{"Package":"gofigR","Type":"Package","Title":"Client for 'GoFigr.io'","Version":"1.1.0","Authors@R":"c(\nperson(family=\"Pacula\", given=\"Maciej\", email=\"maciej@gofigr.io\", role=c(\"cre\", \"aut\")),\nperson(given=\"Flagstaff Solutions, LLC\", role=c(\"cph\"))\n)","Description":"Integrates with your 'RMarkdown' documents to automatically publish\nfigures to the service. Supports both 'knitr' and interactive\nexecution within 'RStudio'.","License":"MIT + file LICENSE","Encoding":"UTF-8","URL":"https://github.com/GoFigr/gofigR","BugReports":"https://github.com/GoFigr/gofigR/issues","RoxygenNote":"7.3.2","Imports":"httr, jsonlite, knitr, base64enc, readr, magick, qrcode,\ndigest, getPass, scriptName, rstudioapi, rsvg, cowplot,\nggplotify, shiny, shinyjs","Suggests":"ggplot2, gplots, rmarkdown, withr, purrr, dtt, devtools,\nuuid, rvest, stringr, torch, torchvision, testthat (>= 3.0.0)","Config/testthat/edition":"3","NeedsCompilation":"no","Packaged":"2025-07-17 20:15:22 UTC; ubuntu","Author":"Maciej Pacula [cre, aut],\nFlagstaff Solutions, LLC [cph]","Maintainer":"Maciej Pacula ","Repository":"CRAN","Date/Publication":"2025-07-18 13:20:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/gofigR_1.1.0.tar.gz","jsonAuthors":[{"name":"Maciej Pacula","email":"maciej@gofigr.io","maintainer":true},{"name":"Flagstaff Solutions, LLC ","email":null,"maintainer":false}],"readme":"# gofigR\n\ngofigR is the R client for , a zero-effort reproducibility engine. It works with any R library which outputs to R graphics devices.\n\n## Compatibility\n\ngofigR integrates with R markdown, both in `knitr` and in interactive sessions in RStudio. GoFigr also works in scripts. We tested with R 4.3.2 but any reasonably recent version should work.\n\n## Installation\n\n``` r\nlibrary(devtools)\ndevtools::install_github(\"gofigr/gofigR\")\n```\n\n## Configuration\n\nOn the R prompt, simply load the `gofigR` package and call `gfconfig()`. You only need to do this once.\n\nIf you don't have an account, you can register at .\n\n``` \n> library(gofigR)\nAttaching package: ‘gofigR’\n\n> gfconfig()\n-------------------------------------------------------------------\n\nWelcome to GoFigr! This wizard will help you get up and running.\n\n-------------------------------------------------------------------\n\n\nUsername: publicdemo\nTesting connection...\n\n => Success\n\nAPI key (leave blank to generate a new one): \nKey name (e.g. Alyssa's laptop): my API key\nFetching workspaces...\n\n1. Scratchpad - e5249bed-40f0-4336-9bd3-fef30d3ed10d\n\nPlease select a default workspace (1-1): 1\n\nConfiguration saved to /Users/maciej/.gofigr. Happy analysis!\n```\n\n## Usage\n\nTo enable GoFigr, simply call `enable` in your setup chunk. You can also optionally specify an `analysis_name` (it will be created automatically if it doesn't exist).\n\n```` {.R .rmd}\n```{r setup, include=FALSE}\nlibrary(gofigR)\ngofigR::enable()\n```\n````\n\n## Publishing plots\n\nTo publish plots, simply call `publish`:\n\n``` r\nhm1 <- Heatmap(matrix(rnorm(100), nrow=10, ncol=10))\n\npublish(hm1, \"Heatmaps are cool!\") # second argument is the figure name\n\n# This works, too\nhm1 %>% publish(\"Heatmaps are cool!\")\n```\n\n## Capturing base graphics\n\nTo capture output from base R plotting, call `publish` with a plotting expression:\n\n``` r\ngofigR::publish({\n base::plot(pressure, main=\"Pressure vs temperature\")\n text(200, 50, \"Note the non-linear relationship\")\n}, data=pressure, figure_name=\"Pressure vs temperature\")\n\ngofigR::publish({\n # The mtcars dataset:\n data <- as.matrix(mtcars)\n\n coul <- colorRampPalette(brewer.pal(8, \"PiYG\"))(25)\n heatmap(data, scale=\"column\", col = coul, main=\"Visualizing mtcars\")\n}, data=mtcars, figure_name=\"Cars\")\n```\n\nNote the optional `data` argument following the expression. It specifies the data which you want to associate with the figure -- it will show up under \"files\" (as `.RDS`) once published.\n\n## Shiny\n\nYou can replace `plotOutput + renderPlot` with `gfPlot + gfPlotServer` and give your users the ability to publish interactive plots to GoFigr. For example:\n\n``` r\nlibrary(shiny)\nlibrary(gofigR)\n\ngofigR::enable()\n\n# Define UI for application that draws a histogram\nui <- fluidPage(\n # Application title\n titlePanel(\"Old Faithful Geyser Data\"),\n\n # Sidebar with a slider input for number of bins\n sidebarLayout(\n sidebarPanel(\n sliderInput(\"bins\",\n \"Number of bins:\",\n min = 1,\n max = 50,\n value = 30)\n ),\n\n # Show a plot of the generated distribution\n mainPanel(\n gfPlot(\"distPlot\"),\n )\n )\n)\n\n# Define server logic required to draw a histogram\nserver <- function(input, output) {\n\n gfPlotServer(\"distPlot\", {\n # generate bins based on input$bins from ui.R\n x <- faithful[, 2]\n bins <- seq(min(x), max(x), length.out = input$bins + 1)\n\n # draw the histogram with the specified number of bins\n hist(x, breaks = bins, col = 'darkgray', border = 'white',\n xlab = 'Waiting time to next eruption (in mins)',\n main = 'Histogram of waiting times')\n }, input, figure_name=\"Old faithful waiting times\")\n}\n\n# Run the application\nshinyApp(ui = ui, server = server)\n```\n\nNote that we pass `input` to `gfPlotServer`. This will capture your current Shiny inputs – they will become available under the \"Metadata\" tab in GoFigr.\n\n## Interactive use\n\nWe support `knitr` as well as interactive sessions in `RStudio`.","jobInfo":{"package":"gofigR","version":"1.1.0","parsingStatus":"success","parserVersion":2,"parsedAt":"2025-07-18T15:30:34+0000"}}

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