From bde411540c9d4839d67f4dfb6ef8f97b85fbab20 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:08:17 +0200 Subject: [PATCH 001/118] Update WORDLIST --- inst/WORDLIST | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/inst/WORDLIST b/inst/WORDLIST index fe2fae16..4006425c 100644 --- a/inst/WORDLIST +++ b/inst/WORDLIST @@ -1,8 +1,7 @@ APSIM -Analyse -Apsim CeCILL Codecov +Combi CropR CroplotR Cropr @@ -29,35 +28,38 @@ STICS Salam Stics SticsRFiles +SticsRPacks Sutcliffe USM Unwatch WIP +aes +args binded bmp bservations +btw +cff colouring -cran cropr df dplyr eps -formater +faaaast ggplot ggplotly ggplots +github heigth -https intercrop intercropping jpeg lai -lm +linetype mafruit masec nRMSE nd -outputed pMSEs pMSEu pictex @@ -76,9 +78,12 @@ sd svg tLimit tSTUD +testthat tex tibble tibbles tidyr usms wmf +xaxis +yaxis From abe41c4f29e12a3a46d483fcfbbf3707cc6aebb6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:33:14 +0200 Subject: [PATCH 002/118] Update test-scatter-plots.R Remove duplicated code --- tests/testthat/test-scatter-plots.R | 4 ---- 1 file changed, 4 deletions(-) diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index 6eb27f99..1736e132 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -198,10 +198,6 @@ tmp <- read.csv( file = "_inputs/tests_scatter_plots.csv", header = TRUE, sep = ";", stringsAsFactors = FALSE ) -tmp <- read.csv( - file = "_inputs/tests_scatter_plots.csv", - header = TRUE, sep = ";", stringsAsFactors = FALSE -) ## Set sim and sim2 depending on mixture or not tmp$sim <- lapply(tmp$mixture, function(x) if (x) sim_mixture else sim_sole_crop) From 34dad91b831b80749b8c15de7d6fa1fb790e8316 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:33:27 +0200 Subject: [PATCH 003/118] Use || instead of | --- R/specific_plotting_scatter.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index c077972f..1bd23414 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -178,14 +178,14 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - if (shape_sit == "none" | shape_sit == "txt") { + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) ), na.rm = TRUE ) - } else if (shape_sit == "symbol" | shape_sit == "group") { + } else if (shape_sit == "symbol" || shape_sit == "group") { p <- p + ggplot2::geom_point( ggplot2::aes( colour = as.factor(paste(.data$Dominance, ":", .data$Plant)), From 558f0c6f4c8c39491d4a180c72d64ecad2c0ac3c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:34:23 +0200 Subject: [PATCH 004/118] Update generic_plotting.R Remove default plot title when all_situations = TRUE (the plot title is used to identify the situation, so no need if all_situations = TRUE) --- R/generic_plotting.R | 2 ++ 1 file changed, 2 insertions(+) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 48e9a1a0..043c1d3c 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -178,6 +178,8 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, plot_title <- if (!is.null(title)) { title[[i]] + } else if (!several_sit) { + NULL # No title by default if it's all situations } else { i } From 8dce71a8baff2df370eb552219d9266c299f2de2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:40:09 +0200 Subject: [PATCH 005/118] Fix linter issues --- R/cropr_formatting.R | 13 +++++++++---- R/specific_plotting_scatter.R | 6 +++--- 2 files changed, 12 insertions(+), 7 deletions(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 96c56c41..c4ca56b3 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -83,7 +83,10 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, # Treating Dominance as a factor if any (for plotting reasons): if (is_mixture_sim) { - sim$Dominance <- factor(sim$Dominance, levels = c("Principal", "Associated")) + sim$Dominance <- factor( + sim$Dominance, + levels = c("Principal", "Associated") + ) } # Adding Dominance to obs if any: @@ -167,7 +170,8 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, if (is_obs_sd) { obs_sd <- obs_sd[, ind] } - if ("sit_name" %in% names(obs)) { # protection for call to summary (no sit_name) + # protection for call to summary (no sit_name): + if ("sit_name" %in% names(obs)) { ind <- obs$sit_name %in% inter_sit obs <- obs[ind, ] if (is_obs_sd) { @@ -182,7 +186,8 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, ind <- colnames(sim)[which(s_lower %in% inter)] sim <- sim[, ind] obs <- obs[, unique(colnames(obs))] - if ("sit_name" %in% names(sim)) { # protection for call to summary (no sit_name) + # protection for call to summary (no sit_name): + if ("sit_name" %in% names(sim)) { ind <- sim$sit_name %in% inter_sit sim <- sim[ind, ] } @@ -200,7 +205,7 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, } } - if (is_mixture_sim & is_mixture_obs) { + if (is_mixture_sim && is_mixture_obs) { rem_vars <- NULL melt_vars <- c("Date", "Plant", "Dominance") } else { diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 1bd23414..b73e0fcb 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -234,7 +234,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, } # Set same limits for x and y axis for sim VS obs scatter plots - if (select_scat == "sim" & reference_var == "Observed") { + if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } @@ -293,7 +293,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, p <- p + ggplot2::ggtitle(title) - if (is_obs_sd & reference_var == "Observed") { + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$sit_name)) p <- add_obs_error_bars(p, colour_factor = "colour_factor" @@ -313,7 +313,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, } # Set same limits for x and y axis for sim VS obs scatter plots - if (select_scat == "sim" & reference_var == "Observed") { + if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } From b27dc8557ba4aa65a3c1926a74b8dd24d043c3c2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:51:43 +0200 Subject: [PATCH 006/118] Update test-scatter-plots.R --- tests/testthat/test-scatter-plots.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index 1736e132..88cc0863 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -271,6 +271,7 @@ invisible(lapply(1:nrow(tmp), function(i) { " is disabled in file _inputs/tests_scatter_plot.csv (see column To_test" )) } else { + message("Testing scatter Plot #", tmp$Number[[i]]) expect_true(is.list(test_plot)) expect_equal(length(test_plot), tmp$length[[i]]) expect_equal(names(test_plot), tmp$name[[i]]) @@ -326,7 +327,7 @@ invisible(lapply(1:nrow(tmp), function(i) { lapply(names(test_plot), function(y) { sit <- NULL - if (y != "all_situations") { + if (y != "all_situations" && !is.null(y)) { sit <- paste0("_", y) } make_snapshot( From 16cd56ac7201d81f1eeb1c800769ba9cb0527370 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:03:01 +0200 Subject: [PATCH 007/118] fix typo --- R/generic_plotting.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 043c1d3c..3775cfd8 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -29,7 +29,7 @@ #' `all_situations= TRUE`. See details. #' @param situation_group A list of lists of situations to gather when #' `shape_sit= "group"`. -#' @param reference_var Variable selected on x-axis when type is scaétter and +#' @param reference_var Variable selected on x-axis when type is scatter and #' select_scat is res. It is possible to select #' between observation and simulation of the reference variable. #' (examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim") From b7b190dd4d94bba04dca25e2e66e8f051b2a0802 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:04:25 +0200 Subject: [PATCH 008/118] | -> || and & -> && --- R/specific_plotting_scatter.R | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index b73e0fcb..561266f8 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -170,7 +170,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( @@ -213,7 +213,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, p <- p + ggplot2::ggtitle(title) - if (is_obs_sd & reference_var == "Observed") { + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$Dominance, ":", p$data$Plant)) p <- add_obs_error_bars(p, colour_factor = "colour_factor" @@ -257,7 +257,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( @@ -265,9 +265,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - if (shape_sit == "none" | shape_sit == "txt") { + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point(na.rm = TRUE) - } else if (shape_sit == "symbol" | shape_sit == "group") { + } else if (shape_sit == "symbol" || shape_sit == "group") { p <- p + ggplot2::geom_point( ggplot2::aes( colour = as.factor(paste(.data$sit_name)) From 661f5277620972c6749e44ae145a127f2e0e07f4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:16:13 +0200 Subject: [PATCH 009/118] Update specific_plotting_scatter.R Remove letter in the legend of shape_sit="txt" (found looking at fig. 5) --- R/specific_plotting_scatter.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 561266f8..d621a533 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -170,7 +170,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( @@ -229,6 +229,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, label = .data$sit_name, colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) ), + show.legend = FALSE, max.overlaps = 100 ) } From 206310cc77fdb848448abf406c7e010f914343b6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:20:50 +0200 Subject: [PATCH 010/118] Update specific_plotting_scatter.R --- R/specific_plotting_scatter.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index d621a533..58676c8a 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -258,7 +258,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( From 43bdaffae0a9ddfca60b9636fff4ed80212f4911 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 17:07:23 +0200 Subject: [PATCH 011/118] Update test-scatter-plots.R --- tests/testthat/test-scatter-plots.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index 88cc0863..38249138 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -231,7 +231,7 @@ tmp$reference_var <- lapply( all_plots <- list() # Test the different variants of plots based on the file _inputs/tests_scatter_plot.csv -invisible(lapply(1:nrow(tmp), function(i) { +invisible(lapply(seq_len(nrow(tmp)), function(i) { test_that(paste0("Test #", tmp$Number[[i]]), { if (tmp$version[i]) { test_plot <- plot(tmp$sim[[i]], tmp$sim2[[i]], From adc91c0ae2a6191fe1583e0d3d929df50d78d5a3 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 4 Jun 2025 09:37:24 +0200 Subject: [PATCH 012/118] Removed WIP badge --- README.Rmd | 3 --- 1 file changed, 3 deletions(-) diff --git a/README.Rmd b/README.Rmd index f051c602..6563ae02 100644 --- a/README.Rmd +++ b/README.Rmd @@ -21,9 +21,6 @@ knitr::opts_chunk$set( -[![Project Status: WIP – Initial development is in progress, but there -has not yet been a stable, usable release suitable for the -public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip) [![Codecov test coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/master/graph/badge.svg)](https://app.codecov.io/gh/SticsRPacks/CroPlotR?branch=master) [![R build From e6893dbaee1f1d646dcccdd7c5ec28d4be0fe171 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 4 Jun 2025 23:19:45 +0200 Subject: [PATCH 013/118] add plot successive --- tests/testthat/test-dynamic-plots.R | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index bdc01f49..8462a5a5 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -453,6 +453,33 @@ test_that("Test plot mixture + version", { } }) + +### successive + +test_that("format of plotting several situations on different graphs", { + test_plot <- plot(sim_rot, obs = obs, + successive = list(list("demo_Wheat1", "demo_BareSoil2", "demo_maize3")), + var = c("resmes", "masec_n"), + all_situations = FALSE) + + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"several situations on different graphs\" not yet implemented (plot return NA)" + ) + } else { + expect_true(is.list(test_plot)) + expect_equal(length(test_plot), 1) + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.8_successive_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + } +}) + + if (!testthat:::on_ci()) { save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_dynamic") print(paste("Plots saved in pdf format in ", tmpdir)) From 400217cfc6695d151da4a50940f0e8defe10926c Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 4 Jun 2025 21:22:49 +0000 Subject: [PATCH 014/118] Style code (GHA) --- tests/testthat/test-dynamic-plots.R | 978 ++++++++++++++-------------- 1 file changed, 490 insertions(+), 488 deletions(-) diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index 8462a5a5..ac5dfe5d 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -1,488 +1,490 @@ -# -# Tests the scatter plots -# -# Automatic tests + generates a pdf and svg in _outputs to visually check the plots -# -# See doc on tests for CroPlotR in doc/doc_on_tests.md - -library(CroPlotR) -library(testthat) - -# # Make the reference data: -# -# workspace <- system.file(file.path("extdata", "stics_example_1"), -# package = "CroPlotR" -# ) -# -# situations <- SticsRFiles::get_usms_list( -# file = file.path(workspace,"usms.xml") -# ) -# -# sim <- SticsRFiles::get_sim( -# workspace = workspace, -# usm = situations, -# usms_file = file.path(workspace,"usms.xml") -# ) -# -# obs <- SticsRFiles::get_obs( -# workspace = workspace, -# usm = situations, -# usms_file = file.path(workspace, "usms.xml") -# ) -# -# # Rotation example -# workspace2 <- system.file( -# file.path("extdata", "stics_example_successive"), -# package = "CroPlotR" -# ) -# situations <- SticsRFiles::get_usms_list( -# file = file.path(workspace2, "usms.xml") -# ) -# sim_rot <- SticsRFiles::get_sim( -# workspace = workspace2, -# usm = situations, -# usms_file = file.path(workspace2, "usms.xml") -# ) -# -# workspace2 <- system.file(file.path("extdata", "stics_example_2"), -# package = "CroPlotR") -# sim2 <- SticsRFiles::get_sim( -# workspace = workspace2, -# usms_file = file.path(workspace2,"usms.xml") -# ) - -# save(sim, sim2, obs, sim_rot, file = "tests/testthat/_inputs/sim_obs.RData") - -# Loading the inputs - -# setwd("tests/testthat") (local test) -load("_inputs/sim_obs.RData") - -# In case of local tests, plots are stored on _outputs folder -if (!testthat:::on_ci()) { - tmpdir <- "_outputs" - if (!file.exists(tmpdir)) { - dir.create(tmpdir) - } -} - -# Function for making snapshot for vdiffr tests - -make_snapshot <- function(name, plot, tmpdir) { - if (is.null(tmpdir)) { - return() - } - - # From https://github.com/r-lib/vdiffr/blob/main/R/expect-doppelganger.R - testthat::local_edition(3) - fig_name <- vdiffr:::str_standardise(name) - file <- file.path(tmpdir, paste0(fig_name, ".svg")) - - print(paste("Making snapshot", name, "and saving in", file)) - - vdiffr:::write_svg(plot, file, name) - - return(file) -} - -if (!exists("pkg_version")) { - pkg_version <- "Test" -} - -if (!exists("tmpdir")) { - tmpdir <- tempdir() - print(paste( - "Temporary folder path not defined before running this script ", - "('tmpdir' object not existing) => snapshots will be saved in.", - tmpdir - )) -} else { - print(paste("Saving snapshots in", tmpdir)) -} - -pkg_version <- paste0("_", pkg_version) - -print(paste("Script called from", getwd())) - -prefix <- "dynamic" - -# Set seed for comparison of graphs (some use random process) -set.seed(1) - -# Run the tests and generate snapshots - -test_that("format of plotting several situations on different graphs", { - test_plot <- plot(sim, obs = obs, all_situations = FALSE) - - if (any(is.na(test_plot))) { - message( - "Dynamic Plot \"several situations on different graphs\" not yet implemented (plot return NA)" - ) - } else { - expect_true(is.list(test_plot)) - expect_equal(length(test_plot), 3) - expect_true(all( - names(test_plot) %in% - c( - "IC_Wheat_Pea_2005-2006_N0", - "SC_Pea_2005-2006_N0", - "SC_Wheat_2005-2006_N0" - ) - )) - - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.1_simple_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - } -}) - -test_that("Tests with no observations", { - test_plot <- suppressWarnings(plot(sim, all_situations = FALSE)) - expect_true(is.list(test_plot)) - expect_equal(length(test_plot), 3) - expect_true(all( - names(test_plot) %in% - c( - "IC_Wheat_Pea_2005-2006_N0", - "SC_Pea_2005-2006_N0", - "SC_Wheat_2005-2006_N0" - ) - )) - expect_error( - plot(sim, select_dyn = "obs", force = FALSE), - "Observations are required" - ) - expect_error( - plot(sim, select_dyn = "common", force = FALSE), - "Observations are required" - ) -}) - - -all_plots <- list() - -### only overlap - -test_that("Test plot only overlap", { - test_plot <- plot( - sim_sole_crop, - obs = obs, - overlap = list(list("lai_n", "masec_n")) - ) - if (any(is.na(test_plot))) { - message( - "Dynamic Plot \"only overlap\" not yet implemented (plot return NA)" - ) - } else { - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$shape, "Variable") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "Variable") - expect_equal( - unique(test_plot$`SC_Pea_2005-2006_N0`$data$group_var), - "lai_n | masec_n" - ) - expect_equal( - unique(test_plot$`SC_Pea_2005-2006_N0`$data$variable), - c("lai_n", "masec_n") - ) - - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.3_overlap_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - ## add title for visual inspection of the graph - test_plot <- lapply(test_plot, function(x) { - x + - ggplot2::labs(caption = "plot only overlap") + - ggplot2::theme( - plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") - ) - }) - all_plots <<- c(all_plots, test_plot) - } -}) - -### only mixture - -test_that("Test plot only mixture", { - test_plot <- plot(sim_mixture, obs = obs) - if (any(is.na(test_plot))) { - message( - "Dynamic Plot \"only mixture\" not yet implemented (plot return NA)" - ) - } else { - all_plots <<- c(all_plots, test_plot) - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, NULL) - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "Plant") - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.4_mixture_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - ## add title for visual inspection of the graph - test_plot <- lapply(test_plot, function(x) { - x + - ggplot2::labs(caption = "plot only mixture") + - ggplot2::theme( - plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") - ) - }) - all_plots <<- c(all_plots, test_plot) - } -}) - -### only version - -test_that("Test plot only version", { - test_plot <- plot(sim_sole_crop, sim2_sole_crop, obs = obs) - if (any(is.na(test_plot))) { - message('Dynamic Plot "only version" not yet implemented (plot return NA)') - } else { - expect_equal( - test_plot$`SC_Pea_2005-2006_N0`$labels$shape, - "Observed_Legend" - ) - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "version") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$group, NULL) - - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.5_version_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - ## add title for visual inspection of the graph - test_plot <- lapply(test_plot, function(x) { - x + - ggplot2::labs(caption = "plot only version") + - ggplot2::theme( - plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") - ) - }) - all_plots <<- c(all_plots, test_plot) - } -}) - - -### overlap + mixture - -test_that("Test plot overlap + mixture", { - test_plot <- plot( - sim_mixture, - obs = obs, - overlap = list(list("lai_n", "masec_n")) - ) - if (any(is.na(test_plot))) { - message( - "Dynamic Plot \"overlap+mixture\" not yet implemented (plot return NA)" - ) - } else { - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, "Plant") - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "Variable") - expect_equal( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$linetype, - "Plant" - ) - expect_equal( - unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$group_var), - "lai_n | masec_n" - ) - expect_equal( - unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$variable), - c("lai_n", "masec_n") - ) - expect_equal( - unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$Plant), - c("ble", "poi") - ) - - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.6_overlap_mixture_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - ## add title for visual inspection of the graph - test_plot <- lapply(test_plot, function(x) { - x + - ggplot2::labs(caption = "plot overlap + mixture") + - ggplot2::theme( - plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") - ) - }) - all_plots <<- c(all_plots, test_plot) - } -}) - -### overlap + version - -test_that("Test plot overlap + version", { - test_plot <- plot( - sim_sole_crop, - sim2_sole_crop, - obs = obs, - overlap = list(list("lai_n", "masec_n")) - ) - if (any(is.na(test_plot))) { - message( - "Dynamic Plot \"overlap+version\" not yet implemented (plot return NA)" - ) - } else { - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$shape, NULL) - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "Variable") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$linetype, "Version") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$group, NULL) - - expect_equal( - all(sapply( - test_plot$`SC_Pea_2005-2006_N0`$layers[sapply( - test_plot$`SC_Pea_2005-2006_N0`$layers, - function(y) "shape" %in% attributes(y$mapping)$names - )], - function(x) grepl("Version_", rlang::eval_tidy(x$mapping$shape)) - )), - TRUE - ) - expect_equal( - all(sapply( - test_plot$`SC_Pea_2005-2006_N0`$layers[sapply( - test_plot$`SC_Pea_2005-2006_N0`$layers, - function(y) "linetype" %in% attributes(y$mapping)$names - )], - function(x) grepl("Version_", rlang::eval_tidy(x$mapping$linetype)) - )), - TRUE - ) - - expect_equal( - unique(test_plot$`SC_Pea_2005-2006_N0`$data$group_var), - "lai_n | masec_n" - ) - expect_equal( - unique(test_plot$`SC_Pea_2005-2006_N0`$data$variable), - c("lai_n", "masec_n") - ) - expect_equal( - unique(test_plot$`SC_Pea_2005-2006_N0`$data$sit_name), - c("SC_Pea_2005-2006_N0") - ) - - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.7_overlap_version_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - ## add title for visual inspection of the graph - test_plot <- lapply(test_plot, function(x) { - x + - ggplot2::labs(caption = "plot overlap + version") + - ggplot2::theme( - plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") - ) - }) - all_plots <<- c(all_plots, test_plot) - } -}) - - -### mixture + version - -test_that("Test plot mixture + version", { - test_plot <- plot(sim_mixture, sim2_mixture, obs = obs) - if (any(is.na(test_plot))) { - message( - "Dynamic Plot \"mixture+version\" not yet implemented (plot return NA)" - ) - } else { - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, NULL) - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "paste(Dominance, \":\", Plant)") - expect_equal( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$linetype, - "version" - ) - - expect_equal( - all(sapply( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers[sapply( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers, - function(y) "shape" %in% attributes(y$mapping)$names - )], - function(x) grepl("Version_", rlang::eval_tidy(x$mapping$shape)) - )), - TRUE - ) - expect_equal( - all(sapply( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers[sapply( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers, - function(y) "linetype" %in% attributes(y$mapping)$names - )], - function(x) grepl("Version_", rlang::eval_tidy(x$mapping$linetype)) - )), - TRUE - ) - - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.7_mixture_version_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - ## add title for visual inspection of the graph - test_plot <- lapply(test_plot, function(x) { - x + - ggplot2::labs(caption = "plot mixture + version") + - ggplot2::theme( - plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") - ) - }) - all_plots <<- c(all_plots, test_plot) - } -}) - - -### successive - -test_that("format of plotting several situations on different graphs", { - test_plot <- plot(sim_rot, obs = obs, - successive = list(list("demo_Wheat1", "demo_BareSoil2", "demo_maize3")), - var = c("resmes", "masec_n"), - all_situations = FALSE) - - if (any(is.na(test_plot))) { - message( - "Dynamic Plot \"several situations on different graphs\" not yet implemented (plot return NA)" - ) - } else { - expect_true(is.list(test_plot)) - expect_equal(length(test_plot), 1) - lapply(names(test_plot), function(x) { - make_snapshot( - paste0(prefix, "_fig.8_successive_", x, pkg_version), - test_plot[[x]], - tmpdir - ) - }) - } -}) - - -if (!testthat:::on_ci()) { - save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_dynamic") - print(paste("Plots saved in pdf format in ", tmpdir)) - save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_dynamic") - print(paste("Plots saved in pdf format in ", tmpdir)) -} +# +# Tests the scatter plots +# +# Automatic tests + generates a pdf and svg in _outputs to visually check the plots +# +# See doc on tests for CroPlotR in doc/doc_on_tests.md + +library(CroPlotR) +library(testthat) + +# # Make the reference data: +# +# workspace <- system.file(file.path("extdata", "stics_example_1"), +# package = "CroPlotR" +# ) +# +# situations <- SticsRFiles::get_usms_list( +# file = file.path(workspace,"usms.xml") +# ) +# +# sim <- SticsRFiles::get_sim( +# workspace = workspace, +# usm = situations, +# usms_file = file.path(workspace,"usms.xml") +# ) +# +# obs <- SticsRFiles::get_obs( +# workspace = workspace, +# usm = situations, +# usms_file = file.path(workspace, "usms.xml") +# ) +# +# # Rotation example +# workspace2 <- system.file( +# file.path("extdata", "stics_example_successive"), +# package = "CroPlotR" +# ) +# situations <- SticsRFiles::get_usms_list( +# file = file.path(workspace2, "usms.xml") +# ) +# sim_rot <- SticsRFiles::get_sim( +# workspace = workspace2, +# usm = situations, +# usms_file = file.path(workspace2, "usms.xml") +# ) +# +# workspace2 <- system.file(file.path("extdata", "stics_example_2"), +# package = "CroPlotR") +# sim2 <- SticsRFiles::get_sim( +# workspace = workspace2, +# usms_file = file.path(workspace2,"usms.xml") +# ) + +# save(sim, sim2, obs, sim_rot, file = "tests/testthat/_inputs/sim_obs.RData") + +# Loading the inputs + +# setwd("tests/testthat") (local test) +load("_inputs/sim_obs.RData") + +# In case of local tests, plots are stored on _outputs folder +if (!testthat:::on_ci()) { + tmpdir <- "_outputs" + if (!file.exists(tmpdir)) { + dir.create(tmpdir) + } +} + +# Function for making snapshot for vdiffr tests + +make_snapshot <- function(name, plot, tmpdir) { + if (is.null(tmpdir)) { + return() + } + + # From https://github.com/r-lib/vdiffr/blob/main/R/expect-doppelganger.R + testthat::local_edition(3) + fig_name <- vdiffr:::str_standardise(name) + file <- file.path(tmpdir, paste0(fig_name, ".svg")) + + print(paste("Making snapshot", name, "and saving in", file)) + + vdiffr:::write_svg(plot, file, name) + + return(file) +} + +if (!exists("pkg_version")) { + pkg_version <- "Test" +} + +if (!exists("tmpdir")) { + tmpdir <- tempdir() + print(paste( + "Temporary folder path not defined before running this script ", + "('tmpdir' object not existing) => snapshots will be saved in.", + tmpdir + )) +} else { + print(paste("Saving snapshots in", tmpdir)) +} + +pkg_version <- paste0("_", pkg_version) + +print(paste("Script called from", getwd())) + +prefix <- "dynamic" + +# Set seed for comparison of graphs (some use random process) +set.seed(1) + +# Run the tests and generate snapshots + +test_that("format of plotting several situations on different graphs", { + test_plot <- plot(sim, obs = obs, all_situations = FALSE) + + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"several situations on different graphs\" not yet implemented (plot return NA)" + ) + } else { + expect_true(is.list(test_plot)) + expect_equal(length(test_plot), 3) + expect_true(all( + names(test_plot) %in% + c( + "IC_Wheat_Pea_2005-2006_N0", + "SC_Pea_2005-2006_N0", + "SC_Wheat_2005-2006_N0" + ) + )) + + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.1_simple_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + } +}) + +test_that("Tests with no observations", { + test_plot <- suppressWarnings(plot(sim, all_situations = FALSE)) + expect_true(is.list(test_plot)) + expect_equal(length(test_plot), 3) + expect_true(all( + names(test_plot) %in% + c( + "IC_Wheat_Pea_2005-2006_N0", + "SC_Pea_2005-2006_N0", + "SC_Wheat_2005-2006_N0" + ) + )) + expect_error( + plot(sim, select_dyn = "obs", force = FALSE), + "Observations are required" + ) + expect_error( + plot(sim, select_dyn = "common", force = FALSE), + "Observations are required" + ) +}) + + +all_plots <- list() + +### only overlap + +test_that("Test plot only overlap", { + test_plot <- plot( + sim_sole_crop, + obs = obs, + overlap = list(list("lai_n", "masec_n")) + ) + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"only overlap\" not yet implemented (plot return NA)" + ) + } else { + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$shape, "Variable") + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "Variable") + expect_equal( + unique(test_plot$`SC_Pea_2005-2006_N0`$data$group_var), + "lai_n | masec_n" + ) + expect_equal( + unique(test_plot$`SC_Pea_2005-2006_N0`$data$variable), + c("lai_n", "masec_n") + ) + + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.3_overlap_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot only overlap") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) + } +}) + +### only mixture + +test_that("Test plot only mixture", { + test_plot <- plot(sim_mixture, obs = obs) + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"only mixture\" not yet implemented (plot return NA)" + ) + } else { + all_plots <<- c(all_plots, test_plot) + expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, NULL) + expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "Plant") + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.4_mixture_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot only mixture") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) + } +}) + +### only version + +test_that("Test plot only version", { + test_plot <- plot(sim_sole_crop, sim2_sole_crop, obs = obs) + if (any(is.na(test_plot))) { + message('Dynamic Plot "only version" not yet implemented (plot return NA)') + } else { + expect_equal( + test_plot$`SC_Pea_2005-2006_N0`$labels$shape, + "Observed_Legend" + ) + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "version") + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$group, NULL) + + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.5_version_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot only version") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) + } +}) + + +### overlap + mixture + +test_that("Test plot overlap + mixture", { + test_plot <- plot( + sim_mixture, + obs = obs, + overlap = list(list("lai_n", "masec_n")) + ) + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"overlap+mixture\" not yet implemented (plot return NA)" + ) + } else { + expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, "Plant") + expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "Variable") + expect_equal( + test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$linetype, + "Plant" + ) + expect_equal( + unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$group_var), + "lai_n | masec_n" + ) + expect_equal( + unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$variable), + c("lai_n", "masec_n") + ) + expect_equal( + unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$Plant), + c("ble", "poi") + ) + + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.6_overlap_mixture_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot overlap + mixture") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) + } +}) + +### overlap + version + +test_that("Test plot overlap + version", { + test_plot <- plot( + sim_sole_crop, + sim2_sole_crop, + obs = obs, + overlap = list(list("lai_n", "masec_n")) + ) + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"overlap+version\" not yet implemented (plot return NA)" + ) + } else { + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$shape, NULL) + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "Variable") + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$linetype, "Version") + expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$group, NULL) + + expect_equal( + all(sapply( + test_plot$`SC_Pea_2005-2006_N0`$layers[sapply( + test_plot$`SC_Pea_2005-2006_N0`$layers, + function(y) "shape" %in% attributes(y$mapping)$names + )], + function(x) grepl("Version_", rlang::eval_tidy(x$mapping$shape)) + )), + TRUE + ) + expect_equal( + all(sapply( + test_plot$`SC_Pea_2005-2006_N0`$layers[sapply( + test_plot$`SC_Pea_2005-2006_N0`$layers, + function(y) "linetype" %in% attributes(y$mapping)$names + )], + function(x) grepl("Version_", rlang::eval_tidy(x$mapping$linetype)) + )), + TRUE + ) + + expect_equal( + unique(test_plot$`SC_Pea_2005-2006_N0`$data$group_var), + "lai_n | masec_n" + ) + expect_equal( + unique(test_plot$`SC_Pea_2005-2006_N0`$data$variable), + c("lai_n", "masec_n") + ) + expect_equal( + unique(test_plot$`SC_Pea_2005-2006_N0`$data$sit_name), + c("SC_Pea_2005-2006_N0") + ) + + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.7_overlap_version_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot overlap + version") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) + } +}) + + +### mixture + version + +test_that("Test plot mixture + version", { + test_plot <- plot(sim_mixture, sim2_mixture, obs = obs) + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"mixture+version\" not yet implemented (plot return NA)" + ) + } else { + expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, NULL) + expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "paste(Dominance, \":\", Plant)") + expect_equal( + test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$linetype, + "version" + ) + + expect_equal( + all(sapply( + test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers[sapply( + test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers, + function(y) "shape" %in% attributes(y$mapping)$names + )], + function(x) grepl("Version_", rlang::eval_tidy(x$mapping$shape)) + )), + TRUE + ) + expect_equal( + all(sapply( + test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers[sapply( + test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers, + function(y) "linetype" %in% attributes(y$mapping)$names + )], + function(x) grepl("Version_", rlang::eval_tidy(x$mapping$linetype)) + )), + TRUE + ) + + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.7_mixture_version_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot mixture + version") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) + } +}) + + +### successive + +test_that("format of plotting several situations on different graphs", { + test_plot <- plot(sim_rot, + obs = obs, + successive = list(list("demo_Wheat1", "demo_BareSoil2", "demo_maize3")), + var = c("resmes", "masec_n"), + all_situations = FALSE + ) + + if (any(is.na(test_plot))) { + message( + "Dynamic Plot \"several situations on different graphs\" not yet implemented (plot return NA)" + ) + } else { + expect_true(is.list(test_plot)) + expect_equal(length(test_plot), 1) + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.8_successive_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + } +}) + + +if (!testthat:::on_ci()) { + save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_dynamic") + print(paste("Plots saved in pdf format in ", tmpdir)) + save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_dynamic") + print(paste("Plots saved in pdf format in ", tmpdir)) +} From 236cd71e2343413964ac4c9be38c635a4f068452 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 4 Jun 2025 23:27:11 +0200 Subject: [PATCH 015/118] add plot successive --- R/cropr_formatting.R | 4 ++-- R/generic_plotting.R | 14 ++++++-------- R/specific_plotting_dynamic.R | 12 +++++++++++- 3 files changed, 19 insertions(+), 11 deletions(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index c4ca56b3..0f45e693 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -296,9 +296,9 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, # Making the data: df <- sim %>% - dplyr::select(-tidyselect::any_of(rem_vars)) %>% + #dplyr::select(-tidyselect::any_of(rem_vars)) %>% reshape2::melt( - id.vars = melt_vars_sim, + id.vars = c(melt_vars_sim,rem_vars), na.rm = TRUE, value.name = "Simulated" ) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 3775cfd8..f7d8f3b2 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -171,19 +171,17 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, p <- list() for (i in common_situations_models) { sim_situation <- formated_situation_list[[i]] - item_case <- detect_item_case( type, detect_mixture(sim_situation), one_version, several_sit, overlap ) - plot_title <- if (!is.null(title)) { + plot_title <- if (!is.null(title)) { title[[i]] - } else if (!several_sit) { - NULL # No title by default if it's all situations + } else if (type == "scatter" && all_situations == TRUE) { + "All situations" } else { i } - p[[i]] <- switch(item_case, # Dynamic plots: "mixture_versions_overlap" = @@ -203,9 +201,9 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, plot_dynamic_versions(sim_situation, i, title = plot_title), "non_mixture_no_versions_overlap" = plot_dynamic_overlap(sim_situation, i, title = plot_title), - "non_mixture_no_versions_no_overlap" = plot_dynamic(sim_situation, i, - title = plot_title - ), + "non_mixture_no_versions_no_overlap" = + plot_dynamic(sim_situation, i, successive, title = plot_title + ), # Scatter plots: "mixture_versions_situations" = NA, diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index 18e6bfb1..dea6ba83 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -46,13 +46,23 @@ NULL #' @keywords internal #' @rdname specific_dynamic_plots -plot_dynamic <- function(df_data, sit, title = NULL) { +plot_dynamic <- function(df_data, sit, successive, title = NULL) { p <- ggplot2::ggplot( df_data, ggplot2::aes(x = .data$Date) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + ggplot2::facet_wrap(~ .data$variable, scales = "free_y") + + if (!is.null(successive)) { + dates = unique(df_data$succession_date) + dates_vlines <- as.POSIXct(dates, tz = "UTC") + p <- p + ggplot2::geom_vline( + xintercept = as.numeric(dates_vlines[-length(dates_vlines)]), + linetype = "dashed", + color = "red" + ) + } if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point(ggplot2::aes(y = .data$Observed), na.rm = TRUE) From fa66ed0a347cc89a7540594957755a18f6cef837 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 4 Jun 2025 21:31:03 +0000 Subject: [PATCH 016/118] Style code (GHA) --- R/cropr_formatting.R | 4 ++-- R/generic_plotting.R | 5 ++--- R/specific_plotting_dynamic.R | 4 ++-- 3 files changed, 6 insertions(+), 7 deletions(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 93fe8fee..a6a9d830 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -296,9 +296,9 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, # Making the data: df <- sim %>% - #dplyr::select(-tidyselect::any_of(rem_vars)) %>% + # dplyr::select(-tidyselect::any_of(rem_vars)) %>% reshape2::melt( - id.vars = c(melt_vars_sim,rem_vars), + id.vars = c(melt_vars_sim, rem_vars), na.rm = TRUE, value.name = "Simulated" ) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index f7d8f3b2..de8faa60 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -175,7 +175,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, type, detect_mixture(sim_situation), one_version, several_sit, overlap ) - plot_title <- if (!is.null(title)) { + plot_title <- if (!is.null(title)) { title[[i]] } else if (type == "scatter" && all_situations == TRUE) { "All situations" @@ -202,8 +202,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, "non_mixture_no_versions_overlap" = plot_dynamic_overlap(sim_situation, i, title = plot_title), "non_mixture_no_versions_no_overlap" = - plot_dynamic(sim_situation, i, successive, title = plot_title - ), + plot_dynamic(sim_situation, i, successive, title = plot_title), # Scatter plots: "mixture_versions_situations" = NA, diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index dea6ba83..771d2634 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -53,9 +53,9 @@ plot_dynamic <- function(df_data, sit, successive, title = NULL) { ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + ggplot2::facet_wrap(~ .data$variable, scales = "free_y") - + if (!is.null(successive)) { - dates = unique(df_data$succession_date) + dates <- unique(df_data$succession_date) dates_vlines <- as.POSIXct(dates, tz = "UTC") p <- p + ggplot2::geom_vline( xintercept = as.numeric(dates_vlines[-length(dates_vlines)]), From 29618016605dcb917febce01b27275b4432837ed Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 4 Jun 2025 23:49:53 +0200 Subject: [PATCH 017/118] add plot successive) --- R/cropr_formatting.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 93fe8fee..825e9104 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -296,9 +296,9 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, # Making the data: df <- sim %>% - #dplyr::select(-tidyselect::any_of(rem_vars)) %>% + dplyr::select(-tidyselect::any_of(rem_vars)) %>% reshape2::melt( - id.vars = c(melt_vars_sim,rem_vars), + id.vars = melt_vars_sim, na.rm = TRUE, value.name = "Simulated" ) From 872cd1d19c9339b2bee5af2f2f436d7eb1974efa Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Thu, 5 Jun 2025 00:05:06 +0200 Subject: [PATCH 018/118] add plot successive --- R/specific_plotting_dynamic.R | 2 ++ 1 file changed, 2 insertions(+) diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index 771d2634..e1311870 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -8,6 +8,8 @@ #' @param df_data A named list of data frame including the data to plot (one df #' per situation) #' @param sit The name of the situation to plot +#' @param successive A list of lists containing the situations to be represented +#' as a contiguous sequence #' @param title The plot title (optional, NULL by default) #' #' @importFrom rlang .data From 107566d947dca806385a966e39f6f827f82a8fc7 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Thu, 5 Jun 2025 00:46:27 +0200 Subject: [PATCH 019/118] add plot successive --- man/specific_dynamic_plots.Rd | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/man/specific_dynamic_plots.Rd b/man/specific_dynamic_plots.Rd index 1569f87b..d2134509 100644 --- a/man/specific_dynamic_plots.Rd +++ b/man/specific_dynamic_plots.Rd @@ -5,7 +5,7 @@ \alias{plot_dynamic} \title{Specific functions to generate dynamic plots} \usage{ -plot_dynamic(df_data, sit, title = NULL) +plot_dynamic(df_data, sit, successive, title = NULL) } \arguments{ \item{df_data}{A named list of data frame including the data to plot (one df @@ -13,6 +13,9 @@ per situation)} \item{sit}{The name of the situation to plot} +\item{successive}{A list of lists containing the situations to be represented +as a contiguous sequence} + \item{title}{The plot title (optional, NULL by default)} } \value{ From b97677c3ed248d5107ea8fb691e44eb16a6114a7 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Thu, 5 Jun 2025 10:38:05 +0200 Subject: [PATCH 020/118] add plot successive --- R/cropr_formatting.R | 3 ++- R/specific_plotting_dynamic.R | 2 +- tests/testthat/test-dynamic-plots.R | 13 +++++++++++-- 3 files changed, 14 insertions(+), 4 deletions(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 825e9104..9febacb2 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -213,7 +213,8 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, melt_vars <- "Date" } if (!is.null(successive)) { - rem_vars <- c(rem_vars, "succession_date") + #rem_vars <- c(rem_vars, "succession_date") + melt_vars <- c(melt_vars, "succession_date") } if ("sit_name" %in% colnames(sim)) { diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index e1311870..9eea4a03 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -62,7 +62,7 @@ plot_dynamic <- function(df_data, sit, successive, title = NULL) { p <- p + ggplot2::geom_vline( xintercept = as.numeric(dates_vlines[-length(dates_vlines)]), linetype = "dashed", - color = "red" + color = "black" ) } diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index ac5dfe5d..fd4dd722 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -331,7 +331,7 @@ test_that("Test plot overlap + version", { sim_sole_crop, sim2_sole_crop, obs = obs, - overlap = list(list("lai_n", "masec_n")) + overlap = list(list("lai_n", "masec_n")), all_situations = FALSE ) if (any(is.na(test_plot))) { message( @@ -456,7 +456,7 @@ test_that("Test plot mixture + version", { ### successive -test_that("format of plotting several situations on different graphs", { +test_that("Test successive plot", { test_plot <- plot(sim_rot, obs = obs, successive = list(list("demo_Wheat1", "demo_BareSoil2", "demo_maize3")), @@ -478,6 +478,15 @@ test_that("format of plotting several situations on different graphs", { tmpdir ) }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot successive") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) } }) From 56cf6b866af51afae6eabc94bde2069d93918d85 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Thu, 5 Jun 2025 08:39:52 +0000 Subject: [PATCH 021/118] Style code (GHA) --- R/cropr_formatting.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 9febacb2..98fc7ae0 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -213,7 +213,7 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, melt_vars <- "Date" } if (!is.null(successive)) { - #rem_vars <- c(rem_vars, "succession_date") + # rem_vars <- c(rem_vars, "succession_date") melt_vars <- c(melt_vars, "succession_date") } From e4a4cea76bdd0f3e33cbb63856f3b9334533fdc4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:08:17 +0200 Subject: [PATCH 022/118] Update WORDLIST --- inst/WORDLIST | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/inst/WORDLIST b/inst/WORDLIST index fe2fae16..4006425c 100644 --- a/inst/WORDLIST +++ b/inst/WORDLIST @@ -1,8 +1,7 @@ APSIM -Analyse -Apsim CeCILL Codecov +Combi CropR CroplotR Cropr @@ -29,35 +28,38 @@ STICS Salam Stics SticsRFiles +SticsRPacks Sutcliffe USM Unwatch WIP +aes +args binded bmp bservations +btw +cff colouring -cran cropr df dplyr eps -formater +faaaast ggplot ggplotly ggplots +github heigth -https intercrop intercropping jpeg lai -lm +linetype mafruit masec nRMSE nd -outputed pMSEs pMSEu pictex @@ -76,9 +78,12 @@ sd svg tLimit tSTUD +testthat tex tibble tibbles tidyr usms wmf +xaxis +yaxis From 1bf0d9ed982bd6bdf8d1404b6b212675066bcfb5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:33:27 +0200 Subject: [PATCH 023/118] Use || instead of | --- R/specific_plotting_scatter.R | 321 ++++++++++++++++++++++++++++++++++ 1 file changed, 321 insertions(+) create mode 100644 R/specific_plotting_scatter.R diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R new file mode 100644 index 00000000..1bd23414 --- /dev/null +++ b/R/specific_plotting_scatter.R @@ -0,0 +1,321 @@ +#' Specific functions to generate scatter plots +#' +#' @description Generate scatter plots for the different cases handled in +#' CroPlotR (plant mixture, plot of residuals, plot several simulation results +#' on same graph, ...) as specified by the different arguments. +#' +#' @param df_data A named list of data frame including the data to plot (one df +#' per situation, or only one df if sit==all_situations) +#' @param sit The name of the situation to plot (or all_situations) +#' @param is_obs_sd TRUE if error standard deviation of observations is provided +#' +#' @importFrom rlang .data +#' @return A ggplot object +#' +#' @details List of the different specific functions: +#' \itemize{ +#' \item `plot_scat_mixture_allsit`: Generate a scatter plot for the case of +#' mixture of crops, single simulation version and all_situations in same plot +#' \item `plot_scat_allsit`: Generate a scatter plot for the case of +#' sole crops, single simulation version and all_situations in same plot +#' } +#' +#' @return A list of ggplot objects +#' +#' @name specific_scatter_plots +#' +NULL + + +#' @keywords internal +#' @description Compute axis bounds (+/-0.05 added to the min/max of the data). +#' @rdname specific_scatter_plots +#' @param y_var_type type of variable to plot ("Simulated" or "Residuals") +#' @return List of x and y axis bounds (xaxis_min, xaxis_max, yaxis_min, +#' yaxis_max) +compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { + # Compute x and y axis min and max to set axis limits + df_min <- df_data %>% + group_by(.data$variable) %>% + summarise(across(where(is.numeric), min)) + df_max <- df_data %>% + group_by(.data$variable) %>% + summarise(across(where(is.numeric), max)) + xaxis_min <- df_min[[reference_var]] - 0.05 * df_min[[reference_var]] + xaxis_max <- df_max[[reference_var]] + 0.05 * df_max[[reference_var]] + yaxis_min <- df_min[[y_var_type]] - 0.05 * df_min[[y_var_type]] + yaxis_max <- df_max[[y_var_type]] + 0.05 * df_max[[y_var_type]] + + if (is_obs_sd && reference_var == "Observed") { + # Update xaxis min and max in case of addition of error bars + df_min <- df_data %>% + mutate(barmin = .data$Observed - 2 * .data$Obs_SD) %>% + group_by(.data$variable) %>% + summarise(across(where(is.numeric), min)) + df_max <- df_data %>% + mutate(barmax = .data$Observed + 2 * .data$Obs_SD) %>% + group_by(.data$variable) %>% + summarise(across(where(is.numeric), max)) + xaxis_min <- df_min[["barmin"]] - 0.05 * df_min[["barmin"]] + xaxis_max <- df_max[["barmax"]] + 0.05 * df_max[["barmax"]] + } + + return(list( + xaxis_min = xaxis_min, xaxis_max = xaxis_max, + yaxis_min = yaxis_min, yaxis_max = yaxis_max + )) +} + + +#' @keywords internal +#' @description Make axis square +#' @rdname specific_scatter_plots +#' @param p A ggplot to modify` +#' @param y_var_type type of variable to plot ("Simulated" or "Residuals") +#' @return The modified ggplot +make_axis_square <- function(df_data, reference_var, y_var_type, is_obs_sd, p) { + axis_bounds <- compute_axis_bounds(df_data, reference_var, y_var_type, is_obs_sd) + axis_min <- pmin(axis_bounds$xaxis_min, axis_bounds$yaxis_min) + axis_max <- pmax(axis_bounds$xaxis_max, axis_bounds$yaxis_max) + p <- p + + ggh4x::facetted_pos_scales( + x = lapply(1:length(axis_min), function(i) { + ggplot2::scale_x_continuous(limits = c(axis_min[i], axis_max[i])) + }), + y = lapply(1:length(axis_min), function(i) { + ggplot2::scale_y_continuous(limits = c(axis_min[i], axis_max[i])) + }) + ) + return(p) +} + +#' Get reference variable for plotting +#' +#' @description Return the reference variable and its display name for scatter +#' plots +#' +#' @param reference_var The reference variable name, if NULL "Observed" is used +#' +#' @keywords internal +#' +#' @return A list with two elements: +#' \itemize{ +#' \item reference_var: The reference variable name: "Observed" or "Reference" +#' \item reference_var_name: The display name for the reference variable +#' } +give_reference_var <- function(reference_var) { + if (is.null(reference_var)) { + reference_var <- "Observed" + reference_var_name <- "Observed" + } else { + reference_var_name <- reference_var + reference_var <- "Reference" + } + return( + list( + reference_var = reference_var, reference_var_name = reference_var_name + ) + ) +} + +#' Get y variable type for plotting +#' +#' @description Return the type of y variable for scatter plots based on +#' selection +#' +#' @param select_scat Selection type, either "sim" for Simulated or any other +#' value for Residuals +#' +#' @keywords internal +#' +#' @return A character string, either "Simulated" or "Residuals" +give_y_var_type <- function(select_scat) { + if (select_scat == "sim") { + y_var_type <- "Simulated" + } else { + y_var_type <- "Residuals" + } + return(y_var_type) +} + + +#' @keywords internal +#' @description Add error bars on observed values in given scatterplot +#' @rdname specific_scatter_plots +#' @param p A ggplot to modify` +#' @param colour_factor The factor to use for colouring the error bars +#' @return The modified ggplot +add_obs_error_bars <- function(p, colour_factor) { + p <- p + + ggplot2::geom_errorbarh( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + colour = .data[[colour_factor]], + height = 0 + ), + na.rm = TRUE + ) + return(p) +} + +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ) + + if (shape_sit == "none" || shape_sit == "txt") { + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) + ), + na.rm = TRUE + ) + } else if (shape_sit == "symbol" || shape_sit == "group") { + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(paste(.data$Dominance, ":", .data$Plant)), + shape = as.factor(paste(.data$sit_name)) + ), + na.rm = TRUE + ) + + ggplot2::scale_shape_discrete(name = "Situation") + } + + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::labs(fill = "Plant") + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + + ggplot2::ggtitle(title) + + if (is_obs_sd & reference_var == "Observed") { + p$data$colour_factor <- as.factor(paste(p$data$Dominance, ":", p$data$Plant)) + p <- add_obs_error_bars(p, + colour_factor = "colour_factor" + ) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + if (shape_sit == "txt") { + p <- p + + ggrepel::geom_text_repel( + ggplot2::aes( + label = .data$sit_name, + colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) + ), + max.overlaps = 100 + ) + } + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" & reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + + p <- p + ggplot2::scale_color_discrete(name = "Plant") + + return(p) +} + + + + +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ) + + if (shape_sit == "none" | shape_sit == "txt") { + p <- p + ggplot2::geom_point(na.rm = TRUE) + } else if (shape_sit == "symbol" | shape_sit == "group") { + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(paste(.data$sit_name)) + ), + na.rm = TRUE + ) + + ggplot2::scale_color_discrete(name = "Situation") + } + + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + + ggplot2::ggtitle(title) + + if (is_obs_sd & reference_var == "Observed") { + p$data$colour_factor <- as.factor(paste(p$data$sit_name)) + p <- add_obs_error_bars(p, + colour_factor = "colour_factor" + ) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + if (shape_sit == "txt") { + p <- p + + ggrepel::geom_text_repel( + ggplot2::aes( + label = .data$sit_name + ), + max.overlaps = 100 + ) + } + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" & reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + + return(p) +} From da1099968da6949a83552528e498df3cdb4c7bf9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 15:40:09 +0200 Subject: [PATCH 024/118] Fix linter issues --- R/specific_plotting_scatter.R | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 1bd23414..b73e0fcb 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -234,7 +234,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, } # Set same limits for x and y axis for sim VS obs scatter plots - if (select_scat == "sim" & reference_var == "Observed") { + if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } @@ -293,7 +293,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, p <- p + ggplot2::ggtitle(title) - if (is_obs_sd & reference_var == "Observed") { + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$sit_name)) p <- add_obs_error_bars(p, colour_factor = "colour_factor" @@ -313,7 +313,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, } # Set same limits for x and y axis for sim VS obs scatter plots - if (select_scat == "sim" & reference_var == "Observed") { + if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } From 8813070a1854d6e5e1d8746534d8ae5d1b1a16c2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:03:01 +0200 Subject: [PATCH 025/118] fix typo --- R/generic_plotting.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 3c7a11ab..52246cdb 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -342,7 +342,7 @@ plot_generic_situation <- function(sim, obs = NULL, obs_sd = NULL, #' `all_situations= TRUE`. See details. #' @param situation_group A list of lists of situations to gather when #' `shape_sit= "group"`. -#' @param reference_var Variable selected on x-axis when type is scaétter and +#' @param reference_var Variable selected on x-axis when type is scatter and #' select_scat is res. It is possible to select #' between observation and simulation of the reference variable. #' (examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim") From 73d92f32b2fa8a4f2b0b0b3e11e41001a6a4b8cd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:04:25 +0200 Subject: [PATCH 026/118] | -> || and & -> && --- R/specific_plotting_scatter.R | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index b73e0fcb..561266f8 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -170,7 +170,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( @@ -213,7 +213,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, p <- p + ggplot2::ggtitle(title) - if (is_obs_sd & reference_var == "Observed") { + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$Dominance, ":", p$data$Plant)) p <- add_obs_error_bars(p, colour_factor = "colour_factor" @@ -257,7 +257,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( @@ -265,9 +265,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - if (shape_sit == "none" | shape_sit == "txt") { + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point(na.rm = TRUE) - } else if (shape_sit == "symbol" | shape_sit == "group") { + } else if (shape_sit == "symbol" || shape_sit == "group") { p <- p + ggplot2::geom_point( ggplot2::aes( colour = as.factor(paste(.data$sit_name)) From 13144dfe158877a5d5aa15bf9906ca62c1e35184 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:16:13 +0200 Subject: [PATCH 027/118] Update specific_plotting_scatter.R Remove letter in the legend of shape_sit="txt" (found looking at fig. 5) --- R/specific_plotting_scatter.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 561266f8..d621a533 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -170,7 +170,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( @@ -229,6 +229,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, label = .data$sit_name, colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) ), + show.legend = FALSE, max.overlaps = 100 ) } From 3f7fed0fdb34490dd995a249f201949795840882 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 16:20:50 +0200 Subject: [PATCH 028/118] Update specific_plotting_scatter.R --- R/specific_plotting_scatter.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index d621a533..58676c8a 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -258,7 +258,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) && !is.na(.data[[y_var_type]])) + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) p <- ggplot2::ggplot( From 093ca855ef70a40c67bc4f559ce39df9416e0a97 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 30 Apr 2025 17:07:23 +0200 Subject: [PATCH 029/118] Update test-scatter-plots.R --- tests/testthat/test-scatter-plots.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index 35ea1a05..a2c71da7 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -215,7 +215,7 @@ tmp$situation_group <- lapply( all_plots <- list() # Test the different variants of plots based on the file _inputs/tests_scatter_plot.csv -invisible(lapply(1:nrow(tmp), function(i) { +invisible(lapply(seq_len(nrow(tmp)), function(i) { test_that(paste0("Test #", tmp$Number[[i]]), { if (tmp$version[i]) { test_plot <- plot(tmp$sim[[i]], tmp$sim2[[i]], From 7b3f870d511c8517517f450e00c617481ea03e82 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 4 Jun 2025 09:37:24 +0200 Subject: [PATCH 030/118] Removed WIP badge --- README.Rmd | 3 --- 1 file changed, 3 deletions(-) diff --git a/README.Rmd b/README.Rmd index 2b50d6b8..d8679c7a 100644 --- a/README.Rmd +++ b/README.Rmd @@ -21,9 +21,6 @@ knitr::opts_chunk$set( -[![Project Status: WIP – Initial development is in progress, but there -has not yet been a stable, usable release suitable for the -public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip) [![Codecov test coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/master/graph/badge.svg)](https://app.codecov.io/gh/SticsRPacks/CroPlotR?branch=master) [![R-CMD-check](https://github.com/SticsRPacks/CroPlotR/actions/workflows/check-standard.yaml/badge.svg?branch=main)](https://github.com/SticsRPacks/CroPlotR/actions/workflows/check-standard.yaml) From 38f939be08b179b8a15b2313b46ef1ce66e7e7a6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 5 Jun 2025 15:05:40 +0200 Subject: [PATCH 031/118] Add plot_scat_persit (per situation) --- R/specific_plotting_scatter.R | 84 ++++++++++++++++++++++++++++++----- 1 file changed, 73 insertions(+), 11 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 58676c8a..94a9e504 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -145,17 +145,19 @@ give_y_var_type <- function(select_scat) { #' @param p A ggplot to modify` #' @param colour_factor The factor to use for colouring the error bars #' @return The modified ggplot -add_obs_error_bars <- function(p, colour_factor) { - p <- p + - ggplot2::geom_errorbarh( - ggplot2::aes( - xmin = .data$Observed - 2 * .data$Obs_SD, - xmax = .data$Observed + 2 * .data$Obs_SD, - colour = .data[[colour_factor]], - height = 0 - ), - na.rm = TRUE - ) +add_obs_error_bars <- function(p, colour_factor = NULL) { + aes_ <- ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + colour = .data[[colour_factor]], + height = 0 + ) + + if (is.null(colour_factor)) { + aes_$colour <- NULL + } + + p <- p + ggplot2::geom_errorbarh(aes_, na.rm = TRUE) return(p) } @@ -320,3 +322,63 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, return(p) } + + +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_persit <- function(df_data, sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ) + + p <- p + ggplot2::geom_point(na.rm = TRUE) + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + ggplot2::ggtitle(title) + + if (is_obs_sd && reference_var == "Observed") { + p <- add_obs_error_bars(p) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + if (shape_sit == "txt") { + p <- p + + ggrepel::geom_text_repel( + ggplot2::aes( + label = .data$sit_name + ), + max.overlaps = 100 + ) + } + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" && reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + + return(p) +} From 10a952e89323738380116c3259b85c3153f8746f Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Thu, 5 Jun 2025 10:38:05 +0200 Subject: [PATCH 032/118] add plot successive --- R/cropr_formatting.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 8a82a531..89f9d583 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -191,7 +191,8 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, melt_vars <- "Date" } if (!is.null(successive)) { - rem_vars <- c(rem_vars, "succession_date") + #rem_vars <- c(rem_vars, "succession_date") + melt_vars <- c(melt_vars, "succession_date") } From 4a5dfbb65d0dac8469375da87351a33d9f7aa61a Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Thu, 5 Jun 2025 08:39:52 +0000 Subject: [PATCH 033/118] Style code (GHA) --- R/cropr_formatting.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 89f9d583..546609a5 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -191,7 +191,7 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, melt_vars <- "Date" } if (!is.null(successive)) { - #rem_vars <- c(rem_vars, "succession_date") + # rem_vars <- c(rem_vars, "succession_date") melt_vars <- c(melt_vars, "succession_date") } From 94f7a6fc3592992fc2e0080fde8597e15470c284 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 5 Jun 2025 16:49:27 +0200 Subject: [PATCH 034/118] Using standard version of pak --- .github/workflows/check-standard.yaml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/.github/workflows/check-standard.yaml b/.github/workflows/check-standard.yaml index 6a1ba404..747b863b 100644 --- a/.github/workflows/check-standard.yaml +++ b/.github/workflows/check-standard.yaml @@ -51,10 +51,6 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: - pak-version: rc - # about pak-version: - # Ubuntu doesn't install the proper version of XML see https://github.com/r-lib/actions/issues/559. Remove when fixed. - # see also: https://stackoverflow.com/questions/73243945/pkgdown-action-failing-at-build-xml extra-packages: | any::rcmdcheck SticsRPacks/SticsRFiles@main From a534cee5ea489f50b5723d1b138ead14726760bd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 5 Jun 2025 16:51:29 +0200 Subject: [PATCH 035/118] And use standard version of pak for vdiffr too --- .github/workflows/vdiffr.yaml | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/.github/workflows/vdiffr.yaml b/.github/workflows/vdiffr.yaml index 1f1bdc7c..11efaf25 100644 --- a/.github/workflows/vdiffr.yaml +++ b/.github/workflows/vdiffr.yaml @@ -5,7 +5,7 @@ on: jobs: snapshot_comparison: - runs-on: ubuntu-latest # Replace with the appropriate runner for your needs + runs-on: ubuntu-latest # Replace with the appropriate runner for your needs steps: - name: Checkout repository @@ -18,10 +18,6 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: - pak-version: rc - # about pak-version: - # Ubuntu doesn't install the proper version of XML see https://github.com/r-lib/actions/issues/559. Remove when fixed. - # see also: https://stackoverflow.com/questions/73243945/pkgdown-action-failing-at-build-xml extra-packages: | any::testthat any::rcmdcheck @@ -37,7 +33,8 @@ jobs: Rscript -e "pkg_version <- 'Latest'; tmpdir <- '${{ runner.temp }}'; testthat::test_file('tests/testthat/test-dynamic-plots.R', stop_on_failure=FALSE); testthat::test_file('tests/testthat/test-scatter-plots.R', stop_on_failure=FALSE)" - name: Cache the snapshot scripts - run: | # Move the scripts and data from tests/testthat to the tmpdir directory so that both run use the same scripts + run: + | # Move the scripts and data from tests/testthat to the tmpdir directory so that both run use the same scripts mv tests/testthat/* ${{ runner.temp }}/ - name: Checkout CroPlotR main branch @@ -64,4 +61,3 @@ jobs: - name: Compare snapshots run: | Rscript -e "tmpdir <- '${{ runner.temp }}'; testthat::test_file('${{ runner.temp }}/vdiffr/test-snapshots.R', stop_on_failure=TRUE)" - From c96558a8149fb725a9cdd5515bc09feac8a1a74a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 23 Jul 2025 11:04:19 +0200 Subject: [PATCH 036/118] Up documentation --- man/bind_rows_sim.Rd | 2 +- man/give_reference_var.Rd | 23 ++++++++ man/give_y_var_type.Rd | 20 +++++++ man/plot_situations.Rd | 2 +- man/specific_scatter_plots.Rd | 95 +++++++++++++++++++++++++++++++++ man/sub-.cropr_simulation.Rd | 2 +- man/summary.cropr_simulation.Rd | 9 ++-- 7 files changed, 147 insertions(+), 6 deletions(-) create mode 100644 man/give_reference_var.Rd create mode 100644 man/give_y_var_type.Rd create mode 100644 man/specific_scatter_plots.Rd diff --git a/man/bind_rows_sim.Rd b/man/bind_rows_sim.Rd index 934285dd..fc9ffb62 100644 --- a/man/bind_rows_sim.Rd +++ b/man/bind_rows_sim.Rd @@ -10,7 +10,7 @@ bind_rows_sim(...) \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}} } \examples{ - \dontrun{ +\dontrun{ bind_rows_sim(sim) # -> bind_rows(sim) diff --git a/man/give_reference_var.Rd b/man/give_reference_var.Rd new file mode 100644 index 00000000..a9ab23fd --- /dev/null +++ b/man/give_reference_var.