https://github.com/csaybar/pal

a palette search engine :fire:
https://github.com/csaybar/pal

Last synced: about 1 month ago
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a palette search engine :fire:

• Host: GitHub
• URL: https://github.com/csaybar/pal
• Owner: csaybar
• License: mit
• Created: 2018-12-10T21:14:26.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2019-01-15T02:25:49.000Z (almost 6 years ago)
• Last Synced: 2024-10-12T19:10:57.853Z (3 months ago)
• Language: R
• Homepage:
• Size: 386 KB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • Changelog: NEWS.md
  • License: LICENSE.md

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README

        
---

output: github_document

---

```{r setup, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/"

)

```

# pal 

[pal](https://github.com/csaybar/pal) is a color palette search engine that will find your ideal color palette by making [cpt-city](http://soliton.vm.bytemark.co.uk/pub/cpt-city/index.html), [hex-color](https://www.color-hex.com/color-palettes/), and [paletteer](https://github.com/EmilHvitfeldt/paletteer) more accessible to realize queries. There are more than 80 000 > palettes waiting to be used!.

## Installation

```r

#You can install the released version of pal:

install.packages("pal")

#or the development version from Github:

#instal.packages("devtools")

devtools::install_github('csaybar/pal')

```

## Usage

`pal` has been designed to be the most intuitive as possible. You can access to any color palette using `pal_search` and `pal_get`.

`pal_search` initializes a S3 object that stores the databases and globals params (See [pal_search](https://www.google.com/)). Additionally, its have four methods:

*  `pal_n`: filter by color palette complexity.

* `pal_colors`: filter considering the distance (in CIELAB color space) to preferable colors.

* `pal_tags`: filter using the label attached to each palette color.

* `plot`: display the multiple palette options in a plot.

```r

# 

pal_search(return = 15, catalogs = c('cpt-city')) +

  pal_colors(blue,yellow) +

  pal_tags(precipitation,rainfall) +

  pal_plot()

```

Once you have decided what your palette is. It is time for pal_get!.

```r

mypal <- pal_get(id = 'cpt0441',

                 n = 10,

                 reverse = TRUE,

                 interpolate = 'spline')

pal_plot(mypal)     

```