get two time series. split them into intersecting windows of length 10. then find the closest 5 neighbors for one time series from the other time series as fast as possible in r

main.r
# Define the time series as vectors of length n
n <- 10000
set.seed(123)
ts1 <- rnorm(n)
ts2 <- rnorm(n)

# Define the window size
w_size <- 10

# Define the number of neighbors to find
k <- 5

# Split the time series into windows
ts1_w <- embed(ts1, w_size)  # a matrix with n-w_size+1 rows and w_size columns
ts2_w <- embed(ts2, w_size)  # a matrix with n-w_size+1 rows and w_size columns

# Compute the pairwise distances between windows using Euclidean distance
library(proxy)
distances <- as.matrix(dist(x = ts1_w, y = ts2_w, method = "euclidean"))

# Find the k-NN for each window in ts1
library(FNN)
knn_result <- get.knnx(distances, k = k, sorted = TRUE, index.return = TRUE)

# The knn_result$nn.index matrix has k columns (the k-NN for each window) and n-w_size+1 rows (the windows in ts1)
# Each row has the indices of the k-NN for the corresponding window in ts1
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