def eliminateWarmUpCustomer(self, vector_data):
"""iterate over the vector and compare the average in order to check for the steady state samples"""
temp_vector = []
rk = []
# mean computation for the customers in the queue
customer_avg = CustomerAverage(vector_data[0][0])
for data in vector_data:
customer_avg.update(data[0], data[1])
x = customer_avg.mean(vector_data[-1][0])
while self.k < len(vector_data) / 100:
temp_vector = vector_data[self.k * 15:]
# mean computation for the customers in the queue
customer_avg = CustomerAverage(temp_vector[0][0])
for data in temp_vector:
customer_avg.update(data[0], data[1])
customer_mean = customer_avg.mean(list(temp_vector)[-1][0])
rk.append(((customer_mean - x) / x))
# DEBUG
print str(((customer_mean - x) / x)) + " -- " + str(
len(temp_vector)) + "/" + str(len(vector_data)) + "\n"
print "\n" + str(self.k) + "/" + str(len(vector_data) / 100)
self.previous_mean = customer_mean
self.k += 1
Graphs.showRk(rk)
time = []
cust = []
for element in vector_data:
time.append(element[0])
cust.append(element[1])
Graphs.customerQueueView(time, cust, "cust", "customer in queue")
Graphs.show()
return temp_vector
def eliminateWarmUpResponseTime(self, vector_data):
"""iterate over the vector and compare the average in order to check for the steady state samples"""
temp_vector = []
rk = []
x = numpy.mean(vector_data)
while self.k <= len(vector_data) / 100:
temp_vector = vector_data[self.k * 15:]
temp_mean = numpy.mean(temp_vector)
rk.append((temp_mean - x) / x)
self.previous_mean = temp_mean
self.k += 1
Graphs.showRk(rk)
Graphs.responseTimeShow(vector_data, x)
Graphs.show()
return temp_vector
