Updates and performance improvements

.Rbuildignore

@@ -17,3 +17,5 @@
 ^\.covrignore$
 ^.*\.log$
 ^touchstone$
+^README\.Rmd$
+^touchstone$

.github/workflows/touchstone-receive.yaml

@@ -1,3 +1,4 @@
+# Modified to follow workflow in EpiNow2
 name: Continuous Benchmarks (Receive)
 
 concurrency:
@@ -6,20 +7,26 @@ concurrency:
 
 on: 
   pull_request:
+    paths:
+      # Where model code is defined: R/, src/, inst/include/
+      - "inst/include/**"
+      - "src/**"
+      - "R/**"
+      # Benchmarking code, config file, and manual trigger
+      - "touchstone/**"
+      - ".github/workflows/touchstone-receive.yaml"
+      - ".github/workflows/touchstone-comment.yaml"
+      - ".benchmark"
 
 permissions:
   contents: read
+  statuses: write
+  pull-requests: write
 
 jobs:
   prepare:
-    runs-on: ubuntu-latest 
-    if:
-      true &&
-      (
-        github.event.pull_request.author_association == 'OWNER' ||
-        github.event.pull_request.author_association == 'MEMBER' ||
-        github.event.pull_request.author_association == 'COLLABORATOR' 
-      )
+    runs-on: ubuntu-latest
+    # Allow benchmarking workflow to run for external contribs
     outputs:
       config: ${{ steps.read_touchstone_config.outputs.config }}
     steps:
@@ -50,10 +57,9 @@ jobs:
       RSPM: ${{ matrix.config.rspm }}
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
     steps:
-      - uses: lorenzwalthert/touchstone/actions/receive@v1
+      - uses: lorenzwalthert/touchstone/actions/receive@main
         with:
           cache-version: 1
           benchmarking_repo: ${{ matrix.config.benchmarking_repo }}
           benchmarking_ref: ${{ matrix.config.benchmarking_ref }}
-          benchmarking_path: ${{ matrix.config.benchmarking_path }} 
-          force_upstream: true
+          benchmarking_path: ${{ matrix.config.benchmarking_path }}

DESCRIPTION

@@ -1,42 +1,48 @@
 Package: pathomove
-Title: Individual-based model of animal movement strategies evolved under pathogen risk
-Version: 1.0.0.0000
+Title: Individual-based model of animal movement strategies evolved under
+    pathogen risk
+Version: 1.0.1
 Authors@R:
-    c(person(given = "Pratik",
-           family = "Gupte",
-           role = c("aut", "cre", "cph"),
-           email = "pratikgupte16@gmail.com",
-           comment = c(ORCID = "https://orcid.org/0000-0001-5294-7819")))
-Description: Runs the Pathomove simulation, a mechanisitic, spatially explicit, individual-based model of the evolution of animal social movement strategies under different scenarios of pathogen transmission risk, primarily focusing on the introduction of a novel pathogen to a population, as described in Gupte et al. (2022) <doi:10.1101/2022.03.09.483239>.
+    person("Pratik", "Gupte", , "pratikgupte16@gmail.com", role = c("aut", "cre", "cph"),
+           comment = c(ORCID = "https://orcid.org/0000-0001-5294-7819"))
+Description: Runs the Pathomove simulation, a mechanisitic, spatially
+    explicit, individual-based model of the evolution of animal social
+    movement strategies under different scenarios of pathogen transmission
+    risk, primarily focusing on the introduction of a novel pathogen to a
+    population, as described in Gupte et al. (2022)
+    <doi:10.1101/2022.03.09.483239>.
+License: MIT + file LICENSE
 URL: https://github.com/pratikunterwegs/pathomove
 BugReports: https://github.com/pratikunterwegs/pathomove/issues
-License: MIT + file LICENSE
-Encoding: UTF-8
-LazyData: true
-Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.1
-LinkingTo: 
-    Rcpp,
-    RcppParallel,
-    BH,
-    testthat
 Imports: 
-    Rcpp,
-    RcppParallel,
     assertthat,
     data.table,
     glue,
     igraph,
-    tidygraph,
-    methods
+    methods,
+    Rcpp,
+    RcppParallel,
+    tidygraph
 Suggests: 
-    testthat (>= 3.0.0),
-    ssh,
-    xml2,
+    covr,
     knitr,
     rmarkdown,
-    covr
-SystemRequirements: 
-    C++14
-VignetteBuilder: knitr
+    spelling,
+    ssh,
+    testthat (>= 3.0.0),
+    xml2
+LinkingTo: 
+    BH,
+    Rcpp,
+    RcppEigen,
+    RcppParallel,
+    testthat
+VignetteBuilder: 
+    knitr
 Config/testthat/edition: 3
+Encoding: UTF-8
+Language: en-GB
+LazyData: true
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.3.2
+SystemRequirements: C++14

