def test_load_from_file(self):
data.load_from_file("data_2.0.xml")
self.assertEqual(
data.get_callback("googleKeyboard", "keyboard", "A_DOWN"),
["touch", "DOWN_AND_UP", "300", "680"])
self.assertEqual(
data.get_callback("default", "alias", "click"),
[["touch", "DOWN", ["arg", "1"], ["arg", "2"]],
["sleep", "0.1"],
["touch", "UP", ["arg", "1"], ["arg", "2"]]
])
def generate_data(path, tokenizer, char_vcb, word_vcb, is_training=False):
'''
Generate data
'''
global root_path
qp_pairs = data.load_from_file(path=path, is_training=is_training)
tokenized_sent = 0
# qp_pairs = qp_pairs[:1000]1
for qp_pair in qp_pairs:
tokenized_sent += 1
data.tokenize(qp_pair, tokenizer, is_training)
for word in qp_pair['question_tokens']:
word_vcb.add(word['word'])
for char in word['word']:
char_vcb.add(char)
for word in qp_pair['passage_tokens']:
word_vcb.add(word['word'])
for char in word['word']:
char_vcb.add(char)
max_query_length = max(len(x['question_tokens']) for x in qp_pairs)
max_passage_length = max(len(x['passage_tokens']) for x in qp_pairs)
#min_passage_length = min(len(x['passage_tokens']) for x in qp_pairs)
cfg.max_query_length = max_query_length
cfg.max_passage_length = max_passage_length
return qp_pairs
def multifit(file=None, taxrate=10, verbose=False):
""" Executa todas Heurísticas com a lista de objetos definidos, utilizando o
valor da taxa definida, e retorna o melhor variante do algorítimo
"""
my_items = load_from_file(file)
if verbose: #imprime alguns detalhes, caso verboso
totalitemvalue, totalitemsize = 0, 0
for i in my_items:
totalitemvalue += i.value
totalitemsize += i.size
print("Itens: Valor: " + str(totalitemvalue) + " Tamanho:" +
str(totalitemsize) + " Taxa: " + str(taxrate))
fit_option = ['first', 'best', 'worst',
'avoidtaxes'] #todas as opções de heuristicas do fit
sort_option = [True, False, 'cheapest',
'expensive'] #todas as opções de ordenação do fit
results = [] #lista dos resultados
for f in fit_option: #para cada heuristica
for s in sort_option: #para cada ordenação
mybox = fit(my_items, fit=f, sortedlist=s,
verbose=False) #executa a heuristica
res = Result(list_of_boxes=mybox, fit_order=f,sort_order=s, \
profit=calc_profit(mybox,taxrate),box_amount=len(mybox)) #salva o resultado em um objeto Result
results.append(res) # e coloca na lista de resultados
results = sorted(
results, key=attrgetter('profit'),
reverse=True) #as melhores resultados são colocadas no topo da lista
finalresult = results[0] #o melhor resultado é o primeiro
if verbose:
for x in results:
x.print_result_h() #se verboso, imprime o resultado
return finalresult #retorna o melhor resultado
def stresstest(itemgen=None, file=None, taxrate=False):
if itemgen == 'normal':
my_items = generate_item_list(amount=100, max_size=1000, max_value=100)
elif itemgen == 'pareto':
my_items = generate_pareto_list(amount=100,
medium_size=400,
medium_value=50,
max_size=1000,
max_value=100)
else:
my_items = load_from_file(file)
totalitemvalue, totalitemsize = 0, 0
for i in my_items:
totalitemvalue += i.value
totalitemsize += i.size
print(str(totalitemsize) + ' ' + str(totalitemvalue))
testtaxrate = taxrate if taxrate else [0, 10, 20, 30, 40, 50, 60]
fit_option = ['first', 'best', 'worst', 'avoidtaxes']
sort_option = [True, False, 'cheapest', 'expensive']
for t in testtaxrate:
results = {}
print("TAX RATE: " + str(t), end=' ')
for f in fit_option:
for s in sort_option:
mybox = fit(my_items, fit=f, sortedlist=s, verbose=False)
l = len(mybox)
# n = fit_option.index(f) + (sort_option.index(s)*10)
# mysum = 0
# for x in mybox: mysum += x.used_size # rint(x.used_size, end=' ')
results[f, s, l] = calc_profit(mybox, t)
for k, v in sorted(results.items(), key=itemgetter(1), reverse=True):
print(str(k), str(v))
break