https://github.com/benmaier/cividis

Register `cividis` with matplotlib, a color map optimized for color vision deficiency, as published in Nuñez, et al. (2018), PLoS ONE 13(7): e0199239 .
https://github.com/benmaier/cividis

cividis colormap cvd matplotlib

Last synced: about 1 month ago
JSON representation

Register `cividis` with matplotlib, a color map optimized for color vision deficiency, as published in Nuñez, et al. (2018), PLoS ONE 13(7): e0199239 .

• Host: GitHub
• URL: https://github.com/benmaier/cividis
• Owner: benmaier
• License: other
• Created: 2018-08-20T09:04:42.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-08-20T13:20:00.000Z (over 6 years ago)
• Last Synced: 2024-10-11T11:06:41.391Z (3 months ago)
• Topics: cividis, colormap, cvd, matplotlib
• Language: Python
• Size: 71.3 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# cividis

Register the color map _cividis_ for matplotlib, as described in

[Nuñez JR, Anderton CR, Renslow RS (2018) Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data. PLoS ONE 13(7): e0199239](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0199239).

## Install

    pip install cividis

## Usage

After installation, just import `cividis` once and it's registered and usable

```python

import cividis

```

Afterwards, you can use it like any other color map.

```python

import matplotlib.pyplot as pl

import numpy as np

x = np.arange(0, 2*np.pi, 0.07)

y = np.arange(0, 2*np.pi, 0.07)

X, Y = np.meshgrid(x,y)

Z = np.cos(X) * np.sin(Y) * 20

Z += np.random.randn(*Z.shape)

pl.figure(figsize=(4,3.375))

pl.imshow(Z,cmap='cividis')

pl.colorbar()

pl.gcf().savefig('xmpl.png',dpi=150)

pl.show()

```

![](https://github.com/benmaier/cividis/raw/master/sandbox/xmpl.png "")

## More examples

### Register cividis as default

This has to be done once in your `matplotlibrc` file, or you call the corresponding function from the package.

```python

import cividis

cividis.make_default()

 ...

pl.imshow(Z)

```

Will give equal results to the above.

### Get an array of N cividis colors

```python

import cividis

color_list = cividis.get_colors(10,n_start=2,n_end=200)

```

Where the function is implemented as

```python

def get_colors(N, n_start=0, n_end=255):

    """Get a color array of `N` entries, where the `N` entries

    are taken at equidistance from the `cividis` array between

    `n_start` and `n_end`"""

    indices = np.linspace(n_start, n_end, N)

    indices = np.array(indices, dtype=int)

    return cividis[indices]

```