Finish v0.3.4

# Conflicts:
#	README.md

API-v0.3.4

@@ -0,0 +1,86 @@
+# API for tsmp package
+
+## Exported functions
+
+as.arccount(.mp)
+as.chain(.mp)
+as.discord(.mp)
+as.fluss(.mp)
+as.matrixprofile(.mp)
+as.motif(.mp)
+as.multimatrixprofile(.mp)
+as.multimotif(.mp)
+as.salient(.mp)
+as.valmod(.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_discord(.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)
+get_data(.mp)
+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_mds(.mp, data, bit_idx = 1)
+salient_score(.mp, gtruth)
+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, pre_scrimp = 1/4)
+sdts_predict(model, data, window_size)
+sdts_score(pred, gtruth, beta = 1)
+sdts_train(data, label, window_size, beta = 1, pat_max = Inf, parallel = TRUE, verbose = 2)
+set_data(.mp, data)
+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", "valmod"), verbose = 2, n_workers = 1, s_size = Inf, must_dim = NULL, exc_dim = NULL, heap_size = 50, .keep_data = TRUE)
+valmod(..., window_min, window_max, heap_size = 50, exclusion_zone = 1/2, lb = TRUE, verbose = 2)
+
+## Own S3 methods
+
+find_discord.MatrixProfile(.mp, data, n_discords = 1, n_neighbors = 3, radius = 3, exclusion_zone = NULL, ...)
+find_motif.MatrixProfile(.mp, data, n_motifs = 3, n_neighbors = 10, 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, ...)
+plot.Chain(x, data, type = c("data", "matrix"), main = "Chain Discover", xlab = "index", ylab, ...)
+plot.Discord(x, data, type = c("data", "matrix"), ncol = 3, main = "Discord Discover", xlab = "index", ylab, ...)
+plot.Fluss(x, data, type = c("data", "matrix"), main = "Fast Low-cost Unipotent Semantic Segmentation", xlab = "index", ylab, ...)
+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, ...)
+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, ...)
+plot.Salient(x, data, main = "Salient Subsections", xlab = "index", ylab, ...)
+plot.SimpleMatrixProfile(x, ylab = "distance", xlab = "index", main = "SiMPle Matrix Profile", ...)
+plot.Valmod(x, ylab = "distance", xlab = "index", main = "Valmod Matrix Profile", ...)
+print.ArcCount(x, ...)
+print.Chain(x, ...)
+print.Discord(x, ...)
+print.Fluss(x, ...)
+print.MatrixProfile(x, ...)
+print.Motif(x, ...)
+print.MultiMatrixProfile(x, ...)
+print.MultiMotif(x, ...)
+print.Salient(x, ...)
+print.SimpleMatrixProfile(x, ...)
+print.Valmod(x, ...)
+
+## Reexported objects
+
+::%>%
+::%T>%

CRAN-RELEASE

@@ -1,2 +1,2 @@
-This package was submitted to CRAN on 2018-10-23.
-Once it is accepted, delete this file and tag the release (commit 0e7131cff8).
+This package was submitted to CRAN on 2019-02-24.
+Once it is accepted, delete this file and tag the release (commit da04b9872c).

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: tsmp
 Type: Package
 Title: Time Series with Matrix Profile
-Version: 0.3.2
+Version: 0.3.4.9000
 Authors@R: c(
     person("Francisco", "Bischoff", email = "[email protected]", role = c("aut", "cre"),
     comment = c(ORCID = "https://orcid.org/0000-0002-5301-8672")),
@@ -25,7 +25,7 @@ Encoding: UTF-8
 Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 6.1.0.9000
+RoxygenNote: 6.1.1
 NeedsCompilation: no
 Suggests: 
     spelling,

