bioRad 0.8.1

.gitignore

@@ -46,4 +46,5 @@ pkgdown/*
 /Meta/
 
 # rosm cache
+rosm.cache/
 rosm.cache

DESCRIPTION

@@ -1,12 +1,12 @@
 Package: bioRad
 Title: Biological Analysis and Visualization of Weather Radar Data
-Version: 0.7.3.9000
+Version: 0.8.1
 Description: Extract, visualize and summarize aerial movements of birds and
     insects from weather radar data. See Dokter, A. M. et al. (2018) 
     "bioRad: biological analysis and visualization of weather radar data" <doi:10.1111/ecog.04028>
     for a software paper describing package and methodologies.
 Authors@R: c(
-    person("Adriaan M.", "Dokter", role = c("aut", "cre"), email = "amd427@cornell.edu", comment = c(ORCID = "0000-0001-6573-066X")),
+    person("Adriaan M.", "Dokter", role = c("aut", "cre"), email = "biorad@cornell.edu", comment = c(ORCID = "0000-0001-6573-066X")),
     person("Peter", "Desmet", role = "aut", email = "peter.desmet@inbo.be", comment = c(ORCID = "0000-0002-8442-8025")),
     person("Bart", "Kranstauber", role = "aut", email = "b.kranstauber@uva.nl", comment = c(ORCID = "0000-0001-8303-780X")),
     person("Cecilia", "Nilsson", role = "aut", email = "cecilia.nilsson709@gmail.com", comment = c(ORCID = "0000-0001-8957-4411")),
@@ -32,7 +32,6 @@ Imports:
     curl,
     dplyr (>= 1.1.0),
     fields,
-    frictionless,
     ggplot2,
     glue,
     graphics,
@@ -44,10 +43,13 @@ Imports:
     readr,
     rhdf5,
     rlang,
+    sf,
     sp,
     stats,
+    stringr,
     suntools,
     tidyr,
+    tidyselect,
     utils,
     viridis,
     viridisLite
@@ -58,14 +60,12 @@ Suggests:
     prettymapr,
     rmarkdown,
     rosm,
-    sf,
     testthat (>= 3.0.0),
-    tidyselect,
     vdiffr,
     vol2birdR
 LazyData: true
 Encoding: UTF-8
 VignetteBuilder: knitr
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2
 Roxygen: list(markdown = TRUE)
 Config/testthat/edition: 3

NAMESPACE

@@ -150,4 +150,3 @@ export(write_pvolfile)
 importFrom(dplyr,"%>%")
 importFrom(dplyr,.data)
 importFrom(methods,as)
-importFrom(stats,na.omit)

NEWS.md

@@ -1,17 +1,39 @@
 
-# bioRad 0.7.3.9000
+# bioRad 0.8.1
+
+## bugfixes
+
+* dbz_all field in VPTS CSV files is now correctly mapped to DBZH field
+
+* non-standard data fields are now retained in vpts objects produced with as.vpts()
+
+# bioRad 0.8.0
+
+## New features
+
+* ENRAM VPTS data exchange format added in package data as `vpts_schema.rda`
+
+* VPTS files are now able to be validated with `validate_vpts()` which uses the schema to check for min/max constraint violations for specific fields, regex and datetime formatting
 
 * speed up `integrate_to_ppi()` and `project_as_ppi()` by using native `sf` functions (#669)
 
+* support for tidyverse select method for polar volume and polar scan objects (#668,#460)
+
 ## Bugfixes
 
-* support for tidyverse select method for polar volume and polar scan objects (#668,#460)
+* Corrected the default refractive index value used in conversion of linear reflectivity (eta) to logarithmic reflectivity (dBZ). The effect is a 7% increase in animal densities in output of functions `integrate_to_ppi()` and `read_cajun()` only (#642).
 
