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coatlesscoatless
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Roll app
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‎.Rbuildignore‎

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^.*\.Rproj$
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^\.Rproj\.user$

‎.github/workflows/convert-and-deploy-app-to-shinylive.yml‎

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on:
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push:
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branches: [main, master]
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release:
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types: [published]
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workflow_dispatch: {}
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name: demo-r-shinylive-app
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jobs:
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demo-r-shinylive-app:
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runs-on: ubuntu-latest
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# Only restrict concurrency for non-PR jobs
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concurrency:
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group: r-shinylive-website-${{ github.event_name != 'pull_request' || github.run_id }}
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# Describe the permissions for obtain repository contents and
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# deploying a GitHub pages website for the repository
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permissions:
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contents: read
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pages: write
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id-token: write
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steps:
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# Obtain the contents of the repository
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- name: "Check out repository"
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uses: actions/checkout@v4
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# Install R on the GitHub Actions worker
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- name: "Setup R"
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uses: r-lib/actions/setup-r@v2
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# Install and pin the shinylive R package dependency
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- name: "Setup R dependency for Shinylive App export"
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uses: r-lib/actions/setup-r-dependencies@v2
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with:
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packages:
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cran::shinylive,
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local::.
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# Export the current working directory as the shiny app
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# using the pinned version of the Shinylive R package
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- name: Create Shinylive App from working directory files
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shell: Rscript {0}
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run: |
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shinylive::export(".", "_site")
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# Upload a tar file that will work with GitHub Pages
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# Make sure to set a retention day to avoid running into a cap
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# This artifact shouldn't be required after deployment onto pages was a success.
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- name: Upload Pages artifact
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uses: actions/upload-pages-artifact@v2
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with:
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retention-days: 1
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# Use an Action deploy to push the artifact onto GitHub Pages
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# This requires the `Action` tab being structured to allow for deployment
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# instead of using `docs/` or the `gh-pages` branch of the repository
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- name: Deploy to GitHub Pages
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id: deployment
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uses: actions/deploy-pages@v2

‎.gitignore‎

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.Rproj.user
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.Rhistory
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.RData
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.Ruserdata
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.DS_Store

‎DESCRIPTION‎

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Package: numericaloptimization
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Title: Numerical Optimization Explorer
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Version: 0.0.0.9000
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Authors@R:
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person("James Joseph", "Balamuta", email = "[email protected]",
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role = c("aut", "cre", "cph"),
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comment = c(ORCID = "0000-0003-2826-8458"))
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Description: A Shiny application for exploring numerical optimization techniques.
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URL: https://github.com/coatless-shiny/numerical-optimization, https://shiny.thecoatlessprofessor.com/numerical-optimization/
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BugReports: https://github.com/coatless-shiny/numerical-optimization/issues
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License: AGPL (>= 3)
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Encoding: UTF-8
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Roxygen: list(markdown = TRUE)
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RoxygenNote: 7.3.2
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Imports:
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shiny,
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plotly,
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bslib,
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bsicons
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Depends:
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R (>= 4.3.0)
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LazyData: true

