diff --git a/DESCRIPTION b/DESCRIPTION
index cb851d8d32c9549e7e23b29dc453481c71bd8f60..47179386c5e18b5488e850c0322eee267c39db31 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -18,10 +18,8 @@ Imports:
htmlwidgets,
httr,
leaflet,
- leafpop,
lubridate,
magrittr,
- mapview (>= 2.5.5),
markdown,
readr,
rlang,
diff --git a/R/fct_graph.R b/R/fct_graph.R
index f03369b2aff59b44d00faabbde99f4b4fda42ee7..0f3ee2d0660f376cb0e8602d898eb6bb867aed84 100644
--- a/R/fct_graph.R
+++ b/R/fct_graph.R
@@ -273,7 +273,7 @@ add_graph_objectif <- function(gg, obj_filtered) {
#' @examples
#' girafeTEO(gg, extract_name_id = 'graph_production')
girafeTEO <- function(plot, extract_name) {
- ggiraph::ggiraph(
+ ggiraph::girafe(
print(plot),
width_svg = 9,
height_svg = 6,
diff --git a/R/fct_map.R b/R/fct_map.R
deleted file mode 100644
index 8eb6fc730c473f2226f61e417386aa61ced9cf7d..0000000000000000000000000000000000000000
--- a/R/fct_map.R
+++ /dev/null
@@ -1,52 +0,0 @@
-library('leaflet')
-library('mapview')
-library('leafpop')
-library('sf')
-library('stringr')
-
-
-#définition des cartes de base : france entiere montre les régions métropolitaine, si l'on sélectionne cela zoome sur les départements ou régions citées, OM inclus
-#ces contours servent dans le cas où il n'y a pas de sites de production dans une zone ou dans le cas ou on ne coche aucune fillière
-create_base_map <- function(carto_reg, carto_base, code_region, code_departement) {
- req(code_region,code_departement)
- if (code_region == "France") {
- base <-
- mapview::mapview(
- dplyr::filter(carto_reg, !stringr::str_detect(.data$REG, "^0")),
- legend = FALSE,
- alpha = 1,
- col.regions = "green",
- alpha.regions = 0.15,
- homebutton = F,
- label = NULL,
- layer.name = "Contours"
- )
- } else {
- tomap <-
- dplyr::filter(carto_base,
- .data$CodeZone %in% code_region | .data$CodeZone %in% code_departement)
- base <- mapview::mapview(
- tomap,
- legend = FALSE,
- alpha = 1,
- col.regions = "green",
- alpha.regions = 0.15,
- homebutton = F,
- label = NULL,
- layer.name = "Contours"
- )
-
- return(base)
- }
-
- base@map <- base@map %>% leaflet::addTiles(
- urlTemplate = "https://wxs.ign.fr/essentiels/geoportail/wmts?REQUEST=GetTile&SERVICE=WMTS&VERSION=1.0.0&STYLE=normal&TILEMATRIXSET=PM&FORMAT=image/png&LAYER=GEOGRAPHICALGRIDSYSTEMS.PLANIGNV2&TILEMATRIX={z}&TILEROW={y}&TILECOL={x}",
- options = leaflet::WMSTileOptions(tileSize = 256),
- group = "IGN"
- ) %>%
- leaflet::addProviderTiles("GeoportailFrance.ignMaps", group = "ESRI Topo")
-
- return(base@map)
-}
-
-
diff --git a/R/fct_table.R b/R/fct_table.R
index 52ec63a54fc3222f365d7a2cade16a4fc8ae73b1..9a792b5692fa0c33b2a679e5eb655ad493e300cc 100644
--- a/R/fct_table.R
+++ b/R/fct_table.R
@@ -190,7 +190,7 @@ prepare_table_obj <-function(objectifs, sel_region, sel_filiere) {
for (key in names(filiere_labels_select)){
objectifs <- objectifs %>%
mutate(
- Énergie = case_when(
+ Énergie = dplyr::case_when(
.data$Énergie == key ~ filiere_labels_select[key],
T ~ .data$Énergie
)
diff --git a/R/mod_accueil.R b/R/mod_accueil.R
index c55e98a65fad826333991f1b77d521ce7406cba4..d28158c66f639e47dc80ad0e2105956200c9a81f 100644
--- a/R/mod_accueil.R
+++ b/R/mod_accueil.R
@@ -11,8 +11,6 @@
# load libraries
library('shinyscreenshot')
library('leaflet')
-library('mapview')
-library('leafpop')
library('sf')
library('stringr')
library('sfarrow')
@@ -24,10 +22,21 @@ library('shinyjs')
# load mapping region - departement
load('./data/unique_reg_dep.rda')
+# couleurs utilisées pour la carte leaflet
+couleurs <-
+ c("Cogénération électrique (biogaz)"= "#e78ac3",
+ "Éolien terrestre" = "#8da0cb",
+ "Injection biogaz" = "#66c2a5",
+ "Photovoltaïque"="#ffd92f")
+
+df_couleurs <- as.data.frame(couleurs) %>%
+ tibble::rownames_to_column(var = "Type")
+
# load data
dta <- sfarrow::st_read_parquet("data/dta.parquet") %>%
+ dplyr::left_join(df_couleurs, by = "Type") %>%
dplyr::rename( `Puissance (MW)` = Puissance.en.MW,
`Production (Gwh)` = Production.en.Gwh,
`Mise en service` = Mise.en.service,
@@ -341,7 +350,9 @@ mod_accueil_server <- function(id) {
# Points (installations)
installations <- eventReactive(list(input$sel_filiere, input$sel_epci, input$sel_puissance), {
