semvec/pypi-packages huggingface dataset:
xanlib 0.2.0
A library to handle the 3D data format XBF from the game Emperor: Battle for Dune.
License: MIT
Requires Python: >=3.10

# xanlib
[![Run tests](https://github.com/Lunaji/xanlib/actions/workflows/tests.yml/badge.svg)](https://github.com/Lunaji/xanlib/actions/workflows/tests.yml)
[![PyPI](https://img.shields.io/pypi/v/xanlib.svg)](https://pypi.org/project/xanlib/)

A Python library to handle the 3D data format XBF of the Xanadu engine, used in the game *Emperor: Battle for Dune*.  
It may be used to load and save all 1521 XBF files from the game.

## Installation
The library can be installed with pip:  
`pip install xanlib`

## Examples
### Console Usage
The following commands entered into a python console will edit the sidebar to move it to the left:
```python
from xanlib import load_xbf, save_xbf
scene = load_xbf('Data/UI0001/SIDEBAR/SIDEBAR1.XBF')
scene['~~0hide#'].transform = tuple(v - 100 if i == 12 else v for i, v in enumerate(scene['~~0hide#'].transform))
save_xbf(scene, 'Output/SIDEBAR1.XBF')
```
Explanation:
1. Import the load and save functions
2. Load the sidebar file
3. Subtract 100 from the x-coordinate of the translation component of the transformation matrix. It is a flat tuple in column-major order, thus need to modify the element at index 12. Because it is a tuple, it has to be entirely replaced.
4. Save to a new file.

Put the new file in a UI/SIDEBAR folder in the game's DATA folder to override the original and view the change in-game.

### blender_import.py
A script that can be run within Blender to import the meshes of a XBF file.
![missile_tank_blender](https://github.com/user-attachments/assets/47bdbe22-556e-4556-bca6-8b0d4c755497)

### extract_animations.py
A script that extracts animation info from the FX Data Header of an xbf file,
provided as a command line argument.  
Currently stand-alone, the code has yet to be integrated into the library.

Example usage:
```bash
python extract_anim_info.py Data/3DDATA0001/Buildings/AT_MGT_H0.xbf
```
will produce:
```
Stationary: 104-133, 0-50, 51-104, 133-163, 163-193
Idle 0: 200-240
Fire 0: 193-275
```

### xbf_viewer.py
A rudimentary vertex animation viewer made with `pygame`. It highlights the normals in these animations.  
(A more functional viewer is [under development](https://github.com/Lunaji/Xanadu-Animation-Viewer))
![pygame_viewer_animation](https://github.com/user-attachments/assets/b20e0c67-2c84-48ac-9d34-cf5c22e3478e)
smurfs 2.0.0rc7
Smart UseR Frequency analySer
License: MIT
Requires Python: <4.0,>=3.10

# SMURFS
![SMURFS Image](https://i.imgur.com/Uh2UhpZ.png)

**SMURFS** provides automatic extraction of frequencies from
timeseries. It provides various interfaces, from a standalone command line tool, to jupyter and python 
integrations and computes possible frequency combinations, directly downloads and reduces (if necessary) data 
of TESS/Kepler/K2 observations and much much more.Smart UseR Frequency analySer
## Getting started

To install smurfs, you need python > 3.5, pip as well as cmake. If you don't have these, install them through the
packet manager of your choice (f.e. _brew_(Mac) or _apt_ (Debian)). For pip check 
[here](https://pip.pypa.io/en/stable/installing/).

## Installation

To install SMURFS, simply run the following command:

```bash
pipx install smurfs
```

if you don't have pipx installed, check [here](https://pipx.pypa.io/stable/installation/) for instructions.

## Quickstart

Using SMURFS as a standalone command line tool is very simple. Simply call ```smurfs``` with a **target**, signal to noise
ratio cutoff and the window size. The target can be either:

- A path to a file, containing 2 columns with time and flux
- Any name of a star, that is resolvable by Simbad and has been observed by the **Kepler**,**K2** or **TESS** missions.

