v0.1

.Rbuildignore

@@ -5,3 +5,14 @@
 ^docs$
 ^pkgdown$
 ^\.github$
+^README\.Rmd$
+^LICENSE\.md$
+^doc$
+^Meta$
+^CODE_OF_CONDUCT\.md$
+^CONTRIBUTING\.md$
+^paper$
+^.vscode$
+^citation.cff$
+^vignettes/articles$
+^cran-comments\.md$

.github/workflows/test-coverage.yaml

@@ -0,0 +1,61 @@
+# 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: [main, master]
+  pull_request:
+
+name: test-coverage.yaml
+
+permissions: read-all
+
+jobs:
+  test-coverage:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::covr, any::xml2
+          needs: coverage
+
+      - name: Test coverage
+        run: |
+          cov <- covr::package_coverage(
+            quiet = FALSE,
+            clean = FALSE,
+            install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
+          )
+          covr::to_cobertura(cov)
+        shell: Rscript {0}
+
+      - uses: codecov/codecov-action@v4
+        with:
+          # Fail if error if not on PR, or if on PR and token is given
+          fail_ci_if_error: ${{ github.event_name != 'pull_request' || secrets.CODECOV_TOKEN }}
+          file: ./cobertura.xml
+          plugin: noop
+          disable_search: true
+          token: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: Show testthat output
+        if: always()
+        run: |
+          ## --------------------------------------------------------------------
+          find '${{ runner.temp }}/package' -name 'testthat.Rout*' -exec cat '{}' \; || true
+        shell: bash
+
+      - name: Upload test results
+        if: failure()
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-test-failures
+          path: ${{ runner.temp }}/package

DESCRIPTION

@@ -1,10 +1,10 @@
 Package: greenAlgoR
 Title: Compute ecological footprint in R 
-Version: 0.0.0.9000
+Version: 0.1
 Authors@R: person("Adrien", "Taudière", email = "[email protected]",
   role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0003-1088-1182"))
 Description: This package computes ecological footprint in R (based on [green-algorithms](https://calculator.green-algorithms.org/). 
-  greenAlgoR also made it simple to compute ecological footprint of {[targets](https://github.com/ropensci/targets)} pipelines.
+  greenAlgoR also made it simple to compute ecological footprint of \{[targets](https://github.com/ropensci/targets)\} pipelines.
 License: GPL (>= 3)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)

NAMESPACE

@@ -3,4 +3,9 @@
 export(csv_from_url_ga)
 export(ga_footprint)
 export(ga_targets)
+export(round_conditionaly)
 export(session_runtime)
+import(benchmarkme)
+import(ggplot2)
+import(targets)
+importFrom(utils,read.csv)

NEWS.md

@@ -1,3 +1,4 @@
 # greenAlgoR 0.1
 
-* Initial CRAN submission.
+* Initial github submission.
+* Creation of function `ga_footprint()` and `ga_targets()`

