Auto Axis Tool

Description

Overlay base plot with a new axis and optional gridlines. The axis spacing can be manually specified or automatically generated, including for date and time axis. A default grid is drawn if called with just the side specified.

Usage

autoaxis(
  side,
  major = NA,
  major_grid = FALSE,
  minor = NA,
  minor_grid = FALSE,
  format = "auto",
  spacing = TRUE,
  tck = -0.03,
  ...
)

Arguments

Details

Major and minor tick marks can be specified in a number of ways:

• As a character string if the axis is datetime, such as 'year' or 'hour' which are passed as by to seq(). These can be prefixed with an integer multiplier, for example '6 hour' or '10 year', as per seq.POSIXt

• As a tick interval using the default spacing = TRUE

• As an approximate number of tick marks to include, using pretty() to find the best interval, using spacing = FALSE. Use a character number if this is a Date or Time axis, such as major = '100' and spacing will be set FALSE automatically.

Major adds labels and ticks, minor is just half-sized ticks marks. Both tick sizes can be changed (or direction changed) using tck.

Three different datetime axis are possible: year, day-offset, seconds-offset. Use format to specify how the label should appear, such as '%b %Y' (see ?strptime)

• Year should be treated as a conventional numeric axis, use major=1/12 not major='month'

• day-offset is an axis of class(x)=='Date' and is identified if the axis range exists within +/-9e4, meaning within dates 1723 - 2216, and minimum interval is 'day'

• second-offset is an axis of class(x)=='POSIXct' and is identified by a range outside of +/-9e4. This will give very strange results if your entire POSIXct axis is within 24 hours of 1970-01-01

A grid can be added at the same time by setting major_grid or minor_grid to TRUE or a colour string. If TRUE, a transparent black is used by default.

Any other options can be passed through to axis() directly (see ?axis), most notably las = 2 to rotate the labels, and cex.axis for label size.

The function will exit with a warning if more than 1000 ticks or gridlines were generated, as this is most likely a mistake with autogenerated date / time intervals and can lead to very slow behaviour.

This does NOT work well for barplot() categorical axis, for this continue to use the basic axis() function with custom labels, see examples.

Value

No return value (NULL)

Examples

plot(sunspots) # This time series is actually given in decimal years
  autoaxis(side=3, major=50, major_grid='coral', minor=10, minor_grid=TRUE, spacing=TRUE)
  autoaxis(side=4, major=11, minor=25, spacing=FALSE, las=2, cex.axis=0.5, tck=0.02)

plot(seq(as.POSIXct('2020-01-01'),as.POSIXct('2020-01-03'),length.out=1e3),
    rnorm(1e3), xlab='POSIXct', xaxt='n')
  autoaxis(side=1, major='day', minor='3 hour', format='%x')
  # Shortcut method to make a default dense grid
  autoaxis(side='3')
  autoaxis(side=2)
  # You can always request a datetime axis (side='4' not 4L) but it will be nonsense
  autoaxis(side='4', col='red')

plot(seq(as.Date('2013-02-01'),as.Date('2020-01-03'),length.out=1e3),
    rnorm(1e3), xlab='Date', xaxt='n')
  autoaxis(side=1, major='10', minor='50', format='%Y')
  autoaxis(side=3, minor='3 month', minor_grid=TRUE)

# Guessing is ambiguous with small values, depends on smallest interval
plot(1:500,runif(500), type='l', xaxt='n', xlab='Time or Date?', main=
  'For small values (<1e5), use interval to guess format\n')
autoaxis(1, major='min', minor='10 sec', format='%M:%S')
autoaxis(3, major='quarter', minor='month', format='%b %Y')

# For barplot() use base functions - remember to set width=1, space=0
# otherwise bars will not be plotted on integer x-coordinates
barplot(mtcars$mpg, width=1, space=0, ylab='mpg')
  # Adjust the x-axis down by 0.5 so that the tick is in centre of each bar
  axis(side=1, at=-0.5+1:length(mtcars$mpg), labels=rownames(mtcars), las=2 )
  # Often prettier, label each bar inside the bar itself using text()
  text(x=-1+1:length(mtcars$mpg), y=1, pos=4,
    labels=rownames(mtcars), srt=90, cex=0.7)
  # autoaxis can still be used for adjusting the numeric scale
  autoaxis(side=2, major=5, major_grid=TRUE, minor=1, minor_grid=TRUE)

Map Colours From Value

Description

Create a vector of colours and associated legend for easier base plots

Usage

autocol(
  x,
  set = "",
  alpha = NA,
  limits = NA,
  na_colour = NA,
  bias = 1,
  legend_len = 6
)

palette.misc

palette.viridis

palette.colorbrewer

Arguments

Format

An object of class list of length 1.