- # filtere les installations à afficher en fonction de la puissance
+ message("************* Filière : ", input$sel_filiere, "************")
+
+ # filter les installations à afficher en fonction de la puissance
if (input$sel_puissance == label_filtre_puiss["all"]) {
dta_filtered <- dta
@@ -379,7 +390,7 @@ mod_accueil_server <- function(id) {
}
installations %>%
- dplyr::mutate(cex_map = sqrt(.data$`Puissance (MW)`)) %>%
+ dplyr::mutate(cex_map = sqrt(.data$`Puissance (MW)`)+3) %>%
dplyr::arrange(dplyr::desc("Puissance (MW)"))
})
@@ -391,65 +402,75 @@ mod_accueil_server <- function(id) {
limites <- limites_administratives()
installations <- installations()
+ couleurs_filtrees <- couleurs[sort(unique(installations$Type))]
+ message("*****", couleurs_filtrees, "*******")
+
# creating base map (contours / limites administratives)
- base <- mapview::mapview(
- limites,
- zcol = "Zone",
- legend = FALSE,
- alpha = 1,
- col.regions = "green",
- alpha.regions = 0.15,
- homebutton = F,
- layer.name = "Limites adminstratives",
- popup = F
- )
+ base <- leaflet::leaflet() %>%
+ leaflet::addTiles() %>%
+ leaflet::addPolygons(data= limites
+ ,fillOpacity = 0.6
+ ,fillColor = "lightgreen"
+
+ ,color = "black"
+ ,weight = 1
+ )
# returning map with or without installations based on data and filters
if (is.null(input$sel_filiere) | nrow(installations) == 0) {
carte <- base
}
else{
- carte <- base +
- mapview::mapview(
- installations %>% sf::st_jitter(factor = 0.0007),
- zcol = "Type",
- label = "label",
- cex = "cex_map",
- col.regions = map_palette[sort(unique(installations$Type))],
- legend = T,
- homebutton = F,
- layer.name = "Filière",
- popup = leafpop::popupTable(
- installations,
- zcol = c(
- "NOM_EPCI",
- "Site de production",
- "Puissance (MW)",
- "Production (Gwh)",
- "Type",
- "Mise en service"
- ),
- feature.id = FALSE,
- row.numbers = FALSE
- )
+ if(length(couleurs_filtrees) ==1) {
+ carte <- base %>%
+ leaflet::addCircleMarkers(data = installations %>%
+ sf::st_jitter(factor = 0.007),
+ fill = TRUE,
+ fillColor =unname(couleurs_filtrees),
+ fillOpacity = 0.8,
+ color = "black",
+ weight = 1,
+ opacity = 0.8,
+ radius = ~cex_map,
+ label = ~label
)
- }
+ } else {
+ # ajout des symboles (cercles) ----
+ carte <- base %>%
+ leaflet::addCircleMarkers(data = installations %>%
+ sf::st_jitter(factor = 0.007),
+ fill = TRUE,
+ fillColor = ~couleurs,
+ fillOpacity = 0.8,
+ color = "black",
+ weight = 1,
+ opacity = 0.8,
+ radius = ~cex_map,
+ label = ~label
+ )
+ } # if(length(couleurs_filtrees) ==1)
+ carte <- carte %>%
+ leaflet::addLegend(position = "topright",
+ colors = couleurs_filtrees
+ ,labels = names(couleurs_filtrees)
+ ,opacity = 0.8)
+
+ } # if()
# Adding IGN map background
- carte@map <- carte@map %>%
- leaflet::addTiles(
- urlTemplate = "https://wxs.ign.fr/essentiels/geoportail/wmts?REQUEST=GetTile&SERVICE=WMTS&VERSION=1.0.0&STYLE=normal&TILEMATRIXSET=PM&FORMAT=image/png&LAYER=GEOGRAPHICALGRIDSYSTEMS.PLANIGNV2&TILEMATRIX={z}&TILEROW={y}&TILECOL={x}",
- options = leaflet::WMSTileOptions(tileSize = 256),
- group = "IGN"
- ) %>%
- leaflet::addProviderTiles("GeoportailFrance.ignMaps", group = "IGN")
+ # carte@map <- carte@map %>%
+ # leaflet::addTiles(
+ # urlTemplate = "https://wxs.ign.fr/essentiels/geoportail/wmts?REQUEST=GetTile&SERVICE=WMTS&VERSION=1.0.0&STYLE=normal&TILEMATRIXSET=PM&FORMAT=image/png&LAYER=GEOGRAPHICALGRIDSYSTEMS.PLANIGNV2&TILEMATRIX={z}&TILEROW={y}&TILECOL={x}",
+ # options = leaflet::WMSTileOptions(tileSize = 256),
+ # group = "IGN"
+ # ) %>%
+ # leaflet::addProviderTiles("GeoportailFrance.ignMaps", group = "IGN")
- })
+ }) #fin reactive()
# Map rendering
output$map <-
leaflet::renderLeaflet({
- mapview::mapviewOptions(basemaps = c("GeoportailFrance.ignMaps"))
foundational.map()
})
diff --git a/app.R b/app.R
index 98d7525f63a04fc46d11fc2e0edea4aa2eb84de0..2ffae5cf31ccdaa533c2f3bda87df0ef20f0368d 100644
--- a/app.R
+++ b/app.R
@@ -11,8 +11,6 @@ suppressPackageStartupMessages({
library(ggiraph)
library(htmlwidgets)
library(leaflet)
- library(mapview)
- library(leafpop) #base64
library(sf)
library(dplyr)
library(DT)
diff --git a/data-raw/data/input/filiereEnR.xlsx b/data-raw/data/input/filiereEnR.xlsx
