[éCow] Ajout partie lignées

R/project/ecow_calculations.R

@@ -12,6 +12,7 @@ suppressPackageStartupMessages({
 })
 source(here::here("R/common/ws_client.R"))
 source(here::here("R/project/preprocessing.R"))
+source(here::here("R/project/postprocessing.R"))
 
 #' Fonction globale de mise à jour des indicateurs eCow pour vaches, taureaux et lignées
 #' Stockage des données directement en base
@@ -74,11 +75,14 @@ calcul_ecow_by_chep <- function(cheptel, step = 3) {
   pps <- params_ponderation$pointage$sevrage
   
   # Ajout à la table vache des informations synthétisées de leur veaux
-  synth <- get_synth_prod_vaches(vaches, prod_vaches_corr, params_ponderation)
+  synth_brute_vaches <- get_synth_prod_parent(vaches, prod_vaches_corr, params_ponderation)
-  synth_vaches <- synth$synthese
+  
+  # Normalisation et calcul des notes carrières
+  synth_norm <- get_note_carriere(synth_brute_vaches, params_ponderation)
+  synth_vaches <- synth_norm$synthese
 
   # calcul des stats, valeurs extremes et references pour la normalisation
-  stats_chep <- synth$stats_chep
+  stats_chep <- synth_norm$stats_chep
 
   ####################################     Calcul des notes campagnes       ########################################
   ####### En réalité on travaille sur les rangs de velages, ce qui correspond dans 99% des cas aux campagnes #######
@@ -96,7 +100,7 @@ calcul_ecow_by_chep <- function(cheptel, step = 3) {
       ptgp   = round(mean(pps$devmus * dmSevrage + pps$devsqe * dsSevrage + pps$af * afSevrage, na.rm = TRUE), 1),
       p120_c = round(mean(pat120Corrige, na.rm = TRUE), 1),
       p210_c = round(mean(pat210Corrige, na.rm = TRUE), 1),
-      prol   = n() * 100,  # --------------------- TODO a tester parce que je pense qu'il faudrait tous les produits d'une vache
+      prol   = n() * 100,  # ------------------------------- TODO a tester parce que je pense qu'il faudrait tous les produits d'une vache
       mort   = round(mean(mortsev == "O" | mortnat == "O") * 100, 1),
       pere   = first(pereGenetique),
       cheptel = first(cheptelNaiss),
@@ -261,113 +265,20 @@ calcul_ecow_by_chep <- function(cheptel, step = 3) {
   # Petits produits issus des filles des taureaux 
   pprod_filles_taureaux <- add_data_ecow(cheptel_ecow$petits_produits, czhbc)
   
-  # TODO quel effet chep ? Comment on l'applique ? 
+  # Calcul de la synthèse par fille de leur produits
-  # PLUS besoin de calculer effet chep car pas de calcul de rang -> fonction de synth à modifier
+  synth_filles_taureaux <- get_synth_prod_parent(filles_taureaux, pprod_filles_taureaux, params_ponderation)
-  
-  synth_ft <- get_synth_prod_vaches(filles_taureaux, pprod_filles_taureaux, params_ponderation)
-  synth_filles_taureaux <- synth_ft$synthese
   
   # Calcul des stats par pere
-  stats_peres <- produits_taureaux %>%
+  stats_prod_directe <- get_stats_parent(produits_taureaux, pereGenetique)
-    group_by(pereGenetique) %>%
-    summarise(
-      nb_prod_in_chep = n(),
-      .groups = "drop"
-    ) %>%
-    filter(nb_prod_in_chep >= 5)
 
-  stats_prod_directe <- produits_taureaux %>%
+  stats_filles <- get_stats_filles(synth_filles_taureaux, "fillestot_", pereGenetique, actif = FALSE)
-    group_by(pereGenetique) %>%
-    summarise(
-      utilgen = round(mean(rangVelageMipg == 1, na.rm = TRUE) * 100, 1),
-      prol    = round(n() / n_distinct(dateNaiss, numeroMipg) * 100, 1),
-      mort    = round((sum(mortsev == "O" | mortnat == "O", na.rm = TRUE)) / n() * 100, 1),
-      
-      txrepros = round(
-        sum(repro == "O", na.rm = TRUE) /
-          sum(is.na(mortsev) & is.na(mortnat)) * 100, 1
-      ),
-      
-      nbpp  = sum(NBPRODIPG, na.rm = TRUE),
-      txvf  = round(mean(conditionNaiss %in% c("1", "2"), na.rm = TRUE) * 100, 1),
-      
-      pnm   = round(mean(poidsNaiss[sexe == "1"], na.rm = TRUE), 1),
-      pnf   = round(mean(poidsNaiss[sexe == "2"], na.rm = TRUE), 1),
-      
-      p120m = round(mean(pat120[sexe == "1"], na.rm = TRUE), 1),
-      p120f = round(mean(pat120[sexe == "2"], na.rm = TRUE), 1),
-      
-      p210m = round(mean(pat210[sexe == "1"], na.rm = TRUE), 1),
-      p210f = round(mean(pat210[sexe == "2"], na.rm = TRUE), 1),
-      
-      dmsev = round(mean(dmSevrage, na.rm = TRUE), 1),
-      dssev = round(mean(dsSevrage, na.rm = TRUE), 1),
-      afsev = round(mean(afSevrage, na.rm = TRUE), 1),
 
