TOPSIS-NANDITA-101917191 3.0

topsis package for MCDM problems

TOPSIS-NANDITA-101917191

submitted by: Nandita Roll no: 101917191 Group: 3CSE8

TOPSIS-NANDITA-101917191 is a Python library for dealing with Multiple Criteria Decision Making(MCDM) problems by using Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS).

Installation

Use the package manager pip to install TOPSIS-NANDITA-101917191.

pip install TOPSIS-NANDITA-101917191

Usage

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

topsis sample.csv "1, 1, 1, 1" "+, -, +, +" output.csv

or vectors can be entered without " "

topsis sample.csv 1,1,1,1 +,-,+,+ output.csv

But the second representation does not provide for inadvertent spaces between vector values. So, if the input string contains spaces, make sure to enclose it between double quotes (" ").

To view usage help, use

topsis /h

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 = [ + , + , - , + ]

input:

topsis sample.csv 0.25,0.25,0.25,0.25 +,+,-,+ output.csv

output:

output.csv

TOPSIS RESULTS (P-Score, Rank) are appended to the input csv and saved

Model	Storage space(in gb)	Camera(in MP)	Price(in $)	Looks(out of 5)	P-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 are removed by the library before processing, in attempt to remove indices and headers. So make sure the csv follows the format as shown in sample.csv.
• Make sure the csv does not contain categorical values

License

MIT