def load(self, filename):
"""
Load the model
"""
f = open(filename, "r")
data = json.load(f)
f.close()
self.Nodes = data["Nodes"]
self.W = [np.array(w) for w in data["W"]]
self.B = [np.array(b) for b in data["B"]]
def save(self, filename):
"""
Save the model to the file 'filename`.
"""
data = {"Nodes": self.Nodes,
"W": [w.tolist() for w in self.W],
"B": [b.tolist() for b in self.B]}
f = open(filename, "w")
json.dump(data, f)
f.close()
def InitTimezone(self):
langlist = []
f = open('/opt/installer/zone.csv')
lines = f.read().split('\n')
for line in lines:
words = line.split("\"")
if len(words) >= 5:
langlist.append(words[5])
langlist.sort()
for lang in langlist:
self.Timezone.Append(lang)
f.close()
def loadBadCh(self):
filename = os.path.join(self.pathName, 'Artifacts', 'badChannels.txt')
if os.path.exists(filename):
with open(filename) as f:
badChannels = f.read()
print 'Bad Channels : {}'.format(badChannels)
else:
os.mkdir(os.path.join(self.pathName, 'Artifcats'))
with open(filename, 'w') as f:
f.write('')
f.close()
badChannels = []
return badChannels
def getSdbCsv(self,fileName):
try:
f = open(fileName, 'rb')
reader = csv.reader(f)
header = reader.next()
for row in reader:
car = Car()
car.get_sdb_csv(row,header)
self.cars[car.id] = car
except csv.Error, e:
f.close()
sys.exit('file %s, line %d: %s' % (fileName, reader.line_num, e))
def updateDeviceList(self):
if self.spectrometer: #self.selected_model['iManufacturer']=='Seabreeze':
functions.close(self.spectrometer)
self.instr_list.clear()
self.instr_list.addItem('Instruments:')
self.device_models, self.device_list = functions.find_devices()
for ii in range(1, (1 + len(self.device_models))):
if self.device_models[str(
ii)]['idVendor'] + ':' + self.device_models[str(
ii)]['idProduct'] == '0xbd7:0xa012':
self.device_name.append('StellarNet')
else:
self.device_name.append(
self.device_models[str(ii)]['idVendor'] + ':' +
self.device_models[str(ii)]['idProduct'])
self.instr_list.addItem(self.device_name[ii - 1])
def writeCarsData2Csv(self, filename,data, mode,historyFile):
global header
#Es para que solo escriba la cabecera la primera vez
if historyFile and os.path.isfile(filename):
header = False
f = open(filename, mode)
csvf = csv.DictWriter(f, Car.PARS.keys(), restval='', extrasaction='raise')
if header:
csvf.writeheader()
for car in data.values():
csvf.writerow(car.get_state_dict())
f.close()
header = True
def get_cars_from_csv(self,filename,repeated = False):
try:
f = open(filename, 'rb')
reader = csv.reader(f)
if header:
reader.next()
for row in reader:
car = Car()
car.get_from_csv(row)
if repeated:
id = car.id+"_"+str(car.state['dtime'])
self.cars[id] = car
else:
self.cars[car.id] = car
except csv.Error, e:
f.close()
sys.exit('file %s, line %d: %s' % (filename, reader.line_num, e))
def handle_bar(timer, data, info, init_cash, transaction, detail_last_min,
memory):
if timer == 0:
memory.status = 0 # -1, stop loss; 0, ready; 1, open
position_new = detail_last_min[0]
if memory.status == -1:
if (timer - memory.stop_loss_time) % 120 == 0:
memory.status = 0
elif memory.status == 0: # ready to open
grd = [0, 0]
grd[0] = gradient(asset_index1, data)
grd[1] = gradient(asset_index2, data)
delta = grd[0] - grd[1]
if abs(delta) > 3 * transaction: # just to ensure interest
current_trend = trend(asset_index1, asset_index2, grd,
data) # trend detection
index = decision(delta, current_trend, asset_index1,
asset_index2) # item decision
operate_index = index[0]
target_index = index[1]
memory.operate_price = np.mean(data[operate_index, 0:3])
memory.target_price = np.mean(data[target_index, 0:3])
memory.operate_index = operate_index
memory.target_index = target_index
memory.operate_time = timer
memory.trend = current_trend
position_new = operation(data, detail_last_min, info,
operate_index, transaction, current_trend,
underwear)
memory.position = position_new
memory.top = detail_last_min[4] - underwear
memory.total = detail_last_min[4]
memory.status = 1
else:
memory.top = peak_update(detail_last_min, memory)
if (detail_last_min[4] - memory.top) / memory.top < -0.1: # stop loss
position_new = np.zeros(13, dtype=np.int)
memory.stop_loss_time = timer
memory.status = -1
print("stop loss")
if close(detail_last_min, memory, timer, data): # close out
position_new = np.zeros(13, dtype=np.int)
memory.status = 0
if timer > 8300:
print('deal')
return position_new, memory
def stop(self):
functions.close(self.spectrometer)
self.goto_time_zero(self.axis)
def close_app(self):
functions.close(self.spectrometer) # closes window
self.close()
car.get_from_csv(row)
if repeated:
id = car.id+"_"+str(car.state['dtime'])
self.cars[id] = car
else:
self.cars[car.id] = car
except csv.Error, e:
f.close()
sys.exit('file %s, line %d: %s' % (filename, reader.line_num, e))
except IOError, e:
return
except StopIteration:
f.close()
return
return self.cars
# """
# Carga la lista de taxis en los diccionarios
# """
def getCarsFromPreviousHist(self,rows):
for row in rows:
car = Car()
car.get_from_csv(row)
self.cars[car.id] = car
return self.cars
s_area=f.square_area(3,4)
print(s_area)
###############FILE HANDLING###############
import os
if os.path.exists("C://python notes//aa.txt"):
os.remove("C://python notes\\aa.txt")
else:
print("file does not exist")
###########
f=open("C://python notes\\a.txt","w")
f.write("adding some data to the file. ")
f.close()
f=open("C://python notes//a.txt","r")
print(f.readline())
f=open("C://python notes//a.txt","a")
f.write("Adding some more data!\n yes.")
f=open("C://python notes//a.txt","r")
print(f.readline())
import os
os.rmdir("C://python notes//AA")
import os
if os.path.exists("C://python notes//aa.txt"):