Holly Kirk

Di Cook

Alicia Allan

Ross Gayler

Roger Peng

Elle Saber

The second rOpenSci [OzUnConf](https://ozunconf17.ropensci.org/) was
held in Melbourne Australia a few weeks ago. A diverse range of
[scientists, developers and general
good-eggs](/blog/2017/10/31/ozunconf2017/) came together to make some
R-magic happen and also learn a lot along the way. Before the conference
began, a huge stack of projects were suggested on the unconf [GitHub
repo](https://github.com/ropensci/ozunconf17/issues). For six
data-visualisation enthusiasts, one issue in particular caught their
eye, and the `ochRe` package was born.

![](/img/blog-images/2017-11-21-ochRe/AusElevationExamplePalettes.png)

The [`ochRe`](https://github.com/ropenscilabs/ochRe) package contains
colour palettes influenced by the Australian landscape, iconic
Australian artists and images. OchRe is originally the brain-child of
[Di Cook](https://twitter.com/visnut), who was inspired by Karthik Ram's
[`wesanderson`](https://github.com/karthik/wesanderson) package.

### Why "ochre"?

Naming our package was the "most important" task facing us after all
jumping on board the project. Fuelled by a selection of pastries we
opened the discussions, fully expecting this to take some time.
Fortunately, we all agreed on the name in less than 5 minutes, which
meant plenty of pastries were left for the serious business of package
building.

Ochre is naturally occuring, brownish-yellow
[pigment](https://en.wikipedia.org/wiki/Ochre) found in many parts of
Australia, so frequently in fact, that Australia is sometimes referred
to as the "land of ochre soil". Additionally, ochre pigment has been
used for thousands of years by Aboriginal people in Australia, with many
culturally important uses from artwork to the preservation of animal
skins.

### Building ochRe

We started our package building journey by each picking an iconic
Australian artwork (this took longer than you might think). Once we had
selected our images, we used the online [Image Color Extract
PHP](https://www.coolphptools.com/color_extract) demo tool to extract
the hex code for the main colours within each image. Some images
required a more selective approach, so where needed the colour code
extraction was done using the eyedropper tool (in macOS) or the Google
Chrome colourPick extension.

Once we were happy with the colours, codes and order for each palette we
loaded this information into `ochRe` as lists of hex codes associated
with the palette name. We adopted `scales` to improve the fucntionality
of the packages when using `ggplot`, in particular to allow manipulation
of colour ramping and transparency. The package also contains a few
simple functions for displaying the different palettes.

Below are some examples of original art work and their associated
palettes:

`namatjira_qual` and `namatjira_div` are both inspired by the
watercolour painting ["Twin
Ghosts"](https://www.menziesartbrands.com/items/twin-ghosts), by
Aboriginal artist Albert Namatjira. `namatjira_div` is ordered for
plotting divergent datasets.

![](/img/blog-images/2017-11-21-ochRe/TwinGhosts_AlbertNamatjira.jpg)![](/img/blog-images/2017-11-21-ochRe/namatjira_qual.png)

The `nolan_ned` palette is inspired by the famous paintings of the
outlaw [Ned Kelly](https://cs.nga.gov.au/detail.cfm?irn=28926) by Sidney
Nolan.

![](/img/blog-images/2017-11-21-ochRe/nedKelly_sidneyNolan.jpg)![](/img/blog-images/2017-11-21-ochRe/nolan_ned.png)

`olsen_seq` has been designed for plotting sequential data, such as a
heat map or landscape layers. The colours come from the abstract piece
["Sydney Sun"](https://artsearch.nga.gov.au/Detail-LRG.cfm?IRN=26102),
1965, by John Olsen.

![](/img/blog-images/2017-11-21-ochRe/sydneySun_johnOlsen.jpg)![](/img/blog-images/2017-11-21-ochRe/olsen_seq.png)

There was a high proportion of ecologists at the \#ozunconf, which
inspired the somewhat pessimistic `healthy_reef` and `dead_reef`
palettes, with the colours taken from recent underwater photgraphs of
the Great Barrier Reef.

### Introducing: `ochRe`

Our package currently contains 16 colour palettes, each one inspired by
either an Australian landscape, an artwork or image by an Australian
artist, or an Australian animal. Some of the palettes are more suited to
displaying continuous data (such as in the Australian elevation maps
above). Other palettes will perform best plotting discrete data (as in
the `parliament` example below).

`ochRe` can be currently be installed from GitHub:

::: {.highlight}
``` {.chroma tabindex="0"}
# You need to install the 'devtools' package firstdevtools::install_github("ropenscilabs/ochRe")
```
:::

You can visualise all 16 palettes using the following code snippet:

::: {.highlight}
``` {.chroma tabindex="0"}
pal_names <- names(ochre_palettes)par(mfrow=c(length(ochre_palettes)/2, 2), lheight = 2, mar=rep(1, 4), adj = 0)for (i in 1:length(ochre_palettes)){    viz_palette(ochre_palettes[[i]], pal_names[i])}
```
:::

![](/img/blog-images/2017-11-21-ochRe/ochrePalettes.png)

Here are some worked examples, showing how to use the palettes for
different types of data visualisation, including both `ggplot` and base
plotting in R.

