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FLAS allows to sort 2d grids based on similarity. This directory contains the python implementation and shows how to use it.
pip install vc_flas
git clone https://github.com/Visual-Computing/LAS_FLAS.git
cd LAS_FLAS/c_python
pip install . # or
pip install -e . # for develop/editable mode
Given that you have N features with D-dimensions, you can sort these features based on similarity with the following code:
import numpy as np
from vc_flas import Grid, flas
N, D = 241, 3
features = np.random.random((N, D))
grid = Grid.from_features(features)
arrangement = flas(grid, wrap=True, radius_decay=0.99)
sorted_features = arrangement.get_sorted_features()
height, width, dim = sorted_features.shape
assert (height, width, dim) == (16, 16, 3)
# show_image(sorted_features)
Often you need not only the features sorted, but other objects (like images for example) as well. See this example for more information on that.
There are more ways to initialize grids. See here for some examples.
Once you have sorted your features, there are some methods to evaluate the quality of the arrangements.
arrangement = flas(grid)
print(arrangement.get_distance_preservation_quality())
print(arrangement.get_mean_neighbor_distance())
print(arrangement.get_distance_ratio_to_optimum())
Kai Barthel, Nico Hezel, Klaus Jung, Bruno Schilling and Konstantin Schall
HTW Berlin, Visual Computing Group, Germany
This is an example implementation of the algorithms from the paper
Improved Evaluation and Generation of Grid Layouts using Distance Preservation Quality and Linear Assignment Sorting
Published in COMPUTER GRAPHICS Forum: (https://onlinelibrary.wiley.com/doi/full/10.1111/cgf.14718)
Reference to cite when you use any of the presented algorithms in a research paper:
@article{https://doi.org/10.1111/cgf.14718,
author = {Barthel, K. U. and Hezel, N. and Jung, K. and Schall, K.},
title = {Improved Evaluation and Generation Of Grid Layouts Using Distance Preservation Quality and Linear Assignment Sorting},
journal = {Computer Graphics Forum},
volume = {42},
number = {1},
pages = {261-276},
keywords = {interaction, user studies, visualization, information visualization, high dimensional sorting, assistive interfaces},
doi = {https://doi.org/10.1111/cgf.14718},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14718},
year = {2023}
}
FAQs
Python implementation of the Fast Linear Assigment Sorting Algorithm
We found that vc-flas demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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