-* Updated the default refractive index value used in conversion of linear reflectivity (eta) to logarithmic reflectivity (dBZ) (#642). The effect is a 7% increase in animal densities in output of functions `integrate_to_ppi()` and `read_cajun()` only.
+* Fixed the handling of empty numeric vectors when plotting clutter maps (#655)
 
-# bioRad 0.7.3
+* Fixed warning when reading VPTS csv containing multiple values in `lat`, `lon`, '`rcs`' or `sd_vvp_threshold` (#651)
 
-## New features
+* Fixed enabling/disabling of `single_pol` flag in `calculate_vp()` (#646)
+
+* Updated the s3 source bucket of `download_vpfiles()` to https://aloftdata.s3-eu-west-1.amazonaws.com (#648)
+
+* Fixed an error in the idw method of `composite_ppi()` that emerged with the evolution of dependency package sp / deprecation of rgdal (#666)
+
+# bioRad 0.7.3
 
 * Replaced the `ggmap` package with `ggspatial` for map visualizations. This change was made as `ggmap` no longer provides reliable open-source basemaps without the necessity to register for an API key (#638).
 
@@ -76,7 +98,6 @@ bioRad 0.7 includes a major backend overhaul that deprecates the use of Docker.
 ## Deprecations
 
 
-
 * Argument `local_install` in `calculate_vp()` and `apply_mistnet()` is now deprecated.
 
 * Functions `check_docker()` and `update_docker()` have been deprecated.

R/apply_mistnet.R

@@ -85,6 +85,7 @@
 #' @examples
 #' \donttest{
 #' # make sure you have installed the MistNet libraries and model, using:
+#' if (requireNamespace("vol2birdR", quietly = TRUE)){
 #' if(!vol2birdR::mistnet_exists()){
 #'    vol2birdR::install_mistnet()
 #'    vol2birdR::install_mistnet_model()
@@ -125,6 +126,7 @@
 #' # Remove file
 #' file.remove(tempfile)
 #' }
+#' }
 apply_mistnet <- function(file, pvolfile_out, verbose = FALSE,
                           mount = dirname(file), load = TRUE,
                           mistnet_elevations = c(0.5, 1.5, 2.5, 3.5, 4.5),

R/as.vpts.R

@@ -1,4 +1,3 @@
-
 #' Convert a dataframe into a vpts object
 #'
 #' @param data a dataframe created from a VPTS CSV file
@@ -18,6 +17,8 @@ as.vpts <- function(data) {
       dplyr::rename(DBZH = "dbz_all")
   }
 
+  validate_vpts(data)
+
   height <- datetime <- source_file <- radar <- NULL
 
   # Throw error if nrows per height are not identical
@@ -35,13 +36,6 @@ as.vpts <- function(data) {
     msg = "`data` must contain data of a single radar."
   )
 
-  if (!exists("cached_schema")) {
-    # Load the schema from the data directory and cache it
-    cached_schema <- jsonlite::fromJSON(system.file("extdata", "vpts-csv-table-schema.json", package = "bioRad"),
-      simplifyDataFrame = FALSE, simplifyVector = TRUE
-    )
-  }
-
   data <- dplyr::mutate(
     data,
     radar = as.factor(radar),
@@ -71,37 +65,55 @@ as.vpts <- function(data) {
     regular <- FALSE
   }
 
-# Get attributes
-radar_height <- data[["radar_height"]][1]
-interval <- unique(heights[-1] - heights[-length(heights)])
-wavelength <- data[["radar_wavelength"]][1]
-
-# Check and warn for multiple values of specific attributes and return only the first values of those attributes
-check_multivalue_attributes <- function(data) {
-  attributes <- c("radar_longitude", "radar_latitude", "rcs", "sd_vvp_threshold")
-  first_values <- list()
-  for (attr in attributes) {
-    if (length(unique(data[[attr]])) > 1) {
-      warning(paste0("multiple `", attr, "` values found, storing only first (",
-                     as.character(data[[attr]][1]), ") as the functional attribute."))
+  # Get attributes
+  radar_height <- data[["radar_height"]][1]
+  interval <- unique(heights[-1] - heights[-length(heights)])
+  wavelength <- data[["radar_wavelength"]][1]
+
+  # Check and warn for multiple values of specific attributes and return only the first values of those attributes
+  check_multivalue_attributes <- function(data) {
+    attributes <- c("radar_longitude", "radar_latitude", "rcs", "sd_vvp_threshold")
+    first_values <- list()
+    for (attr in attributes) {
+      if (length(unique(data[[attr]])) > 1) {
+        warning(paste0("multiple ", as.character(substitute(attr))," values found, storing only first (",
+                       as.character(data[[attr]][1]), ") as the functional attribute."))
+      }
+      first_values[[attr]] <- data[[attr]][1]
     }
-    first_values[[attr]] <- data[[attr]][1]
+      return(first_values)
   }
-    return(first_values)
-}
 
   first_values <- check_multivalue_attributes(data)
-  
+
   # Directly extract and assign values from the list
   lon <- first_values$radar_longitude
   lat <- first_values$radar_latitude
   rcs <- first_values$rcs
   sd_vvp_threshold <- first_values$sd_vvp_threshold
-
-  # Convert dataframe
-  maskvars <- c("radar", "rcs", "sd_vvp_threshold", "radar_latitude", "radar_longitude", "radar_height", "radar_wavelength", "source_file", "datetime", "height", "sunrise", "sunset", "day")
 
