Budgets
Jens Daniel Müller
06 October, 2021
Last updated: 2021-10-06
Checks: 7 0
Knit directory: emlr_obs_analysis/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | f9b4f93 | jens-daniel-mueller | 2021-10-05 | Build site. |
| html | ae93565 | jens-daniel-mueller | 2021-09-29 | Build site. |
| Rmd | c5eb521 | jens-daniel-mueller | 2021-09-29 | coverage maps added |
| html | 960d158 | jens-daniel-mueller | 2021-09-29 | Build site. |
| html | 0573621 | jens-daniel-mueller | 2021-09-29 | Build site. |
| Rmd | f5cf35e | jens-daniel-mueller | 2021-09-29 | rebuildt with vif results |
1 Read files
GLODAP_preprocessed <-
read_csv(
paste(
path_preprocessing,
"GLODAPv2.2021_preprocessed.csv",
sep = ""
)
)2 Time series histogram
map +
geom_raster(data = GLODAP_preprocessed %>%
filter(year %in% c(2013, 2014),
cruise < 2000,
lon > 300,
lon < 350) %>%
count(lat, lon, cruise),
aes(lon, lat, fill = as.factor(cruise))) +
scale_fill_brewer(palette = "Set1")
| Version | Author | Date |
|---|---|---|
| 0573621 | jens-daniel-mueller | 2021-09-29 |
time_histo <- GLODAP_preprocessed %>%
drop_na() %>%
mutate(version = if_else(cruise <1000, "Gruber et al. (2019)",
"Data added"),
version = if_else(cruise %in% c(1041, 1042), "Gruber et al. (2019)", version)) %>%
count(year, version)
GLODAP_preprocessed %>%
drop_na() %>%
mutate(version = if_else(cruise <1000, "Gruber et al. (2019)",
"Data added"),
version = if_else(cruise %in% c(1041, 1042), "Gruber et al. (2019)", version)) %>%
count(version)[38;5;246m# A tibble: 2 × 2[39m
version n
[3m[38;5;246m<chr>[39m[23m [3m[38;5;246m<int>[39m[23m
[38;5;250m1[39m Data added [4m9[24m[4m4[24m402
[38;5;250m2[39m Gruber et al. (2019) [4m2[24m[4m2[24m[4m1[24m038p_time_histo_G19 <-
time_histo %>%
filter(version == "Gruber et al. (2019)") %>%
ggplot() +
geom_col(aes(year, n, fill = version),
col = "grey20") +
scale_fill_manual(values = c("grey70"),
name = "") +
scale_x_continuous(breaks = seq(1900, 2100, 5),
limits = c(1981, 2020)) +
scale_y_continuous(limits = c(0, max(time_histo$n) + 500)) +
coord_cartesian(expand = 0) +
labs(title = "Observations per year") +
theme_classic() +
theme(axis.title = element_blank())
p_time_histo_all <-
time_histo %>%
ggplot() +
geom_col(aes(year, n, fill = version),
col = "grey20") +
scale_fill_manual(values = c("darkgoldenrod1", "grey70"),
name = "") +
scale_x_continuous(breaks = seq(1900, 2100, 5),
limits = c(1981, 2020)) +
scale_y_continuous(limits = c(0, max(time_histo$n) + 500)) +
coord_cartesian(expand = 0) +
labs(title = "Observations per year") +
theme_classic() +
theme(axis.title = element_blank())
p_time_histo_G19
| Version | Author | Date |
|---|---|---|
| 0573621 | jens-daniel-mueller | 2021-09-29 |
p_time_histo_all
| Version | Author | Date |
|---|---|---|
| 0573621 | jens-daniel-mueller | 2021-09-29 |
ggsave(plot = p_time_histo_G19,
path = "output/publication",
filename = "time_histo_G19.png",
