semvec/pypi-packages huggingface dataset:
mplcyberpunk 0.7.6
Add-on for Matplotlib to produce 'Cyberpunk' style plots
License: MIT License
Requires Python: >=3.9

# mplcyberpunk


[![Latest PyPI version](https://img.shields.io/pypi/v/mplcyberpunk.svg)](https://pypi.python.org/pypi/mplcyberpunk)
![example workflow](https://github.com/dhaitz/mplcyberpunk/actions/workflows/test-deploy.yml/badge.svg)
![Python 3.12](https://img.shields.io/badge/python-3.12-blue.svg)


A Python package on top of `matplotlib` to create 'cyberpunk' style plots with 3 additional lines of code.

![](img/demo.png)

## Installation

    pip install mplcyberpunk

## Usage

After importing the package, the _cyberpunk_ stylesheet (dark background etc.) is available via `plt.style.use`.
The line glow and 'underglow' effects are added via calling `add_glow_effects`:

```python
import matplotlib.pyplot as plt
import mplcyberpunk

plt.style.use("cyberpunk")

plt.plot([1, 3, 9, 5, 2, 1, 1], marker='o')
plt.plot([4, 5, 5, 7, 9, 8, 6], marker='o')

mplcyberpunk.add_glow_effects()

plt.show()
```

Result:

![](img/demo.png)

This effect is currently only implemented for lines.

The individual steps are described [here](https://matplotlib.org/matplotblog/posts/matplotlib-cyberpunk-style/) in more detail.


#### Add effects individually

Instead of `add_glow_effects`, you can add the line glow and underglow effects separately:

    mplcyberpunk.make_lines_glow()
    mplcyberpunk.add_underglow()


You can also add the effect to a specific axis object explicitly:

    fig, ax = plt.subplots()
    ...
    mplcyberpunk.make_lines_glow(ax)

![](img/sin.png)


To activate the glow effect only for specific lines, pass a Line2D object or a list of Line2Ds to `make_lines_glow`.


#### Gradient glow

Gradient underglow effect can be added with

    mplcyberpunk.add_glow_effects(gradient_fill=True)

or independently of line glow with

    mplcyberpunk.add_gradient_fill(alpha_gradientglow=0.5)

`add_gradient_fill` takes a `gradient_start` argument for different gradient starting values:

 ![gradient_start](img/gradient_start.png)


#### Different glow configurations:
![underglows](img/underglows.png)


#### Scatter plots

Glow effect can be added to scatter plots via `mplcyberpunk.make_scatter_glow()`:

![](img/scatter.png)

#### Colormap

The default colormap is `cool`:

![colormap](img/colormap.png)

Others:


![colormaps](img/colormaps.png)


#### Bar charts

```python
import matplotlib.pyplot as plt
import mplcyberpunk

plt.style.use('cyberpunk')

categories = ['A', 'B', 'C', 'D', 'E']
values = [25, 67, 19, 45, 10]
colors = ["C0", "C1", "C2", "C3", "C4"]

bars = plt.bar(categories, values, color=colors, zorder=2)

mplcyberpunk.add_bar_gradient(bars=bars)

plt.show()
```

![colormap](img/gradient_bars.png)



## Gallery
![europe](img/europe.png)
![world](img/world.png)

![gradient-fill_1](img/gradient-fill_1.png)
![gradient-fill_2](img/gradient-fill_2.png)


Some images can be bought as posters [here](https://displate.com/sr-artworks/dhaitz).