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shiny.R
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app_logger <- "shinyapp"
source("load_tool_environment.R")
# set up logging at info level
basicConfig(level = 20)
addHandler(writeToFile, logger = app_logger, file = "logging/applogs.log")
ui <- fluidPage(
tags$head(
tags$style(HTML("hr {border-top: 1px solid #000000;}"))
),
# Allows for the use of notifications.
useShinyjs(),
titlePanel("PV System Disturbance Analysis"),
# Input Bar
tabsetPanel(
tabPanel("Main", fluid = TRUE,
sidebarLayout(
sidebarPanel(id = "side_panel",
h4("Settings input file selection"),
textInput("settings_file", "Select JSON file for loading inputs (optional).", value = ""),
shinyFilesButton("load_settings", "Choose File", "Select settings file ...", multiple = FALSE),
tags$hr(),
h4("File selection"),
textInput("database_name", "SQLite database file", value = ""),
fluidRow(
div(
style = "display:inline-block",
shinyFilesButton("choose_database", "Choose File", "Select database file ...", multiple = FALSE)
),
div(style = "display:inline-block", actionButton("load_file_from_settings", "Load from settings file")),
div(style = "display:inline-block", actionButton("connect_to_database", "Connect"))),
tags$hr(),
uiOutput("load_date"),
uiOutput("load_time_start"),
uiOutput("load_time_end"),
radioButtons(
"region_to_load",
label = strong("Regions"),
choices = list("QLD", "NSW", "VIC", "SA", "TAS", "WA"),
selected = "TAS",
inline = TRUE
),
uiOutput("duration"),
HTML("<br><br>"),
textInput("frequency_data", "Frequency data file", value = ""),
shinyFilesButton("choose_frequency_data", "Choose File", "Select fequency data file ...", multiple = FALSE),
HTML("<br><br>"),
actionButton("load_first_filter_settings", "Load from settings file"),
actionButton("load_data", "Load data"),
tags$hr(),
h4("Category Filter"),
uiOutput("cleaned"),
uiOutput("StdVersion"),
uiOutput("size_groupings"),
uiOutput("responses"),
uiOutput("zones"),
uiOutput("compliance"),
uiOutput("compliance_2020"),
uiOutput("reconnection_compliance"),
uiOutput("postcodes"),
uiOutput("manufacturers"),
uiOutput("models"),
uiOutput("sites"),
uiOutput("circuits"),
uiOutput("offsets"),
tags$hr(),
h4("Chart specific filters"),
materialSwitch(
"norm_power_filter_off_at_t0",
label = strong("Normalised power chart: filter out off at t0 circuits:"),
status = "primary",
value = TRUE
),
tags$hr(),
h4("Grouping Categories"),
materialSwitch("standard_agg", label = strong("AS4777:"), status = "primary", value = TRUE),
materialSwitch("grouping_agg", label = strong("Size Grouping:"), status = "primary", value = TRUE),
materialSwitch("response_agg", label = strong("Response Grouping:"), status = "primary", value = FALSE),
materialSwitch("pst_agg", label = strong("Postcodes:"), status = "primary", value = FALSE),
materialSwitch("manufacturer_agg", label = strong("Manufacturer:"),status = "primary", value = FALSE),
materialSwitch("model_agg", label = strong("Models:"), status = "primary", value = FALSE),
materialSwitch("circuit_agg", label = strong("Circuits:"), status = "primary", value = FALSE),
materialSwitch("zone_agg", label = strong("Zones:"), status = "primary", value = FALSE),
materialSwitch("compliance_agg", label = strong("Compliance:"), status = "primary", value = FALSE),
materialSwitch("compliance_2020_agg", label = strong("Compliance 2020:"), status = "primary", value = FALSE),
materialSwitch(
"reconnection_compliance_agg",
label = strong("Reconnection Compliance:"),
status = "primary",
value = FALSE
),
materialSwitch("v_excursion_agg", label = strong("Voltage excursion:"), status = "primary", value = FALSE),
tags$hr(),
h4("Additional Processing"),
radioButtons(
"confidence_category",
label = strong("Grouping category to calculate confidence interval for. Must be a Grouping Category"),
