Removed dependencies on srr and geosphere

DESCRIPTION

@@ -17,13 +17,13 @@ URL: https://github.com/GlobalEcologyLab/poems, https://globalecologylab.github.
 BugReports: https://github.com/GlobalEcologyLab/poems/issues
 Encoding: UTF-8
 RoxygenNote: 7.3.1
-Roxygen: list(markdown = TRUE, roclets = c ("namespace", "rd", "srr::srr_stats_roclet"))
+Roxygen: list(markdown = TRUE)
 Imports:
     abc (>= 2.1),
     doParallel (>= 1.0.16),
     foreach (>= 1.5.1),
-    gdistance (>= 1.3.6),
     geosphere (>= 1.5.10),
+    fossil (>= 0.4.0),
     lhs (>= 1.1.1),
     metRology (>= 0.9.28.1),
     R6 (>= 2.5.0),
@@ -62,7 +62,6 @@ Collate:
     'population_transformation.R'
     'population_transitions.R'
     'population_simulator.R'
-    'srr-stats-standards.R'
 Suggests: 
     knitr,
     rmarkdown,

NAMESPACE

@@ -38,8 +38,7 @@ importFrom(foreach,foreach)
 importFrom(gdistance,costDistance)
 importFrom(gdistance,geoCorrection)
 importFrom(gdistance,transition)
-importFrom(geosphere,distGeo)
-importFrom(geosphere,distm)
+importFrom(fossil,earth.dist)
 importFrom(lhs,randomLHS)
 importFrom(metRology,qtri)
 importFrom(qs,qread)

R/DispersalFriction.R

@@ -1,7 +1,5 @@
 #' R6 class representing a dispersal friction.
-#' @srrstats {G4.0} WHen it writes to disk, this function writes .RData files 
-#' only and does not accept any other specification of file type/suffix.
-#' 
+#'
 #' @description
 #' \code{\link[R6:R6Class]{R6}} class functionality for modeling sea, ice and other
 #' frictional barriers to dispersal within a spatially-explicit population model. The
@@ -108,18 +106,18 @@ DispersalFriction <- R6Class("DispersalFriction",
         dispersal_indices <- as.matrix(dispersal_indices)
       }
 
-      # Convert to matrix if array 
+      # Convert to matrix if array
       if (is.array(dispersal_indices)) {
         dispersal_indices <- as.matrix(dispersal_indices)
       }
 
       # Ensure dispersal indices are correctly set and are consistent with coordinates
-      if (is.null(dispersal_indices) || !all(is.integer(dispersal_indices)) || 
+      if (is.null(dispersal_indices) || !all(is.integer(dispersal_indices)) ||
         !all(dispersal_indices >= 1) ||
         !is.matrix(dispersal_indices) || ncol(dispersal_indices) != 2 ||
         nrow(dispersal_indices) > self$region$region_cells^2 ||
         max(dispersal_indices) > self$region$region_cells) {
-        stop("Dispersal indices must be a two-column matrix representing the 
+        stop("Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix", call. = FALSE)
       }

R/DispersalGenerator.R

@@ -45,8 +45,7 @@
 #' ))
 #'
 #' @importFrom R6 R6Class
-#' @importFrom geosphere distm
-#' @importFrom geosphere distGeo
+#' @importFrom fossil earth.dist
 #' @import raster
 #' @include Generator.R
 #' @include DispersalTemplate.R
@@ -202,7 +201,7 @@ DispersalGenerator <- R6Class("DispersalGenerator",
         }
         if (!self$region$use_raster || (is.logical(use_longlat) && use_longlat) ||
           length(grep("longlat", as.character(raster::crs(self$region$region_raster)), fixed = TRUE)) > 0) {
-          return(distm(coordinates, coordinates, fun = distGeo) / self$distance_scale)
+          return(earth.dist(coordinates, dist = FALSE)*1000 / self$distance_scale)
         } else { # assume coordinates in meters
           if (is.na(raster::crs(self$region$region_raster))) {
             warning("No coordinate reference system (CRS) specified: assuming coordinates are in meters", call. = FALSE)