‎R/modules/landscape-analysis.R‎

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# UI for the landscape analysis module ----
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landscapeAnalysisUI <- function(id) {
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ns <- NS(id)
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## Sidebar layout ----
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layout_sidebar(
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sidebar = sidebar(
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title = "Analysis Settings",
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### Function Selection ----
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selectInput(ns("func"), "Test Function", choices = TEST_FUNCTIONS),
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### Analysis Type ----
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radioButtons(
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ns("analysis_type"),
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"Analysis Type",
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choices = c(
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"Contour Plot" = "contour",
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"3D Surface" = "surface",
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"Gradient Field" = "gradient"
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)
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),
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### Gradient Field specific settings ----
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conditionalPanel(
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condition = sprintf("input['%s'] == 'gradient'", ns("analysis_type")),
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checkboxInput(ns("show_contours"), "Show Contour Lines", value = TRUE)
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),
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### Resolution Settings ----
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sliderInput(
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ns("grid_size"),
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"Grid Resolution",
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min = GRID_RESOLUTION_RANGE[1],
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max = GRID_RESOLUTION_RANGE[2],
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value = DEFAULT_GRID_SIZE
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),
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### Run Button ----
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actionButton(
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ns("analyze"),
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"Generate Analysis",
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class = "btn-lg btn-primary w-100",
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icon = icon("calculator")
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)
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),
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## Main content ----
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layout_column_wrap(
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width = 1,
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### Plot card ----
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card(
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full_screen = TRUE,
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card_header(
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class = "bg-primary",
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span(class = "text-white", "Function Landscape")
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),
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card_body(
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height = "600px",
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conditionalPanel(
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condition = sprintf("!output['%s']", ns("hasAnalysis")),
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div(
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class = "text-center text-muted p-4",
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"Click 'Generate Analysis' to visualize the function landscape"
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)
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),
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plotlyOutput(ns("landscapePlot"), height = "100%")
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)
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),
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### Function information section ----
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card(
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full_screen = TRUE,
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card_header(
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class = "bg-primary",
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span(class = "text-white", "Function Information")
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),
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card_body(
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# Formula section
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div(
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class = "mb-4",
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h4("Mathematical Formula", class = "mb-3"),
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div(
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class = "p-3 rounded",
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style = "min-height: 100px; overflow-x: auto;",
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withMathJax(),
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uiOutput(ns("formulaDisplay"))
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)
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),
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#### Function Properties section ----
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div(
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class = "mb-4",
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h4("Properties", class = "mb-3"),
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div(
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class = "row g-3",
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div(
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class = "col-md-4",
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div(
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class = "p-3 border rounded h-100",
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div(class = "d-flex align-items-center mb-2",
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bsicons::bs_icon("arrows-angle-expand", class = "me-2"),
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span("Domain", class = "fw-bold")
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),
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textOutput(ns("domainValue"))
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)
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),
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div(
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class = "col-md-4",
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div(
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class = "p-3 border rounded h-100",
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div(class = "d-flex align-items-center mb-2",
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bsicons::bs_icon("bullseye", class = "me-2"),
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span("Global Minimum", class = "fw-bold")
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),
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textOutput(ns("minimumValue"))
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)
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),
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div(
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class = "col-md-4",
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div(
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class = "p-3 border rounded h-100",
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div(class = "d-flex align-items-center mb-2",
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bsicons::bs_icon("geo-alt", class = "me-2"),
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span("Minimum Location", class = "fw-bold")
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),
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textOutput(ns("minimumLocation"))
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)
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)
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)
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)
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)
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)
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)
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)
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}
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# Server logic for the landscape analysis module ----
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landscapeAnalysisServer <- function(id) {
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moduleServer(id, function(input, output, session) {
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# Store current function info in a reactive
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current_function <- reactive({ get_function_info(input$func) })
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# Reactive value to track if analysis exists
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has_analysis <- reactiveVal(FALSE)
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# Expose has_analysis to UI
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output$hasAnalysis <- reactive({
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has_analysis()
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})
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outputOptions(output, "hasAnalysis", suspendWhenHidden = FALSE)
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# Render the LaTeX formula
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output$formulaDisplay <- renderUI({
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req(current_function())
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withMathJax(
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sprintf(
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"$$%s$$",
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current_function()$latex %||% "\\text{Formula not available}"
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)
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)
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})
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# Render domain value
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output$domainValue <- renderText({
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req(current_function())
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func <- current_function()
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sprintf("[%g, %g]", func$domain[1], func$domain[2])
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})
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# Render minimum value
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output$minimumValue <- renderText({
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req(current_function())
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sprintf("%g", current_function()$minimum)
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})
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# Render minimum location
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output$minimumLocation <- renderText({
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req(current_function())
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func <- current_function()
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if(length(func$minimum_at) <= 6) {
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sprintf("(%s)", paste(sprintf("%g", func$minimum_at), collapse = ", "))
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} else {
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"x* = 0 (all dims)"
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}
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})
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# Render function description
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output$functionDescription <- renderText({
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req(current_function())
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current_function()$description
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})
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# Clear plot and reset has_analysis when function or analysis type changes
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observeEvent(c(input$func, input$analysis_type), {
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has_analysis(FALSE)
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output$landscapePlot <- renderPlotly({
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plot_ly() %>%
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layout(
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xaxis = list(visible = FALSE),
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yaxis = list(visible = FALSE),
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paper_bgcolor = "rgba(0,0,0,0)",
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plot_bgcolor = "rgba(0,0,0,0)"
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)
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})
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})
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# Generate landscape plot only when analyze button is clicked
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observeEvent(input$analyze, {
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req(input$analysis_type, current_function())
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withProgress(message = 'Generating analysis', value = 0, {
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output$landscapePlot <- renderPlotly({
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plot <- create_landscape_plot(
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current_function(),
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input$analysis_type,
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input$grid_size,
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input$show_contours
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)
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has_analysis(TRUE)
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plot
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})
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})
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})
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})
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}

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