Rename the 'sd' function to 'sdu'

ropensci · Oct 3, 2021 · ec34d83 · ec34d83
1 parent 0b9d298
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diff --git a/NAMESPACE b/NAMESPACE
@@ -48,10 +48,10 @@ export(qplot_walk)
 export(random_mctq)
 export(raw_data)
 export(round_time)
-export(sd)
 export(sd24)
 export(sd_overall)
 export(sd_week)
+export(sdu)
 export(shorter_interval)
 export(sjl)
 export(sjl_rel)

diff --git a/NEWS.md b/NEWS.md
@@ -1,5 +1,9 @@
 # mctq 0.0.0.9001
 
+## Breaking changes
+
+* The `sd()` function is now named as `sdu()`. That was a tough, but necessary, call. Although we tried to preserve the original authors naming pattern for the MCTQ functions, the name `sd` provokes a dangerous name collision with the widely used `stats::sd` (standard deviation) function. That's why we named it as `sdu`. This is the only exception, all the other `mctq` functions maintain a strong naming resemblance with the original authors naming pattern.
+
 ## Added
 
 * @jonkeane was added as a reviewer ('rev').

diff --git a/R/ms.R b/R/ms.R
@@ -56,7 +56,7 @@
 #'   use [mctq::so()] to compute it for the standard or shift version.
 #' @param sd A `Duration` object corresponding to the __sleep duration__ from a
 #'   standard, micro, or shift version of the MCTQ questionnaire. You can use
-#'   [mctq::sd()] to compute it for any MCTQ version.
+#'   [mctq::sdu()] to compute it for any MCTQ version.
 #'
 #' @return A `hms` object corresponding to the vectorized sum of `so` and `(sd /
 #'   2)` in a circular time frame of 24 hours.
@@ -193,10 +193,10 @@ ms <- function(so, sd) {
 #'   questionnaire. You can use [mctq::ms()] to compute it.
 #' @param sd_w A `Duration` object corresponding to the __sleep duration on work
 #'   days__ from a standard, micro, or shift version of the MCTQ questionnaire.
-#'   You can use [mctq::sd()] to compute it.
+#'   You can use [mctq::sdu()] to compute it.
 #' @param sd_f A `Duration` object corresponding to the __sleep duration on
 #'   work-free days__ from a standard, micro, or shift version of the MCTQ
-#'   questionnaire. You can use [mctq::sd()] to compute it.
+#'   questionnaire. You can use [mctq::sdu()] to compute it.
 #' @param sd_week A `Duration` object corresponding to the __average weekly
 #'   sleep duration__ from a standard or micro version of the MCTQ questionnaire
 #'   (you can use [mctq::sd_week()] to compute it) __or__ the __overall sleep