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/specific_plotting_scatter.R +\name{give_reference_var} +\alias{give_reference_var} +\title{Get reference variable for plotting} +\usage{ +give_reference_var(reference_var) +} +\arguments{ +\item{reference_var}{The reference variable name, if NULL "Observed" is used} +} +\value{ +A list with two elements: +\itemize{ +\item reference_var: The reference variable name: "Observed" or "Reference" +\item reference_var_name: The display name for the reference variable +} +} +\description{ +Return the reference variable and its display name for scatter +plots +} +\keyword{internal} diff --git a/man/give_y_var_type.Rd b/man/give_y_var_type.Rd new file mode 100644 index 00000000..9f1c55eb --- /dev/null +++ b/man/give_y_var_type.Rd @@ -0,0 +1,20 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/specific_plotting_scatter.R +\name{give_y_var_type} +\alias{give_y_var_type} +\title{Get y variable type for plotting} +\usage{ +give_y_var_type(select_scat) +} +\arguments{ +\item{select_scat}{Selection type, either "sim" for Simulated or any other +value for Residuals} +} +\value{ +A character string, either "Simulated" or "Residuals" +} +\description{ +Return the type of y variable for scatter plots based on +selection +} +\keyword{internal} diff --git a/man/plot_situations.Rd b/man/plot_situations.Rd index d297b2da..21e9b765 100644 --- a/man/plot_situations.Rd +++ b/man/plot_situations.Rd @@ -63,7 +63,7 @@ as a contiguous sequence when \code{type = "dynamic"} \item{situation_group}{A list of lists of situations to gather when \code{shape_sit= "group"}.} -\item{reference_var}{Variable selected on x-axis when type is scaétter and +\item{reference_var}{Variable selected on x-axis when type is scatter and select_scat is res. It is possible to select between observation and simulation of the reference variable. (examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim")} diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd new file mode 100644 index 00000000..bba0e465 --- /dev/null +++ b/man/specific_scatter_plots.Rd @@ -0,0 +1,95 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/specific_plotting_scatter.R +\name{specific_scatter_plots} +\alias{specific_scatter_plots} +\alias{compute_axis_bounds} +\alias{make_axis_square} +\alias{add_obs_error_bars} +\alias{plot_scat_mixture_allsit} +\alias{plot_scat_allsit} +\alias{plot_scat_persit} +\title{Specific functions to generate scatter plots} +\usage{ +compute_axis_bounds(df_data, reference_var, y_var_type, is_obs_sd) + +make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + +add_obs_error_bars(p, colour_factor = NULL) + +plot_scat_mixture_allsit( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL +) + +plot_scat_allsit( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL +) + +plot_scat_persit( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL +) +} +\arguments{ +\item{df_data}{A named list of data frame including the data to plot (one df +per situation, or only one df if sit==all_situations)} + +\item{y_var_type}{type of variable to plot ("Simulated" or "Residuals")} + +\item{is_obs_sd}{TRUE if error standard deviation of observations is provided} + +\item{p}{A ggplot to modify`} + +\item{colour_factor}{The factor to use for colouring the error bars} + +\item{sit}{The name of the situation to plot (or all_situations)} +} +\value{ +A ggplot object + +A list of ggplot objects + +List of x and y axis bounds (xaxis_min, xaxis_max, yaxis_min, +yaxis_max) + +The modified ggplot + +The modified ggplot +} +\description{ +Generate scatter plots for the different cases handled in +CroPlotR (plant mixture, plot of residuals, plot several simulation results +on same graph, ...) as specified by the different arguments. + +Compute axis bounds (+/-0.05 added to the min/max of the data). + +Make axis square + +Add error bars on observed values in given scatterplot +} +\details{ +List of the different specific functions: +\itemize{ +\item \code{plot_scat_mixture_allsit}: Generate a scatter plot for the case of +mixture of crops, single simulation version and all_situations in same plot +\item \code{plot_scat_allsit}: Generate a scatter plot for the case of +sole crops, single simulation version and all_situations in same plot +} +} +\keyword{internal} diff --git a/man/sub-.cropr_simulation.Rd b/man/sub-.cropr_simulation.Rd index 9baf5364..f3dd4fcf 100644 --- a/man/sub-.cropr_simulation.Rd +++ b/man/sub-.cropr_simulation.Rd @@ -21,7 +21,7 @@ This method ensure keeping the \code{cropr_simulation} attribute when subsetting \examples{ \dontrun{ library(SticsRFiles) -sim = SticsRFiles::get_sim(workspace = "inst/extdata/stics_example_1") +sim <- SticsRFiles::get_sim(workspace = "inst/extdata/stics_example_1") sim[[1]] # returns a `cropr_simulation` list } } diff --git a/man/summary.cropr_simulation.Rd b/man/summary.cropr_simulation.Rd index eba0fae7..dc8f9215 100644 --- a/man/summary.cropr_simulation.Rd +++ b/man/summary.cropr_simulation.Rd @@ -44,9 +44,12 @@ by a model version (or any group actually) \dontrun{ # Importing an example with three situations with observation: workspace <- system.file(file.path("extdata", "stics_example_1"), -package = "CroPlotR") -situations <- SticsRFiles::get_usms_list(usm_path = -file.path(workspace, "usms.xml")) + package = "CroPlotR" +) +situations <- SticsRFiles::get_usms_list( + usm_path = + file.path(workspace, "usms.xml") +) sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) obs <- SticsRFiles::get_obs(workspace = workspace, usm = situations) From 3a92f394db5808db1e8474017b8629083d2282d8 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 23 Jul 2025 11:50:13 +0200 Subject: [PATCH 037/118] Back to beg. june version following pb with rebase --- .github/workflows/check-standard.yaml | 4 + .github/workflows/vdiffr.yaml | 10 +- NAMESPACE | 2 +- R/aesthetics.R | 123 +++++------ R/aesthetics_dynamic.R | 16 +- R/aesthetics_scatter.R | 26 +-- R/cat_situations.R | 101 +++++++-- R/cropr_plotting.R | 4 +- R/cropr_stats.R | 8 +- R/generic_formatting.R | 41 +++- R/generic_stats.R | 107 ++++------ R/parse_plot_situations_arguments.R | 200 ++++++++++++++++++ R/save_plot_pdf.R | 15 +- man/aesthetics.Rd | 61 ------ man/aesthetics_dynamic.Rd | 4 +- man/aesthetics_scatter.Rd | 4 +- man/cat_situations.Rd | 13 +- man/cat_versions.Rd | 20 ++ man/cat_with_situation.Rd | 32 +++ man/detect_item_case.Rd | 30 +++ man/detect_mixture.Rd | 37 ++++ man/detect_mixture_version_overlap.Rd | 2 +- man/detect_mixture_version_situations.Rd | 2 +- man/format_cropr.Rd | 7 - man/generic_formatting.Rd | 10 +- man/parse_plot_situations_args.Rd | 78 +++++++ man/plot_generic_situation.Rd | 114 ---------- man/plot_situations.Rd | 10 +- man/predictor_assessment.Rd | 48 ++--- man/specific_scatter_plots.Rd | 13 +- man/statistics.Rd | 10 +- man/statistics_situations.Rd | 8 +- man/summary.cropr_simulation.Rd | 6 + tests/testthat/_inputs/sim_obs.RData | Bin 92726 -> 94634 bytes .../testthat/_inputs/tests_scatter_plots.csv | 62 ++++-- tests/testthat/test-detect_mixture.R | 12 ++ tests/testthat/test-generic_formatting.R | 56 +++++ tests/testthat/test-generic_statistics.R | 7 +- tests/testthat/test-plotting_formatting.R | 7 +- tests/testthat/vdiffr/test-snapshots.R | 23 +- 40 files changed, 853 insertions(+), 480 deletions(-) create mode 100644 R/parse_plot_situations_arguments.R delete mode 100644 man/aesthetics.Rd create mode 100644 man/cat_versions.Rd create mode 100644 man/cat_with_situation.Rd create mode 100644 man/detect_item_case.Rd create mode 100644 man/detect_mixture.Rd create mode 100644 man/parse_plot_situations_args.Rd delete mode 100644 man/plot_generic_situation.Rd create mode 100644 tests/testthat/test-detect_mixture.R create mode 100644 tests/testthat/test-generic_formatting.R diff --git a/.github/workflows/check-standard.yaml b/.github/workflows/check-standard.yaml index 747b863b..6a1ba404 100644 --- a/.github/workflows/check-standard.yaml +++ b/.github/workflows/check-standard.yaml @@ -51,6 +51,10 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: + pak-version: rc + # about pak-version: + # Ubuntu doesn't install the proper version of XML see https://github.com/r-lib/actions/issues/559. Remove when fixed. + # see also: https://stackoverflow.com/questions/73243945/pkgdown-action-failing-at-build-xml extra-packages: | any::rcmdcheck SticsRPacks/SticsRFiles@main diff --git a/.github/workflows/vdiffr.yaml b/.github/workflows/vdiffr.yaml index 11efaf25..1f1bdc7c 100644 --- a/.github/workflows/vdiffr.yaml +++ b/.github/workflows/vdiffr.yaml @@ -5,7 +5,7 @@ on: jobs: snapshot_comparison: - runs-on: ubuntu-latest # Replace with the appropriate runner for your needs + runs-on: ubuntu-latest # Replace with the appropriate runner for your needs steps: - name: Checkout repository @@ -18,6 +18,10 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: + pak-version: rc + # about pak-version: + # Ubuntu doesn't install the proper version of XML see https://github.com/r-lib/actions/issues/559. Remove when fixed. + # see also: https://stackoverflow.com/questions/73243945/pkgdown-action-failing-at-build-xml extra-packages: | any::testthat any::rcmdcheck @@ -33,8 +37,7 @@ jobs: Rscript -e "pkg_version <- 'Latest'; tmpdir <- '${{ runner.temp }}'; testthat::test_file('tests/testthat/test-dynamic-plots.R', stop_on_failure=FALSE); testthat::test_file('tests/testthat/test-scatter-plots.R', stop_on_failure=FALSE)" - name: Cache the snapshot scripts - run: - | # Move the scripts and data from tests/testthat to the tmpdir directory so that both run use the same scripts + run: | # Move the scripts and data from tests/testthat to the tmpdir directory so that both run use the same scripts mv tests/testthat/* ${{ runner.temp }}/ - name: Checkout CroPlotR main branch @@ -61,3 +64,4 @@ jobs: - name: Compare snapshots run: | Rscript -e "tmpdir <- '${{ runner.temp }}'; testthat::test_file('${{ runner.temp }}/vdiffr/test-snapshots.R', stop_on_failure=TRUE)" + diff --git a/NAMESPACE b/NAMESPACE index fb8aa1f7..ff254ac1 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -67,6 +67,7 @@ importFrom(parallel,parLapply) importFrom(parallel,stopCluster) importFrom(plyr,join_all) importFrom(reshape2,melt) +importFrom(rlang,":=") importFrom(rlang,.data) importFrom(stats,cor) importFrom(stats,lm) @@ -75,4 +76,3 @@ importFrom(stats,qt) importFrom(stats,sd) importFrom(stats,var) importFrom(tidyselect,vars_select_helpers) -importFrom(utils,head) diff --git a/R/aesthetics.R b/R/aesthetics.R index 678d7a46..1c70065b 100644 --- a/R/aesthetics.R +++ b/R/aesthetics.R @@ -18,7 +18,43 @@ template_aesthetics <- function() { } -#' Detect items cases +#' Detects if a situation is a mixture +#' +#' This function checks if the situation is a mixture based on +#' the presence of a column named "Dominance" and the uniqueness +#' of its values. +#' +#' @param sim_situation A data frame containing the simulated data for +#' one situation. +#' @return A logical value indicating if the situation is a mixture. +#' @examples +#' \dontrun{ +#' sim_data <- data.frame( +#' Dominance = c("Principal", "Principal", "Associated", "Associated") +#' ) +#' CroPlotR:::detect_mixture(sim_data) +#' # Output: TRUE +#' +#' sim_data <- data.frame(Dominance = c("Single Crop", "Single Crop")) +#' CroPlotR:::detect_mixture(sim_data) +#' # Output: FALSE +#' +#' sim_data <- data.frame(lai = c(1, 1.2)) +#' CroPlotR:::detect_mixture(sim_data) +#' # Output: FALSE +#' } +detect_mixture <- function(sim_situation) { + is_Dominance <- grep("Dominance", x = colnames(sim_situation), fixed = TRUE) + if (length(is_Dominance) > 0) { + is_mixture <- length(unique(sim_situation[[is_Dominance]])) > 1 + } else { + is_mixture <- FALSE + } + + return(is_mixture) +} + +#' Detect items cases for dynamic plots #' #' This function detects the cases for computing the aesthetics of a plot based on #' whether it is a mixture or not, whether it has one or multiple versions, and @@ -46,7 +82,7 @@ detect_mixture_version_overlap <- function(is_mixture, one_version, overlap) { return(case) } -#' Detect items cases +#' Detect items cases for scatter plots #' #' This function detects the cases for computing the aesthetics of a plot based on #' whether it is a mixture or not, whether it has one or multiple versions, and @@ -62,78 +98,43 @@ detect_mixture_version_overlap <- function(is_mixture, one_version, overlap) { detect_mixture_version_situations <- function(is_mixture, one_version, several_sit) { case <- switch(paste(is_mixture, !one_version, several_sit), "TRUE TRUE TRUE" = "mixture_versions_situations", - "TRUE TRUE FALSE" = "mixture_versions_no_situations", - "TRUE FALSE TRUE" = "mixture_no_versions_situations", - "TRUE FALSE FALSE" = "mixture_no_versions_no_situations", + "TRUE TRUE FALSE" = "mixture_versions_per_situations", + "TRUE FALSE TRUE" = "mixture_no_versions", + "TRUE FALSE FALSE" = "mixture_no_versions", "FALSE TRUE TRUE" = "non_mixture_versions_situations", - "FALSE TRUE FALSE" = "non_mixture_versions_no_situations", + "FALSE TRUE FALSE" = "non_mixture_versions_per_situations", "FALSE FALSE TRUE" = "non_mixture_no_versions_situations", - "FALSE FALSE FALSE" = "non_mixture_no_versions_no_situations" + "FALSE FALSE FALSE" = "non_mixture_no_versions_per_situations" ) return(case) } -#' Manages the aesthetics of the graphics -#' -#' @description Manages the shape, color and line type of the graphics according -#' to their content -#' -#' @param sim A simulation list of data.frames -#' @param obs An observation list of data.frames -#' @param type The type of plot required, either "dynamic" or "scatter" -#' @param overlap A list of lists containing the variables to represent on the -#' same graph when `type = "dynamic"` -#' @param several_sit Boolean. Must be equal to `TRUE` if sim and obs gather -#' more than one situation and if situations should be differentiated -#' on the graph. -#' @param shape_sit Shape to differentiate between situations when -#' `all_situations= TRUE`. See details. -#' @param one_version Boolean. Must be `TRUE` if several versions will be -#' plotted on the same graph. -#' @param iVersion Integer. Version number of sim -#' @param dot_args List of dot arguments given to plot function -#' -#' @details The `shape_sit` argument can be: -#' * "none" (the default): Same shape for all situations. -#' * "txt": Writes the name of the situation above each point. -#' * "symbol": One shape for each situation. -#' * "group": One shape for each group of situations described in -#' `situation_group`. -#' -#' @return An aesthetics expression which will allow to manage the aesthetics -#' of the graphics +#' Detect items cases #' -#' @keywords internal +#' This function returns a unique string based on the type of plot, and +#' whether the situation is a mixture or not, if there is one or multiple +#' versions to plot, and if there is one or several situations to plot +#' into the same plot. +#' The output is used to choose the right plotting function in a switch. #' -aesthetics <- function(sim, obs = NULL, type = c("dynamic", "scatter"), - overlap = NULL, several_sit = FALSE, - shape_sit = c("none", "txt", "symbol", "group"), - one_version = TRUE, iVersion = 1, - dot_args = NULL) { - is_dominance <- grep("Dominance", x = colnames(sim), fixed = TRUE) - if (length(is_dominance) > 0) { - is_mixture <- length(unique(sim[[is_dominance]])) > 1 - } else { - is_mixture <- FALSE - } - is_mixture <- is_mixture && (length(unique(sim$Dominance)) > 1) - - aesthetics <- template_aesthetics() - +#' @param type The type of plot required, either 'dynamic' or 'scatter +#' @param is_mixture A logical value indicating whether the crop is a mixture or not. +#' @param one_version A logical value indicating whether the plot has one or multiple versions (e.g. of the model). +#' @param several_sit A logical value indicating whether there are one or several situations to plot. +#' @param overlap A logical value indicating whether there is any overlapping variables in the plot. +#' +#' @return A unique character string for the plot. +#' +#' @keywords internal +detect_item_case <- function(type, is_mixture, one_version, several_sit, overlap) { if (type == "dynamic") { - aesthetics <- aesthetics_dynamic( - sim, aesthetics, overlap, one_version, iVersion, dot_args, - is_mixture - ) + item_case <- detect_mixture_version_overlap(is_mixture, one_version, overlap) } else if (type == "scatter") { - aesthetics <- aesthetics_scatter( - sim, aesthetics, overlap, several_sit, one_version, iVersion, - dot_args, is_mixture - ) + item_case <- detect_mixture_version_situations(is_mixture, one_version, several_sit) } else { stop("type must be either 'dynamic' or 'scatter'") } - return(aesthetics) + return(item_case) } diff --git a/R/aesthetics_dynamic.R b/R/aesthetics_dynamic.R index 37288ee5..dfe0d983 100644 --- a/R/aesthetics_dynamic.R +++ b/R/aesthetics_dynamic.R @@ -9,7 +9,7 @@ #' same graph when `type = "dynamic"` #' @param one_version Boolean. Must be `TRUE` if several versions will be #' plotted on the same graph. -#' @param iVersion Integer. Version number of sim +#' @param iversion Integer. Version number of sim #' @param dot_args List of dot arguments given to plot function #' @param is_mixture Boolean indicating whether the crop is a mixture or not #' @@ -20,7 +20,7 @@ #' aesthetics_dynamic <- function(sim, aesthetics = template_aesthetics(), overlap = NULL, one_version = TRUE, - iVersion = 1, dot_args = NULL, + iversion = 1, dot_args = NULL, is_mixture = FALSE) { # Define the cases using switch item_case <- detect_mixture_version_overlap(is_mixture, one_version, overlap) @@ -35,17 +35,17 @@ aesthetics_dynamic <- function(sim, aesthetics = template_aesthetics(), list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) } else if (item_case == "non_mixture_versions_no_overlap") { aesthetics$versions$color <- - list("Versions" = names(dot_args[iVersion])) - aesthetics$versions$shape <- list("Versions" = names(dot_args[iVersion])) + list("Versions" = names(dot_args[iversion])) + aesthetics$versions$shape <- list("Versions" = names(dot_args[iversion])) } else if (item_case == "non_mixture_no_versions_overlap") { aesthetics$plot$color <- list("Variable" = quote(.data$variable)) aesthetics$plot$shape <- list("Variable" = quote(.data$variable)) aesthetics$plot$group <- list("Variable" = quote(.data$variable)) } else if (item_case == "mixture_versions_no_overlap") { aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iVersion])) + list("Versions" = names(dot_args[iversion])) aesthetics$versions$shape <- - list("Versions" = names(dot_args[iVersion])) + list("Versions" = names(dot_args[iversion])) aesthetics$versions$color <- list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) aesthetics$plot$group <- @@ -53,8 +53,8 @@ aesthetics_dynamic <- function(sim, aesthetics = template_aesthetics(), } else if (item_case == "non_mixture_versions_overlap") { aesthetics$versions$color <- list("Variable" = quote(.data$variable)) aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iVersion])) - aesthetics$versions$shape <- list("Versions" = names(dot_args[iVersion])) + list("Versions" = names(dot_args[iversion])) + aesthetics$versions$shape <- list("Versions" = names(dot_args[iversion])) aesthetics$plot$color <- list("Variable" = quote(.data$variable)) aesthetics$plot$group <- list("Variable" = quote(.data$variable)) } else if (item_case == "mixture_no_versions_overlap") { diff --git a/R/aesthetics_scatter.R b/R/aesthetics_scatter.R index 83ae70ab..3fb690aa 100644 --- a/R/aesthetics_scatter.R +++ b/R/aesthetics_scatter.R @@ -12,7 +12,7 @@ #' on the graph. #' @param one_version Boolean. Must be `TRUE` if several versions will be #' plotted on the same graph. -#' @param iVersion Integer. Version number of sim +#' @param iversion Integer. Version number of sim #' @param dot_args List of dot arguments given to plot function #' @param is_mixture Boolean indicating whether the crop is a mixture or not #' @@ -23,7 +23,7 @@ #' aesthetics_scatter <- function(sim, aesthetics = template_aesthetics(), overlap = NULL, several_sit = FALSE, - one_version = TRUE, iVersion = 1, + one_version = TRUE, iversion = 1, dot_args = NULL, is_mixture = FALSE) { # Define the cases using switch item_case <- detect_mixture_version_situations(is_mixture, one_version, several_sit) @@ -33,38 +33,38 @@ aesthetics_scatter <- function(sim, aesthetics = template_aesthetics(), aesthetics$plot$color <- list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) } else if (item_case == "non_mixture_versions_no_situations") { - aesthetics$versions$color <- list("Versions" = names(dot_args[iVersion])) + aesthetics$versions$color <- list("Versions" = names(dot_args[iversion])) aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iVersion])) + list("Versions" = names(dot_args[iversion])) } else if (item_case == "non_mixture_no_versions_situations") { - aesthetics$plot$color <- list("Situation" = quote(paste(.data$Sit_Name))) + aesthetics$plot$color <- list("Situation" = quote(paste(.data$sit_name))) } else if (item_case == "mixture_versions_no_situations") { - if (iVersion == 1) { + if (iversion == 1) { aesthetics$versions$color <- list("Versions" = quote(paste(names(dot_args[1])))) aesthetics$versions$linetype <- list("Versions" = quote(paste(names(dot_args[1])))) } else { aesthetics$versions$color <- - list("Versions" = quote(paste(names(dot_args[iVersion])))) + list("Versions" = quote(paste(names(dot_args[iversion])))) aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iVersion])) + list("Versions" = names(dot_args[iversion])) } aesthetics$plot$shape <- list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) } else if (item_case == "non_mixture_versions_situations") { - aesthetics$versions$color <- list("Versions" = names(dot_args[iVersion])) + aesthetics$versions$color <- list("Versions" = names(dot_args[iversion])) aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iVersion])) - aesthetics$plot$shape <- list("Situation" = quote(.data$Sit_Name)) + list("Versions" = names(dot_args[iversion])) + aesthetics$plot$shape <- list("Situation" = quote(.data$sit_name)) } else if (item_case == "mixture_no_versions_situations") { aesthetics$plot$color <- list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - aesthetics$plot$shape <- list("Situation" = quote(.data$Sit_Name)) + aesthetics$plot$shape <- list("Situation" = quote(.data$sit_name)) } else if (item_case == "mixture_versions_situations") { aesthetics$versions$color <- list(quote(paste(.data$Combi))) aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iVersion])) + list("Versions" = names(dot_args[iversion])) } return(aesthetics) } diff --git a/R/cat_situations.R b/R/cat_situations.R index 3a03d9bd..940d7868 100644 --- a/R/cat_situations.R +++ b/R/cat_situations.R @@ -10,9 +10,6 @@ #' (named by situation) #' @param obs_sd A list (each element= situation) of `data.frame`s for the #' standard deviation of the observations (named by situation) -#' @param force Continue if the plot is not possible ? E.g. no observations for -#' scatter plots. If `TRUE`, return `NULL`, else return an error (default). -#' @param verbose Boolean. Print information during execution. #' #' @return A list of three : a list (each element=version) of a list of a single #' simulations `data.frame` named "all_situations", a list of a single @@ -20,21 +17,20 @@ #' #' @keywords internal cat_situations <- - function(list_sim = NULL, obs = NULL, obs_sd = NULL, force = FALSE, - verbose = TRUE) { + function(list_sim = NULL, obs = NULL, obs_sd = NULL) { sits <- lapply(list_sim, names) V_names <- names(list_sim) list_sim <- lapply(seq_along(list_sim), function(x) { - allsim <- bind_rows(list_sim[[x]], .id = "Sit_Name") + allsim <- bind_rows(list_sim[[x]], .id = "sit_name") # Add dominance and plant in sim data of sole crops if one of the other # situations is a mixture if ("Dominance" %in% colnames(allsim)) { for (sit_name in sits[[x]]) { if (length(unique(obs[[sit_name]]$Plant)) == 1) { - allsim$Plant[allsim$Sit_Name == sit_name] <- + allsim$Plant[allsim$sit_name == sit_name] <- unique(obs[[sit_name]]$Plant) } } @@ -52,18 +48,57 @@ cat_situations <- # situations <- names(obs) if (!is.null(obs)) { # bind the obs into a single dataframe - obs <- list(bind_rows(obs, .id = "Sit_Name")) + obs <- list(bind_rows(obs, .id = "sit_name")) names(obs) <- "all_situations" } if (!is.null(obs_sd)) { - obs_sd <- list(bind_rows(obs_sd, .id = "Sit_Name")) + obs_sd <- list(bind_rows(obs_sd, .id = "sit_name")) names(obs_sd) <- "all_situations" } return(list(list_sim, obs, obs_sd)) } +#' Format simulation and observation into a long data frame over versions +#' +#' @description Format the list of simulation data and observation data +#' into a long data frame with a new column for the version +#' +#' @param list_sim A list (each element= version) of a list +#' (each element= situation) of simulations `data.frame`s +#' +#' @return A dataframe +#' +#' @keywords internal +cat_versions <- function(list_sim = NULL) { + version_names <- names(list_sim) + + # Adding the name of the version to each dataframe: + for (i in seq_along(list_sim)) { + for (j in seq_along(list_sim[[i]])) { + list_sim[[i]][[j]]$version <- version_names[i] + } + } + + # Binding the versions for each situation (the versions are in the same + # data frame for each situation): + df_situations <- list() + for (i in seq_along(list_sim)) { + # searching which situation in list_sim[[i]] is in df_situations: + # if it is, bind_rows, else, add it to df_situations + + for (j in names(list_sim[[i]])) { + if (j %in% names(df_situations)) { + df_situations[[j]] <- bind_rows(df_situations[[j]], list_sim[[i]][[j]]) + } else { + df_situations[[j]] <- list_sim[[i]][[j]] + } + } + } + + return(df_situations) +} #' Format simulation data and observation data in order to represent some #' situations as a contiguous sequence @@ -126,7 +161,7 @@ cat_successive <- } if (new_name != "") { obs[[new_name]] <- - dplyr::bind_cols(new_obs, data.frame("Sit_Name" = col_obs)) + dplyr::bind_cols(new_obs, data.frame("sit_name" = col_obs)) } } } @@ -164,7 +199,7 @@ cat_successive <- sim[[sit]] <- NULL } sim[[new_name]] <- - dplyr::bind_cols(new_sim, data.frame("Sit_Name" = col_sim)) + dplyr::bind_cols(new_sim, data.frame("sit_name" = col_sim)) } sim }) @@ -193,21 +228,59 @@ add_situation_col <- function(dot_args, obs, obs_sd = NULL) { for (i in seq_along(dot_args)) { sit_names <- names(dot_args[[i]]) for (j in sit_names) { - dot_args[[i]][[j]]$Sit_Name <- j + dot_args[[i]][[j]]$sit_name <- j } } sit_names <- names(obs) for (j in sit_names) { - obs[[j]]$Sit_Name <- j + obs[[j]]$sit_name <- j } if (!is.null(obs_sd)) { sit_names <- names(obs_sd) for (j in sit_names) { - obs_sd[[j]]$Sit_Name <- j + obs_sd[[j]]$sit_name <- j } } return(list(dot_args, obs, obs_sd)) } + + +#' Format situations +#' +#' Format the data into a list of situations, with the situation repeated +#' as a column name, and the version also as a column name. In the case +#' of `all_situations==TRUE`, the situations are concatenated together +#' into one situation called "all_situations" (the data is a list of +#' one situation). The true situation name is still kept in the column +#' `sit_name` though. +#' +#' @param dot_args The dot arguments (the simulations). +#' @param obs The observations. +#' @param obs_sd The standard deviation of the observations. +#' @param all_situations Boolean. Do we need all situations treated +#' separately or as one. +#' @param v_names The version names. +#' +#' @return The categorized situations. +#' @keywords internal +cat_with_situation <- function(dot_args, obs, obs_sd, all_situations, v_names) { + # function body + if (all_situations) { + # If all_situations, cat all situations together for each version: + list_data <- cat_situations(dot_args, obs, obs_sd) + sim <- unlist(list_data[[1]], recursive = FALSE) + names(sim) <- v_names + sim <- list(all_situations = bind_rows(sim, .id = "version")) + } else { + # If not all_situations, add a column to each data.frame to identify the + # situation: + list_data <- add_situation_col(dot_args, obs, obs_sd) + # And bind the version data.frames together: + sim <- cat_versions(list_data[[1]]) + } + + return(list(sim = sim, obs = list_data[[2]], obs_sd = list_data[[3]])) +} diff --git a/R/cropr_plotting.R b/R/cropr_plotting.R index fd53c558..2f2a123b 100644 --- a/R/cropr_plotting.R +++ b/R/cropr_plotting.R @@ -100,7 +100,7 @@ plot.cropr_simulation <- function(..., obs = NULL, obs_sd = NULL, all_situations = all_situations, overlap = overlap, successive = successive, shape_sit = shape_sit, situation_group = situation_group, reference_var = reference_var, - force = force, verbose = verbose, formater = format_cropr + force = force, verbose = verbose ) } @@ -120,6 +120,6 @@ autoplot.cropr_simulation <- function(..., obs = NULL, obs_sd = NULL, all_situations = all_situations, overlap = overlap, successive = successive, shape_sit = shape_sit, situation_group = situation_group, reference_var = reference_var, - force = force, verbose = verbose, formater = format_cropr + force = force, verbose = verbose ) } diff --git a/R/cropr_stats.R b/R/cropr_stats.R index b0745357..68033809 100644 --- a/R/cropr_stats.R +++ b/R/cropr_stats.R @@ -33,6 +33,12 @@ #' usm_path = #' file.path(workspace, "usms.xml") #' ) +#' package = "CroPlotR" +#' ) +#' situations <- SticsRFiles::get_usms_list( +#' usm_path = +#' file.path(workspace, "usms.xml") +#' ) #' sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) #' obs <- SticsRFiles::get_obs(workspace = workspace, usm = situations) #' @@ -57,6 +63,6 @@ summary.cropr_simulation <- function(..., obs, stats = "all", statistics_situations(..., obs = obs, stat = stat, all_situations = all_situations, - verbose = verbose, formater = format_cropr + verbose = verbose ) } diff --git a/R/generic_formatting.R b/R/generic_formatting.R index 557e3edb..e6275891 100644 --- a/R/generic_formatting.R +++ b/R/generic_formatting.R @@ -15,12 +15,14 @@ #' @param several_sit A logical value indicating whether there are several #' situations to plot. #' @param total_vers An integer indicating the total number of versions. -#' @param num_vers An integer indicating the id of the current version. #' -#' @return A formatted data frame. +#' @return A long data frame with the formatted data, with columns +#' Date, Plant, Dominance, sit_name, version, variable, Simulated, Observed. +#' Column "Combi" can also be added if there are three different +#' characteristics to plot. #' @keywords internal #' -generic_formatting <- function(df, var, overlap, situation_group, type, shape_sit, several_sit, total_vers, num_vers) { +generic_formatting <- function(df, var, overlap, situation_group, type, shape_sit, several_sit, total_vers) { # Filter selected variables if (!is.null(var)) { var <- unique(c(var, subst_parenth(var))) @@ -34,6 +36,12 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si df <- df %>% dplyr::filter(.data$variable %in% var) } + # Replace NAs with "Single-crop" in Dominance in order to make + # the legend understandable + if ("Dominance" %in% colnames(df)) { + levels(df$Dominance) <- c("Principal", "Associated", "Single crop") + df$Dominance[which(is.na(df$Dominance))] <- "Single crop" + } # Replace NAs with "Single-crop" in Dominance in order to make # the legend understandable if ("Dominance" %in% colnames(df)) { @@ -41,6 +49,20 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si df$Dominance[which(is.na(df$Dominance))] <- "Single crop" } + # Add group_var column to data frame if overlap != null + if (!is.null(overlap)) { + df <- dplyr::bind_cols( + df, + data.frame("group_var" = rep(NA, nrow(df))) + ) + for (vars in overlap) { + vars <- unique(c(vars, subst_parenth(vars))) + df$group_var[which(df$variable %in% vars)] <- + paste(intersect(df$variable, vars), collapse = " | ") + } + df$group_var[which(is.na(df$group_var))] <- + as.character(df$variable[which(is.na(df$group_var))]) + } # Add group_var column to data frame if overlap != null if (!is.null(overlap)) { df <- dplyr::bind_cols( @@ -56,16 +78,16 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si as.character(df$variable[which(is.na(df$group_var))]) } - # Change Sit_Name column with names of situation + # Change sit_name column with names of situation # groups if shape_sit=="group" if (several_sit && shape_sit == "group" && !is.null(situation_group)) { for (grp in seq_along(situation_group)) { sits <- situation_group[[grp]] if (!is.null(names(situation_group))) { - df$Sit_Name[which(df$Sit_Name %in% sits)] <- + df$sit_name[which(df$sit_name %in% sits)] <- names(situation_group)[[grp]] } else { - df$Sit_Name[which(df$Sit_Name %in% sits)] <- + df$sit_name[which(df$sit_name %in% sits)] <- paste(sits, collapse = ";") } } @@ -80,7 +102,7 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si data.frame( "Combi" = paste( - rep(paste0("Version_", num_vers), nrow(df)), + df$version, "|", df$variable, "|", paste(df$Dominance, ":", df$Plant) ) @@ -97,8 +119,8 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si data.frame( "Combi" = paste( - rep(paste0("Version_", num_vers), nrow(df)), - "|", df$Sit_Name, "|", + df$version, + "|", df$sit_name, "|", paste(df$Dominance, ":", df$Plant) ) ) @@ -106,4 +128,5 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si } return(df) + return(df) } diff --git a/R/generic_stats.R b/R/generic_stats.R index 799585b7..d6e32d60 100644 --- a/R/generic_stats.R +++ b/R/generic_stats.R @@ -16,10 +16,6 @@ #' @param all_plants Boolean (default = TRUE). If `TRUE`, computes statistics #' for all plants (when applicable). #' @param verbose Boolean. Print information during execution. -#' @param formater The function used to format the models outputs and -#' observations in a standard way. You can design your own function -#' that format one situation and provide it here (see [statistics()] and -#' [format_cropr()] for more information). #' #' @seealso All the functions used to compute the statistics: #' [predictor_assessment()]. @@ -30,7 +26,7 @@ #' @keywords internal statistics_situations <- function(..., obs = NULL, stat = "all", all_situations = TRUE, - all_plants = TRUE, verbose = TRUE, formater) { + all_plants = TRUE, verbose = TRUE) { . <- NULL dot_args <- list(...) @@ -65,7 +61,6 @@ statistics_situations <- function(..., obs = NULL, stat = "all", sim = dot_args[[versions]][[situation]], obs = obs[[situation]], all_situations = all_situations, all_plants = all_plants, verbose = verbose, - formater = formater, stat = stat ) } @@ -91,7 +86,7 @@ statistics_situations <- function(..., obs = NULL, stat = "all", #' Generic simulated/observed statistics for one situation #' #' @description Compute statistics for evaluation of any model outputs against -#' observations, providing a formater function (see [format_cropr()]). +#' observations. #' #' @param sim A simulation data.frame #' @param obs An observation data.frame (variable names must match) @@ -102,9 +97,6 @@ statistics_situations <- function(..., obs = NULL, stat = "all", #' @param all_plants Boolean (default = TRUE). If `TRUE`, computes statistics #' for all plants (when applicable). #' @param verbose Boolean. Print informations during execution. -#' @param formater The function used to format the models outputs and -#' observations in a standard way. You can design your own function -#' that format one situation and provide it here. #' @param stat A character vector of required statistics, "all" for all, or any #' of [predictor_assessment()] (e.g. `"n"` or `"RMSE"`, or both `c("n", "RMSE")`). #' @@ -114,12 +106,13 @@ statistics_situations <- function(..., obs = NULL, stat = "all", #' not the overall simulation mean. #' #' @return A data.frame with statistics for each variable and possibly each -#' grouping variable returned by the formater. +#' grouping variable. #' #' @importFrom reshape2 melt #' @importFrom parallel parLapply stopCluster #' @importFrom dplyr ungroup group_by summarise "%>%" filter #' @importFrom plyr join_all +#' @importFrom rlang ":=" #' @examples #' \dontrun{ #' workspace <- system.file(file.path("extdata", "stics_example_1"), @@ -134,14 +127,13 @@ statistics_situations <- function(..., obs = NULL, stat = "all", #' statistics( #' sim = sim$`IC_Wheat_Pea_2005-2006_N0`, #' obs = obs$`IC_Wheat_Pea_2005-2006_N0`, -#' formater = format_cropr #' ) #' } #' #' @keywords internal #' statistics <- function(sim, obs = NULL, all_situations = FALSE, - all_plants = TRUE, verbose = TRUE, formater, stat = "all") { + all_plants = TRUE, verbose = TRUE, stat = "all") { . <- NULL # To avoid CRAN check note is_obs <- !is.null(obs) && nrow(obs) > 0 @@ -167,10 +159,7 @@ statistics <- function(sim, obs = NULL, all_situations = FALSE, } # Format the data: - formated_df <- formater(sim, obs, - type = "scatter", - all_situations = all_situations - ) + formated_df <- format_cropr(sim, obs, type = "scatter") # In case obs is given but no common variables between obs and sim: if (is.null(formated_df) || is.null(formated_df$Observed)) { @@ -260,7 +249,7 @@ statistics <- function(sim, obs = NULL, all_situations = FALSE, dplyr::summarise(!!cur_stat := do.call(cur_stat, !!arglist_quoted)) }) x <- plyr::join_all(x, by = "variable") - attr(x, "description") <- dplyr::select(all_stats, stat) + attr(x, "description") <- dplyr::select(all_stats, all_of(stat)) return(x) } @@ -301,99 +290,85 @@ statistics <- function(sim, obs = NULL, all_situations = FALSE, #' \item `Slope()`: Slope of regression line, computed using [stats::lm()] #' on sim~obs. #' \item `RMSE()`: Root Mean Squared Error, computed as -#' \deqn{RMSE = \sqrt{\frac{\sum_1^n(\hat{y_i}-y_i)^2}{n}}} -#' {RMSE = sqrt(mean((sim-obs)^2)} +#' \deqn{RMSE = \sqrt{\frac{\sum_1^n(\hat{y_i}-y_i)^2}{n}}}{RMSE = sqrt(mean((sim-obs)^2)} #' \item `RMSEs()`: Systematic Root Mean Squared Error, computed as -#' \deqn{RMSEs = \sqrt{\frac{\sum_1^n(\sim{y_i}-y_i)^2}{n}}} -#' {RMSEs = sqrt(mean((fitted.values(lm(formula=sim~obs))-obs)^2)} +#' \deqn{RMSEs = \sqrt{\frac{\sum_1^n(\sim{y_i}-y_i)^2}{n}}}{RMSEs = sqrt(mean((fitted.values(lm(formula=sim~obs))-obs)^2)} #' \item `RMSEu()`: Unsystematic Root Mean Squared Error, computed as -#' \deqn{RMSEu = \sqrt{\frac{\sum_1^n(\sim{y_i}-\hat{y_i})^2}{n}}} -#' {RMSEu = sqrt(mean((fitted.values(lm(formula=sim~obs))-sim)^2)} +#' \deqn{RMSEu = \sqrt{\frac{\sum_1^n(\sim{y_i}-\hat{y_i})^2}{n}}}{RMSEu = sqrt(mean((fitted.values(lm(formula=sim~obs))-sim)^2)} #' \item `NSE()`: Nash-Sutcliffe Efficiency, alias of EF, provided for user #' convenience. #' \item `nRMSE()`: Normalized Root Mean Squared Error, also denoted as #' CV(RMSE), and computed as: -#' \deqn{nRMSE = \frac{RMSE}{\bar{y}}\cdot100} -#' {nRMSE = (RMSE/mean(obs))*100} +#' \deqn{nRMSE = \frac{RMSE}{\bar{y}}\cdot100}{nRMSE = (RMSE/mean(obs))*100} #' \item `rRMSE()`: Relative Root Mean Squared Error, computed as: -#' \deqn{rRMSE = \frac{RMSE}{\bar{y}}}{rRMSE = (RMSE/mean(obs))} +#' \deqn{rRMSE = \frac{RMSE}{\bar{y}}}{rRMSE = (RMSE/mean(obs))} #' \item `rRMSEs()`: Relative Systematic Root Mean Squared Error, computed as -#' \deqn{rRMSEs = \frac{RMSEs}{\bar{y}}}{rRMSEs = (RMSEs/mean(obs))} +#' \deqn{rRMSEs = \frac{RMSEs}{\bar{y}}}{rRMSEs = (RMSEs/mean(obs))} #' \item `rRMSEu()`: Relative Unsystematic Root Mean Squared Error, -#' computed as -#' \deqn{rRMSEu = \frac{RMSEu}{\bar{y}}}{rRMSEu = (RMSEu/mean(obs))} +#' computed as: +#' \deqn{rRMSEu = \frac{RMSEu}{\bar{y}}}{rRMSEu = (RMSEu/mean(obs))} #' \item `pMSEs()`: Proportion of Systematic Mean Squared Error in Mean #' Square Error, computed as: -#' \deqn{pMSEs = \frac{MSEs}{MSE}}{pMSEs = MSEs/MSE} +#' \deqn{pMSEs = \frac{MSEs}{MSE}}{pMSEs = MSEs/MSE} #' \item `pMSEu()`: Proportion of Unsystematic Mean Squared Error in MEan #' Square Error, computed as: -#' \deqn{pMSEu = \frac{MSEu}{MSE}}{pMSEu = MSEu^2/MSE^2} +#' \deqn{pMSEu = \frac{MSEu}{MSE}}{pMSEu = MSEu^2/MSE^2} #' \item `Bias2()`: Bias squared (1st term of Kobayashi and Salam #' (2000) MSE decomposition): -#' \deqn{Bias2 = Bias^2} +#' \deqn{Bias2 = Bias^2} #' \item `SDSD()`: Difference between sd_obs and sd_sim squared #' (2nd term of Kobayashi and Salam (2000) MSE decomposition), computed as: -#' \deqn{SDSD = (sd\_obs-sd\_sim)^2}{SDSD = (sd\_obs-sd\_sim)^2} +#' \deqn{SDSD = (sd\_obs-sd\_sim)^2}{SDSD = (sd\_obs-sd\_sim)^2} #' \item `LCS()`: Correlation between observed and simulated values #' (3rd term of Kobayashi and Salam (2000) MSE decomposition), computed as: -#' \deqn{LCS = 2*sd\_obs*sd\_sim*(1-r)} +#' \deqn{LCS = 2*sd\_obs*sd\_sim*(1-r)} #' \item `rbias2()`: Relative bias squared, computed as: -#' \deqn{rbias2 = \frac{Bias^2}{\bar{y}^2}} -#' {rbias2 = Bias^2/mean(obs)^2} +#' \deqn{rbias2 = \frac{Bias^2}{\bar{y}^2}}{rbias2 = Bias^2/mean(obs)^2} #' \item `rSDSD()`: Relative difference between sd_obs and sd_sim squared, #' computed as: -#' \deqn{rSDSD = \frac{SDSD}{\bar{y}^2}}{rSDSD = (SDSD/mean(obs)^2)} +#' \deqn{rSDSD = \frac{SDSD}{\bar{y}^2}}{rSDSD = (SDSD/mean(obs)^2)} #' \item `rLCS()`: Relative correlation between observed and simulated values, #' computed as: -#' \deqn{rLCS = \frac{LCS}{\bar{y}^2}}{rLCS = (LCS/mean(obs)^2)} +#' \deqn{rLCS = \frac{LCS}{\bar{y}^2}}{rLCS = (LCS/mean(obs)^2)} #' \item `MAE()`: Mean Absolute Error, computed as: -#' \deqn{MAE = \frac{\sum_1^n(\left|\hat{y_i}-y_i\right|)}{n}} -#' {MAE = mean(abs(sim-obs))} +#' \deqn{MAE = \frac{\sum_1^n(\left|\hat{y_i}-y_i\right|)}{n}}{MAE = mean(abs(sim-obs))} #' \item `ABS()`: Mean Absolute Bias, which is an alias of `MAE()` #' \item `FVU()`: Fraction of variance unexplained, computed as: -#' \deqn{FVU = \frac{SS_{res}}{SS_{tot}}}{FVU = SS_res/SS_tot} +#' \deqn{FVU = \frac{SS_{res}}{SS_{tot}}}{FVU = SS_res/SS_tot} #' \item `MSE()`: Mean squared Error, computed as: -#' \deqn{MSE = \frac{1}{n}\sum_{i=1}^n(Y_i-\hat{Y_i})^2} -#' {MSE = mean((sim-obs)^2)} +#' \deqn{MSE = \frac{1}{n}\sum_{i=1}^n(Y_i-\hat{Y_i})^2}{MSE = mean((sim-obs)^2)} #' \item `EF()`: Model efficiency, also called Nash-Sutcliffe efficiency #' (NSE). This statistic is related to the FVU as #' \eqn{EF= 1-FVU}. It is also related to the \eqn{R^2}{R2} #' because they share the same equation, except SStot is applied #' relative to the identity function (*i.e.* 1:1 line) instead of the -#' regression line. It is computed -#' as: \deqn{EF = 1-\frac{SS_{res}}{SS_{tot}}}{EF = 1-SS_res/SS_tot} +#' regression line. It is computed as: +#' \deqn{EF = 1-\frac{SS_{res}}{SS_{tot}}}{EF = 1-SS_res/SS_tot} #' \item `Bias()`: Modelling bias, simply computed as: -#' \deqn{Bias = \frac{\sum_1^n(\hat{y_i}-y_i)}{n}} -#' {Bias = mean(sim-obs)} +#' \deqn{Bias = \frac{\sum_1^n(\hat{y_i}-y_i)}{n}}{Bias = mean(sim-obs)} #' \item `MAPE()`: Mean Absolute Percent Error, computed as: -#' \deqn{MAPE = \frac{\sum_1^n(\frac{\left|\hat{y_i}-y_i\right|} -#' {y_i})}{n}}{MAPE = mean(abs(obs-sim)/obs)} +#' \deqn{MAPE = \frac{\sum_1^n(\frac{\left|\hat{y_i}-y_i\right|}{y_i})}{n}}{MAPE = mean(abs(obs-sim)/obs)} #' \item `RME()`: Relative mean error, computed as: -#' \deqn{RME = \frac{\sum_1^n(\frac{\hat{y_i}-y_i}{y_i})}{n}} -#' {RME = mean((sim-obs)/obs)} +#' \deqn{RME = \frac{\sum_1^n(\frac{\hat{y_i}-y_i}{y_i})}{n}}{RME = mean((sim-obs)/obs)} #' \item `tSTUD()`: T student test of the mean difference, computed as: -#' \deqn{tSTUD = \frac{Bias}{\sqrt(\frac{var(M)}{n_obs})}} -#' {tSTUD = Bias/sqrt(var(M)/n_obs)} +#' \deqn{tSTUD = \frac{Bias}{\sqrt(\frac{var(M)}{n_obs})}}{tSTUD = Bias/sqrt(var(M)/n_obs)} #' \item `tLimit()`: T student threshold, computed using [qt()]: -#' \deqn{tLimit = qt(1-\frac{\alpha}{2},df=length(obs)-1)} -#' {tLimit = qt(1-risk/2,df =length(obs)-1)} +#' \deqn{tLimit = qt(1-\frac{\alpha}{2},df=length(obs)-1)}{tLimit = qt(1-risk/2,df =length(obs)-1)} #' \item `Decision()`: Decision of the t student test of the mean difference #' (can bias be considered statistically not different from 0 at alpha level #' 0.05, i.e. 5% probability of erroneously rejecting this hypothesis?), #' computed as: -#' \deqn{Decision = abs(tSTUD ) < tLimit} +#' \deqn{Decision = abs(tSTUD ) < tLimit} #' } #' #' @note \eqn{SS_{res}}{SS_res} is the residual sum of squares and -#' \eqn{SS_{tot}}{SS_tot} the total sum of squares. They are computed as: -#' \deqn{SS_{res} = \sum_{i=1}^n (y_i - \hat{y_i})^2} -#' {SS_res= sum((obs-sim)^2)} -#' \deqn{SS_{tot} = \sum_{i=1}^{n}\left(y_{i}-\bar{y}\right)^2} -#' {SS_tot= sum((obs-mean(obs))^2} -#' Also, it should be noted that \eqn{y_i} refers to the observed values -#' and \eqn{\hat{y_i}} to the predicted values, \eqn{\bar{y}} to the mean -#' value of observations and \eqn{\sim{y_i}} to -#' values predicted by linear regression. +#' \eqn{SS_{tot}}{SS_tot} the total sum of squares. They are computed as: +#' \deqn{SS_{res} = \sum_{i=1}^n (y_i - \hat{y_i})^2}{SS_res= sum((obs-sim)^2)} +#' \deqn{SS_{tot} = \sum_{i=1}^{n}\left(y_{i}-\bar{y}\right)^2}{SS_tot= sum((obs-mean(obs))^2} +#' Also, it should be noted that \eqn{y_i} refers to the observed values +#' and \eqn{\hat{y_i}} to the predicted values, \eqn{\bar{y}} to the mean +#' value of observations and \eqn{\sim{y_i}} to +#' values predicted by linear regression. #' #' @return A statistic depending on the function used. #' diff --git a/R/parse_plot_situations_arguments.R b/R/parse_plot_situations_arguments.R new file mode 100644 index 00000000..77eaea1a --- /dev/null +++ b/R/parse_plot_situations_arguments.R @@ -0,0 +1,200 @@ +#' Parse plot situations arguments +#' +#' This function parses the arguments for `plot_situations`. +#' +#' @inheritParams plot_situations +#' +#' @return A list of parsed arguments, eventually corrected according to the +#' compatibility between options. +#' +#' @keywords internal +parse_plot_situations_args <- function( + dot_args, obs = NULL, obs_sd = NULL, + type = c("dynamic", "scatter"), + select_dyn = c("sim", "common", "obs", "all"), + select_scat = c("sim", "res"), var = NULL, + title = NULL, all_situations = TRUE, + overlap = NULL, successive = NULL, + shape_sit = c("none", "txt", "symbol", "group"), + situation_group = NULL, reference_var = NULL, + force = FALSE, verbose = TRUE) { + type <- match.arg(type, c("dynamic", "scatter"), several.ok = FALSE) + select_dyn <- match.arg(select_dyn, c("sim", "common", "obs", "all"), + several.ok = FALSE + ) + + # Now that we have one data.frame only, we can test if we have + # observations / obs_sd: + is_obs <- !is.null(obs) && all(sapply(obs, function(x) nrow(x) > 0)) + is_obs_sd <- !is.null(obs_sd) && all(sapply(obs, function(x) nrow(x) > 0)) + + # Early error on observations (no observations given at all but we need them): + # NB: `generic_formatting` will check if there are common observations + # and simulations + if (!is_obs && (type == "scatter" || select_dyn %in% c("common", "obs"))) { + if (verbose) { + cli::cli_alert_warning( + c( + "Observations are required but not provided, ", + "did you provide `obs = ...`?" + ) + ) + } + if (force) { + return(NULL) + } else { + stop( + "Observations are required but not provided, ", + "did you provide `obs = ...`?" + ) + } + } + + select_scat <- match.arg(select_scat, c("sim", "res"), several.ok = FALSE) + shape_sit <- match.arg(shape_sit, c("none", "txt", "symbol", "group"), + several.ok = FALSE + ) + + if (select_scat == "res" || shape_sit != "none") { + type <- "scatter" + } + + # Disable all_situations when type=="dynamic" temporarily + if (type == "dynamic") { + all_situations <- FALSE + } + + # Enable successive and overlap only when type=="dynamic" + if (!is.null(successive) || !is.null(overlap)) { + type <- "dynamic" + } + + # Text on scatter plots only if all_situations + if (shape_sit != "none") { + all_situations <- TRUE + } + + # Enable reference variable edit only when plotting residual scatter plot + if (!is.null(reference_var)) { + type <- "scatter" + } + + if (!is.null(situation_group)) { + shape_sit <- "group" + } + + if (shape_sit == "group" && is.null(situation_group)) { + if (verbose) { + cli::cli_alert_warning("Argument `situation_group` must be defined + when `shape_sit` is 'group'") + } + if (force) { + return(NULL) + } else { + stop( + "Argument `situation_group` not defined.", + " Use `force = TRUE` to avoid this error." + ) + } + } + + several_sit <- (all_situations || !is.null(successive)) && + shape_sit %in% c("symbol", "group") + + # Name the models: + v_names <- names(dot_args) + if (is.null(v_names) || length(v_names) < length(dot_args)) { + v_names <- paste0("Version_", seq_along(dot_args)) + names(dot_args) <- v_names + } + + # Don't show group in legend if only one: + if (length(v_names) == 1) { + one_version <- TRUE + } else { + one_version <- FALSE + } + + # If there are successive situations: + if (!is.null(successive)) { + # Cat situations that need to be represented as a + # contiguous sequence(dynamic) + list_rot <- cat_successive(dot_args, obs, successive) + dot_args <- list_rot[[1]] + obs <- list_rot[[2]] + } + + if (all_situations) { + common_situations_models <- "all_situations" + } else { + # Intersect situations between versions + common_situations_models <- names(dot_args[[1]]) + + if (length(dot_args) > 1) { + for (index in 2:length(dot_args)) { + common_situations_models <- intersect( + common_situations_models, + names(dot_args[[index]]) + ) + } + } + } + + if (length(title) == 1) { + if (!all_situations) { + title <- rep(title, length(common_situations_models)) + names(title) <- common_situations_models + } else { + title <- NULL + } + } + + if ( + !is.null(title) && + length(title) != length(common_situations_models) && + is.null(names(title)) + ) { + if (verbose) { + cli::cli_alert_danger("Situations number is different from model(s) + outputs, please name the {.code title} argument + with the situations names.") + } + # Situations number is different from models outputs, can't guess + # which title is for which situation. + stop("title argument is not a named list") + } + + if (!is.null(title) && is.null(names(title))) { + # title is provided by the user, is not named, but has same length than + # common_situations_models, so we guess it: + names(title) <- common_situations_models + } + + return( + list( + dot_args = dot_args, + obs = obs, + obs_sd = obs_sd, + type = type, + select_dyn = select_dyn, + select_scat = select_scat, + var = var, + title = title, + all_situations = all_situations, + overlap = overlap, + successive = successive, + shape_sit = shape_sit, + situation_group = situation_group, + reference_var = reference_var, + force = force, + verbose = verbose, + dot_args = dot_args, + v_names = v_names, + one_version = one_version, + several_sit = several_sit, + common_situations_models = common_situations_models, + is_obs = is_obs, + is_obs_sd = is_obs_sd + ) + ) +} diff --git a/R/save_plot_pdf.R b/R/save_plot_pdf.R index 612b562f..4f11232a 100644 --- a/R/save_plot_pdf.R +++ b/R/save_plot_pdf.R @@ -92,7 +92,7 @@ save_plot_pdf <- function(plot, out_dir, file_name = "Graphs", title = "Plots", if (file_per_var) { for (v in vars) { - if (v != "Sit_Name") { + if (v != "sit_name") { pdf(file.path(path, paste0(filename, "-", v, ".pdf")), paper = "a4", width = 7, @@ -154,10 +154,17 @@ save_plot_pdf <- function(plot, out_dir, file_name = "Graphs", title = "Plots", ) plt <- c() for (i in seq_along(plot)) { - for (va in vars) { - if (va %in% plot[[i]]$data$variable) { - plt <- c(plt, extract_plot(plot[i], var = va)) + out <- ggplot2::ggplot_build(plot[[i]]) + if (length(unique(out$data[[1]]$PANEL)) > 1) { + # only for facetted plots + # (plots with overlapped variables should not be extracted per variable ...) + for (va in vars) { + if (va %in% plot[[i]]$data$variable) { + plt <- c(plt, extract_plot(plot[i], var = va)) + } } + } else { + plt <- c(plt, plot[i]) } } p <- 1 diff --git a/man/aesthetics.Rd b/man/aesthetics.Rd deleted file mode 100644 index f49924a1..00000000 --- a/man/aesthetics.Rd +++ /dev/null @@ -1,61 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/aesthetics.R -\name{aesthetics} -\alias{aesthetics} -\title{Manages the aesthetics of the graphics} -\usage{ -aesthetics( - sim, - obs = NULL, - type = c("dynamic", "scatter"), - overlap = NULL, - several_sit = FALSE, - shape_sit = c("none", "txt", "symbol", "group"), - one_version = TRUE, - iVersion = 1, - dot_args = NULL -) -} -\arguments{ -\item{sim}{A simulation list of data.frames} - -\item{obs}{An observation list of data.frames} - -\item{type}{The type of plot required, either "dynamic" or "scatter"} - -\item{overlap}{A list of lists containing the variables to represent on the -same graph when \code{type = "dynamic"}} - -\item{several_sit}{Boolean. Must be equal to \code{TRUE} if sim and obs gather -more than one situation and if situations should be differentiated -on the graph.} - -\item{shape_sit}{Shape to differentiate between situations when -\code{all_situations= TRUE}. See details.} - -\item{one_version}{Boolean. Must be \code{TRUE} if several versions will be -plotted on the same graph.} - -\item{iVersion}{Integer. Version number of sim} - -\item{dot_args}{List of dot arguments given to plot function} -} -\value{ -An aesthetics expression which will allow to manage the aesthetics -of the graphics -} -\description{ -Manages the shape, color and line type of the graphics according -to their content -} -\details{ -The \code{shape_sit} argument can be: -\itemize{ -\item "none" (the default): Same shape for all situations. -\item "txt": Writes the name of the situation above each point. -\item "symbol": One shape for each situation. -\item "group": One shape for each group of situations described in -\code{situation_group}. -} -} -\keyword{internal} diff --git a/man/aesthetics_dynamic.Rd b/man/aesthetics_dynamic.Rd index c53dacc3..4cdaef89 100644 --- a/man/aesthetics_dynamic.Rd +++ b/man/aesthetics_dynamic.Rd @@ -9,7 +9,7 @@ aesthetics_dynamic( aesthetics = template_aesthetics(), overlap = NULL, one_version = TRUE, - iVersion = 1, + iversion = 1, dot_args = NULL, is_mixture = FALSE ) @@ -25,7 +25,7 @@ same graph when \code{type = "dynamic"}} \item{one_version}{Boolean. Must be \code{TRUE} if several versions will be plotted on the same graph.} -\item{iVersion}{Integer. Version number of sim} +\item{iversion}{Integer. Version number of sim} \item{dot_args}{List of dot arguments given to plot function} diff --git a/man/aesthetics_scatter.Rd b/man/aesthetics_scatter.Rd index 144a0f73..49aed062 100644 --- a/man/aesthetics_scatter.Rd +++ b/man/aesthetics_scatter.Rd @@ -10,7 +10,7 @@ aesthetics_scatter( overlap = NULL, several_sit = FALSE, one_version = TRUE, - iVersion = 1, + iversion = 1, dot_args = NULL, is_mixture = FALSE ) @@ -30,7 +30,7 @@ on the graph.} \item{one_version}{Boolean. Must be \code{TRUE} if several versions will be plotted on the same graph.} -\item{iVersion}{Integer. Version number of sim} +\item{iversion}{Integer. Version number of sim} \item{dot_args}{List of dot arguments given to plot function} diff --git a/man/cat_situations.Rd b/man/cat_situations.Rd index e3ce024d..f296c3b4 100644 --- a/man/cat_situations.Rd +++ b/man/cat_situations.Rd @@ -5,13 +5,7 @@ \title{Format simulation data and observation data in order to consider all situations} \usage{ -cat_situations( - list_sim = NULL, - obs = NULL, - obs_sd = NULL, - force = FALSE, - verbose = TRUE -) +cat_situations(list_sim = NULL, obs = NULL, obs_sd = NULL) } \arguments{ \item{list_sim}{A list (each element= version) of a list @@ -22,11 +16,6 @@ cat_situations( \item{obs_sd}{A list (each element= situation) of \code{data.frame}s for the standard deviation of the observations (named by situation)} - -\item{force}{Continue if the plot is not possible ? E.g. no observations for -scatter plots. If \code{TRUE}, return \code{NULL}, else return an error (default).} - -\item{verbose}{Boolean. Print information during execution.} } \value{ A list of three : a list (each element=version) of a list of a single diff --git a/man/cat_versions.Rd b/man/cat_versions.Rd new file mode 100644 index 00000000..368376b1 --- /dev/null +++ b/man/cat_versions.Rd @@ -0,0 +1,20 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/cat_situations.R +\name{cat_versions} +\alias{cat_versions} +\title{Format simulation and observation into a long data frame over versions} +\usage{ +cat_versions(list_sim = NULL) +} +\arguments{ +\item{list_sim}{A list (each element= version) of a list +(each element= situation) of simulations \code{data.frame}s} +} +\value{ +A dataframe +} +\description{ +Format the list of simulation data and observation data +into a long data frame with a new column for the version +} +\keyword{internal} diff --git a/man/cat_with_situation.Rd b/man/cat_with_situation.Rd new file mode 100644 index 00000000..0ce0e548 --- /dev/null +++ b/man/cat_with_situation.Rd @@ -0,0 +1,32 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/cat_situations.R +\name{cat_with_situation} +\alias{cat_with_situation} +\title{Format situations} +\usage{ +cat_with_situation(dot_args, obs, obs_sd, all_situations, v_names) +} +\arguments{ +\item{dot_args}{The dot arguments (the simulations).} + +\item{obs}{The observations.} + +\item{obs_sd}{The standard deviation of the observations.} + +\item{all_situations}{Boolean. Do we need all situations treated +separately or as one.} + +\item{v_names}{The version names.} +} +\value{ +The categorized situations. +} +\description{ +Format the data into a list of situations, with the situation repeated +as a column name, and the version also as a column name. In the case +of \code{all_situations==TRUE}, the situations are concatenated together +into one situation called "all_situations" (the data is a list of +one situation). The true situation name is still kept in the column +\code{sit_name} though. +} +\keyword{internal} diff --git a/man/detect_item_case.Rd b/man/detect_item_case.Rd new file mode 100644 index 00000000..4a3abc9d --- /dev/null +++ b/man/detect_item_case.Rd @@ -0,0 +1,30 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/aesthetics.R +\name{detect_item_case} +\alias{detect_item_case} +\title{Detect items cases} +\usage{ +detect_item_case(type, is_mixture, one_version, several_sit, overlap) +} +\arguments{ +\item{type}{The type of plot required, either 'dynamic' or 'scatter} + +\item{is_mixture}{A logical value indicating whether the crop is a mixture or not.} + +\item{one_version}{A logical value indicating whether the plot has one or multiple versions (e.g. of the model).} + +\item{several_sit}{A logical value indicating whether there are one or several situations to plot.} + +\item{overlap}{A logical value indicating whether there is any overlapping variables in the plot.} +} +\value{ +A unique character string for the plot. +} +\description{ +This function returns a unique string based on the type of plot, and +whether the situation is a mixture or not, if there is one or multiple +versions to plot, and if there is one or several situations to plot +into the same plot. +The output is used to choose the right plotting function in a switch. +} +\keyword{internal} diff --git a/man/detect_mixture.Rd b/man/detect_mixture.Rd new file mode 100644 index 00000000..015816e7 --- /dev/null +++ b/man/detect_mixture.Rd @@ -0,0 +1,37 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/aesthetics.R +\name{detect_mixture} +\alias{detect_mixture} +\title{Detects if a situation is a mixture} +\usage{ +detect_mixture(sim_situation) +} +\arguments{ +\item{sim_situation}{A data frame containing the simulated data for +one situation.} +} +\value{ +A logical value indicating if the situation is a mixture. +} +\description{ +This function checks if the situation is a mixture based on +the presence of a column named "Dominance" and the uniqueness +of its values. +} +\examples{ +\dontrun{ +sim_data <- data.frame( + Dominance = c("Principal", "Principal", "Associated", "Associated") +) +CroPlotR:::detect_mixture(sim_data) +# Output: TRUE + +sim_data <- data.frame(Dominance = c("Single Crop", "Single Crop")) +CroPlotR:::detect_mixture(sim_data) +# Output: FALSE + +sim_data <- data.frame(lai = c(1, 1.2)) +CroPlotR:::detect_mixture(sim_data) +# Output: FALSE +} +} diff --git a/man/detect_mixture_version_overlap.Rd b/man/detect_mixture_version_overlap.Rd index 90beaf60..de6c8be5 100644 --- a/man/detect_mixture_version_overlap.Rd +++ b/man/detect_mixture_version_overlap.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/aesthetics.R \name{detect_mixture_version_overlap} \alias{detect_mixture_version_overlap} -\title{Detect items cases} +\title{Detect items cases for dynamic plots} \usage{ detect_mixture_version_overlap(is_mixture, one_version, overlap) } diff --git a/man/detect_mixture_version_situations.Rd b/man/detect_mixture_version_situations.Rd index 859c35f7..e50dcefa 100644 --- a/man/detect_mixture_version_situations.Rd +++ b/man/detect_mixture_version_situations.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/aesthetics.R \name{detect_mixture_version_situations} \alias{detect_mixture_version_situations} -\title{Detect items cases} +\title{Detect items cases for scatter plots} \usage{ detect_mixture_version_situations(is_mixture, one_version, several_sit) } diff --git a/man/format_cropr.Rd b/man/format_cropr.Rd index 660e08fa..d62f84cc 100644 --- a/man/format_cropr.Rd +++ b/man/format_cropr.Rd @@ -12,7 +12,6 @@ format_cropr( type = c("dynamic", "scatter"), select_dyn = c("sim", "common", "obs", "all"), select_scat = c("sim", "res"), - all_situations = FALSE, successive = NULL, reference_var = NULL, verbose = TRUE @@ -31,12 +30,6 @@ format_cropr( \item{select_scat}{Which data to plot when \code{type= "scatter"}? See details.} -\item{all_situations}{Boolean (default = FALSE). If \code{TRUE}, plot all -situations on the same graph. -If \code{TRUE}, \code{sim} and \code{obs} are respectively an element of the first -element and the -second element of the output of cat_situations.} - \item{successive}{A list of lists containing the situations to be represented as a contiguous sequence when type = "dynamic" (dates should be contiguous) when \code{type = "dynamic"} (implies that the situations are correctly ordered).} diff --git a/man/generic_formatting.Rd b/man/generic_formatting.Rd index 998832f7..d1dbf542 100644 --- a/man/generic_formatting.Rd +++ b/man/generic_formatting.Rd @@ -12,8 +12,7 @@ generic_formatting( type, shape_sit, several_sit, - total_vers, - num_vers + total_vers ) } \arguments{ @@ -36,11 +35,12 @@ based on the situation.} situations to plot.} \item{total_vers}{An integer indicating the total number of versions.} - -\item{num_vers}{An integer indicating the id of the current version.} } \value{ -A formatted data frame. +A long data frame with the formatted data, with columns +Date, Plant, Dominance, sit_name, version, variable, Simulated, Observed. +Column "Combi" can also be added if there are three different +characteristics to plot. } \description{ This function performs generic formatting on a data frame based on the input diff --git a/man/parse_plot_situations_args.Rd b/man/parse_plot_situations_args.Rd new file mode 100644 index 00000000..512dd96e --- /dev/null +++ b/man/parse_plot_situations_args.Rd @@ -0,0 +1,78 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/parse_plot_situations_arguments.R +\name{parse_plot_situations_args} +\alias{parse_plot_situations_args} +\title{Parse plot situations arguments} +\usage{ +parse_plot_situations_args( + dot_args, + obs = NULL, + obs_sd = NULL, + type = c("dynamic", "scatter"), + select_dyn = c("sim", "common", "obs", "all"), + select_scat = c("sim", "res"), + var = NULL, + title = NULL, + all_situations = TRUE, + overlap = NULL, + successive = NULL, + shape_sit = c("none", "txt", "symbol", "group"), + situation_group = NULL, + reference_var = NULL, + force = FALSE, + verbose = TRUE +) +} +\arguments{ +\item{obs}{A list (each element= situation) of observations \code{data.frame}s +(named by situation)} + +\item{obs_sd}{A list (each element= situation) of standard deviations of +observations \code{data.frame}s (named by situation)} + +\item{type}{The type of plot requested, either "dynamic" (date in X, variable +in Y) or scatter (simulated VS observed)} + +\item{select_dyn}{Which data to plot when \code{type= "dynamic"}? See details.} + +\item{select_scat}{Which data to plot when \code{type= "scatter"}? See details.} + +\item{var}{A vector of variables that should be displayed on the graph.} + +\item{title}{A vector of plot titles, named by situation. Use the situation +name if \code{NULL}, recycled if length one.} + +\item{all_situations}{Boolean (default = TRUE). If \code{TRUE}, plot all +situations on the same graph.} + +\item{overlap}{A list of lists containing the variables to represent on the +same graph when \code{type = "dynamic"}.} + +\item{successive}{A list of lists containing the situations to be represented +as a contiguous sequence when \code{type = "dynamic"} +(implies that the situations are correctly ordered).} + +\item{shape_sit}{Shape to differentiate between situations when +\code{all_situations= TRUE}. See details.} + +\item{situation_group}{A list of lists of situations to gather when +\code{shape_sit= "group"}.} + +\item{reference_var}{Variable selected on x-axis when type is scaétter and +select_scat is res. It is possible to select +between observation and simulation of the reference variable. +(examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim")} + +\item{force}{Continue if the plot is not possible ? E.g. no observations for +scatter plots. If \code{TRUE}, return \code{NULL}, else return an error (default).} + +\item{verbose}{Boolean. Print information during execution.} +} +\value{ +A list of parsed arguments, eventually corrected according to the +compatibility between options. +} +\description{ +This function parses the arguments for \code{plot_situations}. +} +\keyword{internal} diff --git a/man/plot_generic_situation.Rd b/man/plot_generic_situation.Rd deleted file mode 100644 index 6b3c0118..00000000 --- a/man/plot_generic_situation.Rd +++ /dev/null @@ -1,114 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/generic_plotting.R -\name{plot_generic_situation} -\alias{plot_generic_situation} -\title{Generic plotting of a situation} -\usage{ -plot_generic_situation( - sim, - obs = NULL, - obs_sd = NULL, - type = c("dynamic", "scatter"), - select_dyn = c("sim", "common", "obs", "all"), - select_scat = c("sim", "res"), - var = var, - title = NULL, - all_situations = TRUE, - overlap = NULL, - successive = NULL, - shape_sit = c("none", "txt", "symbol", "group"), - situation_group = NULL, - total_vers = 1, - num_vers = 1, - reference_var = NULL, - force = FALSE, - verbose = TRUE, - formater -) -} -\arguments{ -\item{sim}{A simulation data.frame} - -\item{obs}{An observation data.frame (variable names must match)} - -\item{obs_sd}{A data.frame of standard deviations of observations} - -\item{select_dyn}{Which data to plot when \code{type= "dynamic"}? See details.} - -\item{select_scat}{Which data to plot when \code{type= "scatter"}? See details.} - -\item{var}{A vector of variables that should be displayed on the graph.} - -\item{title}{The plot title} - -\item{all_situations}{Boolean (default = TRUE). If \code{TRUE}, plot all -situations on the same graph.} - -\item{overlap}{A list of lists containing the variables to represent on -the same graph when \code{type = "dynamic"}.