#************************************************************************************************
#### Graphiques inutilisés dans le rapport de stage -------------------------------------
#************************************************************************************************



#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# graphiques des distributions des concentrations des métaux ----

# Calcium en bonus
ggplot(data_complet, aes(x = calcium)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#FEB37BFF", alpha = 0.7) +
  labs(x= "Calcium", y= "Densité", title= "Répartition des concentrations du Calcium") +
  stat_function(fun = dnorm,
                args = list(mean = mean(data_complet$calcium, na.rm = TRUE),
                            sd = sd(data_complet$calcium, na.rm = TRUE)),
                color = "red", linewidth = 1) +
  xlim(c(0, 200)) +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Magnésium
ggplot(data_complet, aes(x = magnesium)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#39558CFF", alpha = 0.7) +
  labs(x= "Magnésium", y= "Densité", title= "Répartition des concentrations du Magnésium") +
  stat_function(fun = dnorm,
                args = list(mean = mean(data_complet$magnesium, na.rm = TRUE),
                            sd = sd(data_complet$magnesium, na.rm = TRUE)),
                color = "red", linewidth = 1) +
  xlim(c(0, 200)) +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Sodium
ggplot(data_complet, aes(x = sodium)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#D8456CFF", alpha = 0.7) +
  labs(x= "Sodium", y= "Densité", title= "Répartition des concentrations du Sodium") +
  stat_function(fun = dnorm,
                args = list(mean = mean(data_complet$sodium, na.rm = TRUE),
                            sd = sd(data_complet$sodium, na.rm = TRUE)),
                color = "red", linewidth = 1) +
  xlim(c(0, 200)) +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))


# Plomb
ggplot(data_complet, aes(x = plomb)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#21908CFF", alpha = 0.7) +
  labs(x= "Plomb", y= "Densité", title= "Répartition des concentrations du Plomb") +
  stat_function(fun = dnorm,
                args = list(mean = mean(data$plomb, na.rm = TRUE),
                            sd = sd(data$plomb, na.rm = TRUE)),
                color = "red", linewidth = 1) +
  geom_vline(xintercept = 0.31, color = "tomato3", lty = "dashed") +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Nickel
ggplot(data_complet, aes(x = nickel)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#B63679FF", alpha = 0.7) +
  labs(x= "Nickel", y= "Densité", title= "Répartition des concentrations du Nickel") +
  stat_function(fun = dnorm,
                args = list(mean = mean(data$nickel, na.rm = TRUE),
                            sd = sd(data$nickel, na.rm = TRUE)),
                color = "red", linewidth = 1) +
  geom_vline(xintercept = 0.4, color = "tomato3", lty = "dashed") +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Cadmium
ggplot(data_complet, aes(x = cadmium)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#F98C0AFF", alpha = 0.7) +
  labs(x= "Cadmium", y= "Densité", title= "Répartition des concentrations du Cadmium") +
  stat_function(fun = dnorm,
                args = list(mean = mean(data$cadmium, na.rm = TRUE),
                            sd = sd(data$cadmium, na.rm = TRUE)),
                color = "red", linewidth = 1) +
  geom_vline(xintercept = 0.025, color = "tomato3", lty = "dashed") +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))



#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Graphique densité Ci avec BBAC

# BBAC
bbac <- data.frame(
  metal = c("Cadmium", "Nickel", "Plomb"),
  BBAC = c(0.025, 0.400, 0.310),   # mg/kg PF
  unite = "mg/kg PF")

data_long_Ci <- data_complet %>%
  select(cadmium, nickel, plomb) %>%
  pivot_longer(cols = everything(),
               names_to = "metal_raw",
               values_to = "Ci") %>%
  mutate(metal = case_when(
    metal_raw == "cadmium" ~ "Cadmium",
    metal_raw == "nickel" ~ "Nickel",
    metal_raw == "plomb" ~ "Plomb")) %>%
  filter(!is.na(Ci))

ggplot(data_long_Ci, aes(x = Ci, fill = metal, color = metal)) +
  geom_density(alpha = 0.4, linewidth = 0.8) +
  geom_vline(data = bbac,
             aes(xintercept = BBAC, color = metal),
             linetype = "dashed", linewidth = 1.2) +
  geom_text(data = bbac,
            aes(x = BBAC, y = Inf, label = paste0("BBAC=", BBAC)),
            angle = 90, vjust = -0.3, hjust = 1.2, size = 3) +
  facet_wrap(~ metal, scales = "free") +
  scale_fill_manual(values  = c("Cadmium" = "#F98C0AFF",
                                "Nickel" = "#B63679FF",
                                "Plomb" = "#21908CFF")) +
  scale_color_manual(values = c("Cadmium" = "#F98C0AFF",
                                "Nickel" = "#B63679FF",
                                "Plomb" = "#21908CFF")) +
  labs(title = "Distribution des concentrations dans le gammare vs BBAC",
    x = "Concentration (mg/kg PF)",
    y = "Densite") +
  theme_minimal() +
  theme(legend.position = "none",
        plot.title = element_text(face = "bold", hjust = 0.5))



