From ecf0065df6e10cc2ed38ea748d01a74c70727c13 Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Sun, 31 Jan 2021 17:15:45 +0100 Subject: [PATCH 1/9] bug fix re BIs in getToaYaps() & insert mandatory checkInp() in runYaps() --- .Rbuildignore | 1 + CRAN-RELEASE | 2 ++ DESCRIPTION | 2 +- NEWS.md | 7 +++++++ R/checkInp.R | 9 +++++++-- R/getToaYaps.R | 4 ++-- R/prepTmb.R | 2 +- R/runYaps.R | 4 ++++ man/getToaYaps.Rd | 2 +- 9 files changed, 26 insertions(+), 7 deletions(-) create mode 100644 CRAN-RELEASE diff --git a/.Rbuildignore b/.Rbuildignore index 5b1b354..e6719c2 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -15,3 +15,4 @@ ^codecov\.yml$ ^\.travis\.yml$ ^cran-comments\.md$ +^CRAN-RELEASE$ diff --git a/CRAN-RELEASE b/CRAN-RELEASE new file mode 100644 index 0000000..8275019 --- /dev/null +++ b/CRAN-RELEASE @@ -0,0 +1,2 @@ +This package was submitted to CRAN on 2021-01-28. +Once it is accepted, delete this file and tag the release (commit dfb10b1). diff --git a/DESCRIPTION b/DESCRIPTION index 5048fac..7f77501 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: yaps Title: Track Estimation using YAPS (Yet Another Positioning Solver) -Version: 1.2.3 +Version: 1.2.3.9000 Authors@R: c( person("Henrik", "Baktoft", email = "hba@aqua.dtu.dk", role = c("cre", "aut"), comment=c(ORCID = "0000-0002-3644-4960")), person("Karl", "Gjelland", role=c("aut")), person("Uffe H.", "Thygesen", role=c("aut")), diff --git a/NEWS.md b/NEWS.md index 8f14676..7987a4f 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,10 @@ +# yaps v1.2.3.9000 + +## New stuff + +## Bug fixes +* Fix bug in getToaYaps() re number of empty pings + # yaps v1.2.3 ## New stuff diff --git a/R/checkInp.R b/R/checkInp.R index 40bdfe6..318a733 100644 --- a/R/checkInp.R +++ b/R/checkInp.R @@ -4,16 +4,21 @@ #' @export #' @example man/examples/example-yaps_ssu1.R checkInp <- function(inp){ + + # check that all BIs are in range of values in the model + stopifnot(inp$datTmb$rbi_min <= min(diff(inp$params$top))) + stopifnot(inp$datTmb$rbi_max >= max(diff(inp$params$top))) stopifnot(ncol(inp$datTmb$toa) == inp$datTmb$np) stopifnot(nrow(inp$datTmb$toa) == inp$datTmb$nh) + stopifnot(dim(inp$datTmb$H)[2] == 3) + # if z_vec != NULL if(inp$datTmb$how_3d != 'none'){ - stopifnot(dim(inp$datTmb$H)[2] == 3) stopifnot(length(inp$datTmb$z_vec) == inp$datTmb$np) } - print("checkInp passed!") + print("Pre-flight checkInp() passed!") } \ No newline at end of file diff --git a/R/getToaYaps.R b/R/getToaYaps.R index b89bc4f..b6cad2a 100644 --- a/R/getToaYaps.R +++ b/R/getToaYaps.R @@ -4,7 +4,7 @@ #' @inheritParams getInp #' @export #' @example man/examples/example-yaps_ssu1.R -getToaYaps <- function(synced_dat, hydros, rbi_min, rbi_max){ +getToaYaps <- function(synced_dat, hydros, ping_type, rbi_min, rbi_max){ # remove NAs in eposync synced_dat <- synced_dat[!is.na(eposync)] @@ -73,7 +73,7 @@ getToaYaps <- function(synced_dat, hydros, rbi_min, rbi_max){ } else { pings[, next_ping_too_late := diff > rbi_max+.1] } - if(rbi_max > 15){ ### USE PING_TYPE INSTEAD!!!! + if(ping_type != 'sbi'){ pings[next_ping_too_late==TRUE, ping2next:=ping2next+round(diff/rbi_max)] } else { pings[next_ping_too_late==TRUE, ping2next:=round(diff/rbi_max)] # the line above puts in an extra pang for pingType = "sbi" diff --git a/R/prepTmb.R b/R/prepTmb.R index 3ecb8f7..7c7c58e 100644 --- a/R/prepTmb.R +++ b/R/prepTmb.R @@ -72,7 +72,7 @@ getDatTmb <- function(hydros, toa, E_dist, n_ss, pingType, rbi_min, rbi_max, ss_ if(is.null(z_vec)){ how_3d <- 'none' z_vec <- c(1) - } else if(z_vec == "est") { + } else if(z_vec[1] == "est") { how_3d <- 'est' z_vec <- c(1) } else { diff --git a/R/runYaps.R b/R/runYaps.R index 5d91b54..6ff859c 100644 --- a/R/runYaps.R +++ b/R/runYaps.R @@ -11,6 +11,10 @@ #' @example man/examples/example-yaps_ssu1.R #' @export runYaps <- function(inp, maxIter=1000, getPlsd=TRUE, getRep=TRUE, silent=TRUE, opt_fun='nlminb', opt_controls=list(), bounds=list(), tmb_smartsearch=TRUE){ + + # making sure inp is correct... + checkInp(inp) + nobs <- z <- z_sd <- NULL print("Running yaps...") random <- c("X", "Y", "top") diff --git a/man/getToaYaps.Rd b/man/getToaYaps.Rd index e50e306..44276aa 100644 --- a/man/getToaYaps.Rd +++ b/man/getToaYaps.Rd @@ -4,7 +4,7 @@ \alias{getToaYaps} \title{Build TOA matrix from synced data.table - also do some pre-filtering of severe MP, pruning loose ends etc} \usage{ -getToaYaps(synced_dat, hydros, rbi_min, rbi_max) +getToaYaps(synced_dat, hydros, ping_type, rbi_min, rbi_max) } \arguments{ \item{synced_dat}{`data.table` containing synchronized data formatted as output from/or obtained using `applySync()`} From 226df49ae34128865ce8fb5acb35ed15f49cc584 Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Sun, 31 Jan 2021 20:38:51 +0100 Subject: [PATCH 2/9] redo to make getToaYaps() backwards comp --- DESCRIPTION | 2 +- NEWS.md | 2 +- R/getToaYaps.R | 11 ++++++++--- R/prepTmb.R | 1 + R/testYaps.R | 3 ++- man/getToaYaps.Rd | 4 +++- 6 files changed, 16 insertions(+), 7 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 7f77501..548158a 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: yaps Title: Track Estimation using YAPS (Yet Another Positioning Solver) -Version: 1.2.3.9000 +Version: 1.2.3.9001 Authors@R: c( person("Henrik", "Baktoft", email = "hba@aqua.dtu.dk", role = c("cre", "aut"), comment=c(ORCID = "0000-0002-3644-4960")), person("Karl", "Gjelland", role=c("aut")), person("Uffe H.", "Thygesen", role=c("aut")), diff --git a/NEWS.md b/NEWS.md index 7987a4f..bbff04b 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,4 @@ -# yaps v1.2.3.9000 +# yaps v1.2.3.9001 ## New stuff diff --git a/R/getToaYaps.R b/R/getToaYaps.R index b6cad2a..17af785 100644 --- a/R/getToaYaps.R +++ b/R/getToaYaps.R @@ -4,8 +4,13 @@ #' @inheritParams getInp #' @export #' @example man/examples/example-yaps_ssu1.R -getToaYaps <- function(synced_dat, hydros, ping_type, rbi_min, rbi_max){ - +getToaYaps <- function(synced_dat, hydros, rbi_min, rbi_max, pingType=NULL){ + if(is.null(pingType)){ + cat("WARNING: pingType not specified in getToaYaps() - will assume 'rbi'. This will become a fatal error in later versions.\n") + pingType <- 'rbi' + } + stopifnot(pingType %in% c('sbi', 'pbi', 'rbi')) + # remove NAs in eposync synced_dat <- synced_dat[!is.na(eposync)] # remove multipaths... @@ -73,7 +78,7 @@ getToaYaps <- function(synced_dat, hydros, ping_type, rbi_min, rbi_max){ } else { pings[, next_ping_too_late := diff > rbi_max+.1] } - if(ping_type != 'sbi'){ + if(pingType != 'sbi'){ pings[next_ping_too_late==TRUE, ping2next:=ping2next+round(diff/rbi_max)] } else { pings[next_ping_too_late==TRUE, ping2next:=round(diff/rbi_max)] # the line above puts in an extra pang for pingType = "sbi" diff --git a/R/prepTmb.R b/R/prepTmb.R index 7c7c58e..e1f86e8 100644 --- a/R/prepTmb.R +++ b/R/prepTmb.R @@ -17,6 +17,7 @@ #' @return List of input data ready for use in TMB-call #' @export getInp <- function(hydros, toa, E_dist, n_ss, pingType, sdInits=1, rbi_min=0, rbi_max=0, ss_data_what='est', ss_data=0, biTable=NULL, z_vec=NULL, bbox=NULL){ + stopifnot(pingType %in% c('sbi', 'pbi', 'rbi')) inp_params <- getInpParams(hydros, toa, pingType) datTmb <- getDatTmb(hydros, toa, E_dist, n_ss, pingType, rbi_min, rbi_max, ss_data_what, ss_data, biTable, inp_params, z_vec, bbox) params <- getParams(datTmb) diff --git a/R/testYaps.R b/R/testYaps.R index ab9ef95..780158b 100644 --- a/R/testYaps.R +++ b/R/testYaps.R @@ -26,7 +26,8 @@ testYaps <- function(silent=TRUE, pingType='sbi', est_ss=TRUE, opt_fun='nlminb', # pingType <- 'sbi' if(pingType == 'sbi'){ sbi_mean <- 20; sbi_sd <- 1e-3; - rbi_min <- 0; rbi_max <- 0; + rbi_min <- sbi_mean; + rbi_max <- sbi_mean; teleTrack <- simTelemetryTrack(trueTrack, pingType=pingType, sbi_mean=sbi_mean, sbi_sd=sbi_sd) } else { rbi_min = 30 diff --git a/man/getToaYaps.Rd b/man/getToaYaps.Rd index 44276aa..6412397 100644 --- a/man/getToaYaps.Rd +++ b/man/getToaYaps.Rd @@ -4,7 +4,7 @@ \alias{getToaYaps} \title{Build TOA matrix from synced data.table - also do some pre-filtering of severe MP, pruning loose ends etc} \usage{ -getToaYaps(synced_dat, hydros, ping_type, rbi_min, rbi_max) +getToaYaps(synced_dat, hydros, rbi_min, rbi_max, pingType = NULL) } \arguments{ \item{synced_dat}{`data.table` containing synchronized data formatted as output from/or obtained using `applySync()`} @@ -14,6 +14,8 @@ getToaYaps(synced_dat, hydros, ping_type, rbi_min, rbi_max) \item{rbi_min}{Minimum and maximum BI for random burst interval transmitters} \item{rbi_max}{Minimum and maximum BI for random burst interval transmitters} + +\item{pingType}{Type of transmitter to simulate - either stable burst interval ('sbi'), random burst interval ('rbi') or random burst interval but where the random sequence is known a priori} } \description{ Build TOA matrix from synced data.table - also do some pre-filtering of severe MP, pruning loose ends etc From 62139db46159cd2467ee16bc1457be0ea94c7012 Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Sun, 31 Jan 2021 23:36:26 +0100 Subject: [PATCH 3/9] robustify tmb using bounds - EXPERIMENTAL --- DESCRIPTION | 2 +- R/runYaps.R | 23 +++++++++++++---------- 2 files changed, 14 insertions(+), 11 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 548158a..e07e88e 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: yaps Title: Track Estimation using YAPS (Yet Another Positioning Solver) -Version: 1.2.3.9001 +Version: 1.2.3.9002 Authors@R: c( person("Henrik", "Baktoft", email = "hba@aqua.dtu.dk", role = c("cre", "aut"), comment=c(ORCID = "0000-0002-3644-4960")), person("Karl", "Gjelland", role=c("aut")), person("Uffe H.", "Thygesen", role=c("aut")), diff --git a/R/runYaps.R b/R/runYaps.R index 6ff859c..acc2ec2 100644 --- a/R/runYaps.R +++ b/R/runYaps.R @@ -41,6 +41,15 @@ runYaps <- function(inp, maxIter=1000, getPlsd=TRUE, getRep=TRUE, silent=TRUE, o obj$fn(obj$par) TMB::newtonOption(obj, smartsearch=FALSE) } + + if(opt_controls[['use_bounds']]){ + lower <- opt_controls[['lower']] + upper <- opt_controls[['upper']] + opt_controls <- list() + } else { + lower <- -Inf + upper <- Inf + } if(opt_fun == 'nloptr'){ opts <- opt_controls @@ -52,18 +61,12 @@ runYaps <- function(inp, maxIter=1000, getPlsd=TRUE, getRep=TRUE, silent=TRUE, o } else if(opt_fun == 'nlminb'){ control_list <- opt_controls - if(!silent){ - # tictoc::tic() - opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list) - # tictoc::toc() - - # tictoc::tic() - # opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list, lower=c(-10,-10, -10, -10, -10), upper=c(2, 2, 2, 2, -2)) - # opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list, lower=c(-10,-10, -10, -10, -10), upper=c(2, 2, 2, 2, -2)) - # tictoc::toc() + # opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list) + # opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list, lower=c(-50,-15, -100, -50, -20), upper= c(2, 2, 100, 2, -2)) + opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list, lower=lower, upper=upper) } else { - suppressWarnings(opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list)) + suppressWarnings(opt <- stats::nlminb(inp$inits,obj$fn,obj$gr, control = control_list, lower=lower, upper=upper)) } } From bb9c6bf27c63d29a2ecd8792d0116e98cfd560a1 Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Mon, 1 Feb 2021 09:26:51 +0100 Subject: [PATCH 4/9] relax pre-flight checks for ping_type='sbi' --- DESCRIPTION | 2 +- R/checkInp.R | 7 +++++-- R/runYaps.R | 2 +- 3 files changed, 7 insertions(+), 4 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index e07e88e..b7a1ae3 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: yaps Title: Track Estimation using YAPS (Yet Another Positioning Solver) -Version: 1.2.3.9002 +Version: 1.2.3.9003 Authors@R: c( person("Henrik", "Baktoft", email = "hba@aqua.dtu.dk", role = c("cre", "aut"), comment=c(ORCID = "0000-0002-3644-4960")), person("Karl", "Gjelland", role=c("aut")), person("Uffe H.", "Thygesen", role=c("aut")), diff --git a/R/checkInp.R b/R/checkInp.R index 318a733..5c830b9 100644 --- a/R/checkInp.R +++ b/R/checkInp.R @@ -6,8 +6,11 @@ checkInp <- function(inp){ # check that all BIs are in range of values in the model - stopifnot(inp$datTmb$rbi_min <= min(diff(inp$params$top))) - stopifnot(inp$datTmb$rbi_max >= max(diff(inp$params$top))) + # only relevant for ping_types 'rbi' and 'pbi'? + if(inp$datTmb$pingType != 'sbi'){ + stopifnot(inp$datTmb$rbi_min <= min(diff(inp$params$top))) + stopifnot(inp$datTmb$rbi_max >= max(diff(inp$params$top))) + } stopifnot(ncol(inp$datTmb$toa) == inp$datTmb$np) stopifnot(nrow(inp$datTmb$toa) == inp$datTmb$nh) diff --git a/R/runYaps.R b/R/runYaps.R index acc2ec2..23ebe82 100644 --- a/R/runYaps.R +++ b/R/runYaps.R @@ -42,7 +42,7 @@ runYaps <- function(inp, maxIter=1000, getPlsd=TRUE, getRep=TRUE, silent=TRUE, o TMB::newtonOption(obj, smartsearch=FALSE) } - if(opt_controls[['use_bounds']]){ + if( !is.null(opt_controls[['use_bounds']])){ lower <- opt_controls[['lower']] upper <- opt_controls[['upper']] opt_controls <- list() From 69cb1982d828821a258c217ce8afeaefa3cb7ffe Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Fri, 5 Feb 2021 00:17:42 +0100 Subject: [PATCH 5/9] v1.2.3.9005 docs and examples --- .gitignore | 2 + .travis.yml | 1 - DESCRIPTION | 12 +- NEWS.md | 13 +- R/alignBurstSeq.R | 6 +- R/applySync.R | 6 +- R/checkInp.R | 1 + R/checkInpSync.R | 4 +- R/data.R | 2 +- R/fineTuneSyncModel.R | 2 +- R/getBbox.R | 2 +- R/getInp.R | 34 +++++ R/getInpSync.R | 75 +++++++++++ R/getSyncModel.R | 95 ++++++++++++++ R/getToaYaps.R | 1 + R/plotBbox.R | 1 + R/plotYaps.R | 1 + R/prepFiles.R | 3 +- R/prepTmb.R | 34 ----- R/runYaps.R | 31 ++++- R/simTrack.R | 10 +- R/syncGetters.R | 169 ------------------------- R/syncPlotters.R | 5 +- R/tempToSs.R | 1 + R/testYaps.R | 27 ++-- cran-comments.md | 42 ------ man/alignBurstSeq.Rd | 11 +- man/applySync.Rd | 31 +++-- man/checkInp.Rd | 31 +++-- man/checkInpSync.Rd | 33 +++-- man/dat_align.Rd | 14 +- man/examples/example-alignBurstSeq.R | 3 - man/examples/example-bbox.R | 2 - man/examples/example-syncModelPlots.R | 8 +- man/examples/example-yaps_sim.R | 5 +- man/examples/example-yaps_ssu1.R | 22 ++-- man/fineTuneSyncModel.Rd | 110 ++-------------- man/getBbox.Rd | 6 +- man/getInp.Rd | 95 +++++++++++++- man/getInpSync.Rd | 39 +++--- man/getSyncCoverage.Rd | 96 +++++++++++++- man/getSyncModel.Rd | 37 +++--- man/getToaYaps.Rd | 27 ++-- man/plotBbox.Rd | 5 +- man/plotSyncModelCheck.Rd | 13 +- man/plotSyncModelHydros.Rd | 11 +- man/plotSyncModelResids.Rd | 11 +- man/plotYaps.Rd | 3 + man/prepDetections.Rd | 5 +- man/runYaps.Rd | 50 +++++--- man/simHydros.Rd | 7 +- man/simTelemetryTrack.Rd | 7 +- man/simToa.Rd | 5 +- man/simTrueTrack.Rd | 7 +- man/ssu1.Rd | 46 +++---- man/tempToSs.Rd | 3 + man/testYaps.Rd | 29 +++-- tests/testthat/sync_model_f1_ref.RData | Bin 31106 -> 30987 bytes tests/testthat/sync_model_ref.RData | Bin 31296 -> 31178 bytes 59 files changed, 746 insertions(+), 606 deletions(-) create mode 100644 R/getInp.R create mode 100644 R/getInpSync.R create mode 100644 R/getSyncModel.R delete mode 100644 cran-comments.md diff --git a/.gitignore b/.gitignore index b0237dc..9bb2945 100644 --- a/.gitignore +++ b/.gitignore @@ -43,3 +43,5 @@ inst/doc debug.log README.html +cran-comments.md +CRAN-RELEASE diff --git a/.travis.yml b/.travis.yml index 44aeefc..b55a40f 100644 --- a/.travis.yml +++ b/.travis.yml @@ -6,4 +6,3 @@ addons: apt: packages: - libgit2-dev - \ No newline at end of file diff --git a/DESCRIPTION b/DESCRIPTION index b7a1ae3..40de558 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,21 +1,23 @@ Package: yaps Title: Track Estimation using YAPS (Yet Another Positioning Solver) -Version: 1.2.3.9003 +Version: 1.2.3.9005 Authors@R: c( person("Henrik", "Baktoft", email = "hba@aqua.dtu.dk", role = c("cre", "aut"), comment=c(ORCID = "0000-0002-3644-4960")), - person("Karl", "Gjelland", role=c("aut")), - person("Uffe H.", "Thygesen", role=c("aut")), - person("Finn", "Økland", role=c("aut")) + person("Karl", "Gjelland", role=c("aut"), comment=c(ORCID = "0000-0003-4036-4207")), + person("Uffe H.", "Thygesen", role=c("aut"), comment=c(ORCID = "0000-0002-4311-6324")), + person("Finn", "Økland", role=c("aut"), comment=c(ORCID = "0000-0002-1938-5460")) ) Description: Estimate tracks of animals tagged with acoustic transmitters. 