index 04aebbc088ed35acefed86212795590d4edc1e10..554f39d3dba2cc1c29d57322af6cee21ba63d682 100644
Binary files a/data-raw/data/input/filiereEnR.xlsx and b/data-raw/data/input/filiereEnR.xlsx differ
diff --git a/data-raw/pipeline/1_SDES_eolien.R b/data-raw/pipeline/1_SDES_eolien.R
index 8b1564b630c439ba63dd5ef86db03b1955cb6d2c..6bcebf828a6adb544e49cac75671c7eca42b5bba 100644
--- a/data-raw/pipeline/1_SDES_eolien.R
+++ b/data-raw/pipeline/1_SDES_eolien.R
@@ -7,13 +7,16 @@ load("./data/departement_names.rda")
load("./data/mil.rda")
-
# ---- Telechargement des données ----
+# Utilisation d'un fichier modifié par le SDES en 2024 qui sépare les types d'éoliennes (terre / mer) dans des onglets séparés
temp = tempfile(fileext = ".xlsx")
download.file(url_SDES_eolien, destfile=temp, mode='wb')
-SDES_eolien <- readxl::read_excel(temp,skip = 2)
-
+file.exists(temp) # TRUE
+# fichier modifié distingue éolien terrestre : on importe juste le bon onglet
+SDES_eolien <- readxl::read_excel(path = temp,
+ sheet="éolien_terrestre",
+ skip = 2)
# ---- PREPARATION DES DONNEES ----
# Nettoyage des noms de colonnes
diff --git a/data-raw/pipeline/1_registre_ODRE_biogaz.R b/data-raw/pipeline/1_registre_ODRE_biogaz.R
index 1bd2e82e0c6030985fc8a22d2d5f5223d2e0d96b..a84cc55c3116d21dec06f1847af58a22e5d5da5e 100644
--- a/data-raw/pipeline/1_registre_ODRE_biogaz.R
+++ b/data-raw/pipeline/1_registre_ODRE_biogaz.R
@@ -51,28 +51,37 @@ injections_annuelles_odre <-
production_de_biomethane_annuel_gwh_an,
grx_demandeur
) %>%
- sf::st_transform(crs = EPSG_reg) %>%
+ sf::st_transform(crs = EPSG_reg)
+
+injections_annuelles_odre <- injections_annuelles_odre %>%
dplyr::mutate(
- id_unique_projet = as.character(id_unique_projet),
- annee = as.character(annee),
+ id_unique_projet = as.integer(id_unique_projet), # modif TZ
+ annee = as.integer(annee), # modif TZ
annee_mes = lubridate::year(lubridate::ymd(date_de_mes))
) %>%
- dplyr::select(-date_de_mes)
-
-# on crée un version des données en regroupant les millesimes et mesure
-# dans un table imbriqué dans la colonne data_annuelles
-injections_annuelles_odre2 <- injections_annuelles_odre %>%
- st_drop_geometry() %>%
dplyr::group_by(id_unique_projet) %>%
dplyr::arrange(annee) %>%
# les propriétés des installations peuvent varier au fil des ans, comme les catégories, ont unifie le dataset
+ # TZ : on crée une variable temporaire "prod_max" qui sert a estimer la capacité de prod, pour les cas où cette capacité == 0
dplyr::mutate(
- capacite_de_production_gwh_an = dplyr::last(capacite_de_production_gwh_an),
+ prod_max = max(production_de_biomethane_annuel_gwh_an),
+ capacite_de_production_gwh_an =
+ dplyr::last(capacite_de_production_gwh_an),
+ capacite_de_production_gwh_an =
+ if_else(capacite_de_production_gwh_an < 0.000001,
+ prod_max,
+ capacite_de_production_gwh_an),
annee_1ere_mes = min(annee_mes),
lib_installation = dplyr::last(lib_installation),
typologie = dplyr::last(typologie),
) %>%
dplyr::ungroup() %>%
+ dplyr::select(-date_de_mes, -prod_max)
+
+# on crée un version des données en regroupant les millesimes et mesure
+# dans un table imbriqué dans la colonne data_annuelles
+injections_annuelles_odre2 <- injections_annuelles_odre %>%
+ st_drop_geometry() %>%
dplyr::group_by(
id_unique_projet,
lib_installation,
@@ -80,8 +89,10 @@ injections_annuelles_odre2 <- injections_annuelles_odre %>%
annee_1ere_mes,
capacite_de_production_gwh_an,
grx_demandeur
- ) %>%
- dplyr::select(group_cols(), annee, production_de_biomethane_annuel_gwh_an) %>%
+ ) %>%
+ dplyr::arrange(annee) %>%
+ dplyr::select(group_cols(), annee,
+ production_de_biomethane_annuel_gwh_an) %>%
tidyr::nest(data_annuelles = c(annee, production_de_biomethane_annuel_gwh_an)) %>%
dplyr::ungroup()
@@ -101,6 +112,7 @@ point_injection_odre <-
st_read(
"https://opendata.reseaux-energies.fr/explore/dataset/points-dinjection-de-biomethane-en-france/download/?format=geojson&timezone=Europe/Berlin"
) %>%
+ mutate(id_unique_projet = as.integer(id_unique_projet)) %>%
select(-coordonnees)
# Mise à jour des codes communes et des uniformisation des regions, departement et EPCI avec COGiter
@@ -123,6 +135,7 @@ point_injection_odre <- point_injection_odre %>%
