semvec/pypi-packages huggingface dataset:
cave-mapper 0.2.0
Tools for mapping between objects and representations in the CAVE ecosystem
Requires Python: <3.13,>=3.10

# cave-mapper

Tools for mapping between objects and representations in the Connectome Annotation and
Versionining Engine (CAVE) ecosystem.

This package is a work in progress and is mainly a place to stash functions that I
find useful.

## Installation

```bash
pip install cave-mapper
```

or

```bash
uv pip install cave-mapper
```

or 

```bash
uv add install cave-mapper
```

## Available Functions

- `map_points`: This takes points, and a root ID (likely points annotated inside an object) and maps them to voxels/supervoxel IDs that are guaranteed to be part of the root ID. This is useful for mapping points to a specific object in a 3D space.

- `map_points_via_mesh`: This takes points and a root ID (likely points that were annotated on the surface of that object) and maps them to voxels/supervoxel IDs that are guaranteed to be part of the root ID.
tacklebox-cli 0.2.6
A small collection of CLI utilities.
Requires Python: >=3.11

# tacklebox-cli

[<img alt="Actions Status" src="https://c.csw.im/cswimr/tacklebox/badges/workflows/actions.yml/badge.svg?style=plastic">](https://c.csw.im/cswimr/tacklebox/actions?workflow=actions.yml)
[<img alt="PyPI - Version" src="https://img.shields.io/pypi/v/tacklebox-cli?style=plastic">](https://pypi.org/project/tacklebox-cli/)
[<img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/tacklebox-cli?style=plastic">](https://pypi.org/project/tacklebox-cli/)
[<img alt="PyPI - License" src="https://img.shields.io/pypi/l/tacklebox-cli?style=plastic">](https://c.csw.im/cswimr/tacklebox/src/branch/main/LICENSE/)  
tacklebox-cli offers a suite of useful CLI tools.

## Usage

### tacklebox copy / paste

Cross-platform clipboard management tool. Uses system tools such as `wl-copy` on Linux Wayland or `clip.exe` on Windows, and [OSC 52](https://www.reddit.com/r/vim/comments/k1ydpn/a_guide_on_how_to_copy_text_from_anywhere/) escape codes when **copying** over SSH or when no other tools are available. See [`copy_with_tooling()`](https://c.csw.im/cswimr/tacklebox/src/branch/main/tacklebox/commands/clipboard.py) for all supported tools.

```bash
$ echo "a" | tacklebox copy --trim && tacklebox paste
a
```

### tacklebox spectacle (Linux only)

Uses the [zipline.py](https://pypi.org/project/zipline-py/) library alongside KDE's [Spectacle](https://invent.kde.org/plasma/spectacle) application to take a screenshot or screen recording and automatically upload it to a [Zipline](https://github.com/diced/zipline) instance. This automatically reads Spectacle's configuration files to determine file formats.

```bash
$ tacklebox spectacle --mode region \ 
    --server "https://zipline.example.com" \ 
    --token "$(cat /file/containing/zipline/token)" \ 
    | tacklebox copy --trim

# or to record a video
$ tacklebox spectacle --mode region --record \ 
    --server "https://zipline.example.com" \ 
    --token "$(cat /file/containing/zipline/token)" \ 
    | tacklebox copy --trim
```

### tacklebox zipline

Wraps the [zipline.py](https://pypi.org/project/zipline-py/) CLI. See the [zipline.py CLI documentation](https://ziplinepy.readthedocs.io/en/latest/cli.html) for more information.
sekf 0.0.4a0
The Subset Extended Kalman Filter for online updates to neural network models as systems evolve.
Requires Python: >=3.8
Keywords: bayesian inference, ekf, extended kalman filter, kalman filter, online learning, sequential bayesian inference, sequential learning, subset extended kalman filter

# Subset Extended Kalman Filter

Updating Neural Network models as changes in the underlying system occur:

- slowly and monotonically (drift)
- discretely (transfer learning)

## Installation

The only required dependencies aside from the standard library are `numpy>=1.8.0` (for `.npz` file saving) and `torch>=2.0.0` (for `torch.func` functions)

The `sekf` package can be installed using `pip`:

- `pip install sekf` to install from pypi
- `pip install git+https://github.com/joshuaeh/Subset-Extended-Kalman-Filter.git` to install from the github repository
- clone the repository using `git clone https://github.com/joshuaeh/Subset-Extended-Kalman-Filter.git`, then install locally using `pip install -e <path_to_repo>`
- If you are getting a `ModuleNotFoundError`, check that you are using the correct python environment. I've also found it helpful to declare the package name when installing locally using `uv`: `uv pip install -e "sekf @ ."`.  

## TODO

- [ ] documentation
pydjinni 1.0a9
An opinionated Djinni reimplementation written in Python.
Requires Python: >=3.13
Keywords: djinni

<div align="center">

<img src="https://raw.githubusercontent.com/pydjinni/pydjinni/main/docs/assets/logo.png" width="60" height="60" alt="logo">

# PyDjinni


![GitHub](https://img.shields.io/github/license/pydjinni/pydjinni)
![PyPI](https://img.shields.io/pypi/v/pydjinni)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pydjinni)
![PyPI - Downloads](https://img.shields.io/pypi/dm/pydjinni)
![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/pydjinni/pydjinni/workflow.yml)
[![Built with Material for MkDocs](https://img.shields.io/badge/Material_for_MkDocs-526CFE?logo=MaterialForMkDocs&logoColor=white)](https://squidfunk.github.io/mkdocs-material/)

An opinionated Djinni reimplementation written in Python.

</div>



## Features

- **Easy Interface Definition** The PyDjinni IDL allows to define the interface between the host language and C++ with a clean and intuitive syntax.
- **Flexible Configuration** The output can be configured comfortably with a YAML configuration file.
- **Modular** Pydjinni is modular. Additional capabilities can be added through custom plugins.
- **Toolchain** The tool provides additional utilities to help build, package and distribute cross-platform libraries.
- **Python API** The tools functionality can also be used from a Python API, in order to seamlessly embed into custom build processes.

## Installation

### PyPi (recommended)

```shell
pip install pydjinni
```

### Git

To get access to yet unreleased changes, PyDjinni can be installed directly from the git repository:

```shell
pip install git+https://git@github.com/pydjinni/pydjinni.git@main
```