Week 6 - Data analysis

Aim: To perform the data analysis

Objective:

• Data visualizer

  • Your script should take column numbers as the input and plot the respective columns as separate images
  • Each file should be saved by the name of the column
  • The plot labels should be extracted from the file.

• Compatibility check

  • Your code should exit gracefully if a non-compatible file is provided as an input. It should say something like "File not recognized. Please provide a valid CONVERGE output file"

• Basic performance calculation

  • Calculate the area under the P-V diagram. P is in column 2 and V is in column 8.
  • Calculate the power output of this engine. Assume that RPM is 1500
  • This engine consumed 20 micrograms of fuel (per 1 stroke cycle). Calculate its specific fuel consumption.

Code explanation :

Import library
using input syntax and if-else we check the entry of the correct file
Now we take the file to check for valid convergence input value and check using the for loop and with reference #
Take the data from the file
Take input from the user for x and y column and plot the values
Create the p and v values using append and calculate the power

Code:

import matplotlib.pyplot as plt
import numpy as np
from numpy import trapz


fname=input('Enter File name with file extension:')
if fname == 'engine_data.out':
	print('Compatibility check')
else:
	print('File name is invalid, please enter a valid file name')
	exit()

#Fuction to check the compatibility of the input file
def CompCheck(a):
	if "CONVERGE" not in a:
		print('Incompatible File: Please provide a valid CONVERGE output file, program will exit now')
		exit()
	else:
		print('Compatibility Check Success')
		pass

test = []

#Reading the file for compatibility 

for line in open(fname):
	if '#' in line:
		test.append(line.split())


#calling the compatibility function to check for valid converge input file 

CompCheck(test[0])
colnum=len(test[1])
colhead = len(test[2])
col_num = []
col_val = []
col_unit = []
a=test[1].index("column")
for x in range(a, colnum-1):
	col_num.append(x)

for i in test[2]:
	if i is not '#':
		col_val.append(i)

for j in test[3]:
	if j is not '#':
		col_unit.append(j)

print('Available Data')
for i in range(0,len(col_num)):
	print(col_num[i], col_val[i], col_unit[i])

#Section for user choice for the plots required

x = int(input('Enter X Column No.: '))-1
y = int(input('Enter Y Column No.: '))-1

x_label = col_val[x]
y_label = col_val[y]

X = []
Y = []

#Reading the required column data from the file
for line in open(fname):
	if '#' not in line:
		X.append(float(line.split()[x]))
		Y.append(float(line.split()[y]))

#plotting the column values as required by the user		
plt.plot(X, Y, linewidth=2)
plt.xlabel(x_label+col_unit[x])
plt.ylabel(y_label+col_unit[y])
plt.show()

#Engine Performance Calculations

P = []		
V = []       

for line in open(fname):
	if '#' not in line:
		P.append(float(line.split()[1]))
		V.append(float(line.split()[7]))

Pressure = 1e6* np.array(P) 
Volume = np.array(V)
AUC = np.trapz(Pressure, Volume) 
print('Engine Performance Calculations')
print('Work Done', AUC, 'Joules')
cyclepersec = 750/60 
power = AUC*(cyclepersec/1000) 
print('Power Output of the engine @ 1500RPM', power, 'kW')
mf= 20e-6 
SFC= mf*3600/power
print('Specific Fuel Consumption', SFC, 'g/KW.h')

Results:

• Data visualization and basic calculation

• Compatibility check