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Knit directory: bgc_argo_r_argodata/
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Using the argodata package to load in bgc argo data from the server and store it in a dataframe with the corresponding metadata
library(tidyverse)── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──✓ ggplot2 3.3.5 ✓ purrr 0.3.4
✓ tibble 3.1.3 ✓ dplyr 1.0.5
✓ tidyr 1.1.3 ✓ stringr 1.4.0
✓ readr 1.4.0 ✓ forcats 0.5.0── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag() masks stats::lag()# remotes::install_github("ArgoCanada/argodata")
library(argodata)
library(ggplot2)
library(lubridate)
Attaching package: 'lubridate'The following objects are masked from 'package:base':
date, intersect, setdiff, unionSet the cache directory for the argo data. The cache directory stores previously downlaoded files to access them more quickly. Cached files are used indefinitely by default because of the considerable time it takes to refresh them. If you use a persistent cache, you should update the index files regularly by using argo_update_global() (data files are also updated occasionally; update these using argo_update_data())
argo_set_cache_dir('/nfs/kryo/work/updata/bgc_argo_r_argodata')
argo_update_global(max_global_cache_age = Inf) # argument: age of the cached files to update in hours (Inf means always use the cached file, and -Inf means always download from the server)
argo_update_data(max_data_cache_age = Inf)Load in the synthetic (core and bgc merged) index files (uses the data stored on the ifremer server by default), keeping only delayed-mode data (quality checked by PIs)
bgc_subset = argo_global_synthetic_prof() %>%
argo_filter_data_mode(data_mode = 'delayed') %>%
argo_filter_date(date_min = '2013-01-01',
date_max = '2015-12-31')Loading argo_global_synthetic_prof()# check the dates
# max(bgc_subset$date, na.rm = TRUE)
# min(bgc_subset$date, na.rm = TRUE)Read in the adjusted bgc and core variables corresponding to the index files downloaded above, with their quality control flags. (can take a while)
bgc_data = argo_prof_levels(bgc_subset,
vars = c('PRES_ADJUSTED','PRES_ADJUSTED_QC',
'PSAL_ADJUSTED', 'PSAL_ADJUSTED_QC',
'TEMP_ADJUSTED','TEMP_ADJUSTED_QC',
'DOXY_ADJUSTED', 'DOXY_ADJUSTED_QC',
'NITRATE_ADJUSTED', 'NITRATE_ADJUSTED_QC',
'PH_IN_SITU_TOTAL_ADJUSTED', 'PH_IN_SITU_TOTAL_ADJUSTED_QC'), quiet = TRUE)
# read in the profiles (takes a while)The data is read in from the cached files stored in the path specified in set_argo_cache_dir() (in this case, ‘/nfs/kryo/work/updata/bgc_argo_r_argodata’). To download data directly from the files stored on the ifremer server, set max_global_cache_age and max_data_cache_age to -Inf, which will force a new download each time.
Read in the corresponding metadata:
bgc_metadata = argo_prof_prof(bgc_subset) Extracting from 54117 filesJoin the metadata and data together into one dataset
full_data = left_join(bgc_data, bgc_metadata, by = c('file', 'n_prof'))
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] lubridate_1.7.9 argodata_0.0.0.9000 forcats_0.5.0
[4] stringr_1.4.0 dplyr_1.0.5 purrr_0.3.4
[7] readr_1.4.0 tidyr_1.1.3 tibble_3.1.3
[10] ggplot2_3.3.5 tidyverse_1.3.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.7 prettyunits_1.1.1 assertthat_0.2.1 rprojroot_2.0.2
[5] digest_0.6.27 utf8_1.2.2 R6_2.5.1 cellranger_1.1.0
[9] backports_1.1.10 reprex_0.3.0 evaluate_0.14 httr_1.4.2
[13] pillar_1.6.2 progress_1.2.2 rlang_0.4.11 readxl_1.3.1
[17] rstudioapi_0.13 whisker_0.4 jquerylib_0.1.4 blob_1.2.1
[21] rmarkdown_2.10 bit_4.0.4 munsell_0.5.0 broom_0.7.9
[25] compiler_4.0.3 httpuv_1.6.2 modelr_0.1.8 xfun_0.25
[29] pkgconfig_2.0.3 htmltools_0.5.1.1 tidyselect_1.1.0 fansi_0.5.0
[33] tzdb_0.1.2 crayon_1.4.1 dbplyr_1.4.4 withr_2.4.2
[37] later_1.3.0 grid_4.0.3 jsonlite_1.7.2 gtable_0.3.0
[41] lifecycle_1.0.0 DBI_1.1.1 git2r_0.27.1 magrittr_2.0.1
[45] scales_1.1.1 vroom_1.5.5 cli_3.0.1 stringi_1.5.3
[49] fs_1.5.0 promises_1.2.0.1 xml2_1.3.2 bslib_0.2.5.1
[53] ellipsis_0.3.2 generics_0.1.0 vctrs_0.3.8 tools_4.0.3
[57] bit64_4.0.5 glue_1.4.2 RNetCDF_2.4-2 hms_0.5.3
[61] parallel_4.0.3 yaml_2.2.1 colorspace_2.0-2 rvest_0.3.6
[65] knitr_1.33 haven_2.3.1 sass_0.4.0