'yaps' was introduced in 2017 as a transparent open-source tool to estimate positions of fish (and other aquatic animals) tagged with acoustic transmitters. Based on registrations of acoustic transmitters on hydrophones positioned in a fixed array, 'yaps' enables users to synchronize the collected data (i.e. correcting for drift in the internal clocks of the hydrophones/receivers) and subsequently to estimate tracks of the tagged animals. The paper introducing 'yaps' is available in open access at Baktoft, Gjelland, Økland & Thygesen (2017) . Also check out our cookbook with a completely worked through example at Baktoft, Gjelland, Økland, Rehage, Rodemann, Corujo, Viadero & Thygesen (2019) . Additional tutorials will eventually make their way onto the project website at . Depends: R (>= 3.5.0) License: GPL-3 Encoding: UTF-8 LazyData: true +Roxygen: list(markdown = TRUE) RoxygenNote: 7.1.1 LinkingTo: Rcpp, TMB, RcppEigen Imports: circular, cowplot, data.table, ggplot2, ggrepel, nloptr, plyr, Rcpp, reshape2, splusTimeSeries, stats, tictoc, TMB, viridis, zoo Suggests: - covr, + caTools, + covr, knitr, rmarkdown, testthat (>= 2.1.0), diff --git a/NEWS.md b/NEWS.md index bbff04b..7cf60f7 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,15 +1,20 @@ -# yaps v1.2.3.9001 +# yaps v1.2.3.9005 ## New stuff +* More checks in checkInp() to catch typical errors in format of inp. +* EXPERIMENTAL Attempt to robustify runYaps() - use with care. ## Bug fixes -* Fix bug in getToaYaps() re number of empty pings +* Fix bug in getToaYaps() re number of empty pings. +* Docs and examples fixed to meet requirements. +* Make getToaYaps() aware of pingType + # yaps v1.2.3 ## New stuff -* Moved example data `hald` to an external package with yaps example data `yapsdata`. Available from github using devtools::install_github('baktoft/yapsdata') -* Lots of examples and tests added +* Moved example data `hald` to an external package with yaps example data `yapsdata`. Available from github using devtools::install_github('baktoft/yapsdata'). +* Lots of examples and tests added. # yaps v1.2.2 diff --git a/R/alignBurstSeq.R b/R/alignBurstSeq.R index 02a9e4d..5bf465b 100644 --- a/R/alignBurstSeq.R +++ b/R/alignBurstSeq.R @@ -8,8 +8,8 @@ #' @param seq_lng_min Minimum length of sequence of consecutive pings to use for the alignment. Finds first occurence of sequence of this length in the data and compare to the known burst sequence #' @param rbi_min,rbi_max Minimum and maximum burst interval of the transmitter. Used to identify sequence of consecutive pings in the data #' @param plot_diag Logical indicating if visual diagnosis plots should be created. -#' return data.table like input, but with extra columns seq_ping_idx and seq_epo #' @export +#' @return `data.table` like the input `synced_dat`, but with extra columns seq_ping_idx and seq_epo #' @example man/examples/example-alignBurstSeq.R alignBurstSeq <- function(synced_dat, burst_seq, seq_lng_min=10, rbi_min, rbi_max, plot_diag=TRUE){ burst_seq_dt <- data.table::data.table(bi=burst_seq) @@ -52,12 +52,14 @@ alignBurstSeq <- function(synced_dat, burst_seq, seq_lng_min=10, rbi_min, rbi_ma # plot if plot_diag == TRUE if(plot_diag){ + oldpar <- par(no.readonly = TRUE) + on.exit(par(oldpar)) + par(mfrow=c(1,2)) plot(log(seq_diffs)) points(log(seq_diffs[seq_fix_idx]) ~ seq_fix_idx, col="red", pch=20, cex=2) plot(synced_dat[, eposync - seq_epo] ~ synced_dat$ts, pch=".") - par(mfrow=c(1,1)) } return(synced_dat) diff --git a/R/applySync.R b/R/applySync.R index 5d4cffd..d13d6df 100644 --- a/R/applySync.R +++ b/R/applySync.R @@ -1,10 +1,12 @@ #' Apply sync model to toa matrix to obtain synced data +#' #' @param toa Object containing data to be synchronized. Typically a `data.table` as e.g. `ssu1$detections`, but can also be a matrix dim=(n_ping, n_hydo). #' @param hydros data.table formatted as `ssu1$hydros` #' @param sync_model Synchronization model obtained using `getSyncModel()` -#' @example man/examples/example-yaps_ssu1.R - +#' #' @export +#' @return A `data.table` with the now synchronized time-of-arrivals in column `eposync`. +#' @example man/examples/example-yaps_ssu1.R applySync <- function(toa, hydros="", sync_model){ if(is.matrix(toa)) {type <- "toa_matrix" } else if(data.table::is.data.table(toa)) {type <- "detections_table"} diff --git a/R/checkInp.R b/R/checkInp.R index 5c830b9..f6f6232 100644 --- a/R/checkInp.R +++ b/R/checkInp.R @@ -2,6 +2,7 @@ #' #' @param inp Object obtained using `getInp()` #' @export +#' @return No return value, but prints errors/warnings if issues with `inp` is detected. #' @example man/examples/example-yaps_ssu1.R checkInp <- function(inp){ diff --git a/R/checkInpSync.R b/R/checkInpSync.R index 3e61c57..a07dad0 100644 --- a/R/checkInpSync.R +++ b/R/checkInpSync.R @@ -3,6 +3,7 @@ #' @inheritParams getInpSync #' @param inp_sync Object obtained using `getInpSync()` #' @export +#' @return No return value, but prints errors/warnings if issues with `inp_sync` is detected. #' @example man/examples/example-yaps_ssu1.R checkInpSync <- function(inp_sync, silent_check){ # speed of sound stuff @@ -34,7 +35,6 @@ checkInpSync <- function(inp_sync, silent_check){ } else if(!silent_check & min(sync_coverage$N) < 50) { cat("NOTE: At least one hydro has less than 50 pings in an offset_idx - try getSyncCoverage(inp_sync, plot=TRUE) for visual\n and rerun getInpSync() with increased keep_rate\n") } - return(sync_coverage) } #' Quick overview to check if all hydros have enough data within each offset period. @@ -42,6 +42,8 @@ checkInpSync <- function(inp_sync, silent_check){ #' @inheritParams checkInpSync #' @param plot Logical indicating whether to plot a visual or not. #' @export +#' @return A data.table containing number of pings included in each hydro x offset combination. +#' @example man/examples/example-yaps_ssu1.R getSyncCoverage <- function(inp_sync, plot=FALSE){ toa <- inp_sync$dat_tmb_sync$toa nh <- ncol(toa) diff --git a/R/data.R b/R/data.R index f8a0bc7..68e438c 100644 --- a/R/data.R +++ b/R/data.R @@ -19,7 +19,7 @@ #' \item ts Timestamp of detection in POSIXct(). #' \item tag ID of detected tag. #' \item epo Timestamp as number of seconds since Unix epoch. Can be obtained using as.numeric(ts). -#' \item frac Sub-second part of detection timestamp in fractions of second [0-1]. +#' \item frac Sub-second part of detection timestamp in fractions of second (0-1). #' \item serial Serial number of detecting hydrophone. Must match entry in data.table hydros. #' } #' } diff --git a/R/fineTuneSyncModel.R b/R/fineTuneSyncModel.R index 5ab04dd..1107e47 100644 --- a/R/fineTuneSyncModel.R +++ b/R/fineTuneSyncModel.R @@ -3,8 +3,8 @@ #' @param sync_model sync_model obtained using getSyncModel() #' @param eps_threshold Maximum value of residual measured in meter assuming speed of sound = 1450 m/s #' @param silent logical whether to make getSyncModel() silent -#' @example man/examples/example-yaps_ssu1.R #' @export +#' @return Fine tuned `sync_model`. See `?getSyncModel` for more info. #' @example man/examples/example-yaps_ssu1.R fineTuneSyncModel <- function(sync_model, eps_threshold, silent=TRUE){ # original inp_sync diff --git a/R/getBbox.R b/R/getBbox.R index 92c32da..67f3cdf 100644 --- a/R/getBbox.R +++ b/R/getBbox.R @@ -1,12 +1,12 @@ #' Get a standard bounding box to impose spatial constraints #' #' Standard is a rectangle based on coordinates of outer hydros +- the buffer in meters -#' Returns a vector of lenght 6: c(x_min, x_max, y_min, y_max, eps, pen). Limits are given in UTM coordinates. #' @param buffer Number of meters the spatial domain extends beyound the outer hydros. #' @param eps Specifies how well-defined the borders are (eps=1E-2 is very sharp, eps=100 is very soft). #' @param pen Specifies the penalty multiplier. #' @inheritParams getInp #' @export +#' @return Vector of lenght 6: c(x_min, x_max, y_min, y_max, eps, pen). Limits are given in UTM coordinates. #' @example man/examples/example-bbox.R getBbox <- function(hydros, buffer=5, eps=1E-3, pen=1){ x_min <- hydros[which.min(hydros$hx), hx] - buffer diff --git a/R/getInp.R b/R/getInp.R new file mode 100644 index 0000000..6fc5994 --- /dev/null +++ b/R/getInp.R @@ -0,0 +1,34 @@ +#' Get prepared inp-object for use in TMB-call +#' +#' Wrapper-function to compile a list of input needed to run TMB +#' @param hydros Dataframe from simHydros() or Dataframe with columns hx and hy containing positions of the receivers. Translate the coordinates to get the grid centre close to (0;0). +#' @param toa TOA-matrix: matrix with receivers in rows and detections in columns. Make sure that the receivers are in the same order as in hydros, and that the matrix is very regular: one ping per column (inlude empty columns if a ping is not detected). +#' @param E_dist Which distribution to use in the model - "Gaus" = Gaussian, "Mixture" = mixture of Gaussian and t or "t" = pure t-distribution +#' @param n_ss Number of soundspeed estimates: one estimate per hour is usually enough +#' @param pingType Type of transmitter to simulate - either stable burst interval ('sbi'), random burst interval ('rbi') or random burst interval but where the random sequence is known a priori +#' @param rbi_min,rbi_max Minimum and maximum BI for random burst interval transmitters +#' @param sdInits If >0 initial values will be randomized around the normally fixed value using rnorm(length(inits), mean=inits, sd=sdInits) +#' @param ss_data_what What speed of sound (ss) data to be used. Default ss_data_what='est': ss is estimated by the model. Alternatively, if ss_data_what='data': ss_data must be provided and length(ss_data) == ncol(toa) +#' @param ss_data Vector of ss-data to be used if ss_data_what = 'est'. Otherwise ss_data <- 0 (default) +#' @param biTable Table of known burst intervals. Only used when pingType == "pbi". Default=NULL +#' @param z_vec Vector of known depth values (positive real). Default=NULL is which case no 3D is assumed. If z_vec = "est" depth will be estimated. +#' @param bbox Spatial constraints in the form of a bounding box. See ?getBbox for details. + +#' @return List of input data ready for use in `runYaps()` +#' @export +#' @example man/examples/example-yaps_ssu1.R +getInp <- function(hydros, toa, E_dist, n_ss, pingType, sdInits=1, rbi_min=0, rbi_max=0, ss_data_what='est', ss_data=0, biTable=NULL, z_vec=NULL, bbox=NULL){ + stopifnot(pingType %in% c('sbi', 'pbi', 'rbi')) + inp_params <- getInpParams(hydros, toa, pingType) + datTmb <- getDatTmb(hydros, toa, E_dist, n_ss, pingType, rbi_min, rbi_max, ss_data_what, ss_data, biTable, inp_params, z_vec, bbox) + params <- getParams(datTmb) + inits <- getInits(datTmb, sdInits) + return(list( + datTmb = datTmb, + params= params, + inits = inits, + inp_params = inp_params + ) + ) +} + diff --git a/R/getInpSync.R b/R/getInpSync.R new file mode 100644 index 0000000..6b5ab99 --- /dev/null +++ b/R/getInpSync.R @@ -0,0 +1,75 @@ +#' Get object inp for synchronization +#' +#' @param sync_dat List containing data.tables with hydrophone information and detections. See e.g. `?ssu1` for example +#' @param max_epo_diff Sets the upper threshold for differences in TOA of sync tags. Best parameter value depends on burst rate of sync tags and how far apart the internal clocks of the hydros are prior to synchronization. A bit less than half of minimum sync tag burst rate is a good starting choice. +#' @param min_hydros Sets the lower threshold of how many hydrophones need to detect each sync tag ping in order to be included in the sync process. Should be as high as possible while observing that all hydrosphones are contributing. If too low, isolated hydrophones risk falling out completely. Future versions will work towards automising this. +#' @param time_keeper_idx Index of the hydrophone to use as time keeper. Could e.g. be the one with smallest overall clock-drift. +#' @param fixed_hydros_idx Vector of hydro idx's for all hydrophones where the position is assumed to be known with adequate accuracy and precission. Include as many as possible as fixed hydros to reduce overall computation time and reduce overall variability. As a bare minimum two hydros need to be fixed, but we strongly advice to use more than two. +#' @param n_offset_day Specifies the number of hydrophone specific quadratic polynomials to use per day. For PPM based systems, 1 or 2 is often adeqaute. +#' @param n_ss_day Specifies number of speed of sound to estimate per day if no ss data is supplied. It is recommended to use logged water temperature instead. However, estimating SS gives an extra option for sanity-checking the final sync-model. +#' @param ss_data_what Indicates whether to estimate ("est") speed of sound or to use data based on logged water temperature ("data"). +#' @param ss_data data.table containing timestamp and speed of sound for the entire period to by synchronised. Must contain columns 'ts' (POSIXct timestamp) and 'ss' speed of sound in m/s (typical values range 1400 - 1550). +#' @param keep_rate Syncing large data sets can take a really long time. However, there is typically an excess number of sync tag detections +#' and a sub-sample is typically enough for good synchronization. +#' This parameter EITHER specifies a proportion (0-1) of data to keep when sub-sampling +#' OR (if keep_rate > 10) number of pings (approximate) to keep in each hydro X offset_idx combination if enough exists. +#' @param excl_self_detect Logical whether to excluded detections of sync tags on the hydros they are co-located with. Sometimes self detections can introduce excessive residuals in the sync model in which case they should be excluded. +#' @param lin_corr_coeffs Matrix of coefficients used for pre-sync linear correction. `dim(lin_corr_coeffs)=(#hydros, 2)`. +#' @param silent_check Logical whether to get output from `checkInpSync()`. Default is FALSE +#' +#' @export +#' @return List of input data ready for use in `getSyncModel()` +#' @example man/examples/example-yaps_ssu1.R +getInpSync <- function(sync_dat, max_epo_diff, min_hydros, time_keeper_idx, fixed_hydros_idx, n_offset_day, n_ss_day, keep_rate=1, excl_self_detect=TRUE, lin_corr_coeffs=NA, ss_data_what="est", ss_data=c(0), silent_check=FALSE){ + if(length(unique(sync_dat$hydros$serial)) != nrow(sync_dat$hydros)){ + print(sync_dat$hydros[, .N, by=serial][N>=2]) + stop("ERROR: At least one hydrophone serial number is used more than once in sync_dat$hydros!