mt_diffmap function

Creates a difference-heatmap of two trajectory heatmap images.

mt_diffmap creates a difference-heatmap of the trajectory data using gaussian smoothing. Note that this function has beta status.

mt_diffmap(
  x,
  y = NULL,
  condition = NULL,
  use = "trajectories",
  dimensions = c("xpos", "ypos"),
  use2 = "data",
  filename = NULL,
  bounds = NULL,
  xres = 500,
  upscale = 4,
  smooth_radius = 10,
  colors = c("#00863F", "#000000", "#FF1900"),
  n_shades = 1000,
  plot = TRUE,
  ...,
  verbose = TRUE
)

Arguments

• x: an object of class mousetrap), a trajectory object of class array, or an object of class mt_heatmap_raw (as created by mt_heatmap_raw ).
• y: an object of class mousetrap), a trajectory object of class array, or an object of class mt_heatmap_raw (as created by mt_heatmap_raw ). The class of y must match the class of x, unless y is NULL.
• condition: either a character value specifying which variable codes the two conditions (in x[[use2]]) that should be compared - or a vector matching the number of trajectories in x[[use]] that has exactly two levels. mt_diffmap will create a difference-heatmap comparing all trajectories between the two conditions. If condition is specified, y will be ignored (unless x and y are of class heatmap_raw).
• use: a character string specifying which trajectory data should be used.
• dimensions: a character vector specifying the trajectory variables used to create the heatmap. The first two entries are used as x and y-coordinates, the third, if provided, will be added as color information.
• use2: an optional character string specifying where the data that contain the condition variable can be found. Defaults to "data" as x[["data"]] usually contains all non mouse-tracking trial data.
• filename: a character string giving the name of the file. If NULL (the default), the R standard device is used for plotting. Otherwise, the plotting device is inferred from the file extension. Only supports devices tiff , png , pdf .
• bounds: numeric vector specifying the corners (xmin, ymin, xmax, ymax) of the plot region. By default (bounds = NULL), bounds are determined based on the data input.
• xres: an integer specifying the number of pixels along the x-dimension. An xres of 1000 implies an 1000*N px, where N is determined so that the trajectories aspect ratio is preserved (provided the bounds are unchanged).
• upscale: a numeric value by which the output resolution of the image is increased or decreased. Only applies if device is one of tiff, png, or pdf.
• smooth_radius: a numeric value specifying the standard deviation of the gaussian smoothing. If zero, smoothing is omitted.
• colors: a character vector specifying the colors used to color cases of image1 > image2, image1 ~ image2, image1 < image2, respectively. Note that the colors are used in that specific order. Defaults to c("#00863F", "#FFFFFF", "#FF1900") which specifies a green-black-red color gradient.
• n_shades: integer specifying the number of shades for the color gradient between the first and second, and the second and third color in colors.
• plot: logical specifying whether resulting image should be plotted (plot = TRUE, the default). If (plot = FALSE), an object of class mt_object_raw is returned.
• ...: arguments passed to mt_heatmap_raw .
• verbose: logical indicating whether function should report its progress.

Details

mt_diffmap takes two objects that either contain trajectory heatmaps or from which trajectory heatmaps can be computed. Difference-heatmaps are constructed analogously to mt_heatmap_raw .

Examples

## Not run:

mt_diffmap(
  KH2017, condition="Condition",
  xres=400, smooth_radius=6, n_shades=5
)
## End(Not run)

References

Wulff, D. U., Haslbeck, J. M. B., Kieslich, P. J., Henninger, F., & Schulte-Mecklenbeck, M. (2019). Mouse-tracking: Detecting types in movement trajectories. In M. Schulte-Mecklenbeck, A. Kühberger, & J. G. Johnson (Eds.), A Handbook of Process Tracing Methods (pp. 131-145). New York, NY: Routledge.

Kieslich, P. J., Henninger, F., Wulff, D. U., Haslbeck, J. M. B., & Schulte-Mecklenbeck, M. (2019). Mouse-tracking: A practical guide to implementation and analysis. In M. Schulte-Mecklenbeck, A. Kühberger, & J. G. Johnson (Eds.), A Handbook of Process Tracing Methods (pp. 111-130). New York, NY: Routledge.

See Also

mt_heatmap and mt_heatmap_ggplot for plotting trajectory heatmaps.

Author(s)

Dirk U. Wulff

Pascal J. Kieslich