Metadata-Version: 2.4
Name: sparsesampler
Version: 1.0.0
Summary: A Python package for fast sampling with applications on flow cytometry and scRNA-seq data, focusing on retaining rare cell populations.
Author-email: Ehsan Karimiara <e.karimiara@gmail.com>
License-Expression: MIT
Project-URL: Homepage, https://github.com/EhsanKA/sparsesampler
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.24
Requires-Dist: pandas
Requires-Dist: scikit-learn
Dynamic: license-file

# sParseSampler
A python package for fast sampling with applications on flow cytometry and scRNA-seq data focusing on retaining rare cell populations.

# Sparse Sampler Visualization

This project demonstrates a step-by-step sparse sampling process using toy data and PCA binning.

## Animated Sampling Process

The following animation shows how points are selected from a 2D toy dataset using PCA binning. Points are selected category by category (cells with 1 point, 2 points, etc.), and the process is visualized step by step:

- All points start as skyblue.
- When a category is considered, the cells are highlighted in yellow and the points in those cells are shown in gray for visibility.
- Selected points turn red and remain red in all subsequent frames.
- The process continues until the target number of points is reached.

![Sampling Process Animation](./sampling_process.gif)

## Usage

To generate the animation, run:

```bash
python -m sparsesampler.visualization
```

The animation will be saved as `sampling_process.gif` in the project directory.
