def iterative(basename, maximize=False):
capacity, sizes, requests, caches = io.read_file(basename + '.in')
result = 0 #25234071
print('preparing...')
constraints = generate_constraints(capacity, sizes, requests, caches)
s = z3.Optimize() if maximize else z3.Solver()
for c in constraints:
s.add(c)
if maximize:
s.maximize(SERVE)
while True:
target = int(result)
print('solving round for', target)
s.add(SERVE > target)
s.check()
try:
m = s.model()
except z3.Z3Exception:
print('UNSAT')
break
result = int(str(m.evaluate(SERVE)))
print('found', result)
d = {
c: [v for v in videos if m.evaluate(has_video(v, c))]
for c, videos in caches.items()
}
io.write_file("{}/{}.txt".format(basename, result), d)
if maximize:
break
def main():
start = time.clock()
#直接对已经处理过non-word error的语料进行处理
testdata = readfile.read_file(
'E:\\!!!!!!!!!!study\\学习\\大四上\\NLP\\NLP intro\\homework\\1\\spelling-correction\\Assignment1\\'
+ 'result6.txt')
testdata.columns = (['id', 'senten'])
result_list = []
for i in range(100):
can = []
words = nltk.word_tokenize(testdata['senten'][i])
for j in range(len(words)):
p = re.findall(r"[,.?!']", words[j])
n = re.findall(r"[0-9]+", words[j])
if (len(p) == 0 and len(n) == 0):
if j == 0: #开头
can.append(correct_first(words[j], words[j + 1], 0.9))
elif j == len(words) - 1: #结尾
can.append(correct_last(words[j], words[j - 1], 0.9))
else: #中间
can.append(
correct(words[j], words[j - 1], words[j + 1], 0.9))
else:
can.append(words[j])
result_list.append(can)
print("sen " + str(i) + 'have been processed')
print(time.clock() - start)
#把句子复原
result = []
for i in range(len(result_list)):
words = result_list[i]
sen = result_list[i][0].capitalize()
for j in range(1, len(words)):
if words[j] in ',.?!':
sen = sen + words[j]
else:
sen = sen + ' ' + words[j]
result.append(sen)
f = open(
"E:/!!!!!!!!!!study/学习/大四上/NLP/NLP intro/homework/1/spelling-correction/Assignment1/result_iter.txt",
'w')
for i in range(len(result)):
f.write(str(i + 1) + '\t' + result[i] + '\n')
f.close()
#结果
anspath = 'E:/!!!!!!!!!!study/学习/大四上/NLP/NLP intro/homework/1/spelling-correction/Assignment1/ans.txt'
resultpath = 'E:/!!!!!!!!!!study/学习/大四上/NLP/NLP intro/homework/1/spelling-correction/Assignment1/result_iter.txt'
ansfile = open(anspath, 'r')
resultfile = open(resultpath, 'r')
count = 0
for i in range(1000):
ansline = ansfile.readline().split('\t')[1]
ansset = set(nltk.word_tokenize(ansline))
resultline = resultfile.readline().split('\t')[1]
resultset = set(nltk.word_tokenize(resultline))
if ansset == resultset:
count += 1
print(count)
print("Accuracy is : %.2f%%" % (count * 1.00 / 10))
def main():
# if input("Test?: ") == 'y':
# test()
accept = False
while not accept:
try:
grammer_name, grammer = readfile.read_file(input("File name for grammer: "))
except IOError:
print("Invalid filename")
else:
accept = True
verb = input("Verbouse Output? (y/n) ") == 'y'
while 1:
test_string = input('String to test: ')
##Push the string on to it's own stack
input_string = lll()
for i in range(len(test_string)-1, -1 , -1): ## this is kinda strange...
