From 2559a3aca53637bf11959b8ef934dbc132049f4f Mon Sep 17 00:00:00 2001
From: TANMAY <105608756+tanmaydimriGSOC@users.noreply.github.com>
Date: Fri, 20 Mar 2026 00:39:10 +0530
Subject: [PATCH 1/2] Add unit tests for benchmarking metrics and document
 metric_R2 fallback

---
 modules/benchmark/R/metric_R2.R               | 24 +++++++--
 .../benchmark/tests/testthat/test-metrics.R   | 49 +++++++++++++++++++
 2 files changed, 69 insertions(+), 4 deletions(-)
 create mode 100644 modules/benchmark/tests/testthat/test-metrics.R

diff --git a/modules/benchmark/R/metric_R2.R b/modules/benchmark/R/metric_R2.R
index 94e5df7677b..8b4a13e0e6e 100644
--- a/modules/benchmark/R/metric_R2.R
+++ b/modules/benchmark/R/metric_R2.R
@@ -1,11 +1,23 @@
 ##' @name metric_R2
 ##' @title Coefficient of Determination (R2)
 ##' @export
-##' @param metric_dat dataframe
+##' @param metric_dat dataframe with columns \code{model} and \code{obvs}
 ##' @param ... ignored
-##' 
+##'
+##' @details
+##' Computes R-squared using the correlation-based formula:
+##' \eqn{R^2 = \left(\frac{\sum(obs - \bar{obs})(mod - \bar{mod})}
+##' {\sqrt{\sum(obs - \bar{obs})^2} \cdot \sqrt{\sum(mod - \bar{mod})^2}}\right)^2}
+##'
+##' If this formula returns \code{NA} (e.g. when model output is constant
+##' across all observations), the function silently falls back to an
+##' \code{lm()}-based R-squared via \code{summary(lm())$r.squared}.
+##' This fallback may produce unreliable results and triggers a warning
+##' from \code{stats::summary.lm}: "essentially perfect fit: summary may
+##' be unreliable". Consider checking for constant model output before
+##' calling this function.
+##'
 ##' @author Betsy Cowdery
-
 metric_R2 <- function(metric_dat, ...) {
   PEcAn.logger::logger.info("Metric: Coefficient of Determination (R2)")
   numer <- sum((metric_dat$obvs - mean(metric_dat$obvs)) * (metric_dat$model - mean(metric_dat$model)))
@@ -13,6 +25,10 @@ metric_R2 <- function(metric_dat, ...) {
   
   out <- (numer / denom) ^ 2
   
+  # If correlation formula returns NA (e.g. constant model output),
+  # fall back to lm()-based R-squared. Note: this fallback may trigger
+  # "essentially perfect fit" warning from stats::summary.lm and
+  # produce unreliable results in edge cases.
   if(is.na(out)){
     fit <- stats::lm(metric_dat$model ~ metric_dat$obvs)
     out <- summary(fit)$r.squared
@@ -20,4 +36,4 @@ metric_R2 <- function(metric_dat, ...) {
   
   return(out)
   
-} # metric_R2
+} # metric_R2
\ No newline at end of file
diff --git a/modules/benchmark/tests/testthat/test-metrics.R b/modules/benchmark/tests/testthat/test-metrics.R
new file mode 100644
index 00000000000..a5266cc2763
--- /dev/null
+++ b/modules/benchmark/tests/testthat/test-metrics.R
@@ -0,0 +1,49 @@
+# at the top of test-metrics.R, add this:
+if (!requireNamespace("PEcAn.logger", quietly = TRUE)) {
+  PEcAn.logger <- new.env()
+  PEcAn.logger$logger.info <- function(...) invisible(NULL)
+}
+
+test_that("metric_RMSE returns 0 for perfect predictions", {
+  dat <- data.frame(model = c(1, 2, 3), obvs = c(1, 2, 3))
+  expect_equal(metric_RMSE(dat), 0)
+})
+
+test_that("metric_RMSE handles NA values", {
+  dat <- data.frame(model = c(1, NA, 3), obvs = c(1, 2, 3))
+  expect_true(is.numeric(metric_RMSE(dat)))
+})
+
+test_that("metric_RMSE returns numeric", {
+  dat <- data.frame(model = c(2, 4), obvs = c(1, 3))
+  expect_equal(metric_RMSE(dat), 1)
+})
+
+test_that("metric_MAE returns 0 for perfect predictions", {
+  dat <- data.frame(model = c(1, 2, 3), obvs = c(1, 2, 3))
+  expect_equal(metric_MAE(dat), 0)
+})
+
+test_that("metric_MAE returns correct value", {
+  dat <- data.frame(model = c(3, 3), obvs = c(1, 1))
+  expect_equal(metric_MAE(dat), 2)
+})
+
+test_that("metric_cor returns 1 for perfect linear relationship", {
+  dat <- data.frame(model = c(1, 2, 3), obvs = c(1, 2, 3))
+  expect_equal(metric_cor(dat), 1)
+})
+
+test_that("metric_R2 returns 1 for perfect predictions", {
+  dat <- data.frame(model = c(1, 2, 3), obvs = c(1, 2, 3))
+  expect_equal(metric_R2(dat), 1)
+})
+
+test_that("metric_R2 silent NA fallback produces valid output", {
+  dat <- data.frame(model = c(2, 2, 2), obvs = c(1, 2, 3))
+  expect_warning(
+    result <- metric_R2(dat),
+    "essentially perfect fit"
+  )
+  expect_true(is.numeric(result))
+})
\ No newline at end of file

From 08e9e7bda414ea464837bc4f94fdcd46332f8414 Mon Sep 17 00:00:00 2001
From: TANMAY <105608756+tanmaydimriGSOC@users.noreply.github.com>
Date: Tue, 31 Mar 2026 13:46:20 +0530
Subject: [PATCH 2/2] Update metric_R2.Rd to match roxygen documentation

---
 modules/benchmark/man/metric_R2.Rd | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

diff --git a/modules/benchmark/man/metric_R2.Rd b/modules/benchmark/man/metric_R2.Rd
index 65b1feb7fea..41f97646194 100644
--- a/modules/benchmark/man/metric_R2.Rd
+++ b/modules/benchmark/man/metric_R2.Rd
@@ -7,13 +7,26 @@
 metric_R2(metric_dat, ...)
 }
 \arguments{
-\item{metric_dat}{dataframe}
+\item{metric_dat}{dataframe with columns \code{model} and \code{obvs}}
 
 \item{...}{ignored}
 }
 \description{
 Coefficient of Determination (R2)
 }
+\details{
+Computes R-squared using the correlation-based formula:
+\eqn{R^2 = \left(\frac{\sum(obs - \bar{obs})(mod - \bar{mod})}
+{\sqrt{\sum(obs - \bar{obs})^2} \cdot \sqrt{\sum(mod - \bar{mod})^2}}\right)^2}
+
+If this formula returns \code{NA} (e.g. when model output is constant
+across all observations), the function silently falls back to an
+\code{lm()}-based R-squared via \code{summary(lm())$r.squared}.
+This fallback may produce unreliable results and triggers a warning
+from \code{stats::summary.lm}: "essentially perfect fit: summary may
+be unreliable". Consider checking for constant model output before
+calling this function.
+}
 \author{
 Betsy Cowdery
-}
+}
\ No newline at end of file