Two-Way Dissimilarity Plots of Time Series Lists

Plots two sequences, their distance or cost matrix, their least cost path, and all relevant values used to compute dissimilarity.

Unlike distantia(), this function does not accept vectors as inputs for the arguments to compute dissimilarity (distance, diagonal, and weighted), and only plots a pair of sequences at once.

The argument lock_step is not available because this plot does not make sense in such a case.

Usage

distantia_plot(
  tsl = NULL,
  distance = "euclidean",
  diagonal = TRUE,
  weighted = TRUE,
  ignore_blocks = FALSE,
  matrix_type = "cost",
  matrix_color = NULL,
  path_width = 1,
  path_color = "black",
  line_color = NULL,
  line_width = 1,
  text_cex = 1
)

Arguments

tsl

(required, time series list) list of zoo time series. Default: NULL

distance

(optional, character vector) name or abbreviation of the distance method. Valid values are in the columns "names" and "abbreviation" of the dataset distances. Default: "euclidean".

diagonal

(optional, logical vector). If TRUE, diagonals are included in the dynamic time warping computation. Default: TRUE

weighted

(optional, logical vector) If TRUE, diagonal is set to TRUE, and diagonal cost is weighted by a factor of 1.414214. Default: TRUE

ignore_blocks

(optional, logical vector). If TRUE, blocks of consecutive least cost path coordinates are trimmed to avoid inflating the psi dissimilarity Irrelevant if diagonal = TRUE. Default: FALSE.

matrix_type

(optional, character string): one of "cost" or "distance" (the abbreviation "dist" is accepted as well). Default: "cost".

matrix_color

(optional, character vector) vector of colors for the distance or cost matrix. If NULL, uses the palette "Zissou 1" provided by the function grDevices::hcl.colors(). Default: NULL

path_width

(optional, numeric) width of the least cost path. Default: 1

path_color

(optional, character string) color of the least-cost path. Default: "black"

line_color

(optional, character vector) Vector of colors for the time series plot. If not provided, defaults to a subset of matrix_color.

line_width

(optional, numeric vector) Width of the time series plot. Default: 1

text_cex

(optional, numeric) Multiplier of the text size. Default: 1

Value

A plot.

See also

Other dissimilarity_analysis: distantia_aggregate(), distantia_boxplot(), distantia_cluster_hclust(), distantia_cluster_kmeans(), distantia_matrix(), distantia_to_sf()

Examples

#three time series
#climate and ndvi in Fagus sylvatica stands in Spain, Germany, and Sweden
data("fagus_dynamics")

#convert to time series list
#scale and center to neutralize effect of different scales in temperature, rainfall, and ndvi
tsl <- tsl_initialize(
  x = fagus_dynamics,
  name_column = "name",
  time_column = "time"
) |>
  tsl_transform(
    f = f_scale #see help(f_scale)
  )

if(interactive()){
  tsl_plot(
    tsl = tsl,
    guide_columns = 3
    )
}

#visualize dynamic time warping
if(interactive()){

  #plot pair with cost matrix (default)
  distantia_plot(
    tsl = tsl[c("Spain", "Sweden")] #only two time series!
  )

  #plot pair with distance matrix
  distantia_plot(
    tsl = tsl[c("Spain", "Sweden")],
    matrix_type = "distance"
  )

  #plot pair with different distance
  distantia_plot(
    tsl = tsl[c("Spain", "Sweden")],
    distance = "manhattan", #sed data(distances)
    matrix_type = "distance"
  )


  #with different colors
  distantia_plot(
    tsl = tsl[c("Spain", "Sweden")],
    matrix_type = "distance",
    matrix_color = grDevices::hcl.colors(
      n = 100,
      palette = "Inferno"
    ),
    path_color = "white",
    path_width = 2,
    line_color = grDevices::hcl.colors(
      n = 3, #same as variables in tsl
      palette = "Inferno"
    )
  )

}