Merge branch 'master' into pull_requests

.Rbuildignore

@@ -9,3 +9,6 @@ frescalo.exe
 ^docs$
 misc/
 ^appveyor\.yml$
+^\.github$
+^doc$
+^Meta$

.github/.gitignore

@@ -0,0 +1 @@
+*.html

.github/workflows/R-CMD-check.yaml

@@ -0,0 +1,51 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [master, pull_requests]
+  pull_request:
+    branches: [master, pull_requests]
+
+name: R-CMD-check
+
+jobs:
+  R-CMD-check:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: macos-latest,   r: 'release'}
+          - {os: windows-latest, r: 'release'}
+          - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
+          - {os: ubuntu-latest,   r: 'release'}
+          - {os: ubuntu-latest,   r: 'oldrel-1'}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-snapshots: true
+          build_args: 'c("--no-build-vignettes", "--no-manual")'
+          args: 'c("--no-vignettes", "--no-manual")'

.gitignore

@@ -1,5 +1,6 @@
-# History files
+# History files and data files
 .Rhistory
+.Rdata
 
 # Example code in package build process
 *-Ex.R
@@ -11,3 +12,5 @@ frescalo.exe
 sparta.Rproj
 
 misc/
+/doc/
+/Meta/

DESCRIPTION

@@ -1,40 +1,57 @@
-Package: sparta
 Type: Package
+Package: sparta
 Title: Trend Analysis for Unstructured Data
 Version: 0.2.19
 Date: 2020-05-26
-Authors@R: c(person("Tom", "August", role = c("aut", "cre"), email = "[email protected]"),
-             person("Gary", "Powney", role = c("aut")),
-             person("Charlie", "Outhwaite", role = c("aut")),
-             person("Colin", "Harrower", role = c("aut")),
-             person("Mark", "Hill", role = c("aut")),
-             person("Jack", "Hatfield", role = c("aut")),
-             person("Francesca", "Mancini", role = c("aut")),
-             person("Nick", "Isaac", role = c("aut")))
-Maintainer: Tom August <[email protected]>
-Description: Methods used to analyse trends in unstructured
-    occurrence datasets such as those collected by volunteer recording
-    schemes.
+Authors@R: c(
+    person("Dylan", "Carbone", email = "[email protected]", role = c("aut", "cre"),
+           comment = c(ORCID = "0009-0003-5290-786X")),
+    person("Tom", "August", email = "[email protected]", role = "aut",
+           comment = c(ORCID = "0000-0003-1116-3385")),
+    person("Gary", "Powney", role = "aut",
+           comment = c(ORCID = "0000-0003-3313-7786")),
+    person("Charlie", "Outhwaite", role = "aut",
+           comment = c(ORCID = "0000-0001-9997-6780")),
+    person("Jack", "Hatfield", role = "aut",
+           comment = c(ORCID = "0000-0002-6361-0629")),
+    person("Nick", "Isaac", role = "aut",
+           comment = c(ORCID = "0000-0002-4869-8052")),
+    person("Francesca", "Mancini", role = "aut",
+           comment = c(ORCID = "0000-0003-4085-4978")),
+    person("Mark", "Hill", role = "aut",
+           comment = c(ORCID = "0000-0002-3323-4458")),
+    person("Colin", "Harrower", role = "aut",
+           comment = c(ORCID = "0000-0001-5070-5293"))
+  )
+Maintainer: Dylan Carbone <[email protected]>
+Description: Methods used to analyse trends in unstructured occurrence
+    datasets such as those collected by volunteer recording schemes.
 License: MIT + file LICENSE
+URL: https://github.com/BiologicalRecordsCentre/sparta
+BugReports: https://github.com/BiologicalRecordsCentre/sparta/issues
 Depends:
-    R (>= 3.1.0),
-    lme4 (>= 1.0)
+    lme4 (>= 1.0),
+    R (>= 3.5.0)
 Imports:
-    plyr,
+    boot,
     dplyr (>= 0.4.1),
-    sp,
-    reshape2,
-    ggplot2,
     gdata,
+    ggplot2,
     LearnBayes,
+    plyr,
+    reshape2,
     rmarkdown,
-    boot
+    sp,
+    xfun (>= 0.4.3)
 Suggests:
-    testthat (>= 0.8.0),
-    roxygen2,
     knitr,
-    R2jags
-VignetteBuilder: knitr
+    R2jags,
+    roxygen2,
+    testthat (>= 0.8.0),
+VignetteBuilder: 
+    knitr
+Encoding: UTF-8
 LazyData: TRUE
 RoxygenNote: 7.2.3
-Encoding: UTF-8
+SystemRequirements: JAGS
+    (https://sourceforge.net/projects/mcmc-jags/files/JAGS/)

