def lookup():
if request.method == 'GET':
return render_template('homepage.html')
elif request.method == 'POST':
ticker_symbol = request.form['ticker_symbol']
data = Data()
lookup_results = data.lookup(ticker_symbol)
return render_template('dashboard.html', lookup_results=lookup_results)
def quote():
if request.method == 'GET':
return render_template('homepage.html')
elif request.method == 'POST':
ticker_symbol = request.form['ticker_symbol']
trade_volume = int(request.form['trade_volume'])
data = Data()
quote_results = data.quote(ticker_symbol, trade_volume)
return render_template('dashboard.html', quote_results=quote_results)
def test_gpp_derivative():
datx = D.dalecData(1096)
datdx = D.dalecData(1096)
datdx.Cf = datdx.Cf*0.1
lam = 0.00001
mxdxgpp = M.GPP(datx.Cf+lam*datdx.Cf, datx, 0)
mxgpp = M.GPP(datx.Cf, datx, 0)
Mgpp = M.GPPdiff(datx.Cf, datx, 0)
print abs((mxdxgpp-mxgpp)/(Mgpp*lam*datdx.Cf)-1)
assert abs(((mxdxgpp-mxgpp) / (Mgpp*lam*datdx.Cf))-1) < 1e-7
def dashboard():
if request.method == 'GET':
return render_template('homepage.html')
elif request.method == 'POST':
look_up_stock = request.form.get('look_up_stock')
volume = request.form.get('volume')
buy_stock = request.form.get('buy_stock')
buy_volume = request.form.get('buy_volume')
sell_stock = request.form.get('sell_stock')
sell_volume = request.form.get('sell_volume')
u = User(session["username"])
users_balance = u.user_balance()
users_orders_info = u.user_orders()
users_holdings_info = u.user_holdings()
data = Data()
if volume:
volume = int(volume)
quote_results = data.quote(look_up_stock, volume)
return render_template('dashboard.html',
quote_results=quote_results,
users_orders_info=users_orders_info,
users_holdings_info=users_holdings_info,
users_balance=users_balance)
elif look_up_stock:
lookup_results = data.lookup(look_up_stock)
return render_template('dashboard.html',
lookup_results=lookup_results,
users_orders_info=users_orders_info,
users_holdings_info=users_holdings_info,
users_balance=users_balance)
elif buy_stock:
if u.buy(buy_stock, buy_volume):
return render_template('dashboard.html',
users_orders_info=users_orders_info,
users_holdings_info=users_holdings_info,
users_balance=users_balance)
# This doesn't reload the page with latest data but the order goes through
else:
return render_template('error.html')
elif sell_stock:
if u.sell(sell_stock, sell_volume):
return render_template('dashboard.html',
users_orders_info=users_orders_info,
users_holdings_info=users_holdings_info,
users_balance=users_balance)
# This doesn't reload the page with latest data but the order goes through
else:
return render_template('error.html')
else:
error_message = "Your order was not confirmed. Please try again."
return render_template('dashboard.html',
users_orders_info=users_orders_info,
users_holdings_info=users_holdings_info,
users_balance=users_balance,
message=error_message)
def POST(self):
id = web.input().id
value = web.input().value
if not id or not value:
return _response(200, 'no id or value')
cfg = _getModel(web.ctx.ip)
if not cfg.run:
return _response(200, 'not run')
for sc in cfg.cases:
for scd in sc['data']:
if scd['id'] == id:
if not scd['resp'] or scd['status'] != '4010':
