diff --git a/DESCRIPTION b/DESCRIPTION index 968f1494..2cec9a44 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: crestr Title: A Probabilistic Approach to Reconstruct Past Climates Using Palaeoecological Datasets -Version: 1.3.1.9000 +Version: 1.4.0 Authors@R: person(given = "Manuel", family = "Chevalier", diff --git a/NAMESPACE b/NAMESPACE index 70148191..171e119e 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -53,6 +53,7 @@ export(getTaxaTypeFromTaxID) export(getTaxonID) export(getTaxonomy) export(get_taxa_type) +export(identifyDatabase) export(includeTaxa) export(is.crestObj) export(isColourStr) diff --git a/NEWS.md b/NEWS.md index 115ed5ee..2320b9e5 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,9 +1,11 @@ -# crestr 1.3.1.9000 +# crestr 1.4.0 * Improving compatibility with new calibration database - * getResol() - * f_locid() + * `getResol()` + * `f_locid()` + * `identifyDatabase()` * Better factorization of the code + * Adding new references to `cite_crest()` * Fixing issues with `crest.set_modern_data()` * Ok to pass input data in tibble format. * Logging of taxa assignment is fixed. diff --git a/R/cite_data.R b/R/cite_data.R index 77f04409..cafe3492 100644 --- a/R/cite_data.R +++ b/R/cite_data.R @@ -47,43 +47,105 @@ cite_crest <- function(x, verbose=TRUE) { cite_distrib_data <- function(x, verbose=TRUE) { if(base::missing(x)) x - if (x$parameters$taxaType == 1) { + db <- identifyDatabase(x$misc$dbname) + + if(db == 'private-database') { + ## References to cite in case of a private dataset: None + tocite <- c() + if (verbose) cat('You did not use the gbif4crest dataset. No distribution data citations are required.\n') + + } else if (db == 'exampleDB') { + ## References to cite when using the example dataset: None tocite <- c() - list_of_classes <- unique(stats::na.omit(x$inputs$pse[, 'Class_name'])) - citations = list() - citations[['Pinopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Pinopsida occurrence data. https://doi.org/10.15468/dl.x2r7pa.' - citations[['Cycadopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Cycadopsida occurrence data. https://doi.org/10.15468/dl.sfjzxu.' - citations[['Gnetopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Gnetopsida occurrence data. https://doi.org/10.15468/dl.h2kjnc.' - citations[['Gingkoopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Gingkoopsida occurrence data. https://doi.org/10.15468/dl.da9wz8.' - citations[['Lycopodiopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Lycopodiopsida occurrence data. https://doi.org/10.15468/dl.ydhyhz.' - citations[['Anthocerotopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Anthocerotopsida occurrence data. https://doi.org/10.15468/dl.t9zenf.' - citations[['Liliopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Liliopsida occurrence data. https://doi.org/10.15468/dl.axv3yd.' - citations[['Magnoliopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Magnoliopsida occurrence data. https://doi.org/10.15468/dl.ra49dt.' - citations[['Polypodiopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Polypodiopsida occurrence data. https://doi.org/10.15468/dl.87tbp6.' - if (verbose) cat('Please cite the following dataset(s):\n') - for (class in list_of_classes) { - if (verbose) cat(' --> ', citations[[class]], '\n') - tocite <- c(tocite, citations[[class]]) + if (verbose) cat('You did not use the gbif4crest dataset. No distribution data citations are required.\n') + + } else if (db == "gbif4crest_03") { + ## References to cite when using the gbif4crest_03 database + if (x$parameters$taxaType == 1) { + tocite <- c() + list_of_refs <- matrix(c( + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.68HQXG.', 1008772.0, 1045883.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.7BVEJK.', 1045886.0, 1073577.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.MPFC47.', 1073578.0, 1089246.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.NUQ5TN.', 1089248.0, 1116099.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.Q8ZUHH.', 1116101.0, 1145540.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.QWCS68.', 1145541.0, 1184082.