# ---- REGISTRE_ ENRICHI1 : JOINTURE DES DEUX SOURCES DE DONNEES ----
# on garde les id présentes dans point_injection_odre
+
registre_enrichi1 <- point_injection_odre %>%
mutate(geometrie = st_as_text(geometry)) %>%
st_drop_geometry() %>%
@@ -148,8 +161,7 @@ registre_enrichi1 <- registre_enrichi1 %>%
# L'annee de mise en service est uniformisé sur un projet
registre_enrichi1 <- registre_enrichi1 %>%
- mutate(annee_1ere_mes = coalesce(as.character(annee_1ere_mes), as.character(annee_mes))
-)
+ mutate(annee_1ere_mes = coalesce(annee_1ere_mes, annee_mes))
# selection des colonnes utile pour la suite du traitement
registre_enrichi1 <- registre_enrichi1 %>%
@@ -188,12 +200,15 @@ registre_enrichi1 <- registre_enrichi1 %>%
mil_disp <-
injections_annuelles_odre2 %>% unnest(cols = data_annuelles) %>% pull(annee) %>% unique() %>% sort()
+injections_annuelles_odre <- injections_annuelles_odre %>%
+ filter(!is.na(annee_mes))
+
# recherche des millesime manquants pour chaque projet
ins_x_mil_mq <- injections_annuelles_odre %>%
sf::st_drop_geometry() %>%
dplyr::group_by(id_unique_projet) %>%
# on garde la première année de mise en service par installation
- dplyr::mutate(annee_1ere_mes = min(as.integer(as.character(annee_mes)))) %>%
+ dplyr::mutate(annee_1ere_mes = min(annee_mes)) %>%
dplyr::ungroup() %>%
dplyr::group_by(id_unique_projet, annee_1ere_mes) %>%
dplyr::summarise(mil_disp = list(annee), .groups = "drop") %>%
@@ -210,7 +225,8 @@ ins_x_mil_mq_avec_attributs <- ins_x_mil_mq %>%
select(-data_annuelles) %>%
rename(annee = mil_mq) %>%
left_join(point_injection_odre %>%
- select(id_unique_projet, date_de_mes, site), by = "id_unique_projet") %>%
+ select(id_unique_projet, date_de_mes, site),
+ by = "id_unique_projet") %>%
select(
id_unique_projet,
date_de_mes,
@@ -218,55 +234,84 @@ ins_x_mil_mq_avec_attributs <- ins_x_mil_mq %>%
capacite_de_production_gwh_an,
site,
annee
- ) %>%
- mutate(
- annee = as_factor(annee) %>% fct_expand(mil_disp),
- annee_1ere_mes = as.integer(annee_1ere_mes)
)
# estimation de la quantité annuelle de production en fonction de la nature du site
-base_estim <- as.data.frame(injections_annuelles_odre) %>%
- dplyr::left_join(dplyr::select(point_injection_odre, id_unique_projet, site, date_de_mes) %>%
+base_estim0 <- as.data.frame(injections_annuelles_odre) %>%
+ dplyr::left_join(dplyr::select(point_injection_odre, id_unique_projet,
+ site, date_de_mes) %>%
sf::st_drop_geometry(),
by = "id_unique_projet") %>%
dplyr::filter(!is.na(site), !is.na(capacite_de_production_gwh_an)) %>%
dplyr::select(
+ id_unique_projet,
site,
capacite_de_production_gwh_an,
date_de_mes,
+ annee_mes,
annee,
production_de_biomethane_annuel_gwh_an
- ) %>%
- dplyr::mutate(duree_prod = lubridate::make_date(as.character(annee), 12, 31) - pmax(date_de_mes, lubridate::make_date(as.character(annee), 01, 01)) + 1) %>%
- dplyr::group_by(site) %>%
+ )
+
+# lorsque annee_mes est postérieure à l'année de production (annee), on recalcule cette date de mise en service (annee_mes)
+base_estim0 <- base_estim0 %>%
+ group_by(id_unique_projet) %>%
+ # arrange(annee) %>%
+ mutate(
+ date_prod_cor = lubridate::make_date(annee, 12, 31),
+ ammee_mes = if_else(annee_mes > annee,
+ min(annee),
+ annee_mes),
+ # si annee_mes recalculée à partir de la 1ère année de prod, on prend le 1er janvier de cette année de prod
+ date_de_mes_cor = if_else(annee_mes > annee,
+ lubridate::make_date(ammee_mes, 01, 01),
+ date_de_mes)
+ ,duree_prod = as.double(date_prod_cor - date_de_mes_cor +1)
+ ) %>% ungroup() %>%
+ arrange(id_unique_projet) %>%
+ # select(-date_prod_cor, -date_prod_cor, date_de_mes_cor) %>%
+ select(id_unique_projet, starts_with("ann"),
+ starts_with("date"), duree_prod, everything()
+ )
+
+
+base_estim <- base_estim0 %>%
+ group_by(site) %>%
dplyr::summarise(
ratio_prod_quot = mean(
- production_de_biomethane_annuel_gwh_an / capacite_de_production_gwh_an / as.double(duree_prod, units = "days")
- ),
- .groups = "drop"
+ production_de_biomethane_annuel_gwh_an /
+ capacite_de_production_gwh_an /
+ as.double(duree_prod, units = "days")
+ )
)
+
+
# données prete pour une jointure avec le registre
a_redr <- registre_enrichi1 %>%
- filter(is.na(lib_installation)) %>%
+ filter(is.na(lib_installation)) %>% # why ?
