| Name | 102206172-DHRUV JSON |
| Version |
1.0.0
JSON |
| download |
| home_page | https://github.com/Dhruvrstar/TOPSIS |
| Summary | A Python implementation of the TOPSIS method for multi-criteria decision making |
| upload_time | 2025-01-18 23:10:38 |
| maintainer | None |
| docs_url | None |
| author | Dhruv |
| requires_python | >=3.6 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
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No requirements were recorded.
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# TOPSIS Implementation
## Overview
TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making method. This Python package implements the TOPSIS method, allowing you to rank alternatives based on multiple criteria.
This implementation is specifically designed to work with a CSV input file and provides results with TOPSIS scores and ranks.
## Features
- Handles multi-criteria decision-making problems
- Accepts CSV input files
- Outputs a CSV file with TOPSIS scores and ranks
- Validates input data and handles common errors
- Command-line interface for ease of use
## Installation
You can install this package directly from PyPI using pip:
```bash
pip install 102206172_DHRUV
```
## Usage
### Command-Line Interface
After installing the package, you can use it from the command line. The basic usage is:
```bash
topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>
```
### Parameters
- **InputDataFile**: The path to the input CSV file containing the data.
- **Weights**: A string of comma-separated numerical weights (e.g., `"1,1,1,2"`).
- **Impacts**: A string of comma-separated `+` or `-` signs indicating whether each criterion is beneficial (`+`) or non-beneficial (`-`) (e.g., `"+,+,-,+"`).
- **ResultFileName**: The path to the output CSV file where results will be saved.
### Example
Suppose you have an input file named `102206172_data.csv` with the following content:
```csv
Alternative,Criterion1,Criterion2,Criterion3,Criterion4
M1,250,16,12,5
M2,200,6,8,3
M3,300,16,8,4
M4,275,10,10,4
```
You can run the following command:
```bash
topsis 102206172-data.csv "1,1,1,2," "+,+,-,+," 102206172-result.csv
```
This will generate a file `102206172-result.csv` containing the input data along with two additional columns for the TOPSIS score and the rank:
```csv
Alternative,Criterion1,Criterion2,Criterion3,Criterion4,TOPSIS Score,Rank
M1,250,16,12,5,0.556,2
M2,200,6,8,3,0.222,4
M3,300,16,8,4,0.778,1
M4,275,10,10,4,0.444,3
```
### Error Handling
The program includes several checks to handle common errors:
1. **File Not Found**: If the input file is not found, an appropriate error message will be displayed.
2. **Invalid Number of Parameters**: The program checks if the correct number of parameters is provided.
3. **Invalid Data**: The input file must contain at least three columns, with the first column being the name of alternatives, and the rest must contain numeric values.
4. **Weights and Impacts Validation**: The number of weights and impacts must match the number of criteria in the input file. Impacts must be either `+` or `-`.
## Examples
Here are a few examples to demonstrate how the package can be used:
### Example 1: Basic Usage
```bash
topsis data.csv "1,1,1,1" "+,+,+,+" result.csv
```
### Example 2: Different Weights and Impacts
```bash
topsis data.csv "0.5,1,1.5,2" "+,-,+,-" result.csv
```
### Example 3: Handling Errors
If the number of weights or impacts does not match the number of criteria:
```bash
topsis data.csv "1,1,1" "+,+" result.csv
```
This will result in an error message indicating the mismatch.
## Testing
To ensure everything works correctly, you can run some tests. If you haven't already, you can clone the repository and run the tests locally.
```bash
# Clone the repository
git clone https://github.com/Dhruvrstar/TOPSIS.git
# Navigate to the project directory
cd 102206172_DHRUV
# Install the required dependencies
pip install -r requirements.txt
# Run the tests (assuming you've created test scripts)
python -m unittest discover tests
```
## Development
If you'd like to contribute to this project, follow these steps:
1. Fork the repository on GitHub.
2. Clone your fork to your local machine.
3. Create a new branch for your feature or bugfix.
4. Make your changes and commit them with descriptive messages.
5. Push your changes to your fork.
6. Submit a pull request to the original repository.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Contact
If you have any questions, suggestions, or issues, feel free to contact me at `dhruvofff@gmail.com`.
## Acknowledgments
- Thanks to [Name or Organization] for their support.
- Inspired by the original TOPSIS method developed by C.L. Hwang and K. Yoon.
```
### **Instructions for Customization:**
1. **PyPI Badge:** If you want to include the PyPI version badge, replace `102206172_DHRUV` in the badge URL with your actual package name.
2. **Example Commands:** Ensure that the commands and examples match your actual package usage. Replace the placeholder values with real ones.
3. **Contact Information:** Replace `your.email@example.com` with your actual contact email.
4. **Repository URL:** Update any URLs to point to your actual GitHub repository.
5. **Acknowledgments:** Customize the Acknowledgments section with any relevant names or organizations you wish to credit.
By following these steps and customizing the provided template, you'll have a thorough and professional `README.md` file ready for your project!
