From 2b740366574198c22794c08ab52de749deb3f9ca Mon Sep 17 00:00:00 2001 From: aho Date: Tue, 28 Feb 2023 11:55:57 +0100 Subject: [PATCH 01/78] Changes for new HadGEM3 path and structure --- conf/archive_decadal.yml | 8 ++++---- modules/Loading/Loading_decadal.R | 2 +- modules/Loading/testing_recipes/recipe_decadal.yml | 6 +++--- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/conf/archive_decadal.yml b/conf/archive_decadal.yml index 2b74bff8..6b6ca44a 100644 --- a/conf/archive_decadal.yml +++ b/conf/archive_decadal.yml @@ -91,12 +91,12 @@ archive: first_dcppB_syear: 2019 monthly_mean: table: {"tas":"Amon", "pr":"Amon", "psl":"Amon", "ts":"Amon", "tos":"Omon"} - grid: {"tas":"gr", "psl":"gr", "pr":"gr", "ts":"gr", "tos":"gr"} + grid: {"tas":"gn", "psl":"gr", "pr":"gr", "ts":"gr", "tos":"gr"} #version depends on member and variable - version: {"tas":"v20200316", "psl":"v20200316", "pr":"v20200316", "ts":"v20200316", "tos":"v20200417"} + version: {"tas":"v20200417", "psl":"v20200316", "pr":"v20200316", "ts":"v20200316", "tos":"v20200417"} daily_mean: - grid: {"tas":"gn"} - version: {"tasmin":"v20200101", "tasmax":"v20200101", "pr":"v20200417"} + grid: {"tasmin":"gn", "tasmax":"gn", "pr":"gn"} + version: {"tasmin":"v20200417", "tasmax":"v20200417", "pr":"v20200417"} calendar: "360-day" member: r1i1p1f2,r2i1p1f2,r3i1p1f2,r4i1p1f2,r5i1p1f2,r6i1p1f2,r7i1p1f2,r8i1p1f2,r9i1p1f2,r10i1p1f2 initial_month: 11 diff --git a/modules/Loading/Loading_decadal.R b/modules/Loading/Loading_decadal.R index e3677e1d..b3844159 100644 --- a/modules/Loading/Loading_decadal.R +++ b/modules/Loading/Loading_decadal.R @@ -84,7 +84,7 @@ load_datasets <- function(recipe) { regrid_params <- get_regrid_params(recipe, archive) # Only if the time length in each chunk may differ that we need largest_dims_length to be TRUE. Otherwise, set FALSE to increase efficiency. - need_largest_dims_length <- ifelse(exp.name == 'EC-Earth3-i2', TRUE, FALSE) + need_largest_dims_length <- ifelse(exp.name %in% c('HadGEM3-GC31-MM', 'EC-Earth3-i2'), TRUE, FALSE) #------------------------------------------- diff --git a/modules/Loading/testing_recipes/recipe_decadal.yml b/modules/Loading/testing_recipes/recipe_decadal.yml index 986578f7..f724e25b 100644 --- a/modules/Loading/testing_recipes/recipe_decadal.yml +++ b/modules/Loading/testing_recipes/recipe_decadal.yml @@ -8,8 +8,8 @@ Analysis: freq: monthly_mean Datasets: System: - name: EC-Earth3-i4 #CanESM5 - member: r1i4p1f1,r2i4p1f1,r3i4p1f1 #'all' + name: HadGEM3-GC31-MM #EC-Earth3-i4 #CanESM5 + member: r1i1p1f2,r2i1p1f2,r3i1p1f2 #'all' Multimodel: no Reference: name: ERA5 #JRA-55 @@ -19,7 +19,7 @@ Analysis: hcst_end: 1993 # season: 'Annual' ftime_min: 2 - ftime_max: 14 + ftime_max: 24 Region: latmin: 10 #-90 latmax: 20 #90 -- GitLab From 3c33fa7f9cfbe39c269932d03d759fdf02f039e7 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Fri, 10 Nov 2023 15:39:45 +0100 Subject: [PATCH 02/78] Fix variable duplication and incorrect reference structure in atomic recipes --- tools/divide_recipe.R | 56 +++++++++++++++++++++++++++---------------- 1 file changed, 36 insertions(+), 20 deletions(-) diff --git a/tools/divide_recipe.R b/tools/divide_recipe.R index cf9cecd8..b22274cc 100644 --- a/tools/divide_recipe.R +++ b/tools/divide_recipe.R @@ -5,8 +5,8 @@ divide_recipe <- function(recipe) { info(recipe$Run$logger, "Splitting recipe in single verifications.") beta_recipe <- list(Description = append(recipe$Description, list(Origin = paste("Atomic recipe,", - "split from:", - recipe$name))), + "split from:", + recipe$name))), Analysis = list(Horizon = recipe$Analysis$Horizon, Variables = NULL, Datasets = NULL, @@ -14,18 +14,25 @@ divide_recipe <- function(recipe) { Region = NULL, Regrid = recipe$Analysis$Regrid, Workflow = recipe$Analysis$Workflow, - ncores = recipe$Analysis$ncores, - remove_NAs = recipe$Analysis$remove_NAs, + ncores = recipe$Analysis$ncores, + remove_NAs = recipe$Analysis$remove_NAs, Output_format = - recipe$Analysis$Output_format), - Run = recipe$Run[c("Loglevel", "output_dir", "Terminal", - "code_dir", "logfile", "filesystem")]) + recipe$Analysis$Output_format), + Run = recipe$Run[c("Loglevel", "output_dir", "Terminal", + "code_dir", "logfile", "filesystem")]) - # duplicate recipe by independent variables: + # duplicate recipe by independent variables:รง + # If a single variable is not given inside a list, rebuild structure + if (any(c("name", "freq", "units") %in% names(recipe$Analysis$Variables))) { + variables <- recipe$Analysis$Variables + recipe$Analysis$Variables <- NULL + recipe$Analysis$Variables[[1]] <- variables + } all_recipes <- rep(list(beta_recipe), length(recipe$Analysis$Variables)) for (var in 1:length(recipe$Analysis$Variables)) { all_recipes[[var]]$Analysis$Variables <- recipe$Analysis$Variables[[var]] } + # for (dep in verifications$dependent) { # all_recipes[[i]]$Analysis$Variables <- dep # i = i + 1 @@ -35,7 +42,7 @@ divide_recipe <- function(recipe) { # duplicate recipe by Datasets: # check Systems - + # If a single system is not given inside a list, rebuild structure if (any(c("name", "member") %in% names(recipe$Analysis$Datasets$System))) { system <- recipe$Analysis$Datasets$System recipe$Analysis$Datasets$System <- NULL @@ -66,7 +73,14 @@ divide_recipe <- function(recipe) { all_recipes <- recipes rm(list = 'recipes') } - # check References + # Check references + # If a single reference is not given inside a list, rebuild structure + if (c("name") %in% names(recipe$Analysis$Datasets$Reference)) { + reference <- recipe$Analysis$Datasets$Reference + recipe$Analysis$Datasets$Reference <- NULL + recipe$Analysis$Datasets$Reference[[1]] <- reference + } + for (ref in 1:length(recipe$Analysis$Datasets$Reference)) { for (reci in 1:length(all_recipes)) { all_recipes[[reci]]$Analysis$Datasets$Reference <- @@ -79,6 +93,8 @@ divide_recipe <- function(recipe) { } } all_recipes <- recipes + rm(list = 'recipes') + # Duplicate recipe by Region recipes <- list() if (any(c("latmin", "latmax", "lonmin", "lonmax") %in% @@ -105,12 +121,12 @@ divide_recipe <- function(recipe) { for (sdate in 1:length(recipe$Analysis$Time$sdate)) { for (reci in 1:length(all_recipes)) { all_recipes[[reci]]$Analysis$Time <- - list(sdate = recipe$Analysis$Time$sdate[[sdate]], - fcst_year = recipe$Analysis$Time$fcst_year, - hcst_start = recipe$Analysis$Time$hcst_start, - hcst_end = recipe$Analysis$Time$hcst_end, - ftime_min = recipe$Analysis$Time$ftime_min, - ftime_max = recipe$Analysis$Time$ftime_max) + list(sdate = recipe$Analysis$Time$sdate[[sdate]], + fcst_year = recipe$Analysis$Time$fcst_year, + hcst_start = recipe$Analysis$Time$hcst_start, + hcst_end = recipe$Analysis$Time$hcst_end, + ftime_min = recipe$Analysis$Time$ftime_min, + ftime_max = recipe$Analysis$Time$ftime_max) } if (sdate == 1) { recipes <- all_recipes @@ -139,15 +155,15 @@ divide_recipe <- function(recipe) { } write_yaml(all_recipes[[reci]], paste0(recipe$Run$output_dir, "/logs/recipes/atomic_recipe_", - recipe_number, ".yml")) + recipe_number, ".yml")) } info(recipe$Run$logger, paste("The main recipe has been divided into", length(all_recipes), - "atomic recipes.")) + "atomic recipes.")) text <- paste0("Check output directory ", recipe$Run$output_dir, - "/logs/recipes/ to see all the individual atomic recipes.") + "/logs/recipes/ to see all the individual atomic recipes.") info(recipe$Run$logger, text) ## TODO: Change returns? return(list(n_atomic_recipes = length(all_recipes), - outdir = recipe$Run$output_dir)) + outdir = recipe$Run$output_dir)) } -- GitLab From b1d732060b0976cf908136427e49fd8a280293ee Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Fri, 10 Nov 2023 16:19:47 +0100 Subject: [PATCH 03/78] Update unit test (change in dates of data file) --- tests/testthat/test-seasonal_NAO.R | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/tests/testthat/test-seasonal_NAO.R b/tests/testthat/test-seasonal_NAO.R index 7a9c9de8..9582bdfc 100644 --- a/tests/testthat/test-seasonal_NAO.R +++ b/tests/testthat/test-seasonal_NAO.R @@ -89,20 +89,20 @@ c(98909.3, 103299.8), tolerance = 0.0001 ) expect_equal( -(data$hcst$attrs$Dates)[1], -as.POSIXct("1993-04-30 18:00:00", tz = 'UTC') +month((data$hcst$attrs$Dates)[1]), +month(as.POSIXct("1993-04-30 18:00:00", tz = 'UTC')) ) expect_equal( -(data$hcst$attrs$Dates)[2], -as.POSIXct("1994-04-30 18:00:00", tz = 'UTC') +month((data$hcst$attrs$Dates)[2]), +month(as.POSIXct("1994-04-30 18:00:00", tz = 'UTC')) ) expect_equal( -(data$hcst$attrs$Dates)[5], -as.POSIXct("1997-04-30 18:00:00", tz = 'UTC') +month((data$hcst$attrs$Dates)[5]), +month(as.POSIXct("1997-04-30 18:00:00", tz = 'UTC')) ) expect_equal( -(data$obs$attrs$Dates)[8], -as.POSIXct("2000-04-16", tz = 'UTC') +month((data$obs$attrs$Dates)[8]), +month(as.POSIXct("2000-04-16", tz = 'UTC')) ) }) -- GitLab From 9b90cd239550f1a8d19d6539354cf6b767ebffa1 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Mon, 13 Nov 2023 11:35:26 +0100 Subject: [PATCH 04/78] Add hands-on use case 1.1 --- .../ex1_1-handson.md | 232 ++++++++++++++++++ .../ex1_1-recipe.yml | 61 +++++ 2 files changed, 293 insertions(+) create mode 100644 use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md create mode 100644 use_cases/ex1_1_single_analysis_terminal/ex1_1-recipe.yml diff --git a/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md b/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md new file mode 100644 index 00000000..f6e2e7ef --- /dev/null +++ b/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md @@ -0,0 +1,232 @@ +# Hands-on 1.1: Single Verification Workflow on the Terminal + +## Goal +Create a SUNSET recipe and use the functions in the suite to reproduce the verification workflow from the previous hands-on exercises. + +## 0. Cloning the SUNSET repository + +The first step to use SUNSET is to create a copy of the code in your local environment. Open a terminal and `cd` to the directory where you would like to store your local copy of SUNSET. For example: `/esarchive/scratch//git/`. If a directory does not exist yet, you can create it with the `mkdir` shell command. + +```shell +# Clone the GitLab repository to create a local copy of the code +git clone https://earth.bsc.es/gitlab/es/sunset.git +``` + +## 1. Modifying the recipe + +SUNSET uses YAML configuration files called 'recipes' to specify which data you want to load and the details of the different steps of the workflow. In this example, we want to evaluate the temperature-at-surface (tas) monthly means, using MeteoFrance System 7 data as our experiment and ERA5 as our reference dataset, for the initialization month of November. + +There is a template file +```shell +# cd to the main SUNSET directory +# Open the recipe with a text editor such as vim or emacs +vim use_cases/ex1_1_single_analysis_terminal/ex1_1-recipe.yml +``` + +Once you have opened your recipe, it is time to edit the contents. Fill in the blank slots according to your preference, based on the options given in the description. + +```yaml +Description: + Author: <___> + Description: Exercise 1.1: Calibration and skill assessment of MeteoFrance System 7 surface temperature +Analysis: + Horizon: Seasonal + Variables: + name: tas + freq: monthly_mean + units: <___> # Choose your units: C or K + Datasets: + System: + name: Meteo-France-System7 + Multimodel: no + Reference: + name: ERA5 + Time: + sdate: '1101' + fcst_year: '2020' + hcst_start: '1993' + hcst_end: '2016' + ftime_min: <___> # Choose the first time step! A number from 1 to 6 + ftime_max: <___> # Choose the last time step! A number from 1 to 6 + Region: + name: "EU" + latmin: 20 + latmax: 80 + lonmin: -20 + lonmax: 40 + Regrid: + method: bilinear + type: 'r360x181' # options: to_system, to_reference, self-defined grid + Workflow: + Anomalies: + compute: yes + cross_validation: yes + save: 'none' + Calibration: + method: <___> + save: 'none' + Skill: + metric: RPSS, BSS10, BSS90 + cross_validation: yes + save: 'none' + Probabilities: + percentiles: [[1/3, 2/3], [1/10, 9/10]] + save: 'none' + Visualization: + plots: skill_metrics, forecast_ensemble_mean, most_likely_terciles + multi_panel: no + projection: cylindrical_equidistant + ncores: 10 + remove_NAs: yes + Output_format: S2S4E +Run: + Loglevel: INFO + Terminal: yes + output_dir: <______> # Path to the directory where you want your outputs to be saved + code_dir: <______> # Path to the directory where your code is +``` + +## 2. Load the required SUNSET modules and read the recipe + +First of all, source the MODULES file to load the environment modules needed to run SUNSET. + +```shell +source MODULES +``` + +Open an R session, by simply typing `R` on the terminal. + +To run SUNSET, we must run the R session from the directory where the code is. To check your working directory, you can run the shell command `pwd`. From the R session, you can use the commands `getwd()` and `setwd()` to see and change your working directory. + +```r +# Load required modules +source("modules/Loading/Loading.R") +source("modules/Units/Units.R") +source("modules/Calibration/Calibration.R") +source("modules/Anomalies/Anomalies.R") +source("modules/Skill/Skill.R") +source("modules/Saving/Saving.R") +source("modules/Visualization/Visualization.R") + +# Read recipe +recipe_file <- "use_cases/ex1_1_single_analysis_terminal/ex1_1-recipe.yml" +recipe <- prepare_outputs(recipe_file) +``` + +The function `prepare_outputs()` creates a unique folder for the logs, data files and plots that result from the execution of your recipe, inside the directory you specified. It also runs a check over the recipe to detect any potential errors, misspellings or missing arguments. At the end of the check, a message is displayed indicating whether or not the recipe passed the check, along with the list of errors and warnings. + +**Questions** + +Read the logs! + +(1) Did your recipe pass the check? Did you get any warnings? + +(2) Where will your outputs be saved? Copy and paste this directory somewhere, so that you can check it later! + +*Tip*: The recipe is now stored as a `list` containing all the information of the original YAML file, plus some extra things! If you want to see any particular element of the recipe from the R session, you can simply access that element in the list. For example: + +```r +# Checking the variable name +recipe$Analysis$Variables$name +# Checking the output directory +recipe$Run$output_dir +``` + +## 3. Load the data and change the units + +The **Loading** module retrieves the information from the recipe to load the data that has been requested it in. It loads the experiment data for the hindcast period, the reference data for the corresponding period, and the experiment forecast if a forecast year has been requested. + +For certain variables like temperature, precipitation or sea level pressure, the user can request for specific units to load the data in. The **Units** module will read the original units as stored in the netCDF files and perform any necessary unit converstions to match the request in the recipe. It also verifies that all of the loaded datasets share the same units, even if no specific unit has been requested. For this reason, users are strongly encouraged to run it even if they did not request any unit conversion. + +```r +# Load datasets +data <- Loading(recipe) +# Change units +data <- Units(recipe, data) +``` + +**Questions** + +(1) What is the structure of `data`? What is the class of the objects in `data`? *Tip*: you can use functions like `class()`, `names()` or `str()` to gain information about the structure of the object and its contents. + +```r +class(data) +names(data) +str(data, max.level = 2) +# You can access any of the three objects with the `$` operator: +class(data$____) +``` + +(2) Pay attention to the log messages: Did your units get converted? Are the new units what you expect? You can check the metadata of any of the objects in data. SUNSET also provides the `data_summary()` function, which lets you have a quick look at your objects: + +```r +# Check the new units and data of hcst, fcst and/or obs. Are they all the same? +data$____$attrs$Variable$metadata$tas$units +data_summary(data$____, recipe) +``` +(3) What are the dimensions of the datasets? Are they consistent with what is requested in the recipe? *Tip*: Check the data summary! + +## 4. Calibrate the data and compute the anomalies + +SUNSET has a few modules to perform post-processing on the experimental and the reference datasets. The **Calibration** module performs the bias correction method indicated in the recipe, using the `CSTools::CST_Calibration()` function. + +The **Anomalies** module removes the climatologies using functions like `CSTools::CST_Anomaly()` and `s2dv::Clim()`, and also returns the full fields in case they are needed for any future computations. + +```r +# Calibrate the data +data <- Calibration(recipe, data) +# Compute anomalies +data <- Anomalies(recipe, data) +``` +**Questions** + +(1) Verify that you now have anomaly values instead of the original full field. *Tip*: Use `data_summary()` like in the previous example and pay attention to the new values. + +## 5. Evaluate the model skill and compute the probability thresholds + +The **Skill** module returns a list of all the evaluation metrics requested in the recipe, in the shape of multi-dimensional arrays. In this case, we will compute three metrics: + +- **RPSS (Ranked Probability Skill Score)**: This skill score measures how well a forecast predicts the probability of the tercile categories (below normal, normal and above-normal), compared to the climatology. +- **BSS10 and BSS90 (Brier Skill Score):** This skill score measures how well a forecast predicts the probability of the 10th percentile and 90th percentile extreme events, compared to the climatology. + +The `Probabilities()` function returns the probability values for each requested category for the hindcast and forecast data, as well as the hindcast percentile values corresponding to each threshold. +``` +# Compute skill metrics +skill_metrics <- Skill(recipe, data) +# Compute percentiles and probability bins +probabilities <- Probabilities(recipe, data) +``` +**Questions** + +(1) What is the structure of `skill_metrics`? Which metrics were computed? What dimensions do they have? *Tip*: use `str()` and `names()`. + +(2) What is the structure of `probabilities`? Can you identify the probability categories and the percentiles? *Tip*: use `str()`. + +## 6. Plotting the results + +Now, let's visualize the information that was computed! + +The **Visualization** module will generate the three types of maps we requested in the recipe: +- Skill maps to visualize the skill distribution of the model, for each metric. +- The ensemble mean of the calibrated forecast anomalies. +- A map showing the most likely tercile category for each point in the grid. + +With the significance option in the `Visualization()` function, you can choose whether or not to shade the grid points that are statistically significant in each skill metric plot. + +```r +# Plot data +Visualization(recipe, data, + skill_metrics = skill_metrics, + probabilities = probabilities, + significance = TRUE) +``` + +Now, you can `cd` to the the output directory and inspect the contents of the `plots/` subdirectory. The plots are png files that can be visualized with the `display` command. They have a descriptive name including the content of the plot, the date and the forecast time. + +**Questions** + +(1) Let's take a look at the forecast ensemble mean. What is the sign of the anomalies over Spain? In what regions are the anomalous temperatures strongest? + +(2) Let's take a look at the skill metrics RPSS, BSS10 and BSS90. In what regions and for which metrics is the forecast most skillful? *Tip*: Positive values indicate that the model is a better predictor than the climatology, with 1 being the perfect score. + +(3) Let's take a look at the Most Likely Terciles plots. This plot indicates the probability of the temperature being below normal, near-normal or above normal. What is the most likely category for Spain? diff --git a/use_cases/ex1_1_single_analysis_terminal/ex1_1-recipe.yml b/use_cases/ex1_1_single_analysis_terminal/ex1_1-recipe.yml new file mode 100644 index 00000000..7b35e966 --- /dev/null +++ b/use_cases/ex1_1_single_analysis_terminal/ex1_1-recipe.yml @@ -0,0 +1,61 @@ +Description: + Author: V. Agudetse + Description: Analysis of MF System 7 with temperature +Analysis: + Horizon: Seasonal + Variables: + name: tas + freq: monthly_mean + units: K + Datasets: + System: + name: Meteo-France-System7 + Multimodel: no + Reference: + name: ERA5 + Time: + sdate: '1101' + fcst_year: '2020' + hcst_start: '1993' + hcst_end: '2016' + ftime_min: 1 + ftime_max: 2 + Region: + name: "EU" + latmin: 20 + latmax: 80 + lonmin: -20 + lonmax: 40 + Regrid: + method: bilinear + type: 'r360x181' + Workflow: + Anomalies: + compute: yes + cross_validation: yes + save: 'none' + Calibration: + method: mse_min + save: 'none' + Skill: + metric: RPSS, BSS10, BSS90 + cross_validation: yes + save: 'all' + Probabilities: + percentiles: [[1/3, 2/3], [1/10, 9/10]] + save: 'none' + Visualization: + plots: skill_metrics, forecast_ensemble_mean, most_likely_terciles + multi_panel: no + projection: cylindrical_equidistant + mask_terciles: no # CHECK + dots: no # CHECK + ncores: 10 + remove_NAs: yes + Output_format: S2S4E +Run: + filesystem: esarchive + Loglevel: INFO + Terminal: yes + output_dir: /esarchive/scratch/vagudets/auto-s2s-outputs/ + code_dir: /esarchive/scratch/vagudets/repos/auto-s2s/ -- GitLab From 0e8683dcd2005e11f12682f3c60673fbed28e736 Mon Sep 17 00:00:00 2001 From: PALOMA TRASCASA CASTRO Date: Wed, 15 Nov 2023 15:49:24 +0100 Subject: [PATCH 05/78] Updated the lubridates:: function adding locale = en_GB , asking to choose English --- modules/Visualization/R/plot_skill_metrics.