height = 2,
width = 10)
ggsave(plot = p_time_histo_all,
path = "output/publication",
filename = "time_histo_all.png",
height = 2,
width = 10)3 Time series histogram
MLR_basins_in <- c("1", "2", "AIP", "SO_2", "5", "SO_AIP", "SO")
# basinmask$group_id <-
# basinmask %>% group_indices(MLR_basins, basin)
basin_maps <-
map +
geom_raster(data = basinmask %>% filter(MLR_basins %in% MLR_basins_in),
aes(lon, lat, fill = basin)) +
scale_fill_brewer(palette = "Set3", guide = "none") +
facet_wrap( ~ MLR_basins) +
theme(axis.text = element_blank(),
axis.ticks = element_blank())
basin_maps
ggsave(plot = basin_maps,
path = "output/publication",
filename = "basin_maps.png",
height = 5,
width = 10)4 coverage maps
GLODAP_era_grid <- GLODAP_preprocessed %>%
mutate(era = cut(year,
seq(1990, 2020, 10),
labels = c("1990 - 1999", "2000 - 2009", "2010 - 2019"),
right = FALSE)) %>%
group_by(lon, lat, era) %>%
summarise(year_max = max(year),
year_min = min(year)) %>%
ungroup() %>%
drop_na()
coverage_map <-
map +
geom_raster(data = GLODAP_era_grid,
aes(lon, lat)) +
scale_fill_viridis_c() +
facet_grid(. ~ era) +
theme(axis.text = element_blank(),
axis.ticks = element_blank())
coverage_map
| Version | Author | Date |
|---|---|---|
| ae93565 | jens-daniel-mueller | 2021-09-29 |
ggsave(plot = coverage_map,
path = "output/publication",
filename = "coverage_map.png",
height = 2,
width = 8)
sessionInfo()R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: openSUSE Leap 15.2
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] ggforce_0.3.3 metR_0.9.0 scico_1.2.0 patchwork_1.1.1
[5] collapse_1.5.0 forcats_0.5.0 stringr_1.4.0 dplyr_1.0.5
[9] purrr_0.3.4 readr_1.4.0 tidyr_1.1.3 tibble_3.1.3
[13] ggplot2_3.3.5 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] httr_1.4.2 sass_0.4.0 viridisLite_0.3.0
[4] jsonlite_1.7.1 modelr_0.1.8 bslib_0.2.5.1
[7] assertthat_0.2.1 highr_0.8 blob_1.2.1
[10] cellranger_1.1.0 yaml_2.2.1 pillar_1.6.2
[13] backports_1.1.10 lattice_0.20-41 glue_1.4.2
[16] RcppEigen_0.3.3.7.0 digest_0.6.27 RColorBrewer_1.1-2
[19] promises_1.1.1 polyclip_1.10-0 checkmate_2.0.0
[22] rvest_0.3.6 colorspace_2.0-2 htmltools_0.5.1.1
[25] httpuv_1.5.4 Matrix_1.2-18 pkgconfig_2.0.3
[28] broom_0.7.9 haven_2.3.1 scales_1.1.1
[31] tweenr_1.0.2 whisker_0.4 later_1.2.0
[34] git2r_0.27.1 farver_2.0.3 generics_0.1.0
[37] ellipsis_0.3.2 withr_2.3.0 cli_3.0.1
[40] magrittr_1.5 crayon_1.3.4 readxl_1.3.1
[43] evaluate_0.14 fs_1.5.0 fansi_0.4.1
[46] MASS_7.3-53 xml2_1.3.2 RcppArmadillo_0.10.1.2.0
[49] tools_4.0.3 data.table_1.14.0 hms_0.5.3
[52] lifecycle_1.0.0 munsell_0.5.0 reprex_0.3.0
[55] compiler_4.0.3 jquerylib_0.1.4 rlang_0.4.11
[58] grid_4.0.3 rstudioapi_0.13 labeling_0.4.2
[61] rmarkdown_2.10 gtable_0.3.0 DBI_1.1.0
[64] R6_2.5.0 lubridate_1.7.9 knitr_1.33
[67] utf8_1.1.4 rprojroot_2.0.2 stringi_1.5.3
[70] parallel_4.0.3 Rcpp_1.0.5 vctrs_0.3.8
[73] dbplyr_1.4.4 tidyselect_1.1.0 xfun_0.25