R/GenericManager.R

@@ -1,13 +1,11 @@
 #' R6 class representing a generic manager.
-#' @srrstats {G4.0} When a results file suffix is not provided, this class 
-#' defaults to .RData.
-#' 
+#'
 #' @description
 #' \code{\link[R6:R6Class]{R6}} class to represent a generic (abstract) manager for
 #' generating or processing simulation results, as well as optionally generating values
 #' via generators.
-#' 
-#' @examples 
+#'
+#' @examples
 #' generic_manager <- GenericManager$new(
 #'  attr1 = 22:23,
 #'  results_filename_attributes = c("attr1", "example")

R/ResultsManager.R

@@ -1,6 +1,4 @@
 #' R6 class representing a results manager.
-#' @srrstats {G4.0} When a results file suffix is not provided, this class
-#' fills it in with .RData.
 #'
 #' @description
 #' \code{\link[R6:R6Class]{R6}} class to represent a manager for generating summary

R/SimulationManager.R

@@ -1,6 +1,4 @@
 #' R6 class representing a simulation manager.
-#' @srrstats {G4.0} When a results file suffix is not provided, this class
-#' fills it in with .RData.
 #'
 #' @description
 #' \code{\link[R6:R6Class]{R6}} class to represent a manager for running multiple model

R/SpatialCorrelation.R

@@ -32,8 +32,6 @@
 #' env_corr$calculate_distance_matrix() # km
 #'
 #' @importFrom R6 R6Class
-#' @importFrom geosphere distm
-#' @importFrom geosphere distGeo
 #' @include SpatialModel.R
 #' @export SpatialCorrelation
 
@@ -91,7 +89,7 @@ SpatialCorrelation <- R6Class("SpatialCorrelation",
         }
         if (!self$region$use_raster || (is.logical(use_longlat) && use_longlat) ||
           length(grep("longlat", as.character(raster::crs(self$region$region_raster)), fixed = TRUE)) > 0) {
-          return(distm(coordinates, coordinates, fun = distGeo) / self$distance_scale)
+          return(earth.dist(coordinates, dist = FALSE)*1000 / self$distance_scale)
         } else { # assume coordinates in meters
           if (is.na(raster::crs(self$region$region_raster))) {
             warning("No coordinate reference system (CRS) specified: assuming coordinates are in meters", call. = FALSE)

R/Validator.R

@@ -1,15 +1,11 @@
 #' R6 class representing a pattern-oriented validator.
 #'
-#' @srrstats {G1.3} We clearly define here what pattern-oriented validation is.
-#' @srrstats {G4.0} When validation diagnostics are written to disk, they are
-#' always written as .pdf files. No alternative file suffix is accepted.
-#' 
 #' @description
 #' \code{\link[R6:R6Class]{R6}} class for pattern-oriented validation and simulation
 #' model ensemble selection. Pattern-oriented validation is a statistical
 #' approach to compare patterns generated in simulations against observed
 #' empirical patterns.
-#' 
+#'
 #' The class wraps functionality for the validation approach,
 #' typically utilizing an external library, the default being the approximate Bayesian
 #' computation (ABC) \code{\link[abc:abc]{abc}} library, and includes methods for

