Merge pull request #61 from tscnlab/dev

LightLogR 0.9.2 - CRAN release

Author: JZauner

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
-Version: 0.5.3
-Date: 2025-02-24 17:54:45 UTC
-SHA: 0681d9bf9f64ece1aa13412aaaef6162f83be5dc
+Version: 0.9.2
+Date: 2025-06-10 10:54:06 UTC
+SHA: cb69b27469411ee407f80fc6b3358f57c54b8d64

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: LightLogR
 Title: Process Data from Wearable Light Loggers and Optical Radiation Dosimeters
-Version: 0.9.1
+Version: 0.9.2
 Authors@R: c(
     person("Johannes", "Zauner", 
       email = "[email protected]", role = c("aut", "cre"),

NAMESPACE

@@ -19,6 +19,7 @@ export(barroso_lighting_metrics)
 export(bright_dark_period)
 export(centroidLE)
 export(count_difftime)
+export(create_Timedata)
 export(cut_Datetime)
 export(data2reference)
 export(disparity_index)

NEWS.md

@@ -1,3 +1,5 @@
+# LightLogR 0.9.2
+
 # LightLogR 0.9.1
 
 * `add_Date_col()` is a new convenience function to add a Date column to the dataset, optionally showing the weekday.
@@ -12,7 +14,7 @@
 
 * removed `LYS` wearable sample file, due to package size limitations
 
-* `add_Time_col()` replaces `create_Time_data()`
+* `add_Time_col()` replaces `create_Time_data()`, also, the new column is called `Time` by default instead of `Time.data`
 
 * `extract_clusters()` has the option to show the cluster condition in the output with `add.label = TRUE`, e.g., `MEDI>500|d≥30min|i≤5min` for clusters of melanopic EDI larger than 500, at least 30 minutes long (`d`), allowing interruptions of up to 5 minutes at a time (`i`).
 

R/Brown.R

@@ -230,11 +230,16 @@ Brown_rec <- function(state,
 #' `vector_labels`
 #'
 #' @param dataset A light exposure dataframe
-#' @param MEDI.colname The colname containing melanopic EDI values (or, alternatively, Illuminance). Defaults to `MEDI`. Expects a symbol.
-#' @param New.state.colname Name of the new column that will contain the cut data. Expects a symbol.
+#' @param MEDI.colname The colname containing melanopic EDI values (or,
+#'   alternatively, Illuminance). Defaults to `MEDI`. Expects a symbol.
+#' @param New.state.colname Name of the new column that will contain the cut
+#'   data. Expects a symbol.
 #' @param vector_cuts Numeric vector of breaks for the cuts.
-#' @param vector_labels Vecotr of labels for the cuts. Must be one entry shorter than `vector_cuts`.
-#' @param overwrite Logical. Should the `New.state.colname` overwrite a preexisting column in the dataset
+#' @param vector_labels Vector of labels for the cuts. Must be one entry shorter
+#'   than `vector_cuts`. `"default"` will produce nice labels for the default
+#'   setting of `vector_cuts` (and throw an error otherwise).
+#' @param overwrite Logical. Should the `New.state.colname` overwrite a
+#'   preexisting column in the dataset
 #'
 #' @return The input dataset with an additional (or overwritten) column
 #'   containing a cut light vector
@@ -245,18 +250,22 @@ Brown_rec <- function(state,
 #'
 #' @family Brown
 #' @examples
-#' sample.data.environment |> 
-#' Brown_cut() |> 
+#' sample.data.environment |>
+#' Brown_cut(vector_labels = c("0-1lx", "1-10lx", "10-250lx", "250lx-Inf")) |>
 #' dplyr::count(state)
 #' 
 Brown_cut <- function(dataset,
                       MEDI.colname = MEDI,
                       New.state.colname = state,
                       vector_cuts = c(-Inf, 1, 10, 250, Inf),
-                      vector_labels = c("\U{2264}1lx", "\U{2264}10lx", NA, "\U{2265}250lx"),
+                      vector_labels = "default",
                       overwrite = TRUE
                       ){
 