-      nb_femelles = sum(sexe == "2", na.rm = TRUE),
+  stats_filles_act <- get_stats_filles(synth_filles_taureaux, "fillesact_", pereGenetique, actif = TRUE)
-      .groups = "drop"
-    )
-
-  stats_filles <- synth_filles_taureaux %>%
-    group_by(pereGenetique) %>%
-    summarise(
-      nbfilles_avecprod = sum(NBPRODIPG > 0, na.rm = TRUE),
-      pctfilles_avecprod = round(nbfilles_avecprod / n() * 100, 1),
-      isu_fillestot      = ifelse(n() >= 3, sum(embryon == "O", na.rm = TRUE), NA),
-      age_sort_fillestot = ifelse(n() >= 3, round(mean(age_years, na.rm = TRUE), 1), NA),
-      agevel1_fillestot  = ifelse(n() >= 3, round(mean(agevel1, na.rm = TRUE), 1), NA),
-      ivv1_fillestot     = ifelse(n() >= 3, round(mean(ivv1, na.rm = TRUE), 1), NA),
-      ivv2p_fillestot    = ifelse(n() >= 3, round(mean(ivv2Brut, na.rm = TRUE), 1), NA),
-      vieprod_fillestot  = ifelse(n() >= 3, round(mean(tempsprod, na.rm = TRUE), 1), NA),
-      
-      dmad_fillestot     = ifelse(n() >= 3, round(mean(dmcAdulte, na.rm = TRUE), 1), NA),
-      dsad_fillestot     = ifelse(n() >= 3, round(mean(dsAdulte, na.rm = TRUE), 1), NA),
-      afad_fillestot     = ifelse(n() >= 3, round(mean(afAdulte, na.rm = TRUE), 1), NA),
-      
-      prol_fillestot     = ifelse(n() >= 3, round(mean(prol, na.rm = TRUE), 1), NA),
-      mort_fillestot     = ifelse(n() >= 3, round(mean(mort, na.rm = TRUE), 1), NA),
-      txvf_fillestot     = ifelse(n() >= 3, round(mean(txvf, na.rm = TRUE), 1), NA),
-      
-      nbprod_fillestot   = ifelse(n() >= 3, sum(NBPRODIPG, na.rm = TRUE), NA),
-      txrepros_fillestot = ifelse(n() >= 3, round(mean(txrepros, na.rm = TRUE), 1), NA),
-      nbpp_fillestot     = ifelse(n() >= 3, sum(nbpp, na.rm = TRUE), NA),
-      
-      .groups = "drop"
-    )
-
-  stats_filles_act <- synth_filles_taureaux %>%
-    filter(is.na(dateSortDetenteur)) %>%
-    group_by(pereGenetique) %>%
-    summarise(
-      nbfillesact_avecprod = sum(NBPRODIPG > 0, na.rm = TRUE),
-      #pctfillesact_avecprod = round(nbfillesact_avecprod / nbfilles_avecprod * 100, 1),
-      
-      isu_fillesact      = 0,
-      age_sort_fillesact = ifelse(n() >= 3, round(mean(age_years, na.rm = TRUE), 1), NA),
-      agevel1_fillesact  = ifelse(n() >= 3, round(mean(agevel1, na.rm = TRUE), 1), NA),
-      ivv1_fillesact     = ifelse(n() >= 3, round(mean(ivv1, na.rm = TRUE), 1), NA),
-      ivv2p_fillesact    = ifelse(n() >= 3, round(mean(ivv2Brut, na.rm = TRUE), 1), NA),
-      vieprod_fillesact  = ifelse(n() >= 3, round(mean(tempsprod, na.rm = TRUE), 1), NA),
-      
-      dmad_fillesact     = ifelse(n() >= 3, round(mean(dmcAdulte, na.rm = TRUE), 1), NA),
-      dsad_fillesact     = ifelse(n() >= 3, round(mean(dsAdulte, na.rm = TRUE), 1), NA),
-      afad_fillesact     = ifelse(n() >= 3, round(mean(afAdulte, na.rm = TRUE), 1), NA),
-      
-      prol_fillesact     = ifelse(n() >= 3, round(mean(prol, na.rm = TRUE), 1), NA),
-      mort_fillesact     = ifelse(n() >= 3, round(mean(mort, na.rm = TRUE), 1), NA),
-      txvf_fillesact     = ifelse(n() >= 3, round(mean(txvf, na.rm = TRUE), 1), NA),
-      
-      nbprod_fillesact   = ifelse(n() >= 3, sum(NBPRODIPG, na.rm = TRUE), NA),
-      txrepros_fillesact = ifelse(n() >= 3, round(mean(txrepros, na.rm = TRUE), 1), NA),
-      nbpp_fillesact     = ifelse(n() >= 3, sum(nbpp, na.rm = TRUE), NA),
-      
-      .groups = "drop"
-    )
   
   grp_filles_et_act <- stats_filles %>%
     dplyr::left_join(stats_filles_act, by = "pereGenetique") %>%
     mutate(
-      pctfillesact_avecprod = round( nbfillesact_avecprod / nbfilles_avecprod * 100, 1 )
+      pctfillesact_avecprod = round( fillesact_nbavecprod / fillestot_nbavecprod * 100, 1 )
     )
   
   stats_filles_renouv <- produits_cheptel %>%
@@ -381,21 +292,18 @@ calcul_ecow_by_chep <- function(cheptel, step = 3) {
       .groups = "drop"
     )
       
