Skip to main content

It gives the ranking to models as per the TOPSIS score.Please view the instructions so as to run the package smoothly in your terminal.

Project description

TOPSIS PACKAGE - Assignment 1

I have developed a command line python program to implement the TOPSIS. TOPSIS (technique for order performance by similarity to ideal solution) is a useful technique in dealing with multi-attribute or multi-criteria decision making (MADM/MCDM) problems in the real world

Installation

pip install topsis-bhavya-102103345

Usage

Please provide the filename for the CSV, including the .csv extension. After that, enter the weights vector with values separated by commas. Following the weights vector, input the impacts vector, where each element is denoted by a plus (+) or minus (-) sign. Lastly, specify the output file name along with the .csv extension.

py -m topsis.__main__ [input_file_name.csv] [weight as string] [impact as string] [result_file_name.csv]

Example Usage

The below example is for the data have 5 columns. py -m topsis.__main__ "C:\User\...." "1,1,2,0.5,0.75" "+,+,-,-,-" "C:\User\....."

Example Dataset

Fund Name P1 P2 P3 P4 P5
M1 0.78 0.61 5.5 34.7 10.4
M2 0.88 0.77 5 58.4 16.26
M3 0.61 0.37 5.9 39.9 11.7
M4 0.76 0.58 4.2 57.7 15.81
M5 0.84 0.71 3.2 48 13.19
M6 0.76 0.58 4 68.8 18.54
M7 0.81 0.66 6.5 38.2 11.54
M8 0.81 0.66 3.2 32.8 9.37

Output Dataset

Fund Name P1 P2 P3 P4 P5 TOPSIS Score Rank
M1 0.78 0.61 5.5 34.7 10.4 0.5303740545041122 4
M2 0.88 0.77 5 58.4 16.26 0.5372510220778413 3
M3 0.61 0.37 5.9 39.9 11.7 0.4715707210914604 8
M4 0.76 0.58 4.2 57.7 15.81 0.5099483054760279 6
M5 0.84 0.71 3.2 48 13.19 0.57723478293325 1
M6 0.76 0.58 4 68.8 18.54 0.49447887833737925 7
M7 0.81 0.66 6.5 38.2 11.54 0.5244107252631429 5
M8 0.81 0.66 3.2 32.8 9.37 0.5576533672285703 2

Important Points

  1. There should be only numeric columns except the first column i.e. Fund Name.
  2. Input file must contain atleast three columns.

Copyrights

License

© 2024 Bhavya Bhalla

This repository is licensed under the MIT license.

See LICENSE for details.

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

topsis-bhavya-102103345-1.0.2.tar.gz (4.4 kB view details)

Uploaded Source

Built Distribution

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

topsis_bhavya_102103345-1.0.2-py3-none-any.whl (4.9 kB view details)

Uploaded Python 3

File details

Details for the file topsis-bhavya-102103345-1.0.2.tar.gz.

File metadata

  • Download URL: topsis-bhavya-102103345-1.0.2.tar.gz
  • Upload date:
  • Size: 4.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for topsis-bhavya-102103345-1.0.2.tar.gz
Algorithm Hash digest
SHA256 3364e27b099b5e092ad97c9982255f897483dfe77674bf6489844f78bffed9f7
MD5 06b4e48bb5c102ca6284cea1ed6737a4
BLAKE2b-256 f8ca1a88a3106381d6e796de74542054baae4a22fff55e2c9e7cace18ce194ee

See more details on using hashes here.

File details

Details for the file topsis_bhavya_102103345-1.0.2-py3-none-any.whl.

File metadata

File hashes

Hashes for topsis_bhavya_102103345-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 405aa37886d893b79a98f39f313b177a63f61e1afecafa777b161219eb93a757
MD5 72337bdc0e2c0f82cf2e4c8a257d0187
BLAKE2b-256 731a438e8bd9ed18bde339cdd7cf6bfa5db5eccd4699cec7f38503dc08f73c13

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