semvec/pypi-packages huggingface dataset:
pixelpop 0.2.3
Powered by numpyro and jax, package for fitting the GW population with a nonparametric binning scheme, where bins are correlated with only their nearest neighbors. Meant for inferring the GW population distribution nonparametrically in higher dimensions.
License: MIT
Requires Python: >=3.11

# PixelPop

Package for nonparameteric (AKA weakly modeled, data-driven) Bayesian inference of a gravitational wave population, built on `JAX` and `numpyro`. 
Aimed particularly at correlated nonparameteric inference in spaces with dimension 2-3.

This method works by binning the space into a cartesian grid, and inferring the log-rate density in each bin, each of which is a free parameter. 
Each bin is coupled to its nearest-neighbors using an intrinsic conditional-autoregressive (ICAR) model.

The dimension of the inference problem can become very large (e.g. 10^4 for a 2-dimensional space with a density of 100 bins along each axis), and 
we leverage auto-differentiation and GPU acceleration in `JAX`, as well as the efficient No-U-Turn HMC sampler in `numpyro` to sample the posterior.

#### Running PixelPop

Please see the example run scripts in the `examples/` directory.

#### Attribution

Please cite [Heinzel et al. (2025)](https://arxiv.org/abs/2406.16813) if you use PixelPop in your research.

```
@article{Heinzel:2024jlc,
    author = "Heinzel, Jack and Mould, Matthew and {\'A}lvarez-L{\'o}pez, Sof{\'\i}a and Vitale, Salvatore",
    title = "{High resolution nonparametric inference of gravitational-wave populations in multiple dimensions}",
    eprint = "2406.16813",
    archivePrefix = "arXiv",
    primaryClass = "astro-ph.HE",
    doi = "10.1103/PhysRevD.111.063043",
    journal = "Phys. Rev. D",
    volume = "111",
    number = "6",
    pages = "063043",
    year = "2025"
}
```
Additionally, consider citing [Heinzel et al. (2025)](https://arxiv.org/abs/2406.16844) which applies PixelPop to GWTC-3
```
@article{Heinzel:2024hva,
    author = "Heinzel, Jack and Mould, Matthew and Vitale, Salvatore",
    title = "{Nonparametric analysis of correlations in the binary black hole population with LIGO-Virgo-KAGRA data}",
    eprint = "2406.16844",
    archivePrefix = "arXiv",
    primaryClass = "astro-ph.HE",
    doi = "10.1103/PhysRevD.111.L061305",
    journal = "Phys. Rev. D",
    volume = "111",
    number = "6",
    pages = "L061305",
    year = "2025"
},
```
and [Alvarez-Lopez et al. (2025)](https://arxiv.org/abs/2506.20731) which shows PixelPop can accurately recover the complex, multi-dimensional correlations in a realistic population-synthesis population.
```
@article{Alvarez-Lopez:2025ltt,
    author = "Alvarez-Lopez, Sofia and Heinzel, Jack and Mould, Matthew and Vitale, Salvatore",
    title = "{Nowhere left to hide: revealing realistic gravitational-wave populations in high dimensions and high resolution with PixelPop}",
    eprint = "2506.20731",
    archivePrefix = "arXiv",
    primaryClass = "astro-ph.HE",
    month = "6",
    year = "2025"
}
```
hyprtodo 0.1.1
A todo list widget for Hyprland
License: MIT
Requires Python: >=3.8

# hyprtodo

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![PyPI version](https://badge.fury.io/py/hyprtodo.svg)](https://badge.fury.io/py/hyprtodo)

**System tray integration** - Quick access from your system tray
 **Vim-like keybindings** - Navigate with j/k
**Customizable theme** - Edit CSS to match your desktop
**Simple and fast** - Lightweight TUI interface

## Installation

### Linux

**Using pipx (recommended):**
```bash
pipx install hyprtodo
```

**Using pip:**
```bash
pip install hyprtodo
```

### Windows
System Tray integration is not supported with windows. Only running the application

**Clone the repository:**
```bash
git clone https://github.com/williamj48/hyprtodo.git
cd hyprtodo
python3 hyprtodo
```




## Usage

Simply run:
```bash
hyprtodo
```

This will create a system tray icon. Click the icon to open your todo list in a terminal window.

**Keybindings:**
- `j` / `k` - Move down/up
- `Enter` - Add new todo
- `Space` - Toggle selection
- `Ctrl+C` / `q` - Quit
- `Esc` - Unfocus input

Click the "Commit" button or press Enter in the input field to save changes.

## Configuration

### Todo Storage
Your todos are stored at:
```
~/.config/hypr/hyprtodo/todo.txt
```

Do not edit this file. It is meant to only be accessed through the application

### Custom Styling
The CSS theme file is automatically created at:
```
~/.config/hyprtodo/custom.tcss
```

Edit this file to customize colors, borders, and styling to match your desktop theme.

### Terminal Configuration
By default, hyprtodo uses `kitty` as the terminal. To use a different terminal, set the `TERMINAL` environment variable:

```bash
export TERMINAL=alacritty
hyprtodo
```

## Requirements

- Python 3.8+
- Linux with system tray support

## Future Plans

- 🔄 Google Tasks API integration for cloud sync
- 📱 Additional export formats
- 🔔 Desktop notifications for reminders

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Author

William Elder - [williamxelder@gmail.com](mailto:williamxelder@gmail.com)

## Repository

[https://github.com/williamj48/hyprtodo
mcp-cuc-yh 0.1.0
An MCP Server that provides a tool to get the current time with optional timezone support
License: MIT
Requires Python: <4.0,>=3.10

# MCP Time Server

An MCP Server that provides a tool to get the current time with optional timezone support.

## Features

- Provides a `get_current_time` tool to retrieve the current time
- Supports optional timezone parameter
- Simple and lightweight implementation
- Built using the Model Context Protocol (MCP)

## Installation

```bash
pip install mcp-time-server
```

## Usage

### Running the Server

```bash
mcp-time-server
```

This will start the MCP Server using the STDIO transport, which is suitable for local process communication.

### Using the `get_current_time` Tool

The server exposes a single tool called `get_current_time` that can be used by MCP clients.

#### Parameters

- `timezone` (optional): A timezone string, e.g., "Asia/Shanghai", "America/New_York"
  - If not provided, the system's default timezone will be used

#### Return Value

A formatted string representing the current time in the format: `YYYY-MM-DD HH:MM:SS.SSSSSS TIMEZONE`

#### Examples

```python
# Get current time in system default timezone
result = await mcp_client.call_tool("get_current_time")
# Example output: "2023-12-25 13:45:30.123456 EST"

# Get current time in a specific timezone
result = await mcp_client.call_tool("get_current_time", timezone="Asia/Shanghai")
# Example output: "2023-12-26 02:45:30.123456 CST"
```

## Project Structure

```
mcp-time-server/
├── mcp_time_server/
│   ├── __init__.py      # Package initialization
│   └── main.py          # Main server implementation
├── pyproject.toml       # Project configuration
├── README.md            # This file
├── LICENSE              # License file
└── .gitignore           # Git ignore file
```

## License

MIT License - see the LICENSE file for details.

## About MCP

The Model Context Protocol (MCP) is an open-source standard for connecting AI applications to external systems. For more information, visit [modelcontextprotocol.io](https://modelcontextprotocol.io).