def setUp(self):
model = Model(20)
model.load('../testdata/lda_model')
vocabulary = Vocabulary()
vocabulary.load('../testdata/vocabulary.dat')
self.multi_chain_gibbs_sampler = \
MultiChainGibbsSampler(model, vocabulary, 10, 10, 5)
def __init__(self, training_set=None, testing_set=None):
Model.__init__(self, training_set, testing_set)
# points that define the target function
self.point1 = (random.uniform(-1, 1), random.uniform(-1, 1))
self.point2 = (random.uniform(-1, 1), random.uniform(-1, 1))
self.weights = [0., 0., 0.]
def pcajax_validate(request):
if request.method == "POST":
gt = GeetestLib(pc_geetest_id, pc_geetest_key)
challenge = request.POST.get(gt.FN_CHALLENGE, '')
validate = request.POST.get(gt.FN_VALIDATE, '')
seccode = request.POST.get(gt.FN_SECCODE, '')
status = request.session[gt.GT_STATUS_SESSION_KEY]
user_id = request.POST.get('username')
if status:
result = gt.success_validate(challenge, validate, seccode, user_id)
else:
result = gt.failback_validate(challenge, validate, seccode)
if result:
teacher = Model('teacher')
tdata = teacher.find("'" + request.POST.get('username') + "'")
if tdata:
import hashlib
m = hashlib.md5()
m.update(bytes(request.POST['password'], encoding='utf8'))
if tdata[0]['password'] == m.hexdigest():
# 将当前登陆成功的用户信息以adminuser这个key放入到session中
request.session['teacher'] = tdata[0]
result = {"status": "success"}
# return redirect(reverse('teacher_index'))
else:
result = {"status": "fail"}
else:
result = {"status": "fail"}
else:
result = {"status": "fail"}
return HttpResponse(json.dumps(result))
return HttpResponse("error")
def setUp(self):
model = Model(20)
model.load('../testdata/lda_model')
vocabulary = Vocabulary()
vocabulary.load('../testdata/vocabulary.dat')
self.sparselda_gibbs_sampler = \
SparseLDAGibbsSampler(model, vocabulary, 10, 5)
class ModelEvaluatorTest(unittest.TestCase):
def setUp(self):
self.model = Model(20)
self.model.load('../testdata/lda_model')
self.vocabulary = Vocabulary()
self.vocabulary.load('../testdata/vocabulary.dat')
def test_compute_loglikelihood(self):
doc_tokens = [
'macbook',
'ipad', # exist in vocabulary and model
'mac os x',
'chrome', # only exist in vocabulary
'nokia',
'null'
] # inexistent
document = Document(self.model.num_topics)
rand = random.Random()
rand.seed(0)
document.parse_from_tokens(doc_tokens, rand, self.vocabulary,
self.model)
documents = [document, document]
self.assertEqual(
-14.113955684239654,
model_evaluator.compute_loglikelihood(self.model, self.vocabulary,
documents))
def setUp(self):
model = Model(20)
model.load('../testdata/lda_model')
vocabulary = Vocabulary()
vocabulary.load('../testdata/vocabulary.dat')
self.multi_chain_gibbs_sampler = \
MultiChainGibbsSampler(model, vocabulary, 10, 10, 5)
def setUp(self):
self.model = Model(20)
self.model.load('../testdata/lda_model')
self.vocabulary = Vocabulary()
self.vocabulary.load('../testdata/vocabulary.dat')
self.topic_words_stat = TopicWordsStat(self.model, self.vocabulary)
def insert(request):
"""执行添加"""
if request.POST['no'].replace(' ', '') != '':
if request.POST['password'] == request.POST['repassword']:
mod = Model('admin')
# 获取密码并md5
import hashlib
m = hashlib.md5()
m.update(
bytes(request.POST['password'].replace(' ', ''),
encoding='utf8'))
kw = {
'no': request.POST['no'].replace(' ', ''),
'password': m.hexdigest(),
}
if mod.save(kw) > 0:
context = {"info": "添加成功！"}
else:
context = {"info": "添加失败"}
else:
context = {"info": "添加失败"}
