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']))