\n") + } + + if(keep_rate <=0 | (keep_rate > 1 & keep_rate < 10) | (keep_rate >= 10 & keep_rate %% 1 != 0)){ + stop("ERROR: Invalid keep_rate! Must be either ]0;1] or integer >= 10\n") + } + + sync_dat <- appendDetections(sync_dat) + + if(is.na(lin_corr_coeffs[1])){ + lin_corr_coeffs <- matrix(0, nrow=nrow(sync_dat$hydros), ncol=2, byrow=TRUE) + } + + sync_dat <- applyLinCorCoeffsInpSync(sync_dat, lin_corr_coeffs) + + T0 <- min(sync_dat$detections$epo) + + inp_H_info <- getInpSyncHInfo(sync_dat) + + inp_toa_list_all <- getInpSyncToaList(sync_dat, max_epo_diff, min_hydros, excl_self_detect) + fixed_hydros_vec <- getFixedHydrosVec(sync_dat, fixed_hydros_idx) + offset_vals_all <- getOffsetVals(inp_toa_list_all, n_offset_day) + inp_toa_list <- getDownsampledToaList(inp_toa_list_all, offset_vals_all, keep_rate) + offset_vals <- getOffsetVals(inp_toa_list, n_offset_day) + ss_vals <- getSsVals(inp_toa_list, n_ss_day) + if(ss_data_what == "data"){ + ss_data_vec <- getSsDataVec(inp_toa_list, ss_data) + } else { + ss_data_vec <- c(0) + } + + dat_tmb_sync <- getDatTmbSync(sync_dat, time_keeper_idx, inp_toa_list, fixed_hydros_vec, offset_vals, ss_vals, inp_H_info, T0, ss_data_what, ss_data_vec) + params_tmb_sync <- getParamsTmbSync(dat_tmb_sync, ss_data_what) + if(ss_data_what == "est"){ + random_tmb_sync <- c("TOP", "OFFSET", "SLOPE1", "SLOPE2", "SS", "TRUE_H") + } else { + random_tmb_sync <- c("TOP", "OFFSET", "SLOPE1", "SLOPE2", "TRUE_H") + } + # inits_tmb_sync <- c(3, rep(-3,dat_tmb_sync$nh)) + inits_tmb_sync <- c(-3) + inp_params <- list(toa=inp_toa_list$toa, T0=T0, Hx0=inp_H_info$Hx0, Hy0=inp_H_info$Hy0, offset_levels=offset_vals$offset_levels, + ss_levels=ss_vals$ss_levels, max_epo_diff=max_epo_diff, hydros=sync_dat$hydros, + lin_corr_coeffs=lin_corr_coeffs, min_hydros=min_hydros, ss_data=ss_data + ) + + inp_sync <- list(dat_tmb_sync=dat_tmb_sync, params_tmb_sync=params_tmb_sync, random_tmb_sync=random_tmb_sync, inits_tmb_sync=inits_tmb_sync, inp_params=inp_params) + inp_sync$inp_params$sync_coverage <- checkInpSync(inp_sync, silent_check) + return(inp_sync) + +} diff --git a/R/getSyncModel.R b/R/getSyncModel.R new file mode 100644 index 0000000..cf2179d --- /dev/null +++ b/R/getSyncModel.R @@ -0,0 +1,95 @@ +#' Get sync model from inp_sync object obtained by `getInpSync()` +#' +#' @param inp_sync Input data prepared for the sync model using `getInpSync()` +#' @param silent Keep TMB quiet +#' @param fine_tune Logical. Whether to re-run the sync model excluding residual outliers. **Deprecated** use fineTuneSyncModel() instead. +#' @param max_iter Max number of iterations to run TMB. Default=100 seems to work in most cases. +#' @param tmb_smartsearch Logical whether to use the TMB smartsearch in the inner optimizer (see `?TMB::MakeADFun` for info). Default and original implementation is TRUE. However, there seems to be an issue with some versions of `Matrix` that requires `tmb_smartsearch=FALSE`. +#' +#' @export +#' @return List containing relevant data constituting the `sync_model` ready for use in `fineTuneSyncModel()` if needed or in `applySync()` +#' @example man/examples/example-yaps_ssu1.R +getSyncModel <- function(inp_sync, silent=TRUE, fine_tune=FALSE, max_iter=100, tmb_smartsearch=TRUE){ + inp_sync$inp_params$tmb_smartsearch <- tmb_smartsearch + inp_sync$inp_params$max_iter <- max_iter + + dat_tmb <- inp_sync$dat_tmb_sync + params <- inp_sync$params_tmb_sync + random <- inp_sync$random_tmb_sync + inits <- inp_sync$inits_tmb_sync + inp_params <- inp_sync$inp_params + + cat(paste0(Sys.time(), " \n")) + cat(". Running optimization of the sync model. Please be patient - this can take a long time. \n") + if(fine_tune){cat(".... fine tuning is enabled, but is getting deprecated in future version. Consider to use the function fineTuneSyncModel() instead. See ?fineTuneSyncModel for info. \n")} + + tictoc::tic("Fitting sync model: ") + opt <- c() + pl <- c() + plsd <- c() + obj <- c() + + tictoc::tic() + obj <- c() + opt <- c() + report <- c() + gc() + + # config(DLL="yaps_sync") + # ## Reduce memory peak of a parallel model by creating tapes in serial + # config(tape.parallel=0, DLL="yaps_sync") + obj <- TMB::MakeADFun(data = dat_tmb, parameters = params, random = random, DLL = "yaps", inner.control = list(maxit = max_iter), silent=silent) + obj$fn(obj$par) + + if(!tmb_smartsearch){ + TMB::newtonOption(obj, smartsearch=FALSE) + } + + + if(silent){ + # opt <- suppressWarnings(stats::nlminb(inits,obj$fn,obj$gr)) + opt <- suppressWarnings(stats::nlminb(inits,obj$fn,obj$gr, lower=c(-10), upper=c(-2))) + } else { + opt <- stats::nlminb(inits,obj$fn,obj$gr, lower=c(-10), upper=c(-2)) + # opt <- stats::nlminb(inits,obj$fn,obj$gr) + } + + pl <- obj$env$parList() # List of estimates + obj_val <- opt$objective + cat(paste0(".. ", Sys.time()), " \n") + cat(".... obj = ", obj_val, " \n") + report <- obj$report() + + crazy_outliers <- which(abs(report$eps_toa)*1450 > 10000) + fine_outliers <- which(abs(report$eps_toa)*1450 > 1000) + if(length(crazy_outliers > 0)){ + cat(".... some extreme outliers potentially affecting the model where identified \n Consider to run fineTuneSyncModel(sync_model, eps_threshold=10000). See ?fineTuneSyncModel for more info. \n") + # dat_tmb$toa_offset[crazy_outliers] <- NA + } else if(fine_tune){ + cat(".... fine tuning is enabled, but is deprecated. Use the function fineTuneSyncModel() instead. See ?fineTuneSyncModel for info. \n") + # dat_tmb$toa_offset[fine_outliers] <- NA + } + + tictoc::toc() + + jointrep <- try(TMB::sdreport(obj, getJointPrecision=TRUE), silent=silent) + param_names <- rownames(summary(jointrep)) + sds <- summary(jointrep)[,2] + summ <- data.frame(param=param_names, sd=sds) + plsd <- split(summ[,2], f=summ$param) + + pl$TRUE_H[,1] <- pl$TRUE_H[,1] + inp_params$Hx0 + pl$TRUE_H[,2] <- pl$TRUE_H[,2] + inp_params$Hy0 + eps_long <- getEpsLong(report, pl, inp_sync) + + offset_nas <- which(pl$OFFSET == 0) + pl$OFFSET[offset_nas] <- NA + pl$SLOPE1[offset_nas] <- NA + pl$SLOPE2[offset_nas] <- NA + + cat("Sync model done \n") + cat("Consider saving the sync model for later use - e.g. save(sync_model, file='path_to_sync_save'). \n") + + return(list(pl=pl, plsd=plsd, report=report, obj_val=obj_val, eps_long=eps_long, inp_synced=inp_sync)) +} + diff --git a/R/getToaYaps.R b/R/getToaYaps.R index 17af785..3d48619 100644 --- a/R/getToaYaps.R +++ b/R/getToaYaps.R @@ -3,6 +3,7 @@ #' @param synced_dat `data.table` containing synchronized data formatted as output from/or obtained using `applySync()` #' @inheritParams getInp #' @export +#' @return Matrix of time-of-arrivals. One coloumn per hydro, one row per ping. #' @example man/examples/example-yaps_ssu1.R getToaYaps <- function(synced_dat, hydros, rbi_min, rbi_max, pingType=NULL){ if(is.null(pingType)){ diff --git a/R/plotBbox.R b/R/plotBbox.R index 5c897f2..84cb3f3 100644 --- a/R/plotBbox.R +++ b/R/plotBbox.R @@ -1,6 +1,7 @@ #' Graphical representation of spatial constraints #' @inheritParams getInp #' @export +#' @return No return value, called to plot graphic. #' @example man/examples/example-bbox.R plotBbox <- function(hydros, bbox){ Var1 <- Var2 <- NULL diff --git a/R/plotYaps.R b/R/plotYaps.R index 5db2436..f6a0544 100644 --- a/R/plotYaps.R +++ b/R/plotYaps.R @@ -5,6 +5,7 @@ #' @param xlim,ylim Optional vectors of length 2 to set xlim and/or ylim. #' @param main Title of plot - optional. #' @export +#' @return No return value, called to plot graphics. #' @example man/examples/example-plotYaps.R plotYaps <- function(yaps_out, type="map", xlim=NULL, ylim=NULL, main=NULL){ inp <- yaps_out$inp diff --git a/R/prepFiles.R b/R/prepFiles.R index 32f93bb..a0f3dae 100644 --- a/R/prepFiles.R +++ b/R/prepFiles.R @@ -2,8 +2,9 @@ #' @param raw_dat Data file from vendor supplied software #' @param type Type of the vendor file. Currently only 'vemco_vue' is supported. #' @export +#' @return `data.table` containing detections extracted from manufacturer data file. #' @examples \dontrun{ -#' prepped_detections <- prepDetection("path-to-raw-data-file", type="vemco_vue") +#' prepped_detections <- prepDetections("path-to-raw-data-file", type="vemco_vue") #' } prepDetections <- function(raw_dat, type){ detections <- data.table::data.table() diff --git a/R/prepTmb.R b/R/prepTmb.R index e1f86e8..45f6c12 100644 --- a/R/prepTmb.R +++ b/R/prepTmb.R @@ -1,37 +1,3 @@ -#' Get prepared inp-object for use in TMB-call -#' -#' Wrapper-function to compile a list of input needed to run TMB -#' @param hydros Dataframe from simHydros() or Dataframe with columns hx and hy containing positions of the receivers. Translate the coordinates to get the grid centre close to (0;0). -#' @param toa TOA-matrix: matrix with receivers in rows and detections in columns. Make sure that the receivers are in the same order as in hydros, and that the matrix is very regular: one ping per column (inlude empty columns if a ping is not detected). -#' @param E_dist Which distribution to use in the model - "Gaus" = Gaussian, "Mixture" = mixture of Gaussian and t or "t" = pure t-distribution -#' @param n_ss Number of soundspeed estimates: one estimate per hour is usually enough -#' @param pingType Type of transmitter to simulate - either stable burst interval ('sbi'), random burst interval ('rbi') or random burst interval but where the random sequence is known a priori -#' @param rbi_min,rbi_max Minimum and maximum BI for random burst interval transmitters -#' @param sdInits If >0 initial values will be randomized around the normally fixed value using rnorm(length(inits), mean=inits, sd=sdInits) -#' @param ss_data_what What speed of sound (ss) data to be used. Default ss_data_what='est': ss is estimated by the model. Alternatively, if ss_data_what='data': ss_data must be provided and length(ss_data) == ncol(toa) -#' @param ss_data Vector of ss-data to be used if ss_data_what = 'est'. Otherwise ss_data <- 0 (default) -#' @param biTable Table of known burst intervals. Only used when pingType == "pbi". Default=NULL -#' @param z_vec Vector of known depth values (positive real). Default=NULL is which case no 3D is assumed. If z_vec = "est" depth will be estimated. -#' @param bbox Spatial constraints in the form of a bounding box. See ?getBbox for details. - -#' @return List of input data ready for use in TMB-call -#' @export -getInp <- function(hydros, toa, E_dist, n_ss, pingType, sdInits=1, rbi_min=0, rbi_max=0, ss_data_what='est', ss_data=0, biTable=NULL, z_vec=NULL, bbox=NULL){ - stopifnot(pingType %in% c('sbi', 'pbi', 'rbi')) - inp_params <- getInpParams(hydros, toa, pingType) - datTmb <- getDatTmb(hydros, toa, E_dist, n_ss, pingType, rbi_min, rbi_max, ss_data_what, ss_data, biTable, inp_params, z_vec, bbox) - params <- getParams(datTmb) - inits <- getInits(datTmb, sdInits) - return(list( - datTmb = datTmb, - params= params, - inits = inits, - inp_params = inp_params - ) - ) -} - - #' Internal function - get data for input to TMB #' #' Compile data for input to TMB. diff --git a/R/runYaps.R b/R/runYaps.R index 23ebe82..7d8ffd6 100644 --- a/R/runYaps.R +++ b/R/runYaps.R @@ -1,15 +1,32 @@ #' Function to run TMB to estimate track #' -#' @param inp inp-object obtained from getInp() -#' @param maxIter Sets inner.control(maxit) of the tmb-call. Increase if model is not converging. +#' @param inp inp-object obtained from `getInp()` +#' @param maxIter Sets `inner.control(maxit)` of the TMB-call. Increase if model is not converging. #' @param getPlsd,getRep Whether or not to get sd estimates (plsd=TRUE) and reported values (getRep=TRUE). #' @param silent Logical whether to keep the optimization quiet. -#' @param opt_fun Which optimization function to use. Default is 'nlminb' - alternative is 'nloptr' (experimental!). If using 'nloptr', `opt_controls` must be specified. -#' @param opt_controls List of controls passed to optimization function. For instances, tolerances such as x.tol=1E-8. If opt_fun = 'nloptr', `opt_controls` must be a list formatted appropriately. For instance: opt_controls <- list(algorithm="NLOPT_LD_AUGLAG", xtol_abs=1e-12, maxeval=2E+4, print_level = 1, local_opts= list(algorithm="NLOPT_LD_AUGLAG_EQ", xtol_rel=1e-4) ). See `?nloptr` and the NLopt site https://nlopt.readthedocs.io/en/latest/ for more info. Some algorithms in `nloptr` require bounded parameters - see `bounds`. -#' @param bounds List of two vectors specifying lower and upper bounds of fixed parameters. Length of each vector must be equal to number of fixed parameters. For instance, bounds = list(lb = c(-3, -1, -2), ub = c(2,0,1) ). -#' @param tmb_smartsearch Logical whether to use the TMB smartsearch in the inner optimizer (see ?TMB::MakeADFun for info). Default and original implementation is TRUE. However, there seems to be an issue with Matrix v1.3.2 that requires tmb_smartsearch=FALSE. -#' @example man/examples/example-yaps_ssu1.R +#' @param opt_fun Which optimization function to use. Default is `opt_fun = 'nlminb'` - alternative is `opt_fun = 'nloptr'` (experimental!). If using nloptr, `opt_controls` must be specified. +#' @param opt_controls List of controls passed to optimization function. For instances, tolerances such as `x.tol=1E-8`. \cr +#' If `opt_fun = 'nloptr'`, `opt_controls` must be a list formatted appropriately. For instance: \cr +#' `opt_controls <- list( algorithm="NLOPT_LD_AUGLAG", xtol_abs=1e-12, maxeval=2E+4, print_level = 1, local_opts= list(algorithm="NLOPT_LD_AUGLAG_EQ", xtol_rel=1e-4) )`. \cr +#' See `?nloptr` and the NLopt site https://nlopt.readthedocs.io/en/latest/ for more info. Some algorithms in `nloptr` require bounded parameters - see `bounds`. +#' @param bounds List of two vectors specifying lower and upper bounds of fixed parameters. Length of each vector must be equal to number of fixed parameters. For instance, `bounds = list(lb = c(-3, -1, -2), ub = c(2,0,1) )`. +#' @param tmb_smartsearch Logical whether to use the TMB smartsearch in the inner optimizer (see `?TMB::MakeADFun` for info). Default and original implementation is TRUE. However, there seems to be an issue with recent versions of `Matrix` that requires `tmb_smartsearch=FALSE`. +#' #' @export +#' +#' @return List containing results of fitting `yaps` to the data. +#' \describe{ +#' \item{pl}{List containing all parameter estimates.} +#' \item{plsd}{List containing standard errors of parameter estimates.} +#' \item{rep}{List containing `mu_toa`.} +#' \item{obj}{Numeric obj value of the fitted model obtained using `obj$fn()`.} +#' \item{inp}{List containing the `inp` object used in `runYaps()`. See `?getInp` for further info.} +#' \item{conv_status}{Integer convergence status.} +#' \item{conv_message}{Text version of convergence status.} +#' \item{track}{A data.table containing the estimated track including time-of-ping (top), standard errors and number of hydros detecting each ping (nobs).