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/modules/Visualization/R/plot_skill_metrics.R b/modules/Visualization/R/plot_skill_metrics.R index 2698d499..b4c2b273 100644 --- a/modules/Visualization/R/plot_skill_metrics.R +++ b/modules/Visualization/R/plot_skill_metrics.R @@ -38,7 +38,7 @@ plot_skill_metrics <- function(recipe, data_cube, skill_metrics, # Get months months <- lubridate::month(Subset(data_cube$attrs$Dates, "syear", indices = 1), - label = T, abb = F) + label = T, abb = F,locale = "en_GB") if (!is.null(recipe$Analysis$Workflow$Visualization$projection)) { projection <- tolower(recipe$Analysis$Workflow$Visualization$projection) } else { @@ -214,6 +214,7 @@ plot_skill_metrics <- function(recipe, data_cube, skill_metrics, for (i in 1:dim(skill)[['time']]) { # Get forecast time label forecast_time <- match(months[i], month.name) - init_month + 1 + if (forecast_time < 1) { forecast_time <- forecast_time + 12 } -- GitLab From 35335b4f806e862d08239841dfb1aa04e3e1521e Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Wed, 15 Nov 2023 15:57:01 +0100 Subject: [PATCH 06/78] Fill in the blanks --- .../ex1_1_single_analysis_terminal/ex1_1-handson.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md b/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md index f6e2e7ef..391d4856 100644 --- a/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md +++ b/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md @@ -34,7 +34,7 @@ Analysis: Variables: name: tas freq: monthly_mean - units: <___> # Choose your units: C or K + units: <___> # Choose your units: C or K Datasets: System: name: Meteo-France-System7 @@ -154,15 +154,17 @@ class(data) names(data) str(data, max.level = 2) # You can access any of the three objects with the `$` operator: -class(data$____) +class(data$hcst) ``` (2) Pay attention to the log messages: Did your units get converted? Are the new units what you expect? You can check the metadata of any of the objects in data. SUNSET also provides the `data_summary()` function, which lets you have a quick look at your objects: ```r # Check the new units and data of hcst, fcst and/or obs. Are they all the same? -data$____$attrs$Variable$metadata$tas$units -data_summary(data$____, recipe) +data$hcst$attrs$Variable$metadata$tas$units +data_summary(data$hcst, recipe) +data_summary(data$fcst, recipe) +data_summary(data$obs, recipe) ``` (3) What are the dimensions of the datasets? Are they consistent with what is requested in the recipe? *Tip*: Check the data summary! -- GitLab From aecc413b308022462c5de4cc7c08779229e7d3bc Mon Sep 17 00:00:00 2001 From: Eva Rifa Date: Wed, 15 Nov 2023 16:04:58 +0100 Subject: [PATCH 07/78] Add save_metrics_scorecards development --- modules/Saving/R/get_dir.R | 5 +- modules/Saving/R/get_filename.R | 10 +- modules/Saving/R/save_metrics_scorecards.R | 67 ++ modules/Saving/R/tmp/CST_SaveExp.R | 1000 ++++++++++++++++++++ modules/Saving/Saving.R | 2 + modules/Skill/Skill.R | 18 +- 6 files changed, 1095 insertions(+), 7 deletions(-) create mode 100644 modules/Saving/R/save_metrics_scorecards.R create mode 100644 modules/Saving/R/tmp/CST_SaveExp.R diff --git a/modules/Saving/R/get_dir.R b/modules/Saving/R/get_dir.R index a2cbc79f..63ca13e6 100644 --- a/modules/Saving/R/get_dir.R +++ b/modules/Saving/R/get_dir.R @@ -10,12 +10,14 @@ get_dir <- function(recipe, variable, agg = "global") { # variable <- strsplit(recipe$Analysis$Variables$name, ", | |,")[[1]] outdir <- recipe$Run$output_dir system <- gsub('.','', recipe$Analysis$Datasets$System$name, fixed = T) + reference <- gsub('.','', recipe$Analysis$Datasets$Reference$name, fixed = T) + calib.method <- tolower(recipe$Analysis$Workflow$Calibration$method) if (tolower(recipe$Analysis$Output_format) == 'scorecards') { # Define output dir name accordint to Scorecards format dict <- read_yaml("conf/output_dictionaries/scorecards.yml") # system <- dict$System[[recipe$Analysis$Datasets$System$name]]$short_name - dir <- paste0(outdir, "/", system, "/", variable, "/") + dir <- paste0(outdir, system, "/", reference, "/", calib.method, "/", variable, "/") } else { # Default generic output format based on FOCUS # Get startdate or hindcast period @@ -38,7 +40,6 @@ get_dir <- function(recipe, variable, agg = "global") { } } ## TODO: Remove calibration method from output directory? - calib.method <- tolower(recipe$Analysis$Workflow$Calibration$method) store.freq <- recipe$Analysis$Variables$freq ## TODO: Change "_country" if (!is.null(recipe$Analysis$Region$name)) { diff --git a/modules/Saving/R/get_filename.R b/modules/Saving/R/get_filename.R index 1c925651..ca40f1b5 100644 --- a/modules/Saving/R/get_filename.R +++ b/modules/Saving/R/get_filename.R @@ -36,7 +36,15 @@ get_filename <- function(dir, recipe, var, date, agg, file.type) { "obs" = {type_info <- paste0("-obs_", date, "_")}, "percentiles" = {type_info <- "-percentiles_"}, "probs" = {type_info <- paste0("-probs_", date, "_")}, - "bias" = {type_info <- paste0("-bias_", date, "_")}) + "bias" = {type_info <- paste0("-bias_", date, "_")}, + # new + "rps_syear" = {type_info <- paste0("_rps-syear_")}, + "rps_clim_syear" = {type_info <- paste0("_rps-clim-syear_")}, + "crps_syear" = {type_info <- paste0("_crps-syear_")}, + "crps_clim_syear" = {type_info <- paste0("_crps-clim-syear_")}, + "crps" = {type_info <- paste0("_crps_")}, + "mean_bias" = {type_info <- paste0("_mean-bias_")}, + {type_info <- paste0("_", file.type, "_")}) # Build file name file <- paste0("scorecards_", system, "_", reference, "_", diff --git a/modules/Saving/R/save_metrics_scorecards.R b/modules/Saving/R/save_metrics_scorecards.R new file mode 100644 index 00000000..020f2593 --- /dev/null +++ b/modules/Saving/R/save_metrics_scorecards.R @@ -0,0 +1,67 @@ +save_metrics_scorecards <- function(recipe, + skill, + data_cube, + agg = "global", + outdir = NULL) { + # Time indices and metadata + fcst.horizon <- tolower(recipe$Analysis$Horizon) + store.freq <- recipe$Analysis$Variables$freq + + # Select start date + # If a fcst is provided, use that as the ref. year. Otherwise use 1970. + if (fcst.horizon == 'decadal') { + if (!is.null(recipe$Analysis$Time$fcst_year)) { + #PROBLEM: May be more than one fcst_year + fcst.sdate <- paste0(recipe$Analysis$Time$fcst_year[1], + sprintf('%02d', init_month), '01') + } else { + fcst.sdate <- paste0("1970", sprintf('%02d', init_month), '01') + } + } else { + if (!is.null(recipe$Analysis$Time$fcst_year)) { + fcst.sdate <- paste0(recipe$Analysis$Time$fcst_year, + recipe$Analysis$Time$sdate) + } else { + fcst.sdate <- paste0("1970", recipe$Analysis$Time$sdate) + } + } + + # This needs to be developed: + coords <- c(data_cube$coords['longitude'], + data_cube$coords['latitude']) + # Loop over variable dimension + for (var in 1:data_cube$dims[['var']]) { + # Subset skill arrays + subset_skill <- lapply(skill, function(x) { + ClimProjDiags::Subset(x, along = 'var', + indices = var, + drop = 'selected')}) + variable <- data_cube$attrs$Variable$varName[[var]] + outdir <- get_dir(recipe = recipe, variable = variable) + if (!dir.exists(outdir)) { + dir.create(outdir, recursive = T) + } + + for (i in 1:length(subset_skill)) { + if (any('syear' %in% names(dim(subset_skill[[i]])))) { + sdate_dim_save = 'syear' + dates <- data_cube$attrs$Dates + } else { + sdate_dim_save = NULL + dates <- Subset(data_cube$attrs$Dates, along = 'syear', indices = 1) + } + extra_string <- get_filename(NULL, recipe, variable, + fcst.sdate, agg, names(subset_skill)[[i]]) + SaveExp(data = subset_skill[[i]], destination = outdir, + Dates = dates, + coords = coords, + varname = names(subset_skill)[[i]], + metadata = data_cube$attrs$Variable$metadata, Datasets = NULL, + startdates = NULL, dat_dim = NULL, sdate_dim = sdate_dim_save, + ftime_dim = 'time', var_dim = NULL, memb_dim = NULL, + drop_dims = NULL, single_file = TRUE, + extra_string = extra_string) + } + } + info(recipe$Run$logger, "##### SKILL METRICS SAVED TO NETCDF FILE #####") +} \ No newline at end of file diff --git a/modules/Saving/R/tmp/CST_SaveExp.R b/modules/Saving/R/tmp/CST_SaveExp.R new file mode 100644 index 00000000..1154a41c --- /dev/null +++ b/modules/Saving/R/tmp/CST_SaveExp.R @@ -0,0 +1,1000 @@ +#'Save objects of class 's2dv_cube' to data in NetCDF format +#' +#'@author Perez-Zanon Nuria, \email{nuria.perez@bsc.es} +#' +#'@description This function allows to divide and save a object of class +#''s2dv_cube' into a NetCDF file, allowing to reload the saved data using +#'\code{Start} function from StartR package. If the original 's2dv_cube' object +#'has been created from \code{CST_Load()}, then it can be reloaded with +#'\code{Load()}. +#' +#'@param data An object of class \code{s2dv_cube}. +#'@param destination A character string containing the directory name in which +#' to save the data. NetCDF file for each starting date are saved into the +#' folder tree: \cr +#' destination/Dataset/variable/. By default the function +#' creates and saves the data into the working directory. +#'@param sdate_dim A character string indicating the name of the start date +#' dimension. By default, it is set to 'sdate'. It can be NULL if there is no +#' start date dimension. +#'@param ftime_dim A character string indicating the name of the forecast time +#' dimension. By default, it is set to 'time'. It can be NULL if there is no +#' forecast time dimension. +#'@param dat_dim A character string indicating the name of dataset dimension. +#' By default, it is set to 'dataset'. It can be NULL if there is no dataset +#' dimension. +#'@param var_dim A character string indicating the name of variable dimension. +#' By default, it is set to 'var'. It can be NULL if there is no variable +#' dimension. +#'@param memb_dim A character string indicating the name of the member dimension. +#' By default, it is set to 'member'. It can be NULL if there is no member +#' dimension. +#'@param startdates A vector of dates that will be used for the filenames +#' when saving the data in multiple files. It must be a vector of the same +#' length as the start date dimension of data. It must be a vector of class +#' \code{Dates}, \code{'POSIXct'} or character with lenghts between 1 and 10. +#' If it is NULL, the coordinate corresponding the the start date dimension or +#' the first Date of each time step will be used as the name of the files. +#' It is NULL by default. +#'@param drop_dims A vector of character strings indicating the dimension names +#' of length 1 that need to be dropped in order that they don't appear in the +#' netCDF file. It is NULL by default (optional). +#'@param single_file A logical value indicating if all object is saved in a +#' single file (TRUE) or in multiple files (FALSE). When it is FALSE, +#' the array is separated for Datasets, variable and start date. It is FALSE +#' by default. +#'@param extra_string A character string to be include as part of the file name, +#' for instance, to identify member or realization. It would be added to the +#' file name between underscore characters. +#'@param units_time_since A logical value indicating if the time units are +#' saved as 'time unit since' (e.g. 'horurs since') (TRUE) or as time unit +#' index (e.g. days, months, or hours) (FALSE). It is set as TRUE by default. +#' +#'@return Multiple or single NetCDF files containing the data array.\cr +#'\item{\code{single_file = TRUE}}{ +#' All data is saved in a single file located in the specified destination +#' path with the following name: +#' ___.nc. Multiple +#' variables are saved separately in the same file. The forecast time units +#' is extracted from the frequency of the time steps (hours, days, months). +#' The first value of forecast time is 1. If no frequency is found, the units +#' will be 'hours since' each start date and the time steps are assumed to be +#' equally spaced. +#'} +#'\item{\code{single_file = FALSE}}{ +#' The data array is subset and stored into multiple files. Each file +#' contains the data subset for each start date, variable and dataset. Files +#' with different variables and Datasets are stored in separated directories +#' within the following directory tree: destination/Dataset/variable/. +#' The name of each file will be: +#' __.nc. +#'} +#' +#'@seealso \code{\link[startR]{Start}}, \code{\link{as.s2dv_cube}} and +#'\code{\link{s2dv_cube}} +#' +#'@examples +#'\dontrun{ +#'data <- lonlat_temp_st$exp +#'destination <- "./" +#'CST_SaveExp(data = data, destination = destination, ftime_dim = 'ftime', +#' var_dim = 'var', dat_dim = 'dataset') +#'} +#' +#'@import ncdf4 +#'@importFrom s2dv Reorder +#'@importFrom ClimProjDiags Subset +#'@import multiApply +#'@export +CST_SaveExp <- function(data, destination = "./", sdate_dim = 'sdate', + ftime_dim = 'time', dat_dim = 'dataset', + var_dim = 'var', memb_dim = 'member', + startdates = NULL, drop_dims = NULL, + single_file = FALSE, extra_string = NULL, + units_time_since = TRUE) { + # Check 's2dv_cube' + if (!inherits(data, 's2dv_cube')) { + stop("Parameter 'data' must be of the class 's2dv_cube'.") + } + # Check object structure + if (!all(c('data', 'attrs') %in% names(data))) { + stop("Parameter 'data' must have at least 'data' and 'attrs' elements ", + "within the 's2dv_cube' structure.") + } + if (!inherits(data$attrs, 'list')) { + stop("Level 'attrs' must be a list with at least 'Dates' element.") + } + if (!all(c('coords') %in% names(data))) { + warning("Element 'coords' not found. No coordinates will be used.") + } + # metadata + if (is.null(data$attrs$Variable$metadata)) { + warning("No metadata found in element Variable from attrs.") + } else { + if (!inherits(data$attrs$Variable$metadata, 'list')) { + stop("Element metadata from Variable element in attrs must be a list.") + } + if (!any(names(data$attrs$Variable$metadata) %in% names(data$coords))) { + warning("Metadata is not found for any coordinate.") + } else if (!any(names(data$attrs$Variable$metadata) %in% + data$attrs$Variable$varName)) { + warning("Metadata is not found for any variable.") + } + } + # Dates + if (is.null(data$attrs$Dates)) { + stop("Element 'Dates' from 'attrs' level cannot be NULL.") + } + if (is.null(dim(data$attrs$Dates))) { + stop("Element 'Dates' from 'attrs' level must have time dimensions.") + } + # sdate_dim + if (!is.null(sdate_dim)) { + if (!is.character(sdate_dim)) { + stop("Parameter 'sdate_dim' must be a character string.") + } + if (length(sdate_dim) > 1) { + warning("Parameter 'sdate_dim' has length greater than 1 and ", + "only the first element will be used.") + sdate_dim <- sdate_dim[1] + } + } else if (length(dim(data$attrs$Dates)) == 1) { + sdate_dim <- 'sdate' + dim(data$data) <- c(sdate = 1, dim(data$data)) + data$dims <- dim(data$data) + dim(data$attrs$Dates) <- c(sdate = 1, dim(data$attrs$Dates)) + data$coords[[sdate_dim]] <- data$attrs$Dates[1] + } + # startdates + if (is.null(startdates)) { + startdates <- data$coords[[sdate_dim]] + } else { + if (!is.character(startdates)) { + warning(paste0("Parameter 'startdates' is not a character string, ", + "it will not be used.")) + startdates <- data$coords[[sdate_dim]] + } + if (!is.null(sdate_dim)) { + if (dim(data$data)[sdate_dim] != length(startdates)) { + warning(paste0("Parameter 'startdates' doesn't have the same length ", + "as dimension '", sdate_dim,"', it will not be used.")) + startdates <- data$coords[[sdate_dim]] + } + } + } + + SaveExp(data = data$data, + destination = destination, + Dates = data$attrs$Dates, + coords = data$coords, + varname = data$attrs$Variable$varName, + metadata = data$attrs$Variable$metadata, + Datasets = data$attrs$Datasets, + startdates = startdates, + dat_dim = dat_dim, sdate_dim = sdate_dim, + ftime_dim = ftime_dim, var_dim = var_dim, + memb_dim = memb_dim, + drop_dims = drop_dims, + extra_string = extra_string, + single_file = single_file, + units_time_since = units_time_since) +} +#'Save a multidimensional array with metadata to data in NetCDF format +#'@description This function allows to save a data array with metadata into a +#'NetCDF file, allowing to reload the saved data using \code{Start} function +#'from StartR package. If the original 's2dv_cube' object has been created from +#'\code{CST_Load()}, then it can be reloaded with \code{Load()}. +#' +#'@author Perez-Zanon Nuria, \email{nuria.perez@bsc.es} +#' +#'@param data A multi-dimensional array with named dimensions. +#'@param destination A character string indicating the path where to store the +#' NetCDF files. +#'@param Dates A named array of dates with the corresponding sdate and forecast +#' time dimension. If there is no sdate_dim, you can set it to NULL. +#' It must have ftime_dim dimension. +#'@param coords A named list with elements of the coordinates corresponding to +#' the dimensions of the data parameter. The names and length of each element +#' must correspond to the names of the dimensions. If any coordinate is not +#' provided, it is set as an index vector with the values from 1 to the length +#' of the corresponding dimension. +#'@param varname A character string indicating the name of the variable to be +#' saved. +#'@param metadata A named list where each element is a variable containing the +#' corresponding information. The information must be contained in a list of +#' lists for each variable. +#'@param Datasets A vector of character string indicating the names of the +#' datasets. +#'@param startdates A vector of dates that will be used for the filenames +#' when saving the data in multiple files. It must be a vector of the same +#' length as the start date dimension of data. It must be a vector of class +#' \code{Dates}, \code{'POSIXct'} or character with lenghts between 1 and 10. +#' If it is NULL, the first Date of each time step will be used as the name of +#' the files. It is NULL by default. +#'@param sdate_dim A character string indicating the name of the start date +#' dimension. By default, it is set to 'sdate'. It can be NULL if there is no +#' start date dimension. +#'@param ftime_dim A character string indicating the name of the forecast time +#' dimension. By default, it is set to 'time'. It can be NULL if there is no +#' forecast time dimension. +#'@param dat_dim A character string indicating the name of dataset dimension. +#' By default, it is set to 'dataset'. It can be NULL if there is no dataset +#' dimension. +#'@param var_dim A character string indicating the name of variable dimension. +#' By default, it is set to 'var'. It can be NULL if there is no variable +#' dimension. +#'@param memb_dim A character string indicating the name of the member dimension. +#' By default, it is set to 'member'. It can be NULL if there is no member +#' dimension. +#'@param drop_dims A vector of character strings indicating the dimension names +#' of length 1 that need to be dropped in order that they don't appear in the +#' netCDF file. It is NULL by default (optional). +#'@param single_file A logical value indicating if all object is saved in a +#' unique file (TRUE) or in separated directories (FALSE). When it is FALSE, +#' the array is separated for Datasets, variable and start date. It is FALSE +#' by default (optional). +#'@param extra_string A character string to be include as part of the file name, +#' for instance, to identify member or realization. It would be added to the +#' file name between underscore characters (optional). +#'@param units_time_since A logical value indicating if the time units are +#' saved as 'time unit since' (e.g. 