knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" ) options(knitr.kable.NA = "")
r badger::badge_devel("special-uor/smpds", "yellow")
r badger::badge_github_actions("special-uor/smpds")
r badger::badge_cran_release("smpds", "black")
r badger::badge_doi("10.5281/zenodo.6598832", "blue")
r badger::badge_codecov(token = 'UOX3PKOPVT')
The goal of smpds
is to provide access to the SPECIAL Modern Pollen Data Set for Climate Reconstructions (SMPDS).
You can(not) install the released version of SMPDS from CRAN with:
install.packages("smpds")
And the development version from GitHub with:
# install.packages("remotes") remotes::install_github("special-uor/smpds")
data("climate", package = "smpds") data("entity", package = "smpds") data("pollen_count", package = "smpds") data("taxon_name", package = "smpds")
The function smpds::snapshot
takes few different parameters and based on
the first one, x
, it returns a variety of snapshots.
This function returns a list with 3 components:
entity
: data frame (tibble
object) with the metadata associated to the entities.climate
: data frame (tibble
object) with the climate and vegetation reconstructions. This one can be linked to the entity
table using the column called ID_SAMPLE
.pollen_count
: list of data frames (tibble
objects) containing the pollen counts for 3 levels of "amalgamation":clean
intermediate
amalgamated
All these data frames can be linked to the entity
table using the column called ID_SAMPLE
.
:warning: NOTE: the output is returned "invisibly", so you should assign the output of the function to a variable.
output <- smpds::snapshot(...) output$entity output$climate output$pollen_count$clean output$pollen_count$intermediate output$pollen_count$intermediate
entity_name
smpds::snapshot("juodonys_core")
site_name
smpds::snapshot("Petresiunai", use_site_name = TRUE)
ID_ENTITY
smpds::snapshot(2)
ID_SITE
smpds::snapshot(3, use_id_site = TRUE)
smpds::snapshot(1:10)
This will run very slow, so if only few entities are required, it would be better to indicate which, based on the previous examples.
out <- smpds::snapshot()
The function smpds::write_csvs
takes to parameters:
.data
: a list of class snapshot
, this one can be generated using the function smpds::snapshot
(see previous section).prefix
: a prefix name to be included in each individual files, this prefix can include a relative or absolute path to a directory in the local machine.`%>%` <- smpds::`%>%` smpds::snapshot("juodonys_core") %>% smpds::write_csvs(prefix = "juodonys_core")
paths <- list.files(pattern = "juodonys_core", full.names = TRUE) tree <- data.tree::as.Node(data.frame(pathString = paths)) data.tree::SetGraphStyle(tree, rankdir = "TB") data.tree::SetNodeStyle(tree, style = "filled,rounded", shape = "box") print(tree)
`%>%` <- smpds::`%>%` smpds::snapshot("juodonys_core") %>% smpds::write_csvs(prefix = "/special.uor/epd/juodonys_core")
paths <- list.files(pattern = "juodonys_core", full.names = TRUE) %>% stringr::str_replace_all("./", "/special.uor/epd/") tree <- data.tree::as.Node(data.frame(pathString = paths)) data.tree::SetGraphStyle(tree, rankdir = "TB") data.tree::SetNodeStyle(tree, style = "filled,rounded", shape = "box") print(tree)
paths <- list.files(pattern = "juodonys_core", full.names = TRUE) unlink(paths)
smpds::SMPDSv2 %>% smpds::plot_biome()
gdd0
)smpds::SMPDSv2 %>% smpds::plot_gdd()
mtco
)smpds::SMPDSv2 %>% smpds::plot_mtco()
mi
)smpds::SMPDSv2 %>% smpds::plot_mi()
Please note that the SMPDS project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
This package is a companion to the following dataset:
Villegas-Diaz, R., Harrison, S. P., 2022. The SPECIAL Modern Pollen Data Set for Climate Reconstructions, version 2 (SMPDSv2). University of Reading. Dataset. https://doi.org/10.17864/1947.000389
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