R/ga_footprint.R

@@ -16,7 +16,9 @@
 #' - TDP_per_core: https://raw.githubusercontent.com/GreenAlgorithms/green-algorithms-tool/refs/heads/master/data/v2.2/TDP_cpu.csv
 #' - power_draw_per_gb: https://onlinelibrary.wiley.com/doi/10.1002/advs.202100707
 #'
-#' Text from the [green-algorithms](https://github.com/GreenAlgorithms/green-algorithms-tool) website:
+#' Description of the algorithm from the
+#' [green-algorithms](https://github.com/GreenAlgorithms/green-algorithms-tool)
+#'  website:
 #'
 #' """
 #'
@@ -41,18 +43,18 @@
 #'
 #'  The Carbon Intensity depends on the location and the technologies used
 #'  to produce electricity. But note that the "energy needed"
-#'  [...] is independent of the location.
+#'  \[...\] is independent of the location.
 #'
 #'  """
 #'
 #' @param runtime_h Run time in hours (int). If runtime_h == "session",
 #'   the runtime is compute using the actual R session
 #' @param location_code (character list of country or region available in  )
-#' @param PUE (int) Power usage effectiveness of the server.
-#'   See https://github.com/GreenAlgorithms/green-algorithms-tool/blob/master/data/v2.2/defaults_PUE.csv
-#'   for example of values. If you are using your personal computer, set PUE to 1.
-#' @param TDP_per_core (int. in Watt, default 12). Find your cpu TDP and your nb of cpu on
-#'  https://www.techpowerup.com/cpu-specs/ or in
+#' @param PUE (int) Power usage effectiveness of the server. See
+#'  https://github.com/GreenAlgorithms/green-algorithms-tool/blob/master/data/v2.2/defaults_PUE.csv
+#'  for example of values. If you are using your personal computer, set PUE to 1.
+#' @param TDP_per_core (int. in Watt, default 12). Find your cpu TDP and your
+#'  nb of cpu on https://www.techpowerup.com/cpu-specs/ or in
 #'  http://calculator.green-algorithms.org/ if available.
 #'  Owerwrite by cpu_model param.
 #' @param n_cores (int, default 1) Number of cores.
@@ -94,17 +96,20 @@
 #'   A dataframe with `location` and `carbonIntensity`
 #'   columns. Set to carbon_intensity_internal if NULL.
 #'   carbon_intensity_internal is set using command line
-#'   csv_from_url_ga("https://raw.githubusercontent.com/GreenAlgorithms/green-algorithms-tool/refs/heads/master/data/v2.2/CI_aggregated.csv")
+#'   csv_from_url_ga("https://raw.githubusercontent.com/GreenAlgorithms/
+#'   green-algorithms-tool/refs/heads/master/data/v2.2/CI_aggregated.csv")
 #' @param TDP_cpu (default NULL). Advanced users only.
 #'   A dataframe with `model`, `n_cores` and `TDP_per_core`
 #'   columns. Set to TDP_cpu_internal if NULL.
 #'   TDP_cpu_internal is set using command line
-#'   csv_from_url_ga("https://raw.githubusercontent.com/GreenAlgorithms/green-algorithms-tool/refs/heads/master/data/v2.2/TDP_cpu.csv")
+#'   csv_from_url_ga("https://raw.githubusercontent.com/GreenAlgorithms/
+#'   green-algorithms-tool/refs/heads/master/data/v2.2/TDP_cpu.csv")
 #' @param ref_value (default NULL). Advanced users only.
 #'   A dataframe with `variable` and `value`
 #'   columns. Set to ref_value_internal if NULL.
 #'   ref_value_internal is set using command line
-#'   csv_from_url_ga("https://raw.githubusercontent.com/GreenAlgorithms/green-algorithms-tool/refs/heads/master/data/v2.2/referenceValues.csv")
+#'   csv_from_url_ga("https://raw.githubusercontent.com/GreenAlgorithms/
+#'   green-algorithms-tool/refs/heads/master/data/v2.2/referenceValues.csv")
 #'
 #' @return A list of values
 #'  - `runtime_h`: the input run time in hours
@@ -158,18 +163,44 @@
 #'
 #' ggplot(res_ga$ref_value, aes(y = variable, x = as.numeric(value), fill = log10(prop_footprint))) +
 #'   geom_col() +
-#'   geom_col(data = data.frame(variable = "Total", value = res_ga$carbon_footprint_total_gCO2), fill = "grey30") +
-#'   geom_col(data = data.frame(variable = "Cores", value = res_ga$carbon_footprint_cores), fill = "darkred") +
-#'   geom_col(data = data.frame(variable = "Memory", value = res_ga$carbon_footprint_memory), fill = "orange") +
-#'   geom_col(data = data.frame(variable = "Mass storage", value = res_ga$carbon_footprint_storage), fill = "violet") +
-#'   scale_x_continuous(trans = "log1p") +
-#'   geom_vline(xintercept = res_ga$carbon_footprint_total_gCO2, col = "grey30", lwd = 1.2) +
-#'   geom_label(aes(label = round_conditionaly(prop_footprint)), fill = "grey90",position = position_stack(vjust = 1.1)) +
-#'   labs(title="Carbon footprint of the analysis",
-#'   subtitle = paste0("(", res_ga$carbon_footprint_total_gCO2, " g CO2",")"),
-#'   caption = "Please cite Lannelongue et al. 2021 (10.1002/advs.202100707)") +
+#'   geom_col(data = data.frame(
+#'     variable = "Total",
+#'     value = res_ga$carbon_footprint_total_gCO2
+#'   ), fill = "grey30") +
+#'   geom_col(data = data.frame(
+#'     variable = "Cores",
+#'     value = res_ga$carbon_footprint_cores
+#'   ), fill = "darkred") +
+#'   geom_col(data = data.frame(
+#'     variable = "Memory",
+#'     value = res_ga$carbon_footprint_memory
+#'   ), fill = "orange") +
+#'   geom_col(data = data.frame(
+#'     variable = "Mass storage",
+#'     value = res_ga$carbon_footprint_storage
+#'   ), fill = "violet") +
+#'   scale_x_continuous(
+#'     trans = "log1p",
+#'     breaks = c(0, 10^c(1:max(log1p(as.numeric(res_ga$ref_value$value)))))
+#'   ) +
+#'   geom_vline(
+#'     xintercept = res_ga$carbon_footprint_total_gCO2,
+#'     col = "grey30", lwd = 1.2
+#'   ) +
+#'   geom_label(aes(label = round_conditionaly(prop_footprint)),
+#'     fill = "grey90", position = position_stack(vjust = 1.1)
+#'   ) +
+#'   labs(
+#'     title = "Carbon footprint of the analysis",
+#'     subtitle = paste0(
+#'       "(", res_ga$carbon_footprint_total_gCO2,
+#'       " g CO2", ")"
+#'     ),
+#'     caption = "Please cite Lannelongue et al. 2021 (10.1002/advs.202100707)"
+#'   ) +
 #'   xlab("Carbon footprint (g CO2) in log10") +
-#'   ylab("Modality")
+#'   ylab("Modality") +
+#'   theme(legend.position = "none")
 ga_footprint <- function(runtime_h = NULL,
                          location_code = "WORLD",
                          PUE = 1.67,
@@ -269,7 +300,7 @@ ga_footprint <- function(runtime_h = NULL,
 