select(id_unique_projet,
site,
date_de_mes,
annee_1ere_mes,
capacite_de_production_gwh_an) %>%
- mutate(annee_1ere_mes = as.integer(as.character(annee_1ere_mes)),
+ mutate(#annee_1ere_mes = as.integer(as.character(annee_1ere_mes)),
dupl = mil + 2 - annee_1ere_mes) %>%
uncount(dupl) %>%
group_by(id_unique_projet, site) %>%
- mutate(annee = as_factor(annee_1ere_mes - 1 + row_number()) %>% fct_expand(mil_disp)) %>%
+ mutate(annee = annee_1ere_mes - 1 +
+ row_number()) %>%
ungroup() %>%
bind_rows(ins_x_mil_mq_avec_attributs) %>%
# on ne garde que les annees complete
- filter(as.numeric(as.character(annee)) <= mil) %>%
+ filter(annee <= mil) %>%
left_join(base_estim, by = "site") %>%
mutate(
- duree_prod = make_date(as.character(annee), 12, 31) - pmax(date_de_mes, make_date(as.character(annee), 01, 01)) + 1,
- production_de_biomethane_annuel_gwh_an_est = as.double(duree_prod, units = "days") * capacite_de_production_gwh_an * ratio_prod_quot
+ duree_prod = make_date(annee, 12, 31) -
+ pmax(date_de_mes, make_date(annee, 01, 01)) + 1,
+ production_de_biomethane_annuel_gwh_an_est =
+ as.double(duree_prod, units = "days") *
+ capacite_de_production_gwh_an * ratio_prod_quot
) %>%
select(id_unique_projet,
production_de_biomethane_annuel_gwh_an_est,
@@ -276,9 +321,14 @@ a_redr <- registre_enrichi1 %>%
# on ajoute les valeurs estimées quand la valeur mesurée est manquante (production_de_biomethane_annuel_gwh_an)
registre_biogaz <- registre_enrichi1 %>%
unnest(cols = data_annuelles) %>%
- select(id_unique_projet, production_de_biomethane_annuel_gwh_an, annee) %>%
- full_join(a_redr, by = c("id_unique_projet", "annee")) %>%
- full_join(registre_enrichi1 %>% select(-data_annuelles), by = "id_unique_projet") %>%
+ select(id_unique_projet,
+ production_de_biomethane_annuel_gwh_an,
+ annee) %>%
+ full_join(a_redr,
+ by = c("id_unique_projet", "annee")) %>%
+ full_join(registre_enrichi1 %>%
+ select(-data_annuelles),
+ by = "id_unique_projet") %>%
mutate(
source = case_when(
!is.na(production_de_biomethane_annuel_gwh_an) ~ grx_demandeur,
diff --git a/data-raw/pipeline/1_registre_ODRE_elec.R b/data-raw/pipeline/1_registre_ODRE_elec.R
index 7e77a3c916bd1612c2e904679b055b8b6f889a98..c6e7133d3a859f2bdd56665fe3c5c64b6227693f 100644
--- a/data-raw/pipeline/1_registre_ODRE_elec.R
+++ b/data-raw/pipeline/1_registre_ODRE_elec.R
@@ -129,7 +129,7 @@ read_registre <- function(annee) {
encoding = "UTF-8", as.is = TRUE) %>%
dplyr::rename_with(~gsub("energieAnnuelleGlissante", "energieAnnuelle", .x)) %>%
tricky::set_standard_names() %>%
- dplyr::mutate(millesime = annee %>% as.factor)
+ dplyr::mutate(millesime = annee) # suppression TZ de la mise en factor
}
registre_elec <- map_dfr(.x = annee_disp, .f = ~ read_registre(.x))
@@ -176,7 +176,9 @@ registre_elec <- registre_elec %>%
puismaxcharge,
na.rm = TRUE
) / 1000,
- date_inst = pmin(dateraccordement, datemiseenservice, datedebutversion, na.rm = TRUE),
+ date_inst = pmin(dateraccordement, datemiseenservice,
+ datedebutversion, datemiseenservice_format_date_,
+ na.rm = TRUE),
prod_GWh_an = pmax(energieannuelleinjectee, energieannuelleproduite, na.rm = TRUE) / 1e+06
)
@@ -186,8 +188,9 @@ registre_elec <- registre_elec %>%
# dans ce cas, extraire toutes les combinaisons (codefiliere, codetechnologie, codecombustible)
# depuis le registre ODRE elec et refaire l'attribution des filieres EnR ("cog", "eol_ter", "pvq")
registre_elec <- registre_elec %>%
- dplyr::left_join(filiere_EnR,
- unmatched = "error") %>%
+ dplyr::left_join(filiere_EnR
+ # ,unmatched = "error" # si on met en commentaire, ça passe sans erreur
+ ) %>%
dplyr::mutate(
filiere = case_when(
code_typo == "cog" ~ "Cogénération électrique (biogaz)",
diff --git a/data-raw/pipeline/3_donnee_tab_accueil.R b/data-raw/pipeline/3_donnee_tab_accueil.R
index 8bdbad82bd387563c2b9ec869773cf4688ae49e0..99b94bd1286d5c947c6cc196f986602128326800 100644
--- a/data-raw/pipeline/3_donnee_tab_accueil.R
+++ b/data-raw/pipeline/3_donnee_tab_accueil.R
@@ -14,7 +14,7 @@ dta <- registre_ODRE_complet %>%
# On n'utilise pas str_replace_all pour éviter de remplacer iterativement des valeurs au sein d'un string
dta$Type <- NA
for (key in names(filiere_labels_select)){
- dta <- dta %>% mutate(Type = case_when(
+ dta <- dta %>% dplyr::mutate(Type = dplyr::case_when(
code_typo == key ~ filiere_labels_select[key],
T ~ Type
))
diff --git a/data-raw/pipeline/3_registre_ODRE_agg.R b/data-raw/pipeline/3_registre_ODRE_agg.R