choices = list(
"none",
"response_category",
"compliance_status",
"compliance_status_2020",
"reconnection_compliance_status"
),
selected = "none",
inline = TRUE
),
materialSwitch(inputId = "raw_upscale", label = strong("Upscaled Data"), status = "primary", right = FALSE),
tags$hr(),
h4("Event information"),
uiOutput("event_date"),
uiOutput("pre_event_interval"),
uiOutput("window_length"),
uiOutput("post_event_ufls_window_length"),
uiOutput("event_latitude"),
uiOutput("event_longitude"),
uiOutput("zone_one_radius"),
uiOutput("zone_two_radius"),
uiOutput("zone_three_radius"),
tags$hr(),
uiOutput("update_plots"),
actionButton("load_second_filter_settings", "Load from settings file"),
shinySaveButton("save_settings", "Save settings file", "Save file as ...", filetype = list("json"))
),
#Output
mainPanel(
plotlyOutput(outputId = "PlotlyTest"),
uiOutput("save_agg_power"),
HTML("<br>"),
uiOutput("save_underlying"),
HTML("<br>"),
uiOutput("save_circuit_summary"),
HTML("<br>"),
uiOutput("batch_save"),
HTML("<br>"),
uiOutput("save_ideal_response"),
HTML("<br>"),
uiOutput("save_ideal_response_downsampled"),
HTML("<br>"),
uiOutput("save_ideal_response_2020"),
HTML("<br>"),
uiOutput("save_ideal_response_downsampled_2020"),
HTML("<br>"),
uiOutput("save_manufacturer_disconnection_summary"),
HTML("<br>"),
uiOutput("save_manufacturer_disconnection_summary_with_separate_ufls_counts"),
HTML("<br>"),
uiOutput("save_upscaled_disconnection_summary"),
HTML("<br>"),
uiOutput("save_upscaled_disconnection_summary_with_separate_ufls_counts"),
HTML("<br>"),
uiOutput("save_voltage_excursion_summary"),
HTML("<br><br>"),
plotlyOutput(outputId = "NormPower"),
plotlyOutput(outputId = "Frequency"),
plotlyOutput(outputId = "Voltage"),
plotlyOutput(outputId = "ResponseCount"),
uiOutput("save_response_count"),
plotlyOutput(outputId = "distance_response"),
uiOutput(outputId = "save_distance_response"),
plotlyOutput(outputId = "ZoneCount"),
uiOutput("save_zone_count"),
plotlyOutput(outputId = "VoltageVisualization"),
uiOutput("save_disconnection_percentage"),
plotlyOutput(outputId = "map"),
uiOutput(outputId = "save_circuit_kml"),
HTML("<br><br>"),
dataTableOutput("sample_count_table"),
HTML("<br><br>"),
uiOutput("save_sample_count")
)
)
),
tabPanel("Data Cleaning", fluid = TRUE,
mainPanel(
plotlyOutput("site_plot"),
h4(paste0(
"Editing the tables below changes the connected database, to use these changes in the analysis data must ",
"be reloaded on the main tab."
)),
h4("Cleaned site data (select to view trace)"),
DTOutput("site_details_editor"),
h4("Cleaned Circuit data (select to view trace)"),
DTOutput("circuit_details_editor")
)
),
tabPanel(
"Manual compliance",
fluid = TRUE,
mainPanel(
plotlyOutput("compliance_plot"),
h4(paste0(
"Editing the compliance value changes the connected database, to use these changes in the analysis data ",
"must be reloaded on the main tab."
)),
uiOutput("manual_compliance_type"),
uiOutput("compliance_cleaned_or_raw"),
uiOutput("compliance_circuits"),
uiOutput("set_c_id_compliance"),
fluidRow(
div(style = "display:inline-block", uiOutput("get_previous_c_id")),
div(style = "display:inline-block", uiOutput("get_next_c_id")))
)
),
tabPanel(
"Settings",
fluid = TRUE,
sidebarLayout(
sidebarPanel(
id = "side_panel",
h3("Droop response compliance settings"),
numericInput("compliance_threshold", label = strong("Compliance threshold"), value = 0.5, max = 1, min = 0),
numericInput(
"start_buffer",
label = strong("Start buffer, allowed time to reach compliance threshold, in seconds."),
value = 60
),
numericInput(
"end_buffer",
label = strong("End buffer, allowed time for system ending response early, in seconds."),
value = 60
),
numericInput(
"end_buffer_responding",
label = strong(
"Response time, window length for systems to be considered Non Compliant Responding, in seconds."
