----------
## Table of contents
* [Overview](https://github.com/sepandhaghighi/samila#overview)
* [Installation](https://github.com/sepandhaghighi/samila#installation)
* [Usage](https://github.com/sepandhaghighi/samila#usage)
* [Mathematical Details](https://github.com/sepandhaghighi/samila#mathematical-details)
* [Try Samila in Your Browser](https://github.com/sepandhaghighi/samila#try-samila-in-your-browser)
* [Issues & Bug Reports](https://github.com/sepandhaghighi/samila#issues--bug-reports)
* [Social Media](https://github.com/sepandhaghighi/samila#social-media)
* [Contribution](https://github.com/sepandhaghighi/samila/blob/master/.github/CONTRIBUTING.md)
* [References](https://github.com/sepandhaghighi/samila#references)
* [Acknowledgments](https://github.com/sepandhaghighi/samila#acknowledgments)
* [Authors](https://github.com/sepandhaghighi/samila/blob/master/AUTHORS.md)
* [License](https://github.com/sepandhaghighi/samila/blob/master/LICENSE)
* [Show Your Support](https://github.com/sepandhaghighi/samila#show-your-support)
* [Changelog](https://github.com/sepandhaghighi/samila/blob/master/CHANGELOG.md)
* [Code of Conduct](https://github.com/sepandhaghighi/samila/blob/master/.github/CODE_OF_CONDUCT.md)
## Overview
Samila is a generative art generator written in Python, Samila lets you create images based on many thousand points. The position of every single point is calculated by a formula, which has random parameters. Because of the random numbers, every image looks different.
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## Installation
### Source code
- Download [Version 1.1](https://github.com/sepandhaghighi/samila/archive/v1.1.zip) or [Latest Source](https://github.com/sepandhaghighi/samila/archive/dev.zip)
- Run `pip install -r requirements.txt` or `pip3 install -r requirements.txt` (Need root access)
- Run `python3 setup.py install` or `python setup.py install` (Need root access)
### PyPI
- Check [Python Packaging User Guide](https://packaging.python.org/installing/)
- Run `pip install samila==1.1` or `pip3 install samila==1.1` (Need root access)
### Easy install
- Run `easy_install --upgrade samila` (Need root access)
### Conda
- Check [Conda Managing Package](https://conda.io)
- `conda install -c sepandhaghighi samila` (Need root access)
## Usage
### Magic
```pycon
>>> import matplotlib.pyplot as plt
>>> from samila import GenerativeImage
>>> g = GenerativeImage()
>>> g.generate()
>>> g.plot()
>>> plt.show()
```
### Basic
```pycon
>>> import random
>>> import math
>>> def f1(x, y):
result = random.uniform(-1,1) * x**2 - math.sin(y**2) + abs(y-x)
return result
>>> def f2(x, y):
result = random.uniform(-1,1) * y**3 - math.cos(x**2) + 2*x
return result
>>> g = GenerativeImage(f1, f2)
>>> g.generate()
>>> g.plot()
>>> g.seed
188781
>>> plt.show()
```
### Projection
```pycon
>>> from samila import Projection
>>> g = GenerativeImage(f1, f2)
>>> g.generate()
>>> g.plot(projection=Projection.POLAR)
>>> g.seed
829730
>>> plt.show()
```
* Supported projections : `RECTILINEAR`, `POLAR`, `AITOFF`, `HAMMER`, `LAMBERT`, `MOLLWEIDE` and `RANDOM`
* Default projection is `RECTILINEAR`
### Marker
```pycon
>>> from samila import Marker
>>> g = GenerativeImage(f1, f2)
>>> g.generate()
>>> g.plot(marker=Marker.CIRCLE, spot_size=10)
>>> g.seed
448742
>>> plt.show()
```
* Supported markers : `POINT`, `PIXEL`, `CIRCLE`, `TRIANGLE_DOWN`, `TRIANGLE_UP`, `TRIANGLE_LEFT`, `TRIANGLE_RIGHT`, `TRI_DOWN`, `TRI_UP`, `TRI_LEFT`, `TRI_RIGHT`, `OCTAGON`, `SQUARE`, `PENTAGON`, `PLUS`, `PLUS_FILLED`, `STAR`, `HEXAGON_VERTICAL`, `HEXAGON_HORIZONTAL`, `X`, `X_FILLED`, `DIAMOND`, `DIAMON_THIN`, `VLINE`, `HLINE` and `RANDOM`
* Default marker is `POINT`
### Rotation
You can even rotate your art by using `rotation` parameter. Enter your desired rotation for the image in degrees and you will have it.
