@@ -184,13 +184,9 @@ def unique_int_gene_from_range(self,
184184 all_gene_values = numpy.asarray(all_gene_values,
185185 dtype[0])
186186
187- values_to_select_from = list(set(list(all_gene_values)) - set(solution))
188- 189- if len(values_to_select_from) == 0:
190- # If there are no values, then keep the current gene value.
191- selected_value = solution[gene_index]
192- else:
193- selected_value = random.choice(values_to_select_from)
187+ selected_value = self.select_unique_value(gene_values=all_gene_values,
188+ solution=solution,
189+ gene_index=gene_index)
194190
195191 selected_value = dtype[0](selected_value)
196192
@@ -224,39 +220,57 @@ def unique_float_gene_from_range(self,
224220 # The gene_type is of the form [type, precision]
225221 dtype = gene_type
226222
227- for trial_index in range(num_trials):
228- temp_val = numpy.random.uniform(low=min_val,
229- high=max_val,
230- size=1)[0]
223+ # We cannot have a list of all values out of a continous range.
224+ # Solution is to create a subset (e.g. 100) of all the values.
225+ some_gene_values = numpy.random.uniform(low=min_val,
226+ high=max_val,
227+ size=100)
231228
232- # If mutation is by replacement, do not add the current gene value into the list.
233- # This is to avoid replacing the value by itself again. We are doing nothing in this case.
234- if mutation_by_replacement:
235- pass
236- else:
237- temp_val = temp_val + solution[gene_index]
229+ # If mutation is by replacement, do not add the current gene value into the list.
230+ # This is to avoid replacing the value by itself again. We are doing nothing in this case.
231+ if mutation_by_replacement:
232+ pass
233+ else:
234+ some_gene_values = some_gene_values + solution[gene_index]
235+ 236+ if not dtype[1] is None:
237+ # Precision is available and we have to round the number.
238+ # Convert the data type and round the number.
239+ some_gene_values = numpy.round(numpy.asarray(some_gene_values,
240+ dtype[0]),
241+ dtype[1])
242+ else:
243+ # There is no precision and rounding the number is not needed. The type is [type, None]
244+ # Just convert the data type.
245+ some_gene_values = numpy.asarray(some_gene_values,
246+ dtype[0])
247+ 248+ selected_value = self.select_unique_value(gene_values=some_gene_values,
249+ solution=solution,
250+ gene_index=gene_index)
251+ return selected_value
238252
239- if not dtype[1] is None :
240- # Precision is available and we have to round the number.
241- # Convert the data type and round the number.
242- temp_val = numpy.round(dtype[0](temp_val),
243- dtype[1])
244- else :
245- # There is no precision and rounding the number is not needed. The type is [type, None]
246- # Just convert the data type .
247- temp_val = dtype[0](temp_val)
248- 249- if temp_val in solution and trial_index == (num_trials - 1):
250- # If there are no values, then keep the current gene value.
251- if not self.suppress_warnings: warnings.warn("You set 'allow_duplicate_genes=False' but cannot find a value to prevent duplicates.")
252- selected_value = solution[gene_index]
253- elif temp_val in solution:
254- # Keep trying in the other remaining trials.
255- continue
256- else:
257- # Unique gene value found.
258- selected_value = temp_val
259- break
253+ def select_unique_value(self, gene_values, solution, gene_index) :
254+ 255+ """
256+ Select a unique value (if possible) from a list of gene values.
257+ 258+ Args :
259+ gene_values (NumPy Array): An array of values from which a unique value should be selected.
260+ solution (list): A solution containing genes, potentially with duplicate values .
261+ 262+ Returns:
263+ selected_gene: The new (hopefully unique) value of the gene. If no unique value can be found, the original gene value is returned.
264+ """
265+ 266+ values_to_select_from = list(set(list(gene_values)) - set( solution))
267+ 268+ if len(values_to_select_from) == 0:
269+ # If there are no values, then keep the current gene value.
270+ if not self.suppress_warnings: warnings.warn("You set 'allow_duplicate_genes=False' but cannot find a value to prevent duplicates.")
271+ selected_value = solution[gene_index]
272+ else:
273+ selected_value = random.choice(values_to_select_from)
260274
261275 return selected_value
262276
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