Merge pull request #25 from TanguyBarthelemy/develop

T --> TRUE and F --> FALSE

R/arima.R

@@ -150,7 +150,7 @@ arima_model<-function(name="arima", ar=1, delta=1, ma=1, variance=1){
  .jarray(as.numeric(model$ar)),
  .jarray(as.numeric(model$delta)),
  .jarray(as.numeric(model$ma)),
- as.numeric(model$var), F))
+ as.numeric(model$var), FALSE))
 }
 
 #' Sum ARIMA Models
@@ -236,7 +236,7 @@ arima_properties<-function(model, nspectrum=601, nacf=36){
 #' @export
 #'
 #' @examples
-ucarima_model<-function(model=NULL, components, complements=NULL, checkmodel=F){
+ucarima_model<-function(model=NULL, components, complements=NULL, checkmodel=FALSE){
  if (is.null(model))
  model<-arima_lsum(components)
  else if (! is(model, "JD3_ARIMA") && ! is(model, "JD3_SARIMA")) stop("Invalid model")

R/calendars.R

@@ -676,7 +676,7 @@ weighted_calendar<-function(calendars, weights){
 #' More information on calendar correction in JDemetra+ online documentation:
 #' \url{https://jdemetra-new-documentation.netlify.app/}
 #' @export
-national_calendar<-function(days, mean_correction=T){
+national_calendar<-function(days, mean_correction=TRUE){
  if (! is.list(days)) stop ('Days should be a list of holidays')
  return (structure(list(days=days, mean_correction=mean_correction), class=c('JD3_CALENDAR', 'JD3_CALENDARDEFINITION')))
 }
@@ -836,4 +836,3 @@ print.JD3_WEIGHTEDCALENDAR <- function (x, ...)
 
  return(invisible(x))
 }
-

R/display.R

@@ -131,7 +131,7 @@ print.summary.JD3_SARIMA_ESTIMATION<-function(x, digits = max(3L, getOption("dig
  stde<-sqrt(diag(cov))
  sel<-fr$type=='ESTIMATED'
  t<-fr$value[sel]/stde
- pval<-2*pt(abs(t), ndf, lower.tail = F)
+ pval<-2*pt(abs(t), ndf, lower.tail = FALSE)
  fr$stde[sel]<-stde
  fr$t[sel]<-t
  fr$pvalue[sel]<-pval
@@ -163,7 +163,7 @@ print.summary.JD3_SARIMA_ESTIMATION<-function(x, digits = max(3L, getOption("dig
  if (length(estimate) > 0){
  stde <- sqrt(diag(x$parameters$cov))
  t<-estimate/stde
- pval<-2*pt(abs(t), ndf, lower.tail = F)
+ pval<-2*pt(abs(t), ndf, lower.tail = FALSE)
  table <- data.frame(estimate, "ESTIMATED", stde, t, pval)
  colnames(table) <- c("Estimate", "Type", "Std. Error",
  "T-stat", "Pr(>|t|)")
@@ -313,7 +313,7 @@ print.JD3_SARIMA_ESTIMATE<-function(x, digits = max(3L, getOption("digits") - 3L
  sel<-xregs$type=='ESTIMATED'
  t<-xregs$value[sel]/stde
  ndf<-q$estimation$likelihood$neffectiveobs-q$estimation$likelihood$nparams+1
- pval<-2*pt(abs(t), ndf, lower.tail = F)
+ pval<-2*pt(abs(t), ndf, lower.tail = FALSE)
  xregs$stde[sel]<-stde
  xregs$t[sel]<-t
  xregs$pvalue[sel]<-pval
@@ -331,7 +331,7 @@ print.JD3_SARIMA_ESTIMATE<-function(x, digits = max(3L, getOption("digits") - 3L
  if (length(estimate) > 0){
  stde <- sqrt(diag(x$bvar))
  t<-estimate/stde
- pval<-2*pt(abs(t), ndf, lower.tail = F)
+ pval<-2*pt(abs(t), ndf, lower.tail = FALSE)
  table <- data.frame(estimate, "ESTIMATED", stde, t, pval)
  colnames(table) <- c("Estimate", "Type", "Std. Error",
  "T-stat", "Pr(>|t|)")

R/jd2r.R

@@ -151,5 +151,3 @@ NULL
  , as.integer(period), as.integer(start[1]), as.integer(start[2]), as.integer(n))
  return (jdom)
 }
-
-