#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# graphiques métal en fonction du calcium

# Plomb en fonction du calcium
ggplot(data_complet, aes(x = calcium, y = plomb)) +
  geom_point(color = "#21908CFF", size = 2.5, alpha = 0.75) +
  geom_smooth(method = "lm", color = "#5DC863FF", linewidth = 1) +
  geom_line(y=0.31, linewidth = 1, color = "darkred") +
  labs(title = "Concentration en plomb en fonction du calcium",
    x = "Concentration en calcium (mg/L)",
    y = "Concentration en plomb (mg/kg de PF)") +
  theme_bw() +
  theme(plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Nickel en fonction du calcium
ggplot(data_complet, aes(x = calcium, y = nickel)) +
  geom_point(color = "#51127CFF", size = 2.5, alpha = 0.75) +
  geom_smooth(method = "lm", color = "#B63679FF", linewidth = 1) +
  geom_line(y=0.4, linewidth = 1, color = "darkred") +
  labs(title = "Concentration en nickel en fonction du calcium",
    x = "Concentration en calcium (mg/L)",
    y = "Concentration en nickel (mg/kg de PF)") +
  theme_bw() +
  theme(plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Cadmium en fonction du calcium
ggplot(data_complet, aes(x = calcium, y = cadmium)) +
  geom_point(color = "#BB3754FF", size = 2.5, alpha = 0.75) +
  geom_smooth(method = "lm", color = "#F98C0AFF", linewidth = 1) +
  geom_line(y=0.025, linewidth = 1, color = "darkred") +
  ylim(0, 0.4) +
  labs(title = "Concentration en cadmium en fonction du calcium",
    x = "Concentration en calcium (mg/L)",
    y = "Concentration en cadmium (mg/kg de PF)") +
  theme_bw() +
  theme(plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))



#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Ratio Ci/Ceau du nickel en fonction des ions

# ratio Ci/Ceau en fonction du calcium
data_complet %>%
  filter(!is.na(nickel), !is.na(Ceau_med_ugL_Nickel),
         Ceau_med_ugL_Nickel > 0, !is.na(classe_calcium)) %>%
  mutate(ratio_Ni = nickel / Ceau_med_ugL_Nickel) %>%
  ggplot(aes(x = classe_calcium, y = ratio_Ni, fill = classe_calcium)) +
  geom_boxplot(alpha = 0.7) +
  scale_y_log10() +
  scale_fill_viridis_d() +
  labs(x = "Classe de calcium (mg/L)",
       y = "Ratio Ci/Ceau (mg/kg PF / µg/L) (échelle log)") +
  theme_minimal() +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, hjust = 1),
        plot.title = element_text(face = "bold", hjust = 0.5)) +
  theme(axis.title = element_text(size = 16),
        axis.text = element_text(size = 16),
        legend.title = element_text(size = 16, face = "bold"),
        legend.text = element_text(size = 16))

# ratio Ci/Ceau en fonction du magnésium
data_complet %>%
  filter(!is.na(nickel), !is.na(Ceau_med_ugL_Nickel),
         Ceau_med_ugL_Nickel > 0, !is.na(classe_magnesium)) %>%
  mutate(ratio_Ni = nickel / Ceau_med_ugL_Nickel) %>%
  ggplot(aes(x = classe_magnesium, y = ratio_Ni, fill = classe_magnesium)) +
  geom_boxplot(alpha = 0.7) +
  scale_y_log10() +
  scale_fill_viridis_d() +
  labs(x = "Classe de magnésium (mg/L)",
       y = "Ratio Ci/Ceau (mg/kg PF / µg/L) (échelle log)") +
  theme_minimal() +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, hjust = 1),
        plot.title = element_text(face = "bold", hjust = 0.5)) +
  theme(axis.title = element_text(size = 16),
        axis.text = element_text(size = 16),
        legend.title = element_text(size = 16, face = "bold"),
        legend.text = element_text(size = 16))

