape(y_coords)[1] == 1: #1-dim obj func
168151
y_plot_filler = np.array(y_coords[:,0])*0.0
169152
self.ax2.set_title("Global Best Fitness Relation to Target")
170-
self.ax2.set_xlabel("$F_{1}(x,y)$")
153+
self.ax2.set_xlabel("$F_{1}(x_1,x_2)$")
171154
self.ax2.set_ylabel("filler coords")
155+
self.ax2.set_zlabel("filler coords")
172156
self.scatter = self.ax2.scatter(y_coords, y_plot_filler, marker='o', s=40, facecolor="none", edgecolors="k")
173157

174158
elif np.shape(y_coords)[1] == 2: #2-dim obj func
175159
self.ax2.set_title("Global Best Fitness Relation to Target")
176-
self.ax2.set_xlabel("$F_{1}(x,y)$")
177-
self.ax2.set_ylabel("$F_{2}(x,y)$")
160+
self.ax2.set_xlabel("$F_{1}(x_1,x_2)$")
161+
self.ax2.set_ylabel("$F_{2}(x_1,x_2)$")
162+
self.ax2.set_zlabel("filler coords")
178163
self.scatter = self.ax2.scatter(y_coords[:,0], y_coords[:,1], marker='o', s=40, facecolor="none", edgecolors="k")
179164

180165
elif np.shape(y_coords)[1] == 3: #3-dim obj fun
181166
self.ax2.set_title("Global Best Fitness Relation to Target")
182-
self.ax2.set_xlabel("$F_{1}(x,y)$")
183-
self.ax2.set_ylabel("$F_{2}(x,y)$")
184-
self.ax2.set_zlabel("$F_{3}(x,y)$")
167+
self.ax2.set_xlabel("$F_{1}(x_1,x_2)$")
168+
self.ax2.set_ylabel("$F_{2}(x_1,x_2)$")
169+
self.ax2.set_zlabel("$F_{3}(x_1,x_2)$")
185170
self.scatter = self.ax2.scatter(y_coords[:,0], y_coords[:,1], y_coords[:,2], marker='o', s=40, facecolor="none", edgecolors="k")
186171

187172

0 commit comments

Comments
 (0)