semvec/pypi-packages huggingface dataset:
pybarycuda 1.0.0
A tiny CUDA library for fast barycentric operations
License: MIT

# pybarycuda

Pybaracuda is python wrapper for Barycuda - which
is a tiny CUDA accelerated library with no dependencies that
performs various barycentric operations. This is an attempt to speed-up
a 3D renderer that I'm working on.

Currently, the library exposes the following functions:  
* `point_in_simplex` - takes an array of points, the vertices
of a 2D/3D simplex, and tells you if each point lies inside the
simplex.  
* `bary_simplex` - takes an array of points, the vertices of
a 2D/3D simplex, and returns the barycentric coordinates for
each point.

# Development
See the Github [repo](https://github.com/postmalloc/barycuda).

## References
Shirley, P. (2009) Fundamentals of Computer Graphics  
https://en.wikipedia.org/wiki/Barycentric_coordinate_system  
https://math.stackexchange.com/questions/1226707/how-to-check-if-point-x-in-mathbbrn-is-in-a-n-simplex
pysastra 0.1.0
Lightweight Natural Language Processing for Indonesian Language.
License: MIT
Requires Python: >=3.6.3

# pySastra

Lightweight Natural Language Processing for Indonesian Language.

# Design Plan

| Planned | Pipeline         | Description               |
|---------|------------------|---------------------------------------------|
| 🟠 | Language         | A text-processing pipeline. |
| 🟡 | Tokenizer        | Segment text, and create Doc objects with the discovered segment boundaries.|
| 🟠 | Lemmatizer       | Determine the base forms of words.|
| 🟡 | Morphology       | Assign linguistic features like lemmas, noun case, verb tense etc. based on the word and its part-of-speech tag.|
| 🟠 | Tagger           | Annotate part-of-speech tags on Doc objects.|
| 🔄 | DependencyParser | Annotate syntactic dependencies on Doc objects.|
| 🔄 | EntityRecognizer | Annotate named entities, e.g. persons or products, on Doc objects.|
| 🔄 | TextCategorizer  | Assign categories or labels to Doc objects.|
| 🔄 | Matcher          | Match sequences of tokens, based on pattern rules, similar to regular expressions.|
| 🔄 | PhraseMatcher    | Match sequences of tokens based on phrases.|
| 🔄 | EntityRuler      | Add entity spans to the Doc using token-based rules or exact phrase matches.|
| 🔄 | Sentencizer      | Implement custom sentence boundary detection logic that doesn’t require the dependency parse.|

🟢 Completed With Test
🟡 Completed
🟠 On Progress 
🔄 Planned

`reference : spaCy language pipeline`