lowerSpreadProb and maxFireSpread default to the fireSenseUtils constants

NEWS.md

@@ -1,3 +1,7 @@
+# fireSense_spreadPredict (development version)
+
+- `lowerSpreadProb` and `maxFireSpread` default to `fireSenseUtils::spreadProbFloor` (0.13) and `fireSenseUtils::spreadProbCeiling` (0.276; `maxFireSpread` was 0.28), the one floor and ceiling `fireSense_spreadFit` and the objective use. `maxFireSpread` does not change a prediction. Needs the `fireSenseUtils` change in PredictiveEcology/fireSenseUtils (floor to be set once it has a version).
+
 # fireSense_spreadPredict 1.1.3
 
 - A ledger row from a fit with an intercept (a parameter named `fireSenseUtils::spreadInterceptTxt`, from `fireSense_dataPrepFit`'s `spreadIntercept`) is predicted with it: `spreadProbOneELF()` adds a column of 1s for it after rescaling and centring, and subtracts the row's stored covariate centres (`fireSenseUtils::spreadFitCovCentreTxt`, `ledgerCovCentre()`) from the rescaled covariates, as the fit did. With several ELFs each row uses its own. A row without them, such as every row written so far, predicts exactly as before. Needs fireSenseUtils >= 0.2.3.9083 (PredictiveEcology/fireSenseUtils#131).

fireSense_spreadPredict.R

@@ -19,15 +19,17 @@ defineModule(sim, list(
                   "ggplot2", "viridis",
                   "PredictiveEcology/fireSenseUtils@development (>= 0.2.3.9083)"),
   parameters = bindrows(
-    defineParameter(name = "lowerSpreadProb", class = "numeric", default = 0.13,
-                    desc = "Lower asymptote of the 2- and 3-parameter logistic."),
+    defineParameter(name = "lowerSpreadProb", class = "numeric", default = fireSenseUtils::spreadProbFloor,
+                    desc = paste("Lower asymptote of the 2- and 3-parameter logistic. Default",
+                                 "`fireSenseUtils::spreadProbFloor`, the same constant `fireSense_spreadFit` fits with.")),
     defineParameter("ELFblendWidth", "numeric", default = 20000,
                     desc = paste("With several ELFs: each ELF's model also predicts this far (m) outside its own",
                                  "pixels, and where predictions overlap they are averaged with weights that fall",
                                  "linearly from 1 inside the ELF to 0 at this distance outside it. 50/50 at a",
                                  "boundary. The default is the buffer fireSenseUtils::makeELFs() puts around ELFs.")),
-    defineParameter("maxFireSpread", "numeric", default = 0.28,
-                    desc = paste("Upper limit on `spreadProb` used when fitting. Here it is only checked",
+    defineParameter("maxFireSpread", "numeric", default = fireSenseUtils::spreadProbCeiling,
+                    desc = paste("Upper limit on `spreadProb` used when fitting (default",
+                                 "`fireSenseUtils::spreadProbCeiling`). Here it is only checked",
                                  "to be the same in every module that defines it.")),
     defineParameter(".rep", "integer", default = 1L, min = 1L, max = NA,
                     desc = paste("Which replicate this prediction is. It selects parameter set",

tests/testthat/test-metadata.R

@@ -49,13 +49,20 @@ test_that("parameters have the expected names, classes and defaults", {
   expected <- data.frame(
     class   = c("integer", "numeric", "numeric", "numeric", "character", "logical", "numeric", "numeric", "numeric"),
     ## .runInitialTime defaults to start(sim), which is 0 when only metadata is parsed
-    default = c("1L", "0", "1", "NA", "NA", "FALSE", "20000", "0.13", "0.28"),
+    default = c("1L", "0", "1", "NA", "NA", "FALSE", "20000", "0.13", "0.276"),
     row.names = c(".rep", ".runInitialTime", ".runInterval", ".saveInitialTime", ".studyAreaName", ".useCache",
                   "ELFblendWidth", "lowerSpreadProb", "maxFireSpread")
   )
   expect_identical(paramTable(md), expected)
 })
 
+test_that("lowerSpreadProb and maxFireSpread default to fireSenseUtils' one floor and one ceiling", {
+  md <- SpaDES.core::moduleMetadata(module = moduleName, path = modulePath)
+  dflt <- function(nm) md$parameters$default[[match(nm, md$parameters$paramName)]]
+  expect_identical(dflt("lowerSpreadProb"), fireSenseUtils::spreadProbFloor)
+  expect_identical(dflt("maxFireSpread"), fireSenseUtils::spreadProbCeiling)
+})
+
 test_that("fireSenseUtils is a declared dependency, so CI installs it", {
   md <- SpaDES.core::moduleMetadata(module = moduleName, path = modulePath)
   expect_true(any(grepl("^PredictiveEcology/fireSenseUtils@development", unlist(md$reqdPkgs))))