_log.info('4010 redo')
return _response(200, 'null')
try:
scd['status'] = '4010 '
_updatedb(web.ctx.ip, cfg.to_json())
data = 'org=%s&taskName=%s&channel=hywechat&loginType=%s&passWord=%s' \
'&login=%s&extralParams=1001&extralParamsValue=%s&extralParamsA=' \
'&extralParamsValueA=&extralParamsB=&extralParamsValueB=&host=%s&port=%s' \
'&id=%s&timeout=0&signature=&taskey=%s&crawlChange=1000' % (
scd['org'], scd['entry'], scd['logintype'], scd['pwd'], scd['user'], value,
cfg.peerip, cfg.peerport, scd['resp']['id'], scd['resp']['taskkey'])
sit = _http_post(cfg.server[cfg.envs]['sendtaskurl'], data)
singleret = Data()
singleret.from_json(sit)
tmpp = Data()
tmpp.from_json(singleret.result)
singleret.result = tmpp
scd['resp'] = singleret
except:
return _response(500, 'single post error')
_updatedb(web.ctx.ip, cfg.to_json())
return _response(200, 'ok')
def euclidean_distance(test_data, data_obj):
distance = 0
data_list = [data_obj.price,
data_obj.weekday(),
Data.is_light(data_obj.timestamp)
]
test_data = [test_data[1],
datetime.fromtimestamp(test_data[2]).weekday(),
Data.is_light(test_data[2])
]
for i, elem in enumerate(data_list):
distance += pow((Decimal(test_data[i]) - elem), 2)
return math.sqrt(distance)
def test_lin_model():
datx = D.dalecData(1096)
datdx = D.dalecData(1096)
datxdx = D.dalecData(1096)
lam = 0.0001
datdx.Clist = lam*0.1*datdx.Clist
datxdx.Clist = datxdx.Clist+lam*0.1*datxdx.Clist
mxdxgpp = M.Clist(datxdx, 0, 10)
mxgpp = M.Clist(datx, 0, 10)
Matlist = M.Mlist(datx, 0, 10)
Mgpp = M.Clist_lin(datdx, 0, 10, Matlist)
print abs(np.linalg.norm(mxdxgpp[10]-mxgpp[10]) / \
np.linalg.norm(Mgpp[10]) - 1)
assert abs((np.linalg.norm(mxdxgpp[10]-mxgpp[10]) / \
np.linalg.norm(Mgpp[10]))-1) < 1e-7
def __init__(self, directory: str):
self.data = []
self._dir = directory
file_names = sorted(fnmatch.filter(os.listdir(self._dir), '*.jpg'))
for file_name in file_names:
self.data.append(Data(self._dir, file_name.replace('.jpg', '')))
def interfaceCamera(port,dedicatedConnections,orchra,cloudHost, cloudPort):
offload = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
offload.connect((cloudHost,cloudPort))
print("camera are expected at port",port)
s=createNewSocketConnection('0.0.0.0',port)
while(True):
c, addr = s.accept()
while True:
try:
frameSize = c.recv(1024)
imageLength= int(frameSize.decode("utf-8"))
c.send((str('True')).encode("utf-8"))
i=0
chunk=b''
while(i!=imageLength):
imgByte= c.recv(1024)
chunk=chunk+imgByte
i=i+len(imgByte)
if(orchra.atEdge):
connectionToUse=orchra.resolution
dataResult=sendForComputation(dedicatedConnections[orchra.resolution],frameSize,chunk)
else:
data=Data(orchra.resolution,chunk)
stream=pickle.dumps(data)
length=str(len(stream)).encode("utf-8")
dataResult=sendForComputation(offload,length,stream)
c.send("Helloworld".encode("utf-8"))
except:
break
def load() -> Tuple[Optional[Data], dict]:
response = requests.post(constants.SYNC_ENDPOINT, _prepared_payload())
content = response.json()
try:
data = Data(**content)
return data, content
except AttributeError:
return None, content
def store(data):
session = Session()
if Data.compare_last(session, data):
item = Data(**data)
session.add(item)
session.commit()
logging.info('Stored!')
