Last updated: 2022-01-21

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Knit directory: emlr_obs_analysis/analysis/

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Rmd 2c3fa75 jens-daniel-mueller 2022-01-21 cleaned alluvial plots
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Rmd e58f510 jens-daniel-mueller 2022-01-20 added relative changes to alluvial plots
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html cc31f4b jens-daniel-mueller 2022-01-20 Build site.
Rmd 416e107 jens-daniel-mueller 2022-01-20 added delta dcant map
html 11a800b jens-daniel-mueller 2022-01-20 Build site.
Rmd 81a40d5 jens-daniel-mueller 2022-01-20 updated alluvial plots
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Rmd 2ae5966 jens-daniel-mueller 2022-01-20 updated alluvial plots
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Rmd 0fb2ae5 jens-daniel-mueller 2022-01-19 printed column inv from AIP standard runs
html f347cd7 jens-daniel-mueller 2022-01-18 Build site.
Rmd 86b711c jens-daniel-mueller 2022-01-18 plot hemisphere budgets and publication results

1 Read files

version_id_pattern <- "103"

# identify required version IDs

Version_IDs_1 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = paste0("v_1", version_id_pattern))

Version_IDs_2 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = paste0("v_2", version_id_pattern))

Version_IDs_3 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
                            pattern = paste0("v_3", version_id_pattern))

Version_IDs <- c(Version_IDs_1, Version_IDs_2, Version_IDs_3)

print(Version_IDs)
[1] "v_1103" "v_2103" "v_3103"
for (i_Version_IDs in Version_IDs) {
  # i_Version_IDs <- Version_IDs[1]
  
  print(i_Version_IDs)
  
  path_version_data     <-
    paste(path_observations,
          i_Version_IDs,
          "/data/",
          sep = "")
  
  # load and join data files
  
  dcant_inv <-
    read_csv(paste(path_version_data,
                   "dcant_inv.csv",
                   sep = ""))
  
  dcant_inv_mod_truth <-
    read_csv(paste(path_version_data,
                   "dcant_inv_mod_truth.csv",
                   sep = "")) %>%
    filter(method == "total") %>%
    select(-method)
  
  dcant_inv_bias <-
    read_csv(paste(path_version_data,
                   "dcant_inv_bias.csv",
                   sep = "")) %>%
    mutate(Version_ID = i_Version_IDs)
  
  dcant_inv <- bind_rows(dcant_inv,
                         dcant_inv_mod_truth) %>%
    mutate(Version_ID = i_Version_IDs)
  
  dcant_budget_lat_grid <-
    read_csv(paste(path_version_data,
                   "dcant_budget_lat_grid.csv",
                   sep = "")) %>%
    mutate(Version_ID = i_Version_IDs)
  
  dcant_budget_lon_grid <-
    read_csv(paste(path_version_data,
                   "dcant_budget_lon_grid.csv",
                   sep = "")) %>%
    mutate(Version_ID = i_Version_IDs)
  
  
  params_local <-
    read_rds(paste(path_version_data,
                   "params_local.rds",
                   sep = ""))
  
  params_local <- bind_cols(
    Version_ID = i_Version_IDs,
    # {{config}} := str_c(params_local${{config}}, collapse = "|"),
    tref1 = params_local$tref1,
    tref2 = params_local$tref2)
  
  tref <- read_csv(paste(path_version_data,
                         "tref.csv",
                         sep = ""))
  
  params_local <- params_local %>%
    mutate(
      median_year_1 = sort(tref$median_year)[1],
      median_year_2 = sort(tref$median_year)[2],
      duration = median_year_2 - median_year_1,
      period = paste(median_year_1, "-", median_year_2)
    )
  
  if (exists("dcant_inv_all")) {
    dcant_inv_all <- bind_rows(dcant_inv_all, dcant_inv)
  }
  
  if (!exists("dcant_inv_all")) {
    dcant_inv_all <- dcant_inv
  }
  
  if (exists("dcant_inv_bias_all")) {
    dcant_inv_bias_all <- bind_rows(dcant_inv_bias_all, dcant_inv_bias)
  }
  
  if (!exists("dcant_inv_bias_all")) {
    dcant_inv_bias_all <- dcant_inv_bias
  }
  
  if (exists("dcant_budget_lat_grid_all")) {
    dcant_budget_lat_grid_all <- bind_rows(dcant_budget_lat_grid_all, dcant_budget_lat_grid)
  }
  
  if (!exists("dcant_budget_lat_grid_all")) {
    dcant_budget_lat_grid_all <- dcant_budget_lat_grid
  }
  
