def analyseTotalMem(mem, core): totalMemList = [] for i in range(len(mem)): store = [] for index in range(len(mem[i])): store.append(int(mem[i][index]) * int(core[i][index])) totalMemList.append(store) Counter = [] for item in totalMemList: store = [] sorted_mem = np.sort(item) yvals = np.arange(len(sorted_mem)) / float(len(sorted_mem) - 1) store.append(sorted_mem) store.append(yvals) Counter.append(store) for index in range(len(Counter)): plt.plot(Counter[index][0], Counter[index][1], graphTypes[index], label=fileNames[index]) plt.ticklabel_format(style='plain') plt.xlabel("Memory Size (MB)") plt.ylabel("Number of jobs (%)") plt.legend(loc='upper left') plt.xscale("log") plt.ylim(-0.05, 1) plt.show()
def graphJobSize(jobSize): Counter = [] for item in jobSize: store = [] sorted_runTime = np.sort(item) yvals = np.arange(len(sorted_runTime)) / float(len(sorted_runTime) - 1) store.append(sorted_runTime) store.append(yvals) Counter.append(store) for index in range(len(Counter)): plt.plot(Counter[index][0], Counter[index][1], graphTypes[index], label=fileNames[index]) # plt.ticklabel_format(style='plain') plt.xlabel("Job Size (Cores)") plt.ylabel("Number of Jobs (%)") plt.legend(loc='lower right') plt.xscale("log") plt.ylim(-0.05, 1) plt.show()
def days_from_rental(x) : max_value=max(x['Rental Booked']) v.append((datetime.now()-max_value).total_seconds()/(3600*24)) c.append(mean(x['Customer ID']))