input_string = input_string.push(test_string[i])
stack = lll()
stack = stack.push('S')
if verb == True:
print('Test String | Stack')
input_string.print_all(); print(' ', end = '');
stack.print_all(); print()
while True:
input_string, str_pop = input_string.pop()
stack, stk_pop = stack.pop()
s_result = None
if(stk_pop != str_pop):
s_result = grammer.search(stk_pop, str_pop)
if s_result:
for i in range(len(s_result)-1, 0, -1):#push all but first char
stack = stack.push(s_result[i])
else:
good = False ##String is not part of language
break
if(stk_pop == str_pop) and (str_pop == '$'):
good = True
break
if verb == True:
input_string.print_all(); print(' ', end = ''); stack.print_all(); print()
if good == True:
print(test_string + ' is in the language of ' + grammer_name)
else:
print(test_string + ' is NOT in the language of ' + grammer_name)
if input("Test another string? (y/n) ") != 'y':
break
def run_training():
train_log_dir = '/home/viplab/Desktop/vgg_var2/log/train/'
tfrecords_file = '/home/viplab/Desktop/vgg_var2/tfrecord/train.tfrecords'
save_dir = '/home/viplab/Desktop/vgg_var2/tfrecord/'
image_list, obj_label_list = readfile.read_file()
N_SAMPLES = len(obj_label_list)
readfile.convert_to_tfrecord(image_list, obj_label_list, save_dir, 'train')
train_batch, label_batch = readfile.read_and_decode(
tfrecords_file, BATCH_SIZE, IMG_W, IMG_H, N_CLASSES)
print('train_batch', train_batch)
x = tf.placeholder(tf.float32, shape=[BATCH_SIZE, IMG_W, IMG_H, 3])
y = tf.placeholder(tf.float32, shape=[BATCH_SIZE, N_CLASSES])
train_logits = VGG19.VGG19(x, N_CLASSES)
train_loss = VGG19.losses(train_logits, y)
train__acc = VGG19.evaACC(train_logits, y)
train_op = VGG19.trainning(train_loss, learning_rate)
#將之前定義的所有summary op整合在一起
summary_op = tf.summary.merge_all()
saver = tf.train.Saver() #存module
sess = tf.Session()
#對所有變量初始化
sess.run(tf.global_variables_initializer())
sess.run(tf.local_variables_initializer())
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
#創建一個file writer 用來寫數據
train_writer = tf.summary.FileWriter(train_log_dir, sess.graph)
counter = 0
k = 0
try:
for step in np.arange(0, EPOCH):
print("epoch: ", step)
k = 0
while k < int(N_SAMPLES / BATCH_SIZE):
if coord.should_stop():
break
#print('train_batch',train_batch)
image, label = sess.run([train_batch, label_batch])
_, tra_loss, tra_acc = sess.run(
[train_op, train_loss, train__acc],
feed_dict={
x: image,
y: label
})
counter += 1
print('Step %d, train loss = %.2f, train accuracy = %.4f%%' %
(counter, tra_loss, tra_acc * 100))
#if counter %50 = 0 :
#summary_str = sess.run(summary_op)
#train_writer.add_summary(summary_str, counter)
checkpoint_path = os.path.join(train_log_dir, 'model.ckpt')
saver.save(sess, checkpoint_path, global_step=counter)
k += 1
except tf.errors.OutOfRangeError:
print('Done training -- epoch limit reached')
finally:
coord.request_stop()
coord.join(threads)
sess.close()
'u': 21,
'v': 22,
'w': 23,
'x': 24,
'y': 25,
'z': 26
}
filename = 'thefile.txt'
if len(sys.argv) > 1:
filename = sys.argv[1]
if len(sys.argv) > 2:
delimiter = sys.argv[2].strip('"')
file_str = readfile.read_file(filename)
lines = file_str.split(delimiter)
print lines
highest = 0, ''
#break each line up into sentences
for line in lines:
#sline = line.replace('\n','')
#print 'sline={0}'.format(sline)
line_amount = 0
for l_char in line:
#making the assumption that the encoding of the file is ascii