diff --git a/R/sd.R b/R/sd.R
@@ -4,14 +4,21 @@
 #'
 #' `r lifecycle::badge("maturing")`
 #'
-#' `sd()` computes the __sleep duration__ for standard, micro, and shift
+#' `sdu()` computes the __sleep duration__ for standard, micro, and shift
 #' versions of the Munich Chronotype Questionnaire (MCTQ).
 #'
+#' Please note that, although we tried to preserve the original authors naming
+#' pattern for the MCTQ functions, the name `sd` provokes a dangerous name
+#' collision with the widely used [stats::sd] (standard deviation) function.
+#' That's why we named it as `sdu`. This is the only exception, all the other
+#' `mctq` functions maintain a strong naming resemblance with the original
+#' authors naming pattern.
+#'
 #' @section Guidelines:
 #'
 #' Roenneberg, Allebrandt, Merrow, & Vetter (2012), Ghotbi et al. (2020), Juda,
 #' Vetter, & Roenneberg (2013), and The Worldwide Experimental Platform (n.d.)
-#' guidelines for `sd()` (\eqn{SD}) computation are as follows.
+#' guidelines for `sdu()` (\eqn{SD}) computation are as follows.
 #'
 #' ## Notes
 #'
@@ -71,26 +78,26 @@
 #'
 #' so <- hms::parse_hm("23:00")
 #' se <- hms::parse_hm("08:00")
-#' sd(so, se)
+#' sdu(so, se)
 #' #> [1] "32400s (~9 hours)" # Expected
 #'
 #' so <- hms::parse_hm("02:00")
 #' se <- hms::parse_hm("12:30")
-#' sd(so, se)
+#' sdu(so, se)
 #' #> [1] "37800s (~10.5 hours)" # Expected
 #'
 #' so <- hms::parse_hm("03:15")
 #' se <- hms::as_hms(NA)
-#' sd(so, se)
+#' sdu(so, se)
 #' #> [1] NA # Expected
 #'
 #' ## Vector example
 #'
 #' so <- c(hms::parse_hm("04:12"), hms::parse_hm("21:20"))
 #' se <- c(hms::parse_hm("14:30"), hms::parse_hm("03:45"))
-#' sd(so, se)
+#' sdu(so, se)
 #' #> [1] "37080s (~10.3 hours)" "23100s (~6.42 hours)" # Expected
-sd <- function(so, se) {
+sdu <- function(so, se) {
     checkmate::assert_class(so, "hms")
     checkmate::assert_class(se, "hms")
     assert_identical(so, se, type = "length")
@@ -229,7 +236,7 @@ napd <- function(napo, nape) {
 #' morning shift; \eqn{E} = evening shift; \eqn{N} = night shift.
 #'
 #' @param sd A `Duration` object corresponding to the __sleep duration__ from
-#'   the shift version of the MCTQ questionnaire. You can use [mctq::sd()] to
+#'   the shift version of the MCTQ questionnaire. You can use [mctq::sdu()] to
 #'   compute it.
 #' @param napd A `Duration` object corresponding to the __nap duration__ from
 #'   the shift version of the MCTQ questionnaire. You can use [mctq::napd()] to
@@ -343,10 +350,10 @@ sd24 <- function(sd, napd, nap) {
 #'
 #' @param sd_w A `Duration` object corresponding to the __sleep duration on
 #'   workdays__ from a standard or micro version of the MCTQ questionnaire. You
-#'   can use [mctq::sd()] to compute it.
+#'   can use [mctq::sdu()] to compute it.
 #' @param sd_f A `Duration` object corresponding to the __sleep duration on
 #'   work-free days__ from a standard or micro version of the MCTQ
-#'   questionnaire. You can use [mctq::sd()] to compute it.
+#'   questionnaire. You can use [mctq::sdu()] to compute it.
 #'
 #' @return A `Duration` object corresponding to the vectorized weighted mean of
 #'   `sd_w` and `sd_f` with `wd` and `fd(wd)` as weights.
@@ -486,10 +493,10 @@ sd_week <- function(sd_w, sd_f, wd) {
 #'
 #' @param sd_w A `Duration` object corresponding to the __sleep duration between
 #'   two days in a particular shift__ from a shift version of the MCTQ
-#'   questionnaire. You can use [mctq::sd()] to compute it.
+#'   questionnaire. You can use [mctq::sdu()] to compute it.
 #' @param sd_f A `Duration` object corresponding to the __sleep duration between
 #'   two free days after a particular shift__ from a shift version of the MCTQ
-#'   questionnaire. You can use [mctq::sd()] to compute it.
+#'   questionnaire. You can use [mctq::sdu()] to compute it.
 #' @param n_w An [integerish][checkmate::test_integerish()] `numeric` object or
 #'   an `integer` object corresponding to the __number of days worked in a
 #'   particular shift within a shift cycle__ from a shift version of the MCTQ

diff --git a/R/sjl.R b/R/sjl.R
@@ -388,12 +388,12 @@ sjl_weighted <- function(sjl, n_w) {
     sjl <- lapply(sjl, abs)
     n_w <- lapply(n_w, as.integer)
 
-    foo <- function(x, y) {
+    reduce <- function(x, y) {
         out <- Reduce("*", list(x, y))
         lubridate::as.duration(out)
     }
 
-    sjl <- mapply(foo, n_w, sjl, SIMPLIFY = FALSE)
+    sjl <- mapply(reduce, n_w, sjl, SIMPLIFY = FALSE)
     sjl <- Reduce("+", sjl)
     n_w <- Reduce("+", n_w)
 

diff --git a/README.Rmd b/README.Rmd
@@ -88,7 +88,7 @@ Note that the `mctq` functions uses a similar naming scheme to that used in the
 * `fd()`: compute MCTQ work-free days
 * `so()`: compute MCTQ local time of sleep onset
 * `gu()`: compute MCTQ local time of getting out of bed
-* `sd()`: compute MCTQ sleep duration
+* `sdu()`: compute MCTQ sleep duration
 * `tbt()`: compute MCTQ total time in bed
 * `ms()`: compute MCTQ local time of mid-sleep
 * `napd()`: compute MCTQ nap duration (only for MCTQ Shift)

diff --git a/README.md b/README.md
@@ -132,7 +132,7 @@ computation necessary.
 -   `fd()`: compute MCTQ work-free days
 -   `so()`: compute MCTQ local time of sleep onset
 -   `gu()`: compute MCTQ local time of getting out of bed
--   `sd()`: compute MCTQ sleep duration
+-   `sdu()`: compute MCTQ sleep duration
 -   `tbt()`: compute MCTQ total time in bed
 -   `ms()`: compute MCTQ local time of mid-sleep
 -   `napd()`: compute MCTQ nap duration (only for MCTQ Shift)