An object of class list of length 8.

An object of class list of length 35.

Details

Helper function for using colours in R's default plot() and legend(). Colours from built-in palettes are automatically scaled to return a vector of colours and create options('autolegend') which contains the correct legend mapping for autolegend().

A discrete palette is used for factor and character inputs whilst a continuous palette is used for integer and numeric.

Colour sets built-in so far are held in lists starting pals. and can be visualized most easily with pals_display(). The set argument can be any of the colour set names listed here (such as 'magma'), or from palette.pals(), or finally as a custom-defined vector, such as set = rainbow(5).

The current lists of palettes included with paletteknife all being with pal.

• pals.viridis

  All of the continuous palette forked from the viridisLite package maintained by Simon Garnier.

  • Contains: cividis inferno magma mako plasma rocket turbo viridis

• pals.rcolorbrewer

  All of the palettes included in RColorBrewer

  • Categorical: Accent Set1 Set2 Set3 Paired Pastel1 Pastel2 Dark2

  • Continuous: Greys Blues BuGn BuPu Greens GnBu PuBu Purples PuBuGn YlGnBu YlGn YlOrBr YlOrRd Oranges OrRd Reds RdPu PuRd

  • Divergent: Spectral RdYlBu RdYlGn BrBG RdBu RdGy PiYG PRGn PuOr

• pals.misc

  • Sasha Trubetskoy (2017): List of 20 Simple, Distinct Colors: sasha

Custom limits can be specified using c(0,10). This is useful if multiple plots using the same range are required for cross-comparison. Default behaviour (limits = NA) sets the range to exactly fit.

The skew of the colourscale can be adjusted with bias, for example if x has an exponential distribution, a bias value > 1 will bring out contrast at the low end.

Value

A character vector of colours of equal length to input x, sampled from the chosen set. This allows it to be used for plotting directly. Information for a legend (containing every level for categorical data, or approximately length legend_len for continuous) is stored in options('autolegend') and not returned explicitly.

Examples

plot(iris$Sepal.Length, iris$Petal.Length, cex=3, pch=16,
    col=autocol(iris$Petal.Width, set='PuBuGn', alpha=0.8, legend_len=12) )
  autolegend('topleft', title='Petal.Width', ncol=3)
  # Also try simplest "autolegend()" for click-to-draw

# Try scales which include NA in both colour and alpha channel
with(airquality, plot(Temp, col=autocol(x=Solar.R, set='YlOrRd', alpha=Ozone,
    na_colour='cyan'), pch=16, cex=sqrt(Wind) ))
  # Note inset=1 draws on opposite side ie above not below plot area
  autolegend('bottom', inset=1, bty='n', horiz=TRUE)


# Here we want a summary plot ordered by level, so need to create a colour vector to match
# 'Alphabet' is a built-in colour set, see "palette.pals()"
mixedbag = as.factor(sample(letters,1000,replace=TRUE))
  plot(x=mixedbag, y=rnorm(1000), col=autocol(levels(mixedbag), set='Alphabet'))
  autolegend('bottom', ncol=9, cex=0.7)

# Maintain the order of strings
barplot(1:8, col=autocol(LETTERS[8:1]))
  autolegend('topleft')

# Any unusual formats are coerced to numeric and the legend converted back
mydates = as.Date('2000-01-01')+0:100
  plot(mydates, pch=16, col=autocol(mydates, set=rainbow(10), bias=2) )
  autolegend(x=0, y=mydates[100], title='My Dates')

# Timeseries objects plot as a line, but can overlay with points()
plot(airmiles)
  points(airmiles, pch=15, col=autocol(airmiles, set='Reds'))

# Use the limits to clip or augment the colour-scale
layout(matrix(1:2))
  plot(runif(10), col=autocol(1:10, limits=c(0,20)), pch=16,
    main='Data split over two plots with same scale')
  plot(runif(10), col=autocol(c(100,20:12), limits=c(0,20)), pch=16)
  text(1, 0.5, pos=4, xpd=NA,
'This point has a
value of 100 but
clipped to max
colour == 20')
  autolegend('bottom', inset=1, horiz=TRUE) # Draws above!
  layout(1)

Add Auto-Generated Legend

Description

Add a legend for the last autocol() set generated

Usage

autolegend(...)

Arguments

Details

If no location (such as 'top', 'above', or an x,y coordinate) is given, then it calls the locator() crosshairs so the position of the legend can be picked interactively. All arguments are passed to legend(), see ?legend for a full list.

Positions 'above' and 'below' are allowed which shorthand for inset and horizontal (see example).