As an example, we can take a look at the star Gamma Doradus:
```
smurfs "Gamma Doradus" 4 2
```

SMURFS creates a result folder after running the code. In this case it has the following structure
```
- Gamma_Doradus
    - data
        - _combinations.csv
        - _result.csv
        - LC_residual.txt
        - LC.txt
        - PS_residual.txt
        - PS.txt         
    - plots
        - LC_residual.pdf
        - LC.pdf
        - PS_residual.pdf
        - PS_result.pdf
        - PS.pdf
```
The ```LC*.txt``` files contain the light curves, original and residual. The ```PS*.txt``` files contain the 
original as well as the residual amplitude spectrum. ```_combinations.csv``` shows all combination frequencies for the 
result and ```_result.csv``` gives the result for a given run.

## Citing

If you use this software in your research, consider citing  it using Zenodo.

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3768032.svg)](https://doi.org/10.5281/zenodo.3768032)


If you use SMURFS to extract LC data from FFIs, you should also cite the awesome people of Eleanor.

[Feinstein et al. 2019](https://ui.adsabs.harvard.edu/abs/2019PASP..131i4502F/abstract)


 
## Documentation

Full documentation is available [here](https://smurfs.readthedocs.io/en/master/)
PyARV 0.2.8
Approximate random variables
License: MIT
Requires Python: >=3.12

# PyARV

Python wrapper of a C implementation of
approximate random variables as detailed in:

>Michael B. Giles and Oliver Sheridan-Methven. 
> _Approximating
inverse cumulative distribution functions to produce
approximate random variables._ 
> ACM Transactions
on Mathematical Software, 49(3), Article 26, September 2023, 29 pages. 
> [https://doi.org/10.1145/3604935](https://doi.org/10.1145/3604935)

## Authors

Dr Oliver Sheridan-Methven  
[oliver.sheridan-methven@hotmail.co.uk](mailto:oliver.sheridan-methven@hotmail.co.uk)

## Documentation

The full documentation can be found here: [Documentation](https://oliversheridanmethven.github.io/pyarv/).
dir-magic 1.2.0
DirMagic is a library written in Python to brute force directories and subdomains
License: MIT
Requires Python: <4.0,>=3.10

# DirMagic

[![Testing](https://github.com/heroesofcode/DirMagic/actions/workflows/Testing.yml/badge.svg)](https://github.com/heroesofcode/DirMagic/actions/workflows/Testing.yml)
[![Python 3.10](https://img.shields.io/badge/python-3.10-yellow.svg)](https://www.python.org/)
[![GitHub](https://img.shields.io/github/license/heroesofcode/DirMagic)](https://github.com/joaolfp/DirMagic/blob/master/LICENSE)

DirMagic is a library written in Python to brute force directories and subdomains

## Installation
```
git clone https://github.com/heroesofcode/DirMagic.git
```

## Usage

```
cd DirMagic
pip install -r requirements.txt
python3 dirMagic.py
```

1 - Find directories

<img src="https://github.com/heroesofcode/DirMagic/blob/master/assets/dir.png">

2 - Find subdomains

<img src="https://github.com/heroesofcode/DirMagic/blob/master/assets/subdomain.png">

### WordLists

You can create your own wordlist with .txt, follow the example below

wordlist.txt
```
admin
login
dashboard
blog
```

Below are some WordList links for downloads

- If you're running on [Kali Linux](https://www.kali.org/), it's already installed on the system, just follow this [documentation](https://www.kali.org/tools/wordlists/).
- [SecLists](https://github.com/danielmiessler/SecLists) is a repository that has several wordlists to download.

## Contribution

* To contribute, from a fork in the project please feel free to give suggestions, improvements and feel free to add features. After you contribute, open a pull request.

## Contributors

<a href="https://github.com/heroesofcode/DirMagic/graphs/contributors">
  <img src="https://contrib.rocks/image?repo=heroesofcode/DirMagic" />
</a>

## License
DirMagic is released under the MIT license. See [LICENSE](https://github.com/heroesofcode/DirMagic/blob/master/LICENSE) for details.