#' hm_model UI Function
#' @description A shiny Module.
#' @param id,input,output,session Internal parameters for {shiny}.
#' @importFrom shiny NS tagList
#' @noRd
mod_hm_model_ui <- function(id){
ns <- NS(id)
tagList(
fluidRow(
box(width = 12, title = "Selected Folders",
verbatimTextOutput(ns('selected_folders'))
)),
fluidRow(
column(4,
box(width = NULL, title = 'HM-Model/CP Analyzer Controls',
shinyWidgets::radioGroupButtons(
inputId = ns('which_obs'),
label = "Analyze which obs?",
choices = c("All" = "all",
"Single Obs" = "single"),
justified = TRUE,
checkIcon = list(
yes = tags$i(class = "fa fa-check-square",
style = "color: black"),
no = tags$i(class = "fa fa-square-o",
style = "color: black"))
),
#conditionalPanel(conditions = "input.which_obs == 'single
fluidRow(
column(6,
actionButton(inputId = ns("options"),
label = "Options",
icon = icon("cog"),
width = "100%",
style = 'margin-top: 25px;')
),
column(6,
actionButton(inputId = ns("analyze_trap"),
label = "Run Analysis",
icon = icon("running"),
width = "100%",
style = 'margin-top: 25px;')
)
)
)
),
column(8,
box(width = NULL, title = 'Info Table',
actionButton(ns('info_table'), 'Refresh Info'),
DT::DTOutput(ns('table')) %>% shinycssloaders::withSpinner(type = 8, color = "#373B38")
),
) # col close
),
# fluidRow(
# box(width = 12, title = 'Results',
# background = 'black',
tags$style(".small-box.bg-yellow { background-color: #1B9E77 !important; color: #f2f2f2 !important; }"),
fluidRow(
column(4,
valueBoxOutput(ns('observation'), width = NULL)
),
column(4,
valueBoxOutput(ns('n_events'), width = NULL)
),
column(4,
valueBoxOutput(ns('s2n'), width = NULL)
)),
fluidRow(
column(9,
tabBox(width = NULL, title = 'Insights', side = 'right',
tabPanel("MV Plot",
plotOutput(ns('mv_by_state')) %>% shinycssloaders::withSpinner(type = 8, color = "#373B38")
),
tabPanel("Numbers",
plotOutput(ns("numbers"))
)
)
),
column(3,
box(width = NULL, title = 'Review Analysis',
actionButton(ns('view_results'),
'View Results',
width = '100%',
icon = icon('area-chart'),
style = 'margin-bottom: 25px;'),
shinyWidgets::radioGroupButtons(
inputId = ns('quality_control'),
label = "Should analysis be accepted?",
choices = c("No" = FALSE,
"Yes" = TRUE),
justified = TRUE,
selected = FALSE,
checkIcon = list(
yes = tags$i(class = "fa fa-check-square",
style = "color: black"),
no = tags$i(class = "fa fa-square-o",
style = "color: black"))
),
actionButton(ns('save_review'),
'Save Review',
width = '100%',
icon = icon('save'),
style = "margin-top: 25px;")
)
), #col close
),
# fluidRow(
# box(width = 4, title = 'HM-Model Summary',
# verbatimTextOutput(ns('hm_model_summary')) %>% shinycssloaders::withSpinner(type = 8, color = "#373B38")
# ),
# box(width = 8, title = 'Real Time Event Frequency',
# plotOutput(ns('event_freq')) %>% shinycssloaders::withSpinner(type = 8, color = "#373B38")
# )
# ), #rowclose
#
# fluidRow(
# box(width = 12, title = 'HM-Model Data (Running Mean & Variance)', collapsible = T, collapsed = T,
# dygraphs::dygraphOutput(ns('hm_model_dygraph1'), height = "250px") %>% shinycssloaders::withSpinner(type = 8, color = "#373B38"),
# dygraphs::dygraphOutput(ns('hm_model_dygraph2'), height = "250px") %>% shinycssloaders::withSpinner(type = 8, color = "#373B38")
# ),
#
# ),
# # fluidRow(
# # box(width = 12, title = 'Running Mean (HM-Model Data)',
# #
# # ),
#
# #),
fluidRow(
column(12,
box(width = NULL, title = 'Analyzed Data', collapsible = T, collapsed = T,
actionButton(ns("review_options"), "Review Options"),
