Metadata-Version: 2.1
Name: distinctipy
Version: 1.0
Summary: A lightweight package for generating visually distinct colours.
Home-page: https://github.com/alan-turing-institute/distinctipy
Author: Jack Roberts
Author-email: jroberts@turing.ac.uk
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown

# distinctipy

*distinctipy* is a lightweight python package providing functions to generate
colours that are visually distinct from one another.

Commonly available qualitative colormaps provided by the likes of matplotlib
generally have no more than 20 colours, but for some applications it is useful
to have many more colours that are clearly different from one another.
*distinctipy* can generate lists of colours of any length, with each new colour
added to the list being as visually distinct from the pre-existing colours in
 the list as possible.

 ![36colours](https://raw.githubusercontent.com/alan-turing-institute/distinctipy/master/distinctipy/examples/36colours.png)

## Installation

*distinctipy* is designed for Python 3 and can be installed with pip by running:

```python
pip3 install distinctipy
```

Alternatively clone this repo and then in its parent directory run:
```bash
pip3 install -r requirements.txt
pip3 install .
```

## Usage and Examples

*distinctipy* can:
* Generate N visually distinct colours (`distinctipy.get_colors(N)`)
* Generate colours that are optimally distinct from a pre-existing list of colours (`distinctipy.get_colors(N, existing_colors)`)
* Generate pastel colours (`distinctipy.get_colors(N, pastel_factor=0.7)`)
* Select black or white as the best font colour for any background colour (`distinctipy.get_text_color(background_color)`)
* Convert lists of colours into matplotlib colormaps (`distinctipy.get_colormap(colors)`)
* Invert colours (`distinctipy.invert_colors(colors)`)
* Nicely display generated colours (`distinctipy.color_swatch(colors)`)
* Compare distinctipy colours to other common colormaps (`examples.plot_example()`)

For example, to create and then display N = 36 visually distinct colours:

```python
from distinctipy import distinctipy

# number of colours to generate
N = 36

# generate N visually distinct colours
colors = distinctipy.get_colors(N)

# display the colours
distinctipy.color_swatch(colors)
```

More detailed usage and example output can be found in the notebook **[examples.ipynb](https://github.com/alan-turing-institute/distinctipy/blob/master/examples.ipynb)**.

## References

*distinctipy* was heavily influenced and inspired by several web sources and
stack overflow answers. In particular:
* **Random generation of distinct colours:** [Andrew Dewes on GitHub](https://gist.github.com/adewes/5884820)
* **Colour distance metric:** [Thiadmer Riemersma at CompuPhase](https://www.compuphase.com/cmetric.htm)
* **Best text colour for background:** [Mark Ransom on Stack Overflow](https://stackoverflow.com/a/3943023)

Thanks!


