semvec/pypi-packages huggingface dataset:
topsis-lovish-102117148 1.0.2
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.
License: MIT

# 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-lovish-102117148```

## 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 

<br>

## 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.

<br>
rnaseeker 1.0.0
RNA-seq scripts and libraries
License: MIT
Requires Python: >=3.7
Keywords: rna,rnaseq,dna,fasta,fastq,bio,gene

# RNAseeker

## RNA-seq scripts and libraries

Josh Tompkin

<jtompkin-dev@proton.me>

<https://github.com/jtompkin/rnaseeker>

### Install with pip

```bash
pip3 install rnaseeker
```

### Command line programs

- go_filter: Filter gProfiler output and format for Revigo

```bash
rnaseeker go-filter [-h] [-v] [-c TERM_COLUMN] [-d IN_DELIMITER] [-o OUT_FILE] [-p PVAL_COLUMN] [-i ID_COLUMN] [-s OUT_DELIMITER] [--no-format] [--header] [-f FILTER_TERMS] [--filter-file FILTER_PATH] gProfiler_file
```

- fasta_filter: Filter fasta sequences by length and 'N' content

```bash
rnaseeker fasta-filter [-h] [-o OUT_PATH] [-l LINE_LENGTH] fasta_path minimum_basepairs
```

- fasta_split: Split fasta/fastq files

```bash
rnaseeker fasta-split [-h] [-v] [-i INPUT] [-f {fasta,fastq}] [-s] [-p [PREFIX]] [--header-prefix [REGEX]] [-d DIRECTORY] [-e EXTENSION] number
```

### Python libraries

- sequence
  - sequence_io: Manipulate sequence files and store sequence information
Topsis-102116022 1.0.0
Calculates Topsis Score and Rank
License: MIT

## Topsis-Kunal-102116022

# TOPSIS

Submitted By: **Kunal Arora - 102116022**.

Type: **Package**.

Title: **TOPSIS**.

Version: **1.0.0**.

Date: **28-01-2024**.

Author: **Kunal Arora**.

Maintainer: **Kunal Arora <arorakunal0930@gmail.com>**.

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

---

## What is TOPSIS?

**T**echnique for **O**rder **P**reference by **S**imilarity to **I**deal **S**olution
(TOPSIS) originated in the 1980s as a multi-criteria decision making method.
TOPSIS chooses the alternative of shortest Euclidean distance from the ideal solution,
and greatest distance from the negative-ideal solution.

<br>

## Using this package:

```bash
pip install Topsis-Kunal-102116022
```

### In Command Prompt

```bash
topsis data.csv "1,1,1,1" "+,+,-,+" result.csv
```

## Input file (data.csv)

| Model | Correlation | R<sup>2</sup> | RMSE | Accuracy |
| ----- | ----------- | ------------- | ---- | -------- |
| M1    | 0.79        | 0.62          | 1.25 | 60.89    |
| M2    | 0.66        | 0.44          | 2.89 | 63.07    |
| M3    | 0.56        | 0.31          | 1.57 | 62.87    |
| M4    | 0.82        | 0.67          | 2.68 | 70.19    |
| M5    | 0.75        | 0.56          | 1.3  | 80.39    |


<br>

## Output file (result.csv)

| Model | Correlation | R<sup>2</sup> | RMSE | Accuracy | Topsis_score | Rank |
| ----- | ----------- | ------------- | ---- | -------- | ------------ | ---- |
| M1    | 0.79        | 0.62          | 1.25 | 60.89    | 0.7722       | 2    |
| M2    | 0.66        | 0.44          | 2.89 | 63.07    | 0.2255       | 5    |
| M3    | 0.56        | 0.31          | 1.57 | 62.87    | 0.4388       | 4    |
| M4    | 0.82        | 0.67          | 2.68 | 70.19    | 0.5238       | 3    |
| M5    | 0.75        | 0.56          | 1.3  | 80.39    | 0.8113       | 1    |

<br>
The output file contains columns of input file along with two additional columns having **Topsis_score** and **Rank**
pywxdump-mini 2.4.2
微信信息获取工具
License: MIT
Requires Python: >=3.6, <4

# <center>PyWxDump</center>

[![Python](https://img.shields.io/badge/Python-3-blue.svg)](https://www.python.org/)
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[![PyPI](https://img.shields.io/pypi/v/pywxdump)](https://pypi.org/project/pywxdump/)
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# 一、项目介绍

## 1. 项目简介

[PyWxDump](https://github.com/xaoyaoo/pywxdump) 超级简化版本，仅支持key以及wxid以及filepath的导出，不支持其他功能。

主要面向安全人员

# 二、使用说明

```shell
pip install pywxdump-mini # 或者下载exe文件（7.5M），地址 https://github.com/xaoyaoo/pywxdumpmini/releases
wxinfo # 查看微信信息 包含key wxid filepath
```

参看  https://github.com/xaoyaoo/pywxdump

# 三、免责声明（非常重要！！！！！！！）

本项目仅供学习交流使用，请勿用于非法用途，否则后果自负。

您应该在下载保存，编译使用本项目的24小时内，删除本项目的源代码和（编译出的）程序。

本项目仅允许在授权情况下对数据库进行备份，严禁用于非法目的，否则自行承担所有相关责任。

下载、保存、进一步浏览源代码或者下载安装、编译使用本程序，表示你同意本警告，并承诺遵守它;

请勿利用本项目的相关技术从事非法测试，如因此产生的一切不良后果与项目作者无关。

# 四、许可证

```text
MIT License

Copyright (c) 2023 xaoyaoo

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

PyWxDump is hosted at: https://github.com/xaoyaoo/PyWxDump

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
```