Column inventories
Jens Daniel Müller
28 June, 2022
Last updated: 2022-06-28
Checks: 7 0
Knit directory: emlr_obs_analysis/analysis/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | b52b159 | jens-daniel-mueller | 2022-06-27 | Build site. |
| html | 09b0780 | jens-daniel-mueller | 2022-05-24 | Build site. |
| html | 25da2fb | jens-daniel-mueller | 2022-05-24 | Build site. |
| html | e09320d | jens-daniel-mueller | 2022-04-12 | Build site. |
| html | 8dca96a | jens-daniel-mueller | 2022-04-12 | Build site. |
| html | acad2e2 | jens-daniel-mueller | 2022-04-09 | Build site. |
| html | c3a6238 | jens-daniel-mueller | 2022-03-08 | Build site. |
| Rmd | 775eb4f | jens-daniel-mueller | 2022-03-08 | moving eras analysis implemented |
version_id_pattern <- "m"
config <- "MLR_basins"1 Read files
# identify required version IDs
Version_IDs_1 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
pattern = paste0("v_1", "m"))
Version_IDs_2 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
pattern = paste0("v_2", "m"))
Version_IDs_3 <- list.files(path = "/nfs/kryo/work/jenmueller/emlr_cant/observations",
pattern = paste0("v_3", "m"))
Version_IDs <- c(Version_IDs_1, Version_IDs_2, Version_IDs_3)
print(Version_IDs) [1] "v_1m00" "v_1m01" "v_1m02" "v_1m03" "v_1m04" "v_1m05" "v_1m06" "v_1m07"
[9] "v_1m08" "v_1m09" "v_1m10"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,
MLR_basins := str_c(params_local$MLR_basins, collapse = "|"),
tref1 = params_local$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$median_year)[2],
duration = median_year_2 - median_year_1,
period = paste(median_year_1, "-", median_year_2)
)
if (exists("dcant_inv_all")) {
dcant_inv_all <- bind_rows(dcant_inv_all, dcant_inv)
}
if (!exists("dcant_inv_all")) {
dcant_inv_all <- dcant_inv
}
if (exists("dcant_inv_bias_all")) {
dcant_inv_bias_all <- bind_rows(dcant_inv_bias_all, dcant_inv_bias)
}
if (!exists("dcant_inv_bias_all")) {
dcant_inv_bias_all <- dcant_inv_bias
}
if (exists("dcant_budget_lat_grid_all")) {
dcant_budget_lat_grid_all <- bind_rows(dcant_budget_lat_grid_all, dcant_budget_lat_grid)
}
if (!exists("dcant_budget_lat_grid_all")) {
dcant_budget_lat_grid_all <- dcant_budget_lat_grid
}
if (exists("dcant_budget_lon_grid_all")) {
dcant_budget_lon_grid_all <- bind_rows(dcant_budget_lon_grid_all, dcant_budget_lon_grid)
}
if (!exists("dcant_budget_lon_grid_all")) {
dcant_budget_lon_grid_all <- dcant_budget_lon_grid
}
if (exists("params_local_all")) {
params_local_all <- bind_rows(params_local_all, params_local)
}
if (!exists("params_local_all")) {
params_local_all <- params_local
}
}[1] "v_1m00"
[1] "v_1m01"
[1] "v_1m02"
[1] "v_1m03"
[1] "v_1m04"
[1] "v_1m05"
[1] "v_1m06"
[1] "v_1m07"
[1] "v_1m08"
[1] "v_1m09"
[1] "v_1m10"rm(dcant_inv,
dcant_inv_bias,
dcant_inv_mod_truth,
dcant_budget_lat_grid,
dcant_budget_lon_grid,
params_local,
tref)
# params_local_all <-
# params_local_all %>%
# mutate(period = factor(period, c("1994 - 2004", "2004 - 2014", "1994 - 2014")))dcant_inv_all <- dcant_inv_all %>%
filter(inv_depth == params_global$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")2 Individual cases