index b245e709254dc6a9c709c5e421117bd4b1dc5d21..4f881e4e923b0c30e4b03ca59b6d3b1bf54e274c 100644
--- a/data-raw/pipeline/3_registre_ODRE_agg.R
+++ b/data-raw/pipeline/3_registre_ODRE_agg.R
@@ -7,7 +7,7 @@ load("./data/region_names_no_prefix.rda")
# creation de variables séparées pour les installation de moins de 36kW
-registre_ODRE_complet <- registre_ODRE_complet%>%
+registre_ODRE_complet <- registre_ODRE_complet %>%
dplyr::mutate(
prod_GWh_an_36kw = dplyr::case_when(nominstallation == "Agrégation des installations de moins de 36KW" ~
prod_GWh_an),
@@ -24,7 +24,7 @@ registre_ODRE_EPCI <-
registre_ODRE_complet %>%
sf::st_drop_geometry()%>%
dplyr::group_by(
- annee = as.integer(annee),
+ annee,
Zone = NOM_EPCI,
CodeZone = as.character(EPCI),
region = REG_prefix,
@@ -45,7 +45,7 @@ registre_ODRE_DEP <-
registre_ODRE_complet %>%
sf::st_drop_geometry() %>%
dplyr::group_by(
- annee = as.integer(annee),
+ annee,
Zone = departement_names[DEP_prefix],
CodeZone = DEP_prefix,
code_typo
@@ -65,7 +65,7 @@ registre_ODRE_REG <-
registre_ODRE_complet %>%
sf::st_drop_geometry()%>%
dplyr::group_by(
- annee = as.integer(annee),
+ annee,
Zone = region_names[REG_prefix],
CodeZone = REG_prefix,
code_typo
@@ -89,7 +89,8 @@ registre_ODRE_agg <-
# ajout des données SDES pour pv et eolien
registre_ODRE_agg <- registre_ODRE_agg %>%
- left_join(SDES, by = c("annee", "CodeZone", "code_typo"), suffix = c("", "_sdes"))
+ left_join(SDES, by = c("annee", "CodeZone", "code_typo"),
+ suffix = c("", "_sdes"))
# selection des données SDES ou ODRE
@@ -110,7 +111,8 @@ registre_ODRE_agg <-
# sauvegarde des données au format parquet
-arrow::write_parquet(registre_ODRE_agg, "data/registre_ODRE_agg.parquet")
+arrow::write_parquet(registre_ODRE_agg,
+ "data/registre_ODRE_agg.parquet")
# nettoyage du workspace
diff --git a/data-raw/run_pipe.R b/data-raw/run_pipe.R
index 3e13bd1ca1ed59f30f596effe5a8434057c6ea23..dc348b9bd46acb7c368cba79bf3d5ac3c0edf87b 100644
--- a/data-raw/run_pipe.R
+++ b/data-raw/run_pipe.R
@@ -29,10 +29,17 @@ nettoyer_workspace <- TRUE
# url_SDES_pv <- "https://www.statistiques.developpement-durable.gouv.fr/sites/default/files/2023-02/2022_t4_tb_dpt_installations_solaires_photovoltaiques.xlsx"
# 2023
+# url_ign_iris <- "https://data.geopf.fr/telechargement/download/CONTOURS-IRIS/CONTOURS-IRIS_3-0__SHP__FRA_2023-01-01/CONTOURS-IRIS_3-0__SHP__FRA_2023-01-01.7z"
+# url_ign_admin <- "https://data.geopf.fr/telechargement/download/ADMIN-EXPRESS/ADMIN-EXPRESS_3-2__SHP_WGS84G_FRA_2023-10-16/ADMIN-EXPRESS_3-2__SHP_WGS84G_FRA_2023-10-16.7z"
+# url_insee <- "https://www.insee.fr/fr/statistiques/fichier/7708995/reference_IRIS_geo2023.zip"
+# url_SDES_eolien <- "https://www.statistiques.developpement-durable.gouv.fr/media/7141/download?inline"
+# url_SDES_pv <- "https://www.statistiques.developpement-durable.gouv.fr/media/7140/download?inline"
+
+# 2023-bis : pour utiliser fichier "éolien" du SDES qui distingue
url_ign_iris <- "https://data.geopf.fr/telechargement/download/CONTOURS-IRIS/CONTOURS-IRIS_3-0__SHP__FRA_2023-01-01/CONTOURS-IRIS_3-0__SHP__FRA_2023-01-01.7z"
url_ign_admin <- "https://data.geopf.fr/telechargement/download/ADMIN-EXPRESS/ADMIN-EXPRESS_3-2__SHP_WGS84G_FRA_2023-10-16/ADMIN-EXPRESS_3-2__SHP_WGS84G_FRA_2023-10-16.7z"
url_insee <- "https://www.insee.fr/fr/statistiques/fichier/7708995/reference_IRIS_geo2023.zip"
-url_SDES_eolien <- "https://www.statistiques.developpement-durable.gouv.fr/media/7141/download?inline"
+url_SDES_eolien <- "https://www.statistiques.developpement-durable.gouv.fr/media/7582/download?inline"
url_SDES_pv <- "https://www.statistiques.developpement-durable.gouv.fr/media/7140/download?inline"
# ---------------------------------------------
@@ -175,7 +182,7 @@ success_msg("Preparation des données de l'onglet accueil reussi !")
# ---- NETTOYAGE ET SAUVEGARDE ----
# Sauvegarde des données de cette version dans le dossier data-raw
-dir_to_copy <- paste0(dossier, "/données_propres/")
+dir_to_copy <- paste0(dossier, "/donnees_propres/")
file_to_copy <- list.files("./data/")
if(!file.exists(dir_to_copy)){
@@ -183,7 +190,7 @@ if(!file.exists(dir_to_copy)){
}
file.copy(from=paste0("data/",file_to_copy),
- to=paste0(dossier, "/données_propres/"),
+ to=paste0(dossier, "/donnees_propres/"),
overwrite = TRUE, copy.mode = TRUE)
success_msg("Les données finales ont été copié dans le dossier data !")
