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# The 'handwriterApp' R package performs writership analysis of handwritten
# documents. Copyright (C) 2024 Iowa State University of Science and Technology
# on behalf of its Center for Statistics and Applications in Forensic Evidence
#
# This program is free software: you can redistribute it and/or modify it under
# the terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along with
# this program. If not, see <https://www.gnu.org/licenses/>.
caseQDSidebarUI <- function(id) {
ns <- shiny::NS(id)
shiny::tagList(
shiny::fluidRow(shiny::column(5, set_indices(id = ns("qd_writer_start_char"), label = "Start location")),
shiny::column(5, set_indices(id = ns("qd_writer_end_char"), label = "End location"))),
shiny::helpText(id="qd_docID_help", "Where are the document numbers located in the file names?"),
shiny::fluidRow(shiny::column(5, set_indices(id = ns("qd_doc_start_char"), label = "Start location")),
shiny::column(5, set_indices(id = ns("qd_doc_end_char"), label = "End location"))),
shiny::helpText("Select the questioned document."),
shiny::fileInput(ns("qd_upload"), "", accept = ".png", multiple=TRUE)
)
}
caseQDBodyUI <- function(id){
ns <- shiny::NS(id)
shiny::tagList(
shinycssloaders::withSpinner(shiny::uiOutput(ns("qd_results"))),
selectImageUI(ns("qd"))
)
}
caseQDServer <- function(id, global) {
shiny::moduleServer(
id,
function(input, output, session) {
shiny::observeEvent(input$qd_upload, {
global$qd_paths <- input$qd_upload$datapath # filepaths for temp docs not filepaths on disk
global$qd_names <- input$qd_upload$name
# copy qd to main directory
create_dir(file.path(global$main_dir, "data", "questioned_docs"))
copy_docs_to_project(main_dir = global$main_dir, paths = global$qd_paths, names = global$qd_names, type = "questioned")
# get filepaths and names from main_dir > data > questioned_docs folder
global$qd_paths <- list_docs(global$main_dir, type = "questioned", filepaths = TRUE)
# get a named vector where the names are the filenames and the values
# are the full filepaths to use with the selectInput so the user sees only
# sees the filenames in the drop-down menu but behind the scenes the app
# gets the filepaths
global$qd_names <- list_names_in_named_vector(global$qd_paths)
# analyze
global$analysis <- handwriter::analyze_questioned_documents(main_dir = global$main_dir,
questioned_docs = file.path(global$main_dir, "data", "questioned_docs"),
model = global$model,
num_cores = 1,
writer_indices = c(input$qd_writer_start_char, input$qd_writer_end_char),
doc_indices = c(input$qd_doc_start_char, input$qd_doc_end_char))
})
# Display analysis ----
# NOTE: this is UI that lives inside server so that the heading is hidden
# if analysis doesn't exist
output$qd_analysis <- shiny::renderTable({
shiny::req(global$analysis)
make_posteriors_df(global$analysis)
})
output$qd_results <- shiny::renderUI({
ns <- session$ns
shiny::req(global$analysis)
shiny::tagList(
shiny::h1("EVALUATION RESULTS"),
shiny::HTML("<p>The table shows the posterior probability of writership for each questioned document and each known writer. Each
column corresponds to a questioned document and each row corresponds to a known writer. The posterior probability of
writership in each column sums to 100%.</p>"),
shiny::tableOutput(ns("qd_analysis")),
shiny::br()
)
})
selectImageServer("qd", global, "questioned")
}
)
}
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