+  if(all(vector_labels == "default", c(-Inf, 1, 10, 250, Inf) %in% vector_cuts)) {
+    vector_labels <- c("\U{2264}1lx", "\U{2264}10lx", NA, "\U{2265}250lx")
+  }
+  
   stopifnot("vector_cuts need to be numeric" = 
               is.numeric(vector_cuts),
             "vector_labels need to be shorter by exactly one compared to vector_cuts" = 

R/add_Time_col.R

@@ -43,3 +43,20 @@ add_Time_col <- function(dataset,
   if(output.dataset) dataset else dataset[[colname.defused({{ Time.colname }})]]
 
 }
+
+
+#' create_Timedata
+#'
+#' @param ... Input arguments to [add_Time_col()]
+#'
+#' @returns a `data.frame` object identical to `dataset` but with the added
+#'   column of Time-of-Day data, or a `vector` with the Time-of-Day-data
+#' @export
+#'
+#' @examples
+#' sample.data.environment %>% create_Timedata()
+#' 
+create_Timedata <- function(...) {
+  .Deprecated("add_Time_col", msg = "`create_Timedata()` is deprecated as of LightLogR 0.9.1. Please use `add_Time_col()` instead. ")
+  add_Time_col(...)
+}

R/clusters.R

@@ -55,7 +55,7 @@
 #'   groups further, e.g. through [summarize_numeric()] - having an empty group
 #'   present is important when averaging numbers.
 #' @param add.label Logical. Option to add a label to the output containing the
-#'   condition. E.g., `MEDI>500|d≥30min|i≤5min` for clusters of melanopic EDI
+#'   condition. E.g., `MEDI>500|d>=30min|i<=5min` for clusters of melanopic EDI
 #'   larger than 500, at least 30 minutes long (`d`), allowing interruptions of
 #'   up to 5 minutes at a time (`i`).
 #'
@@ -78,8 +78,7 @@
 #'  extract_clusters(
 #'   MEDI > 250,
 #'   cluster.duration = "1 hour",
-#'   interruption.duration = "5 mins",
-#'   add.label = TRUE
+#'   interruption.duration = "5 mins"
 #' )
 extract_clusters <- function(
     data,

R/data.r

@@ -88,7 +88,7 @@
 #'   <https://www.cie.co.at/publications/cie-system-metrology-optical-radiation-iprgc-influenced-responses-light-0>
 #' @source
 #'   <https://cie.co.at/datatable/cie-spectral-luminous-efficiency-photopic-vision>
-#' @source <http://files.cie.co.at/S026_Table2_Data.xlsx>
+#' @source <https://files.cie.co.at/CIE S 026 alpha-opic Toolbox.xlsx>
 #' @references CIE (2019). ISO/CIE 11664-1:2019(E). Colorimetry — Part 1: CIE
 #'   standard colorimetric observers. Vienna, CIE
 #' @references CIE (2018). CIE S 026/E:2018. CIE system for metrology of optical

R/gg_gaps.R

@@ -139,7 +139,7 @@ gg_gaps <- function(dataset,
     dataset |> 
       gg_days(y.axis = {{ Variable.colname }}, x.axis = {{ Datetime.colname }},...) +
       ggplot2::geom_point(data = irregulars, col = col.irregular) +
-      ggplot2::labs(title = paste0("Irregular data (", col.irregular ,")"))
+      ggplot2::labs(title = paste0("Irregular data (", col.irregular ," dots)"))
 
     return(plot)
   }
@@ -150,7 +150,7 @@ gg_gaps <- function(dataset,
     data_regular |> 
       gg_days(y.axis = {{ Variable.colname }}, x.axis = {{ Datetime.colname }},...) |> 
       gg_state(gaps, fill = fill.gaps, alpha = alpha) +
-      ggplot2::labs(title = paste0("Gaps in the data (", fill.gaps ,")"))
+      ggplot2::labs(title = paste0("Gaps in the data (", fill.gaps ," areas)"))
 