-  stats_taureaux <- stats_peres %>%
+  stats_taureaux <- stats_prod_directe %>%
-    dplyr::left_join(stats_prod_directe,   by = "pereGenetique") %>%
     dplyr::left_join(grp_filles_et_act,    by = "pereGenetique") %>%
     dplyr::left_join(stats_filles_renouv,  by = "pereGenetique") %>%
-    dplyr::left_join(taureaux,             by = "pereGenetique")
+    dplyr::left_join(taureaux %>% select(anim, nom, dateNaiss, nomCheptelNaiss),  by = c("pereGenetique" = "anim")) %>%
-  
+    mutate(
-  # Récupère le nom 
+      nom = replace(nom, is.na(nom), ""),
-  stats_taureaux <- stats_taureaux %>%
+      cheptel = cheptel,
-    select(-nom, -dateNaiss, -nomCheptelNaiss) %>%
+      across(where(is.numeric), ~ trunc(.x * 100) / 100)
-    dplyr::left_join(taureaux %>% select(anim, nom, dateNaiss, nomCheptelNaiss),
+      )
-      by = c("pereGenetique" = "anim")) %>%
-    mutate(nom = replace(nom, is.na(nom), ""))  %>%
-    mutate(across(where(is.numeric), ~ trunc(.x * 100) / 100))
 
-  save_data_taureau(stats_taureaux, cheptel)
+  message("Enregistrement données taureaux")
+  save_data_taureau(stats_taureaux)
   
   if (step == 2) {
     t1 <- Sys.time()
@@ -408,137 +316,48 @@ calcul_ecow_by_chep <- function(cheptel, step = 3) {
   ###################################################################################################################
   
   fondatrices <- cheptel_ecow$fondatrices
-  descendants <- cheptel_ecow$descendants
+  descendants <- add_data_ecow(cheptel_ecow$descendants, czhbc)
 