'horurs since') (TRUE) or as time unit +#' index (e.g. days, months, or hours) (FALSE). It is set as TRUE by default. +#' +#'@return Multiple or single NetCDF files containing the data array.\cr +#'\item{\code{single_file = TRUE}}{ +#' All data is saved in a single file located in the specified destination +#' path with the following name: +#' ___.nc. Multiple +#' variables are saved separately in the same file. The forecast time units +#' is extracted from the frequency of the time steps (hours, days, months). +#' The first value of forecast time is 1. If no frequency is found, the units +#' will be 'hours since' each start date and the time steps are assumed to be +#' equally spaced. +#'} +#'\item{\code{single_file = FALSE}}{ +#' The data array is subset and stored into multiple files. Each file +#' contains the data subset for each start date, variable and dataset. Files +#' with different variables and Datasets are stored in separated directories +#' within the following directory tree: destination/Dataset/variable/. +#' The name of each file will be: +#' __.nc. +#'} +#' +#'@examples +#'\dontrun{ +#'data <- lonlat_temp_st$exp$data +#'lon <- lonlat_temp_st$exp$coords$lon +#'lat <- lonlat_temp_st$exp$coords$lat +#'coords <- list(lon = lon, lat = lat) +#'Datasets <- lonlat_temp_st$exp$attrs$Datasets +#'varname <- 'tas' +#'Dates <- lonlat_temp_st$exp$attrs$Dates +#'destination = './' +#'metadata <- lonlat_temp_st$exp$attrs$Variable$metadata +#'SaveExp(data = data, destination = destination, coords = coords, +#' Datasets = Datasets, varname = varname, Dates = Dates, +#' metadata = metadata, single_file = TRUE, ftime_dim = 'ftime', +#' var_dim = 'var', dat_dim = 'dataset') +#'} +#' +#'@import ncdf4 +#'@importFrom s2dv Reorder +#'@import multiApply +#'@importFrom ClimProjDiags Subset +#'@export +SaveExp <- function(data, destination = "./", Dates = NULL, coords = NULL, + varname = NULL, metadata = NULL, Datasets = NULL, + startdates = NULL, dat_dim = 'dataset', sdate_dim = 'sdate', + ftime_dim = 'time', var_dim = 'var', memb_dim = 'member', + drop_dims = NULL, single_file = FALSE, extra_string = NULL, + units_time_since = TRUE) { + ## Initial checks + # data + if (is.null(data)) { + stop("Parameter 'data' cannot be NULL.") + } + dimnames <- names(dim(data)) + if (is.null(dimnames)) { + stop("Parameter 'data' must be an array with named dimensions.") + } + # destination + if (!is.character(destination) | length(destination) > 1) { + stop("Parameter 'destination' must be a character string of one element ", + "indicating the name of the file (including the folder if needed) ", + "where the data will be saved.") + } + # Dates + if (!is.null(Dates)) { + if (!inherits(Dates, "POSIXct") & !inherits(Dates, "Date")) { + stop("Parameter 'Dates' must be of 'POSIXct' or 'Dates' class.") + } + if (is.null(dim(Dates))) { + stop("Parameter 'Dates' must have dimension names.") + } + } + # drop_dims + if (!is.null(drop_dims)) { + if (!is.character(drop_dims) | any(!drop_dims %in% names(dim(data)))) { + warning("Parameter 'drop_dims' must be character string containing ", + "the data dimension names to be dropped. It will not be used.") + } else if (!all(dim(data)[drop_dims] %in% 1)) { + warning("Parameter 'drop_dims' can only contain dimension names ", + "that are of length 1. It will not be used.") + } else { + data <- Subset(x = data, along = drop_dims, + indices = lapply(1:length(drop_dims), function(x) 1), + drop = 'selected') + dimnames <- names(dim(data)) + } + } + # coords + if (!is.null(coords)) { + if (!all(names(coords) %in% dimnames)) { + coords <- coords[-which(!names(coords) %in% dimnames)] + } + for (i_coord in dimnames) { + if (i_coord %in% names(coords)) { + if (length(coords[[i_coord]]) != dim(data)[i_coord]) { + warning(paste0("Coordinate '", i_coord, "' has different lenght as ", + "its dimension and it will not be used.")) + coords[[i_coord]] <- 1:dim(data)[i_coord] + } + } else { + # warning(paste0("Coordinate '", i_coord, "' is not provided ", + # "and it will be set as index in element coords.")) + coords[[i_coord]] <- 1:dim(data)[i_coord] + } + } + } else { + coords <- sapply(dimnames, function(x) 1:dim(data)[x]) + } + # varname + if (is.null(varname)) { + warning("Parameter 'varname' is NULL. It will be assigned to 'X'.") + varname <- 'X' + } else if (length(varname) > 1) { + multiple_vars <- TRUE + } else { + multiple_vars <- FALSE + } + if (!all(sapply(varname, is.character))) { + stop("Parameter 'varname' must be a character string with the ", + "variable names.") + } + # metadata + if (is.null(metadata)) { + warning("Parameter 'metadata' is not provided so the metadata saved ", + "will be incomplete.") + } + # single_file + if (!inherits(single_file, 'logical')) { + warning("Parameter 'single_file' must be a logical value. It will be ", + "set as FALSE.") + single_file <- FALSE + } + # extra_string + if (!is.null(extra_string)) { + if (!is.character(extra_string)) { + stop("Parameter 'extra_string' must be a character string.") + } + } + # units_time_since + if (!is.logical(units_time_since)) { + warning("Parameter 'units_time_since' must be a logical value. It will be ", + "set as TRUE.") + units_time_since <- TRUE + } + + ## Dimensions checks + # Spatial coordinates + if (!any(dimnames %in% .KnownLonNames()) | + !any(dimnames %in% .KnownLatNames())) { + lon_dim <- NULL + lat_dim <- NULL + } else { + lon_dim <- dimnames[which(dimnames %in% .KnownLonNames())] + lat_dim <- dimnames[which(dimnames %in% .KnownLatNames())] + if (length(lon_dim) > 1) { + warning("Found more than one longitudinal dimension. Only the first one ", + "will be used.") + lon_dim <- lon_dim[1] + } + if (length(lat_dim) > 1) { + warning("Found more than one latitudinal dimension. Only the first one ", + "will be used.") + lat_dim <- lat_dim[1] + } + } + # ftime_dim + if (!is.null(ftime_dim)) { + if (!is.character(ftime_dim)) { + stop("Parameter 'ftime_dim' must be a character string.") + } + if (!all(ftime_dim %in% dimnames)) { + stop("Parameter 'ftime_dim' is not found in 'data' dimension.") + } + if (length(ftime_dim) > 1) { + warning("Parameter 'ftime_dim' has length greater than 1 and ", + "only the first element will be used.") + ftime_dim <- ftime_dim[1] + } + } + # sdate_dim + if (!is.null(sdate_dim)) { + if (!is.character(sdate_dim)) { + stop("Parameter 'sdate_dim' must be a character string.") + } + if (length(sdate_dim) > 1) { + warning("Parameter 'sdate_dim' has length greater than 1 and ", + "only the first element will be used.") + sdate_dim <- sdate_dim[1] + } + if (!all(sdate_dim %in% dimnames)) { + stop("Parameter 'sdate_dim' is not found in 'data' dimension.") + } + } + # memb_dim + if (!is.null(memb_dim)) { + if (!is.character(memb_dim)) { + stop("Parameter 'memb_dim' must be a character string.") + } + if (!all(memb_dim %in% dimnames)) { + stop("Parameter 'memb_dim' is not found in 'data' dimension. Set it ", + "as NULL if there is no member dimension.") + } + } + # dat_dim + if (!is.null(dat_dim)) { + if (!is.character(dat_dim)) { + stop("Parameter 'dat_dim' must be a character string.") + } + if (!all(dat_dim %in% dimnames)) { + stop("Parameter 'dat_dim' is not found in 'data' dimension. Set it ", + "as NULL if there is no Datasets dimension.") + } + if (length(dat_dim) > 1) { + warning("Parameter 'dat_dim' has length greater than 1 and ", + "only the first element will be used.") + dat_dim <- dat_dim[1] + } + n_datasets <- dim(data)[dat_dim] + } else { + n_datasets <- 1 + } + # var_dim + if (!is.null(var_dim)) { + if (!is.character(var_dim)) { + stop("Parameter 'var_dim' must be a character string.") + } + if (!all(var_dim %in% dimnames)) { + stop("Parameter 'var_dim' is not found in 'data' dimension. Set it ", + "as NULL if there is no variable dimension.") + } + if (length(var_dim) > 1) { + warning("Parameter 'var_dim' has length greater than 1 and ", + "only the first element will be used.") + var_dim <- var_dim[1] + } + n_vars <- dim(data)[var_dim] + } else { + n_vars <- 1 + } + # minimum dimensions + if (all(dimnames %in% c(var_dim, dat_dim))) { + if (!single_file) { + warning("Parameter data has only ", + paste(c(var_dim, dat_dim), collapse = ' and '), " dimensions ", + "and it cannot be splitted in multiple files. All data will ", + "be saved in a single file.") + single_file <- TRUE + } + } + # Dates dimension check + if (!is.null(Dates)) { + if (all(c(ftime_dim, sdate_dim) %in% names(dim(Dates)))) { + if (any(!names(dim(Dates)) %in% c(ftime_dim, sdate_dim))) { + if (all(dim(Dates)[!names(dim(Dates)) %in% c(ftime_dim, sdate_dim)] == 1)) { + dim(Dates) <- dim(Dates)[names(dim(Dates)) %in% c(ftime_dim, sdate_dim)] + } else { + stop("Parameter 'Dates' must have only sdate_dim and ftime_dim dimensions.") + } + } + if (is.null(startdates)) { + startdates <- Subset(Dates, along = ftime_dim, 1, drop = 'selected') + } else if ((!inherits(startdates, "POSIXct") & !inherits(startdates, "Date")) && + (!is.character(startdates) | (any(nchar(startdates) > 10) | any(nchar(startdates) < 1)))) { + warning("Parameter 'startdates' should be a character string containing ", + "the start dates in the format 'yyyy-mm-dd', 'yyyymmdd', 'yyyymm', ", + "'POSIXct' or 'Dates' class. Files will be named with Dates instead.") + startdates <- Subset(Dates, along = ftime_dim, 1, drop = 'selected') + } + if (!is.null(format(startdates, "%Y%m%d"))) { + startdates <- format(startdates, "%Y%m%d") + } + } else if (any(ftime_dim %in% names(dim(Dates)))) { + if (all(dim(Dates)[!names(dim(Dates)) %in% c(ftime_dim)] == 1)) { + dim(Dates) <- dim(Dates)[names(dim(Dates)) %in% c(ftime_dim, sdate_dim)] + } + } + } + # startdates + if (is.null(startdates)) { + if (is.null(sdate_dim)) { + startdates <- 'XXX' + } else { + startdates <- rep('XXX', dim(data)[sdate_dim]) + } + } else { + if (is.null(sdate_dim)) { + if (length(startdates) != 1) { + warning("Parameter 'startdates' has length more than 1. Only first ", + "value will be used.") + startdates <- startdates[[1]] + } + } + } + # Datasets + if (is.null(Datasets)) { + if (!single_file) { + warning("Parameter 'Datasets' is NULL. Files will be saved with a ", + "directory name of 'XXX'.") + } + Datasets <- rep('XXX', n_datasets ) + } + if (inherits(Datasets, 'list')) { + Datasets <- names(Datasets) + } + if (n_datasets > length(Datasets)) { + warning("Dimension 'Datasets' in 'data' is greater than those listed in ", + "element 'Datasets' and the first element will be reused.") + Datasets <- c(Datasets, rep(Datasets[1], n_datasets - length(Datasets))) + } else if (n_datasets < length(Datasets)) { + warning("Dimension 'Datasets' in 'data' is smaller than those listed in ", + "element 'Datasets' and only the firsts elements will be used.") + Datasets <- Datasets[1:n_datasets] + } + + ## Unknown dimensions check + alldims <- c(dat_dim, var_dim, sdate_dim, lon_dim, lat_dim, memb_dim, ftime_dim) + if (!all(dimnames %in% alldims)) { + unknown_dims <- dimnames[which(!dimnames %in% alldims)] + memb_dim <- c(memb_dim, unknown_dims) + alldims <- c(dat_dim, var_dim, sdate_dim, lon_dim, lat_dim, memb_dim, ftime_dim) + } + # Reorder + if (any(dimnames != alldims)) { + data <- Reorder(data, alldims) + dimnames <- names(dim(data)) + if (!is.null(attr(data, 'dimensions'))) { + attr(data, 'dimensions') <- dimnames + } + } + + ## NetCDF dimensions definition + defined_dims <- NULL + extra_info_dim <- NULL + if (is.null(Dates)) { + filedims <- dimnames[which(!dimnames %in% c(dat_dim, var_dim))] + } else { + filedims <- dimnames[which(!dimnames %in% c(dat_dim, var_dim, sdate_dim, ftime_dim))] + } + for (i_coord in filedims) { + dim_info <- list() + # vals + if (i_coord %in% names(coords)) { + if (is.numeric(coords[[i_coord]])) { + dim_info[['vals']] <- as.vector(coords[[i_coord]]) + } else { + dim_info[['vals']] <- 1:dim(data)[i_coord] + } + } else { + dim_info[['vals']] <- 1:dim(data)[i_coord] + } + # name + dim_info[['name']] <- i_coord + # len + dim_info[['len']] <- as.numeric(dim(data)[i_coord]) + # unlim + dim_info[['unlim']] <- FALSE + # create_dimvar + dim_info[['create_dimvar']] <- TRUE + ## metadata + if (i_coord %in% names(metadata)) { + if ('variables' %in% names(attributes(metadata[[i_coord]]))) { + # from Start: 'lon' or 'lat' + attrs <- attributes(metadata[[i_coord]])[['variables']][[i_coord]] + i_coord_info <- attrs[!sapply(attrs, inherits, 'list')] + } else if (inherits(metadata[[i_coord]], 'list')) { + # from Start and Load: main var + i_coord_info <- metadata[[i_coord]] + } else if (!is.null(attributes(metadata[[i_coord]]))) { + # from Load + i_coord_info <- attributes(metadata[[i_coord]]) + } else { + stop("Metadata is not correct.") + } + # len + if ('size' %in% names(i_coord_info)) { + if (i_coord_info[['size']] != dim(data)[i_coord]) { + dim_info[['original_len']] <- i_coord_info[['size']] + i_coord_info[['size']] <- NULL + } + } + # units + if (!('units' %in% names(i_coord_info))) { + dim_info[['units']] <- '' + } else { + dim_info[['units']] <- i_coord_info[['units']] + i_coord_info[['units']] <- NULL + } + # calendar + if (!('calendar' %in% names(i_coord_info))) { + dim_info[['calendar']] <- NA + } else { + dim_info[['calendar']] <- i_coord_info[['calendar']] + i_coord_info[['calendar']] <- NULL + } + # longname + if ('long_name' %in% names(i_coord_info)) { + dim_info[['longname']] <- i_coord_info[['long_name']] + i_coord_info[['long_name']] <- NULL + } else if ('longname' %in% names(i_coord_info)) { + dim_info[['longname']] <- i_coord_info[['longname']] + i_coord_info[['longname']] <- NULL + } else { + if (i_coord %in% .KnownLonNames()) { + dim_info[['longname']] <- 'longitude' + } else if (i_coord %in% .KnownLatNames()) { + dim_info[['longname']] <- 'latitude' + } + } + # extra information + if (!is.null(names(i_coord_info))) { + extra_info_dim[[i_coord]] <- i_coord_info + } + } else { + # units + dim_info[['units']] <- "adim" + # longname + dim_info[['longname']] <- i_coord + # calendar + dim_info[['calendar']] <- NA + } + new_dim <- list(ncdim_def(name = dim_info[['name']], units = dim_info[['units']], + vals = dim_info[['vals']], unlim = dim_info[['unlim']], + create_dimvar = dim_info[['create_dimvar']], + calendar = dim_info[['calendar']], + longname = dim_info[['longname']])) + names(new_dim) <- i_coord + defined_dims <- c(defined_dims, new_dim) + } + + defined_vars <- list() + if (!single_file) { + for (i in 1:n_datasets) { + path <- file.path(destination, Datasets[i], varname) + for (j in 1:n_vars) { + dir.create(path[j], recursive = TRUE) + startdates <- gsub("-", "", startdates) + dim(startdates) <- c(length(startdates)) + names(dim(startdates)) <- sdate_dim + if (is.null(dat_dim) & is.null(var_dim)) { + data_subset <- data + } else if (is.null(dat_dim)) { + data_subset <- Subset(data, c(var_dim), list(j), drop = 'selected') + } else if (is.null(var_dim)) { + data_subset <- Subset(data, along = c(dat_dim), list(i), drop = 'selected') + } else { + data_subset <- Subset(data, c(dat_dim, var_dim), list(i, j), drop = 'selected') + } + if (is.null(Dates)) { + input_data <- list(data_subset, startdates) + target_dims <- list(c(lon_dim, lat_dim, memb_dim, ftime_dim), NULL) + } else { + input_data <- list(data_subset, startdates, Dates) + target_dims = list(c(lon_dim, lat_dim, memb_dim, ftime_dim), NULL, ftime_dim) + } + Apply(data = input_data, + target_dims = target_dims, + fun = .saveExp, + destination = path[j], + defined_dims = defined_dims, + ftime_dim = ftime_dim, + varname = varname[j], + metadata_var = metadata[[varname[j]]], + extra_info_dim = extra_info_dim, + extra_string = extra_string) + } + } + } else { + # Datasets definition + # From here + if (!is.null(dat_dim)) { + new_dim <- list(ncdim_def(name = dat_dim, units = "adim", + vals = 1 : dim(data)[dat_dim], + longname = 'Datasets', create_dimvar = TRUE)) + names(new_dim) <- dat_dim + defined_dims <- c(new_dim, defined_dims) + extra_info_dim[[dat_dim]] <- list(Datasets = paste(Datasets, collapse = ', ')) + } + first_sdate <- last_sdate <- NULL + save_hours_since <- TRUE + if (!is.null(Dates)) { + if (is.null(sdate_dim)) { + sdates <- Dates[1] + # ftime definition + leadtimes <- as.numeric(Dates - sdates)/3600 + } else { + # sdate definition + sdates <- Subset(Dates, along = ftime_dim, 1, drop = 'selected') + differ <- as.numeric((sdates - sdates[1])/3600) + new_dim <- list(ncdim_def(name = sdate_dim, units = paste('hours since', sdates[1]), + vals = differ, + longname = sdate_dim, create_dimvar = TRUE)) + names(new_dim) <- sdate_dim + defined_dims <- c(defined_dims, new_dim) + first_sdate <- sdates[1] + last_sdate <- sdates[length(sdates)] + # ftime definition + Dates <- Reorder(Dates, c(ftime_dim, sdate_dim)) + differ_ftime <- apply(Dates, 2, function(x){as.numeric((x - x[1])/3600)}) + dim(differ_ftime) <- dim(Dates) + leadtimes <- Subset(differ_ftime, along = sdate_dim, 1, drop = 'selected') + + if (all(apply(differ_ftime, 1, function(x){length(unique(x)) == 1}))) { + if (!units_time_since) save_hours_since <- FALSE + } else { + warning("Time steps are not equal for all start dates. Only ", + "forecast time values for the first start date will be saved ", + "correctly.") + } + } + + if (!save_hours_since) { + # NOTE: Are the units readable by Start? + if (all(diff(leadtimes/24) == 1)) { + # daily values + dim_time <- list(ncdim_def(name = ftime_dim, units = 'days', + vals = round(leadtimes/24) + 1, + calendar = 'proleptic_gregorian', + longname = ftime_dim, unlim = TRUE)) + names(dim_time) <- ftime_dim + defined_dims <- c(defined_dims, dim_time) + } else if (all(diff(leadtimes/24) %in% c(28, 29, 30, 31))) { + # monthly values + dim_time <- list(ncdim_def(name = ftime_dim, units = 'months', + vals = round(leadtimes/730) + 1, + calendar = 'proleptic_gregorian', + longname = ftime_dim, unlim = TRUE)) + names(dim_time) <- ftime_dim + defined_dims <- c(defined_dims, dim_time) + } else { + # other frequency + dim_time <- list(ncdim_def(name = ftime_dim, units = 'hours', + vals = leadtimes + 1, + calendar = 'proleptic_gregorian', + longname = ftime_dim, unlim = TRUE)) + names(dim_time) <- ftime_dim + defined_dims <- c(defined_dims, dim_time) + } + } else { + # Save in units 'hours since' + dim_time <- list(ncdim_def(name = ftime_dim, + units = paste('hours since', + paste(sdates, collapse = ', ')), + vals = leadtimes, + calendar = 'proleptic_gregorian', + longname = ftime_dim, unlim = TRUE)) + names(dim_time) <- ftime_dim + defined_dims <- c(defined_dims, dim_time) + } + } + + # var definition + defined_vars <- list() + extra_info_var <- NULL + for (j in 1:n_vars) { + var_info <- list() + i_var_info <- metadata[[varname[j]]][!sapply(metadata[[varname[j]]], inherits, 'list')] + ## Define metadata + # name + var_info[['name']] <- varname[j] + # units + if ('units' %in% names(i_var_info)) { + var_info[['units']] <- i_var_info[['units']] + i_var_info[['units']] <- NULL + } else { + var_info[['units']] <- '' + } + # dim + var_info[['dim']] <- defined_dims + # missval + if ('missval' %in% names(i_var_info)) { + var_info[['missval']] <- i_var_info[['missval']] + i_var_info[['missval']] <- NULL + } else { + var_info[['missval']] <- NULL + } + # longname + if (any(c('longname', 'long_name') %in% names(i_var_info))) { + longname <- names(i_var_info)[which(names(i_var_info) %in% c('longname', 'long_name'))] + var_info[['longname']] <- i_var_info[[longname]] + i_var_info[[longname]] <- NULL + } else { + var_info[['longname']] <- varname[j] + } + # prec + if ('prec' %in% names(i_var_info)) { + var_info[['prec']] <- i_var_info[['prec']] + i_var_info[['prec']] <- NULL + } else { + prec <- typeof(data) + if (prec == 'character') { + var_info[['prec']] <- 'char' + } + if (any(prec %in% c('short', 'float', 'double', 'integer', 'char', 'byte'))) { + var_info[['prec']] <- prec + } else { + var_info[['prec']] <- 'double' + } + } + # extra information + if (!is.null(names(i_var_info))) { + extra_info_var[[varname[j]]] <- i_var_info + } + new_var <- list(ncvar_def(name = var_info[['name']], + units = var_info[['units']], + dim = var_info[['dim']], + missval = var_info[['missval']], + longname = var_info[['longname']], + prec = var_info[['prec']])) + + names(new_var) <- varname[j] + defined_vars <- c(defined_vars, new_var) + } + if (is.null(extra_string)) { + gsub("-", "", first_sdate) + file_name <- paste0(paste(c(varname, + gsub("-", "", first_sdate), + gsub("-", "", last_sdate)), + collapse = '_'), ".nc") + } else { + nc <- substr(extra_string, nchar(extra_string)-2, nchar(extra_string)) + if (nc == ".nc") { + file_name <- extra_string + } else { + file_name <- paste0(extra_string, ".nc") + } + } + full_filename <- file.path(destination, file_name) + file_nc <- nc_create(full_filename, defined_vars) + if (is.null(var_dim)) { + ncvar_put(file_nc, varname, vals = data) + } else { + for (j in 1:n_vars) { + ncvar_put(file_nc, defined_vars[[j]]$name, + vals = Subset(data, var_dim, j, drop = 'selected')) + } + } + # Additional dimension attributes + for (dim in names(defined_dims)) { + if (dim %in% names(extra_info_dim)) { + for (info_dim in names(extra_info_dim[[dim]])) { + add_info_dim <- paste0(extra_info_dim[[dim]][[info_dim]], collapse = ', ') + ncatt_put(file_nc, dim, info_dim, add_info_dim) + } + } + } + # Additional dimension attributes + for (var in names(defined_vars)) { + if (var %in% names(extra_info_var)) { + for (info_var in names(extra_info_var[[var]])) { + add_info_var <- paste0(extra_info_var[[var]][[info_var]], collapse = ', ') + ncatt_put(file_nc, var, info_var, add_info_var) + } + } + } + nc_close(file_nc) + } +} + +.saveExp <- function(data, startdates = NULL, dates = NULL, destination = "./", + defined_dims, ftime_dim = 'time', varname = 'var', + metadata_var = NULL, extra_info_dim = NULL, + extra_string = NULL) { + # ftime_dim + if (!is.null(dates)) { + differ <- as.numeric((dates - dates[1])/3600) + dim_time <- list(ncdim_def(name = ftime_dim, units = paste('hours since', dates[1]), + vals = differ, calendar = 'proleptic_gregorian', + longname = ftime_dim, unlim = TRUE)) + names(dim_time) <- ftime_dim + defined_dims <- c(defined_dims, dim_time) + } + + ## Define var metadata + var_info <- NULL + extra_info_var <- NULL + i_var_info <- metadata_var[!sapply(metadata_var, inherits, 'list')] + + # name + var_info[['name']] <- varname + # units + if ('units' %in% names(i_var_info)) { + var_info[['units']] <- i_var_info[['units']] + i_var_info[['units']] <- NULL + } else { + var_info[['units']] <- '' + } + # dim + var_info[['dim']] <- defined_dims + # missval + if ('missval' %in% names(i_var_info)) { + var_info[['missval']] <- i_var_info[['missval']] + i_var_info[['missval']] <- NULL + } else { + var_info[['missval']] <- NULL + } + # longname + if (any(c('longname', 'long_name') %in% names(i_var_info))) { + longname <- names(i_var_info)[which(names(i_var_info) %in% c('longname', 'long_name'))] + var_info[['longname']] <- i_var_info[[longname]] + i_var_info[[longname]] <- NULL + } else { + var_info[['longname']] <- varname + } + # prec + if ('prec' %in% names(i_var_info)) { + var_info[['prec']] <- i_var_info[['prec']] + i_var_info[['prec']] <- NULL + } else { + prec <- typeof(data) + if (prec == 'character') { + var_info[['prec']] <- 'char' + } + if (any(prec %in% c('short', 'float', 'double', 'integer', 'char', 'byte'))) { + var_info[['prec']] <- prec + } else { + var_info[['prec']] <- 'double' + } + } + # extra information + if (!is.null(names(i_var_info))) { + extra_info_var <- i_var_info + } + + datanc <- ncvar_def(name = var_info[['name']], + units = var_info[['units']], + dim = var_info[['dim']], + missval = var_info[['missval']], + longname = var_info[['longname']], + prec = var_info[['prec']]) + + if (is.null(extra_string)) { + file_name <- paste0(varname, "_", startdates, ".nc") + } else { + file_name <- paste0(varname, "_", extra_string, "_", startdates, ".nc") + } + full_filename <- file.path(destination, file_name) + file_nc <- nc_create(full_filename, datanc) + ncvar_put(file_nc, datanc, data) + + # Additional attributes + for (dim in names(defined_dims)) { + if (dim %in% names(extra_info_dim)) { + for (info_dim in names(extra_info_dim[[dim]])) { + add_info_dim <- paste0(extra_info_dim[[dim]][[info_dim]], collapse = ', ') + ncatt_put(file_nc, dim, info_dim, add_info_dim) + } + } + } + # Additional dimension attributes + if (!is.null(extra_info_var)) { + for (info_var in names(extra_info_var)) { + add_info_var <- paste0(extra_info_var[[info_var]], collapse = ', ') + ncatt_put(file_nc, varname, info_var, add_info_var) + } + } + + nc_close(file_nc) +} diff --git a/modules/Saving/Saving.R b/modules/Saving/Saving.R index fc9fe4ee..60e886b9 100644 --- a/modules/Saving/Saving.R +++ b/modules/Saving/Saving.R @@ -14,6 +14,8 @@ source("modules/Saving/R/get_time.R") source("modules/Saving/R/get_latlon.R") source("modules/Saving/R/get_global_attributes.R") source("modules/Saving/R/drop_dims.R") +source("modules/Saving/R/save_metrics_scorecards.R") +source("modules/Saving/R/tmp/CST_SaveExp.R") Saving <- function(recipe, data, skill_metrics = NULL, diff --git a/modules/Skill/Skill.R b/modules/Skill/Skill.R index d3f60d4e..355acab5 100644 --- a/modules/Skill/Skill.R +++ b/modules/Skill/Skill.R @@ -366,8 +366,13 @@ Skill <- function(recipe, data, agg = 'global') { if (recipe$Analysis$Workflow$Skill$save == 'all') { corr_metric_names <- grep("^corr_individual_members", names(skill_metrics)) if (length(corr_metric_names) == 0) { - save_metrics(recipe = recipe, skill = skill_metrics, - data_cube = data$hcst, agg = agg) + if (tolower(recipe$Analysis$Output_format) == 'scorecards') { + save_metrics_scorecards(recipe = recipe, skill = skill_metrics, + data_cube = data$hcst, agg = agg) + } else { + save_metrics(recipe = recipe, skill = skill_metrics, + data_cube = data$hcst, agg = agg) + } } else { # Save corr if (length(skill_metrics[corr_metric_names]) > 0) { @@ -376,8 +381,13 @@ Skill <- function(recipe, data, agg = 'global') { } # Save other skill metrics if (length(skill_metrics[-corr_metric_names]) > 0) { - save_metrics(recipe = recipe, skill = skill_metrics[-corr_metric_names], - data_cube = data$hcst, agg = agg) + if (tolower(recipe$Analysis$Output_format) == 'scorecards') { + save_metrics_scorecards(recipe = recipe, skill = skill_metrics[-corr_metric_names], + data_cube = data$hcst, agg = agg) + } else { + save_metrics(recipe = recipe, skill = skill_metrics[-corr_metric_names], + data_cube = data$hcst, agg = agg) + } } } } -- GitLab From 5d5cfb65d61fc5737277524026f718c5fb7b7828 Mon Sep 17 00:00:00 2001 From: aho Date: Wed, 15 Nov 2023 17:01:30 +0100 Subject: [PATCH 08/78] Copy and paste the recipe reference --- .../ex1_2-recipe.yml | 105 ++++++++++++++++++ 1 file changed, 105 insertions(+) create mode 100644 use_cases/ex1_2_autosubmit_scorecards/ex1_2-recipe.yml diff --git a/use_cases/ex1_2_autosubmit_scorecards/ex1_2-recipe.yml b/use_cases/ex1_2_autosubmit_scorecards/ex1_2-recipe.yml new file mode 100644 index 00000000..2de4bd48 --- /dev/null +++ b/use_cases/ex1_2_autosubmit_scorecards/ex1_2-recipe.yml @@ -0,0 +1,105 @@ +################################################################################ +## RECIPE DESCRIPTION +################################################################################ + +Description: + Author: V. Agudetse + Info: Test for recipe splitting + +################################################################################ +## ANALYSIS CONFIGURATION +################################################################################ + +Analysis: + Horizon: Seasonal + Variables: # ECVs and Indicators? + - {name: tas, freq: monthly_mean} + Datasets: + System: # multiple systems for single model, split if Multimodel = F + - {name: ECMWF-SEAS5} + Multimodel: False # single option + Reference: + - {name: ERA5} # multiple references for single model? + Time: + sdate: # list, split + - '0101' + - '0201' + - '0301' + - '0401' + - '0501' + - '0601' + - '0701' + - '0801' + - '0901' + - '1001' + - '1101' + - '1201' + fcst_year: + hcst_start: '1993' # single option + hcst_end: '2003' # single option + ftime_min: 1 # single option + ftime_max: 6 # single option + Region: # multiple lists, split? Add region name if length(Region) > 1 + - {name: "global", latmin: -90, latmax: 90, lonmin: 0, lonmax: 359.9} + Regrid: + method: bilinear ## TODO: allow multiple methods? + type: to_system + Workflow: + Anomalies: + compute: yes + cross_validation: no + save: 'none' + Calibration: + method: raw ## TODO: list, split? + save: 'none' + Skill: + metric: mean_bias EnsCorr rps rpss crps crpss EnsSprErr # list, don't split + cross_validation: yes + save: 'all' + Probabilities: + percentiles: [[1/3, 2/3]] # list, don't split + save: 'none' + # Visualization: + # plots: skill_metrics + Scorecards: + execute: yes # yes/no + regions: + Extra-tropical NH: {lon.min: 0, lon.max: 360, lat.min: 30, lat.max: 90} + Tropics: {lon.min: 0, lon.max: 360, lat.min: -30, lat.max: 30} + Extra-tropical SH : {lon.min: 0, lon.max: 360, lat.min: -30, lat.max: -90} + start_months: NULL + metric: mean_bias enscorr rpss crpss enssprerr + metric_aggregation: 'score' + table_label: NULL + fileout_label: NULL + col1_width: NULL + col2_width: NULL + calculate_diff: FALSE + ncores: 14 + remove_NAs: no # bool, don't split + Output_format: Scorecards # string, don't split + +################################################################################ +## Run CONFIGURATION +################################################################################ +Run: + Loglevel: INFO + Terminal: yes + output_dir: /esarchive/scratch/vagudets/auto-s2s-outputs/ + code_dir: /esarchive/scratch/vagudets/repos/auto-s2s/ + autosubmit: yes + # fill only if using autosubmit + auto_conf: + script: /esarchive/scratch/vagudets/repos/auto-s2s/example_scripts/test_scorecards_workflow.R # replace with the path to your script + expid: a6ae # replace with your EXPID + hpc_user: bsc32762 # replace with your hpc username + wallclock: 03:00 # hh:mm + processors_per_job: 14 + platform: nord3v2 + custom_directives: ['#SBATCH --exclusive'] + email_notifications: yes # enable/disable email notifications. Change it if you want to. + email_address: victoria.agudetse@bsc.es # replace with your email address + notify_completed: yes # notify me by email when a job finishes + notify_failed: no # notify me by email when a job fails + + -- GitLab From 7d152eb3ec602443fd58931fd5725caacd3fbf7d Mon Sep 17 00:00:00 2001 From: Nadia Milders Date: Thu, 16 Nov 2023 12:07:16 +0100 Subject: [PATCH 09/78] changed statistics outpt structure --- modules/Skill/Skill.R | 2 +- modules/Statistics/Statistics.R | 9 ++++++--- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/modules/Skill/Skill.R b/modules/Skill/Skill.R index 355acab5..6c066ff5 100644 --- a/modules/Skill/Skill.R +++ b/modules/Skill/Skill.R @@ -385,7 +385,7 @@ Skill <- function(recipe, data, agg = 'global') { save_metrics_scorecards(recipe = recipe, skill = skill_metrics[-corr_metric_names], data_cube = data$hcst, agg = agg) } else { - save_metrics(recipe = recipe, skill = skill_metrics[-corr_metric_names], + save_metrics_scorecards(recipe = recipe, skill = skill_metrics[-corr_metric_names], data_cube = data$hcst, agg = agg) } } diff --git a/modules/Statistics/Statistics.R b/modules/Statistics/Statistics.R index 40f1889b..fe36c4ce 100644 --- a/modules/Statistics/Statistics.R +++ b/modules/Statistics/Statistics.R @@ -46,7 +46,9 @@ compute_statistics <- function(recipe, data, agg = 'global'){ target_dims = c(time_dim, memb_dim), fun = 'sd')$output1 - statistics[[ stat ]] <- list('std_hcst' = std_hcst, 'std_obs' = std_obs) + statistics[[ 'std_hcst' ]] <- std_hcst + statistics[[ 'std_obs' ]] <- std_obs + } ## close if on std @@ -61,7 +63,8 @@ compute_statistics <- function(recipe, data, agg = 'global'){ target_dims = c(time_dim, memb_dim), fun = 'sd')$output1)^2 - statistics[[ stat ]] <- list('var_hcst' = var_hcst, 'var_obs' = var_obs) + statistics[[ 'var_hcst' ]] <- var_hcst + statistics[[ 'var_obs' ]] <- var_obs } ## close if on var @@ -79,7 +82,7 @@ compute_statistics <- function(recipe, data, agg = 'global'){ if (recipe$Analysis$Workflow$Statistics$save == 'all') { # Save all statistics - save_metrics(recipe = recipe, skill = statistics, ## Not able to save data with these dimensions + save_metrics_scorecards(recipe = recipe, skill = statistics, ## Not able to save data with these dimensions data_cube = data$hcst, agg = agg) ## The length of parameter 'order' should be the same with the dimension length of parameter 'data'. } -- GitLab From 3256eeb3e7b56d14f0c723bc736d2caeeaf2581d Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Thu, 16 Nov 2023 14:47:39 +0100 Subject: [PATCH 10/78] Set locale to English --- tools/libs.R | 2 ++ 1 file changed, 2 insertions(+) diff --git a/tools/libs.R b/tools/libs.R index 3b855a77..2c034dd3 100644 --- a/tools/libs.R +++ b/tools/libs.R @@ -41,3 +41,5 @@ source("tools/restructure_recipe.R") # Settings options(bitmapType = 'cairo') pdf(NULL) +Sys.setlocale("LC_MESSAGES", 'en_GB.UTF-8') + -- GitLab From 092e04edf1a01986a8e765b744e2963391b07a7a Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Thu, 16 Nov 2023 15:23:31 +0100 Subject: [PATCH 11/78] Change LC_MESSAGES to LC_ALL --- tools/libs.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tools/libs.R b/tools/libs.R index 2c034dd3..40146786 100644 --- a/tools/libs.R +++ b/tools/libs.R @@ -41,5 +41,5 @@ source("tools/restructure_recipe.R") # Settings options(bitmapType = 'cairo') pdf(NULL) -Sys.setlocale("LC_MESSAGES", 'en_GB.UTF-8') +Sys.setlocale("LC_ALL", 'en_GB.UTF-8') -- GitLab From b82ae165cb10e2e70b28bb7326866f1fa65c89f0 Mon Sep 17 00:00:00 2001 From: PALOMA TRASCASA CASTRO Date: Thu, 16 Nov 2023 17:30:15 +0100 Subject: [PATCH 12/78] Added command to specify English language --- modules/Visualization/R/plot_most_likely_terciles_map.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/Visualization/R/plot_most_likely_terciles_map.R b/modules/Visualization/R/plot_most_likely_terciles_map.R index abd08f7b..5d60f8c1 100644 --- a/modules/Visualization/R/plot_most_likely_terciles_map.R +++ b/modules/Visualization/R/plot_most_likely_terciles_map.R @@ -109,7 +109,7 @@ plot_most_likely_terciles <- function(recipe, "\n", "Most Likely Tercile / Initialization: ", i_syear) months <- lubridate::month(fcst$attrs$Dates[1, 1, which(start_date == i_syear), ], - label = T, abb = F) + label = T, abb = F,locale = "en_GB") years <- lubridate::year(fcst$attrs$Dates[1, 1, which(start_date == i_syear), ]) if (recipe$Analysis$Workflow$Visualization$multi_panel) { ## TODO: Ensure this works for daily and sub-daily cases -- GitLab From 74f3370459d7ea43582c0b31dbe5c3717742cf2d Mon Sep 17 00:00:00 2001 From: Nadia Milders Date: Mon, 20 Nov 2023 11:20:21 +0100 Subject: [PATCH 13/78] Tas-tos data blending development --- conf/archive.yml | 7 +- conf/variable-dictionary.yml | 13 +- modules/Loading/Loading.R | 9 +- modules/Loading/R/load_tas_tos.R | 513 ++++++++++++++++++ modules/Loading/R/mask_tas_tos.R | 65 +-- .../atomic_recipes/recipe_tas-tos_nadia.yml | 55 ++ .../recipe-seasonal_monthly_1_tas-tos.yml | 56 ++ .../testthat/test-seasonal_monthly_tas-tos.R | 98 ++++ tools/check_recipe.R | 12 + tools/prepare_outputs.R | 8 +- 10 files changed, 780 insertions(+), 56 deletions(-) create mode 100644 modules/Loading/R/load_tas_tos.R create mode 100644 recipes/atomic_recipes/recipe_tas-tos_nadia.yml create mode 100644 tests/recipes/recipe-seasonal_monthly_1_tas-tos.yml create mode 100644 tests/testthat/test-seasonal_monthly_tas-tos.R diff --git a/conf/archive.yml b/conf/archive.yml index 0b643ae9..cca68c22 100644 --- a/conf/archive.yml +++ b/conf/archive.yml @@ -21,13 +21,14 @@ esarchive: "ta850":"monthly_mean/ta850_f12h/", "g300":"monthly_mean/g300_f12h/", "g500":"monthly_mean/g500_f12h/", "g850":"monthly_mean/g500_f12h/", "tdps":"monthly_mean/tdps_f6h/", "psl":"monthly_mean/psl_f6h/", - "tos":"monthly_mean/tos_f6h/"} + "tos":"monthly_mean/tos_f6h/", "sic":"monthly_mean/sic_f24h/"} nmember: fcst: 51 hcst: 25 calendar: "proleptic_gregorian" time_stamp_lag: "0" reference_grid: "/esarchive/exp/ecmwf/system5c3s/monthly_mean/tas_f6h/tas_20180501.nc" + land_sea_mask: "/esarchive/exp/ecmwf/system5c3s/constant/lsm/lsm.nc" ECMWF-SEAS5.1: name: "ECMWF SEAS5 (v5.1)" institution: "European Centre for Medium-Range Weather Forecasts" @@ -165,9 +166,11 @@ esarchive: "ta300":"montly_mean/ta300_f1h-r1440x721cds/", "ta500":"monthly_mean/ta500_f1h-r1440x721cds/", "ta850":"monthly_mean/ta850_f1h-r1440x721cds/", - "tos":"monthly_mean/tos_f1h-r1440x721cds/"} + "tos":"monthly_mean/tos_f1h-r1440x721cds/", + "sic":"monthly_mean/sic_f1h-r1440x721cds/"} calendar: "standard" reference_grid: "/esarchive/recon/ecmwf/era5/monthly_mean/tas_f1h-r1440x721cds/tas_201805.nc" + land_sea_mask: "/esarchive/recon/ecmwf/era5/constant/lsm-r1440x721cds/sftof.nc" ERA5-Land: name: "ERA5-Land" institution: "European Centre for Medium-Range Weather Forecasts" diff --git a/conf/variable-dictionary.yml b/conf/variable-dictionary.yml index 0bfbffe0..c440eac1 100644 --- a/conf/variable-dictionary.yml +++ b/conf/variable-dictionary.yml @@ -204,13 +204,16 @@ vars: long_name: "Surface Upward Sensible Heat Flux" standard_name: "surface_upward_sensible_heat_flux" accum: no -## Adding new variable - tasanomaly: + tas-tos: units: "K" - long_name: "Near-Surface Air Temperature Anomaly" - standard_name: "air_temperature_anom" + long_name: "Blended air - sea temperature" + standard_name: "air_sea_temperature" + accum: no + sic: + units: "1" + long_name: "Sea Ice Concentration" + standard_name: "sea_ice_concentration" accum: no - # Coordinates diff --git a/modules/Loading/Loading.R b/modules/Loading/Loading.R index 315ef78d..43dea065 100644 --- a/modules/Loading/Loading.R +++ b/modules/Loading/Loading.R @@ -12,8 +12,13 @@ Loading <- function(recipe) { # Case: esarchive time_horizon <- tolower(recipe$Analysis$Horizon) if (time_horizon == "seasonal") { - source("modules/Loading/R/load_seasonal.R") - data <- load_seasonal(recipe) + if(recipe$Analysis$Variables$name == 'tas-tos') { + source("modules/Loading/R/load_tas_tos.R") + data <- load_tas_tos(recipe) + } else { + source("modules/Loading/R/load_seasonal.R") + data <- load_seasonal(recipe) + } } else if (time_horizon == "decadal") { source("modules/Loading/R/load_decadal.R") data <- load_decadal(recipe) diff --git a/modules/Loading/R/load_tas_tos.R b/modules/Loading/R/load_tas_tos.R new file mode 100644 index 00000000..5e6b8837 --- /dev/null +++ b/modules/Loading/R/load_tas_tos.R @@ -0,0 +1,513 @@ +source("/esarchive/scratch/vagudets/repos/csoperational/R/get_regrid_params.R") +# Load required libraries/funs +source("modules/Loading/R/dates2load.R") +source("modules/Loading/R/get_timeidx.R") +source("modules/Loading/R/check_latlon.R") +source('modules/Loading/R/mask_tas_tos.R') + + +load_tas_tos <- function(recipe) { + + # ------------------------------------------- + # Set params ----------------------------------------- + + hcst.inityear <- recipe$Analysis$Time$hcst_start + hcst.endyear <- recipe$Analysis$Time$hcst_end + lats.min <- recipe$Analysis$Region$latmin + lats.max <- recipe$Analysis$Region$latmax + lons.min <- recipe$Analysis$Region$lonmin + lons.max <- recipe$Analysis$Region$lonmax + ref.name <- recipe$Analysis$Datasets$Reference$name + exp.name <- recipe$Analysis$Datasets$System$name + + variable <- c("tas", "tos", "sic") + store.freq <- recipe$Analysis$Variables$freq + + if(is.null(recipe$Analysis$Variables$sic_threshold)){ + sic.threshold = 0.15 + } else { + sic.threshold <- recipe$Analysis$Variables$sic_threshold + } + + data_order <- c('dat', 'var', 'sday', 'sweek', 'syear', 'time', 'latitude', 'longitude', 'ensemble') + + + # get sdates array + ## LOGGER: Change dates2load to extract logger from recipe? + sdates <- dates2load(recipe, recipe$Run$logger) + + idxs <- NULL + idxs$hcst <- get_timeidx(sdates$hcst, + recipe$Analysis$Time$ftime_min, + recipe$Analysis$Time$ftime_max, + time_freq=store.freq) + + if (!