     return(plot)
   }
@@ -159,6 +159,6 @@ gg_gaps <- function(dataset,
     gg_days(y.axis = {{ Variable.colname }}, x.axis = {{ Datetime.colname }},...) |> 
     gg_state(gaps, fill = fill.gaps, alpha = alpha) +
     ggplot2::geom_point(data = irregulars, col = col.irregular) +
-    ggplot2::labs(title = paste0("Gaps (", fill.gaps ,") and irregular (", col.irregular ,") data"))
+    ggplot2::labs(title = paste0("Gaps (", fill.gaps ," areas) and irregular (", col.irregular ," dots) data"))
 
 }

R/gg_state.R

@@ -38,11 +38,8 @@
 #' #(+aggregating Data to 5 minute intervals & reducing it to three days)
 #' state_data <-
 #'   sample.data.environment |>
-#'    dplyr::mutate(state = MEDI > 250,
-#'                  state2 = cut(MEDI,
-#'                               breaks = c(-1,1,10,250, Inf),
-#'                               labels = c("≤1lx", "≤10lx", NA, "≥250lx"))
-#'                               ) |>
+#'    dplyr::mutate(state = MEDI > 250) |>
+#'    Brown_cut(MEDI, state2) |> 
 #'    aggregate_Datetime(unit = "5 mins") |>
 #'    filter_Datetime(length = "3 days")
 #'

README.Rmd

@@ -18,7 +18,7 @@ knitr::opts_chunk$set(
 <!-- badges: start -->
 
 [![R-CMD-check](https://github.com/tscnlab/LightLogR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tscnlab/LightLogR/actions/workflows/R-CMD-check.yaml) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11562600.svg)](https://doi.org/10.5281/zenodo.11562600) [![CRAN status](https://www.r-pkg.org/badges/version/LightLogR)](https://CRAN.R-project.org/package=LightLogR)
-[![status](https://joss.theoj.org/papers/3a1057dccd315b7eb8683c1b969402e2/status.svg)](https://joss.theoj.org/papers/3a1057dccd315b7eb8683c1b969402e2)
+[![status](https://joss.theoj.org/papers/10.21105/joss.07601/status.svg)](https://joss.theoj.org/papers/10.21105/joss.07601)
 
 <!-- badges: end -->
 

README.md

@@ -9,7 +9,7 @@
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11562600.svg)](https://doi.org/10.5281/zenodo.11562600)
 [![CRAN
 status](https://www.r-pkg.org/badges/version/LightLogR)](https://CRAN.R-project.org/package=LightLogR)
-[![status](https://joss.theoj.org/papers/3a1057dccd315b7eb8683c1b969402e2/status.svg)](https://joss.theoj.org/papers/3a1057dccd315b7eb8683c1b969402e2)
+[![status](https://joss.theoj.org/papers/10.21105/joss.07601/status.svg)](https://joss.theoj.org/papers/10.21105/joss.07601)
 
 <!-- badges: end -->
 

_pkgdown.yml

@@ -47,6 +47,7 @@ reference:
     - add_Date_col
     - aggregate_Date
     - aggregate_Datetime
+    - create_Timedata
     - cut_Datetime
     - dst_change_handler
     - filter_Datetime

cran-comments.md

@@ -1,3 +1,12 @@
+## Submission Version 0.9.2
+
+### R CMD check results
+
+0 errors ✔ | 0 warnings ✔ | 1 note ✖
+
+* Note 1: unable to verify current time. 
+  Time server seems to be unavailable
+
 ## Resubmission #1 (Version 0.5.3)
 
 This is a resubmission. In this version I put some examples for gg_doubleplot and gg_photoperiod in /dontrun to avoid long runtime. I further rebuilt the package with the latest R-devel to correct the discrepancies with Authors@R and Author field.