# API for tsmp package

## Exported functions

as.arccount(.mp)
as.chain(.mp)
as.fluss(.mp)
as.matrixprofile(.mp)
as.motif(.mp)
as.multimatrixprofile(.mp)
as.multimotif(.mp)
as.salient(.mp)
av_apply(.mp)
av_complexity(.mp, data, dilution_factor = 0, apply = FALSE)
av_hardlimit_artifact(.mp, data, apply = FALSE)
av_motion_artifact(.mp, data, apply = FALSE)
av_stop_word(.mp, data, stop_word_loc, exclusion_zone = NULL, threshold = 0.1, apply = FALSE)
av_zerocrossing(.mp, data, apply = FALSE)
fast_movavg(data, window_size)
fast_movsd(data, window_size)
find_chains(.mp)
find_motif(.mp, ...)
fluss(.mp, num_segments, exclusion_zone = NULL)
fluss_cac(.mp, exclusion_zone = NULL)
fluss_extract(.mpac, num_segments, exclusion_zone = NULL)
fluss_score(gtruth, extracted, data_size)
mass(data_fft, query_window, data_size, window_size, data_mean, data_sd, query_mean, query_sd)
mass_pre(data, data_size, query = NULL, query_size = NULL, window_size)
mstomp(data, window_size, exclusion_zone = 1/2, verbose = 2, must_dim = NULL, exc_dim = NULL)
mstomp_par(data, window_size, exclusion_zone = 1/2, verbose = 2, must_dim = NULL, exc_dim = NULL, n_workers = 2)
plot_arcs(pairs, alpha = NULL, quality = 30, lwd = 15, col = c("blue", "orange"), main = "Arc Plot", ylab, xlab = "Profile Index", ...)
salient_subsequences(.mp, data, n_bits = 8, n_cand = 10, exclusion_zone = NULL, verbose = 2)
scrimp(..., window_size, exclusion_zone = 1/2, verbose = 2, s_size = Inf)
sdts_predict(model, data, window_size)
sdts_score(gtruth, pred, beta = 1)
sdts_train(data, label, window_size, beta = 1, pat_max = Inf, parallel = TRUE, verbose = 2)
simple_fast(..., window_size, exclusion_zone = 1/2, verbose = 2)
stamp(..., window_size, exclusion_zone = 1/2, verbose = 2, s_size = Inf)
stamp_par(..., window_size, exclusion_zone = 1/2, verbose = 2, s_size = Inf, n_workers = 2)
stomp(..., window_size, exclusion_zone = 1/2, verbose = 2)
stomp_par(..., window_size, exclusion_zone = 1/2, verbose = 2, n_workers = 2)
tsmp(..., window_size, exclusion_zone = 1/2, mode = c("stomp", "stamp", "simple", "mstomp", "scrimp"), verbose = 2, s_size = Inf, must_dim = NULL, exc_dim = NULL, n_workers = 1, .keep_data = TRUE)

## Own S3 methods

find_motif.MatrixProfile(.mp, data, n_motifs = 3, radius = 3, exclusion_zone = NULL, ...)
find_motif.MultiMatrixProfile(.mp, data, n_motifs = 3, mode = c("guided", "unconstrained"), n_bit = 4, exclusion_zone = NULL, n_dim = NULL, ...)

## Foreign S3 methods

plot.ArcCount(x, data, type = c("data", "matrix"), exclusion_zone = NULL, edge_limit = NULL, threshold = stats::quantile(x$cac, 0.1), main = "Arcs Discover", xlab = "index", ylab = "distance", ...)
plot.Chain(x, data, type = c("data", "matrix"), main = "Chain Discover", xlab = "index", ylab = "distance", ...)
plot.Fluss(x, data, type = c("data", "matrix"), main = "Fast Low-cost Unipotent Semantic Segmentation", xlab = "index", ylab = "distance", ...)
plot.MatrixProfile(x, ylab = "distance", xlab = "index", main = "Unidimensional Matrix Profile", ...)
plot.Motif(x, data, type = c("data", "matrix"), ncol = 3, main = "MOTIF Discover", xlab = "index", ylab = "distance", ...)
plot.MultiMatrixProfile(x, ylab = "distance", xlab = "index", main = "Multidimensional Matrix Profile", ...)
plot.MultiMotif(x, data, type = c("data", "matrix"), ncol = 3, main = "Multidimensional MOTIF Discover", xlab = "index", ylab = "distance", ...)
print.ArcCount(x, ...)
print.Chain(x, ...)
print.Fluss(x, ...)
print.MatrixProfile(x, ...)
print.Motif(x, ...)
print.MultiMatrixProfile(x, ...)
print.MultiMotif(x, ...)