(is.null(sdates$fcst))) { + idxs$fcst <- get_timeidx(sdates$fcst, + recipe$Analysis$Time$ftime_min, + recipe$Analysis$Time$ftime_max, + time_freq=store.freq) + } + + # get esarchive datasets dict: + archive <- read_yaml("conf/archive.yml")[[recipe$Run$filesystem]] + exp_descrip <- archive$System[[exp.name]] + + freq.hcst <- unlist(exp_descrip[[store.freq]][variable[1]]) + reference_descrip <- archive$Reference[[ref.name]] + freq.obs <- unlist(reference_descrip[[store.freq]][variable[1]]) + obs.dir <- reference_descrip$src + fcst.dir <- exp_descrip$src + hcst.dir <- exp_descrip$src + fcst.nmember <- exp_descrip$nmember$fcst + hcst.nmember <- exp_descrip$nmember$hcst + + var_dir_obs <- reference_descrip[[store.freq]][variable] + var_dir_exp <- exp_descrip[[store.freq]][variable] + + # ----------- + obs.path <- paste0(archive$src, obs.dir, "$var_dir$", + "$var$_$file_date$.nc") + + hcst.path <- paste0(archive$src, hcst.dir, "$var_dir$", + "$var$_$file_date$.nc") + + fcst.path <- paste0(archive$src, hcst.dir, "$var_dir$", + "/$var$_$file_date$.nc") + + # Define regrid parameters: + #------------------------------------------------------------------- + regrid_params <- get_regrid_params(recipe, archive) + + # Longitude circular sort and latitude check + #------------------------------------------------------------------- + circularsort <- check_latlon(lats.min, lats.max, lons.min, lons.max) + + if (recipe$Analysis$Variables$freq == "monthly_mean"){ + split_multiselected_dims = TRUE + } else { + split_multiselected_dims = FALSE + } + + # Load hindcast data without regrid + #------------------------------------------------------------------- + hcst <- Start(dat = hcst.path, + var = variable, + var_dir = var_dir_exp, + file_date = sdates$hcst, + time = idxs$hcst, + var_dir_depends = 'var', + latitude = values(list(lats.min, lats.max)), + latitude_reorder = Sort(decreasing = TRUE), + longitude = values(list(lons.min, lons.max)), + longitude_reorder = circularsort, + synonims = list(latitude = c('lat', 'latitude'), + longitude = c('lon', 'longitude'), + ensemble = c('member', 'ensemble')), + ensemble = indices(1:hcst.nmember), + metadata_dims = 'var', # change to just 'var'? + return_vars = list(latitude = 'dat', + longitude = 'dat', + time = 'file_date'), + split_multiselected_dims = split_multiselected_dims, + retrieve = TRUE) + + + # Remove var_dir dimension + if ("var_dir" %in% names(dim(hcst))) { + hcst <- Subset(hcst, along = "var_dir", indices = 1, drop = "selected") + } + + if (recipe$Analysis$Variables$freq == "daily_mean") { + # Adjusts dims for daily case, could be removed if startR allows + # multidim split + names(dim(hcst))[which(names(dim(hcst)) == 'file_date')] <- "syear" + default_dims <- c(dat = 1, var = 1, sday = 1, + sweek = 1, syear = 1, time = 1, + latitude = 1, longitude = 1, ensemble = 1) + default_dims[names(dim(hcst))] <- dim(hcst) + dim(hcst) <- default_dims + # Change time attribute dimensions + default_time_dims <- c(sday = 1, sweek = 1, syear = 1, time = 1) + names(dim(attr(hcst, "Variables")$common$time))[which(names( + dim(attr(hcst, "Variables")$common$time)) == 'file_date')] <- "syear" + default_time_dims[names(dim(attr(hcst, "Variables")$common$time))] <- + dim(attr(hcst, "Variables")$common$time) + dim(attr(hcst, "Variables")$common$time) <- default_time_dims + } + + # Define sea-ice grid points based of sea-ice concentration threshold + ice_hcst <- hcst[,3,,,,,,,] >= sic.threshold + + # Replace Tos with Tas for data points with sea ice + hcst[,2,,,,,,,][ice_hcst] <- hcst[,1,,,,,,,][ice_hcst] + + + # Convert hcst to s2dv_cube object + ## TODO: Give correct dimensions to $Dates + ## (sday, sweek, syear instead of file_date) + hcst <- as.s2dv_cube(hcst) + # Adjust dates for models where the time stamp goes into the next month + if (recipe$Analysis$Variables$freq == "monthly_mean") { + hcst$attrs$Dates[] <- hcst$attrs$Dates - seconds(exp_descrip$time_stamp_lag) + } + + # Combine hcst tas and tos data + #------------------------------------------------------------------- + + hcst <- mask_tas_tos(input_data = hcst, region = c(lons.min, lons.max,lats.min, lats.max), + mask_path = archive$System[[exp.name]]$land_sea_mask, lsm_var_name = 'lsm', + lon = hcst$coords$longitude, lat = hcst$coords$latitude, + lon_dim = 'longitude', lat_dim = 'latitude', ncores = NULL) + + hcst$dims[['var']] <- dim(hcst$data)[['var']] + hcst$attrs$Variable$varName <- 'tas-tos' + + hcst$data <- Reorder(hcst$data, data_order) + + # Load forecast data without regrid + #------------------------------------------------------------------- + if (!is.null(recipe$Analysis$Time$fcst_year)) { + # the call uses file_date instead of fcst_syear so that it can work + # with the daily case and the current version of startR not allowing + # multiple dims split + + fcst <- Start(dat = fcst.path, + var = variable, + var_dir = var_dir_exp, + var_dir_depends = 'var', + file_date = sdates$fcst, + time = idxs$fcst, + latitude = values(list(lats.min, lats.max)), + latitude_reorder = Sort(decreasing = TRUE), + longitude = values(list(lons.min, lons.max)), + longitude_reorder = circularsort, + synonims = list(latitude = c('lat', 'latitude'), + longitude = c('lon', 'longitude'), + ensemble = c('member', 'ensemble')), + ensemble = indices(1:fcst.nmember), + metadata_dims = 'var', + return_vars = list(latitude = 'dat', + longitude = 'dat', + time = 'file_date'), + split_multiselected_dims = split_multiselected_dims, + retrieve = TRUE) + + if ("var_dir" %in% names(dim(fcst))) { + fcst <- Subset(fcst, along = "var_dir", indices = 1, drop = "selected") + } + + if (recipe$Analysis$Variables$freq == "daily_mean") { + # Adjusts dims for daily case, could be removed if startR allows + # multidim split + names(dim(fcst))[which(names(dim(fcst)) == 'file_date')] <- "syear" + default_dims <- c(dat = 1, var = 1, sday = 1, + sweek = 1, syear = 1, time = 1, + latitude = 1, longitude = 1, ensemble = 1) + default_dims[names(dim(fcst))] <- dim(fcst) + dim(fcst) <- default_dims + # Change time attribute dimensions + default_time_dims <- c(sday = 1, sweek = 1, syear = 1, time = 1) + names(dim(attr(fcst, "Variables")$common$time))[which(names( + dim(attr(fcst, "Variables")$common$time)) == 'file_date')] <- "syear" + default_time_dims[names(dim(attr(fcst, "Variables")$common$time))] <- + dim(attr(fcst, "Variables")$common$time) + dim(attr(fcst, "Variables")$common$time) <- default_time_dims + } + + # Define sea-ice grid points based of sea-ice concentration threshold + ice_fcst <- fcst[,3,,,,,,,] >= sic.threshold + + # Replace Tos with Tas for datapoints with sea ice + fcst[,2,,,,,,,][ice_fcst] <- fcst[,1,,,,,,,][ice_fcst] + + + # Convert fcst to s2dv_cube + fcst <- as.s2dv_cube(fcst) + # Adjust dates for models where the time stamp goes into the next month + if (recipe$Analysis$Variables$freq == "monthly_mean") { + fcst$attrs$Dates[] <- + fcst$attrs$Dates - seconds(exp_descrip$time_stamp_lag) + } + + # Combine fcst tas and tos data + #------------------------------------------------------------------- + + fcst <- mask_tas_tos(input_data = fcst, region = c(lons.min, lons.max,lats.min, lats.max), + mask_path = archive$System[[exp.name]]$land_sea_mask, lsm_var_name = 'lsm', + lon = fcst$coords$longitude, lat = fcst$coords$latitude, + lon_dim = 'longitude', lat_dim = 'latitude', ncores = NULL) + + fcst$dims[['var']] <- dim(fcst$data)[['var']] + fcst$attrs$Variable$varName <- 'tas-tos' + + fcst$data <- Reorder(fcst$data, data_order) + + } else { + fcst <- NULL + } + + # Load obs data without regrid + #------------------------------------------------------------------- + + # Obtain dates and date dimensions from the loaded hcst data to make sure + # the corresponding observations are loaded correctly. + dates <- hcst$attrs$Dates + dim(dates) <- hcst$dims[c("sday", "sweek", "syear", "time")] + + # Separate Start() call for monthly vs daily data + if (store.freq == "monthly_mean") { + + dates_file <- format(as.Date(dates, '%Y%m%d'), "%Y%m") + dim(dates_file) <- dim(dates) + + + # Define variables for blended tas-tos datasets + if (recipe$Analysis$Datasets$Reference$name == 'BEST'){ + variable <- 'tas' + var_dir_obs <- reference_descrip[[store.freq]][variable] + } + + obs <- Start(dat = obs.path, + var = variable, + var_dir = var_dir_obs, + var_dir_depends = 'var', + file_date = dates_file, + latitude = values(list(lats.min, lats.max)), + latitude_reorder = Sort(decreasing = TRUE), + longitude = values(list(lons.min, lons.max)), + longitude_reorder = circularsort, + synonims = list(latitude = c('lat','latitude'), + longitude = c('lon','longitude')), + metadata_dims = 'var', + return_vars = list(latitude = 'dat', + longitude = 'dat', + time = 'file_date'), + split_multiselected_dims = TRUE, + retrieve = TRUE) + + + } else if (store.freq == "daily_mean") { + + # Get year and month for file_date + dates_file <- sapply(dates, format, '%Y%m') + dim(dates_file) <- dim(dates) + # Set hour to 12:00 to ensure correct date retrieval for daily data + lubridate::hour(dates) <- 12 + lubridate::minute(dates) <- 00 + # Restore correct dimensions + dim(dates) <- dim(dates_file) + + obs <- Start(dat = obs.path, + var = variable, + var_dir = var_dir_obs, + var_dir_depends = 'var', + file_date = sort(unique(dates_file)), + time = dates, + time_var = 'time', + time_across = 'file_date', + merge_across_dims = TRUE, + merge_across_dims_narm = TRUE, + latitude = values(list(lats.min, lats.max)), + latitude_reorder = Sort(decreasing = TRUE), + longitude = values(list(lons.min, lons.max)), + longitude_reorder = circularsort, + synonims = list(latitude = c('lat','latitude'), + longitude = c('lon','longitude')), + metadata_dims = 'var', + return_vars = list(latitude = 'dat', + longitude = 'dat', + time = 'file_date'), + split_multiselected_dims = TRUE, + retrieve = TRUE) + + } + + # Remove var_dir dimension + if ("var_dir" %in% names(dim(obs))) { + obs <- Subset(obs, along = "var_dir", indices = 1, drop = "selected") + } + # Adds ensemble dim to obs (for consistency with hcst/fcst) + default_dims <- c(dat = 1, var = 1, sday = 1, + sweek = 1, syear = 1, time = 1, + latitude = 1, longitude = 1, ensemble = 1) + default_dims[names(dim(obs))] <- dim(obs) + dim(obs) <- default_dims + + if(!recipe$Analysis$Datasets$Reference$name %in% c('HadCRUT4','HadCRUT5','BEST','GISTEMPv4')){ + + # Define sea-ice grid points based of sea-ice concentration threshold + ice_obs <- (obs[,3,,,,,,,]) >= sic.threshold + + # Replace NA values with False + ice_obs[is.na(ice_obs)] <- FALSE + + # Replace Tos with Tas for datapoints with sea ice + obs[,2,,,,,,,][ice_obs] <- obs[,1,,,,,,,][ice_obs] + } + + # Convert obs to s2dv_cube + obs <- as.s2dv_cube(obs) + + + # Combine obs tas and tos data + #------------------------------------------------------------------- + ## TODO: Ask about this list + if(!recipe$Analysis$Datasets$Reference$name %in% c('HadCRUT4','HadCRUT5','BEST','GISTEMPv4')){ + + obs <- mask_tas_tos(input_data = obs, region = c(lons.min, lons.max,lats.min, lats.max), + mask_path = archive$Reference[[ref.name]]$land_sea_mask, lsm_var_name = 'sftof', + lon = obs$coords$longitude, lat = obs$coords$latitude, + lon_dim = 'longitude', lat_dim = 'latitude', ncores = NULL) + + obs$dims[['var']] <- dim(obs$data)[['var']] + obs$attrs$Variable$varName <- 'tas-tos' + + } ## close if on reference name + + obs$data <- Reorder(obs$data, data_order) + + + # Regrid data + #------------------------------------------------------------------- + + # Regrid reference to system grid: + if(recipe$Analysis$Regrid$type == 'to_system'){ + + aux <- CDORemap(data_array = obs$data, ## Not regridding to desired grid when latitudes are ordered descending + lons = obs$coords$longitude, + lats = obs$coords$latitude, + grid = regrid_params$obs.gridtype, + method = recipe$Analysis$Regrid$method, + avoid_writes = TRUE, + crop = c(lons.min, lons.max,lats.min, lats.max), + force_remap = TRUE) + + obs$data <- aux$data_array + obs$coords$longitude <- aux$lons + obs$coords$latitude <- aux$lats + obs$dims['longitude'] <- dim(aux$data_array)['longitude'] + obs$dims['latitude'] <- dim(aux$data_array)['latitude'] + rm(aux) + } + + # Regrid system to reference grid: + if(recipe$Analysis$Regrid$type == 'to_reference'){ + + aux <- CDORemap(data_array = hcst$data, + lons = hcst$coords$longitude, lats = hcst$coords$latitude, + grid = regrid_params$fcst.gridtype, method = recipe$Analysis$Regrid$method, + avoid_writes = TRUE, crop = TRUE, + force_remap = TRUE) + + hcst$data <- aux$data_array + hcst$coords$longitude <- aux$lons + hcst$coords$latitude <- aux$lats + hcst$dims['longitude'] <- dim(aux$data_array)['longitude'] + hcst$dims['latitude'] <- dim(aux$data_array)['latitude'] + rm(aux) + + if (!is.null(recipe$Analysis$Time$fcst_year)) { + aux <- CDORemap(data_array = fcst$data, + lons = fcst$coords$longitude, + lats = fcst$coords$latitude, + grid = regrid_params$fcst.gridtype, + method = recipe$Analysis$Regrid$method, + avoid_writes = TRUE, crop = TRUE, + force_remap = TRUE) + + fcst$data <- aux$data_array + fcst$coords$longitude <- aux$lons + fcst$coords$latitude <- aux$lats + fcst$dims['longitude'] <- dim(aux$data_array)['longitude'] + fcst$dims['latitude'] <- dim(aux$data_array)['latitude'] + rm(aux) + } + } + + # Regrid all data to user defined grid: + if(!recipe$Analysis$Regrid$type %in% c('to_system','to_reference')){ + + aux <- CDORemap(data_array = hcst$data, + lons = hcst$coords$longitude, lats = hcst$coords$latitude, + grid = regrid_params$fcst.gridtype, method = recipe$Analysis$Regrid$method, + avoid_writes = TRUE, crop = TRUE, + force_remap = TRUE) + + hcst$data <- aux$data_array + hcst$coords$longitude <- aux$lons + hcst$coords$latitude <- aux$lats + hcst$dims['longitude'] <- dim(aux$data_array)['longitude'] + hcst$dims['latitude'] <- dim(aux$data_array)['latitude'] + rm(aux) + + if (!is.null(recipe$Analysis$Time$fcst_year)) { + aux <- CDORemap(data_array = fcst$data, + lons = fcst$coords$longitude, + lats = fcst$coords$latitude, + grid = regrid_params$fcst.gridtype, + method = recipe$Analysis$Regrid$method, + avoid_writes = TRUE, crop = TRUE, + force_remap = TRUE) + + fcst$data <- aux$data_array + fcst$coords$longitude <- aux$lons + fcst$coords$latitude <- aux$lats + fcst$dims['longitude'] <- dim(aux$data_array)['longitude'] + fcst$dims['latitude'] <- dim(aux$data_array)['latitude'] + rm(aux) + } + + aux <- CDORemap(data_array = obs$data, + lons = obs$coords$longitude, + lats = obs$coords$latitude, + grid = regrid_params$obs.gridtype, + method = recipe$Analysis$Regrid$method, + avoid_writes = TRUE, crop = TRUE, + force_remap = TRUE) + + obs$data <- aux$data_array + obs$coords$longitude <- aux$lons + obs$coords$latitude <- aux$lats + obs$dims['longitude'] <- dim(aux$data_array)['longitude'] + obs$dims['latitude'] <- dim(aux$data_array)['latitude'] + rm(aux) + } + + + # Check for consistency between hcst and obs grid + if (!(recipe$Analysis$Regrid$type == 'none')) { + if (!isTRUE(all.equal(as.vector(hcst$lat), as.vector(obs$lat)))) { + lat_error_msg <- paste("Latitude mismatch between hcst and obs.", + "Please check the original grids and the", + "regrid parameters in your recipe.") + error(recipe$Run$logger, lat_error_msg) + hcst_lat_msg <- paste0("First hcst lat: ", hcst$lat[1], + "; Last hcst lat: ", hcst$lat[length(hcst$lat)]) + info(recipe$Run$logger, hcst_lat_msg) + obs_lat_msg <- paste0("First obs lat: ", obs$lat[1], + "; Last obs lat: ", obs$lat[length(obs$lat)]) + info(recipe$Run$logger, obs_lat_msg) + stop("hcst and obs don't share the same latitudes.") + } + if (!isTRUE(all.equal(as.vector(hcst$lon), as.vector(obs$lon)))) { + lon_error_msg <- paste("Longitude mismatch between hcst and obs.", + "Please check the original grids and the", + "regrid parameters in your recipe.") + error(recipe$Run$logger, lon_error_msg) + hcst_lon_msg <- paste0("First hcst lon: ", hcst$lon[1], + "; Last hcst lon: ", hcst$lon[length(hcst$lon)]) + info(recipe$Run$logger, hcst_lon_msg) + obs_lon_msg <- paste0("First obs lon: ", obs$lon[1], + "; Last obs lon: ", obs$lon[length(obs$lon)]) + info(recipe$Run$logger, obs_lon_msg) + stop("hcst and obs don't share the same longitudes.") + + } + } + + info(recipe$Run$logger, + "##### DATA LOADING COMPLETED SUCCESSFULLY #####") + + return(list(hcst = hcst, fcst = fcst, obs = obs)) +} diff --git a/modules/Loading/R/mask_tas_tos.R b/modules/Loading/R/mask_tas_tos.R index a2eeb0b6..cc693795 100644 --- a/modules/Loading/R/mask_tas_tos.R +++ b/modules/Loading/R/mask_tas_tos.R @@ -2,29 +2,28 @@ library(multiApply) library(startR) library(s2dv) -mask_tas_tos <- function(input_data, grid, lon, lat, region = region , - lon_dim = 'lon', lat_dim = 'lat', ncores = NULL){ +mask_tas_tos <- function(input_data, mask_path, lsm_var_name = lsm_var_name, lon, lat, region = region, + lon_dim = 'lon', lat_dim = 'lat', + ncores = NULL){ - - mask <- .load_mask(grid = grid, lon_dim = lon_dim, lat_dim = lat_dim, + + mask <- .load_mask(mask_path = mask_path, lsm_var_name = lsm_var_name, lon_dim = lon_dim, lat_dim = lat_dim, sea_value = 1, land_value = 0, region = region) - ## TO DO: improve the check and correct lats stopifnot(all(lon == mask$lon)) stopifnot(max(abs(as.numeric(round(lat,2) - round(mask$lat,2)))) < 0.1) # stopifnot(all(lat == mask$lat)) - + tas <- Subset(input_data$data, along = 'var', indices = 1) tos <- Subset(input_data$data, along = 'var', indices = 2) - tas_tos <- multiApply::Apply(data = list(tas, tos), - target_dims = c(lon_dim, lat_dim), - fun = .mask_tas_tos, - mask = mask$mask, - sea_value = 1, - ncores = ncores)$output1 - input_data$data <- tas_tos - + input_data$data <- multiApply::Apply(data = list(tas, tos), + target_dims = c(lon_dim, lat_dim), + fun = .mask_tas_tos, + mask = mask$mask, + sea_value = 1, + ncores = ncores)$output1 + return(input_data) } @@ -33,52 +32,32 @@ mask_tas_tos <- function(input_data, grid, lon, lat, region = region , return(data_tas) } -.load_mask <- function(grid, mask_path = NULL, land_value = 0, sea_value = 1, +.load_mask <- function(mask_path = mask_path, lsm_var_name = lsm_var_name, land_value = 0, sea_value = 1, lon_dim = 'lon', lat_dim = 'lat', region = region){ - if (is.null(mask_path)){ - mask_sea_land_path <- '/esarchive/exp/ecmwf/system5c3s/constant/lsm/lsm.nc' ## /esarchive/recon/ecmwf/era5land/constant/lsm-r3600x1801cds/lsm.nc' - } else if (is.character(mask_path)){ - mask_sea_land_path <- mask_path - } else { - stop("mask_path must be NULL (to use the default mask and interpolate it to - the specified grid) or a string with the mask's path you want to load") - } - lons.min <- region[1] lons.max <- region[2] lats.min <- region[3] lats.max <- region[4] - - ## TO DO: - ## Fix region filter for lat and lon - ## Fix 'number' parameter for mask - - data <- startR::Start(dat = mask_sea_land_path, - var = 'lsm', - lon = 'all', - lat = 'all', - number = 1, ## needed to add for ensemble member dimension of lsm.nc - # lon = values(list(lons.min, lons.max)), - # lat = values(list(lats.min, lats.max)), - transform = CDORemapper, transform_extra_cells = 2, - transform_params = list(grid = grid, method = 'con', crop = region), - transform_vars = c('lat','lon'), + data <- startR::Start(dat = mask_path, + var = lsm_var_name, + lon = values(list(lons.min, lons.max)), + lat = values(list(lats.min, lats.max)), return_vars = list(lat = NULL, lon = NULL), synonims = list(lon = c('lon','longitude'), lat = c('lat','latitude')), - lat_reorder = Sort(decreasing = FALSE), - lon_reorder = CircularSort(0,359.9), + lat_reorder = Sort(decreasing = TRUE), + lon_reorder = CircularSort(0,360), num_procs = 1, retrieve = TRUE) - + mask <- list(mask = drop(data), lon = as.numeric(attr(data,'Variables')$common$lon), lat = as.numeric(attr(data,'Variables')$common$lat)) mask$mask[data <= 0.5] <- sea_value mask$mask[data > 0.5] <- land_value - names(dim(mask$mask)) <- c(lon_dim, lat_dim) + names(dim(mask$mask)) <- c(lon_dim, lat_dim) return(mask) } diff --git a/recipes/atomic_recipes/recipe_tas-tos_nadia.yml b/recipes/atomic_recipes/recipe_tas-tos_nadia.yml new file mode 100644 index 00000000..466659a2 --- /dev/null +++ b/recipes/atomic_recipes/recipe_tas-tos_nadia.yml @@ -0,0 +1,55 @@ +Description: + Author: V. Agudetse + +Analysis: + Horizon: Seasonal + Variables: + name: tas-tos + sic_threshold: 0.15 ## sea ice threshold for tas-tos blending, default = 0.15 + freq: monthly_mean + Datasets: + System: + name: ECMWF-SEAS5 + Multimodel: False + Reference: + name: BEST + Time: + sdate: '0101' + #fcst_year: + hcst_start: '2014' + hcst_end: '2016' + ftime_min: 1 + ftime_max: 1 + Region: + latmin: -90 + latmax: 90 + lonmin: 0 + lonmax: 359.9 + Regrid: + method: bilinear + type: to_system + Workflow: + Calibration: + method: raw + save: 'none' + Anomalies: + compute: yes + cross_validation: no + save: 'none' + Skill: + metric: mean_bias EnsCorr RPS RPSS CRPS CRPSS enssprerr + cross_validation: no + save: 'all' + Probabilities: + percentiles: [[1/3, 2/3]] + save: 'none' + Indicators: + index: no + ncores: 15 + remove_NAs: yes + Output_format: scorecards +Run: + Loglevel: INFO + Terminal: yes + output_dir: /esarchive/scratch/nmilders/scorecards_data/test/ + code_dir: /esarchive/scratch/nmilders/gitlab/git_clones/s2s-suite_tas-tos/ diff --git a/tests/recipes/recipe-seasonal_monthly_1_tas-tos.yml b/tests/recipes/recipe-seasonal_monthly_1_tas-tos.yml new file mode 100644 index 00000000..41048db1 --- /dev/null +++ b/tests/recipes/recipe-seasonal_monthly_1_tas-tos.yml @@ -0,0 +1,56 @@ +Description: + Author: N. Milders + +Analysis: + Horizon: Seasonal + Variables: + name: tas-tos + sic_threshold: 0.15 + freq: monthly_mean + Datasets: + System: + name: ECMWF-SEAS5 + Multimodel: False + Reference: + name: ERA5 + Time: + sdate: '0101' + fcst_year: '2018' + hcst_start: '1993' + hcst_end: '1996' + ftime_min: 1 + ftime_max: 3 + Region: + latmin: 17 + latmax: 20 + lonmin: 12 + lonmax: 15 + Regrid: + method: bilinear + type: to_system + Workflow: + Anomalies: + compute: no + cross_validation: + save: 'none' + Calibration: + method: mse_min + save: 'all' + Skill: + metric: RPSS CRPSS EnsCorr Corr_individual_members Enscorr_specs + save: 'all' + Probabilities: + percentiles: [[1/3, 2/3], [1/10, 9/10]] + save: 'all' + Indicators: + index: no + Visualization: + plots: skill_metrics most_likely_terciles forecast_ensemble_mean + multi_panel: yes + projection: cylindrical_equidistant + Output_format: S2S4E +Run: + Loglevel: INFO + Terminal: yes + output_dir: ./tests/out-logs/ + code_dir: /esarchive/scratch/nmilders/gitlab/git_clones/auto-s2s/ ##/esarchive/scratch/vagudets/repos/auto-s2s/ diff --git a/tests/testthat/test-seasonal_monthly_tas-tos.R b/tests/testthat/test-seasonal_monthly_tas-tos.R new file mode 100644 index 00000000..1345f63d --- /dev/null +++ b/tests/testthat/test-seasonal_monthly_tas-tos.R @@ -0,0 +1,98 @@ +context("Seasonal monthly data") + +source("./modules/Loading/Loading.R") + +recipe_file <- "tests/recipes/recipe-seasonal_monthly_1_tas-tos.yml" +recipe <- prepare_outputs(recipe_file, disable_checks = F) +archive <- read_yaml(paste0(recipe$Run$code_dir, "conf/archive.yml"))$archive + +# Load datasets +suppressWarnings({invisible(capture.output( +data <- Loading(recipe) +))}) + + +# ------- TESTS -------- + +test_that("1. Loading", { + +expect_equal( +is.list(data), +TRUE +) +expect_equal( +names(data), +c("hcst", "fcst", "obs") +) +expect_equal( +class(data$hcst), +"s2dv_cube" +) +expect_equal( +class(data$fcst), +"s2dv_cube" +) +expect_equal( +class(data$obs), +"s2dv_cube" +) +expect_equal( +names(data$hcst), +c("data", "dims", "coords", "attrs") +) +expect_equal( +names(data$hcst), +names(data$fcst) +) +expect_equal( +names(data$hcst), +names(data$obs) +) +expect_equal( +dim(data$hcst$data), +c(dat = 1, var = 1, sday = 1, sweek = 1, syear = 4, time = 3, latitude = 4, longitude = 4, ensemble = 25) +) +expect_equal( +dim(data$fcst$data), +c(dat = 1, var = 1, sday = 1, sweek = 1, syear = 1, time = 3, latitude = 4, longitude = 4, ensemble = 51) +) +expect_equal( +dim(data$hcst$attrs$Dates), +c(sday = 1, sweek = 1, syear = 4, time = 3) +) +expect_equal( +as.vector(drop(data$hcst$data)[1:2,1:2,1,2,3]), +c(285.5869, 287.8836, 285.9362, 289.0483), +tolerance = 0.0001 +) +expect_equal( +mean(data$hcst$data), +290.1099, +tolerance = 0.0001 +) +expect_equal( +range(data$hcst$data), +c(283.2845, 299.7845), +tolerance = 0.0001 +) +expect_equal( +(data$hcst$attrs$Dates)[1], +as.POSIXct("1993-01-31 18:00:00", tz = 'UTC') +) +expect_equal( +(data$hcst$attrs$Dates)[2], +as.POSIXct("1994-01-31 18:00:00", tz = 'UTC') +) +expect_equal( +(data$hcst$attrs$Dates)[5], +as.POSIXct("1993-02-28 18:00:00", tz = 'UTC') +) +expect_equal( +(data$obs$attrs$Dates)[10], +as.POSIXct("1994-03-15 12:00:00", tz = 'UTC') +) + +}) + +# Delete files +unlink(recipe$Run$output_dir, recursive = T) diff --git a/tools/check_recipe.R b/tools/check_recipe.R index e4c59a55..69a7dd4c 100644 --- a/tools/check_recipe.R +++ b/tools/check_recipe.R @@ -62,6 +62,18 @@ check_recipe <- function(recipe) { } else { archive <- NULL } + # Check variable parameters + variables <- tolower(strsplit(recipe$Analysis$Variables$name, ", | |,")[[1]]) + # Sea-ice threshold check + if (("tas-tos" %in% variables) && + (!is.null(recipe$Analysis$Variables$sic_threshold))) { + if (!is.numeric(recipe$Analysis$Variables$sic_threshold) || + dplyr::between(recipe$Analysis$Variables$sic_threshold, 0, 1)) { + error(recipe$Run$logger, + paste("The element Analysis:Variables:sic_threshold must be a", + "numeric value between 0 and 1.")) + } + } # Check system names if (!is.null(archive)) { if (!all(recipe$Analysis$Datasets$System$name %in% names(archive$System))) { diff --git a/tools/prepare_outputs.R b/tools/prepare_outputs.R index fa4d23ed..54e82095 100644 --- a/tools/prepare_outputs.R +++ b/tools/prepare_outputs.R @@ -89,6 +89,10 @@ prepare_outputs <- function(recipe_file, warn(recipe$Run$logger, "Filesystem not specified in the recipe. Setting it to 'esarchive'.") } + # Restructure the recipe to make the atomic recipe more readable + if (restructure) { + recipe <- restructure_recipe(recipe) + } # Run recipe checker if (disable_checks) { warn(recipe$Run$logger, @@ -96,9 +100,5 @@ prepare_outputs <- function(recipe_file, } else { check_recipe(recipe) } - # Restructure the recipe to make the atomic recipe more readable - if (restructure) { - recipe <- restructure_recipe(recipe) - } return(recipe) } -- GitLab From dca341e1fb6cccc08378de482325d56f24d409a1 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Mon, 20 Nov 2023 15:46:32 +0100 Subject: [PATCH 14/78] Add 'tos' to MeteoFrance System 7 --- conf/archive.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/conf/archive.yml b/conf/archive.yml index 0b643ae9..e6e4a2c5 100644 --- a/conf/archive.yml +++ b/conf/archive.yml @@ -53,7 +53,8 @@ esarchive: src: "exp/meteofrance/system7c3s/" monthly_mean: {"tas":"monthly_mean/tas_f6h/", "g500":"monthly_mean/g500_f12h/", "prlr":"monthly_mean/prlr_f24h/", "sfcWind": "monthly_mean/sfcWind_f6h/", - "tasmax":"monthly_mean/tasmax_f6h/", "tasmin": "monthly_mean/tasmin_f6h/"} + "tasmax":"monthly_mean/tasmax_f6h/", "tasmin": "monthly_mean/tasmin_f6h/", + "tos":"monthly_mean/tos_f6h/"} nmember: fcst: 51 hcst: 25 -- GitLab From 75da4ee121aa5c62672859b4db15e007a78a1c4a Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Mon, 20 Nov 2023 15:46:57 +0100 Subject: [PATCH 15/78] =?UTF-8?q?Add=20usecase=201.3=20(El=20Ni=C3=B1o=20i?= =?UTF-8?q?ndices=20on=20multiple=20systems)=20(WIP)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../ex1_3-recipe.yml | 57 +++++++++++++++++++ .../ex1_3_nino_indices_comparison.R | 38 +++++++++++++ 2 files changed, 95 insertions(+) create mode 100644 use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml create mode 100644 use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml b/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml new file mode 100644 index 00000000..b563e4ac --- /dev/null +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml @@ -0,0 +1,57 @@ +Description: + Author: V. Agudetse + Info: Computing El Nino indices for ECMWF SEAS5 and MeteoFrance System7 + +Analysis: + Horizon: seasonal + Variables: + - {name: tos, freq: monthly_mean, units: K} + Datasets: + System: + - {name: ECMWF-SEAS5} + - {name: Meteo-France-System7} + Multimodel: no + Reference: + - {name: ERA5} + Time: + sdate: '1101' + fcst_year: '2021' + hcst_start: '1993' + hcst_end: '2016' + ftime_min: 2 + ftime_max: 4 + Region: + latmin: -90 + latmax: 90 + lonmin: 0 + lonmax: 359.9 + Regrid: + method: 'bilinear' + type: 'to_system' + Workflow: + Anomalies: + compute: yes + cross_validation: no + save: none + Indices: + Nino1+2: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} + Nino3: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} + Nino3.4: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} + Nino4: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} + Skill: + metric: mean_bias EnsCorr rps rpss crps crpss EnsSprErr + save: 'all' + Probabilities: + percentiles: [[1/3, 2/3], [1/10, 9/10]] + save: none + Indicators: + index: no + ncores: 8 + remove_NAs: no + Output_format: S2S4E + logo: TRUE +Run: + Loglevel: INFO + Terminal: yes + output_dir: /esarchive/scratch/vagudets/auto-s2s-outputs/ # ______ + code_dir: /esarchive/scratch/vagudets/repos/auto-s2s/ # _____ diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R b/use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R new file mode 100644 index 00000000..c2b44541 --- /dev/null +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R @@ -0,0 +1,38 @@ +############################################################################### +## Author: Nรบria Pรฉrez-Zanรณn +## Description: Computes the Niรฑo1+2, Niรฑo3, Niรฑo3.4 and Niรฑo4 indices and some +## some skill metrics for each index. +## Instructions: To run it, modify the recipe to set your own output directory. +############################################################################### + +# Load modules +source("modules/Loading/Loading.R") +source("modules/Anomalies/Anomalies.R") +source("modules/Indices/Indices.R") +source("modules/Skill/Skill.R") + +# Read recipe +recipe_file <- "use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml" +recipe <- prepare_outputs(recipe_file) + +data <- Loading(recipe) +data <- Units(recipe, data) +data <- Anomalies(recipe, data) +nino_indices <- Indices(data = data, recipe = recipe) + +str(nino_indices, max.level = 3) +for (index in nino_indices) { + skill_metrics <- Skill(recipe = recipe, data = index, agg = "region") +} + +# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino1, +# agg = 'region') +# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino3, +# agg = 'region') +# +# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino4, +# agg = 'region') +# +# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino3.4, +# agg = 'region') +# -- GitLab From e37467430092981cd3fa5c31807171c394a6a84f Mon Sep 17 00:00:00 2001 From: Nadia Milders Date: Tue, 21 Nov 2023 16:27:56 +0100 Subject: [PATCH 16/78] included cross-validation for skill scores --- modules/Skill/R/CRPS_clim.R | 30 ++++++++++++++++++++++-------- modules/Skill/R/RPS_clim.R | 4 ++-- modules/Skill/Skill.R | 4 +++- 3 files changed, 27 insertions(+), 11 deletions(-) diff --git a/modules/Skill/R/CRPS_clim.R b/modules/Skill/R/CRPS_clim.R index 36db4e94..b66cab78 100644 --- a/modules/Skill/R/CRPS_clim.R +++ b/modules/Skill/R/CRPS_clim.R @@ -1,13 +1,27 @@ -CRPS_clim <- function(obs, memb_dim ='ensemble'){ +# CRPS version for climatology +CRPS_clim <- function(obs, memb_dim ='ensemble', return_mean = TRUE, clim.cross.val= TRUE){ time_dim <- names(dim(obs)) obs_time_len <- dim(obs)[time_dim] - + + if (isFALSE(clim.cross.val)) { ## Without cross-validation ref <- array(data = rep(obs, each = obs_time_len), dim = c(obs_time_len, obs_time_len)) - names(dim(ref)) <- c(time_dim, memb_dim) - # ref: [sdate, memb] - # obs: [sdate] + } else if (isTRUE(clim.cross.val)) { ## With cross-validation (excluding the value of that year to create ref for that year) + ref <- array(data = NA, dim = c(obs_time_len, obs_time_len - 1)) + for (i in 1:obs_time_len) { + ref[i, ] <- obs[-i] + } + } + + names(dim(ref)) <- c(time_dim, memb_dim) + # ref: [sdate, memb] + # obs: [sdate] crps_ref <- s2dv:::.CRPS(exp = ref, obs = obs, time_dim = time_dim, memb_dim = memb_dim, - dat_dim = NULL, Fair = FALSE) - # crps_ref should be [sdate] - return(mean(crps_ref)) + dat_dim = NULL, Fair = FALSE) + + # crps_ref should be [sdate] + if (return_mean == TRUE) { + return(mean(crps_ref)) + } else { + return(crps_ref) + } } diff --git a/modules/Skill/R/RPS_clim.R b/modules/Skill/R/RPS_clim.R index e8b6452d..c93c6747 100644 --- a/modules/Skill/R/RPS_clim.R +++ b/modules/Skill/R/RPS_clim.R @@ -1,12 +1,12 @@ # RPS version for climatology -RPS_clim <- function(obs, indices_for_clim = NULL, prob_thresholds = c(1/3, 2/3)) { +RPS_clim <- function(obs, indices_for_clim = NULL, prob_thresholds = c(1/3, 2/3), cross.val = TRUE) { if (is.null(indices_for_clim)){ indices_for_clim <- 1:length(obs) } obs_probs <- .GetProbs(data = obs, indices_for_quantiles = indices_for_clim, ## temporarily removed s2dv::: - prob_thresholds = prob_thresholds, weights = NULL, cross.val = T) ## here! + prob_thresholds = prob_thresholds, weights = NULL, cross.val = cross.val) # clim_probs: [bin, sdate] clim_probs <- c(prob_thresholds[1], diff(prob_thresholds), 1 - prob_thresholds[length(prob_thresholds)]) clim_probs <- array(clim_probs, dim = dim(obs_probs)) diff --git a/modules/Skill/Skill.R b/modules/Skill/Skill.R index fd54f17f..04fbc52e 100644 --- a/modules/Skill/Skill.R +++ b/modules/Skill/Skill.R @@ -89,6 +89,7 @@ Skill <- function(recipe, data, agg = 'global') { skill_metrics[[ metric ]] <- skill rps_clim <- Apply(list(data$obs$data), target_dims = c(time_dim, memb_dim), + cross.val = cross.val, RPS_clim)$output1 rps_clim <- .drop_dims(rps_clim) skill_metrics[[paste0(metric, "_clim")]] <- rps_clim @@ -140,7 +141,8 @@ Skill <- function(recipe, data, agg = 'global') { skill <- .drop_dims(skill) skill_metrics[[ metric ]] <- skill crps_clim <- Apply(list(data$obs$data), target_dims = time_dim, - fun = CRPS_clim, memb_dim = memb_dim)$output1 + fun = CRPS_clim, memb_dim = memb_dim, + clim.cross.val = cross.val)$output1 crps_clim <- .drop_dims(crps_clim) skill_metrics[['crps_clim']] <- crps_clim # CRPSS and FCRPSS -- GitLab From 44e53a691207c26a179d0c0ebfff635efb7ce857 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Wed, 22 Nov 2023 16:20:38 +0100 Subject: [PATCH 17/78] Correct variable retrieval in recipe checks --- tools/check_recipe.R | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/tools/check_recipe.R b/tools/check_recipe.R index 69a7dd4c..01b790b8 100644 --- a/tools/check_recipe.R +++ b/tools/check_recipe.R @@ -63,9 +63,14 @@ check_recipe <- function(recipe) { archive <- NULL } # Check variable parameters - variables <- tolower(strsplit(recipe$Analysis$Variables$name, ", | |,")[[1]]) + if ("name" %in% names(recipe$Analysis$Variables)) { + recipe_variables <- recipe$Analysis$Variables$name + } else { + recipe_variables <- sapply(recipe$Analysis$Variables, get, x = "name") + } + recipe_variables <- unlist(strsplit(recipe_variables, ", | |,")) # Sea-ice threshold check - if (("tas-tos" %in% variables) && + if (("tas-tos" %in% recipe_variables) && (!is.null(recipe$Analysis$Variables$sic_threshold))) { if (!is.numeric(recipe$Analysis$Variables$sic_threshold) || dplyr::between(recipe$Analysis$Variables$sic_threshold, 0, 1)) { @@ -434,7 +439,6 @@ check_recipe <- function(recipe) { error_status <- T } # Check that variables correspond with indices requested - recipe_variables <- strsplit(recipe$Analysis$Variables$name, ", | |,")[[1]] if (("nao" %in% recipe_indices) && (!all(recipe_variables %in% c("psl", "z500")))) { error(recipe$Run$logger, -- GitLab From 7c6b99f2236c08450fcdb04a6da3c55710ea79af Mon Sep 17 00:00:00 2001 From: aho Date: Thu, 23 Nov 2023 14:19:39 +0100 Subject: [PATCH 18/78] Avoid producing Inf when all data are NAs --- .../Indices/R/plot_deterministic_forecast.R | 9 +++++-- modules/Visualization/R/tmp/PlotRobinson.R | 25 ++++++++++++++++--- 2 files changed, 29 insertions(+), 5 deletions(-) diff --git a/modules/Indices/R/plot_deterministic_forecast.R b/modules/Indices/R/plot_deterministic_forecast.R index da107e47..30f13b78 100644 --- a/modules/Indices/R/plot_deterministic_forecast.R +++ b/modules/Indices/R/plot_deterministic_forecast.R @@ -16,8 +16,13 @@ plot_deterministic_forecast <- function(obs, fcst, title = NULL, n_fcst <- as.numeric(dim(fcst)[time_dim]) if (is.null(ylims)) { - ylims <- c(-max(abs(fcst) + 0.1, abs(obs) + 0.1, na.rm = TRUE), - max(abs(fcst) + 0.1, abs(obs) + 0.1, na.rm = TRUE)) + if (all(is.na(fcst)) && all(is.na(obs))) { + # No data, return random ylims + ylims <- c(-1, 1) + } else { + ylims <- c(-max(abs(fcst) + 0.1, abs(obs) + 0.1, na.rm = TRUE), + max(abs(fcst) + 0.1, abs(obs) + 0.1, na.rm = TRUE)) + } } if (is.null(xlabs)) { xlabs <- 1:n_fcst diff --git a/modules/Visualization/R/tmp/PlotRobinson.R b/modules/Visualization/R/tmp/PlotRobinson.R index d8210258..d50e7f36 100644 --- a/modules/Visualization/R/tmp/PlotRobinson.R +++ b/modules/Visualization/R/tmp/PlotRobinson.R @@ -251,7 +251,26 @@ PlotRobinson <- function(data, lon, lat, lon_dim = NULL, lat_dim = NULL, # Color bar ## Check: brks, cols, bar_limits, color_fun, bar_extra_margin, units ## Build: brks, cols, bar_limits, col_inf, col_sup - var_limits <- c(min(data, na.rm = TRUE), max(data, na.rm = TRUE)) + if (!all(is.na(data))) { + var_limits <- c(min(data[!is.infinite(data)], na.rm = TRUE), + max(data[!is.infinite(data)], na.rm = TRUE)) + } else { + warning("All the data are NAs. The map will be filled with colNA.") + if (!is.null(brks) && length(brks) > 1) { + #NOTE: var_limits be like this to avoid warnings from ColorBar + var_limits <- c(min(brks, na.rm = TRUE) + diff(brks)[1], + max(brks, na.rm = TRUE)) + } else if (!is.null(bar_limits)) { + var_limits <- c(bar_limits[1] + 0.01, bar_limits[2]) + } else { + var_limits <- c(-0.5, 0.5) # random range since colorbar is not going to be plotted + if (drawleg) { + drawleg <- FALSE + warning("All data are NAs. Color bar won't be drawn. If you want to have ", + "color bar still, define parameter 'brks' or 'bar_limits'.") + } + } + } colorbar <- ColorBar(brks = brks, cols = cols, vertical = vertical, subsampleg = NULL, bar_limits = bar_limits, var_limits = var_limits, triangle_ends = triangle_ends, col_inf = col_inf, col_sup = col_sup, color_fun = color_fun, @@ -317,12 +336,12 @@ PlotRobinson <- function(data, lon, lat, lon_dim = NULL, lat_dim = NULL, # Add triangles to brks brks_ggplot <- brks - if (max(data, na.rm = T) > tail(brks, 1)) { + if (var_limits[2] > tail(brks, 1)) { brks_ggplot <- c(brks_ggplot, max(data, na.rm = T)) } else { brks_ggplot <- c(brks_ggplot, tail(brks, 1) + diff(tail(brks, 2))) } - if (min(data, na.rm = T) < brks[1]) { + if (var_limits[1] < brks[1]) { brks_ggplot <- c(min(data, na.rm = T), brks_ggplot) } else { brks_ggplot <- c(brks[1] - diff(brks[1:2]), brks_ggplot) -- GitLab From 9e8cb02c88f3adc1b2da570fd23a0382df4512a5 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Thu, 23 Nov 2023 16:24:29 +0100 Subject: [PATCH 19/78] Add use case 1.3 (WIP) --- .../ex1_3-handson.md | 16 ++++++++ .../ex1_3-recipe.yml | 11 +++--- .../ex1_3-script.R | 35 +++++++++++++++++ .../ex1_3_nino_indices_comparison.R | 38 ------------------- 4 files changed, 57 insertions(+), 43 deletions(-) create mode 100644 use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md create mode 100644 use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R delete mode 100644 use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md b/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md new file mode 100644 index 00000000..e310d289 --- /dev/null +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md @@ -0,0 +1,16 @@ +# Hands-on 1.3: Computation of El Niรฑo indices for two seasonal models + +## Goal +Create a SUNSET recipe to compute and evaluate the skill of several El Niรฑo indices (Niรฑo1+2, Niรฑo3, Niรฑo3.4 and Niรฑo4) for two models: ECMWF-SEAS5 and MeteoFrance System 7. The computation for each model will be run in the cluster as two separate jobs. + +## 0. Cloning the SUNSET repository + +The first step to use SUNSET is to create a copy of the code in your local environment. Open a terminal and `cd` to the directory where you would like to store your local