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