R/plot_DetectionOverTime.R

@@ -4,8 +4,8 @@
 
 #' @param model a fitted sparta model of class \code{OccDet}.
 #' @param spname optional name of the species (used for plotting)
-#' @param bins number of points to estimate across the year. Defaults to 12
-#' @param density_function whether the model used a density function to fit Julian date. This form was implemented from version 0.1.48 onwards. For models ran using earlier versions of the package this should be set to FALSE
+#' @param min.yr Minimum year for the detection (e.g., 1990).
+#' @param CI Confidence interval
 #' 
 #' @details 
 #' Takes a object of \code{OccDet}

R/plot_DetectionPhenology.R

@@ -1,26 +1,26 @@
-#' Diagnostics for the detectability with respect to Julian Date 
-#' 
+#' Diagnostics for the detectability with respect to Julian Date
+#'
 #' Creates a plot of detectability over the season and calculates some simple statistics
 #'
 #' @param model a fitted sparta model of class \code{OccDet}.
 #' @param spname optional name of the species (used for plotting)
 #' @param bins number of points to estimate across the year. Defaults to 12
 #' @param density_function whether the model used a density function to fit Julian date. This form was implemented from version 0.1.48 onwards. For models ran using earlier versions of the package this should be set to FALSE
-#' 
-#' @details 
+#'
+#' @details
 #' Takes a object of \code{OccDet} fitted with the \code{jul_date} option
-#' 
+#'
 #' Calculates the phenology of detection and produces a plot of detectability over time for the reference data type.
 #'
 #' @return This function returns plot showing the detection probability on the y axis and Julian day on the x.
 #'         The data within the output list shows the Julian day for each point estimated (equal to the number of bins)
 #'         and the mean detection probability with 95% credible intervals.
-#' 
-#' @references van Strien, A.J., Termaat, T., Groenendijk, D., Mensing, V. & Kéry, M. (2010) 
-#'             Site-occupancy models may offer new opportunities for dragonfly monitoring based on daily species lists. 
+#'
+#' @references van Strien, A.J., Termaat, T., Groenendijk, D., Mensing, V. & Kéry, M. (2010)
+#'             Site-occupancy models may offer new opportunities for dragonfly monitoring based on daily species lists.
 #'             \emph{Basic and Applied Ecology}, 11, 495–503.
 #'
-#' @importFrom reshape2 melt 
+#' @importFrom reshape2 melt
 #' @importFrom plyr ddply
 #' @importFrom ggplot2 ggplot
 #' @importFrom boot inv.logit
@@ -34,64 +34,65 @@
 ###########################################
 
 
-plot_DetectionPhenology <- function(model, spname=NULL, bins=12, density_function = TRUE){
-
+plot_DetectionPhenology <- function(model, spname = NULL, bins = 12, density_function = TRUE) {
   data <- model$BUGSoutput$sims.list
-  
-  if(!"beta1" %in% names(data))
+
+  if (!"beta1" %in% names(data)) {
     stop("no phenological effect was modelled!")
+  }
 