} - -\item{successive}{A list of lists containing the situations to be represented -as a contiguous sequence when \code{type = "dynamic"} -(implies that the situations are correctly ordered).} - -\item{shape_sit}{Shape to differentiate between situations when -\code{all_situations= TRUE}. See details.} - -\item{situation_group}{A list of lists of situations to gather when -\code{shape_sit= "group"}.} - -\item{reference_var}{Variable selected on x-axis when type is scatter and -select_scat is res. It is possible to select -between observation and simulation of the reference variable. -(examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim")} - -\item{force}{Continue if the plot is not possible ? E.g. no observations for -scatter plots. If \code{TRUE}, return \code{NULL}, else return an error (default).} - -\item{verbose}{Boolean. Print information during execution.} - -\item{formater}{The function used to format the models outputs and -observations in a standard way. You can design your own function that format -one situation and provide it here.} -} -\value{ -A ggplot object -} -\description{ -Plots outputs of a model (and observations) for one situation. -This function is used as a generic plotting function for any models. -To use it with your own model, please provide a wrapper function around your -model to format the outputs used by this function (see \code{\link[=format_cropr]{format_cropr()}} for a -template), and then provide your custom function as an argument to this one. -} -\details{ -The \code{select_dyn} argument can be: -\itemize{ -\item "sim" (the default): all variables with simulations outputs, and -observations when there are some -\item "common": variables with simulations outputs and observations in common -\item "obs": all variables with observations, and simulations outputs -when there are some -\item "all": all variables with any observations or simulations outputs -} - -The \code{select_scat} argument can be: -\itemize{ -\item "sim" (the default): plots observations in X and simulations in Y. -\item "res": plots observations in X and residuals(observations-simulations)in Y. -} - -The \code{shape_sit} argument can be: -\itemize{ -\item "none" (the default): Same shape for all situations. -\item "txt": Writes the name of the situation above each point. -\item "symbol": One shape for each situation. -\item "group": One shape for each group of situations described in -\code{situation_group}. -} -} -\note{ -The error bar will be equal to 2*\code{obs_sd} on each side of the point to -have 95\% confidence. -} -\keyword{internal} diff --git a/man/plot_situations.Rd b/man/plot_situations.Rd index 21e9b765..2b75b7c8 100644 --- a/man/plot_situations.Rd +++ b/man/plot_situations.Rd @@ -20,8 +20,7 @@ plot_situations( situation_group = NULL, reference_var = NULL, force = FALSE, - verbose = TRUE, - formater + verbose = TRUE ) } \arguments{ @@ -63,7 +62,7 @@ as a contiguous sequence when \code{type = "dynamic"} \item{situation_group}{A list of lists of situations to gather when \code{shape_sit= "group"}.} -\item{reference_var}{Variable selected on x-axis when type is scatter and +\item{reference_var}{Variable selected on x-axis when type is scaétter and select_scat is res. It is possible to select between observation and simulation of the reference variable. (examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim")} @@ -72,11 +71,6 @@ between observation and simulation of the reference variable. scatter plots. If \code{TRUE}, return \code{NULL}, else return an error (default).} \item{verbose}{Boolean. Print information during execution.} - -\item{formater}{The function used to format the models outputs and -observations in a standard way. You can design your own function -that format one situation and provide it here (see \code{\link[=plot_generic_situation]{plot_generic_situation()}} -and \code{\link[=format_cropr]{format_cropr()}} for more information).} } \value{ A (printed) list of ggplot objects, each element being a plot for diff --git a/man/predictor_assessment.Rd b/man/predictor_assessment.Rd index 29b4d383..cc125ef5 100644 --- a/man/predictor_assessment.Rd +++ b/man/predictor_assessment.Rd @@ -164,26 +164,22 @@ on sim~obs. \item \code{Slope()}: Slope of regression line, computed using \code{\link[stats:lm]{stats::lm()}} on sim~obs. \item \code{RMSE()}: Root Mean Squared Error, computed as -\deqn{RMSE = \sqrt{\frac{\sum_1^n(\hat{y_i}-y_i)^2}{n}}} -{RMSE = sqrt(mean((sim-obs)^2)} +\deqn{RMSE = \sqrt{\frac{\sum_1^n(\hat{y_i}-y_i)^2}{n}}}{RMSE = sqrt(mean((sim-obs)^2)} \item \code{RMSEs()}: Systematic Root Mean Squared Error, computed as -\deqn{RMSEs = \sqrt{\frac{\sum_1^n(\sim{y_i}-y_i)^2}{n}}} -{RMSEs = sqrt(mean((fitted.values(lm(formula=sim~obs))-obs)^2)} +\deqn{RMSEs = \sqrt{\frac{\sum_1^n(\sim{y_i}-y_i)^2}{n}}}{RMSEs = sqrt(mean((fitted.values(lm(formula=sim~obs))-obs)^2)} \item \code{RMSEu()}: Unsystematic Root Mean Squared Error, computed as -\deqn{RMSEu = \sqrt{\frac{\sum_1^n(\sim{y_i}-\hat{y_i})^2}{n}}} -{RMSEu = sqrt(mean((fitted.values(lm(formula=sim~obs))-sim)^2)} +\deqn{RMSEu = \sqrt{\frac{\sum_1^n(\sim{y_i}-\hat{y_i})^2}{n}}}{RMSEu = sqrt(mean((fitted.values(lm(formula=sim~obs))-sim)^2)} \item \code{NSE()}: Nash-Sutcliffe Efficiency, alias of EF, provided for user convenience. \item \code{nRMSE()}: Normalized Root Mean Squared Error, also denoted as CV(RMSE), and computed as: -\deqn{nRMSE = \frac{RMSE}{\bar{y}}\cdot100} -{nRMSE = (RMSE/mean(obs))*100} +\deqn{nRMSE = \frac{RMSE}{\bar{y}}\cdot100}{nRMSE = (RMSE/mean(obs))*100} \item \code{rRMSE()}: Relative Root Mean Squared Error, computed as: \deqn{rRMSE = \frac{RMSE}{\bar{y}}}{rRMSE = (RMSE/mean(obs))} \item \code{rRMSEs()}: Relative Systematic Root Mean Squared Error, computed as \deqn{rRMSEs = \frac{RMSEs}{\bar{y}}}{rRMSEs = (RMSEs/mean(obs))} \item \code{rRMSEu()}: Relative Unsystematic Root Mean Squared Error, -computed as +computed as: \deqn{rRMSEu = \frac{RMSEu}{\bar{y}}}{rRMSEu = (RMSEu/mean(obs))} \item \code{pMSEs()}: Proportion of Systematic Mean Squared Error in Mean Square Error, computed as: @@ -201,8 +197,7 @@ Square Error, computed as: (3rd term of Kobayashi and Salam (2000) MSE decomposition), computed as: \deqn{LCS = 2*sd\_obs*sd\_sim*(1-r)} \item \code{rbias2()}: Relative bias squared, computed as: -\deqn{rbias2 = \frac{Bias^2}{\bar{y}^2}} -{rbias2 = Bias^2/mean(obs)^2} +\deqn{rbias2 = \frac{Bias^2}{\bar{y}^2}}{rbias2 = Bias^2/mean(obs)^2} \item \code{rSDSD()}: Relative difference between sd_obs and sd_sim squared, computed as: \deqn{rSDSD = \frac{SDSD}{\bar{y}^2}}{rSDSD = (SDSD/mean(obs)^2)} @@ -210,36 +205,29 @@ computed as: computed as: \deqn{rLCS = \frac{LCS}{\bar{y}^2}}{rLCS = (LCS/mean(obs)^2)} \item \code{MAE()}: Mean Absolute Error, computed as: -\deqn{MAE = \frac{\sum_1^n(\left|\hat{y_i}-y_i\right|)}{n}} -{MAE = mean(abs(sim-obs))} +\deqn{MAE = \frac{\sum_1^n(\left|\hat{y_i}-y_i\right|)}{n}}{MAE = mean(abs(sim-obs))} \item \code{ABS()}: Mean Absolute Bias, which is an alias of \code{MAE()} \item \code{FVU()}: Fraction of variance unexplained, computed as: \deqn{FVU = \frac{SS_{res}}{SS_{tot}}}{FVU = SS_res/SS_tot} \item \code{MSE()}: Mean squared Error, computed as: -\deqn{MSE = \frac{1}{n}\sum_{i=1}^n(Y_i-\hat{Y_i})^2} -{MSE = mean((sim-obs)^2)} +\deqn{MSE = \frac{1}{n}\sum_{i=1}^n(Y_i-\hat{Y_i})^2}{MSE = mean((sim-obs)^2)} \item \code{EF()}: Model efficiency, also called Nash-Sutcliffe efficiency (NSE). This statistic is related to the FVU as \eqn{EF= 1-FVU}. It is also related to the \eqn{R^2}{R2} because they share the same equation, except SStot is applied relative to the identity function (\emph{i.e.} 1:1 line) instead of the -regression line. It is computed -as: \deqn{EF = 1-\frac{SS_{res}}{SS_{tot}}}{EF = 1-SS_res/SS_tot} +regression line. It is computed as: +\deqn{EF = 1-\frac{SS_{res}}{SS_{tot}}}{EF = 1-SS_res/SS_tot} \item \code{Bias()}: Modelling bias, simply computed as: -\deqn{Bias = \frac{\sum_1^n(\hat{y_i}-y_i)}{n}} -{Bias = mean(sim-obs)} +\deqn{Bias = \frac{\sum_1^n(\hat{y_i}-y_i)}{n}}{Bias = mean(sim-obs)} \item \code{MAPE()}: Mean Absolute Percent Error, computed as: -\deqn{MAPE = \frac{\sum_1^n(\frac{\left|\hat{y_i}-y_i\right|} - {y_i})}{n}}{MAPE = mean(abs(obs-sim)/obs)} +\deqn{MAPE = \frac{\sum_1^n(\frac{\left|\hat{y_i}-y_i\right|}{y_i})}{n}}{MAPE = mean(abs(obs-sim)/obs)} \item \code{RME()}: Relative mean error, computed as: -\deqn{RME = \frac{\sum_1^n(\frac{\hat{y_i}-y_i}{y_i})}{n}} -{RME = mean((sim-obs)/obs)} +\deqn{RME = \frac{\sum_1^n(\frac{\hat{y_i}-y_i}{y_i})}{n}}{RME = mean((sim-obs)/obs)} \item \code{tSTUD()}: T student test of the mean difference, computed as: -\deqn{tSTUD = \frac{Bias}{\sqrt(\frac{var(M)}{n_obs})}} -{tSTUD = Bias/sqrt(var(M)/n_obs)} +\deqn{tSTUD = \frac{Bias}{\sqrt(\frac{var(M)}{n_obs})}}{tSTUD = Bias/sqrt(var(M)/n_obs)} \item \code{tLimit()}: T student threshold, computed using \code{\link[=qt]{qt()}}: -\deqn{tLimit = qt(1-\frac{\alpha}{2},df=length(obs)-1)} -{tLimit = qt(1-risk/2,df =length(obs)-1)} +\deqn{tLimit = qt(1-\frac{\alpha}{2},df=length(obs)-1)}{tLimit = qt(1-risk/2,df =length(obs)-1)} \item \code{Decision()}: Decision of the t student test of the mean difference (can bias be considered statistically not different from 0 at alpha level 0.05, i.e. 5\% probability of erroneously rejecting this hypothesis?), @@ -250,10 +238,8 @@ computed as: \note{ \eqn{SS_{res}}{SS_res} is the residual sum of squares and \eqn{SS_{tot}}{SS_tot} the total sum of squares. They are computed as: -\deqn{SS_{res} = \sum_{i=1}^n (y_i - \hat{y_i})^2} -{SS_res= sum((obs-sim)^2)} -\deqn{SS_{tot} = \sum_{i=1}^{n}\left(y_{i}-\bar{y}\right)^2} -{SS_tot= sum((obs-mean(obs))^2} +\deqn{SS_{res} = \sum_{i=1}^n (y_i - \hat{y_i})^2}{SS_res= sum((obs-sim)^2)} +\deqn{SS_{tot} = \sum_{i=1}^{n}\left(y_{i}-\bar{y}\right)^2}{SS_tot= sum((obs-mean(obs))^2} Also, it should be noted that \eqn{y_i} refers to the observed values and \eqn{\hat{y_i}} to the predicted values, \eqn{\bar{y}} to the mean value of observations and \eqn{\sim{y_i}} to diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd index bba0e465..9e60cb39 100644 --- a/man/specific_scatter_plots.Rd +++ b/man/specific_scatter_plots.Rd @@ -7,14 +7,13 @@ \alias{add_obs_error_bars} \alias{plot_scat_mixture_allsit} \alias{plot_scat_allsit} -\alias{plot_scat_persit} \title{Specific functions to generate scatter plots} \usage{ compute_axis_bounds(df_data, reference_var, y_var_type, is_obs_sd) make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) -add_obs_error_bars(p, colour_factor = NULL) +add_obs_error_bars(p, colour_factor) plot_scat_mixture_allsit( df_data, @@ -35,16 +34,6 @@ plot_scat_allsit( is_obs_sd, title = NULL ) - -plot_scat_persit( - df_data, - sit, - select_scat, - shape_sit, - reference_var, - is_obs_sd, - title = NULL -) } \arguments{ \item{df_data}{A named list of data frame including the data to plot (one df diff --git a/man/statistics.Rd b/man/statistics.Rd index 294c7f1c..8bdee54f 100644 --- a/man/statistics.Rd +++ b/man/statistics.Rd @@ -10,7 +10,6 @@ statistics( all_situations = FALSE, all_plants = TRUE, verbose = TRUE, - formater, stat = "all" ) } @@ -29,20 +28,16 @@ for all plants (when applicable).} \item{verbose}{Boolean. Print informations during execution.} -\item{formater}{The function used to format the models outputs and -observations in a standard way. You can design your own function -that format one situation and provide it here.} - \item{stat}{A character vector of required statistics, "all" for all, or any of \code{\link[=predictor_assessment]{predictor_assessment()}} (e.g. \code{"n"} or \code{"RMSE"}, or both \code{c("n", "RMSE")}).} } \value{ A data.frame with statistics for each variable and possibly each -grouping variable returned by the formater. +grouping variable. } \description{ Compute statistics for evaluation of any model outputs against -observations, providing a formater function (see \code{\link[=format_cropr]{format_cropr()}}). +observations. } \note{ Because this function has the purpose to assess model quality, all @@ -64,7 +59,6 @@ obs <- SticsRFiles::get_obs(workspace = workspace, usm = situations) statistics( sim = sim$`IC_Wheat_Pea_2005-2006_N0`, obs = obs$`IC_Wheat_Pea_2005-2006_N0`, - formater = format_cropr ) } diff --git a/man/statistics_situations.Rd b/man/statistics_situations.Rd index 263b84ad..65c2ba02 100644 --- a/man/statistics_situations.Rd +++ b/man/statistics_situations.Rd @@ -10,8 +10,7 @@ statistics_situations( stat = "all", all_situations = TRUE, all_plants = TRUE, - verbose = TRUE, - formater + verbose = TRUE ) } \arguments{ @@ -32,11 +31,6 @@ statistics for all situations.} for all plants (when applicable).} \item{verbose}{Boolean. Print information during execution.} - -\item{formater}{The function used to format the models outputs and -observations in a standard way. You can design your own function -that format one situation and provide it here (see \code{\link[=statistics]{statistics()}} and -\code{\link[=format_cropr]{format_cropr()}} for more information).} } \value{ A \code{\link[tibble:as_tibble]{tibble::as_tibble()}} with statistics grouped by group diff --git a/man/summary.cropr_simulation.Rd b/man/summary.cropr_simulation.Rd index dc8f9215..3d6907b8 100644 --- a/man/summary.cropr_simulation.Rd +++ b/man/summary.cropr_simulation.Rd @@ -46,6 +46,12 @@ by a model version (or any group actually) workspace <- system.file(file.path("extdata", "stics_example_1"), package = "CroPlotR" ) +situations <- SticsRFiles::get_usms_list( + usm_path = + file.path(workspace, "usms.xml") +) + package = "CroPlotR" +) situations <- SticsRFiles::get_usms_list( usm_path = file.path(workspace, "usms.xml") diff --git a/tests/testthat/_inputs/sim_obs.RData b/tests/testthat/_inputs/sim_obs.RData index 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situation;TRUE;FALSE;FALSE;none;NULL;Plant;NULL;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1 -2;Mixture, All situations;TRUE;FALSE;TRUE;none;NULL;Plant;NULL;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1 -3;Mixture, shape_sit=txt, All situations;TRUE;FALSE;TRUE;txt;NULL;Plant;NULL;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1 -4;Mixture, shape_sit=symbol, All situations;TRUE;FALSE;TRUE;symbol;NULL;Plant;Situation;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1 -5;Mixture (shape_sit=group), All situations;TRUE;FALSE;TRUE;group;NULL;Plant;Situation;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1 -6;Sole crop, Versions, per situation;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -7;Sole crop, Versions, All situations;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -8;Sole crop, Versions, shape_sit=txt, All situations;FALSE;TRUE;TRUE;txt;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -9;Sole crop, Versions, shape_sit=symbol, All situations;FALSE;TRUE;TRUE;symbol;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -10;Sole crop, Versions (shape_sit=group), All situations;FALSE;TRUE;TRUE;group;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -11;Sole crop, All situations, shape_sit=symbol;FALSE;FALSE;TRUE;symbol;NULL;Situation;NULL;NULL;NULL;Version;NULL;NULL;NULL;3;2;1 -12;Sole crop, All situations, shape_sit=group;FALSE;FALSE;TRUE;group;NULL;Situation;NULL;NULL;NULL;Version;NULL;NULL;NULL;3;2;1 -13;Mixture, versions, per situation;TRUE;TRUE;FALSE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -14;Mixture, versions, All situations;TRUE;TRUE;TRUE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -15;Mixture, versions, shape_sit=txt, All situations;TRUE;TRUE;TRUE;txt;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1 -16;Mixture, versions, shape_sit=symbol, All situations;TRUE;TRUE;TRUE;symbol;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1 -17;Mixture, versions, shape_sit=group, All situations;TRUE;TRUE;TRUE;group;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1 +Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var;init_col;init_shape;init_linetype;init_group;version_col;version_shape;version_linetype;version_group;nb_geom_point;nb_geom_smooth;nb_abline;To_test;add_sd_obs +1;Mixture, per situation;sim;TRUE;FALSE;FALSE;none;NULL;Plant;NULL;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1;TRUE;TRUE +2;Mixture, All situations;sim;TRUE;FALSE;TRUE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +3;Mixture, All situations, reference_var=lai_n_sim;sim;TRUE;FALSE;TRUE;none;lai_n_sim;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +4;Mixture, All situations, reference_var=lai_n_obs;sim;TRUE;FALSE;TRUE;none;lai_n_obs;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +5;Mixture, shape_sit=txt, All situations;sim;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +6;Mixture, shape_sit=symbol, All situations;sim;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +7;Mixture (shape_sit=group), All situations;sim;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +8;Sole crop, per situation;sim;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;FALSE +9;Sole crop, All situations;sim;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;TRUE +10;Sole crop, Versions, per situation;sim;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +11;Sole crop, Versions, All situations;sim;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +12;Sole crop, Versions, shape_sit=txt, All situations;sim;FALSE;TRUE;TRUE;txt;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +13;Sole crop, Versions, shape_sit=symbol, All situations;sim;FALSE;TRUE;TRUE;symbol;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +14;Sole crop, Versions (shape_sit=group), All situations;sim;FALSE;TRUE;TRUE;group;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +15;Sole crop, All situations, shape_sit=symbol;sim;FALSE;FALSE;TRUE;symbol;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE +16;Sole crop, All situations, shape_sit=group;sim;FALSE;FALSE;TRUE;group;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE +17;Mixture, versions, per situation;sim;TRUE;TRUE;FALSE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +18;Mixture, versions, All situations;sim;TRUE;TRUE;TRUE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +19;Mixture, versions, shape_sit=txt, All situations;sim;TRUE;TRUE;TRUE;txt;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +20;Mixture, versions, shape_sit=symbol, All situations;sim;TRUE;TRUE;TRUE;symbol;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;FALSE +21;Mixture, versions, shape_sit=group, All situations;sim;TRUE;TRUE;TRUE;group;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;TRUE +22;Mixture, per situation, res;res;TRUE;FALSE;FALSE;none;NULL;Plant;NULL;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1;TRUE;FALSE +23;Mixture, All situations, res;res;TRUE;FALSE;TRUE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +24;Mixture, All situations, reference_var=lai_n_sim, res;res;TRUE;FALSE;TRUE;none;lai_n_sim;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +25;Mixture, All situations, reference_var=lai_n_obs, res;res;TRUE;FALSE;TRUE;none;lai_n_obs;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +26;Mixture, All situations, reference_var=lai_n_res, res;res;TRUE;FALSE;TRUE;none;lai_n_res;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +27;Mixture, shape_sit=txt, All situations, res;res;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +28;Mixture, shape_sit=symbol, All situations, res;res;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +29;Mixture (shape_sit=group), All situations, res;res;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +30;Sole crop, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +31;Sole crop, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +32;Sole crop, Versions, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +33;Sole crop, Versions, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +34;Sole crop, Versions, shape_sit=txt, All situations, res;res;FALSE;TRUE;TRUE;txt;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +35;Sole crop, Versions, shape_sit=symbol, All situations, res;res;FALSE;TRUE;TRUE;symbol;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +36;Sole crop, Versions (shape_sit=group), All situations, res;res;FALSE;TRUE;TRUE;group;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +37;Sole crop, All situations, shape_sit=symbol, res;res;FALSE;FALSE;TRUE;symbol;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE +38;Sole crop, All situations, shape_sit=group, res;res;FALSE;FALSE;TRUE;group;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE +39;Mixture, versions, per situation, res;res;TRUE;TRUE;FALSE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +40;Mixture, versions, All situations, res;res;TRUE;TRUE;TRUE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +41;Mixture, versions, shape_sit=txt, All situations, res;res;TRUE;TRUE;TRUE;txt;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE +42;Mixture, versions, shape_sit=symbol, All situations, res;res;TRUE;TRUE;TRUE;symbol;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;FALSE +43;Mixture, versions, shape_sit=group, All situations, res;res;TRUE;TRUE;TRUE;group;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;TRUE diff --git a/tests/testthat/test-detect_mixture.R b/tests/testthat/test-detect_mixture.R new file mode 100644 index 00000000..210276d3 --- /dev/null +++ b/tests/testthat/test-detect_mixture.R @@ -0,0 +1,12 @@ +test_that("detect_mixture", { + sim_data <- data.frame( + Dominance = c("Principal", "Principal", "Associated", "Associated") + ) + expect_true(CroPlotR:::detect_mixture(sim_data)) + + sim_data <- data.frame(Dominance = c("Single Crop", "Single Crop")) + expect_false(CroPlotR:::detect_mixture(sim_data)) + + sim_data <- data.frame(lai = c(1, 1.2)) + expect_false(CroPlotR:::detect_mixture(sim_data)) +}) diff --git a/tests/testthat/test-generic_formatting.R b/tests/testthat/test-generic_formatting.R new file mode 100644 index 00000000..8908d5a7 --- /dev/null +++ b/tests/testthat/test-generic_formatting.R @@ -0,0 +1,56 @@ +# Loading the inputs (see test-plot to reproduce the data) +load("_inputs/sim_obs.RData") +# load("tests/testthat/_inputs/sim_obs.RData") + +# Prepare the data until format_cropr: +all_situations <- TRUE +type <- "dynamic" +var <- "lai_n" +args_list <- CroPlotR:::parse_plot_situations_args( + list(sim), + obs = obs, type = type, var = var, all_situations = all_situations +) + +situations_outputs <- cat_with_situation( + args_list$dot_args, args_list$obs, args_list$obs_sd, + args_list$all_situations, args_list$v_names +) + +sit <- args_list$common_situations_models[1] +df_sit <- format_cropr( + situations_outputs$sim[[sit]], + situations_outputs$obs[[sit]], + situations_outputs$obs_sd[[sit]], + args_list$type, + args_list$select_dyn, + args_list$select_scat, + args_list$successive, + args_list$reference_var, + args_list$verbose +) + + +# Apply generic_formatting: +df_all <- generic_formatting( + df_sit, + args_list$var, + args_list$overlap, + args_list$situation_group, + args_list$type, args_list$shape_sit, + args_list$several_sit, + 1 +) + +# Apply tests: +test_that("generic_formatting", { + expect_s3_class(df_all, "data.frame") + expect_equal(nrow(df_all), 620) + expect_equal(unique(df_all$sit_name), "IC_Wheat_Pea_2005-2006_N0") + expect_equal(unique(df_all$Plant), c("ble", "poi")) + expect_equal(as.character(min(df_all$Date)), "2005-09-26") + expect_equal(as.character(max(df_all$Date)), "2006-08-01") + expect_equal(unique(df_all$version), "Version_1") + expect_equal(unique(df_all$variable), "lai_n") + expect_equal(mean(df_all$Simulated), 0.21725255, tolerance = 1e-8) + expect_equal(mean(df_all$Observed, na.rm = TRUE), 0.7625, tolerance = 1e-8) +}) diff --git a/tests/testthat/test-generic_statistics.R b/tests/testthat/test-generic_statistics.R index fbf808e6..21499fde 100644 --- a/tests/testthat/test-generic_statistics.R +++ b/tests/testthat/test-generic_statistics.R @@ -6,7 +6,7 @@ test_that("format of statistics", { statistics( sim = sim$`IC_Wheat_Pea_2005-2006_N0`, obs = obs$`IC_Wheat_Pea_2005-2006_N0`, - all_situations = FALSE, formater = format_cropr + all_situations = FALSE ) expect_true(is.data.frame(df_stats)) expect_equal(ncol(df_stats), 39) @@ -18,7 +18,7 @@ test_that("statistics with no obs return NULL", { df_stats <- statistics( sim = sim$`IC_Wheat_Pea_2005-2006_N0`, obs = NULL, - all_situations = FALSE, formater = format_cropr + all_situations = FALSE ) expect_true(is.null(df_stats)) }) @@ -123,6 +123,9 @@ test_that("statistical criteria", { 1:3, ncol(df_stats) )], 5) + # To update the reference, make the test locally, and use snapshot_accept() + # Careful, accept only if the new reference is better than the old one and you + # know what you are doing. expect_snapshot_value(df_stats, style = "json2") }) diff --git a/tests/testthat/test-plotting_formatting.R b/tests/testthat/test-plotting_formatting.R index 1c5413f4..4c536a45 100644 --- a/tests/testthat/test-plotting_formatting.R +++ b/tests/testthat/test-plotting_formatting.R @@ -1,13 +1,12 @@ load("_inputs/sim_obs.RData") test_that("Dynamics plot with wrong args values", { - expect_error(plot(sim, all_situations = FALSE, var = c("lai_n", "masec", "mafruit"))) + expect_error(suppressWarnings(plot(sim, all_situations = FALSE, var = c("lai_n", "masec", "mafruit")))) expect_error(plot(sim, all_situations = FALSE, var = c("lai_n"), type = "dynamics")) - expect_error(plot(sim, all_situations = FALSE, var = c("lai_n"), select_dyn = "obs")) + expect_error(plot(sim, all_situations = FALSE, var = c("lai_n"), select_dyn = "obs", force = FALSE)) }) - test_that("Scatter plot with wrong args values", { expect_error(plot(sim, obs = obs, type = "scatter", var = c("lai_n", "masec", "mafruit"))) - expect_error(plot(sim, type = "scatter", var = c("lai_n"), select_scat = "obs")) + expect_error(plot(sim, type = "scatter", var = c("lai_n"), select_scat = "obs", force = FALSE)) }) diff --git a/tests/testthat/vdiffr/test-snapshots.R b/tests/testthat/vdiffr/test-snapshots.R index 557b64cc..467a330b 100644 --- a/tests/testthat/vdiffr/test-snapshots.R +++ b/tests/testthat/vdiffr/test-snapshots.R @@ -1,8 +1,7 @@ # These tests need R version >= 4.2 for testhat >= 3.0.0. # Also, we only test on the OS and R version the snapshots were built on. -# pkg_version <- "Release"; source('tests/testthat/vdiffr/generate-snapshots.R') -# pkg_version <- "Latest"; source('tests/testthat/vdiffr/generate-snapshots.R') +# snapshots are generated in test-***-plots.R scripts if (!exists("tmpdir")) { stop(paste( @@ -11,11 +10,29 @@ if (!exists("tmpdir")) { )) } -figs <- list.files(tmpdir, pattern = "*fig.*\\.svg$", full.names = TRUE) +figs <- list.files(tmpdir, pattern = "*fig.*\\.svg$", full.names = FALSE) latest_figs <- figs[grepl("latest.svg$", figs)] release_figs <- figs[grepl("release.svg$", figs)] +# grep beginning of latest_figs in release_figs +prefix_latest_figs <- sapply(latest_figs, function(x) substr(x, 1, nchar(x) - 11)) +prefix_release_figs <- sapply(release_figs, function(x) substr(x, 1, nchar(x) - 12)) + +missing_figs <- setdiff(prefix_release_figs, prefix_latest_figs) +if (length(missing_figs) > 0) { + message(paste( + "Warning: figure(s) ", + paste(missing_figs, collapse = ", "), + "not generated for latest version.", + "\n They will therefore not be taken into account in snapshot comparison." + )) + release_figs <- paste0(prefix_latest_figs, "-release.svg") +} + +release_figs <- file.path(tmpdir, release_figs) +latest_figs <- file.path(tmpdir, latest_figs) + set.seed(1) mapply( From 87f69ab5c3452b29ce33455488707c5418950276 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 23 Jul 2025 12:05:46 +0200 Subject: [PATCH 038/118] Using standard version of pak (not rc) --- .github/workflows/check-standard.yaml | 4 ---- .github/workflows/vdiffr.yaml | 10 +++------- 2 files changed, 3 insertions(+), 11 deletions(-) diff --git a/.github/workflows/check-standard.yaml b/.github/workflows/check-standard.yaml index 6a1ba404..747b863b 100644 --- a/.github/workflows/check-standard.yaml +++ b/.github/workflows/check-standard.yaml @@ -51,10 +51,6 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: - pak-version: rc - # about pak-version: - # Ubuntu doesn't install the proper version of XML see https://github.com/r-lib/actions/issues/559. Remove when fixed. - # see also: https://stackoverflow.com/questions/73243945/pkgdown-action-failing-at-build-xml extra-packages: | any::rcmdcheck SticsRPacks/SticsRFiles@main diff --git a/.github/workflows/vdiffr.yaml b/.github/workflows/vdiffr.yaml index 1f1bdc7c..11efaf25 100644 --- a/.github/workflows/vdiffr.yaml +++ b/.github/workflows/vdiffr.yaml @@ -5,7 +5,7 @@ on: jobs: snapshot_comparison: - runs-on: ubuntu-latest # Replace with the appropriate runner for your needs + runs-on: ubuntu-latest # Replace with the appropriate runner for your needs steps: - name: Checkout repository @@ -18,10 +18,6 @@ jobs: - uses: r-lib/actions/setup-r-dependencies@v2 with: - pak-version: rc - # about pak-version: - # Ubuntu doesn't install the proper version of XML see https://github.com/r-lib/actions/issues/559. Remove when fixed. - # see also: https://stackoverflow.com/questions/73243945/pkgdown-action-failing-at-build-xml extra-packages: | any::testthat any::rcmdcheck @@ -37,7 +33,8 @@ jobs: Rscript -e "pkg_version <- 'Latest'; tmpdir <- '${{ runner.temp }}'; testthat::test_file('tests/testthat/test-dynamic-plots.R', stop_on_failure=FALSE); testthat::test_file('tests/testthat/test-scatter-plots.R', stop_on_failure=FALSE)" - name: Cache the snapshot scripts - run: | # Move the scripts and data from tests/testthat to the tmpdir directory so that both run use the same scripts + run: + | # Move the scripts and data from tests/testthat to the tmpdir directory so that both run use the same scripts mv tests/testthat/* ${{ runner.temp }}/ - name: Checkout CroPlotR main branch @@ -64,4 +61,3 @@ jobs: - name: Compare snapshots run: | Rscript -e "tmpdir <- '${{ runner.temp }}'; testthat::test_file('${{ runner.temp }}/vdiffr/test-snapshots.R', stop_on_failure=TRUE)" - From 737ce0507e52b3fe5439c1986ab6de6db3a4cbee Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 23 Jul 2025 12:07:36 +0200 Subject: [PATCH 039/118] Up doc --- man/parse_plot_situations_args.Rd | 2 +- man/plot_situations.Rd | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/man/parse_plot_situations_args.Rd b/man/parse_plot_situations_args.Rd index 512dd96e..669be03c 100644 --- a/man/parse_plot_situations_args.Rd +++ b/man/parse_plot_situations_args.Rd @@ -58,7 +58,7 @@ as a contiguous sequence when \code{type = "dynamic"} \item{situation_group}{A list of lists of situations to gather when \code{shape_sit= "group"}.} -\item{reference_var}{Variable selected on x-axis when type is scaétter and +\item{reference_var}{Variable selected on x-axis when type is scatter and select_scat is res. It is possible to select between observation and simulation of the reference variable. (examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim")} diff --git a/man/plot_situations.Rd b/man/plot_situations.Rd index 2b75b7c8..3efc5b87 100644 --- a/man/plot_situations.Rd +++ b/man/plot_situations.Rd @@ -62,7 +62,7 @@ as a contiguous sequence when \code{type = "dynamic"} \item{situation_group}{A list of lists of situations to gather when \code{shape_sit= "group"}.} -\item{reference_var}{Variable selected on x-axis when type is scaétter and +\item{reference_var}{Variable selected on x-axis when type is scatter and select_scat is res. It is possible to select between observation and simulation of the reference variable. (examples : reference_var = "lai_n_obs", reference_var = "mafruit_sim")} From 65503d63948d07e024626b591efd1ea0c2139c21 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 23 Jul 2025 17:03:59 +0200 Subject: [PATCH 040/118] update scatter plot fig 1 --- tests/testthat/_inputs/tests_scatter_plots.csv | 4 ++-- tests/testthat/test-scatter-plots.R | 4 +++- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index fde9a033..54b279c2 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -1,5 +1,5 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var;init_col;init_shape;init_linetype;init_group;version_col;version_shape;version_linetype;version_group;nb_geom_point;nb_geom_smooth;nb_abline;To_test;add_sd_obs -1;Mixture, per situation;sim;TRUE;FALSE;FALSE;none;NULL;Plant;NULL;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1;TRUE;TRUE +1;Mixture, per situation;sim;TRUE;FALSE;FALSE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 2;Mixture, All situations;sim;TRUE;FALSE;TRUE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 3;Mixture, All situations, reference_var=lai_n_sim;sim;TRUE;FALSE;TRUE;none;lai_n_sim;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 4;Mixture, All situations, reference_var=lai_n_obs;sim;TRUE;FALSE;TRUE;none;lai_n_obs;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE @@ -20,7 +20,7 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 19;Mixture, versions, shape_sit=txt, All situations;sim;TRUE;TRUE;TRUE;txt;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE 20;Mixture, versions, shape_sit=symbol, All situations;sim;TRUE;TRUE;TRUE;symbol;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;FALSE 21;Mixture, versions, shape_sit=group, All situations;sim;TRUE;TRUE;TRUE;group;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;TRUE -22;Mixture, per situation, res;res;TRUE;FALSE;FALSE;none;NULL;Plant;NULL;NULL;NULL;NULL;NULL;NULL;NULL;3;2;1;TRUE;FALSE +22;Mixture, per situation, res;res;TRUE;FALSE;FALSE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 23;Mixture, All situations, res;res;TRUE;FALSE;TRUE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 24;Mixture, All situations, reference_var=lai_n_sim, res;res;TRUE;FALSE;TRUE;none;lai_n_sim;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 25;Mixture, All situations, reference_var=lai_n_obs, res;res;TRUE;FALSE;TRUE;none;lai_n_obs;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index 38249138..d6c89af4 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -260,7 +260,7 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { ) } - if (any(is.na(test_plot))) { + if (all(is.na(test_plot))) { message(paste( "Scatter Plot #", tmp$Number[[i]], " decribed in file _inputs/tests_scatter_plot.csv not yet implemented (plot return NA)" @@ -271,6 +271,7 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { " is disabled in file _inputs/tests_scatter_plot.csv (see column To_test" )) } else { + print(paste("##########################", tmp$Number[[i]])) message("Testing scatter Plot #", tmp$Number[[i]]) expect_true(is.list(test_plot)) expect_equal(length(test_plot), tmp$length[[i]]) @@ -319,6 +320,7 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { } ## add title for visual inspection of the graph + test_plot <- test_plot[sapply(test_plot, function(x) inherits(x, "ggplot"))] test_plot <- lapply(test_plot, function(x) { x + ggplot2::labs(caption = paste0("Plot #", i, "\n", tmp$Title[[i]])) + From 8d43f2b6518caa08429926e1c4f827f429f12156 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 23 Jul 2025 17:07:21 +0200 Subject: [PATCH 041/118] update scatter plot fig 1 --- tests/testthat/test-scatter-plots.R | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index d6c89af4..a54bb2ce 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -271,7 +271,6 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { " is disabled in file _inputs/tests_scatter_plot.csv (see column To_test" )) } else { - print(paste("##########################", tmp$Number[[i]])) message("Testing scatter Plot #", tmp$Number[[i]]) expect_true(is.list(test_plot)) expect_equal(length(test_plot), tmp$length[[i]]) From 9e82a2ff61321d43dc390af0f5a5aa3bcdb822e7 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 3 Sep 2025 09:27:53 +0200 Subject: [PATCH 042/118] feat: extend scatter plot with non_mixture_no_versions_per_situations case --- R/generic_plotting.R | 14 +++++++++++--- R/specific_plotting_scatter.R | 8 ++++++-- 2 files changed, 17 insertions(+), 5 deletions(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index de8faa60..97a5ebb7 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -171,8 +171,9 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, p <- list() for (i in common_situations_models) { sim_situation <- formated_situation_list[[i]] + mixture <- detect_mixture(sim_situation) item_case <- detect_item_case( - type, detect_mixture(sim_situation), one_version, several_sit, overlap + type, mixture, one_version, several_sit, overlap ) plot_title <- if (!is.null(title)) { @@ -219,9 +220,16 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, plot_scat_allsit( sim_situation, i, select_scat, shape_sit, reference_var, is_obs_sd, - title = plot_title + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture ), - "non_mixture_no_versions_per_situations" = NA + "non_mixture_no_versions_per_situations" = #NA + plot_scat_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture + ) ) } diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 58676c8a..ccf7c1bc 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -250,12 +250,13 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, #' @keywords internal #' @rdname specific_scatter_plots plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, - reference_var, is_obs_sd, title = NULL) { + reference_var, is_obs_sd, title = NULL, + several_sit=FALSE,one_version = FALSE, + mixture = FALSE) { tmp <- give_reference_var(reference_var) reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) @@ -317,6 +318,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } + if (several_sit == FALSE && one_version == TRUE && mixture == FALSE) { + p <- p + ggplot2::theme(legend.position = "none") + } return(p) } From b45829138e395200d0568831c015920c57695129 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 3 Sep 2025 10:09:10 +0200 Subject: [PATCH 043/118] Fix: use of get_usm_list (#79) As done in 917e287. Reapplied the changes manually instead of merging from main, to avoid troubles caused by previous rebase. --- R/cropr_bind_split.R | 4 ++-- R/cropr_plotting.R | 2 +- R/cropr_stats.R | 4 ++-- R/generic_plotting.R | 2 +- R/generic_stats.R | 2 +- man/bind_rows.Rd | 2 +- man/plot.cropr_simulation.Rd | 2 +- man/plot.statistics.Rd | 2 +- man/split_df2sim.Rd | 2 +- man/statistics.Rd | 2 +- man/summary.cropr_simulation.Rd | 4 ++-- 11 files changed, 14 insertions(+), 14 deletions(-) diff --git a/R/cropr_bind_split.R b/R/cropr_bind_split.R index 7a0f6766..b84abd0a 100644 --- a/R/cropr_bind_split.R +++ b/R/cropr_bind_split.R @@ -33,7 +33,7 @@ #' package = "CroPlotR" #' ) #' situations <- SticsRFiles::get_usms_list( -#' usm_path = +#' file = #' file.path(workspace, "usms.xml") #' ) #' sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) @@ -111,7 +111,7 @@ bind_rows_sim <- function(...) { #' package = "CroPlotR" #' ) #' situations <- SticsRFiles::get_usms_list( -#' usm_path = +#' file = #' file.path(workspace, "usms.xml") #' ) #' sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/R/cropr_plotting.R b/R/cropr_plotting.R index 2f2a123b..94760f30 100644 --- a/R/cropr_plotting.R +++ b/R/cropr_plotting.R @@ -77,7 +77,7 @@ #' package = "CroPlotR" #' ) #' situations <- SticsRFiles::get_usms_list( -#' usm_path = +#' file = #' file.path(workspace, "usms.xml") #' ) #' sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/R/cropr_stats.R b/R/cropr_stats.R index 68033809..6b07d2fe 100644 --- a/R/cropr_stats.R +++ b/R/cropr_stats.R @@ -30,13 +30,13 @@ #' package = "CroPlotR" #' ) #' situations <- SticsRFiles::get_usms_list( -#' usm_path = +#' file = #' file.path(workspace, "usms.xml") #' ) #' package = "CroPlotR" #' ) #' situations <- SticsRFiles::get_usms_list( -#' usm_path = +#' file = #' file.path(workspace, "usms.xml") #' ) #' sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index de8faa60..49b6c390 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -265,7 +265,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, #' package = "CroPlotR" #' ) #' situations <- SticsRFiles::get_usms_list( -#' usm_path = +#' file = #' file.path(workspace, "usms.xml") #' ) #' sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/R/generic_stats.R b/R/generic_stats.R index d6e32d60..385531b5 100644 --- a/R/generic_stats.R +++ b/R/generic_stats.R @@ -119,7 +119,7 @@ statistics_situations <- function(..., obs = NULL, stat = "all", #' package = "CroPlotR" #' ) #' situations <- SticsRFiles::get_usms_list( -#' usm_path = +#' file = #' file.path(workspace, "usms.xml") #' ) #' sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/man/bind_rows.Rd b/man/bind_rows.Rd index 91da8e1d..b380541d 100644 --- a/man/bind_rows.Rd +++ b/man/bind_rows.Rd @@ -39,7 +39,7 @@ workspace <- system.file(file.path("extdata", "stics_example_1"), package = "CroPlotR" ) situations <- SticsRFiles::get_usms_list( - usm_path = + file = file.path(workspace, "usms.xml") ) sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/man/plot.cropr_simulation.Rd b/man/plot.cropr_simulation.Rd index 17aa93f9..1674d1be 100644 --- a/man/plot.cropr_simulation.Rd +++ b/man/plot.cropr_simulation.Rd @@ -143,7 +143,7 @@ workspace <- system.file(file.path("extdata", "stics_example_1"), package = "CroPlotR" ) situations <- SticsRFiles::get_usms_list( - usm_path = + file = file.path(workspace, "usms.xml") ) sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/man/plot.statistics.Rd b/man/plot.statistics.Rd index 07877173..3f6395ae 100644 --- a/man/plot.statistics.Rd +++ b/man/plot.statistics.Rd @@ -60,7 +60,7 @@ workspace <- system.file(file.path("extdata", "stics_example_1"), package = "CroPlotR" ) situations <- SticsRFiles::get_usms_list( - usm_path = + file = file.path(workspace, "usms.xml") ) sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/man/split_df2sim.Rd b/man/split_df2sim.Rd index 774f5941..4e7034c2 100644 --- a/man/split_df2sim.Rd +++ b/man/split_df2sim.Rd @@ -31,7 +31,7 @@ workspace <- system.file(file.path("extdata", "stics_example_1"), package = "CroPlotR" ) situations <- SticsRFiles::get_usms_list( - usm_path = + file = file.path(workspace, "usms.xml") ) sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/man/statistics.Rd b/man/statistics.Rd index 8bdee54f..3d8c0730 100644 --- a/man/statistics.Rd +++ b/man/statistics.Rd @@ -51,7 +51,7 @@ workspace <- system.file(file.path("extdata", "stics_example_1"), package = "CroPlotR" ) situations <- SticsRFiles::get_usms_list( - usm_path = + file = file.path(workspace, "usms.xml") ) sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) diff --git a/man/summary.cropr_simulation.Rd b/man/summary.cropr_simulation.Rd index 3d6907b8..a953bf37 100644 --- a/man/summary.cropr_simulation.Rd +++ b/man/summary.cropr_simulation.Rd @@ -47,13 +47,13 @@ workspace <- system.file(file.path("extdata", "stics_example_1"), package = "CroPlotR" ) situations <- SticsRFiles::get_usms_list( - usm_path = + file = file.path(workspace, "usms.xml") ) package = "CroPlotR" ) situations <- SticsRFiles::get_usms_list( - usm_path = + file = file.path(workspace, "usms.xml") ) sim <- SticsRFiles::get_sim(workspace = workspace, usm = situations) From 13fb1713f8c246567e653c3270b64464e45f57d4 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 3 Sep 2025 10:37:14 +0200 Subject: [PATCH 044/118] feat: extend scatter plot with non_mixture_no_versions_per_situations case --- R/generic_plotting.R | 2 +- R/specific_plotting_scatter.R | 3 +++ man/specific_scatter_plots.Rd | 11 ++++++++++- 3 files changed, 14 insertions(+), 2 deletions(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index e43e37db..eedf4814 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -223,7 +223,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, title = plot_title, several_sit = several_sit, one_version = one_version, mixture = mixture ), - "non_mixture_no_versions_per_situations" = #NA + "non_mixture_no_versions_per_situations" = plot_scat_allsit( sim_situation, i, select_scat, shape_sit, reference_var, is_obs_sd, diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index ccf7c1bc..711c0798 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -8,6 +8,9 @@ #' per situation, or only one df if sit==all_situations) #' @param sit The name of the situation to plot (or all_situations) #' @param is_obs_sd TRUE if error standard deviation of observations is provided +#' @param mixture TRUE if the plot is for a mixture of crops +#' @param one_version TRUE if the plot is for one version +#' @param several_sit TRUE if the plot is for several situations #' #' @importFrom rlang .data #' @return A ggplot object diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd index 9e60cb39..9c142db4 100644 --- a/man/specific_scatter_plots.Rd +++ b/man/specific_scatter_plots.Rd @@ -32,7 +32,10 @@ plot_scat_allsit( shape_sit, reference_var, is_obs_sd, - title = NULL + title = NULL, + several_sit = FALSE, + one_version = FALSE, + mixture = FALSE ) } \arguments{ @@ -48,6 +51,12 @@ per situation, or only one df if sit==all_situations)} \item{colour_factor}{The factor to use for colouring the error bars} \item{sit}{The name of the situation to plot (or all_situations)} + +\item{several_sit}{TRUE if the plot is for several situations} + +\item{one_version}{TRUE if the plot is for one version} + +\item{mixture}{TRUE if the plot is for a mixture of crops} } \value{ A ggplot object From 25122ff0c1291e51541d1f623c734e383c444cc8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 14:45:01 +0200 Subject: [PATCH 045/118] Use Figure number from the reference csv for naming the figure instead of the line number --- tests/testthat/test-scatter-plots.R | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index a54bb2ce..41d4db1b 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -332,7 +332,15 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { sit <- paste0("_", y) } make_snapshot( - paste0(prefix, "_fig.", i, "_", tmp$Title[[i]], sit, pkg_version), + paste0( + prefix, + "_fig.", + tmp$Number[[i]], + "_", + tmp$Title[[i]], + sit, + pkg_version + ), test_plot[[y]], tmpdir ) From 887d990cf6bd177a530d70a2c9cd6bc877c90149 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 14:51:21 +0200 Subject: [PATCH 046/118] Make Scatter Fig 8 and 9 --- R/generic_plotting.R | 4 ++-- R/specific_plotting_scatter.R | 18 ++++++++++-------- tests/testthat/_inputs/tests_scatter_plots.csv | 4 ++-- 3 files changed, 14 insertions(+), 12 deletions(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index eedf4814..d277b4ee 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -223,8 +223,8 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, title = plot_title, several_sit = several_sit, one_version = one_version, mixture = mixture ), - "non_mixture_no_versions_per_situations" = - plot_scat_allsit( + "non_mixture_no_versions_per_situations" = + plot_scat_allsit( sim_situation, i, select_scat, shape_sit, reference_var, is_obs_sd, title = plot_title, several_sit = several_sit, diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 711c0798..51f4ed27 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -148,14 +148,13 @@ give_y_var_type <- function(select_scat) { #' @param p A ggplot to modify` #' @param colour_factor The factor to use for colouring the error bars #' @return The modified ggplot -add_obs_error_bars <- function(p, colour_factor) { +add_obs_error_bars <- function(p, colour_factor = NULL) { p <- p + - ggplot2::geom_errorbarh( + ggplot2::geom_linerange( ggplot2::aes( xmin = .data$Observed - 2 * .data$Obs_SD, xmax = .data$Observed + 2 * .data$Obs_SD, colour = .data[[colour_factor]], - height = 0 ), na.rm = TRUE ) @@ -253,8 +252,8 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, #' @keywords internal #' @rdname specific_scatter_plots plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, - reference_var, is_obs_sd, title = NULL, - several_sit=FALSE,one_version = FALSE, + reference_var, is_obs_sd, title = NULL, + several_sit = FALSE, one_version = FALSE, mixture = FALSE) { tmp <- give_reference_var(reference_var) reference_var <- tmp$reference_var @@ -299,9 +298,12 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ggplot2::ggtitle(title) if (is_obs_sd && reference_var == "Observed") { - p$data$colour_factor <- as.factor(paste(p$data$sit_name)) - p <- add_obs_error_bars(p, - colour_factor = "colour_factor" + p <- p + ggplot2::geom_linerange( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + ), + na.rm = TRUE ) } diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index 54b279c2..ac9644f6 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -6,8 +6,8 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 5;Mixture, shape_sit=txt, All situations;sim;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 6;Mixture, shape_sit=symbol, All situations;sim;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 7;Mixture (shape_sit=group), All situations;sim;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -8;Sole crop, per situation;sim;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;FALSE -9;Sole crop, All situations;sim;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;TRUE +8;Sole crop, per situation;sim;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;FALSE +9;Sole crop, All situations;sim;FALSE;FALSE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;TRUE 10;Sole crop, Versions, per situation;sim;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE 11;Sole crop, Versions, All situations;sim;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE 12;Sole crop, Versions, shape_sit=txt, All situations;sim;FALSE;TRUE;TRUE;txt;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE From 47e3cb442b279078edc1088a45ff6edc5fac1257 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 15:14:30 +0200 Subject: [PATCH 047/118] Delete figures generated by previous tests before running the new tests --- tests/testthat/test-dynamic-plots.R | 4 ++++ tests/testthat/test-scatter-plots.R | 4 ++++ 2 files changed, 8 insertions(+) diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index fd4dd722..bcfc318e 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -63,6 +63,10 @@ if (!testthat:::on_ci()) { tmpdir <- "_outputs" if (!file.exists(tmpdir)) { dir.create(tmpdir) + } else { + # Delete the dynamic figures that are already present ("dynamic-fig...") + list.files(tmpdir, pattern = paste0("^dynamic-fig.*.svg$"), full.names = TRUE) |> + file.remove() } } diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index 41d4db1b..03a73c82 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -78,6 +78,10 @@ if (!testthat:::on_ci()) { tmpdir <- "_outputs" if (!file.exists(tmpdir)) { dir.create(tmpdir) + } else { + # Delete the scatter figures that are already present ("scatter-fig...") + list.files(tmpdir, pattern = paste0("^scatter-fig.*.svg$"), full.names = TRUE) |> + file.remove() } } From 1b17001bfc5b20e19448afd57650b883b323c139 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 16:22:58 +0200 Subject: [PATCH 048/118] Add version back to the simulation data when scatter or select_dyn == "obs" or "common" --- R/cropr_formatting.R | 3 +++ 1 file changed, 3 insertions(+) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 98fc7ae0..ba4d6776 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -184,6 +184,9 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, # Plot all observations, and only sim that are observed if (is_obs && select_dyn %in% c("obs", "common") || type == "scatter") { ind <- colnames(sim)[which(s_lower %in% inter)] + if ("version" %in% s_lower) { + ind <- unique(c(ind, "version")) + } sim <- sim[, ind] obs <- obs[, unique(colnames(obs))] # protection for call to summary (no sit_name): From d7bcccc5fe259ffce3969e6837ad2540c986e877 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 16:37:56 +0200 Subject: [PATCH 049/118] Add mixture_versions_per_situations -> plots 17 and 18 --- R/generic_plotting.R | 8 ++- R/specific_plotting_scatter.R | 92 +++++++++++++++++++++++++++++++++++ 2 files changed, 98 insertions(+), 2 deletions(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index d277b4ee..7941f298 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -207,8 +207,12 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, # Scatter plots: "mixture_versions_situations" = NA, - "mixture_versions_per_situations" = NA, - "mixture_no_versions" = + "mixture_versions_per_situations" = plot_scat_mixture_versions( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "mixture_no_versions" = # per sit and all sit share the same call plot_scat_mixture_allsit( sim_situation, i, select_scat, shape_sit, reference_var, is_obs_sd, diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 51f4ed27..957a56cb 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -247,6 +247,98 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, } +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ) + + if (shape_sit == "none" || shape_sit == "txt") { + p <- p + ggplot2::geom_point( + ggplot2::aes( + shape = as.factor(paste(.data$Dominance, ":", .data$Plant)), + colour = as.factor(.data$version) + ), + na.rm = TRUE + ) + + ggplot2::labs(color = "Version", shape = "Plant") + } else if (shape_sit == "symbol" || shape_sit == "group") { + # ! In this case we loose the colour by species for mixtures, because + # there would be three aesthetics to handle (situation, version and + # species). We made this decision because the user explicitly asks + # for shape to be the situation name. If they want to color by species, + # they can put shape_sit = "none" or shape_sit = "txt" to have it all. + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(.data$version), + shape = as.factor(.data$sit_name) + ), + na.rm = TRUE + ) + + ggplot2::labs(color = "Version", shape = "Situation") + } + + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + ggplot2::ggtitle(title) + + if (is_obs_sd && reference_var == "Observed") { + p <- p + + ggplot2::geom_linerange( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + colour = as.factor(.data$version), + ), + na.rm = TRUE + ) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + if (shape_sit == "txt") { + p <- p + + ggrepel::geom_text_repel( + ggplot2::aes( + label = .data$sit_name, + colour = as.factor(.data$version) + ), + show.legend = FALSE, + max.overlaps = 100 + ) + } + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" && reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + + return(p) +} #' @keywords internal From 991c5c334e752fee9d354ae6113bd0fe4f013669 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 16:44:43 +0200 Subject: [PATCH 050/118] Update specific_plotting_scatter.R --- R/specific_plotting_scatter.R | 1 - 1 file changed, 1 deletion(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 957a56cb..81f4e147 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -209,7 +209,6 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, fullrange = TRUE, na.rm = TRUE ) + ggplot2::xlab(reference_var_name) + - ggplot2::labs(fill = "Plant") + ggplot2::facet_wrap(~variable, scales = "free") p <- p + From c43086d5b7fe9e913874e8ae39c690e38ba43d97 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 16:53:39 +0200 Subject: [PATCH 051/118] Update tests_scatter_plots.csv Sole crop, per situation shouldn't have version == TRUE in the ref csv file --- tests/testthat/_inputs/tests_scatter_plots.csv | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index ac9644f6..2922e398 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -28,7 +28,7 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 27;Mixture, shape_sit=txt, All situations, res;res;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 28;Mixture, shape_sit=symbol, All situations, res;res;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 29;Mixture (shape_sit=group), All situations, res;res;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -30;Sole crop, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +30;Sole crop, per situation, res;res;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 31;Sole crop, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 32;Sole crop, Versions, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE 33;Sole crop, Versions, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE From 2222d8579dbee6e075a51e776e683423a8b2f030 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Thu, 16 Oct 2025 17:21:10 +0200 Subject: [PATCH 052/118] mixture_versions_situations and mixture_versions_per_situations share the same code --- R/aesthetics.R | 4 ++-- R/generic_plotting.R | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/R/aesthetics.R b/R/aesthetics.R index 1c70065b..0e5af4a9 100644 --- a/R/aesthetics.R +++ b/R/aesthetics.R @@ -97,8 +97,8 @@ detect_mixture_version_overlap <- function(is_mixture, one_version, overlap) { #' @keywords internal detect_mixture_version_situations <- function(is_mixture, one_version, several_sit) { case <- switch(paste(is_mixture, !one_version, several_sit), - "TRUE TRUE TRUE" = "mixture_versions_situations", - "TRUE TRUE FALSE" = "mixture_versions_per_situations", + "TRUE TRUE TRUE" = "mixture_versions", + "TRUE TRUE FALSE" = "mixture_versions", "TRUE FALSE TRUE" = "mixture_no_versions", "TRUE FALSE FALSE" = "mixture_no_versions", "FALSE TRUE TRUE" = "non_mixture_versions_situations", diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 7941f298..cc87a2bb 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -183,6 +183,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, } else { i } + print(item_case) p[[i]] <- switch(item_case, # Dynamic plots: "mixture_versions_overlap" = @@ -206,8 +207,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, plot_dynamic(sim_situation, i, successive, title = plot_title), # Scatter plots: - "mixture_versions_situations" = NA, - "mixture_versions_per_situations" = plot_scat_mixture_versions( + "mixture_versions" = plot_scat_mixture_versions( # per sit and all sit share the same call sim_situation, i, select_scat, shape_sit, reference_var, is_obs_sd, title = plot_title From 3405bd5eebef37c6ca9aeecad09131b901c3385d Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Fri, 17 Oct 2025 10:04:23 +0200 Subject: [PATCH 053/118] update csv file --- tests/testthat/_inputs/tests_scatter_plots.csv | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index 54b279c2..ac9644f6 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -6,8 +6,8 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 5;Mixture, shape_sit=txt, All situations;sim;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 6;Mixture, shape_sit=symbol, All situations;sim;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 7;Mixture (shape_sit=group), All situations;sim;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -8;Sole crop, per situation;sim;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;FALSE -9;Sole crop, All situations;sim;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;TRUE +8;Sole crop, per situation;sim;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;FALSE +9;Sole crop, All situations;sim;FALSE;FALSE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;TRUE 10;Sole crop, Versions, per situation;sim;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE 11;Sole crop, Versions, All situations;sim;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE 12;Sole crop, Versions, shape_sit=txt, All situations;sim;FALSE;TRUE;TRUE;txt;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE From e642740b75397e021e8ac2c69f6571fc3796cf5e Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Fri, 17 Oct 2025 10:08:42 +0200 Subject: [PATCH 054/118] WIP: local changes before pulling --- R/generic_plotting.R | 16 +++++- R/specific_plotting_scatter.R | 87 ++++++++++++++++++++++++++++- man/specific_scatter_plots.Rd | 14 +++++ tests/testthat/test-scatter-plots.R | 1 + 4 files changed, 113 insertions(+), 5 deletions(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index eedf4814..78db83be 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -214,8 +214,20 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, reference_var, is_obs_sd, title = plot_title ), - "non_mixture_versions_situations" = NA, - "non_mixture_versions_per_situations" = NA, + "non_mixture_versions_situations" = + plot_scat_version_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture + ), + "non_mixture_versions_per_situations" = + plot_scat_version_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture + ), "non_mixture_no_versions_situations" = plot_scat_allsit( sim_situation, i, select_scat, shape_sit, diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 711c0798..ecbfb085 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -148,14 +148,13 @@ give_y_var_type <- function(select_scat) { #' @param p A ggplot to modify` #' @param colour_factor The factor to use for colouring the error bars #' @return The modified ggplot -add_obs_error_bars <- function(p, colour_factor) { +add_obs_error_bars <- function(p, colour_factor = NULL) { p <- p + - ggplot2::geom_errorbarh( + ggplot2::geom_linerange( ggplot2::aes( xmin = .data$Observed - 2 * .data$Obs_SD, xmax = .data$Observed + 2 * .data$Obs_SD, colour = .data[[colour_factor]], - height = 0 ), na.rm = TRUE ) @@ -282,6 +281,88 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ggplot2::scale_color_discrete(name = "Situation") } + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + + ggplot2::ggtitle(title) + + if (is_obs_sd && reference_var == "Observed") { + p <- p + ggplot2::geom_linerange( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + ), + na.rm = TRUE + ) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + if (shape_sit == "txt") { + p <- p + + ggrepel::geom_text_repel( + ggplot2::aes( + label = .data$sit_name + ), + max.overlaps = 100 + ) + } + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" && reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + if (several_sit == FALSE && one_version == TRUE && mixture == FALSE) { + p <- p + ggplot2::theme(legend.position = "none") + } + + return(p) +} + + +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_version_allsit <- function(df_data, sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL, + several_sit=FALSE,one_version = FALSE, + mixture = FALSE) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + print(head(df_data)) + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) #, colour = .data$version) + ) + + if (shape_sit == "none" || shape_sit == "txt") { + p <- p + ggplot2::geom_point(na.rm = TRUE) + } else if (shape_sit == "symbol" || shape_sit == "group") { + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(paste(.data$sit_name)) + ), + na.rm = TRUE + ) + + ggplot2::scale_color_discrete(name = "Situation") + } + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd index 9c142db4..65eaadd4 100644 --- a/man/specific_scatter_plots.Rd +++ b/man/specific_scatter_plots.Rd @@ -7,6 +7,7 @@ \alias{add_obs_error_bars} \alias{plot_scat_mixture_allsit} \alias{plot_scat_allsit} +\alias{plot_scat_version_allsit} \title{Specific functions to generate scatter plots} \usage{ compute_axis_bounds(df_data, reference_var, y_var_type, is_obs_sd) @@ -37,6 +38,19 @@ plot_scat_allsit( one_version = FALSE, mixture = FALSE ) + +plot_scat_version_allsit( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL, + several_sit = FALSE, + one_version = FALSE, + mixture = FALSE +) } \arguments{ \item{df_data}{A named list of data frame including the data to plot (one df diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index a54bb2ce..7ba6f19b 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -194,6 +194,7 @@ test_that("Extract plots of one variable", { # Test labels of ggplot in function of the case (see doc/aesthetics_scatter.xlsx) ## Read the file describing the configurations and results of the tests + tmp <- read.csv( file = "_inputs/tests_scatter_plots.csv", header = TRUE, sep = ";", stringsAsFactors = FALSE From a692b6570138c9abef39022d822b0061f774da58 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Fri, 17 Oct 2025 11:18:31 +0200 Subject: [PATCH 055/118] update generic plotting --- R/generic_plotting.R | 196 ++++++++++++++++++++++--------------------- 1 file changed, 99 insertions(+), 97 deletions(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 78db83be..ccddb899 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -76,7 +76,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, all_situations, overlap, successive, shape_sit, situation_group, reference_var, force, verbose ) - + dot_args <- args_list$dot_args obs <- args_list$obs obs_sd <- args_list$obs_sd @@ -99,15 +99,15 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, common_situations_models <- args_list$common_situations_models is_obs <- args_list$is_obs is_obs_sd <- args_list$is_obs_sd - + situations_outputs <- cat_with_situation( dot_args, obs, obs_sd, all_situations, v_names ) - + sim <- situations_outputs$sim obs <- situations_outputs$obs obs_sd <- situations_outputs$obs_sd - + # Testing if the obs and sim have the same plants names: if (is_obs && !is.null(obs$Plant) && !is.null(sim$Plant)) { common_crops <- unique(sim$Plant) %in% unique(obs$Plant) @@ -118,7 +118,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, )) } } - + formated_situation_list <- lapply( common_situations_models, function(x) { @@ -135,17 +135,17 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, var, overlap, situation_group, type, shape_sit, several_sit, length(dot_args) ) - + if ( is.null(df_sit) || + ( + is.null(df_sit$Observed) && ( - is.null(df_sit$Observed) && - ( - type == "scatter" || - select_dyn == "common" || - select_dyn == "obs" - ) + type == "scatter" || + select_dyn == "common" || + select_dyn == "obs" ) + ) ) { # No common observations and simulations when type=="scatter" or # select_dyn=="common" or select_dyn=="obs" @@ -161,13 +161,13 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, stop("No observations found for situation ", unique(df_sit$sit_name)) } } - + df_sit } ) - + names(formated_situation_list) <- common_situations_models - + p <- list() for (i in common_situations_models) { sim_situation <- formated_situation_list[[i]] @@ -175,7 +175,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, item_case <- detect_item_case( type, mixture, one_version, several_sit, overlap ) - + plot_title <- if (!is.null(title)) { title[[i]] } else if (type == "scatter" && all_situations == TRUE) { @@ -183,70 +183,72 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, } else { i } - p[[i]] <- switch(item_case, - # Dynamic plots: - "mixture_versions_overlap" = - plot_dynamic_mixture_versions_overlap(sim_situation, i, - title = plot_title - ), - "mixture_versions_no_overlap" = - plot_dynamic_mixture_versions(sim_situation, i, title = plot_title), - "mixture_no_versions_overlap" = - plot_dynamic_mixture_overlap(sim_situation, i, title = plot_title), - "mixture_no_versions_no_overlap" = plot_dynamic_mixture(sim_situation, i, - title = plot_title - ), - "non_mixture_versions_overlap" = - plot_dynamic_versions_overlap(sim_situation, i, title = plot_title), - "non_mixture_versions_no_overlap" = - plot_dynamic_versions(sim_situation, i, title = plot_title), - "non_mixture_no_versions_overlap" = - plot_dynamic_overlap(sim_situation, i, title = plot_title), - "non_mixture_no_versions_no_overlap" = - plot_dynamic(sim_situation, i, successive, title = plot_title), - # Scatter plots: - "mixture_versions_situations" = NA, - "mixture_versions_per_situations" = NA, - "mixture_no_versions" = - plot_scat_mixture_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), - "non_mixture_versions_situations" = - plot_scat_version_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ), - "non_mixture_versions_per_situations" = - plot_scat_version_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ), - "non_mixture_no_versions_situations" = - plot_scat_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ), - "non_mixture_no_versions_per_situations" = - plot_scat_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ) + p[[i]] <- switch(item_case, + # Dynamic plots: + "mixture_versions_overlap" = + plot_dynamic_mixture_versions_overlap(sim_situation, i, + title = plot_title + ), + "mixture_versions_no_overlap" = + plot_dynamic_mixture_versions(sim_situation, i, title = plot_title), + "mixture_no_versions_overlap" = + plot_dynamic_mixture_overlap(sim_situation, i, title = plot_title), + "mixture_no_versions_no_overlap" = plot_dynamic_mixture(sim_situation, i, + title = plot_title + ), + "non_mixture_versions_overlap" = + plot_dynamic_versions_overlap(sim_situation, i, title = plot_title), + "non_mixture_versions_no_overlap" = + plot_dynamic_versions(sim_situation, i, title = plot_title), + "non_mixture_no_versions_overlap" = + plot_dynamic_overlap(sim_situation, i, title = plot_title), + "non_mixture_no_versions_no_overlap" = + plot_dynamic(sim_situation, i, successive, title = plot_title), + + # Scatter plots: + "mixture_versions" = plot_scat_mixture_versions( # per sit and all sit share the same call + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "mixture_no_versions" = # per sit and all sit share the same call + plot_scat_mixture_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_versions_situations" = + plot_scat_versions_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_versions_per_situations" = + plot_scat_versions_per_sit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_no_versions_situations" = + plot_scat_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture + ), + "non_mixture_no_versions_per_situations" = + plot_scat_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture + ) ) } - + names(p) <- common_situations_models - + return(p) } @@ -310,25 +312,25 @@ plot.statistics <- function(x, xvar = c("group", "situation"), xvar <- match.arg(xvar, c("group", "situation")) type <- match.arg(type, c("bar", "radar")) group_bar <- match.arg(group_bar, c("rows", "stack", "dodge")) - + is_one_group <- length(unique(x$group)) == 1 # test if there is one group only is_all_situations <- unique(unique(x$situation) == "all_situations") # test if there are all situations - + nvar <- length(unique(x$variable)) - + x <- x %>% reshape2::melt( id.vars = c("group", "situation", "variable"), variable.name = "statistic" ) - + if (type == "bar") { if (is.null(title)) { title <- "" } - + if (xvar == "group") { filling <- quote(.data$situation) xvariable <- quote(.data$group) @@ -346,7 +348,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), showlegend <- length(unique(x$statistic)) > 1 } } - + if (group_bar == "rows") { x <- x %>% @@ -366,36 +368,36 @@ plot.statistics <- function(x, xvar = c("group", "situation"), cols = ggplot2::vars(.data$variable), scales = "free" ) + ggplot2::geom_col(ggplot2::aes(fill = .data$statistic), - position = group_bar + position = group_bar ) + ggplot2::ggtitle(title) } - + # Rotate variable names if too many variables if (nvar > 8) { x <- x + ggplot2::theme(strip.text.x = ggplot2::element_text(angle = 90)) } - + # Rotate situation names if they are on x-axis if (xvar == "situation" || (group_bar == "stack" && xvar == "situation")) { x <- x + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90)) } - + if (!showlegend) { x <- x + ggplot2::guides(fill = "none") } - + # No need to label x-axis if only one value if ((xvar == "situation" && is_all_situations) || - (xvar == "group" && is_one_group)) { + (xvar == "group" && is_one_group)) { x <- x + ggplot2::xlab("") + ggplot2::theme(axis.text.x = ggplot2::element_blank()) + ggplot2::theme(axis.ticks.x = ggplot2::element_blank()) } - + # No need to label rows if only one if (group_bar != "rows" && ((xvar == "group" && is_all_situations) || - (xvar == "situation" && is_one_group))) { + (xvar == "situation" && is_one_group))) { x <- x + ggplot2::theme(strip.text.y = ggplot2::element_blank()) } } else { @@ -409,10 +411,10 @@ plot.statistics <- function(x, xvar = c("group", "situation"), stop("No statistical criteria to plot. Use `force = TRUE` to avoid this error.") } } - + x <- x %>% dplyr::filter(.data$statistic == crit_radar) # v_names <- unique(x$group) - + x <- x %>% ggplot2::ggplot(ggplot2::aes( @@ -431,12 +433,12 @@ plot.statistics <- function(x, xvar = c("group", "situation"), }) + ggplot2::scale_x_discrete() + ggplot2::ggproto("CoordRadar", - ggplot2::CoordPolar, - theta = "x", r = "y", start = -pi / 6, - direction = sign(1), is_linear = function(coord) TRUE + ggplot2::CoordPolar, + theta = "x", r = "y", start = -pi / 6, + direction = sign(1), is_linear = function(coord) TRUE ) } - - + + x } From 9f43b80beea3bbbe4851e60799168444bbd9c5a9 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Fri, 17 Oct 2025 11:40:22 +0200 Subject: [PATCH 056/118] update plotting scatter --- R/specific_plotting_scatter.R | 205 ++++++++++++++++++++++++---------- 1 file changed, 145 insertions(+), 60 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 0e24f6bf..33468f7b 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -48,7 +48,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_max <- df_max[[reference_var]] + 0.05 * df_max[[reference_var]] yaxis_min <- df_min[[y_var_type]] - 0.05 * df_min[[y_var_type]] yaxis_max <- df_max[[y_var_type]] + 0.05 * df_max[[y_var_type]] - + if (is_obs_sd && reference_var == "Observed") { # Update xaxis min and max in case of addition of error bars df_min <- df_data %>% @@ -62,7 +62,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_min <- df_min[["barmin"]] - 0.05 * df_min[["barmin"]] xaxis_max <- df_max[["barmax"]] + 0.05 * df_max[["barmax"]] } - + return(list( xaxis_min = xaxis_min, xaxis_max = xaxis_max, yaxis_min = yaxis_min, yaxis_max = yaxis_max @@ -169,17 +169,17 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( @@ -197,7 +197,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::scale_shape_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -210,19 +210,19 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$Dominance, ":", p$data$Plant)) p <- add_obs_error_bars(p, - colour_factor = "colour_factor" + colour_factor = "colour_factor" ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -234,14 +234,14 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + p <- p + ggplot2::scale_color_discrete(name = "Plant") - + return(p) } @@ -254,17 +254,17 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( @@ -289,7 +289,7 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::labs(color = "Version", shape = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -302,9 +302,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( @@ -316,9 +316,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -330,12 +330,12 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + return(p) } @@ -353,13 +353,13 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point(na.rm = TRUE) } else if (shape_sit == "symbol" || shape_sit == "group") { @@ -371,7 +371,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::scale_color_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -384,10 +384,10 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( ggplot2::aes( @@ -397,9 +397,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -409,7 +409,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) @@ -417,43 +417,125 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, if (several_sit == FALSE && one_version == TRUE && mixture == FALSE) { p <- p + ggplot2::theme(legend.position = "none") } - + return(p) } + + + + + #' @keywords internal #' @rdname specific_scatter_plots -plot_scat_version_allsit <- function(df_data, sit, select_scat, shape_sit, - reference_var, is_obs_sd, title = NULL, - several_sit=FALSE,one_version = FALSE, - mixture = FALSE) { +plot_scat_versions_per_sit <- function(df_data, + sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { tmp <- give_reference_var(reference_var) reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - print(head(df_data)) + p <- ggplot2::ggplot( df_data, - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) #, colour = .data$version) + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) + + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(.data$version) + ), + na.rm = TRUE + ) + + ggplot2::labs(color = "Version") + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + ggplot2::ggtitle(title) + + if (is_obs_sd && reference_var == "Observed") { + p <- p + + ggplot2::geom_linerange( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + colour = as.factor(.data$version), + ), + na.rm = TRUE + ) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" && reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + + return(p) +} + +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_versions_allsit <- function(df_data, + sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ) + if (shape_sit == "none" || shape_sit == "txt") { - p <- p + ggplot2::geom_point(na.rm = TRUE) + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(.data$version) + ), + na.rm = TRUE + ) + + ggplot2::labs(color = "Version") } else if (shape_sit == "symbol" || shape_sit == "group") { + # ! In this case we loose the colour by species for mixtures, because + # there would be three aesthetics to handle (situation, version and + # species). We made this decision because the user explicitly asks + # for shape to be the situation name. If they want to color by species, + # they can put shape_sit = "none" or shape_sit = "txt" to have it all. p <- p + ggplot2::geom_point( ggplot2::aes( - colour = as.factor(paste(.data$sit_name)) + colour = as.factor(.data$version), + shape = as.factor(.data$sit_name) ), na.rm = TRUE ) + - ggplot2::scale_color_discrete(name = "Situation") + ggplot2::labs(color = "Version", shape = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -466,36 +548,39 @@ plot_scat_version_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - - p <- p + - ggplot2::ggtitle(title) - + + p <- p + ggplot2::ggtitle(title) + if (is_obs_sd && reference_var == "Observed") { - p$data$colour_factor <- as.factor(paste(p$data$sit_name)) - p <- add_obs_error_bars(p, - colour_factor = "colour_factor" - ) + p <- p + + ggplot2::geom_linerange( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + colour = as.factor(.data$version), + ), + na.rm = TRUE + ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( ggplot2::aes( - label = .data$sit_name + label = .data$sit_name, + colour = as.factor(.data$version) ), + show.legend = FALSE, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - if (several_sit == FALSE && one_version == TRUE && mixture == FALSE) { - p <- p + ggplot2::theme(legend.position = "none") - } - + return(p) -} +} \ No newline at end of file From 0890578129ad010d6a28eae259124bfd2283f3d5 Mon Sep 17 00:00:00 2001 From: Cyrille MIDINGOYI <34443570+cyrillemidingoyi@users.noreply.github.com> Date: Fri, 17 Oct 2025 11:51:30 +0200 Subject: [PATCH 057/118] update scatter plot with non mixture version (#93) * update csv file * WIP: local changes before pulling * update generic plotting * update plotting scatter --- R/generic_plotting.R | 188 ++++++++++++----------- R/specific_plotting_scatter.R | 228 ++++++++++++++++++++++++---- man/specific_scatter_plots.Rd | 14 ++ tests/testthat/test-scatter-plots.R | 1 + 4 files changed, 310 insertions(+), 121 deletions(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index cc87a2bb..ccddb899 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -76,7 +76,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, all_situations, overlap, successive, shape_sit, situation_group, reference_var, force, verbose ) - + dot_args <- args_list$dot_args obs <- args_list$obs obs_sd <- args_list$obs_sd @@ -99,15 +99,15 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, common_situations_models <- args_list$common_situations_models is_obs <- args_list$is_obs is_obs_sd <- args_list$is_obs_sd - + situations_outputs <- cat_with_situation( dot_args, obs, obs_sd, all_situations, v_names ) - + sim <- situations_outputs$sim obs <- situations_outputs$obs obs_sd <- situations_outputs$obs_sd - + # Testing if the obs and sim have the same plants names: if (is_obs && !is.null(obs$Plant) && !is.null(sim$Plant)) { common_crops <- unique(sim$Plant) %in% unique(obs$Plant) @@ -118,7 +118,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, )) } } - + formated_situation_list <- lapply( common_situations_models, function(x) { @@ -135,17 +135,17 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, var, overlap, situation_group, type, shape_sit, several_sit, length(dot_args) ) - + if ( is.null(df_sit) || + ( + is.null(df_sit$Observed) && ( - is.null(df_sit$Observed) && - ( - type == "scatter" || - select_dyn == "common" || - select_dyn == "obs" - ) + type == "scatter" || + select_dyn == "common" || + select_dyn == "obs" ) + ) ) { # No common observations and simulations when type=="scatter" or # select_dyn=="common" or select_dyn=="obs" @@ -161,13 +161,13 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, stop("No observations found for situation ", unique(df_sit$sit_name)) } } - + df_sit } ) - + names(formated_situation_list) <- common_situations_models - + p <- list() for (i in common_situations_models) { sim_situation <- formated_situation_list[[i]] @@ -175,7 +175,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, item_case <- detect_item_case( type, mixture, one_version, several_sit, overlap ) - + plot_title <- if (!is.null(title)) { title[[i]] } else if (type == "scatter" && all_situations == TRUE) { @@ -183,62 +183,72 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, } else { i } - print(item_case) - p[[i]] <- switch(item_case, - # Dynamic plots: - "mixture_versions_overlap" = - plot_dynamic_mixture_versions_overlap(sim_situation, i, - title = plot_title - ), - "mixture_versions_no_overlap" = - plot_dynamic_mixture_versions(sim_situation, i, title = plot_title), - "mixture_no_versions_overlap" = - plot_dynamic_mixture_overlap(sim_situation, i, title = plot_title), - "mixture_no_versions_no_overlap" = plot_dynamic_mixture(sim_situation, i, - title = plot_title - ), - "non_mixture_versions_overlap" = - plot_dynamic_versions_overlap(sim_situation, i, title = plot_title), - "non_mixture_versions_no_overlap" = - plot_dynamic_versions(sim_situation, i, title = plot_title), - "non_mixture_no_versions_overlap" = - plot_dynamic_overlap(sim_situation, i, title = plot_title), - "non_mixture_no_versions_no_overlap" = - plot_dynamic(sim_situation, i, successive, title = plot_title), - # Scatter plots: - "mixture_versions" = plot_scat_mixture_versions( # per sit and all sit share the same call - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), - "mixture_no_versions" = # per sit and all sit share the same call - plot_scat_mixture_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), - "non_mixture_versions_situations" = NA, - "non_mixture_versions_per_situations" = NA, - "non_mixture_no_versions_situations" = - plot_scat_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ), - "non_mixture_no_versions_per_situations" = - plot_scat_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ) + p[[i]] <- switch(item_case, + # Dynamic plots: + "mixture_versions_overlap" = + plot_dynamic_mixture_versions_overlap(sim_situation, i, + title = plot_title + ), + "mixture_versions_no_overlap" = + plot_dynamic_mixture_versions(sim_situation, i, title = plot_title), + "mixture_no_versions_overlap" = + plot_dynamic_mixture_overlap(sim_situation, i, title = plot_title), + "mixture_no_versions_no_overlap" = plot_dynamic_mixture(sim_situation, i, + title = plot_title + ), + "non_mixture_versions_overlap" = + plot_dynamic_versions_overlap(sim_situation, i, title = plot_title), + "non_mixture_versions_no_overlap" = + plot_dynamic_versions(sim_situation, i, title = plot_title), + "non_mixture_no_versions_overlap" = + plot_dynamic_overlap(sim_situation, i, title = plot_title), + "non_mixture_no_versions_no_overlap" = + plot_dynamic(sim_situation, i, successive, title = plot_title), + + # Scatter plots: + "mixture_versions" = plot_scat_mixture_versions( # per sit and all sit share the same call + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "mixture_no_versions" = # per sit and all sit share the same call + plot_scat_mixture_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_versions_situations" = + plot_scat_versions_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_versions_per_situations" = + plot_scat_versions_per_sit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_no_versions_situations" = + plot_scat_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture + ), + "non_mixture_no_versions_per_situations" = + plot_scat_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, several_sit = several_sit, + one_version = one_version, mixture = mixture + ) ) } - + names(p) <- common_situations_models - + return(p) } @@ -302,25 +312,25 @@ plot.statistics <- function(x, xvar = c("group", "situation"), xvar <- match.arg(xvar, c("group", "situation")) type <- match.arg(type, c("bar", "radar")) group_bar <- match.arg(group_bar, c("rows", "stack", "dodge")) - + is_one_group <- length(unique(x$group)) == 1 # test if there is one group only is_all_situations <- unique(unique(x$situation) == "all_situations") # test if there are all situations - + nvar <- length(unique(x$variable)) - + x <- x %>% reshape2::melt( id.vars = c("group", "situation", "variable"), variable.name = "statistic" ) - + if (type == "bar") { if (is.null(title)) { title <- "" } - + if (xvar == "group") { filling <- quote(.data$situation) xvariable <- quote(.data$group) @@ -338,7 +348,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), showlegend <- length(unique(x$statistic)) > 1 } } - + if (group_bar == "rows") { x <- x %>% @@ -358,36 +368,36 @@ plot.statistics <- function(x, xvar = c("group", "situation"), cols = ggplot2::vars(.data$variable), scales = "free" ) + ggplot2::geom_col(ggplot2::aes(fill = .data$statistic), - position = group_bar + position = group_bar ) + ggplot2::ggtitle(title) } - + # Rotate variable names if too many variables if (nvar > 8) { x <- x + ggplot2::theme(strip.text.x = ggplot2::element_text(angle = 90)) } - + # Rotate situation names if they are on x-axis if (xvar == "situation" || (group_bar == "stack" && xvar == "situation")) { x <- x + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90)) } - + if (!showlegend) { x <- x + ggplot2::guides(fill = "none") } - + # No need to label x-axis if only one value if ((xvar == "situation" && is_all_situations) || - (xvar == "group" && is_one_group)) { + (xvar == "group" && is_one_group)) { x <- x + ggplot2::xlab("") + ggplot2::theme(axis.text.x = ggplot2::element_blank()) + ggplot2::theme(axis.ticks.x = ggplot2::element_blank()) } - + # No need to label rows if only one if (group_bar != "rows" && ((xvar == "group" && is_all_situations) || - (xvar == "situation" && is_one_group))) { + (xvar == "situation" && is_one_group))) { x <- x + ggplot2::theme(strip.text.y = ggplot2::element_blank()) } } else { @@ -401,10 +411,10 @@ plot.statistics <- function(x, xvar = c("group", "situation"), stop("No statistical criteria to plot. Use `force = TRUE` to avoid this error.") } } - + x <- x %>% dplyr::filter(.data$statistic == crit_radar) # v_names <- unique(x$group) - + x <- x %>% ggplot2::ggplot(ggplot2::aes( @@ -423,12 +433,12 @@ plot.statistics <- function(x, xvar = c("group", "situation"), }) + ggplot2::scale_x_discrete() + ggplot2::ggproto("CoordRadar", - ggplot2::CoordPolar, - theta = "x", r = "y", start = -pi / 6, - direction = sign(1), is_linear = function(coord) TRUE + ggplot2::CoordPolar, + theta = "x", r = "y", start = -pi / 6, + direction = sign(1), is_linear = function(coord) TRUE ) } - - + + x } diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 81f4e147..33468f7b 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -48,7 +48,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_max <- df_max[[reference_var]] + 0.05 * df_max[[reference_var]] yaxis_min <- df_min[[y_var_type]] - 0.05 * df_min[[y_var_type]] yaxis_max <- df_max[[y_var_type]] + 0.05 * df_max[[y_var_type]] - + if (is_obs_sd && reference_var == "Observed") { # Update xaxis min and max in case of addition of error bars df_min <- df_data %>% @@ -62,7 +62,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_min <- df_min[["barmin"]] - 0.05 * df_min[["barmin"]] xaxis_max <- df_max[["barmax"]] + 0.05 * df_max[["barmax"]] } - + return(list( xaxis_min = xaxis_min, xaxis_max = xaxis_max, yaxis_min = yaxis_min, yaxis_max = yaxis_max @@ -169,17 +169,17 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( @@ -197,7 +197,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::scale_shape_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -210,19 +210,19 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$Dominance, ":", p$data$Plant)) p <- add_obs_error_bars(p, - colour_factor = "colour_factor" + colour_factor = "colour_factor" ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -234,14 +234,14 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + p <- p + ggplot2::scale_color_discrete(name = "Plant") - + return(p) } @@ -254,17 +254,17 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( @@ -289,7 +289,7 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::labs(color = "Version", shape = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -302,9 +302,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( @@ -316,9 +316,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -330,12 +330,12 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + return(p) } @@ -353,13 +353,13 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point(na.rm = TRUE) } else if (shape_sit == "symbol" || shape_sit == "group") { @@ -371,7 +371,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::scale_color_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -384,10 +384,10 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( ggplot2::aes( @@ -397,9 +397,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -409,7 +409,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) @@ -417,6 +417,170 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, if (several_sit == FALSE && one_version == TRUE && mixture == FALSE) { p <- p + ggplot2::theme(legend.position = "none") } + + return(p) +} + + + + + + +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_versions_per_sit <- function(df_data, + sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ) + + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(.data$version) + ), + na.rm = TRUE + ) + + ggplot2::labs(color = "Version") + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + ggplot2::ggtitle(title) + + if (is_obs_sd && reference_var == "Observed") { + p <- p + + ggplot2::geom_linerange( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + colour = as.factor(.data$version), + ), + na.rm = TRUE + ) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" && reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + return(p) } + + +#' @keywords internal +#' @rdname specific_scatter_plots +plot_scat_versions_allsit <- function(df_data, + sit, select_scat, shape_sit, + reference_var, is_obs_sd, title = NULL) { + tmp <- give_reference_var(reference_var) + reference_var <- tmp$reference_var + reference_var_name <- tmp$reference_var_name + y_var_type <- give_y_var_type(select_scat) + + df_data <- + df_data %>% + dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) + + p <- + ggplot2::ggplot( + df_data, + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ) + + if (shape_sit == "none" || shape_sit == "txt") { + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(.data$version) + ), + na.rm = TRUE + ) + + ggplot2::labs(color = "Version") + } else if (shape_sit == "symbol" || shape_sit == "group") { + # ! In this case we loose the colour by species for mixtures, because + # there would be three aesthetics to handle (situation, version and + # species). We made this decision because the user explicitly asks + # for shape to be the situation name. If they want to color by species, + # they can put shape_sit = "none" or shape_sit = "txt" to have it all. + p <- p + ggplot2::geom_point( + ggplot2::aes( + colour = as.factor(.data$version), + shape = as.factor(.data$sit_name) + ), + na.rm = TRUE + ) + + ggplot2::labs(color = "Version", shape = "Situation") + } + + p <- p + + ggplot2::geom_abline( + intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), + color = "grey30", linetype = 2 + ) + + ggplot2::geom_smooth( + method = lm, color = "blue", + se = FALSE, linewidth = 0.6, formula = y ~ x, + fullrange = TRUE, na.rm = TRUE + ) + + ggplot2::xlab(reference_var_name) + + ggplot2::facet_wrap(~variable, scales = "free") + + p <- p + ggplot2::ggtitle(title) + + if (is_obs_sd && reference_var == "Observed") { + p <- p + + ggplot2::geom_linerange( + ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD, + colour = as.factor(.data$version), + ), + na.rm = TRUE + ) + } + + p <- p + ggplot2::theme(aspect.ratio = 1) + + if (shape_sit == "txt") { + p <- p + + ggrepel::geom_text_repel( + ggplot2::aes( + label = .data$sit_name, + colour = as.factor(.data$version) + ), + show.legend = FALSE, + max.overlaps = 100 + ) + } + + # Set same limits for x and y axis for sim VS obs scatter plots + if (select_scat == "sim" && reference_var == "Observed") { + p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) + } + + return(p) +} \ No newline at end of file diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd index 9c142db4..65eaadd4 100644 --- a/man/specific_scatter_plots.Rd +++ b/man/specific_scatter_plots.Rd @@ -7,6 +7,7 @@ \alias{add_obs_error_bars} \alias{plot_scat_mixture_allsit} \alias{plot_scat_allsit} +\alias{plot_scat_version_allsit} \title{Specific functions to generate scatter plots} \usage{ compute_axis_bounds(df_data, reference_var, y_var_type, is_obs_sd) @@ -37,6 +38,19 @@ plot_scat_allsit( one_version = FALSE, mixture = FALSE ) + +plot_scat_version_allsit( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL, + several_sit = FALSE, + one_version = FALSE, + mixture = FALSE +) } \arguments{ \item{df_data}{A named list of data frame including the data to plot (one df diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index 03a73c82..b6dd8961 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -198,6 +198,7 @@ test_that("Extract plots of one variable", { # Test labels of ggplot in function of the case (see doc/aesthetics_scatter.xlsx) ## Read the file describing the configurations and results of the tests + tmp <- read.csv( file = "_inputs/tests_scatter_plots.csv", header = TRUE, sep = ";", stringsAsFactors = FALSE From 61ea4e10fb326c08e1bba1519996cb7ad6fb118c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Fri, 17 Oct 2025 14:53:01 +0200 Subject: [PATCH 058/118] Fix #91 --- R/aesthetics.R | 12 +- R/aesthetics_scatter.R | 6 +- R/generic_formatting.R | 10 +- R/generic_plotting.R | 202 +++++++++++------------ R/parse_plot_situations_arguments.R | 12 +- R/specific_plotting_scatter.R | 114 +++++++------ tests/testthat/test-generic_formatting.R | 2 +- 7 files changed, 185 insertions(+), 173 deletions(-) diff --git a/R/aesthetics.R b/R/aesthetics.R index 0e5af4a9..50358e0e 100644 --- a/R/aesthetics.R +++ b/R/aesthetics.R @@ -90,13 +90,13 @@ detect_mixture_version_overlap <- function(is_mixture, one_version, overlap) { #' #' @param is_mixture A logical value indicating whether the crop is a mixture or not. #' @param one_version A logical value indicating whether the plot has one or multiple versions (e.g. of the model). -#' @param several_sit A logical value indicating whether there are one or several situations to plot. +#' @param has_distinct_situations A logical value indicating whether there are one or several situations to plot. #' #' @return A character string indicating the case for computing the aesthetics of the plot. #' #' @keywords internal -detect_mixture_version_situations <- function(is_mixture, one_version, several_sit) { - case <- switch(paste(is_mixture, !one_version, several_sit), +detect_mixture_version_situations <- function(is_mixture, one_version, has_distinct_situations) { + case <- switch(paste(is_mixture, !one_version, has_distinct_situations), "TRUE TRUE TRUE" = "mixture_versions", "TRUE TRUE FALSE" = "mixture_versions", "TRUE FALSE TRUE" = "mixture_no_versions", @@ -121,17 +121,17 @@ detect_mixture_version_situations <- function(is_mixture, one_version, several_s #' @param type The type of plot required, either 'dynamic' or 'scatter #' @param is_mixture A logical value indicating whether the crop is a mixture or not. #' @param one_version A logical value indicating whether the plot has one or multiple versions (e.g. of the model). -#' @param several_sit A logical value indicating whether there are one or several situations to plot. +#' @param has_distinct_situations A logical value indicating whether there are one or several situations to plot. #' @param overlap A logical value indicating whether there is any overlapping variables in the plot. #' #' @return A unique character string for the plot. #' #' @keywords internal -detect_item_case <- function(type, is_mixture, one_version, several_sit, overlap) { +detect_item_case <- function(type, is_mixture, one_version, has_distinct_situations, overlap) { if (type == "dynamic") { item_case <- detect_mixture_version_overlap(is_mixture, one_version, overlap) } else if (type == "scatter") { - item_case <- detect_mixture_version_situations(is_mixture, one_version, several_sit) + item_case <- detect_mixture_version_situations(is_mixture, one_version, has_distinct_situations) } else { stop("type must be either 'dynamic' or 'scatter'") } diff --git a/R/aesthetics_scatter.R b/R/aesthetics_scatter.R index 3fb690aa..3ba255a2 100644 --- a/R/aesthetics_scatter.R +++ b/R/aesthetics_scatter.R @@ -7,7 +7,7 @@ #' @param aesthetics Template aesthetics list #' @param overlap A list of lists containing the variables to represent on the #' same graph when `type = "dynamic"` -#' @param several_sit Boolean. Must be equal to `TRUE` if sim and obs gather +#' @param has_distinct_situations Boolean. Must be equal to `TRUE` if sim and obs gather #' more than one situation and if situations should be differentiated #' on the graph. #' @param one_version Boolean. Must be `TRUE` if several versions will be @@ -22,11 +22,11 @@ #' @keywords internal #' aesthetics_scatter <- function(sim, aesthetics = template_aesthetics(), - overlap = NULL, several_sit = FALSE, + overlap = NULL, has_distinct_situations = FALSE, one_version = TRUE, iversion = 1, dot_args = NULL, is_mixture = FALSE) { # Define the cases using switch - item_case <- detect_mixture_version_situations(is_mixture, one_version, several_sit) + item_case <- detect_mixture_version_situations(is_mixture, one_version, has_distinct_situations) # Manage the aesthetics according to the case: if (item_case == "mixture_no_versions_no_situations") { diff --git a/R/generic_formatting.R b/R/generic_formatting.R index e6275891..a3058b0e 100644 --- a/R/generic_formatting.R +++ b/R/generic_formatting.R @@ -12,7 +12,7 @@ #' scatter). #' @param shape_sit A logical value indicating whether the shape should be #' based on the situation. -#' @param several_sit A logical value indicating whether there are several +#' @param has_distinct_situations A logical value indicating whether there are several #' situations to plot. #' @param total_vers An integer indicating the total number of versions. #' @@ -22,7 +22,7 @@ #' characteristics to plot. #' @keywords internal #' -generic_formatting <- function(df, var, overlap, situation_group, type, shape_sit, several_sit, total_vers) { +generic_formatting <- function(df, var, overlap, situation_group, type, shape_sit, has_distinct_situations, total_vers) { # Filter selected variables if (!is.null(var)) { var <- unique(c(var, subst_parenth(var))) @@ -80,7 +80,7 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si # Change sit_name column with names of situation # groups if shape_sit=="group" - if (several_sit && shape_sit == "group" && !is.null(situation_group)) { + if (has_distinct_situations && shape_sit == "group" && !is.null(situation_group)) { for (grp in seq_along(situation_group)) { sits <- situation_group[[grp]] if (!is.null(names(situation_group))) { @@ -109,9 +109,9 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si ) ) } - # NB: several_sit means one plot for all situation (or successive) and shape + # NB: has_distinct_situations means one plot for all situation (or successive) and shape # is symbol or group - if (type == "scatter" && several_sit && (total_vers > 1) && + if (type == "scatter" && has_distinct_situations && (total_vers > 1) && ("Plant" %in% colnames(df))) { df <- dplyr::bind_cols( diff --git a/R/generic_plotting.R b/R/generic_plotting.R index ccddb899..69755801 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -76,7 +76,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, all_situations, overlap, successive, shape_sit, situation_group, reference_var, force, verbose ) - + dot_args <- args_list$dot_args obs <- args_list$obs obs_sd <- args_list$obs_sd @@ -95,19 +95,19 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, verbose <- args_list$verbose v_names <- args_list$v_names one_version <- args_list$one_version - several_sit <- args_list$several_sit + has_distinct_situations <- args_list$has_distinct_situations common_situations_models <- args_list$common_situations_models is_obs <- args_list$is_obs is_obs_sd <- args_list$is_obs_sd - + situations_outputs <- cat_with_situation( dot_args, obs, obs_sd, all_situations, v_names ) - + sim <- situations_outputs$sim obs <- situations_outputs$obs obs_sd <- situations_outputs$obs_sd - + # Testing if the obs and sim have the same plants names: if (is_obs && !is.null(obs$Plant) && !is.null(sim$Plant)) { common_crops <- unique(sim$Plant) %in% unique(obs$Plant) @@ -118,7 +118,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, )) } } - + formated_situation_list <- lapply( common_situations_models, function(x) { @@ -133,19 +133,19 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, ) %>% generic_formatting( var, overlap, situation_group, type, shape_sit, - several_sit, length(dot_args) + has_distinct_situations, length(dot_args) ) - + if ( is.null(df_sit) || - ( - is.null(df_sit$Observed) && ( - type == "scatter" || - select_dyn == "common" || - select_dyn == "obs" + is.null(df_sit$Observed) && + ( + type == "scatter" || + select_dyn == "common" || + select_dyn == "obs" + ) ) - ) ) { # No common observations and simulations when type=="scatter" or # select_dyn=="common" or select_dyn=="obs" @@ -161,21 +161,21 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, stop("No observations found for situation ", unique(df_sit$sit_name)) } } - + df_sit } ) - + names(formated_situation_list) <- common_situations_models - + p <- list() for (i in common_situations_models) { sim_situation <- formated_situation_list[[i]] mixture <- detect_mixture(sim_situation) item_case <- detect_item_case( - type, mixture, one_version, several_sit, overlap + type, mixture, one_version, has_distinct_situations, overlap ) - + plot_title <- if (!is.null(title)) { title[[i]] } else if (type == "scatter" && all_situations == TRUE) { @@ -185,70 +185,70 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, } p[[i]] <- switch(item_case, - # Dynamic plots: - "mixture_versions_overlap" = - plot_dynamic_mixture_versions_overlap(sim_situation, i, - title = plot_title - ), - "mixture_versions_no_overlap" = - plot_dynamic_mixture_versions(sim_situation, i, title = plot_title), - "mixture_no_versions_overlap" = - plot_dynamic_mixture_overlap(sim_situation, i, title = plot_title), - "mixture_no_versions_no_overlap" = plot_dynamic_mixture(sim_situation, i, - title = plot_title - ), - "non_mixture_versions_overlap" = - plot_dynamic_versions_overlap(sim_situation, i, title = plot_title), - "non_mixture_versions_no_overlap" = - plot_dynamic_versions(sim_situation, i, title = plot_title), - "non_mixture_no_versions_overlap" = - plot_dynamic_overlap(sim_situation, i, title = plot_title), - "non_mixture_no_versions_no_overlap" = - plot_dynamic(sim_situation, i, successive, title = plot_title), - - # Scatter plots: - "mixture_versions" = plot_scat_mixture_versions( # per sit and all sit share the same call - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), - "mixture_no_versions" = # per sit and all sit share the same call - plot_scat_mixture_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), - "non_mixture_versions_situations" = - plot_scat_versions_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), - "non_mixture_versions_per_situations" = - plot_scat_versions_per_sit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), - "non_mixture_no_versions_situations" = - plot_scat_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ), - "non_mixture_no_versions_per_situations" = - plot_scat_allsit( - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title, several_sit = several_sit, - one_version = one_version, mixture = mixture - ) + # Dynamic plots: + "mixture_versions_overlap" = + plot_dynamic_mixture_versions_overlap(sim_situation, i, + title = plot_title + ), + "mixture_versions_no_overlap" = + plot_dynamic_mixture_versions(sim_situation, i, title = plot_title), + "mixture_no_versions_overlap" = + plot_dynamic_mixture_overlap(sim_situation, i, title = plot_title), + "mixture_no_versions_no_overlap" = plot_dynamic_mixture(sim_situation, i, + title = plot_title + ), + "non_mixture_versions_overlap" = + plot_dynamic_versions_overlap(sim_situation, i, title = plot_title), + "non_mixture_versions_no_overlap" = + plot_dynamic_versions(sim_situation, i, title = plot_title), + "non_mixture_no_versions_overlap" = + plot_dynamic_overlap(sim_situation, i, title = plot_title), + "non_mixture_no_versions_no_overlap" = + plot_dynamic(sim_situation, i, successive, title = plot_title), + + # Scatter plots: + "mixture_versions" = plot_scat_mixture_versions( # per sit and all sit share the same call + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "mixture_no_versions" = # per sit and all sit share the same call + plot_scat_mixture_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_versions_situations" = + plot_scat_versions_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_versions_per_situations" = + plot_scat_versions_per_sit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), + "non_mixture_no_versions_situations" = + plot_scat_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, has_distinct_situations = has_distinct_situations, + one_version = one_version, mixture = mixture + ), + "non_mixture_no_versions_per_situations" = + plot_scat_allsit( + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title, has_distinct_situations = has_distinct_situations, + one_version = one_version, mixture = mixture + ) ) } - + names(p) <- common_situations_models - + return(p) } @@ -312,25 +312,25 @@ plot.statistics <- function(x, xvar = c("group", "situation"), xvar <- match.arg(xvar, c("group", "situation")) type <- match.arg(type, c("bar", "radar")) group_bar <- match.arg(group_bar, c("rows", "stack", "dodge")) - + is_one_group <- length(unique(x$group)) == 1 # test if there is one group only is_all_situations <- unique(unique(x$situation) == "all_situations") # test if there are all situations - + nvar <- length(unique(x$variable)) - + x <- x %>% reshape2::melt( id.vars = c("group", "situation", "variable"), variable.name = "statistic" ) - + if (type == "bar") { if (is.null(title)) { title <- "" } - + if (xvar == "group") { filling <- quote(.data$situation) xvariable <- quote(.data$group) @@ -348,7 +348,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), showlegend <- length(unique(x$statistic)) > 1 } } - + if (group_bar == "rows") { x <- x %>% @@ -368,36 +368,36 @@ plot.statistics <- function(x, xvar = c("group", "situation"), cols = ggplot2::vars(.data$variable), scales = "free" ) + ggplot2::geom_col(ggplot2::aes(fill = .data$statistic), - position = group_bar + position = group_bar ) + ggplot2::ggtitle(title) } - + # Rotate variable names if too many variables if (nvar > 8) { x <- x + ggplot2::theme(strip.text.x = ggplot2::element_text(angle = 90)) } - + # Rotate situation names if they are on x-axis if (xvar == "situation" || (group_bar == "stack" && xvar == "situation")) { x <- x + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90)) } - + if (!showlegend) { x <- x + ggplot2::guides(fill = "none") } - + # No need to label x-axis if only one value if ((xvar == "situation" && is_all_situations) || - (xvar == "group" && is_one_group)) { + (xvar == "group" && is_one_group)) { x <- x + ggplot2::xlab("") + ggplot2::theme(axis.text.x = ggplot2::element_blank()) + ggplot2::theme(axis.ticks.x = ggplot2::element_blank()) } - + # No need to label rows if only one if (group_bar != "rows" && ((xvar == "group" && is_all_situations) || - (xvar == "situation" && is_one_group))) { + (xvar == "situation" && is_one_group))) { x <- x + ggplot2::theme(strip.text.y = ggplot2::element_blank()) } } else { @@ -411,10 +411,10 @@ plot.statistics <- function(x, xvar = c("group", "situation"), stop("No statistical criteria to plot. Use `force = TRUE` to avoid this error.") } } - + x <- x %>% dplyr::filter(.data$statistic == crit_radar) # v_names <- unique(x$group) - + x <- x %>% ggplot2::ggplot(ggplot2::aes( @@ -433,12 +433,12 @@ plot.statistics <- function(x, xvar = c("group", "situation"), }) + ggplot2::scale_x_discrete() + ggplot2::ggproto("CoordRadar", - ggplot2::CoordPolar, - theta = "x", r = "y", start = -pi / 6, - direction = sign(1), is_linear = function(coord) TRUE + ggplot2::CoordPolar, + theta = "x", r = "y", start = -pi / 6, + direction = sign(1), is_linear = function(coord) TRUE ) } - - + + x } diff --git a/R/parse_plot_situations_arguments.R b/R/parse_plot_situations_arguments.R index 77eaea1a..1c71c022 100644 --- a/R/parse_plot_situations_arguments.R +++ b/R/parse_plot_situations_arguments.R @@ -98,7 +98,15 @@ parse_plot_situations_args <- function( } } - several_sit <- (all_situations || !is.null(successive)) && + # has_distinct_situations expresses whether, in the plot being built, + # situations are visually distinguished (e.g. by color/shape). + # It is independent from the input 'all_situations' (which controls whether + # we draw one plot per situation or merge in a single plot). + # Examples: + # - Multiple situations but all blended with the same aesthetics -> FALSE + # - Multiple situations with distinct aesthetics (symbol/group) -> TRUE + # - Only one situation -> FALSE + has_distinct_situations <- (all_situations || !is.null(successive)) && shape_sit %in% c("symbol", "group") # Name the models: @@ -191,7 +199,7 @@ parse_plot_situations_args <- function( dot_args = dot_args, v_names = v_names, one_version = one_version, - several_sit = several_sit, + has_distinct_situations = has_distinct_situations, common_situations_models = common_situations_models, is_obs = is_obs, is_obs_sd = is_obs_sd diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 33468f7b..302b3fbb 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -10,7 +10,7 @@ #' @param is_obs_sd TRUE if error standard deviation of observations is provided #' @param mixture TRUE if the plot is for a mixture of crops #' @param one_version TRUE if the plot is for one version -#' @param several_sit TRUE if the plot is for several situations +#' @param has_distinct_situations TRUE if the plot is for several situations #' #' @importFrom rlang .data #' @return A ggplot object @@ -48,7 +48,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_max <- df_max[[reference_var]] + 0.05 * df_max[[reference_var]] yaxis_min <- df_min[[y_var_type]] - 0.05 * df_min[[y_var_type]] yaxis_max <- df_max[[y_var_type]] + 0.05 * df_max[[y_var_type]] - + if (is_obs_sd && reference_var == "Observed") { # Update xaxis min and max in case of addition of error bars df_min <- df_data %>% @@ -62,7 +62,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_min <- df_min[["barmin"]] - 0.05 * df_min[["barmin"]] xaxis_max <- df_max[["barmax"]] + 0.05 * df_max[["barmax"]] } - + return(list( xaxis_min = xaxis_min, xaxis_max = xaxis_max, yaxis_min = yaxis_min, yaxis_max = yaxis_max @@ -169,17 +169,17 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( @@ -197,7 +197,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::scale_shape_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -210,19 +210,19 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$Dominance, ":", p$data$Plant)) p <- add_obs_error_bars(p, - colour_factor = "colour_factor" + colour_factor = "colour_factor" ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -234,14 +234,14 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + p <- p + ggplot2::scale_color_discrete(name = "Plant") - + return(p) } @@ -254,17 +254,17 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( @@ -289,7 +289,7 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::labs(color = "Version", shape = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -302,9 +302,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( @@ -316,9 +316,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -330,12 +330,12 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + return(p) } @@ -344,7 +344,7 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, #' @rdname specific_scatter_plots plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, reference_var, is_obs_sd, title = NULL, - several_sit = FALSE, one_version = FALSE, + has_distinct_situations = FALSE, one_version = FALSE, mixture = FALSE) { tmp <- give_reference_var(reference_var) reference_var <- tmp$reference_var @@ -353,13 +353,13 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point(na.rm = TRUE) } else if (shape_sit == "symbol" || shape_sit == "group") { @@ -371,7 +371,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::scale_color_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -384,10 +384,10 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( ggplot2::aes( @@ -397,9 +397,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -409,15 +409,19 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - if (several_sit == FALSE && one_version == TRUE && mixture == FALSE) { + if ( + has_distinct_situations == FALSE && + one_version == TRUE && + mixture == FALSE + ) { p <- p + ggplot2::theme(legend.position = "none") } - + return(p) } @@ -436,17 +440,17 @@ plot_scat_versions_per_sit <- function(df_data, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + p <- p + ggplot2::geom_point( ggplot2::aes( colour = as.factor(.data$version) @@ -466,9 +470,9 @@ plot_scat_versions_per_sit <- function(df_data, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( @@ -480,14 +484,14 @@ plot_scat_versions_per_sit <- function(df_data, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + return(p) } @@ -501,17 +505,17 @@ plot_scat_versions_allsit <- function(df_data, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( @@ -535,7 +539,7 @@ plot_scat_versions_allsit <- function(df_data, ) + ggplot2::labs(color = "Version", shape = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -548,9 +552,9 @@ plot_scat_versions_allsit <- function(df_data, ) + ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~variable, scales = "free") - + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( @@ -562,9 +566,9 @@ plot_scat_versions_allsit <- function(df_data, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -576,11 +580,11 @@ plot_scat_versions_allsit <- function(df_data, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + return(p) -} \ No newline at end of file +} diff --git a/tests/testthat/test-generic_formatting.R b/tests/testthat/test-generic_formatting.R index 8908d5a7..021875d7 100644 --- a/tests/testthat/test-generic_formatting.R +++ b/tests/testthat/test-generic_formatting.R @@ -37,7 +37,7 @@ df_all <- generic_formatting( args_list$overlap, args_list$situation_group, args_list$type, args_list$shape_sit, - args_list$several_sit, + args_list$has_distinct_situations, 1 ) From 880d46d53b8ed3419e8dce7bd268d438e0aa7544 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Fri, 17 Oct 2025 15:13:59 +0200 Subject: [PATCH 059/118] update test_scatter_csv file --- .../testthat/_inputs/tests_scatter_plots.csv | 46 +++++++++---------- 1 file changed, 23 insertions(+), 23 deletions(-) diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index 2922e398..a363048c 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -6,20 +6,20 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 5;Mixture, shape_sit=txt, All situations;sim;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 6;Mixture, shape_sit=symbol, All situations;sim;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 7;Mixture (shape_sit=group), All situations;sim;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -8;Sole crop, per situation;sim;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;FALSE -9;Sole crop, All situations;sim;FALSE;FALSE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;2;1;1;TRUE;TRUE -10;Sole crop, Versions, per situation;sim;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE -11;Sole crop, Versions, All situations;sim;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -12;Sole crop, Versions, shape_sit=txt, All situations;sim;FALSE;TRUE;TRUE;txt;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE -13;Sole crop, Versions, shape_sit=symbol, All situations;sim;FALSE;TRUE;TRUE;symbol;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -14;Sole crop, Versions (shape_sit=group), All situations;sim;FALSE;TRUE;TRUE;group;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +8;Sole crop, per situation;sim;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +9;Sole crop, All situations;sim;FALSE;FALSE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +10;Sole crop, Versions, per situation;sim;FALSE;TRUE;FALSE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE +11;Sole crop, Versions, All situations;sim;FALSE;TRUE;TRUE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +12;Sole crop, Versions, shape_sit=txt, All situations;sim;FALSE;TRUE;TRUE;txt;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE +13;Sole crop, Versions, shape_sit=symbol, All situations;sim;FALSE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +14;Sole crop, Versions (shape_sit=group), All situations;sim;FALSE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 15;Sole crop, All situations, shape_sit=symbol;sim;FALSE;FALSE;TRUE;symbol;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE 16;Sole crop, All situations, shape_sit=group;sim;FALSE;FALSE;TRUE;group;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE -17;Mixture, versions, per situation;sim;TRUE;TRUE;FALSE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -18;Mixture, versions, All situations;sim;TRUE;TRUE;TRUE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE -19;Mixture, versions, shape_sit=txt, All situations;sim;TRUE;TRUE;TRUE;txt;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -20;Mixture, versions, shape_sit=symbol, All situations;sim;TRUE;TRUE;TRUE;symbol;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;FALSE -21;Mixture, versions, shape_sit=group, All situations;sim;TRUE;TRUE;TRUE;group;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;TRUE +17;Mixture, versions, per situation;sim;TRUE;TRUE;FALSE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +18;Mixture, versions, All situations;sim;TRUE;TRUE;TRUE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE +19;Mixture, versions, shape_sit=txt, All situations;sim;TRUE;TRUE;TRUE;txt;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +20;Mixture, versions, shape_sit=symbol, All situations;sim;TRUE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;FALSE +21;Mixture, versions, shape_sit=group, All situations;sim;TRUE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;TRUE 22;Mixture, per situation, res;res;TRUE;FALSE;FALSE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 23;Mixture, All situations, res;res;TRUE;FALSE;TRUE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 24;Mixture, All situations, reference_var=lai_n_sim, res;res;TRUE;FALSE;TRUE;none;lai_n_sim;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE @@ -29,16 +29,16 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 28;Mixture, shape_sit=symbol, All situations, res;res;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 29;Mixture (shape_sit=group), All situations, res;res;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 30;Sole crop, per situation, res;res;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -31;Sole crop, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -32;Sole crop, Versions, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE -33;Sole crop, Versions, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -34;Sole crop, Versions, shape_sit=txt, All situations, res;res;FALSE;TRUE;TRUE;txt;NULL;NULL;NULL;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE -35;Sole crop, Versions, shape_sit=symbol, All situations, res;res;FALSE;TRUE;TRUE;symbol;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -36;Sole crop, Versions (shape_sit=group), All situations, res;res;FALSE;TRUE;TRUE;group;NULL;NULL;Situation;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE +31;Sole crop, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;Version;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +32;Sole crop, Versions, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE +33;Sole crop, Versions, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +34;Sole crop, Versions, shape_sit=txt, All situations, res;res;FALSE;TRUE;TRUE;txt;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE +35;Sole crop, Versions, shape_sit=symbol, All situations, res;res;FALSE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +36;Sole crop, Versions (shape_sit=group), All situations, res;res;FALSE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 37;Sole crop, All situations, shape_sit=symbol, res;res;FALSE;FALSE;TRUE;symbol;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE 38;Sole crop, All situations, shape_sit=group, res;res;FALSE;FALSE;TRUE;group;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE -39;Mixture, versions, per situation, res;res;TRUE;TRUE;FALSE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -40;Mixture, versions, All situations, res;res;TRUE;TRUE;TRUE;none;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;FALSE -41;Mixture, versions, shape_sit=txt, All situations, res;res;TRUE;TRUE;TRUE;txt;NULL;NULL;Plant;NULL;NULL;Version;NULL;Version;NULL;4;3;1;TRUE;TRUE -42;Mixture, versions, shape_sit=symbol, All situations, res;res;TRUE;TRUE;TRUE;symbol;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;FALSE -43;Mixture, versions, shape_sit=group, All situations, res;res;TRUE;TRUE;TRUE;group;NULL;NULL;NULL;NULL;NULL;Combi;NULL;Version;NULL;4;3;1;TRUE;TRUE +39;Mixture, versions, per situation, res;res;TRUE;TRUE;FALSE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +40;Mixture, versions, All situations, res;res;TRUE;TRUE;TRUE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE +41;Mixture, versions, shape_sit=txt, All situations, res;res;TRUE;TRUE;TRUE;txt;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE +42;Mixture, versions, shape_sit=symbol, All situations, res;res;TRUE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;FALSE +43;Mixture, versions, shape_sit=group, All situations, res;res;TRUE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;TRUE From c7b7e99920951c2bf544fffec1430824be927757 Mon Sep 17 00:00:00 2001 From: Cyrille MIDINGOYI <34443570+cyrillemidingoyi@users.noreply.github.com> Date: Fri, 17 Oct 2025 15:37:57 +0200 Subject: [PATCH 060/118] update test_scatter_csv file (#96) update test_scatter_csv file --- tests/testthat/_inputs/tests_scatter_plots.csv | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index a363048c..7fb8fcd9 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -41,4 +41,4 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 40;Mixture, versions, All situations, res;res;TRUE;TRUE;TRUE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 41;Mixture, versions, shape_sit=txt, All situations, res;res;TRUE;TRUE;TRUE;txt;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE 42;Mixture, versions, shape_sit=symbol, All situations, res;res;TRUE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;FALSE -43;Mixture, versions, shape_sit=group, All situations, res;res;TRUE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;TRUE +43;Mixture, versions, shape_sit=group, All situations, res;res;TRUE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;TRUE \ No newline at end of file From ac32d987620745118329f794c8b48dafa8b4683d Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 10 Dec 2025 14:28:35 +0100 Subject: [PATCH 061/118] Fix warning "Unknown or uninitialised column: Plant Occurs when other models than STICS are used. Due to a misspecified test. Solve SticsRPacks/CroptimizR#75 --- R/cropr_formatting.R | 2 +- R/generic_plotting.R | 80 ++++++++++++++++++++++---------------------- R/generic_stats.R | 2 +- 3 files changed, 42 insertions(+), 42 deletions(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index ba4d6776..8ade52f9 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -76,7 +76,7 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, is_mixture_sim <- detect_mixture(sim) is_mixture_obs <- detect_mixture(obs) - if (is_mixture_obs && is_obs && is.null(obs$Plant)) { + if (is_mixture_obs && is_obs && !