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.UK2XV6.', 1184083.0, 1202306.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.ZGMNQ9.', 1000002.0, 1211608.0), + c('The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.Y9KPWC.', 1000065.0, 1008427.0) + ), byrow=TRUE, ncol=3)[9:1, ] + + list_of_ids <- unique(unlist(lapply(x$modelling$distributions, function(d) {if(is.na(d)[1]){return(-1)}else{return(unique(d[,1]))}}))) + + f <- function(ids, refs) { + ids <- ids>=as.numeric(refs[2]) & ids<=as.numeric(refs[3]) + if(sum(ids) > 0) return(TRUE) + return(FALSE) + } + + for(i in 1:nrow(list_of_refs)) { + if(f(list_of_ids, list_of_refs[i, ])) { + tocite <- c(tocite, list_of_refs[i, 1]) + } + } + } else if (x$parameters$taxaType == 2) { + tocite <- c() + if (verbose) cat('Please cite the following dataset: ', tocite, '\n') + } else if (x$parameters$taxaType == 4) { + tocite <- 'The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.68HQXG.' + if (verbose) cat('Please cite the following dataset: ', tocite, '\n') + } else if (x$parameters$taxaType == 5) { + tocite <- 'The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.68HQXG.' + if (verbose) cat('Please cite the following dataset: ', tocite, '\n') + } else if (x$parameters$taxaType == 3) { + tocite <- c() + if (verbose) cat('Please cite the following dataset: ', tocite, '\n') + } else if (x$parameters$taxaType == 6) { + tocite <- c( + 'The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024. https://doi.org/10.15468/DL.ZGMNQ9.', + 'The Global Biodiversity Information Facility, 2024. Occurrence data downloaded on 25 August 2024.https://doi.org/10.15468/DL.68HQXG.' + ) } - } else if (x$parameters$taxaType == 2) { - tocite <- 'GBIF.org (Date accessed: 24 September 2020) Beetles occurrence data. https://doi.org/10.15468/dl.nteruy.' - if (verbose) cat('Please cite the following dataset: ', tocite, '\n') + if (verbose) cat('Please cite the following dataset(s): ', tocite, '\n') + + } else if (db == "gbif4crest_02") { + ## References to cite when using the gbif4crest_02 database + tocite <- c() + if (x$parameters$taxaType == 1) { + list_of_classes <- unique(stats::na.omit(x$inputs$pse[, 'Class_name'])) + citations = list() + citations[['Pinopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Pinopsida occurrence data. https://doi.org/10.15468/dl.x2r7pa.' + citations[['Cycadopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Cycadopsida occurrence data. https://doi.org/10.15468/dl.sfjzxu.' + citations[['Gnetopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Gnetopsida occurrence data. https://doi.org/10.15468/dl.h2kjnc.' + citations[['Gingkoopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Gingkoopsida occurrence data. https://doi.org/10.15468/dl.da9wz8.' + citations[['Lycopodiopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Lycopodiopsida occurrence data. https://doi.org/10.15468/dl.ydhyhz.' + citations[['Anthocerotopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Anthocerotopsida occurrence data. https://doi.org/10.15468/dl.t9zenf.' + citations[['Liliopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Liliopsida occurrence data. https://doi.org/10.15468/dl.axv3yd.' + citations[['Magnoliopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Magnoliopsida occurrence data. https://doi.org/10.15468/dl.ra49dt.' + citations[['Polypodiopsida']] <- 'GBIF.org (Date accessed: 24 September 2020) Polypodiopsida occurrence data. https://doi.org/10.15468/dl.87tbp6.' + if (verbose) cat('Please cite the following dataset(s):\n') + for (class in list_of_classes) { + if (verbose) cat(' --> ', citations[[class]], '\n') + tocite <- c(tocite, citations[[class]]) + } + } else if (x$parameters$taxaType == 2) { + tocite <- 'GBIF.org (Date accessed: 24 September 2020) Beetles occurrence data. https://doi.org/10.15468/dl.nteruy.' + if (verbose) cat('Please cite the following dataset: ', tocite, '\n') } else if (x$parameters$taxaType == 4) { tocite <- 'GBIF.org (Date accessed: 24 September 2020) Foraminifera occurrence data. https://doi.org/10.15468/dl.692yg6.' if (verbose) cat('Please cite the following dataset: ', tocite, '\n') - } else if (x$parameters$taxaType == 5) { - tocite <- 'GBIF.org (Date accessed: 24 September 2020) Diatoms occurrence data. https://doi.org/10.15468/dl.vfr257.' - if (verbose) cat('Please cite the following dataset: ', tocite, '\n') - } else if (x$parameters$taxaType == 3) { - tocite <- 'GBIF.org (Date accessed: 24 September 2020) Chironomids occurrence data. https://doi.org/10.15468/dl.jv3wsh.' - if (verbose) cat('Please cite the following dataset: ', tocite, '\n') - } else if (x$parameters$taxaType == 6) { - tocite <- 'GBIF.org (Date accessed: 24 September 2020) Rodentia occurrence data. https://doi.org/10.15468/dl.fscw6q.' - if (verbose) cat('Please cite the following dataset: ', tocite, '\n') - } else { - if (verbose) cat('You did not use the gbif4crest dataset. No distribution data citations are required.\n') - tocite <- NULL - } + } else if (x$parameters$taxaType == 5) { + tocite <- 'GBIF.org (Date accessed: 24 September 2020) Diatoms occurrence data. https://doi.org/10.15468/dl.vfr257.' + if (verbose) cat('Please cite the following dataset: ', tocite, '\n') + } else if (x$parameters$taxaType == 3) { + tocite <- 'GBIF.org (Date accessed: 24 September 2020) Chironomids occurrence data. https://doi.org/10.15468/dl.jv3wsh.' + if (verbose) cat('Please cite the following dataset: ', tocite, '\n') + } else if (x$parameters$taxaType == 6) { + tocite <- 'GBIF.org (Date accessed: 24 September 2020) Rodentia occurrence data. https://doi.org/10.15468/dl.fscw6q.' + } + if (verbose) cat('Please cite the following dataset(s): ', tocite, '\n') + } + invisible(tocite) } @@ -103,7 +165,7 @@ cite_climate_data <- function(x, verbose=TRUE) { if(base::missing(x)) x if (x$parameters$taxaType == 0) { - if (verbose) cat('You have not used the provided calibration dataset. No climate reference are required.\n') + if (verbose) cat('You have not used the gbif4crest calibration dataset. No climate reference are required.\n') tocite <- NULL } else { ref1 <- "Fick, S.E. and Hijmans, R.J., 2017, WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37, pp. 4302-4315." diff --git a/R/utils.R b/R/utils.R index 9747b0af..061e6f2a 100644 --- a/R/utils.R +++ b/R/utils.R @@ -493,3 +493,32 @@ getResol <- function(crest) { if(grepl('gbif4crest_02-5m', crest$misc$dbname, fixed = TRUE)) return(1/12) return(1/4) } + + +#' Identify the calibration database used. +#' +#' Identify the calibration database used. +#' +#' @param dbname A functional crestObj or a database name. +#' @return A string uniquely characterising the database used. Possible values +#' are 'privateDB', 'exampleDB', 'gbif4crest_02', and 'gbif4crest_03'. +#' @export +#' @examples +#' identifyDatabase(reconstr) +#' +identifyDatabase <- function(dbname) { + if(is.crestObj(dbname)) dbname <- dbname$misc$dbname + if(dbname == 'private-database') return('privateDB') + if(grepl("exampleDB",dbname, fixed=TRUE)) return('exampleDB') + params <- tryCatch( + { + dbRequest("SELECT * FROM params", dbname=dbname) + }, + error = function(cond) { + # Choose a return value in case of error + NA + } + ) + if(is.na(params)[1]) return('gbif4crest_02') + return('gbif4crest_03') +} diff --git a/README.Rmd b/README.Rmd index bb14e10e..8bb77a78 100644 --- a/README.Rmd +++ b/README.Rmd @@ -13,7 +13,7 @@ knitr::opts_chunk$set( ) ``` -# crestr +# **crestr** An R package to perform probabilistic palaeoclimate reconstructions from palaeoecological datasets [![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/) @@ -28,7 +28,6 @@ knitr::opts_chunk$set( [![R-CMD-check](https://github.com/mchevalier2/crestr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/mchevalier2/crestr/actions/workflows/R-CMD-check.yaml) -# **crestr** An R package to perform probabilistic palaeoclimate reconstructions from palaeoecological datasets `crestr` produces probabilistic reconstructions of past climate change from fossil assemblage data [(Chevalier, 2022)](https://cp.copernicus.org/articles/18/821/2022/). `crestr` works by analysing how certain biological indicators (like plant or animal remains) respond to climate factors, using statistical methods to estimate these relationships. These relationships are mdelled as probability density functions (_PDFs_; see [Chevalier *et al.