# Topsis Value Calculator
Selection of an appropriate Multiple Attribute Decision Making (MADM) method for providing a solution to a given MADM problem is always challenging endeavour. The challenge is even greater for situations where for a specific MADM problem there exist multiple MADM methods with similar degree of suitability. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) helps solve MADM problems.
This is a Python package implementing TOPSIS method for multi-criteria decision analysis.
## Installation
**$ pip install TOPSIS-102003105**
In the commandline, you can write as -
**$ python <package_name> <path to input_data_file_name>
<weights as strings> <impacts as strings> <result_file_name>**
E.g for input data file as data.csv, command will be like
**$ python 102003105.py 102003105-data.csv "0,1,1,1,2,1" "+,-,-,+,-,+" 102003105-Result1.csv**
This will give the output in 102003105-Result1.csv file
License -> MIT
Raw data
{
"_id": null,
"home_page": "https://github.com/AdiK1806/Topsis-Aditya-102003105",
"name": "102003105",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "topsis,TIET,Thapar",
"author": "Aditya Kuthiala",
"author_email": "adityakuthiala1806@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/a8/6c/3c96b039b0d28d8ffe73c181ceeb4d7d88058f7e0456e37fe8133839f8b1/102003105-1.0.5.tar.gz",
"platform": null,
"description": "# Topsis Value Calculator\nSelection of an appropriate Multiple Attribute Decision Making (MADM) method for providing a solution to a given MADM problem is always challenging endeavour. The challenge is even greater for situations where for a specific MADM problem there exist multiple MADM methods with similar degree of suitability. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) helps solve MADM problems.\n\n\nThis is a Python package implementing TOPSIS method for multi-criteria decision analysis.\n\n\n\n\n## Installation\n\n**$ pip install TOPSIS-102003105** \n\nIn the commandline, you can write as -\n **$ python <package_name> <path to input_data_file_name> \n <weights as strings> <impacts as strings> <result_file_name>**\n\t\n\nE.g for input data file as data.csv, command will be like\n **$ python 102003105.py 102003105-data.csv \"0,1,1,1,2,1\" \"+,-,-,+,-,+\" 102003105-Result1.csv**\n\n\nThis will give the output in 102003105-Result1.csv file\n\nLicense -> MIT",
"bugtrack_url": null,
"license": "MIT",
"summary": "A Python package to find TOPSIS for Multi-Criteria Decision Analysis Method",
"version": "1.0.5",
"split_keywords": [
"topsis",
"tiet",
"thapar"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "a86c3c96b039b0d28d8ffe73c181ceeb4d7d88058f7e0456e37fe8133839f8b1",
"md5": "1094556103495f7dcc2b42b9e9f0fd0d",
"sha256": "6bc035406f49f1607816818b7c4ac595cb91f240c1bf96c534d44d466dda0605"
},
"downloads": -1,
"filename": "102003105-1.0.5.tar.gz",
"has_sig": false,
"md5_digest": "1094556103495f7dcc2b42b9e9f0fd0d",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 2923,
"upload_time": "2023-01-22T14:02:03",
"upload_time_iso_8601": "2023-01-22T14:02:03.941799Z",
"url": "https://files.pythonhosted.org/packages/a8/6c/3c96b039b0d28d8ffe73c181ceeb4d7d88058f7e0456e37fe8133839f8b1/102003105-1.0.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-01-22 14:02:03",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "AdiK1806",
"github_project": "Topsis-Aditya-102003105",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "102003105"
}
JSON