NAMESPACE

@@ -17,6 +17,7 @@ export(make_parameter_file)
 export(run_pathomove)
 export(use_cluster)
 exportClasses(pathomove_output)
+import(RcppEigen)
 import(data.table)
 importFrom(Rcpp,sourceCpp)
 importFrom(RcppParallel,RcppParallelLibs)

R/RcppExports.R

@@ -75,9 +75,10 @@ get_test_landscape <- function(nItems, landsize, nClusters, clusterSpread, regen
 #' pathogen introduction are drawn.
 #' @param seed An integer number that is the seed for the R RNG. Defaults to
 #' zero.
+#' @param print_progress A boolean for whether to print progress.
 #' @export
 #' @return An S4 class, `pathomove_output`, with simulation outcomes.
-run_pathomove <- function(scenario = 1L, popsize = 100L, nItems = 1800L, landsize = 60.0, nClusters = 60L, clusterSpread = 1.0, tmax = 100L, genmax = 100L, g_patho_init = 70L, n_samples = 5L, range_food = 1.0, range_agents = 1.0, range_move = 1.0, handling_time = 5L, regen_time = 50L, pTransmit = 0.05, p_v_transmit = 0.05, initialInfections = 20L, costInfect = 0.25, multithreaded = TRUE, dispersal = 2.0, infect_percent = FALSE, vertical = FALSE, reprod_threshold = FALSE, mProb = 0.01, mSize = 0.01, spillover_rate = 1.0, seed = 0L) {
-    .Call(`_pathomove_run_pathomove`, scenario, popsize, nItems, landsize, nClusters, clusterSpread, tmax, genmax, g_patho_init, n_samples, range_food, range_agents, range_move, handling_time, regen_time, pTransmit, p_v_transmit, initialInfections, costInfect, multithreaded, dispersal, infect_percent, vertical, reprod_threshold, mProb, mSize, spillover_rate, seed)
+run_pathomove <- function(scenario = 1L, popsize = 100L, nItems = 1800L, landsize = 60.0, nClusters = 60L, clusterSpread = 1.0, tmax = 100L, genmax = 100L, g_patho_init = 70L, n_samples = 5L, range_food = 1.0, range_agents = 1.0, range_move = 1.0, handling_time = 5L, regen_time = 50L, pTransmit = 0.05, p_v_transmit = 0.05, initialInfections = 20L, costInfect = 0.25, multithreaded = TRUE, dispersal = 2.0, infect_percent = FALSE, vertical = FALSE, reprod_threshold = FALSE, mProb = 0.01, mSize = 0.01, spillover_rate = 1.0, seed = 0L, print_progress = FALSE) {
+    .Call(`_pathomove_run_pathomove`, scenario, popsize, nItems, landsize, nClusters, clusterSpread, tmax, genmax, g_patho_init, n_samples, range_food, range_agents, range_move, handling_time, regen_time, pTransmit, p_v_transmit, initialInfections, costInfect, multithreaded, dispersal, infect_percent, vertical, reprod_threshold, mProb, mSize, spillover_rate, seed, print_progress)
 }
 

R/fun_check_cluster.R

@@ -6,8 +6,10 @@
 #' @return None, should check and prepare cluster.
 #' @export
 #'
-check_prepare_cluster <- function(ssh_con = "some_server",
-                                  password = "your_password") {
+check_prepare_cluster <- function(
+  ssh_con = "some_server",
+  password = "your_password"
+) {
   message("checking cluster for pathomove")
   # connect to server
   s <- ssh::ssh_connect(ssh_con, passwd = password)