```pycon
>>> g = GenerativeImage(f1, f2)
>>> g.generate()
>>> g.plot(rotation=45)
```
* Default rotation is 0
### Range
```pycon
>>> g = GenerativeImage(f1, f2)
>>> g.generate(start=-2*math.pi, step=0.01, stop=0)
>>> g.plot()
>>> g.seed
234752
>>> plt.show()
```
### Color
```pycon
>>> g = GenerativeImage(f1, f2)
>>> g.generate()
>>> g.plot(color="yellow", bgcolor="black", projection=Projection.POLAR)
>>> g.seed
1018273
>>> plt.show()
```
* Supported colors are available in `VALID_COLORS` list
* `color` and `bgcolor` parameters supported formats:
1. Color name (example: `color="yellow"`)
2. RGB/RGBA (example: `color=(0.1,0.1,0.1)`, `color=(0.1,0.1,0.1,0.1)`)
3. Hex (example: `color="#eeefff"`)
4. Random (example: `color="random"`)
5. Complement (example: `color="complement", bgcolor="blue"`)
6. Transparent (example: `bgcolor="transparent"`)
7. List (example: `color=["black", "#fffeef",...]`)
⚠️ **Transparent** mode is only available for background
⚠️ **List** mode is only available for color
⚠️ In **List** mode, the length of this list must be equal to the lengths of data1 and data2
#### Point Color
You can make your custom color map and use it in Samila
```pycon
>>> colorarray = [
... [0.7, 0.2, 0.2, 1],
... [0.6, 0.3, 0.2, 1],
... "black",
... [0.4, 0.4, 0.3, 1],
... [0.3, 0.4, 0.4, 1],
... "#ff2561"]
>>> g.generate()
>>> g.seed
454893
>>> g.plot(cmap=colorarray, color=g.data2, projection=Projection.POLAR)
>>> plt.show()
```
### Regeneration
```pycon
>>> g = GenerativeImage(f1, f2)
>>> g.generate(seed=1018273)
>>> g.plot(projection=Projection.POLAR)
>>> plt.show()
```
### NFT.storage
Upload generated image directly to [NFT.storage](https://NFT.storage)
```pycon
>>> g.nft_storage(api_key="YOUR_API_KEY", timeout=5000)
{'status': True, 'message': 'FILE_LINK'}
```
You can also upload your config/data to nft storage as follows:
```pycon
>>> g.nft_storage(api_key="API_KEY", upload_config=True)
{'status': {'image': True, 'config':True}, 'message': {'image':'IMAGE_FILE_LINK', 'config':'CONFIG_FILE_LINK'}
```
or
```pycon
>>> g.nft_storage(api_key="API_KEY", upload_data=True)
{'status': {'image': True, 'data':True}, 'message': {'image':'IMAGE_FILE_LINK', 'data':'DATA_FILE_LINK'}
```
* Default timeout is **3000** seconds
### Save image
Save generated image
```pycon
>>> g.save_image(file_adr="test.png")
{'status': True, 'message': 'FILE_PATH'}
```
Save generated image in higher resolutions
```pycon
>>> g.save_image(file_adr="test.png", depth=5)
{'status': True, 'message': 'FILE_PATH'}
```
### Save data
Save generated image data
```pycon
>>> g.save_data(file_adr="data.json")
{'status': True, 'message': 'FILE_PATH'}
```
So you can load it into a `GenerativeImage` instance later by
```pycon
>>> g = GenerativeImage(data=open('data.json', 'r'))
```
Data structure:
```JSON
{
"plot": {
"projection": "polar",
"bgcolor": "black",
"color": "snow",
"spot_size": 0.01
},
"matplotlib_version": "3.0.3",
"data1": [
0.3886741692042526,
22.57390286376703,
-0.1646310981668766,
66.23632344600155
],
"data2": [
-0.14588750183600108,
20.197945942677833,
0.5485453260942901,
-589.3284610518896
]
}
```
### Save config
Save generated image config. It contains string formats of functions which is also human readable.
```pycon
>>> g.save_config(file_adr="config.json")
{'status': True, 'message': 'FILE_PATH'}
```
So you can load it into a `GenerativeImage` instance later by
```pycon
>>> g = GenerativeImage(config=open('config.json', 'r'))
```
Config structure:
```JSON
{
"matplotlib_version": "3.0.3",
"generate": {
"seed": 379184,
"stop": 3.141592653589793,
"step": 0.01,
"start": -3.141592653589793
},
"f2": "random.uniform(-1,1)*math.cos(x*(y**3))+random.uniform(-1,1)*math.ceil(y-x)",
"f1": "random.uniform(-1,1)*math.ceil(y)-random.uniform(-1,1)*y**2+random.uniform(-1,1)*abs(y-x)",
"plot": {
"color": "snow",
"bgcolor": "black",
"projection": "polar",
"spot_size": 0.01
}
}
```
## Mathematical details
Samila is simply a transformation between a square-shaped space from the Cartesian coordinate system to any arbitrary coordination like [Polar coordinate system](https://en.wikipedia.org/wiki/Polar_coordinate_system).
### Example
We have set of points in the first space (left square) which can be defined as follow:
And below functions are used for transformation:
```pycon
>>> def f1(x, y):
result = random.uniform(-1,1) * x**2 - math.sin(y**2) + abs(y-x)
return result
>>> def f2(x, y):
result = random.uniform(-1,1) * y**3 - math.cos(x**2) + 2*x
return result
```
here we use `Projection.POLAR` so later space will be the polar space and we have:
```pycon
>>> g = GenerativeImage(f1, f2)
>>> g.generate(seed=10)
>>> g.plot(projection=Projection.POLAR)
```
## Try Samila in your browser!
Samila can be used online in interactive Jupyter Notebooks via the Binder or Colab services! Try it out now! :
[](https://mybinder.org/v2/gh/sepandhaghighi/samila/master)
[](https://colab.research.google.com/github/sepandhaghighi/samila/blob/master)
* Check `examples` folder
## Issues & bug reports
Just fill an issue and describe it. We'll check it ASAP! or send an email to [info@samila.site](mailto:info@samila.site "info@samila.site").
- Please complete the issue template
You can also join our discord server
## Social media
1. [Instagram](https://www.instagram.com/samila_arts)
2. [Telegram](https://t.me/samila_arts)
3. [Twitter](https://twitter.com/samila_arts)
4. [Discord](https://discord.com/invite/94bz5QGZWb)
## References
1- Schönlieb, Carola-Bibiane, and Franz Schubert. "Random simulations for generative art construction–some examples." Journal of Mathematics and the Arts 7.1 (2013): 29-39.
2- Create Generative Art with R
3- NFT.storage : Free decentralized storage and bandwidth for NFTs
## Acknowledgments
This project was funded through the **Next Step Microgrant**, a program established by [Protocol Labs](https://protocol.ai/).
## Show your support
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