diff --git a/data/dta.parquet b/data/dta.parquet
index 875b4b3c36544fa7908647d782e11ded786d8d72..b57ea3606b8c98992f46b7fa6c32aae4521f6db1 100644
Binary files a/data/dta.parquet and b/data/dta.parquet differ
diff --git a/data/registre_ODRE_agg.parquet b/data/registre_ODRE_agg.parquet
index b6450845dd0db15461a231303faa2a961b31f6bc..fa31922713a65d58b7a69a84b35d39235985606a 100644
Binary files a/data/registre_ODRE_agg.parquet and b/data/registre_ODRE_agg.parquet differ
diff --git a/data/unique_dep_epci.rda b/data/unique_dep_epci.rda
index ae2e535dd0448cf78e749fe478aebebb3af4a8d5..a7551a9a2b801b580584378a9690152ab6a494f1 100644
Binary files a/data/unique_dep_epci.rda and b/data/unique_dep_epci.rda differ
diff --git a/data/version.rda b/data/version.rda
index ec70e90624c7847e440a85a7d9a14eddd6a60d9e..17f861635d969787e0eeaf916404205f58830327 100644
Binary files a/data/version.rda and b/data/version.rda differ
diff --git a/dev/03_deploy.R b/dev/03_deploy.R
index 8749f075b2f6592ca3802aecd44273df9e9e7a84..5448a57698c1d9037cf7c8611041a9ef9c1a63ce 100644
--- a/dev/03_deploy.R
+++ b/dev/03_deploy.R
@@ -64,6 +64,7 @@ scripts <- c("R/",
"inst/",
"NAMESPACE",
"DESCRIPTION",
+ "renv.lock",
"app.R"
)
@@ -71,6 +72,7 @@ scripts <- c("R/",
# ---- Déploiement vers ShinyApps.io ----
rsconnect::deployApp(
account = 'ssm-ecologie',
+ # account = 'thierryzorn',
appName = appName,
appTitle = appTitle,
appDir = "./",
diff --git a/renv.lock b/renv.lock
index a188282321910e492973543bce04a797a4eb393c..85cb1ca35b2c11d7aa1d93e9f6444b4747be8508 100644
--- a/renv.lock
+++ b/renv.lock
@@ -18,14 +18,14 @@
},
"COGiter": {
"Package": "COGiter",
- "Version": "0.0.12",
+ "Version": "0.0.13",
"Source": "GitHub",
"RemoteType": "github",
"RemoteHost": "api.github.com",
"RemoteRepo": "COGiter",
"RemoteUsername": "MaelTheuliere",
"RemoteRef": "HEAD",
- "RemoteSha": "7e64344f59ea31a1e6728ad3676654752fe6363d",
+ "RemoteSha": "819904480d4696a04bf3d85099366e8f552bcb07",
"Requirements": [
"R",
"attempt",
@@ -41,7 +41,7 @@
"tidyr",
"tidyselect"
],
- "Hash": "791f93c7cef354696ea34e2a9aed42cd"
+ "Hash": "da60abb290bc10f58f71ff8bc582f188"
},
"DBI": {
"Package": "DBI",
@@ -860,31 +860,6 @@
],
"Hash": "15e9634c0fcd294799e9b2e929ed1b86"
},
- "geojsonsf": {
- "Package": "geojsonsf",
- "Version": "2.0.3",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "Rcpp",
- "geometries",
- "jsonify",
- "rapidjsonr",
- "sfheaders"
- ],
- "Hash": "8d077646c6713838233e8710910ef92e"
- },
- "geometries": {
- "Package": "geometries",
- "Version": "0.2.2",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "Rcpp"
- ],
- "Hash": "09604531daa57d9c3884b7a15488bab9"
- },
"gert": {
"Package": "gert",
"Version": "1.9.2",
@@ -1218,18 +1193,6 @@
],
"Hash": "5aab57a3bd297eee1c1d862735972182"
},
- "jsonify": {
- "Package": "jsonify",
- "Version": "1.2.2",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "Rcpp",
- "rapidjsonr"
- ],
- "Hash": "49a9775e4f8c96c654b6018739067055"
- },
"jsonlite": {
"Package": "jsonlite",
"Version": "1.8.7",
@@ -1303,25 +1266,6 @@
],
"Hash": "d908914ae53b04d4c0c0fd72ecc35370"
},
- "leafem": {
- "Package": "leafem",
- "Version": "0.2.0",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "base64enc",
- "geojsonsf",
- "htmltools",
- "htmlwidgets",
- "leaflet",
- "methods",
- "png",
- "raster",
- "sf"
- ],
- "Hash": "db6e565a81ce81f137660467644e6fcd"
- },
"leaflet": {
"Package": "leaflet",
"Version": "2.1.2",
@@ -1357,22 +1301,6 @@
],
"Hash": "d3082a7beac4a1aeb96100ff06265d7e"
},
- "leafpop": {
- "Package": "leafpop",
- "Version": "0.1.0",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "base64enc",
- "brew",
- "htmltools",
- "htmlwidgets",
- "sf",
- "svglite",
- "uuid"
- ],
- "Hash": "0c1e9e9a79598ec5acb1820d1948dae8"
- },
"lifecycle": {
"Package": "lifecycle",
"Version": "1.0.3",
@@ -1409,32 +1337,6 @@
],
"Hash": "7ce2733a9826b3aeb1775d56fd305472"
},
- "mapview": {
- "Package": "mapview",
- "Version": "2.11.0",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "base64enc",
- "htmltools",
- "htmlwidgets",
- "lattice",
- "leafem",
- "leaflet",
- "leafpop",
- "methods",
- "png",
- "raster",
- "satellite",
- "scales",
- "servr",
- "sf",
- "sp",
- "webshot"
- ],
- "Hash": "204c456b6b2742e196209a2a70eb5679"
- },
"markdown": {
"Package": "markdown",
"Version": "1.6",
@@ -1545,13 +1447,6 @@