R/fun_handle_data.R

@@ -9,8 +9,7 @@
 #' @return A `data.table` with all reported generations.
 #' @export
 #'
-get_trait_data <- function(object,
-                           scaled_preferences = TRUE) {
+get_trait_data <- function(object, scaled_preferences = TRUE) {
   # setting variables to NULL
   sF <- NULL
   sH <- NULL
@@ -40,7 +39,8 @@ get_trait_data <- function(object,
   )
 
   trait_data_ <- Map(
-    trait_data_, generations_,
+    trait_data_,
+    generations_,
     f = function(td_, g_) {
       td_$gen <- g_
       data.table::as.data.table(td_)
@@ -52,11 +52,15 @@ get_trait_data <- function(object,
 
   # scale weights if required
   if (scaled_preferences) {
-    trait_data_[, c("sF", "sH", "sN") := lapply(
-      .SD, function(tr_) {
-        tr_ / (abs(sF) + abs(sH) + abs(sN))
-      }
-    ), .SDcols = c("sF", "sH", "sN")][] # add [] for printing output
+    trait_data_[,
+      c("sF", "sH", "sN") := lapply(
+        .SD,
+        function(tr_) {
+          tr_ / (abs(sF) + abs(sH) + abs(sN))
+        }
+      ),
+      .SDcols = c("sF", "sH", "sN")
+    ][] # add [] for printing output
   }
 
   return(trait_data_)

R/fun_make_parameters.R

@@ -7,10 +7,7 @@
 #' @return Writes a parameter file.
 #' @export
 #'
-make_parameter_file <- function(replicates,
-                                ...,
-                                which_file = "this_file.csv") {
-
+make_parameter_file <- function(replicates, ..., which_file = "this_file.csv") {
   # make combinations
   parameters <- data.table::CJ(
     ...,

R/fun_process_networks.R

@@ -1,4 +1,3 @@
-
 #' Get network data from Rds files.
 #'
 #' @param output A `pathomove_output` object.
@@ -41,20 +40,18 @@ get_networks <- function(output, assoc_threshold = 5) {
   }
 
   # work on nodes
-  nodes <- Map(nodes, output@gens_edge_lists,
-    f = function(n, g) {
-      n$gen <- g
-      n$id <- seq_len(nrow(n))
-      data.table::setDT(n)
-
-      # add simulation parameter data
-      n[, names(agent_parameters) := agent_parameters]
-      n[, names(eco_parameters) := eco_parameters]
-
-      n <- get_social_strategy(n)
-      n
-    }
-  )
+  nodes <- Map(nodes, output@gens_edge_lists, f = function(n, g) {
+    n$gen <- g
+    n$id <- seq_len(nrow(n))
+    data.table::setDT(n)
+
+    # add simulation parameter data
+    n[, names(agent_parameters) := agent_parameters]
+    n[, names(eco_parameters) := eco_parameters]
+
+    n <- get_social_strategy(n)
+    n
+  })
 
   assertthat::assert_that(
     length(el) == length(nodes),

R/fun_social_info.R

@@ -17,12 +17,18 @@ get_social_strategy <- function(df) {
     msg = "get_social_strat: data does not have social weights"
   )
   data.table::setDT(df)
-  df[, social_strat := data.table::fcase(
-    (sH > 0 & sN > 0), "agent tracking",
-    (sH > 0 & sN < 0), "handler tracking",
-    (sH < 0 & sN > 0), "non-handler tracking",
-    (sH < 0 & sN < 0), "agent avoiding"
-  )][]
+  df[,
+    social_strat := data.table::fcase(
+      (sH > 0 & sN > 0),
+      "agent tracking",
+      (sH > 0 & sN < 0),
+      "handler tracking",
+      (sH < 0 & sN > 0),
+      "non-handler tracking",
+      (sH < 0 & sN < 0),
+      "agent avoiding"
+    )
+  ][]
 }
 
 #' Get functional variation in movement weights.
@@ -45,10 +51,11 @@ get_functional_variation <- function(df) {
   )
 