-  data <- df_to_mat_list(data, maskvars, cached_schema)
+  # column names not to store in the vpts$data slot
+  radvars_exclude <- c("radar","datetime","height","rcs","sd_vvp_threshold","radar_latitude","radar_longitude","radar_height","radar_wavelength")
+  # radvars to include in vpts$data slot
+  radvars <- names(data)[!names(data) %in% radvars_exclude]
+
+  # calculate number of vertical profiles present
+  n_vp <- nrow(data)/length(heights)
+
+  # cast data.frame to list of matrices
+  data_output <- lapply(radvars, function(x) matrix(data[[x]],ncol=n_vp))
+  names(data_output)=radvars
+
+  # List of vectors to check
+  vectors_to_check <- list(heights = heights, interval = interval, radar_height = radar_height, lon = lon, lat = lat)
+
+  # Identify empty vectors
+  empty_vectors <- names(vectors_to_check)[sapply(vectors_to_check, function(v) length(v) == 0)]
+
+  # Stop execution if any empty vectors are found
+  if (length(empty_vectors) > 0) {
+      stop("Empty vectors detected: ", paste(empty_vectors, collapse=", "))
+  }
 
   # Create vpts object
   output <- list(
@@ -110,7 +122,7 @@ check_multivalue_attributes <- function(data) {
     height = heights,
     daterange = c(min(datetime), max(datetime)),
     timesteps = difftimes,
-    data = data,
+    data = data_output,
     attributes = list(
       where = data.frame(
         interval = as.integer(interval),

R/calculate_vp.R

@@ -173,18 +173,22 @@
 #' # Locate and read the polar volume example file
 #' pvolfile_source <- system.file("extdata", "volume.h5", package = "bioRad")
 #'
-#' # Copy the file to a home directory with read/write permissions
+#' # Copy the file to a temporary directory with read/write permissions
 #' pvolfile <- paste0(tempdir(),"/volume.h5")
 #' file.copy(pvolfile_source, pvolfile)
 #'
 #' # Calculate the profile
+#' if (requireNamespace("vol2birdR", quietly = TRUE)) {
 #' vp <- calculate_vp(pvolfile)
-#'
+#' 
 #' # Get summary info
 #' vp
 #'
 #' # Clean up
 #' file.remove(pvolfile)
+#'
+#' }
+#'
 calculate_vp <- function(file, vpfile = "", pvolfile_out = "",
                          autoconf = FALSE, verbose = FALSE, warnings = TRUE,
                          mount, sd_vvp_threshold,

R/composite_ppi.R

@@ -75,8 +75,10 @@
 #' composite <- composite_ppi(ppis, method = "max", res=1000)
 #'
 #' # Plot the calculated max product on the basemap
+#' if (all(sapply(c("ggspatial","prettymapr", "rosm"), requireNamespace, quietly = TRUE))) {
 #' map(composite)
 #' }
+#' }
 composite_ppi <-
   function(x,
            param = "all",

R/data.R

@@ -70,3 +70,14 @@
 # example_vpts$attributes$where$lat <- 42.2
 # example_vpts$attributes$where$lon <- -75.98
 # save(example_vpts, file = "data/example_vpts.rda", compress = "xz")
+
+#' ENRAM-defined VPTS schema
+#'
+#' A dataset containing the schema definitions for VPTS data validation.
+#' @rdname vpts_schema
+#' @keywords internal
+#' @return A list object containing the data model for the standard VPTS exchange format.
+#' @examples
+#' # Reload vpts_schema from package (e.g. in case it was altered)
+#' data(vpts_schema)
+"vpts_schema"