* (2014)](https://www.doi.org/10.5194/cp-10-2081-2014) and [Chevalier (2019)](https://www.doi.org/10.1016/j.gloplacha.2019.01.016)). The theory underpinning this package is explained in section [_A bit of theory_](https://www.manuelchevalier.com/crestr/articles/theory.html) and is illustrated with an application based on pseudo-data in section [_Get Started_](https://www.manuelchevalier.com/crestr/articles/get-started.html). The different vignettes present different aspects of the structure of the package and the data it contains, along with applications based on real data. diff --git a/README.md b/README.md index ae267317..0259f862 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ -# crestr +# **crestr** An R package to perform probabilistic palaeoclimate reconstructions from palaeoecological datasets @@ -12,8 +12,7 @@ stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https:// [![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://lifecycle.r-lib.org/articles/stages.html) -
-![CRAN/METACRAN](https://img.shields.io/cran/v/crestr) [![GitHub R +
![CRAN/METACRAN](https://img.shields.io/cran/v/crestr) [![GitHub R package version](https://img.shields.io/github/r-package/v/mchevalier2/crestr)](https://img.shields.io/github/r-package/v/mchevalier2/crestr)
![Total @@ -23,34 +22,52 @@ month downloads](https://cranlogs.r-pkg.org/badges/crestr)
[![R-CMD-check](https://github.com/mchevalier2/crestr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/mchevalier2/crestr/actions/workflows/R-CMD-check.yaml) - -# **crestr** An R package to perform probabilistic palaeoclimate reconstructions from palaeoecological datasets - -`crestr` produces probabilistic reconstructions of past climate change from fossil assemblage data [(Chevalier, 2022)](https://cp.copernicus.org/articles/18/821/2022/). `crestr` works by analysing how certain biological indicators (like plant or animal remains) respond to climate factors, using statistical methods to estimate these relationships. These relationships are mdelled as probability density functions (_PDFs_; see [Chevalier *et al.* (2014)](https://www.doi.org/10.5194/cp-10-2081-2014) and [Chevalier (2019)](https://www.doi.org/10.1016/j.gloplacha.2019.01.016)). The theory underpinning this package is explained in section [_A bit of theory_](https://www.manuelchevalier.com/crestr/articles/theory.html) and is illustrated with an application based on pseudo-data in section [_Get Started_](https://www.manuelchevalier.com/crestr/articles/get-started.html). The different vignettes present different aspects of the structure of the package and the data it contains, along with applications based on real data. - - -**Why choose `crestr`?** Unlike traditional methods, crestr uses probabilistic techniques to provide more accurate and flexible climate reconstructions. **Its focus on accessibility means you don’t need to be an expert coder to get meaningful results.** - +`crestr` produces probabilistic reconstructions of past climate change +from fossil assemblage data [(Chevalier, +2022)](https://cp.copernicus.org/articles/18/821/2022/). `crestr` works +by analysing how certain biological indicators (like plant or animal +remains) respond to climate factors, using statistical methods to +estimate these relationships. These relationships are mdelled as +probability density functions (*PDFs*; see [Chevalier *et al.* +(2014)](https://www.doi.org/10.5194/cp-10-2081-2014) and [Chevalier +(2019)](https://www.doi.org/10.1016/j.gloplacha.2019.01.016)). The +theory underpinning this package is explained in section [*A bit of +theory*](https://www.manuelchevalier.com/crestr/articles/theory.html) +and is illustrated with an application based on pseudo-data in section +[*Get +Started*](https://www.manuelchevalier.com/crestr/articles/get-started.html). +The different vignettes present different aspects of the structure of +the package and the data it contains, along with applications based on +real data. + +**Why choose `crestr`?** Unlike traditional methods, crestr uses +probabilistic techniques to provide more accurate and flexible climate +reconstructions. **Its focus on accessibility means you don’t need to be +an expert coder to get meaningful results.**
