semvec/pypi-packages huggingface dataset:
morphomapping 0.0.8
Analyze ImageStream Data
Requires Python: >=3.9
Keywords: analysis, cytometry, imaging flow cytometry

# MorphoMapping

[![Documentation][badge-docs]][link-docs]
[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

[badge-docs]: https://img.shields.io/readthedocs/morphomapping
 
MorphoMapping is an analytical framework designed for the analysis of Imaging Flow Cytometry (IFC) data. It is based on our Python package, morphomapping, which provides tools for dimensionality reduction and clustering of IFC data. Step 2 and Step 4 can be considered optional.

# Description

| workflow | details | 
| --- | --- |
| Step 1 | IFC Data Acquisation|
| Step 2 | Convert .daf to .FCS (R)|
| Step 3 | morphomapping (Python)|
| Step 4 | Cluster Analysis (R)|

# Getting started

Please refer to the [documentation][link-docs].

# Installation

It is recommended to choose conda as your package manager. Conda can be obtained, e.g., by installing the Miniconda distribution. For detailed instructions, please refer to the respective documentation.

With conda installed, open your terminal and create a new environment by executing the following commands::

    conda create -n morphomapping python=3.10
    conda activate morphomapping

## PyPI

Install morphomapping via the pypi release:

    pip install morphomapping


## Development Version

In order to get the latest version, install from [GitHub](https://github.com/Wguido/MorphoMapping) using
    
    pip install git+https://github.com/Wguido/MorphoMapping@main

Alternatively, clone the repository to your local hard drive via

    git clone https://github.com/Wguido/MorphoMapping.git && cd MorphoMapping
    git checkout --track origin/main
    pip install .

Note that while MorphoMapping is in beta phase, you need to have access to the private repo.

## Jupyter notebooks

Jupyter notebooks are highly recommended due to their extensive visualization capabilities. Install jupyter via

    conda install jupyter

and run the notebook by entering `jupyter-notebook` into the terminal.


## Dependencies
* The following Python packages are needed for MorphoMapping:
  
| Package | 
| --- | 
| `bokeh` | 
| `flowkit` | 
| `hdbscan` | 
| `matplotlib` | 
| `numpy` | 
| `openpyxl` | 
| `pandas` | 
| `scikit-learn` | 
| `umap-learn` | 

* The following R libraries (R V.4.2.1)  are required for MorphoMapping's optional DAFtoFCS-Converter and the Cluster Analysis:
  
| Library | Version |
| --- | --- |
| `ggplot2` | *3.4.4*  |
| `ggpubr` | *0.6.0*  |
| `here` | *1.0.1*  |
| `IFC` | *0.2.1*  |
| `rstatix` | *0.7.2*  |


[link-docs]: https://morphomapping.readthedocs.io
muteract 0.2.0
Interactive and Iterative Prompt Mutation Interface for LLM Developers and Evaluators
Requires Python: >=3.10

# Muteract [![PyPI version](https://badge.fury.io/py/your-package-name.svg)](https://pypi.org/project/muteract/0.1.3/) [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE) 

Interactive and Iterative Prompt Mutation Interface for LLM Developers and Evaluators
![Screenshot of the Muteract User Interface](images/UI.png "Muteract User Interface")

## Table of Contents

- [Muteract  ](#muteract--)
  - [Table of Contents](#table-of-contents)
  - [Introduction](#introduction)
  - [Getting Started](#getting-started)
    - [Installation](#installation)
    - [Usage](#usage)
  - [Configuration](#configuration)
  - [Acknowledgements](#acknowledgements)
  - [Contributing](#contributing)
  - [License](#license)

## Introduction

Muteract - an interactive and iterative prompt mutation interface that enables LLM developers and evaluators to input natural language (NL) text prompts, apply mutations, analyze variations in textual responses, and archive results.

![structure](images/Muteract-Arch.drawio.svg)

As of now, this tool provides only Radamsa as the mutator, since it works directly on the bytes in a prompt and can be applied to various modalities. We plan to add more mutators for specific to images, text etc. in the future.

The interaction flow of Muteract is

![flowchart](images/Muteract-Flow.drawio.svg)


## Getting Started

Muteract is a python based tool. Make sure python is installed before following the [Installation](#installation) guide.

### Installation

Muteract can be installed with a simple pip command.

```bash
# Installation command
pip install muteract
```

All the dependencies are taken care by the installation.

### Usage
Ensure that the OpenAI API Key is configured in the environment variable `OPEN_AI_API_KEY` before starting the application.

Just running the Muteract command will open the GUI:
```bash
muteract
```


## Configuration

```
Python version above 3.10 is needed for running the application, along with a browser that supports ES2017.
```

## Acknowledgements
This tool is being developed by [SET-IITGN Group](https://sites.google.com/view/shouvick/shouvick-mondal) in collaboration with [HAIx Lab, IITGN](https://labs.iitgn.ac.in/haix/).

This work is supported by Grant No. IP/IITGN/CSE/SM/2324/02
and Grant No. IP/IITGN/CSE/YM/2324/05 from IIT Gandhinagar,
Gujarat, India.

## Contributing

Conrtibutions are accepted via pull requests. The PRs will be accepted only if they are suitable for the tool.

## License
[Apache License](LICENSE)