else:
context = {"info": "添加失败"}
return render(request, "myadmin/info.html", context)
def __init__(self, records, mixtures):
Model.__init__(self, records)
self.mixtures = mixtures
self.mu = np.random.permutation(records)[0:mixtures]
self.cov = np.ones(
(mixtures, self.dimensions, self.dimensions)) * np.cov(records.T)
self.theta = np.ones(mixtures) * (1 / mixtures)
def update(request, uid):
"""执行编辑信息"""
if request.POST['password'] == request.POST['repassword']:
mod = Model('teacher')
# 获取密码并md5
import hashlib
m = hashlib.md5()
m.update(bytes(request.POST['password'], encoding='utf8'))
kw = {
'no': uid,
'faculty': request.POST['faculty'],
'age': request.POST['age'],
'sex': request.POST['sex'],
'position': request.POST['position'],
'degree': request.POST['degree'],
'phone': request.POST['phone'],
'password': m.hexdigest(),
}
try:
if mod.update(kw) > 0:
context = {"info": "修改成功！"}
else:
context = {"info": "修改失败"}
except Exception as err:
print(err)
context = {"info": "修改失败"}
else:
context = {"info": "修改失败"}
return render(request, "myadmin/info.html", context)
def setUp(self):
self.model = Model(20)
self.model.load('../testdata/lda_model')
self.vocabulary = Vocabulary()
self.vocabulary.load('../testdata/vocabulary.dat')
self.model_evaluator = ModelEvaluator(self.model, self.vocabulary)
def insert(request):
"""执行添加"""
mod = Model('teacher')
# 获取密码并md5
import hashlib
m = hashlib.md5(b'000000')
try:
kw = {
'no': request.POST['no'].strip(),
'faculty': request.POST['faculty'],
'name': request.POST['name'],
'age': request.POST['age'],
'sex': request.POST['sex'],
'position': request.POST['position'],
'degree': request.POST['degree'],
'phone': request.POST['phone'],
'password': m.hexdigest(),
}
if mod.save(kw) > 0:
context = {"info": "添加成功！"}
else:
context = {"info": "添加失败"}
except:
context = {"info": "添加失败"}
return render(request, "myadmin/info.html", context)
def dologin(request):
"""执行登陆"""
# 验证码判断
verifycode = request.session['verifycode']
code = request.POST['code']
if verifycode != code:
context = {'info': '验证码错误！'}
return render(request, "myadmin/login.html", context)
try:
# 根据登陆账号获取用户信息
user = Model('admin')
user = user.find("'" + request.POST['username'] + "'")
if user is not None:
import hashlib
m = hashlib.md5()
m.update(bytes(request.POST['password'], encoding='utf8'))
print(m.hexdigest())
# 校验密码是否正确
if user[0]['password'] == m.hexdigest():
# 将当前登陆成功的用户信息以adminuser这个key放入到session中
request.session['adminuser'] = user[0]
return redirect(reverse('myadmin_index'))
else:
context = {'info': "登陆密码错误"}
else:
context = {'info': "此用户非后台管理账户"}
except Exception as err:
print(err)
context = {'info': "登陆账号不存在"}
return render(request, 'myadmin/login.html', context)
def setUp(self):
model = Model(20)
model.load('../testdata/lda_model')
vocabulary = Vocabulary()
vocabulary.load('../testdata/vocabulary.dat')
self.sparselda_gibbs_sampler = \
SparseLDAGibbsSampler(model, vocabulary, 10, 5)
def delete(request, uid):
"""删除信息"""
mod = Model('teaching')
if mod.delete(id=uid) > 0:
context = {"info": "删除成功"}
else:
context = {"info": "删除失败"}
return render(request, "myadmin/info.html", context)
def index(request):
data = request.session['teacher']
mod = Model('faculty')
title = mod.findAll()
for faculty in title:
if data['faculty'] == faculty['no']:
data['faculty'] = faculty['name']
data.pop('password')
return render(request, "web/teacher/index.html", {'data': data})
def edit(request, uid):
"""加载编辑信息页面"""
