Version bump

Author: Fifis

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: pnd
 Type: Package
 Title: Parallel Numerical Derivatives, Gradients, Jacobians, and Hessians of Arbitrary Accuracy Order
-Version: 0.1.0
+Version: 0.1.1
 Authors@R: person(given = c("Andreï", "Victorovitch"), family = "Kostyrka",
         role = c("aut", "cre"), email="andrei.kostyrka@gmail.com")
 Maintainer: Andreï Victorovitch Kostyrka <andrei.kostyrka@gmail.com>

NEWS.md

@@ -18,7 +18,7 @@
 - DEV: Check the compatibility between the function and its documentation
 - DEV: Check the release with `todor::todor_package()`, `lintr::lint_package()`, `R CMD check --as-cran`, and `goodpractice::gp(checks = all_checks()[!grepl("^lintr", all_checks())])`
 
-# pnd 0.1.1 (2025-07-XX)
+# pnd 0.1.1 (2025-09-04)
 - Fix: added a simpler and more reliable fall-back option for `step.M`
 - Feature: added plotting methods for `step...` functions
 - Feature: added arbitrary derivation and accuracy order to Curtis--Reid method

R/gradient.R

@@ -102,7 +102,7 @@ checkDimensions <- function(FUN, x, f0 = NULL, func = NULL,
   l <- length(f0)
 
   # The element-wise mapping by definition is having equal lengths of input and output
-  # TODO: This is NOT guaranteed, however, to guess correctly:
+  # This is NOT guaranteed, however, to guess correctly:
   # f(x) := c(sum(x), prod(x), sd(x)) evaluated at x = 1:3 would SEEM vectorised; more checks needed
 
   # 5 valid cases remain after ruling out such things as parallelised + multivalued
@@ -529,7 +529,6 @@ GenD <- function(FUN, x, elementwise = NA, vectorised = NA, multivalued = NA,
   attr(jac, "step.size") <- h
   if (autostep) {
     attr(jac, "step.size.method") <- hmethod
-    # TODO: use in printing
     attr(jac, "step.search") <- h.auto
   } else if (all(h == h.default)) {
     attr(jac, "step.size.method") <- "default"

R/methods.R

@@ -8,7 +8,7 @@
 #' # Printing whilst preserving names
 #' x <- structure(1:3, names = c("Andy", "Bradley", "Ca"))
 #' print(Grad(function(x) prod(sin(x)), 1))  # 1D derivative
-#' print(Grad(function(x) prod(sin(x)), x))
+#' print(Grad(function(x) prod(sin(x)), x, h = "CR"))
 #' print(Jacobian(function(x) c(prod(sin(x)), sum(exp(x))), x))
 print.GenD <- function(x, digits = 4, shave.spaces = TRUE,
                        begin = "", sep = "  ", end = "", ...) {

R/zzz.R

@@ -1,7 +1,7 @@
 #' @importFrom Rdpack reprompt
 
 .onAttach <- function(libname, pkgname) {
-  packageStartupMessage("Parallel numerical derivatives v.0.1.0 (2025-05-20).")
+  packageStartupMessage("Parallel numerical derivatives v.0.1.1 (2025-05-20).")
 
   # The number of cores is auto-detected based on the OS
   os <- Sys.info()[["sysname"]]

inst/CITATION

@@ -5,9 +5,9 @@ bibentry(
   title = "pnd: Parallel Numerical Derivatives, Gradients, {J}acobians, and {H}essians of Arbitrary Accuracy Order",
   author = person(given=c("Andreï", "Victorovitch"), family="Kostyrka", role = c("aut", "cre"), email = "andrei.kostyrka@gmail.com"),
   year = "2025",
-  note = "R package version 0.1.0",
+  note = "R package version 0.1.1",
   organization = "University of Luxembourg",
-  textVersion = "Kostyrka, Andreï V. (2025). pnd: Parallel Numerical Derivatives, Gradients, Jacobians, and Hessians of Arbitrary Accuracy Order. R package version 0.1.0. https://CRAN.R-project.org/package=pnd",
+  textVersion = "Kostyrka, Andreï V. (2025). pnd: Parallel Numerical Derivatives, Gradients, Jacobians, and Hessians of Arbitrary Accuracy Order. R package version 0.1.1. https://CRAN.R-project.org/package=pnd",
   url = "https://CRAN.R-project.org/package=pnd"
 )
 
@@ -17,8 +17,8 @@ bibentry(
   author = person(given=c("Andreï", "Victorovitch"), family="Kostyrka", role = c("aut", "cre"), email = "andrei.kostyrka@gmail.com"),
   year = "2025",
   organization = "University of Luxembourg",
-  note = "Vignette for the R package pnd 0.1.0.",
-  textVersion = "Kostyrka, Andreï V. (2025). Fast and accurate parallel numerical derivatives in R. Vignette for the R package pnd 0.1.0.",
+  note = "Vignette for the R package pnd 0.1.1.",
+  textVersion = "Kostyrka, Andreï V. (2025). Fast and accurate parallel numerical derivatives in R. Vignette for the R package pnd 0.1.1.",
   url = "https://github.com/Fifis/pnd/tree/main/vignettes"
 )
 
@@ -28,8 +28,8 @@ bibentry(
   author = person(given=c("Andreï", "Victorovitch"), family="Kostyrka", role = c("aut", "cre"), email = "andrei.kostyrka@gmail.com"),
   year = "2025",
   organization = "University of Luxembourg",
-  note = "Vignette for the R package pnd 0.1.0.",
-  textVersion = "Kostyrka, Andreï V. (2025). Step-size-selection algorithm benchmark. Vignette for the R package pnd 0.1.0.",
+  note = "Vignette for the R package pnd 0.1.1.",
+  textVersion = "Kostyrka, Andreï V. (2025). Step-size-selection algorithm benchmark. Vignette for the R package pnd 0.1.1.",
   url = "https://github.com/Fifis/pnd/tree/main/vignettes"
 )
 
@@ -39,7 +39,7 @@ bibentry(
   author = person(given=c("Andreï", "Victorovitch"), family="Kostyrka", role = c("aut", "cre"), email = "andrei.kostyrka@gmail.com"),
   year = "2025",
   organization = "University of Luxembourg",
-  note = "Vignette for the R package pnd 0.1.0.",
-  textVersion = "Kostyrka, Andreï V. (2025). Compatilibility of pnd with the syntax of numDeriv. Vignette for the R package pnd 0.1.0.",
+  note = "Vignette for the R package pnd 0.1.1.",
+  textVersion = "Kostyrka, Andreï V. (2025). Compatilibility of pnd with the syntax of numDeriv. Vignette for the R package pnd 0.1.1.",
   url = "https://github.com/Fifis/pnd/tree/main/vignettes"
 )