Skip to main content

A simple TOPSIS implementation package.

Project description

TOPSIS Package

Overview

The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is a multi-criteria decision analysis (MCDA) technique used to evaluate and rank alternatives based on multiple criteria. This Python package provides a simple implementation of the TOPSIS method.

Features

  • Easy to use function to perform the TOPSIS method on decision matrices.

  • Accepts customizable weights for each criterion.

  • Supports both beneficial and non-beneficial criteria (impacts).

  • Returns preference scores and ranks for the alternatives.

    Parameters: data (list of lists): Decision matrix (alternatives x criteria). weights (list): List of weights for each criterion. impacts (list): '+' for beneficial, '-' for non-beneficial criteria.

    Returns: list: Preference scores for each alternative. list: Ranks of each alternative.

Installation

You can install the Topsis Package using pip from PyPI.

From PyPI:

Run the following command in your terminal or command prompt:

pip install topsis-package  

Installation

Install the package using pip:

pip install 102217109_topsis

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

102217109_topsis-1.0.0.tar.gz (2.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

102217109_topsis-1.0.0-py3-none-any.whl (2.5 kB view details)

Uploaded Python 3

File details

Details for the file 102217109_topsis-1.0.0.tar.gz.

File metadata

  • Download URL: 102217109_topsis-1.0.0.tar.gz
  • Upload date:
  • Size: 2.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.11.11

File hashes

Hashes for 102217109_topsis-1.0.0.tar.gz
Algorithm Hash digest
SHA256 c8018cccdda10baa4f98fff16834440e42046dbd45e90fe38c52b2567854abcb
MD5 c6297e658a666a283d2501a416109b8d
BLAKE2b-256 261bb8660b585d3776aeda5cf73df7785bbfe23b3ce5c6ae2e5c537aa8c98505

See more details on using hashes here.

File details

Details for the file 102217109_topsis-1.0.0-py3-none-any.whl.

File metadata

File hashes

Hashes for 102217109_topsis-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e9836171d4d71a7f7a4aa3c8e2567d8c3a8c259a9831e403d8eb510442ead91e
MD5 488c4a6d048bbb96cd06a64b136f6627
BLAKE2b-256 ab339f4b026d8e064c28bc084cc24cdc2e5f7ff78e720418bccc1ab55d8e2057

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page