-  vaches_lignees <- descendants %>% 
+  vaches_lignees <- descendants %>% filter(anim %in% descendants$mereGenetique)
-    filter(anim %in% descendants$mereIpg)
+  produits_lignees <- descendants %>% filter(mereGenetique %in% vaches_lignees$anim)
-  produits_lignees <- add_data_ecow(
+
-    descendants %>% 
+  synth_vaches_lignees <- get_synth_prod_parent(vaches_lignees, produits_lignees, params_ponderation)
-      filter(mereIpg %in% descendants$anim)
+
+  # calcul des stats par fondatrice, ne gardant que celles ayant plus de 5 descendants dans le cheptel_________________
+
+  stats_prod <- get_stats_parent(descendants, fondatrice) # produits lignées ou descendants ????
+  
+  stats_fem_tot <- get_stats_filles(synth_vaches_lignees, "femtot_", fondatrice, actif = FALSE)
+  
+  stats_fem_act <- get_stats_filles(synth_vaches_lignees, "femact_", fondatrice, actif = TRUE)
+
+  stats_renouv <- descendants %>%
+    filter(
+      is.na(NBPRODIPG),# TODO valider avec Lauréna que c'est bien ce champ là qu'on veut 
+      sexe == "2",
+      is.na(dateSortDetenteur)
+    ) %>%
+    group_by(fondatrice) %>%
+    summarise(
+      nbfilles_renouv = n(),
+      .groups = "drop"
     )
-  # 
+  
-  # # TODO quel effet chep ? Comment on l'applique ? 
+  stats_lignees <- stats_prod %>%
-  # 
+    dplyr::left_join(stats_fem_tot,  by = "fondatrice") %>%
-  # synth_vaches_lignees <- get_synth_prod_vaches(vaches_lignees, produits_lignees, params_ponderation, stats_chep)
+    dplyr::left_join(stats_fem_act,  by = "fondatrice") %>%
-  # 
+    dplyr::left_join(stats_renouv,   by = "fondatrice") %>%
-  # # calcul des stats par fondatrice ______________________________________________
+    dplyr::left_join(fondatrices %>% select(anim, nom, dateNaiss, nomCheptelNaiss),  by = c("fondatrice" = "anim")) %>%
-  # 
+    mutate(
-  # stats_prod <- produits_lignees %>%stats_prod <- produits_ligne%
+      pctfem_avecprod =
-  # summarise(
+        round(femtot_nbavecprod / nb_femelles* 100, 1),
-  #   nb_desc_in_chep = n(),
+      pctfemact_avecprod =
-  #   
+        round(femact_nbavecprod / nb_femelles * 100, 1),
-  #   utilgen = round(mean(ravelamere == 1, na.rm = TRUE) * 100, 1),
+      cheptel = cheptel
-  #   
+    )
-  #   prol = round(
+
-  #     n() / n_distinct(danais, mere) * 100, 1
+  message("Enregistrement données lignées")
-  #   ),
+  save_data_lignees(stats_lignees)
-  #   
-  #   mort = round(mean(mortsev == "O", na.rm = TRUE) * 100, 1),
-  #   
-  #   txrepros = round(
-  #     sum(repro == "O", na.rm = TRUE) /
-  #       sum(is.na(mortsev)) * 100, 1
-  #   ),
-  #   
-  #   nbpp = sum(nbdescendants, na.rm = TRUE),
-  #   
-  #   txvf = round(mean(conais %in% c("1", "2"), na.rm = TRUE) * 100, 1),
-  #   
-  #   pnm   = round(mean(ponais[sexbov == "1"], na.rm = TRUE), 1),
-  #   pnf   = round(mean(ponais[sexbov == "2"], na.rm = TRUE), 1),
-  #   
-  #   p120m = round(mean(pat04m[sexbov == "1"], na.rm = TRUE), 1),
-  #   p120f = round(mean(pat04m[sexbov == "2"], na.rm = TRUE), 1),
-  #   
-  #   p210m = round(mean(pat07m[sexbov == "1"], na.rm = TRUE), 1),
-  #   p210f = round(mean(pat07m[sexbov == "2"], na.rm = TRUE), 1),
-  #   
-  #   dmsev = round(mean(devmus[sexbov == "1"], na.rm = TRUE), 1),   # A CORRIGER CF TAUREAUX 
-  #   dssev = round(mean(devsqe[sexbov == "2"], na.rm = TRUE), 1),
-  #   
-  #   nb_fem_prod = sum(sexbov == "2", na.rm = TRUE)
-  # ) %>%
-  #   filter(nb_desc_in_chep >= 5)
-  # 
-  # stats_fem_tot <- synth_vaches_lignees %>%
-  #   group_by(fondatrice) %>%
-  #   summarise(
-  #     nbfem_avecprod = n(),
-  #     
-  #     isu_femtot       = ifelse(n() >= 3, round(mean(indisu, na.rm = TRUE), 1), NA),
-  #     age_sort_femtot  = ifelse(n() >= 3, round(mean(age_years, na.rm = TRUE), 1), NA),
-  #     agevel1_femtot   = ifelse(n() >= 3, round(mean(agevel1, na.rm = TRUE), 1), NA),
-  #     vieprod_femtot   = ifelse(n() >= 3, round(mean(tempsprod, na.rm = TRUE), 1), NA),
-  #     ivv1_femtot      = ifelse(n() >= 3, round(mean(ivv1, na.rm = TRUE), 1), NA),
-  #     ivv2p_femtot     = ifelse(n() >= 3, round(mean(as.numeric(ivv2p), na.rm = TRUE), 1), NA),
-  #     
-  #     dmad_femtot      = ifelse(n() >= 3, round(mean(dmC, na.rm = TRUE), 1), NA),
-  #     dsad_femtot      = ifelse(n() >= 3, round(mean(ds, na.rm = TRUE), 1), NA),
-  #     afad_femtot      = ifelse(n() >= 3, round(mean(af, na.rm = TRUE), 1), NA),
-  #     
-  #     prol_femtot      = ifelse(n() >= 3, round(mean(prol, na.rm = TRUE), 1), NA),
-  #     mort_femtot      = ifelse(n() >= 3, round(mean(mort, na.rm = TRUE), 1), NA),
-  #     txvf_femtot      = ifelse(n() >= 3, round(mean(txvf, na.rm = TRUE), 1), NA),
-  #     
-  #     nbprod_femtot    = ifelse(n() >= 3, sum(nbdescendants, na.rm = TRUE), NA),
-  #     txrepros_femtot  = ifelse(n() >= 3, round(mean(txrepros, na.rm = TRUE), 1), NA),
-  #     nbpp_femtot      = ifelse(n() >= 3, sum(nbpp, na.rm = TRUE), NA)
-  #   )
-  # 
-  # stats_fem_act <- synth_vaches_lignees %>%
-  #   filter(is.na(dasort)) %>%
-  #   group_by(fondatrice) %>%
-  #   summarise(
-  #     nbfemact_avecprod = n(),
-  #     
-  #     isu_femact      = ifelse(n() >= 3, round(mean(indisu, na.rm = TRUE), 1), NA),
-  #     age_sort_femact = ifelse(n() >= 3, round(mean(age_years, na.rm = TRUE), 1), NA),
-  #     agevel1_femact  = ifelse(n() >= 3, round(mean(agevel1, na.rm = TRUE), 1), NA),
-  #     vieprod_femact  = ifelse(n() >= 3, round(mean(tempsprod, na.rm = TRUE), 1), NA),
-  #     ivv1_femact     = ifelse(n() >= 3, round(mean(ivv1, na.rm = TRUE), 1), NA),
-  #     ivv2p_femact    = ifelse(n() >= 3, round(mean(as.numeric(ivv2p), na.rm = TRUE), 1), NA),
-  #     
-  #     dmad_femact     = ifelse(n() >= 3, round(mean(dmC, na.rm = TRUE), 1), NA),
-  #     dsad_femact     = ifelse(n() >= 3, round(mean(ds, na.rm = TRUE), 1), NA),
-  #     afad_femact     = ifelse(n() >= 3, round(mean(af, na.rm = TRUE), 1), NA),
-  #     
-  #     prol_femact     = ifelse(n() >= 3, round(mean(prol, na.rm = TRUE), 1), NA),
-  #     mort_femact     = ifelse(n() >= 3, round(mean(mort, na.rm = TRUE), 1), NA),
-  #     txvf_femact     = ifelse(n() >= 3, round(mean(txvf, na.rm = TRUE), 1), NA),
-  #     
-  #     nbprod_femact   = ifelse(n() >= 3, sum(nbdescendants, na.rm = TRUE), NA),
-  #     txrepros_femact = ifelse(n() >= 3, round(mean(txrepros, na.rm = TRUE), 1), NA),
-  #     nbpp_femact     = ifelse(n() >= 3, sum(nbpp, na.rm = TRUE), NA)
-  #   )
-  # 
-  # stats_renouv <- inv_desc %>%
-  #   filter(
-  #     nbdescendants == 0,
-  #     sexbov == "2",
-  #     actif == "1"
-  #   ) %>%
-  #   group_by(fondatrice) %>%
-  #   summarise(nbfem_renouv = n())
-  # 
-  # stats_lignees <- stats_prod %>%
-  #   dplyr::left_join(stats_fem_tot,  by = "fondatrice") %>%
-  #   dplyr::left_join(stats_fem_act,  by = "fondatrice") %>%
-  #   dplyr::left_join(stats_renouv,   by = "fondatrice") %>%
-  #   mutate(
-  #     pctfem_avecprod =
-  #       round(nbfem_avecprod / nb_fem_prod * 100, 1),
-  #     pctfemact_avecprod =
-  #       round(nbfemact_avecprod / nb_fem_prod * 100, 1)
-  #   )
-  # 
-  # stats_lignees_final <- fondatrices %>%
-  #   mutate(anim = trim_str(anim)) %>%
-  #   dplyr::left_join(
-  #     stats_lignees %>% mutate(fondatrice = trim_str(fondatrice)),
-  #     by = c("anim" = "fondatrice")
-  #   )
-  # 
-  # save_data_lignees(stats_lignees_final)
   t1 <- Sys.time()
   message("Fin du traitement. Temps d'exécution : ", round(difftime(t1, t0, units = "secs"), 2), " sec")
 }