-> **_NOTE:_** While active development of crestr has concluded, its robust features will continue to provide valuable insights for palaeoclimate research. The available documentation and resources will remain accessible for independent use. In addition, I am committed to maintaining this bug-free. As such, please reach out at if you encounter technical issues. - - +> ***NOTE:*** While active development of crestr has concluded, its +> robust features will continue to provide valuable insights for +> palaeoclimate research. The available documentation and resources will +> remain accessible for independent use. In addition, I am committed to +> maintaining this bug-free. As such, please reach out at +> if you encounter technical issues. ## Installation -Ready to explore the climate history hidden in your data? Install `crestr` now and leverage its robust tools for your research. +Ready to explore the climate history hidden in your data? Install +`crestr` now and leverage its robust tools for your research. -The package is available from [GitHub](https://github.com/mchevalier2/crestr/) and can be installed as follow: +The package is available from +[GitHub](https://github.com/mchevalier2/crestr/) and can be installed as +follow: ``` r if(!require(devtools)) install.packages("devtools") devtools::install_github("mchevalier2/crestr") ``` - - ## How to use `crestr` ### Online documentation @@ -148,6 +165,8 @@ recons <- crest( shape = c("normal", "lognormal"), selectedTaxa = crest_ex_selection, dbname = "crest_example" ) +#> Warning in climate_from_xy(crest$misc$site_info[["long"]], +#> crest$misc$site_info[["lat"]], : No climate associated with these coordinates. #> Warning in crest.get_modern_data(pse = pse, taxaType = taxaType, climate = #> climate, : The classification of one or more taxa into species was not #> successful. Use PSE_log() with the output of this function for details. @@ -227,8 +246,8 @@ names(recons) #> [5] "misc" lapply(recons$reconstructions, names) #> $bio1 -#> [1] "likelihood" "uncertainties" "optima" -#> +#> [1] "likelihood" "uncertainties" "optima" +#> #> $bio12 #> [1] "likelihood" "uncertainties" "optima" ``` diff --git a/_pkgdown.yml b/_pkgdown.yml index 5a7ce7f0..c9ae9e6f 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -42,25 +42,24 @@ navbar: text: Prepare your data href: articles/technicalities.html calibration: - text: Calibration data - href: articles/calibration-data.html + text: Dive into gbif4crest + href: articles/calibration-data-v3.html reference: - text: Reference + text: Take the control href: reference/index.html - community: - text: Community - href: articles/community.html vignettes: - text: Vignettes + text: More menu: - - text: Using the _gbif4crest_ database + - text: Using the gbif4crest database href: articles/databasing-with-crestr.html - text: Understanding warnings href: articles/warnings.html - - text: MD96-2048 Reconstruction - href: articles/limpopo.html + - text: gbif4crest v2 (old release) + href: articles/calibration-data-v3.html + - text: Community + href: articles/community.html news: - text: News + text: Latest changes href: news/index.html github: icon: fab fa-github fa-lg @@ -136,6 +135,7 @@ reference: - '`getDistribTaxa`' - '`getTaxonID`' - '`getTaxonomy`' + - '`identifyDatabase`' - '`testConnection`' - title: "Modelling functions" desc: "Functions used model the data. Not to be used." diff --git a/crestr_1.3.1.9000.pdf b/crestr_1.4.0.pdf similarity index 61% rename from crestr_1.3.1.9000.pdf rename to crestr_1.4.0.pdf index 04ecb6f4..046e8db7 100644 Binary files a/crestr_1.3.1.9000.pdf and b/crestr_1.4.0.pdf differ diff --git a/docs/404.html b/docs/404.html index 14bef9f1..43732efb 100644 --- a/docs/404.html +++ b/docs/404.html @@ -32,7 +32,7 @@ crestr - 1.3.1.9000 + 1.4.0 @@ -54,36 +54,36 @@ Prepare your data
  • - Calibration data + Dive into gbif4crest
  • - Reference -
    • -
  • - Community + Take the control