("Plant" %in% colnames(obs))) { stop("Detected intercrop from simulation, but the 'Plant' column is missing from the observations.") } diff --git a/R/generic_plotting.R b/R/generic_plotting.R index c08e6a59..d98974c2 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -76,7 +76,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, all_situations, overlap, successive, shape_sit, situation_group, reference_var, force, verbose ) - + dot_args <- args_list$dot_args obs <- args_list$obs obs_sd <- args_list$obs_sd @@ -99,17 +99,17 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, common_situations_models <- args_list$common_situations_models is_obs <- args_list$is_obs is_obs_sd <- args_list$is_obs_sd - + situations_outputs <- cat_with_situation( dot_args, obs, obs_sd, all_situations, v_names ) - + sim <- situations_outputs$sim obs <- situations_outputs$obs obs_sd <- situations_outputs$obs_sd - + # Testing if the obs and sim have the same plants names: - if (is_obs && !is.null(obs$Plant) && !is.null(sim$Plant)) { + if (is_obs && "Plant" %in% colnames(obs) && "Plant" %in% colnames(sim)) { common_crops <- unique(sim$Plant) %in% unique(obs$Plant) if (any(!common_crops)) { cli::cli_alert_warning(paste0( @@ -118,7 +118,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, )) } } - + formated_situation_list <- lapply( common_situations_models, function(x) { @@ -135,17 +135,17 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, var, overlap, situation_group, type, shape_sit, has_distinct_situations, length(dot_args) ) - + if ( is.null(df_sit) || - ( - is.null(df_sit$Observed) && ( - type == "scatter" || - select_dyn == "common" || - select_dyn == "obs" + is.null(df_sit$Observed) && + ( + type == "scatter" || + select_dyn == "common" || + select_dyn == "obs" + ) ) - ) ) { # No common observations and simulations when type=="scatter" or # select_dyn=="common" or select_dyn=="obs" @@ -161,13 +161,13 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, stop("No observations found for situation ", unique(df_sit$sit_name)) } } - + df_sit } ) - + names(formated_situation_list) <- common_situations_models - + p <- list() for (i in common_situations_models) { sim_situation <- formated_situation_list[[i]] @@ -175,7 +175,7 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, item_case <- detect_item_case( type, mixture, one_version, has_distinct_situations, overlap ) - + plot_title <- if (!is.null(title)) { title[[i]] } else if (type == "scatter" && all_situations == TRUE) { @@ -246,9 +246,9 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, ) ) } - + names(p) <- common_situations_models - + return(p) } @@ -312,25 +312,25 @@ plot.statistics <- function(x, xvar = c("group", "situation"), xvar <- match.arg(xvar, c("group", "situation")) type <- match.arg(type, c("bar", "radar")) group_bar <- match.arg(group_bar, c("rows", "stack", "dodge")) - + is_one_group <- length(unique(x$group)) == 1 # test if there is one group only is_all_situations <- unique(unique(x$situation) == "all_situations") # test if there are all situations - + nvar <- length(unique(x$variable)) - + x <- x %>% reshape2::melt( id.vars = c("group", "situation", "variable"), variable.name = "statistic" ) - + if (type == "bar") { if (is.null(title)) { title <- "" } - + if (xvar == "group") { filling <- quote(.data$situation) xvariable <- quote(.data$group) @@ -348,7 +348,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), showlegend <- length(unique(x$statistic)) > 1 } } - + if (group_bar == "rows") { x <- x %>% @@ -368,36 +368,36 @@ plot.statistics <- function(x, xvar = c("group", "situation"), cols = ggplot2::vars(.data$variable), scales = "free" ) + ggplot2::geom_col(ggplot2::aes(fill = .data$statistic), - position = group_bar + position = group_bar ) + ggplot2::ggtitle(title) } - + # Rotate variable names if too many variables if (nvar > 8) { x <- x + ggplot2::theme(strip.text.x = ggplot2::element_text(angle = 90)) } - + # Rotate situation names if they are on x-axis if (xvar == "situation" || (group_bar == "stack" && xvar == "situation")) { x <- x + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90)) } - + if (!showlegend) { x <- x + ggplot2::guides(fill = "none") } - + # No need to label x-axis if only one value if ((xvar == "situation" && is_all_situations) || - (xvar == "group" && is_one_group)) { + (xvar == "group" && is_one_group)) { x <- x + ggplot2::xlab("") + ggplot2::theme(axis.text.x = ggplot2::element_blank()) + ggplot2::theme(axis.ticks.x = ggplot2::element_blank()) } - + # No need to label rows if only one if (group_bar != "rows" && ((xvar == "group" && is_all_situations) || - (xvar == "situation" && is_one_group))) { + (xvar == "situation" && is_one_group))) { x <- x + ggplot2::theme(strip.text.y = ggplot2::element_blank()) } } else { @@ -411,10 +411,10 @@ plot.statistics <- function(x, xvar = c("group", "situation"), stop("No statistical criteria to plot. Use `force = TRUE` to avoid this error.") } } - + x <- x %>% dplyr::filter(.data$statistic == crit_radar) # v_names <- unique(x$group) - + x <- x %>% ggplot2::ggplot(ggplot2::aes( @@ -433,12 +433,12 @@ plot.statistics <- function(x, xvar = c("group", "situation"), }) + ggplot2::scale_x_discrete() + ggplot2::ggproto("CoordRadar", - ggplot2::CoordPolar, - theta = "x", r = "y", start = -pi / 6, - direction = sign(1), is_linear = function(coord) TRUE + ggplot2::CoordPolar, + theta = "x", r = "y", start = -pi / 6, + direction = sign(1), is_linear = function(coord) TRUE ) } - - + + x } diff --git a/R/generic_stats.R b/R/generic_stats.R index 385531b5..9f652380 100644 --- a/R/generic_stats.R +++ b/R/generic_stats.R @@ -144,7 +144,7 @@ statistics <- function(sim, obs = NULL, all_situations = FALSE, } # Testing if the obs and sim have the same plants names: - if (is_obs && !is.null(obs$Plant) && !is.null(sim$Plant)) { + if (is_obs && "Plant" %in% colnames(obs) && "Plant" %in% colnames(sim)) { common_crops <- unique(sim$Plant) %in% unique(obs$Plant) if (any(!common_crops)) { From 4fbe999d104e5e5eb58f287c7ef8e6050a2ed681 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Thu, 11 Dec 2025 09:59:09 +0100 Subject: [PATCH 062/118] Rename variable to var in data dataframe for plotly compatibility "variable" is a name used by plotly when rendering plots so using this name in our dataframe creates conflicts with ggplotly overlay function --- DESCRIPTION | 2 +- R/aesthetics_dynamic.R | 16 +-- R/extract_plot.R | 4 +- R/generic_formatting.R | 31 ++++-- R/generic_plotting.R | 47 +++++---- R/save_plot_pdf.R | 6 +- R/specific_plotting_dynamic.R | 22 ++-- R/specific_plotting_scatter.R | 123 ++++++++++++----------- man/aesthetics_scatter.Rd | 4 +- man/detect_item_case.Rd | 10 +- man/detect_mixture_version_situations.Rd | 8 +- man/generic_formatting.Rd | 5 +- man/specific_scatter_plots.Rd | 47 +++++++-- tests/testthat/test-dynamic-plots.R | 6 +- tests/testthat/test-generic_formatting.R | 2 +- 15 files changed, 196 insertions(+), 137 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index d20cc1a9..68890f7d 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -59,4 +59,4 @@ Encoding: UTF-8 Language: en-US LazyData: true Roxygen: list(markdown = TRUE) -RoxygenNote: 7.3.1 +RoxygenNote: 7.3.3 diff --git a/R/aesthetics_dynamic.R b/R/aesthetics_dynamic.R index dfe0d983..b79833d8 100644 --- a/R/aesthetics_dynamic.R +++ b/R/aesthetics_dynamic.R @@ -38,9 +38,9 @@ aesthetics_dynamic <- function(sim, aesthetics = template_aesthetics(), list("Versions" = names(dot_args[iversion])) aesthetics$versions$shape <- list("Versions" = names(dot_args[iversion])) } else if (item_case == "non_mixture_no_versions_overlap") { - aesthetics$plot$color <- list("Variable" = quote(.data$variable)) - aesthetics$plot$shape <- list("Variable" = quote(.data$variable)) - aesthetics$plot$group <- list("Variable" = quote(.data$variable)) + aesthetics$plot$color <- list("Variable" = quote(.data$var)) + aesthetics$plot$shape <- list("Variable" = quote(.data$var)) + aesthetics$plot$group <- list("Variable" = quote(.data$var)) } else if (item_case == "mixture_versions_no_overlap") { aesthetics$versions$linetype <- list("Versions" = names(dot_args[iversion])) @@ -51,15 +51,15 @@ aesthetics_dynamic <- function(sim, aesthetics = template_aesthetics(), aesthetics$plot$group <- list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) } else if (item_case == "non_mixture_versions_overlap") { - aesthetics$versions$color <- list("Variable" = quote(.data$variable)) + aesthetics$versions$color <- list("Variable" = quote(.data$var)) aesthetics$versions$linetype <- list("Versions" = names(dot_args[iversion])) aesthetics$versions$shape <- list("Versions" = names(dot_args[iversion])) - aesthetics$plot$color <- list("Variable" = quote(.data$variable)) - aesthetics$plot$group <- list("Variable" = quote(.data$variable)) + aesthetics$plot$color <- list("Variable" = quote(.data$var)) + aesthetics$plot$group <- list("Variable" = quote(.data$var)) } else if (item_case == "mixture_no_versions_overlap") { - aesthetics$plot$linetype <- list("Variable" = quote(.data$variable)) - aesthetics$plot$shape <- list("Variable" = quote(.data$variable)) + aesthetics$plot$linetype <- list("Variable" = quote(.data$var)) + aesthetics$plot$shape <- list("Variable" = quote(.data$var)) aesthetics$plot$color <- list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) aesthetics$plot$group <- NULL # ! do we need this? diff --git a/R/extract_plot.R b/R/extract_plot.R index ccf1199b..0bba59b2 100644 --- a/R/extract_plot.R +++ b/R/extract_plot.R @@ -58,9 +58,9 @@ extract_plot <- function(plot, var = NULL, situation = NULL, force = FALSE, if (!is.null(var)) { for (name in situations_names) { if (!is.null(class(ex[[name]]))) { - if (any(var %in% ex[[name]]$data$variable)) { + if (any(var %in% ex[[name]]$data$var)) { ex[[name]]$data <- ex[[name]]$data %>% - dplyr::filter(.data$variable %in% var) + dplyr::filter(.data$var %in% var) } else { ex[[name]] <- ggplot2::ggplot() + ggplot2::theme_void() diff --git a/R/generic_formatting.R b/R/generic_formatting.R index a3058b0e..81764d50 100644 --- a/R/generic_formatting.R +++ b/R/generic_formatting.R @@ -12,7 +12,8 @@ #' scatter). #' @param shape_sit A logical value indicating whether the shape should be #' based on the situation. -#' @param has_distinct_situations A logical value indicating whether there are several +#' @param has_distinct_situations A logical value indicating whether there +#' are several #' situations to plot. #' @param total_vers An integer indicating the total number of versions. #' @@ -22,7 +23,16 @@ #' characteristics to plot. #' @keywords internal #' -generic_formatting <- function(df, var, overlap, situation_group, type, shape_sit, has_distinct_situations, total_vers) { +generic_formatting <- function( + df, + var, + overlap, + situation_group, + type, + shape_sit, + has_distinct_situations, + total_vers +) { # Filter selected variables if (!is.null(var)) { var <- unique(c(var, subst_parenth(var))) @@ -80,7 +90,8 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si # Change sit_name column with names of situation # groups if shape_sit=="group" - if (has_distinct_situations && shape_sit == "group" && !is.null(situation_group)) { + if (has_distinct_situations && shape_sit == "group" && + !is.null(situation_group)) { for (grp in seq_along(situation_group)) { sits <- situation_group[[grp]] if (!is.null(names(situation_group))) { @@ -95,7 +106,7 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si # Add combination column if there are three different characteristics if (type == "dynamic" && !is.null(overlap) && (total_vers > 1) && - ("Plant" %in% colnames(df))) { + ("Plant" %in% colnames(df))) { df <- dplyr::bind_cols( df, @@ -109,10 +120,10 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si ) ) } - # NB: has_distinct_situations means one plot for all situation (or successive) and shape - # is symbol or group + # NB: has_distinct_situations means one plot for all situation (or + # successive) and shape is symbol or group if (type == "scatter" && has_distinct_situations && (total_vers > 1) && - ("Plant" %in% colnames(df))) { + ("Plant" %in% colnames(df))) { df <- dplyr::bind_cols( df, @@ -127,6 +138,8 @@ generic_formatting <- function(df, var, overlap, situation_group, type, shape_si ) } - return(df) - return(df) + # Rename variable to var + df <- dplyr::rename(df, var = variable) + + df } diff --git a/R/generic_plotting.R b/R/generic_plotting.R index d98974c2..d55617a4 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -136,16 +136,14 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, has_distinct_situations, length(dot_args) ) - if ( - is.null(df_sit) || + if (is.null(df_sit) || ( + is.null(df_sit$Observed) && ( - is.null(df_sit$Observed) && - ( - type == "scatter" || - select_dyn == "common" || - select_dyn == "obs" - ) + type == "scatter" || + select_dyn == "common" || + select_dyn == "obs" ) + ) ) { # No common observations and simulations when type=="scatter" or # select_dyn=="common" or select_dyn=="obs" @@ -207,11 +205,12 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, plot_dynamic(sim_situation, i, successive, title = plot_title), # Scatter plots: - "mixture_versions" = plot_scat_mixture_versions( # per sit and all sit share the same call - sim_situation, i, select_scat, shape_sit, - reference_var, is_obs_sd, - title = plot_title - ), + "mixture_versions" = + plot_scat_mixture_versions( # per sit and all sit share the same call + sim_situation, i, select_scat, shape_sit, + reference_var, is_obs_sd, + title = plot_title + ), "mixture_no_versions" = # per sit and all sit share the same call plot_scat_mixture_allsit( sim_situation, i, select_scat, shape_sit, @@ -355,7 +354,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), ggplot2::ggplot(ggplot2::aes(y = .data$value, x = !!xvariable)) + ggplot2::facet_grid( rows = ggplot2::vars(.data$statistic), - cols = ggplot2::vars(.data$variable), scales = "free" + cols = ggplot2::vars(.data$var), scales = "free" ) + ggplot2::geom_col(ggplot2::aes(fill = !!filling), position = "dodge") + ggplot2::ggtitle(title) @@ -365,9 +364,10 @@ plot.statistics <- function(x, xvar = c("group", "situation"), ggplot2::ggplot(ggplot2::aes(y = .data$value, x = !!xvariable)) + ggplot2::facet_grid( rows = ggplot2::vars(!!filling), - cols = ggplot2::vars(.data$variable), scales = "free" + cols = ggplot2::vars(.data$var), scales = "free" ) + - ggplot2::geom_col(ggplot2::aes(fill = .data$statistic), + ggplot2::geom_col( + ggplot2::aes(fill = .data$statistic), position = group_bar ) + ggplot2::ggtitle(title) @@ -389,7 +389,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), # No need to label x-axis if only one value if ((xvar == "situation" && is_all_situations) || - (xvar == "group" && is_one_group)) { + (xvar == "group" && is_one_group)) { x <- x + ggplot2::xlab("") + ggplot2::theme(axis.text.x = ggplot2::element_blank()) + ggplot2::theme(axis.ticks.x = ggplot2::element_blank()) @@ -397,7 +397,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), # No need to label rows if only one if (group_bar != "rows" && ((xvar == "group" && is_all_situations) || - (xvar == "situation" && is_one_group))) { + (xvar == "situation" && is_one_group))) { x <- x + ggplot2::theme(strip.text.y = ggplot2::element_blank()) } } else { @@ -408,7 +408,10 @@ plot.statistics <- function(x, xvar = c("group", "situation"), if (force) { return(NULL) } else { - stop("No statistical criteria to plot. Use `force = TRUE` to avoid this error.") + stop( + "No statistical criteria to plot. + Use `force = TRUE` to avoid this error." + ) } } @@ -418,7 +421,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), x <- x %>% ggplot2::ggplot(ggplot2::aes( - x = .data$variable, y = .data$value, + x = .data$var, y = .data$value, group = .data$group, colour = .data$group, fill = .data$group )) + @@ -432,13 +435,13 @@ plot.statistics <- function(x, xvar = c("group", "situation"), title }) + ggplot2::scale_x_discrete() + - ggplot2::ggproto("CoordRadar", + ggplot2::ggproto( + "CoordRadar", ggplot2::CoordPolar, theta = "x", r = "y", start = -pi / 6, direction = sign(1), is_linear = function(coord) TRUE ) } - x } diff --git a/R/save_plot_pdf.R b/R/save_plot_pdf.R index 4f11232a..87d33bbb 100644 --- a/R/save_plot_pdf.R +++ b/R/save_plot_pdf.R @@ -86,7 +86,7 @@ save_plot_pdf <- function(plot, out_dir, file_name = "Graphs", title = "Plots", vars <- NULL for (d in plot) { - vars <- c(vars, as.character(d$data$variable)) + vars <- c(vars, as.character(d$data$var)) } vars <- unique(vars) @@ -113,7 +113,7 @@ save_plot_pdf <- function(plot, out_dir, file_name = "Graphs", title = "Plots", ind <- which(rmse == i) for (j in ind) { sit <- names(plot)[j] - if (v %in% unique(plot[[sit]]$data$variable)) { + if (v %in% unique(plot[[sit]]$data$var)) { gg <- ex[sit] gg[[1]]$labels$title <- paste0(sit, " | RMSE : ", round(i, 3)) plt <- c(plt, gg) @@ -159,7 +159,7 @@ save_plot_pdf <- function(plot, out_dir, file_name = "Graphs", title = "Plots", # only for facetted plots # (plots with overlapped variables should not be extracted per variable ...) for (va in vars) { - if (va %in% plot[[i]]$data$variable) { + if (va %in% plot[[i]]$data$var) { plt <- c(plt, extract_plot(plot[i], var = va)) } } diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index 9eea4a03..eae7d9e7 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -54,7 +54,7 @@ plot_dynamic <- function(df_data, sit, successive, title = NULL) { ggplot2::aes(x = .data$Date) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + - ggplot2::facet_wrap(~ .data$variable, scales = "free_y") + ggplot2::facet_wrap(~ .data$var, scales = "free_y") if (!is.null(successive)) { dates <- unique(df_data$succession_date) @@ -94,7 +94,7 @@ plot_dynamic_mixture <- function(df_data, sit, title = NULL) { ) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + - ggplot2::facet_wrap(~ .data$variable, scales = "free_y") + + ggplot2::facet_wrap(~ .data$var, scales = "free_y") + ggplot2::labs(colour = "Plant") @@ -123,7 +123,7 @@ plot_dynamic_mixture_overlap <- function(df_data, sit, title = NULL) { df_data, ggplot2::aes( x = .data$Date, - colour = .data$variable, + colour = .data$var, linetype = paste(.data$Dominance, ": ", .data$Plant), shape = paste(.data$Dominance, ": ", .data$Plant) ) @@ -140,7 +140,7 @@ plot_dynamic_mixture_overlap <- function(df_data, sit, title = NULL) { .data$Dominance, ": ", .data$Plant ), - color = .data$variable, + color = .data$var, ), na.rm = TRUE ) @@ -176,7 +176,7 @@ plot_dynamic_versions <- function(df_data, sit, title = NULL) { ggplot2::aes(x = .data$Date, colour = .data$version) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + - ggplot2::facet_wrap(~ .data$variable, scales = "free") + ggplot2::facet_wrap(~ .data$var, scales = "free") if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point( @@ -212,7 +212,7 @@ plot_dynamic_versions <- function(df_data, sit, title = NULL) { plot_dynamic_overlap <- function(df_data, sit, title = NULL) { p <- ggplot2::ggplot( df_data, - ggplot2::aes(x = .data$Date, colour = .data$variable) + ggplot2::aes(x = .data$Date, colour = .data$var) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + ggplot2::facet_wrap(~ .data$group_var, scales = "free") + @@ -220,7 +220,7 @@ plot_dynamic_overlap <- function(df_data, sit, title = NULL) { if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point( - ggplot2::aes(y = .data$Observed, shape = .data$variable), + ggplot2::aes(y = .data$Observed, shape = .data$var), na.rm = TRUE ) if ("Obs_SD" %in% colnames(df_data)) { @@ -253,7 +253,7 @@ plot_dynamic_versions_overlap <- function(df_data, sit, title = NULL) { p <- ggplot2::ggplot( df_data, ggplot2::aes( - x = .data$Date, colour = .data$variable, + x = .data$Date, colour = .data$var, linetype = .data$version ) ) + @@ -263,7 +263,7 @@ plot_dynamic_versions_overlap <- function(df_data, sit, title = NULL) { if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point( - ggplot2::aes(y = .data$Observed, colour = .data$variable), + ggplot2::aes(y = .data$Observed, colour = .data$var), na.rm = TRUE ) if ("Obs_SD" %in% colnames(df_data)) { @@ -272,7 +272,7 @@ plot_dynamic_versions_overlap <- function(df_data, sit, title = NULL) { ggplot2::aes( ymin = .data$Observed - 2 * .data$Obs_SD, ymax = .data$Observed + 2 * .data$Obs_SD, - colour = .data$variable + colour = .data$var ), na.rm = TRUE ) @@ -293,7 +293,7 @@ plot_dynamic_mixture_versions <- function(df_data, sit, title = NULL) { ) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + - ggplot2::facet_wrap(~ .data$variable, scales = "free") + ggplot2::facet_wrap(~ .data$var, scales = "free") if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point( diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index bfef9554..0999e355 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -39,10 +39,10 @@ NULL compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { # Compute x and y axis min and max to set axis limits df_min <- df_data %>% - group_by(.data$variable) %>% + group_by(.data$var) %>% summarise(across(where(is.numeric), min)) df_max <- df_data %>% - group_by(.data$variable) %>% + group_by(.data$var) %>% summarise(across(where(is.numeric), max)) xaxis_min <- df_min[[reference_var]] - 0.05 * df_min[[reference_var]] xaxis_max <- df_max[[reference_var]] + 0.05 * df_max[[reference_var]] @@ -53,11 +53,11 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { # Update xaxis min and max in case of addition of error bars df_min <- df_data %>% mutate(barmin = .data$Observed - 2 * .data$Obs_SD) %>% - group_by(.data$variable) %>% + group_by(.data$var) %>% summarise(across(where(is.numeric), min)) df_max <- df_data %>% mutate(barmax = .data$Observed + 2 * .data$Obs_SD) %>% - group_by(.data$variable) %>% + group_by(.data$var) %>% summarise(across(where(is.numeric), max)) xaxis_min <- df_min[["barmin"]] - 0.05 * df_min[["barmin"]] xaxis_max <- df_max[["barmax"]] + 0.05 * df_max[["barmax"]] @@ -169,20 +169,21 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) ), na.rm = TRUE @@ -190,6 +191,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, } else if (shape_sit == "symbol" || shape_sit == "group") { p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), colour = as.factor(paste(.data$Dominance, ":", .data$Plant)), shape = as.factor(paste(.data$sit_name)) ), @@ -197,7 +199,7 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::scale_shape_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -209,20 +211,18 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, fullrange = TRUE, na.rm = TRUE ) + ggplot2::xlab(reference_var_name) + - ggplot2::facet_wrap(~variable, scales = "free") - + ggplot2::facet_wrap(~ .data$var, scales = "free") + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p$data$colour_factor <- as.factor(paste(p$data$Dominance, ":", p$data$Plant)) - p <- add_obs_error_bars(p, - colour_factor = "colour_factor" - ) + p <- add_obs_error_bars(p, colour_factor = "colour_factor") } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -234,14 +234,14 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + p <- p + ggplot2::scale_color_discrete(name = "Plant") - + return(p) } @@ -254,20 +254,21 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), shape = as.factor(paste(.data$Dominance, ":", .data$Plant)), colour = as.factor(.data$version) ), @@ -282,6 +283,7 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, # they can put shape_sit = "none" or shape_sit = "txt" to have it all. p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), colour = as.factor(.data$version), shape = as.factor(.data$sit_name) ), @@ -289,7 +291,7 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, ) + ggplot2::labs(color = "Version", shape = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -301,10 +303,10 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, fullrange = TRUE, na.rm = TRUE ) + ggplot2::xlab(reference_var_name) + - ggplot2::facet_wrap(~variable, scales = "free") - + ggplot2::facet_wrap(~ .data$var, scales = "free") + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( @@ -316,9 +318,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -330,12 +332,12 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + return(p) } @@ -344,8 +346,8 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, #' @rdname specific_scatter_plots plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, reference_var, is_obs_sd, title = NULL, - has_distinct_situations = FALSE, one_version = FALSE, - mixture = FALSE) { + has_distinct_situations = FALSE, + one_version = FALSE, mixture = FALSE) { tmp <- give_reference_var(reference_var) reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name @@ -353,25 +355,30 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + if (shape_sit == "none" || shape_sit == "txt") { - p <- p + ggplot2::geom_point(na.rm = TRUE) + p <- p + ggplot2::geom_point( + ggplot2::aes( + text = paste0("Situation: ", .data$sit_name) + ), + na.rm = TRUE + ) } else if (shape_sit == "symbol" || shape_sit == "group") { p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), colour = as.factor(paste(.data$sit_name)) ), na.rm = TRUE ) + ggplot2::scale_color_discrete(name = "Situation") } - + p <- p + ggplot2::geom_abline( intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), @@ -383,11 +390,11 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, fullrange = TRUE, na.rm = TRUE ) + ggplot2::xlab(reference_var_name) + - ggplot2::facet_wrap(~variable, scales = "free") - + ggplot2::facet_wrap(~ .data$var, scales = "free") + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( ggplot2::aes( @@ -397,9 +404,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( @@ -409,7 +416,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, max.overlaps = 100 ) } - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) @@ -421,7 +428,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ) { p <- p + ggplot2::theme(legend.position = "none") } - + return(p) } @@ -440,17 +447,17 @@ plot_scat_versions_per_sit <- function(df_data, reference_var <- tmp$reference_var reference_var_name <- tmp$reference_var_name y_var_type <- give_y_var_type(select_scat) - + df_data <- df_data %>% dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - + p <- ggplot2::ggplot( df_data, ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) ) - + p <- p + ggplot2::geom_point( ggplot2::aes( colour = as.factor(.data$version) @@ -469,10 +476,10 @@ plot_scat_versions_per_sit <- function(df_data, fullrange = TRUE, na.rm = TRUE ) + ggplot2::xlab(reference_var_name) + - ggplot2::facet_wrap(~variable, scales = "free") - + ggplot2::facet_wrap(~ .data$var, scales = "free") + p <- p + ggplot2::ggtitle(title) - + if (is_obs_sd && reference_var == "Observed") { p <- p + ggplot2::geom_linerange( @@ -484,23 +491,17 @@ plot_scat_versions_per_sit <- function(df_data, na.rm = TRUE ) } - + p <- p + ggplot2::theme(aspect.ratio = 1) - + # Set same limits for x and y axis for sim VS obs scatter plots if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } - + return(p) } - - - - - - #' @keywords internal #' @rdname specific_scatter_plots plot_scat_versions_per_sit <- function(df_data, @@ -539,7 +540,7 @@ plot_scat_versions_per_sit <- function(df_data, fullrange = TRUE, na.rm = TRUE ) + ggplot2::xlab(reference_var_name) + - ggplot2::facet_wrap(~variable, scales = "free") + ggplot2::facet_wrap(~ .data$var, scales = "free") p <- p + ggplot2::ggtitle(title) @@ -589,6 +590,7 @@ plot_scat_versions_allsit <- function(df_data, if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), colour = as.factor(.data$version) ), na.rm = TRUE @@ -602,6 +604,7 @@ plot_scat_versions_allsit <- function(df_data, # they can put shape_sit = "none" or shape_sit = "txt" to have it all. p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), colour = as.factor(.data$version), shape = as.factor(.data$sit_name) ), @@ -621,7 +624,7 @@ plot_scat_versions_allsit <- function(df_data, fullrange = TRUE, na.rm = TRUE ) + ggplot2::xlab(reference_var_name) + - ggplot2::facet_wrap(~variable, scales = "free") + ggplot2::facet_wrap(~ .data$var, scales = "free") p <- p + ggplot2::ggtitle(title) diff --git a/man/aesthetics_scatter.Rd b/man/aesthetics_scatter.Rd index 49aed062..d5321111 100644 --- a/man/aesthetics_scatter.Rd +++ b/man/aesthetics_scatter.Rd @@ -8,7 +8,7 @@ aesthetics_scatter( sim, aesthetics = template_aesthetics(), overlap = NULL, - several_sit = FALSE, + has_distinct_situations = FALSE, one_version = TRUE, iversion = 1, dot_args = NULL, @@ -23,7 +23,7 @@ aesthetics_scatter( \item{overlap}{A list of lists containing the variables to represent on the same graph when \code{type = "dynamic"}} -\item{several_sit}{Boolean. Must be equal to \code{TRUE} if sim and obs gather +\item{has_distinct_situations}{Boolean. Must be equal to \code{TRUE} if sim and obs gather more than one situation and if situations should be differentiated on the graph.} diff --git a/man/detect_item_case.Rd b/man/detect_item_case.Rd index 4a3abc9d..cefa32c4 100644 --- a/man/detect_item_case.Rd +++ b/man/detect_item_case.Rd @@ -4,7 +4,13 @@ \alias{detect_item_case} \title{Detect items cases} \usage{ -detect_item_case(type, is_mixture, one_version, several_sit, overlap) +detect_item_case( + type, + is_mixture, + one_version, + has_distinct_situations, + overlap +) } \arguments{ \item{type}{The type of plot required, either 'dynamic' or 'scatter} @@ -13,7 +19,7 @@ detect_item_case(type, is_mixture, one_version, several_sit, overlap) \item{one_version}{A logical value indicating whether the plot has one or multiple versions (e.g. of the model).} -\item{several_sit}{A logical value indicating whether there are one or several situations to plot.} +\item{has_distinct_situations}{A logical value indicating whether there are one or several situations to plot.} \item{overlap}{A logical value indicating whether there is any overlapping variables in the plot.} } diff --git a/man/detect_mixture_version_situations.Rd b/man/detect_mixture_version_situations.Rd index e50dcefa..fe342d63 100644 --- a/man/detect_mixture_version_situations.Rd +++ b/man/detect_mixture_version_situations.Rd @@ -4,14 +4,18 @@ \alias{detect_mixture_version_situations} \title{Detect items cases for scatter plots} \usage{ -detect_mixture_version_situations(is_mixture, one_version, several_sit) +detect_mixture_version_situations( + is_mixture, + one_version, + has_distinct_situations +) } \arguments{ \item{is_mixture}{A logical value indicating whether the crop is a mixture or not.} \item{one_version}{A logical value indicating whether the plot has one or multiple versions (e.g. of the model).} -\item{several_sit}{A logical value indicating whether there are one or several situations to plot.} +\item{has_distinct_situations}{A logical value indicating whether there are one or several situations to plot.} } \value{ A character string indicating the case for computing the aesthetics of the plot. diff --git a/man/generic_formatting.Rd b/man/generic_formatting.Rd index d1dbf542..352efdb2 100644 --- a/man/generic_formatting.Rd +++ b/man/generic_formatting.Rd @@ -11,7 +11,7 @@ generic_formatting( situation_group, type, shape_sit, - several_sit, + has_distinct_situations, total_vers ) } @@ -31,7 +31,8 @@ scatter).} \item{shape_sit}{A logical value indicating whether the shape should be based on the situation.} -\item{several_sit}{A logical value indicating whether there are several +\item{has_distinct_situations}{A logical value indicating whether there +are several situations to plot.} \item{total_vers}{An integer indicating the total number of versions.} diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd index 65eaadd4..73e6a566 100644 --- a/man/specific_scatter_plots.Rd +++ b/man/specific_scatter_plots.Rd @@ -6,15 +6,17 @@ \alias{make_axis_square} \alias{add_obs_error_bars} \alias{plot_scat_mixture_allsit} +\alias{plot_scat_mixture_versions} \alias{plot_scat_allsit} -\alias{plot_scat_version_allsit} +\alias{plot_scat_versions_per_sit} +\alias{plot_scat_versions_allsit} \title{Specific functions to generate scatter plots} \usage{ compute_axis_bounds(df_data, reference_var, y_var_type, is_obs_sd) make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) -add_obs_error_bars(p, colour_factor) +add_obs_error_bars(p, colour_factor = NULL) plot_scat_mixture_allsit( df_data, @@ -26,6 +28,16 @@ plot_scat_mixture_allsit( title = NULL ) +plot_scat_mixture_versions( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL +) + plot_scat_allsit( df_data, sit, @@ -34,22 +46,39 @@ plot_scat_allsit( reference_var, is_obs_sd, title = NULL, - several_sit = FALSE, + has_distinct_situations = FALSE, one_version = FALSE, mixture = FALSE ) -plot_scat_version_allsit( +plot_scat_versions_per_sit( df_data, sit, select_scat, shape_sit, reference_var, is_obs_sd, - title = NULL, - several_sit = FALSE, - one_version = FALSE, - mixture = FALSE + title = NULL +) + +plot_scat_versions_per_sit( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL +) + +plot_scat_versions_allsit( + df_data, + sit, + select_scat, + shape_sit, + reference_var, + is_obs_sd, + title = NULL ) } \arguments{ @@ -66,7 +95,7 @@ per situation, or only one df if sit==all_situations)} \item{sit}{The name of the situation to plot (or all_situations)} -\item{several_sit}{TRUE if the plot is for several situations} +\item{has_distinct_situations}{TRUE if the plot is for several situations} \item{one_version}{TRUE if the plot is for one version} diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index bcfc318e..5a3ba3d6 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -189,7 +189,7 @@ test_that("Test plot only overlap", { "lai_n | masec_n" ) expect_equal( - unique(test_plot$`SC_Pea_2005-2006_N0`$data$variable), + unique(test_plot$`SC_Pea_2005-2006_N0`$data$var), c("lai_n", "masec_n") ) @@ -301,7 +301,7 @@ test_that("Test plot overlap + mixture", { "lai_n | masec_n" ) expect_equal( - unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$variable), + unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$var), c("lai_n", "masec_n") ) expect_equal( @@ -373,7 +373,7 @@ test_that("Test plot overlap + version", { "lai_n | masec_n" ) expect_equal( - unique(test_plot$`SC_Pea_2005-2006_N0`$data$variable), + unique(test_plot$`SC_Pea_2005-2006_N0`$data$var), c("lai_n", "masec_n") ) expect_equal( diff --git a/tests/testthat/test-generic_formatting.R b/tests/testthat/test-generic_formatting.R index 021875d7..3564ad3f 100644 --- a/tests/testthat/test-generic_formatting.R +++ b/tests/testthat/test-generic_formatting.R @@ -50,7 +50,7 @@ test_that("generic_formatting", { expect_equal(as.character(min(df_all$Date)), "2005-09-26") expect_equal(as.character(max(df_all$Date)), "2006-08-01") expect_equal(unique(df_all$version), "Version_1") - expect_equal(unique(df_all$variable), "lai_n") + expect_equal(unique(df_all$var), "lai_n") expect_equal(mean(df_all$Simulated), 0.21725255, tolerance = 1e-8) expect_equal(mean(df_all$Observed, na.rm = TRUE), 0.7625, tolerance = 1e-8) }) From b10893947f8947def2cac455456e2700f6d200af Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Thu, 11 Dec 2025 10:43:19 +0100 Subject: [PATCH 063/118] Remove duplicate code in specific_plotting_scatter.R --- R/specific_plotting_scatter.R | 71 +---------------------------------- man/specific_scatter_plots.Rd | 10 ----- 2 files changed, 1 insertion(+), 80 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 0999e355..afe0f239 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -432,76 +432,6 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, return(p) } - - - - - - -#' @keywords internal -#' @rdname specific_scatter_plots -plot_scat_versions_per_sit <- function(df_data, - sit, select_scat, shape_sit, - reference_var, is_obs_sd, title = NULL) { - tmp <- give_reference_var(reference_var) - reference_var <- tmp$reference_var - reference_var_name <- tmp$reference_var_name - y_var_type <- give_y_var_type(select_scat) - - df_data <- - df_data %>% - dplyr::filter(!is.na(.data[[reference_var]]) & !is.na(.data[[y_var_type]])) - - p <- - ggplot2::ggplot( - df_data, - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) - ) - - p <- p + ggplot2::geom_point( - ggplot2::aes( - colour = as.factor(.data$version) - ), - na.rm = TRUE - ) + - ggplot2::labs(color = "Version") - p <- p + - ggplot2::geom_abline( - intercept = 0, slope = ifelse(select_scat == "sim", 1, 0), - color = "grey30", linetype = 2 - ) + - ggplot2::geom_smooth( - method = lm, color = "blue", - se = FALSE, linewidth = 0.6, formula = y ~ x, - fullrange = TRUE, na.rm = TRUE - ) + - ggplot2::xlab(reference_var_name) + - ggplot2::facet_wrap(~ .data$var, scales = "free") - - p <- p + ggplot2::ggtitle(title) - - if (is_obs_sd && reference_var == "Observed") { - p <- p + - ggplot2::geom_linerange( - ggplot2::aes( - xmin = .data$Observed - 2 * .data$Obs_SD, - xmax = .data$Observed + 2 * .data$Obs_SD, - colour = as.factor(.data$version), - ), - na.rm = TRUE - ) - } - - p <- p + ggplot2::theme(aspect.ratio = 1) - - # Set same limits for x and y axis for sim VS obs scatter plots - if (select_scat == "sim" && reference_var == "Observed") { - p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) - } - - return(p) -} - #' @keywords internal #' @rdname specific_scatter_plots plot_scat_versions_per_sit <- function(df_data, @@ -524,6 +454,7 @@ plot_scat_versions_per_sit <- function(df_data, p <- p + ggplot2::geom_point( ggplot2::aes( + text = paste0("Situation: ", .data$sit_name), colour = as.factor(.data$version) ), na.rm = TRUE diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd index 73e6a566..bcafc695 100644 --- a/man/specific_scatter_plots.Rd +++ b/man/specific_scatter_plots.Rd @@ -61,16 +61,6 @@ plot_scat_versions_per_sit( title = NULL ) -plot_scat_versions_per_sit( - df_data, - sit, - select_scat, - shape_sit, - reference_var, - is_obs_sd, - title = NULL -) - plot_scat_versions_allsit( df_data, sit, From 5638c8b123478305f8b990873dc64de18914f385 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Tue, 16 Dec 2025 14:18:16 +0100 Subject: [PATCH 064/118] Rename variable to var in plot.statistics function --- R/generic_plotting.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/generic_plotting.R b/R/generic_plotting.R index d55617a4..6b621dd4 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -323,7 +323,8 @@ plot.statistics <- function(x, xvar = c("group", "situation"), reshape2::melt( id.vars = c("group", "situation", "variable"), variable.name = "statistic" - ) + ) %>% + dplyr::rename(var = variable) if (type == "bar") { if (is.null(title)) { From e11dd9ee0b55389145b0d5671d1b10089e80561d Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Mon, 12 Jan 2026 11:52:05 +0100 Subject: [PATCH 065/118] Remove unused aesthetics code --- R/aesthetics.R | 20 ---------- R/aesthetics_dynamic.R | 74 ----------------------------------- R/aesthetics_scatter.R | 70 --------------------------------- R/specific_plotting_scatter.R | 2 +- man/aesthetics_dynamic.Rd | 42 -------------------- man/aesthetics_scatter.Rd | 47 ---------------------- man/template_aesthetics.Rd | 16 -------- 7 files changed, 1 insertion(+), 270 deletions(-) delete mode 100644 R/aesthetics_dynamic.R delete mode 100644 R/aesthetics_scatter.R delete mode 100644 man/aesthetics_dynamic.Rd delete mode 100644 man/aesthetics_scatter.Rd delete mode 100644 man/template_aesthetics.Rd diff --git a/R/aesthetics.R b/R/aesthetics.R index 50358e0e..5b0a0d4a 100644 --- a/R/aesthetics.R +++ b/R/aesthetics.R @@ -1,23 +1,3 @@ -#' Template aesthetics -#' -#' This function returns a template list of aesthetics for a plot, including -#' color, shape, linetype, and group. -#' -#' @return A list of aesthetics for a plot. -#' -#' @keywords internal -template_aesthetics <- function() { - aesthetics <- list( - "plot" = list( - "color" = list(NULL), "shape" = list(NULL), - "linetype" = list(NULL), "group" = list(NULL) - ), - "versions" = list("shape" = list(NULL), "linetype" = list(NULL)) - ) - return(aesthetics) -} - - #' Detects if a situation is a mixture #' #' This function checks if the situation is a mixture based on diff --git a/R/aesthetics_dynamic.R b/R/aesthetics_dynamic.R deleted file mode 100644 index b79833d8..00000000 --- a/R/aesthetics_dynamic.R +++ /dev/null @@ -1,74 +0,0 @@ -#' Manages the aesthetics of the graphics for dynamic plots -#' -#' @description Manages the shape, color and line type of the graphics according -#' to their content -#' -#' @param sim A simulation list of data.frames -#' @param aesthetics Template aesthetics list -#' @param overlap A list of lists containing the variables to represent on the -#' same graph when `type = "dynamic"` -#' @param one_version Boolean. Must be `TRUE` if several versions will be -#' plotted on the same graph. -#' @param iversion Integer. Version number of sim -#' @param dot_args List of dot arguments given to plot function -#' @param is_mixture Boolean indicating whether the crop is a mixture or not -#' -#' @return An aesthetics expression which will allow to manage the aesthetics -#' of the graphics -#' -#' @keywords internal -#' -aesthetics_dynamic <- function(sim, aesthetics = template_aesthetics(), - overlap = NULL, one_version = TRUE, - iversion = 1, dot_args = NULL, - is_mixture = FALSE) { - # Define the cases using switch - item_case <- detect_mixture_version_overlap(is_mixture, one_version, overlap) - - # Manage the aesthetics according to the case: - if (item_case == "mixture_no_versions_no_overlap") { - aesthetics$plot$color <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - aesthetics$plot$shape <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - aesthetics$plot$group <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - } else if (item_case == "non_mixture_versions_no_overlap") { - aesthetics$versions$color <- - list("Versions" = names(dot_args[iversion])) - aesthetics$versions$shape <- list("Versions" = names(dot_args[iversion])) - } else if (item_case == "non_mixture_no_versions_overlap") { - aesthetics$plot$color <- list("Variable" = quote(.data$var)) - aesthetics$plot$shape <- list("Variable" = quote(.data$var)) - aesthetics$plot$group <- list("Variable" = quote(.data$var)) - } else if (item_case == "mixture_versions_no_overlap") { - aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iversion])) - aesthetics$versions$shape <- - list("Versions" = names(dot_args[iversion])) - aesthetics$versions$color <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - aesthetics$plot$group <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - } else if (item_case == "non_mixture_versions_overlap") { - aesthetics$versions$color <- list("Variable" = quote(.data$var)) - aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iversion])) - aesthetics$versions$shape <- list("Versions" = names(dot_args[iversion])) - aesthetics$plot$color <- list("Variable" = quote(.data$var)) - aesthetics$plot$group <- list("Variable" = quote(.data$var)) - } else if (item_case == "mixture_no_versions_overlap") { - aesthetics$plot$linetype <- list("Variable" = quote(.data$var)) - aesthetics$plot$shape <- list("Variable" = quote(.data$var)) - aesthetics$plot$color <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - aesthetics$plot$group <- NULL # ! do we need this? - } else if (item_case == "mixture_versions_overlap") { - aesthetics$versions$color <- list(quote(paste(.data$Combi))) - aesthetics$versions$shape <- list(quote(paste(.data$Combi))) - aesthetics$versions$linetype <- list(quote(paste(.data$Combi))) - aesthetics$plot$group <- list(quote(paste(.data$Combi))) - } - - return(aesthetics) -} diff --git a/R/aesthetics_scatter.R b/R/aesthetics_scatter.R deleted file mode 100644 index 3ba255a2..00000000 --- a/R/aesthetics_scatter.R +++ /dev/null @@ -1,70 +0,0 @@ -#' Manages the aesthetics of the graphics for scatter plots -#' -#' @description Manages the shape, color and line type of the graphics according -#' to their content -#' -#' @param sim A simulation list of data.frames -#' @param aesthetics Template aesthetics list -#' @param overlap A list of lists containing the variables to represent on the -#' same graph when `type = "dynamic"` -#' @param has_distinct_situations Boolean. Must be equal to `TRUE` if sim and obs gather -#' more than one situation and if situations should be differentiated -#' on the graph. -#' @param one_version Boolean. Must be `TRUE` if several versions will be -#' plotted on the same graph. -#' @param iversion Integer. Version number of sim -#' @param dot_args List of dot arguments given to plot function -#' @param is_mixture Boolean indicating whether the crop is a mixture or not -#' -#' @return An aesthetics expression which will allow to manage the aesthetics -#' of the graphics -#' -#' @keywords internal -#' -aesthetics_scatter <- function(sim, aesthetics = template_aesthetics(), - overlap = NULL, has_distinct_situations = FALSE, - one_version = TRUE, iversion = 1, - dot_args = NULL, is_mixture = FALSE) { - # Define the cases using switch - item_case <- detect_mixture_version_situations(is_mixture, one_version, has_distinct_situations) - - # Manage the aesthetics according to the case: - if (item_case == "mixture_no_versions_no_situations") { - aesthetics$plot$color <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - } else if (item_case == "non_mixture_versions_no_situations") { - aesthetics$versions$color <- list("Versions" = names(dot_args[iversion])) - aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iversion])) - } else if (item_case == "non_mixture_no_versions_situations") { - aesthetics$plot$color <- list("Situation" = quote(paste(.data$sit_name))) - } else if (item_case == "mixture_versions_no_situations") { - if (iversion == 1) { - aesthetics$versions$color <- - list("Versions" = quote(paste(names(dot_args[1])))) - aesthetics$versions$linetype <- - list("Versions" = quote(paste(names(dot_args[1])))) - } else { - aesthetics$versions$color <- - list("Versions" = quote(paste(names(dot_args[iversion])))) - aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iversion])) - } - aesthetics$plot$shape <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - } else if (item_case == "non_mixture_versions_situations") { - aesthetics$versions$color <- list("Versions" = names(dot_args[iversion])) - aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iversion])) - aesthetics$plot$shape <- list("Situation" = quote(.data$sit_name)) - } else if (item_case == "mixture_no_versions_situations") { - aesthetics$plot$color <- - list("Plant" = quote(paste(.data$Dominance, ":", .data$Plant))) - aesthetics$plot$shape <- list("Situation" = quote(.data$sit_name)) - } else if (item_case == "mixture_versions_situations") { - aesthetics$versions$color <- list(quote(paste(.data$Combi))) - aesthetics$versions$linetype <- - list("Versions" = names(dot_args[iversion])) - } - return(aesthetics) -} diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index afe0f239..c34188b3 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -48,7 +48,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_max <- df_max[[reference_var]] + 0.05 * df_max[[reference_var]] yaxis_min <- df_min[[y_var_type]] - 0.05 * df_min[[y_var_type]] yaxis_max <- df_max[[y_var_type]] + 0.05 * df_max[[y_var_type]] - + if (is_obs_sd && reference_var == "Observed") { # Update xaxis min and max in case of addition of error bars df_min <- df_data %>% diff --git a/man/aesthetics_dynamic.Rd b/man/aesthetics_dynamic.Rd deleted file mode 100644 index 4cdaef89..00000000 --- a/man/aesthetics_dynamic.Rd +++ /dev/null @@ -1,42 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/aesthetics_dynamic.R -\name{aesthetics_dynamic} -\alias{aesthetics_dynamic} -\title{Manages the aesthetics of the graphics for dynamic plots} -\usage{ -aesthetics_dynamic( - sim, - aesthetics = template_aesthetics(), - overlap = NULL, - one_version = TRUE, - iversion = 1, - dot_args = NULL, - is_mixture = FALSE -) -} -\arguments{ -\item{sim}{A simulation list of data.frames} - -\item{aesthetics}{Template aesthetics list} - -\item{overlap}{A list of lists containing the variables to represent on the -same graph when \code{type = "dynamic"}} - -\item{one_version}{Boolean. Must be \code{TRUE} if several versions will be -plotted on the same graph.} - -\item{iversion}{Integer. Version number of sim} - -\item{dot_args}{List of dot arguments given to plot function} - -\item{is_mixture}{Boolean indicating whether the crop is a mixture or not} -} -\value{ -An aesthetics expression which will allow to manage the aesthetics -of the graphics -} -\description{ -Manages the shape, color and line type of the graphics according -to their content -} -\keyword{internal} diff --git a/man/aesthetics_scatter.Rd b/man/aesthetics_scatter.Rd deleted file mode 100644 index d5321111..00000000 --- a/man/aesthetics_scatter.Rd +++ /dev/null @@ -1,47 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/aesthetics_scatter.R -\name{aesthetics_scatter} -\alias{aesthetics_scatter} -\title{Manages the aesthetics of the graphics for scatter plots} -\usage{ -aesthetics_scatter( - sim, - aesthetics = template_aesthetics(), - overlap = NULL, - has_distinct_situations = FALSE, - one_version = TRUE, - iversion = 1, - dot_args = NULL, - is_mixture = FALSE -) -} -\arguments{ -\item{sim}{A simulation list of data.frames} - -\item{aesthetics}{Template aesthetics list} - -\item{overlap}{A list of lists containing the variables to represent on the -same graph when \code{type = "dynamic"}} - -\item{has_distinct_situations}{Boolean. Must be equal to \code{TRUE} if sim and obs gather -more than one situation and if situations should be differentiated -on the graph.} - -\item{one_version}{Boolean. Must be \code{TRUE} if several versions will be -plotted on the same graph.} - -\item{iversion}{Integer. Version number of sim} - -\item{dot_args}{List of dot arguments given to plot function} - -\item{is_mixture}{Boolean indicating whether the crop is a mixture or not} -} -\value{ -An aesthetics expression which will allow to manage the aesthetics -of the graphics -} -\description{ -Manages the shape, color and line type of the graphics according -to their content -} -\keyword{internal} diff --git a/man/template_aesthetics.Rd b/man/template_aesthetics.Rd deleted file mode 100644 index e45d37fb..00000000 --- a/man/template_aesthetics.Rd +++ /dev/null @@ -1,16 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/aesthetics.R -\name{template_aesthetics} -\alias{template_aesthetics} -\title{Template aesthetics} -\usage{ -template_aesthetics() -} -\value{ -A list of aesthetics for a plot. -} -\description{ -This function returns a template list of aesthetics for a plot, including -color, shape, linetype, and group. -} -\keyword{internal} From f7fa2b4b49d25b1b6edcc1d717b7027f06dd1909 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Mon, 12 Jan 2026 14:39:07 +0100 Subject: [PATCH 066/118] Remove fixed ggplot2 version from test-coverage.yaml file --- .github/workflows/test-coverage.yaml | 6 ------ 1 file changed, 6 deletions(-) diff --git a/.github/workflows/test-coverage.yaml b/.github/workflows/test-coverage.yaml index 1344a749..5bca2299 100644 --- a/.github/workflows/test-coverage.yaml +++ b/.github/workflows/test-coverage.yaml @@ -29,12 +29,6 @@ jobs: extra-packages: any::covr needs: coverage - - name: Force ggplot2 version 3.5.2 - run: | - install.packages("remotes") - remotes::install_version("ggplot2", version = "3.5.2", upgrade = "never") - shell: Rscript {0} - - name: Test coverage run: | covr::codecov( From c4850afc2a3b332156df98e5019c962b3ac5feda Mon Sep 17 00:00:00 2001 From: vrahier Date: Mon, 12 Jan 2026 13:41:37 +0000 Subject: [PATCH 067/118] Style code (GHA) --- R/generic_formatting.R | 6 +++--- R/generic_plotting.R | 6 +++--- R/parse_plot_situations_arguments.R | 19 ++++++++++--------- R/specific_plotting_scatter.R | 2 +- 4 files changed, 17 insertions(+), 16 deletions(-) diff --git a/R/generic_formatting.R b/R/generic_formatting.R index 81764d50..1365897d 100644 --- a/R/generic_formatting.R +++ b/R/generic_formatting.R @@ -91,7 +91,7 @@ generic_formatting <- function( # Change sit_name column with names of situation # groups if shape_sit=="group" if (has_distinct_situations && shape_sit == "group" && - !is.null(situation_group)) { + !is.null(situation_group)) { for (grp in seq_along(situation_group)) { sits <- situation_group[[grp]] if (!is.null(names(situation_group))) { @@ -106,7 +106,7 @@ generic_formatting <- function( # Add combination column if there are three different characteristics if (type == "dynamic" && !is.null(overlap) && (total_vers > 1) && - ("Plant" %in% colnames(df))) { + ("Plant" %in% colnames(df))) { df <- dplyr::bind_cols( df, @@ -123,7 +123,7 @@ generic_formatting <- function( # NB: has_distinct_situations means one plot for all situation (or # successive) and shape is symbol or group if (type == "scatter" && has_distinct_situations && (total_vers > 1) && - ("Plant" %in% colnames(df))) { + ("Plant" %in% colnames(df))) { df <- dplyr::bind_cols( df, diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 09917c41..32806000 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -390,7 +390,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), # No need to label x-axis if only one value if ((xvar == "situation" && is_all_situations) || - (xvar == "group" && is_one_group)) { + (xvar == "group" && is_one_group)) { x <- x + ggplot2::xlab("") + ggplot2::theme(axis.text.x = ggplot2::element_blank()) + ggplot2::theme(axis.ticks.x = ggplot2::element_blank()) @@ -398,7 +398,7 @@ plot.statistics <- function(x, xvar = c("group", "situation"), # No need to label rows if only one if (group_bar != "rows" && ((xvar == "group" && is_all_situations) || - (xvar == "situation" && is_one_group))) { + (xvar == "situation" && is_one_group))) { x <- x + ggplot2::theme(strip.text.y = ggplot2::element_blank()) } } else { @@ -445,4 +445,4 @@ plot.statistics <- function(x, xvar = c("group", "situation"), } x -} \ No newline at end of file +} diff --git a/R/parse_plot_situations_arguments.R b/R/parse_plot_situations_arguments.R index 1c71c022..e3c66e5b 100644 --- a/R/parse_plot_situations_arguments.R +++ b/R/parse_plot_situations_arguments.R @@ -9,15 +9,16 @@ #' #' @keywords internal parse_plot_situations_args <- function( - dot_args, obs = NULL, obs_sd = NULL, - type = c("dynamic", "scatter"), - select_dyn = c("sim", "common", "obs", "all"), - select_scat = c("sim", "res"), var = NULL, - title = NULL, all_situations = TRUE, - overlap = NULL, successive = NULL, - shape_sit = c("none", "txt", "symbol", "group"), - situation_group = NULL, reference_var = NULL, - force = FALSE, verbose = TRUE) { + dot_args, obs = NULL, obs_sd = NULL, + type = c("dynamic", "scatter"), + select_dyn = c("sim", "common", "obs", "all"), + select_scat = c("sim", "res"), var = NULL, + title = NULL, all_situations = TRUE, + overlap = NULL, successive = NULL, + shape_sit = c("none", "txt", "symbol", "group"), + situation_group = NULL, reference_var = NULL, + force = FALSE, verbose = TRUE +) { type <- match.arg(type, c("dynamic", "scatter"), several.ok = FALSE) select_dyn <- match.arg(select_dyn, c("sim", "common", "obs", "all"), several.ok = FALSE diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index c34188b3..3bb5b26b 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -62,7 +62,7 @@ compute_axis_bounds <- function(df_data, reference_var, y_var_type, is_obs_sd) { xaxis_min <- df_min[["barmin"]] - 0.05 * df_min[["barmin"]] xaxis_max <- df_max[["barmax"]] + 0.05 * df_max[["barmax"]] } - + return(list( xaxis_min = xaxis_min, xaxis_max = xaxis_max, yaxis_min = yaxis_min, yaxis_max = yaxis_max From 418b4dde84697cb14a84bae777961ff804422038 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Mon, 12 Jan 2026 14:48:36 +0100 Subject: [PATCH 068/118] Revert zzz.R --- R/zzz.R | 41 +++++++++++++++++++---------------------- 1 file changed, 19 insertions(+), 22 deletions(-) diff --git a/R/zzz.R b/R/zzz.R index 1d15c423..845bc319 100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -1,26 +1,23 @@ -.onAttach <- function(libname, pkgname) { - required_max_version <- "4.0.0" - installed_version <- as.character(utils::packageVersion("ggplot2")) - - if (package_version(installed_version) >= package_version(required_max_version)) { - packageStartupMessage( - sprintf( - "/!\ CroPlotR scatter plots may not work properly with ggplot2 %s or higher.\nPlease use ggplot2 3.5.2 or earlier. This issue will be fixed in a future release.", - installed_version - ) - ) - packageStartupMessage("") +text_col <- function(x) { + # This function is adapted from: https://github.com/tidyverse/tidyverse + # If RStudio not available, messages already printed in black + if (!rstudioapi::isAvailable()) { + return(x) + } + if (!rstudioapi::hasFun("getThemeInfo")) { + return(x) } + theme <- rstudioapi::getThemeInfo() - packageStartupMessage( - "Learn CroPlotR at: https://SticsRPacks.github.io/CroPlotR" - ) - packageStartupMessage("") + if (isTRUE(theme$dark)) crayon::white(x) else crayon::black(x) +} - cite <- utils::citation("CroPlotR") - # Remove underscores around titles (used by R to indicate italics) - cite_text <- gsub("_([^_]*)_", "\\1", format(cite, style = "text")) - packageStartupMessage("Please cite CroPlotR in your work:") - packageStartupMessage(format(cite_text, style = "text")) -} +.onAttach <- function(libname, pkgname) { + packageStartupMessage( + text_col(paste( + "Learn CroPlotR at:", + crayon::blue$underline$bold("https://SticsRPacks.github.io/CroPlotR") + )) + ) +} \ No newline at end of file From 79fcffe75dbb5ff697dd7f63e68e5145dbaa9682 Mon Sep 17 00:00:00 2001 From: vrahier Date: Mon, 12 Jan 2026 13:50:23 +0000 Subject: [PATCH 069/118] Style code (GHA) --- R/zzz.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/zzz.R b/R/zzz.R index 845bc319..72739878 100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -20,4 +20,4 @@ text_col <- function(x) { crayon::blue$underline$bold("https://SticsRPacks.github.io/CroPlotR") )) ) -} \ No newline at end of file +} From 71195c139919fbcf4d313d07359c20414cdcd801 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Mon, 12 Jan 2026 16:14:01 +0100 Subject: [PATCH 070/118] Remove tests on ggplot$labels as they are not as consistant in ggplot2 > v4 related to #86 --- R/specific_plotting_dynamic.R | 24 ++++++++++++------------ tests/testthat/test-dynamic-plots.R | 29 ----------------------------- tests/testthat/test-scatter-plots.R | 9 +++++---- 3 files changed, 17 insertions(+), 45 deletions(-) diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index eae7d9e7..0cc2c6e8 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -94,8 +94,7 @@ plot_dynamic_mixture <- function(df_data, sit, title = NULL) { ) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + - ggplot2::facet_wrap(~ .data$var, scales = "free_y") + - ggplot2::labs(colour = "Plant") + ggplot2::facet_wrap(~ .data$var, scales = "free_y") if ("Observed" %in% colnames(df_data)) { @@ -114,7 +113,8 @@ plot_dynamic_mixture <- function(df_data, sit, title = NULL) { } p <- p + - ggplot2::ggtitle(title) + ggplot2::ggtitle(title) + + ggplot2::labs(colour = "Plant") return(p) } @@ -129,8 +129,7 @@ plot_dynamic_mixture_overlap <- function(df_data, sit, title = NULL) { ) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + - ggplot2::facet_wrap(~ .data$group_var, scales = "free") + - ggplot2::labs(colour = "Variable", linetype = "Plant", shape = "Plant") + ggplot2::facet_wrap(~ .data$group_var, scales = "free") if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point( @@ -159,10 +158,8 @@ plot_dynamic_mixture_overlap <- function(df_data, sit, title = NULL) { p <- p + ggplot2::ggtitle(title) + ggplot2::guides( - colour = ggplot2::guide_legend( - title = "Variable", - override.aes = list(shape = NA) - ), + colour = ggplot2::guide_legend(title = "Variable"), + # add override.aes = list(shape = NA) in prev guide_legend? linetype = ggplot2::guide_legend(title = "Plant", order = 1), shape = ggplot2::guide_legend(title = "Plant", order = 1) ) @@ -181,6 +178,7 @@ plot_dynamic_versions <- function(df_data, sit, title = NULL) { if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point( ggplot2::aes(y = .data$Observed, shape = .data$Observed_Legend), + # NB: the shape is constant, but used to have a legend entry color = "black", na.rm = TRUE ) @@ -258,8 +256,7 @@ plot_dynamic_versions_overlap <- function(df_data, sit, title = NULL) { ) ) + ggplot2::geom_line(ggplot2::aes(y = .data$Simulated)) + - ggplot2::facet_wrap(~ .data$group_var, scales = "free") + - ggplot2::labs(colour = "Variable", linetype = "Version") + ggplot2::facet_wrap(~ .data$group_var, scales = "free") if ("Observed" %in% colnames(df_data)) { p <- p + ggplot2::geom_point( @@ -278,8 +275,11 @@ plot_dynamic_versions_overlap <- function(df_data, sit, title = NULL) { ) } } + p <- p + - ggplot2::ggtitle(title) + ggplot2::ggtitle(title) + + ggplot2::labs(colour = "Variable", linetype = "Version") + return(p) } diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index 4f176f96..b98d909b 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -182,8 +182,6 @@ test_that("Test plot only overlap", { "Dynamic Plot \"only overlap\" not yet implemented (plot return NA)" ) } else { - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$shape, "Variable") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "Variable") expect_equal( unique(test_plot$`SC_Pea_2005-2006_N0`$data$group_var), "lai_n | masec_n" @@ -222,8 +220,6 @@ test_that("Test plot only mixture", { ) } else { all_plots <<- c(all_plots, test_plot) - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, NULL) - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "Plant") lapply(names(test_plot), function(x) { make_snapshot( paste0(prefix, "_fig.4_mixture_", x, pkg_version), @@ -250,13 +246,6 @@ test_that("Test plot only version", { if (any(is.na(test_plot))) { message('Dynamic Plot "only version" not yet implemented (plot return NA)') } else { - expect_equal( - test_plot$`SC_Pea_2005-2006_N0`$labels$shape, - "Observed_Legend" - ) - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "version") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$group, NULL) - lapply(names(test_plot), function(x) { make_snapshot( paste0(prefix, "_fig.5_version_", x, pkg_version), @@ -290,12 +279,6 @@ test_that("Test plot overlap + mixture", { "Dynamic Plot \"overlap+mixture\" not yet implemented (plot return NA)" ) } else { - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, "Plant") - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "Variable") - expect_equal( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$linetype, - "Plant" - ) expect_equal( unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$group_var), "lai_n | masec_n" @@ -342,11 +325,6 @@ test_that("Test plot overlap + version", { "Dynamic Plot \"overlap+version\" not yet implemented (plot return NA)" ) } else { - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$shape, NULL) - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$colour, "Variable") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$linetype, "Version") - expect_equal(test_plot$`SC_Pea_2005-2006_N0`$labels$group, NULL) - expect_equal( all(sapply( test_plot$`SC_Pea_2005-2006_N0`$layers[sapply( @@ -409,13 +387,6 @@ test_that("Test plot mixture + version", { "Dynamic Plot \"mixture+version\" not yet implemented (plot return NA)" ) } else { - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$shape, NULL) - expect_equal(test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$colour, "paste(Dominance, \":\", Plant)") - expect_equal( - test_plot$`IC_Wheat_Pea_2005-2006_N0`$labels$linetype, - "version" - ) - expect_equal( all(sapply( test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers[sapply( diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index b6dd8961..d4ebcdd7 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -292,10 +292,11 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { expect_equal(length(grep("GeomAbline", layers_class)), tmp$nb_abline[i]) ## Check attributes in plot labels - expect_equal(test_plot[[1]]$labels$col, init_col) - expect_equal(test_plot[[1]]$labels$shape, init_shape) - expect_equal(test_plot[[1]]$labels$linetype, init_linetype) - expect_equal(test_plot[[1]]$labels$group, init_group) + # expect_equal(test_plot[[1]]$labels$col, init_col) + # expect_equal(test_plot[[1]]$labels$shape, init_shape) + # expect_equal(test_plot[[1]]$labels$linetype, init_linetype) + # expect_equal(test_plot[[1]]$labels$group, init_group) + # NB: commented as ggplot2 v4 computes labels differently and it's not reliable anymore ## Check attributes in plot layers if (tmp$version_col[i] != "NULL") { From db0fdc8e9ec84721f38e597310cfdfbb23d164c3 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Mon, 12 Jan 2026 16:49:32 +0100 Subject: [PATCH 071/118] Fix check-standard.yaml file format --- .github/workflows/check-standard.yaml | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/.github/workflows/check-standard.yaml b/.github/workflows/check-standard.yaml index bb6ee99b..89caaebc 100644 --- a/.github/workflows/check-standard.yaml +++ b/.github/workflows/check-standard.yaml @@ -71,8 +71,7 @@ jobs: repository: SticsRPacks/SticsRTests event-type: R-CMD-check client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repo": "${{ github.event.repository.name }}"}' - - - name: Wait for SticsRTests workflow to complete (block-and-fail) + - name: Wait for SticsRTests workflow to complete (block-and-fail) uses: actions/github-script@v6 with: github-token: ${{ secrets.TRIGGER_PAT }} From 00aa6b5e681e69af1a251673375ef13e9215368b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Mon, 12 Jan 2026 17:00:05 +0100 Subject: [PATCH 072/118] Update test-dynamic-plots.R test again the plot labels for dynamic plots --- tests/testthat/test-dynamic-plots.R | 29 +++++++++++++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index b98d909b..9a53e777 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -182,6 +182,9 @@ test_that("Test plot only overlap", { "Dynamic Plot \"only overlap\" not yet implemented (plot return NA)" ) } else { + labels <- ggplot2::get_labs(test_plot$`SC_Pea_2005-2006_N0`) + expect_equal(labels$shape, "Variable") + expect_equal(labels$colour, "Variable") expect_equal( unique(test_plot$`SC_Pea_2005-2006_N0`$data$group_var), "lai_n | masec_n" @@ -220,6 +223,9 @@ test_that("Test plot only mixture", { ) } else { all_plots <<- c(all_plots, test_plot) + labels <- ggplot2::get_labs(test_plot$`IC_Wheat_Pea_2005-2006_N0`) + expect_equal(labels$shape, NULL) + expect_equal(labels$colour, "Plant") lapply(names(test_plot), function(x) { make_snapshot( paste0(prefix, "_fig.4_mixture_", x, pkg_version), @@ -246,6 +252,14 @@ test_that("Test plot only version", { if (any(is.na(test_plot))) { message('Dynamic Plot "only version" not yet implemented (plot return NA)') } else { + labels <- ggplot2::get_labs(test_plot$`SC_Pea_2005-2006_N0`) + expect_equal( + labels$shape, + "Observations" + ) + expect_equal(labels$colour, "Version") + expect_equal(labels$group, NULL) + lapply(names(test_plot), function(x) { make_snapshot( paste0(prefix, "_fig.5_version_", x, pkg_version), @@ -279,6 +293,10 @@ test_that("Test plot overlap + mixture", { "Dynamic Plot \"overlap+mixture\" not yet implemented (plot return NA)" ) } else { + labels <- ggplot2::get_labs(test_plot$`IC_Wheat_Pea_2005-2006_N0`) + expect_equal(labels$shape, "Plant") + expect_equal(labels$colour, "Variable") + expect_equal(labels$linetype, "Plant") expect_equal( unique(test_plot$`IC_Wheat_Pea_2005-2006_N0`$data$group_var), "lai_n | masec_n" @@ -325,6 +343,11 @@ test_that("Test plot overlap + version", { "Dynamic Plot \"overlap+version\" not yet implemented (plot return NA)" ) } else { + labels <- ggplot2::get_labs(test_plot$`SC_Pea_2005-2006_N0`) + expect_equal(labels$shape, NULL) + expect_equal(labels$colour, "Variable") + expect_equal(labels$linetype, "Version") + expect_equal(labels$group, NULL) expect_equal( all(sapply( test_plot$`SC_Pea_2005-2006_N0`$layers[sapply( @@ -378,6 +401,7 @@ test_that("Test plot overlap + version", { } }) + ### mixture + version test_that("Test plot mixture + version", { @@ -387,6 +411,11 @@ test_that("Test plot mixture + version", { "Dynamic Plot \"mixture+version\" not yet implemented (plot return NA)" ) } else { + labels <- ggplot2::get_labs(test_plot$`IC_Wheat_Pea_2005-2006_N0`) + expect_equal(labels$shape, NULL) + expect_equal(labels$colour, "paste(Dominance, \":\", Plant)") + expect_equal(labels$linetype, "version") + expect_equal( all(sapply( test_plot$`IC_Wheat_Pea_2005-2006_N0`$layers[sapply( From ece0931932aeb2fa5599c75ecee86ac636bff41b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Mon, 12 Jan 2026 17:06:03 +0100 Subject: [PATCH 073/118] Roll-back tests on labels for scatter plots --- .../testthat/_inputs/tests_scatter_plots.csv | 38 +++++++++---------- tests/testthat/test-scatter-plots.R | 10 ++--- 2 files changed, 24 insertions(+), 24 deletions(-) diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index 7fb8fcd9..4ce09e52 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -1,11 +1,11 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var;init_col;init_shape;init_linetype;init_group;version_col;version_shape;version_linetype;version_group;nb_geom_point;nb_geom_smooth;nb_abline;To_test;add_sd_obs -1;Mixture, per situation;sim;TRUE;FALSE;FALSE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -2;Mixture, All situations;sim;TRUE;FALSE;TRUE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -3;Mixture, All situations, reference_var=lai_n_sim;sim;TRUE;FALSE;TRUE;none;lai_n_sim;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -4;Mixture, All situations, reference_var=lai_n_obs;sim;TRUE;FALSE;TRUE;none;lai_n_obs;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -5;Mixture, shape_sit=txt, All situations;sim;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -6;Mixture, shape_sit=symbol, All situations;sim;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -7;Mixture (shape_sit=group), All situations;sim;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +1;Mixture, per situation;sim;TRUE;FALSE;FALSE;none;NULL;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +2;Mixture, All situations;sim;TRUE;FALSE;TRUE;none;NULL;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +3;Mixture, All situations, reference_var=lai_n_sim;sim;TRUE;FALSE;TRUE;none;lai_n_sim;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +4;Mixture, All situations, reference_var=lai_n_obs;sim;TRUE;FALSE;TRUE;none;lai_n_obs;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +5;Mixture, shape_sit=txt, All situations;sim;TRUE;FALSE;TRUE;txt;NULL;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +6;Mixture, shape_sit=symbol, All situations;sim;TRUE;FALSE;TRUE;symbol;NULL;"Plant";Situation;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +7;Mixture (shape_sit=group), All situations;sim;TRUE;FALSE;TRUE;group;NULL;"Plant";Situation;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 8;Sole crop, per situation;sim;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 9;Sole crop, All situations;sim;FALSE;FALSE;TRUE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 10;Sole crop, Versions, per situation;sim;FALSE;TRUE;FALSE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE @@ -13,21 +13,21 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 12;Sole crop, Versions, shape_sit=txt, All situations;sim;FALSE;TRUE;TRUE;txt;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 13;Sole crop, Versions, shape_sit=symbol, All situations;sim;FALSE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE 14;Sole crop, Versions (shape_sit=group), All situations;sim;FALSE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE -15;Sole crop, All situations, shape_sit=symbol;sim;FALSE;FALSE;TRUE;symbol;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE -16;Sole crop, All situations, shape_sit=group;sim;FALSE;FALSE;TRUE;group;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE +15;Sole crop, All situations, shape_sit=symbol;sim;FALSE;FALSE;TRUE;symbol;NULL;Situation;NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE +16;Sole crop, All situations, shape_sit=group;sim;FALSE;FALSE;TRUE;group;NULL;Situation;NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE 17;Mixture, versions, per situation;sim;TRUE;TRUE;FALSE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE 18;Mixture, versions, All situations;sim;TRUE;TRUE;TRUE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 19;Mixture, versions, shape_sit=txt, All situations;sim;TRUE;TRUE;TRUE;txt;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE 20;Mixture, versions, shape_sit=symbol, All situations;sim;TRUE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;FALSE 21;Mixture, versions, shape_sit=group, All situations;sim;TRUE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Combi;NULL;Version;NULL;1;1;1;TRUE;TRUE -22;Mixture, per situation, res;res;TRUE;FALSE;FALSE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -23;Mixture, All situations, res;res;TRUE;FALSE;TRUE;none;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -24;Mixture, All situations, reference_var=lai_n_sim, res;res;TRUE;FALSE;TRUE;none;lai_n_sim;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -25;Mixture, All situations, reference_var=lai_n_obs, res;res;TRUE;FALSE;TRUE;none;lai_n_obs;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -26;Mixture, All situations, reference_var=lai_n_res, res;res;TRUE;FALSE;TRUE;none;lai_n_res;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -27;Mixture, shape_sit=txt, All situations, res;res;TRUE;FALSE;TRUE;txt;NULL;"as.factor(paste(Dominance, "":"", Plant))";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -28;Mixture, shape_sit=symbol, All situations, res;res;TRUE;FALSE;TRUE;symbol;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -29;Mixture (shape_sit=group), All situations, res;res;TRUE;FALSE;TRUE;group;NULL;"as.factor(paste(Dominance, "":"", Plant))";as.factor(paste(sit_name));NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +22;Mixture, per situation, res;res;TRUE;FALSE;FALSE;none;NULL;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +23;Mixture, All situations, res;res;TRUE;FALSE;TRUE;none;NULL;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +24;Mixture, All situations, reference_var=lai_n_sim, res;res;TRUE;FALSE;TRUE;none;lai_n_sim;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +25;Mixture, All situations, reference_var=lai_n_obs, res;res;TRUE;FALSE;TRUE;none;lai_n_obs;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +26;Mixture, All situations, reference_var=lai_n_res, res;res;TRUE;FALSE;TRUE;none;lai_n_res;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +27;Mixture, shape_sit=txt, All situations, res;res;TRUE;FALSE;TRUE;txt;NULL;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +28;Mixture, shape_sit=symbol, All situations, res;res;TRUE;FALSE;TRUE;symbol;NULL;"Plant";Situation;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE +29;Mixture (shape_sit=group), All situations, res;res;TRUE;FALSE;TRUE;group;NULL;"Plant";Situation;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 30;Sole crop, per situation, res;res;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 31;Sole crop, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;Version;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 32;Sole crop, Versions, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE @@ -35,8 +35,8 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 34;Sole crop, Versions, shape_sit=txt, All situations, res;res;FALSE;TRUE;TRUE;txt;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 35;Sole crop, Versions, shape_sit=symbol, All situations, res;res;FALSE;TRUE;TRUE;symbol;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE 36;Sole crop, Versions (shape_sit=group), All situations, res;res;FALSE;TRUE;TRUE;group;NULL;Version;Situation;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE -37;Sole crop, All situations, shape_sit=symbol, res;res;FALSE;FALSE;TRUE;symbol;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE -38;Sole crop, All situations, shape_sit=group, res;res;FALSE;FALSE;TRUE;group;NULL;as.factor(paste(sit_name));NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE +37;Sole crop, All