frames_graph creates a list of ggplot2 graphs displaying movement-environment interaction. Each object represents a single frame. Each frame can be viewed or modified individually. The returned list of frames can be animated using animate_frames.

frames_graph(m, r_list, r_times, r_type = "gradient",
  fade_raster = FALSE, return_data = FALSE, graph_type = "flow",
  path_size = 1, path_legend = TRUE, path_legend_title = "Names",
  val_min = NULL, val_max = NULL, val_by = 0.1, verbose = T)

Arguments

m

move or moveStack of uniform time scale and time lag, e.g. prepared with align_move (recommended). May contain a column named colour to control path colours (see details).

r_list

list of raster or rasterStack. Each list element referrs to the times given in r_times. Use single-layer raster objects for gradient or discrete data (see r_type). Use a rasterStack containing three bands for RGB imagery (in the order red, green, blue).

r_times

list of POSIXct times. Each list element represents the time of the corresponding element in r_list. Must be of same length as r_list.

r_type

character, either "gardient" or "discrete". Ignored, if r_list contains rasterStacks of three bands, which are treated as RGB.

fade_raster

logical, if TRUE, r_list is interpolated over time based on r_times. If FALSE, r_list elements are assigned to those frames closest to the equivalent times in r_times.

return_data

logical, if TRUE, instead of a list of frames, a data.frame containing the values extracted from r_list per individual, location and time is returned. This data.frame can be used to create your own multi- or monotemporal ggplot2 movement-environemnt interaction graphs.

graph_type

character, defines the type of multi-temporal graph that should be drawn as frames. Currently supported graphs are:

  • "flow", a time flow graph with frame time on the x axis and values of the visited cell at x on the y axis per individual track

  • "hist", a cumulative histogram with cell values on the x axis and time-cumulative counts of visits on the y axis per individual track.

path_size

numeric, size of each path.

path_legend

logical, wether to add a path legend from m or not. Legend tracks and colours will be ordered by the tracks' temporal apperances, not by their order in m.

path_legend_title

character, path legend title. Default is "Names".

val_min

numeric, minimum value of the value axis. If undefined, the minimum is collected automatically.

val_max

numeric, maximum value of the value axis. If undefined, the maximum is collected automatically.

val_by

numeric, increment of the value axis sequence. Default is 0.1. If graph_type = "discrete", this value should be an integer of 1 or greater.

verbose

logical, if TRUE, messages on the function's progress are displayed (default).

Value

List of ggplot2 objects, each representing a single frame. If return_data is TRUE, a data.frame is returned (see return_data).

Details

To later on side-by-side join spatial frames created using frames_spatial with frames created with frames_graph for animation, equal inputs must have been used for both function calls for each of the arguments m, r_list, r_times and fade_raster.

See also

Examples

# NOT RUN {
library(moveVis)
library(move)
library(ggplot2)

data("move_data", "basemap_data")
# align movement
m <- align_move(move_data, res = 4, unit = "mins")

# create spatial frames with frames_spatial:
r_list <- basemap_data[[1]]
r_times <- basemap_data[[2]]

frames.sp <- frames_spatial(m, r_list = r_list, r_times = r_times, r_type = "gradient",
                            fade_raster = TRUE)

# use the same inputs to create a non-spatial graph, e.g. a flow graph:
frames.gr <- frames_graph(m, r_list = r_list, r_times = r_times, r_type = "gradient",
                          fade_raster = TRUE, graph_type = "flow")
# take a look
frames.gr[[100]]

# make a histogram graph:
frames.gr <- frames_graph(m, r_list = r_list, r_times = r_times, r_type = "gradient",
                          fade_raster = TRUE, graph_type = "hist")
# change the value interval:
frames.gr <- frames_graph(m, r_list = r_list, r_times = r_times, r_type = "gradient",
                          fade_raster = TRUE, graph_type = "hist", val_by = 0.01)

# }# NOT RUN {
frames.gr[[100]]
# manipulate the labels, since now they are very dense:
# just replace the current scale
frames.gr <- add_gg(frames.gr, expr(scale_x_continuous(breaks=seq(0,1,0.1),
                                    labels=seq(0,1,0.1), expand = c(0,0))))
frames.gr[[100]]

# the same can be done for discrete data, histogram will then be shown as bin plots

# to make your own graphs, use frames_graph to return data instead of frames
data.gr <- frames_graph(m, r_list = r_list, r_times = r_times, r_type = "gradient",
                        fade_raster = TRUE, return_data = TRUE)

# animate the frames created with frames_graph;
animate_frames(frames, out_file = tempfile(fileext = ".gif"))
# }# NOT RUN {
# see all add_ functions on how to customize your frames created with frames_spatial
# or frames_graph

# see ?animate_frames on how to animate your list of frames

# }