2.1 Absoulte values
dcant_inv_all %>%
filter(data_source %in% c("mod", "obs")) %>%
p_map_cant_inv(var = "dcant") +
facet_grid(period ~ data_source) +
theme(axis.text = element_blank(),
axis.ticks = element_blank())
2.2 Biases
dcant_inv_bias_all %>%
p_map_cant_inv(var = "dcant_bias",
col = "bias") +
facet_grid(period ~ .) +
theme(axis.text = element_blank(),
axis.ticks = element_blank())
2.2.1 Density distribution
dcant_inv_bias_all %>%
filter(abs(dcant_bias) < 10) %>%
ggplot(aes(dcant_bias, col = period)) +
scale_color_brewer(palette = "Paired") +
geom_vline(xintercept = 0) +
geom_density()
| Version | Author | Date |
|---|---|---|
| c3a6238 | jens-daniel-mueller | 2022-03-08 |
2.3 Lat grid budgets
dcant_budget_lat_grid_all %>%
arrange(lat_grid) %>%
ggplot(aes(lat_grid, dcant, col = period)) +
geom_hline(yintercept = 0) +
geom_path() +
coord_flip() +
scale_color_viridis_d() +
facet_grid(basin_AIP ~ data_source)
| Version | Author | Date |
|---|---|---|
| c3a6238 | jens-daniel-mueller | 2022-03-08 |
2.4 Lon grid budgets
dcant_budget_lon_grid_all %>%
arrange(lon_grid) %>%
ggplot(aes(lon_grid, dcant, col = period)) +
geom_hline(yintercept = 0) +
geom_path() +
scale_color_viridis_d() +
facet_grid(basin_AIP ~ data_source)
| Version | Author | Date |
|---|---|---|
| c3a6238 | jens-daniel-mueller | 2022-03-08 |
sessionInfo()R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.3
Matrix products: default
BLAS: /usr/local/R-4.1.2/lib64/R/lib/libRblas.so
LAPACK: /usr/local/R-4.1.2/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] colorspace_2.0-2 marelac_2.1.10 shape_1.4.6 ggforce_0.3.3
[5] metR_0.11.0 scico_1.3.0 patchwork_1.1.1 collapse_1.7.0
[9] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4
[13] readr_2.1.1 tidyr_1.1.4 tibble_3.1.6 ggplot2_3.3.5
[17] tidyverse_1.3.1 workflowr_1.7.0
loaded via a namespace (and not attached):
[1] fs_1.5.2 bit64_4.0.5 lubridate_1.8.0 gsw_1.0-6
[5] RColorBrewer_1.1-2 httr_1.4.2 rprojroot_2.0.2 tools_4.1.2
[9] backports_1.4.1 bslib_0.3.1 utf8_1.2.2 R6_2.5.1
[13] DBI_1.1.2 withr_2.4.3 tidyselect_1.1.1 processx_3.5.2
[17] bit_4.0.4 compiler_4.1.2 git2r_0.29.0 cli_3.1.1
[21] rvest_1.0.2 xml2_1.3.3 labeling_0.4.2 sass_0.4.0
[25] scales_1.1.1 checkmate_2.0.0 SolveSAPHE_2.1.0 callr_3.7.0
[29] digest_0.6.29 rmarkdown_2.11 oce_1.5-0 pkgconfig_2.0.3
[33] htmltools_0.5.2 highr_0.9 dbplyr_2.1.1 fastmap_1.1.0
[37] rlang_1.0.2 readxl_1.3.1 rstudioapi_0.13 jquerylib_0.1.4
[41] generics_0.1.1 farver_2.1.0 jsonlite_1.7.3 vroom_1.5.7
[45] magrittr_2.0.1 Rcpp_1.0.8 munsell_0.5.0 fansi_1.0.2
[49] lifecycle_1.0.1 stringi_1.7.6 whisker_0.4 yaml_2.2.1
[53] MASS_7.3-55 grid_4.1.2 parallel_4.1.2 promises_1.2.0.1
[57] crayon_1.4.2 haven_2.4.3 hms_1.1.1 seacarb_3.3.0
[61] knitr_1.37 ps_1.6.0 pillar_1.6.4 reprex_2.0.1
[65] glue_1.6.0 evaluate_0.14 getPass_0.2-2 data.table_1.14.2
[69] modelr_0.1.8 vctrs_0.3.8 tzdb_0.2.0 tweenr_1.0.2
[73] httpuv_1.6.5 cellranger_1.1.0 gtable_0.3.0 polyclip_1.10-0
[77] assertthat_0.2.1 xfun_0.29 broom_0.7.11 later_1.3.0
[81] viridisLite_0.4.0 ellipsis_0.3.2 here_1.0.1