semvec/pypi-packages huggingface dataset:
topsis-Pulkit-102103239 1.0.0
A Python package to find TOPSIS for MCDM (Multi-Criteria Decision Analysis Method)
License: MIT
Keywords: TOPSIS,MCDM

# Topsis
TOPSIS( Technique for order for preference by similarity to Ideal solution ) for MCDM (Multiple criteria decision making) in Python compiled by Pulkit Sanan, 102103239, TIET, Patiala. 

## Installation
Use the package manager pip to install.
```pip install topsis_Pulkit_102103239```

## 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 (+,-) and enter the output file name followed by .csv extension.

```python [InputDataFile as .csv] [Weights as a string] [Impacts as a string] [ResultFileName as .csv]```

### Example
```topsis_Pulkit_102103239 sample.csv "1,1,1,1" "-,+,+,+" output.csv```

## Please Note That"

The first column and first row are removed by the library before processing, in attempt to remove indices and headers. So the csv MUST follow the format as shown in sample.csv shown in the Example section.
The input data file MUST contain three or more columns.
The second to last columns of the data file MUST contain NUMERIC values.
The number of weights, impacts and columns (second to last) MUST be SAME.
Impacts MUST either be '+' or '-'.
Impacts and Weights MUST be separated by , (comma).

## License

© 2024 Pulkit Sanan

This reopsitory is licensed under MIT License. See LICENSE for details.
topsis-kartikye-102103708 1.0.1
A Python package to find TOPSIS for MCDM (Multi-Criteria Decision Analysis Method)
License: MIT
Keywords: TOPSIS,MCDM

# Topsis
TOPSIS( Technique for order for preference by similarity to Ideal solution ) for MCDM (Multiple criteria decision making) in Python compiled by Kartikye Chadda, 102103708, TIET, Patiala. 

## Installation
Use the package manager pip to install topsis-3283.
```pip install topsis_kartikye_102103708```

## 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 (+,-) and enter the output file name followed by .csv extension.

```python [InputDataFile as .csv] [Weights as a string] [Impacts as a string] [ResultFileName as .csv]```

### Example
```topsis_kartikye_102103708 sample.csv "1,1,1,1" "-,+,+,+" output.csv```

## Please Note That"

The first column and first row are removed by the library before processing, in attempt to remove indices and headers. So the csv MUST follow the format as shown in sample.csv shown in the Example section.
The input data file MUST contain three or more columns.
The second to last columns of the data file MUST contain NUMERIC values.
The number of weights, impacts and columns (second to last) MUST be SAME.
Impacts MUST either be '+' or '-'.
Impacts and Weights MUST be separated by , (comma).

## License

Â© 2024 Katikye Chadda

This reopsitory is licensed under MIT License. See LICENSE for details.
PhasorMath 0.0.2
A basic python package for phasor calculation and phasor represention
License: MIT
Requires Python: >=3.8

# PhasorMath

  

## Introduction

PhasorMath is a Python package designed to perform fundamental calculations with phasors, visualize phasors, and calculate symmetrical components for unbalanced three-phase systems.

  

## Key Features:

  

1.  **Phasor Calculations:** Simplify the manipulation of phasors with comprehensive set of functions, allowing basic arithmetic operations, conversion between polar and rectangular forms, and more.

2.  **Visualization Tools:** Plot phasors, visualize unbalanced three-phase systems, and observe symmetrical components with interactive plots.

3.  **Symmetrical Components:** Tackle unbalanced three-phase systems with Phasor's symmetrical component calculation capabilities.

  

## Installation

  

Simply execute the following command in your terminal. Make sure your python version is 3.8:

```

pip install PhasorMath

```

  

## Documentation

  

https://hansanaprabashwara.github.io/PhasorMath/

  

## Compatibility

  

This package is compatible with Python 3.8