View source: R/psi_cost_path.R
psi_cost_path | R Documentation |
Demonstration function to compute the least cost path within a least cost matrix.
psi_cost_path(
dist_matrix = NULL,
cost_matrix = NULL,
diagonal = TRUE,
bandwidth = 1
)
dist_matrix |
(required, numeric matrix) Distance matrix generated by |
cost_matrix |
(required, numeric matrix) Cost matrix generated from the distance matrix with |
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 Sakoe-Chiba band) 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 |
data frame
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()
#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
)
}
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