Merge remote-tracking branch 'origin/master'

.github/workflows/revdepcheck.yaml

@@ -0,0 +1,18 @@
+on:
+  workflow_dispatch:
+    inputs:
+      which:
+        type: choice
+        description: Which dependents to check
+        options:
+        - strong
+        - most
+
+name: Reverse dependency check
+
+jobs:
+  revdep_check:
+    name: Reverse check ${{ inputs.which }} dependents
+    uses: r-devel/recheck/.github/workflows/recheck.yml@v1
+    with:
+      which: ${{ inputs.which }}

DESCRIPTION

@@ -2,12 +2,12 @@ Type: Package
 Package: metR
 Language: en-GB
 Title: Tools for Easier Analysis of Meteorological Fields
-Version: 0.15.0.9000
+Version: 0.16.0.9000
 Authors@R: 
     c(person(given = "Elio",
            family = "Campitelli",
            role = c("cre", "aut"),
-           email = "[email protected]",
+           email = "[email protected]",
            comment = c(ORCID = "0000-0002-7742-9230")))
 Description: Many useful functions and extensions for dealing
     with meteorological data in the tidy data framework. Extends 'ggplot2'
@@ -59,5 +59,5 @@ ByteCompile: yes
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2
 VignetteBuilder: knitr

NEWS.md

@@ -1,14 +1,24 @@
 # metR (development version)
 
+## Bug fixes
+
+-   Longitude scales now properly pass the `trans`/`transform` argument.
+
+# metR 0.16.0
+
 ## New features
 
--   `EOF()`'s `rotate` argument now will take a function to apply to the EOF loadings. `rotate = TRUE` is still supported but deprecated and will default to using `function(x) stats::varimax(x, normalize = FALSE)`.
+-   `EOF()`'s `rotate` argument now will take a function to apply to the EOF loadings.
+    `rotate = TRUE` is still supported but deprecated and will default to using `function(x) stats::varimax(x, normalize = FALSE)`.
+
+-   Contour functions gain a `proj.latlon` to decide if the projection needs to go to latlon coordinates or to projected coordinates.
 
 ## Breaking changes
 
--   The `GetSMNData()` function is defunct. The functionality is a hack and hard to maintain and it's also very specific and should be out of scope for a general package.
+-   The `GetSMNData()` function is defunct. The functionality was a hack and hard to maintain and it's also very specific and should be out of scope for a general package.
 -   The `trans` argument of scales has been renamed to `transform` following ggplot2's change.
 -   `scale_mag()` internals are now much simpler and inherits all the functionality from common continuous scales. (thanks @teunbrand for the suggestion, #186)
+-   The `step` computed variable in `geom_streamline()` now goes from 0 to the total number of steps instead of from negative half to positive half.
 
 # metR 0.15.0
 

R/EOF.R

@@ -33,7 +33,7 @@
 #'
 #' There are some methods implemented
 #' * [summary]
-#' * [screeplot] and the equivalent [autoplot]
+#' * [screeplot] and the equivalent [ggplot2::autoplot]
 #' * [cut.eof]
 #' * [predict]
 #'

R/GetSMNData.R

@@ -1,10 +1,4 @@
 #' Get Meteorological data
-#'
-#' Downloads minimum and maximum temperature station data from
-#' Argentina's National Weather Service's public access. Data availability is not
-#' guaranteed so you are encouraged to check it on
-#' [the website](https://www.smn.gob.ar/descarga-de-datos).
-#'
 #' This function is defunct.
 #'
 #' @param date date vector of dates to fetch data
@@ -14,32 +8,8 @@
 #' @param file.dir optional directory where to save and/or retrieve data
 #'
 #' @return
-#' For `type = "hourly"`, a data.frame with observations of
-#' \describe{
-#'    \item{date}{date}
-#'    \item{t}{temperature in degrees celsius}
-#'    \item{rh}{relative humidity in %}
-#'    \item{slp}{sea level pressure in hPa}
-#'    \item{dir}{wind direction in clockwise degrees from 6 o'clock}
-#'    \item{V}{wind magnitude in m/s}
-#'    \item{station}{station name}
-#' }
-#'
-#' For `type = "daily"`, a data.frame with observations of
-#' \describe{
-#'    \item{date}{date}
-#'    \item{tmax}{maximum daily temperature in degrees celsius}
-#'    \item{tmin}{minimum daily temperature in degrees celsius}
-#'    \item{station}{station name}
-#' }
+#' Nothing
 #'
-#' For `type = "radiation"`, a data.frame with observations of
-#' \describe{
-#'    \item{date}{date}
-#'    \item{global}{global radiation in W/m^2}
-#'    \item{diffuse}{diffuse radiation in W/m^2}
-#'    \item{station}{station name}
-#' }
 #' @export
 GetSMNData <- function(date, type = c("hourly", "daily", "radiation"),  bar = FALSE,
                        cache = TRUE, file.dir = tempdir()) {