# ratio Ci/Ceau en fonction du sodium
data_complet %>%
  filter(!is.na(nickel), !is.na(Ceau_med_ugL_Nickel),
         Ceau_med_ugL_Nickel > 0, !is.na(classe_sodium)) %>%
  mutate(ratio_Ni = nickel / Ceau_med_ugL_Nickel) %>%
  ggplot(aes(x = classe_sodium, y = ratio_Ni, fill = classe_sodium)) +
  geom_boxplot(alpha = 0.7) +
  scale_y_log10() +
  scale_fill_viridis_d() +
  labs(x = "Classe de sodium (mg/L)",
       y = "Ratio Ci/Ceau (mg/kg PF / µg/L) (échelle log)") +
  theme_minimal() +
  theme(legend.position = "none",
        axis.text.x = element_text(angle = 45, hjust = 1),
        plot.title = element_text(face = "bold", hjust = 0.5)) +
  theme(axis.title = element_text(size = 16),
        axis.text = element_text(size = 16),
        legend.title = element_text(size = 16, face = "bold"),
        legend.text = element_text(size = 16))




#************************************************************************************************
#### Graphiques 3D des concentrations d'ions ----------------------------------------------------
#************************************************************************************************


# enlever les NA pour pas les mettre dans le graphe
data_3D <- naiades %>% filter(!is.na(calcium), !is.na(sodium), !is.na(magnesium))

plot_ly(
  data = data_3D, x = ~calcium, y = ~sodium, z = ~magnesium,
  type = "scatter3d", mode = "markers",
  marker = list(size = 4, color = ~calcium, colorscale = "Viridis", showscale = TRUE),
  text = ~code_stat,
  hovertemplate = paste(
    "Station: %{text}<br>", "Calcium: %{x} mg/L<br>", "Sodium: %{y} mg/L<br>",
    "Magnesium: %{z} mg/L") ) %>%
  layout(scene = list(
      xaxis = list(title = "Calcium (mg/L)"),
      yaxis = list(title = "Sodium (mg/L)"),
      zaxis = list(title = "Magnesium (mg/L)")
    ),
    title = "Concentrations en ions par station")



#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Graphiques distributions Ceau prédite (BLM)

# Cadmium
ggplot(data_complet, aes(x = Ceau_Cd_ugL)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#F98C0AFF", alpha = 0.7) +
  labs(x= "Cadmium", y= "Densité", title= "Répartition des concentrations prédites du Cadmium") +
  stat_function(fun = dnorm, args = list(mean = mean(Ceau_Cd_ugL, na.rm = TRUE),
                            sd = sd(Ceau_Cd_ugL, na.rm = TRUE)),
                color = "red", linewidth = 1) +
  geom_vline(xintercept = 0.4, color = "tomato3", lty = "dashed") +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Nickel
ggplot(data_complet, aes(x = Ceau_Ni_ugL)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#B63679FF", alpha = 0.7) +
  labs(x= "Nickel", y= "Densité", title= "Répartition des concentrations prédites du Nickel") +
  stat_function(fun = dnorm, args = list(mean = mean(Ceau_Ni_ugL, na.rm = TRUE),
                            sd = sd(Ceau_Ni_ugL,   na.rm = TRUE)),
                color = "red", linewidth = 1) +
  geom_vline(xintercept = 0.4, color = "tomato3", lty = "dashed") +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))

# Plomb
ggplot(data_complet, aes(x = Ceau_Pb_ugL)) +
  geom_histogram(aes(y = after_stat(density)), bins = 50, fill = "#21908CFF", alpha = 0.7) +
  labs(x= "Plomb", y= "Densité", title= "Répartition des concentrations prédites du Plomb") +
  stat_function(fun = dnorm, args = list(mean = mean(Ceau_Pb_ugL, na.rm = TRUE),
                            sd = sd(Ceau_Pb_ugL,   na.rm = TRUE)),
                color = "red", linewidth = 1) +
  geom_vline(xintercept = 0.4, color = "tomato3", lty = "dashed") +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5, face = "bold", size = 14),
    axis.title = element_text(size = 12),
    axis.text = element_text(size = 10))


#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Graphiques cartes: Ceau prédite (BLM) vs NQE



#+++++++++++++++++++++++++++++++++++++++++
# Seuils NQE eau (µg/L)