R/project/postprocessing.R

@@ -40,19 +40,13 @@ maj_ecow_for_all <- function() {
   maj_ecow_for_list_cheptels(list_chep)
 }
 
-mafonctiondetest <- function(cheptel){ 
-  source(here::here("R/common/ws_client.R"))
-  cheptel_ecow <-  get_cheptel_ecow(cheptel)
-  vaches <- cheptel_ecow$vaches
-  return(length(vaches))
-}
-
 #' Mise à jour de l'indicateur Ecow pour une liste de cheptels et gestion des erreurs
 #' @param list_cheptels  list. Liste de numéros de cheptels avec le FR devant
 maj_ecow_for_list_cheptels <- function(list_cheptels){
   total <- length(list_cheptels)
   start_time <- Sys.time()
   message(sprintf("🚀 Début traitement - %s cheptels à traiter", total))
+  flush.console()
   
   res <- lapply(seq_along(list_cheptels), function(i) {
     num_chep <- list_cheptels[[i]]
@@ -60,17 +54,21 @@ maj_ecow_for_list_cheptels <- function(list_cheptels){
       tryCatch(
         {
           message(sprintf("[%s/%s] Traitement cheptel %s ...", i, total, num_chep))
-          out <- calcul_ecow_by_chep(num_chep, 1) # Pour l'instant on s'arrête aux vaches
+          flush.console()
+          out <- calcul_ecow_by_chep(num_chep, 3) # Pour l'instant on s'arrête aux vaches
           message(sprintf("✓ OK cheptel %s", num_chep))
+          flush.console()
           out
         },
         error = function(e) {
           message(sprintf("✗ ERREUR cheptel %s : %s", num_chep, conditionMessage(e)))
+          flush.console()
           NULL
         }
       ),
       warning = function(w) {
         message(sprintf("! AVERTISSEMENT cheptel %s : %s", num_chep, conditionMessage(w)))
+        flush.console()
         invokeRestart("muffleWarning")
       }
     )
@@ -84,6 +82,25 @@ maj_ecow_for_list_cheptels <- function(list_cheptels){
   return(res)
 }
 
+
+maj_ecow_from_csv <- function() {
+  
+  cheptels <- read.csv('cheptels_liste.csv', stringsAsFactors = FALSE)
+  
+  if (!"login" %in% names(cheptels)) {
+    stop("Colonne 'login' absente du CSV")
+  }
+  
+  if (nrow(cheptels) == 0) {
+    message("Aucun cheptel à traiter")
+    return(NULL)
+  }
+  
+  maj_ecow_for_list_cheptels(as.list(cheptels$login))
+  
+}
+
+
 format_duration <- function(seconds) {
   h <- as.integer(seconds %/% 3600)
   m <- as.integer((seconds %% 3600) %/% 60)
@@ -95,22 +112,17 @@ format_duration <- function(seconds) {
 save_data_vaches <- function(vaches){
   tabfinal <- vaches %>%
     select(
-      cheptelDetenteur, anim, nom, nom_pere, embryon, donneuse, porteuse,
+      cheptelDetenteur, anim, nom, nom_pere, embryon, donneuse, porteuse, tempsprod, age_years, ecowcarr, rg_carr, ptgV,
-      tempsprod, age_years, ecowcarr, rg_carr,
+      agevel1, ivv1, ivv2Brut, prol, mort, txrepros, nbpp, txvf, 
-      ptgV, agevel1, ivv1, ivv2Brut,
+      pn_m, pn_f, p120_m, p120_f, p210_m, p210_f, ptgP, moyecowcamp, rg_camp
-      prol, mort, txrepros, nbpp,
-      txvf, pn_m, pn_f,
-      p120_m, p120_f, p210_m, p210_f,
-      ptgP,
-      moyecowcamp, rg_camp
     ) %>%
     arrange(rg_carr)
   