#if unicode support is needed, unichr() function can be used
#!/usr/bin/env python2
# sam1.py
# Perrine Letellier
#
import numpy as np
from scipy import ndimage
import networkx as nx
import readfile
import operator
time = 54000
nb_car = 8
source = 4516
graph = readfile.read_file("links.txt")
f=open("sol","w")
print>>f, nb_car
for car in range(nb_car) :
costs_dict = dict()
paths_dict = dict()
time_dict = dict()
for vertice in graph.nodes() :
a,b = nx.shortest_path(graph, source, vertice, weight='cost')
costs_dict[str(vertice)] = a
paths_dict[str(vertice)] = b
#compute the time needed for each path
total = 0
def dump_to_db(host='localhost', port=3306):
try:
connection = pymysql.connect(
host=host,
port=port,
user=db_username,
password=db_password,
)
except Exception as e:
raise e
print('Mysql连接失败！')
return None
else:
print('Mysql连接成功')
cursor = connection.cursor()
files = _read_files(databases_dir)
if not files:
print('Database文件夹为空')
return None
#读取所有数据库
query = "show databases"
cursor.execute(query)
_databases = cursor.fetchall()
for file in files:
try:
database, data, cols_name = read_file(
os.path.join(databases_dir, file))
except Exception as e:
raise e
print(f'处理{file}出错！')
continue
if (database, ) in _databases:
print(f"数据库{database}已存在")
continue
# 创建数据库
try:
sql = "create database " + f"`{database}`"
cursor.execute(sql)
except Exception as e:
print(f'创建数据库{database}失败!')
continue
print(f'数据库{database}创建成功!')
sql = 'use ' + f"`{database}`"
cursor.execute(sql)
for table_name in data:
try:
sql = "drop table if exists " + f"{table_name}"
cursor.execute(sql)
#创建表
sql = f'create table `{table_name}` (`id` int not null auto_increment, '
for col in cols_name[table_name]:
sql += f'`{col}` varchar(45),'
sql += 'primary key (`id`) )'
try:
cursor.execute(sql)
except Exception as e:
print(f'创建表{table_name}失败！')
continue
else:
print(f'创建表{table_name}成功！')
#写入数据 row是某一个表的一行数据
for i, rows in enumerate(data[table_name]):
#插入数据库
base_sql = f"insert into `{table_name}` ("
for col in cols_name[table_name]:
base_sql += f"`{col}`,"
base_sql = base_sql[:-1]
base_sql += ") values ("
sql = ""
for d in rows:
d = d.replace("'", "\\'")
sql += f"'{d}'," #机场信息里面带有"'"
sql = sql[:-1]
sql += ")"
try:
#插入一条数据
cursor.execute(base_sql + sql)
except Exception as e:
raise e
break
else:
print(
f'表{table_name}已完成{int((i+1)/len(data[table_name])*100)}%',
end='\r')
except Exception as e:
print(f'表{table_name}插入数据失败！')
try:
connection.commit()
except Exception as e:
print(f"数据库{database}:表{table_name} 插入数据失败！")
connection.rollback()
connection.close()
delimiter = '. '
alphabet = {'a':1, 'b':2, 'c':3, 'd':4, 'e':5, 'f':6, 'g':7,
'h':8, 'i':9, 'j':10, 'k':11, 'l':12, 'm':13, 'n':14,
'o':15, 'p':16, 'q':17, 'r':18, 's':19, 't':20,
'u':21, 'v':22, 'w':23, 'x':24, 'y':25, 'z':26}
filename = 'thefile.txt'
if len(sys.argv) > 1:
filename = sys.argv[1]
if len(sys.argv) > 2:
delimiter = sys.argv[2].strip('"');
file_str = readfile.read_file(filename)
lines = file_str.split(delimiter);
print lines
highest = 0,''
#break each line up into sentences
for line in lines:
#sline = line.replace('\n','')
#print 'sline={0}'.format(sline)
line_amount = 0
for l_char in line :
#making the assumption that the encoding of the file is ascii
#if unicode support is needed, unichr() function can be used
def read_file(path):
return readfile.read_file(path)