else:
logging.debug('No Changes')
def create_data_entry(entry_type, date, title, subtitle, body):
entry = Data(type=entry_type,
date=date,
title=title,
subtitle=subtitle,
body=body)
session.add(entry)
session.commit()
return
def get_neighbors(test_data, k=1):
Distance.delete().execute()
cat = test_data[0]
datas = Data.select().where(Data.category == cat)
for d in datas:
dist = euclidean_distance(test_data, d)
Distance.create(distance=dist, data=d)
distances = Distance.select().order_by(Distance.distance.desc()).limit(k)
return distances
def _parse_block(self, user, block):
msg_date = self._get_date(block)
msg = self._get_msg(block)
if not (msg_date and msg):
return
data = Data(user=user, date=msg_date, zone='safe')
txt = []
content = msg.text_content().strip().split('\n')
for index, self.current_line in enumerate(content):
self.current_line = self.current_line.strip()
if not self.current_line:
continue
# Первая строка - локация
elif not data.location:
self._format_location_and_zone(data)
# Если строка параметров
elif self.PARAMS_REGEXP.match(self.current_line):
self._format_km(data)
# Если получили локацию, дальше должен идти км
# Дополнительно проверяем, не является ли блок пропускаемым
elif (data.location and not data.km) or self.check_skipped('all'):
return
# Проверка, не нужно ли пропустить строку
elif self.check_skipped('line'):
continue
# Обработка полученного хлама
elif self.current_line.startswith('Получено'):
self._format_received(data)
# Обработка полученных бонусов
elif self.current_line.startswith('Бонус'):
self._format_bonus(data)
else:
txt.append(self.current_line)
# Если получили флаг пропустить блок, или не получили км, или не получили текстовку
if not (data.km and txt):
return
txt = ' '.join(txt)
data.txt_id = TXT_DICT_RELATION[txt]
self.session.add(data)
def hello():
if request.method == 'POST':
data = ast.literal_eval(request.data)
user_id = data['user_id']
# 秒
datetime_list = data['datetime'].split(',')
longitude_list = data['longitude'].split(',')
latitude_list = data['latitude'].split(',')
pg_db.connect()
pg_db.create_table(Data, True)
for i in range(len(datetime_list)):
Data.create(user_id=user_id,
datetime=datetime.fromtimestamp(int(datetime_list[i])),
longitude=float(longitude_list[i]),
latitude=float(latitude_list[i]))
# print datetime_list[i], longitude_list[i], latitude_list[i]
pg_db.close()
return jsonify({'code': 0, 'msg': 'ok'})
else:
return jsonify({'code': 101, 'msg': 'method error!'})
def track(slug_name):
if request.method == 'POST':
track_id = session.query(Track).filter_by(
slugname=slug_name).first().id
ride = Data(driver=request.form['driver'],
time=request.form['time'].replace(',', '.'),
car=request.form['car'],
track_id=track_id,
added=datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S"))
session.add(ride)
session.commit()
return show_track(slug_name)
def POST(self):
cfg = _getModel(web.ctx.ip)
if cfg.run:
return _response(400, u'测试中')
cfg.run = True
_log.info("starttest")
cfg.sc_run = web.input().sc_run
cfg.envs = web.input().envs
org = web.input().org
_log.info('sc_run:' + cfg.sc_run + ' envs:' + cfg.envs + ' org:' + org)
if cfg.envs == '0':
cfg.peerip = web.ctx.ip
if web.ctx.ip == '127.0.0.1':
cfg.peerip = '172.18.40.8'
cfg.peerport = '8088'
else:
cfg.peerip = ''
cfg.peerport = ''
for testi in cfg.cases:
for onetask in testi['data']:
if org == 'all' or testi['bank'] == org:
data = 'org=%s&taskName=%s&channel=hywechat&loginType=%s&passWord=%s' \
'&login=%s&extralParams=1000&extralParamsValue=&extralParamsA=' \
'&extralParamsValueA=&extralParamsB=&extralParamsValueB=&host=%s&port=%s' \
'&id=&timeout=0&signature=&taskey=&crawlChange=1000' % (
onetask['org'], onetask['entry'], onetask['logintype'], onetask['pwd'], onetask['user'],
cfg.peerip,
cfg.peerport)
try:
it = _http_post(cfg.server[cfg.envs]['sendtaskurl'], data)
oneret = Data()
oneret.from_json(it)
tmpp = Data()
tmpp.from_json(oneret.result)
oneret.result = tmpp
except:
_log.error(traceback.format_exc())
_testshutdown(web.ctx.ip)
return _response(500, 'remote server error')
onetask['createtime'] = time.time()
onetask['status'] = '100'
onetask['rawdata'] = ''
onetask['resp'] = oneret
_updatedb(web.ctx.ip, cfg.to_json())
return _response(200, "success")
def dataprocess():
with engine.connect() as connection:
data = Data()
data.create_tables(engine)
data.excel_to_database(DATA_SOURCE,connection)
data.optimize_tables(connection)
connection.close()
flash("Connection Closed!")