} +#' } +#' +#' @example man/examples/example-yaps_ssu1.R runYaps <- function(inp, maxIter=1000, getPlsd=TRUE, getRep=TRUE, silent=TRUE, opt_fun='nlminb', opt_controls=list(), bounds=list(), tmb_smartsearch=TRUE){ # making sure inp is correct... diff --git a/R/simTrack.R b/R/simTrack.R index d92253b..6d11426 100644 --- a/R/simTrack.R +++ b/R/simTrack.R @@ -13,7 +13,7 @@ #' @param start_pos Specify the starting position of the track with c(x0, y0) #' @param ss Simulations model for Speed of Sound - defaults to 'rw' = RW-model. #' -#' @return Dataframe containing a simulated track +#' @return `data.frame` containing a simulated track #' @export #' @example man/examples/example-yaps_sim.R simTrueTrack <- function(model='rw', n, deltaTime=1, D=NULL, shape=NULL, scale=NULL, addDielPattern=TRUE, ss='rw', start_pos=NULL){ @@ -78,7 +78,7 @@ simTrueTrack <- function(model='rw', n, deltaTime=1, D=NULL, shape=NULL, scale=N #' @param sbi_mean,sbi_sd Mean and SD of burst interval when pingType = 'sbi' #' @inheritParams getInp #' -#' @return Data frame containing time of ping and true positions +#' @return `data.frame` containing time of ping and true positions #' @export #' @example man/examples/example-yaps_sim.R simTelemetryTrack <- function(trueTrack, pingType, sbi_mean=NULL, sbi_sd=NULL, rbi_min=NULL, rbi_max=NULL){ @@ -110,8 +110,9 @@ simTelemetryTrack <- function(trueTrack, pingType, sbi_mean=NULL, sbi_sd=NULL, r #' #' @param auto If TRUE, attempts to find a decent array configuration to cover the simulated true track. #' @param trueTrack Track obtained from simTrueTrack(). -#' @return Dataframe containing X and Y for hydros +#' #' @export +#' @return `data.frame` containing X and Y for hydros #' @example man/examples/example-yaps_sim.R simHydros <- function(auto=TRUE, trueTrack=NULL){ try(if(auto == TRUE & is.null(trueTrack)) stop("When auto is TRUE, trueTrack needs to be supplied")) @@ -138,8 +139,9 @@ simHydros <- function(auto=TRUE, trueTrack=NULL){ #' @param pMP Probability of multipath propagated signal 0-1 #' @param tempRes Temporal resolution of the hydrophone. PPM systems are typially 1/1000 sec. Other systems are as high as 1/19200 sec. #' @inheritParams getInp -#' @return List containing TOA matrix (toa) and matrix indicating, which obs are multipath (mp_mat) +#' #' @export +#' @return List containing TOA matrix (toa) and matrix indicating, which obs are multipath (mp_mat) #' @example man/examples/example-yaps_sim.R simToa <- function(telemetryTrack, hydros, pingType, sigmaToa, pNA, pMP, tempRes=NA){ #correct toa diff --git a/R/syncGetters.R b/R/syncGetters.R index acfb232..cf701e4 100644 --- a/R/syncGetters.R +++ b/R/syncGetters.R @@ -1,172 +1,3 @@ -#' Get sync model from inp_sync object obtained by getInpSync() -#' @param inp_sync Input data prepared for the sync model using `getInpSync()` -#' @param silent Keep TMB quiet -#' @param fine_tune Logical. Whether to re-run the sync model excluding residual outliers. Consider to use fineTuneSyncModel() instead. -#' @param max_iter Max number of iterations to run TMB. Default=100 seems to work in most cases. -#' @param tmb_smartsearch Logical whether to use the TMB smartsearch in the inner optimizer (see ?TMB::MakeADFun for info). Default and original implementation is TRUE. However, there seems to be an issue with Matrix v1.3.2 that requires tmb_smartsearch=FALSE. -#' @example man/examples/example-yaps_ssu1.R - -#' @export -getSyncModel <- function(inp_sync, silent=TRUE, fine_tune=FALSE, max_iter=100, tmb_smartsearch=TRUE){ - inp_sync$inp_params$tmb_smartsearch <- tmb_smartsearch - inp_sync$inp_params$max_iter <- max_iter - - dat_tmb <- inp_sync$dat_tmb_sync - params <- inp_sync$params_tmb_sync - random <- inp_sync$random_tmb_sync - inits <- inp_sync$inits_tmb_sync - inp_params <- inp_sync$inp_params - - cat(paste0(Sys.time(), " \n")) - cat(". Running optimization of the sync model. Please be patient - this can take a long time. \n") - if(fine_tune){cat(".... fine tuning is enabled, but is getting deprecated in this function. Consider to use the function fineTuneSyncModel() instead. See ?fineTuneSyncModel for info. \n")} - - tictoc::tic("Fitting sync model: ") - opt <- c() - pl <- c() - plsd <- c() - obj <- c() - - tictoc::tic() - obj <- c() - opt <- c() - report <- c() - gc() - - # config(DLL="yaps_sync") - # ## Reduce memory peak of a parallel model by creating tapes in serial - # config(tape.parallel=0, DLL="yaps_sync") - obj <- TMB::MakeADFun(data = dat_tmb, parameters = params, random = random, DLL = "yaps", inner.control = list(maxit = max_iter), silent=silent) - obj$fn(obj$par) - - if(!tmb_smartsearch){ - TMB::newtonOption(obj, smartsearch=FALSE) - } - - - if(silent){ - # opt <- suppressWarnings(stats::nlminb(inits,obj$fn,obj$gr)) - opt <- suppressWarnings(stats::nlminb(inits,obj$fn,obj$gr, lower=c(-10), upper=c(-2))) - } else { - opt <- stats::nlminb(inits,obj$fn,obj$gr, lower=c(-10), upper=c(-2)) - # opt <- stats::nlminb(inits,obj$fn,obj$gr) - } - - pl <- obj$env$parList() # List of estimates - obj_val <- opt$objective - cat(paste0(".. ", Sys.time()), " \n") - cat(".... obj = ", obj_val, " \n") - report <- obj$report() - - crazy_outliers <- which(abs(report$eps_toa)*1450 > 10000) - fine_outliers <- which(abs(report$eps_toa)*1450 > 1000) - if(length(crazy_outliers > 0)){ - cat(".... some extreme outliers potentially affecting the model where identified \n Consider to run fineTuneSyncModel(sync_model, eps_threshold=10000). See ?fineTuneSyncModel for more info. \n") - # dat_tmb$toa_offset[crazy_outliers] <- NA - } else if(fine_tune){ - cat(".... fine tuning is enabled, but is deprecated. Use the function fineTuneSyncModel() instead. See ?fineTuneSyncModel for info. \n") - # dat_tmb$toa_offset[fine_outliers] <- NA - } - - tictoc::toc() - - jointrep <- try(TMB::sdreport(obj, getJointPrecision=TRUE), silent=silent) - param_names <- rownames(summary(jointrep)) - sds <- summary(jointrep)[,2] - summ <- data.frame(param=param_names, sd=sds) - plsd <- split(summ[,2], f=summ$param) - - pl$TRUE_H[,1] <- pl$TRUE_H[,1] + inp_params$Hx0 - pl$TRUE_H[,2] <- pl$TRUE_H[,2] + inp_params$Hy0 - eps_long <- getEpsLong(report, pl, inp_sync) - - offset_nas <- which(pl$OFFSET == 0) - pl$OFFSET[offset_nas] <- NA - pl$SLOPE1[offset_nas] <- NA - pl$SLOPE2[offset_nas] <- NA - - cat("Sync model done \n") - cat("Consider saving the sync model for later use - e.g. save(sync_model, file='path_to_sync_save'). \n") - - return(list(pl=pl, plsd=plsd, report=report, obj_val=obj_val, eps_long=eps_long, inp_synced=inp_sync)) -} - - - - -#' Get object inp for synchronization -#' @param sync_dat List containing data.tables with hydrophone information and detections. See e.g. `?ssu1` for example -#' @param max_epo_diff Sets the upper threshold for differences in TOA of sync tags. Best parameter value depends on burst rate of sync tags and how far apart the internal clocks of the hydros are prior to synchronization. A bit less than half of minimum sync tag burst rate is a good starting choice. -#' @param min_hydros Sets the lower threshold of how many hydrophones need to detect each sync tag ping in order to be included in the sync process. Should be as high as possible while observing that all hydrosphones are contributing. If too low, isolated hydrophones risk falling out completely. Future versions will work towards automising this. -#' @param time_keeper_idx Index of the hydrophone to use as time keeper. Could e.g. be the one with smallest overall clock-drift. -#' @param fixed_hydros_idx Vector of hydro idx's for all hydrophones where the position is assumed to be known with adequate accuracy and precission. Include as many as possible as fixed hydros to reduce overall computation time and reduce overall variability. As a bare minimum two hydros need to be fixed, but we strongly advice to use more than two. -#' @param n_offset_day Specifies the number of hydrophone specific quadratic polynomials to use per day. For PPM based systems, 1 or 2 is often adeqaute. -#' @param n_ss_day Specifies number of speed of sound to estimate per day if no ss data is supplied. It is recommended to use logged water temperature instead. However, estimating SS gives an extra option for sanity-checking the final sync-model. -#' @param ss_data_what Indicates whether to estimate ("est") speed of sound or to use data based on logged water temperature ("data"). -#' @param ss_data data.table containing timestamp and speed of sound for the entire period to by synchronised. Must contain columns 'ts' (POSIXct timestamp) and 'ss' speed of sound in m/s (typical values range 1400 - 1550). -#' @param keep_rate Syncing large data sets can take a really long time. However, there is typically an excess number of sync tag detections -#' and a sub-sample is typically enough for good synchronization. -#' This parameter EITHER specifies a proportion (0-1) of data to keep when sub-sampling -#' OR (if keep_rate > 10) number of pings (approximate) to keep in each hydro X offset_idx combination if enough exists. -#' @param excl_self_detect Logical whether to excluded detections of sync tags on the hydros they are co-located with. Sometimes self detections can introduce excessive residuals in the sync model in which case they should be excluded. -#' @param lin_corr_coeffs Matrix of coefficients used for pre-sync linear correction. dim(lin_corr_coeffs)=(#hydros, 2). -#' @param silent_check Logical whether to get output from checkInpSync(). Default is FALSE -#' @example man/examples/example-yaps_ssu1.R -#' @export -getInpSync <- function(sync_dat, max_epo_diff, min_hydros, time_keeper_idx, fixed_hydros_idx, n_offset_day, n_ss_day, keep_rate=1, excl_self_detect=TRUE, lin_corr_coeffs=NA, ss_data_what="est", ss_data=c(0), silent_check=FALSE){ - if(length(unique(sync_dat$hydros$serial)) != nrow(sync_dat$hydros)){ - print(sync_dat$hydros[, .N, by=serial][N>=2]) - stop("ERROR: At least one hydrophone serial number is used more than once in sync_dat$hydros!\n") - } - - if(keep_rate <=0 | (keep_rate > 1 & keep_rate < 10) | (keep_rate >= 10 & keep_rate %% 1 != 0)){ - stop("ERROR: Invalid keep_rate! Must be either ]0;1] or integer >= 10\n") - } - - sync_dat <- appendDetections(sync_dat) - - if(is.na(lin_corr_coeffs[1])){ - lin_corr_coeffs <- matrix(0, nrow=nrow(sync_dat$hydros), ncol=2, byrow=TRUE) - } - - sync_dat <- applyLinCorCoeffsInpSync(sync_dat, lin_corr_coeffs) - - T0 <- min(sync_dat$detections$epo) - - inp_H_info <- getInpSyncHInfo(sync_dat) - - inp_toa_list_all <- getInpSyncToaList(sync_dat, max_epo_diff, min_hydros, excl_self_detect) - fixed_hydros_vec <- getFixedHydrosVec(sync_dat, fixed_hydros_idx) - offset_vals_all <- getOffsetVals(inp_toa_list_all, n_offset_day) - inp_toa_list <- getDownsampledToaList(inp_toa_list_all, offset_vals_all, keep_rate) - offset_vals <- getOffsetVals(inp_toa_list, n_offset_day) - ss_vals <- getSsVals(inp_toa_list, n_ss_day) - if(ss_data_what == "data"){ - ss_data_vec <- getSsDataVec(inp_toa_list, ss_data) - } else { - ss_data_vec <- c(0) - } - - dat_tmb_sync <- getDatTmbSync(sync_dat, time_keeper_idx, inp_toa_list, fixed_hydros_vec, offset_vals, ss_vals, inp_H_info, T0, ss_data_what, ss_data_vec) - params_tmb_sync <- getParamsTmbSync(dat_tmb_sync, ss_data_what) - if(ss_data_what == "est"){ - random_tmb_sync <- c("TOP", "OFFSET", "SLOPE1", "SLOPE2", "SS", "TRUE_H") - } else { - random_tmb_sync <- c("TOP", "OFFSET", "SLOPE1", "SLOPE2", "TRUE_H") - } - # inits_tmb_sync <- c(3, rep(-3,dat_tmb_sync$nh)) - inits_tmb_sync <- c(-3) - inp_params <- list(toa=inp_toa_list$toa, T0=T0, Hx0=inp_H_info$Hx0, Hy0=inp_H_info$Hy0, offset_levels=offset_vals$offset_levels, - ss_levels=ss_vals$ss_levels, max_epo_diff=max_epo_diff, hydros=sync_dat$hydros, - lin_corr_coeffs=lin_corr_coeffs, min_hydros=min_hydros, ss_data=ss_data - ) - - inp_sync <- list(dat_tmb_sync=dat_tmb_sync, params_tmb_sync=params_tmb_sync, random_tmb_sync=random_tmb_sync, inits_tmb_sync=inits_tmb_sync, inp_params=inp_params) - inp_sync$inp_params$sync_coverage <- checkInpSync(inp_sync, silent_check) - return(inp_sync) - -} - #' Internal function. Extract speed of sounds for each timestamp used in sync-process from supplied data. #' @inheritParams getInpSync #' @noRd diff --git a/R/syncPlotters.R b/R/syncPlotters.R index c09494a..8a0cf03 100644 --- a/R/syncPlotters.R +++ b/R/syncPlotters.R @@ -2,8 +2,9 @@ #' #' @param sync_model Synchronization model obtained using `getSyncModel()` #' @param by What to facet/group the plot by? Currently supports one of 'overall', 'sync_tag', 'hydro', 'quantiles', 'temporal', 'temporal_hydro', 'temporal_sync_tag' -#' @example man/examples/example-syncModelPlots.R #' @export +#' @return No return value, called to plot graphics. +#' @example man/examples/example-syncModelPlots.R plotSyncModelResids <- function(sync_model, by='overall'){ eps_long <- sync_model$eps_long if(by == 'overall'){ @@ -55,6 +56,7 @@ plotSyncModelResids <- function(sync_model, by='overall'){ #' Plot hydrophone positions. Especially useful if some hydro re-positioned as part of the sync model. #' @param sync_model Synchronization model obtained using `getSyncModel()` #' @export +#' @return No return value, called to plot graphics. #' @example man/examples/example-syncModelPlots.R plotSyncModelHydros <- function(sync_model){ z_synced <- NULL @@ -90,6 +92,7 @@ plotSyncModelHydros <- function(sync_model){ #' @param sync_model Synchronization model obtained using `getSyncModel()` #' @param by What to facet/group the plot by? Currently supports one of 'sync_bin_sync', 'sync_bin_hydro', 'sync_bin_sync_smooth', 'sync_bin_hydro_smooth', 'hydro', 'sync_tag' #' @export +#' @return No return value, called to plot graphics. #' @example man/examples/example-syncModelPlots.R plotSyncModelCheck <- function(sync_model, by=""){ sync_check_dat <- getSyncCheckDat(sync_model) diff --git a/R/tempToSs.R b/R/tempToSs.R index 9f18e1e..d820ab5 100644 --- a/R/tempToSs.R +++ b/R/tempToSs.R @@ -4,6 +4,7 @@ #' @param sal Water slinity in parts per thousand (promille) #' @param depth Depth in meters - default = 5 m - can typically be ignored #' @export +#' @return Vector of estimated speed of sound in water. #' @examples #' water_temp <- rnorm(100, 20, 2) #' ss <- tempToSs(temp=water_temp, sal=0, depth=5) diff --git a/R/testYaps.R b/R/testYaps.R index 780158b..e910b3f 100644 --- a/R/testYaps.R +++ b/R/testYaps.R @@ -8,22 +8,18 @@ #' @inheritParams getInp #' @inheritParams runYaps #' @export +#' @return If `return_yaps == TRUE`, the fitted `yaps` object. See `?runYaps` for further info. + #' @examples -#' \dontrun{ -#' # To test basic functionality of yaps using simulated data +#' #' # To test basic functionality of yaps using simulated data #' testYaps() #' # # # Three pingTypes are availabe: -#' # # # fixed burst interval ('sbi'), -#' # # # random burst interval with UNKNOWN burst interval sequence('rbi'), -#' # # # random burst interval with KNOWN burst interval sequence ('pbi') -#' testYaps(pingType='sbi') -#' testYaps(pingType='rbi') -#' testYaps(pingType='pbi') -#' } +#' # # # fixed burst interval (testYaps(pingType='sbi')), +#' # # # random burst interval with UNKNOWN burst interval sequence('testYaps(pingType='rbi')), +#' # # # random burst interval with KNOWN burst interval sequence (testYaps(pingType='pbi')) testYaps <- function(silent=TRUE, pingType='sbi', est_ss=TRUE, opt_fun='nlminb', opt_controls=list(), bounds=list(), return_yaps=FALSE, tmb_smartsearch=TRUE){ set.seed(42) trueTrack <- simTrueTrack(model='crw', n = 2000, deltaTime=1, shape=1, scale=0.5, addDielPattern=TRUE, ss='rw') - # pingType <- 'sbi' if(pingType == 'sbi'){ sbi_mean <- 20; sbi_sd <- 1e-3; rbi_min <- sbi_mean; @@ -52,14 +48,11 @@ testYaps <- function(silent=TRUE, pingType='sbi', est_ss=TRUE, opt_fun='nlminb', ss_data <- teleTrack$ss } inp <- getInp(hydros, toa, E_dist="Mixture", n_ss=5, pingType=pingType, sdInits=0, ss_data_what=ss_data_what, ss_data=ss_data, rbi_min=rbi_min, rbi_max=rbi_max, biTable=biTable) - # print(str(inp)) maxIter <- 500 - # suppressWarnings(outTmb <- runTmb(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE, x.tol=1E-3)) - outTmb <- runTmb(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE, silent=silent, opt_fun=opt_fun, opt_controls, bounds, tmb_smartsearch) - # print(str(outTmb)) - pl <- outTmb$pl + yaps <- runYaps(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE, silent=silent, opt_fun=opt_fun, opt_controls, bounds, tmb_smartsearch) + pl <- yaps$pl yaps_out <- data.table::data.table(X=pl$X + inp$inp_params$Hx0, Y=pl$Y + inp$inp_params$Hy0) - plsd <- outTmb$plsd + plsd <- yaps$plsd plot(y~x, data=trueTrack, type="l", xlim=range(hydros$hx), ylim=range(hydros$hy), asp=1, lwd=2) lines(y~x, data=teleTrack) points(hy~hx, data=hydros, col="green", pch=20, cex=3) @@ -67,5 +60,5 @@ testYaps <- function(silent=TRUE, pingType='sbi', est_ss=TRUE, opt_fun='nlminb', if(!silent) {cat("You should now see a plot of a simulted track - if so YAPS core functions are working \n")} - if(return_yaps) {return(outTmb)} + if(return_yaps) {return(yaps)} } diff --git a/cran-comments.md b/cran-comments.md deleted file mode 100644 index 1b0aa68..0000000 --- a/cran-comments.md +++ /dev/null @@ -1,42 +0,0 @@ -## Comments - -* This is first submission of this package to CRAN. - -* The package contains compiled c++ code, hence it is not possible to bring down the installed package size. - -* win-builder mentions possibly mis-spelled words in DESCRIPTION. These are all author names. - -## Test environments -* Local Windows 10, R 4.0.3, R 4.1.0 (2021-01-20 r79850) -* Ubuntu 16.04 (travis), R 4.0.2 -* Ubuntu 20.04 (github action), R release, R devel -* Windows-latest (github action), R 3.6, R release, R devel -* macOS-latest (github action), R 3.6, R release -* win-builder (oldrelease, release, devel) - -## R CMD check results - -0 errors | 0 warnings | 2 notes - -checking CRAN incoming feasibility ... NOTE -Maintainer: 'Henrik Baktoft ' -New submission - -checking installed package size ... NOTE -installed size is 21.6Mb -sub-directories of 1Mb or more: -libs 19.6Mb - ---- - -On win-builder (oldrelease, release, devel): - -Possibly mis-spelled words in DESCRIPTION: - Baktoft (9:579, 9:729) - Corujo (9:774) - Gjelland (9:588, 9:738) - Rehage (9:756) - Rodemann (9:764) - Thygesen (9:607, 9:792) - Viadero (9:782) - Økland (9:598, 9:748) diff --git a/man/alignBurstSeq.Rd b/man/alignBurstSeq.Rd index 0a812a8..ef9dfd6 100644 --- a/man/alignBurstSeq.Rd +++ b/man/alignBurstSeq.Rd @@ -22,16 +22,17 @@ alignBurstSeq( \item{rbi_min, rbi_max}{Minimum and maximum burst interval of the transmitter. Used to identify sequence of consecutive pings in the data} -\item{plot_diag}{Logical indicating if visual diagnosis plots should be created. -return data.table like input, but with extra columns seq_ping_idx and seq_epo} +\item{plot_diag}{Logical indicating if visual diagnosis plots should be created.} +} +\value{ +\code{data.table} like the input \code{synced_dat}, but with extra columns seq_ping_idx and seq_epo } \description{ -Identifies where in the sequence of known burst intervals the detected data is from. +Identifies where in the sequence of known burst intervals the detected data is from. Add extra columns to data.table containing ping index of the burst sequence (seq_ping_idx) and expected time of ping (seq_epo). Only to be used for 'random' burst interval data when you know the burst sequence. } \examples{ -\dontrun{ # Align data from a tag with known random burst interval to the burst interval sequence # using the hald data included in `yapsdata` (see ?yapsdata::hald for info). synced_dat_1315 <- dat_align$synced_dat_1315 @@ -40,6 +41,4 @@ rbi_min <- 60 rbi_max <- 120 aligned_dat <- alignBurstSeq(synced_dat=synced_dat_1315, burst_seq=seq_1315, rbi_min=rbi_min, rbi_max=rbi_max, plot_diag=TRUE) - -} } diff --git a/man/applySync.Rd b/man/applySync.Rd index 32c3698..3142574 100644 --- a/man/applySync.Rd +++ b/man/applySync.Rd @@ -7,17 +7,20 @@ applySync(toa, hydros = "", sync_model) } \arguments{ -\item{toa}{Object containing data to be synchronized. Typically a `data.table` as e.g. `ssu1$detections`, but can also be a matrix dim=(n_ping, n_hydo).} +\item{toa}{Object containing data to be synchronized. Typically a \code{data.table} as e.g. \code{ssu1$detections}, but can also be a matrix dim=(n_ping, n_hydo).} -\item{hydros}{data.table formatted as `ssu1$hydros`} +\item{hydros}{data.table formatted as \code{ssu1$hydros}} -\item{sync_model}{Synchronization model obtained using `getSyncModel()`} +\item{sync_model}{Synchronization model obtained using \code{getSyncModel()}} +} +\value{ +A \code{data.table} with the now synchronized time-of-arrivals in column \code{eposync}. } \description{ Apply sync model to toa matrix to obtain synced data } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -45,8 +48,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -56,11 +58,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -72,7 +74,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -83,6 +86,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -102,6 +107,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/checkInp.Rd b/man/checkInp.Rd index 2af1a30..1cb1151 100644 --- a/man/checkInp.Rd +++ b/man/checkInp.Rd @@ -2,18 +2,21 @@ % Please edit documentation in R/checkInp.R \name{checkInp} \alias{checkInp} -\title{Check consistency of `inp` object obtained from `getInp()`} +\title{Check consistency of \code{inp} object obtained from \code{getInp()}} \usage{ checkInp(inp) } \arguments{ -\item{inp}{Object obtained using `getInp()`} +\item{inp}{Object obtained using \code{getInp()}} +} +\value{ +No return value, but prints errors/warnings if issues with \code{inp} is detected. } \description{ -Check consistency of `inp` object obtained from `getInp()` +Check consistency of \code{inp} object obtained from \code{getInp()} } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -41,8 +44,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -52,11 +54,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -68,7 +70,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -79,6 +82,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -98,6 +103,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/checkInpSync.Rd b/man/checkInpSync.Rd index fbbc5bd..e9b74d4 100644 --- a/man/checkInpSync.Rd +++ b/man/checkInpSync.Rd @@ -2,20 +2,23 @@ % Please edit documentation in R/checkInpSync.R \name{checkInpSync} \alias{checkInpSync} -\title{Check consistency of `inp_sync` object obtained from `getInpSync()`} +\title{Check consistency of \code{inp_sync} object obtained from \code{getInpSync()}} \usage{ checkInpSync(inp_sync, silent_check) } \arguments{ -\item{inp_sync}{Object obtained using `getInpSync()`} +\item{inp_sync}{Object obtained using \code{getInpSync()}} -\item{silent_check}{Logical whether to get output from checkInpSync(). Default is FALSE} +\item{silent_check}{Logical whether to get output from \code{checkInpSync()}. Default is FALSE} +} +\value{ +No return value, but prints errors/warnings if issues with \code{inp_sync} is detected. } \description{ -Check consistency of `inp_sync` object obtained from `getInpSync()` +Check consistency of \code{inp_sync} object obtained from \code{getInpSync()} } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -43,8 +46,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -54,11 +56,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -70,7 +72,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -81,6 +84,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -100,6 +105,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/dat_align.Rd b/man/dat_align.Rd index 9508166..f4a616c 100644 --- a/man/dat_align.Rd +++ b/man/dat_align.Rd @@ -7,12 +7,12 @@ \format{ A list containing 2 items: \describe{ - \item{synced_dat_1315}{ - data.table containing synced detections of tag 1315. - } - \item{synced_dat_1315}{ - vector of small part of the complete sequence of known random BIs. - } +\item{synced_dat_1315}{ +data.table containing synced detections of tag 1315. +} +\item{synced_dat_1315}{ +vector of small part of the complete sequence of known random BIs. +} } } \usage{ @@ -21,6 +21,6 @@ dat_align \description{ Function alignBurstSeq() is used to align synced detection data with a sequence of known random burst intervals (BI). \cr This step is needed to take advantage of the extra information available when working with random BI data with a known sequence. \cr -This small sample is obtained from the accompanying data package `yapsdata`. +This small sample is obtained from the accompanying data package \code{yapsdata}. } \keyword{datasets} diff --git a/man/examples/example-alignBurstSeq.R b/man/examples/example-alignBurstSeq.R index b1e94bf..4eda6c8 100644 --- a/man/examples/example-alignBurstSeq.R +++ b/man/examples/example-alignBurstSeq.R @@ -1,4 +1,3 @@ -\dontrun{ # Align data from a tag with known random burst interval to the burst interval sequence # using the hald data included in `yapsdata` (see ?yapsdata::hald for info). synced_dat_1315 <- dat_align$synced_dat_1315 @@ -7,5 +6,3 @@ rbi_min <- 60 rbi_max <- 120 aligned_dat <- alignBurstSeq(synced_dat=synced_dat_1315, burst_seq=seq_1315, rbi_min=rbi_min, rbi_max=rbi_max, plot_diag=TRUE) - -} \ No newline at end of file diff --git a/man/examples/example-bbox.R b/man/examples/example-bbox.R index cb81f58..1bfefcc 100644 --- a/man/examples/example-bbox.R +++ b/man/examples/example-bbox.R @@ -1,6 +1,4 @@ -\dontrun{ hydros <- ssu1$hydros colnames(hydros) <- c('serial','hx','hy','hz','sync_tag','idx') bbox <- getBbox(hydros) plotBbox(hydros, bbox) -} \ No newline at end of file diff --git a/man/examples/example-syncModelPlots.R b/man/examples/example-syncModelPlots.R index fb8f79f..f5a3a20 100644 --- a/man/examples/example-syncModelPlots.R +++ b/man/examples/example-syncModelPlots.R @@ -1,4 +1,4 @@ -\dontrun{ +\donttest{ sync_model <- ssu1$sync_model plotSyncModelHydros(sync_model) @@ -15,8 +15,4 @@ plotSyncModelCheck(sync_model, by = "hydro") plotSyncModelCheck(sync_model, by = "sync_tag") plotSyncModelCheck(sync_model, by = "sync_bin_sync") plotSyncModelCheck(sync_model, by = "sync_bin_hydro") -# # # if more sync periods are used, these two can be applied -# plotSyncModelCheck(sync_model, by = "sync_bin_sync_smooth") -# plotSyncModelCheck(sync_model, by = "sync_bin_hydro_smooth") - -} \ No newline at end of file +} diff --git a/man/examples/example-yaps_sim.R b/man/examples/example-yaps_sim.R index 2e4c505..ea30e32 100644 --- a/man/examples/example-yaps_sim.R +++ b/man/examples/example-yaps_sim.R @@ -1,4 +1,4 @@ -\dontrun{ +\donttest{ library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds @@ -38,7 +38,7 @@ if(pingType == 'sbi'){ pl <- c() maxIter <- ifelse(pingType=="sbi", 500, 5000) -outTmb <- runTmb(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) +outTmb <- runYaps(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) # Estimates in pl pl <- outTmb$pl @@ -55,5 +55,4 @@ plot(y~x, data=trueTrack, type="l", xlim=range(hydros$hx), ylim=range(hydros$hy) lines(y~x, data=teleTrack) points(hy~hx, data=hydros, col="green", pch=20, cex=3) lines(pl$Y~pl$X, col="red") - } \ No newline at end of file diff --git a/man/examples/example-yaps_ssu1.R b/man/examples/example-yaps_ssu1.R index 5e50bf1..7a42e5d 100644 --- a/man/examples/example-yaps_ssu1.R +++ b/man/examples/example-yaps_ssu1.R @@ -1,4 +1,4 @@ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -26,8 +26,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -37,11 +36,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -53,7 +52,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -64,6 +64,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -83,5 +85,5 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } \ No newline at end of file diff --git a/man/fineTuneSyncModel.Rd b/man/fineTuneSyncModel.Rd index b7870c1..e898ab8 100644 --- a/man/fineTuneSyncModel.Rd +++ b/man/fineTuneSyncModel.Rd @@ -14,12 +14,15 @@ fineTuneSyncModel(sync_model, eps_threshold, silent = TRUE) \item{silent}{logical whether to make getSyncModel() silent} } +\value{ +Fine tuned \code{sync_model}. See \code{?getSyncModel} for more info. +} \description{ Fine-tune an already fitted sync_model Wrapper function to re-run getSyncModel() using the same data, but excluding outliers. Note dimensions of data might change if eps_threshold results in empty rows in the TOA-matrix. } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -47,8 +50,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -58,11 +60,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -74,7 +76,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -85,93 +88,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps -par(mfrow=c(2,2)) -plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") -lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) -lines(y~x, data=yaps_out$track, col="red") - -plot(utm_x~ts, data=ssu1$gps, col="blue", type="l", lwd=2) -points(x~top, data=yaps_out$track, col="red") -lines(x~top, data=yaps_out$track, col="red") -lines(x-2*x_sd~top, data=yaps_out$track, col="red", lty=2) -lines(x+2*x_sd~top, data=yaps_out$track, col="red", lty=2) - -plot(utm_y~ts, data=ssu1$gps, col="blue", type="l", lwd=2) -points(y~top, data=yaps_out$track, col="red") -lines(y~top, data=yaps_out$track, col="red") -lines(y-2*y_sd~top, data=yaps_out$track, col="red", lty=2) -lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) - -plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") -lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) -} -\dontrun{ -library(yaps) -set.seed(42) - -# # # Example using the ssu1 data included in package. See ?ssu1 for info. -# # # Set parameters to use in the sync model - these will differ per study -max_epo_diff <- 120 -min_hydros <- 2 -time_keeper_idx <- 5 -fixed_hydros_idx <- c(2:3, 6, 8, 11, 13:17) -n_offset_day <- 2 -n_ss_day <- 2 -keep_rate <- 15 - -# # # Get input data ready for getSyncModel() -inp_sync <- getInpSync(sync_dat=ssu1, max_epo_diff, min_hydros, time_keeper_idx, - fixed_hydros_idx, n_offset_day, n_ss_day, keep_rate=keep_rate, silent_check=TRUE) - -# # # Check that inp_sync is ok -checkInpSync(inp_sync, silent_check=FALSE) - -# # # Also take a look at coverage of the sync data -getSyncCoverage(inp_sync, plot=TRUE) - -# # # Fit the sync model -sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) - -# # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) - -# # # Visualize the resulting sync model -plotSyncModelResids(sync_model, by = "overall") -plotSyncModelResids(sync_model, by = "quantiles") -plotSyncModelResids(sync_model, by = "sync_tag") -plotSyncModelResids(sync_model, by = "hydro") -plotSyncModelResids(sync_model, by = "temporal_hydro") -plotSyncModelResids(sync_model, by = "temporal_sync_tag") - -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) - -# # # Apply the sync_model to detections data. -detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) - -# # # Prepare data for running yaps -hydros_yaps <- data.table::data.table(sync_model$pl$TRUE_H) -colnames(hydros_yaps) <- c('hx','hy','hz') -focal_tag <- 15266 -rbi_min <- 20 -rbi_max <- 40 -synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) -inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", - sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) - -# # # Check that inp is ok -checkInp(inp) - -# # # Run yaps on the prepared data to estimate track -yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) - -# # # Plot the results and compare to "the truth" obtained using gps +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -191,6 +109,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/getBbox.Rd b/man/getBbox.Rd index eb3a1a7..549d556 100644 --- a/man/getBbox.Rd +++ b/man/getBbox.Rd @@ -15,15 +15,15 @@ getBbox(hydros, buffer = 5, eps = 0.001, pen = 1) \item{pen}{Specifies the penalty multiplier.