Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly
Sign up
Appearance settings

Commit c6949e1

Browse files
Refactor code to remove duplicate sections
1 parent f492bb3 commit c6949e1

File tree

1 file changed

+140
-72
lines changed

1 file changed

+140
-72
lines changed

‎pygad/helper/unique.py

Lines changed: 140 additions & 72 deletions
Original file line numberDiff line numberDiff line change
@@ -25,7 +25,7 @@ def solve_duplicate_genes_randomly(self,
2525
max_val (int): The maximum value of the range to sample a number randomly.
2626
mutation_by_replacement (bool): Indicates if mutation is performed by replacement.
2727
gene_type (type): The data type of the gene (e.g., int, float).
28-
num_trials (int): The maximum number of attempts to resolve duplicates by changing the gene values.
28+
num_trials (int): The maximum number of attempts to resolve duplicates by changing the gene values. Only works for floating-point gene types.
2929
3030
Returns:
3131
tuple:
@@ -42,53 +42,48 @@ def solve_duplicate_genes_randomly(self,
4242
num_unsolved_duplicates = 0
4343
if len(not_unique_indices) > 0:
4444
for duplicate_index in not_unique_indices:
45-
for trial_index in range(num_trials):
46-
if self.gene_type_single == True:
47-
dtype = gene_type
48-
else:
49-
dtype = gene_type[duplicate_index]
50-
51-
if dtype[0] in pygad.GA.supported_int_types:
52-
temp_val = self.unique_int_gene_from_range(solution=new_solution,
53-
gene_index=duplicate_index,
54-
min_val=min_val,
55-
max_val=max_val,
56-
mutation_by_replacement=mutation_by_replacement,
57-
gene_type=gene_type)
58-
else:
59-
temp_val = numpy.random.uniform(low=min_val,
60-
high=max_val,
61-
size=1)[0]
62-
if mutation_by_replacement:
45+
if self.gene_type_single == True:
46+
dtype = gene_type
47+
else:
48+
dtype = gene_type[duplicate_index]
49+
50+
if dtype[0] in pygad.GA.supported_int_types:
51+
temp_val = self.unique_int_gene_from_range(solution=new_solution,
52+
gene_index=duplicate_index,
53+
min_val=min_val,
54+
max_val=max_val,
55+
mutation_by_replacement=mutation_by_replacement,
56+
gene_type=gene_type)
57+
else:
58+
temp_val = self.unique_float_gene_from_range(solution=new_solution,
59+
gene_index=duplicate_index,
60+
min_val=min_val,
61+
max_val=max_val,
62+
mutation_by_replacement=mutation_by_replacement,
63+
gene_type=gene_type,
64+
num_trials=num_trials)
65+
"""
66+
temp_val = numpy.random.uniform(low=min_val,
67+
high=max_val,
68+
size=1)[0]
69+
if mutation_by_replacement:
6370
pass
64-
else:
71+
else:
6572
temp_val = new_solution[duplicate_index] + temp_val
73+
"""
74+
75+
if temp_val in new_solution:
76+
num_unsolved_duplicates = num_unsolved_duplicates + 1
77+
if not self.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {solution[duplicate_index]}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
78+
else:
79+
# Unique gene value found.
80+
new_solution[duplicate_index] = temp_val
81+
82+
# Update the list of duplicate indices after each iteration.
83+
_, unique_gene_indices = numpy.unique(new_solution, return_index=True)
84+
not_unique_indices = set(range(len(solution))) - set(unique_gene_indices)
85+
# self.logger.info("not_unique_indices INSIDE", not_unique_indices)
6686

67-
# Similar to the round_genes() method in the pygad module,
68-
# Create a round_gene() method to round a single gene.
69-
if not dtype[1] is None:
70-
temp_val = numpy.round(dtype[0](temp_val),
71-
dtype[1])
72-
else:
73-
temp_val = dtype[0](temp_val)
74-
75-
if temp_val in new_solution and trial_index == (num_trials - 1):
76-
num_unsolved_duplicates = num_unsolved_duplicates + 1
77-
if not self.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {solution[duplicate_index]}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
78-
elif temp_val in new_solution:
79-
# Keep trying in the other remaining trials.
80-
continue
81-
else:
82-
# Unique gene value found.
83-
new_solution[duplicate_index] = temp_val
84-
break
85-
86-
# TODO Move this code outside the loops.
87-
# Update the list of duplicate indices after each iteration.
88-
_, unique_gene_indices = numpy.unique(new_solution, return_index=True)
89-
not_unique_indices = set(range(len(solution))) - set(unique_gene_indices)
90-
# self.logger.info("not_unique_indices INSIDE", not_unique_indices)
91-
9287
return new_solution, not_unique_indices, num_unsolved_duplicates
9388