situations, shape_sit=symbol, res;res;FALSE;FALSE;TRUE;symbol;NULL;Situation;NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;TRUE +38;Sole crop, All situations, shape_sit=group, res;res;FALSE;FALSE;TRUE;group;NULL;Situation;NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE 39;Mixture, versions, per situation, res;res;TRUE;TRUE;FALSE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE 40;Mixture, versions, All situations, res;res;TRUE;TRUE;TRUE;none;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 41;Mixture, versions, shape_sit=txt, All situations, res;res;TRUE;TRUE;TRUE;txt;NULL;Version;Plant;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index d4ebcdd7..bdab0b7c 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -292,11 +292,11 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { expect_equal(length(grep("GeomAbline", layers_class)), tmp$nb_abline[i]) ## Check attributes in plot labels - # expect_equal(test_plot[[1]]$labels$col, init_col) - # expect_equal(test_plot[[1]]$labels$shape, init_shape) - # expect_equal(test_plot[[1]]$labels$linetype, init_linetype) - # expect_equal(test_plot[[1]]$labels$group, init_group) - # NB: commented as ggplot2 v4 computes labels differently and it's not reliable anymore + labels <- ggplot2::get_labs(test_plot[[1]]) + expect_equal(labels$col, init_col) + expect_equal(labels$shape, init_shape) + expect_equal(labels$linetype, init_linetype) + expect_equal(labels$group, init_group) ## Check attributes in plot layers if (tmp$version_col[i] != "NULL") { From ef07d9b7def486e72a9966341193944c6eba7021 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Mon, 12 Jan 2026 17:16:36 +0100 Subject: [PATCH 074/118] Use labels instead of text in aes for ggplotly compatibility --- R/specific_plotting_scatter.R | 69 +++++++++++++++++------------------ README.md | 40 ++++++++++---------- 2 files changed, 55 insertions(+), 54 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 3bb5b26b..e93f5b95 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -177,13 +177,15 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, p <- ggplot2::ggplot( df_data, - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + label = .data$sit_name + ) ) if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) ), na.rm = TRUE @@ -191,7 +193,6 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, } else if (shape_sit == "symbol" || shape_sit == "group") { p <- p + ggplot2::geom_point( ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), colour = as.factor(paste(.data$Dominance, ":", .data$Plant)), shape = as.factor(paste(.data$sit_name)) ), @@ -206,6 +207,8 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), + inherit.aes = FALSE, method = lm, color = "blue", se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE @@ -227,7 +230,6 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, p <- p + ggrepel::geom_text_repel( ggplot2::aes( - label = .data$sit_name, colour = as.factor(paste(.data$Dominance, ":", .data$Plant)) ), show.legend = FALSE, @@ -262,13 +264,15 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, p <- ggplot2::ggplot( df_data, - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + label = .data$sit_name + ) ) if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), shape = as.factor(paste(.data$Dominance, ":", .data$Plant)), colour = as.factor(.data$version) ), @@ -283,7 +287,6 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, # they can put shape_sit = "none" or shape_sit = "txt" to have it all. p <- p + ggplot2::geom_point( ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), colour = as.factor(.data$version), shape = as.factor(.data$sit_name) ), @@ -298,6 +301,8 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), + inherit.aes = FALSE, method = lm, color = "blue", se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE @@ -325,7 +330,6 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, p <- p + ggrepel::geom_text_repel( ggplot2::aes( - label = .data$sit_name, colour = as.factor(.data$version) ), show.legend = FALSE, @@ -358,20 +362,17 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, p <- ggplot2::ggplot( df_data, - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + label = .data$sit_name + ) ) if (shape_sit == "none" || shape_sit == "txt") { - p <- p + ggplot2::geom_point( - ggplot2::aes( - text = paste0("Situation: ", .data$sit_name) - ), - na.rm = TRUE - ) + p <- p + ggplot2::geom_point(na.rm = TRUE) } else if (shape_sit == "symbol" || shape_sit == "group") { p <- p + ggplot2::geom_point( ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), colour = as.factor(paste(.data$sit_name)) ), na.rm = TRUE @@ -385,6 +386,8 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), + inherit.aes = FALSE, method = lm, color = "blue", se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE @@ -408,13 +411,7 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, p <- p + ggplot2::theme(aspect.ratio = 1) if (shape_sit == "txt") { - p <- p + - ggrepel::geom_text_repel( - ggplot2::aes( - label = .data$sit_name - ), - max.overlaps = 100 - ) + p <- p + ggrepel::geom_text_repel(max.overlaps = 100) } # Set same limits for x and y axis for sim VS obs scatter plots @@ -449,14 +446,14 @@ plot_scat_versions_per_sit <- function(df_data, p <- ggplot2::ggplot( df_data, - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + label = .data$sit_name, + ) ) p <- p + ggplot2::geom_point( - ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), - colour = as.factor(.data$version) - ), + ggplot2::aes(colour = as.factor(.data$version)), na.rm = TRUE ) + ggplot2::labs(color = "Version") @@ -466,7 +463,9 @@ plot_scat_versions_per_sit <- function(df_data, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), method = lm, color = "blue", + inherit.aes = FALSE, se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE ) + @@ -515,13 +514,15 @@ plot_scat_versions_allsit <- function(df_data, p <- ggplot2::ggplot( df_data, - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]) + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + label = .data$sit_name + ) ) if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point( ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), colour = as.factor(.data$version) ), na.rm = TRUE @@ -535,7 +536,6 @@ plot_scat_versions_allsit <- function(df_data, # they can put shape_sit = "none" or shape_sit = "txt" to have it all. p <- p + ggplot2::geom_point( ggplot2::aes( - text = paste0("Situation: ", .data$sit_name), colour = as.factor(.data$version), shape = as.factor(.data$sit_name) ), @@ -550,6 +550,8 @@ plot_scat_versions_allsit <- function(df_data, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( + ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), + inherit.aes = FALSE, method = lm, color = "blue", se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE @@ -576,10 +578,7 @@ plot_scat_versions_allsit <- function(df_data, if (shape_sit == "txt") { p <- p + ggrepel::geom_text_repel( - ggplot2::aes( - label = .data$sit_name, - colour = as.factor(.data$version) - ), + ggplot2::aes(colour = as.factor(.data$version)), show.legend = FALSE, max.overlaps = 100 ) diff --git a/README.md b/README.md index 97bd4268..1a0f1a3c 100644 --- a/README.md +++ b/README.md @@ -31,24 +31,26 @@ page](https://github.com/SticsRPacks/CroPlotR). ## Table of Contents -- [1. Installation](#1-installation) -- [2. Examples](#2-examples) - - [2.1 Plotting](#21-plotting) - - [2.1.1 Dynamic plots](#211-dynamic-plots) - - [2.1.2 Scatter plots](#212-scatter-plots) - - [2.1.3 Group comparison](#213-group-comparison) - - [2.1.4 Plot saving](#214-plot-saving) - - [2.1.5 Plot extracting](#215-plot-extracting) - - [2.2 Statistics](#22-statistics) - - [2.2.1 Dynamic plots](#221-simple-case) - - [2.2.2 Several groups](#222-several-groups) - - [2.2.3 Statistics plot](#223-statistics-plot) - - [2.3 Data manipulation](#23-data-manipulation) -- [3. Tools](#3-tools) - - [3.1 ggplotly](#31-ggplotly) - - [3.2 patchwork](#32-patchwork) -- [4. Help](#4-help) -- [5. Citation](#5-Citation) +- [CroPlotR](#croplotr) + - [Table of Contents](#table-of-contents) + - [1. Installation](#1-installation) + - [2. Examples](#2-examples) + - [2.1 Plotting](#21-plotting) + - [2.1.1 Dynamic plots](#211-dynamic-plots) + - [2.1.2 Scatter plots](#212-scatter-plots) + - [2.1.3 Group comparison](#213-group-comparison) + - [2.1.4 Plot saving](#214-plot-saving) + - [2.1.5 Plot extracting](#215-plot-extracting) + - [2.2 Statistics](#22-statistics) + - [2.2.1 Simple case](#221-simple-case) + - [2.2.2 Several groups](#222-several-groups) + - [2.2.3 Statistics plot](#223-statistics-plot) + - [2.3 Data manipulation](#23-data-manipulation) + - [3. Tools](#3-tools) + - [3.1 ggplotly](#31-ggplotly) + - [3.2 patchwork](#32-patchwork) + - [4. Help](#4-help) + - [5. Citation](#5-citation) ## 1. Installation @@ -820,7 +822,7 @@ function. ``` r library(plotly) -ggplotly(plot(sim, obs = obs, type = "dynamic")[[1]]) +ggplotly(plot(sim, obs = obs, type = "dynamic")[[1]], tooltip = c("label")) ``` ### 3.2 patchwork From e0561ceb1e77688bc87522fe67fc140a77ea9655 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Mon, 12 Jan 2026 17:16:58 +0100 Subject: [PATCH 075/118] Avoid saving plots twice (bad previous merge?) --- tests/testthat/test-dynamic-plots.R | 2 -- tests/testthat/test-scatter-plots.R | 2 -- 2 files changed, 4 deletions(-) diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index 9a53e777..07b9024b 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -497,6 +497,4 @@ test_that("Test successive plot", { if (!testthat:::on_ci()) { save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_dynamic") print(paste("Plots saved in pdf format in ", tmpdir)) - save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_dynamic") - print(paste("Plots saved in pdf format in ", tmpdir)) } diff --git a/tests/testthat/test-scatter-plots.R b/tests/testthat/test-scatter-plots.R index bdab0b7c..48f74f09 100644 --- a/tests/testthat/test-scatter-plots.R +++ b/tests/testthat/test-scatter-plots.R @@ -362,6 +362,4 @@ invisible(lapply(seq_len(nrow(tmp)), function(i) { if (!testthat:::on_ci()) { save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_scatter") print(paste("Plots saved in pdf format in ", tmpdir)) - save_plot_pdf(all_plots, out_dir = tmpdir, file_name = "all_plots_scatter") - print(paste("Plots saved in pdf format in ", tmpdir)) } From dbc97c3bd89d575d820747d7baf5367ba348f5ea Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Mon, 12 Jan 2026 17:18:37 +0100 Subject: [PATCH 076/118] Fix zzz.R --- R/zzz.R | 28 +++++++++------------------- 1 file changed, 9 insertions(+), 19 deletions(-) diff --git a/R/zzz.R b/R/zzz.R index 72739878..48fbdb2f 100644 --- a/R/zzz.R +++ b/R/zzz.R @@ -1,23 +1,13 @@ -text_col <- function(x) { - # This function is adapted from: https://github.com/tidyverse/tidyverse - # If RStudio not available, messages already printed in black - if (!rstudioapi::isAvailable()) { - return(x) - } - if (!rstudioapi::hasFun("getThemeInfo")) { - return(x) - } - theme <- rstudioapi::getThemeInfo() - - if (isTRUE(theme$dark)) crayon::white(x) else crayon::black(x) -} - - .onAttach <- function(libname, pkgname) { packageStartupMessage( - text_col(paste( - "Learn CroPlotR at:", - crayon::blue$underline$bold("https://SticsRPacks.github.io/CroPlotR") - )) + "Learn CroPlotR at: https://SticsRPacks.github.io/CroPlotR" ) + packageStartupMessage("") + + cite <- utils::citation("CroPlotR") + # Remove underscores around titles (used by R to indicate italics) + cite_text <- gsub("_([^_]*)_", "\\1", format(cite, style = "text")) + + packageStartupMessage("Please cite CroPlotR in your work:") + packageStartupMessage(format(cite_text, style = "text")) } From a718bc93d6725fff3df61444fbda9de4bffeb0e7 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Mon, 12 Jan 2026 22:07:52 +0100 Subject: [PATCH 077/118] fix: added gh4x >= 0.3.1 in Description file (#116) Lower versions caused many warnings. --- DESCRIPTION | 1 + 1 file changed, 1 insertion(+) diff --git a/DESCRIPTION b/DESCRIPTION index 01419dfa..875ce2c3 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -36,6 +36,7 @@ Depends: Imports: cli, dplyr, + ggh4x (>= 0.3.1), ggplot2, ggrepel, gridExtra, From 148db737bcf609cf8710695a251a8f5524baeaef Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 10:25:16 +0100 Subject: [PATCH 078/118] fix adding line regression per version per sit --- R/specific_plotting_scatter.R | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index e93f5b95..04f6f1d0 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -463,8 +463,11 @@ plot_scat_versions_per_sit <- function(df_data, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), - method = lm, color = "blue", + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + colour = as.factor(.data$version) + ), + method = lm, inherit.aes = FALSE, se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE From f7bd75ccbcc89119125e46257cf17fb6edbc3ddb Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Tue, 13 Jan 2026 10:56:08 +0100 Subject: [PATCH 079/118] Fix to display the 0.0 for residual plots --- R/specific_plotting_scatter.R | 44 +++++++++++++++++++++++++++++++++++ man/specific_scatter_plots.Rd | 8 +++++++ 2 files changed, 52 insertions(+) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 04f6f1d0..cf25307d 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -92,6 +92,35 @@ make_axis_square <- function(df_data, reference_var, y_var_type, is_obs_sd, p) { return(p) } +#' @keywords internal +#' @description Ensure that the Y axis includes zero when all values in a facet +#' are strictly positive or strictly negative. +#' @rdname specific_scatter_plots +#' @param p A ggplot to modify` +#' @param y_var_type type of variable to plot ("Simulated" or "Residuals") +#' @return The modified ggplot +force_y_axis <- function(df_data, reference_var, y_var_type, is_obs_sd, p) { + axis_bounds <- compute_axis_bounds( + df_data, + reference_var, + y_var_type, + is_obs_sd + ) + y_min <- axis_bounds$yaxis_min + y_max <- axis_bounds$yaxis_max + + # New y limits per facet + y_min_new <- ifelse(y_min > 0, 0, y_min) + y_max_new <- ifelse(y_max < 0, 0, y_max) + + p + + ggh4x::facetted_pos_scales( + y = lapply(seq_along(y_min_new), function(i) { + ggplot2::scale_y_continuous(limits = c(y_min_new[i], y_max_new[i])) + }) + ) +} + #' Get reference variable for plotting #' #' @description Return the reference variable and its display name for scatter @@ -241,6 +270,9 @@ plot_scat_mixture_allsit <- function(df_data, sit, select_scat, shape_sit, if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } + if (select_scat == "res") { + p <- force_y_axis(df_data, reference_var, y_var_type, is_obs_sd, p) + } p <- p + ggplot2::scale_color_discrete(name = "Plant") @@ -341,6 +373,9 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } + if (select_scat == "res") { + p <- force_y_axis(df_data, reference_var, y_var_type, is_obs_sd, p) + } return(p) } @@ -418,6 +453,9 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } + if (select_scat == "res") { + p <- force_y_axis(df_data, reference_var, y_var_type, is_obs_sd, p) + } if ( has_distinct_situations == FALSE && one_version == TRUE && @@ -495,6 +533,9 @@ plot_scat_versions_per_sit <- function(df_data, if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } + if (select_scat == "res") { + p <- force_y_axis(df_data, reference_var, y_var_type, is_obs_sd, p) + } return(p) } @@ -591,6 +632,9 @@ plot_scat_versions_allsit <- function(df_data, if (select_scat == "sim" && reference_var == "Observed") { p <- make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) } + if (select_scat == "res") { + p <- force_y_axis(df_data, reference_var, y_var_type, is_obs_sd, p) + } return(p) } diff --git a/man/specific_scatter_plots.Rd b/man/specific_scatter_plots.Rd index bcafc695..7a1727f2 100644 --- a/man/specific_scatter_plots.Rd +++ b/man/specific_scatter_plots.Rd @@ -4,6 +4,7 @@ \alias{specific_scatter_plots} \alias{compute_axis_bounds} \alias{make_axis_square} +\alias{force_y_axis} \alias{add_obs_error_bars} \alias{plot_scat_mixture_allsit} \alias{plot_scat_mixture_versions} @@ -16,6 +17,8 @@ compute_axis_bounds(df_data, reference_var, y_var_type, is_obs_sd) make_axis_square(df_data, reference_var, y_var_type, is_obs_sd, p) +force_y_axis(df_data, reference_var, y_var_type, is_obs_sd, p) + add_obs_error_bars(p, colour_factor = NULL) plot_scat_mixture_allsit( @@ -101,6 +104,8 @@ yaxis_max) The modified ggplot +The modified ggplot + The modified ggplot } \description{ @@ -112,6 +117,9 @@ Compute axis bounds (+/-0.05 added to the min/max of the data). Make axis square +Ensure that the Y axis includes zero when all values in a facet +are strictly positive or strictly negative. + Add error bars on observed values in given scatterplot } \details{ From 98ba7c29e84ce8cd08449b7eada3cde18da35813 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 10:56:45 +0100 Subject: [PATCH 080/118] fix plot shape=sit-text --- R/specific_plotting_scatter.R | 10 +++++++++- 1 file changed, 9 insertions(+), 1 deletion(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 04f6f1d0..1a88d7f4 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -475,7 +475,15 @@ plot_scat_versions_per_sit <- function(df_data, ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~ .data$var, scales = "free") - p <- p + ggplot2::ggtitle(title) + p <- p + ggplot2::ggtitle(title) + + if (shape_sit == "txt") { + ggrepel::geom_text_repel( + ggplot2::aes(label = .data$sit_name), + na.rm = TRUE, + show.legend = FALSE, + max.overlaps = Inf + ) + } if (is_obs_sd && reference_var == "Observed") { p <- p + From 3748916eb749d4530b0ae340419acb030503135b Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 09:59:49 +0000 Subject: [PATCH 081/118] Style code (GHA) --- R/specific_plotting_scatter.R | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index e6c3f5d9..a01f718a 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -514,14 +514,14 @@ plot_scat_versions_per_sit <- function(df_data, ggplot2::facet_wrap(~ .data$var, scales = "free") p <- p + ggplot2::ggtitle(title) + - if (shape_sit == "txt") { - ggrepel::geom_text_repel( - ggplot2::aes(label = .data$sit_name), - na.rm = TRUE, - show.legend = FALSE, - max.overlaps = Inf - ) - } + if (shape_sit == "txt") { + ggrepel::geom_text_repel( + ggplot2::aes(label = .data$sit_name), + na.rm = TRUE, + show.legend = FALSE, + max.overlaps = Inf + ) + } if (is_obs_sd && reference_var == "Observed") { p <- p + From fabb320e304be2dddb1b7d50108a58bfb63353c3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Tue, 13 Jan 2026 11:11:07 +0100 Subject: [PATCH 082/118] Update specific_plotting_dynamic.R fix last 4 warnings in the tests (use the dates as dates, because the x axis is already a date object) --- R/specific_plotting_dynamic.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index 0cc2c6e8..0b9aeb03 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -59,8 +59,9 @@ plot_dynamic <- function(df_data, sit, successive, title = NULL) { if (!is.null(successive)) { dates <- unique(df_data$succession_date) dates_vlines <- as.POSIXct(dates, tz = "UTC") + p <- p + ggplot2::geom_vline( - xintercept = as.numeric(dates_vlines[-length(dates_vlines)]), + xintercept = dates_vlines[-length(dates_vlines)], linetype = "dashed", color = "black" ) From c3d8a1a875a8ea00a7502f1df186779b59064b19 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 11:16:47 +0100 Subject: [PATCH 083/118] fix adding line regression case of version all situations --- R/specific_plotting_scatter.R | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index a01f718a..5aff532a 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -602,9 +602,12 @@ plot_scat_versions_allsit <- function(df_data, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + colour = as.factor(.data$version) + ), inherit.aes = FALSE, - method = lm, color = "blue", + method = lm, se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE ) + From dd6d8471e28656bbd3d6e1e26ed519de0f2cd023 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 11:34:35 +0100 Subject: [PATCH 084/118] fix adding line regression per version for mixture_versiont --- R/specific_plotting_scatter.R | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 5aff532a..6573c9d0 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -333,9 +333,12 @@ plot_scat_mixture_versions <- function(df_data, sit, select_scat, shape_sit, color = "grey30", linetype = 2 ) + ggplot2::geom_smooth( - ggplot2::aes(y = .data[[y_var_type]], x = .data[[reference_var]]), + ggplot2::aes( + y = .data[[y_var_type]], x = .data[[reference_var]], + colour = as.factor(.data$version) + ), inherit.aes = FALSE, - method = lm, color = "blue", + method = lm, se = FALSE, linewidth = 0.6, formula = y ~ x, fullrange = TRUE, na.rm = TRUE ) + From 93d2c3951aa7444876e73add468ef378e31d7617 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 13:22:45 +0100 Subject: [PATCH 085/118] fix title test plot 31 --- tests/testthat/_inputs/tests_scatter_plots.csv | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/testthat/_inputs/tests_scatter_plots.csv b/tests/testthat/_inputs/tests_scatter_plots.csv index 4ce09e52..29e4c533 100644 --- a/tests/testthat/_inputs/tests_scatter_plots.csv +++ b/tests/testthat/_inputs/tests_scatter_plots.csv @@ -28,8 +28,8 @@ Number;Title;select_scat ;mixture;version;all_situations;shape_sit;reference_var 27;Mixture, shape_sit=txt, All situations, res;res;TRUE;FALSE;TRUE;txt;NULL;"Plant";NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 28;Mixture, shape_sit=symbol, All situations, res;res;TRUE;FALSE;TRUE;symbol;NULL;"Plant";Situation;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE 29;Mixture (shape_sit=group), All situations, res;res;TRUE;FALSE;TRUE;group;NULL;"Plant";Situation;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE -30;Sole crop, per situation, res;res;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;FALSE -31;Sole crop, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;Version;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE +30;Sole crop, per situation, res;res;FALSE;FALSE;FALSE;none;NULL;NULL;NULL;NULL;NULL;Version;NULL;NULL;NULL;1;1;1;TRUE;FALSE +31;Sole crop, Versions, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;Version;NULL;NULL;NULL;NULL;NULL;NULL;NULL;1;1;1;TRUE;TRUE 32;Sole crop, Versions, per situation, res;res;FALSE;TRUE;FALSE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE 33;Sole crop, Versions, All situations, res;res;FALSE;TRUE;TRUE;none;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;TRUE 34;Sole crop, Versions, shape_sit=txt, All situations, res;res;FALSE;TRUE;TRUE;txt;NULL;Version;NULL;NULL;NULL;Version;NULL;Version;NULL;1;1;1;TRUE;FALSE From c034c087ef8e6e203246bea5920630e34bd88e54 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Tue, 13 Jan 2026 14:05:17 +0100 Subject: [PATCH 086/118] Fix color of the error bars --- R/specific_plotting_scatter.R | 18 ++++++++++++------ 1 file changed, 12 insertions(+), 6 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 6573c9d0..b7691159 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -405,7 +405,6 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, label = .data$sit_name ) ) - if (shape_sit == "none" || shape_sit == "txt") { p <- p + ggplot2::geom_point(na.rm = TRUE) } else if (shape_sit == "symbol" || shape_sit == "group") { @@ -437,13 +436,20 @@ plot_scat_allsit <- function(df_data, sit, select_scat, shape_sit, ggplot2::ggtitle(title) if (is_obs_sd && reference_var == "Observed") { - p <- p + ggplot2::geom_linerange( - ggplot2::aes( + line_aes <- NULL + if (shape_sit == "symbol" || shape_sit == "group") { + line_aes <- ggplot2::aes( xmin = .data$Observed - 2 * .data$Obs_SD, xmax = .data$Observed + 2 * .data$Obs_SD, - ), - na.rm = TRUE - ) + colour = as.factor(paste(.data$sit_name)) + ) + } else { + line_aes <- ggplot2::aes( + xmin = .data$Observed - 2 * .data$Obs_SD, + xmax = .data$Observed + 2 * .data$Obs_SD + ) + } + p <- p + ggplot2::geom_linerange(line_aes, na.rm = TRUE) } p <- p + ggplot2::theme(aspect.ratio = 1) From 2f22269a001814397cc8eec4f3682e04c612c452 Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 14:44:14 +0100 Subject: [PATCH 087/118] fix remove duplicated code --- R/generic_formatting.R | 20 -------------------- 1 file changed, 20 deletions(-) diff --git a/R/generic_formatting.R b/R/generic_formatting.R index 1365897d..9efb7087 100644 --- a/R/generic_formatting.R +++ b/R/generic_formatting.R @@ -46,12 +46,6 @@ generic_formatting <- function( df <- df %>% dplyr::filter(.data$variable %in% var) } - # Replace NAs with "Single-crop" in Dominance in order to make - # the legend understandable - if ("Dominance" %in% colnames(df)) { - levels(df$Dominance) <- c("Principal", "Associated", "Single crop") - df$Dominance[which(is.na(df$Dominance))] <- "Single crop" - } # Replace NAs with "Single-crop" in Dominance in order to make # the legend understandable if ("Dominance" %in% colnames(df)) { @@ -59,20 +53,6 @@ generic_formatting <- function( df$Dominance[which(is.na(df$Dominance))] <- "Single crop" } - # Add group_var column to data frame if overlap != null - if (!is.null(overlap)) { - df <- dplyr::bind_cols( - df, - data.frame("group_var" = rep(NA, nrow(df))) - ) - for (vars in overlap) { - vars <- unique(c(vars, subst_parenth(vars))) - df$group_var[which(df$variable %in% vars)] <- - paste(intersect(df$variable, vars), collapse = " | ") - } - df$group_var[which(is.na(df$group_var))] <- - as.character(df$variable[which(is.na(df$group_var))]) - } # Add group_var column to data frame if overlap != null if (!is.null(overlap)) { df <- dplyr::bind_cols( From 11e07bee8569f610322e3fd1b8fadae7d4b38f71 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Tue, 13 Jan 2026 15:49:06 +0100 Subject: [PATCH 088/118] Closes #117 + fix an issue for scatter plots where we detected a mixture in the obs even if that usm is not used (not present in the sim) --- R/cropr_formatting.R | 106 +++++++++++++++-------- R/generic_formatting.R | 30 ++----- R/generic_plotting.R | 5 +- tests/testthat/test-dynamic-plots.R | 25 ++++++ tests/testthat/test-generic_formatting.R | 2 +- 5 files changed, 107 insertions(+), 61 deletions(-) diff --git a/R/cropr_formatting.R b/R/cropr_formatting.R index 8ade52f9..3ac9493a 100644 --- a/R/cropr_formatting.R +++ b/R/cropr_formatting.R @@ -16,6 +16,8 @@ #' @param reference_var Variable selected on x-axis when type is scatter and #' select_scat is res. It is possible to select between observation and #' simulation of the reference variable. +#' @param variable A character vector indicating the variables to be kept in +#' the formatted data frame. If NULL (default), all variables are kept. #' @param verbose Logical value for displaying information while running. #' #' @details The `select_dyn` argument can be: @@ -63,6 +65,7 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, select_dyn = c("sim", "common", "obs", "all"), select_scat = c("sim", "res"), successive = NULL, reference_var = NULL, + variable = NULL, verbose = TRUE) { type <- match.arg(type, c("dynamic", "scatter"), several.ok = FALSE) select_dyn <- match.arg(select_dyn, c("sim", "common", "obs", "all"), @@ -73,6 +76,22 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, is_obs <- !is.null(obs) && isTRUE(nrow(obs) > 0) is_obs_sd <- !is.null(obs_sd) && isTRUE(nrow(obs_sd) > 0) + # Keep only the situations that are in both sim and obs if any + if (type == "scatter") { + if (!is_obs) { + stop("No observations found, impossible to make scatter plot.") + } + if ("sit_name" %in% colnames(obs) && "sit_name" %in% colnames(sim)) { + inter_sit <- intersect(unique(obs$sit_name), unique(sim$sit_name)) + obs <- filter(obs, .data$sit_name %in% inter_sit) + + if (is_obs_sd) { + obs_sd <- filter(obs_sd, .data$sit_name %in% inter_sit) + } + sim <- filter(sim, .data$sit_name %in% inter_sit) + } + } + is_mixture_sim <- detect_mixture(sim) is_mixture_obs <- detect_mixture(obs) @@ -89,6 +108,58 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, ) } + # Check variable names: + if (!is.null(variable)) { + variable <- unique(subst_parenth(variable)) + var_exist <- variable %in% unique(colnames(sim)) + if (!all(var_exist)) { + stop( + "Unknown variable(s) in input data.frame: ", + paste(variable[!var_exist], collapse = ", ") + ) + } + } + + # Defining variables to keep depending on the case: + if (is_mixture_sim || is_mixture_obs) { + rem_vars <- NULL + melt_vars <- c("Date", "Plant", "Dominance") + } else { + rem_vars <- c("Plant") + melt_vars <- "Date" + } + + if (!is.null(successive)) { + melt_vars <- c(melt_vars, "succession_date") + } + + if ("sit_name" %in% colnames(sim)) { + melt_vars <- c(melt_vars, "sit_name") + } + + # By default, we use the same variables to melt and then to join: + join_vars <- c(melt_vars, "variable") + + # But if there are several versions of the model, we add the version + # for melting, but not for joining because the obs and obs_sd are the + # same for all versions: + if ("version" %in% colnames(sim)) { + melt_vars_sim <- c(melt_vars, "version") + } else { + melt_vars_sim <- melt_vars + } + + # Identify which columns are character vectors: + string_cols <- names(sim)[sapply(sim, is.character)] + + if (!is.null(variable)) { + rem_vars <- setdiff(colnames(sim), c(melt_vars_sim, variable)) + } + + # Add them to the variables removed from the data frame, + # but remove the ones that are used for melting: + rem_vars <- setdiff(union(rem_vars, string_cols), melt_vars_sim) + # Adding Dominance to obs if any: if (is_obs && is_mixture_obs) { if (is.null(obs$Dominance)) { @@ -208,41 +279,6 @@ format_cropr <- function(sim, obs = NULL, obs_sd = NULL, } } - if (is_mixture_sim && is_mixture_obs) { - rem_vars <- NULL - melt_vars <- c("Date", "Plant", "Dominance") - } else { - rem_vars <- c("Plant") - melt_vars <- "Date" - } - if (!is.null(successive)) { - # rem_vars <- c(rem_vars, "succession_date") - melt_vars <- c(melt_vars, "succession_date") - } - - if ("sit_name" %in% colnames(sim)) { - melt_vars <- c(melt_vars, "sit_name") - } - - # By default, we use the same variables to melt and then to join: - join_vars <- c(melt_vars, "variable") - - # But if there are several versions of the model, we add the version - # for melting, but not for joining because the obs and obs_sd are the - # same for all versions: - if ("version" %in% colnames(sim)) { - melt_vars_sim <- c(melt_vars, "version") - } else { - melt_vars_sim <- melt_vars - } - - # Identify which columns are character vectors: - string_cols <- names(sim)[sapply(sim, is.character)] - - # Add them to the variables removed from the data frame, - # but remove the ones that are used for melting: - rem_vars <- setdiff(union(rem_vars, string_cols), melt_vars_sim) - # Create data frame like sim or obs to change reference variable when # residual scatter plot if (!is.null(reference_var)) { diff --git a/R/generic_formatting.R b/R/generic_formatting.R index 1365897d..222292f5 100644 --- a/R/generic_formatting.R +++ b/R/generic_formatting.R @@ -4,7 +4,6 @@ #' parameters. #' #' @param df A data frame to be formatted (e.g. output from `format_cropr`). -#' @param var A character string indicating the variable to be formatted. #' @param overlap A logical value indicating whether there is any overlapping #' variables desired in the plot. #' @param situation_group A character string indicating the situation group. @@ -24,28 +23,13 @@ #' @keywords internal #' generic_formatting <- function( - df, - var, - overlap, - situation_group, - type, - shape_sit, - has_distinct_situations, - total_vers -) { - # Filter selected variables - if (!is.null(var)) { - var <- unique(c(var, subst_parenth(var))) - var_exist <- var %in% unique(df$variable) - if (!all(var_exist)) { - stop( - "Unknown variable(s) in input data.frame: ", - paste(var[!var_exist], collapse = ", ") - ) - } - df <- df %>% dplyr::filter(.data$variable %in% var) - } - + df, + overlap, + situation_group, + type, + shape_sit, + has_distinct_situations, + total_vers) { # Replace NAs with "Single-crop" in Dominance in order to make # the legend understandable if ("Dominance" %in% colnames(df)) { diff --git a/R/generic_plotting.R b/R/generic_plotting.R index 32806000..44ec8e40 100644 --- a/R/generic_plotting.R +++ b/R/generic_plotting.R @@ -129,10 +129,11 @@ plot_situations <- function(..., obs = NULL, obs_sd = NULL, type, select_dyn, select_scat, successive = successive, reference_var = reference_var, - verbose = verbose + verbose = verbose, + variable = var ) %>% generic_formatting( - var, overlap, situation_group, type, shape_sit, + overlap, situation_group, type, shape_sit, has_distinct_situations, length(dot_args) ) diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index 07b9024b..e57f4001 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -245,6 +245,31 @@ test_that("Test plot only mixture", { } }) +# Also add a test without observations: +test_that("Test plot only mixture without obs", { + test_plot <- plot(sim_mixture) + all_plots <<- c(all_plots, test_plot) + labels <- ggplot2::get_labs(test_plot$`IC_Wheat_Pea_2005-2006_N0`) + expect_equal(labels$shape, NULL) + expect_equal(labels$colour, "Plant") + lapply(names(test_plot), function(x) { + make_snapshot( + paste0(prefix, "_fig.4_mixture_no_obs_", x, pkg_version), + test_plot[[x]], + tmpdir + ) + }) + ## add title for visual inspection of the graph + test_plot <- lapply(test_plot, function(x) { + x + + ggplot2::labs(caption = "plot only mixture without obs") + + ggplot2::theme( + plot.caption = ggplot2::element_text(hjust = 0.5, color = "red") + ) + }) + all_plots <<- c(all_plots, test_plot) +}) + ### only version test_that("Test plot only version", { diff --git a/tests/testthat/test-generic_formatting.R b/tests/testthat/test-generic_formatting.R index 3564ad3f..374192ee 100644 --- a/tests/testthat/test-generic_formatting.R +++ b/tests/testthat/test-generic_formatting.R @@ -26,6 +26,7 @@ df_sit <- format_cropr( args_list$select_scat, args_list$successive, args_list$reference_var, + args_list$var, args_list$verbose ) @@ -33,7 +34,6 @@ df_sit <- format_cropr( # Apply generic_formatting: df_all <- generic_formatting( df_sit, - args_list$var, args_list$overlap, args_list$situation_group, args_list$type, args_list$shape_sit, From a4e4ee3652be402671fd8f9aec8f197f16fd9be0 Mon Sep 17 00:00:00 2001 From: VEZY Date: Tue, 13 Jan 2026 14:58:19 +0000 Subject: [PATCH 089/118] Style code (GHA) --- R/generic_formatting.R | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/R/generic_formatting.R b/R/generic_formatting.R index 262e8fa9..d7ab9f19 100644 --- a/R/generic_formatting.R +++ b/R/generic_formatting.R @@ -23,13 +23,14 @@ #' @keywords internal #' generic_formatting <- function( - df, - overlap, - situation_group, - type, - shape_sit, - has_distinct_situations, - total_vers) { + df, + overlap, + situation_group, + type, + shape_sit, + has_distinct_situations, + total_vers +) { # Replace NAs with "Single-crop" in Dominance in order to make # the legend understandable if ("Dominance" %in% colnames(df)) { From b15f4d19469d7c23e7117842dd0b7fa7be569e7c Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 16:03:55 +0100 Subject: [PATCH 090/118] update dynamic test script --- tests/testthat/test-dynamic-plots.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/testthat/test-dynamic-plots.R b/tests/testthat/test-dynamic-plots.R index 07b9024b..27b8c9bb 100644 --- a/tests/testthat/test-dynamic-plots.R +++ b/tests/testthat/test-dynamic-plots.R @@ -413,8 +413,8 @@ test_that("Test plot mixture + version", { } else { labels <- ggplot2::get_labs(test_plot$`IC_Wheat_Pea_2005-2006_N0`) expect_equal(labels$shape, NULL) - expect_equal(labels$colour, "paste(Dominance, \":\", Plant)") - expect_equal(labels$linetype, "version") + expect_equal(labels$colour, "Plant") + expect_equal(labels$linetype, "Version") expect_equal( all(sapply( From a7bb1dd3d0f0f1d749ca66c3967a9940c3f2e13c Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Tue, 13 Jan 2026 16:05:47 +0100 Subject: [PATCH 091/118] update legend mixture version without dominance --- R/specific_plotting_dynamic.R | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/R/specific_plotting_dynamic.R b/R/specific_plotting_dynamic.R index 0b9aeb03..2e1413d9 100644 --- a/R/specific_plotting_dynamic.R +++ b/R/specific_plotting_dynamic.R @@ -313,6 +313,10 @@ plot_dynamic_mixture_versions <- function(df_data, sit, title = NULL) { } } p <- p + - ggplot2::ggtitle(title) + ggplot2::ggtitle(title) + + ggplot2::labs( + colour = "Plant", + linetype = "Version" + ) return(p) } From 9c26b032bf82bba48566108f8854e11d274ef6ad Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Tue, 13 Jan 2026 17:46:31 +0100 Subject: [PATCH 092/118] Re-organize the sections + add section for cropr_simulation (continue after this one) --- README.Rmd | 251 ++++++++++++++++++++++++++++++++--------------------- 1 file changed, 154 insertions(+), 97 deletions(-) diff --git a/README.Rmd b/README.Rmd index d8679c7a..8b02de31 100644 --- a/README.Rmd +++ b/README.Rmd @@ -28,19 +28,14 @@ coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/master/graph/badge.s -`CroPlotR` aims at the standardization of the process of analyzing the -outputs from crop models such as -[STICS](https://www6.paca.inrae.fr/stics_eng/), -[APSIM](https://www.apsim.info/) or really any model. +`CroPlotR` aims at the standardization of the process of analyzing the outputs from crop models such as +[STICS](https://www6.paca.inrae.fr/stics_eng/), [APSIM](https://www.apsim.info/) or really any model. -Its use does not need any particular adaptation if your model has been -wrapped with the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) -package. +Its use does not need any particular adaptation if your model has been wrapped with the +[CroptimizR](https://github.com/SticsRPacks/CroptimizR) package thanks to the use of the `cropr_simulation` standard of data representation (see section below). -If you want to be notified when a new release of this package is made, -you can tick the Releases box in the "Watch / Unwatch =\> Custom" menu -at the top right of [this -page](https://github.com/SticsRPacks/CroPlotR). +If you want to be notified when a new release of this package is made, you can tick the Releases box in the "Watch / Unwatch =\> Custom" menu +at the top right of [this page](https://github.com/SticsRPacks/CroPlotR). ## Table of Contents @@ -63,11 +58,10 @@ page](https://github.com/SticsRPacks/CroPlotR). - [4. Help](#4-help) - [5. Citation](#5-Citation) -## 1. Installation +## Installation -You can install the released version of CroPlotR from -[Github](https://github.com/SticsRPacks/CroPlotR) either using -`devtools` or the lightweight `remotes` package: +You can install the released version of CroPlotR from [Github](https://github.com/SticsRPacks/CroPlotR) either using +`devtools` or the more lightweight `remotes` package: - With `devtools` @@ -82,41 +76,32 @@ devtools::install_github("SticsRPacks/CroPlotR@*release") remotes::install_github("SticsRPacks/CroPlotR@*release") ``` -Normally, all the package dependencies will be installed for CRAN -packages. +## Introduction -## 2. Examples +Only one function is exported for plots [`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html) +(and its alias `autoplot()`), and one for the statistics [`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html). +These functions should be the only one you need for all your plots and summary statistics. Additional ones are provided to simplify the +manipulation of simulated data (see [2.3 Data manipulation](#23-data-manipulation)). -At the moment, only one function is exported for plots -[`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html) -(and its alias `autoplot()`), and one for the statistics -[`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html). -These functions should be the only one you need for all your plots and -summary statistics. Additional ones are provided to simplify the -manipulation of simulated data (see [2.3 Data -manipulation](#23-data-manipulation)). +In the following, an example using the STICS crop model is presented. If you want to use another model for which a wrapper has been designed for +the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, just consider defining the `sim` variable used in the examples below as +`sim <- result$sim_list`, where `result` is the list returned by your model wrapper. Examples of use of CroPlotR with Stics and APSIM model +wrappers can be found in [CroptimizR's website](https://sticsrpacks.github.io/CroptimizR/) (see Articles tab). -In the following, an example using the STICS crop model is presented. If -you want to use another model for which a wrapper has been designed for -the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, -just consider defining the `sim` variable used in the examples below as -`sim <- result$sim_list`, where `result` is the list returned by your -model wrapper. Examples of use of CroPlotR with Stics and APSIM model -wrappers can be found in [CroptimizR's -website](https://sticsrpacks.github.io/CroptimizR/) (see Articles tab). +In the following examples, we use the `sim` and `obs` objects, which contains a simulation of two situations: -In the following example a simulation of three situations (called USM in -STICS) with their observations is used: - -- an intercrop of Wheat and pea - a Pea in sole crop - a Wheat in sole crop -Let's import the simulation and observation data: +We also use an intercrop situation with Wheat and Pea together, stored in `sim_intercrop` and `obs_intercrop`. -```{r} -library(CroPlotR) +

+ +Code to import the data + +To reproduce the data used in this file, you can use the following code snippet. It will import the data from an example simulation from the STICS model. +```{r} # Importing an example with three situations with observation: workspace <- system.file( file.path("extdata", "stics_example_1"), @@ -127,23 +112,82 @@ situations <- SticsRFiles::get_usms_list( file = file.path(workspace, "usms.xml") ) +usms_sole_crop <- c("SC_Pea_2005-2006_N0", "SC_Wheat_2005-2006_N0") +usms_intercrop <- c("IC_Wheat_Pea_2005-2006_N0") + sim <- SticsRFiles::get_sim( workspace = workspace, - usms_file = file.path(workspace, "usms.xml") + usms_file = file.path(workspace, "usms.xml"), + usm = usms_sole_crop +) + +sim_intercrop <- SticsRFiles::get_sim( + workspace = workspace, + usms_file = file.path(workspace, "usms.xml"), + usm = usms_intercrop ) obs <- SticsRFiles::get_obs( workspace = workspace, - usm = situations, + usm = usms_sole_crop, + usms_file = file.path(workspace, "usms.xml") +) + +obs_intercrop <- SticsRFiles::get_obs( + workspace = workspace, + usm = usms_intercrop, usms_file = file.path(workspace, "usms.xml") ) ``` -### 2.1 Plotting +## Data structure -#### 2.1.1 Dynamic plots +The `sim` and `obs` objects are named lists of `data.frame`s. Each element of +the list corresponds to a situation (a crop in a given year with a given management). Each `data.frame` contains the simulated or observed variables for this situation. -Here is an application of dynamic plots for the 3 situations: +Here's the structure of the `sim` object: + +```{r} +str(sim) +``` + +Or more visually: + +```{r} +lapply(sim, head) +``` + +The structure of the `obs` object is similar: + +```{r} +str(obs) +``` + +Note that the simulation structure is a special structure called `cropr_simulation`. You can easily make such an object from a named list of data.frames, and giving +the class attribute `cropr_simulation`, e.g.: + +```{r} +sim_test <- list( + situation_1 = data.frame( + Date = as.Date("2000-01-01") + 0:9, + var1 = rnorm(10), + var2 = rnorm(10) + ), + situation_2 = data.frame( + Date = as.Date("2001-01-01") + 0:9, + var1 = rnorm(10), + var2 = rnorm(10) + ) +) + +class(sim_test) <- append(class(sim_test), "cropr_simulation") +``` + +## Dynamic plots + +### Simple dynamic plot + +Here is an application of dynamic plots for two example situations: ```{r} p <- plot(sim, obs = obs) @@ -184,6 +228,12 @@ or index: p[[1]] ``` +### Observations + +{To fill} + +### Successive situations + It is possible to aggregate plots of multiple situations on the same graph when situations follow one another over time. This can be done using the `successive` parameter. @@ -211,6 +261,8 @@ plot( ) ``` +### Overlaying variables + We can also overlay variables thanks to the "overlap" parameter with dynamic plots. @@ -226,7 +278,50 @@ plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) > [sec_axis](https://ggplot2.tidyverse.org/reference/sec_axis.html) on > the resulting plot. -#### 2.1.2 Scatter plots +### Versions comparisons + +We can compare groups of simulations alongside by simply adding the +simulations objects one after the other (that is why the first argument +of the function is `...`). Group simulations can be the results of +simulations from different model versions, or simulations with different +parameter values. + +```{r} +workspace2 <- system.file( + file.path("extdata", "stics_example_2"), + package = "CroPlotR" +) + +sim2 <- SticsRFiles::get_sim( + workspace = workspace2, + usms_file = file.path(workspace2, "usms.xml") +) + +plot(sim, sim2, obs = obs, all_situations = FALSE) +``` + +Here only one plot is outputted because `workspace2` only contains the +intercrop situation. + +We can also name the corresponding group in the plot by naming them +while passing to the `plot()` function: + +```{r} +plot( + "New version" = sim, + original = sim2, + obs = obs, + type = "scatter", + all_situations = FALSE +) +``` + +### Intercrops + +{Add this section} + + +## Scatter plots Here are the same plots, but presented as scatter plots: @@ -357,45 +452,7 @@ obs_sd$`SC_Wheat_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] <- plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) ``` -#### 2.1.3 Group comparison - -We can compare groups of simulations alongside by simply adding the -simulations objects one after the other (that is why the first argument -of the function is `...`). Group simulations can be the results of -simulations from different model versions, or simulations with different -parameter values. - -```{r} -workspace2 <- system.file( - file.path("extdata", "stics_example_2"), - package = "CroPlotR" -) - -sim2 <- SticsRFiles::get_sim( - workspace = workspace2, - usms_file = file.path(workspace2, "usms.xml") -) - -plot(sim, sim2, obs = obs, all_situations = FALSE) -``` - -Here only one plot is outputted because `workspace2` only contains the -intercrop situation. - -We can also name the corresponding group in the plot by naming them -while passing to the `plot()` function: - -```{r} -plot( - "New version" = sim, - original = sim2, - obs = obs, - type = "scatter", - all_situations = FALSE -) -``` - -#### 2.1.4 Plot saving +## Plot saving The plots can be saved to disk using the `save_plot_png()` function as follows: @@ -426,7 +483,7 @@ plots <- plot(sim, obs = obs) save_plot_pdf(plot = plots, out_dir = "path/to/directory", file_per_var = FALSE) ``` -#### 2.1.5 Plot extracting +## Plot extraction When we have plots with several variables and several situations, the `extract_plot` function allows to keep the situations and variables that @@ -444,9 +501,9 @@ extract_plot( ) ``` -### 2.2 Statistics +## Statistics -#### 2.2.1 Simple case +### Simple case Here is an application of summary statistics for the 3 situations: @@ -479,7 +536,7 @@ s <- summary(sim, obs = obs, all_situations = TRUE) knitr::kable(s) ``` -#### 2.2.2 Several groups +### Several groups We can get statistics for each group of simulations by simply adding the simulations objects one after the other (as for the `plot()` function). @@ -531,7 +588,7 @@ Please read the help from and [`predictor_assessment()`](https://sticsrpacks.github.io/CroPlotR/reference/predictor_assessment.html). -#### 2.2.3 Statistics plot +### Statistics plot It is also possible to plot the statistics: @@ -646,7 +703,7 @@ plot( ) ``` -### 2.3 Data manipulation +## Data manipulation Observation lists can easily be handled using e.g. [dplyr](https://CRAN.R-project.org/package=dplyr), @@ -677,9 +734,9 @@ sim_new <- split_df2sim(df) lapply(sim_new, head) ``` -## 3. Tools +## Tools -### 3.1 ggplotly +### Interactivity with ggplotly The ggplotly function in plotly library makes it very easy to create interactive graphics from a ggplot. Do not hesitate to call it with your @@ -692,7 +749,7 @@ library(plotly) ggplotly(plot(sim, obs = obs, type = "dynamic")[[1]]) ``` -### 3.2 patchwork +### Combining plots with patchwork There is also the patchwork library that allows you to easily combine several ggplot into one. @@ -708,7 +765,7 @@ plot4 <- plot(sim, obs = obs, var = "masec_n")[[1]] plot1 + plot2 + plot3 + plot4 + plot_layout(ncol = 2) ``` -## 4. Help +## Finding help You can find help for the functions directly using the name of the function followed by the class of the object you need the method for: @@ -730,7 +787,7 @@ function followed by the class of the object you need the method for: If you have any problem, please [fill an issue](https://github.com/SticsRPacks/CroPlotR/issues) on Github. -## 5. Citation +## Citation If you have used this package for a study that led to a publication or report, please cite us. You can either use the citation tool from Github From 71a9753359f945ce786348f8cdf51805193d7e8a Mon Sep 17 00:00:00 2001 From: cyrillemidingoyi Date: Wed, 14 Jan 2026 10:28:52 +0100 Subject: [PATCH 093/118] fix Set the color of situation names according to the version --- R/specific_plotting_scatter.R | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index b7691159..9e7765b3 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -522,15 +522,17 @@ plot_scat_versions_per_sit <- function(df_data, ggplot2::xlab(reference_var_name) + ggplot2::facet_wrap(~ .data$var, scales = "free") - p <- p + ggplot2::ggtitle(title) + - if (shape_sit == "txt") { + p <- p + ggplot2::ggtitle(title) + if (shape_sit == "txt") { + p <- p + ggrepel::geom_text_repel( - ggplot2::aes(label = .data$sit_name), - na.rm = TRUE, + ggplot2::aes( + colour = as.factor(.data$version) + ), show.legend = FALSE, - max.overlaps = Inf + max.overlaps = 100 ) - } + } if (is_obs_sd && reference_var == "Observed") { p <- p + From c54b7e6aea6f33e91e62ae65265faf1760d435cb Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 14 Jan 2026 10:33:54 +0100 Subject: [PATCH 094/118] docs: update functions doc (#123) --- man/format_cropr.Rd | 4 ++++ man/generic_formatting.Rd | 3 --- 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/man/format_cropr.Rd b/man/format_cropr.Rd index d62f84cc..50596bf8 100644 --- a/man/format_cropr.Rd +++ b/man/format_cropr.Rd @@ -14,6 +14,7 @@ format_cropr( select_scat = c("sim", "res"), successive = NULL, reference_var = NULL, + variable = NULL, verbose = TRUE ) } @@ -38,6 +39,9 @@ when \code{type = "dynamic"} (implies that the situations are correctly ordered) select_scat is res. It is possible to select between observation and simulation of the reference variable.} +\item{variable}{A character vector indicating the variables to be kept in +the formatted data frame. If NULL (default), all variables are kept.} + \item{verbose}{Logical value for displaying information while running.} } \value{ diff --git a/man/generic_formatting.Rd b/man/generic_formatting.Rd index 352efdb2..fb075113 100644 --- a/man/generic_formatting.Rd +++ b/man/generic_formatting.Rd @@ -6,7 +6,6 @@ \usage{ generic_formatting( df, - var, overlap, situation_group, type, @@ -18,8 +17,6 @@ generic_formatting( \arguments{ \item{df}{A data frame to be formatted (e.g. output from \code{format_cropr}).} -\item{var}{A character string indicating the variable to be formatted.} - \item{overlap}{A logical value indicating whether there is any overlapping variables desired in the plot.} From edb6a9bf72f75641dbe8f7c31151221be9175c64 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Wed, 14 Jan 2026 11:04:18 +0100 Subject: [PATCH 095/118] Fix Ylim for plot of residues Closes #122 --- R/specific_plotting_scatter.R | 17 +++++++++++++++-- 1 file changed, 15 insertions(+), 2 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 9e7765b3..08f0c0d5 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -113,10 +113,23 @@ force_y_axis <- function(df_data, reference_var, y_var_type, is_obs_sd, p) { y_min_new <- ifelse(y_min > 0, 0, y_min) y_max_new <- ifelse(y_max < 0, 0, y_max) + expand_range <- function(min, max, mult = 0.05) { + delta <- max - min + if (delta == 0) delta <- abs(min) + 1e-9 + c(min - delta * mult, max + delta * mult) + } + + lims <- Map(function(lo, hi) { + base_min <- min(lo, 0) + base_max <- max(hi, 0) + + expand_range(base_min, base_max, 0.05) + }, y_min, y_max) + p + ggh4x::facetted_pos_scales( - y = lapply(seq_along(y_min_new), function(i) { - ggplot2::scale_y_continuous(limits = c(y_min_new[i], y_max_new[i])) + y = lapply(lims, function(l) { + ggplot2::scale_y_continuous(limits = l) }) ) } From b106e8747aa4dd9eb8efe4d92fa9a9478fb8cb32 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 14 Jan 2026 11:21:42 +0100 Subject: [PATCH 096/118] Build data on the fly and put it on a RData that users can import + move around things --- README.Rmd | 210 ++++++++++++---------- inst/extdata/readme_sim_obs_example.RData | Bin 0 -> 60242 bytes man/figures/README-unnamed-chunk-10-1.png | Bin 8183 -> 34519 bytes man/figures/README-unnamed-chunk-10-2.png | Bin 0 -> 36633 bytes man/figures/README-unnamed-chunk-12-1.png | Bin 8643 -> 36633 bytes man/figures/README-unnamed-chunk-15-1.png | Bin 8141 -> 27847 bytes man/figures/README-unnamed-chunk-15-2.png | Bin 0 -> 32228 bytes man/figures/README-unnamed-chunk-16-1.png | Bin 7035 -> 51388 bytes man/figures/README-unnamed-chunk-17-1.png | Bin 33309 -> 34370 bytes man/figures/README-unnamed-chunk-17-2.png | Bin 0 -> 34162 bytes man/figures/README-unnamed-chunk-19-1.png | Bin 7876 -> 32692 bytes man/figures/README-unnamed-chunk-20-1.png | Bin 8850 -> 38794 bytes man/figures/README-unnamed-chunk-21-1.png | Bin 7895 -> 31161 bytes man/figures/README-unnamed-chunk-22-1.png | Bin 8247 -> 70930 bytes man/figures/README-unnamed-chunk-23-1.png | Bin 10144 -> 38943 bytes man/figures/README-unnamed-chunk-24-1.png | Bin 10072 -> 33948 bytes man/figures/README-unnamed-chunk-25-1.png | Bin 0 -> 38128 bytes man/figures/README-unnamed-chunk-26-1.png | Bin 7800 -> 51747 bytes man/figures/README-unnamed-chunk-27-1.png | Bin 8093 -> 45980 bytes man/figures/README-unnamed-chunk-28-1.png | Bin 7800 -> 45980 bytes man/figures/README-unnamed-chunk-29-1.png | Bin 5815 -> 43580 bytes man/figures/README-unnamed-chunk-32-1.png | Bin 8583 -> 37074 bytes man/figures/README-unnamed-chunk-43-1.png | Bin 10628 -> 28690 bytes man/figures/README-unnamed-chunk-44-1.png | Bin 0 -> 23011 bytes man/figures/README-unnamed-chunk-45-1.png | Bin 14120 -> 33752 bytes man/figures/README-unnamed-chunk-46-1.png | Bin 0 -> 37880 bytes man/figures/README-unnamed-chunk-47-1.png | Bin 14169 -> 34252 bytes man/figures/README-unnamed-chunk-48-1.png | Bin 0 -> 53343 bytes man/format_cropr.Rd | 4 + man/generic_formatting.Rd | 3 - 30 files changed, 122 insertions(+), 95 deletions(-) create mode 100644 inst/extdata/readme_sim_obs_example.RData create mode 100644 man/figures/README-unnamed-chunk-10-2.png create mode 100644 man/figures/README-unnamed-chunk-15-2.png create mode 100644 man/figures/README-unnamed-chunk-17-2.png create mode 100644 man/figures/README-unnamed-chunk-25-1.png create mode 100644 man/figures/README-unnamed-chunk-44-1.png create mode 100644 man/figures/README-unnamed-chunk-46-1.png create mode 100644 man/figures/README-unnamed-chunk-48-1.png diff --git a/README.Rmd b/README.Rmd index 8b02de31..e3909e61 100644 --- a/README.Rmd +++ b/README.Rmd @@ -95,13 +95,11 @@ In the following examples, we use the `sim` and `obs` objects, which contains a We also use an intercrop situation with Wheat and Pea together, stored in `sim_intercrop` and `obs_intercrop`. -
- -Code to import the data +
Code to import the data To reproduce the data used in this file, you can use the following code snippet. It will import the data from an example simulation from the STICS model. -```{r} +```{r, include = FALSE} # Importing an example with three situations with observation: workspace <- system.file( file.path("extdata", "stics_example_1"), @@ -138,8 +136,45 @@ obs_intercrop <- SticsRFiles::get_obs( usm = usms_intercrop, usms_file = file.path(workspace, "usms.xml") ) + +workspace_2 <- system.file( + file.path("extdata", "stics_example_successive"), + package = "CroPlotR" +) + +situations <- SticsRFiles::get_usms_list( + file = file.path(workspace_2, "usms.xml") +) + +sim_rot <- SticsRFiles::get_sim( + workspace = workspace_2, + usm = situations, + usms_file = file.path(workspace_2, "usms.xml") +) + +sim2 <- sim[2] +# Generate randomness around lai_n and masec_n for the second simulation +set.seed(123) +for (sit in names(sim2)) { + sim2[[sit]]$lai_n <- sim[[sit]]$lai_n * (1.1 + rnorm(nrow(sim2[[sit]]), mean = 0, sd = 0.01)) + sim2[[sit]]$masec_n <- sim[[sit]]$masec_n * (1.1 + rnorm(nrow(sim2[[sit]]), mean = 0, sd = 0.01)) +} + +# Write a .RData file for reproducibility for the users +save( + sim, sim2, sim_intercrop, obs, obs_intercrop, sim_rot, + file = "inst/extdata/readme_sim_obs_example.RData" +) +``` + +```{r} +library(CroPlotR) +rdata_path <- system.file(file.path("extdata", "readme_sim_obs_example.RData"), package = "CroPlotR") +load(rdata_path) ``` +
+ ## Data structure The `sim` and `obs` objects are named lists of `data.frame`s. Each element of @@ -147,12 +182,6 @@ the list corresponds to a situation (a crop in a given year with a given managem Here's the structure of the `sim` object: -```{r} -str(sim) -``` - -Or more visually: - ```{r} lapply(sim, head) ``` @@ -160,7 +189,7 @@ lapply(sim, head) The structure of the `obs` object is similar: ```{r} -str(obs) +lapply(obs, head) ``` Note that the simulation structure is a special structure called `cropr_simulation`. You can easily make such an object from a named list of data.frames, and giving @@ -190,39 +219,30 @@ class(sim_test) <- append(class(sim_test), "cropr_simulation") Here is an application of dynamic plots for two example situations: ```{r} -p <- plot(sim, obs = obs) +p <- plot(sim) ``` -Note that the `obs` argument is explicitly named. This is because the -first argument of the function is `...` (we'll see why in a minute). - The plot function returns a named list of ggplot objects. -To plot all of them, just do +To plot all of them, just call the object: ```{r} p ``` -or simply - -```{r, eval=FALSE} -plot(sim, obs = obs) -``` - -In this case, the elements of the list take the name of the situations. +In this case, the list is named with the situation: ```{r} names(p) ``` -To plot only one of the graph, access it using its name: +To plot only one of the graph, access it using its name (with backticks if necessary): ```{r} -p$`IC_Wheat_Pea_2005-2006_N0` +p$`SC_Wheat_2005-2006_N0` ``` -or index: +or index it: ```{r, eval=FALSE} p[[1]] @@ -230,30 +250,30 @@ p[[1]] ### Observations -{To fill} +We can also add observations to the dynamic plots by passing the `obs` argument: -### Successive situations +```{r} +p <- plot(sim, obs = obs) +``` + +Note that it is mandatory to explicitly name the `obs` argument (`obs = ...`). -It is possible to aggregate plots of multiple situations on the same -graph when situations follow one another over time. This can be done -using the `successive` parameter. + +### Filter variables + +By default, all variables are returned by `plot()`, but you can filter them using the `var` argument: ```{r} -workspace <- system.file( - file.path("extdata", "stics_example_successive"), - package = "CroPlotR" -) +plot(sim, obs = obs, var = c("lai_n")) +``` -situations <- SticsRFiles::get_usms_list( - file = file.path(workspace, "usms.xml") -) +### Successive situations -sim_rot <- SticsRFiles::get_sim( - workspace = workspace, - usm = situations, - usms_file = file.path(workspace, "usms.xml") -) +It is possible to aggregate plots of multiple situations on the same +graph when situations follow one another over time. This can be done +using the `successive` parameter: +```{r} plot( sim_rot, var = c("resmes", "masec_n"), @@ -278,51 +298,10 @@ plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) > [sec_axis](https://ggplot2.tidyverse.org/reference/sec_axis.html) on > the resulting plot. -### Versions comparisons - -We can compare groups of simulations alongside by simply adding the -simulations objects one after the other (that is why the first argument -of the function is `...`). Group simulations can be the results of -simulations from different model versions, or simulations with different -parameter values. - -```{r} -workspace2 <- system.file( - file.path("extdata", "stics_example_2"), - package = "CroPlotR" -) - -sim2 <- SticsRFiles::get_sim( - workspace = workspace2, - usms_file = file.path(workspace2, "usms.xml") -) - -plot(sim, sim2, obs = obs, all_situations = FALSE) -``` - -Here only one plot is outputted because `workspace2` only contains the -intercrop situation. - -We can also name the corresponding group in the plot by naming them -while passing to the `plot()` function: - -```{r} -plot( - "New version" = sim, - original = sim2, - obs = obs, - type = "scatter", - all_situations = FALSE -) -``` - -### Intercrops - -{Add this section} - - ## Scatter plots +### Simple scatter plot + Here are the same plots, but presented as scatter plots: ```{r} @@ -331,7 +310,9 @@ plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) plots$`IC_Wheat_Pea_2005-2006_N0` ``` -Residues can also be represented against observations: +### Plotting residuals + +Residuals can also be represented against observations: ```{r} # Only plotting the first situation again: @@ -346,6 +327,8 @@ plots <- plot( plots[[1]] ``` +### Grouping situations + All these data can also be represented with a single graph for all situations: @@ -353,6 +336,8 @@ situations: plot(sim, obs = obs, type = "scatter", all_situations = TRUE) ``` +### Reference variable on the x-axis + When plotting residual scatter plots, `reference_var` allows to choose the reference variable on the x-axis. Thus, the observations or simulations of this reference variable (to be chosen by suffixing the @@ -370,6 +355,8 @@ plot( ) ``` +### Different shapes for situations + The points on the graphs can be shown in different shapes to differentiate between situations when `all_situations = TRUE`. If desired, the names of the situations can be displayed. @@ -377,7 +364,7 @@ desired, the names of the situations can be displayed. ```{r} plot( sim, - obs = obs[c(2, 3)], + obs = obs, type = "scatter", all_situations = TRUE, shape_sit = "txt" @@ -428,13 +415,47 @@ plot( ) ``` -By default, all variables are returned by `plot()`, but you can filter -them using the `var` argument: +## Comparing model versions + +We can compare groups of simulations by simply adding the +simulations objects one after the other (that is why we have to explicitely name the `obs` argument). +Group simulations can be the results of simulations from different model versions, or simulations with +different parameter values. + +Here's an example of a dynamic plot comparing two model versions: ```{r} -plot(sim, obs = obs, type = "scatter", all_situations = TRUE, var = c("lai_n")) +plot(sim, sim2, obs = obs, all_situations = FALSE) +``` + +There is one plot only here because `sim2` only contains one situation ("SC_Wheat_2005-2006_N0"). + +We can also name the corresponding group in the plot by naming them while passing to the `plot()` function: + +```{r} +plot( + original = sim, + "New version" = sim2, + obs = obs, + type = "scatter", + all_situations = FALSE +) ``` +We can also compare groups of simulations with scatter plots: + +```{r} +plot( + original = sim, + "New version" = sim2, + obs = obs, + type = "scatter", + all_situations = FALSE +) +``` + +## Error bars + Error bars related to observations can also be added to the graph using the `obs_sd` parameter which must be of the same shape as `obs`. In our example, we will create a false data frame with the only purpose of @@ -452,6 +473,11 @@ obs_sd$`SC_Wheat_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] <- plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) ``` +## Intercrops + +{Add this section} + + ## Plot saving The plots can be saved to disk using the `save_plot_png()` function as @@ -497,7 +523,7 @@ plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) extract_plot( plots, - situation = c("IC_Wheat_Pea_2005-2006_N0"), var = c("masec_n") + situation = c("SC_Wheat_2005-2006_N0"), var = c("masec_n") ) ``` diff --git a/inst/extdata/readme_sim_obs_example.RData b/inst/extdata/readme_sim_obs_example.RData new file mode 100644 index 0000000000000000000000000000000000000000..c12af5511e5f21b827204c3e679f60edb972a222 GIT binary patch literal 60242 zcmagFcUV*1x9|H}5CxG}X-a)ndR1xC1q2K&Kq%6c4xuQWKtMo5KtQ_mP?FGl2n0e@ z1VmZ_gkA&$LMWjGkkF35-@bd_bMHC(ob{|{J!8$b{#kR*F}~w7`4X=F_3!J_hArK5 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It is possible to select between observation and simulation of the reference variable.} +\item{variable}{A character vector indicating the variables to be kept in +the formatted data frame. If NULL (default), all variables are kept.} + \item{verbose}{Logical value for displaying information while running.} } \value{ diff --git a/man/generic_formatting.Rd b/man/generic_formatting.Rd index 352efdb2..fb075113 100644 --- a/man/generic_formatting.Rd +++ b/man/generic_formatting.Rd @@ -6,7 +6,6 @@ \usage{ generic_formatting( df, - var, overlap, situation_group, type, @@ -18,8 +17,6 @@ generic_formatting( \arguments{ \item{df}{A data frame to be formatted (e.g. output from \code{format_cropr}).} -\item{var}{A character string indicating the variable to be formatted.} - \item{overlap}{A logical value indicating whether there is any overlapping variables desired in the plot.} From b5e27c961b2498bc49d39f5e3d81c99a3114232f Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Wed, 14 Jan 2026 11:35:40 +0100 Subject: [PATCH 097/118] Remove useless code --- R/specific_plotting_scatter.R | 4 ---- 1 file changed, 4 deletions(-) diff --git a/R/specific_plotting_scatter.R b/R/specific_plotting_scatter.R index 08f0c0d5..0bef8bd5 100644 --- a/R/specific_plotting_scatter.R +++ b/R/specific_plotting_scatter.R @@ -109,10 +109,6 @@ force_y_axis <- function(df_data, reference_var, y_var_type, is_obs_sd, p) { y_min <- axis_bounds$yaxis_min y_max <- axis_bounds$yaxis_max - # New y limits per facet - y_min_new <- ifelse(y_min > 0, 0, y_min) - y_max_new <- ifelse(y_max < 0, 0, y_max) - expand_range <- function(min, max, mult = 0.05) { delta <- max - min if (delta == 0) delta <- abs(min) + 1e-9 From 28e702f569f2b54d873276b27b08de27cce48f79 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 14 Jan 2026 11:37:55 +0100 Subject: [PATCH 098/118] Update TOC + add intercrops + put data structure section further down --- README.Rmd | 191 ++++++++++++---------- inst/extdata/readme_sim_obs_example.RData | Bin 60242 -> 60051 bytes 2 files changed, 105 insertions(+), 86 deletions(-) diff --git a/README.Rmd b/README.Rmd index e3909e61..6f56cfa6 100644 --- a/README.Rmd +++ b/README.Rmd @@ -39,24 +39,39 @@ at the top right of [this page](https://github.com/SticsRPacks/CroPlotR). ## Table of Contents -- [1. Installation](#1-installation) -- [2. Examples](#2-examples) - - [2.1 Plotting](#21-plotting) - - [2.1.1 Dynamic plots](#211-dynamic-plots) - - [2.1.2 Scatter plots](#212-scatter-plots) - - [2.1.3 Group comparison](#213-group-comparison) - - [2.1.4 Plot saving](#214-plot-saving) - - [2.1.5 Plot extracting](#215-plot-extracting) - - [2.2 Statistics](#22-statistics) - - [2.2.1 Dynamic plots](#221-simple-case) - - [2.2.2 Several groups](#222-several-groups) - - [2.2.3 Statistics plot](#223-statistics-plot) - - [2.3 Data manipulation](#23-data-manipulation) -- [3. Tools](#3-tools) - - [3.1 ggplotly](#31-ggplotly) - - [3.2 patchwork](#32-patchwork) -- [4. Help](#4-help) -- [5. Citation](#5-Citation) + +- [CroPlotR](#croplotr) + - [Table of Contents](#table-of-contents) + - [Installation](#installation) + - [Introduction](#introduction) + - [Dynamic plots](#dynamic-plots) + - [Simple dynamic plot](#simple-dynamic-plot) + - [Observations](#observations) + - [Filter variables](#filter-variables) + - [Successive situations](#successive-situations) + - [Overlaying variables](#overlaying-variables) + - [Scatter plots](#scatter-plots) + - [Simple scatter plot](#simple-scatter-plot) + - [Plotting residuals](#plotting-residuals) + - [Grouping situations](#grouping-situations) + - [Reference variable on the x-axis](#reference-variable-on-the-x-axis) + - [Different shapes for situations](#different-shapes-for-situations) + - [Comparing model versions](#comparing-model-versions) + - [Error bars](#error-bars) + - [Intercrops](#intercrops) + - [Plot saving](#plot-saving) + - [Plot extraction](#plot-extraction) + - [Statistics](#statistics) + - [Simple case](#simple-case) + - [Several groups](#several-groups) + - [Statistics plot](#statistics-plot) + - [Data manipulation](#data-manipulation) + - [Tools](#tools) + - [Interactivity with ggplotly](#interactivity-with-ggplotly) + - [Combining plots with patchwork](#combining-plots-with-patchwork) + - [Data structure](#data-structure) + - [Finding help](#finding-help) + - [Citation](#citation) ## Installation @@ -175,43 +190,6 @@ load(rdata_path)

