def _init_hashtables(self):
""" Initialize the hash tables such that each record will be in the
form of "[storage1, storage2, ...]" """
self.hash_tables = [
storage(self.storage_config, i) for i in range(self.num_hashtables)
]
def __init__(self, params):
print 'initializing......'
self.params = params
self.sess = tf.Session()
self.storage = storage(self.params['db_size'],
self.params['input_dims_proc'])
self.engine = emulator(rom_name='breakout.bin', vis=True)
self.params['num_act'] = len(self.engine.legal_actions)
self.build_nets()
self.Q_global = 0
self.cost_disp = 0
def test(epoch):
global best_acc
net.eval()
test_loss = 0
correct = 0
total = 0
with torch.no_grad():
for batch_idx, (inputs, targets) in enumerate(testloader):
inputs, targets = inputs.to(device), targets.to(device)
outputs, sec_out, sec_in = net(inputs)
loss = criterion(outputs, targets)
test_loss += loss.item()
_, predicted = outputs.max(1)
total += targets.size(0)
correct += predicted.eq(targets).sum().item()
progress_bar(
batch_idx, len(testloader),
'Loss: %.3f | Acc: %.3f%% (%d/%d)' %
(test_loss /
(batch_idx + 1), 100. * correct / total, correct, total))
# Save checkpoint.
acc = 100. * correct / total
if acc > best_acc:
print('Saving..')
state = {
'net': net.state_dict(),
'acc': acc,
'epoch': epoch,
}
if not os.path.isdir('checkpoint'):
os.mkdir('checkpoint')
torch.save(state, './checkpoint/ckpt.t7')
best_acc = acc
if acc > 50:
all_train_loader = chain(trainloader, extraloader)
storage(all_train_loader, 'train')
storage(testloader, 'test')
def pic_info():
"""图片上传"""
user = g.user
print(user, "图片上传")
if request.method == "GET":
if not user:
return redirect('/')
data = {'user_info': user.to_dict() if user else None}
return render_template('news/user_pic_info.html', data=data)
avatar = request.files.get('avatar')
if not avatar:
return jsonify(errno=RET.PARAMERR, errmsg='请传入图片')
image = avatar.read()
key = storage(image)
if not key:
return jsonify(errno=RET.THIRDERR, errmsg='第三方系统出现问题')
user.avatar_url = key
db.session.commit()
data = {'avatar_url': QINIU_DOMIN_PREFIX + key}
return jsonify(errno=RET.OK, errmsg='设置成功', data=data)
def __init__(self):
solarData = np.empty(0)
reactorData = np.empty(0)
hotT = 863
coldT = 563
# import solar and reactor mass flow rate data
with open('SolarNew.csv', newline='') as Solar:
reader = csv.DictReader(Solar)
for row in reader:
solarData = np.append(solarData, row)
with open('ReactorNew.csv', newline='') as Reactor:
reader = csv.DictReader(Reactor)
for row in reader:
reactorData = np.append(reactorData, row)
# set steam generator mass flow rate
m_SteamGen = 1500
# creat array to hold stored energy amounts
energy = np.array([])
# assume thermocline is initially in average position
thermocline_position = 5
# loop through 7 days, with 144 10 min intervals per day
k=0
for j in range(7):
for i in range(1440):
solar = solarData[i]
m_Solar = float(solar['Mass flow rate'])
reactor = reactorData[i]
m_Reactor = float(reactor['Mass flow rate'])
m_HOT = m_Solar + m_Reactor
m_COLD = m_SteamGen
print(m_HOT)
TankStorage = storage(hotT, coldT, m_HOT, m_COLD, 30, 2.5, 0.026, thermocline_position=thermocline_position)
if k % 500 == 0:
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
ax.bar(0, TankStorage.thermocline_location, 0.4, color='b')
ax.bar(0, TankStorage.thermocline_height, 0.4, bottom=TankStorage.thermocline_location, color='rebeccapurple')
ax.bar(0, 10-(TankStorage.thermocline_location+TankStorage.thermocline_height), 0.4,bottom=TankStorage.thermocline_location+TankStorage.thermocline_height, color='r')
ax.set_ylabel('Hot and Cold Storage')
ax.yaxis.set_major_formatter(mtick.PercentFormatter(10))
label1 = 'Day: '+str(j+1)
if i < 60:
label2 = 'Time: 12:'+str(i%60).zfill(2)+' AM'
elif 60 <= i < 720:
label2 = 'Time: '+str(int(i/60)).zfill(2)+':'+str(i%60).zfill(2)+' AM'
elif 720 <= i < 780:
label2 = 'Time: '+str(int(i/60)).zfill(2)+':'+str(i%60).zfill(2)+' AM'
else:
label2 = 'Time: '+str(int((i/60))-12).zfill(2)+':'+str(i%60).zfill(2)+' PM'
label3 = 'Stored Energy: ' + str(round(TankStorage.energy_stored)) +' MWh'
ax.set_xlabel(label1+'\n'+label2+'\n'+label3)
ax.set_title('Thermal Energy Storage Tank')
ax.set_xticks([])
ax.set_yticks([0,1,2,3,4,5,6,7,8,9,10])
filename = os.getcwd()+'\\graphs\\tank'+str(k)+'.png'
#plt.savefig(filename, dpi=250, bbox_inches='tight')
plt.show()
energy = np.append(energy, TankStorage.energy_stored)
thermocline_position = TankStorage.thermocline_location
area = TankStorage.Area
k+=1
# Create .gif
# frames = []
# imgs = sorted(glob.glob('**/*.png', recursive=True), key=os.path.getmtime)
# for i in imgs:
# nf = Image.open(i)
# frames.append(nf)
# frames[0].save('tank.gif', format='GIF', append_images=frames[1:],save_all=True, duration=200, loop=0)
# # Show stored energy graph
fig2 = plt.figure()
ax = fig2.add_axes([0,0,1,1])
ax.plot(np.arange(10080), energy)
ax.set_xlabel('Time (hr)')
ax.set_ylabel('Energy Stored (MWh)')
ax.set_title('Energy Stored over 1 week')
ax.set_xlim(left=0,right=10090)
plt.savefig('exergy-1week.png', dpi=250, bbox_inches='tight')
plt.show()
# Energy Stored at 10 min intervals over 1 week:
self.StoredEnergy = energy
self.hotT = hotT
self.coldT = coldT
self.massflowrate = m_SteamGen