R/download_pvolfiles.R

@@ -21,6 +21,7 @@
 #' a message and a progress bar in the console indicating the download status. 
 #' @examples
 #' # create temporary directory
+#' if (requireNamespace("aws.s3", quietly = TRUE)) {
 #' temp_dir <- paste0(tempdir(),"/bioRad_tmp_files")
 #' dir.create(temp_dir)
 #' download_pvolfiles(
@@ -32,6 +33,7 @@
 #' )
 #' # Clean up
 #' unlink(temp_dir, recursive = TRUE)
+#' }
 download_pvolfiles <- function(date_min, date_max, radar,
                                directory = ".", overwrite = FALSE,
                                bucket = "noaa-nexrad-level2") {

R/download_vpfiles.R

@@ -21,6 +21,7 @@
 #' @export
 #'
 #' @seealso
+#' * [read_vpts()]
 #' * [select_vpfiles()]
 #' * [read_vpfiles()]
 #'

R/hooks.R

@@ -1,9 +1,10 @@
 .onLoad <- function(libname, pkgname) {
   register_all_s3_methods() # dynamically registers non-imported pkgs (tidyverse) # nocov
 }
+
 .onAttach <- function(libname, pkgname) {
   packageStartupMessage(paste("Welcome to", pkgname, "version", utils::packageVersion(pkgname)))
-  if (rlang::is_installed("vol2birdR")) {
+  if (requireNamespace("vol2birdR", quietly = TRUE)) {
     packageStartupMessage(paste("using vol2birdR version ", utils::packageVersion("vol2birdR"), ifelse(vol2birdR::mistnet_exists(), " (MistNet installed)", " (MistNet not installed)"), sep = ""))
   }
 }

R/integrate_to_ppi.R

@@ -119,7 +119,9 @@
 #' plot(ppi, param = "VID", zlim = c(0, 200))
 #'
 #' # Download a basemap and map the ppi
+#' if (all(sapply(c("ggspatial","prettymapr", "rosm"), requireNamespace, quietly = TRUE))) {
 #' map(ppi)
+#' }
 #'
 #' # The ppi can also be projected on a user-defined raster, as follows:
 #'

R/list_vpts_aloft.R

@@ -16,7 +16,9 @@
 #' @export
 #'
 #' @examples
-#' list_vpts_aloft(radars = "bejab")
+#' if (requireNamespace("aws.s3", quietly = TRUE)) {
+#' list_vpts_aloft(radars = "bejab", date_min='2018-10-01', date_max = '2018-12-31')
+#' }
 list_vpts_aloft <- function(date_min = NULL,
                             date_max = NULL,
                             radars = NULL,

R/map.R

@@ -47,6 +47,7 @@
 #' # Project a scan as a ppi
 #' ppi <- project_as_ppi(example_scan)
 #' \donttest{
+#' if (all(sapply(c("ggspatial","prettymapr", "rosm"), requireNamespace, quietly = TRUE))) {
 #' # Choose a basemap
 #' basemap <- rosm::osm.types()[1]
 #'
@@ -71,6 +72,7 @@
 #' # Crop the map
 #' map(ppi, map = basemap, xlim = c(12.4, 13.2), ylim = c(56, 56.5))
 #' }
+#' }
 map <- function(x, ...) {
   UseMethod("map", x)
 }
@@ -108,7 +110,7 @@ map.ppi <- function(x, map="cartolight", param, alpha = 0.7, xlim, ylim, zlim =
   }
 
   # check that suggested dependencies are presetn
-  rlang::check_installed(c("ggspatial","prettymapr"),'to map ppi\'s')
+  rlang::check_installed(c("ggspatial","prettymapr", "rosm"),'to map ppi\'s')
 
   assert_valid_basemap <- function(basemap) {
     valid_types <- rosm::osm.types()
@@ -160,7 +162,7 @@ map.ppi <- function(x, map="cartolight", param, alpha = 0.7, xlim, ylim, zlim =
 
   # convert to google earth mercator projection
   data <- suppressWarnings(
-    as.data.frame(sp::spTransform(as(data,"SpatialPointsDataFrame"), sp::CRS("+init=epsg:3857")))
+    as.data.frame(sp::spTransform(methods::as(data,"SpatialPointsDataFrame"), sp::CRS("+init=epsg:3857")))
   )
   # bring z-values within plotting range
   index <- which(data$z < zlim[1])