def __plot_complete_mix():
'''
Plots all TS of a mix in a single image using multiple axis
'''
# Connect with times
connection = times_client.connect()
plot_mix = pdata.mix_2
cols = 5
rows = len(plot_mix) / cols + 1
index = 0
print rows
fig = plt.figure()
fig.set_figheight(20)
fig.set_figwidth(40)
for desc in plot_mix:
name = desc.name
timeSeries = connection.load(__times_name(True, name, POSTFIX_USER))
_, demand = util.to_array(timeSeries)
index += 1
ax = fig.add_subplot(rows, cols, index)
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.plot(range(0, len(demand)), demand)
plt.savefig(configuration.path('mix_overlay', 'png'))
# Close times connection
times_client.close()
def __dump_to_csv():
connection = times_client.connect()
demands = []
for desc in selected:
timeSeries = connection.load(__times_name(True, desc.name, POSTFIX_NORM))
_, demand = util.to_array(timeSeries)
demands.append((desc.name, demand))
import csv
with open(configuration.path('traces', 'csv'), 'wb') as csvfile:
spamwriter = csv.writer(csvfile, delimiter='\t')
row = []
for demand in demands:
row.append(demand[0])
spamwriter.writerow(row)
l = len(demands[0][1])
for i in xrange(0, l):
row = []
for demand in demands:
if i < len(demand[1]):
row.append(demand[1][i])
else:
print 'warn'
row.append(0)
spamwriter.writerow(row)
times_client.close()
def __dump_user_profile_maxes():
'''
Used to verify that all user profiles have user values below MAX_USERS
'''
# Connect with times
connection = times_client.connect()
for name in connection.find('.*%s$' % (POSTFIX_USER)):
result = util.to_array(connection.load(name))[1]
if np.max(result) > MAX_USERS:
print '%s - %i' % (name, np.max(result))
times_client.close()
def __plot_overlay_mix():
'''
Plots all TS of a mix in a single axis graph
'''
# Connect with times
connection = times_client.connect()
# Plot selected
selected_mix0 = ['O2_retail_ADDORDER', 'SIS_163_cpu', 'SIS_393_cpu']
selected_mix1 = ['SIS_222_cpu', 'SIS_213_cpu', 'SIS_387_cpu']
plot_mix = selected_mix1
# Plot all from a set
# plot_mix = []
# for i in xrange(a, a + 100):
# print selected[i].name
# plot_mix.append(selected[i].name)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.set_xlim([0, 300])
for name in plot_mix:
timeSeries = connection.load(__times_name(True, name, POSTFIX_USER))
print timeSeries
_, demand = util.to_array(timeSeries)
demand = demand[7:289 + 7]
ax.plot(range(0, len(demand)), demand, linewidth=0.7)
xt = [(t * 60 / 5) for t in xrange(0, 25)]
xl = [t for t in xrange(0, 25)]
ax.set_xticks(xt)
ax.set_xticklabels(xl)
ax.set_xlabel('Time in hours')
ax.set_ylabel('Load in number of users')
# plt.show()
plt.savefig(configuration.path('overlay', 'png'))
plt.savefig(configuration.path('mix1', 'pdf'))
# Close times connection
times_client.close()
def __renter(self,showTable=True):
if showTable :
# clear()
self.__print()
print()
print("+------------------------------------------+")
print("+ Ingrese los numeros separados por coma, +")
print("+ como en este ejemplo: 1,8,7,6 +")
print("+------------------------------------------+")
print()
print(" Presione:")
print(" 1.- Para un nuevo juego")
print(" 2.- Para ver instrucciones")
print(" 3.- Ver tablero")
print(" 0.- Para salir")
inp = to_array(input("Ingrese su opcion: "))
if(inp == 0):#Salir del juego
exit()
elif(inp == 1):#Reiniciamos el juego
self.begin()
elif(inp == 2):#Mostramos las instrucciones
self.__instruc()
elif(inp == 3):#Mostramos el tablero con el menu
self.__renter()
elif type(inp) is list: #Ingrasamos los valores
#Validamos que no se guarde en el tablero
#Varias veces los mismos valores
if self.codebreaker.addTurn(inp):
self.__update(inp)
else:
print()
print("+------------------------------------------+")
print("+ Ya se han ingreso esto valores: +")
print("+ {0},{1},{2},{3} +".format(*inp))
print("+------------------------------------------+")
self.__renter(False)
else:#Mostrar otra vez el menu
self.__renter()
def __winner(self,win=True):
if win:
self.__print()
print()
print("+------------------------------------------+")
print("+ Felicitaciones has GANADO!!!! +")
print("+------------------------------------------+")
else :
print()
print("+------------------------------------------+")
print("+ Has PERDIDO!!!! :( :( :( :( +")
print("+------------------------------------------+")
print()
print(" Presione:")
print(" 1.- Para un nuevo juego")
print(" 0.- Para salir")
inp = to_array(input("Ingrese su opcion: "))
if(inp == 0):#Salir de juego
exit()
elif(inp == 1):#Reiniciar el juego
self.begin()
else:#Mostrar otra vez el menu
self.__winner(win)
def process_trace(connection, name, cycle_time):
timeSeries = connection.load(name)
time, demand = util.to_array(timeSeries)
return __extract_profile(time, demand, timeSeries.frequency, cycle_time)
# Get the longest period
ret = np.max(periods)
return ret, acf, ped
if __name__ == '__main__':
import matplotlib.pyplot as plt
# Connect and load TS
connection = times_client.connect()
ll = connection.find('RAW_O2_.*')
for name in ll:
timeSeries = connection.load(name)
time, demand = util.to_array(timeSeries)
period, acf, ped = __period_calc(timeSeries.frequency, demand, time)
# Calculate profile
freq, profile = __extract_profile(time, demand, timeSeries.frequency, period, hour(1), lambda x: np.mean(x))
freq, profile_upper = __extract_profile(time, demand, timeSeries.frequency, period, hour(1), lambda x: np.percentile(x, 95))
freq, profile_lower = __extract_profile(time, demand, timeSeries.frequency, period, hour(1), lambda x: np.percentile(x, 15))
# Plotting
fig = plt.figure()
folder = 'C:/temp/'
ax = fig.add_subplot(111)
ax.fill_between(xrange(len(profile)), profile_lower, profile_upper, interpolate=True, facecolor='lightgray', lw=0)
ax.plot(range(len(profile)), profile)
plt.savefig('%s/%s_profile.png' % (folder, name), dpi=30)
def process_trace(connection, name, modifier, additive, scale, shift):
timeSeries = connection.load(name)
time, demand = util.to_array(timeSeries)
interval = timeSeries.frequency
return timeSeries.frequency, __add_modifier(time, demand, interval, modifier, additive, scale, shift)
def process_trace(connection, name, cycle_time, day):
timeSeries = connection.load(name)
time, demand = util.to_array(timeSeries)
return __sample_day(time, demand, timeSeries.frequency, cycle_time, period=day)
def __load(name):
timeSeries = connection.load(name)
_, demand = util.to_array(timeSeries)
return timeSeries.frequency, demand
def process_trace(connection, name, ifreq, cycle_time, day):
timeSeries = connection.load(name)
time,demand = util.to_array(timeSeries)
return sample_day(name, time, demand, ifreq, cycle_time, day=day)