Metadata-Version: 2.4
Name: lick
Version: 0.7.0
Summary: A high level Line Integral Convolution (LIC) library, including post-processing and visualization
Author: G. Wafflard-Fernandez, C.M.T. Robert
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-Expression: GPL-3.0-only
Classifier: Programming Language :: Python :: 3
Classifier: Typing :: Typed
License-File: LICENSE
Requires-Dist: matplotlib>=3.4.0
Requires-Dist: numpy>=1.21.0, <3
Requires-Dist: rlic>=0.2.1
Requires-Dist: scipy>=1.5.4
Project-URL: Homepage, https://github.com/volodia99/lick

# lick
[![PyPI](https://img.shields.io/pypi/v/lick.svg?logo=pypi&logoColor=white&label=PyPI)](https://pypi.org/project/lick/)
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Line Integral Convolution Knit : 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)).

Authors: Gaylor Wafflard-Fernandez, Clément Robert

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

<p align="center">
    <img src="https://raw.githubusercontent.com/volodia99/lick/main/imgs/lick.png" width="800"></a>
</p>

## 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 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,
    niter_lic=5,
    kernel_length=64,
    cmap="inferno",
    stream_density=0.5
)
plt.show()
```