Legend labels and fill are generated by either autopal() or autocol() and stored in the global options('autolegend') where they can be manipulated if needs be.

See more examples in ?autocol for a plot() and autolegend() work flow.

Value

No return value (NULL)

Examples

# Simplest version: click-to-draw with locator()
plot(1:10, pch=16, col=autocol(1:10, 'Blues', legend_len=5))
# autolegend() # Try me! And click on plot to add legend

# Other neat versions -- note ?legend
autolegend('above', title='Above plot')
# Exactly equivalent to...
autolegend('bottom', inset=1, horiz=TRUE, bty='n')
autolegend(x=6, y=4, ncol=2, title='Draw at (6,4)')
autolegend('topleft', title='"topleft"', ncol=2, bty='n')

# Use pch (and optionally pt.cex) in legend -- these get recycled
autolegend('bottom', horiz=TRUE, pch=16, pt.cex=3, title='pch=16, pt.cex=3')
autolegend('right', pch=1:10, pt.cex=2, title='pch=1:10')

# Manipulate the legend text, for example with format(), this is a bit long-winded!
heatmap(as.matrix(eurodist), col=autopal('turbo', limits=range(eurodist)) )
current_legend = options('autolegend')[[1]]
options(autolegend = list(format(current_legend[[1]], big.mark=','), current_legend[[2]]))
autolegend('bottom', inset=1, horiz=TRUE, title='Misleading miles between cities')

# No helper exists yet for creating size or shape legends -- follow this idea...
with(airquality, plot(Temp, pch=16, cex=Solar.R/100, col=autocol(Ozone, set='Reds')))
cex_legend = pretty(airquality$Solar.R)
legend('bottom', pt.cex=cex_legend/100, legend=cex_legend, pch=1,
  horiz=TRUE, title='Solar.R', bty='n' )
autolegend('above', title='Ozone')

Auto-Palette

Description

Return a palette vector from one of the built-in sets

Usage

autopal(set = "", n = 30, limits = NA, bias = 1, legend_len = 6)

Arguments

Details

This can be used where a palette is provided rather than a mapped colour vector, for example image(). The limits must be specified for autolegend() information to be updated. Custom colour limits can be set using breaks or levels (see examples) if the same colour range is needed across several plots.

See ?autocol for list of all available colour sets.

Value

A character vector of colours of length n giving a continuous colour palette sampled from set. If limits are specified, information for a colour legend is produced of approximate length legend_len. This is stored in options('autolegend') and not returned explicitly.

Examples

image(volcano, col=autopal('RdYlGn', n=100, limits=c(50,200), bias=1.5),
    breaks=seq(50,200,length.out=101) )
  autolegend('bottom', inset=1, ncol=5)

# Or using the slightly smarter filled.contour
filled.contour(volcano, col=autopal('RdYlGn', n=20, limits=c(100,150)),
  levels=seq(50,200,length.out=21) )

Auto Zoom to Create a Dynamic Plot

Description

Replaces plot() with an interactive loop which allows user to click twice on the plot window to redraw with new limits. Press ESCAPE to finish.

Usage

autozoom(x, ..., after = NULL)

Arguments

Details

Click twice to set the new plot extents. If both clicks are on one of the axis (outside of the plot area) then only this axis is zoomed. Click twice on the same spot to reset the zoom to the entire plot.

Extras such as axes or legends are added using the after argument.

Examples

## Not run: 
autozoom(airmiles)

autozoom(faithful, cex=runif(272), after={autoaxis(3); autoaxis(4)})

autozoom(faithful, col=autocol(runif(272)), pch=16,
  after=autolegend('above') )

## End(Not run)

Built-in Paletteknife Palettes

Description

Plot a list of palettes for comparison

Usage

palette.display(palette = palette.colorbrewer)

Arguments

Value

No return value (NULL)

Examples

palette.display(c(palette.misc,palette.colorbrewer,palette.viridis))

palette.display(c(list(rainbow=rainbow(10), default=palette()),
               palette.misc, palette.colorbrewer[c('Paired','Set1','Set2')] ))

palette.display(list(rainbow=rainbow(45)[30:1], turbo=palette.viridis$turbo ))

# Call by vector of names - here it gets 'Paired' from palette.colorbrewer
palette.display(palette.pals() )

# Bit of fun ordering a list of palettes (MUST be same palette size)
mat_cols = do.call(rbind, lapply(palette.colorbrewer[9:26],
                          function(hex) as.vector(rgb2hsv(col2rgb(hex)))))
palette.display(palette.colorbrewer[9:26][hclust(dist(mat_cols))$order])