} } +\value{ +Vector of lenght 6: c(x_min, x_max, y_min, y_max, eps, pen). Limits are given in UTM coordinates. +} \description{ Standard is a rectangle based on coordinates of outer hydros +- the buffer in meters -Returns a vector of lenght 6: c(x_min, x_max, y_min, y_max, eps, pen). Limits are given in UTM coordinates. } \examples{ -\dontrun{ hydros <- ssu1$hydros colnames(hydros) <- c('serial','hx','hy','hz','sync_tag','idx') bbox <- getBbox(hydros) plotBbox(hydros, bbox) } -} diff --git a/man/getInp.Rd b/man/getInp.Rd index 417c979..987f207 100644 --- a/man/getInp.Rd +++ b/man/getInp.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/prepTmb.R +% Please edit documentation in R/getInp.R \name{getInp} \alias{getInp} \title{Get prepared inp-object for use in TMB-call} @@ -46,8 +46,99 @@ getInp( \item{bbox}{Spatial constraints in the form of a bounding box. See ?getBbox for details.} } \value{ -List of input data ready for use in TMB-call +List of input data ready for use in \code{runYaps()} } \description{ Wrapper-function to compile a list of input needed to run TMB } +\examples{ +\donttest{ +library(yaps) +set.seed(42) + +# # # Example using the ssu1 data included in package. See ?ssu1 for info. +# # # Set parameters to use in the sync model - these will differ per study +max_epo_diff <- 120 +min_hydros <- 2 +time_keeper_idx <- 5 +fixed_hydros_idx <- c(2:3, 6, 8, 11, 13:17) +n_offset_day <- 2 +n_ss_day <- 2 +keep_rate <- 15 + +# # # Get input data ready for getSyncModel() +inp_sync <- getInpSync(sync_dat=ssu1, max_epo_diff, min_hydros, time_keeper_idx, + fixed_hydros_idx, n_offset_day, n_ss_day, keep_rate=keep_rate, silent_check=TRUE) + +# # # Check that inp_sync is ok +checkInpSync(inp_sync, silent_check=FALSE) + +# # # Also take a look at coverage of the sync data +getSyncCoverage(inp_sync, plot=TRUE) + +# # # Fit the sync model +sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) + +# # # On some systems it might work better, if we disbale the smartsearch feature in TMB +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() + +# # # Visualize the resulting sync model +plotSyncModelResids(sync_model, by = "overall") +plotSyncModelResids(sync_model, by = "quantiles") +plotSyncModelResids(sync_model, by = "sync_tag") +plotSyncModelResids(sync_model, by = "hydro") +plotSyncModelResids(sync_model, by = "temporal_hydro") +plotSyncModelResids(sync_model, by = "temporal_sync_tag") + +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) + +# # # Apply the sync_model to detections data. +detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) + +# # # Prepare data for running yaps +hydros_yaps <- data.table::data.table(sync_model$pl$TRUE_H) +colnames(hydros_yaps) <- c('hx','hy','hz') +focal_tag <- 15266 +rbi_min <- 20 +rbi_max <- 40 +synced_dat <- detections_synced[tag == focal_tag] +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) +inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", + sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) + +# # # Check that inp is ok +checkInp(inp) + +# # # Run yaps on the prepared data to estimate track +yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) + +# # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) +par(mfrow=c(2,2)) +plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") +lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) +lines(y~x, data=yaps_out$track, col="red") + +plot(utm_x~ts, data=ssu1$gps, col="blue", type="l", lwd=2) +points(x~top, data=yaps_out$track, col="red") +lines(x~top, data=yaps_out$track, col="red") +lines(x-2*x_sd~top, data=yaps_out$track, col="red", lty=2) +lines(x+2*x_sd~top, data=yaps_out$track, col="red", lty=2) + +plot(utm_y~ts, data=ssu1$gps, col="blue", type="l", lwd=2) +points(y~top, data=yaps_out$track, col="red") +lines(y~top, data=yaps_out$track, col="red") +lines(y-2*y_sd~top, data=yaps_out$track, col="red", lty=2) +lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) + +plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") +lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) +par(oldpar) +} +} diff --git a/man/getInpSync.Rd b/man/getInpSync.Rd index a7a56a6..80a01fb 100644 --- a/man/getInpSync.Rd +++ b/man/getInpSync.Rd @@ -1,5 +1,5 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/syncGetters.R +% Please edit documentation in R/getInpSync.R \name{getInpSync} \alias{getInpSync} \title{Get object inp for synchronization} @@ -21,7 +21,7 @@ getInpSync( ) } \arguments{ -\item{sync_dat}{List containing data.tables with hydrophone information and detections. See e.g. `?ssu1` for example} +\item{sync_dat}{List containing data.tables with hydrophone information and detections. See e.g. \code{?ssu1} for example} \item{max_epo_diff}{Sets the upper threshold for differences in TOA of sync tags. Best parameter value depends on burst rate of sync tags and how far apart the internal clocks of the hydros are prior to synchronization. A bit less than half of minimum sync tag burst rate is a good starting choice.} @@ -35,26 +35,29 @@ getInpSync( \item{n_ss_day}{Specifies number of speed of sound to estimate per day if no ss data is supplied. It is recommended to use logged water temperature instead. However, estimating SS gives an extra option for sanity-checking the final sync-model.} -\item{keep_rate}{Syncing large data sets can take a really long time. However, there is typically an excess number of sync tag detections -and a sub-sample is typically enough for good synchronization. -This parameter EITHER specifies a proportion (0-1) of data to keep when sub-sampling +\item{keep_rate}{Syncing large data sets can take a really long time. However, there is typically an excess number of sync tag detections +and a sub-sample is typically enough for good synchronization. +This parameter EITHER specifies a proportion (0-1) of data to keep when sub-sampling OR (if keep_rate > 10) number of pings (approximate) to keep in each hydro X offset_idx combination if enough exists.} \item{excl_self_detect}{Logical whether to excluded detections of sync tags on the hydros they are co-located with. Sometimes self detections can introduce excessive residuals in the sync model in which case they should be excluded.} -\item{lin_corr_coeffs}{Matrix of coefficients used for pre-sync linear correction. dim(lin_corr_coeffs)=(#hydros, 2).} +\item{lin_corr_coeffs}{Matrix of coefficients used for pre-sync linear correction. \verb{dim(lin_corr_coeffs)=(#hydros, 2)}.} \item{ss_data_what}{Indicates whether to estimate ("est") speed of sound or to use data based on logged water temperature ("data").} \item{ss_data}{data.table containing timestamp and speed of sound for the entire period to by synchronised. Must contain columns 'ts' (POSIXct timestamp) and 'ss' speed of sound in m/s (typical values range 1400 - 1550).} -\item{silent_check}{Logical whether to get output from checkInpSync(). Default is FALSE} +\item{silent_check}{Logical whether to get output from \code{checkInpSync()}. Default is FALSE} +} +\value{ +List of input data ready for use in \code{getSyncModel()} } \description{ Get object inp for synchronization } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -82,8 +85,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -93,11 +95,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -109,7 +111,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -120,6 +123,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -139,6 +144,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/getSyncCoverage.Rd b/man/getSyncCoverage.Rd index 906604e..908a487 100644 --- a/man/getSyncCoverage.Rd +++ b/man/getSyncCoverage.Rd @@ -7,10 +7,104 @@ getSyncCoverage(inp_sync, plot = FALSE) } \arguments{ -\item{inp_sync}{Object obtained using `getInpSync()`} +\item{inp_sync}{Object obtained using \code{getInpSync()}} \item{plot}{Logical indicating whether to plot a visual or not.} } +\value{ +A data.table containing number of pings included in each hydro x offset combination. +} \description{ Quick overview to check if all hydros have enough data within each offset period. } +\examples{ +\donttest{ +library(yaps) +set.seed(42) + +# # # Example using the ssu1 data included in package. See ?ssu1 for info. +# # # Set parameters to use in the sync model - these will differ per study +max_epo_diff <- 120 +min_hydros <- 2 +time_keeper_idx <- 5 +fixed_hydros_idx <- c(2:3, 6, 8, 11, 13:17) +n_offset_day <- 2 +n_ss_day <- 2 +keep_rate <- 15 + +# # # Get input data ready for getSyncModel() +inp_sync <- getInpSync(sync_dat=ssu1, max_epo_diff, min_hydros, time_keeper_idx, + fixed_hydros_idx, n_offset_day, n_ss_day, keep_rate=keep_rate, silent_check=TRUE) + +# # # Check that inp_sync is ok +checkInpSync(inp_sync, silent_check=FALSE) + +# # # Also take a look at coverage of the sync data +getSyncCoverage(inp_sync, plot=TRUE) + +# # # Fit the sync model +sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) + +# # # On some systems it might work better, if we disbale the smartsearch feature in TMB +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() + +# # # Visualize the resulting sync model +plotSyncModelResids(sync_model, by = "overall") +plotSyncModelResids(sync_model, by = "quantiles") +plotSyncModelResids(sync_model, by = "sync_tag") +plotSyncModelResids(sync_model, by = "hydro") +plotSyncModelResids(sync_model, by = "temporal_hydro") +plotSyncModelResids(sync_model, by = "temporal_sync_tag") + +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) + +# # # Apply the sync_model to detections data. +detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) + +# # # Prepare data for running yaps +hydros_yaps <- data.table::data.table(sync_model$pl$TRUE_H) +colnames(hydros_yaps) <- c('hx','hy','hz') +focal_tag <- 15266 +rbi_min <- 20 +rbi_max <- 40 +synced_dat <- detections_synced[tag == focal_tag] +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) +inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", + sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) + +# # # Check that inp is ok +checkInp(inp) + +# # # Run yaps on the prepared data to estimate track +yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) + +# # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) +par(mfrow=c(2,2)) +plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") +lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) +lines(y~x, data=yaps_out$track, col="red") + +plot(utm_x~ts, data=ssu1$gps, col="blue", type="l", lwd=2) +points(x~top, data=yaps_out$track, col="red") +lines(x~top, data=yaps_out$track, col="red") +lines(x-2*x_sd~top, data=yaps_out$track, col="red", lty=2) +lines(x+2*x_sd~top, data=yaps_out$track, col="red", lty=2) + +plot(utm_y~ts, data=ssu1$gps, col="blue", type="l", lwd=2) +points(y~top, data=yaps_out$track, col="red") +lines(y~top, data=yaps_out$track, col="red") +lines(y-2*y_sd~top, data=yaps_out$track, col="red", lty=2) +lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) + +plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") +lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) +par(oldpar) +} +} diff --git a/man/getSyncModel.Rd b/man/getSyncModel.Rd index bc3eade..08c4c71 100644 --- a/man/getSyncModel.Rd +++ b/man/getSyncModel.Rd @@ -1,8 +1,8 @@ % Generated by roxygen2: do not edit by hand -% Please edit documentation in R/syncGetters.R +% Please edit documentation in R/getSyncModel.R \name{getSyncModel} \alias{getSyncModel} -\title{Get sync model from inp_sync object obtained by getInpSync()} +\title{Get sync model from inp_sync object obtained by \code{getInpSync()}} \usage{ getSyncModel( inp_sync, @@ -13,21 +13,24 @@ getSyncModel( ) } \arguments{ -\item{inp_sync}{Input data prepared for the sync model using `getInpSync()`} +\item{inp_sync}{Input data prepared for the sync model using \code{getInpSync()}} \item{silent}{Keep TMB quiet} -\item{fine_tune}{Logical. Whether to re-run the sync model excluding residual outliers. Consider to use fineTuneSyncModel() instead.} +\item{fine_tune}{Logical. Whether to re-run the sync model excluding residual outliers. \strong{Deprecated} use fineTuneSyncModel() instead.} \item{max_iter}{Max number of iterations to run TMB. Default=100 seems to work in most cases.} -\item{tmb_smartsearch}{Logical whether to use the TMB smartsearch in the inner optimizer (see ?TMB::MakeADFun for info). Default and original implementation is TRUE. However, there seems to be an issue with Matrix v1.3.2 that requires tmb_smartsearch=FALSE.} +\item{tmb_smartsearch}{Logical whether to use the TMB smartsearch in the inner optimizer (see \code{?TMB::MakeADFun} for info). Default and original implementation is TRUE. However, there seems to be an issue with some versions of \code{Matrix} that requires \code{tmb_smartsearch=FALSE}.} +} +\value{ +List containing relevant data constituting the \code{sync_model} ready for use in \code{fineTuneSyncModel()} if needed or in \code{applySync()} } \description{ -Get sync model from inp_sync object obtained by getInpSync() +Get sync model from inp_sync object obtained by \code{getInpSync()} } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -55,8 +58,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -66,11 +68,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -82,7 +84,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -93,6 +96,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -112,6 +117,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/getToaYaps.Rd b/man/getToaYaps.Rd index 6412397..b8a6d6f 100644 --- a/man/getToaYaps.Rd +++ b/man/getToaYaps.Rd @@ -7,7 +7,7 @@ getToaYaps(synced_dat, hydros, rbi_min, rbi_max, pingType = NULL) } \arguments{ -\item{synced_dat}{`data.table` containing synchronized data formatted as output from/or obtained using `applySync()`} +\item{synced_dat}{\code{data.table} containing synchronized data formatted as output from/or obtained using \code{applySync()}} \item{hydros}{Dataframe from simHydros() or Dataframe with columns hx and hy containing positions of the receivers. Translate the coordinates to get the grid centre close to (0;0).