diff --git a/_pkgdown.yml b/_pkgdown.yml
@@ -20,7 +20,7 @@ reference:
   - fd
   - so
   - gu
-  - sd
+  - sdu
   - tbt
   - ms
   - napd

diff --git a/codemeta.json b/codemeta.json
@@ -19,7 +19,7 @@
     "name": "R",
     "url": "https://r-project.org"
   },
-  "runtimePlatform": "R version 4.1.0 (2021-05-18)",
+  "runtimePlatform": "R version 4.1.1 (2021-08-10)",
   "author": [
     {
       "@type": "Person",
@@ -85,35 +85,11 @@
       },
       "sameAs": "https://CRAN.R-project.org/package=covr"
     },
-    {
-      "@type": "SoftwareApplication",
-      "identifier": "crayon",
-      "name": "crayon",
-      "provider": {
-        "@id": "https://cran.r-project.org",
-        "@type": "Organization",
-        "name": "Comprehensive R Archive Network (CRAN)",
-        "url": "https://cran.r-project.org"
-      },
-      "sameAs": "https://CRAN.R-project.org/package=crayon"
-    },
     {
       "@type": "SoftwareApplication",
       "identifier": "datasets",
       "name": "datasets"
     },
-    {
-      "@type": "SoftwareApplication",
-      "identifier": "emojifont",
-      "name": "emojifont",
-      "provider": {
-        "@id": "https://cran.r-project.org",
-        "@type": "Organization",
-        "name": "Comprehensive R Archive Network (CRAN)",
-        "url": "https://cran.r-project.org"
-      },
-      "sameAs": "https://CRAN.R-project.org/package=emojifont"
-    },
     {
       "@type": "SoftwareApplication",
       "identifier": "ggplot2",
@@ -238,6 +214,7 @@
       "@type": "SoftwareApplication",
       "identifier": "checkmate",
       "name": "checkmate",
+      "version": ">= 2.0.0",
       "provider": {
         "@id": "https://cran.r-project.org",
         "@type": "Organization",
@@ -250,6 +227,7 @@
       "@type": "SoftwareApplication",
       "identifier": "cli",
       "name": "cli",
+      "version": ">= 3.0.1",
       "provider": {
         "@id": "https://cran.r-project.org",
         "@type": "Organization",
@@ -262,7 +240,7 @@
       "@type": "SoftwareApplication",
       "identifier": "dplyr",
       "name": "dplyr",
-      "version": ">= 0.2",
+      "version": ">= 1.0.7",
       "provider": {
         "@id": "https://cran.r-project.org",
         "@type": "Organization",
@@ -275,6 +253,7 @@
       "@type": "SoftwareApplication",
       "identifier": "hms",
       "name": "hms",
+      "version": ">= 1.1.0",
       "provider": {
         "@id": "https://cran.r-project.org",
         "@type": "Organization",
@@ -287,6 +266,7 @@
       "@type": "SoftwareApplication",
       "identifier": "lifecycle",
       "name": "lifecycle",
+      "version": ">= 1.0.0",
       "provider": {
         "@id": "https://cran.r-project.org",
         "@type": "Organization",
@@ -299,7 +279,7 @@
       "@type": "SoftwareApplication",
       "identifier": "lubridate",
       "name": "lubridate",
-      "version": ">= 1.7.9",
+      "version": ">= 1.7.10",
       "provider": {
         "@id": "https://cran.r-project.org",
         "@type": "Organization",
@@ -310,8 +290,8 @@
     }
   ],
   "releaseNotes": "https://github.com/gipso/mctq/blob/master/NEWS.md",
-  "fileSize": "0KB",
-  "contIntegration": "https://codecov.io/gh/gipso/mctq",
+  "fileSize": "752.841KB",
+  "contIntegration": ["https://github.com/gipso/mctq/actions", "https://codecov.io/gh/gipso/mctq"],
   "developmentStatus": ["https://www.repostatus.org/#active", "https://www.tidyverse.org/lifecycle/#maturing"],
   "keywords": [
     "chronobiology",

diff --git a/data-raw/micro_mctq.R b/data-raw/micro_mctq.R
@@ -1,8 +1,6 @@
 # Source the file before running the functions
 # Don't forget to uncomment the `library` functions below
 