NAMESPACE

@@ -1,35 +1,42 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(find_discord,MatrixProfile)
 S3method(find_motif,MatrixProfile)
 S3method(find_motif,MultiMatrixProfile)
 S3method(plot,ArcCount)
 S3method(plot,Chain)
+S3method(plot,Discord)
 S3method(plot,Fluss)
 S3method(plot,MatrixProfile)
 S3method(plot,Motif)
 S3method(plot,MultiMatrixProfile)
 S3method(plot,MultiMotif)
 S3method(plot,Salient)
 S3method(plot,SimpleMatrixProfile)
+S3method(plot,Valmod)
 S3method(print,ArcCount)
 S3method(print,Chain)
+S3method(print,Discord)
 S3method(print,Fluss)
 S3method(print,MatrixProfile)
 S3method(print,Motif)
 S3method(print,MultiMatrixProfile)
 S3method(print,MultiMotif)
 S3method(print,Salient)
 S3method(print,SimpleMatrixProfile)
+S3method(print,Valmod)
 export("%>%")
 export("%T>%")
 export(as.arccount)
 export(as.chain)
+export(as.discord)
 export(as.fluss)
 export(as.matrixprofile)
 export(as.motif)
 export(as.multimatrixprofile)
 export(as.multimotif)
 export(as.salient)
+export(as.valmod)
 export(av_apply)
 export(av_complexity)
 export(av_hardlimit_artifact)
@@ -39,6 +46,7 @@ export(av_zerocrossing)
 export(fast_movavg)
 export(fast_movsd)
 export(find_chains)
+export(find_discord)
 export(find_motif)
 export(fluss)
 export(fluss_cac)
@@ -64,5 +72,6 @@ export(stamp_par)
 export(stomp)
 export(stomp_par)
 export(tsmp)
+export(valmod)
 importFrom(magrittr,"%>%")
 importFrom(magrittr,"%T>%")

NEWS

@@ -1,6 +1,20 @@
 <!-- NEWS.md is generated from NEWS.Rmd. Please edit that file -->
-tsmp 0.3.1.9000
-===============
+tsmp 0.3.4
+==========
+
+-   Added `find_discord()` and its `print()` and `plot()` functions.
+-   Changed `plot()` for motifs to show where are the neighbors. Same
+    for discord.
+-   Added `valmod()` for Variable Length Motif Discovery.
+-   Changed `find_motif()` for compatibility with `valmod()`.
+
+tsmp 0.3.3
+==========
+
+-   Fixed `find_chains()` not returning the longest chain. Issue \#33
+
+tsmp 0.3.2
+==========
 
 -   Fixed Matrix Profile print, dimensions are now reported correctly.
 -   Fixed pipe imports. Issue \#22