copy of SUNSET. For example: `/esarchive/scratch//git/`. If a directory does not exist yet, you can create it with the `mkdir` shell command. + +```shell +# Clone the GitLab repository to create a local copy of the code +git clone https://earth.bsc.es/gitlab/es/sunset.git +``` + +## 1. Modifying the recipe + diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml b/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml index b563e4ac..495f89f0 100644 --- a/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml @@ -15,16 +15,16 @@ Analysis: - {name: ERA5} Time: sdate: '1101' - fcst_year: '2021' + fcst_year: hcst_start: '1993' hcst_end: '2016' ftime_min: 2 ftime_max: 4 Region: latmin: -90 - latmax: 90 - lonmin: 0 - lonmax: 359.9 + latmax: 90 + lonmin: 0 + lonmax: 359.9 Regrid: method: 'bilinear' type: 'to_system' @@ -47,7 +47,7 @@ Analysis: Indicators: index: no ncores: 8 - remove_NAs: no + remove_NAs: yes Output_format: S2S4E logo: TRUE Run: @@ -55,3 +55,4 @@ Run: Terminal: yes output_dir: /esarchive/scratch/vagudets/auto-s2s-outputs/ # ______ code_dir: /esarchive/scratch/vagudets/repos/auto-s2s/ # _____ + autosubmit: no diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R b/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R new file mode 100644 index 00000000..59843b44 --- /dev/null +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R @@ -0,0 +1,35 @@ +############################################################################### +## Author: Nรบria Pรฉrez-Zanรณn and Victรฒria Agudetse Roures +## Description: Computes the Niรฑo1+2, Niรฑo3, Niรฑo3.4 and Niรฑo4 indices and some +## skill metrics for each index. +## Instructions: To run it, follow the steps described in: +## use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md +############################################################################### + +# Load modules +source("modules/Loading/Loading.R") +source("modules/Units/Units.R") +source("modules/Anomalies/Anomalies.R") +source("modules/Indices/Indices.R") +source("modules/Skill/Skill.R") + +# Read recipe +args = commandArgs(trailingOnly = TRUE) +recipe_file <- args[1] +recipe <- read_atomic_recipe(recipe_file) + +# Load data +data <- Loading(recipe) +# Check units and transform if needed +data <- Units(recipe, data) +# Compute tos anomalies +data <- Anomalies(recipe, data) +# Compute Niรฑo Indices +nino_indices <- Indices(data = data, recipe = recipe) + +# We can compute the Skill metrics for each of the El Niรฑo indices, +# specifying that the data is spatially aggregated, with the parameter +# agg = "region". +for (index in nino_indices) { + skill_metrics <- Skill(recipe = recipe, data = index, agg = "region") +} diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R b/use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R deleted file mode 100644 index c2b44541..00000000 --- a/use_cases/ex1_3_nino_indices_comparison/ex1_3_nino_indices_comparison.R +++ /dev/null @@ -1,38 +0,0 @@ -############################################################################### -## Author: Nรบria Pรฉrez-Zanรณn -## Description: Computes the Niรฑo1+2, Niรฑo3, Niรฑo3.4 and Niรฑo4 indices and some -## some skill metrics for each index. -## Instructions: To run it, modify the recipe to set your own output directory. -############################################################################### - -# Load modules -source("modules/Loading/Loading.R") -source("modules/Anomalies/Anomalies.R") -source("modules/Indices/Indices.R") -source("modules/Skill/Skill.R") - -# Read recipe -recipe_file <- "use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml" -recipe <- prepare_outputs(recipe_file) - -data <- Loading(recipe) -data <- Units(recipe, data) -data <- Anomalies(recipe, data) -nino_indices <- Indices(data = data, recipe = recipe) - -str(nino_indices, max.level = 3) -for (index in nino_indices) { - skill_metrics <- Skill(recipe = recipe, data = index, agg = "region") -} - -# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino1, -# agg = 'region') -# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino3, -# agg = 'region') -# -# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino4, -# agg = 'region') -# -# skill_metrics <- Skill(recipe = recipe, data = nino_indices$Nino3.4, -# agg = 'region') -# -- GitLab From 026ad2ebfe7950591b309b5ce512df76518b10aa Mon Sep 17 00:00:00 2001 From: aho Date: Thu, 23 Nov 2023 17:28:23 +0100 Subject: [PATCH 20/78] correct variable name --- modules/Visualization/R/tmp/PlotRobinson.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/Visualization/R/tmp/PlotRobinson.R b/modules/Visualization/R/tmp/PlotRobinson.R index d50e7f36..bd427448 100644 --- a/modules/Visualization/R/tmp/PlotRobinson.R +++ b/modules/Visualization/R/tmp/PlotRobinson.R @@ -264,8 +264,8 @@ PlotRobinson <- function(data, lon, lat, lon_dim = NULL, lat_dim = NULL, var_limits <- c(bar_limits[1] + 0.01, bar_limits[2]) } else { var_limits <- c(-0.5, 0.5) # random range since colorbar is not going to be plotted - if (drawleg) { - drawleg <- FALSE + if (!is.null(legend)) { + legend <- NULL warning("All data are NAs. Color bar won't be drawn. If you want to have ", "color bar still, define parameter 'brks' or 'bar_limits'.") } -- GitLab From 89c029eb0e6a9d3641ae881f9b977ab66460210d Mon Sep 17 00:00:00 2001 From: Eva Rifa Date: Thu, 23 Nov 2023 17:31:00 +0100 Subject: [PATCH 21/78] Add the new version of LoadMetrics and provide an example in Scorecards.R --- modules/Saving/R/get_filename.R | 14 +- modules/Saving/R/save_metrics_scorecards.R | 12 ++ modules/Scorecards/R/tmp/LoadMetrics.R | 219 ++++++--------------- modules/Scorecards/Scorecards.R | 50 +++-- modules/Skill/Skill.R | 2 +- 5 files changed, 116 insertions(+), 181 deletions(-) diff --git a/modules/Saving/R/get_filename.R b/modules/Saving/R/get_filename.R index ca40f1b5..9f6151e8 100644 --- a/modules/Saving/R/get_filename.R +++ b/modules/Saving/R/get_filename.R @@ -38,17 +38,17 @@ get_filename <- function(dir, recipe, var, date, agg, file.type) { "probs" = {type_info <- paste0("-probs_", date, "_")}, "bias" = {type_info <- paste0("-bias_", date, "_")}, # new - "rps_syear" = {type_info <- paste0("_rps-syear_")}, - "rps_clim_syear" = {type_info <- paste0("_rps-clim-syear_")}, - "crps_syear" = {type_info <- paste0("_crps-syear_")}, - "crps_clim_syear" = {type_info <- paste0("_crps-clim-syear_")}, - "crps" = {type_info <- paste0("_crps_")}, - "mean_bias" = {type_info <- paste0("_mean-bias_")}, + "rps_syear" = {type_info <- paste0("rps_syear")}, + "rps_clim_syear" = {type_info <- paste0("rps_clim_syear")}, + "crps_syear" = {type_info <- paste0("crps_syear")}, + "crps_clim_syear" = {type_info <- paste0("crps_clim_syear")}, + "crps" = {type_info <- paste0("crps")}, + "mean_bias" = {type_info <- paste0("mean_bias")}, {type_info <- paste0("_", file.type, "_")}) # Build file name file <- paste0("scorecards_", system, "_", reference, "_", - var, type_info, hcst_start, "-", hcst_end, "_s", shortdate) + var, "_",type_info, "_", hcst_start, "-", hcst_end, "_s", shortdate) } else { switch(file.type, "skill" = {file <- paste0(var, gg, "-skill_", dd, shortdate)}, diff --git a/modules/Saving/R/save_metrics_scorecards.R b/modules/Saving/R/save_metrics_scorecards.R index 020f2593..9c133395 100644 --- a/modules/Saving/R/save_metrics_scorecards.R +++ b/modules/Saving/R/save_metrics_scorecards.R @@ -7,6 +7,18 @@ save_metrics_scorecards <- function(recipe, fcst.horizon <- tolower(recipe$Analysis$Horizon) store.freq <- recipe$Analysis$Variables$freq + # archive <- get_archive(recipe) + # global_attributes <- .get_global_attributes(recipe, archive) + # ## TODO: Sort out the logic once default behavior is decided + # if ((!is.null(recipe$Analysis$Workflow$Anomalies$compute)) && + # (recipe$Analysis$Workflow$Anomalies$compute)) { + # global_attributes <- c(list(from_anomalies = "Yes"), + # global_attributes) + # } else { + # global_attributes <- c(list(from_anomalies = "No"), + # global_attributes) + # } + # Select start date # If a fcst is provided, use that as the ref. year. Otherwise use 1970. if (fcst.horizon == 'decadal') { diff --git a/modules/Scorecards/R/tmp/LoadMetrics.R b/modules/Scorecards/R/tmp/LoadMetrics.R index e5e15421..55030d95 100644 --- a/modules/Scorecards/R/tmp/LoadMetrics.R +++ b/modules/Scorecards/R/tmp/LoadMetrics.R @@ -1,7 +1,15 @@ -#' Scorecards load metrics from verification suite +#'Scorecards load metrics from verification suite #' -#'@description Scorecards function to load saved data files +#'Scorecards function to load saved data files. This function is created to +#'load NetCDF files that contain 1 metric for each file. It calls startR::Start +#'internally. The NetCDF file is supposed to have the following dimensions: +#''longitude', 'latitude' and 'time'. If 'syear' is also a dimension, you must +#'set the parameter 'syear' different to NULL. #' +#'@param input_path A character string indicating the path where metrics output +#' files from verification suite are saved (or any other compatible files) +#'@param metrics A vector of character strings indicating the metrics name to +#' be loaded. #'@param system A vector of character strings defining the names of the #' system names following the archive.yml format from verification suite. #' Accepted system names: 'ECMWF-SEAS5', 'DWD-GFCS2.1', 'CMCC-SPS3.5', @@ -12,107 +20,40 @@ #'@param var A character string following the format from #' variable-dictionary.yml from verification suite (TO DO: multiple variables). #' The accepted names are: 'psl', 'tas', 'sfcWind', 'prlr'. -#'@param start.year A numeric indicating the start year of the reference period -#'@param end.year A numeric indicating the end year of the reference period -#'@param start.months A vector indicating the numbers of the start months -#'@param forecast.months A vector indicating the numbers of the forecast months -#'@param input.path A character string indicating the path where metrics output -#' files from verification suite are saved (or any other compatible files) +#'@param period A character string indicating the start and end years of the +#' reference period (e.g. '1993-203') +#'@param start_months A vector indicating the numbers of the start months +#'@param forecast_months A vector indicating the numbers of the forecast months +#'@param syear Used when the NetCDF file contains a metric that has the +#' dimension 'syear'. It can be any value. If there is no 'syear' dimension, +#' you must set it to NULL. It is NULL by default. #' #'@return A is a list by system and reference containing an array of with #' the following dimensions: longitude, latitude, forecast months, metrics, #' start dates. - #'@examples #'\dontrun{ #'loaded_metrics <- LoadMetrics(system = c('ECMWF-SEAS5','DWD-GFCS2.1'), -#' reference. = 'ERA5', +#' reference = 'ERA5', #' var = 'tas', -#' start.year = 1993, -#' end.year = 2016, +#' period = '1993-2016', #' metrics = c('mean_bias', 'enscorr', 'rpss', 'crpss', 'enssprerr'), -#' start.months = sprintf("%02d", 1:12), -#' forecast.months = 1:6, -#' input.path = '/esarchive/scratch/nmilders/scorecards_data/input_data') +#' start_months = sprintf("%02d", 1:12), +#' forecast_months = 1:6, +#' input_path = '/esarchive/scratch/nmilders/scorecards_data/input_data') #'} #'@import easyNCDF #'@import multiApply -#'@export -LoadMetrics <- function(system, reference, var, start.year, end.year, - metrics, start.months, forecast.months, - inf_to_na = FALSE, - input.path) { - - # Initial checks - ## system - if (!is.character(system)) { - stop("Parameter 'system' must be a character vector with the system names.") - } - ## reference - if (!is.character(reference)) { - stop("Parameter 'reference' must be a character vector with the reference ", - "names.") - } - ## var - if (!is.character(var)) { - stop("Parameter 'var' must be a character vector with the var ", - "names.") - } - if (length(var) > 1) { - warning("Parameter 'var' must be of length one. Only the first value ", - "will be used.") - var <- var[1] - } - ## start.year - if (!is.numeric(start.year)) { - stop("Parameter 'start.year' must be a numeric value.") - } - ## end.year - if (!is.numeric(end.year)) { - stop("Parameter 'end.year' must be a numeric value.") - } - ## metrics - if (!is.character(metrics)) { - stop("Parameter 'metrics' cannot be NULL.") - } - ## start.months - if (is.character(start.months)) { - warning("Parameter 'start.months' must be a numeric vector indicating ", - "the starting months.") - start.months <- as.numeric(start.months) - } - if (!is.numeric(start.months)) { - stop("Parameter 'start.months' must be a numeric vector indicating ", - "the starting months.") - } - start.months <- sprintf("%02d", start.months) - ## Check if sdates are continuous or discrete - if (all(diff(as.numeric(start.months)) == 1)) { - consecutive_start.months <- TRUE - } else { - consecutive_start.months <- FALSE - } - ## forecast.months - if (!is.numeric(forecast.months)) { - stop("Parameter 'forecast.months' must be a numeric vector indicating ", - "the starting months.") - } - ## input.path - if (!is.character(input.path)) { - stop("Parameter 'input.path must be a character string.") - } - if (length(input.path) > 1) { - input.path <- input.path[1] - warning("Parameter 'input.path' has length greater than 1 and only the ", - "first element will be used.") - } +LoadMetrics <- function(input_path, metrics, var, system, reference, + period = NULL, start_months = NULL, + forecast_months = NULL, inf_to_na = FALSE, + calib_method = NULL, syear = NULL) { + ## Remove . from names system <- gsub('.','', system, fixed = T) reference <- gsub('.','', reference, fixed = T) - period <- paste0(start.year, "-", end.year) - ## Define empty list to saved data all_metrics <- sapply(system, function(x) NULL) ## Load data for each system @@ -122,14 +63,15 @@ LoadMetrics <- function(system, reference, var, start.year, end.year, ## Load data for each reference for (ref in 1:length(reference)) { ## Call function to load metrics data - met <- .Loadmetrics(input.path = input.path, # recipe$Run$output, + met <- .loadmetrics(input_path = input_path, # recipe$Run$output, system = system[sys], reference = reference[ref], var = var, period = period, - start.months = start.months, - forecast.months = forecast.months, - metrics = metrics) + start_months = start_months, + forecast_months = forecast_months, + metrics = metrics, calib_method = calib_method, + syear = syear) ## Save metric data as array in reference list by_reference[[reference[ref]]] <- met ## Remove -Inf from crpss data if variable is precipitation @@ -142,74 +84,41 @@ LoadMetrics <- function(system, reference, var, start.year, end.year, } ## close loop on system return(all_metrics) -} ## close function +} -############################################################ +.loadmetrics <- function(input_path, metrics, var, system = NULL, + reference = NULL, period = NULL, start_months = NULL, + forecast_months = NULL, calib_method = NULL, + syear = NULL) { + # (1) Create the path to the files + directory_path <- paste0(input_path, system, "/", reference, "/", + calib_method, "/", var, "/") + file_path <- paste0(directory_path, "scorecards_", system, "_", reference, + "_", var, "_$var$_", period, "_s", "$smonths$", ".nc") -.Loadmetrics <- function(input.path, system, reference, - var, period, start.months, - forecast.months, metrics) { - - ## Load data for each start date - allfiles <- sapply(start.months, function(m) { - paste0(input.path, "/", system, "/", var, - "/scorecards_", system, "_", reference, "_", - var, "-skill_", period, "_s", m, # mod.pressure, - ".nc")}) - allfiles_exist <- sapply(allfiles, file.exists) - - # Check dims - files_exist_by_month <- seq(1:length(allfiles))[allfiles_exist] - allfiledims <- sapply(allfiles[allfiles_exist], easyNCDF::NcReadDims) - if (length(files_exist_by_month) == 0) { - stop("No files are found.") - } + # (2) Create the startR arguments list + if (is.null(forecast_months)) forecast_months <- 'all' + if (is.null(start_months)) start_months <- 'all' - num_dims <- numeric(dim(allfiledims)[1]) - for (i in 1:dim(allfiledims)[1]) { - if (length(unique(allfiledims[i,])) > 1) { - warning(paste0("Dimensions of system ", system," with var ", var, - " don't match.")) - } - num_dims[i] <- max(allfiledims[i,]) # We take the largest dimension + args = list(dat = file_path, + var = metrics, + longitude = 'all', + latitude = 'all', + time = forecast_months, + syear = "all", + smonths = start_months, + return_vars = list(longitude = 'dat', + latitude = 'dat', + time = NULL), + metadata_dims = c('dat', 'var'), + retrieve = TRUE) + + if (is.null(syear)) { + args$syear <- NULL } - # dims: [metric, longitude, latitude, time, smonth] - # or [metric, region, time, smonth] - - # Loop for file - dim(allfiles) <- c(dat = 1, sdate = length(allfiles)) - - array_met_by_sdate <- Apply(data = allfiles, target_dims = 'dat', fun = function(x) { - if (file.exists(x)) { - res <- easyNCDF::NcToArray(x, vars_to_read = metrics, unlist = T, - drop_var_dim = T) - names(dim(res)) <- NULL - } else { - res <- array(dim = c(length(metrics), allfiledims[-1,1])) - names(dim(res)) <- NULL - } - res})$output1 - - dim(array_met_by_sdate) <- c(metric = length(metrics), allfiledims[-1,1], - sdate = length(allfiles)) + + # (3): Call startR + loaded_metrics_start <- do.call(Start, args = args) - # Attributes - # Read attributes from the first existing file - if ("region" %in% rownames(allfiledims)) { - file_for_att <- ncdf4::nc_open(allfiles[allfiles_exist[1]]) - region <- ncdf4::ncatt_get(file_for_att, 'region') - ncdf4::nc_close(file_for_att) - attributes(array_met_by_sdate)$region <- region - } else { - lon <- easyNCDF::NcToArray(allfiles[allfiles_exist][1], vars_to_read = 'longitude', - unlist = T, drop_var_dim = T) - lat <- easyNCDF::NcToArray(allfiles[allfiles_exist][1], vars_to_read = 'latitude', - unlist = T, drop_var_dim = T) - attributes(array_met_by_sdate)$lon <- lon - attributes(array_met_by_sdate)$lat <- lat - } - attributes(array_met_by_sdate)$metrics <- metrics - attributes(array_met_by_sdate)$start.months <- start.months - attributes(array_met_by_sdate)$forecast.months <- forecast.months - return(array_met_by_sdate) + return(loaded_metrics_start) } diff --git a/modules/Scorecards/Scorecards.R b/modules/Scorecards/Scorecards.R index 0dbcd921..8312735a 100644 --- a/modules/Scorecards/Scorecards.R +++ b/modules/Scorecards/Scorecards.R @@ -28,13 +28,18 @@ Scorecards <- function(recipe) { start.year <- as.numeric(recipe$Analysis$Time$hcst_start) end.year <- as.numeric(recipe$Analysis$Time$hcst_end) forecast.months <- recipe$Analysis$Time$ftime_min : recipe$Analysis$Time$ftime_max - - if (recipe$Analysis$Workflow$Scorecards$start_months == 'all') { - start.months <- 1:12 - } else { - start.months <- as.numeric(strsplit(recipe$Analysis$Workflow$Scorecards$start_months, - split = ", | |,")[[1]]) - } + calib.method <- tolower(recipe$Analysis$Workflow$Calibration$method) + + # NOTE (Eva): This condition needs to be checked, in my case + # (recipe$Analysis$Workflow$Scorecards$start_months = NULL) + start.months <- 1:12 # I added this line + # Needs to be corrected: + # if (recipe$Analysis$Workflow$Scorecards$start_months == 'all') { + # start.months <- 1:12 + # } else { + # start.months <- as.numeric(strsplit(recipe$Analysis$Workflow$Scorecards$start_months, + # split = ", | |,")[[1]]) + # } regions <- recipe$Analysis$Workflow$Scorecards$regions for (i in names(regions)){regions[[i]] <- unlist(regions[[i]])} @@ -76,17 +81,26 @@ Scorecards <- function(recipe) { ncores <- 1 # recipe$Analysis$ncores ## Load data files - loaded_metrics <- LoadMetrics(system = system, - reference = reference, - var = var, - start.year = start.year, - end.year = end.year, - metrics = metrics.load, - start.months = start.months, - forecast.months = forecast.months, - inf_to_na = inf.to.na, - input.path = input.path) - + start.months <- sprintf("%02d", start.months) + period <- paste0(start.year, "-", end.year) + + # NOTE (Eva): This is an example: + if (any(metrics.load %in% 'rps_syear')) { + metric_rps_syear <- .loadmetrics(input_path = input.path, system = system, + reference = reference, var = var, + period = period, start_months = start.months, + forecast_months = forecast.months, + metrics = 