9489
def solve_duplicate_genes_by_space(self,
@@ -167,14 +162,14 @@ def unique_int_gene_from_range(self,
167162
Args:
168163
solution (list): A solution containing genes, potentially with duplicate values.
169164
gene_index (int): The index of the gene for which to find a unique value.
170-
min_val (int): The minimum value of the range to sample a number randomly.
171-
max_val (int): The maximum value of the range to sample a number randomly.
165+
min_val (int): The minimum value of the range to sample an integer randomly.
166+
max_val (int): The maximum value of the range to sample an integer randomly.
172167
mutation_by_replacement (bool): Indicates if mutation is performed by replacement.
173-
gene_type (type): The data type of the gene (e.g., int, float).
168+
gene_type (type): The data type of the gene (e.g., int, int8, uint16, etc).
174169
step (int, optional): The step size for generating candidate values. Defaults to 1.
175170
176171
Returns:
177-
int: The new value of the gene. If no unique value can be found, the original gene value is returned.
172+
int: The new integer value of the gene. If no unique value can be found, the original gene value is returned.
178173
"""
179174

180175
# The gene_type is of the form [type, precision]
@@ -194,22 +189,86 @@ def unique_int_gene_from_range(self,
194189
else:
195190
all_gene_values = all_gene_values + solution[gene_index]
196191

197-
# After adding solution[gene_index] to the list, we have to change the data type again.
198-
# TODO: The gene data type is converted twine. One above and one here.
199-
all_gene_values = numpy.asarray(all_gene_values,
200-
dtype)
192+
# After adding solution[gene_index] to the list, we have to change the data type again.
193+
all_gene_values = numpy.asarray(all_gene_values,
194+
dtype)
201195

202196
values_to_select_from = list(set(list(all_gene_values)) - set(solution))
203197

204198
if len(values_to_select_from) == 0:
205199
# If there are no values, then keep the current gene value.
206-
if not self.suppress_warnings: warnings.warn("You set 'allow_duplicate_genes=False' but there is no enough values to prevent duplicates.")
207200
selected_value = solution[gene_index]
208201
else:
209202
selected_value = random.choice(values_to_select_from)
203+
204+
selected_value = dtype[0](selected_value)
210205

211206
return selected_value
212207

208+
def unique_float_gene_from_range(self,
209+
solution,
210+
gene_index,
211+
min_val,
212+
max_val,
213+
mutation_by_replacement,
214+
gene_type,
215+
num_trials=10):
216+
217+
"""
218+
Finds a unique floating-point value for a specific gene in a solution.
219+
220+
Args:
221+
solution (list): A solution containing genes, potentially with duplicate values.
222+
gene_index (int): The index of the gene for which to find a unique value.
223+
min_val (int): The minimum value of the range to sample a floating-point number randomly.
224+
max_val (int): The maximum value of the range to sample a floating-point number randomly.
225+
mutation_by_replacement (bool): Indicates if mutation is performed by replacement.
226+
gene_type (type): The data type of the gene (e.g., float, float16, float32, etc).
227+
num_trials (int): The maximum number of attempts to resolve duplicates by changing the gene values.
228+
229+
Returns:
230+
int: The new floating-point value of the gene. If no unique value can be found, the original gene value is returned.
231+
"""
232+
233+
# The gene_type is of the form [type, precision]
234+
dtype = gene_type
235+
236+
for trial_index in range(num_trials):
237+
temp_val = numpy.random.uniform(low=min_val,
238+
high=max_val,
239+
size=1)[0]
240+
241+
# If mutation is by replacement, do not add the current gene value into the list.
242+
# This is to avoid replacing the value by itself again. We are doing nothing in this case.
243+
if mutation_by_replacement:
244+
pass
245+
else:
246+
temp_val = temp_val + solution[gene_index]
247+
248+
if not dtype[1] is None:
249+
# Precision is available and we have to round the number.
250+
# Convert the data type and round the number.
251+
temp_val = numpy.round(dtype[0](temp_val),
252+
dtype[1])
253+
else:
254+
# There is no precision and rounding the number is not needed. The type is [type, None]
255+
# Just convert the data type.
256+
temp_val = dtype[0](temp_val)
257+
258+
if temp_val in solution and trial_index == (num_trials - 1):
259+
# If there are no values, then keep the current gene value.
260+
if not self.suppress_warnings: warnings.warn("You set 'allow_duplicate_genes=False' but cannot find a value to prevent duplicates.")
261+
selected_value = solution[gene_index]
262+
elif temp_val in solution:
263+
# Keep trying in the other remaining trials.
264+
continue
265+
else:
266+
# Unique gene value found.
267+
selected_value = temp_val
268+
break
269+
270+
return selected_value
271+
213272
def unique_genes_by_space(self,
214273
new_solution,
215274
gene_type,
@@ -225,7 +284,7 @@ def unique_genes_by_space(self,
225284
new_solution (list): A solution containing genes with duplicate values.
226285
gene_type (type): The data type of the gene (e.g., int, float).
227286
not_unique_indices (list): The indices of genes with duplicate values.
228-
num_trials (int): The maximum number of attempts to resolve duplicates for each gene.
287+
num_trials (int): The maximum number of attempts to resolve duplicates for each gene. Only works for floating-point numbers.
229288
230289
Returns:
231290
tuple:
@@ -236,22 +295,18 @@ def unique_genes_by_space(self,
236295