   # Renomme les colonnes pour correspondre aux noms des champs dans la table ecow_vaches
   colnames(tabfinal) <- c(
-    "cheptel", "num_vache", "nom_vache", "pere", "isu", "donneuse", "porteuse", "pourc_vie_productive", "age_annees", "note_ecow_carr", "rang_carr", "pointage_vache", "age_1_velage_m", "ivv1_j",
+    "cheptel", "num_vache", "nom_vache", "pere", "isu", "donneuse", "porteuse", "pourc_vie_productive", "age_annees", "note_ecow_carr", "rang_carr", "pointage_vache", 
-    "ivv2plus_j", "prolificite_pourc", "mortalite_av_sevr_pourc", "pourc_produits_repros", "nb_petits_produits", "pourc_velages_tranquilles", "pn_males_kg",
+    "age_1_velage_m", "ivv1_j", "ivv2plus_j", "prolificite_pourc", "mortalite_av_sevr_pourc", "pourc_produits_repros", "nb_petits_produits", "pourc_velages_tranquilles", 
-    "pn_femelles_kg", "p120_males_kg", "p120_femelles_kg", "p210_males_kg", "p210_femelles_kg", "pointage_produits", "moy_notes_ecow_campagne", "rang_campagne"
+    "pn_males_kg", "pn_femelles_kg", "p120_males_kg", "p120_femelles_kg", "p210_males_kg", "p210_femelles_kg", "pointage_produits", "moy_notes_ecow_campagne", "rang_campagne"
   )
   
   tab_format <- tabfinal %>%
@@ -162,28 +174,26 @@ save_data_campagne <- function(synth_camp){
   dbDisconnect(con) 
 }
 
-save_data_taureau <- function(data_taureaux, cheptel){
+save_data_taureau <- function(data_taureaux){
   # Stockage des données écow_taureaux
   filtered_taureaux <- data_taureaux %>%
     select(
-      cheptelDetenteur, pereGenetique, nom, dateNaiss, nomCheptelNaiss, nb_prod_in_chep, utilgen, prol, mort, txrepros, nbpp, txvf, pnm, pnf, p120m, p120f, p210m, p210f, 
+      cheptel, pereGenetique, nom, dateNaiss, nomCheptelNaiss, nb_prod_in_chep, utilgen, prol, mort, txrepros, nbpp, txvf, pnm, pnf, p120m, p120f, p210m, p210f, 
-      dmsev, dssev, afsev, nbfilles_avecprod, pctfilles_avecprod, isu_fillestot, age_sort_fillestot, agevel1_fillestot, ivv1_fillestot, ivv2p_fillestot, 
+      dmsev, dssev, afsev,  fillestot_nbavecprod, fillestot_pctavecprod, fillestot_isu, fillestot_age_sort, fillestot_agevel1, fillestot_ivv1, fillestot_ivv2p, 
-      vieprod_fillestot, dmad_fillestot, dsad_fillestot, afad_fillestot, nbprod_fillestot, txrepros_fillestot, nbpp_fillestot, prol_fillestot,
+      fillestot_vieprod, fillestot_dmad, fillestot_dsad, fillestot_afad, fillestot_nbprod, fillestot_txrepros, fillestot_nbpp, fillestot_prol, fillestot_mort, 
-      mort_fillestot, txvf_fillestot, nbfillesact_avecprod, pctfillesact_avecprod, isu_fillesact, age_sort_fillesact, agevel1_fillesact, ivv1_fillesact, 
+      fillestot_txvf, fillesact_nbavecprod, fillesact_pctavecprod, fillesact_isu, fillesact_age_sort, fillesact_agevel1, fillesact_ivv1, fillesact_ivv2p, 
-      ivv2p_fillesact, vieprod_fillesact, dmad_fillesact, dsad_fillesact, afad_fillesact, nbprod_fillesact, txrepros_fillesact, nbpp_fillesact,
+      fillesact_vieprod, fillesact_dmad, fillesact_dsad, fillesact_afad, fillesact_nbprod, fillesact_txrepros, fillesact_nbpp, fillesact_prol, fillesact_mort, 
-      prol_fillesact, mort_fillesact, txvf_fillesact, nbfilles_renouv
+      fillesact_txvf, nbfilles_renouv
     )
   
   colnames(filtered_taureaux) <- c(
     "cheptel", "anim", "nom", "date_naissance", "nom_chep_naiss", "nb_prod_in_chep", "utilgen", "prol", "mort", "txrepros", "nbpp", "txvf", "pnm", "pnf", "p120m", "p120f", "p210m", "p210f", 
     "dmsev", "dssev", "afsev", "nbfilles_avecprod", "pctfilles_avecprod", "isu_fillestot", "age_sort_fillestot", "agevel1_fillestot", "ivv1_fillestot", "ivv2p_fillestot", 
-    "vieprod_fillestot", "dmad_fillestot", "dsad_fillestot", "afad_fillestot", "nbprod_fillestot", "txrepros_fillestot", "nbpp_fillestot", "prol_fillestot", 
+    "vieprod_fillestot", "dmad_fillestot", "dsad_fillestot", "afad_fillestot", "nbprod_fillestot", "txrepros_fillestot", "nbpp_fillestot", "prol_fillestot", "mort_fillestot", 
-    "mort_fillestot", "txvf_fillestot", "nbfillesact_avecprod", "pctfillesact_avecprod", "isu_fillesact", "age_sort_fillesact", "agevel1_fillesact", "ivv1_fillesact", 
+    "txvf_fillestot", "nbfillesact_avecprod", "pctfillesact_avecprod", "isu_fillesact", "age_sort_fillesact", "agevel1_fillesact", "ivv1_fillesact", "ivv2p_fillesact", 
-    "ivv2p_fillesact", "vieprod_fillesact", "dmad_fillesact", "dsad_fillesact", "afad_fillesact", "nbprod_fillesact", "txrepros_fillesact", "nbpp_fillesact", 
+    "vieprod_fillesact", "dmad_fillesact", "dsad_fillesact", "afad_fillesact", "nbprod_fillesact", "txrepros_fillesact", "nbpp_fillesact", "prol_fillesact", "mort_fillesact", 
-    "prol_fillesact", "mort_fillesact", "txvf_fillesact", "nbfilles_renouv"
+    "txvf_fillesact", "nbfilles_renouv"
   )
-  
-  filtered_taureaux$cheptel <- cheptel
 
