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Merge incidence and prevalence population and estimates #262

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merged 2 commits into from
Feb 3, 2025
Merged

Merge incidence and prevalence population and estimates #262

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9ac4817
Merge incidence and prevalence population and estimates
martaalcalde Feb 3, 2025
e658605
Update ui.R
martaalcalde Feb 3, 2025
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302 changes: 110 additions & 192 deletions inst/shiny/server.R
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Original file line number Diff line number Diff line change
Expand Up @@ -646,7 +646,7 @@ server <- function(input, output, session) {
# summarise_large_scale_characteristics -----
## Tidy summarise_large_scale_characteristics -----
getTidyDataSummariseLargeScaleCharacteristics <- shiny::reactive({
browser()

if (is.null(dataFiltered$summarise_large_scale_characteristics)) {
validate("No large scale characteristics in results")
}
Expand Down Expand Up @@ -1047,9 +1047,12 @@ browser()


# incidence -----
incidenceFiltered <- shiny::reactive({

dataFiltered$incidence |>
filterIncidence <- shiny::reactive({
if (is.null(dataFiltered$incidence)) {
validate("No incidence in results")
}

result <- dataFiltered$incidence |>
filter(cdm_name %in%
input$incidence_grouping_cdm_name) |>
filterGroup(outcome_cohort_name %in%
Expand All @@ -1062,21 +1065,18 @@ browser()
input$incidence_settings_denominator_days_prior_observation) |>
filterAdditional(analysis_interval %in%
input$incidence_settings_analysis_interval)

if (nrow(result) == 0) {
validate("No results found for selected inputs")
}
return(result)
})

## Table incidence -----
createTableIncidence <- shiny::reactive({

if (is.null(dataFiltered$incidence)) {
validate("No incidence in results")
}

result <- incidenceFiltered()

if (nrow(result) == 0) {
validate("No results found for selected inputs")
}
IncidencePrevalence::tableIncidence(
result,
filterIncidence(),
groupColumn = c("cdm_name", "outcome_cohort_name"),
hide = "denominator_cohort_name",
settingsColumn = c("denominator_age_group",
Expand Down Expand Up @@ -1104,90 +1104,54 @@ browser()
gt::gtsave(data = obj, filename = file)
}
)
## Plot incidence_population -----
createPlotIncidencePopulation <- shiny::reactive({

if(!is.null(input$incidence_population_plot_facet) &&
isTRUE(input$incidence_population_plot_facet_free)){
plotIncidencePopulation(x = input$incidence_population_plot_x,
y = input$incidence_population_plot_y,
result = incidenceFiltered(),
facet = NULL,
colour = input$incidence_population_plot_colour

) +
facet_wrap(facets = input$incidence_population_plot_facet, scales = "free")
} else {
plotIncidencePopulation(x = input$incidence_population_plot_x,
y = input$incidence_population_plot_y,
result = incidenceFiltered(),
facet = input$incidence_population_plot_facet,
colour = input$incidence_population_plot_colour

)
}



})

output$incidence_population_plot <- renderUI({
if(isTRUE(input$incidence_population_plot_interactive)){
plot <- plotly::ggplotly(createPlotIncidencePopulation())
} else {
plot <- renderPlot(createPlotIncidencePopulation())
}
plot
})

output$incidence_population_plot_download <- shiny::downloadHandler(
filename = "incidence_population_plot.png",
content = function(file) {
obj <- createPlotIncidencePopulation()
ggplot2::ggsave(
filename = file,
plot = obj,
width = as.numeric(input$incidence_population_plot_download_width),
height = as.numeric(input$incidence_population_plot_download_height),
units = input$incidence_population_plot_download_units,
dpi = as.numeric(input$incidence_population_plot_download_dpi)
)
}
)

## Plot incidence -----
createPlotIncidence <- shiny::reactive({
if (is.null(dataFiltered$incidence)) {
validate("No incidence in results")
}

result <- incidenceFiltered()

if (nrow(result) == 0) {
validate("No results found for selected inputs")
}

if(!is.null(input$incidence_plot_facet) &&
isTRUE(input$incidence_plot_facet_free)){
IncidencePrevalence::plotIncidence(
result,
x = input$incidence_plot_x,
ribbon = FALSE,
facet = input$incidence_plot_facet,
colour = input$incidence_plot_colour
) +
facet_wrap(facets = input$incidence_plot_facet, scales = "free")
} else {
IncidencePrevalence::plotIncidence(
result <- filterIncidence()

x <- input$incidence_plot_x
y <- input$incidence_plot_y
facet <- input$incidence_plot_facet
facet_free <- input$incidence_plot_facet_free
colour <- input$incidence_plot_colour

# Plot incidence estimates
if(y == "incidence_estimates"){
plot <- IncidencePrevalence::plotIncidence(
result,
x = input$incidence_plot_x,
x = x,
ribbon = FALSE,
facet = input$incidence_plot_facet,
colour = input$incidence_plot_colour
facet = facet,
colour = colour
)

if(!is.null(facet) && isTRUE(facet_free)){
plot <- plot +
facet_wrap(facets = facet, scales = "free")
}
}else{
# Plot incidence population
if(!is.null(facet) && isTRUE(facet_free)){
plot <- plotIncidencePopulation(x = x,
y = y,
result = result,
facet = NULL,
colour = colour

) +
facet_wrap(facets = facet, scales = "free")
} else {
plot <- plotIncidencePopulation(x = x,
y = y,
result = result,
facet = facet,
colour = colour