# Seuils NQE en µg/L
NQE_Cd <- 0.08
NQE_Ni <- 4.0
NQE_Pb <- 1.2

# NQE Cd ajustée au calcium (CaCO3) de la station
NQE_Cd_calcique <- function(calcium_mgL) {
  durete <- calcium_mgL * 2.5  # conversion Ca en CaCO3 pour les classes NQE
  case_when(
    durete < 40 ~ 0.08,
    durete >= 40 & durete < 50 ~ 0.09,
    durete >= 50 & durete < 100 ~ 0.15,
    durete >= 100 ~ 0.25,
    TRUE ~ NA_real_)
}

# on ajoute une colonne dans data_complet pour le seuil NQE
data_complet <- data_complet %>%
  mutate(
    NQE_Cd_stat = NQE_Cd_calcique(calcium),
    classe_Ceau_Cd = case_when(
      is.na(Ceau_Cd_ugL) | is.na(NQE_Cd_stat) ~ NA_character_,
      Ceau_Cd_ugL <= NQE_Cd_stat ~ "En dessous de la NQE",
      Ceau_Cd_ugL >  NQE_Cd_stat ~ "Au dessus de la NQE"
    ) %>% factor(levels = c("En dessous de la NQE", "Au dessus de la NQE")))


# Créer les classes pour Ni et Pb
data_complet <- data_complet %>%
  mutate(
    classe_Ceau_Ni = cut(Ceau_Ni_ugL,
                         breaks = c(0, NQE_Ni, Inf),
                         labels = c("En dessous de la NQE", "Au dessus de la NQE"),
                         include.lowest = TRUE),
    
    classe_Ceau_Pb = cut(Ceau_Pb_ugL,
                         breaks = c(0, NQE_Pb, Inf),
                         labels = c("En dessous de la NQE", "Au dessus de la NQE"),
                         include.lowest = TRUE))

# Nombre de stations dans chaque cas + nombre NA
table(data_complet$classe_Ceau_Cd, useNA = "always")
table(data_complet$classe_Ceau_Ni, useNA = "always")
table(data_complet$classe_Ceau_Pb, useNA = "always")



# Cadmium
ggplot() +
  geom_polygon(data = france,
               aes(x = long, y = lat, group = group), fill = "grey91", color = "white") +
  geom_point(data = data_complet %>%
               filter(!is.na(classe_Ceau_Cd), !is.na(longitude)) %>%
               arrange(classe_Ceau_Cd),
             aes(x = longitude, y = latitude, color = classe_Ceau_Cd), size = 3) +
  scale_color_manual(values = c("En dessous de la NQE" = "#F98C0AFF",
                                "Au dessus de la NQE" = "tomato4"),
                     name = "Cadmium vs NQE") +
  annotate("text", y = 51.5, x = 3,
           label = "bold(`Cadmium prédit vs NQE (ajustée aux niveaux de calcium)`)",
           size  = 5, parse = TRUE) +
  theme_void() +
  theme(legend.position = "right")


# Nickel
ggplot() +
  geom_polygon(data = france,
               aes(x = long, y = lat, group = group), fill = "grey91", color = "white") +
  geom_point(data = data_complet %>%
               filter(!is.na(classe_Ceau_Ni), !is.na(longitude)) %>%
               arrange(classe_Ceau_Ni),
             aes(x = longitude, y = latitude, color = classe_Ceau_Ni), size = 3) +
  scale_color_manual(values = c("En dessous de la NQE" = "#B63679FF",
                                "Au dessus de la NQE" = "tomato4"),
                     name = "Nickel (µg/L)") +
  annotate("text", y = 51.5, x = 3,
           label = "bold(`Nickel prédit vs NQE`)",
           size = 6, parse = TRUE) +
  theme_void() +
  theme(legend.position = "right")

# Plomb
ggplot() +
  geom_polygon(data = france,
               aes(x = long, y = lat, group = group), fill = "grey91", color = "white") +
  geom_point(data = data_complet %>%
               filter(!is.na(classe_Ceau_Pb), !is.na(longitude)) %>%
               arrange(classe_Ceau_Pb),
             aes(x = longitude, y = latitude, color = classe_Ceau_Pb),
             size = 3) +
  scale_color_manual(values = c("En dessous de la NQE" = "#21908CFF",
                                "Au dessus de la NQE" = "tomato4"),
                     name = "Plomb (µg/L)") +
  annotate("text", y = 51.5, x = 3,
           label = "bold(`Plomb prédit vs NQE`)",
           size = 6, parse = TRUE) +
  theme_void() +
  theme(legend.position = "right")