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"description": "# TOPSIS Implementation\n\n## Overview\n\nTOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision-making method. This Python package implements the TOPSIS method, allowing you to rank alternatives based on multiple criteria.\n\nThis implementation is specifically designed to work with a CSV input file and provides results with TOPSIS scores and ranks.\n\n## Features\n\n- Handles multi-criteria decision-making problems\n- Accepts CSV input files\n- Outputs a CSV file with TOPSIS scores and ranks\n- Validates input data and handles common errors\n- Command-line interface for ease of use\n\n## Installation\n\nYou can install this package directly from PyPI using pip:\n\n```bash\npip install 102206172_DHRUV\n```\n\n## Usage\n\n### Command-Line Interface\n\nAfter installing the package, you can use it from the command line. The basic usage is:\n\n```bash\ntopsis <InputDataFile> <Weights> <Impacts> <ResultFileName>\n```\n\n### Parameters\n\n- **InputDataFile**: The path to the input CSV file containing the data.\n- **Weights**: A string of comma-separated numerical weights (e.g., `\"1,1,1,2\"`).\n- **Impacts**: A string of comma-separated `+` or `-` signs indicating whether each criterion is beneficial (`+`) or non-beneficial (`-`) (e.g., `\"+,+,-,+\"`).\n- **ResultFileName**: The path to the output CSV file where results will be saved.\n\n### Example\n\nSuppose you have an input file named `102206172_data.csv` with the following content:\n\n```csv\nAlternative,Criterion1,Criterion2,Criterion3,Criterion4\nM1,250,16,12,5\nM2,200,6,8,3\nM3,300,16,8,4\nM4,275,10,10,4\n```\n\nYou can run the following command:\n\n```bash\ntopsis 102206172-data.csv \"1,1,1,2,\" \"+,+,-,+,\" 102206172-result.csv\n```\n\nThis will generate a file `102206172-result.csv` containing the input data along with two additional columns for the TOPSIS score and the rank:\n\n```csv\nAlternative,Criterion1,Criterion2,Criterion3,Criterion4,TOPSIS Score,Rank\nM1,250,16,12,5,0.556,2\nM2,200,6,8,3,0.222,4\nM3,300,16,8,4,0.778,1\nM4,275,10,10,4,0.444,3\n```\n\n### Error Handling\n\nThe program includes several checks to handle common errors:\n\n1. **File Not Found**: If the input file is not found, an appropriate error message will be displayed.\n2. **Invalid Number of Parameters**: The program checks if the correct number of parameters is provided.\n3. **Invalid Data**: The input file must contain at least three columns, with the first column being the name of alternatives, and the rest must contain numeric values.\n4. **Weights and Impacts Validation**: The number of weights and impacts must match the number of criteria in the input file. Impacts must be either `+` or `-`.\n\n## Examples\n\nHere are a few examples to demonstrate how the package can be used:\n\n### Example 1: Basic Usage\n\n```bash\ntopsis data.csv \"1,1,1,1\" \"+,+,+,+\" result.csv\n```\n\n### Example 2: Different Weights and Impacts\n\n```bash\ntopsis data.csv \"0.5,1,1.5,2\" \"+,-,+,-\" result.csv\n```\n\n### Example 3: Handling Errors\n\nIf the number of weights or impacts does not match the number of criteria:\n\n```bash\ntopsis data.csv \"1,1,1\" \"+,+\" result.csv\n```\n\nThis will result in an error message indicating the mismatch.\n\n## Testing\n\nTo ensure everything works correctly, you can run some tests. If you haven't already, you can clone the repository and run the tests locally.\n\n```bash\n# Clone the repository\ngit clone https://github.com/Dhruvrstar/TOPSIS.git\n\n# Navigate to the project directory\ncd 102206172_DHRUV\n\n# Install the required dependencies\npip install -r requirements.txt\n\n# Run the tests (assuming you've created test scripts)\npython -m unittest discover tests\n```\n\n## Development\n\nIf you'd like to contribute to this project, follow these steps:\n\n1. Fork the repository on GitHub.\n2. Clone your fork to your local machine.\n3. Create a new branch for your feature or bugfix.\n4. Make your changes and commit them with descriptive messages.\n5. Push your changes to your fork.\n6. Submit a pull request to the original repository.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Contact\n\nIf you have any questions, suggestions, or issues, feel free to contact me at `dhruvofff@gmail.com`.\n\n## Acknowledgments\n\n- Thanks to [Name or Organization] for their support.\n- Inspired by the original TOPSIS method developed by C.L. Hwang and K. Yoon.\n```\n\n### **Instructions for Customization:**\n\n1. **PyPI Badge:** If you want to include the PyPI version badge, replace `102206172_DHRUV` in the badge URL with your actual package name.\n \n2. **Example Commands:** Ensure that the commands and examples match your actual package usage. Replace the placeholder values with real ones.\n\n3. **Contact Information:** Replace `your.email@example.com` with your actual contact email.\n\n4. **Repository URL:** Update any URLs to point to your actual GitHub repository.\n\n5. **Acknowledgments:** Customize the Acknowledgments section with any relevant names or organizations you wish to credit.\n\nBy following these steps and customizing the provided template, you'll have a thorough and professional `README.md` file ready for your project!\n",
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