NEWS.Rmd

@@ -21,7 +21,17 @@ knitr::opts_chunk$set(
 )
 ```
 
-# tsmp 0.3.1.9000
+# tsmp 0.3.4
+* Added `find_discord()` and its `print()` and `plot()` functions.
+* Changed `plot()` for motifs to show where are the neighbors. Same for discord. 
+* Added `valmod()` for Variable Length Motif Discovery.
+* Changed `find_motif()` for compatibility with `valmod()`.
+
+# tsmp 0.3.3
+
+* Fixed `find_chains()` not returning the longest chain. Issue #33
+
+# tsmp 0.3.2
 
 * Fixed Matrix Profile print, dimensions are now reported correctly.
 * Fixed pipe imports. Issue #22

NEWS.md

@@ -1,11 +1,23 @@
 NEWS
 ================
 Francisco Bischoff
-\- 23 Oct 2018
+\- 23 Feb 2019
 
 <!-- NEWS.md is generated from NEWS.Rmd. Please edit that file -->
 
-# tsmp 0.3.1.9000
+# tsmp 0.3.4
+
+  - Added `find_discord()` and its `print()` and `plot()` functions.
+  - Changed `plot()` for motifs to show where are the neighbors. Same
+    for discord.
+  - Added `valmod()` for Variable Length Motif Discovery.
+  - Changed `find_motif()` for compatibility with `valmod()`.
+
+# tsmp 0.3.3
+
+  - Fixed `find_chains()` not returning the longest chain. Issue \#33
+
+# tsmp 0.3.2
 
   - Fixed Matrix Profile print, dimensions are now reported correctly.
   - Fixed pipe imports. Issue \#22

R/annotations.R

@@ -17,8 +17,11 @@
 #' w <- 50
 #' mp <- tsmp(data, window_size = w, verbose = 0)
 #' av <- av_zerocrossing(mp, apply = TRUE)
-#'
 av_zerocrossing <- function(.mp, data, apply = FALSE) {
+  if ("Valmod" %in% class(.mp)) {
+    stop("Error: Function not implemented for objects of class `Valmod`.")
+  }
+
   if (missing(data) && !is.null(.mp$data)) {
     data <- .mp$data[[1]]
   }
@@ -62,8 +65,11 @@ av_zerocrossing <- function(.mp, data, apply = FALSE) {
 #' w <- 50
 #' mp <- tsmp(data, window_size = w, verbose = 0)
 #' av <- av_complexity(mp, apply = TRUE)
-#'
 av_complexity <- function(.mp, data, dilution_factor = 0, apply = FALSE) {
+  if ("Valmod" %in% class(.mp)) {
+    stop("Error: Function not implemented for objects of class `Valmod`.")
+  }
+
   if (missing(data) && !is.null(.mp$data)) {
     data <- .mp$data[[1]]
   }
@@ -113,8 +119,11 @@ av_complexity <- function(.mp, data, dilution_factor = 0, apply = FALSE) {
 #' w <- 50
 #' mp <- tsmp(data, window_size = w, verbose = 0)
 #' av <- av_motion_artifact(mp, apply = TRUE)
-#'
 av_motion_artifact <- function(.mp, data, apply = FALSE) {
+  if ("Valmod" %in% class(.mp)) {
+    stop("Error: Function not implemented for objects of class `Valmod`.")
+  }
+
   if (missing(data) && !is.null(.mp$data)) {
     data <- .mp$data[[1]]
   }
@@ -171,8 +180,11 @@ av_motion_artifact <- function(.mp, data, apply = FALSE) {
 #' w <- 50
 #' mp <- tsmp(data, window_size = w, verbose = 0)
 #' av <- av_stop_word(mp, stop_word_loc = 150, apply = TRUE)
-#'
 av_stop_word <- function(.mp, data, stop_word_loc, exclusion_zone = NULL, threshold = 0.1, apply = FALSE) {
+  if ("Valmod" %in% class(.mp)) {
+    stop("Error: Function not implemented for objects of class `Valmod`.")
+  }
+
   if (missing(data) && !is.null(.mp$data)) {
     data <- .mp$data[[1]]
   }
@@ -234,8 +246,11 @@ av_stop_word <- function(.mp, data, stop_word_loc, exclusion_zone = NULL, thresh
 #' w <- 50
 #' mp <- tsmp(data, window_size = w, verbose = 0)
 #' av <- av_hardlimit_artifact(mp, apply = TRUE)
-#'
 av_hardlimit_artifact <- function(.mp, data, apply = FALSE) {
+  if ("Valmod" %in% class(.mp)) {
+    stop("Error: Function not implemented for objects of class `Valmod`.")
+  }
+
   if (missing(data) && !is.null(.mp$data)) {
     data <- .mp$data[[1]]
   }
@@ -287,13 +302,12 @@ av_hardlimit_artifact <- function(.mp, data, apply = FALSE) {
 #' mp <- tsmp(data, window_size = w, verbose = 0)
 #' mp <- av_complexity(mp)
 #' av <- av_apply(mp)
-
 av_apply <- function(.mp) {
-  if (!any(class(.mp) %in% "MatrixProfile")) {
+  if (!("MatrixProfile" %in% class(.mp))) {
     stop("Error: First argument must be an object of class `MatrixProfile`.")
   }
 
-  if (!any(class(.mp) %in% "AnnotationVector")) {
+  if (!("AnnotationVector" %in% class(.mp))) {
     stop("Error: First argument must be an object of class `AnnotationVector`.")
   }
 

R/find-chains.R

@@ -13,14 +13,17 @@
 #' @examples
 #' w <- 50
 #' data <- mp_gait_data
-#' mp <- tsmp(data, window_size = w, exclusion_zone = 1/4, verbose = 0)
+#' mp <- tsmp(data, window_size = w, exclusion_zone = 1 / 4, verbose = 0)
 #' mp <- find_chains(mp)
-#'
 find_chains <- function(.mp) {
-  if (!any(class(.mp) %in% "MatrixProfile")) {
+  if (!("MatrixProfile" %in% class(.mp))) {
     stop("Error: First argument must be an object of class `MatrixProfile`.")
   }
 
+  if ("Valmod" %in% class(.mp)) {
+    stop("Error: Function not implemented for objects of class `Valmod`.")
+  }
+
   size <- length(.mp$rpi)
   chain_length <- rep(1, size)
   chain_set <- list()
@@ -52,7 +55,9 @@ find_chains <- function(.mp) {
   mean <- Inf
   for (i in seq_len(length(chain_set))) {
     if (length(chain_set[[i]]) == l) {
-      n <- mean(.mp$rmp[chain_set[[i]]])
+      vals <- .mp$rmp[chain_set[[i]]]
+      vals <- vals[!is.infinite(vals)]
+      n <- mean(vals)
       if (n < mean) {
         mean <- n
         best_chain <- chain_set[[i]]