R/modellingcontext.R

@@ -270,7 +270,7 @@ modelling_context<-function(calendars=NULL, variables=NULL){
  if (any(mts_var)) {
  # case of a simple mts dictionary
  for (i in which(mts_var)) {
- all_var <- lapply(1:ncol(variables[[i]]), function(j) {
+ all_var <- lapply(seq_len(ncol(variables[[i]])), function(j) {
  variables[[i]][, j]
  })
  names(all_var) <- colnames(variables[[i]])
@@ -383,5 +383,3 @@ modelling_context<-function(calendars=NULL, variables=NULL){
  p<-.r2p_context(r)
  return (.p2jd_context(p))
 }
-
-

R/procresults.R

@@ -6,7 +6,7 @@ RSLT<-'JD3_ProcResults'
 
 #' @export
 #' @rdname jd3_utilities
-.jd3_object<-function(jobjRef, subclasses=NULL, result=F){
+.jd3_object<-function(jobjRef, subclasses=NULL, result=FALSE){
  if (result)
  classes<-c(OBJ, RSLT, subclasses)
  else
@@ -64,5 +64,3 @@ user_defined <- function(object, userdefined = NULL){
  class(result) <- c("user_defined")
  result
 }
-
-

R/protobuf.R

@@ -239,7 +239,7 @@ NULL
 #' @rdname jd3_utilities
 .p2r_ucarima<-function(p){
  model<-.p2r_arima(p$model)
- return (ucarima_model(model,lapply(p$components, function(z){.p2r_arima(z)}), lapply(p$complements, function(z){.p2r_arima(z)}), F))
+ return (ucarima_model(model,lapply(p$components, function(z){.p2r_arima(z)}), lapply(p$complements, function(z){.p2r_arima(z)}), FALSE))
 }
 
 
@@ -459,7 +459,7 @@ NULL
 
 #' @export
 #' @rdname jd3_utilities
-.p2r_sa_decomposition<-function(p, full=F){
+.p2r_sa_decomposition<-function(p, full=FALSE){
  if (full){
  return (list(mode = .enum_extract(sa.DecompositionMode, p$mode),
  series=.p2r_sa_component(p$series),
@@ -526,6 +526,3 @@ NULL
  p$forecast<-r$forecast
  return (p)
 }
-
-
-

R/regarima_generic.R

@@ -76,4 +76,3 @@ residuals.JD3_REGARIMA_RSLTS <- function(object, ...){
  object <- object$estimation
  object$res
 }
-

R/regarima_rslts.R

@@ -39,4 +39,3 @@ NULL
  tnames<-lapply(p$residuals_tests, function(z){z$key})
  testonresiduals<-`names<-`(tlist, tnames)
 }
-

R/spec_regarima.R

@@ -1549,4 +1549,3 @@ set_span <- function(x,
  }
  x
 }
-

R/tests_regular.R

@@ -67,7 +67,7 @@ print.JD3_TEST<-function(x, details=FALSE, ...){
 #' ljungbox(random_t(2, 100), lag = 24, k =1)
 #' ljungbox(ABS$X0.2.09.10.M, lag = 24, k =1)
 #' @export
-ljungbox<-function(data, k=1, lag=1, nhp=0, sign=0, mean=T){
+ljungbox<-function(data, k=1, lag=1, nhp=0, sign=0, mean=TRUE){
  jtest<-.jcall("jdplus/toolkit/base/r/stats/Tests", "Ljdplus/toolkit/base/api/stats/StatisticalTest;", "ljungBox",
  as.numeric(data), as.integer(k), as.integer(lag), as.integer(nhp), as.integer(sign), as.logical(mean))
  return (.jd2r_test(jtest))
@@ -112,7 +112,7 @@ doornikhansen<-function(data){
 
 #' @export
 #' @describeIn normality_tests Jarque-Bera test
-jarquebera<-function(data, k=0, sample=T){
+jarquebera<-function(data, k=0, sample=TRUE){
  jtest<-.jcall("jdplus/toolkit/base/r/stats/Tests", "Ljdplus/toolkit/base/api/stats/StatisticalTest;", "jarqueBera",
  as.numeric(data), as.integer(k), as.logical(sample))
  return (.jd2r_test(jtest))
@@ -141,15 +141,15 @@ NULL
 
 #' @describeIn runstests Runs test around mean or median
 #' @export
-testofruns<-function(data, mean=T, number=T){
+testofruns<-function(data, mean=TRUE, number=TRUE){
  jtest<-.jcall("jdplus/toolkit/base/r/stats/Tests", "Ljdplus/toolkit/base/api/stats/StatisticalTest;", "testOfRuns",
  as.numeric(data), as.logical(mean), as.logical(number))
  return (.jd2r_test(jtest))
 }
 