R/ReadNetCDF.R

@@ -358,6 +358,7 @@ time_units_factor <- c("days" = 24*3600,
 
 
 .parse_time <- function(time, units, calendar = NULL) {
+    calendar <- tolower(calendar)
     has_since <- grepl("since", units)
     if (!has_since) {
         return(time)
@@ -373,7 +374,7 @@ time_units_factor <- c("days" = 24*3600,
     }
 
 
-    if (!is.null(calendar)) {
+    if (length(calendar) != 0) {
         time <- as.POSIXct(PCICt::as.PCICt(time*time_units_factor[time_unit], cal = calendar, origin = origin),
                            cal = "standard", tz = "UTC", origin = origin)
     } else {

R/WriteNetCDF.R

@@ -0,0 +1,90 @@
+WriteNetCDF <- function(data, file, vars, dims = NULL) {
+
+    if (is.null(names(vars))) {
+        names(vars) <- vars
+    }
+
+    if (any(!names(vars) %in% colnames(data))) {
+        stop("vars not found in data")
+    }
+
+    if (is.null(dims)) {
+        dims <- rev(setdiff(colnames(data), names(vars)))
+    }
+
+    if (is.null(names(dims))) {
+        names(dims) <- dims
+    }
+
+    if (any(!names(dims) %in% colnames(data))) {
+        stop("dims not found in data")
+    }
+
+    order <- do.call(base::order, args = lapply(rev(names(dims)), \(x) data[[x]]))
+
+    nc_dims <- vector(length(dims), mode = "list")
+    for (d in seq_along(dims)) {
+        vals <- data[[names(dims)[d]]][order]
+        vals <- as.numeric(unique(vals))
+
+        n <- length(vals)
+        units <- get_units(data[[names(dims)[d]]])
+        nc_dims[[d]] <- ncdf4::ncdim_def(name = dims[d],
+                                         units = units,
+                                         vals = vals,
+                                         unlim = FALSE,
+                                         create_dimvar = TRUE,
+                                         calendar = NA,
+                                         longname = dims[d])
+    }
+
+    missing_value <- -999
+    nc_vars <- vector(length(vars), mode = "list")
+    for (v in seq_along(vars)) {
+        nc_vars[[v]] <- ncdf4::ncvar_def(name = vars[v],
+                                         units = "",
+                                         dim = nc_dims,
+                                         longname = vars[v],
+                                         missval = missing_value)
+
+    }
+
+    nc_file <- ncdf4::nc_create(file, nc_vars)
+
+    for (v in seq_along(vars)) {
+        ncdf4::ncvar_put(nc_file,
+                         varid = nc_vars[[v]],
+                         vals = data[[names(vars[v])]][order])
+    }
+
+    ncdf4::nc_close(nc_file)
+
+    return(invisible(file))
+}
+
+#' @keywords internal
+get_units <- function(x) {
+    UseMethod("get_units")
+}
+
+#' @keywords internal
+get_units.default <- function(x) {
+    return("")
+}
+
+#' @keywords internal
+get_units.Date <- function(x) {
+    return("days since 1970-01-01 00:00:00")
+}
+
+#' @keywords internal
+get_units.POSIXlt <- function(x) {
+    return("seconds since 1970-01-01 00:00:00")
+}
+
+#' @keywords internal
+get_units.POSIXct <- function(x) {
+    return("seconds since 1970-01-01 00:00:00")
+}
+
+