  if (exists("dcant_budget_lon_grid_all")) {
    dcant_budget_lon_grid_all <- bind_rows(dcant_budget_lon_grid_all, dcant_budget_lon_grid)
  }
  
  if (!exists("dcant_budget_lon_grid_all")) {
    dcant_budget_lon_grid_all <- dcant_budget_lon_grid
  }

  if (exists("params_local_all")) {
    params_local_all <- bind_rows(params_local_all, params_local)
  }
  
  if (!exists("params_local_all")) {
    params_local_all <- params_local
  }
  
  
}
[1] "v_1103"
[1] "v_2103"
[1] "v_3103"
rm(dcant_inv,
   dcant_inv_bias,
   dcant_inv_mod_truth,
   dcant_budget_lat_grid,
   dcant_budget_lon_grid,
   params_local,
   tref)

# params_local_all <-
#   params_local_all %>%
#   mutate(period = factor(period, c("1994 - 2004", "2004 - 2014", "1994 - 2014")))
dcant_inv_all <- dcant_inv_all %>%
  filter(inv_depth == params_global$inventory_depth_standard)

dcant_budget_lat_grid_all <- dcant_budget_lat_grid_all %>% 
  filter(inv_depth == params_global$inventory_depth_standard)

dcant_budget_lon_grid_all <- dcant_budget_lon_grid_all %>% 
  filter(inv_depth == params_global$inventory_depth_standard)
dcant_budget_lat_grid_all <- dcant_budget_lat_grid_all %>%
  pivot_wider(names_from = estimate,
              values_from = value) %>%
  filter(period != "1994 - 2014",
         method == "total")

dcant_budget_lon_grid_all <- dcant_budget_lon_grid_all %>%
  pivot_wider(names_from = estimate,
              values_from = value) %>%
  filter(period != "1994 - 2014",
         method == "total")
# Version_IDs <- Version_IDs[1:length(Version_IDs)-1]

for (i_Version_IDs in Version_IDs) {
  # i_Version_IDs <- Version_IDs[1]
  
  print(i_Version_IDs)
  
  path_version_data     <-
    paste(path_observations,
          i_Version_IDs,
          "/data/",
          sep = "")
  
  # load and join data files
  
  dcant_budget_basin_MLR <-
    read_csv(paste(path_version_data,
                   "dcant_budget_basin_MLR.csv",
                   sep = ""))
  
  dcant_budget_basin_MLR_mod_truth <-
    read_csv(paste(
      path_version_data,
      "dcant_budget_basin_MLR_mod_truth.csv",
      sep = ""
    ))
  
    
  dcant_budget_basin_MLR <- bind_rows(dcant_budget_basin_MLR,
                                      dcant_budget_basin_MLR_mod_truth)
  
  dcant_budget_basin_MLR <- dcant_budget_basin_MLR %>%
    mutate(Version_ID = i_Version_IDs)
  

  if (exists("dcant_budget_basin_MLR_all")) {
    dcant_budget_basin_MLR_all <-
      bind_rows(dcant_budget_basin_MLR_all, dcant_budget_basin_MLR)
  }
  
  if (!exists("dcant_budget_basin_MLR_all")) {
    dcant_budget_basin_MLR_all <- dcant_budget_basin_MLR
  }

}
[1] "v_1103"
[1] "v_2103"
[1] "v_3103"
rm(
  dcant_budget_basin_MLR,
  dcant_budget_basin_MLR_mod_truth
)
dcant_budget_basin_MLR_all <- dcant_budget_basin_MLR_all %>%
  filter(estimate == "dcant", 
         method == "total") %>% 
  select(-c(estimate, method)) %>% 
  rename(dcant = value)

dcant_budget_basin_MLR_all <- dcant_budget_basin_MLR_all %>%
  filter(inv_depth == params_global$inventory_depth_standard)
dcant_budget <- expression(Delta * C["ant"]~(PgC))

2 Individual cases

2.1 Absoulte values

2.1.1 dcant

dcant_inv_all %>%
  filter(data_source %in% c("mod", "obs"),
         period != "1994 - 2014") %>%
  group_by(data_source) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~ p_map_cant_inv(df = .x,
                     var = "dcant",
                     subtitle_text = paste("data_source:",
                                           unique(.x$data_source))) +
      facet_grid(period ~ .) +
      theme(axis.text = element_blank(),
            axis.ticks = element_blank())
  )
[[1]]

Version Author Date
48ec4c6 jens-daniel-mueller 2022-01-19

[[2]]