#************************************************************************************************
#### Comparaison Ceau prédite (BLM) vs Ceau mesurée (Naiades) ----------------------------------
#************************************************************************************************


# Nickel
data_complet %>%
  filter(!is.na(Ceau_Ni_ugL), !is.na(Ceau_med_ugL_Nickel)) %>%
  ggplot(aes(x = Ceau_med_ugL_Nickel, y = Ceau_Ni_ugL)) +
  geom_point(color = "#B63679FF", size = 3, alpha = 0.7) +
  geom_abline(slope = 1, intercept = 0, # droite 1:1
              linetype = "dashed", color = "grey40") +
  labs(title = "Nickel: concentration prédite (BLM) vs mesurée dans l'eau",
    x = "Ceau mesurée Naiades (µg/L)",
    y = "Ceau prédite BLM (µg/L)") +
  theme_minimal() +
  theme(plot.title = element_text(face = "bold", hjust = 0.5))

# Plomb
data_complet %>%
  filter(!is.na(Ceau_Pb_ugL), !is.na(Ceau_med_ugL_Plomb)) %>%
  ggplot(aes(x = Ceau_med_ugL_Plomb, y = Ceau_Pb_ugL)) +
  geom_point(color = "#21908CFF", size = 3, alpha = 0.7) +
  geom_abline(slope = 1, intercept = 0, # droite 1:1
              linetype = "dashed", color = "grey40") +
  labs(title = "Plomb: concentration prédite (BLM) vs mesurée dans l'eau",
    x = "Ceau mesurée Naiades (µg/L)",
    y = "Ceau prédite BLM (µg/L)") +
  xlim(c(0,1)) + ylim(c(0, 0.02)) +
  theme_minimal() +
  theme(plot.title = element_text(face = "bold", hjust = 0.5))



#************************************************************************************************
#### Modèle TK (comparaison avec TK-BLM) -------------------------------------------------------
#************************************************************************************************


#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Graphiques comparaison prédite TK vs réelle

# Nickel
data_complet %>%
  filter(!is.na(Ceau_Ni_TK_ugL), !is.na(Ceau_med_ugL_Nickel),
         !is.infinite(Ceau_Ni_TK_ugL), Ceau_Ni_TK_ugL > 0) %>%
  ggplot(aes(x = Ceau_med_ugL_Nickel, y = Ceau_Ni_TK_ugL)) +
  geom_point(color = "#B63679FF", size = 2.5, alpha = 0.6) +
  geom_abline(slope = 1, intercept = 0,
              linetype = "dashed", color = "grey40") +
  geom_hline(yintercept = 4.0, color = "red",
             linetype = "dotted", linewidth = 0.8) +
  annotate("text", x = Inf, y = 4.0, label = "NQE = 4 µg/L",
           color = "red", hjust = 1.1, vjust = -0.3, size = 3) +
  labs(title = "Nickel : Ceau prédite (TK) vs mesurée (Naiades)",
       x = "Ceau mesurée Naiades (µg/L)",
       y = "Ceau prédite TK (µg/L)") +
  theme_minimal() +
  theme(plot.title = element_text(face = "bold", hjust = 0.5))

# Plomb
data_complet %>%
  filter(!is.na(Ceau_Pb_TK_ugL), !is.na(Ceau_med_ugL_Plomb),
         !is.infinite(Ceau_Pb_TK_ugL), Ceau_Pb_TK_ugL > 0) %>%
  ggplot(aes(x = Ceau_med_ugL_Plomb, y = Ceau_Pb_TK_ugL)) +
  geom_point(color = "#21908CFF", size = 2.5, alpha = 0.6) +
  geom_abline(slope = 1, intercept = 0,
              linetype = "dashed", color = "grey40") +
  geom_hline(yintercept = 1.2, color = "red",
             linetype = "dotted", linewidth = 0.8) +
  annotate("text", x = Inf, y = 1.2, label = "NQE = 1.2 µg/L",
           color = "red", hjust = 1.1, vjust = -0.3, size = 3) +
  labs(title = "Plomb : Ceau prédite (TK) vs mesurée (Naiades)",
       x = "Ceau mesurée Naiades (µg/L)",
       y = "Ceau prédite TK (µg/L)") +
  theme_minimal() +
  theme(plot.title = element_text(face = "bold", hjust = 0.5))