mod = Model('subject')
ob = mod.find(no=uid)
if ob is not None:
context = {"user": ob}
return render(request, "myadmin/subject/edit.html", context)
else:
context = {"info": "没有找到要修改的信息！"}
return render(request, "myadmin/info.html", context)
def edit(request, uid):
"""加载编辑信息页面"""
mod = Model('teacher')
ob = mod.find("'" + str(uid) + "'")
if ob is not None:
context = {"teacher": ob}
return render(request, "web/teacher/edit.html", context)
else:
context = {"info": "没有找到要修改的信息！"}
return render(request, "web/info.html", context)
def edit(request, uid):
"""加载编辑信息页面"""
mod = Model('admin')
ob = mod.find(no="'" + uid + "'")
print(ob)
if ob is not None:
context = {"user": ob}
return render(request, "myadmin/vip/edit.html", context)
else:
context = {"info": "没有找到要修改的信息！"}
return render(request, "myadmin/info.html", context)
def __init__(self, training_set=None, testing_set=None, weights=None):
Model.__init__(self, training_set, testing_set)
if weights is None:
self.weights = np.array([[0., 0., 0.]]).T
else:
self.weights = weights
# points that define the target function
self.point1 = (random.uniform(-1, 1), random.uniform(-1, 1))
self.point2 = (random.uniform(-1, 1), random.uniform(-1, 1))
def __init__(self, training_set=None, testing_set=None, weights=None):
Model.__init__(self, training_set, testing_set)
if weights is None:
self.weights = np.array([[0., 0., 0.]]).T
else:
self.weights = weights
# points that define the target function
self.point1 = (random.uniform(-1, 1), random.uniform(-1, 1))
self.point2 = (random.uniform(-1, 1), random.uniform(-1, 1))
def index(request):
"""浏览信息"""
mod = Model('subject')
umod = mod.findAll()
mywhere = []
# 获取、判断并封装关keyword键搜索
kw = request.GET.get("keyword", None)
if kw:
# 查询账户中只要含有关键字的都可以
list = []
for vo in umod:
if vo['no'].find(kw) >= 0 or vo['name'].find(kw) >= 0:
list.append(vo)
mywhere.append("keyword=" + kw)
else:
list = umod
# 获取、判断并封装学分score搜索条件
score = request.GET.get('score', '')
if score != '':
temp = []
for vo in list:
if vo['score'] == float(score):
temp.append(vo)
mywhere.append("score=" + kw)
list = temp
# 执行分页处理
pIndex = int(request.GET.get("p", 1))
page = Paginator(list, 4) # 以50条每页创建分页对象
maxpages = page.num_pages # 最大页数
# 判断页数是否越界
if pIndex > maxpages:
pIndex = maxpages
if pIndex < 1:
pIndex = 1
list2 = page.page(pIndex) # 当前页数据
# 获取页面列表信息
if maxpages < 5:
plist = page.page_range # 页码数列表
else:
if pIndex <= 3:
plist = range(1, 6)
elif pIndex >= maxpages - 3:
plist = range(maxpages - 4, maxpages + 1)
else:
plist = range(pIndex - 2, pIndex + 3)
context = {"list": list2, 'plist': plist, 'pIndex': pIndex, 'maxpages': maxpages, 'mywhere': mywhere}
return render(request, "myadmin/subject/index.html", context)
def insert(request):
"""执行添加"""
mod = Model('teaching')
print(request.POST['teacher'])
kw = {
'no': request.POST['teacher'],
'subject': request.POST['subject'],
'class': request.POST['class'],
}
if mod.save(kw) > 0:
context = {"info": "添加成功！"}
else:
context = {"info": "添加失败"}
return render(request, "myadmin/info.html", context)
def setUp(self):
self.model = Model(20)
self.model.load('../testdata/lda_model')
self.vocabulary = Vocabulary()
self.vocabulary.load('../testdata/vocabulary.dat')
self.topic_words_stat = TopicWordsStat(self.model, self.vocabulary)
def create_model(self, name, model_object, y, X, model_algo, model_params, tag=""):
db = self.fetch_model_db()
curr_num = len(db) + 1
name = str(curr_num) + "_" + name
#init Dataset