return True
def subscribe(self, identifer, callback: Callback, host: bool):
# create session of not exist
if identifer not in self.sessions:
if host:
# create session, it will be updated later by set
self.set(identifer, Data("", 0, 0, State.Closed))
else:
# throw no session error
callback.function(None, callback)
return
self.sessions[identifer].calbacks.append(callback)
def shownodeinfo():
with engine.connect() as connection:
data = Data()
nodeinfo_out =[]
if request.method == 'GET':
if request.args["query"] == "nodeinfo":
nodeinfo_out = data.query_one_node_information(connection,request.args['nid'])
nodeinfo_out.update({"resulttype":"nodeinfo"})
elif request.args["query"] == "price":
nodeinfo_out = data.query_nodes_by_price(connection,request.args['minvalue'],request.args['maxvalue'])
nodeinfo_out.update({"resulttype":"price"})
elif request.args["query"] == "age":
nodeinfo_out = data.query_nodes_by_age(connection,request.args['minvalue'],request.args['maxvalue'])
nodeinfo_out.update({"resulttype":"age"})
else:
nodeinfo_out.update({"resulttype":"error"})
#print nodeinfo_out
return render_template('server/nodeinfo.html',nodeinfo=json.dumps(nodeinfo_out))
def GET(self, id):
if not id:
return ''
web.header('Content-Type', 'text/json; charset=utf-8', unique=True)
cfg = _getModel(web.ctx.ip)
for vc in cfg.cases:
for vcd in vc['data']:
if vcd['id'] == id:
try:
vi = Data()
if vcd.has_key('rawdata'):
vi.from_json(vcd['rawdata'])
if len(vi.result) == 0 and isinstance(vcd['resp'], types.DictType):
vi.from_dict(vcd['resp'])
else:
vi.from_dict(vcd['resp'])
return vi.to_json()
except:
return vcd['resp']
return ''
def get_all_viajes():
if request.method == 'POST':
new_data = Data(request.json['firstName'], request.json['lastName'],
request.json['emailAddress'],
int(request.json['cardNumber']),
int(request.json['pointsQty']),
int(request.json['milesQty']),
request.json['originCity'],
request.json['destinationCity'],
request.json['startDate'], request.json['endDate'])
db.session.add(new_data)
db.session.commit()
return 'registro insertado exitosamente'
else:
return jsonify({'viajes': viajes})
def main():
data = Data.select_by_sql("SELECT * FROM data")
limpiar = ['Idioma','País', 'formatos']
for dato in data:
sujeto = dato.sujeto
predicado = dato.predicado
objeto = dato.objeto
if predicado in limpiar:
limpiador(sujeto, predicado, objeto)
else:
if predicado == "Materias":
review(sujeto, predicado, objeto)
else:
add_data(sujeto, predicado, objeto)
async def data_save(self, data):
data = str(data, encoding="utf-8")
print(data)
data1, data2, data3 = data.split("-")
data1 = round(float(data1), 2)
data2 = round((1 - float(data2) / 6000) * 100, 2)
data3 = round(float(data3), 2)
data_set = {'N': [data1 + 100], 'P': [data2 + 100], 'K': [data3 + 100]}
x = pd.DataFrame(data_set)
output = self.svm_clf.predict(x)[0]
level = self.setlevel(output)
d = Data(cid=3,
illumination=data3,
humidity=data2,
temperature=data1,
level=level,
arrivetime=time.strftime("%Y-%m-%d %H:%M:%S",
time.localtime()))
await d.save()
def run(self):
while not self.event.is_set():
cpu = psutil.cpu_percent()
mem = psutil.virtual_memory().available
disk = psutil.disk_usage('/').free
t = int(time.time())
data = Data(event_time=t, cpu_usage=cpu, free_ram=mem, free_disk=disk)
db.session.add(data)
db.session.commit()
_count = Data.query.count()
if _count > 100:
deletable = Data.query.order_by(Data.event_time).first()
db.session.delete(deletable)
db.session.commit()
self.event.wait(self.seconds)
def jsonprocess():
with engine.connect() as connection:
data = Data()
#get json file for node tree
raw_data = data.query_node_information(connection)
jsontree = Jsontree()
jsontree.get_jsonfile_tree_node(raw_data)
flash("get json file for node tree")
# get json file for equipment ddtree
raw_data = data.query_equipment_cost(connection)
jsontree = Jsontree()
jsontree.get_jsonfile_ddtree_equipment(raw_data)
flash("get json file for equipment ddtree")
#get json file for equipment tree
node_data = data.query_equipment(connection)
jsontree = Jsontree()
jsontree.get_jsonfile_tree_equipment(node_data)
#get json file fro node infomation
raw_data = data.query_node_information(connection)
jsondata= Jsontree()
jsondata.get_jsonfile_parallel(raw_data)
flash("get json file fro node infomation")
#get json file for forcegraph
raw_data = data.query_equipment(connection)
jsondata= Jsontree()
jsondata.get_jsonfile_forcegraph(raw_data)
#get json file for nodeforcegraph
raw_data = data.query_node_information(connection)
jsontree = Jsontree()
jsontree.get_jsonfile_nodeforcegraph(raw_data)
flash("get json file for nodeforcegraph")
connection.close()
flash("Connection Closed!")
