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A high level Line Integral Convolution (LIC) library, including post-processing and visualization

Project description

lick

PyPI pre-commit.ci status

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, Clément Robert

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

Installation

Install with pip

pip install lick

To import lick:

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

import numpy as np
import matplotlib.pyplot as plt
from lick import lick_box_plot

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
lick_box_plot(
    fig,
    ax,
    x,
    y,
    v1,
    v2,
    field,
    size_interpolated=256,
    xmin=1,
    xmax=9,
    ymin=1,
    ymax=4,
    kernel=np.sin(np.linspace(0, np.pi, 64)),
    niter_lic=5,
    post_lic="north-west-light-source",
    cmap="inferno",
    stream_density=0.5,
)
plt.show()

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