model = Model(self.model_export_dir, name, model_object, y, X, model_algo, model_params, tag)
#save {name: path} to model db
model_path = model.get_model_path()
db[name] = model_path
self.save_model_db(db)
#add to live models
self.live_models.append(model)
return model
def insert(request):
"""执行添加"""
mod = Model('subject')
try:
kw = {
'no': request.POST['no'],
'name': request.POST['name'],
'score': request.POST['score'],
}
if mod.save(kw) > 0:
context = {"info": "添加成功！"}
else:
context = {"info": "添加失败"}
except:
context = {"info": "添加失败"}
return render(request, "myadmin/info.html", context)
class TopicWordsStatTest(unittest.TestCase):
def setUp(self):
self.model = Model(20)
self.model.load("../testdata/lda_model")
self.vocabulary = Vocabulary()
self.vocabulary.load("../testdata/vocabulary.dat")
self.topic_words_stat = TopicWordsStat(self.model, self.vocabulary)
def test_save(self):
print self.topic_words_stat.save("../testdata/topic_top_words.dat", 0.8)
def test_get_topic_top_words(self):
print self.topic_words_stat.get_topic_top_words(0.8)
def test_compute_topic_word_distribution(self):
print self.topic_words_stat.compute_topic_word_distribution()
def main(args):
model = Model(0)
model.load(args.model_dir)
vocabulary = Vocabulary()
vocabulary.load(args.vocabulary)
multi_chain_gibbs_sampler = MultiChainGibbsSampler(model, vocabulary,
args.num_markov_chains, args.total_iterations,
args.burn_in_iterations)
fp = open(args.documents, 'r')
for doc_str in fp.readlines():
doc_str = doc_str.decode('gbk')
doc_tokens = doc_str.strip().split('\t')
topic_dist = multi_chain_gibbs_sampler.infer_topics(doc_tokens)
print doc_str
print topic_dist
fp.close()
def update(request, uid):
"""执行编辑信息"""
mod = Model('teaching')
kw = {
'no': uid,
'subject': request.POST['subject'],
'class': request.POST['class'],
}
try:
if mod.update(kw) > 0:
context = {"info": "修改成功！"}
else:
context = {"info": "修改失败"}
except Exception as err:
print(err)
context = {"info": "修改失败"}
return render(request, "myadmin/info.html", context)
def main(args):
model = Model(0)
model.load(args.model_dir)
vocabulary = Vocabulary()
vocabulary.load(args.vocabulary)
multi_chain_gibbs_sampler = MultiChainGibbsSampler(model, vocabulary,
args.num_markov_chains,
args.total_iterations,
args.burn_in_iterations)
fp = open(args.documents, 'r')
for doc_str in fp.readlines():
doc_str = doc_str.decode('gbk')
doc_tokens = doc_str.strip().split('\t')
topic_dist = multi_chain_gibbs_sampler.infer_topics(doc_tokens)
print doc_str
print topic_dist
fp.close()
class TopicWordsStatTest(unittest.TestCase):
def setUp(self):
self.model = Model(20)
self.model.load('../testdata/lda_model')
self.vocabulary = Vocabulary()
self.vocabulary.load('../testdata/vocabulary.dat')
self.topic_words_stat = TopicWordsStat(self.model, self.vocabulary)
def test_save(self):
print self.topic_words_stat.save('../testdata/topic_top_words.dat',
0.8)
def test_get_topic_top_words(self):
print self.topic_words_stat.get_topic_top_words(0.8)
def test_compute_topic_word_distribution(self):
print self.topic_words_stat.compute_topic_word_distribution()
class ModelEvaluatorTest(unittest.TestCase):
def setUp(self):
self.model = Model(20)
self.model.load('../testdata/lda_model')
self.vocabulary = Vocabulary()
self.vocabulary.load('../testdata/vocabulary.dat')
def test_compute_loglikelihood(self):
doc_tokens = ['macbook', 'ipad', # exist in vocabulary and model
'mac os x', 'chrome', # only exist in vocabulary
