[Work][Python]Spec power automation-4

Environment: Windows server 2019, python 2.7

This blog follows from the previous blog.

There are three steps which I want to develop for automation.

In this section of this blog, the target is output a summary excel and plot chart.

There are four types from spec power log.

2. Power from Intel PTU.

3. Windows cpu usage log.

4.Spec power log.

We need get time interval from each loading 100%, 70%, 50%, 30% and idle to get 1, 2, 3 data log. For example, we need get 10:39:23 PM to 11:00:25 PMdata.

My solution is that all time covert to 24-hour clock and compute it as sec number. For example, 22:39:23 is 22 x60 x60 + 39x60+23=81563 and 23:00:25 is 23x60x60+0x60+25=82825. So we can get 81563 to 82825 data. The code is as below.

Convert time to 24-hour clock.

def twenfour(ins):
time_24=''
ins=ins.strip()
is_pm = ins[-2:].lower() == 'pm'
time_list = list(map(int, ins[:-2].split(':')))

if is_pm and time_list[0] < 12:
time_list[0] += 12
if not is_pm and time_list[0] == 12:
time_list[0] = 0
time_24=':'.join(map(lambda x: str(x).rjust(2, '0'),time_list))
return time_24

Convert time to sec number.

def time2int(n):
time_list = list(map(int, n.split(':')))
t_sum=(time_list[0]*60*60)+(time_list[1]*60)+time_list[2]
return t_sum

Output time point for getting record data.

def timepoint(day,time24, df,x,y,z,s):
timeindf=''
l=len(time24)
dl=len(df)
time_point=[]
for j in range(l):
for i in range(s,dl):
if day[j] in df[x][i]:
timeindf=df[x][i][y:z].strip()
diff=time24[j]-time2int(timeindf)
if diff<6 and diff>-6:
time_point.append(i)
break
return time_point

Save output excel is by using below code.

writer = pd.ExcelWriter('C:\Spec_power_auto\Summary.xlsx', engine='xlsxwriter')dx.to_excel(writer, sheet_name='Sheet1')writer.save()

If I can get log successfully, we can output plot chart as below code.

def plotcpu(a, alltime2,all_data1,all_data2,b,c):
plt.ylabel(a)
plt.xlabel('Time ')
plt.xticks(np.arange(0, len(all_time2), 700))
plt.plot(all_time2,all_data1,color='red')
plt.plot(all_data2,color='blue')
plt.legend(['CPU0','CPU1'])
plt.savefig(b+c+'.jpeg')
plt.show()

The summary example is as below.

The plot chart is as below.

Reference:

http://www.spec.org/power_ssj2008/

Interesting in any computer science.