-## Data structure - -The `sim` and `obs` objects are named lists of `data.frame`s. Each element of -the list corresponds to a situation (a crop in a given year with a given management). Each `data.frame` contains the simulated or observed variables for this situation. - -Here's the structure of the `sim` object: - -```{r} -lapply(sim, head) -``` - -The structure of the `obs` object is similar: - -```{r} -lapply(obs, head) -``` - -Note that the simulation structure is a special structure called `cropr_simulation`. You can easily make such an object from a named list of data.frames, and giving -the class attribute `cropr_simulation`, e.g.: - -```{r} -sim_test <- list( - situation_1 = data.frame( - Date = as.Date("2000-01-01") + 0:9, - var1 = rnorm(10), - var2 = rnorm(10) - ), - situation_2 = data.frame( - Date = as.Date("2001-01-01") + 0:9, - var1 = rnorm(10), - var2 = rnorm(10) - ) -) - -class(sim_test) <- append(class(sim_test), "cropr_simulation") -``` - ## Dynamic plots ### Simple dynamic plot @@ -219,33 +197,7 @@ class(sim_test) <- append(class(sim_test), "cropr_simulation") Here is an application of dynamic plots for two example situations: ```{r} -p <- plot(sim) -``` - -The plot function returns a named list of ggplot objects. - -To plot all of them, just call the object: - -```{r} -p -``` - -In this case, the list is named with the situation: - -```{r} -names(p) -``` - -To plot only one of the graph, access it using its name (with backticks if necessary): - -```{r} -p$`SC_Wheat_2005-2006_N0` -``` - -or index it: - -```{r, eval=FALSE} -p[[1]] +plot(sim) ``` ### Observations @@ -253,12 +205,11 @@ p[[1]] We can also add observations to the dynamic plots by passing the `obs` argument: ```{r} -p <- plot(sim, obs = obs) +plot(sim, obs = obs) ``` Note that it is mandatory to explicitly name the `obs` argument (`obs = ...`). - ### Filter variables By default, all variables are returned by `plot()`, but you can filter them using the `var` argument: @@ -307,7 +258,7 @@ Here are the same plots, but presented as scatter plots: ```{r} # Only plotting the first situation for this one: plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) -plots$`IC_Wheat_Pea_2005-2006_N0` +plots$`SC_Pea_2005-2006_N0` ``` ### Plotting residuals @@ -475,8 +426,18 @@ plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) ## Intercrops -{Add this section} +We can also plot intercrop situations. Here is an example of dynamic plots +with an intercrop situation: +```{r} +plot(sim_intercrop, obs = obs_intercrop) +``` + +And here is an example of scatter plots with an intercrop situation: + +```{r} +plot(sim_intercrop, obs = obs_intercrop, type = "scatter", all_situations = TRUE) +``` ## Plot saving @@ -511,6 +472,27 @@ save_plot_pdf(plot = plots, out_dir = "path/to/directory", file_per_var = FALSE) ## Plot extraction +The plot function returns a named list of ggplot objects. The names of the +list correspond to the situations simulated: + +```{r} +p <- plot(sim) + +names(p) +``` + +To plot only one of the graph, access it using its name (with backticks if necessary): + +```{r} +p$`SC_Wheat_2005-2006_N0` +``` + +or index it: + +```{r, eval=FALSE} +p[[1]] +``` + When we have plots with several variables and several situations, the `extract_plot` function allows to keep the situations and variables that we need. @@ -791,6 +773,43 @@ plot4 <- plot(sim, obs = obs, var = "masec_n")[[1]] plot1 + plot2 + plot3 + plot4 + plot_layout(ncol = 2) ``` +## Data structure + +The `sim` and `obs` objects are named lists of `data.frame`s. Each element of +the list corresponds to a situation (a crop in a given year with a given management). Each `data.frame` contains the simulated or observed variables for this situation. + +Here's the structure of the `sim` object: + +```{r} +lapply(sim, head) +``` + +The structure of the `obs` object is similar: + +```{r} +lapply(obs, head) +``` + +Note that the simulation structure is a special structure called `cropr_simulation`. You can easily make such an object from a named list of data.frames, and giving +the class attribute `cropr_simulation`, e.g.: + +```{r} +sim_test <- list( + situation_1 = data.frame( + Date = as.Date("2000-01-01") + 0:9, + var1 = rnorm(10), + var2 = rnorm(10) + ), + situation_2 = data.frame( + Date = as.Date("2001-01-01") + 0:9, + var1 = rnorm(10), + var2 = rnorm(10) + ) +) + +class(sim_test) <- append(class(sim_test), "cropr_simulation") +``` + ## Finding help You can find help for the functions directly using the name of the diff --git a/inst/extdata/readme_sim_obs_example.RData b/inst/extdata/readme_sim_obs_example.RData index c12af5511e5f21b827204c3e679f60edb972a222..1c6558830396a6d494e5d2551982771e4237b38c 100644 GIT binary patch literal 60051 zcmagl2{aq+|1kW!i@QZ}*IHGywXbQdwbxd)?^|pwYL65_g>aXmrD*ND*msIV2%)8_ z_C&-UYLC5$Erhqf|MQ%8d!G0I&Y3yaH8ba2GiT!dl)l%!Gg&d&e{XB2gFWcRZ)7WJ9eC!A^YK`e9d!(gr*E4=7;+NE9K!IU(>k$075tNP}fVe6=jdj?mJyhMI^sxdeYFW-M* 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deletions(-) diff --git a/README.Rmd b/README.Rmd index 6f56cfa6..a269db2c 100644 --- a/README.Rmd +++ b/README.Rmd @@ -42,38 +42,38 @@ at the top right of [this page](https://github.com/SticsRPacks/CroPlotR). - [CroPlotR](#croplotr) - [Table of Contents](#table-of-contents) - - [Installation](#installation) - - [Introduction](#introduction) - - [Dynamic plots](#dynamic-plots) - - [Simple dynamic plot](#simple-dynamic-plot) - - [Observations](#observations) - - [Filter variables](#filter-variables) - - [Successive situations](#successive-situations) - - [Overlaying variables](#overlaying-variables) - - [Scatter plots](#scatter-plots) - - [Simple scatter plot](#simple-scatter-plot) - - [Plotting residuals](#plotting-residuals) - - [Grouping situations](#grouping-situations) - - [Reference variable on the x-axis](#reference-variable-on-the-x-axis) - - [Different shapes for situations](#different-shapes-for-situations) - - [Comparing model versions](#comparing-model-versions) - - [Error bars](#error-bars) - - [Intercrops](#intercrops) - - [Plot saving](#plot-saving) - - [Plot extraction](#plot-extraction) - - [Statistics](#statistics) - - [Simple case](#simple-case) - - [Several groups](#several-groups) - - [Statistics plot](#statistics-plot) - - [Data manipulation](#data-manipulation) - - [Tools](#tools) - - [Interactivity with ggplotly](#interactivity-with-ggplotly) - - [Combining plots with patchwork](#combining-plots-with-patchwork) - - [Data structure](#data-structure) - - [Finding help](#finding-help) - - [Citation](#citation) - -## Installation + - [1. Installation](#1-installation) + - [2. Introduction](#2-introduction) + - [3. Dynamic plots](#3-dynamic-plots) + - [3.1. Simple dynamic plot](#31-simple-dynamic-plot) + - [3.2. Observations](#32-observations) + - [3.3. Filter variables](#33-filter-variables) + - [3.4. Successive situations](#34-successive-situations) + - [3.5. Overlaying variables](#35-overlaying-variables) + - [4. Scatter plots](#4-scatter-plots) + - [4.1. Simple scatter plot](#41-simple-scatter-plot) + - [4.2. Plotting residuals](#42-plotting-residuals) + - [4.3. Grouping situations](#43-grouping-situations) + - [4.4. Reference variable on the x-axis](#44-reference-variable-on-the-x-axis) + - [4.5. Different shapes for situations](#45-different-shapes-for-situations) + - [5. Comparing model versions](#5-comparing-model-versions) + - [6. Error bars](#6-error-bars) + - [7. Intercrops](#7-intercrops) + - [8. Plot saving](#8-plot-saving) + - [9. Plot extraction](#9-plot-extraction) + - [10. Statistics](#10-statistics) + - [10.1. Simple case](#101-simple-case) + - [10.2. Several groups](#102-several-groups) + - [10.3. Statistics plot](#103-statistics-plot) + - [11. Data manipulation](#11-data-manipulation) + - [12. Tools](#12-tools) + - [12.1. Interactivity with ggplotly](#121-interactivity-with-ggplotly) + - [12.2. Combining plots with patchwork](#122-combining-plots-with-patchwork) + - [13. Data structure](#13-data-structure) + - [14. Finding help](#14-finding-help) + - [15. Citation](#15-citation) + +## 1. Installation You can install the released version of CroPlotR from [Github](https://github.com/SticsRPacks/CroPlotR) either using `devtools` or the more lightweight `remotes` package: @@ -91,7 +91,7 @@ devtools::install_github("SticsRPacks/CroPlotR@*release") remotes::install_github("SticsRPacks/CroPlotR@*release") ``` -## Introduction +## 2. Introduction Only one function is exported for plots [`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html) (and its alias `autoplot()`), and one for the statistics [`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html). @@ -190,9 +190,9 @@ load(rdata_path)
-## Dynamic plots +## 3. Dynamic plots -### Simple dynamic plot +### 3.1. Simple dynamic plot Here is an application of dynamic plots for two example situations: @@ -200,7 +200,7 @@ Here is an application of dynamic plots for two example situations: plot(sim) ``` -### Observations +### 3.2. Observations We can also add observations to the dynamic plots by passing the `obs` argument: @@ -210,7 +210,7 @@ plot(sim, obs = obs) Note that it is mandatory to explicitly name the `obs` argument (`obs = ...`). -### Filter variables +### 3.3. Filter variables By default, all variables are returned by `plot()`, but you can filter them using the `var` argument: @@ -218,7 +218,7 @@ By default, all variables are returned by `plot()`, but you can filter them usin plot(sim, obs = obs, var = c("lai_n")) ``` -### Successive situations +### 3.4. Successive situations It is possible to aggregate plots of multiple situations on the same graph when situations follow one another over time. This can be done @@ -232,7 +232,7 @@ plot( ) ``` -### Overlaying variables +### 3.5. Overlaying variables We can also overlay variables thanks to the "overlap" parameter with dynamic plots. @@ -249,9 +249,9 @@ plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) > [sec_axis](https://ggplot2.tidyverse.org/reference/sec_axis.html) on > the resulting plot. -## Scatter plots +## 4. Scatter plots -### Simple scatter plot +### 4.1. Simple scatter plot Here are the same plots, but presented as scatter plots: @@ -261,7 +261,7 @@ plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) plots$`SC_Pea_2005-2006_N0` ``` -### Plotting residuals +### 4.2. Plotting residuals Residuals can also be represented against observations: @@ -278,7 +278,7 @@ plots <- plot( plots[[1]] ``` -### Grouping situations +### 4.3. Grouping situations All these data can also be represented with a single graph for all situations: @@ -287,7 +287,7 @@ situations: plot(sim, obs = obs, type = "scatter", all_situations = TRUE) ``` -### Reference variable on the x-axis +### 4.4. Reference variable on the x-axis When plotting residual scatter plots, `reference_var` allows to choose the reference variable on the x-axis. Thus, the observations or @@ -306,7 +306,7 @@ plot( ) ``` -### Different shapes for situations +### 4.5. Different shapes for situations The points on the graphs can be shown in different shapes to differentiate between situations when `all_situations = TRUE`. If @@ -366,7 +366,7 @@ plot( ) ``` -## Comparing model versions +## 5. Comparing model versions We can compare groups of simulations by simply adding the simulations objects one after the other (that is why we have to explicitely name the `obs` argument). @@ -405,7 +405,7 @@ plot( ) ``` -## Error bars +## 6. Error bars Error bars related to observations can also be added to the graph using the `obs_sd` parameter which must be of the same shape as `obs`. In our @@ -424,7 +424,7 @@ obs_sd$`SC_Wheat_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] <- plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) ``` -## Intercrops +## 7. Intercrops We can also plot intercrop situations. Here is an example of dynamic plots with an intercrop situation: @@ -439,7 +439,7 @@ And here is an example of scatter plots with an intercrop situation: plot(sim_intercrop, obs = obs_intercrop, type = "scatter", all_situations = TRUE) ``` -## Plot saving +## 8. Plot saving The plots can be saved to disk using the `save_plot_png()` function as follows: @@ -470,7 +470,7 @@ plots <- plot(sim, obs = obs) save_plot_pdf(plot = plots, out_dir = "path/to/directory", file_per_var = FALSE) ``` -## Plot extraction +## 9. Plot extraction The plot function returns a named list of ggplot objects. The names of the list correspond to the situations simulated: @@ -509,9 +509,9 @@ extract_plot( ) ``` -## Statistics +## 10. Statistics -### Simple case +### 10.1. Simple case Here is an application of summary statistics for the 3 situations: @@ -544,7 +544,7 @@ s <- summary(sim, obs = obs, all_situations = TRUE) knitr::kable(s) ``` -### Several groups +### 10.2. Several groups We can get statistics for each group of simulations by simply adding the simulations objects one after the other (as for the `plot()` function). @@ -596,7 +596,7 @@ Please read the help from and [`predictor_assessment()`](https://sticsrpacks.github.io/CroPlotR/reference/predictor_assessment.html). -### Statistics plot +### 10.3. Statistics plot It is also possible to plot the statistics: @@ -711,7 +711,7 @@ plot( ) ``` -## Data manipulation +## 11. Data manipulation Observation lists can easily be handled using e.g. [dplyr](https://CRAN.R-project.org/package=dplyr), @@ -742,9 +742,9 @@ sim_new <- split_df2sim(df) lapply(sim_new, head) ``` -## Tools +## 12. Tools -### Interactivity with ggplotly +### 12.1. Interactivity with ggplotly The ggplotly function in plotly library makes it very easy to create interactive graphics from a ggplot. Do not hesitate to call it with your @@ -757,7 +757,7 @@ library(plotly) ggplotly(plot(sim, obs = obs, type = "dynamic")[[1]]) ``` -### Combining plots with patchwork +### 12.2. Combining plots with patchwork There is also the patchwork library that allows you to easily combine several ggplot into one. @@ -773,7 +773,7 @@ plot4 <- plot(sim, obs = obs, var = "masec_n")[[1]] plot1 + plot2 + plot3 + plot4 + plot_layout(ncol = 2) ``` -## Data structure +## 13. Data structure The `sim` and `obs` objects are named lists of `data.frame`s. Each element of the list corresponds to a situation (a crop in a given year with a given management). Each `data.frame` contains the simulated or observed variables for this situation. @@ -810,7 +810,7 @@ sim_test <- list( class(sim_test) <- append(class(sim_test), "cropr_simulation") ``` -## Finding help +## 14. Finding help You can find help for the functions directly using the name of the function followed by the class of the object you need the method for: @@ -832,7 +832,7 @@ function followed by the class of the object you need the method for: If you have any problem, please [fill an issue](https://github.com/SticsRPacks/CroPlotR/issues) on Github. -## Citation +## 15. Citation If you have used this package for a study that led to a publication or report, please cite us. You can either use the citation tool from Github From 853cf5b24bace033a39f6daa02e6a5be3bc218cd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 14 Jan 2026 11:50:28 +0100 Subject: [PATCH 100/118] Update README.Rmd re-work text a little bit --- README.Rmd | 378 +++++++++++++++++++++++++++-------------------------- 1 file changed, 191 insertions(+), 187 deletions(-) diff --git a/README.Rmd b/README.Rmd index a269db2c..6cd38939 100644 --- a/README.Rmd +++ b/README.Rmd @@ -28,14 +28,14 @@ coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/master/graph/badge.s -`CroPlotR` aims at the standardization of the process of analyzing the outputs from crop models such as -[STICS](https://www6.paca.inrae.fr/stics_eng/), [APSIM](https://www.apsim.info/) or really any model. +`CroPlotR` standardizes the analysis and visualization of crop model outputs, including models such as +[STICS](https://www6.paca.inrae.fr/stics_eng/), [APSIM](https://www.apsim.info/), and others. -Its use does not need any particular adaptation if your model has been wrapped with the -[CroptimizR](https://github.com/SticsRPacks/CroptimizR) package thanks to the use of the `cropr_simulation` standard of data representation (see section below). +The package works seamlessly with models wrapped using the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) +package through the `cropr_simulation` data format (see [section 13](#13-data-structure)). -If you want to be notified when a new release of this package is made, you can tick the Releases box in the "Watch / Unwatch =\> Custom" menu -at the top right of [this page](https://github.com/SticsRPacks/CroPlotR). +**Stay updated:** To receive notifications about new releases, click "Watch" → "Custom" → "Releases" at the top +of [this repository](https://github.com/SticsRPacks/CroPlotR). ## Table of Contents @@ -75,44 +75,51 @@ at the top right of [this page](https://github.com/SticsRPacks/CroPlotR). ## 1. Installation -You can install the released version of CroPlotR from [Github](https://github.com/SticsRPacks/CroPlotR) either using -`devtools` or the more lightweight `remotes` package: +Install the latest release from [GitHub](https://github.com/SticsRPacks/CroPlotR) using either `devtools` or `remotes`: -- With `devtools` +**Using `remotes` (recommended):** ```{r eval=FALSE} -devtools::install_github("SticsRPacks/CroPlotR@*release") +# install.packages("remotes") +remotes::install_github("SticsRPacks/CroPlotR@*release") ``` -- With `remotes` +**Using `devtools`:** ```{r eval=FALSE} -# install.packages("remotes") -remotes::install_github("SticsRPacks/CroPlotR@*release") +devtools::install_github("SticsRPacks/CroPlotR@*release") ``` ## 2. Introduction -Only one function is exported for plots [`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html) -(and its alias `autoplot()`), and one for the statistics [`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html). -These functions should be the only one you need for all your plots and summary statistics. Additional ones are provided to simplify the -manipulation of simulated data (see [2.3 Data manipulation](#23-data-manipulation)). +### Core Functions -In the following, an example using the STICS crop model is presented. If you want to use another model for which a wrapper has been designed for -the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, just consider defining the `sim` variable used in the examples below as -`sim <- result$sim_list`, where `result` is the list returned by your model wrapper. Examples of use of CroPlotR with Stics and APSIM model -wrappers can be found in [CroptimizR's website](https://sticsrpacks.github.io/CroptimizR/) (see Articles tab). +CroPlotR provides two main functions: -In the following examples, we use the `sim` and `obs` objects, which contains a simulation of two situations: +- **[`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html)** (alias: `autoplot()`) for creating visualizations +- **[`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html)** for computing statistical metrics -- a Pea in sole crop -- a Wheat in sole crop +These functions cover most visualization and analysis needs. Additional helper functions are available for data manipulation +(see [section 11](#11-data-manipulation)). -We also use an intercrop situation with Wheat and Pea together, stored in `sim_intercrop` and `obs_intercrop`. +### Using CroPlotR with Model Wrappers -
Code to import the data +If you're using a model wrapper from the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, +simply extract the simulations as: `sim <- result$sim_list`. For detailed examples with STICS and APSIM, +visit [CroptimizR's documentation](https://sticsrpacks.github.io/CroptimizR/) (Articles tab). -To reproduce the data used in this file, you can use the following code snippet. It will import the data from an example simulation from the STICS model. +### Example Data + +The following examples use simulation and observation data from the STICS crop model: + +**Sole crops** (`sim` and `obs`): +- Pea in sole crop (situation: `SC_Pea_2005-2006_N0`) +- Wheat in sole crop (situation: `SC_Wheat_2005-2006_N0`) + +**Intercrop** (`sim_intercrop` and `obs_intercrop`): +- Wheat and Pea intercrop (situation: `IC_Wheat_Pea_2005-2006_N0`) + +
Click to view code for loading example data ```{r, include = FALSE} # Importing an example with three situations with observation: @@ -190,39 +197,39 @@ load(rdata_path)
-## 3. Dynamic plots +## 3. Dynamic Plots + +Dynamic plots show variable values over time, making them ideal for visualizing temporal patterns in crop model outputs. -### 3.1. Simple dynamic plot +### 3.1. Simple Dynamic Plot -Here is an application of dynamic plots for two example situations: +Create basic time-series plots for all variables and situations: ```{r} plot(sim) ``` -### 3.2. Observations +### 3.2. Adding Observations -We can also add observations to the dynamic plots by passing the `obs` argument: +Overlay observed data on simulated outputs for model validation: ```{r} plot(sim, obs = obs) ``` -Note that it is mandatory to explicitly name the `obs` argument (`obs = ...`). +> **Note:** The `obs` argument must be explicitly named. -### 3.3. Filter variables +### 3.3. Filtering Variables -By default, all variables are returned by `plot()`, but you can filter them using the `var` argument: +By default, all variables are plotted. Use `var` to select specific variables: ```{r} plot(sim, obs = obs, var = c("lai_n")) ``` -### 3.4. Successive situations +### 3.4. Successive Situations -It is possible to aggregate plots of multiple situations on the same -graph when situations follow one another over time. This can be done -using the `successive` parameter: +Combine multiple sequential situations (e.g., crop rotations) into a single continuous timeline using the `successive` parameter: ```{r} plot( @@ -232,28 +239,25 @@ plot( ) ``` -### 3.5. Overlaying variables +### 3.5. Overlaying Variables -We can also overlay variables thanks to the "overlap" parameter with -dynamic plots. +Plot multiple variables on the same graph using the `overlap` parameter: ```{r} plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) ``` -> Note that it is not possible to scale the variables right now from the -> plot function (see -> [issue](https://github.com/SticsRPacks/CroPlotR/issues/2)). If you -> want to do so, you are encouraged to scale before the plotting -> function, and to add a second axis using -> [sec_axis](https://ggplot2.tidyverse.org/reference/sec_axis.html) on -> the resulting plot. +> **Note:** Automatic variable scaling is not yet available ([see issue](https://github.com/SticsRPacks/CroPlotR/issues/2)). +> To scale variables, transform your data before plotting and add a secondary axis using +> [`sec_axis()`](https://ggplot2.tidyverse.org/reference/sec_axis.html). -## 4. Scatter plots +## 4. Scatter Plots -### 4.1. Simple scatter plot +Scatter plots compare simulated versus observed values, providing visual assessment of model performance. -Here are the same plots, but presented as scatter plots: +### 4.1. Simple Scatter Plot + +Create observed vs. simulated scatter plots by setting `type = "scatter"`: ```{r} # Only plotting the first situation for this one: @@ -261,9 +265,9 @@ plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) plots$`SC_Pea_2005-2006_N0` ``` -### 4.2. Plotting residuals +### 4.2. Plotting Residuals -Residuals can also be represented against observations: +Visualize model residuals (observed - simulated) using `select_scat = "res"`: ```{r} # Only plotting the first situation again: @@ -278,22 +282,18 @@ plots <- plot( plots[[1]] ``` -### 4.3. Grouping situations +### 4.3. Grouping Situations -All these data can also be represented with a single graph for all -situations: +Combine all situations in a single plot using `all_situations = TRUE`: ```{r} plot(sim, obs = obs, type = "scatter", all_situations = TRUE) ``` -### 4.4. Reference variable on the x-axis +### 4.4. Reference Variable on the X-axis -When plotting residual scatter plots, `reference_var` allows to choose -the reference variable on the x-axis. Thus, the observations or -simulations of this reference variable (to be chosen by suffixing the -variable name by "\_obs" or "\_sim") will be compared to the residuals -of each of the variables. +For residual plots, use `reference_var` to specify which variable appears on the x-axis. +Suffix the variable name with `_obs` or `_sim` to choose observed or simulated values: ```{r} plot( @@ -306,11 +306,11 @@ plot( ) ``` -### 4.5. Different shapes for situations +### 4.5. Distinguishing Situations with Shapes + +When plotting multiple situations together (`all_situations = TRUE`), differentiate them using the `shape_sit` parameter. -The points on the graphs can be shown in different shapes to -differentiate between situations when `all_situations = TRUE`. If -desired, the names of the situations can be displayed. +**Display situation names as text labels:** ```{r} plot( @@ -322,9 +322,7 @@ plot( ) ``` -As you can see, this can quickly become unreadable depending on the -number of points and length of situation names; That is why you can -simply assign a different symbol to each situation. +Text labels can become cluttered with many data points. Use distinct symbols instead: ```{r} plot( @@ -336,8 +334,7 @@ plot( ) ``` -It is also possible to represent a group of situations with the same -symbol when, for example, clusters are identified. +**Group multiple situations under a single symbol** (e.g., for identified clusters): ```{r} plot( @@ -350,8 +347,7 @@ plot( ) ``` -You can also name your `situation_group` list and thus customize (e.g -shorten) the plot legend. +**Customize legend labels** by naming your `situation_group` list: ```{r} plot( @@ -366,22 +362,22 @@ plot( ) ``` -## 5. Comparing model versions +## 5. Comparing Model Versions -We can compare groups of simulations by simply adding the -simulations objects one after the other (that is why we have to explicitely name the `obs` argument). -Group simulations can be the results of simulations from different model versions, or simulations with -different parameter values. +Compare different model versions or parameter sets by passing multiple simulation objects to `plot()`. +This is why the `obs` argument must be explicitly named. -Here's an example of a dynamic plot comparing two model versions: +### Dynamic Plot Comparison ```{r} plot(sim, sim2, obs = obs, all_situations = FALSE) ``` -There is one plot only here because `sim2` only contains one situation ("SC_Wheat_2005-2006_N0"). +There is only one plot here because `sim2` contains a single situation ("SC_Wheat_2005-2006_N0"). + +### Naming Model Versions -We can also name the corresponding group in the plot by naming them while passing to the `plot()` function: +Provide descriptive names for each simulation group: ```{r} plot( @@ -393,7 +389,9 @@ plot( ) ``` -We can also compare groups of simulations with scatter plots: +### Scatter Plot Comparison + +Model versions can also be compared using scatter plots: ```{r} plot( @@ -405,13 +403,12 @@ plot( ) ``` -## 6. Error bars +## 6. Error Bars + +Add uncertainty estimates to observations using the `obs_sd` parameter, which must have the same structure as `obs`. +Error bars represent ±2 standard deviations (95% confidence interval). -Error bars related to observations can also be added to the graph using -the `obs_sd` parameter which must be of the same shape as `obs`. In our -example, we will create a false data frame with the only purpose of -having a preview of the result. To have 95% confidence, the error bar is -equal to two standard deviations on each side of the point. +The example below creates synthetic standard deviations for demonstration: ```{r} obs_sd <- obs @@ -426,23 +423,25 @@ plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) ## 7. Intercrops -We can also plot intercrop situations. Here is an example of dynamic plots -with an intercrop situation: +CroPlotR automatically handles intercrop situations where multiple plant species are grown together. + +### Dynamic Plots for Intercrops ```{r} plot(sim_intercrop, obs = obs_intercrop) ``` -And here is an example of scatter plots with an intercrop situation: +### Scatter Plots for Intercrops ```{r} plot(sim_intercrop, obs = obs_intercrop, type = "scatter", all_situations = TRUE) ``` -## 8. Plot saving +## 8. Saving Plots + +### Save as PNG -The plots can be saved to disk using the `save_plot_png()` function as -follows: +Export individual plots as PNG files using `save_plot_png()`: ```{r eval=FALSE} plots <- plot("New version" = sim, original = sim2, obs = obs, type = "scatter") @@ -459,10 +458,9 @@ plots <- plot( save_plot_png(., out_dir = "path/to/directory", suffix = "_scatter") ``` -They can also be saved using the `save_plot_pdf()` function that which, -from a list of ggplots, generates a pdf file. If the `file_per_var` -parameter is TRUE, in this case the function generates one pdf file per -variable. +### Save as PDF + +Export plots to PDF using `save_plot_pdf()`. Set `file_per_var = TRUE` to create separate PDFs for each variable: ```{r eval=FALSE} plots <- plot(sim, obs = obs) @@ -470,10 +468,9 @@ plots <- plot(sim, obs = obs) save_plot_pdf(plot = plots, out_dir = "path/to/directory", file_per_var = FALSE) ``` -## 9. Plot extraction +## 9. Extracting Individual Plots -The plot function returns a named list of ggplot objects. The names of the -list correspond to the situations simulated: +The `plot()` function returns a named list of ggplot objects, where names correspond to situations: ```{r} p <- plot(sim) @@ -481,24 +478,28 @@ p <- plot(sim) names(p) ``` -To plot only one of the graph, access it using its name (with backticks if necessary): +### Access by Name + +Access individual plots using their situation name (use backticks if the name contains special characters): ```{r} p$`SC_Wheat_2005-2006_N0` ``` -or index it: +### Access by Index + +Alternatively, use numeric indexing: ```{r, eval=FALSE} p[[1]] ``` -When we have plots with several variables and several situations, the -`extract_plot` function allows to keep the situations and variables that -we need. +### Filtering Plots -In the following example, we want to extract the intercrop situation and -the "masec_n" variable. +Use `extract_plot()` to filter plots by situation and/or variable. This is useful when working with many +situations and variables. + +Example: Extract only the wheat situation and the `masec_n` variable: ```{r} plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) @@ -511,9 +512,11 @@ extract_plot( ## 10. Statistics -### 10.1. Simple case +Compute performance metrics to quantitatively evaluate model accuracy. + +### 10.1. Basic Usage -Here is an application of summary statistics for the 3 situations: +Calculate statistics for each situation individually: ```{r eval=FALSE} summary(sim, obs = obs, all_situations = FALSE) @@ -524,16 +527,12 @@ s <- summary(sim, obs = obs, all_situations = FALSE) knitr::kable(s) ``` -Note that as for the `plot()` function the `obs` argument is explicitly -named. This is because the first argument of the function is `...` to be -able to compare groups (i.e. model versions or simulation with different -parameter values). In this example, a message warns the user because -some observed values have a zero value which causes a division by zero -in the calculation of certain statistical criteria, these values are -therefore filtered for the calculation of these criteria. +> **Note:** The `obs` argument must be explicitly named (same reason as for `plot()`). The warning message +> indicates that zero-valued observations were filtered out to avoid division-by-zero errors in certain metrics. + +### Aggregated Statistics -And as for the `plot()` function again, it is possible to compute the -statistical criteria for all situations at once. +Compute statistics across all situations simultaneously: ```{r eval=FALSE} summary(sim, obs = obs, all_situations = TRUE) @@ -544,10 +543,9 @@ s <- summary(sim, obs = obs, all_situations = TRUE) knitr::kable(s) ``` -### 10.2. Several groups +### 10.2. Comparing Multiple Groups -We can get statistics for each group of simulations by simply adding the -simulations objects one after the other (as for the `plot()` function). +Compute statistics for multiple simulation groups (e.g., different model versions or parameter sets): ```{r eval=FALSE} summary(sim, sim2, obs = obs) @@ -558,8 +556,7 @@ s <- summary(sim, sim2, obs = obs) knitr::kable(s) ``` -We can also name the corresponding group in the plot by naming them -while passing to the `summary()` function: +Provide descriptive names for clarity: ```{r eval=FALSE} summary("New version" = sim, original = sim2, obs = obs) @@ -570,8 +567,9 @@ s <- summary("New version" = sim, original = sim2, obs = obs) knitr::kable(s) ``` -By default, all statistics are returned by `summary`, but you can filter -them using the `stat` argument: +### Selecting Specific Statistics + +By default, all available statistics are computed. Use the `stats` argument to select specific metrics: ```{r eval=FALSE} summary( @@ -596,13 +594,11 @@ Please read the help from and [`predictor_assessment()`](https://sticsrpacks.github.io/CroPlotR/reference/predictor_assessment.html). -### 10.3. Statistics plot +### 10.3. Visualizing Statistics -It is also possible to plot the statistics: +Plot statistical metrics for visual comparison using `plot()` on the summary output. -In a rather obvious way, the resulting graph will take into account all -the situations simultaneously or not according to the parameter given to -`summary`. Here is an example with `all_situations = FALSE`. +**Separate plots per situation** (`all_situations = FALSE`): ```{r} stats <- summary( @@ -615,7 +611,7 @@ stats <- summary( plot(stats) ``` -And here is an example with `all_situations = TRUE`. +**Combined plot for all situations** (`all_situations = TRUE`): ```{r} stats <- summary( @@ -629,8 +625,10 @@ stats <- summary( plot(stats) ``` -We can choose to plot either the group or the situation in x (and the -other is used for grouping and colouring): +### Customizing Plot Layout + +Control which variable appears on the x-axis using the `xvar` parameter. The other variable is used for +grouping and color coding: ```{r} stats <- summary( @@ -644,8 +642,9 @@ stats <- summary( plot(stats, xvar = "situation", title = "Situation in X") ``` -In the previous examples, each line corresponds to a statistical -criterion. These can also be stacked. +### Bar Chart Layouts + +**Stacked bars** (`group_bar = "stack"`): ```{r} stats <- summary( @@ -659,7 +658,7 @@ stats <- summary( plot(stats, xvar = "situation", title = "Stacked columns", group_bar = "stack") ``` -Or put side by side. +**Side-by-side bars** (`group_bar = "dodge"`): ```{r} stats <- summary( @@ -678,8 +677,9 @@ plot( ) ``` -To compare different versions on a single criterion, the function -produces a radar graph like the following one. +### Radar Charts + +Compare model versions across multiple variables using a radar chart (`type = "radar"`) for a single metric: ```{r} sim$`SC_Pea_2005-2006_N0`$mafruit <- @@ -711,45 +711,39 @@ plot( ) ``` -## 11. Data manipulation +## 11. Data Manipulation -Observation lists can easily be handled using e.g. -[dplyr](https://CRAN.R-project.org/package=dplyr), -[tidyr](https://CRAN.R-project.org/package=tidyr) or -[tibble](https://CRAN.R-project.org/package=tibble) packages. +### Working with Standard R Packages -The use of these packages on simulated data as returned by CroptimizR -model wrappers is sometimes prevented by their attribute -`cropr_simulation`. To easily manipulate simulated data we thus provide -two functions for (i) binding rows of data simulated on different -situations in a single data.frame or tibble and (ii) go back to the -original (cropr) format by splitting this single data.frame or tibble. +Observation data can be easily manipulated using packages like [dplyr](https://CRAN.R-project.org/package=dplyr), +[tidyr](https://CRAN.R-project.org/package=tidyr), or [tibble](https://CRAN.R-project.org/package=tibble). -```{r} -df <- bind_rows(sim) -head(df) -``` +However, the `cropr_simulation` attribute on simulated data can interfere with some operations. CroPlotR provides +two helper functions to facilitate data manipulation: + +### Converting to Data Frame -The resulting data.frame/tibble can then easily be manipulated using -standard R packages. The column `situation` contains the name of the -corresponding situation (as given in the named list `sim`). +Use `bind_rows()` to combine all situations into a single data frame: -To go back to the original format of simulated data handled by CroPlotR, -use the `split_df2sim` function: +The `situation` column identifies the source situation for each row. This format is compatible with standard +data manipulation packages. + +### Converting Back to CroPlotR Format + +After manipulation, use `split_df2sim()` to restore the original `cropr_simulation` structure: ```{r} sim_new <- split_df2sim(df) lapply(sim_new, head) ``` -## 12. Tools +## 12. Integration with Other Packages + +CroPlotR works seamlessly with popular R visualization packages to enhance your plots. -### 12.1. Interactivity with ggplotly +### 12.1. Interactive Plots with plotly -The ggplotly function in plotly library makes it very easy to create -interactive graphics from a ggplot. Do not hesitate to call it with your -plot and move your mouse over the graph to discover the features of this -function. +Convert any ggplot to an interactive visualization using `plotly::ggplotly()`: ```{r, eval = FALSE} library(plotly) @@ -757,10 +751,9 @@ library(plotly) ggplotly(plot(sim, obs = obs, type = "dynamic")[[1]]) ``` -### 12.2. Combining plots with patchwork +### 12.2. Combining Plots with patchwork -There is also the patchwork library that allows you to easily combine -several ggplot into one. +Create complex multi-panel layouts using the [patchwork](https://CRAN.R-project.org/package=patchwork) package: ```{r} library(patchwork) @@ -773,25 +766,33 @@ plot4 <- plot(sim, obs = obs, var = "masec_n")[[1]] plot1 + plot2 + plot3 + plot4 + plot_layout(ncol = 2) ``` -## 13. Data structure +## 13. Data Structure + +### Understanding the `cropr_simulation` Format + +Both `sim` and `obs` objects are named lists of data frames: -The `sim` and `obs` objects are named lists of `data.frame`s. Each element of -the list corresponds to a situation (a crop in a given year with a given management). Each `data.frame` contains the simulated or observed variables for this situation. +- **List names**: Correspond to situation identifiers (e.g., crop-year-management combinations) +- **Data frames**: Contain variable values for each situation, with one row per time step -Here's the structure of the `sim` object: +### Simulation Data Structure ```{r} lapply(sim, head) ``` -The structure of the `obs` object is similar: +### Observation Data Structure + +Observations follow the same structure: ```{r} lapply(obs, head) ``` -Note that the simulation structure is a special structure called `cropr_simulation`. You can easily make such an object from a named list of data.frames, and giving -the class attribute `cropr_simulation`, e.g.: +### Creating Custom `cropr_simulation` Objects + +You can create compatible simulation objects from your own data by adding the `cropr_simulation` class attribute +to a named list of data frames: ```{r} sim_test <- list( @@ -810,12 +811,13 @@ sim_test <- list( class(sim_test) <- append(class(sim_test), "cropr_simulation") ``` -## 14. Finding help +## 14. Getting Help + +### Documentation -You can find help for the functions directly using the name of the -function followed by the class of the object you need the method for: +Access help for specific functions by specifying the class: -- plot: +**For plotting functions:** ```{r eval=FALSE} ?plot.cropr_simulation @@ -823,18 +825,20 @@ function followed by the class of the object you need the method for: ?plot.statistics ``` -- statistics: +**For statistical functions:** ```{r eval=FALSE} ?summary.cropr_simulation ``` -If you have any problem, please [fill an -issue](https://github.com/SticsRPacks/CroPlotR/issues) on Github. +### Reporting Issues + +If you encounter problems or have suggestions, please [open an issue](https://github.com/SticsRPacks/CroPlotR/issues) +on GitHub. ## 15. Citation -If you have used this package for a study that led to a publication or -report, please cite us. You can either use the citation tool from Github -if you used the last version, or use `citation("CroPlotR")` from R -otherwise. +If CroPlotR contributed to a publication or report, please cite it: + +- **For the latest version**: Use the citation tool in the GitHub repository sidebar +- **For older versions**: Run `citation("CroPlotR")` in R to get the appropriate citation From 7b2030cfb14ec8b2c268fe2aafc348e2a95f5937 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?R=C3=A9mi=20Vezy?= Date: Wed, 14 Jan 2026 12:08:41 +0100 Subject: [PATCH 101/118] Update README.Rmd Fix issue with simulations in patchwork -> simulations were wrongly modified above --- README.Rmd | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/README.Rmd b/README.Rmd index 6cd38939..711553d4 100644 --- a/README.Rmd +++ b/README.Rmd @@ -686,10 +686,6 @@ sim$`SC_Pea_2005-2006_N0`$mafruit <- (15 / 10) * sim$`SC_Pea_2005-2006_N0`$masec_n sim$`SC_Wheat_2005-2006_N0`$mafruit <- (15 / 20) * sim$`SC_Wheat_2005-2006_N0`$masec_n -sim2$`IC_Wheat_Pea_2005-2006_N0`$mafruit <- - sim2$`IC_Wheat_Pea_2005-2006_N0`$masec_n -obs$`IC_Wheat_Pea_2005-2006_N0`$mafruit <- - (12 / 10) * obs$`IC_Wheat_Pea_2005-2006_N0`$masec_n obs$`SC_Pea_2005-2006_N0`$mafruit <- (18 / 10) * obs$`SC_Pea_2005-2006_N0`$masec_n obs$`SC_Wheat_2005-2006_N0`$mafruit <- @@ -725,6 +721,11 @@ two helper functions to facilitate data manipulation: Use `bind_rows()` to combine all situations into a single data frame: +```{r} +df <- bind_rows(sim) +head(df) +``` + The `situation` column identifies the source situation for each row. This format is compatible with standard data manipulation packages. From 0d09665989f2d60175f586ddc4222e18569cceaf Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Fri, 16 Jan 2026 15:20:00 +0100 Subject: [PATCH 102/118] Fix extract plot Closes #125 --- R/extract_plot.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/extract_plot.R b/R/extract_plot.R index 0bba59b2..9723c72f 100644 --- a/R/extract_plot.R +++ b/R/extract_plot.R @@ -60,7 +60,7 @@ extract_plot <- function(plot, var = NULL, situation = NULL, force = FALSE, if (!is.null(class(ex[[name]]))) { if (any(var %in% ex[[name]]$data$var)) { ex[[name]]$data <- ex[[name]]$data %>% - dplyr::filter(.data$var %in% var) + dplyr::filter(.data$var %in% !!var) } else { ex[[name]] <- ggplot2::ggplot() + ggplot2::theme_void() From fb4b9bf0a94cebcd176cf848ccbc6195b026fcb4 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Sat, 17 Jan 2026 18:11:43 +0100 Subject: [PATCH 103/118] Fix incorrect links --- README.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.Rmd b/README.Rmd index a269db2c..25ee7e36 100644 --- a/README.Rmd +++ b/README.Rmd @@ -32,7 +32,7 @@ coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/master/graph/badge.s [STICS](https://www6.paca.inrae.fr/stics_eng/), [APSIM](https://www.apsim.info/) or really any model. Its use does not need any particular adaptation if your model has been wrapped with the -[CroptimizR](https://github.com/SticsRPacks/CroptimizR) package thanks to the use of the `cropr_simulation` standard of data representation (see section below). +[CroptimizR](https://github.com/SticsRPacks/CroptimizR) package thanks to the use of the `cropr_simulation` standard of data representation (see section [Data structure](#13-data-structure)). If you want to be notified when a new release of this package is made, you can tick the Releases box in the "Watch / Unwatch =\> Custom" menu at the top right of [this page](https://github.com/SticsRPacks/CroPlotR). @@ -96,7 +96,7 @@ remotes::install_github("SticsRPacks/CroPlotR@*release") Only one function is exported for plots [`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html) (and its alias `autoplot()`), and one for the statistics [`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html). These functions should be the only one you need for all your plots and summary statistics. Additional ones are provided to simplify the -manipulation of simulated data (see [2.3 Data manipulation](#23-data-manipulation)). +manipulation of simulated data (see section [Data manipulation](#11-data-manipulation)). In the following, an example using the STICS crop model is presented. If you want to use another model for which a wrapper has been designed for the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, just consider defining the `sim` variable used in the examples below as From 97d1e086765c1e244344a1c527a95301ba84508e Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Sat, 17 Jan 2026 18:19:58 +0100 Subject: [PATCH 104/118] Improve README comments (#111) --- README.Rmd | 55 +++++++++++++++++++++++------------------------------- 1 file changed, 23 insertions(+), 32 deletions(-) diff --git a/README.Rmd b/README.Rmd index 25ee7e36..2c9ecbcb 100644 --- a/README.Rmd +++ b/README.Rmd @@ -103,7 +103,7 @@ the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, just consid `sim <- result$sim_list`, where `result` is the list returned by your model wrapper. Examples of use of CroPlotR with Stics and APSIM model wrappers can be found in [CroptimizR's website](https://sticsrpacks.github.io/CroptimizR/) (see Articles tab). -In the following examples, we use the `sim` and `obs` objects, which contains a simulation of two situations: +In the following examples, we use the `sim` and `obs` objects, which contain simulations and observations for two situations: - a Pea in sole crop - a Wheat in sole crop @@ -194,7 +194,7 @@ load(rdata_path) ### 3.1. Simple dynamic plot -Here is an application of dynamic plots for two example situations: +Here is an application of dynamic plots. By default, the plot function generate plots for all the variables and situations included in the data structure provided (in this example two variables, named `lai_n` and `masec_n`, and two situations, named `SC_Pea_2005-2006_N0` and `SC_Wheat_2005-2006_N0`: ```{r} plot(sim) @@ -202,7 +202,7 @@ plot(sim) ### 3.2. Observations -We can also add observations to the dynamic plots by passing the `obs` argument: +We can also add observations to the dynamic plots by passing observed values for the variables and situations considered using the `obs` argument: ```{r} plot(sim, obs = obs) @@ -222,7 +222,7 @@ plot(sim, obs = obs, var = c("lai_n")) It is possible to aggregate plots of multiple situations on the same graph when situations follow one another over time. This can be done -using the `successive` parameter: +using the `successive` parameter (used with three situations named `demo_Wheat1`, `demo_BareSoil2` and `demo_maize3` in this example): ```{r} plot( @@ -234,7 +234,7 @@ plot( ### 3.5. Overlaying variables -We can also overlay variables thanks to the "overlap" parameter with +We can also overlay variables thanks to the `overlap` parameter with dynamic plots. ```{r} @@ -253,20 +253,19 @@ plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) ### 4.1. Simple scatter plot -Here are the same plots, but presented as scatter plots: +Scatter plots can also be generated using the same plot function. By default they plot simulated against observed values for the different variables: ```{r} -# Only plotting the first situation for this one: plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) -plots$`SC_Pea_2005-2006_N0` +# Only displaying the first situation for this one: +plots[[1]] ``` ### 4.2. Plotting residuals -Residuals can also be represented against observations: +Residuals (Observed - Simulated values) can also be represented against observations: ```{r} -# Only plotting the first situation again: plots <- plot( sim, obs = obs, @@ -274,8 +273,8 @@ plots <- plot( select_scat = "res", all_situations = FALSE ) - -plots[[1]] +# Only displaying the first situation again, but this time using its name: +plots$`SC_Pea_2005-2006_N0` ``` ### 4.3. Grouping situations @@ -289,11 +288,10 @@ plot(sim, obs = obs, type = "scatter", all_situations = TRUE) ### 4.4. Reference variable on the x-axis -When plotting residual scatter plots, `reference_var` allows to choose -the reference variable on the x-axis. Thus, the observations or -simulations of this reference variable (to be chosen by suffixing the -variable name by "\_obs" or "\_sim") will be compared to the residuals -of each of the variables. +When plotting scatter plots, `reference_var` allows to choose +the reference variable on the x-axis. In this case the data provided (simulated or residuals) for all the different variables will be plotted against the observed, +simulated or residual values for this reference variable (to be chosen by suffixing the +variable name by "\_obs", "\_sim" or "\_res"). ```{r} plot( @@ -323,7 +321,7 @@ plot( ``` As you can see, this can quickly become unreadable depending on the -number of points and length of situation names; That is why you can +number of points and length of situation names. That is why you can simply assign a different symbol to each situation. ```{r} @@ -373,7 +371,7 @@ simulations objects one after the other (that is why we have to explicitely name Group simulations can be the results of simulations from different model versions, or simulations with different parameter values. -Here's an example of a dynamic plot comparing two model versions: +Here's an example of a dynamic plot comparing the results obtained from two model versions: ```{r} plot(sim, sim2, obs = obs, all_situations = FALSE) @@ -399,9 +397,7 @@ We can also compare groups of simulations with scatter plots: plot( original = sim, "New version" = sim2, - obs = obs, - type = "scatter", - all_situations = FALSE + obs = obs ) ``` @@ -497,7 +493,7 @@ When we have plots with several variables and several situations, the `extract_plot` function allows to keep the situations and variables that we need. -In the following example, we want to extract the intercrop situation and +In the following example, we want to extract the situation "SC_Wheat_2005-2006_N0" and the "masec_n" variable. ```{r} @@ -513,7 +509,7 @@ extract_plot( ### 10.1. Simple case -Here is an application of summary statistics for the 3 situations: +Here is an application of summary statistics: ```{r eval=FALSE} summary(sim, obs = obs, all_situations = FALSE) @@ -527,10 +523,7 @@ knitr::kable(s) Note that as for the `plot()` function the `obs` argument is explicitly named. This is because the first argument of the function is `...` to be able to compare groups (i.e. model versions or simulation with different -parameter values). In this example, a message warns the user because -some observed values have a zero value which causes a division by zero -in the calculation of certain statistical criteria, these values are -therefore filtered for the calculation of these criteria. +parameter values). And as for the `plot()` function again, it is possible to compute the statistical criteria for all situations at once. @@ -591,10 +584,7 @@ s <- summary( knitr::kable(s) ``` -Please read the help from -[`summary.cropr_simulation()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html) -and -[`predictor_assessment()`](https://sticsrpacks.github.io/CroPlotR/reference/predictor_assessment.html). +For more details about the list of available statistical criterion and their definition, please read the help from [`predictor_assessment()`](https://sticsrpacks.github.io/CroPlotR/reference/predictor_assessment.html). ### 10.3. Statistics plot @@ -808,6 +798,7 @@ sim_test <- list( ) class(sim_test) <- append(class(sim_test), "cropr_simulation") +head(sim_test) ``` ## 14. Finding help From 728588d53ad895f6513af475cfaf3cf661fb8dc7 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Sun, 18 Jan 2026 22:53:59 +0100 Subject: [PATCH 105/118] refactor: improve realism of synthetic data generation (#111) --- README.Rmd | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.Rmd b/README.Rmd index 2c9ecbcb..460ef788 100644 --- a/README.Rmd +++ b/README.Rmd @@ -167,12 +167,12 @@ sim_rot <- SticsRFiles::get_sim( usms_file = file.path(workspace_2, "usms.xml") ) -sim2 <- sim[2] -# Generate randomness around lai_n and masec_n for the second simulation -set.seed(123) +# Generate synthetic data mimicking the output of a simulation from a newer model version (for illustration purposes) +sim2 <- sim for (sit in names(sim2)) { - sim2[[sit]]$lai_n <- sim[[sit]]$lai_n * (1.1 + rnorm(nrow(sim2[[sit]]), mean = 0, sd = 0.01)) - sim2[[sit]]$masec_n <- sim[[sit]]$masec_n * (1.1 + rnorm(nrow(sim2[[sit]]), mean = 0, sd = 0.01)) + sim2[[sit]]$lai_n <- sim[[sit]]$lai_n * 1.1 + sim2[[sit]]$masec_n <- sim[[sit]]$masec_n * 1.1 + sim2[[sit]]$mafruit <- sim[[sit]]$mafruit * 1.1 } # Write a .RData file for reproducibility for the users From 35abf118ac236d6b1f046bee39e0fbe227e0004f Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Sun, 18 Jan 2026 22:55:41 +0100 Subject: [PATCH 106/118] refactor: update example dataset (#111) --- inst/extdata/readme_sim_obs_example.RData | Bin 60051 -> 61860 bytes .../IC_Wheat_Pea_2005-2006_N0a.obs | 32 +- .../IC_Wheat_Pea_2005-2006_N0p.obs | 32 +- .../stics_example_1/SC_Pea_2005-2006_N0.obs | 34 +- .../stics_example_1/SC_Wheat_2005-2006_N0.obs | 34 +- .../mod_sSC_Pea_2005-2006_N0.sti | 622 +++++++++--------- .../mod_sSC_Wheat_2005-2006_N0.sti | 622 +++++++++--------- .../mod_saIC_Wheat_Pea_2005-2006_N0.sti | 622 +++++++++--------- .../mod_spIC_Wheat_Pea_2005-2006_N0.sti | 622 +++++++++--------- 9 files changed, 1268 insertions(+), 1352 deletions(-) diff --git a/inst/extdata/readme_sim_obs_example.RData 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refactor: simulated data was saved instead of recomputed for sake of simplicity (#111) --- README.Rmd | 1 - 1 file changed, 1 deletion(-) diff --git a/README.Rmd b/README.Rmd index 460ef788..ea652b17 100644 --- a/README.Rmd +++ b/README.Rmd @@ -672,7 +672,6 @@ To compare different versions on a single criterion, the function produces a radar graph like the following one. ```{r} -sim$`SC_Pea_2005-2006_N0`$mafruit <- (15 / 10) * sim$`SC_Pea_2005-2006_N0`$masec_n sim$`SC_Wheat_2005-2006_N0`$mafruit <- (15 / 20) * sim$`SC_Wheat_2005-2006_N0`$masec_n From d019b821df4201c0d899440d718b3643b1a3ca16 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Sun, 18 Jan 2026 22:59:07 +0100 Subject: [PATCH 108/118] refactor: simulated data saved instead of recomputed for sake of simplicity (#111) --- README.Rmd | 12 ------------ 1 file changed, 12 deletions(-) diff --git a/README.Rmd b/README.Rmd index ea652b17..5692fb7c 100644 --- a/README.Rmd +++ b/README.Rmd @@ -672,18 +672,6 @@ To compare different versions on a single criterion, the function produces a radar graph like the following one. ```{r} - (15 / 10) * sim$`SC_Pea_2005-2006_N0`$masec_n -sim$`SC_Wheat_2005-2006_N0`$mafruit <- - (15 / 20) * sim$`SC_Wheat_2005-2006_N0`$masec_n -sim2$`IC_Wheat_Pea_2005-2006_N0`$mafruit <- - sim2$`IC_Wheat_Pea_2005-2006_N0`$masec_n -obs$`IC_Wheat_Pea_2005-2006_N0`$mafruit <- - (12 / 10) * obs$`IC_Wheat_Pea_2005-2006_N0`$masec_n -obs$`SC_Pea_2005-2006_N0`$mafruit <- - (18 / 10) * obs$`SC_Pea_2005-2006_N0`$masec_n -obs$`SC_Wheat_2005-2006_N0`$mafruit <- - (15 / 12) * obs$`SC_Wheat_2005-2006_N0`$masec_n - stats <- summary( "New version" = sim, original = sim2, From fe4611ca8e0c2e9ae36f8920c31a12d6738526c5 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Sun, 18 Jan 2026 23:02:05 +0100 Subject: [PATCH 109/118] refactor: improved illustration of group comparison (#111) --- README.Rmd | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.Rmd b/README.Rmd index 5692fb7c..176c90a6 100644 --- a/README.Rmd +++ b/README.Rmd @@ -385,9 +385,7 @@ We can also name the corresponding group in the plot by naming them while passin plot( original = sim, "New version" = sim2, - obs = obs, - type = "scatter", - all_situations = FALSE + obs = obs ) ``` @@ -397,7 +395,9 @@ We can also compare groups of simulations with scatter plots: plot( original = sim, "New version" = sim2, - obs = obs + obs = obs, + type = "scatter", + all_situations = FALSE ) ``` From c9b4248ff4e637b1bebf7446e11df110e2b895a1 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Sun, 18 Jan 2026 23:03:14 +0100 Subject: [PATCH 110/118] refactor: update stored figures (#111) --- man/figures/README-unnamed-chunk-10-1.png | Bin 34519 -> 7875 bytes man/figures/README-unnamed-chunk-10-2.png | Bin 36633 -> 8484 bytes man/figures/README-unnamed-chunk-11-1.png | Bin 8207 -> 8521 bytes man/figures/README-unnamed-chunk-12-1.png | Bin 36633 -> 6732 bytes man/figures/README-unnamed-chunk-13-1.png | Bin 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zh$8S)Qo@~94x=;IB)V~H?_L%?LH1ppkOVe&>njMiqvz71t39)N9dxX)>7MQ3k1A56 zOQQi{d3n2n+r#uYQN}s@z%2d3p&P}s@VRv5TTt&v!j1H}?RX7!PI1zCG%|=-(N&uM z(C}ekxu^FTEugx3L14==GD?&$=uI6QNsr^l`<<(hKb;3tk;7_EPxpuQ+4mjdu841Q zXK8!KiyQ%cvhxrn*zE+{6Kz0#Ho-GLv02+Xd#QErZf1pI9$`YfY7q12857sJ>eU6N z_`)z)Ppj*~Yp~ZmxE&(z)7F3W)A`*8EY48#yjT@6I96+-&0U{wX7ey?p8{k`94xF< z6@Y=ut1`(N{h^HWVOrKUyW6dcR6(dGy#|R;^b;#m57z5Bp+1q;g^HI$l&kwljta5>jTtTBoGuF;98m zLtZ1P-7mS}^ZAz-V}c9To0PoIyP(|VjoP47iRI#fPH8UhhDehx3=gf%GJ5yE7+snG zHfyRMKKq>meFOcLGRM!g9&WxJ!e&0p-{<;MzzdUj1qtGj@aCy>r6`A>WEYDM=U>Zs zGjf^`(D2&+k9*36=Etb4H*rdrCf(2h@Fwhr!DV-)jl8=`sD9#U{z%uMYD`En z5gpf|wzetO&i&DQsZvwzPwUD8Ps+{~QVsr>ya9Zk6aN4vJP-Z zLU_zQIp|wH)6S#rSmX?&l)YMi*Z32h-m0M~nV$}2myAuU9_xs9l5_pN)N8|N_$;T3 zF}4s}x9gC5peWYz^jEu?B?b6zG09%)q(!x_gJoy2wt<)HK1!~1wh~}q#F)R@rTt~H z;_8^NB`uh4_endQjOzdZ7ta3z%s%?b4Mse$sGR-;kn;MDV4}VSuJtKIRbJ(iGJ)|U zm2T?hv`lWBmzK Date: Wed, 21 Jan 2026 21:42:21 +0100 Subject: [PATCH 111/118] docs: fix broken links in README --- README.Rmd | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/README.Rmd b/README.Rmd index 2477d634..aaaf909b 100644 --- a/README.Rmd +++ b/README.Rmd @@ -46,8 +46,8 @@ of [this repository](https://github.com/SticsRPacks/CroPlotR). - [2. Introduction](#2-introduction) - [3. Dynamic plots](#3-dynamic-plots) - [3.1. Simple dynamic plot](#31-simple-dynamic-plot) - - [3.2. Observations](#32-observations) - - [3.3. Filter variables](#33-filter-variables) + - [3.2. Adding Observations](#32-adding-observations) + - [3.3. Filtering variables](#33-filtering-variables) - [3.4. Successive situations](#34-successive-situations) - [3.5. Overlaying variables](#35-overlaying-variables) - [4. Scatter plots](#4-scatter-plots) @@ -55,22 +55,22 @@ of [this repository](https://github.com/SticsRPacks/CroPlotR). - [4.2. Plotting residuals](#42-plotting-residuals) - [4.3. Grouping situations](#43-grouping-situations) - [4.4. Reference variable on the x-axis](#44-reference-variable-on-the-x-axis) - - [4.5. Different shapes for situations](#45-different-shapes-for-situations) + - [4.5. Distinguishing Situations with Shapes](#45-distinguishing-situations-with-shapes) - [5. Comparing model versions](#5-comparing-model-versions) - [6. Error bars](#6-error-bars) - [7. Intercrops](#7-intercrops) - - [8. Plot saving](#8-plot-saving) - - [9. Plot extraction](#9-plot-extraction) + - [8. Saving Plots](#8-saving-plots) + - [9. Extracting Individual Plots](#9-extracting-individual-plots) - [10. Statistics](#10-statistics) - - [10.1. Simple case](#101-simple-case) - - [10.2. Several groups](#102-several-groups) - - [10.3. Statistics plot](#103-statistics-plot) + - [10.1. Basic Usage](#101-basic-usage) + - [10.2. Comparing Multiple Groups](#102-comparing-multiple-groups) + - [10.3. Visualizing Statistics](#103-visualizing-statistics) - [11. Data manipulation](#11-data-manipulation) - - [12. Tools](#12-tools) - - [12.1. Interactivity with ggplotly](#121-interactivity-with-ggplotly) + - [12. Integration with Other Packages](#12-integration-with-other-packages) + - [12.1. Interactive Plots with plotly](#121-interactive-plots-with-plotly) - [12.2. Combining plots with patchwork](#122-combining-plots-with-patchwork) - [13. Data structure](#13-data-structure) - - [14. Finding help](#14-finding-help) + - [14. Getting help](#14-getting-help) - [15. Citation](#15-citation) ## 1. Installation From f40f1304bb47188217530f6748670c65bc053066 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 21 Jan 2026 21:44:24 +0100 Subject: [PATCH 112/118] docs: improved text in README --- README.Rmd | 57 ++++++++++++++++++++++++++++++------------------------ 1 file changed, 32 insertions(+), 25 deletions(-) diff --git a/README.Rmd b/README.Rmd index aaaf909b..bab58acd 100644 --- a/README.Rmd +++ b/README.Rmd @@ -105,18 +105,20 @@ These functions cover most visualization and analysis needs. Additional helper f ### Using CroPlotR with Model Wrappers If you're using a model wrapper from the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, -simply extract the simulations as: `sim <- result$sim_list`. For detailed examples with STICS and APSIM, +you can simply extract the simulations with: `sim <- result$sim_list`, where `result` is the object returned by the model wrapper. For detailed examples with STICS and APSIM, visit [CroptimizR's documentation](https://sticsrpacks.github.io/CroptimizR/) (Articles tab). ### Example Data The following examples use simulation and observation data from the STICS crop model: -**Sole crops** (`sim` and `obs`): +**Sole crops** (objects `sim` and `obs`): + - Pea in sole crop (situation: `SC_Pea_2005-2006_N0`) - Wheat in sole crop (situation: `SC_Wheat_2005-2006_N0`) **Intercrop** (`sim_intercrop` and `obs_intercrop`): + - Wheat and Pea intercrop (situation: `IC_Wheat_Pea_2005-2006_N0`)