actionButton(ns("snapshot"), "", icon = icon("camera")),
dygraphs::dygraphOutput(ns('overlay_dygraph'), height = '400px') %>% shinycssloaders::withSpinner(type = 8, color = "#373B38")
)
)
# ) #rowclose
# ) #results box close
)
)#taglist clost
}
#' hm_model Server Function
#' @noRd
#' @param input,output,session,f module parameters
mod_hm_model_server <- function(input, output, session, f){
ns <- session$ns
observeEvent(f$obs$path, {
req(f$obs$path)
o <- fread(file.path(f$obs$path, "options.csv"))
if(is.null(o$channels)){
o$channels <- 1
}
if(o$channels == 1){
hm$use_channel_options <- c("Mean/Var", "Variance")
} else {
hm$use_channel_options <- c("Covariance", "Mean/Var", "Variance")
}
})
hm <- reactiveValues(analyze = 0, use_channels_options = c("Mean/Var", "Variance"))
observeEvent(input$analyze_trap, {
golem::print_dev(input$which_obs)
defend_if_empty(f$date, ui = "Please select a folder", type = 'error')
defend_if_blank(f$date_input, ui = 'Select a date', type = 'error')
if(input$which_obs == 'single'){
defend_if_empty(f$obs_input, ui = 'Select an obs', type = 'error')
defend_if_not_equal(substring(f$obs_input, 1, 3), 'obs', ui = 'Select an obs', type = 'error')
}
showNotification('Analysis will begin shortly...', type = 'message', duration = 2)
hm$analyze <- hm$analyze + 1
})
observeEvent(hm$analyze, ignoreInit = T, {
if(input$which_obs =='single'){
file <- list_files(f$obs$path, pattern = 'trap-data.csv')
trap_data <- purrr::map(file$path, data.table::fread, nrows = 1)
} else {
files <- list_files(f$date$path, pattern = 'trap-data.csv', recursive = T)
trap_data <- purrr::map(files$path, data.table::fread, nrows = 1)
}
opt <- reactiveValuesToList(isolate(a))
withProgress(message = 'Analyzing trap data', value = 0, max = 1, min = 0, {
purrr::walk(trap_data, ~(
trap_data = .x,
f = f,
hz = a$hz,
w_width = a$w_width,
w_slide = a$w_slide,
use_channels = a$use_channels,
em_random_start = a$em_random_start,
front_cp_method = a$front_cp_method,
back_cp_method = a$back_cp_method,
cp_running_var_window = a$cp_running_var_window,
displacement_type = a$displacement_type,
opt = opt,
is_shiny = TRUE)
)
})
shinyWidgets::sendSweetAlert(session = session,
title = "Analysis Complete",
text = "Results saved to 'lasertrapr' folder",
type = "success")
shinyjs::click('info_table')
})
trap_data <- eventReactive(input$view_results, {
defend_if_empty(f$obs, ui = 'Please select an obs folder', type = 'error')
defend_if_blank(f$obs_input, ui = 'Please select an obs folder', type = 'error')
filenames <- c('trap-data.csv', 'measured-events.csv', 'hm-model-data.csv', 'options.csv')
paths <- purrr::map(filenames, ~list_files(f$obs$path, pattern = .x))
data <- purrr::map(paths, ~data.table::fread(.x$path))
names(data) <- c('trap', 'events', 'running', 'options')
data
})
output$overlay_dygraph <- dygraphs::renderDygraph({
req(trap_data())
hz <- trap_data()$options$hz[[1]]
channels <- trap_data()$options$channels[[1]]
## if(is.null(channels)) channels <- 1
## if(channels == 1){
raw <- trap_data()$trap$processed_bead
## } else if(channels == 2){
## if(trap_data()$options$preferred_channel[[1]] == 1){
## raw <- trap_data()$trap$processed_bead_1
## } else {
## raw <- trap_data()$trap$processed_bead_2
## }
## }
d <- data.frame(index = (1:nrow(trap_data()$trap)/hz),
raw = raw,
model = trap_data()$trap$hm_overlay)
periods_df <- data.table::data.table(start = trap_data()$events$cp_event_start_dp/hz,