 #' @describeIn runstests up and down runs test
 #' @export
-testofupdownruns<-function(data, number=T){
+testofupdownruns<-function(data, number=TRUE){
  jtest<-.jcall("jdplus/toolkit/base/r/stats/Tests", "Ljdplus/toolkit/base/api/stats/StatisticalTest;", "testOfUpDownRuns",
  as.numeric(data), as.logical(number))
  return (.jd2r_test(jtest))
@@ -167,15 +167,15 @@ testofupdownruns<-function(data, number=T){
 #' autocorrelations_partial(x)
 #' autocorrelations_inverse(x)
 #' @export
-autocorrelations<-function(data, mean=T, n=15){
+autocorrelations<-function(data, mean=TRUE, n=15){
  res = .jcall("jdplus/toolkit/base/r/stats/Tests", "[D", "autocorrelations",
  as.numeric(data), as.logical(mean), as.integer(n))
  names(res) <- seq_len(n)
  return (res)
 }
 #' @export
 #' @rdname autocorrelations
-autocorrelations_partial<-function(data, mean=T, n=15){
+autocorrelations_partial<-function(data, mean=TRUE, n=15){
  res <- .jcall("jdplus/toolkit/base/r/stats/Tests", "[D", "partialAutocorrelations",
  as.numeric(data), as.logical(mean), as.integer(n))
  names(res) <- seq_len(n)
@@ -217,9 +217,3 @@ kurtosis<-function(data){
 mad<-function(data, centile=50, medianCorrected=TRUE){
  return (.jcall("jdplus/toolkit/base/r/stats/Tests", "D", "mad",as.numeric(data), as.numeric(centile), as.logical(medianCorrected)))
 }
-
-
-
-
-
-

R/tests_seasonality.R

@@ -149,4 +149,3 @@ seasonality_canovahansen<-function(data, p0, p1, np, original=FALSE){
  as.numeric(data), as.numeric(p0), as.numeric(p1), as.integer(np), as.logical(original))
  return (jtest)
 }
-

R/timeseries.R

@@ -39,7 +39,7 @@ aggregate.default<-function(s, nfreq=1,
  jd_s<-.r2jd_tsdata(s)
  jd_agg<-.jcall("jdplus/toolkit/base/r/timeseries/TsUtility", "Ljdplus/toolkit/base/api/timeseries/TsData;", "aggregate", jd_s, as.integer(nfreq), conversion, complete)
  if (is.jnull(jd_agg)){
- return (NULL);
+ return (NULL)
  }
  else{
  return (.jd2r_tsdata(jd_agg))
@@ -85,7 +85,7 @@ clean_extremities<-function(s){
  jd_scleaned<-.jcall("jdplus/toolkit/base/r/timeseries/TsUtility", "Ljdplus/toolkit/base/api/timeseries/TsData;", "cleanExtremities", jd_s)
 
  if (is.jnull(jd_scleaned)){
- return (NULL);
+ return (NULL)
  }
  else{
  return (.jd2r_tsdata(jd_scleaned))
@@ -167,7 +167,7 @@ ts_adjust.default<-function(s, method=c("LeapYear", "LengthOfPeriod"), reverse =
  jd_s<-.r2jd_tsdata(s)
  jd_st<-.jcall("jdplus/toolkit/base/r/modelling/Transformation", "Ljdplus/toolkit/base/api/timeseries/TsData;", "adjust", jd_s, method, as.logical(reverse))
  if (is.jnull(jd_st)){
- return (NULL);
+ return (NULL)
  }
  else{
  return (.jd2r_tsdata(jd_st))

R/utils.R

@@ -63,5 +63,3 @@ likelihood<-function(nobs, neffectiveobs=NA, nparams=0, ll, adjustedll=NA, aic,
  aic=aic, aicc=aicc, bic=bic, bicc=bicc, ssq=ssq),
  class = "JD3_LIKELIHOOD"))
 }
-
-

R/zzz.R

@@ -34,5 +34,3 @@ NULL
  DATE_MAX<<-dateOf(9999, 12, 31)
 
 }
-
-

rjd3toolkit.Rproj

@@ -1,12 +1,12 @@
 Version: 1.0
 
-RestoreWorkspace: Default
-SaveWorkspace: Default
-AlwaysSaveHistory: Default
+RestoreWorkspace: No
+SaveWorkspace: No
+AlwaysSaveHistory: No
 
 EnableCodeIndexing: Yes
 UseSpacesForTab: Yes
-NumSpacesForTab: 2
+NumSpacesForTab: 4
 Encoding: UTF-8
 
 RnwWeave: Sweave
@@ -21,3 +21,5 @@ PackageInstallArgs: --no-multiarch --with-keep.source
 PackageBuildBinaryArgs: --no-multiarch
 PackageCheckArgs: --no-multiarch
 PackageRoxygenize: rd,collate,namespace,vignette
+
+UseNativePipeOperator: Yes