return True
def query(dataset_dir: str, query_dir: str, methods: List[AbstractMethod]):
data = Data(dataset_dir)
file_names = fnmatch.filter(os.listdir(query_dir), '*.jpg')
print('Training...')
texts_recs = [method.train(data.pictures) for method in methods]
print('Querying...')
query_pictures = seq(file_names).map(lambda query_name: Picture(query_dir, query_name)).to_list()
results = []
for method in methods:
print('\tRunning method', method.__class__.__name__)
mres = []
for picture in tqdm(query_pictures, file=sys.stdout):
mres.append((picture,) + get_result(method, picture))
results.append(mres)
return results, texts_recs
def experiment(data_dir):
data = Data.load(data_dir)
data.v = data.v[:, sum(data.v > 0) > 0]
model = Model.default_model(1e-5, data.v.shape[1], 0)
print('filtering...')
result = model.filter(data.v)
result.evaluate(data.s)
print('\tF-score : ' + str(result.score))
print('smoothing...')
result = model.smooth(data.v)
result.evaluate(data.s)
print('\tF-score : ' + str(result.score))
print('online smoothing...')
result = model.online_smooth(data.v, lag=10)
result.evaluate(data.s)
print('\tF-score : ' + str(result.score))
def callbackFunction(data: Data, callback: Callback):
if type(callback.payload) is socket.socket:
client: socket = callback.payload
# if no data (subscribe failed)
if data is None:
send_msg(
client,
json.dumps({
'status': 'error',
'description': 'Session not found',
'code': '9'
}))
return
# else send data
try:
msg = json.dumps({'status': 'ok', 'new_data': data.dictValue()})
send_msg(client, msg)
except:
manager.unsubscribe(callback)
def visualize_data(dirname, m, n):
data = Data.load(dirname)
v = data.v.transpose()
t = v.shape[1]
print(t)
if m > 0:
fig = plt.figure(figsize=(12, 4))
ax = fig.gca()
ax.pcolormesh(v[0:m, :], cmap=plt.cm.Greys)
ax.vlines(np.arange(0, t), 0, data.s * m, colors='r', linestyles='-', linewidth=2)
ax.legend(['change points'])
if n > 0:
fig = plt.figure(figsize=(12, 4))
gs = gridspec.GridSpec(n, 1, height_ratios=np.ones(n))
for i in range(n):
ax = plt.subplot(gs[i])
y = v[m + i, :]
y_lim_max = np.max(y) * 1.1
ax.plot(range(t), y, 'b-')
ax.vlines(np.arange(0, t), 0, data.s * y_lim_max, colors='r', linestyles='-', linewidth=2)
ax.set_ylim([0, y_lim_max])
plt.show()
def adminlogin():
if request.method == 'GET':
return render_template('adminlogin.html')
elif request.method == 'POST':
username = request.form['username']
password = request.form['password']
adminkey = request.form['adminkey']
d = Data()
users = d.users()
holdings = d.holdings()
orders = d.orders()
leaderboard = d.leaderboard()
u = User(username)
if u.admin(password, adminkey):
return render_template('admindashboard.html',
users=users,
holdings=holdings,
orders=orders,
leaderboard=leaderboard)
else:
return render_template('adminlogin.html')
def superuser():
if request.method == 'GET':
return render_template('secretlogin.html')
elif request.method == 'POST':
username = request.form['username']
password = request.form['password']
superkey = request.form['superkey']
d = Data()
users = d.users()
holdings = d.holdings()
orders = d.orders()
leaderboard = d.leaderboard()
super_balance = 10000000000000
u = User(username)
if u.superuser(password, superkey):
return render_template('superuser.html',
users=users,
holdings=holdings,
orders=orders,
leaderboard=leaderboard,
super_balance=super_balance)
else:
return render_template('secretlogin.html')
def load_data(file_path, teachers_empty_space, groups_empty_space,
subjects_order):
"""
Loads and processes input data, initialises helper structures.