'rps_syear', + calib_method = calib.method, syear = TRUE) + } else if (any(metrics.load %in% c('crps', 'mean_bias'))) { + metrics <- LoadMetrics(input_path = input.path, system = system, + reference = reference, var = var, + period = period, start_months = start.months, + forecast_months = forecast.months, + metrics = c('crps', 'mean_bias'), + calib_method = calib.method) + } + if('region' %in% names(dim(loaded_metrics[[1]][[1]]))){ diff --git a/modules/Skill/Skill.R b/modules/Skill/Skill.R index 6c066ff5..9ffd6369 100644 --- a/modules/Skill/Skill.R +++ b/modules/Skill/Skill.R @@ -67,7 +67,7 @@ Skill <- function(recipe, data, agg = 'global') { cross.val <- recipe$Analysis$Workflow$Skill$cross_validation } skill_metrics <- list() - for (metric in strsplit(metrics, ", | |,")[[1]]) { + for (metric in strsplit(metrics, ", | |,")) { # Whether the fair version of the metric is to be computed if (metric %in% c('frps', 'frpss', 'bss10', 'bss90', 'fcrps', 'fcrpss')) { -- GitLab From 1323dc4e4ce3f3c721ff272fc760fb6cfccc0611 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Fri, 24 Nov 2023 10:06:32 +0100 Subject: [PATCH 22/78] Bugfix: name subdirectories when no calibration method is chosen --- modules/Saving/R/get_dir.R | 15 +++++++++------ modules/Saving/R/get_filename.R | 2 +- tools/prepare_outputs.R | 2 +- 3 files changed, 11 insertions(+), 8 deletions(-) diff --git a/modules/Saving/R/get_dir.R b/modules/Saving/R/get_dir.R index a2cbc79f..b8463114 100644 --- a/modules/Saving/R/get_dir.R +++ b/modules/Saving/R/get_dir.R @@ -38,18 +38,21 @@ get_dir <- function(recipe, variable, agg = "global") { } } ## TODO: Remove calibration method from output directory? - calib.method <- tolower(recipe$Analysis$Workflow$Calibration$method) + if (!is.null(recipe$Analysis$Workflow$Calibration$method)) { + calib.method <- paste0(tolower(recipe$Analysis$Workflow$Calibration$method), "-") + } else { + calib.method <- "" + } store.freq <- recipe$Analysis$Variables$freq - ## TODO: Change "_country" if (!is.null(recipe$Analysis$Region$name)) { outdir <- paste0(outdir, "/", recipe$Analysis$Region$name) } switch(tolower(agg), - "country" = {dir <- paste0(outdir, "/", system, "/", calib.method, - "-", store.freq, "/", variable, - "_country/", fcst.sdate, "/")}, + "region" = {dir <- paste0(outdir, "/", system, "/", calib.method, + store.freq, "/", variable, + "_region/", fcst.sdate, "/")}, "global" = {dir <- paste0(outdir, "/", system, "/", calib.method, - "-", store.freq, "/", variable, "/", + store.freq, "/", variable, "/", fcst.sdate, "/")}) } diff --git a/modules/Saving/R/get_filename.R b/modules/Saving/R/get_filename.R index 1c925651..54bea81c 100644 --- a/modules/Saving/R/get_filename.R +++ b/modules/Saving/R/get_filename.R @@ -16,7 +16,7 @@ get_filename <- function(dir, recipe, var, date, agg, file.type) { } switch(tolower(agg), - "country" = {gg <- "-country"}, + "region" = {gg <- "-region"}, "global" = {gg <- ""}) system <- gsub('.','', recipe$Analysis$Datasets$System$name, fixed = T) diff --git a/tools/prepare_outputs.R b/tools/prepare_outputs.R index 54e82095..f9942525 100644 --- a/tools/prepare_outputs.R +++ b/tools/prepare_outputs.R @@ -91,7 +91,7 @@ prepare_outputs <- function(recipe_file, } # Restructure the recipe to make the atomic recipe more readable if (restructure) { - recipe <- restructure_recipe(recipe) + recipe <- restructure_recipe(recipe) } # Run recipe checker if (disable_checks) { -- GitLab From 681d409c123267df48805680d355200ffada4e95 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Fri, 24 Nov 2023 11:02:01 +0100 Subject: [PATCH 23/78] Add Calibration to recipe and script --- .../ex1_3-recipe.yml | 20 +++++++++---------- .../ex1_3-script.R | 2 ++ 2 files changed, 11 insertions(+), 11 deletions(-) diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml b/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml index 495f89f0..a4231e6a 100644 --- a/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml @@ -26,26 +26,24 @@ Analysis: lonmin: 0 lonmax: 359.9 Regrid: - method: 'bilinear' - type: 'to_system' + method: bilinear + type: to_system Workflow: + Calibration: + method: mse_min + save: none Anomalies: compute: yes cross_validation: no save: none Indices: - Nino1+2: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} - Nino3: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} - Nino3.4: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} - Nino4: {save: 'all', plot_ts: TRUE, plot_sp: TRUE} + Nino1+2: {save: all, plot_ts: yes, plot_sp: yes} + Nino3: {save: all, plot_ts: yes, plot_sp: yes} + Nino3.4: {save: all, plot_ts: yes, plot_sp: yes} + Nino4: {save: all, plot_ts: yes, plot_sp: yes} Skill: metric: mean_bias EnsCorr rps rpss crps crpss EnsSprErr save: 'all' - Probabilities: - percentiles: [[1/3, 2/3], [1/10, 9/10]] - save: none - Indicators: - index: no ncores: 8 remove_NAs: yes Output_format: S2S4E diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R b/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R index 59843b44..146d0d78 100644 --- a/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R @@ -22,6 +22,8 @@ recipe <- read_atomic_recipe(recipe_file) data <- Loading(recipe) # Check units and transform if needed data <- Units(recipe, data) +# Calibrate data +data <- Calibration(recipe, data) # Compute tos anomalies data <- Anomalies(recipe, data) # Compute Niรฑo Indices -- GitLab From b532d159da5880222356549b7a56aca1db13442b Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Fri, 24 Nov 2023 14:59:42 +0100 Subject: [PATCH 24/78] Write explanations for use case 3 (WIP) --- .../ex1_3-handson.md | 85 ++++++++++++++++++- 1 file changed, 84 insertions(+), 1 deletion(-) diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md b/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md index e310d289..0f3f19d4 100644 --- a/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md @@ -1,7 +1,9 @@ # Hands-on 1.3: Computation of El Niรฑo indices for two seasonal models ## Goal -Create a SUNSET recipe to compute and evaluate the skill of several El Niรฑo indices (Niรฑo1+2, Niรฑo3, Niรฑo3.4 and Niรฑo4) for two models: ECMWF-SEAS5 and MeteoFrance System 7. The computation for each model will be run in the cluster as two separate jobs. +Create a SUNSET recipe to compute and evaluate the skill of several El Niรฑo indices (Niรฑo1+2, Niรฑo3, Niรฑo3.4 and Niรฑo4) for two models: ECMWF-SEAS5 and MeteoFrance System 7. We include the information for both of the models in a single recipe, and the SUNSET Launcher will split the recipe into two 'atomic recipes': one for each model. The computation for atomic recipe will be run in the cluster as two separate jobs. + +It is also possible to split a recipe along different Reference datasets, Variables and Start Dates. ## 0. Cloning the SUNSET repository @@ -14,3 +16,84 @@ git clone https://earth.bsc.es/gitlab/es/sunset.git ## 1. Modifying the recipe +The template recipe for this use case can be found in `use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml`. You should open it with an editor such as emacs or vim: + +```shell +# cd to the main SUNSET directory +# Open the recipe with a text editor such as vim or emacs +vim use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml +``` + +Then, under the 'Run' section of the recipe, you should edit the parameters `output_dir` and `code_dir` to point to your desire output directory and to the directory where your SUNSET code is stored, respectively. + +Feel free to also modify other aspects of the reicpe according to your particular needs. You can read more about the parameters and the available modules in the SUNSET wiki. + +## 2. The user-defined script + +The SUNSET Launcher is a bash script named launch_SUNSET.sh that can be found in the main directory of the SUNSET repository. When working without Autosubmit, it runs in two steps: + +1. Running the recipe checks, splitting the recipe into atomic recipes and creating the directory for the outputs. +2. Sending jobs to the cluster to run the user-defined script for each atomic recipe, using SLURM. + +The prepare_outputs() function is already incorporated into the first step. For that reason, it does not need to be included in the user-defined script in this particular case. In its place, we will use the function read_atomic_recipe(). The recipe path is passed as an argument onto the R script. The beginning of our script should look like this: + +```R +# Load the modules to be used +source("modules/Loading/Loading.R") +source("modules/Units/Units.R") +source("modules/Anomalies/Anomalies.R") +source("modules/Indices/Indices.R") +source("modules/Skill/Skill.R") + +# Define the recipe path as the first argument from the command line +args = commandArgs(trailingOnly = TRUE) +recipe_file <- args[1] +# Read the atomic recipe +recipe <- read_atomic_recipe(recipe_file) +``` + +The rest of the user-defined script can be written in the same way as any other SUNSET script: + +```R +# Load data +data <- Loading(recipe) +# Check units and transform if needed +data <- Units(recipe, data) +# Calibrate data +data <- Calibration(recipe, data) +# Compute tos anomalies +data <- Anomalies(recipe, data) +# Compute Niรฑo Indices +nino_indices <- Indices(data = data, recipe = recipe) + +# We can compute the Skill metrics for each of the El Niรฑo indices, +# specifying that the data is spatially aggregated, with the parameter +# agg = "region". +for (index in nino_indices) { + nino_skill_metrics <- Skill(recipe = recipe, data = index, agg = "region") +} +``` + +A complete, ready-to-use sample of this example script can be found in `use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R`. You can execute it as-is or copy it and modify it according to your specific needs. + +## 3. Launching the jobs with the SUNSET Launcher + +When working without Autosubmit, the SUNSET Launcher should be run directly from the HPC machine where the jobs will run(for example, Nord3v2). Make sure to ssh to the machine first. You can obtain detailed usage information by running: + +```shell +bash launch_SUNSET.sh --help +``` + +The mandatory arguments are the paths to the recipe and the script. We can also include other optional arguments to be used by SLURM, such as the number of CPUs to request (--cpus), the wallclock time for each job (--wallclock) and other extra directives (--custom_directives). You can refer to the [Nord3v2 user guide](https://www.bsc.es/user-support/nord3v2.php#jobdirectives) and the [SLURM sbatch documentation](https://slurm.schedmd.com/sbatch.html) for more information on the available options for the parameters. + +In this case, we are giving each job a wallclock time of 1 hour and requesting exclusive usage of all the cores in one node. The shell command to run SUNSET will look like this: + +```shell +bash launch_SUNSET.sh use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R --wallclock=01:00:00 --custom_directives="--exclusive" +``` + +You can check the status of your running jobs with the `squeue` command. The SLURM logs will be inside of your $code_dir, in a subfolder named 'out-logs'. It can be useful to check them in case of errors. + +## 4. Results and plots + + -- GitLab From eb664fab24ca2316bb5a61ddbec99d11dab159ef Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Fri, 24 Nov 2023 15:00:48 +0100 Subject: [PATCH 25/78] fix typo --- use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md b/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md index 391d4856..6315cd86 100644 --- a/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md +++ b/use_cases/ex1_1_single_analysis_terminal/ex1_1-handson.md @@ -16,7 +16,8 @@ git clone https://earth.bsc.es/gitlab/es/sunset.git SUNSET uses YAML configuration files called 'recipes' to specify which data you want to load and the details of the different steps of the workflow. In this example, we want to evaluate the temperature-at-surface (tas) monthly means, using MeteoFrance System 7 data as our experiment and ERA5 as our reference dataset, for the initialization month of November. -There is a template file +There is a template file for this hands-on tutorial, which you can open with a text editor: + ```shell # cd to the main SUNSET directory # Open the recipe with a text editor such as vim or emacs -- GitLab From 252efc91dc355360a7cf23c33e352db512e20c82 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Fri, 24 Nov 2023 16:55:39 +0100 Subject: [PATCH 26/78] Refine split.R autosubmit checks --- split.R | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/split.R b/split.R index 8328e460..9bd95e86 100755 --- a/split.R +++ b/split.R @@ -34,7 +34,7 @@ recipe <- prepare_outputs(recipe_file = arguments$recipe, ## TODO: Add autosubmit yes/no to the parameters? run_parameters <- divide_recipe(recipe) -if (recipe$Run$autosubmit) { +if (!is.null(recipe$Run$autosubmit) && (recipe$Run$autosubmit)) { write_autosubmit_conf(recipe, run_parameters$n_atomic_recipes) sink(arguments$tmpfile, append = FALSE) # Run with... @@ -56,4 +56,7 @@ if (recipe$Run$autosubmit) { cat("TRUE") } sink() +} else { + stop("Autosubmit is not selected but no temp file was provided by the + launcher. Please open an issue to report the problem.") } -- GitLab From 5b56b359f3de9ff305eaa35db539405c8932611a Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Mon, 27 Nov 2023 12:46:54 +0100 Subject: [PATCH 27/78] Fix month name in plot titles --- modules/Indices/R/compute_nino.R | 41 +++++++++++++++++++------------- 1 file changed, 25 insertions(+), 16 deletions(-) diff --git a/modules/Indices/R/compute_nino.R b/modules/Indices/R/compute_nino.R index 8fd2c9c8..915dc9ce 100644 --- a/modules/Indices/R/compute_nino.R +++ b/modules/Indices/R/compute_nino.R @@ -208,6 +208,7 @@ compute_nino <- function(data, recipe, region, standardised = TRUE, } } if (plot_sp) { + ## TODO: Remove sourcing of plot robinson and viz module code source("modules/Visualization/R/tmp/PlotRobinson.R") source("modules/Indices/R/correlation_eno.R") source("modules/Visualization/R/get_proj_code.R") @@ -227,28 +228,36 @@ compute_nino <- function(data, recipe, region, standardised = TRUE, correl_hcst <- Apply(list(data$hcst$data, nino$hcst$data), target_dims = c('syear', 'ensemble'), fun = function(x, y) { - x <- apply(x, 1, mean, na.rm = TRUE) - y <- apply(y, 1, mean, na.rm = TRUE) - dim(y) <- c(syear = length(y)) - dim(x) <- c(syear = length(x)) - res <- .correlation_eno(x, y, - time_dim = 'syear', method = 'pearson', alpha = alpha, - test.type = 'two-sided', pval = FALSE)}, - ncores = recipe$Analysis$ncores) + x <- apply(x, 1, mean, na.rm = TRUE) + y <- apply(y, 1, mean, na.rm = TRUE) + dim(y) <- c(syear = length(y)) + dim(x) <- c(syear = length(x)) + res <- .correlation_eno(x, y, time_dim = 'syear', + method = 'pearson', + alpha = alpha, + test.type = 'two-sided', + pval = FALSE)}, + ncores = recipe$Analysis$ncores) correl_hcst_full <- Apply(list(data$hcst$data, nino$hcst$data), target_dims = c('syear', 'ensemble'), fun = function(x,y) { - dim(y) <- c(syear = length(y)) - dim(x) <- c(syear = length(x)) - res <- .correlation_eno(x, y, - time_dim = 'syear', method = 'pearson', alpha = alpha, - test.type = 'two-sided', pval = FALSE)}, + dim(y) <- c(syear = length(y)) + dim(x) <- c(syear = length(x)) + res <- .correlation_eno(x, y, + time_dim = 'syear', + method = 'pearson', + alpha = alpha, + test.type = 'two-sided', + pval = FALSE)}, ncores = recipe$Analysis$ncores) + months <- lubridate::month(Subset(data$hcst$attrs$Dates, "syear", indices = 1), + label = T, abb = F, locale = "en_GB") + for (tstep in 1:dim(nino$obs$data)['time']) { map <- Subset(correl_obs$r, along = 'time', ind = tstep, drop = T) sig <- Subset(correl_obs$sig, along = 'time', ind = tstep, drop = T) if (tolower(recipe$Analysis$Horizon) == "seasonal") { - mes <- as.numeric(substr(recipe$Analysis$Time$sdate, 1,2)) + + mes <- as.numeric(substr(recipe$Analysis$Time$sdate, 1, 2)) + (tstep - 1) + (recipe$Analysis$Time$ftime_min - 1) mes <- ifelse(mes > 12, mes - 12, mes) fmonth <- sprintf("%02d", tstep - 1 + recipe$Analysis$Time$ftime_min) @@ -313,7 +322,7 @@ compute_nino <- function(data, recipe, region, standardised = TRUE, toptitle <- paste(recipe$Analysis$Datasets$System$name, "\n", "Ni\u00F1o", region_name, "SST Index -",var_name, "\n", "Correlation /", - month.abb[as.numeric(fmonth)], + month.abb[mes], "/", recipe$Analysis$Time$hcst_start, "-", recipe$Analysis$Time$hcst_end) plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/", @@ -367,7 +376,7 @@ compute_nino <- function(data, recipe, region, standardised = TRUE, toptitle <- paste(recipe$Analysis$Datasets$System$name, "\n", "Ni\u00F1o", region_name, "SST Index -",var_name, "\n", " Correlation /", - month.abb[as.numeric(fmonth)], + month.abb[mes], "/", recipe$Analysis$Time$hcst_start, "-", recipe$Analysis$Time$hcst_end) plotfile <- paste0(recipe$Run$output_dir, "/plots/Indices/", -- GitLab From fb5f099d5f5cbdbf7b77928999bc5e21af5e5ff2 Mon Sep 17 00:00:00 2001 From: Victoria Agudetse Roures Date: Mon, 27 Nov 2023 14:17:30 +0100 Subject: [PATCH 28/78] Edit 1.3 script, add figures --- .../ex1_3-handson.md | 11 ++++++++++- .../ex1_3-script.R | 2 +- .../nino34_ECMWF-SEAS5_ERA5_s1101_ftime02.png | Bin 0 -> 61630 bytes ...Meteo-France-System7_ERA5_s1101_ftime02.png | Bin 0 -> 59446 bytes ...n_tos_ensmean_ECMWF-SEAS5_s1101_ftime02.png | Bin 0 -> 937910 bytes ...mean_Meteo-France-System7_s1101_ftime02.png | Bin 0 -> 918256 bytes 6 files changed, 11 insertions(+), 2 deletions(-) create mode 100644 use_cases/ex1_3_nino_indices_comparison/figures/nino34_ECMWF-SEAS5_ERA5_s1101_ftime02.png create mode 100644 use_cases/ex1_3_nino_indices_comparison/figures/nino34_Meteo-France-System7_ERA5_s1101_ftime02.png create mode 100644 use_cases/ex1_3_nino_indices_comparison/figures/nino34_correlation_tos_ensmean_ECMWF-SEAS5_s1101_ftime02.png create mode 100644 use_cases/ex1_3_nino_indices_comparison/figures/nino34_correlation_tos_ensmean_Meteo-France-System7_s1101_ftime02.png diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md b/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md index 0f3f19d4..42068784 100644 --- a/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-handson.md @@ -92,8 +92,17 @@ In this case, we are giving each job a wallclock time of 1 hour and requesting e bash launch_SUNSET.sh use_cases/ex1_3_nino_indices_comparison/ex1_3-recipe.yml use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R --wallclock=01:00:00 --custom_directives="--exclusive" ``` -You can check the status of your running jobs with the `squeue` command. The SLURM logs will be inside of your $code_dir, in a subfolder named 'out-logs'. It can be useful to check them in case of errors. +You can check the status of your running jobs with the `squeue` command. The SLURM logs will be inside of your code directory, in a subfolder named 'out-logs'. It can be useful to check them in case of errors. ## 4. Results and plots +The spatial pattern and time series plots that were requested are saved inside `plots/Indices/` in the output directory. There will be one set of plots for each El Niรฑo index, with a descriptive file name providing information about the content of the plot, the system/reference datasets, the start date and the forecast time. Here are some examples of the results: +Spatial correlation for the ensemble mean: + +![](./figures/nino34_correlation_tos_ensmean_ECMWF-SEAS5_s1101_ftime02.png) +![](./figures/nino34_correlation_tos_ensmean_Meteo-France-System7_s1101_ftime02.png) + +Time series comparison between the model and the reference dataset (ERA5): +![](./figures/nino34_ECMWF-SEAS5_ERA5_s1101_ftime02.png) +![](./figures/nino34_Meteo-France-System7_ERA5_s1101_ftime02.png) diff --git a/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R b/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R index 146d0d78..c2b0ba34 100644 --- a/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R +++ b/use_cases/ex1_3_nino_indices_comparison/ex1_3-script.R @@ -23,7 +23,7 @@ data <- Loading(recipe) # Check units and transform if needed data <- Units(recipe, data) # Calibrate data -data <- Calibration(recipe, data) +# data <- Calibration(recipe, data) # Compute tos anomalies data <- Anomalies(recipe, data) # Compute Niรฑo 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