-library(magrittr)
-
 # library(checkmate)
 # library(dplyr)
 # library(hms)
@@ -466,7 +464,7 @@ validate_micro_mctq <- function(write = FALSE) {
 
         micro_mctq <- micro_mctq %>%
             dplyr::mutate(
-                sd_i = mctq::sd(!!as.symbol(so_i), !!as.symbol(se_i)),
+                sd_i = mctq::sdu(!!as.symbol(so_i), !!as.symbol(se_i)),
                 dummy = dplyr::case_when(
                     sd_i < lubridate::dhours(2) |
                         sd_i > lubridate::dhours(18) ~ TRUE,
@@ -548,10 +546,10 @@ analyze_micro_mctq <- function(write = FALSE, round = TRUE, hms = FALSE) {
         dplyr::mutate(
             fd = fd(wd),
 
-            sd_w = sd(so_w, se_w),
+            sd_w = sdu(so_w, se_w),
             msw = ms(so_w, sd_w),
 
-            sd_f = sd(so_f, se_f),
+            sd_f = sdu(so_f, se_f),
             msf = ms(so_f, sd_f),
 
             sd_week = sd_week(sd_w, sd_f, wd),

diff --git a/data-raw/random_mctq.R b/data-raw/random_mctq.R
@@ -1,8 +1,6 @@
 # Source the file before running the functions
 # Don't forget to uncomment the `library` functions below
 
-library(magrittr)
-
 # library(checkmate)
 # library(cli)
 # library(glue)

diff --git a/data-raw/shift_mctq.R b/data-raw/shift_mctq.R
@@ -1,8 +1,6 @@
 # Source the file before running the functions
 # Don't forget to uncomment the `library` functions below
 
-library(magrittr)
-
 # library(checkmate)
 # library(dplyr)
 # library(hms)
@@ -1320,7 +1318,7 @@ validate_shift_mctq <- function(write = FALSE) {
         test <- shift_mctq %>%
             dplyr::mutate(
                 so_i = mctq::so(!!as.symbol(sprep_i), !!as.symbol(slat_i)),
-                sd_i = mctq::sd(so_i, !!as.symbol(se_i)),
+                sd_i = mctq::sdu(so_i, !!as.symbol(se_i)),
                 dummy = dplyr::case_when(
                     sd_i < lubridate::dhours(2) |
                         sd_i > lubridate::dhours(18) ~ TRUE,
@@ -1426,7 +1424,7 @@ analyze_shift_mctq <- function(write = FALSE, round = TRUE, hms = FALSE) {
                     gu(!!as.symbol(paste0("se", i)),
                        !!as.symbol(paste0("tgu", i))),
                 !!as.symbol(paste0("sd", i)) :=
-                    sd(!!as.symbol(paste0("so", i)),
+                    sdu(!!as.symbol(paste0("so", i)),
                        !!as.symbol(paste0("se", i))),
                 !!as.symbol(paste0("tbt", i)) :=
                     tbt(!!as.symbol(paste0("bt", i)),

diff --git a/data-raw/std_mctq.R b/data-raw/std_mctq.R
@@ -1,8 +1,6 @@
 # Source the file before running the functions
 # Don't forget to uncomment the `library` functions below
 
-library(magrittr)
-
 # library(checkmate)
 # library(dplyr)
 # library(hms)
@@ -794,7 +792,7 @@ validate_std_mctq <- function(write = FALSE) {
         test <- std_mctq %>%
             dplyr::mutate(
                 so_i = mctq::so(!!as.symbol(sprep_i), !!as.symbol(slat_i)),
-                sd_i = mctq::sd(so_i, !!as.symbol(se_i)),
+                sd_i = mctq::sdu(so_i, !!as.symbol(se_i)),
                 dummy = dplyr::case_when(
                     sd_i < lubridate::dhours(2) |
                         sd_i > lubridate::dhours(18) ~ TRUE,
@@ -894,13 +892,13 @@ analyze_std_mctq <- function(write = FALSE, round = TRUE, hms = FALSE) {
             fd = fd(wd),
             so_w = so(sprep_w, slat_w),
             gu_w = gu(se_w, si_w),
-            sd_w = sd(so_w, se_w),
+            sd_w = sdu(so_w, se_w),
             tbt_w = tbt(bt_w, gu_w),
             msw = ms(so_w, sd_w),
 
             so_f = so(sprep_f, slat_f),
             gu_f = gu(se_f, si_f),
-            sd_f = sd(so_f, se_f),
+            sd_f = sdu(so_f, se_f),
             tbt_f = tbt(bt_f, gu_f),
             msf = ms(so_f, sd_f),
 

diff --git a/data-raw/vignette_mctq.R b/data-raw/vignette_mctq.R
@@ -1,8 +1,6 @@
 # Source the file before running the function
 # Don't forget to uncomment the `library` functions below
 
-library(magrittr)
-
 # library(checkmate)
 # library(dplyr)
 # library(mctq)