)
}
}
return(plot)
})

output$incidence_plot <- renderUI({
if(isTRUE(input$incidence_plot_interactive)){
plot <- plotly::ggplotly(createPlotIncidence())
Expand All @@ -1210,14 +1174,14 @@ browser()
)
}
)





# prevalence -----
prevalenceFiltered <- shiny::reactive({

dataFiltered$prevalence |>
filterPrevalence <- shiny::reactive({
if (is.null(dataFiltered$prevalence)) {
validate("No prevalence in results")
}

result <- dataFiltered$prevalence |>
filter(cdm_name %in%
input$prevalence_grouping_cdm_name) |>
filterGroup(outcome_cohort_name %in%
Expand All @@ -1230,18 +1194,16 @@ browser()
input$prevalence_settings_denominator_days_prior_observation) |>
filterAdditional(analysis_interval %in%
input$prevalence_settings_analysis_interval)
})
## Table prevalence ----
createTablePrevalence <- shiny::reactive({
if (is.null(dataFiltered$prevalence)) {
validate("No prevalence in results")
}

result <- prevalenceFiltered()


if (nrow(result) == 0) {
validate("No results found for selected inputs")
}

return(result)
})
## Table prevalence ----
createTablePrevalence <- shiny::reactive({
result <- filterPrevalence()

IncidencePrevalence::tablePrevalence(
result,
Expand Down Expand Up @@ -1272,97 +1234,53 @@ browser()
gt::gtsave(data = obj, filename = file)
}
)
## Plot population_prevalence ----
createPlotPrevalencePopulation <- shiny::reactive({

if (is.null(dataFiltered$prevalence)) {
validate("No prevalence in results")
}

result <- prevalenceFiltered()

if (nrow(result) == 0) {
validate("No results found for selected inputs")
}

if(!is.null(input$prevalence_population_plot_facet) &&
isTRUE(input$prevalence_population_plot_facet_free)){
IncidencePrevalence::plotPrevalencePopulation(
result = result,
x = input$prevalence_population_plot_x,
y = input$prevalence_population_plot_y,
facet = NULL,
colour = input$prevalence_population_plot_colour
) +
facet_wrap(facets = input$prevalence_population_plot_facet, scales = "free")
} else {
IncidencePrevalence::plotPrevalencePopulation(
result = result,
x = input$prevalence_population_plot_x,
y = input$prevalence_population_plot_y,
facet = input$prevalence_population_plot_facet,
colour = input$prevalence_population_plot_colour
)
}

})
output$prevalence_population_plot <- renderUI({
if(isTRUE(input$prevalence_population_plot_interactive)){
plot <- plotly::ggplotly(createPlotPrevalencePopulation())
} else {
plot <- renderPlot(createPlotPrevalencePopulation())
}
plot
})
output$prevalence_population_plot_download <- shiny::downloadHandler(
filename = "prevalence_population_plot.png",
content = function(file) {
obj <- createPlotPrevalence()
ggplot2::ggsave(
filename = file,
plot = obj,
width = as.numeric(input$prevalence_population_plot_download_width),
height = as.numeric(input$prevalence_population_plot_download_height),
units = input$prevalence_population_plot_download_units,
dpi = as.numeric(input$prevalence_population_plot_download_dpi)
)
}
)
## Plot prevalence -----
## Plot prevalence ----
createPlotPrevalence <- shiny::reactive({

if (is.null(dataFiltered$prevalence)) {
validate("No prevalence in results")
}

result <- prevalenceFiltered()

if (nrow(result) == 0) {
validate("No results found for selected inputs")
}

if(!is.null(input$prevalence_plot_facet) &&
isTRUE(input$prevalence_plot_facet_free)){
IncidencePrevalence::plotPrevalence(
result,
x = input$prevalence_plot_x,
ribbon = FALSE,
facet = input$prevalence_plot_facet,
colour = input$prevalence_plot_colour
) +
facet_wrap(facets = input$prevalence_plot_facet, scales = "free")
} else {
IncidencePrevalence::plotPrevalence(
result <- filterPrevalence()

x <- input$prevalence_plot_x
y <- input$prevalence_plot_y
facet <- input$prevalence_plot_facet
facet_free <- input$prevalence_plot_facet_free
colour <- input$prevalence_plot_colour

if(y == "prevalence_estimates"){
plot <- IncidencePrevalence::plotPrevalence(
result,
x = input$prevalence_plot_x,
x = x,
ribbon = FALSE,
facet = input$prevalence_plot_facet,
colour = input$prevalence_plot_colour
facet = facet,
colour = colour
)

if(!is.null(facet) && isTRUE(facet_free)){
plot <- plot +
facet_wrap(facets = facet, scales = "free")
}
}else{
if(!is.null(facet) && isTRUE(input$facet_free)){
plot <- IncidencePrevalence::plotPrevalencePopulation(
result = result,
x = x,
y = y,
facet = NULL,
colour = colour) +
facet_wrap(facets = facet, scales = "free")
} else {
plot <- IncidencePrevalence::plotPrevalencePopulation(
result = result,
x = x,
y = y,
facet = facet,
colour = colour
)
}
}



return(plot)

})

output$prevalence_plot <- renderUI({
if(isTRUE(input$prevalence_plot_interactive)){
plot <- plotly::ggplotly(createPlotPrevalence())
Expand Down
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