Monday, December 9, 2013

Data mountains and streams - stacked area plots in R

Below are two functions for producing stacked area plots. The first is the more typical approach where sequential series are stacked on top of another (function: plot.stacked), while the second approach is the more aesthetically-oriented version called a "stream plot" (function:, which alternates series on either side of a meandering baseline (see here for the motivation, and here for the inspiration). 

Arguments are similar for both functions regarding the input of x and y series and polygon attributes (fill color, border color, border line width). The stream plot also requires that the degree of meandering for the baseline be defined by the arguments frac.rand and spar; frac.rand, controls the meander amplitude (uniform random numbers added to baseline as a fraction of the total y range) and spar controls the amount of smoothing (as fit by the function smooth.spline).

The plot above colors the series with a color gradient of when the first appear in the series, while the plot below colors series by their maximum value. The order of the plotting of the series can also affect the the emphasis on the plot. By default, plotting order is sequential by column, although two ordering options are built-in to the functions: order by maximum value, and order by first appearance.

The plot.stacked function:

Thursday, December 5, 2013

New version of image.scale function

(Note: the most recent version, imageScale can be found in the sinkr package:

Below is an updated version of the image.scale function. In the old version, one had to constantly use additional arguments to suppress axes and their labels. The new version contains the additional arguments axis.pos (1, 2, 3, or 4) for defining the side of the axis, and add.axis (TRUE or FALSE), for defining whether the axis is plotted. Based on the position of the axis, the scale color levels are automatically drawn in a horizontal (axis.pos = 1[bottom] or 3[top]) or vertical (axis.pos = 2[left] or 4[right]) orientation. For the right plot above, the argument add.axis=FALSE so that additional control over axis ticks and labels could be added in an additional step with axis(). The function mtext() can be used to add additional labels to the scale.

The image.scale function: