lick

Package that uses a Line Integral Convolution library to clothe a 2D field (ex: density field) with a LIC texture, given two vector fields (ex: velocity (vx, vy))

https://github.com/la-niche/lick

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    1 of 4 committers (25.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.1%) to scientific vocabulary

Keywords from Contributors

mesh dynamics exoplanet pipeline-testing spacy-extension datacleaner data-profilers hydrology energy-system gtk
Last synced: 11 months ago · JSON representation

Repository

Package that uses a Line Integral Convolution library to clothe a 2D field (ex: density field) with a LIC texture, given two vector fields (ex: velocity (vx, vy))

Basic Info
  • Host: GitHub
  • Owner: la-niche
  • License: gpl-3.0
  • Language: Python
  • Default Branch: main
  • Size: 9.69 MB
Statistics
  • Stars: 4
  • Watchers: 2
  • Forks: 2
  • Open Issues: 1
  • Releases: 13
Created over 4 years ago · Last pushed 11 months ago
Metadata Files
Readme License Citation

README.md

lick

PyPI pre-commit.ci status Ruff

Line Integral Convolution Knit : clothe a 2D field (ex: density field) with a LIC texture, given two vector fields (ex: velocity (vx, vy)).

This package builds on top of rLIC, adding post-processing and visualization functionalities.

Authors: Gaylor Wafflard-Fernandez, Clment Robert

Author-email: gaylor.wafflard@univ-grenoble-alpes.fr

Installation

Install with pip

pip install lick

To import lick:

python import lick as lk

The important functions are lick_box and lick_box_plot. While lick_box interpolates the data and perform a line integral convolution, lick_box_plot directly plots the final image. Use lick_box if you want to have more control of the plots you want to do with the lic. Use lick_box_plot if you want to take advantage of the fine-tuning of the pcolormesh parameters.

Example

```python import numpy as np import matplotlib.pyplot as plt from lick import lickboxplot

fig, ax = plt.subplots() x = np.geomspace(0.1, 10, 128) y = np.geomspace(0.1, 5, 128) a, b = np.meshgrid(x, y) v1 = np.cos(a) v2 = np.sin(b) field = v1 ** 2 + v2 ** 2 lickboxplot( fig, ax, x, y, v1, v2, field, sizeinterpolated=256, xmin=1, xmax=9, ymin=1, ymax=4, niterlic=5, kernellength=64, cmap="inferno", streamdensity=0.5 ) plt.show() ```

Owner

  • Name: la niche
  • Login: la-niche
  • Kind: organization

GitHub Events

Total
  • Issues event: 1
  • Watch event: 1
  • Delete event: 4
  • Issue comment event: 1
  • Push event: 9
  • Pull request event: 20
  • Fork event: 1
  • Create event: 4
Last Year
  • Issues event: 1
  • Watch event: 1
  • Delete event: 4
  • Issue comment event: 1
  • Push event: 9
  • Pull request event: 20
  • Fork event: 1
  • Create event: 4

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 201
  • Total Committers: 4
  • Avg Commits per committer: 50.25
  • Development Distribution Score (DDS): 0.433
Past Year
  • Commits: 54
  • Committers: 3
  • Avg Commits per committer: 18.0
  • Development Distribution Score (DDS): 0.37
Top Committers
Name Email Commits
Clément Robert c****2@p****m 114
dependabot[bot] 4****] 52
Volodia99 g****d@u****r 27
pre-commit-ci[bot] 6****] 8
Committer Domains (Top 20 + Academic)

Dependencies

.github/workflows/cd.yml actions
  • actions/checkout v3 composite
  • actions/download-artifact v3 composite
  • actions/upload-artifact v3 composite
  • pypa/cibuildwheel v2.11.2 composite
  • pypa/gh-action-pypi-publish v1.5.1 composite
.github/workflows/ci.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • actions/upload-artifact v2 composite
.github/workflows/bleeding-edge.yaml actions
  • actions/checkout v4 composite
  • actions/setup-python v4 composite
pyproject.toml pypi
  • matplotlib >=3.4.0
  • numpy >=1.19.3,<2.0
  • packaging >=20.9
  • scikit-image >=0.18.1
  • scipy >=1.5.4
requirements/tests.txt pypi
  • pytest >=6.1 test
  • pytest-mpl >=0.16.1 test
requirements/typecheck.txt pypi
  • mypy ==1.5.1
setup.py pypi