https://github.com/dhaitz/mplcyberpunk

"Cyberpunk style" for matplotlib plots
https://github.com/dhaitz/mplcyberpunk

dataviz matplotlib plotting python visualization

Last synced: about 2 months ago
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"Cyberpunk style" for matplotlib plots

• Host: GitHub
• URL: https://github.com/dhaitz/mplcyberpunk
• Owner: dhaitz
• License: mit
• Created: 2020-03-29T17:22:58.000Z (over 4 years ago)
• Default Branch: main
• Last Pushed: 2024-01-30T08:15:26.000Z (8 months ago)
• Last Synced: 2024-07-09T08:43:27.216Z (2 months ago)
• Topics: dataviz, matplotlib, plotting, python, visualization
• Language: Python
• Homepage:
• Size: 2.87 MB
• Stars: 1,641
• Watchers: 17
• Forks: 68
• Open Issues: 13
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# mplcyberpunk

[![Latest PyPI version](https://img.shields.io/pypi/v/mplcyberpunk.svg)](https://pypi.python.org/pypi/mplcyberpunk)

[![Build Status](https://travis-ci.com/dhaitz/mplcyberpunk.svg?branch=master)](https://travis-ci.com/dhaitz/mplcyberpunk)

[![Python 3.9](https://img.shields.io/badge/python-3.11-blue.svg)](https://www.python.org/downloads/release/python-390/)

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).

## Requirements

Depends only on `matplotlib`.