GitHub - sepandhaghighi/samila: Generative Art Generator
Extracto
Generative Art Generator. Contribute to sepandhaghighi/samila development by creating an account on GitHub.
Contenido
Table of contents
- Overview
- Installation
- Usage
- Mathematical Details
- Try Samila in Your Browser
- Issues & Bug Reports
- Social Media
- Contribution
- References
- Acknowledgments
- Authors
- License
- Show Your Support
- Changelog
- Code of Conduct
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.
Installation
Source code
- Download Version 1.0 or Latest Source
- Run
pip install -r requirements.txtorpip3 install -r requirements.txt(Need root access) - Run
python3 setup.py installorpython setup.py install(Need root access)
PyPI
- Check Python Packaging User Guide
- Run
pip install samila==1.0orpip3 install samila==1.0(Need root access)
Easy install
- Run
easy_install --upgrade samila(Need root access)
Conda
- Check Conda Managing Package
conda install -c sepandhaghighi samila(Need root access)
Usage
Magic
>>> import matplotlib.pyplot as plt >>> from samila import GenerativeImage >>> g = GenerativeImage() >>> g.generate() >>> g.plot() >>> plt.show()
Basic
>>> 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
>>> 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,MOLLWEIDEandRANDOM - Default projection is
RECTILINEAR
Marker
>>> 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,HLINEandRANDOM - Default marker is
POINT
Range
>>> g = GenerativeImage(f1, f2) >>> g.generate(start=-2*math.pi, step=0.01, stop=0) >>> g.plot() >>> g.seed 234752 >>> plt.show()
Color
>>> 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_COLORSlist -
colorandbgcolorparameters supported formats:- Color name (example:
color="yellow") - RGB/RGBA (example:
color=(0.1,0.1,0.1),color=(0.1,0.1,0.1,0.1)) - Hex (example:
color="#eeefff") - Random (example:
color="random") - Complement (example:
color="complement", bgcolor="blue") - Transparent (example:
bgcolor="transparent") - List (example:
color=["black", "#fffeef",...])
- Color name (example:
Point Color
You can make your custom color map and use it in Samila
>>> 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
>>> g = GenerativeImage(f1, f2) >>> g.generate(seed=1018273) >>> g.plot(projection=Projection.POLAR) >>> plt.show()
NFT.storage
Upload generated image directly to NFT.storage
>>> g.nft_storage(api_key="YOUR_API_KEY") {'status': True, 'message': 'FILE_LINK'}
You can also upload your config/data to nft storage as follows:
>>> 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
>>> g.nft_storage(api_key="API_KEY", upload_data=True) {'status': {'image': True, 'data':True}, 'message': {'image':'IMAGE_FILE_LINK', 'data':'DATA_FILE_LINK'}
Save image
Save generated image
>>> g.save_image(file_adr="test.png") {'status': True, 'message': 'FILE_PATH'}
Save generated image in higher resolutions
>>> g.save_image(file_adr="test.png", depth=5) {'status': True, 'message': 'FILE_PATH'}
Save data
Save generated image data
>>> g.save_data(file_adr="data.json") {'status': True, 'message': 'FILE_PATH'}
So you can load it into a GenerativeImage instance later by
>>> g = GenerativeImage(data=open('data.json', 'r'))
Data structure:
{
"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.
>>> g.save_config(file_adr="config.json") {'status': True, 'message': 'FILE_PATH'}
So you can load it into a GenerativeImage instance later by
>>> g = GenerativeImage(config=open('config.json', 'r'))
Config structure:
{
"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.
Example
We have set of points in the first space (left square) which can be define as follow:
And bellow functions are used for transformation:
>>> 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 uses Projection.POLAR so later space will be the polar space and we have:
>>> 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! :
- Check
examplesfolder
Issues & bug reports
Just fill an issue and describe it. We'll check it ASAP! or send an email to info@samila.site.
- Please complete the issue template
You can also join our discord server
Social media
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.
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