stop = trap_data()$events$cp_event_stop_dp/hz,
keep = trap_data()$events$keep,
event_user_excluded = trap_data()$events$event_user_excluded,
front_signal_ratio = trap_data()$events$front_signal_ratio,
back_signal_ratio = trap_data()$events$back_signal_ratio,
color = scales::alpha("#D95F02" , 0.4))
periods_df <- periods_df[keep == T & event_user_excluded == F]
periods_df <- periods_df[front_signal_ratio >= ro$front_signal_ratio & back_signal_ratio >= ro$back_signal_ratio]
# add a column providiing the real event number
# so when user filters out events, the events retain their real event number
# making it easier to pick other events to exclude
events <- trap_data()$events
events$id <- 1:nrow(trap_data()$events)
labels <- events[keep == T & event_user_excluded == F]
# get the peak nm index to put the labels here
## pni <- events$peak_nm_index
# if(nrow(excluded_events) == 0 ){
# overlay_dy <- dygraphs::dygraph(d) %>% #raw_data_dygraph
# dygraphs::dySeries('raw', color = 'black', strokeWidth = 2) %>%
# dygraphs::dySeries('model', color = "#1B9E77", strokeWidth = 2) %>%
# dygraphs::dyRangeSelector(fillColor ='white', strokeColor = 'black') %>%
# add_shades(periods_df) %>% #raw_periods
# #add_shades(excluded_events, color = "grey60") %>%
# add_labels_hmm(trap_data()$events, peak_nm_index = pni, labelLoc = 'bottom') %>% #results$events
# dygraphs::dyAxis('x', label = 'seconds', drawGrid = FALSE) %>%
# dygraphs::dyAxis('y', label = 'nm', drawGrid = FALSE) %>%
# dygraphs::dyUnzoom()
# } else {
overlay_dy <- dygraphs::dygraph(d) |> #raw_data_dygraph
dygraphs::dySeries('raw', color = 'black') |>
dygraphs::dySeries('model', color = "#1B9E77", strokeWidth = 2) |>
dygraphs::dyRangeSelector(fillColor ='white', strokeColor = 'black') |>
add_shades(periods_df) |> #raw_periods
#add_shades(excluded_events, color = "#BDBDBD") %>%
add_labels_hmm(labels, labelLoc = 'bottom') |> #results$events
dygraphs::dyAxis('x', label = 'seconds', drawGrid = FALSE) |>
dygraphs::dyAxis('y', label = 'nm', drawGrid = FALSE) |>
dygraphs::dyUnzoom()
# }
})
output$mv_by_state <- renderPlot({
req(trap_data())
mv_data <- trap_data()$running
mv_data$state <- factor(mv_data$state, levels = c(1, 2))
mv1 <- ggplot2::ggplot(mv_data)+
geom_point(aes(x = run_mean, y = run_var, color = state), size = 3, alpha = 0.5)+
scale_color_manual(values = c("#1B9E77", "#D95F02"))+
ggtitle('Mean-Variance (overlayed)')+
ylab('Variance')+
xlab('Mean (nm)')+
theme_linedraw(base_size = 18)+
theme(legend.position = 'none')
mv2 <- ggplot(mv_data)+
geom_point(aes(x = run_mean, y = run_var, color = state), size = 3, alpha = 0.5)+
scale_color_manual(values = c("#1B9E77", "#D95F02"))+
facet_wrap(~state)+
ggtitle('Mean-Variance (by state)')+
ylab('')+
xlab('Mean (nm)')+
theme_linedraw(base_size = 18)
gridExtra::grid.arrange(mv1, mv2, nrow = 1)
})
output$observation <- renderValueBox({
req(trap_data())
valueBox(
unique(trap_data()$trap$obs),
paste(f$conditions$name, f$date_input),
icon = icon("folder-open"),
color = 'yellow'
)
})
output$n_events <- renderValueBox({
req(trap_data())
valueBox(
nrow(trap_data()$events[keep == T]),
"Events",
icon = icon("slack-hash"),
color = 'yellow'
)
})
output$s2n <- renderValueBox({
req(trap_data())
valueBox(
round(unique(trap_data()$running$var_signal_ratio), 2),
"Signal-to-noise",
icon = icon("signal"),
color = 'yellow'
)
})
output$selected_folders <- renderPrint({
ob <- if(input$which_obs == 'single'){
validate(need(substring(f$obs_input, 1, 3) == 'obs', message = 'Please select an obs folder to analyze'))