README.Rmd

@@ -13,18 +13,6 @@ knitr::opts_chunk$set(
 )
 ```
 
-```{r srr-tags, eval = FALSE, echo = FALSE}
-#' General statistical software standards addressed in documentation outside of .R files
-#'
-#' @srrstats {G1.0} References from the literature for this package are given in the References section of this document.
-#' @srrstats {G1.1} The README explains how this package relates to other algorithms.
-#' @srrstats {G1.2} A life-cycle statement is provided in the CONTRIBUTING.md document.
-#' @srrstats {G1.3} Here we define the statistical term "pattern-oriented modeling."
-#' @srrstats {G1.4} All documentation of functions and classes is done with roxygen2 tags. 
-#' There are no non-exported functions or classes.
-#' @srrstats {SP2.1} `poems` uses `sf` and not `sp`.
-```
-
 # poems: Pattern-oriented ensemble modeling system (for spatially explicit populations) <img src='man/figures/logo.svg' align="right" height="125" />
 
 <!-- badges: start -->

tests/testthat/test_dispersal_friction.R

@@ -85,52 +85,52 @@ test_that("distance multiplier calculation errors", {
   )
   expect_error(
     dispersal_friction$calculate_distance_multipliers(dispersal_indices = "wrong"),
-    "Dispersal indices must be a two-column matrix representing the 
+    "Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix"
   )
   expect_error(
     dispersal_friction$calculate_distance_multipliers(dispersal_indices = dispersal_indices - 1),
-    "Dispersal indices must be a two-column matrix representing the 
+    "Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix"
   )
   expect_error(
     dispersal_friction$calculate_distance_multipliers(dispersal_indices = dispersal_indices + 1),
-    "Dispersal indices must be a two-column matrix representing the 
+    "Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix"
   )
   expect_error(
     dispersal_friction$calculate_distance_multipliers(dispersal_indices = dispersal_indices / 3),
-    "Dispersal indices must be a two-column matrix representing the 
+    "Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix"
   )
   expect_error(
     dispersal_friction$calculate_distance_multipliers(dispersal_indices = as.vector(dispersal_indices)),
-    "Dispersal indices must be a two-column matrix representing the 
+    "Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix"
   )
   expect_error(
     dispersal_friction$calculate_distance_multipliers(dispersal_indices = cbind(dispersal_indices, dispersal_indices[, 1])),
-    "Dispersal indices must be a two-column matrix representing the 
+    "Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix"
   )
   dispersal_indices <- which(distance_matrix > 0, arr.ind = TRUE)
   expect_error(
     dispersal_friction$calculate_distance_multipliers(dispersal_indices = rbind(dispersal_indices, dispersal_indices)),
-    "Dispersal indices must be a two-column matrix representing the 
+    "Dispersal indices must be a two-column matrix representing the
         target and source coordinate index for each in-range migration, or a
         data.frame or array that can be converted to such a two-column matrix"
   )
 })
 
 test_that("distance multiplier calculations", {
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates) / 1000
   dispersal_indices <- which(distance_matrix > 1 & distance_matrix <= 350, arr.ind = TRUE)
   colnames(dispersal_indices) <- c("target_pop", "source_pop")
   conductance_matrix <- array(1, c(16, 10))

tests/testthat/test_dispersal_generator.R

@@ -43,7 +43,7 @@ test_that("initialization and parameter setting", {
 test_that("calculate distance matrix and classes", {
   # Region with longlat coordinates
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo)
+  distance_matrix <- fossil::earth.dist(coordinates, dist = FALSE)*1000
   dispersal_gen <- DispersalGenerator$new()
   expect_error(
     dispersal_gen$calculate_distance_matrix(),
@@ -78,7 +78,7 @@ test_that("calculate distance matrix and classes", {
 
 test_that("calculate distance data", {
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   dispersal_gen <- DispersalGenerator$new()
   # Manually calculate expected distance data (no dispersal friction)
   distance_data <- which(distance_matrix > 1 & distance_matrix <= 400, arr.ind = TRUE)
@@ -121,7 +121,7 @@ test_that("calculate distance data", {
 
 test_that("calculate dispersals", {
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   dispersal_gen <- DispersalGenerator$new(coordinates = coordinates, distance_classes = seq(100, 400, 20))
   # Pre-calculation required
   expect_equal(
@@ -167,7 +167,7 @@ test_that("calculate dispersals", {
 
 test_that("connect dispersal friction object", {
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   dispersal_gen <- DispersalGenerator$new(coordinates = coordinates, distance_classes = seq(100, 400, 20))
   dispersal_gen$calculate_distance_data(distance_matrix = distance_matrix)