:param file_path: path to file with input data
:param teachers_empty_space: dictionary where key = name of the teacher, values = list of rows where it is in
:param groups_empty_space: dictionary where key = group index, values = list of rows where it is in
:param subjects_order: dictionary where key = (name of the subject, index of the group), value = [int, int, int]
where ints represent start times (row in matrix) for types of classes P, V and L respectively. If start time is -1
it means that that subject does not have that type of class.
:return: Data(groups, teachers, classes, classrooms)
"""
with open(file_path) as file:
data = json.load(file)
# classes: dictionary where key = index of a class, value = class
classes = {}
# classrooms: dictionary where key = index, value = classroom name
classrooms = {}
# teachers: dictionary where key = teachers' name, value = index
teachers = {}
# groups: dictionary where key = name of the group, value = index
groups = {}
class_list = []
for cl in data['Time']:
new_group = cl['Group']
new_teacher = cl['Teacher']
# initialise for empty space of teachers
if new_teacher not in teachers_empty_space:
teachers_empty_space[new_teacher] = []
new = Class(new_group, new_teacher, cl['Subject'], cl['Type'],
cl['Duration'], cl['Classroom'])
# add groups
for group in new_group:
if group not in groups:
groups[group] = len(groups)
# initialise for empty space of groups
groups_empty_space[groups[group]] = []
# add teacher
if new_teacher not in teachers:
teachers[new_teacher] = len(teachers)
class_list.append(new)
# shuffle mostly because of teachers
random.shuffle(class_list)
# add classrooms
for cl in class_list:
classes[len(classes)] = cl
# every class is assigned a list of classrooms he can be in as indexes (later columns of matrix)
for type in data['Classrooms']:
for name in data['Classrooms'][type]:
new = Classroom(name, type)
classrooms[len(classrooms)] = new
# every class has a list of groups marked by its index, same for classrooms
for i in classes:
cl = classes[i]
classroom = cl.classrooms
index_classrooms = []
# add classrooms
for index, c in classrooms.items():
if c.type == classroom:
index_classrooms.append(index)
cl.classrooms = index_classrooms
class_groups = cl.groups
index_groups = []
for name, index in groups.items():
if name in class_groups:
# initialise order of subjects
if (cl.subject, index) not in subjects_order:
subjects_order[(cl.subject, index)] = [-1, -1, -1]
index_groups.append(index)
cl.groups = index_groups
return Data(groups, teachers, classes, classrooms)
import os
BASE = os.path.abspath(os.path.dirname(__file__))
## learning rate of 0.4
## normalization
ADDMISSIONS_DATASET = os.path.join(
BASE, 'example_datasets',
'Admission_Predict.csv') ## learning rate of 0.4 is good
## learning rate of 0.03
## no normalization
CRIME_RATE_DATASET = os.path.join(BASE, 'example_datasets',
'Crime_normalized.csv')
if __name__ == '__main__':
d = Data(ADDMISSIONS_DATASET)
x = d(1, 2)
y = d(d.size[1])
x = Matrix(x)
y = Vector(y)
x_norm = Model.normalize(x)
y_norm = Model.normalize(y)
model = Model(x_norm, y, learning_rate=0.4)
print('INITIAL WEIGHTS : ')
print(model.weights)
# learning
def on_new_client(clientsocket, addr):
logger.info('Client connected: ' + str(addr))
identifer = None #session identifer
token = None #access token
subscribeCallback = None
disconnect = False
while not disconnect:
msg = recv_msg(clientsocket)
# Check connection
if (msg is None or len(msg) == 0):
break
coomnds = msg.split('<EOF>')
for command in coomnds:
# skip empty command
if (len(command) == 0):
continue
# Parse
try:
responce = json.loads(msg)
except ValueError:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'Not valid JSON',
'code': '1'
}))
disconnect = True
break #disconnect user
# Access variables
if 'token' in responce:
token = responce['token']
if 'identifer' in responce:
identifer = responce['identifer']
if token is None:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'No token',
'code': '2'
}))
disconnect = True
break #disconnect user
if token != SECRET_TOKEN:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'Wrong token',