   # transform weights
-  df[, c("sF", "sH", "sN") := lapply(.SD, function(x) {
-    x / (abs(sF) + abs(sH) + abs(sN))
-  }),
-  .SDcols = c("sF", "sH", "sN")
+  df[,
+    c("sF", "sH", "sN") := lapply(.SD, function(x) {
+      x / (abs(sF) + abs(sH) + abs(sN))
+    }),
+    .SDcols = c("sF", "sH", "sN")
   ][]
 }
 
@@ -95,8 +102,10 @@ get_agent_avoidance <- function(df) {
   data.table::setDT(df)
   d_ <- copy(df)
   # avoidance is sum of negative agent weights
-  d_[, agent_avoidance := (fifelse(sH < 0, sH, 0) + fifelse(sN < 0, sN, 0)) /
-    (abs(sH) + abs(sN) + abs(sF))]
+  d_[,
+    agent_avoidance := (fifelse(sH < 0, sH, 0) + fifelse(sN < 0, sN, 0)) /
+      (abs(sH) + abs(sN) + abs(sF))
+  ]
   # assign to original df, modified by reference
   df[, agent_avoidance := d_$agent_avoidance]
 }

R/fun_use_cluster.R

@@ -13,14 +13,15 @@
 #' @return Runs a job which makes more jobs.
 #' @export
 #'
-use_cluster <- function(ssh_con = "some_server",
-                        password = "your_password",
-                        script = "which_script.R",
-                        folder = "pathomove",
-                        tag = "scenario_tag",
-                        template_job = "some_template.sh",
-                        parameter_file = "which_parameters.csv") {
-
+use_cluster <- function(
+  ssh_con = "some_server",
+  password = "your_password",
+  script = "which_script.R",
+  folder = "pathomove",
+  tag = "scenario_tag",
+  template_job = "some_template.sh",
+  parameter_file = "which_parameters.csv"
+) {
   # connect to server
   s <- ssh::ssh_connect(ssh_con, passwd = password)
 

R/pathomove-package.R

@@ -1,4 +1,5 @@
 ## usethis namespace: start
+#' @import RcppEigen
 #' @importFrom data.table :=
 #' @importFrom data.table .BY
 #' @importFrom data.table .EACHI

README.md

@@ -1,7 +1,7 @@
 # Source code for _Pathomove_, an individual-based model for the evolution of animal movement strategies under the risk of pathogen transmission
 
 <!-- badges: start -->
-  [![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)
+  [![Project Status: Inactive – The project has reached a stable, usable state but is no longer being actively developed; support/maintenance will be provided as time allows.](https://www.repostatus.org/badges/latest/inactive.svg)](https://www.repostatus.org/#inactive)
   [![R-CMD-check](https://github.com/pratikunterwegs/pathomove/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/pratikunterwegs/pathomove/actions/workflows/R-CMD-check.yaml)
   [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6331816.svg)](https://doi.org/10.5281/zenodo.6331816)
   [![Codecov test coverage](https://codecov.io/gh/pratikunterwegs/pathomove/branch/main/graph/badge.svg)](https://codecov.io/gh/pratikunterwegs/pathomove?branch=main)
@@ -159,7 +159,7 @@ The workflow to run this model to replicate the results presented in our _biorXi
 
 A basic working example of how to use this package can be found in the script in the `vignettes` directory, `vignettes/basic_usage.Rmd`.
 
-**Note:** In order to have completely reproducible simulations, it is necessary to run the simulation in single-threaded mode. Multi-threaded simualtion runs are _not_ reproducible.
+**Note:** In order to have completely reproducible simulations, it is necessary to run the simulation in single-threaded mode. Multi-threaded simulation runs are _not_ reproducible.
 
 The basic workflow for the package is:
 

air.toml

@@ -0,0 +1,2 @@
+[format]
+exclude = ["RcppExports.R"]

inst/WORDLIST

@@ -0,0 +1,21 @@
+CMD
+Codecov
+Github
+Groningen
+Groningen's
+HPC
+Makevars
+Rcpp
+RcppParallel
+Rds
+Rtrees
+SLURM
+TBB
+Weissing
+Zenodo
+biorXiv
+doi
+etc
+mechanisitic
+timesteps
+zenodo