Version Author Date
48ec4c6 jens-daniel-mueller 2022-01-19
dcant_inv_all %>%
  filter(data_source %in% c("mod", "obs"),
         period != "1994 - 2014") %>%
  select(data_source, lon, lat, basin_AIP, period, dcant) %>% 
  pivot_wider(names_from = period,
              values_from = dcant) %>% 
  mutate(delta_dcant = `2004 - 2014` - `1994 - 2004`) %>% 
  group_by(data_source) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~ p_map_cant_inv(df = .x,
                     var = "delta_dcant",
                     subtitle_text = paste("data_source:",
                                           unique(.x$data_source)),
                     col = "divergent") +
      # facet_grid(period ~ .) +
      theme(axis.text = element_blank(),
            axis.ticks = element_blank())
  )
[[1]]

Version Author Date
cc31f4b jens-daniel-mueller 2022-01-20

[[2]]

Version Author Date
cc31f4b jens-daniel-mueller 2022-01-20

2.1.2 dcant pos

dcant_inv_all %>%
  filter(data_source %in% c("mod", "obs"),
         period != "1994 - 2014") %>%
  group_by(data_source) %>%
  group_split() %>%
  # head(1) %>%
  map(
    ~ p_map_cant_inv(df = .x,
                     var = "dcant_pos",
                     subtitle_text = paste("data_source:",
                                           unique(.x$data_source))) +
      facet_grid(period ~ .) +
      theme(axis.text = element_blank(),
            axis.ticks = element_blank())
  )
[[1]]

Version Author Date
cc31f4b jens-daniel-mueller 2022-01-20

[[2]]

Version Author Date
cc31f4b jens-daniel-mueller 2022-01-20

3 Basins hemisphere

3.1 Individual cases

3.1.1 Absoulte values

dcant_budget_basin_MLR_all_plot <- dcant_budget_basin_MLR_all %>%
  filter(period != "1994 - 2014",
         data_source == "obs") %>%
  mutate(
    basin = str_replace(basin, "_", ". "),
        basin = fct_relevel(
      basin,
      "N. Pacific",
      "S. Pacific",
      "N. Atlantic",
      "S. Atlantic",
      "Indian"
    )
  )
g1 <- dcant_budget_basin_MLR_all_plot %>%
  ggplot(aes(
    y = dcant,
    x = period,
    alluvium = basin,
    fill  = basin,
    stratum = basin
  )) +
  stat_alluvium(decreasing = FALSE) +
  stat_stratum(decreasing = FALSE) +
  stat_stratum(geom = "text",
               decreasing = FALSE,
               aes(label = paste(
                 round(after_stat(max-min),1)
                 # 100*round(after_stat(prop), 2), "%"
                 ))) +
  ggrepel::geom_label_repel(
    data = dcant_budget_basin_MLR_all_plot %>% filter(period == "2004 - 2014"),
    stat = "stratum",
    size = 4,
    nudge_x = .5,
    point.padding = 3,
    aes(fill = basin, label = basin),
    decreasing = FALSE
  )+
  scale_fill_brewer(palette = "Paired", guide = "none") +
  scale_y_continuous(limits = c(0, 32), expand = c(0, 0)) +
  labs(y = dcant_budget) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1),
        axis.title.x = element_blank()) +
  theme_classic()

newdat <- tibble(layer_data(g1))

change <- 
  newdat %>% 
  select(x, alluvium, count) %>% 
  pivot_wider(names_from = x,
              values_from = count) %>% 
  mutate(dcant_change = round(100*(`2` - `1`) / `1`)) %>% 
  select(alluvium, dcant_change)

coord <- newdat %>%
  filter(x == 2) %>% 
  select(x, y, alluvium)

new_layer <- full_join(
  change,
  coord
)

new_layer <- new_layer %>% 
  mutate(dcant_change = as.character(dcant_change),
         dcant_change = if_else(str_detect(dcant_change, "-"),
                                dcant_change,
                                paste0("+", dcant_change)),
         dcant_change = paste(dcant_change, "%"))

g1 +
  geom_text(data = new_layer,
            aes(
              x = x - 0.3,
              y = y,
              label = dcant_change
            ),
            inherit.aes = FALSE)

g2 <- dcant_budget_basin_MLR_all_plot %>%
  ggplot(aes(
    y = dcant,
    x = period,
    alluvium = basin,
    fill  = basin,
    stratum = basin,
    label = basin
  )) +
  geom_alluvium() +
  geom_stratum() +
  stat_stratum(geom = "text",
               aes(label = paste(
                 round(after_stat(count),1)
                 # 100*round(after_stat(prop), 2), "%"
                 ))) +
  ggrepel::geom_label_repel(
    data = dcant_budget_basin_MLR_all_plot %>% filter(period == "2004 - 2014"),
    stat = "stratum",
    size = 4,
    nudge_x = .5,
    point.padding = 3,
    aes(fill = basin)
  )+
  scale_fill_brewer(palette = "Paired", guide = "none") +
  scale_color_brewer(palette = "Paired", guide = "none") +
  scale_y_continuous(limits = c(0, 32.5), expand = c(0, 0)) +
  guides(y = "none") +
  labs(title = dcant_budget) +
  theme_classic() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1),
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        plot.title = element_text(hjust = 0.5))


