Navigation menu changes

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: LightLogR
 Title: Process Data from Wearable Light Loggers and Optical Radiation Dosimeters
-Version: 0.10.0
+Version: 0.10.1
 Authors@R: c(
     person("Johannes", "Zauner", 
       email = "johannes.zauner@tum.de", role = c("aut", "cre"),

NEWS.md

@@ -1,3 +1,9 @@
+# LightLogR 0.10.1
+
+* `extract_metric()` give more helpful error messages when using a base dataset without start/end columns.
+
+* `mean_daily()` can output the number of days that factor into the calculations by setting `.n = TRUE`.
+
 # LightLogR 0.10.0 **High noon**
 
 ## General improvements and new functions

R/extract_metric.R

@@ -61,6 +61,9 @@ extract_metric <- function(
 
   #if identifying.colname ist not part of the dataset, it will be added from the extracted_data
   if (!cc.name %in% names(data)) {
+    if(!all(c("start", "end") %in% names(extracted_data))) {
+      stop("start and/or end columns are missing in extracted_data, please either choose and `identifying.colname` that is part of `extracted_data`, or add start and end columns.")
+    }
     data <- 
       data |>
       dplyr::left_join(

R/mean_daily.R

@@ -35,6 +35,8 @@
 #'   affected).
 #' @param Datetime2Time.circular Logical of whether Time should be circular.
 #'   Will be ignored if `Datetime2Time = FALSE`. Default is `FALSE`.
+#' @param .n Logical, whether the number of days that went into each category
+#'   should be output. Default is `FALSE`.
 #'
 #' @return A dataframe with three rows representing average weekday, weekend,
 #'   and mean daily values of all numeric columns
@@ -69,7 +71,8 @@ mean_daily <- function(data,
                        filter.empty = FALSE,
                        sub.zero = FALSE,
                        Datetime2Time = TRUE,
-                       Datetime2Time.circular = FALSE
+                       Datetime2Time.circular = FALSE,
+                       .n = FALSE
                        ) {
 
   # Input validation
@@ -134,6 +137,7 @@ mean_daily <- function(data,
                                      mean(x, na.rm = na.rm)
                                    },
                                    .names = "{prefix}{.col}"), 
+                     .n = dplyr::n(),
                      .groups = "drop_last") 
 
   if(nrow(weekday_type) == 0) {
@@ -172,14 +176,15 @@ mean_daily <- function(data,
       )
       )|>
     dplyr::summarize(
-      dplyr::across(-c({{ Weekend.type }}, dplyr::where(lubridate::is.Date)),
+      dplyr::across(-c({{ Weekend.type }}, .n, dplyr::where(lubridate::is.Date)),
                     \(x) if(inherits(x, "Duration")) {
                       lubridate::duration(sum(x*.weight)/7) |> round(0)
                     } else if (inherits(x, "hms")) {
                       hms::as_hms((sum(x*.weight)/7) |> round(0)) 
                     } else {
                       sum(x*.weight)/7
                     }),
+      .n = sum(.n),
       .groups = "keep"
     ) |>
     dplyr::select(-.weight) |>
@@ -191,6 +196,10 @@ mean_daily <- function(data,
     dplyr::bind_rows(mean_daily) |> 
     dplyr::arrange({{ Weekend.type }}, .by_group = TRUE)
 
+  if(!.n) {
+    weekday_type <- weekday_type |> dplyr::select(-.n)
+  }
+
   #filter out empty rows
   if(filter.empty){
     weekday_type |>

README.Rmd

@@ -330,7 +330,7 @@ If you would like to use a metric you don't find represented in LightLogR, pleas
 
 ## About the creation and funding of LightLogR
 
-**LightLogR** is developed by the [*Translational Sensory & Circadian Neuroscience*](https://www.tscnlab.org) lab, a joint group from the [Technical University of Munich](https://www.tum.de/en/) and the [Max Planck Institute for Biological Neuroscience Unit (MPS/TUM/TUMCREATE)\*](https://www.tscnlab.org), a joint group based at the [Technical University of Munich](https://www.tum.de/en/), [TUMCREATE](https://www.tum-create.edu.sg/), the [Max Planck Institute for Biological Cybernetics](https://www.mpg.de/152075/biological-cybernetics).
+**LightLogR** is developed by the [*Translational Sensory & Circadian Neuroscience Unit (MPS/TUM/TUMCREATE*](https://www.tscnlab.org), a joint group based at the [Max Planck Institute for Biological Cybernetics](https://www.mpg.de/152075/biological-cybernetics), the [Technical University of Munich](https://www.tum.de/en/), and [TUMCREATE](https://www.tum-create.edu.sg/), .
 
 [*MeLiDos*](https://www.melidos.eu) is a joint, [EURAMET](https://www.euramet.org)-funded project involving sixteen partners across Europe, aimed at developing a metrology and a standard workflow for wearable light logger data and optical radiation dosimeters. Its primary contributions towards fostering FAIR data include the development of a common file format, robust metadata descriptors, and an accompanying open-source software ecosystem.
 

_pkgdown.yml

@@ -9,6 +9,8 @@ navbar:
     newsletter:
       text: Newsletter
       menu:
+      - text: January 2026
+        href: Edition02.html
       - text: July 2025
         href: Edition01.html
     resources:
@@ -19,8 +21,8 @@ navbar:
       - text: Course website
         href: https://tscnlab.github.io/LightLogR_webinar/
         target: "_blank"
-      - text: Flyer (2025/26)
-        href: pdf/Online_course_series_2025-26.pdf
+      - text: Flyer
+        href: https://tscnlab.github.io/LightLogR_webinar/assets/Online_course_series_2025-26.pdf
         target: "_blank"
       - text: ---
       - text: Talks
@@ -47,7 +49,7 @@ navbar:
         - text: The whole game
           href: articles/Day.html
         - text: Visual experience
-          href: https://tscnlab.github.io/ZaunerEtAl_JVis_2025/
+          href: https://tscnlab.github.io/ZaunerEtAl_JVis_2026/
           target: "_blank"
         - text: '---'
         - text: 'General Workflow'