{"Package":"sapfluxnetr","Title":"Working with 'Sapfluxnet' Project Data","Version":"0.1.5","Authors@R":"c(\nperson(\"Victor\", \"Granda\", email = \"victorgrandagarcia@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-0469-1991\")),\nperson(\"Rafael\", \"Poyatos\", email = \"r.poyatos@creaf.uab.cat\", role = \"aut\", comment = c(ORCID = \"0000-0003-0521-2523\")),\nperson(\"Victor\", \"Flo\", email = \"v.flo@creaf.uab.cat\", role = \"aut\", comment = c(ORCID = \"0000-0003-1908-4577\")),\nperson(\"Jacob\", \"Nelson\", email = \"\", role = 'ctb', comment = c(ORCID = \"0000-0002-4663-2420\")),\nperson(\"Sapfluxnet Core Team\", email = \"sapfluxnet@creaf.uab.cat\", role = 'cph')\n)","Description":"Access, modify, aggregate and plot data from the 'Sapfluxnet' project,\nthe first global database of sap flow measurements.","Depends":"R (>= 3.5.0)","License":"MIT + file LICENSE","Encoding":"UTF-8","LazyData":"true","Imports":"assertthat, dplyr, furrr, ggplot2, glue, lubridate, magrittr,\nmethods, purrr, rlang, stats, stringr, tibble, tidyr","RoxygenNote":"7.3.2","Collate":"'data.R' 'getters.R' 'helpers.R' 'imports.R' 'metrics.R'\n'sfn_data_classes.R' 'sfn_data_generics.R' 'sfn_data_methods.R'\n'sfn_dplyr.R' 'visualizations.R'","Suggests":"future, knitr, remotes, rmarkdown, testthat, xtable","Config/testthat/edition":"3","Config/testthat/parallel":"true","VignetteBuilder":"knitr","URL":"https://github.com/sapfluxnet/sapfluxnetr","BugReports":"https://github.com/sapfluxnet/sapfluxnetr/issues","NeedsCompilation":"no","Packaged":"2025-07-24 07:37:45 UTC; malditobarbudo","Author":"Victor Granda [aut, cre] (ORCID:\n),\nRafael Poyatos [aut] (ORCID: ),\nVictor Flo [aut] (ORCID: ),\nJacob Nelson [ctb] (ORCID: ),\nSapfluxnet Core Team [cph]","Maintainer":"Victor Granda ","Repository":"CRAN","Date/Publication":"2025-07-24 08:00:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/sapfluxnetr_0.1.5.tar.gz","jsonAuthors":[{"name":"Victor Granda","email":"victorgrandagarcia@gmail.com","maintainer":true},{"name":"Rafael Poyatos","email":"r.poyatos@creaf.uab.cat","maintainer":false},{"name":"Victor Flo","email":"v.flo@creaf.uab.cat","maintainer":false},{"name":"Jacob Nelson","email":null,"maintainer":false},{"name":"Sapfluxnet Core Team ","email":"sapfluxnet@creaf.uab.cat","maintainer":false}],"readme":"\n# sapfluxnetr\n\n[![CRAN\nstatus](https://www.r-pkg.org/badges/version/sapfluxnetr)](https://CRAN.R-project.org/package=sapfluxnetr)\n[![CRAN RStudio mirror\ndownloads](https://cranlogs.r-pkg.org/badges/grand-total/sapfluxnetr?color=blue)](https://r-pkg.org/pkg/sapfluxnetr)\n[![R build\nstatus](https://github.com/sapfluxnet/sapfluxnetr/workflows/R-CMD-check/badge.svg)](https://github.com/sapfluxnet/sapfluxnetr/actions)\n\n`sapfluxnetr` provides tools for a tidy data analysis for the first\nglobal database of sap flow measurements\n\n## Examples\n\nYou can work with individual sites:\n\n``` r\n# load packages\nlibrary(sapfluxnetr)\nlibrary(ggplot2)\n\n# ARG_MAZ example site data\ndata('ARG_MAZ', package = 'sapfluxnetr')\ndata('sfn_metadata_ex', package = 'sapfluxnetr')\n\n# plot site sapflow measurements versus vpd\nsfn_plot(ARG_MAZ, formula_env = ~ vpd)\n```\n\n

\n\n``` r\n\n# daily sapflow and environmental metrics\narg_maz_metrics <- daily_metrics(\n ARG_MAZ, tidy = TRUE, metadata = sfn_metadata_ex\n)\n#> [1] \"Crunching data for ARG_MAZ. In large datasets this could take a while\"\n#> [1] \"General data for ARG_MAZ\"\n\n# plot daily aggregations\nggplot(arg_maz_metrics, aes(x = vpd_q_95, y = sapflow_q_95, colour = pl_code)) +\n geom_point()\n```\n\n

\n\nYou can work with multiple sites also:\n\n``` r\n# ARG_TRE and AUS_CAN_ST2_MIX example sites\ndata('ARG_TRE', package = 'sapfluxnetr')\ndata('AUS_CAN_ST2_MIX', package = 'sapfluxnetr')\nmulti_sfn <- sfn_data_multi(ARG_TRE, ARG_MAZ, AUS_CAN_ST2_MIX)\n\n# plotting the individual sites. It creates a list of plots\nplots_list <- sfn_plot(multi_sfn, formula_env = ~ vpd)\nplots_list[['AUS_CAN_ST2_MIX']]\n#> Warning: Removed 526066 rows containing missing values or values outside the scale range\n#> (`geom_point()`).\n```\n\n

\n\n``` r\n\n# daily sapflow standard metrics\nmulti_metrics <- daily_metrics(\n multi_sfn, tidy = TRUE, metadata = sfn_metadata_ex\n)\n#> [1] \"Crunching data for ARG_TRE. In large datasets this could take a while\"\n#> [1] \"General data for ARG_TRE\"\n#> [1] \"Crunching data for ARG_MAZ. In large datasets this could take a while\"\n#> [1] \"General data for ARG_MAZ\"\n#> [1] \"Crunching data for AUS_CAN_ST2_MIX. In large datasets this could take a while\"\n#> [1] \"General data for AUS_CAN_ST2_MIX\"\n\n# plot daily aggregations\nggplot(multi_metrics, aes(x = vpd_q_95, y = sapflow_q_95, colour = si_code)) +\n geom_point(alpha = 0.2)\n#> Warning: Removed 10966 rows containing missing values or values outside the scale range\n#> (`geom_point()`).\n```\n\n

\n\n## Installation\n\nYou can install sapfluxnetr from CRAN:\n\n``` r\ninstall.packages('sapfluxnetr')\n```\n\nBe advised, `sapfluxnetr` is in active development and can contain\nundiscovered bugs. If you find something not working as expected fill a\nbug at \n\n## Overview\n\nPlease see\n`vignette('sapfluxnetr-quick-guide', package = 'sapfluxnetr')` for a\ndetailed overview of the package capabilities.","jobInfo":{"package":"sapfluxnetr","version":"0.1.5","parsingStatus":"success","parserVersion":2,"parsedAt":"2025-07-24T09:30:33+0000"}}

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Examples