   con <- get_db_connection()
   
@@ -198,14 +208,35 @@ save_data_taureau <- function(data_taureaux, cheptel){
 }
 
 save_data_lignees <- function(stats_lignees){
+  filtered_lignees <- stats_lignees %>%
+    select(
+      cheptel, fondatrice, nom, dateNaiss, nomCheptelNaiss, nb_prod_in_chep, utilgen, prol, mort, txrepros, nbpp, txvf, pnm, pnf, p120m, 
+      p120f, p210m, p210f, dmsev, dssev, afsev, femtot_nbavecprod, femtot_pctavecprod, femtot_isu, femtot_age_sort, femtot_agevel1, femtot_ivv1, 
+      femtot_ivv2p, femtot_vieprod, femtot_dmad, femtot_dsad, femtot_afad, femtot_nbprod, femtot_txrepros, femtot_nbpp, femtot_prol, 
+      femtot_mort, femtot_txvf, femact_nbavecprod, femact_pctavecprod, femact_isu, femact_age_sort, femact_agevel1, femact_ivv1, 
+      femact_ivv2p, femact_vieprod, femact_dmad, femact_dsad, femact_afad, femact_nbprod, femact_txrepros, femact_nbpp, femact_prol, 
+      femact_mort, femact_txvf, nbfilles_renouv
+    )
+  
+  colnames(filtered_lignees) <- c(
+    "cheptel", "anim", "nom", "date_naissance", "nom_chep_naiss", "nb_desc_in_chep", "utilgen", "prol", "mort", "txrepros", "nbpp", "txvf", "pnm", "pnf", "p120m", 
+    "p120f", "p210m", "p210f", "dmsev", "dssev", "afsev", "nbfem_avecprod", "pctfem_avecprod", "isu_femtot", "age_sort_femtot", "agevel1_femtot", "ivv1_femtot", 
+    "ivv2p_femtot", "vieprod_femtot", "dmad_femtot", "dsad_femtot", "afad_femtot", "nbprod_femtot", "txrepros_femtot", "nbpp_femtot", "prol_femtot", 
+    "mort_femtot", "txvf_femtot", "nbfemact_avecprod", "pctfemact_avecprod", "isu_femact", "age_sort_femact", "agevel1_femact", "ivv1_femact", 
+    "ivv2p_femact", "vieprod_femact", "dmad_femact", "dsad_femact", "afad_femact", "nbprod_femact", "txrepros_femact", "nbpp_femact", "prol_femact", 
+    "mort_femact", "txvf_femact", "nbfem_renouv" 
+  )
+  
+  
   con <- get_db_connection()
   
   dbWriteTable(
     con,
     Id(schema = "hbc", table = "ecow_lignees"),
-    stats_lignees,
+    filtered_lignees,
     append = TRUE,
     row.names = FALSE
   )
   dbDisconnect(con) 
-}
+}
+

R/project/preprocessing.R

@@ -96,7 +96,7 @@ get_stats_tbl <- function(tab, nom_tab, cols, conditions = NULL, nom_cond = NA)
   })
 }
 
-get_synth_prod_vaches <- function(vaches, produits, params_ponderation){
+get_synth_prod_parent <- function(vaches, produits, params_ponderation){
   # On récupère les coefficients de pondération pour les pointages adultes 
   ppa <- params_ponderation$pointage$adulte
   
@@ -206,7 +206,9 @@ get_synth_prod_vaches <- function(vaches, produits, params_ponderation){
       c(ptgP, pn_m, pn_f, pn_corr, p120_m, p120_f, p120_corr, p210_m, p210_f, p210_corr),
       ~ ifelse(is.nan(.), NA_real_, .)
     ))
-  
+}
+
+get_note_carriere <- function(v_ref, params_ponderation){
   # calcul des stats, valeurs extremes et references pour la normalisation
   stats_chep <- get_stats_tbl(
     tab = v_ref,
@@ -216,7 +218,7 @@ get_synth_prod_vaches <- function(vaches, produits, params_ponderation){
   )
   
   # =========================
-  # 3) Normalisations
+  # Normalisation
   # =========================
   v_norm <- v_ref %>%
     mutate(
@@ -278,7 +280,7 @@ get_synth_prod_vaches <- function(vaches, produits, params_ponderation){
     )
   
