About The Project:
Table of Contents
System Requirements:
Installation:
🔥 Open your ./bashrc file and add lines given below at the bottom of file.
Add sourcing to find command:
🔥 Copy the following commands in your ./bashrc file
##Package command Finder:
export IDCODE="${HOME}/PathToDir/.../Data_driven_Kinetics/"
export PATH=$PATH:$IDCODE
alias IDprediction="pwd>${HOME}/PathToDir/.../Data_driven_Kinetics/filelocation.txt && Run.sh"
Replace "/PathToDir/.../" with your directory location.
Example:
If repo is cloned in ./home directory then configure .bashrc using following command:
##Package command Finder:
export IDCODE="${HOME}/Data_driven_Kinetics/"
export PATH=$PATH:$IDCODE
alias IDprediction="pwd>${HOME}/Data_driven_Kinetics/filelocation.txt && Run.sh"
Source the changes:
🔥 (IMPORTANT) To configure the changes in .bashrc, write following command in terminal.
cd
source .bashrc
Install dependency:
🔥 To install all the dependency use INSTALL.sh file. Write the commands given below in the terminal
chmod +x INSTALL.sh
./INSTALL.sh
Make Run.sh file executable:
chmod +x Run.sh
Commands to run the program:
All set!
Now, open terminal and type following commands to generate result.
IDprediction -flag file_name.csv
Input arguments to 'IDprediction' are specified as below:
Consider the data file as 'file_name.csv'
🔥 -a : ‘Analyze’ the data-set by selecting certain parameters
IDprediction -a file_name.csv
IDprediction -b FuelSMILES
IDprediction -b CCC
IDprediction -b CCCCCC
🔥 -h : Generates 'histogram’ plots of parameters for each fuel individually
IDprediction -h file_name.csv
🔥 -m : To find out multiple linear regression of data
IDprediction -c 0.05 -l 10 -r True -s 0.05 -m file_name.csv
IDprediction -c 0.05 -r False -t file_name.csv
IDprediction -e test_data.csv
🔥 -k : To run code multiple ‘(k)’ times and store all test prediction result in different directory
IDprediction -k testset.csv
🔥 -f : Probability density ‘function’ plot of testing result after running code 'k' times
IDprediction -f testset.csv
🔥 -p : Plot and obtain of average value of coefficient from coefficient file (If coefficient result obtained many times and there is variation in coefficients)
IDprediction -p coefficient_3.csv
🔥 -o : To run any 'other’ dataset than fuel
IDprediction -c 0.05 -l 10 -o anyFile.csv
Don’t forget to make changes in ’feature selection.py file’
Examples:
Example:1 Run the following commands to generate models and make predictions using Ignition delay data:
cd TryYourself/nAlkaneIDT/
IDprediction -c 0.1 -t trainset.csv
IDprediction -e testset.csv
Example:2 Run the following commands to generate models and make predictions using Wine quality data:
cd TryYourself/WineQuality/
IDprediction -c 0.1 -o trainset.csv
IDprediction -e testset.csv
Make appropriate changes in ’feature selection.py' file to change features accordingly to the data. (Check manual)