newdat <- tibble(layer_data(g2))

change_basin <- 
  newdat %>% 
  select(x, alluvium, count) %>% 
  pivot_wider(names_from = x,
              values_from = count) %>% 
  mutate(dcant_change = round(100*(`2` - `1`) / `1`)) %>% 
  select(alluvium, dcant_change)

coord_basin <- newdat %>%
  filter(x == 2) %>% 
  select(x, y, alluvium)

new_layer_basin <- full_join(
  change_basin,
  coord_basin
)

new_layer_basin <- new_layer_basin %>% 
  mutate(dcant_change = as.character(dcant_change),
         dcant_change = if_else(str_detect(dcant_change, "-"),
                                dcant_change,
                                paste0("+", dcant_change)),
         dcant_change = paste(dcant_change, "%"))

new_layer_total <- 
  newdat %>% 
  select(x, alluvium, count) %>% 
  group_by(x) %>% 
  summarise(dcant_change = sum(count)) %>% 
  ungroup()

new_layer_total <- new_layer_total %>% 
  mutate(y = dcant_change,
         dcant_change = as.character(round(dcant_change,1)),
         dcant_change = paste("global:",dcant_change))

g2 +
  geom_text(data = new_layer_basin,
            aes(
              x = x - 0.3,
              y = y,
              label = dcant_change
            ),
            inherit.aes = FALSE) +
  geom_label(data = new_layer_total,
            aes(
              x = x,
              y = y + 1,
              label = dcant_change
            ),
            inherit.aes = FALSE)


sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.3

Matrix products: default
BLAS:   /usr/local/R-4.0.3/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.0.3/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ggalluvial_0.12.3 ggforce_0.3.3     metR_0.9.0        scico_1.2.0      
 [5] patchwork_1.1.1   collapse_1.5.0    forcats_0.5.0     stringr_1.4.0    
 [9] dplyr_1.0.5       purrr_0.3.4       readr_1.4.0       tidyr_1.1.3      
[13] tibble_3.1.3      ggplot2_3.3.5     tidyverse_1.3.0   workflowr_1.6.2  

loaded via a namespace (and not attached):
 [1] httr_1.4.2               viridisLite_0.3.0        jsonlite_1.7.1          
 [4] modelr_0.1.8             assertthat_0.2.1         highr_0.8               
 [7] blob_1.2.1               cellranger_1.1.0         ggrepel_0.8.2           
[10] yaml_2.2.1               pillar_1.6.2             backports_1.1.10        
[13] lattice_0.20-41          glue_1.4.2               RcppEigen_0.3.3.7.0     
[16] digest_0.6.27            RColorBrewer_1.1-2       promises_1.1.1          
[19] polyclip_1.10-0          checkmate_2.0.0          rvest_0.3.6             
[22] colorspace_2.0-2         htmltools_0.5.0          httpuv_1.5.4            
[25] Matrix_1.2-18            pkgconfig_2.0.3          broom_0.7.9             
[28] haven_2.3.1              scales_1.1.1             tweenr_1.0.2            
[31] whisker_0.4              later_1.2.0              git2r_0.27.1            
[34] generics_0.1.0           farver_2.0.3             ellipsis_0.3.2          
[37] withr_2.3.0              cli_3.0.1                magrittr_1.5            
[40] crayon_1.3.4             readxl_1.3.1             evaluate_0.14           
[43] fs_1.5.0                 fansi_0.4.1              MASS_7.3-53             
[46] xml2_1.3.2               RcppArmadillo_0.10.1.0.0 tools_4.0.3             
[49] data.table_1.14.0        hms_0.5.3                lifecycle_1.0.0         
[52] munsell_0.5.0            reprex_0.3.0             compiler_4.0.3          
[55] rlang_0.4.10             grid_4.0.3               rstudioapi_0.13         
[58] labeling_0.4.2           rmarkdown_2.10           gtable_0.3.0            
[61] DBI_1.1.0                R6_2.5.0                 lubridate_1.7.9         
[64] knitr_1.33               utf8_1.1.4               rprojroot_2.0.2         
[67] stringi_1.5.3            parallel_4.0.3           Rcpp_1.0.5              
[70] vctrs_0.3.8              dbplyr_1.4.4             tidyselect_1.1.0        
[73] xfun_0.25