semvec/pypi-packages huggingface dataset:
ando 0.0.1
Manipulate, scrape, and analyze visual media
License: MIT

# ando ��
[![License: MIT](https://img.shields.io/badge/packager-pypak-dbd3cd.svg)](https://github.com/concurrent-studio/pypak) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) ![PyPI](https://img.shields.io/pypi/v/ando)

Manipulate, scrape, and analyze visual media
[CONCURRENT STUDIO™](https://www.concurrent.studio)


## ⏳ Installation
### �� Pip
```bash
pip3 install ando
```

### �� Source
```bash
git clone https://github.com/concurrent-studio/ando.git
cd ando
pip3 install -e .
```

## Documentation 
A brief description of modules and submodules exists below.  
For ruther information, see the [usage guide](https://concurrent-studio.github.io/ando/).

### �� Modules + Submodules
##### Usage
```python
import ando
```

##### Components
- Color
    - `color_delta`
        - Compute the percent difference between two given colors
    - `get_colors`
        - Get a color palette from a given image
-  Face
    - `get_faces`
        - Get all faces from an image
    - `get_eyes`
        - Get all eyes from an image
    - `get_landmarks`
        - Get facial landmarks from an image
    - `average_faces`
        - Compute the average of all faces in a directory
- Face3D
    - `face_to_3d`
        - Turn a 2D image of a face into a 3D object
- I/O
    - `download`
        - Download an image or video from a url
    - `write_points_to_disk`
        - Write a list of points to disk
    - `get_points_from_disk`
        - Get points saved through above function
    - `load_png`
        - Load a png file by switching out alpha channel for a color
- Transform
    - `draw_points_on_image`
        - Draw a set of points on top of an image
    - `draw_rect_on_image`
        - Draw a rectangle on top of an image
    - `create_collage`
        - Create a collage from a list of images
kozai 0.3.0
Evolve hierarchical triples.
License: MIT
Requires Python: >=3.6
Keywords: kozai lidov triple dynamics orbit star

# Kozai

Kozai is a Python package to evolve hierarchical triples in the secular
approximation.  Hierarchical triples may be evolved either using the
Delaunay formalism (Naoz et al. 2013b) or the vectorial formalism (Katz et
al. 2011).  The quadrupole, octupole, and hexadecapole terms of the
Hamiltonian may be toggled to be included (or not) in the equations of
motion.  Post-Newtonian terms may also be toggled to include both
relativistic precession (PN 1) and gravitational radiation (PN 2.5) using
terms from Blaes et al. (2002). 

The package provides a TripleDelaunay object which may be integrated using
the Delaunay orbital elements and a TripleVectorial which may be integrated
using the eccentricity and angular momentum vectors.  This allows the
integration to occur within the context of an external Python program.

The underlying integrator is from the SciPy ODE package.  By default this
package uses VODE as its integration algorithm, but the algorithm may be
changed to any of the other integration algorithms supported by the SciPy
ODE package.

## Installation

The Kozai package is available on PyPI and can be installed with pip:

```
pip install kozai
```

Or, if you do not have the permissions to run the above:

```
pip install --user kozai
```

## Tutorial

An IPython notebook tutorial is in the docs folder.  The tutorial can be
also be accessed online [here.][1]

Note that you will need to separately install `matplotlib` to run the tutorial
if you don't have it installed already.  `matplotlib` will be installed if you
install the `requirements-dev.txt` file described below.

## Development

If you want to do any development on the `kozai` package it can help to install
the dependencies in the `requirements-dev.txt` file.  If you are in the root
directory of the `kozai` repository you can do this as follows:

```sh
pip install -r requirements-dev.txt
```

## References

- [Antognini, 2015, ArXiv 1504.05957][5]
- [Blaes, O., Lee, M.H., & Socrates, A., 2002, ApJ, 578, 775][2]
- [Katz, B., Dong, S., & Malhotra, R., 2011, PhRvL, 107, 181101][3]
- [Naoz, S., Farr, W.M., Lithwick, Y., Rasio, F.A., & Teyssandier, J., 2013b,
  MNRAS, 431, 2155][4]

[1]: http://nbviewer.ipython.org/url/www.astronomy.ohio-state.edu/~antognini/kozai_tutorial.ipynb
[2]: http://adsabs.harvard.edu/abs/2002ApJ...578..775B
[3]: http://adsabs.harvard.edu/abs/2011PhRvL.107r1101K
[4]: http://adsabs.harvard.edu/abs/2013MNRAS.431.2155N
[5]: http://arxiv.org/abs/1504.05957