An example using base R and the `winmar` palette, this is based on an
iconic photograph by Wayne Ludbey, "Nicky Winmar St Kilda Footballer",
1993. In the photo, Aboriginal AFL player Nicky Winmar is baring his
skin in response to racial abuse during an AFL game.

::: {.highlight}
``` {.chroma tabindex="0"}
## basic example codepal <- colorRampPalette(ochre_palettes[["winmar"]])image(volcano, col = pal(20))
```
:::

![](/img/blog-images/2017-11-21-ochRe/VolcanoWithWinmar.png)

Paired scatter plot using the `emu_Woman_paired` palette, inspired by
"Emu Woman", 1988-89, by Emily Kame Kngwarreye.

::: {.highlight}
``` {.chroma tabindex="0"}
library(tidyverse)library(ochRe)library(naniar)# Exploring missing values benefits from a paired palette, like the emu women# Here missing status on air temperature is shown in a plot of the two wind variablesdata(oceanbuoys)oceanbuoys <- oceanbuoys %>% add_shadow(humidity, air_temp_c) ggplot(oceanbuoys, aes(x=wind_ew, y=wind_ns, colour=air_temp_c_NA)) +     geom_point(alpha=0.8) +     scale_colour_ochre(palette="emu_woman_paired") +    theme_bw() + theme(aspect.ratio=1)# Slightly more complicated, forcing the pairsclrs <- ochre_palettes$emu_woman_paired[11:12]ggplot(oceanbuoys, aes(x=wind_ew, y=wind_ns, colour=air_temp_c_NA)) +     geom_point(alpha=0.8) +     scale_colour_manual(values=clrs) +    theme_bw() + theme(aspect.ratio=1)
```
:::

![](/img/blog-images/2017-11-21-ochRe/Ochre_Example1.png)

A map of the Australian electoral boundaries, using the `galah` palette.
[Galahs](https://en.wikipedia.org/wiki/Galah) are a common species of
cockatoo found throughout mainland Australia.

::: {.highlight}
``` {.chroma tabindex="0"}
# Map of the 2016 Australian electoral boundaries# with the galah palettelibrary(eechidna)library(ggthemes)data(nat_map_2016)data(nat_data_2016)ggplot(aes(map_id=id), data=nat_data_2016) +    geom_map(aes(fill=Area_SqKm), map=nat_map_2016) +    expand_limits(x=nat_map$long, y=nat_map$lat) +     scale_fill_ochre(palette="galah", discrete=FALSE) +    theme_map()
```
:::

![](/img/blog-images/2017-11-21-ochRe/Ochre_Example2.png)

Results of the 2016 Australian election to the senate, coloured by
political party using the `parliament` palette. The colours for this
palette were taken from the
[tapestry](https://www.aph.gov.au/~/media/06%20Visit%20Parliament/66%20Parl%20House%20Art%20Collection/661%20five%20treasures/five%20treasures%20detail%20pics/M19840057UntitledBOYDunframed.png?la=en)
by Arthur Boyd found in the Great Hall of Parliament House.

::: {.highlight}
``` {.chroma tabindex="0"}
# Election resultssenate <- read_csv("http://results.aec.gov.au/20499/Website/Downloads/SenateSenatorsElectedDownload-20499.csv",                    skip = 1)coalition <- c("Country Liberals (NT)", "Liberal", "Liberal National Party of Queensland",                "The Nationals")labor <- c("Australian Labor Party", "Australian Labor Party (Northern Territory) Branch",            "Labor")greens <- c("The Greens", "Australian Greens", "The Greens (WA)")senate <- senate %>% mutate(PartyNm = ifelse(as.character(PartyNm) %in% coalition,                                              "Liberal National Coalition", PartyNm))senate <- senate %>% mutate(PartyNm = ifelse(as.character(PartyNm) %in% labor,                                              "Australian Labor Party", PartyNm))senate <- senate %>% mutate(PartyNm = ifelse(as.character(PartyNm) %in% greens,                                              "Australian Greens", PartyNm))senate$PartyNm <- factor(senate$PartyNm,                          levels = names(sort(table(senate$PartyNm),                             decreasing = T)))ggplot(data = senate, aes(x = PartyNm, fill = PartyNm)) +     geom_bar() + xlab("") +     ylab("") + scale_fill_ochre(palette="parliament") + coord_flip() +     theme_bw() + theme(legend.position = "None") 
```
:::

![](/img/blog-images/2017-11-21-ochRe/Ochre_Example3.png)

For more information about the individual palettes available in `ochRe`
visit our
[vignette](https://github.com/ropenscilabs/ochRe/tree/master/vignettes)

All of the `ochRe` team had a great time at \#ozunconf, Thank you to the
organisers for a brilliant event. Special Thanks to [Michael
Sumner](https://github.com/mdsumner) for providing code to access the
Australian elevation map you see at the start of this post.


The second rOpenSci OzUnConf was held in Melbourne Australia a few weeks ago. A diverse range of scientists, developers and general good-eggs came together to make some R-magic happen and also learn a lot along the way. Before the conference began, a huge stack of projects were suggested on the unconf  GitHub repo. For six data-visualisation enthusiasts, one issue in particular caught their eye, and the ochRe package was born.

Publicaciones de Rogue Scholar

ochRe - Australia themed colour palettes