'nokia', 'null'] # inexistent
document = Document(self.model.num_topics)
rand = random.Random()
rand.seed(0)
document.parse_from_tokens(
doc_tokens, rand, self.vocabulary, self.model)
documents = [document, document]
self.assertEqual(-14.113955684239654,
model_evaluator.compute_loglikelihood(self.model, self.vocabulary, documents))
def update(request, uid):
"""执行编辑信息"""
mod = Model('admin')
ob = mod.find("'" + uid + "'")
import hashlib
m = hashlib.md5()
m.update(bytes(request.POST['old_password'], encoding='utf8'))
if request.POST['password'] == request.POST['repassword'] and ob[0][
'password'] == m.hexdigest():
mod = Model('admin')
m = hashlib.md5()
m.update(bytes(request.POST['password'], encoding='utf8'))
kw = {
'no': uid,
'password': m.hexdigest(),
}
try:
if mod.update(kw) > 0:
context = {"info": "修改成功！"}
else:
context = {"info": "修改失败"}
except Exception as err:
print(err)
context = {"info": "修改失败"}
else:
context = {"info": "修改失败"}
return render(request, "myadmin/info.html", context)
def createCharRNNSequence(cls,
input_melody,
measureInSec=None,
elementsPerMeasure=None):
print(input_melody)
charSequence = [noteToChord[mel['pitch']] for mel in input_melody]
charSequenceInput = ''.join(charSequence)
if len(charSequenceInput) < sample:
charSequence = charSequenceInput * math.ceil(
sample / len(charSequenceInput))
charSequence = charSequence[:sample]
tf.reset_default_graph()
with open(os.path.join(save_dir, 'config.pkl'), 'rb') as f:
saved_args = cPickle.load(f)
with open(os.path.join(save_dir, 'chars_vocab.pkl'), 'rb') as f:
chars, vocab = cPickle.load(f)
model = Model(saved_args, training=False)
with tf.Session() as sess:
tf.global_variables_initializer().run()
saver = tf.train.Saver(tf.global_variables())
ckpt = tf.train.get_checkpoint_state(save_dir)
if ckpt and ckpt.model_checkpoint_path:
saver.restore(sess, ckpt.model_checkpoint_path)
newCharSeq = model.sample(sess, chars, vocab, n, charSequence,
sample)
print('newCharSeq', newCharSeq, newCharSeq[len(charSequence):])
newCharSeq = newCharSeq[len(charSequence):]
newCharSeq = newCharSeq[:len(charSequenceInput)]
print(charSequence, newCharSeq)
newPitchs = [chordToNote[char] for char in newCharSeq]
for idx, pitch in enumerate(newPitchs):
input_melody[idx]['pitch'] = pitch
return input_melody
def test_model():
EXPECTED_MSG = repr(
TypeError(
"Can't instantiate abstract class Model with abstract methods __call__, __init__"
)) # nopep8
has_type_error = False
try:
my_model = Model()
except TypeError as e:
msg = e.__repr__()
has_type_error = True
assert has_type_error
assert msg == EXPECTED_MSG
def edit(request, uid):
"""加载编辑信息页面"""
mod = Model('teaching')
ob = mod.find(no=uid)
teacher = Model('teacher')
subject = Model('subject')
list1 = teacher.find(no=uid)
list2 = subject.findAll()
ob[0].update({'teacher': list1[0].get('name')})
print(ob)
print(list2)
if ob is not None:
context = {"teaching": ob, 'subject': list2}
return render(request, "myadmin/teaching/edit.html", context)
else:
context = {"info": "没有找到要修改的信息！"}
return render(request, "myadmin/info.html", context)
def add(request):
"""加载添加页面"""
teacher = Model('teacher')
subject = Model('subject')
list1 = teacher.findAll()
list2 = subject.findAll()
context = {"teacher": list1, 'subject': list2}
return render(request, "myadmin/teaching/add.html", context)
def __init__(self, training_set=None, testing_set=None):
Model.__init__(self, training_set, testing_set)