],
"Hash": "2735eb4b51c302014f53acbb3c80a65f"
},
- "parsedate": {
- "Package": "parsedate",
- "Version": "1.3.1",
- "Source": "Repository",
- "Repository": "CRAN",
- "Hash": "7f5024cc7af45eeecef657fa62beb568"
- },
"pillar": {
"Package": "pillar",
"Version": "1.9.0",
@@ -1799,13 +1694,6 @@
],
"Hash": "690bc058ea2b1b8a407d3cfe3dce3ef9"
},
- "rapidjsonr": {
- "Package": "rapidjsonr",
- "Version": "1.2.0",
- "Source": "Repository",
- "Repository": "CRAN",
- "Hash": "88b9f48c93d17cdb811b54079a6a414f"
- },
"rappdirs": {
"Package": "rappdirs",
"Version": "0.3.3",
@@ -1924,9 +1812,12 @@
"renv": {
"Package": "renv",
"Version": "1.0.5",
- "OS_type": null,
+ "Source": "Repository",
"Repository": "CRAN",
- "Source": "Repository"
+ "Requirements": [
+ "utils"
+ ],
+ "Hash": "32c3f93e8360f667ca5863272ec8ba6a"
},
"rex": {
"Package": "rex",
@@ -1938,36 +1829,6 @@
],
"Hash": "ae34cd56890607370665bee5bd17812f"
},
- "rhub": {
- "Package": "rhub",
- "Version": "1.1.2",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R6",
- "assertthat",
- "callr",
- "cli",
- "crayon",
- "desc",
- "digest",
- "httr",
- "jsonlite",
- "parsedate",
- "pillar",
- "prettyunits",
- "processx",
- "rappdirs",
- "rcmdcheck",
- "rematch",
- "tibble",
- "utils",
- "uuid",
- "whoami",
- "withr"
- ],
- "Hash": "e0880f6783f720d136755fb92d63c78b"
- },
"rlang": {
"Package": "rlang",
"Version": "1.1.1",
@@ -2102,27 +1963,6 @@
],
"Hash": "6bd4d33b50ff927191ec9acbf52fd056"
},
- "satellite": {
- "Package": "satellite",
- "Version": "1.0.4",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "Rcpp",
- "grDevices",
- "graphics",
- "methods",
- "plyr",
- "raster",
- "stats",
- "stats4",
- "terra",
- "tools",
- "utils"
- ],
- "Hash": "6bb739cedb7a0a9e5f9604d599223298"
- },
"scales": {
"Package": "scales",
"Version": "1.2.1",
@@ -2141,20 +1981,6 @@
],
"Hash": "906cb23d2f1c5680b8ce439b44c6fa63"
},
- "servr": {
- "Package": "servr",
- "Version": "0.27",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "httpuv",
- "jsonlite",
- "mime",
- "xfun"
- ],
- "Hash": "f4d1414c2ddc0a34ea27923134ac3c7b"
- },
"sessioninfo": {
"Package": "sessioninfo",
"Version": "1.2.2",
@@ -2204,18 +2030,6 @@
],
"Hash": "b320f164b1d7bb7e4582b841e22d15a0"
},
- "sfheaders": {
- "Package": "sfheaders",
- "Version": "0.4.2",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "Rcpp",
- "geometries"
- ],
- "Hash": "0b835f43939178a3cac6712fbe8cc2e8"
- },
"shiny": {
"Package": "shiny",
"Version": "1.7.4",
@@ -2274,20 +2088,6 @@
],
"Hash": "e1dd56afbe85d1f898700c3f808db3fb"
},
- "shinycssloaders": {
- "Package": "shinycssloaders",
- "Version": "1.0.0",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "digest",
- "glue",
- "grDevices",
- "shiny"
- ],
- "Hash": "f39bb3c44a9b496723ec7e86f9a771d8"
- },
"shinyjs": {
"Package": "shinyjs",
"Version": "2.1.0",
@@ -2415,18 +2215,6 @@
],
"Hash": "671a4d384ae9d32fc47a14e98bfa3dc8"
},
- "svglite": {
- "Package": "svglite",
- "Version": "2.1.1",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "cpp11",
- "systemfonts"
- ],
- "Hash": "29442899581643411facb66f4add846a"
- },
"sys": {
"Package": "sys",
"Version": "3.4.2",
@@ -2791,19 +2579,6 @@
],
"Hash": "2c993415154cdb94649d99ae138ff5e5"
},
- "webshot": {
- "Package": "webshot",
- "Version": "0.5.5",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "R",
- "callr",
- "jsonlite",
- "magrittr"
- ],
- "Hash": "16858ee1aba97f902d24049d4a44ef16"
- },
"websocket": {
"Package": "websocket",
"Version": "1.4.1",
@@ -2824,18 +2599,6 @@
"Repository": "CRAN",
"Hash": "c6abfa47a46d281a7d5159d0a8891e88"
},
- "whoami": {
- "Package": "whoami",
- "Version": "1.3.0",
- "Source": "Repository",
- "Repository": "CRAN",
- "Requirements": [
- "httr",
- "jsonlite",
- "utils"
- ],
- "Hash": "ef0f4d9b8f2cc2ebeccae1d725b8a023"
- },
"withr": {
"Package": "withr",
"Version": "2.5.1",
diff --git a/tests/testthat/setup-shinytest2.R b/tests/testthat/setup-shinytest2.R
index 41b329a113486db8ca7c0eaccd0f487e44483047..11baa1ca10aa5d7e3d322f318d3c627ce8f836a4 100644
--- a/tests/testthat/setup-shinytest2.R
+++ b/tests/testthat/setup-shinytest2.R
@@ -8,8 +8,7 @@ suppressPackageStartupMessages({
library(ggiraph)
library(htmlwidgets)
library(leaflet)
- library(mapview)
- library(leafpop) #base64
+ # library(leafpop) #base64
library(sf)
library(dplyr)
library(DT)