Color telemetry objects by time
These functions facilitate the coloring of tracks by annotating tracking data with time/location specific information and computing color arguments for plot.
annotate(object,by="all",cores=1,...) color(object,by="time",col.fn=NULL,alpha=1,dt=NULL,cores=1,...)
object |
A |
by |
What to |
col.fn |
Optional coloring function that can take a [0,1] interval and alpha channel argument. |
alpha |
Base alpha channel value. |
dt |
Sampling interval specification for making oversampled times more transparent. If |
cores |
Number of annotations or overlap calculations to peform in parallel. |
... |
Additional arguments. |
Annotated telemetry objects are required for color by arguments "sun", "moon", "season", or "tropic".
by="time" colors tracking data with a gradient that increases in time.
by="sun" colors according to the sine of the sun's altitude, which is proportional to solar flux during daylight hours.
by="moon" colors according to the illuminated fraction of the moon.
by="season" colors according to the length of the day, and therefore corresponds to the local season.
by="tropic" currently colors according to the calender day, but will eventually be upgraded to tropical-year cycle.
by="individual" assigns colors to minimize the maximum combined spatial and color overlap.
Finding the best color assignment is an NP-hard problem that is here approximated in O(N^3) time with a custom greedy algorithm.
Other named columns in the telemetry object can also be used with color, by specifying the column name with by.
annotate returns an annotated telemetry object with extra columns to facilitate coloring.
color returns a valid col argument for {plot.telemetry}.
C. H. Fleming.
# Load package and data library(ctmm) data(buffalo) # assign distinct colors to buffalo COL <- color(buffalo,by='individual') # Notice the separation into RGB and CMY for maximum contrast plot(buffalo,col=COL) # annotate buffalo with sunlight data and compute colors buffalo <- annotate(buffalo,cores=2) # CRAN policy limits to 2 cores COL <- color(buffalo,by='sun') # use North-preserving projection and plot projection(buffalo) <- median(buffalo) plot(buffalo,col=COL)
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