def compute_upper_bound(docs, evaluation_info, length, iterations,
population_size, THRESHOLD):
sim_mat = evaluation_info['sim_matrix']['sim_mat'].T
SCU_Props = evaluation_info['sim_matrix']['SCUProps']
Source_Props = evaluation_info['sim_matrix']['SourceProps']
sentences = []
for _, doc in docs:
for s in doc:
sentences.append(s)
sentences = clean_sentences(sentences, Source_Props, sim_mat, THRESHOLD)
gen_opt = GeneticAlgorithm.GeneticOptimizer(
PEAK.PEAK,
sentences,
evaluation_info,
length,
population_size=population_size,
survival_rate=0.4,
mutation_rate=0.2,
reproduction_rate=0.4,
THRESHOLD=THRESHOLD,
maximization=True)
summary, score = gen_opt.evolve(iterations)
text_summary = []
for s in summary:
text_summary.append(s.get_text())
return text_summary