f$obs$name
} else {
validate(need(f$date_input, message = 'Please select date folder to analyze'))
'Analyze all'
}
cat('Project:', f$project$name, ' | Conditions:', f$conditions$name, ' | Date:', f$date$name, ' | Observation:', ob)
})
info <- eventReactive(input$info_table, {
defend_if_empty(f$date, ui = 'Please select a date folder', type = 'error')
showNotification('Refreshing table', type = 'message')
files <- list_files(f$date$path, pattern = 'options.csv', recursive = T)
purrr::map_df(files$path, ~data.table::fread(.,
select = c("obs", "include", "analyzer", "report", "review"),
nrows = 1))
})
output$table <- DT::renderDT({
req(info())
info() %>%
dplyr::rename('Obs' = obs,
'Include' = include,
'Analyzer' = analyzer,
#'Status' = status,
'Report' = report,
'Review' = review) %>%
DT::datatable() %>%
DT::formatStyle('Include',
color = DT::styleEqual(c(F, T), c('red', 'black'))
) %>%
DT::formatStyle('Report',
color = DT::styleEqual(c('error', 'success'), c('red', 'black'))
) %>%
DT::formatStyle('Review',
color = DT::styleEqual(c(NA, F, T), c('grey', 'red', 'green'))
)
})
#### SAVE REVIEW ####
observeEvent(input$save_review, {
allow_if('obs_input' %in% names(f), ui = 'Select an obs', type = 'error')
defend_if_blank(f$obs_input, ui = 'Select an obs', type = 'error')
withProgress(message = 'Saving Review', {
td <- list_files(f$obs$path, pattern = 'options.csv')
trap <- data.table::fread(td$path)
setProgress(0.7)
trap_reviewed <- trap %>%
dplyr::mutate(review = input$quality_control)
data.table::fwrite(trap_reviewed, file = file.path(f$obs$path, 'options.csv'))
setProgress(1, detail = 'Done')
})
showNotification('Review saved' , type = 'message')
shinyjs::click('info_table')
})
# output$obs_2_review <- renderPrint({
#
# validate(need(substring(f$obs_input, 1, 3) == 'obs', message = 'Please select an obs folder to analyze'))
#
# validate(need(substring(f$obs_input, 1, 3) == 'obs', message = 'Please select an obs folder to analyze'))
# cat('Revewing ', f$obs$name)
#
# })
a <- reactiveValues(w_width = 150,
w_slide = "1/2",
em_random_start = FALSE,
use_channels = "Mean/Var",
front_cp_method = "Mean/Var",
back_cp_method = "Mean/Var",
cp_running_var_window = 5,
displacement_type = "avg")
observeEvent(input$set_options, {
a$w_width <- input$w_width
a$w_slide <- input$w_slide
a$em_random_start <- input$em_random_start
a$use_channels <- input$use_channels
a$front_cp_method <-input$front_cp_method
a$back_cp_method <-input$back_cp_method
a$cp_running_var_window <- input$cp_running_var_window
a$displacement_type <- input$displacement_type
removeModal()
})
#### Analysis Options ####
observeEvent(input$options, {
showModal(
modalDialog(
title = "Set Analysis Parameters",
footer = tagList(modalButton("Cancel"), actionButton(ns("set_options"), "OK")),
tabsetPanel(
tabPanel("HM-Model",
fluidRow(
column(6,
numericInput(ns("w_width"), "Window Width", value = a$w_width, width = "100%")
),
column(6,
shinyWidgets::sliderTextInput(ns("w_slide"),
"Slide Window", c("1-Pt", "1/4", "1/2", "3/4", "No-overlap"),
grid = TRUE,
selected = a$w_slide,
width = "100%")
)
) ,
fluidRow(
column(6,
shinyWidgets::prettyRadioButtons(
inputId = ns("use_channels"),
label = "Channels",
choices = hm$use_channels_options,
selected = a$use_channels,
inline = TRUE,
status = "primary",
fill = TRUE
)
),
column(4,
div(style = "margin-top: 25px;",
shinyWidgets::prettyCheckbox(inputId = ns('em_random_start'),
value = a$em_random_start,