} @@ -17,11 +17,14 @@ getToaYaps(synced_dat, hydros, rbi_min, rbi_max, pingType = NULL) \item{pingType}{Type of transmitter to simulate - either stable burst interval ('sbi'), random burst interval ('rbi') or random burst interval but where the random sequence is known a priori} } +\value{ +Matrix of time-of-arrivals. One coloumn per hydro, one row per ping. +} \description{ Build TOA matrix from synced data.table - also do some pre-filtering of severe MP, pruning loose ends etc } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -49,8 +52,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -60,11 +62,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -76,7 +78,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -87,6 +90,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -106,6 +111,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/plotBbox.Rd b/man/plotBbox.Rd index 71c3f98..bdb01b5 100644 --- a/man/plotBbox.Rd +++ b/man/plotBbox.Rd @@ -11,14 +11,15 @@ plotBbox(hydros, bbox) \item{bbox}{Spatial constraints in the form of a bounding box. See ?getBbox for details.} } +\value{ +No return value, called to plot graphic. +} \description{ Graphical representation of spatial constraints } \examples{ -\dontrun{ hydros <- ssu1$hydros colnames(hydros) <- c('serial','hx','hy','hz','sync_tag','idx') bbox <- getBbox(hydros) plotBbox(hydros, bbox) } -} diff --git a/man/plotSyncModelCheck.Rd b/man/plotSyncModelCheck.Rd index 6ad776d..3e10c52 100644 --- a/man/plotSyncModelCheck.Rd +++ b/man/plotSyncModelCheck.Rd @@ -7,17 +7,20 @@ plotSyncModelCheck(sync_model, by = "") } \arguments{ -\item{sync_model}{Synchronization model obtained using `getSyncModel()`} +\item{sync_model}{Synchronization model obtained using \code{getSyncModel()}} \item{by}{What to facet/group the plot by? Currently supports one of 'sync_bin_sync', 'sync_bin_hydro', 'sync_bin_sync_smooth', 'sync_bin_hydro_smooth', 'hydro', 'sync_tag'} } +\value{ +No return value, called to plot graphics. +} \description{ -Delta values indicate absolute difference between true and estimated distances based on pairwise relative distances to sync_tag. +Delta values indicate absolute difference between true and estimated distances based on pairwise relative distances to sync_tag. For instance, a ping from sync_tag t colocated with hydro Ht is detected by hydros H1 and H2. The pairwise relative distance to sync tag is then delta = abs((true_dist(Ht, H1) - true_dist(Ht, H2)) - (est_dist(Ht, H1) - est_dist(Ht, H2))) } \examples{ -\dontrun{ +\donttest{ sync_model <- ssu1$sync_model plotSyncModelHydros(sync_model) @@ -34,9 +37,5 @@ plotSyncModelCheck(sync_model, by = "hydro") plotSyncModelCheck(sync_model, by = "sync_tag") plotSyncModelCheck(sync_model, by = "sync_bin_sync") plotSyncModelCheck(sync_model, by = "sync_bin_hydro") -# # # if more sync periods are used, these two can be applied -# plotSyncModelCheck(sync_model, by = "sync_bin_sync_smooth") -# plotSyncModelCheck(sync_model, by = "sync_bin_hydro_smooth") - } } diff --git a/man/plotSyncModelHydros.Rd b/man/plotSyncModelHydros.Rd index 6e8f4b0..ac82a54 100644 --- a/man/plotSyncModelHydros.Rd +++ b/man/plotSyncModelHydros.Rd @@ -7,13 +7,16 @@ plotSyncModelHydros(sync_model) } \arguments{ -\item{sync_model}{Synchronization model obtained using `getSyncModel()`} +\item{sync_model}{Synchronization model obtained using \code{getSyncModel()}} +} +\value{ +No return value, called to plot graphics. } \description{ Plot hydrophone positions. Especially useful if some hydro re-positioned as part of the sync model. } \examples{ -\dontrun{ +\donttest{ sync_model <- ssu1$sync_model plotSyncModelHydros(sync_model) @@ -30,9 +33,5 @@ plotSyncModelCheck(sync_model, by = "hydro") plotSyncModelCheck(sync_model, by = "sync_tag") plotSyncModelCheck(sync_model, by = "sync_bin_sync") plotSyncModelCheck(sync_model, by = "sync_bin_hydro") -# # # if more sync periods are used, these two can be applied -# plotSyncModelCheck(sync_model, by = "sync_bin_sync_smooth") -# plotSyncModelCheck(sync_model, by = "sync_bin_hydro_smooth") - } } diff --git a/man/plotSyncModelResids.Rd b/man/plotSyncModelResids.Rd index a7ede98..17f325c 100644 --- a/man/plotSyncModelResids.Rd +++ b/man/plotSyncModelResids.Rd @@ -7,15 +7,18 @@ plotSyncModelResids(sync_model, by = "overall") } \arguments{ -\item{sync_model}{Synchronization model obtained using `getSyncModel()`} +\item{sync_model}{Synchronization model obtained using \code{getSyncModel()}} \item{by}{What to facet/group the plot by? Currently supports one of 'overall', 'sync_tag', 'hydro', 'quantiles', 'temporal', 'temporal_hydro', 'temporal_sync_tag'} } +\value{ +No return value, called to plot graphics. +} \description{ Plot residuals of sync_model to enable check of model } \examples{ -\dontrun{ +\donttest{ sync_model <- ssu1$sync_model plotSyncModelHydros(sync_model) @@ -32,9 +35,5 @@ plotSyncModelCheck(sync_model, by = "hydro") plotSyncModelCheck(sync_model, by = "sync_tag") plotSyncModelCheck(sync_model, by = "sync_bin_sync") plotSyncModelCheck(sync_model, by = "sync_bin_hydro") -# # # if more sync periods are used, these two can be applied -# plotSyncModelCheck(sync_model, by = "sync_bin_sync_smooth") -# plotSyncModelCheck(sync_model, by = "sync_bin_hydro_smooth") - } } diff --git a/man/plotYaps.Rd b/man/plotYaps.Rd index d9e7c54..36382aa 100644 --- a/man/plotYaps.Rd +++ b/man/plotYaps.Rd @@ -15,6 +15,9 @@ plotYaps(yaps_out, type = "map", xlim = NULL, ylim = NULL, main = NULL) \item{main}{Title of plot - optional.} } +\value{ +No return value, called to plot graphics. +} \description{ Basic plots of yaps output } diff --git a/man/prepDetections.Rd b/man/prepDetections.Rd index b4b8cd4..6f5ecfa 100644 --- a/man/prepDetections.Rd +++ b/man/prepDetections.Rd @@ -11,11 +11,14 @@ prepDetections(raw_dat, type) \item{type}{Type of the vendor file. Currently only 'vemco_vue' is supported.} } +\value{ +\code{data.table} containing detections extracted from manufacturer data file. +} \description{ Experimental! Prepare detections data.table from raw data - csv-files exported from vendor software } \examples{ \dontrun{ -prepped_detections <- prepDetection("path-to-raw-data-file", type="vemco_vue") +prepped_detections <- prepDetections("path-to-raw-data-file", type="vemco_vue") } } diff --git a/man/runYaps.Rd b/man/runYaps.Rd index 7a56089..6d40a01 100644 --- a/man/runYaps.Rd +++ b/man/runYaps.Rd @@ -30,27 +30,43 @@ runTmb( ) } \arguments{ -\item{inp}{inp-object obtained from getInp()} +\item{inp}{inp-object obtained from \code{getInp()}} -\item{maxIter}{Sets inner.control(maxit) of the tmb-call. Increase if model is not converging.} +\item{maxIter}{Sets \code{inner.control(maxit)} of the TMB-call. Increase if model is not converging.} \item{getPlsd, getRep}{Whether or not to get sd estimates (plsd=TRUE) and reported values (getRep=TRUE).} \item{silent}{Logical whether to keep the optimization quiet.} -\item{opt_fun}{Which optimization function to use. Default is 'nlminb' - alternative is 'nloptr' (experimental!). If using 'nloptr', `opt_controls` must be specified.} +\item{opt_fun}{Which optimization function to use. Default is \code{opt_fun = 'nlminb'} - alternative is \code{opt_fun = 'nloptr'} (experimental!). If using nloptr, \code{opt_controls} must be specified.} -\item{opt_controls}{List of controls passed to optimization function. For instances, tolerances such as x.tol=1E-8. If opt_fun = 'nloptr', `opt_controls` must be a list formatted appropriately. For instance: opt_controls <- list(algorithm="NLOPT_LD_AUGLAG", xtol_abs=1e-12, maxeval=2E+4, print_level = 1, local_opts= list(algorithm="NLOPT_LD_AUGLAG_EQ", xtol_rel=1e-4) ). See `?nloptr` and the NLopt site https://nlopt.readthedocs.io/en/latest/ for more info. Some algorithms in `nloptr` require bounded parameters - see `bounds`.} +\item{opt_controls}{List of controls passed to optimization function. For instances, tolerances such as \code{x.tol=1E-8}. \cr +If \code{opt_fun = 'nloptr'}, \code{opt_controls} must be a list formatted appropriately. For instance: \cr +\code{opt_controls <- list( algorithm="NLOPT_LD_AUGLAG", xtol_abs=1e-12, maxeval=2E+4, print_level = 1, local_opts= list(algorithm="NLOPT_LD_AUGLAG_EQ", xtol_rel=1e-4) )}. \cr +See \code{?nloptr} and the NLopt site https://nlopt.readthedocs.io/en/latest/ for more info. Some algorithms in \code{nloptr} require bounded parameters - see \code{bounds}.} -\item{bounds}{List of two vectors specifying lower and upper bounds of fixed parameters. Length of each vector must be equal to number of fixed parameters. For instance, bounds = list(lb = c(-3, -1, -2), ub = c(2,0,1) ).} +\item{bounds}{List of two vectors specifying lower and upper bounds of fixed parameters. Length of each vector must be equal to number of fixed parameters. For instance, \code{bounds = list(lb = c(-3, -1, -2), ub = c(2,0,1) )}.} -\item{tmb_smartsearch}{Logical whether to use the TMB smartsearch in the inner optimizer (see ?TMB::MakeADFun for info). Default and original implementation is TRUE. However, there seems to be an issue with Matrix v1.3.2 that requires tmb_smartsearch=FALSE.} +\item{tmb_smartsearch}{Logical whether to use the TMB smartsearch in the inner optimizer (see \code{?TMB::MakeADFun} for info). Default and original implementation is TRUE. However, there seems to be an issue with recent versions of \code{Matrix} that requires \code{tmb_smartsearch=FALSE}.} +} +\value{ +List containing results of fitting \code{yaps} to the data. +\describe{ +\item{pl}{List containing all parameter estimates.} +\item{plsd}{List containing standard errors of parameter estimates.} +\item{rep}{List containing \code{mu_toa}.} +\item{obj}{Numeric obj value of the fitted model obtained using \code{obj$fn()}.} +\item{inp}{List containing the \code{inp} object used in \code{runYaps()}. See \code{?getInp} for further info.} +\item{conv_status}{Integer convergence status.} +\item{conv_message}{Text version of convergence status.} +\item{track}{A data.table containing the estimated track including time-of-ping (top), standard errors and number of hydros detecting each ping (nobs).} +} } \description{ Function to run TMB to estimate track } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) @@ -78,8 +94,7 @@ getSyncCoverage(inp_sync, plot=TRUE) sync_model <- getSyncModel(inp_sync, silent=TRUE, max_iter=200, tmb_smartsearch = TRUE) # # # On some systems it might work better, if we disbale the smartsearch feature in TMB -# sync_model_no_smartsearch <- getSyncModel(inp_sync, silent=TRUE, max_iter=5000, - # tmb_smartsearch = FALSE) +# # # To do so, set tmb_smartsearch = FALSE in getSyncModel() # # # Visualize the resulting sync model plotSyncModelResids(sync_model, by = "overall") @@ -89,11 +104,11 @@ plotSyncModelResids(sync_model, by = "hydro") plotSyncModelResids(sync_model, by = "temporal_hydro") plotSyncModelResids(sync_model, by = "temporal_sync_tag") -# # # If the above plots show outlier, sync_model can be fine tuned by excluding these. -# # # This should typically be done gradually as e.g. -# sync_model_f1 <- fineTuneSyncModel(sync_model, eps_threshold=1E4, silent=TRUE) -# sync_model_f2 <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) -# sync_model_f3 <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) +# # # If the above plots show outliers, sync_model can be fine tuned by excluding these. +# # # Use fineTuneSyncModel() for this. +# # # This should typically be done sequentially using eps_thresholds of e.g. 1E4, 1E3, 1E2, 1E2 +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E3, silent=TRUE) +sync_model <- fineTuneSyncModel(sync_model, eps_threshold=1E2, silent=TRUE) # # # Apply the sync_model to detections data. detections_synced <- applySync(toa=ssu1$detections, hydros=ssu1$hydros, sync_model) @@ -105,7 +120,8 @@ focal_tag <- 15266 rbi_min <- 20 rbi_max <- 40 synced_dat <- detections_synced[tag == focal_tag] -toa <- getToaYaps(synced_dat, hydros_yaps, rbi_min, rbi_max) +toa <- getToaYaps(synced_dat=synced_dat, hydros=hydros_yaps, pingType='rbi', + rbi_min=rbi_min, rbi_max=rbi_max) inp <- getInp(hydros_yaps, toa, E_dist="Mixture", n_ss=5, pingType="rbi", sdInits=1, rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what="est", ss_data=0) @@ -116,6 +132,8 @@ checkInp(inp) yaps_out <- runYaps(inp, silent=TRUE, tmb_smartsearch=TRUE, maxIter=500) # # # Plot the results and compare to "the truth" obtained using gps + +oldpar <- par(no.readonly = TRUE) par(mfrow=c(2,2)) plot(hy~hx, data=hydros_yaps, asp=1, xlab="UTM X", ylab="UTM Y", pch=20, col="green") lines(utm_y~utm_x, data=ssu1$gps, col="blue", lwd=2) @@ -135,6 +153,6 @@ lines(y+2*y_sd~top, data=yaps_out$track, col="red", lty=2) plot(nobs~top, data=yaps_out$track, type="p", main="#detecting hydros per ping") lines(caTools::runmean(nobs, k=10)~top, data=yaps_out$track, col="orange", lwd=2) - +par(oldpar) } } diff --git a/man/simHydros.Rd b/man/simHydros.Rd index 74e80f8..414c6cc 100644 --- a/man/simHydros.Rd +++ b/man/simHydros.Rd @@ -12,13 +12,13 @@ simHydros(auto = TRUE, trueTrack = NULL) \item{trueTrack}{Track obtained from simTrueTrack().} } \value{ -Dataframe containing X and Y for hydros +\code{data.frame} containing X and Y for hydros } \description{ Sim hydrophone array configuration } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds @@ -58,7 +58,7 @@ if(pingType == 'sbi'){ pl <- c() maxIter <- ifelse(pingType=="sbi", 500, 5000) -outTmb <- runTmb(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) +outTmb <- runYaps(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) # Estimates in pl pl <- outTmb$pl @@ -75,6 +75,5 @@ plot(y~x, data=trueTrack, type="l", xlim=range(hydros$hx), ylim=range(hydros$hy) lines(y~x, data=teleTrack) points(hy~hx, data=hydros, col="green", pch=20, cex=3) lines(pl$Y~pl$X, col="red") - } } diff --git a/man/simTelemetryTrack.Rd b/man/simTelemetryTrack.Rd index 7de0ed3..5bf958a 100644 --- a/man/simTelemetryTrack.Rd +++ b/man/simTelemetryTrack.Rd @@ -25,14 +25,14 @@ simTelemetryTrack( \item{rbi_max}{Minimum and maximum BI for random burst interval transmitters} } \value{ -Data frame containing time of ping and true positions +\code{data.frame} containing time of ping and true positions } \description{ Based on a known true track obtained using simTrueTrack, this function will give true positions at time-of-pings, which are also in the output. TOPs are determined by user-specified transmitter type. Number of pings are determined automatically based on track length and transmitter specifications. } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds @@ -72,7 +72,7 @@ if(pingType == 'sbi'){ pl <- c() maxIter <- ifelse(pingType=="sbi", 500, 5000) -outTmb <- runTmb(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) +outTmb <- runYaps(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) # Estimates in pl pl <- outTmb$pl @@ -89,6 +89,5 @@ plot(y~x, data=trueTrack, type="l", xlim=range(hydros$hx), ylim=range(hydros$hy) lines(y~x, data=teleTrack) points(hy~hx, data=hydros, col="green", pch=20, cex=3) lines(pl$Y~pl$X, col="red") - } } diff --git a/man/simToa.Rd b/man/simToa.Rd index 8ff08fe..35aefad 100644 --- a/man/simToa.Rd +++ b/man/simToa.Rd @@ -28,7 +28,7 @@ List containing TOA matrix (toa) and matrix indicating, which obs are multipath Provides the TOA matrix for the specified telemetryTrack. Probability of NA (pNA) and observation noise (sigmaToa) can be specified. } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds @@ -68,7 +68,7 @@ if(pingType == 'sbi'){ pl <- c() maxIter <- ifelse(pingType=="sbi", 500, 5000) -outTmb <- runTmb(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) +outTmb <- runYaps(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) # Estimates in pl pl <- outTmb$pl @@ -85,6 +85,5 @@ plot(y~x, data=trueTrack, type="l", xlim=range(hydros$hx), ylim=range(hydros$hy) lines(y~x, data=teleTrack) points(hy~hx, data=hydros, col="green", pch=20, cex=3) lines(pl$Y~pl$X, col="red") - } } diff --git a/man/simTrueTrack.Rd b/man/simTrueTrack.Rd index 54d22eb..f8ef63a 100644 --- a/man/simTrueTrack.Rd +++ b/man/simTrueTrack.Rd @@ -36,14 +36,14 @@ simTrueTrack( \item{start_pos}{Specify the starting position of the track with c(x0, y0)} } \value{ -Dataframe containing a simulated track +\code{data.frame} containing a simulated track } \description{ Produces a simulated regular time-spaced track following the specified movement model. Linear movement between consecutive observations is assumed. The output contains x, y, time and sound speed at each simulated position. } \examples{ -\dontrun{ +\donttest{ library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds @@ -83,7 +83,7 @@ if(pingType == 'sbi'){ pl <- c() maxIter <- ifelse(pingType=="sbi", 500, 5000) -outTmb <- runTmb(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) +outTmb <- runYaps(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE) # Estimates in pl pl <- outTmb$pl @@ -100,6 +100,5 @@ plot(y~x, data=trueTrack, type="l", xlim=range(hydros$hx), ylim=range(hydros$hy) lines(y~x, data=teleTrack) points(hy~hx, data=hydros, col="green", pch=20, cex=3) lines(pl$Y~pl$X, col="red") - } } diff --git a/man/ssu1.Rd b/man/ssu1.Rd index 4e6a159..b515ca9 100644 --- a/man/ssu1.Rd +++ b/man/ssu1.Rd @@ -7,29 +7,29 @@ \format{ A list containing 3 data.tables: \describe{ - \item{hydros}{ - \itemize{ - \item serial Hydrophone serial number. - \item x,y,z Position of hydrophones in UTM. - \item sync_tag ID of co-located sync tag. Must be identical to entries in data.table detections$tag. - \item idx Unique values from 1:nrow(hydros). - } - } - \item{detections}{ - \itemize{ - \item ts Timestamp of detection in POSIXct(). - \item tag ID of detected tag. - \item epo Timestamp as number of seconds since Unix epoch. Can be obtained using as.numeric(ts). - \item frac Sub-second part of detection timestamp in fractions of second [0-1]. - \item serial Serial number of detecting hydrophone. Must match entry in data.table hydros. - } - } - \item{gps}{ - \itemize{ - \item ts Timestamp of gps position in POSIXct(). - \item utm_x, utm_y Coordinates of position. Same projection and coordinate system as used in hydros. - } - } +\item{hydros}{ +\itemize{ +\item serial Hydrophone serial number. +\item x,y,z Position of hydrophones in UTM. +\item sync_tag ID of co-located sync tag. Must be identical to entries in data.table detections$tag. +\item idx Unique values from 1:nrow(hydros). +} +} +\item{detections}{ +\itemize{ +\item ts Timestamp of detection in POSIXct(). +\item tag ID of detected tag. +\item epo Timestamp as number of seconds since Unix epoch. Can be obtained using as.numeric(ts). +\item frac Sub-second part of detection timestamp in fractions of second (0-1). +\item serial Serial number of detecting hydrophone. Must match entry in data.table hydros. +} +} +\item{gps}{ +\itemize{ +\item ts Timestamp of gps position in POSIXct(). +\item utm_x, utm_y Coordinates of position. Same projection and coordinate system as used in hydros. +} +} } } \usage{ diff --git a/man/tempToSs.Rd b/man/tempToSs.Rd index 3b8be8d..e562f6c 100644 --- a/man/tempToSs.Rd +++ b/man/tempToSs.Rd @@ -14,6 +14,9 @@ tempToSs(temp, sal, depth = 5) \item{depth}{Depth in meters - default = 5 m - can typically be ignored} } +\value{ +Vector of estimated speed of sound in water. +} \description{ Calculate speed of sound from water temperature, salinity and depth Based on H. Medwin (1975) Speed of sound in water: A simple equation for realistic parameters. (https://doi.org/10.1121/1.380790) diff --git a/man/testYaps.Rd b/man/testYaps.Rd index 71542e4..14e33b2 100644 --- a/man/testYaps.Rd +++ b/man/testYaps.Rd @@ -22,30 +22,31 @@ testYaps( \item{est_ss}{Logical whether to test using ss_data_what = 'est' (est_ss = TRUE) or ss_data_what = 'data' (est_ss = FALSE)} -\item{opt_fun}{Which optimization function to use. Default is 'nlminb' - alternative is 'nloptr' (experimental!). If using 'nloptr', `opt_controls` must be specified.} +\item{opt_fun}{Which optimization function to use. Default is \code{opt_fun = 'nlminb'} - alternative is \code{opt_fun = 'nloptr'} (experimental!). If using nloptr, \code{opt_controls} must be specified.} -\item{opt_controls}{List of controls passed to optimization function. For instances, tolerances such as x.tol=1E-8. If opt_fun = 'nloptr', `opt_controls` must be a list formatted appropriately. For instance: opt_controls <- list(algorithm="NLOPT_LD_AUGLAG", xtol_abs=1e-12, maxeval=2E+4, print_level = 1, local_opts= list(algorithm="NLOPT_LD_AUGLAG_EQ", xtol_rel=1e-4) ). See `?nloptr` and the NLopt site https://nlopt.readthedocs.io/en/latest/ for more info. Some algorithms in `nloptr` require bounded parameters - see `bounds`.} +\item{opt_controls}{List of controls passed to optimization function. For instances, tolerances such as \code{x.tol=1E-8}. \cr +If \code{opt_fun = 'nloptr'}, \code{opt_controls} must be a list formatted appropriately. For instance: \cr +\code{opt_controls <- list( algorithm="NLOPT_LD_AUGLAG", xtol_abs=1e-12, maxeval=2E+4, print_level = 1, local_opts= list(algorithm="NLOPT_LD_AUGLAG_EQ", xtol_rel=1e-4) )}. \cr +See \code{?nloptr} and the NLopt site https://nlopt.readthedocs.io/en/latest/ for more info. Some algorithms in \code{nloptr} require bounded parameters - see \code{bounds}.} -\item{bounds}{List of two vectors specifying lower and upper bounds of fixed parameters. Length of each vector must be equal to number of fixed parameters. For instance, bounds = list(lb = c(-3, -1, -2), ub = c(2,0,1) ).} +\item{bounds}{List of two vectors specifying lower and upper bounds of fixed parameters. Length of each vector must be equal to number of fixed parameters. For instance, \code{bounds = list(lb = c(-3, -1, -2), ub = c(2,0,1) )}.} \item{return_yaps}{Logical whether to return the fitted yaps model. Default=FALSE.} -\item{tmb_smartsearch}{Logical whether to use the TMB smartsearch in the inner optimizer (see ?TMB::MakeADFun for info). Default and original implementation is TRUE. However, there seems to be an issue with Matrix v1.3.2 that requires tmb_smartsearch=FALSE.} +\item{tmb_smartsearch}{Logical whether to use the TMB smartsearch in the inner optimizer (see \code{?TMB::MakeADFun} for info). Default and original implementation is TRUE. However, there seems to be an issue with recent versions of \code{Matrix} that requires \code{tmb_smartsearch=FALSE}.} +} +\value{ +If \code{return_yaps == TRUE}, the fitted \code{yaps} object. See \code{?runYaps} for further info. } \description{ -Run `testYaps()` to check that the core functions of YAPS is working correctly. +Run \code{testYaps()} to check that the core functions of YAPS is working correctly. Output should be a random simulated (black) and estimated (red) track. } \examples{ -\dontrun{ -# To test basic functionality of yaps using simulated data +#' # To test basic functionality of yaps using simulated data testYaps() # # # Three pingTypes are availabe: -# # # fixed burst interval ('sbi'), -# # # random burst interval with UNKNOWN burst interval sequence('rbi'), -# # # random burst interval with KNOWN burst interval sequence ('pbi') -testYaps(pingType='sbi') -testYaps(pingType='rbi') -testYaps(pingType='pbi') -} +# # # fixed burst interval (testYaps(pingType='sbi')), +# # # random burst interval with UNKNOWN burst interval sequence('testYaps(pingType='rbi')), +# # # random burst interval with KNOWN burst interval sequence (testYaps(pingType='pbi')) } diff --git a/tests/testthat/sync_model_f1_ref.RData b/tests/testthat/sync_model_f1_ref.RData index 49e434996fd5872a89532555a46a766414fba7d5..7931fcfae585a97886ac433715f928fa26b26f0c 100644 GIT binary patch delta 30510 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z8{k9j))ZJzYRN|MGj-l{9+yAe2J|e|IS}|9-+xW#sWCn~5U$AZ<*k6D^4CrxO>Hs(giIY45@h^JdiSPD-ahK@vfS*&pkF?Nv z_9c*xca@t%#zG3smzkeEcsmA{c^duMFp5eun#BUg#f<}v$!*h9J8Ltg#1i+l{ZDU=_m_?FVl$gbcYwYxJCJbN} zIg|W%Aq4pEeWjBjcpXS;6VWsBx)b|PQ;2SnSCq*cK=5`nvj{PZFl!uH+aNCb z5vOte^a@(O_0FEI4t+0l_gy~g&HiNz`*mve3*GFunaG=yhIk==wfFw6Yn+^!jobri z_4)3hpq*VGhM$XrQw+aT1breL@NIeY8=zc&fBxX-x84B#>0hsKyd}uPeuI#VRpI(m z&FoLb#Yx|vRk;7e!lqA#MY}Y!NV3*L)%VUhc6Zop=j^f8 z&dHS-KUuz*{yQC3ZIGMm8av0eo}SDf&P Date: Fri, 5 Feb 2021 00:45:55 +0100 Subject: [PATCH 6/9] reduce track length in example to run faster --- man/examples/example-yaps_sim.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/man/examples/example-yaps_sim.R b/man/examples/example-yaps_sim.R index ea30e32..6417631 100644 --- a/man/examples/example-yaps_sim.R +++ b/man/examples/example-yaps_sim.R @@ -2,7 +2,7 @@ library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds -trueTrack <- simTrueTrack(model='crw', n = 3000, deltaTime=1, shape=1, +trueTrack <- simTrueTrack(model='crw', n = 1000, deltaTime=1, shape=1, scale=0.5, addDielPattern=TRUE, ss='rw') # Simulate telemetry observations from true track. From e66da79f252faa17ab2e39ee4200b6660eabd460 Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Fri, 5 Feb 2021 01:04:59 +0100 Subject: [PATCH 7/9] reduce track length in example to run faster --- man/simHydros.Rd | 2 +- man/simTelemetryTrack.Rd | 2 +- man/simToa.Rd | 2 +- man/simTrueTrack.Rd | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/man/simHydros.Rd b/man/simHydros.Rd index 414c6cc..f774552 100644 --- a/man/simHydros.Rd +++ b/man/simHydros.Rd @@ -22,7 +22,7 @@ Sim hydrophone array configuration library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds -trueTrack <- simTrueTrack(model='crw', n = 3000, deltaTime=1, shape=1, +trueTrack <- simTrueTrack(model='crw', n = 1000, deltaTime=1, shape=1, scale=0.5, addDielPattern=TRUE, ss='rw') # Simulate telemetry observations from true track. diff --git a/man/simTelemetryTrack.Rd b/man/simTelemetryTrack.Rd index 5bf958a..b432243 100644 --- a/man/simTelemetryTrack.Rd +++ b/man/simTelemetryTrack.Rd @@ -36,7 +36,7 @@ Number of pings are determined automatically based on track length and transmitt library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds -trueTrack <- simTrueTrack(model='crw', n = 3000, deltaTime=1, shape=1, +trueTrack <- simTrueTrack(model='crw', n = 1000, deltaTime=1, shape=1, scale=0.5, addDielPattern=TRUE, ss='rw') # Simulate telemetry observations from true track. diff --git a/man/simToa.Rd b/man/simToa.Rd index 35aefad..ab08bbf 100644 --- a/man/simToa.Rd +++ b/man/simToa.Rd @@ -32,7 +32,7 @@ Provides the TOA matrix for the specified telemetryTrack. Probability of NA (pNA library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds -trueTrack <- simTrueTrack(model='crw', n = 3000, deltaTime=1, shape=1, +trueTrack <- simTrueTrack(model='crw', n = 1000, deltaTime=1, shape=1, scale=0.5, addDielPattern=TRUE, ss='rw') # Simulate telemetry observations from true track. diff --git a/man/simTrueTrack.Rd b/man/simTrueTrack.Rd index f8ef63a..a1870e4 100644 --- a/man/simTrueTrack.Rd +++ b/man/simTrueTrack.Rd @@ -47,7 +47,7 @@ The output contains x, y, time and sound speed at each simulated position. library(yaps) set.seed(42) # Simulate true track of animal movement of n seconds -trueTrack <- simTrueTrack(model='crw', n = 3000, deltaTime=1, shape=1, +trueTrack <- simTrueTrack(model='crw', n = 1000, deltaTime=1, shape=1, scale=0.5, addDielPattern=TRUE, ss='rw') # Simulate telemetry observations from true track. From f5b577b81bbdef0104153b29ecc7b936ddaba0fc Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Fri, 5 Feb 2021 08:27:21 +0100 Subject: [PATCH 8/9] bump version --- DESCRIPTION | 2 +- NEWS.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 40de558..6ac3895 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: yaps Title: Track Estimation using YAPS (Yet Another Positioning Solver) -Version: 1.2.3.9005 +Version: 1.2.4 Authors@R: c( person("Henrik", "Baktoft", email = "hba@aqua.dtu.dk", role = c("cre", "aut"), comment=c(ORCID = "0000-0002-3644-4960")), person("Karl", "Gjelland", role=c("aut"), comment=c(ORCID = "0000-0003-4036-4207")), person("Uffe H.", "Thygesen", role=c("aut"), comment=c(ORCID = "0000-0002-4311-6324")), diff --git a/NEWS.md b/NEWS.md index 7cf60f7..0294eec 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,4 @@ -# yaps v1.2.3.9005 +# yaps v1.2.4 ## New stuff * More checks in checkInp() to catch typical errors in format of inp. From db3439c6247ecb07f724d3cfa50a91372467f87b Mon Sep 17 00:00:00 2001 From: Henrik Baktoft Date: Wed, 10 Feb 2021 14:49:36 +0100 Subject: [PATCH 9/9] v1.2.4 - CRAN --- CRAN-RELEASE | 2 -- NEWS.md | 1 + README.Rmd | 4 +++- README.md | 9 ++++++--- 4 files changed, 10 insertions(+), 6 deletions(-) delete mode 100644 CRAN-RELEASE diff --git a/CRAN-RELEASE b/CRAN-RELEASE deleted file mode 100644 index 8275019..0000000 --- a/CRAN-RELEASE +++ /dev/null @@ -1,2 +0,0 @@ -This package was submitted to CRAN on 2021-01-28. -Once it is accepted, delete this file and tag the release (commit dfb10b1). diff --git a/NEWS.md b/NEWS.md index 0294eec..f21ca2c 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,6 +1,7 @@ # yaps v1.2.4 ## New stuff +* Now on CRAN * More checks in checkInp() to catch typical errors in format of inp. * EXPERIMENTAL Attempt to robustify runYaps() - use with care. diff --git a/README.Rmd b/README.Rmd index 410bd3f..2f74324 100644 --- a/README.Rmd +++ b/README.Rmd @@ -19,9 +19,11 @@ knitr::opts_chunk$set( ``` +[![CRAN Status Badge](https://www.r-pkg.org/badges/version/yaps)](https://cran.r-project.org/package=yaps) [![R-CMD-check](https://github.com/baktoft/yaps/workflows/R-CMD-check/badge.svg)](https://github.com/baktoft/yaps/actions) -[![Codecov test coverage](https://codecov.io/gh/baktoft/yaps/branch/master/graph/badge.svg)](https://codecov.io/gh/baktoft/yaps?branch=master) [![Travis build status](https://travis-ci.org/baktoft/yaps.svg?branch=master)](https://travis-ci.org/baktoft/yaps) +[![Codecov test coverage](https://codecov.io/gh/baktoft/yaps/branch/master/graph/badge.svg)](https://codecov.io/gh/baktoft/yaps?branch=master) +[![CRAN RStudio mirror downloads](https://cranlogs.r-pkg.org/badges/grand-total/yaps)](https://cran.r-project.org/package=yaps) diff --git a/README.md b/README.md index 5254254..c094508 100644 --- a/README.md +++ b/README.md @@ -2,12 +2,15 @@ +[![CRAN Status +Badge](https://www.r-pkg.org/badges/version/yaps)](https://cran.r-project.org/package=yaps) [![R-CMD-check](https://github.com/baktoft/yaps/workflows/R-CMD-check/badge.svg)](https://github.com/baktoft/yaps/actions) -[![Codecov test -coverage](https://codecov.io/gh/baktoft/yaps/branch/master/graph/badge.svg)](https://codecov.io/gh/baktoft/yaps?branch=master) [![Travis build status](https://travis-ci.org/baktoft/yaps.svg?branch=master)](https://travis-ci.org/baktoft/yaps) - +[![Codecov test +coverage](https://codecov.io/gh/baktoft/yaps/branch/master/graph/badge.svg)](https://codecov.io/gh/baktoft/yaps?branch=master) +[![CRAN RStudio mirror +downloads](https://cranlogs.r-pkg.org/badges/grand-total/yaps)](https://cran.r-project.org/package=yaps) # YAPS - (Yet Another Positioning Solver)