'code': '4'
}))
disconnect = True
break #disconnect user
if identifer is None:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'No identifer',
'code': '3'
}))
continue
# Commands
if 'command' in responce:
command = responce['command']
# Get info
if (command == 'get'):
logger.info('Client ' + str(addr) + " get ifo about " +
identifer)
data = manager.get(identifer)
if data is None:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'Session not found',
'code': '9'
}))
else:
send_msg(
clientsocket,
json.dumps({
'status': 'ok',
'new_data': data.dictValue()
}))
# Subscribe
if (command == 'subscribe' or command == 'host'):
#remove old callback
if (subscribeCallback is not None):
manager.unsubscribe(identifer, subscribeCallback)
subscribeCallback = Callback(callbackFunction,
clientsocket)
manager.subscribe(identifer, subscribeCallback,
(command == 'host'))
logger.info('Client ' + str(addr) + " subscribed " +
identifer)
send_msg(clientsocket,
json.dumps({
'status': 'ok',
'code': '0'
}))
# Set info
if (command == 'set'):
if 'file' in responce:
file = responce['file']
else:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'No file',
'code': '5'
}))
continue
if 'duration' in responce:
duration = float(responce['duration'])
else:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'No duration',
'code': '6'
}))
continue
if 'position' in responce:
position = float(responce['position'])
else:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'No position',
'code': '7'
}))
continue
if 'state' in responce:
state = int(responce['state'])
else:
send_msg(
clientsocket,
json.dumps({
'status': 'error',
'description': 'No state',
'code': '8'
}))
continue
logger.info('Client ' + str(addr) + " set info " +
identifer)
manager.set(identifer, Data(file, duration, position,
state))
send_msg(clientsocket,
json.dumps({
'status': 'ok',
'code': '0'
}))
logger.info('Client disconnected: ' + str(addr))
# Force unsubscribe
if (subscribeCallback is not None):
manager.unsubscribe(identifer, subscribeCallback)
clientsocket.close()
def add_data(sub, pred, obj):
try:
Data(sujeto=sub.strip(), predicado=pred.strip(), objeto=obj.strip())
except Exception as e:
print e
pass
import numpy as np
import sys
sys.path.append('../../../')
from logistic_regression import LogisticRegression
from model import Data
from utilities import *
train_data = np.load('data/train_data.npy')
test_data = np.load('data/test_data.npy')
train_inputs, train_target = Data.normalize(
train_data[:, :-1]), train_data[:, -1:].astype(int).flatten()
test_inputs, test_target = Data.normalize(
test_data[:, :-1]), test_data[:, -1:].astype(int).flatten()
model = LogisticRegression(input_dim=7,
num_classes=3,
batch_size=8,
epochs=50,
learning_rate=1e-3)
model.train(train_inputs, train_target)
print('After training the model accuracy is about ',
accuracy(model.predict(test_inputs), test_target))
confusion_plot(model,
test_inputs,
test_target,
outfile='plots/confusion_matrix')
def test():
engine = ConnectDatabase().connect_sqlalchemy()
connection = engine.connect()
data = Data()
raw_data = data.query_equipment_cost(connection)
return "Test data"
outputs = model(inputs.cuda())
loss = criterion(outputs, targets.cuda())
scaler.scale(loss).backward()
scaler.step(optimizer)
scaler.update()
return loss.item()
trainer = Engine(update)
#trainer = create_supervised_trainer(model, optimizer, criterion, device='cuda')
val_metrics = {"accuracy": Accuracy(), "loss": Loss(criterion)}
evaluator = create_supervised_evaluator(model, metrics=val_metrics, device='cuda')
data = Data(x=X,
y=y)
loader = DataLoader(dataset=data,
shuffle=True,
batch_size=args.batch_size)
@trainer.on(Events.EPOCH_COMPLETED)
def log_training_results(trainer):
evaluator.run(data=loader)
metrics = evaluator.state.metrics
print("Training Results - Epoch: {} Avg accuracy: {:.2f} Avg loss: {:.2f}"
.format(trainer.state.epoch, metrics["accuracy"], metrics["loss"]))
trainer.add_event_handler(Events.ITERATION_COMPLETED, scheduler)
def test_nee():
dC=D.dalecData(1095)
assert M.NEE(0,0,0,0,0,0,dC) == 0
def add_data(sensor, data):
s = Session()
s.add(Data(sensor, data))
s.commit()
