Topsis-Cherish-102003647 0.2

It is a topsis package.

for: Topsis_Cherish_102003647 submitted by: Cherish Mahajan Roll no: 102003647 Group: 3COE25

Topsis_Cherish_102003647 is a Python library for solving Multiple Criteria Decision Making(MCDM) problems by Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).

Installation

Use the package manager pip to install Topsis-Cherish-102003647.

pip install Topsis_Cherish_102003647

Usage

Enter csv filename followed by .csv extension, then enter the weights vector with vector values separated by commas, followed by the impacts vector with comma separated signs (+,-)

Input

And using this package in Python as :

import topsispy as tp
a =[
     [250, 16, 12, 5],
     [200, 16, 8, 3],
     [300, 32, 16, 4],
     [275, 32, 8, 4],
     [225, 16, 16, 2]
   ]
w = [0.25, 0.25, 0.25, 0.25]
sign = [-1, 1, 1, 1]
tp.topsis(a, w, sign)

The package can be used via commandline as :

$ python [package name] [path of csv as string] [list of weights as string] [list of sign as string]

Example

sample.csv

A csv file showing data for different mobile handsets having varying features.

Model	Storage space(in gb)	Camera(in MP)	Price(in $)	Looks(out of 5)
M1	16	12	250	5
M2	16	8	200	3
M3	32	16	300	4
M4	32	8	275	4
M5	16	16	225	2

weights vector = [ 0.25 , 0.25 , 0.25 , 0.25 ]

impacts vector = [ + , + , - , + ]

Output:

  TOPSIS RESULTS
  As per the given sample, the output file looks as given below :

Model	Storage space(in gb)	Camera(in MP)	Price(in $)	Looks(out of 5)	Topsis Score	Rank
M1	16	12	250	5	0.534277	3
M2	16	8	200	3	0.308368	5
M3	32	16	300	4	0.691632	1
M4	32	8	275	4	0.534737	2
M5	16	16	225	2	0.401046	4

Other notes

• The first column and first row have only been omitted by the library Topsis-Cherish-102003647 before processing, in attempt to remove indices and headers. So make sure the csv follows the format as shown in sample.csv otherwise the code will have issues in working properly.
• Make sure the csv does not contain categorical values since the code takes into account all the values which are encoded as numerical values.
• The Topsis-Cherish-102003647 works on the sample data and calculates the topsis score according to which it provides the rank to each available option.