      Click to view code for loading example data @@ -203,20 +205,21 @@ Dynamic plots show variable values over time, making them ideal for visualizing ### 3.1. Simple Dynamic Plot -Create basic time-series plots for all variables and situations: +Create basic time-series plots for all variables and situations simulated (in this example, three variables, `lai_n`, `masec_n` and `mafruit`, and two situations, `SC_Pea_2005-2006_N0` and `SC_Wheat_2005-2006_N0`): ```{r} plot(sim) ``` -By default, the plot function generate plots for all the variables and situations included in the data structure provided (in this example two variables, named `lai_n` and `masec_n`, and two situations, named `SC_Pea_2005-2006_N0` and `SC_Wheat_2005-2006_N0`. ### 3.2. Adding Observations -Overlay observed data on simulated outputs for model validation using the `obs` argument: +Overlay observed data on simulated outputs using the `obs` argument: ```{r} -plot(sim, obs = obs) +plots <- plot(sim, obs = obs) +# Only displaying the first situation for this one: +plots[[1]] ``` > **Note:** The `obs` argument must be explicitly named. @@ -226,7 +229,9 @@ plot(sim, obs = obs) By default, all variables are plotted. Use `var` to select specific variables: ```{r} -plot(sim, obs = obs, var = c("lai_n")) +plots <- plot(sim, obs = obs, var = c("lai_n")) +# Only displaying the first situation for this one: +plots[[1]] ``` ### 3.4. Successive Situations @@ -246,7 +251,9 @@ plot( Plot multiple variables on the same graph using the `overlap` parameter: ```{r} -plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) +plots <- plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) +# Only displaying the first situation for this one: +plots[[1]] ``` > **Note:** Automatic variable scaling is not yet available ([see issue](https://github.com/SticsRPacks/CroPlotR/issues/2)). @@ -285,7 +292,7 @@ plots$`SC_Pea_2005-2006_N0` ### 4.3. Grouping Situations -Combine all situations in a single plot using `all_situations = TRUE`: +Combine data from all situations in a single plot using `all_situations = TRUE`: ```{r} plot(sim, obs = obs, type = "scatter", all_situations = TRUE) @@ -293,7 +300,7 @@ plot(sim, obs = obs, type = "scatter", all_situations = TRUE) ### 4.4. Reference Variable on the X-axis -For residual plots, use `reference_var` to specify which variable appears on the x-axis. +Use `reference_var` to specify which variable appears on the x-axis. Suffix the variable name with `_obs`, `_sim` or `_res` to choose observed, simulated or residual values: ```{r} @@ -371,21 +378,23 @@ This is why the `obs` argument must be explicitly named. ### Dynamic Plot Comparison ```{r} -plot(sim, sim2, obs = obs, all_situations = FALSE) +plots <- plot(sim, sim2, obs = obs, all_situations = FALSE) +# Only displaying the first situation for this one: +plots[[1]] ``` -**There is only one plot here because `sim2` contains a single situation ("SC_Wheat_2005-2006_N0").** - ### Naming Model Versions Provide descriptive names for each simulation group: ```{r} -plot( +plots <- plot( original = sim, "New version" = sim2, obs = obs ) +# Only displaying the first situation for this one: +plots[[1]] ``` ### Scatter Plot Comparison @@ -393,13 +402,15 @@ plot( Model versions can also be compared using scatter plots: ```{r} -plot( +plots <- plot( original = sim, "New version" = sim2, obs = obs, type = "scatter", all_situations = FALSE ) +# Only displaying the first situation for this one: +plots[[1]] ``` ## 6. Error Bars @@ -422,7 +433,7 @@ plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) ## 7. Intercrops -CroPlotR automatically handles intercrop situations where multiple plant species are grown together. +CroPlotR automatically handles simulations of intercrop situations where multiple plant species are grown together. ### Dynamic Plots for Intercrops @@ -511,7 +522,7 @@ extract_plot( ## 10. Statistics -Compute performance metrics to quantitatively evaluate model accuracy. +Compute performance metrics to quantitatively compare simulated and observed values. ### 10.1. Basic Usage @@ -526,8 +537,7 @@ s <- summary(sim, obs = obs, all_situations = FALSE) knitr::kable(s) ``` -> **Note:** The `obs` argument must be explicitly named (same reason as for `plot()`). The warning message -> indicates that zero-valued observations were filtered out to avoid division-by-zero errors in certain metrics. +> **Note:** The `obs` argument must be explicitly named (same reason as for `plot()`). ### Aggregated Statistics @@ -682,7 +692,7 @@ stats <- summary( "New version" = sim, original = sim2, obs = obs, - stats = c("R2", "nRMSE"), + stats = c("nRMSE"), all_situations = TRUE ) @@ -761,7 +771,7 @@ plot1 + plot2 + plot3 + plot4 + plot_layout(ncol = 2) Both `sim` and `obs` objects are named lists of data frames: - **List names**: Correspond to situation identifiers (e.g., crop-year-management combinations) -- **Data frames**: Contain variable values for each situation, with one row per time step +- **Data frames**: Store variable values for each situation, with one row per time step and one column per simulated or observed variable. They include a `Date` column as a time reference (at Date or POSIXct format), and may optionally contain `Plant` and `Dominance` columns to indicate crop names and their status (“Principal” or “Associated”) in intercrop datasets. ### Simulation Data Structure @@ -827,7 +837,4 @@ on GitHub. ## 15. Citation -If CroPlotR contributed to a publication or report, please cite it: - -- **For the latest version**: Use the citation tool in the GitHub repository sidebar -- **For older versions**: Run `citation("CroPlotR")` in R to get the appropriate citation +If CroPlotR contributed to a publication or report, please cite it using the reference corresponding to the version you used. To obtain the correct citation, run citation("CroPlotR") in R. From 427e14a4449ce432a033ceb78780b3129b5d35c5 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 21 Jan 2026 21:46:34 +0100 Subject: [PATCH 113/118] docs: simplify standard deviation data handling --- README.Rmd | 21 +++++++++++---------- 1 file changed, 11 insertions(+), 10 deletions(-) diff --git a/README.Rmd b/README.Rmd index bab58acd..cd786c20 100644 --- a/README.Rmd +++ b/README.Rmd @@ -184,9 +184,19 @@ for (sit in names(sim2)) { sim2[[sit]]$mafruit <- sim[[sit]]$mafruit * 1.1 } +# Generate synthetic data mimicking standard deviation of observations (for illustration purposes) +vars <- c("lai_n", "masec_n", "mafruit") +p <- 0.20 +obs_sd <- lapply(obs, function(df) { + df_sd <- df + common_vars <- intersect(vars, names(df_sd)) + df_sd[common_vars] <- lapply(df_sd[common_vars], function(x) p * x) + df_sd +}) # Write a .RData file for reproducibility for the users save( sim, sim2, sim_intercrop, obs, obs_intercrop, sim_rot, + obs_sd, file = "inst/extdata/readme_sim_obs_example.RData" ) ``` @@ -416,18 +426,9 @@ plots[[1]] ## 6. Error Bars Add uncertainty estimates to observations using the `obs_sd` parameter, which must have the same structure as `obs`. -Error bars represent ±2 standard deviations (95% confidence interval). - -The example below creates synthetic standard deviations for demonstration: +Error bars are then displayed as ±2 standard deviations, corresponding to an approximate 95% confidence interval under the assumption of Gaussian observation errors. ```{r} -obs_sd <- obs -names_obs <- names(obs_sd$`SC_Pea_2005-2006_N0`) -obs_sd$`SC_Pea_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] <- - 0.05 * obs_sd$`SC_Pea_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] -obs_sd$`SC_Wheat_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] <- - 0.2 * obs_sd$`SC_Wheat_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] - plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) ``` From d8fd05cc0b6ab2bde929d4fc71bf9e79775197fa Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Wed, 21 Jan 2026 21:47:00 +0100 Subject: [PATCH 114/118] docs: added Valentine in list of contributors --- DESCRIPTION | 1 + 1 file changed, 1 insertion(+) diff --git a/DESCRIPTION b/DESCRIPTION index 875ce2c3..9afba78d 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -15,6 +15,7 @@ Authors@R: c( comment = c(ORCID = "0000-0002-4044-4322")), person("Michel", "Giner", , "michel.giner@cirad.fr", role = "aut", comment = c(ORCID = "0000-0002-9310-2377")), + person("Valentine", "Rahier", role = "ctb"), person("Amine", "Barkaoui", role = "ctb"), person("Patrick", "Lutz", role = "ctb") ) From 7ed86d5ab20365bf3fe0f7c971d4e84e66e80264 Mon Sep 17 00:00:00 2001 From: Valentine Rahier Date: Thu, 22 Jan 2026 16:14:17 +0100 Subject: [PATCH 115/118] Fix scatterplots axes limits after extract_plot Fixes #127 --- R/extract_plot.R | 30 ++++++++++++++++++++---------- 1 file changed, 20 insertions(+), 10 deletions(-) diff --git a/R/extract_plot.R b/R/extract_plot.R index 9723c72f..84251f5f 100644 --- a/R/extract_plot.R +++ b/R/extract_plot.R @@ -50,17 +50,30 @@ extract_plot <- function(plot, var = NULL, situation = NULL, force = FALSE, ) } stop("plot argument is not a named list") - } else { - situations_names <- names(plot) } ex <- plot - if (!is.null(var)) { - for (name in situations_names) { + if (!is.null(situations)) { + situations <- match.arg(situations, names(plot), several.ok = TRUE) + ex <- ex[situations] + } + + selected_vars <- var + if (!is.null(selected_vars)) { + for (name in names(ex)) { if (!is.null(class(ex[[name]]))) { - if (any(var %in% ex[[name]]$data$var)) { + if (any(selected_vars %in% ex[[name]]$data$var)) { + gb <- ggplot2::ggplot_build(ex[[name]]) + layout <- gb$layout$layout %>% + dplyr::filter(.data$var %in% selected_vars) + ex[[name]]$facet$new_x_scales <- ex[[name]]$facet$new_x_scales[ + layout$PANEL + ] + ex[[name]]$facet$new_y_scales <- ex[[name]]$facet$new_y_scales[ + layout$PANEL + ] ex[[name]]$data <- ex[[name]]$data %>% - dplyr::filter(.data$var %in% !!var) + dplyr::filter(.data$var %in% selected_vars) } else { ex[[name]] <- ggplot2::ggplot() + ggplot2::theme_void() @@ -68,9 +81,6 @@ extract_plot <- function(plot, var = NULL, situation = NULL, force = FALSE, } } } - if (!is.null(situations)) { - situations <- match.arg(situations, names(plot), several.ok = TRUE) - ex <- ex[situations] - } ex } + From aeaff8ccbf7a1862d5f067d538d88a88b28bd6cf Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Thu, 22 Jan 2026 22:25:39 +0100 Subject: [PATCH 116/118] docs: add example data for plot of standard deviation --- inst/extdata/readme_sim_obs_example.RData | Bin 61860 -> 62165 bytes .../IC_Wheat_Pea_2005-2006_N0a.sd | 26 ++++++++++++++++ .../IC_Wheat_Pea_2005-2006_N0p.sd | 26 ++++++++++++++++ .../stics_example_1/SC_Pea_2005-2006_N0.sd | 28 ++++++++++++++++++ .../stics_example_1/SC_Wheat_2005-2006_N0.sd | 28 ++++++++++++++++++ 5 files changed, 108 insertions(+) create mode 100644 inst/extdata/stics_example_1/IC_Wheat_Pea_2005-2006_N0a.sd 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+2006;11;29;333;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99;-999.99 From 125c4a1a04ca44b7e22989d53c70caad234145d0 Mon Sep 17 00:00:00 2001 From: Samuel Buis Date: Thu, 22 Jan 2026 22:25:54 +0100 Subject: [PATCH 117/118] docs: update README.md --- README.Rmd | 3 +- README.md | 970 ++++++++++++---------- man/figures/README-unnamed-chunk-12-1.png | Bin 6732 -> 6725 bytes man/figures/README-unnamed-chunk-14-1.png | Bin 6706 -> 6558 bytes man/figures/README-unnamed-chunk-22-1.png | Bin 9215 -> 8817 bytes man/figures/README-unnamed-chunk-30-1.png | Bin 8176 -> 7974 bytes man/figures/README-unnamed-chunk-50-1.png | Bin 0 -> 11489 bytes 7 files changed, 547 insertions(+), 426 deletions(-) create mode 100644 man/figures/README-unnamed-chunk-50-1.png diff --git a/README.Rmd b/README.Rmd index cd786c20..748b70b4 100644 --- a/README.Rmd +++ b/README.Rmd @@ -22,8 +22,7 @@ knitr::opts_chunk$set( [![Codecov test -coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/master/graph/badge.svg)](https://app.codecov.io/gh/SticsRPacks/CroPlotR?branch=master) -[![R-CMD-check](https://github.com/SticsRPacks/CroPlotR/actions/workflows/check-standard.yaml/badge.svg?branch=main)](https://github.com/SticsRPacks/CroPlotR/actions/workflows/check-standard.yaml) +coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/main/graph/badge.svg)](https://app.codecov.io/gh/SticsRPacks/CroPlotR?branch=main) [![DOI](https://zenodo.org/badge/263962392.svg)](https://zenodo.org/badge/latestdoi/263962392) diff --git a/README.md b/README.md index 1a0f1a3c..27ef66ed 100644 --- a/README.md +++ b/README.md @@ -5,219 +5,205 @@ -[![Project Status: WIP – Initial development is in progress, but there -has not yet been a stable, usable release suitable for the -public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip) [![Codecov test -coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/master/graph/badge.svg)](https://app.codecov.io/gh/SticsRPacks/CroPlotR?branch=master) -[![R-CMD-check](https://github.com/SticsRPacks/CroPlotR/actions/workflows/check-standard.yaml/badge.svg?branch=main)](https://github.com/SticsRPacks/CroPlotR/actions/workflows/check-standard.yaml) +coverage](https://codecov.io/gh/SticsRPacks/CroPlotR/branch/main/graph/badge.svg)](https://app.codecov.io/gh/SticsRPacks/CroPlotR?branch=main) [![DOI](https://zenodo.org/badge/263962392.svg)](https://zenodo.org/badge/latestdoi/263962392) -`CroPlotR` aims at the standardization of the process of analyzing the -outputs from crop models such as +`CroPlotR` standardizes the analysis and visualization of crop model +outputs, including models such as [STICS](https://www6.paca.inrae.fr/stics_eng/), -[APSIM](https://www.apsim.info/) or really any model. +[APSIM](https://www.apsim.info/), and others. -Its use does not need any particular adaptation if your model has been -wrapped with the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) -package. +The package works seamlessly with models wrapped using the +[CroptimizR](https://github.com/SticsRPacks/CroptimizR) package through +the `cropr_simulation` data format (see [section Data +structure](#13-data-structure)). -If you want to be notified when a new release of this package is made, -you can tick the Releases box in the “Watch / Unwatch =\> Custom” menu -at the top right of [this -page](https://github.com/SticsRPacks/CroPlotR). +**Stay updated:** To receive notifications about new releases, click +“Watch” → “Custom” → “Releases” at the top of [this +repository](https://github.com/SticsRPacks/CroPlotR). ## Table of Contents - [CroPlotR](#croplotr) - [Table of Contents](#table-of-contents) - [1. Installation](#1-installation) - - [2. Examples](#2-examples) - - [2.1 Plotting](#21-plotting) - - [2.1.1 Dynamic plots](#211-dynamic-plots) - - [2.1.2 Scatter plots](#212-scatter-plots) - - [2.1.3 Group comparison](#213-group-comparison) - - [2.1.4 Plot saving](#214-plot-saving) - - [2.1.5 Plot extracting](#215-plot-extracting) - - [2.2 Statistics](#22-statistics) - - [2.2.1 Simple case](#221-simple-case) - - [2.2.2 Several groups](#222-several-groups) - - [2.2.3 Statistics plot](#223-statistics-plot) - - [2.3 Data manipulation](#23-data-manipulation) - - [3. Tools](#3-tools) - - [3.1 ggplotly](#31-ggplotly) - - [3.2 patchwork](#32-patchwork) - - [4. Help](#4-help) - - [5. Citation](#5-citation) + - [2. Introduction](#2-introduction) + - [3. Dynamic plots](#3-dynamic-plots) + - [3.1. Simple dynamic plot](#31-simple-dynamic-plot) + - [3.2. Adding Observations](#32-adding-observations) + - [3.3. Filtering variables](#33-filtering-variables) + - [3.4. Successive situations](#34-successive-situations) + - [3.5. Overlaying variables](#35-overlaying-variables) + - [4. Scatter plots](#4-scatter-plots) + - [4.1. Simple scatter plot](#41-simple-scatter-plot) + - [4.2. Plotting residuals](#42-plotting-residuals) + - [4.3. Grouping situations](#43-grouping-situations) + - [4.4. Reference variable on the + x-axis](#44-reference-variable-on-the-x-axis) + - [4.5. Distinguishing Situations with + Shapes](#45-distinguishing-situations-with-shapes) + - [5. Comparing model versions](#5-comparing-model-versions) + - [6. Error bars](#6-error-bars) + - [7. Intercrops](#7-intercrops) + - [8. Saving Plots](#8-saving-plots) + - [9. Extracting Individual Plots](#9-extracting-individual-plots) + - [10. Statistics](#10-statistics) + - [10.1. Basic Usage](#101-basic-usage) + - [10.2. Comparing Multiple Groups](#102-comparing-multiple-groups) + - [10.3. Visualizing Statistics](#103-visualizing-statistics) + - [11. Data manipulation](#11-data-manipulation) + - [12. Integration with Other + Packages](#12-integration-with-other-packages) + - [12.1. Interactive Plots with + plotly](#121-interactive-plots-with-plotly) + - [12.2. Combining plots with + patchwork](#122-combining-plots-with-patchwork) + - [13. Data structure](#13-data-structure) + - [14. Getting help](#14-getting-help) + - [15. Citation](#15-citation) ## 1. Installation -You can install the released version of CroPlotR from -[Github](https://github.com/SticsRPacks/CroPlotR) either using -`devtools` or the lightweight `remotes` package: +Install the latest release from +[GitHub](https://github.com/SticsRPacks/CroPlotR) using either +`devtools` or `remotes`: -- With `devtools` +**Using `remotes` (recommended):** ``` r -devtools::install_github("SticsRPacks/CroPlotR@*release") +# install.packages("remotes") +remotes::install_github("SticsRPacks/CroPlotR@*release") ``` -- With `remotes` +**Using `devtools`:** ``` r -# install.packages("remotes") -remotes::install_github("SticsRPacks/CroPlotR@*release") +devtools::install_github("SticsRPacks/CroPlotR@*release") ``` -Normally, all the package dependencies will be installed for CRAN -packages. +## 2. Introduction -## 2. Examples +### Core Functions -At the moment, only one function is exported for plots -[`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html) -(and its alias `autoplot()`), and one for the statistics -[`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html). -These functions should be the only one you need for all your plots and -summary statistics. Additional ones are provided to simplify the -manipulation of simulated data (see [2.3 Data -manipulation](#23-data-manipulation)). +CroPlotR provides two main functions: -In the following, an example using the STICS crop model is presented. If -you want to use another model for which a wrapper has been designed for -the [CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, -just consider defining the `sim` variable used in the examples below as -`sim <- result$sim_list`, where `result` is the list returned by your -model wrapper. Examples of use of CroPlotR with Stics and APSIM model -wrappers can be found in [CroptimizR’s -website](https://sticsrpacks.github.io/CroptimizR/) (see Articles tab). +- **[`plot()`](https://sticsrpacks.github.io/CroPlotR/reference/plot.cropr_simulation.html)** + (alias: `autoplot()`) for creating visualizations +- **[`summary()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html)** + for computing statistical metrics -In the following example a simulation of three situations (called USM in -STICS) with their observations is used: +These functions cover most visualization and analysis needs. Additional +helper functions are available for data manipulation (see [section Data +manipulation](#11-data-manipulation)). -- an intercrop of Wheat and pea -- a Pea in sole crop -- a Wheat in sole crop +### Using CroPlotR with Model Wrappers -Let’s import the simulation and observation data: +If you’re using a model wrapper from the +[CroptimizR](https://github.com/SticsRPacks/CroptimizR) package, you can +simply extract the simulations with: `sim <- result$sim_list`, where +`result` is the object returned by the model wrapper. For detailed +examples with STICS and APSIM, visit [CroptimizR’s +documentation](https://sticsrpacks.github.io/CroptimizR/) (Articles +tab). -``` r -library(CroPlotR) +### Example Data -# Importing an example with three situations with observation: -workspace <- system.file( - file.path("extdata", "stics_example_1"), - package = "CroPlotR" -) +The following examples use simulation and observation data from the +STICS crop model: -situations <- SticsRFiles::get_usms_list( - file = file.path(workspace, "usms.xml") -) +**Sole crops** (objects `sim` and `obs`): -sim <- SticsRFiles::get_sim( - workspace = workspace, - usms_file = file.path(workspace, "usms.xml") -) -#> mod_spIC_Wheat_Pea_2005-2006_N0.stimod_saIC_Wheat_Pea_2005-2006_N0.sti -#> mod_sSC_Pea_2005-2006_N0.sti -#> mod_sSC_Wheat_2005-2006_N0.sti - -obs <- SticsRFiles::get_obs( - workspace = workspace, - usm = situations, - usms_file = file.path(workspace, "usms.xml") -) -#> IC_Wheat_Pea_2005-2006_N0p.obsIC_Wheat_Pea_2005-2006_N0a.obs -#> SC_Pea_2005-2006_N0.obs -#> SC_Wheat_2005-2006_N0.obs -``` +- Pea in sole crop (situation: `SC_Pea_2005-2006_N0`) +- Wheat in sole crop (situation: `SC_Wheat_2005-2006_N0`) -### 2.1 Plotting +**Intercrop** (`sim_intercrop` and `obs_intercrop`): -#### 2.1.1 Dynamic plots +- Wheat and Pea intercrop (situation: `IC_Wheat_Pea_2005-2006_N0`) -Here is an application of dynamic plots for the 3 situations: +
      + +Click to view code for loading example data + ``` r -p <- plot(sim, obs = obs) +library(CroPlotR) +#> Registered S3 method overwritten by 'CroPlotR': +#> method from +#> [.cropr_simulation SticsRFiles +#> Learn CroPlotR at: https://SticsRPacks.github.io/CroPlotR +#> +#> Please cite CroPlotR in your work: +#> Vezy R, Buis S, Midingoyi C, Lecharpentier P, Giner M (2025). +#> CroPlotR: A Package to Analyze Crop Model Simulations Outputs with +#> Plots and Statistics. R package version 0.11.0, +#> https://doi.org/10.5281/zenodo.4442330, +#> . +rdata_path <- system.file(file.path("extdata", "readme_sim_obs_example.RData"), package = "CroPlotR") +load(rdata_path) ``` -Note that the `obs` argument is explicitly named. This is because the -first argument of the function is `...` (we’ll see why in a minute). +
      -The plot function returns a named list of ggplot objects. +## 3. Dynamic Plots -To plot all of them, just do +Dynamic plots show variable values over time, making them ideal for +visualizing temporal patterns in crop model outputs. -``` r -p -#> $`IC_Wheat_Pea_2005-2006_N0` -``` +### 3.1. Simple Dynamic Plot - +Create basic time-series plots for all variables and situations +simulated (in this example, three variables, `lai_n`, `masec_n` and +`mafruit`, and two situations, `SC_Pea_2005-2006_N0` and +`SC_Wheat_2005-2006_N0`): - #> - #> $`SC_Pea_2005-2006_N0` +``` r +plot(sim) +#> $`SC_Pea_2005-2006_N0` +``` - + #> #> $`SC_Wheat_2005-2006_N0` - + -or simply +### 3.2. Adding Observations -``` r -plot(sim, obs = obs) -``` - -In this case, the elements of the list take the name of the situations. +Overlay observed data on simulated outputs using the `obs` argument: ``` r -names(p) -#> [1] "IC_Wheat_Pea_2005-2006_N0" "SC_Pea_2005-2006_N0" "SC_Wheat_2005-2006_N0" +plots <- plot(sim, obs = obs) +# Only displaying the first situation for this one: +plots[[1]] ``` -To plot only one of the graph, access it using its name: + -``` r -p$`IC_Wheat_Pea_2005-2006_N0` -``` +> **Note:** The `obs` argument must be explicitly named. - +### 3.3. Filtering Variables -or index: +By default, all variables are plotted. Use `var` to select specific +variables: ``` r -p[[1]] +plots <- plot(sim, obs = obs, var = c("lai_n")) +# Only displaying the first situation for this one: +plots[[1]] ``` -It is possible to aggregate plots of multiple situations on the same -graph when situations follow one another over time. This can be done -using the `successive` parameter. + -``` r -workspace <- system.file( - file.path("extdata", "stics_example_successive"), - package = "CroPlotR" -) - -situations <- SticsRFiles::get_usms_list( - file = file.path(workspace, "usms.xml") -) +### 3.4. Successive Situations -sim_rot <- SticsRFiles::get_sim( - workspace = workspace, - usm = situations, - usms_file = file.path(workspace, "usms.xml") -) -#> mod_sdemo_Wheat1.sti -#> mod_sdemo_BareSoil2.sti -#> mod_sdemo_maize3.sti +Combine multiple sequential situations (e.g., crop rotations) into a +single continuous timeline using the `successive` parameter: +``` r plot( sim_rot, var = c("resmes", "masec_n"), @@ -226,52 +212,50 @@ plot( #> $`demo_Wheat1 | demo_BareSoil2 | demo_maize3 | ` ``` - + + +### 3.5. Overlaying Variables -We can also overlay variables thanks to the “overlap” parameter with -dynamic plots. +Plot multiple variables on the same graph using the `overlap` parameter: ``` r -plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) -#> $`IC_Wheat_Pea_2005-2006_N0` +plots <- plot(sim, obs = obs, overlap = list(list("lai_n", "masec_n"))) +# Only displaying the first situation for this one: +plots[[1]] ``` - + - #> - #> $`SC_Pea_2005-2006_N0` - - - - #> - #> $`SC_Wheat_2005-2006_N0` +> **Note:** Automatic variable scaling is not yet available ([see +> issue](https://github.com/SticsRPacks/CroPlotR/issues/2)). To scale +> variables, transform your data before plotting and add a secondary +> axis using +> [`sec_axis()`](https://ggplot2.tidyverse.org/reference/sec_axis.html). - +## 4. Scatter Plots -> Note that it is not possible to scale the variables right now from the -> plot function (see -> [issue](https://github.com/SticsRPacks/CroPlotR/issues/2)). If you -> want to do so, you are encouraged to scale before the plotting -> function, and to add a second axis using -> [sec_axis](https://ggplot2.tidyverse.org/reference/sec_axis.html) on -> the resulting plot. +Scatter plots compare simulated versus observed values, providing visual +assessment of model performance. -#### 2.1.2 Scatter plots +### 4.1. Simple Scatter Plot -Here are the same plots, but presented as scatter plots: +Create observed vs. simulated scatter plots by setting +`type = "scatter"`: ``` r -# Only plotting the first situation for this one: plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) -plots$`IC_Wheat_Pea_2005-2006_N0` +# Only displaying the first situation for this one: +plots[[1]] ``` - + + +### 4.2. Plotting Residuals -Residues can also be represented against observations: +Visualize model residuals (observed - simulated values) using +`select_scat = "res"`: ``` r -# Only plotting the first situation again: plots <- plot( sim, obs = obs, @@ -279,27 +263,29 @@ plots <- plot( select_scat = "res", all_situations = FALSE ) - -plots[[1]] +# Only displaying the first situation again, but this time using its name: +plots$`SC_Pea_2005-2006_N0` ``` - + + +### 4.3. Grouping Situations -All these data can also be represented with a single graph for all -situations: +Combine data from all situations in a single plot using +`all_situations = TRUE`: ``` r plot(sim, obs = obs, type = "scatter", all_situations = TRUE) #> $all_situations ``` - + -When plotting residual scatter plots, `reference_var` allows to choose -the reference variable on the x-axis. Thus, the observations or -simulations of this reference variable (to be chosen by suffixing the -variable name by “\_obs” or “\_sim”) will be compared to the residuals -of each of the variables. +### 4.4. Reference Variable on the X-axis + +Use `reference_var` to specify which variable appears on the x-axis. +Suffix the variable name with `_obs`, `_sim` or `_res` to choose +observed, simulated or residual values: ``` r plot( @@ -313,16 +299,19 @@ plot( #> $all_situations ``` - + + +### 4.5. Distinguishing Situations with Shapes + +When plotting multiple situations together (`all_situations = TRUE`), +differentiate them using the `shape_sit` parameter. -The points on the graphs can be shown in different shapes to -differentiate between situations when `all_situations = TRUE`. If -desired, the names of the situations can be displayed. +**Display situation names as text labels:** ``` r plot( sim, - obs = obs[c(2, 3)], + obs = obs, type = "scatter", all_situations = TRUE, shape_sit = "txt" @@ -330,11 +319,10 @@ plot( #> $all_situations ``` - + -As you can see, this can quickly become unreadable depending on the -number of points and length of situation names; That is why you can -simply assign a different symbol to each situation. +Text labels can become cluttered with many data points. Use distinct +symbols instead: ``` r plot( @@ -347,10 +335,10 @@ plot( #> $all_situations ``` - + -It is also possible to represent a group of situations with the same -symbol when, for example, clusters are identified. +**Group multiple situations under a single symbol** (e.g., for +identified clusters): ``` r plot( @@ -364,10 +352,9 @@ plot( #> $all_situations ``` - + -You can also name your `situation_group` list and thus customize (e.g -shorten) the plot legend. +**Customize legend labels** by naming your `situation_group` list: ``` r plot( @@ -383,87 +370,100 @@ plot( #> $all_situations ``` - + + +## 5. Comparing Model Versions -By default, all variables are returned by `plot()`, but you can filter -them using the `var` argument: +Compare different model versions or parameter sets by passing multiple +simulation objects to `plot()`. This is why the `obs` argument must be +explicitly named. + +### Dynamic Plot Comparison ``` r -plot(sim, obs = obs, type = "scatter", all_situations = TRUE, var = c("lai_n")) -#> $all_situations +plots <- plot(sim, sim2, obs = obs, all_situations = FALSE) +# Only displaying the first situation for this one: +plots[[1]] ``` - + -Error bars related to observations can also be added to the graph using -the `obs_sd` parameter which must be of the same shape as `obs`. In our -example, we will create a false data frame with the only purpose of -having a preview of the result. To have 95% confidence, the error bar is -equal to two standard deviations on each side of the point. +### Naming Model Versions -``` r -obs_sd <- obs -names_obs <- names(obs_sd$`SC_Pea_2005-2006_N0`) -obs_sd$`SC_Pea_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] <- - 0.05 * obs_sd$`SC_Pea_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] -obs_sd$`SC_Wheat_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] <- - 0.2 * obs_sd$`SC_Wheat_2005-2006_N0`[, !(names_obs %in% c("Date", "Plant"))] +Provide descriptive names for each simulation group: -plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) -#> $all_situations +``` r +plots <- plot( + original = sim, + "New version" = sim2, + obs = obs +) +# Only displaying the first situation for this one: +plots[[1]] ``` - + -#### 2.1.3 Group comparison +### Scatter Plot Comparison -We can compare groups of simulations alongside by simply adding the -simulations objects one after the other (that is why the first argument -of the function is `...`). Group simulations can be the results of -simulations from different model versions, or simulations with different -parameter values. +Model versions can also be compared using scatter plots: ``` r -workspace2 <- system.file( - file.path("extdata", "stics_example_2"), - package = "CroPlotR" +plots <- plot( + original = sim, + "New version" = sim2, + obs = obs, + type = "scatter", + all_situations = FALSE ) +# Only displaying the first situation for this one: +plots[[1]] +``` -sim2 <- SticsRFiles::get_sim( - workspace = workspace2, - usms_file = file.path(workspace2, "usms.xml") -) -#> mod_spIC_Wheat_Pea_2005-2006_N0.stimod_saIC_Wheat_Pea_2005-2006_N0.sti + -plot(sim, sim2, obs = obs, all_situations = FALSE) -#> $`IC_Wheat_Pea_2005-2006_N0` +## 6. Error Bars + +Add uncertainty estimates to observations using the `obs_sd` parameter, +which must have the same structure as `obs`. Error bars are then +displayed as ±2 standard deviations, corresponding to an approximate 95% +confidence interval under the assumption of Gaussian observation errors. + +``` r +plot(sim, obs = obs, obs_sd = obs_sd, type = "scatter", all_situations = TRUE) +#> $all_situations ``` - + -Here only one plot is outputted because `workspace2` only contains the -intercrop situation. +## 7. Intercrops -We can also name the corresponding group in the plot by naming them -while passing to the `plot()` function: +CroPlotR automatically handles simulations of intercrop situations where +multiple plant species are grown together. + +### Dynamic Plots for Intercrops ``` r -plot( - "New version" = sim, - original = sim2, - obs = obs, - type = "scatter", - all_situations = FALSE -) +plot(sim_intercrop, obs = obs_intercrop) #> $`IC_Wheat_Pea_2005-2006_N0` ``` - + + +### Scatter Plots for Intercrops + +``` r +plot(sim_intercrop, obs = obs_intercrop, type = "scatter", all_situations = TRUE) +#> $all_situations +``` + + + +## 8. Saving Plots -#### 2.1.4 Plot saving +### Save as PNG -The plots can be saved to disk using the `save_plot_png()` function as -follows: +Export individual plots as PNG files using `save_plot_png()`: ``` r plots <- plot("New version" = sim, original = sim2, obs = obs, type = "scatter") @@ -480,10 +480,10 @@ plots <- plot( save_plot_png(., out_dir = "path/to/directory", suffix = "_scatter") ``` -They can also be saved using the `save_plot_pdf()` function that which, -from a list of ggplots, generates a pdf file. If the `file_per_var` -parameter is TRUE, in this case the function generates one pdf file per -variable. +### Save as PDF + +Export plots to PDF using `save_plot_pdf()`. Set `file_per_var = TRUE` +to create separate PDFs for each variable: ``` r plots <- plot(sim, obs = obs) @@ -491,114 +491,132 @@ plots <- plot(sim, obs = obs) save_plot_pdf(plot = plots, out_dir = "path/to/directory", file_per_var = FALSE) ``` -#### 2.1.5 Plot extracting +## 9. Extracting Individual Plots + +The `plot()` function returns a named list of ggplot objects, where +names correspond to situations: + +``` r +p <- plot(sim) + +names(p) +#> [1] "SC_Pea_2005-2006_N0" "SC_Wheat_2005-2006_N0" +``` + +### Access by Name + +Access individual plots using their situation name (use backticks if the +name contains special characters): + +``` r +p$`SC_Wheat_2005-2006_N0` +``` + + + +### Access by Index + +Alternatively, use numeric indexing: + +``` r +p[[1]] +``` + +### Filtering Plots -When we have plots with several variables and several situations, the -`extract_plot` function allows to keep the situations and variables that -we need. +Use `extract_plot()` to filter plots by situation and/or variable. This +is useful when working with many situations and variables. -In the following example, we want to extract the intercrop situation and -the “masec_n” variable. +Example: Extract only the wheat situation and the `masec_n` variable: ``` r plots <- plot(sim, obs = obs, type = "scatter", all_situations = FALSE) extract_plot( plots, - situation = c("IC_Wheat_Pea_2005-2006_N0"), var = c("masec_n") + situation = c("SC_Wheat_2005-2006_N0"), var = c("masec_n") ) -#> $`IC_Wheat_Pea_2005-2006_N0` +#> $`SC_Wheat_2005-2006_N0` ``` - + -### 2.2 Statistics +## 10. Statistics -#### 2.2.1 Simple case +Compute performance metrics to quantitatively compare simulated and +observed values. -Here is an application of summary statistics for the 3 situations: +### 10.1. Basic Usage + +Calculate statistics for each situation individually: ``` r summary(sim, obs = obs, all_situations = FALSE) ``` - #> Attention: some observed values are zero. They are filtered for the computation of MAPE - #> Attention: some observed values are zero. They are filtered for the computation of RME - | group | situation | variable | n_obs | mean_obs | mean_sim | r_means | sd_obs | sd_sim | CV_obs | CV_sim | R2 | SS_res | Inter | Slope | RMSE | RMSEs | RMSEu | nRMSE | rRMSE | rRMSEs | rRMSEu | pMSEs | pMSEu | Bias2 | SDSD | LCS | rbias2 | rSDSD | rLCS | MAE | FVU | MSE | EF | Bias | ABS | MAPE | RME | tSTUD | tLimit | Decision | |:---|:---|:---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|:---| -| Version_1 | IC_Wheat_Pea_2005-2006_N0 | lai_n | 8 | 0.762500 | 0.6135987 | 80.47197 | 0.6326306 | 0.5508654 | 82.96794 | 89.77616 | 0.8082574 | 0.7167893 | 0.0166871 | 0.7828349 | 0.2993304 | 0.1966900 | 0.2256362 | 39.25644 | 0.3925644 | 0.2579541 | 0.2959163 | 0.4317805 | 0.5682195 | 0.0221716 | 0.0066855 | 0.0703740 | 0.0381344 | 0.0114989 | 0.1210410 | 0.2323863 | 0.1925422 | 0.0895987 | 0.7441455 | -0.1489013 | 0.2323863 | 0.3156233 | -0.2466048 | -1.5171559 | 2.364624 | OK | -| Version_1 | IC_Wheat_Pea_2005-2006_N0 | masec_n | 10 | 3.450000 | 3.2975700 | 95.58174 | 1.9615810 | 2.1296432 | 56.85742 | 64.58220 | 0.9631080 | 1.8866224 | -0.3782750 | 1.0654623 | 0.4343527 | 0.1951283 | 0.3880557 | 12.58993 | 0.1258993 | 0.0565589 | 0.1124799 | 0.2018159 | 0.7981841 | 0.0232349 | 0.0282449 | 0.1555633 | 0.0019521 | 0.0023730 | 0.0130698 | 0.3477720 | 0.0477697 | 0.1886622 | 0.9455209 | -0.1524300 | 0.3477720 | 0.1927375 | -0.1469491 | -1.1243151 | 2.262157 | OK | -| Version_1 | SC_Pea_2005-2006_N0 | lai_n | 3 | 2.622222 | 1.7386367 | 66.30394 | 1.5135732 | 1.3463799 | 57.72101 | 77.43883 | 0.6945994 | 3.7558828 | -0.2053841 | 0.7413638 | 1.1189106 | 0.9396204 | 0.6075149 | 42.67032 | 0.4267032 | 0.3583298 | 0.2316794 | 0.7052029 | 0.2947971 | 0.7807234 | 0.0279536 | 0.6789027 | 0.1135424 | 0.0040654 | 0.0987344 | 0.8835856 | 0.3085491 | 1.2519609 | 0.1802618 | -0.8835856 | 0.8835856 | 0.3901011 | -0.3901011 | -1.8203030 | 4.302653 | OK | -| Version_1 | SC_Pea_2005-2006_N0 | masec_n | 4 | 5.451667 | 4.3825425 | 80.38904 | 3.7848396 | 3.7494028 | 69.42537 | 85.55314 | 0.8907017 | 9.3636018 | -0.7144037 | 0.9349336 | 1.5300001 | 1.0901888 | 1.0734937 | 28.06481 | 0.2806481 | 0.1999735 | 0.1969111 | 0.5077156 | 0.4922844 | 1.1430265 | 0.0012558 | 1.5959095 | 0.0384590 | 0.0000423 | 0.0536970 | 1.1660625 | 0.1114949 | 2.3409005 | 0.7821153 | -1.0691242 | 1.1660625 | 0.3308096 | -0.3198354 | -1.6919332 | 3.182446 | OK | -| Version_1 | SC_Wheat_2005-2006_N0 | lai_n | 3 | 1.273333 | 1.4022867 | 110.12723 | 0.4396684 | 0.6236645 | 34.52893 | 44.47482 | 0.0098002 | 1.1058377 | 1.2234797 | 0.1404243 | 0.6071347 | 0.3344381 | 0.5067186 | 47.68074 | 0.4768074 | 0.2626477 | 0.3979465 | 0.3034319 | 0.6965681 | 0.0166290 | 0.0338546 | 0.4941208 | 0.0102561 | 0.0208801 | 0.3047537 | 0.5115933 | 2.7312604 | 0.3686126 | -1.8602948 | 0.1289533 | 0.5115933 | 0.4881989 | 0.1825306 | 0.3073876 | 4.302653 | OK | -| Version_1 | SC_Wheat_2005-2006_N0 | masec_n | 4 | 5.393750 | 6.0159025 | 111.53469 | 3.1594630 | 3.9552603 | 58.57637 | 65.74675 | 0.9637756 | 4.8187352 | -0.6129841 | 1.2289940 | 1.0975809 | 0.8829841 | 0.6519378 | 20.34912 | 0.2034912 | 0.1637050 | 0.1208691 | 0.6471914 | 0.3528086 | 0.3870737 | 0.6332935 | 0.4568533 | 0.0133049 | 0.0217682 | 0.0157035 | 0.6221525 | 0.1092090 | 1.2046838 | 0.8390892 | 0.6221525 | 0.6221525 | 0.0866369 | 0.0866369 | 1.1917478 | 3.182446 | OK | +| Version_1 | SC_Pea_2005-2006_N0 | lai_n | 3 | 2.622222 | 1.738637 | 66.30394 | 1.5135732 | 1.3463799 | 57.72101 | 77.43883 | 0.6945994 | 3.7558828 | -0.2053841 | 0.7413638 | 1.1189106 | 0.9396204 | 0.6075149 | 42.670319 | 0.4267032 | 0.3583298 | 0.2316794 | 0.7052029 | 0.2947971 | 0.7807234 | 0.0279536 | 0.6789027 | 0.1135424 | 0.0040654 | 0.0987344 | 0.8835856 | 0.3085491 | 1.2519609 | 0.1802618 | -0.8835856 | 0.8835856 | 0.3901011 | -0.3901011 | -1.8203030 | 4.302653 | OK | +| Version_1 | SC_Pea_2005-2006_N0 | mafruit | 1 | 4.355000 | 4.742713 | 108.90270 | NA | NA | NA | NA | 0.0000000 | 0.1503211 | 4.7427127 | NA | 0.3877127 | 0.3877127 | 0.0000000 | 8.902703 | 0.0890270 | 0.0890270 | 0.0000000 | 1.0000000 | 0.0000000 | 0.1503211 | NA | NA | 0.0079258 | NA | NA | 0.3877127 | NA | 0.1503211 | -Inf | 0.3877127 | 0.3877127 | 0.0890270 | 0.0890270 | NA | NaN | Insufficient size | +| Version_1 | SC_Pea_2005-2006_N0 | masec_n | 4 | 5.451667 | 4.382542 | 80.38904 | 3.7848396 | 3.7494028 | 69.42537 | 85.55314 | 0.8907017 | 9.3636018 | -0.7144037 | 0.9349336 | 1.5300001 | 1.0901888 | 1.0734937 | 28.064815 | 0.2806481 | 0.1999735 | 0.1969111 | 0.5077156 | 0.4922844 | 1.1430265 | 0.0012558 | 1.5959095 | 0.0384590 | 0.0000423 | 0.0536970 | 1.1660625 | 0.1114949 | 2.3409005 | 0.7821153 | -1.0691242 | 1.1660625 | 0.3308096 | -0.3198354 | -1.6919332 | 3.182446 | OK | +| Version_1 | SC_Wheat_2005-2006_N0 | lai_n | 3 | 1.273333 | 1.402287 | 110.12723 | 0.4396684 | 0.6236645 | 34.52893 | 44.47482 | 0.0098002 | 1.1058377 | 1.2234797 | 0.1404243 | 0.6071347 | 0.3344381 | 0.5067186 | 47.680736 | 0.4768074 | 0.2626477 | 0.3979465 | 0.3034319 | 0.6965681 | 0.0166290 | 0.0338546 | 0.4941208 | 0.0102561 | 0.0208801 | 0.3047537 | 0.5115933 | 2.7312604 | 0.3686126 | -1.8602948 | 0.1289533 | 0.5115933 | 0.4881989 | 0.1825306 | 0.3073876 | 4.302653 | OK | +| Version_1 | SC_Wheat_2005-2006_N0 | mafruit | 1 | 3.825000 | 5.675395 | 148.37634 | NA | NA | NA | NA | 0.0000000 | 3.4239617 | 5.6753950 | NA | 1.8503950 | 1.8503950 | 0.0000000 | 48.376340 | 0.4837634 | 0.4837634 | 0.0000000 | 1.0000000 | 0.0000000 | 3.4239617 | NA | NA | 0.2340270 | NA | NA | 1.8503950 | NA | 3.4239617 | -Inf | 1.8503950 | 1.8503950 | 0.4837634 | 0.4837634 | NA | NaN | Insufficient size | +| Version_1 | SC_Wheat_2005-2006_N0 | masec_n | 4 | 5.393750 | 6.015903 | 111.53469 | 3.1594630 | 3.9552603 | 58.57637 | 65.74675 | 0.9637756 | 4.8187352 | -0.6129841 | 1.2289940 | 1.0975809 | 0.8829841 | 0.6519378 | 20.349124 | 0.2034912 | 0.1637050 | 0.1208691 | 0.6471914 | 0.3528086 | 0.3870737 | 0.6332935 | 0.4568533 | 0.0133049 | 0.0217682 | 0.0157035 | 0.6221525 | 0.1092090 | 1.2046838 | 0.8390892 | 0.6221525 | 0.6221525 | 0.0866369 | 0.0866369 | 1.1917478 | 3.182446 | OK | + +> **Note:** The `obs` argument must be explicitly named (same reason as +> for `plot()`). -Note that as for the `plot()` function the `obs` argument is explicitly -named. This is because the first argument of the function is `...` to be -able to compare groups (i.e. model versions or simulation with different -parameter values). In this example, a message warns the user because -some observed values have a zero value which causes a division by zero -in the calculation of certain statistical criteria, these values are -therefore filtered for the calculation of these criteria. +### Aggregated Statistics -And as for the `plot()` function again, it is possible to compute the -statistical criteria for all situations at once. +Compute statistics across all situations simultaneously: ``` r summary(sim, obs = obs, all_situations = TRUE) ``` - #> Attention: some observed values are zero. They are filtered for the computation of MAPE - #> Attention: some observed values are zero. They are filtered for the computation of RME - | group | situation | variable | n_obs | mean_obs | mean_sim | r_means | sd_obs | sd_sim | CV_obs | CV_sim | R2 | SS_res | Inter | Slope | RMSE | RMSEs | RMSEu | nRMSE | rRMSE | rRMSEs | rRMSEu | pMSEs | pMSEu | Bias2 | SDSD | LCS | rbias2 | rSDSD | rLCS | MAE | FVU | MSE | EF | Bias | ABS | MAPE | RME | tSTUD | tLimit | Decision | |:---|:---|:---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|:---| -| Version_1 | all_situations | lai_n | 14 | 1.270476 | 1.023683 | 80.57474 | 1.085427 | 0.8698547 | 85.43465 | 84.97306 | 0.6923882 | 5.57851 | 0.1764799 | 0.6668389 | 0.6312408 | 0.4270089 | 0.4648960 | 49.68537 | 0.4968537 | 0.3361015 | 0.3659227 | 0.4575977 | 0.5424023 | 0.0609069 | 0.0464714 | 0.3170527 | 0.0377341 | 0.0287907 | 0.1964257 | 0.4317590 | 0.3085546 | 0.398465 | 0.6357717 | -0.2467933 | 0.4317590 | 0.3773867 | -0.1751950 | -1.5315489 | 2.160369 | OK | -| Version_1 | all_situations | masec_n | 18 | 4.326759 | 4.142749 | 95.74715 | 2.710052 | 2.9836105 | 62.63468 | 72.02007 | 0.8994510 | 16.06896 | -0.3749370 | 1.0441269 | 0.9448386 | 0.2176378 | 0.9194312 | 21.83710 | 0.2183710 | 0.0503004 | 0.2124988 | 0.0530583 | 0.9469417 | 0.0338598 | 0.0748344 | 0.8345469 | 0.0018087 | 0.0039974 | 0.0445785 | 0.5905878 | 0.1238200 | 0.892720 | 0.8712985 | -0.1840104 | 0.5905878 | 0.1998423 | -0.1334603 | -0.8186637 | 2.109816 | OK | +| Version_1 | all_situations | lai_n | 6 | 1.947778 | 1.570462 | 80.62838 | 1.2407801 | 0.9563566 | 63.702343 | 60.89653 | 0.4849226 | 4.861720 | 0.5250179 | 0.5367367 | 0.9001593 | 0.6463004 | 0.6265641 | 46.21468 | 0.4621468 | 0.3318142 | 0.3216815 | 0.5155017 | 0.4844983 | 0.1423674 | 0.0808967 | 0.7206064 | 0.0375260 | 0.0213232 | 0.1899413 | 0.6975894 | 0.5206137 | 0.8102867 | 0.3684171 | -0.3773161 | 0.6975894 | 0.4391500 | -0.1037853 | -1.0323533 | 2.570582 | OK | +| Version_1 | all_situations | mafruit | 2 | 4.090000 | 5.209054 | 127.36073 | 0.3747666 | 0.6595060 | 9.162997 | 12.66076 | 1.0000000 | 3.574283 | 12.4065456 | -1.7597779 | 1.3368401 | 1.3368401 | 0.0000000 | 32.68558 | 0.3268558 | 0.3268558 | 0.0000000 | 1.0000000 | 0.0000000 | 1.2522815 | 0.0810765 | 0.9886432 | 0.0748610 | 0.0048467 | 0.0591007 | 1.1190538 | 7.6163742 | 1.7871414 | -24.4487917 | 1.1190538 | 1.1190538 | 0.2863952 | 0.2863952 | 1.5301393 | 12.706205 | OK | +| Version_1 | all_situations | masec_n | 8 | 5.422708 | 5.199223 | 95.87870 | 3.2277449 | 3.6731078 | 59.522746 | 70.64725 | 0.8562305 | 14.182337 | -0.5109084 | 1.0530035 | 1.3314624 | 0.2748750 | 1.3027800 | 24.55346 | 0.2455346 | 0.0506896 | 0.2402453 | 0.0426199 | 0.9573801 | 0.0499459 | 0.1983481 | 1.7706190 | 0.0016985 | 0.0067452 | 0.0602133 | 0.8941075 | 0.1889905 | 1.7727921 | 0.8055306 | -0.2234858 | 0.8941075 | 0.2087232 | -0.1165992 | -0.4504803 | 2.364624 | OK | -#### 2.2.2 Several groups +### 10.2. Comparing Multiple Groups -We can get statistics for each group of simulations by simply adding the -simulations objects one after the other (as for the `plot()` function). +Compute statistics for multiple simulation groups (e.g., different model +versions or parameter sets): ``` r summary(sim, sim2, obs = obs) ``` - #> Attention: some observed values are zero. They are filtered for the computation of MAPE - #> Attention: some observed values are zero. They are filtered for the computation of RME - #> Attention: some observed values are zero. They are filtered for the computation of MAPE - #> Attention: some observed values are zero. They are filtered for the computation of RME - | group | situation | variable | n_obs | mean_obs | mean_sim | r_means | sd_obs | sd_sim | CV_obs | CV_sim | R2 | SS_res | Inter | Slope | RMSE | RMSEs | RMSEu | nRMSE | rRMSE | rRMSEs | rRMSEu | pMSEs | pMSEu | Bias2 | SDSD | LCS | rbias2 | rSDSD | rLCS | MAE | FVU | MSE | EF | Bias | ABS | MAPE | RME | tSTUD | tLimit | Decision | |:---|:---|:---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|:---| -| Version_1 | all_situations | lai_n | 14 | 1.270476 | 1.0236829 | 80.57474 | 1.0854269 | 0.8698547 | 85.43465 | 84.97306 | 0.6923882 | 5.578510 | 0.1764799 | 0.6668389 | 0.6312408 | 0.4270089 | 0.4648960 | 49.68537 | 0.4968537 | 0.3361015 | 0.3659227 | 0.4575977 | 0.5424023 | 0.0609069 | 0.0464714 | 0.3170527 | 0.0377341 | 0.0287907 | 0.1964257 | 0.4317590 | 0.3085546 | 0.3984650 | 0.6357717 | -0.2467933 | 0.4317590 | 0.3773867 | -0.1751950 | -1.5315489 | 2.160369 | OK | -| Version_1 | all_situations | masec_n | 18 | 4.326759 | 4.1427489 | 95.74715 | 2.7100517 | 2.9836105 | 62.63468 | 72.02007 | 0.8994510 | 16.068959 | -0.3749370 | 1.0441269 | 0.9448386 | 0.2176378 | 0.9194312 | 21.83710 | 0.2183710 | 0.0503004 | 0.2124988 | 0.0530583 | 0.9469417 | 0.0338598 | 0.0748344 | 0.8345469 | 0.0018087 | 0.0039974 | 0.0445785 | 0.5905878 | 0.1238200 | 0.8927200 | 0.8712985 | -0.1840104 | 0.5905878 | 0.1998423 | -0.1334603 | -0.8186637 | 2.109816 | OK | -| Version_2 | all_situations | lai_n | 8 | 0.762500 | 0.5993112 | 78.59820 | 0.6326306 | 0.4383225 | 82.96794 | 73.13770 | 0.1192180 | 3.019054 | 0.4168988 | 0.2392294 | 0.6143141 | 0.4788662 | 0.3847972 | 80.56578 | 0.8056578 | 0.6280213 | 0.5046521 | 0.6076416 | 0.3923584 | 0.0266306 | 0.0377556 | 0.3631029 | 0.0458037 | 0.0649385 | 0.6245253 | 0.5046413 | 1.0015919 | 0.3773818 | -0.0776372 | -0.1631888 | 0.5046413 | 0.5726006 | -0.2460595 | -0.7290203 | 2.364624 | OK | -| Version_2 | all_situations | masec_n | 10 | 3.450000 | 3.3168750 | 96.14130 | 1.9615810 | 3.2725657 | 56.85742 | 98.66412 | 0.6237332 | 39.937521 | -1.2288238 | 1.3175938 | 1.9984374 | 0.6058240 | 1.9043974 | 57.92572 | 0.5792572 | 0.1756012 | 0.5519992 | 0.0918992 | 0.9081008 | 0.0177223 | 1.7186808 | 2.6991301 | 0.0014890 | 0.1443966 | 0.2267700 | 1.7338590 | 1.1481394 | 3.9937521 | -0.1532570 | -0.1331250 | 1.7338590 | 0.5148451 | -0.1538282 | -0.2002885 | 2.262157 | OK | +| Version_1 | all_situations | lai_n | 6 | 1.947778 | 1.570462 | 80.62838 | 1.2407801 | 0.9563566 | 63.702343 | 60.89653 | 0.4849226 | 4.861720 | 0.5250179 | 0.5367367 | 0.9001593 | 0.6463004 | 0.6265641 | 46.21468 | 0.4621468 | 0.3318142 | 0.3216815 | 0.5155017 | 0.4844983 | 0.1423674 | 0.0808967 | 0.7206064 | 0.0375260 | 0.0213232 | 0.1899413 | 0.6975894 | 0.5206137 | 0.8102867 | 0.3684171 | -0.3773161 | 0.6975894 | 0.4391500 | -0.1037853 | -1.0323533 | 2.570582 | OK | +| Version_1 | all_situations | mafruit | 2 | 4.090000 | 5.209054 | 127.36073 | 0.3747666 | 0.6595060 | 9.162997 | 12.66076 | 1.0000000 | 3.574283 | 12.4065456 | -1.7597779 | 1.3368401 | 1.3368401 | 0.0000000 | 32.68558 | 0.3268558 | 0.3268558 | 0.0000000 | 1.0000000 | 0.0000000 | 1.2522815 | 0.0810765 | 0.9886432 | 0.0748610 | 0.0048467 | 0.0591007 | 1.1190538 | 7.6163742 | 1.7871414 | -24.4487917 | 1.1190538 | 1.1190538 | 0.2863952 | 0.2863952 | 1.5301393 | 12.706205 | OK | +| Version_1 | all_situations | masec_n | 8 | 5.422708 | 5.199223 | 95.87870 | 3.2277449 | 3.6731078 | 59.522746 | 70.64725 | 0.8562305 | 14.182337 | -0.5109084 | 1.0530035 | 1.3314624 | 0.2748750 | 1.3027800 | 24.55346 | 0.2455346 | 0.0506896 | 0.2402453 | 0.0426199 | 0.9573801 | 0.0499459 | 0.1983481 | 1.7706190 | 0.0016985 | 0.0067452 | 0.0602133 | 0.8941075 | 0.1889905 | 1.7727921 | 0.8055306 | -0.2234858 | 0.8941075 | 0.2087232 | -0.1165992 | -0.4504803 | 2.364624 | OK | +| Version_2 | all_situations | lai_n | 6 | 1.947778 | 1.727508 | 88.69122 | 1.2407801 | 1.0519922 | 63.702343 | 60.89653 | 0.4849226 | 4.432653 | 0.5775197 | 0.5904103 | 0.8595205 | 0.5135666 | 0.6892205 | 44.12826 | 0.4412826 | 0.2636679 | 0.3538496 | 0.3570105 | 0.6429895 | 0.0485188 | 0.0356408 | 0.7926671 | 0.0127889 | 0.0093944 | 0.2089354 | 0.6060845 | 0.5380247 | 0.7387754 | 0.4241570 | -0.2202699 | 0.6060845 | 0.4168965 | -0.0141638 | -0.5928365 | 2.570582 | OK | +| Version_2 | all_situations | mafruit | 2 | 4.090000 | 5.729959 | 140.09680 | 0.3747666 | 0.7254566 | 9.162997 | 12.66076 | 1.0000000 | 6.589424 | 13.6472001 | -1.9357557 | 1.8151341 | 1.8151341 | 0.0000000 | 44.37981 | 0.4437981 | 0.4437981 | 0.0000000 | 1.0000000 | 0.0000000 | 2.6894663 | 0.1229835 | 1.0875076 | 0.1607754 | 0.0073519 | 0.0650108 | 1.6399592 | 8.6186616 | 3.2947118 | -45.9165084 | 1.6399592 | 1.6399592 | 0.4150347 | 0.4150347 | 2.1079838 | 12.706205 | OK | +| Version_2 | all_situations | masec_n | 8 | 5.422708 | 5.719145 | 105.46658 | 3.2277449 | 4.0404186 | 59.522746 | 70.64725 | 0.8562305 | 18.959832 | -0.5619992 | 1.1583039 | 1.5394736 | 0.5624266 | 1.4330581 | 28.38939 | 0.2838939 | 0.1037169 | 0.2642698 | 0.1334711 | 0.8665289 | 0.0878745 | 0.6604385 | 1.9476809 | 0.0029883 | 0.0224595 | 0.0662347 | 1.2014558 | 0.2503393 | 2.3699790 | 0.7400211 | 0.2964364 | 1.2014558 | 0.2545956 | -0.0282592 | 0.5191739 | 2.364624 | OK | -We can also name the corresponding group in the plot by naming them -while passing to the `summary()` function: +Provide descriptive names for clarity: ``` r summary("New version" = sim, original = sim2, obs = obs) ``` - #> Attention: some observed values are zero. They are filtered for the computation of MAPE - #> Attention: some observed values are zero. They are filtered for the computation of RME - #> Attention: some observed values are zero. They are filtered for the computation of MAPE - #> Attention: some observed values are zero. They are filtered for the computation of RME - | group | situation | variable | n_obs | mean_obs | mean_sim | r_means | sd_obs | sd_sim | CV_obs | CV_sim | R2 | SS_res | Inter | Slope | RMSE | RMSEs | RMSEu | nRMSE | rRMSE | rRMSEs | rRMSEu | pMSEs | pMSEu | Bias2 | SDSD | LCS | rbias2 | rSDSD | rLCS | MAE | FVU | MSE | EF | Bias | ABS | MAPE | RME | tSTUD | tLimit | Decision | |:---|:---|:---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|:---| -| New version | all_situations | lai_n | 14 | 1.270476 | 1.0236829 | 80.57474 | 1.0854269 | 0.8698547 | 85.43465 | 84.97306 | 0.6923882 | 5.578510 | 0.1764799 | 0.6668389 | 0.6312408 | 0.4270089 | 0.4648960 | 49.68537 | 0.4968537 | 0.3361015 | 0.3659227 | 0.4575977 | 0.5424023 | 0.0609069 | 0.0464714 | 0.3170527 | 0.0377341 | 0.0287907 | 0.1964257 | 0.4317590 | 0.3085546 | 0.3984650 | 0.6357717 | -0.2467933 | 0.4317590 | 0.3773867 | -0.1751950 | -1.5315489 | 2.160369 | OK | -| New version | all_situations | masec_n | 18 | 4.326759 | 4.1427489 | 95.74715 | 2.7100517 | 2.9836105 | 62.63468 | 72.02007 | 0.8994510 | 16.068959 | -0.3749370 | 1.0441269 | 0.9448386 | 0.2176378 | 0.9194312 | 21.83710 | 0.2183710 | 0.0503004 | 0.2124988 | 0.0530583 | 0.9469417 | 0.0338598 | 0.0748344 | 0.8345469 | 0.0018087 | 0.0039974 | 0.0445785 | 0.5905878 | 0.1238200 | 0.8927200 | 0.8712985 | -0.1840104 | 0.5905878 | 0.1998423 | -0.1334603 | -0.8186637 | 2.109816 | OK | -| original | all_situations | lai_n | 8 | 0.762500 | 0.5993112 | 78.59820 | 0.6326306 | 0.4383225 | 82.96794 | 73.13770 | 0.1192180 | 3.019054 | 0.4168988 | 0.2392294 | 0.6143141 | 0.4788662 | 0.3847972 | 80.56578 | 0.8056578 | 0.6280213 | 0.5046521 | 0.6076416 | 0.3923584 | 0.0266306 | 0.0377556 | 0.3631029 | 0.0458037 | 0.0649385 | 0.6245253 | 0.5046413 | 1.0015919 | 0.3773818 | -0.0776372 | -0.1631888 | 0.5046413 | 0.5726006 | -0.2460595 | -0.7290203 | 2.364624 | OK | -| original | all_situations | masec_n | 10 | 3.450000 | 3.3168750 | 96.14130 | 1.9615810 | 3.2725657 | 56.85742 | 98.66412 | 0.6237332 | 39.937521 | -1.2288238 | 1.3175938 | 1.9984374 | 0.6058240 | 1.9043974 | 57.92572 | 0.5792572 | 0.1756012 | 0.5519992 | 0.0918992 | 0.9081008 | 0.0177223 | 1.7186808 | 2.6991301 | 0.0014890 | 0.1443966 | 0.2267700 | 1.7338590 | 1.1481394 | 3.9937521 | -0.1532570 | -0.1331250 | 1.7338590 | 0.5148451 | -0.1538282 | -0.2002885 | 2.262157 | OK | +| New version | all_situations | lai_n | 6 | 1.947778 | 1.570462 | 80.62838 | 1.2407801 | 0.9563566 | 63.702343 | 60.89653 | 0.4849226 | 4.861720 | 0.5250179 | 0.5367367 | 0.9001593 | 0.6463004 | 0.6265641 | 46.21468 | 0.4621468 | 0.3318142 | 0.3216815 | 0.5155017 | 0.4844983 | 0.1423674 | 0.0808967 | 0.7206064 | 0.0375260 | 0.0213232 | 0.1899413 | 0.6975894 | 0.5206137 | 0.8102867 | 0.3684171 | -0.3773161 | 0.6975894 | 0.4391500 | -0.1037853 | -1.0323533 | 2.570582 | OK | +| New version | all_situations | mafruit | 2 | 4.090000 | 5.209054 | 127.36073 | 0.3747666 | 0.6595060 | 9.162997 | 12.66076 | 1.0000000 | 3.574283 | 12.4065456 | -1.7597779 | 1.3368401 | 1.3368401 | 0.0000000 | 32.68558 | 0.3268558 | 0.3268558 | 0.0000000 | 1.0000000 | 0.0000000 | 1.2522815 | 0.0810765 | 0.9886432 | 0.0748610 | 0.0048467 | 0.0591007 | 1.1190538 | 7.6163742 | 1.7871414 | -24.4487917 | 1.1190538 | 1.1190538 | 0.2863952 | 0.2863952 | 1.5301393 | 12.706205 | OK | +| New version | all_situations | masec_n | 8 | 5.422708 | 5.199223 | 95.87870 | 3.2277449 | 3.6731078 | 59.522746 | 70.64725 | 0.8562305 | 14.182337 | -0.5109084 | 1.0530035 | 1.3314624 | 0.2748750 | 1.3027800 | 24.55346 | 0.2455346 | 0.0506896 | 0.2402453 | 0.0426199 | 0.9573801 | 0.0499459 | 0.1983481 | 1.7706190 | 0.0016985 | 0.0067452 | 0.0602133 | 0.8941075 | 0.1889905 | 1.7727921 | 0.8055306 | -0.2234858 | 0.8941075 | 0.2087232 | -0.1165992 | -0.4504803 | 2.364624 | OK | +| original | all_situations | lai_n | 6 | 1.947778 | 1.727508 | 88.69122 | 1.2407801 | 1.0519922 | 63.702343 | 60.89653 | 0.4849226 | 4.432653 | 0.5775197 | 0.5904103 | 0.8595205 | 0.5135666 | 0.6892205 | 44.12826 | 0.4412826 | 0.2636679 | 0.3538496 | 0.3570105 | 0.6429895 | 0.0485188 | 0.0356408 | 0.7926671 | 0.0127889 | 0.0093944 | 0.2089354 | 0.6060845 | 0.5380247 | 0.7387754 | 0.4241570 | -0.2202699 | 0.6060845 | 0.4168965 | -0.0141638 | -0.5928365 | 2.570582 | OK | +| original | all_situations | mafruit | 2 | 4.090000 | 5.729959 | 140.09680 | 0.3747666 | 0.7254566 | 9.162997 | 12.66076 | 1.0000000 | 6.589424 | 13.6472001 | -1.9357557 | 1.8151341 | 1.8151341 | 0.0000000 | 44.37981 | 0.4437981 | 0.4437981 | 0.0000000 | 1.0000000 | 0.0000000 | 2.6894663 | 0.1229835 | 1.0875076 | 0.1607754 | 0.0073519 | 0.0650108 | 1.6399592 | 8.6186616 | 3.2947118 | -45.9165084 | 1.6399592 | 1.6399592 | 0.4150347 | 0.4150347 | 2.1079838 | 12.706205 | OK | +| original | all_situations | masec_n | 8 | 5.422708 | 5.719145 | 105.46658 | 3.2277449 | 4.0404186 | 59.522746 | 70.64725 | 0.8562305 | 18.959832 | -0.5619992 | 1.1583039 | 1.5394736 | 0.5624266 | 1.4330581 | 28.38939 | 0.2838939 | 0.1037169 | 0.2642698 | 0.1334711 | 0.8665289 | 0.0878745 | 0.6604385 | 1.9476809 | 0.0029883 | 0.0224595 | 0.0662347 | 1.2014558 | 0.2503393 | 2.3699790 | 0.7400211 | 0.2964364 | 1.2014558 | 0.2545956 | -0.0282592 | 0.5191739 | 2.364624 | OK | + +### Selecting Specific Statistics -By default, all statistics are returned by `summary`, but you can filter -them using the `stat` argument: +By default, all available statistics are computed. Use the `stats` +argument to select specific metrics: ``` r summary( @@ -609,23 +627,23 @@ summary( | group | situation | variable | R2 | nRMSE | |:------------|:---------------|:---------|----------:|---------:| -| New version | all_situations | lai_n | 0.6923882 | 49.68537 | -| New version | all_situations | masec_n | 0.8994510 | 21.83710 | -| original | all_situations | lai_n | 0.1192180 | 80.56578 | -| original | all_situations | masec_n | 0.6237332 | 57.92572 | - -Please read the help from -[`summary.cropr_simulation()`](https://sticsrpacks.github.io/CroPlotR/reference/summary.cropr_simulation.html) -and +| New version | all_situations | lai_n | 0.4849226 | 46.21468 | +| New version | all_situations | mafruit | 1.0000000 | 32.68558 | +| New version | all_situations | masec_n | 0.8562305 | 24.55346 | +| original | all_situations | lai_n | 0.4849226 | 44.12826 | +| original | all_situations | mafruit | 1.0000000 | 44.37981 | +| original | all_situations | masec_n | 0.8562305 | 28.38939 | + +For more details about the list of available statistical criterion and +their definition, please read the help from [`predictor_assessment()`](https://sticsrpacks.github.io/CroPlotR/reference/predictor_assessment.html). -#### 2.2.3 Statistics plot +### 10.3. Visualizing Statistics -It is also possible to plot the statistics: +Plot statistical metrics for visual comparison using `plot()` on the +summary output. -In a rather obvious way, the resulting graph will take into account all -the situations simultaneously or not according to the parameter given to -`summary`. Here is an example with `all_situations = FALSE`. +**Separate plots per situation** (`all_situations = FALSE`): ``` r stats <- summary( @@ -638,9 +656,9 @@ stats <- summary( plot(stats) ``` - + -And here is an example with `all_situations = TRUE`. +**Combined plot for all situations** (`all_situations = TRUE`): ``` r stats <- summary( @@ -654,10 +672,12 @@ stats <- summary( plot(stats) ``` - + + +### Customizing Plot Layout -We can choose to plot either the group or the situation in x (and the -other is used for grouping and colouring): +Control which variable appears on the x-axis using the `xvar` parameter. +The other variable is used for grouping and color coding: ``` r stats <- summary( @@ -671,10 +691,11 @@ stats <- summary( plot(stats, xvar = "situation", title = "Situation in X") ``` - + -In the previous examples, each line corresponds to a statistical -criterion. These can also be stacked. +### Bar Chart Layouts + +**Stacked bars** (`group_bar = "stack"`): ``` r stats <- summary( @@ -688,9 +709,9 @@ stats <- summary( plot(stats, xvar = "situation", title = "Stacked columns", group_bar = "stack") ``` - + -Or put side by side. +**Side-by-side bars** (`group_bar = "dodge"`): ``` r stats <- summary( @@ -709,30 +730,19 @@ plot( ) ``` - + -To compare different versions on a single criterion, the function -produces a radar graph like the following one. +### Radar Charts -``` r -sim$`SC_Pea_2005-2006_N0`$mafruit <- - (15 / 10) * sim$`SC_Pea_2005-2006_N0`$masec_n -sim$`SC_Wheat_2005-2006_N0`$mafruit <- - (15 / 20) * sim$`SC_Wheat_2005-2006_N0`$masec_n -sim2$`IC_Wheat_Pea_2005-2006_N0`$mafruit <- - sim2$`IC_Wheat_Pea_2005-2006_N0`$masec_n -obs$`IC_Wheat_Pea_2005-2006_N0`$mafruit <- - (12 / 10) * obs$`IC_Wheat_Pea_2005-2006_N0`$masec_n -obs$`SC_Pea_2005-2006_N0`$mafruit <- - (18 / 10) * obs$`SC_Pea_2005-2006_N0`$masec_n -obs$`SC_Wheat_2005-2006_N0`$mafruit <- - (15 / 12) * obs$`SC_Wheat_2005-2006_N0`$masec_n +Compare model versions across multiple variables using a radar chart +(`type = "radar"`) for a single metric: +``` r stats <- summary( "New version" = sim, original = sim2, obs = obs, - stats = c("R2", "nRMSE"), + stats = c("nRMSE"), all_situations = TRUE ) @@ -744,94 +754,91 @@ plot( ) ``` - + + +## 11. Data Manipulation -### 2.3 Data manipulation +### Working with Standard R Packages -Observation lists can easily be handled using e.g. +Observation data can be easily manipulated using packages like [dplyr](https://CRAN.R-project.org/package=dplyr), -[tidyr](https://CRAN.R-project.org/package=tidyr) or -[tibble](https://CRAN.R-project.org/package=tibble) packages. +[tidyr](https://CRAN.R-project.org/package=tidyr), or +[tibble](https://CRAN.R-project.org/package=tibble). + +However, the `cropr_simulation` attribute on simulated data can +interfere with some operations. CroPlotR provides two helper functions +to facilitate data manipulation: + +### Converting to Data Frame -The use of these packages on simulated data as returned by CroptimizR -model wrappers is sometimes prevented by their attribute -`cropr_simulation`. To easily manipulate simulated data we thus provide -two functions for (i) binding rows of data simulated on different -situations in a single data.frame or tibble and (ii) go back to the -original (cropr) format by splitting this single data.frame or tibble. +Use `bind_rows()` to combine all situations into a single data frame: ``` r df <- bind_rows(sim) head(df) -#> situation Date lai_n masec_n Plant Dominance mafruit -#> 1 IC_Wheat_Pea_2005-2006_N0 2005-09-26 0 0 ble Principal NA -#> 2 IC_Wheat_Pea_2005-2006_N0 2005-09-27 0 0 ble Principal NA -#> 3 IC_Wheat_Pea_2005-2006_N0 2005-09-28 0 0 ble Principal NA -#> 4 IC_Wheat_Pea_2005-2006_N0 2005-09-29 0 0 ble Principal NA -#> 5 IC_Wheat_Pea_2005-2006_N0 2005-09-30 0 0 ble Principal NA -#> 6 IC_Wheat_Pea_2005-2006_N0 2005-10-01 0 0 ble Principal NA +#> situation Date lai_n masec_n mafruit Plant +#> 1 SC_Pea_2005-2006_N0 2005-09-26 0 0 0 poi +#> 2 SC_Pea_2005-2006_N0 2005-09-27 0 0 0 poi +#> 3 SC_Pea_2005-2006_N0 2005-09-28 0 0 0 poi +#> 4 SC_Pea_2005-2006_N0 2005-09-29 0 0 0 poi +#> 5 SC_Pea_2005-2006_N0 2005-09-30 0 0 0 poi +#> 6 SC_Pea_2005-2006_N0 2005-10-01 0 0 0 poi ``` -The resulting data.frame/tibble can then easily be manipulated using -standard R packages. The column `situation` contains the name of the -corresponding situation (as given in the named list `sim`). +The `situation` column identifies the source situation for each row. +This format is compatible with standard data manipulation packages. -To go back to the original format of simulated data handled by CroPlotR, -use the `split_df2sim` function: +### Converting Back to CroPlotR Format + +After manipulation, use `split_df2sim()` to restore the original +`cropr_simulation` structure: ``` r sim_new <- split_df2sim(df) lapply(sim_new, head) -#> $`IC_Wheat_Pea_2005-2006_N0` -#> Date lai_n masec_n Plant Dominance -#> 1 2005-09-26 0 0 ble Principal -#> 2 2005-09-27 0 0 ble Principal -#> 3 2005-09-28 0 0 ble Principal -#> 4 2005-09-29 0 0 ble Principal -#> 5 2005-09-30 0 0 ble Principal -#> 6 2005-10-01 0 0 ble Principal -#> #> $`SC_Pea_2005-2006_N0` -#> Date lai_n masec_n Plant mafruit -#> 1 2005-09-26 0 0 poi 0 -#> 2 2005-09-27 0 0 poi 0 -#> 3 2005-09-28 0 0 poi 0 -#> 4 2005-09-29 0 0 poi 0 -#> 5 2005-09-30 0 0 poi 0 -#> 6 2005-10-01 0 0 poi 0 +#> Date lai_n masec_n mafruit Plant +#> 1 2005-09-26 0 0 0 poi +#> 2 2005-09-27 0 0 0 poi +#> 3 2005-09-28 0 0 0 poi +#> 4 2005-09-29 0 0 0 poi +#> 5 2005-09-30 0 0 0 poi +#> 6 2005-10-01 0 0 0 poi #> #> $`SC_Wheat_2005-2006_N0` -#> Date lai_n masec_n Plant mafruit -#> 1 2005-09-26 0 0 ble 0 -#> 2 2005-09-27 0 0 ble 0 -#> 3 2005-09-28 0 0 ble 0 -#> 4 2005-09-29 0 0 ble 0 -#> 5 2005-09-30 0 0 ble 0 -#> 6 2005-10-01 0 0 ble 0 +#> Date lai_n masec_n mafruit Plant +#> 1 2005-09-26 0 0 0 ble +#> 2 2005-09-27 0 0 0 ble +#> 3 2005-09-28 0 0 0 ble +#> 4 2005-09-29 0 0 0 ble +#> 5 2005-09-30 0 0 0 ble +#> 6 2005-10-01 0 0 0 ble ``` -## 3. Tools +## 12. Integration with Other Packages -### 3.1 ggplotly +CroPlotR works seamlessly with popular R visualization packages to +enhance your plots. -The ggplotly function in plotly library makes it very easy to create -interactive graphics from a ggplot. Do not hesitate to call it with your -plot and move your mouse over the graph to discover the features of this -function. +### 12.1. Interactive Plots with plotly + +Convert any ggplot to an interactive visualization using +`plotly::ggplotly()`: ``` r library(plotly) -ggplotly(plot(sim, obs = obs, type = "dynamic")[[1]], tooltip = c("label")) +ggplotly(plot(sim, obs = obs, type = "dynamic")[[1]]) ``` -### 3.2 patchwork +### 12.2. Combining Plots with patchwork -There is also the patchwork library that allows you to easily combine -several ggplot into one. +Create complex multi-panel layouts using the +[patchwork](https://CRAN.R-project.org/package=patchwork) package: ``` r library(patchwork) +#> Warning: le package 'patchwork' a été compilé avec la version R 4.4.3 plot1 <- plot(sim, obs = obs, type = "scatter", var = "lai_n")[[1]] plot2 <- plot(sim, obs = obs, var = "lai_n")[[1]] @@ -841,14 +848,128 @@ plot4 <- plot(sim, obs = obs, var = "masec_n")[[1]] plot1 + plot2 + plot3 + plot4 + plot_layout(ncol = 2) ``` - + + +## 13. Data Structure + +### Understanding the `cropr_simulation` Format + +Both `sim` and `obs` objects are named lists of data frames: + +- **List names**: Correspond to situation identifiers (e.g., + crop-year-management combinations) +- **Data frames**: Store variable values for each situation, with one + row per time step and one column per simulated or observed variable. + They include a `Date` column as a time reference (at Date or POSIXct + format), and may optionally contain `Plant` and `Dominance` columns to + indicate crop names and their status (“Principal” or “Associated”) in + intercrop datasets. + +### Simulation Data Structure + +``` r +lapply(sim, head) +#> $`SC_Pea_2005-2006_N0` +#> Date lai_n masec_n mafruit Plant +#> 1 2005-09-26 0 0 0 poi +#> 2 2005-09-27 0 0 0 poi +#> 3 2005-09-28 0 0 0 poi +#> 4 2005-09-29 0 0 0 poi +#> 5 2005-09-30 0 0 0 poi +#> 6 2005-10-01 0 0 0 poi +#> +#> $`SC_Wheat_2005-2006_N0` +#> Date lai_n masec_n mafruit Plant +#> 1 2005-09-26 0 0 0 ble +#> 2 2005-09-27 0 0 0 ble +#> 3 2005-09-28 0 0 0 ble +#> 4 2005-09-29 0 0 0 ble +#> 5 2005-09-30 0 0 0 ble +#> 6 2005-10-01 0 0 0 ble +``` + +### Observation Data Structure + +Observations follow the same structure: + +``` r +lapply(obs, head) +#> $`SC_Pea_2005-2006_N0` +#> Date mafruit masec_n lai_n Plant +#> 1 2006-03-29 NA 0.7833333 0.880000 poi +#> 2 2006-04-26 NA 3.9833333 3.613333 poi +#> 3 2006-05-15 NA 8.2066667 3.373333 poi +#> 4 2006-06-13 4.355 NA NA poi +#> 5 2006-06-14 NA 8.8333333 NA poi +#> +#> $`SC_Wheat_2005-2006_N0` +#> Date mafruit masec_n lai_n Plant +#> 1 2006-03-29 NA 1.430 1.090 ble +#> 2 2006-04-26 NA 4.405 1.775 ble +#> 3 2006-05-15 NA 7.165 0.955 ble +#> 4 2006-06-14 NA 8.575 NA ble +#> 5 2006-07-04 3.825 NA NA ble +``` + +### Creating Custom `cropr_simulation` Objects + +You can create compatible simulation objects from your own data by +adding the `cropr_simulation` class attribute to a named list of data +frames: + +``` r +sim_test <- list( + situation_1 = data.frame( + Date = as.Date("2000-01-01") + 0:9, + var1 = rnorm(10), + var2 = rnorm(10) + ), + situation_2 = data.frame( + Date = as.Date("2001-01-01") + 0:9, + var1 = rnorm(10), + var2 = rnorm(10) + ) +) + +class(sim_test) <- append(class(sim_test), "cropr_simulation") +head(sim_test) +#> $situation_1 +#> Date var1 var2 +#> 1 2000-01-01 0.17851245 0.99830079 +#> 2 2000-01-02 -0.18501293 -1.40498186 +#> 3 2000-01-03 0.99458587 -2.51209777 +#> 4 2000-01-04 1.42358872 1.49718481 +#> 5 2000-01-05 0.99588785 -1.15765880 +#> 6 2000-01-06 1.80768707 -0.38440228 +#> 7 2000-01-07 -1.57172087 -0.06107318 +#> 8 2000-01-08 1.03827066 -1.73751647 +#> 9 2000-01-09 -0.02226482 -0.31848179 +#> 10 2000-01-10 1.44859084 0.63979278 +#> +#> $situation_2 +#> Date var1 var2 +#> 1 2001-01-01 0.7242881 -2.32230396 +#> 2 2001-01-02 -1.7797979 0.57906373 +#> 3 2001-01-03 -1.1308429 0.84785651 +#> 4 2001-01-04 0.5645866 -0.33415060 +#> 5 2001-01-05 0.5719987 1.00692496 +#> 6 2001-01-06 2.0015839 -0.08801978 +#> 7 2001-01-07 -1.1901460 -0.17226188 +#> 8 2001-01-08 -1.5696923 0.26070868 +#> 9 2001-01-09 -0.2458506 0.25828618 +#> 10 2001-01-10 1.5008699 -0.14129121 +#> +#> attr(,"class") +#> [1] "list" "cropr_simulation" +``` + +## 14. Getting Help -## 4. Help +### Documentation -You can find help for the functions directly using the name of the -function followed by the class of the object you need the method for: +Access help for specific functions by specifying the class: -- plot: +**For plotting functions:** ``` r ?plot.cropr_simulation @@ -856,18 +977,19 @@ function followed by the class of the object you need the method for: ?plot.statistics ``` -- statistics: +**For statistical functions:** ``` r ?summary.cropr_simulation ``` -If you have any problem, please [fill an -issue](https://github.com/SticsRPacks/CroPlotR/issues) on Github. +### Reporting Issues + +If you encounter problems or have suggestions, please [open an +issue](https://github.com/SticsRPacks/CroPlotR/issues) on GitHub. -## 5. Citation +## 15. Citation -If you have used this package for a study that led to a publication or -report, please cite us. You can either use the citation tool from Github -if you used the last version, or use `citation("CroPlotR")` from R -otherwise. +If CroPlotR contributed to a publication or report, please cite it using +the reference corresponding to the version you used. 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21:35:48 +0000 Subject: [PATCH 118/118] Style code (GHA) --- R/extract_plot.R | 1 - 1 file changed, 1 deletion(-) diff --git a/R/extract_plot.R b/R/extract_plot.R index 84251f5f..a281e153 100644 --- a/R/extract_plot.R +++ b/R/extract_plot.R @@ -83,4 +83,3 @@ extract_plot <- function(plot, var = NULL, situation = NULL, force = FALSE, } ex } -