237296
num_unsolved_duplicates = 0
238297
for duplicate_index in not_unique_indices:
239-
for trial_index in range(num_trials):
240-
temp_val = self.unique_gene_by_space(solution=new_solution,
241-
gene_idx=duplicate_index,
242-
gene_type=gene_type,
243-
build_initial_pop=build_initial_pop)
244-
245-
if temp_val in new_solution and trial_index == (num_trials - 1):
246-
# self.logger.info("temp_val, duplicate_index", temp_val, duplicate_index, new_solution)
247-
num_unsolved_duplicates = num_unsolved_duplicates + 1
248-
if not self.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {new_solution[duplicate_index]}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
249-
elif temp_val in new_solution:
250-
continue
251-
else:
252-
new_solution[duplicate_index] = temp_val
253-
# self.logger.info("SOLVED", duplicate_index)
254-
break
298+
temp_val = self.unique_gene_by_space(solution=new_solution,
299+
gene_idx=duplicate_index,
300+
gene_type=gene_type,
301+
build_initial_pop=build_initial_pop,
302+
num_trials=num_trials)
303+
304+
if temp_val in new_solution:
305+
# self.logger.info("temp_val, duplicate_index", temp_val, duplicate_index, new_solution)
306+
num_unsolved_duplicates = num_unsolved_duplicates + 1
307+
if not self.suppress_warnings: warnings.warn(f"Failed to find a unique value for gene with index {duplicate_index} whose value is {new_solution[duplicate_index]}. Consider adding more values in the gene space or use a wider range for initial population or random mutation.")
308+
else:
309+
new_solution[duplicate_index] = temp_val
255310

256311
# Update the list of duplicate indices after each iteration.
257312
_, unique_gene_indices = numpy.unique(new_solution, return_index=True)
@@ -264,7 +319,8 @@ def unique_gene_by_space(self,
264319
solution,
265320
gene_idx,
266321
gene_type,
267-
build_initial_pop=False):
322+
build_initial_pop=False,
323+
num_trials=10):
268324

269325
"""
270326
Returns a unique value for a specific gene based on its value space to resolve duplicates.
@@ -273,6 +329,7 @@ def unique_gene_by_space(self,
273329
solution (list): A solution containing genes with duplicate values.
274330
gene_idx (int): The index of the gene that has a duplicate value.
275331
gene_type (type): The data type of the gene (e.g., int, float).
332+
num_trials (int): The maximum number of attempts to resolve duplicates for each gene. Only works for floating-point numbers.
276333
277334
Returns:
278335
Any: A unique value for the gene, if one exists; otherwise, the original gene value. """
@@ -320,9 +377,20 @@ def unique_gene_by_space(self,
320377
low = self.random_mutation_min_val
321378
high = self.random_mutation_max_val
322379

380+
"""
323381
value_from_space = numpy.random.uniform(low=low,
324382
high=high,
325383
size=1)[0]
384+
"""
385+
386+
value_from_space = self.unique_float_gene_from_range(solution=solution,
387+
gene_index=gene_idx,
388+
min_val=low,
389+
max_val=high,
390+
mutation_by_replacement=True,
391+
gene_type=dtype,
392+
num_trials=num_trials)
393+
326394

327395
elif type(curr_gene_space) is dict:
328396
if self.gene_type_single == True:

0 commit comments

Comments
(0)

AltStyle によって変換されたページ (->オリジナル) /