mousetrap (version 1.0.0)

mt_plot: Plot trajectory data.

Description

mt_plot can be used for plotting a number of individual trajectories. mt_plot_aggregate can be used for plotting aggregated trajectories. The color and linetype can be varied depending on a set of condition variables using the color and linetype arguments. If the x and y arguments are varied, this function can also be used for plotting velocity and acceleration profiles.

Usage

mt_plot(data, use = "trajectories", use2 = "data", x = "xpos",
  y = "ypos", color = NULL, linetype = NULL, only_ggplot = FALSE, ...)

mt_plot_aggregate(data, use = "trajectories", use2 = "data", x = "xpos",
  y = "ypos", color = NULL, linetype = NULL, only_ggplot = FALSE,
  subject_id = NULL, ...)

Arguments

data

a mousetrap data object created using one of the mt_import functions (e.g., mt_import_mousetrap).

use

a character string specifying which trajectories should be plotted. The corresponding trajectories are selected from data using data[[use]]. Usually, this value corresponds to either "trajectories", "tn_trajectories" or "av_trajectories

use2

a character string specifying where the data that contain the variables used for determining the color and linetype can be found (in case these arguments are specified). Defaults to "data" as data[["data"]] usu

x

a character string specifying which dimension in the trajectory array should be displayed on the x-axis (defaults to xpos).

y

a character string specifying which dimension in the trajectory array should be displayed on the y-axis (defaults to ypos).

color

an optional character string specifying which variable in data[[use2]] should be used for coloring the trajectories.

linetype

an optional character string specifying which variable in data[[use2]] should be used for varying the linetype of the trajectories.

only_ggplot

logical. If TRUE, only the ggplot object is returned. If FALSE(the default), the trajectories are plotted using geom_path.

...

additional arguments passed on to mt_reshape (such as subset).

subject_id

a character string specifying which column contains the subject identifier. Only relevant for mt_plot_aggregate. If specified, aggregation will be performed within subjects first. Note that aggregation will be performed separately for e

Functions

• mt_plot: Plot individual trajectory data
• mt_plot_aggregate: Plot aggregated trajectory data

Details

mt_plot internally uses mt_reshape for reshaping trajectories into a long format. Next, it creates a ggplot object using the ggplot function of the ggplot2 package. The aes mappings are taken from the function arguments for x, y etc.; in addition, the group mapping is set to mt_id. If return_ggplot=FALSE, the trajectories are plotted using the geom_path function of the ggplot2 package. mt_plot_aggregate works similarly, but uses mt_aggregate for reshaping and aggregating trajectories prior to plotting. Please note that this function is intended as a quick and easy solution for visualizing mouse trajectories. For additional flexibility, we recommend that mt_reshape or mt_aggregate be used in conjunction with ggplot to create custom visualizations.

See Also

mt_plot_add_rect for adding rectangles representing the response buttons to the plot. mt_plot_riverbed for plotting the relative frequency of a selected variable across time. mt_plot_per_trajectory for individually plotting all trajectories as individual pdf files.

Examples

# Load ggplot2
library(ggplot2)

# Time-normalize trajectories
mt_example <- mt_time_normalize(mt_example)
  
# Plot all time-normalized trajectories
# varying the color depending on the condition
mt_plot(mt_example, use="tn_trajectories",
  x="xpos", y="ypos", color="Condition")
        
# ... with custom colors
mt_plot(mt_example, use="tn_trajectories",
  x="xpos", y="ypos", color="Condition") +
  scale_color_brewer(type="qual")
   
# Plot aggregated time-normalized trajectories per condition
mt_plot_aggregate(mt_example, use="tn_trajectories",
  x="xpos", y="ypos", color="Condition")
                  
# ... first aggregating trajectories within subjects
mt_plot_aggregate(mt_example, use="tn_trajectories",
  x="xpos", y="ypos", color="Condition",
  subject_id="subject_nr")
        
# ... adding points for each position to the plot
mt_plot_aggregate(mt_example, use="tn_trajectories",
  x="xpos", y="ypos", color="Condition")+
  geom_point()                   
        
# Plot velocity profiles based on the averaged trajectories
# varying the color depending on the condition
mt_example <- mt_calculate_derivatives(mt_example)
mt_example <- mt_average(mt_example, interval_size = 100)
mt_plot(mt_example, use="av_trajectories",
  x="timestamps", y="vel", color="Condition")