-  # the base: alpha.p is common to all models: 
+  # the base: alpha.p is common to all models:
   # it's the logit probability of detection on a single species list
   # use the average value across years
   pDet1 <- rowMeans(data$alpha.p)
   # pDet1 is an array of dims equal to (niter, nyr)
-  
+
   # Julian dates are 1:
-  jul_dates <- seq(from=1, to=365, length.out=bins)
-  
-  if(density_function == TRUE){ 
-    if(!"beta3" %in% names(data))
+  jul_dates <- seq(from = 1, to = 365, length.out = bins)
+
+  if (density_function == TRUE) {
+    if (!"beta3" %in% names(data)) {
       stop("beta3 not found. Please check that the density function method was used")
+    }
     # we ran the Julian Date option
     # So let's calculate the detection probabilities
-    
-    pDet <- melt(sapply(jul_dates, function(jd){
-      pDet1 + data$beta3[,1] * (1/((2*pi)^0.5 * data$beta2[,1]) * exp(-((jd - data$beta1[,1])^2 / (2* data$beta2[,1]^2))))
+
+    pDet <- melt(sapply(jul_dates, function(jd) {
+      pDet1 + data$beta3[, 1] * (1 / ((2 * pi)^0.5 * data$beta2[, 1]) * exp(-((jd - data$beta1[, 1])^2 / (2 * data$beta2[, 1]^2))))
     }))
-  }else{
+  } else {
     cjd <- jul_dates - 182
     # we ran the Julian Date option
     # So let's scale the detection probabilities to end June (day 180)
-    pDet <- melt(sapply(cjd, function(jd){
-      pDet1 + jd * data$beta1[,1] +  jd^2 * data$beta2[,1]
-    })) 
+    pDet <- melt(sapply(cjd, function(jd) {
+      pDet1 + jd * data$beta1[, 1] + jd^2 * data$beta2[, 1]
+    }))
   }
-  
-  names(pDet) <- c("it", "bin","lgt_pDet")
+
+  names(pDet) <- c("it", "bin", "lgt_pDet")
   pDet$pDet <- inv.logit(pDet$lgt_pDet)
-  
+
   # now summarize these posterior distributions
-  pDet_summary <-ddply(
-    pDet, .(bin), summarise, 
+  pDet_summary <- ddply(
+    pDet, .(bin), summarise,
     mean_pDet = mean(pDet),
     lower95CI = quantile(pDet, 0.025),
-    upper95CI = quantile(pDet, 0.975))
-
-    # now convert the jds back to their equivalent Julian Dates
-  if(density_function == FALSE){pDet_summary$cJulDate <- cjd[pDet_summary$bin]}
-  pDet_summary$JulianDay <- jul_dates[pDet_summary$bin] 
+    upper95CI = quantile(pDet, 0.975)
+  )
+
+  # now convert the jds back to their equivalent Julian Dates
+  if (density_function == FALSE) {
+    pDet_summary$cJulDate <- cjd[pDet_summary$bin]
+  }
+  pDet_summary$JulianDay <- jul_dates[pDet_summary$bin]
 
   # now plot the detection over time
-  gp <- ggplot(data=pDet_summary, x=JulianDay, y=mean_pDet) +
-    geom_line(aes(x=JulianDay, y=mean_pDet)) +
-    geom_ribbon(aes(x=JulianDay, ymin=lower95CI, ymax=upper95CI), alpha=0.2) +
+  gp <- ggplot(data = pDet_summary, x = JulianDay, y = mean_pDet) +
+    geom_line(aes(x = JulianDay, y = mean_pDet)) +
+    geom_ribbon(aes(x = JulianDay, ymin = lower95CI, ymax = upper95CI), alpha = 0.2) +
     ylab("Detection probability") +
     ggtitle(spname) +
     theme_bw()
-  gp 
 
-  # calculate some simple stats
-
+  return(gp)
 }
-

README.md

@@ -1,10 +1,9 @@
 ![Sparta banner](https://raw.githubusercontent.com/AugustT/sparta/master/logo.png)
 
 <!-- badges: start -->
-[![Travis Build Status](https://travis-ci.org/BiologicalRecordsCentre/sparta.svg)](https://travis-ci.org/BiologicalRecordsCentre/sparta)
-[![AppVeyor build status](https://ci.appveyor.com/api/projects/status/github/augustt/sparta?branch=master&svg=true)](https://ci.appveyor.com/project/augustt/sparta)
 [![codecov.io](https://codecov.io/github/BiologicalRecordsCentre/sparta/coverage.svg?branch=master)](https://codecov.io/github/BiologicalRecordsCentre/sparta?branch=master)
 [![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
+[![R-CMD-check](https://github.com/DylanCarbone/sparta/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/DylanCarbone/sparta/actions/workflows/R-CMD-check.yaml)
 <!-- badges: end -->
 
 This R package includes methods used to analyse trends in unstructured occurrence datasets and a range of useful functions for mapping such data in the UK. The package is under continious development, but you can find stable releases in the release section. Note that frescalo currently uses an .exe compiled only for windows.