Data Analysis in PYTHON

AIM : Write a program in PYTHON to create a data visualizer tool.

Compatability check

• The 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"

Data visualizer

• The 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.

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 micro grams of fuel (per 1 stroke cycle). Calculate its specific fuel consumption.

EXPLANATION OF CODE :

1) Firstly we import all the necessacry libraries.

2) We then check if the data file is compatable or not and we open and read it . Here we use a keyword called enumerate as it assigns the values for each line and are stored in the variable ' i '. To read and append the column names we used the ' if '#' in l ' statement .

3) To read and append the column values we used the ' if '#' not in line ' statement and proceeded for the further calculations .

4) Plotting the graphs and saving the names of given axis by splitting the names into different columns and labelling the axis by them .

eg : c = l.split()

xname = c[x]

plt.xlabel(c[x])

5) To calculate area under the PV curve we use :np.trapz(pressure,volume) where trapz is a definite integral as approximated by trapezodial rule , which is used to calculate the area under given x & y locations .

Power = `(2*pi*area*10^6 *1500)/(60/1000)`

Specific fuel consumption = `(3600*20e-6*1500)/(60*power)`

PYTHON CODE :

""" PROGRAM TO PERFORM DATA ANALYSIS """

import math 
import matplotlib.pyplot as plt 
import numpy as np 
 

# COMPATABILITY CHECK 

try :
	open('engine_data.out','r')
except :                                                    # if the output displays FileNotFoundError then we print the below
	print('File not recognized. Please provide a valid CONVERGE output file.')
	
file_name = open('engine_data.out','r')                     # opening and reading the file 
for i,l in enumerate(file_name):                            # enumerate keyword stores assigned values in the 'i' variable  
     if '#' in l :
     	if i == 2:
     		c = l.split()

# DATA VISUALIZER 

x = 1                                                       # crank angle 
y = 8                                                       # volume
xname = c[x]
yname = c[y]
xdata = []
ydata = []

for line in open('engine_data.out','r'):                    # feeding data into the file name arrays
      if '#' not in line:
     	 xdata.append(float(line.split()[x-1]))             # appending the data into the specific file name 
     	 ydata.append(float(line.split()[y-1]))           

# GRAPH PLOTS FOR CRANK ANGLE AND VOLUME 

plt.plot(xdata,ydata)
plt.xlabel(c[x])
plt.ylabel(c[y])
plt.savefig('volume&crank.png')
plt.show()

# INPUTS FOR PV GRAPH 

x = 2                                                     # pressure 
y = 8                                                     # volume
pressure = []
volume = []
for line in open('engine_data.out','r'):
	if '#' not in line:
		pressure.append(float(line.split()[x]))
		volume.append(float(line.split()[y]))

# GRAPH PLOTS FOR PRESSURE AND VOLUME 

plt.plot(volume,pressure)
plt.xlabel('volume')
plt.ylabel('pressure')
plt.show()

# BASIC PERFORMANCE CALCULATION

area = np.trapz(pressure,volume)
print('Area under the PV curve = ',area)

power = 2*math.pi*area*pow(10,6)*1500/(60/1000)
print('Power = ',power,'Watt')

sfc = (3600*20e-6*1500)/(60*power)
print('Specific fuel consumption = ',sfc,'gram/KW*hr')

GRAPHS & OUTPUTS :

1) Crank angle V/S Volume :

2) Pressure V/S Volume :

3) Performance calculation output :

4) Compatibility check with wrong file name :

ERRORS :

CORRECTIONS : for i,l in enumerate(f):