R/geom_contour_fill.R

@@ -20,6 +20,8 @@
 #'    - A numeric value for constant imputation
 #'    - A function that takes a vector and returns a numeric (e.g. `mean`)
 # #' @param xwrap,ywrap vector of length two used to wrap the circular dimension.
+#' @param proj.latlon Logical indicating if the projection step should project
+#' from a cartographic projection to a lon/lat grid or the other way around.
 #'
 #' @section Aesthetics:
 #' \code{geom_contour_fill} understands the following aesthetics (required aesthetics are in bold):
@@ -67,6 +69,7 @@ geom_contour_fill <- function(mapping = NULL, data = NULL,
                          bins = NULL,
                          binwidth = NULL,
                          proj = NULL,
+                         proj.latlon = TRUE,
                          clip = NULL,
                          kriging = FALSE,
                          global.breaks = TRUE,
@@ -90,6 +93,7 @@ geom_contour_fill <- function(mapping = NULL, data = NULL,
             na.fill = na.fill,
             kriging = kriging,
             proj = proj,
+            proj.latlon = proj.latlon,
             clip = clip,
             global.breaks = global.breaks,
             ...

R/geom_contour_tanaka.R

@@ -81,6 +81,7 @@ geom_contour_tanaka <- function(mapping = NULL, data = NULL,
                                 range = c(0.01, 0.5),
                                 smooth = 0,
                                 proj = NULL,
+                                proj.latlon = TRUE,
                                 clip = NULL,
                                 kriging = FALSE,
                                 na.rm = FALSE,
@@ -107,6 +108,7 @@ geom_contour_tanaka <- function(mapping = NULL, data = NULL,
             smooth = smooth,
             kriging = kriging,
             proj = proj,
+            proj.latlon = proj.latlon,
             clip = clip,
             ...
         )

R/geom_streamline.R

@@ -545,6 +545,7 @@ streamline.f <- function(field, dt = 0.1, S = 3, skip.x = 1, skip.y = 1, nx = NU
     points[, group := interaction(group, piece, end)]
     points[, line := group]
 
+    points[, step := seq(1, .N), by = .(group)]
     return(points[, .(x, y, group, piece, end, step, dx, dy, line)])
 }
 

R/metR-package.R

@@ -1,14 +1,14 @@
 #' @section Overview:
 #' Conceptually it's divided into *visualization tools* and *data tools*.
 #' The former are geoms, stats and scales that help with plotting using
-#' [ggplot2], such as [stat_contour_fill] or [scale_y_level], while the
+#' 'ggplot2', such as [stat_contour_fill] or [scale_y_level], while the
 #' later are functions for common data processing tools in the atmospheric
 #' sciences, such as [Derivate] or [EOF]; these are implemented to work in the
-#' [data.table] paradigm, but also work with regular data frames.
+#' 'data.table' paradigm, but also work with regular data frames.
 #'
 #' To get started, check the vignettes:
 #' * Visualization Tools: `vignette("Visualization-tools", package = "metR")`
-#' * Working with Data: `vignette("Working-with-data", package = "metR")`
+#' * Working with Data: `vignette("Working-with-data", package = "metR")    `
 #'
 #' @name metR
 #' @docType package

R/scale_longitude.R

@@ -36,13 +36,11 @@ scale_x_longitude <- function(name = "", ticks = 30,
                               breaks = seq(-180, 360, by = ticks),
                               expand = c(0, 0),
                               labels = LonLabel,
-                              trans = "identity",
                               ...) {
     # labels = waiver()
     ggplot2::scale_x_continuous(name = name, expand = expand,
                                 breaks = breaks,
                                 labels = labels,
-                                trans = trans,
                                 ...)
 }
 
@@ -52,7 +50,6 @@ scale_y_longitude <- function(name = "", ticks = 60,
                               breaks = seq(-180, 360, by = ticks),
                               expand = c(0, 0),
                               labels = LonLabel,
-                              trans = "identity",
                               ...) {
     ggplot2::scale_y_continuous(name = name, expand = expand,
                        breaks = breaks,