   if (add_ref_values) {
     if (is.null(ref_value)) {
-      ref_value <- ref_value_internal[order(as.numeric(ref_value_internal$value)),]
+      ref_value <- ref_value_internal[order(as.numeric(ref_value_internal$value)), ]
       rownames(ref_value) <- NULL
     }
     res[["ref_value"]] <- rbind(
@@ -291,7 +322,7 @@ ga_footprint <- function(runtime_h = NULL,
     res[["energy_needed_kWh"]] <- res[["energy_needed_kWh"]] + res[["power_draw_storage_kWh"]]
     res[["carbon_footprint_total_gCO2"]] <- res[["carbon_footprint_cores"]] + res[["carbon_footprint_memory"]] + res[["carbon_footprint_storage"]]
 
-     if (add_ref_values) {
+    if (add_ref_values) {
       res[["ref_value"]] <- rbind(
         c("Total", res$carbon_footprint_total_gCO2, NA),
         c("Cores", res$carbon_footprint_cores, NA),
@@ -308,9 +339,9 @@ ga_footprint <- function(runtime_h = NULL,
 
     # to force ggplot to keep row order
     res[["ref_value"]]$variable <- factor(res[["ref_value"]]$variable,
-                                          levels = res[["ref_value"]]$variable )
-
-}
+      levels = res[["ref_value"]]$variable
+    )
+  }
 