label = "EM Random Start?",
status = "primary",
shape = "curve",
outline = TRUE)
)
)
)
), #hm-model tab close
tabPanel("Changepoint",
fluidRow(
column(6,
h4("Front"),
shinyWidgets::prettyRadioButtons(
inputId = ns("front_cp_method"),
label = "Channels",
choices = c("Mean/Var", "Variance"),
selected = a$front_cp_method,
inline = TRUE,
status = "primary",
fill = TRUE
)
),
column(6,
h4("Back"),
shinyWidgets::prettyRadioButtons(
inputId = ns("back_cp_method"),
label = "Channels",
choices = c("Mean/Var", "Variance"),
selected = a$back_cp_method,
inline = TRUE,
status = "primary",
fill = TRUE
)
)
),
sliderInput(ns("cp_running_var_window"), "Running Variance Window Width", min = 5, max = 100, value = a$cp_running_var_window, width = "100%")
), #cp tab panel
tabPanel("Displacements",
radioButtons(inputId = ns('displacement_type'),
label = 'Displacement Calculation Method',
choices = list("Average" = "avg",
"Peak" = "peak"),
inline = TRUE,
selected = a$displacement_type)
)
)
)
)
observe({
if(is.null(input$back_cp_method)){
shinyjs::hide("cp_running_var_window")
} else {
if(input$back_cp_method == "Variance" || input$front_cp_method == "Variance"){
shinyjs::show("cp_running_var_window")
} else {
shinyjs::hide("cp_running_var_window")
}
}
})
})
#### Review Options ####
ro <- reactiveValues(front_signal_ratio = 0,
back_signal_ratio = 0)
which_events_user_excluded <- eventReactive(trap_data()$events, {
req(trap_data())
which(trap_data()$events$event_user_excluded == TRUE)
})
output$number_excluded_events <- renderText({
paste0("Events excluded: ", toString(which_events_user_excluded()))
})
observeEvent(input$review_options, {
showModal(
modalDialog(
title = "Review Options",
footer = tagList(modalButton("Cancel"), actionButton(ns("set_review_options"), "OK")),
size = "l",
tabsetPanel(
tabPanel("Exclude Events",
br(),
column(3,
selectInput(ns("exclude_event_manual"),
label = "Select events to modify",
choices = 1:nrow(trap_data()$events),
multiple = T
)
),
column(3,
shinyWidgets::radioGroupButtons(
inputId = ns('include_exclude'),
label = "Include or Exclude?",
choices = c("Include" = "include",
"Exclude" = "exclude"),
selected = "exclude",
justified = TRUE,
checkIcon = list(
yes = tags$i(class = "fa fa-check-square",
style = "color: black"),
no = tags$i(class = "fa fa-square-o",
style = "color: black"))
)
),
div(style = "padding-top: 15px", verbatimTextOutput(ns("number_excluded_events")))
),
tabPanel("Signal Filter",
column(6,
sliderInput(ns("front_signal_ratio"),
"Front Signal-to-noise Filter",
min = 0,
max = 4,
value = 0,
step = 0.1)
),
column(6,
sliderInput(ns("back_signal_ratio"),
"Back Signal-to-noise Filter",
min = 0,
max = 4,
value = 0,
step = 0.1)
)
)
)
)
)
})
observeEvent(input$snapshot, {
showModal(
modalDialog(
title = "Snapshot",
footer = tagList(modalButton("Cancel"), actionButton(ns("save_plot_overlay"), "Save")),
size = "l",
fluidRow(
column(2,
colourpicker::colourInput(ns("export_plot_event_color"),
label = "Events Color",
value = "red",
showColour = "both"),
),
column(4,
sliderInput(ns("export_plot_height"),
label = "Height (in)",
min = 0,
max = 20,
step = 0.5,
value = 2.5),
),
column(4,
sliderInput(ns("export_plot_width"),
label = "Width (in)",
min = 0,
max = 50,
step = 1,
value = 18),
),
column(2,
div(style = "padding-top: 30px;",
checkboxInput(ns("save_as_gg"),
"Save as ggplot?",
FALSE)
)
)
),
fluidRow(
plotOutput(ns("export_ggplot"), height = "175px")
)
)
)
})
observeEvent(input$set_review_options, {
