Least Cost Path

Demonstration function to compute the least cost path within a least cost matrix.

Usage

psi_cost_path(
  dist_matrix = NULL,
  cost_matrix = NULL,
  diagonal = TRUE,
  bandwidth = 1
)

Arguments

dist_matrix

(required, numeric matrix) Distance matrix generated by psi_distance_matrix(). Default: NULL

cost_matrix

(required, numeric matrix) Cost matrix generated from the distance matrix with psi_cost_matrix(). Default: NULL

diagonal

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

bandwidth

(optional, numeric) Proportion of space at each side of the cost matrix diagonal (aka Itakura parallelogram) defining a valid region for dynamic time warping, used to control the flexibility of the warping path. This method prevents degenerate alignments due to differences in magnitude between time series when the data is not properly scaled. If 1 (default), DTW is unconstrained. If 0, DTW is fully constrained and the warping path follows the matrix diagonal. Recommended values may vary depending on the nature of the data. Ignored if lock_step = TRUE. Default: 1.

Value

data frame

See also

Other psi_demo: psi_auto_distance(), psi_auto_sum(), psi_cost_matrix(), psi_cost_path_sum(), psi_distance_lock_step(), psi_distance_matrix(), psi_equation()

Examples

#distance metric
d <- "euclidean"

#simulate two irregular time series
x <- zoo_simulate(
  name = "x",
  rows = 100,
  seasons = 2,
  seed = 1
)

y <- zoo_simulate(
  name = "y",
  rows = 80,
  seasons = 2,
  seed = 2
)

if(interactive()){
  zoo_plot(x = x)
  zoo_plot(x = y)
}

#distance matrix
dist_matrix <- psi_distance_matrix(
  x = x,
  y = y,
  distance = d
)

#diagonal least cost path
#------------------------

cost_matrix <- psi_cost_matrix(
  dist_matrix = dist_matrix,
  diagonal = TRUE
)

cost_path <- psi_cost_path(
  dist_matrix = dist_matrix,
  cost_matrix = cost_matrix,
  diagonal = TRUE
)

if(interactive()){
  utils_matrix_plot(
    m = cost_matrix,
    path = cost_path
    )
}


#orthogonal least cost path
#--------------------------
cost_matrix <- psi_cost_matrix(
  dist_matrix = dist_matrix,
  diagonal = FALSE
)

cost_path <- psi_cost_path(
  dist_matrix = dist_matrix,
  cost_matrix = cost_matrix,
  diagonal = FALSE
)

if(interactive()){
  utils_matrix_plot(
    m = cost_matrix,
    path = cost_path
  )
}