Data analysis using Python

AIM: For this challenge, you will be create a data visualizer tool. Your task is to write a script that does the following.

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. If, I request for a plot between column 1 (crank angle) and column 8(volume), then the label information should automatically be extracted and must appear as labels in the plots. THIS SHOULD NOT BE DONE MANUALLY.

Compatability check:

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

SOLUTION:

Coding:

"""
File parsing in python
"""

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

#Compatability check
try:
  f=open('engine_data.out','r')

except:
  print('File not recognized. Please provide a valid CONVERGE output file')
  sys.exit()

#starting file parsing
file = 'engine_data.out'
count_rows = 0
count_columns = 0
count_header=0
column_title = []
column_units = []

for line in open(file,'r'):
	if '#' not in line:
		count_rows = count_rows + 1
		count_columns = len(str.split(line))
	else:
		count_header = count_header +1

		if count_header == 3:
			for i in range(0,len(str.split(line))):
				column_title.append(str.split(line)[i])

		elif count_header == 4:
			line_content = str.split(line)
			for i in range(0,len(str.split(line))):
				column_units.append(str.split(line)[i])

#Compatability check

if (count_header < 4 or count_rows < 1 or count_columns < 8):
	print('File not recognized. Please provide a valid CONVERGE output file')

else:
	#Plotting of all columns

 	for i in range(0,count_columns):
 		data_array=[]
 		for j in open(file,'r'):
 			if '#' not in j:
 				data_array.append(float(j.split()[i]))

 		plt.plot(data_array)
 		plt.ylabel(column_title[i+1] + column_units[i+1])
 		plt.savefig(column_title[i+1]+'.png')
 		plt.figure()

 		del data_array

 	#Plotting of given data columns

 	x_axis_column_num=8
 	y_axis_column_num=2
 	x_array=[]
 	y_array=[]


 	for k in open(file,'r'):
 		if '#' not in k:
 			y_array.append(float(k.split()[y_axis_column_num-1]))
 			x_array.append(float(k.split()[x_axis_column_num-1]))

 	plt.plot(x_array,y_array)
 	plt.xlabel(column_title[x_axis_column_num]+column_units[x_axis_column_num])
 	plt.ylabel(column_title[y_axis_column_num]+column_units[y_axis_column_num])
 	plt.savefig(column_title[x_axis_column_num] +' VS '+ column_title[y_axis_column_num]+'.png')
 	plt.figure()

    #Calculating area under the pv curve
 	d = x_array[1] - x_array[0]
 	work = []  
 	for i in range(0,len(x_array), 2):
 		work.append((y_array[i]*2*d))
 	Area = 0
 	for w in work:
 	    Area = Area + w 
 	print('Area under PV diagram:', Area, 'MJ')


    #Calculating power output of the engine
 	RPM = 1500
 	power = Area * 1e+06*RPM/(9550)
 	print('Power Output of the Engine:',power,'kw')

 	#Calculatig specific fuel consumption
 	fuel_per_stroke = 20*1e-06
 	fuel_per_sec = fuel_per_stroke*RPM*60
 	SFC = fuel_per_sec/ (power * 1e+03)
 	print('Specific Fuel Consumption:',SFC,'g/J')
	

Output:

PV Diagram:

Plots for all the columns:

Explanation:

• Parse means to ''resolve (a sentence) into its component parts and describe their syntactic roles''. In computing, parsing is 'an act of parsing a string or a text'. [Google Dictionary]File parsing in computer language means to give a meaning to the characters of a text file as per the formal grammar. A parser is a program that parses the text files.
• In this challenge, we first open the output data file then we calculate the total numbers of columns and rows.
• In that file first 5 rows is the header of the file. Row 3 and 4 having engine parameters title and its units.
• Remaining rows contains values of engine parameters. First we read the row 3 and split the titles separately and stored in column_titles.
• Similarly, read the row 4 and split the units and stored in column_units.
• Here, we checking the compatability of file, if the file is not compatable it shows like this "File not recognized. Please provide a valid CONVERGE output file".
• Now, we read the egine parameters values and separate each columns and stored in data_array. Then plot the data_array and label them from column_titles(Not using manually).
• Similarly delete the data_array and stored the second column and plot the data_array, this is repeated for all the columns.
• The plotting of all the columns is stored in file as shown in the output.
• Next, we plot the graph between column 8 and column 2. So, split the each lines and stored only column 8 and column 2 values in two separate arrays.
• Now, plot the two arrays and label from column_titles and column_units instead of labelling manually.
• Finally calculate the area under pv diagram, power output and specific fuel consumption of the engine as shown in the coding.