ro$front_signal_ratio <- input$front_signal_ratio
ro$back_signal_ratio <- input$back_signal_ratio
golem::print_dev("before if")
if(!rlang::is_empty(input$exclude_event_manual)){
excluded_data <- trap_data()$events
golem::print_dev("setting val true")
if(input$include_exclude == "exclude"){
excluded_data$event_user_excluded[as.numeric(input$exclude_event_manual)] <- TRUE
} else if(input$include_exclude == "include"){
excluded_data$event_user_excluded[as.numeric(input$exclude_event_manual)] <- FALSE
}
data.table::fwrite(excluded_data, file = file.path(f$obs$path, 'measured-events.csv'))
showNotification(paste0("The following events were modified: ", toString(input$exclude_event_manual), " - Refreshing..."), duration = 3, type = "message")
}
removeModal()
shinyjs::click("view_results")
})
observe({
output$export_ggplot <- renderPlot(height = 175, {
plot_overlay(obs_path = f$obs$path,
time_period_dp = input$overlay_dygraph_date_window,
color = input$export_plot_event_color)
})
})
observeEvent(input$save_plot_overlay,{
dir_summary <- file.path(f$project$path, "summary")
if(!dir.exists(dir_summary)) dir.create(dir_summary)
dir_fig <- file.path(dir_summary, "figures")
if(!dir.exists(dir_fig)) dir.create(dir_fig)
file_name <- file.path(dir_fig,
paste0(
f$conditions$name,
"_",
f$date$name,
"_",
f$obs$name,
"_",
round(input$overlay_dygraph_date_window[[1]], 4),
"-",
round(input$overlay_dygraph_date_window[[2]], 4)
)
)
gg <- plot_overlay(obs_path = f$obs$path,
time_period_dp = input$overlay_dygraph_date_window,
color = input$export_plot_event_color)
if(input$save_as_gg){
saveRDS(gg, file = paste0(file_name, ".rds"))
} else {
cowplot::ggsave2(file = paste0(file_name, ".pdf"),
plot = gg,
height = as.numeric(input$export_plot_height),
width = as.numeric(input$export_plot_width),
units = "in")
}
showNotification("Plot Saved", type = "message")
removeModal()
})
output$numbers <- renderPlot({
req(trap_data())
measured_events <- trap_data()$events
step <-
ggplot()+
## geom_dotplot(data = measured_events, aes(displacement_nm),
## fill = "grey40",
## binwidth = 2)+
stat_ecdf(data = measured_events, aes(x = displacement_nm), pad = FALSE)+
geom_vline(aes(xintercept = mean(measured_events$displacement_nm)), linetype = "dashed")+
geom_label(aes(mean(measured_events$displacement_nm),
y = 1,
label = paste0("bar(x)==", round(mean(measured_events$displacement_nm), 1))),
parse = TRUE,
size = 6)+
ggtitle("Displacements")+
xlab("nanometers")+
ylab('ECDF')+
# scale_x_continuous(breaks = sort(c(seq(-100, 100, by = 20), round(mean(measured_events$displacement_nm), 1))))+
cowplot::theme_cowplot(18)+
theme(
axis.text.y = element_blank(),
axis.line.y = element_blank(),
axis.ticks.y = element_blank()
)
time_on <-
ggplot()+
stat_ecdf(data = measured_events, aes(x = time_on_ms),
pad = FALSE)+
geom_vline(aes(xintercept = mean(measured_events$time_on_ms)), linetype = "dashed")+
geom_label(aes(mean(measured_events$time_on_ms), y = 1,
label = paste0("bar(x)==", round(mean((measured_events$time_on_ms), 0)))),
parse = TRUE,
size = 6)+
ggtitle("Time On")+
xlab("milliseconds")+
ylab('ECDF')+
cowplot::theme_cowplot(18)+
theme(
axis.text.y = element_blank(),
axis.line.y = element_blank(),
axis.ticks.y = element_blank()
)
cowplot::plot_grid(step, time_on)
})
}
## To be copied in the UI
# mod_hm_model_ui("hm_model_ui")
## To be copied in the server
# callModule(mod_hm_model_server, "hm_model_ui")
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