   return(res)
 }

R/ga_targets.R

@@ -1,4 +1,4 @@
-#' Compute footprint in grams of CO2 for {targets} pipelines
+#' Compute footprint in grams of CO2 for \{targets\} pipelines
 #'
 #' @description
 #'
@@ -40,7 +40,10 @@
 #'           command = Sys.sleep(2),
 #'           description = "Sleep 2 seconds"
 #'         ),
-#'         tar_target(x, writeLines(targets::tar_option_get("error"), "error.txt"))
+#'         tar_target(x, writeLines(
+#'           targets::tar_option_get("error"),
+#'           "error.txt"
+#'         ))
 #'       )
 #'     },
 #'     ask = FALSE
@@ -59,14 +62,41 @@
 #'       add_storage_estimation = TRUE
 #'     )
 #'
-#'   ggplot(res_gat$ref_value, aes(y = reorder(variable, as.numeric(value)), x = as.numeric(value), fill = log10(prop_footprint))) +
+#'   ggplot(res_gat$ref_value, aes(
+#'     y = reorder(variable, as.numeric(value)),
+#'     x = as.numeric(value), fill = log10(prop_footprint)
+#'   )) +
 #'     geom_col() +
-#'     geom_col(data = data.frame(variable = "Total ", value = res_gat$carbon_footprint_gCO2), fill = "grey30") +
-#'     geom_col(data = data.frame(variable = "Cores", value = res_gat$carbon_intensity * res_gat$power_draw_for_cores_kWh), fill = "darkred") +
-#'     geom_col(data = data.frame(variable = "Memory", value = res_gat$carbon_intensity * res_gat$power_draw_for_memory_kWh), fill = "orange") +
-#'     geom_col(data = data.frame(variable = "Storage", value = res_gat$carbon_intensity * res_gat$power_draw_per_gb), fill = "violet") +
+#'     geom_col(data = data.frame(
+#'       variable = "Total ",
+#'       value = res_gat$carbon_footprint_total_gCO2
+#'     ), fill = "grey30") +
+#'     geom_col(
+#'       data = data.frame(
+#'         variable = "Cores",
+#'         value = res_gat$carbon_intensity * res_gat$power_draw_for_cores_kWh
+#'       ),
+#'       fill = "darkred"
+#'     ) +
+#'     geom_col(
+#'       data = data.frame(
+#'         variable = "Memory",
+#'         value = res_gat$carbon_intensity * res_gat$power_draw_for_memory_kWh
+#'       ),
+#'       fill = "orange"
+#'     ) +
+#'     geom_col(
+#'       data = data.frame(
+#'         variable = "Storage",
+#'         value = res_gat$carbon_intensity * res_gat$power_draw_per_gb
+#'       ),
+#'       fill = "violet"
+#'     ) +
 #'     scale_x_continuous(trans = "log1p") +
-#'     geom_vline(xintercept = res_gat$carbon_footprint_gCO2, col = "grey30", lwd = 1.2) +
+#'     geom_vline(
+#'       xintercept = res_gat$carbon_footprint_total_gCO2,
+#'       col = "grey30", lwd = 1.2
+#'     ) +
 #'     geom_label(aes(label = round(prop_footprint, 1)), fill = "grey90") +
 #'     xlab("g CO^2") +
 #'     ylab("Modality")
@@ -121,8 +151,8 @@ ga_targets <- function(names = NULL,
     df_meta <- tar_meta_raw
   }
 
-  runtime_targets <- sum(df_meta$seconds, na.rm = TRUE) / 3600
-  power_draw_stocks <- sum(df_meta$bytes, na.rm = TRUE) / 10^9
+  runtime_targets <- sum(as.numeric(df_meta$seconds), na.rm = TRUE) / 3600
+  power_draw_stocks <- sum(as.numeric(df_meta$bytes), na.rm = TRUE) / 10^9
 
   res <- ga_footprint(
     runtime_h = as.numeric(runtime_targets),

R/greenAlgo-package.R

@@ -0,0 +1,7 @@
+#' \code{greenAlgoR} package
+#'
+#'  This package computes ecological footprint in R (based on [green-algorithms](https://calculator.green-algorithms.org/).
+#'  greenAlgoR also made it simple to compute ecological footprint of {[targets](https://github.com/ropensci/targets)} pipelines..
+#' @name greenAlgoR-package
+#' @import ggplot2 targets benchmarkme
+NULL