Skip to main content

This is a topsis package of version 0.5

Project description

Topsis:-MULTIPLE-CRITERIA DECISION MAKING

TOPSIS

Submitted By: SANJOLI AGARWAL 102003425.

Date: 21-JAN-2023.

Description: Evaluation of alternatives based on multiple criteria using TOPSIS method..


What is TOPSIS?

Technique for Order Preference by Similarity to Ideal Solution TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution, and greatest distance from the negative-ideal solution.


How to install this package:

>>pip install Topsis_Sanjoli_102003425

In Command Prompt

>> topsis data.csv "1,1,1,1" "+,+,-,+" result.csv

Input file (data.csv)

The decision matrix should be constructed with each row representing a Model alternative, and each column representing a criterion like Attribute, Price or cost, Storage Space ,Camera,Looks.

Attribute Price or cost Storage Space Camera Looks
Mobile 1 250$ 16GB 12MP 5
Mobile 2 200$ 16GB 8MP 3
Mobile 3 300$ 32GB 16MP 4
Mobile 4 275$ 32GB 8MP 4
Mobile 5 225$ 16GB 16MP 2

Weights (weights) is not already normalised will be normalised later in the code.

Information of benefit positive(+) or negative(-) impact criteria should be provided in impacts.


Output file (result.csv)

Attribute Price or cost Storage Space Camera Looks Topsis_score Rank
Mobile 1 250$ 16GB 12MP 5 0.4228 4
Mobile 2 200$ 16GB 8MP 3 0.4635 3
Mobile 3 300$ 32GB 16MP 4 0.5097 2
Mobile 4 275$ 32GB 8MP 4 0.3772 5
Mobile 5 225$ 16GB 16MP 2 0.6871 1

The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**

Project details


Release history Release notifications | RSS feed

This version

0.5

Download files

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

Source Distribution

Topsis_Sanjoli_102003425-0.5.tar.gz (3.5 kB view details)

Uploaded Source

Built Distribution

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

Topsis_Sanjoli_102003425-0.5-py3-none-any.whl (4.2 kB view details)

Uploaded Python 3

File details

Details for the file Topsis_Sanjoli_102003425-0.5.tar.gz.

File metadata

  • Download URL: Topsis_Sanjoli_102003425-0.5.tar.gz
  • Upload date:
  • Size: 3.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.5

File hashes

Hashes for Topsis_Sanjoli_102003425-0.5.tar.gz
Algorithm Hash digest
SHA256 cfde516586f3f004c455224786d20ecf9364dae006ee574be5880eb4bf8235b0
MD5 79ead0bb2ae60240658b2fcc8ca33d5e
BLAKE2b-256 96c7964861cdb4a5fc7e8392210ee13348fc2f5f40c7795a202fe5f2613f37cd

See more details on using hashes here.

File details

Details for the file Topsis_Sanjoli_102003425-0.5-py3-none-any.whl.

File metadata

File hashes

Hashes for Topsis_Sanjoli_102003425-0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 a3268939ae8b9fe570ae8daf285d99d261520a50ab80acdb4c8c137077e55f88
MD5 bb06ba37379e9725b592682389bfbc60
BLAKE2b-256 d95aee2ee0c3084af9b7b4ee9dfc396911fe7d2e1cb561fa39f3e02f397f959d

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