semvec/pypi-packages huggingface dataset:
pygments-httpie 0.1
A Pygments lexer for the the output of httpie.
License: MIT
Requires Python: >=3.5
Keywords: lexer,http,httpie

# pygments-http

----

A minimalistic Pygments lexer for the output of [`httpie`](https://github.com/jakubroztocil/httpie).

The main lexer class here borrows code heavily from the `ColorFormatter` class from `httpie`.

The `httpie` license is included in the root of this repository.
fast-gpu-voronoi 0.0.3
GPU-Accelerated Jump Flooding Algorithm for Voronoi Diagram in log*(n)
License: MIT
Requires Python: >=3.1.0


[**Demo (Google Colab)**](https://colab.research.google.com/drive/1feoho8M_1a4tOpYFDPkqDVJeWHwdhJox?usp=sharing)

<div align="center">
  <img src="docs/figure_jka_star_intro.png" alt="JFA*" width="500px" /><br />
</div>

<br/>

|     | Research | Authors |
|:----|:---------|:--------|
| \[[slides](https://maciejczyzewski.github.io/fast_gpu_voronoi/slides_small.pdf)\] | __GPU-Accelerated Jump Flooding Algorithm for Voronoi Diagram in log*(n)__ [this] | Maciej A. Czyzewski |
| \[[article](https://vgl.csa.iisc.ac.in/pdf/pub/ICVGIP14_Talha.pdf)\] | Facet-JFA: Faster computation of discrete Voronoi diagrams [2014] | Talha Bin Masood, Hari Krishna Malladi, Vijay Natarajan |
| \[[article](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.101.8568&rep=rep1&type=pdf)\] | Jump Flooding in GPU with Applications to Voronoi Diagram and Distance Transform [2006] | Guodong Rong, Tiow-Seng Tan |

# Implemented Algorithms

<table>
<thead>
<tr>
<th></th>
<th>JFA*</th>
<th>JFA+</th>
<th>JFA</th>
</tr>
</thead>
<tbody>
<tr>
<td>used improvement</td>
<td>noise+selection</td>
<td>noise</td>
<td>--</td>
<td rowspan="4"><img src="docs/figure_3d.png" alt="results" width="350px" /></td>
</tr>
<tr>
<td>num. of needed steps</td>
<td><strong>log*(n)</strong></td>
<td>log4(p)</td>
<td>log2(p)</td>
</tr>
<tr>
<td>step size</td>
<td>p/(3^i)</td>
<td>p/(2^i)</td>
<td>p/(2^i)</td>
</tr>
<tr>
<td>research</td>
<td>(our)</td>
<td>(our)</td>
<td>[Guodong 2006]</td>
</tr>
</tbody>
</table>

# Installation & Example

Project can be installed using `pip`:

```bash
$ pip3 install fast_gpu_voronoi
```

Here is a small example to whet your appetite:

```python3
from fast_gpu_voronoi       import Instance
from fast_gpu_voronoi.jfa   import JFA_star
from fast_gpu_voronoi.debug import save

I = Instance(alg=JFA_star, x=50, y=50, \
        pts=[[ 7,14], [33,34], [27,10],
             [35,10], [23,42], [34,39]])
I.run()

print(I.M.shape)                 # (50, 50, 1)
save(I.M, I.x, I.y, force=True)  # __1_debug.png
```

# Development

If you want to contribute, first clone git repository and then run tests:

```bash
$ git clone git@github.com:maciejczyzewski/fast_gpu_voronoi.git
$ pip3 install -r requirements.txt
$ pytest
```

# Results

| Our method                      | Current best          |
|:-------------------------------:|:---------------------:|
| JFA\*                           | JFA                   |
| ![JFA_star](docs/jfa_star2.gif) | ![JFA](docs/jfa2.gif) |
| steps = log\*(2000) = 4          | steps = log(720) ~= 10 |

_...for x = 720; y = 720; seeds = 2000 (read as n = 2000; p = 720)._

# Thanks

<div align="center">
  <img src="docs/PP_logo.jpg" alt="Poznan University of Technology" width="600px" /><br />
  <img src="docs/opencl_logo.svg" alt="OpenCl" width="200px" />
</div>