   # =========================
-  # 4) Note carrière (pondérée)
+  # Note carrière (pondérée)
   # ========================
   # Récupère les paramètres de pondérations, ATTENTION, il faut que leurs noms soient parfaitement identiques à ceux de v_norm
   weights <- purrr::map_dbl(params_ponderation$carriere, 1)
@@ -315,3 +317,84 @@ get_synth_prod_vaches <- function(vaches, produits, params_ponderation){
   list(synthese = v_final, stats_chep = stats_chep)
 }
 
+get_stats_parent <- function(produits, regroupement){
+  produits %>%
+    group_by({{regroupement}}) %>%
+    summarise(
+      nb_prod_in_chep = n(),
+      utilgen = round(mean(rangVelageMipg == 1, na.rm = TRUE) * 100, 1),
+      prol    = round(n() / n_distinct(dateNaiss, numeroMipg) * 100, 1),
+      mort    = round((sum(mortsev == "O" | mortnat == "O", na.rm = TRUE)) / n() * 100, 1),
+      
+      txrepros = round(
+        sum(repro == "O", na.rm = TRUE) /
+          sum(is.na(mortsev) & is.na(mortnat)) * 100, 1
+      ),
+      
+      nbpp  = sum(NBPRODIPG, na.rm = TRUE),
+      txvf  = round(mean(conditionNaiss %in% c("1", "2"), na.rm = TRUE) * 100, 1),
+      
+      pnm   = round(mean(poidsNaiss[sexe == "1"], na.rm = TRUE), 1),
+      pnf   = round(mean(poidsNaiss[sexe == "2"], na.rm = TRUE), 1),
+      
+      p120m = round(mean(pat120[sexe == "1"], na.rm = TRUE), 1),
+      p120f = round(mean(pat120[sexe == "2"], na.rm = TRUE), 1),
+      
+      p210m = round(mean(pat210[sexe == "1"], na.rm = TRUE), 1),
+      p210f = round(mean(pat210[sexe == "2"], na.rm = TRUE), 1),
+      
+      dmsev = round(mean(dmSevrage, na.rm = TRUE), 1),
+      dssev = round(mean(dsSevrage, na.rm = TRUE), 1),
+      afsev = round(mean(afSevrage, na.rm = TRUE), 1),
+      
+      nb_femelles = sum(sexe == "2", na.rm = TRUE),
+      .groups = "drop"
+    ) %>%
+    filter(nb_prod_in_chep >= 5)
+}
+
+#' Renvoie les statistiques des produits pour les éléments ayant plus de 3 produits
+#' @param regroupement character. Champs sur lequel on veut faire le regroupement
+#' @param actif booléen. Filtre sur les produits 
+#' selon le champs {}
+#' @return Liste d'adhérents 
+get_stats_filles <- function(df, prefix, regroupement, actif = FALSE) {
+  nb <- df %>% 
+    group_by({{regroupement}}) %>%
+    summarise(
+      "{prefix}count" := n(),
+      .groups = "drop"
+    )
+  
+  if (actif) {
+    df <- df %>% filter(is.na(dateSortDetenteur))
+  }
+  
+  res <- df %>% group_by({{regroupement}}) %>%
+    summarise(
+      "{prefix}nbavecprod" := sum(NBPRODIPG > 0, na.rm = TRUE),
+      "{prefix}pctavecprod" := round(sum(NBPRODIPG > 0, na.rm = TRUE) / n() * 100, 1),
+      "{prefix}isu" := ifelse(n() >= 3, sum(embryon == "O", na.rm = TRUE), NA),
+      "{prefix}age_sort" := ifelse(n() >= 3, round(mean(age_years, na.rm = TRUE), 1), NA),
+      "{prefix}agevel1" := ifelse(n() >= 3, round(mean(agevel1, na.rm = TRUE), 1), NA),
+      "{prefix}ivv1" := ifelse(n() >= 3, round(mean(ivv1, na.rm = TRUE), 1), NA),
+      "{prefix}ivv2p" := ifelse(n() >= 3, round(mean(ivv2Brut, na.rm = TRUE), 1), NA),
+      "{prefix}vieprod" := ifelse(n() >= 3, round(mean(tempsprod, na.rm = TRUE), 1), NA),
+      
+      "{prefix}dmad" := ifelse(n() >= 3, round(mean(dmcAdulte, na.rm = TRUE), 1), NA),
+      "{prefix}dsad" := ifelse(n() >= 3, round(mean(dsAdulte, na.rm = TRUE), 1), NA),
+      "{prefix}afad" := ifelse(n() >= 3, round(mean(afAdulte, na.rm = TRUE), 1), NA),
+      
+      "{prefix}prol" := ifelse(n() >= 3, round(mean(prol, na.rm = TRUE), 1), NA),
+      "{prefix}mort" := ifelse(n() >= 3, round(mean(mort, na.rm = TRUE), 1), NA),
+      "{prefix}txvf" := ifelse(n() >= 3, round(mean(txvf, na.rm = TRUE), 1), NA),
+      
+      "{prefix}nbprod" := ifelse(n() >= 3, sum(NBPRODIPG, na.rm = TRUE), NA),
+      "{prefix}txrepros" := ifelse(n() >= 3, round(mean(txrepros, na.rm = TRUE), 1), NA),
+      "{prefix}nbpp" := ifelse(n() >= 3, sum(nbpp, na.rm = TRUE), NA),
+      
+      .groups = "drop"
+    )
+  
+  res <- left_join(res, nb, by = rlang::as_name(rlang::ensym(regroupement)))
+}