Plot tag data time series

Plot time series in a single or multi-paneled figure. This is useful, for example, for comparing measurements across different sensors in an animaltag data object. The time axis is automatically displayed in seconds, minutes, hours, or days according to the span of the data.

plott(
  X,
  fsx = NULL,
  r = FALSE,
  offset = 0,
  date_time_axis = FALSE,
  recording_start = NULL,
  panel_heights = rep.int(1, length(X)),
  panel_labels = names(X),
  line_colors,
  interactive = FALSE,
  par_opts,
  ...
)

Arguments

X	List whose elements are either lists (containing data and metadata) or vectors/matrices of time series data. See details.
fsx	(Optional) A numeric vector whose length matches the number of sensor data streams (list elements) in X. (If shorter, fsx will be recycled to the appropriate length). fsx gives the sampling rate in Hz for each data object. Sampling rates are not needed when the data object(s) X are list(s) that contain sampling rate information -- and beware, because fsx (if given) will override sensor metadata.
r	(Optional) Logical. Should the direction of the y-axis be flipped? Default is FALSE. If r is of length one (or shorter than the number of sensor data streams in X) it will be recycled to match the number of sensor data streams. Reversed y-axes are useful, for example, for plotting dive profiles which match the physical situation (with greater depths lower in the display). If the name of a sensor list is "P" or contains the word "depth", it will automatically be reversed.
offset	(Optional) A vector of offsets, in seconds, between the start of each sensor data stream and the start of the first one. For example, if acceleration data collection started and then depth data collection commenced 436 seconds later, then the offset for the depth data would be 436.
date_time_axis	(Optional) Logical. Should the x-axis units be date-times rather than time-since-start-of-recording? Ignored if recording_start is not provided and X does not contain metadata on recording start time. Default is FALSE.
recording_start	(Optional) The start time of the tag recording as a POSIXct object. If provided, the time axis will show calendar date/times; if not, it will show days/hours/minutes/seconds (as appropriate) since time 0 = the start of recording. If a character string is provided it will be coerced to POSIXct with as.POSIXct.
panel_heights	(Optional) A vector of relative or absolute heights for the different panels (one entry for each sensor data stream in X). Default is equal-height panels. If panel_heights is a numeric vector, it is interpreted as relative panel heights. To specify absolute panel heights in centimeters using lcm (see help for layout).
panel_labels	(Optional) A list of y-axis labels for the panels. Defaults to names(X).
line_colors	(Optional) A list of colors for lines for multivariate data streams (for example, if a panel plots tri-axial acceleration, it will have three lines -- their line colors will be the first three in this list). May be specified in any specification R understands for colors. Defaults to c("#000000", "#009E73", "#9ad0f3", "#0072B2", "#e79f00", "#D55E00")
interactive	(Optional) Should an interactive figure (allowing zoom/pan/etc.) be produced? Default is FALSE. Interactive plotting requires the zoom package for its zm function.
par_opts	(Optional) A list of options to be passed to par before plotting. Default is mar=c(1,5,0,0), oma=c(2,0,2,1), las=1, lwd=1, cex=0.8.
...	Additional arguments to be passed to plot.

Value

A plot of time-series data

Details

If the input data X is an animaltag object, then all sensor variables in the object will be plotted. To plot only selected sensors from the animaltag object my_tag, for example, the input X=list(my_tag$A, my_tag$M) would plot just the accelerometer and magnetometer data. If possible, the plot will have

Note

This is a flexible plotting tool which can be used to display and explore sensor data with different sampling rates on a uniform time grid.

Examples

if (FALSE) {
HS <- harbor_seal
list <- list(depth = HS$P$data, A = HS$A$data)
plott(list, HS$P$sampling_rate, r = c(TRUE, FALSE))
}