   # Errors, warnings, consistency checks
@@ -232,7 +232,7 @@ test_that("connect dispersal friction object", {
 test_that("calculate distance data with dispersal friction object", {
   # Region and conductance values with longlat coordinates
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   # Distance data base as before
   dispersal_gen <- DispersalGenerator$new(coordinates = coordinates, distance_classes = seq(100, 400, 20))
   dispersal_gen$calculate_distance_data(distance_matrix = distance_matrix)
@@ -279,7 +279,7 @@ test_that("calculate distance data with dispersal friction object", {
 
 test_that("calculate dispersals with dispersal friction", {
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   conductance_matrix <- array(1, c(16, 10))
   conductance_matrix[1, 1] <- 0.5
   conductance_matrix[c(2, 3, 5, 6, 7, 9, 10, 11), 2] <- 0 # isolate coordinate (1, 1)
@@ -333,7 +333,7 @@ test_that("calculate dispersals with dispersal friction", {
     region = region, distance_classes = seq(100, 400, 20),
     proportion = 0.4, breadth = 110, max_distance = 300
   )
-  distance_matrix <- geosphere::distm(region$coordinates, region$coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   distance_matrix[which(distance_matrix < 1)] <- 0 # ensure actual zero distance for self-referenced cells
   dispersal_gen$calculate_distance_data(distance_matrix = distance_matrix)
   dispersal_gen$calculate_dispersals()
@@ -353,7 +353,7 @@ test_that("calculate dispersals with dispersal friction", {
 
 test_that("cloning and generation", {
   coordinates <- data.frame(x = rep(1:4, 4), y = rep(1:4, each = 4))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   distance_matrix[which(distance_matrix < 1)] <- 0 # ensure actual zero distance for self-referenced cells
   dispersal_gen <- DispersalGenerator$new(coordinates = coordinates, distance_classes = seq(100, 400, 20))
   expect_equal(dispersal_gen$generative_requirements, list(dispersal_data = "default"))

tests/testthat/test_population_dispersal_function.R

@@ -549,7 +549,7 @@ test_that("density dependent dispersal", {
     distance_scale = 1000,
     distance_classes = seq(100, 400, 20)
   )
-  distance_matrix <- geosphere::distm(region$coordinates, region$coordinates, fun = geosphere::distGeo) / 1000
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F)
   distance_matrix[which(distance_matrix < 1)] <- 0 # ensure actual zero distance for self-referenced cells
   dispersal_gen$calculate_distance_data(distance_matrix = distance_matrix)
   dispersal_gen$calculate_dispersals(type = "matrix")

tests/testthat/test_spatial_correlation.R

@@ -37,7 +37,7 @@ test_that("initialization and parameter setting", {
 test_that("calculate distance matrix", {
   # Latitude/longitude coordinates
   coordinates1 <- array(c(1:4, 4:1), c(7, 2))
-  distance_matrix1 <- geosphere::distm(coordinates1, coordinates1, fun = geosphere::distGeo)
+  distance_matrix1 <- fossil::earth.dist(coordinates, dist = FALSE)*1000
   spatial_correlation <- SpatialCorrelation$new()
   expect_error(
     spatial_correlation$calculate_distance_matrix(),
@@ -84,7 +84,7 @@ test_that("calculate distance matrix", {
 test_that("calculate correlations", {
   # Default threshold (0.0000001)
   coordinates <- array(c(1:4, 4:1), c(7, 2))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000 # km
+  distance_matrix <- fossil::earth.dist(coordinates, dist = FALSE) # km
   correlation_matrix <- 0.6 * exp(-1 * distance_matrix / 200)
   diag(correlation_matrix) <- 1
   spatial_correlation <- SpatialCorrelation$new(correlation_amplitude = 0.6, correlation_breadth = 200)
@@ -119,7 +119,7 @@ test_that("calculate correlations", {
 
 test_that("calculate Cholesky decomposition", {
   coordinates <- array(c(1:4, 4:1), c(7, 2))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000 # km
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   correlation_matrix <- 0.6 * exp(-1 * distance_matrix / 200)
   diag(correlation_matrix) <- 1
   spatial_correlation <- SpatialCorrelation$new(
@@ -137,7 +137,7 @@ test_that("calculate Cholesky decomposition", {
 
 test_that("calculate compact decomposition", {
   coordinates <- array(c(1:4, 4:1), c(7, 2))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000 # km
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   correlation_matrix <- 0.6 * exp(-1 * distance_matrix / 32)
   diag(correlation_matrix) <- 1
   spatial_correlation <- SpatialCorrelation$new(
@@ -158,7 +158,7 @@ test_that("calculate compact decomposition", {
 
 test_that("generate correlated normal deviates", {
   coordinates <- array(c(1:4, 4:1), c(7, 2))
-  distance_matrix <- geosphere::distm(coordinates, coordinates, fun = geosphere::distGeo) / 1000 # km
+  distance_matrix <- fossil::earth.dist(coordinates, dist = F) # km
   correlation_matrix <- 0.6 * exp(-1 * distance_matrix / 32)
   diag(correlation_matrix) <- 1
   spatial_correlation <- SpatialCorrelation$new(