Conveniently maps data values (numeric or factor/character) to colours according to a given colour vector or colour palette.

## Usage

```
pal_numeric(
palette,
domain,
na.color = "#808080",
alpha = FALSE,
reverse = FALSE
)
pal_bin(
palette,
domain,
bins = 7,
pretty = TRUE,
na.color = "#808080",
alpha = FALSE,
reverse = FALSE,
right = FALSE
)
pal_quantile(
palette,
domain,
n = 4,
probs = seq(0, 1, length.out = n + 1),
na.color = "#808080",
alpha = FALSE,
reverse = FALSE,
right = FALSE
)
pal_factor(
palette,
domain,
levels = NULL,
ordered = FALSE,
na.color = "#808080",
alpha = FALSE,
reverse = FALSE
)
```

## Arguments

- palette
An object of class

`palettes_colour`

or`palettes_colour`

.- domain
The possible values that can be mapped.

For

`pal_numeric`

and`pal_bin`

, this can be a simple numeric range (e.g.`c(0, 100)`

);`pal_quantile`

needs representative numeric data; and`pal_factor`

needs categorical data.If

`NULL`

, then whenever the resulting colour function is called, the`x`

value will represent the domain. This implies that if the function is invoked multiple times, the encoding between values and colours may not be consistent; if consistency is needed, you must provide a non-`NULL`

domain.- na.color
The colour to return for

`NA`

values. Note that`na.color = NA`

is valid.- alpha
Whether alpha channels should be respected or ignored. If

`TRUE`

then colors without explicit alpha information will be treated as fully opaque.- reverse
Whether the colours in

`palette`

should be used in reverse order. For example, if the default order of a palette goes from blue to green, then`reverse = TRUE`

will result in the colors going from green to blue.- bins
Either a numeric vector of two or more unique cut points or a single number (greater than or equal to 2) giving the number of intervals into which the domain values are to be cut.

- pretty
Whether to use the function

`pretty()`

to generate the bins when the argument`bins`

is a single number. When`pretty = TRUE`

, the actual number of bins may not be the number of bins you specified. When`pretty = FALSE`

,`seq()`

is used to generate the bins and the breaks may not be "pretty".- right
parameter supplied to

`base::cut()`

. See Details- n
Number of equal-size quantiles desired. For more precise control, use the

`probs`

argument instead.- probs
See

`stats::quantile()`

. If provided, the`n`

argument is ignored.- levels
An alternate way of specifying levels; if specified, domain is ignored

- ordered
If

`TRUE`

and`domain`

needs to be coerced to a factor, treat it as already in the correct order

## Value

A function that takes a single parameter `x`

; when called with a
vector of numbers (except for `pal_factor`

, which expects
factors/characters), #RRGGBB colour strings are returned (unless
`alpha = TRUE`

in which case #RRGGBBAA may also be possible).

## Details

`pal_numeric`

is a simple linear mapping from continuous numeric
data to an interpolated palette.

`pal_bin`

also maps continuous numeric data, but performs
binning based on value (see the `base::cut()`

function). `pal_bin`

defaults for the `cut`

function are `include.lowest = TRUE`

and
`right = FALSE`

.

`pal_quantile`

similarly bins numeric data, but via the
`stats::quantile()`

function.

`pal_factor`

maps factors to colours. If the palette is
discrete and has a different number of colours than the number of factors,
interpolation is used.

## Examples

```
pal <- pal_bin(met_palettes$Tam, domain = 0:100)
plot(as_colour(pal(sort(runif(16, 0, 100)))))
# Exponential distribution, mapped continuously
pal <- pal_numeric(met_palettes$Tam, domain = NULL)
plot(as_colour(pal(sort(rexp(16)))))
# Exponential distribution, mapped by interval
pal <- pal_bin(met_palettes$Tam, domain = NULL, bins = 4)
plot(as_colour(pal(sort(rexp(16)))))
# Exponential distribution, mapped by quantile
pal <- pal_quantile(met_palettes$Tam, domain = NULL)
plot(as_colour(pal(sort(rexp(16)))))
# Categorical data; by default, the values being coloured span the gamut...
pal <- pal_factor(met_palettes$Java, domain = NULL)
plot(as_colour(pal(LETTERS[1:5])))
# ...unless the data is a factor, without droplevels...
pal <- pal_factor(met_palettes$Java, domain = NULL)
plot(as_colour(pal(factor(LETTERS[1:5], levels = LETTERS))))
# ...or the domain is stated explicitly.
pal <- pal_factor(met_palettes$Java, domain = NULL, levels = LETTERS)
plot(as_colour(pal(LETTERS[1:5])))
```