),
value = 120
),
h3("Over-frequency droop response compliance settings AS4777.2:2020"),
numericInput(
"compliance_threshold_2020",
label = strong("Compliance threshold"),
value = 0.5,
max = 1,
min = 0
),
numericInput(
"start_buffer_2020",
label = strong("Start buffer, allowed time to reach compliance threshold, in seconds."),
value = 10
),
numericInput(
"end_buffer_2020",
label = strong(
paste0(
"End buffer, allowed time for system ending response early, in seconds. ",
"Note, AS4777.2:2020 ideal response profile is calculated separately to the 2015 response profile."
)
),
value = 0
),
numericInput(
"end_buffer_responding_2020",
label = strong(
"Response time, window length for systems to be considered Non Compliant Responding, in seconds."
),
value = 120
),
h3("Reconnection compliance settings"),
numericInput(
"reconnection_threshold",
label = strong("The level at which a circuit is considered to have reconnected."),
value = 0.95,
max = 1,
min = 0
),
numericInput(
"ramp_rate_threshold",
label = strong("Reconnection ramp rate threshold for assessing compliance, in pct/min."),
value = 0.333
),
numericInput(
"total_ramp_threshold_for_compliance",
label = strong("Total ramp threshold for compliance, in pct"),
value = 0.125
),
numericInput(
"total_ramp_threshold_for_non_compliance",
label = strong("Total ramp threshold for non compliance, in pct"),
value = 0.25
),
numericInput(
"ramp_rate_change_resource_limit_threshold",
label = strong("Ramp rate change threshold for detecting resource limitation, in pct/min"),
value = -0.1
),
h3("UFLS settings"),
numericInput(
"pre_event_ufls_window_length",
label = strong(
paste0(
"Pre-event UFLS Window: The time window before the event used to determine if the connection with a ",
"device is stable enough to determine its UFLS status, in minutes."
)
),
value = 5
),
numericInput(
"pre_event_ufls_stability_threshold",
label = strong(
paste0(
"The fraction of the Pre-event UFLS Window that needs to be sampled for the connection with a device ",
"to be considered stable enough to determine its UFLS status."
)
),
value = 0.6,
max = 1,
min = 0
),
h3("Misc settings"),
numericInput(
"disconnecting_threshold",
label = strong(
paste0(
"Disconnecting threshold, level below which circuit is considered to have disconnected. ",
"Note that this value is used in the compliance calculations but NOT the response categorisation."
)
),
value = 0.05,
max = 1,
min = 0
),
numericInput(
"NED_threshold",
label = strong(
paste0(
"Minimum proportion of sampled seconds allowed within post event interval to not have a Not enough ",
"data response"
)
),
value = 0.8,
max = 1,
min = 0
),
materialSwitch(
"exclude_solar_edge",
label = strong("Exclude solar edge from reconnection summary."),
status = "primary",
value = FALSE
),
materialSwitch(
"exclude_islanded_circuits",
label = strong("Exclude islanded circuits from figures and results"),
status = "primary",
value = TRUE
),
actionButton("load_backend_settings", "Load from settings file")
),
mainPanel()
)
),
tabPanel("Assumptions and Methodology", fluid = TRUE, documentation_panel())
)
)
reset_sidebar <- function(input, output, session, stringsAsFactors) {
output$cleaned <- renderUI({})
output$postcodes <- renderUI({})
output$manufacturers <- renderUI({})
output$models <- renderUI({})
output$sites <- renderUI({})
output$circuits <- renderUI({})
output$size_groupings <- renderUI({})
output$StdVersion <- renderUI({})
output$responses <- renderUI({})
output$zones <- renderUI({})
output$compliance <- renderUI({})
output$compliance_2020 <- renderUI({})
output$reconnection_compliance <- renderUI({})
output$offsets <- renderUI({})
shinyjs::hide("norm_power_filter_off_at_t0")
shinyjs::hide("standard_agg")
shinyjs::hide("raw_upscale")
shinyjs::hide("pst_agg")
shinyjs::hide("grouping_agg")
shinyjs::hide("grouping_agg")
shinyjs::hide("manufacturer_agg")
shinyjs::hide("response_agg")
shinyjs::hide("circuit_agg")
shinyjs::hide("zone_agg")
shinyjs::hide("compliance_agg")
shinyjs::hide("compliance_2020_agg")
shinyjs::hide("reconnection_compliance_agg")
shinyjs::hide("v_excursion_agg")
shinyjs::hide("save_settings")
shinyjs::hide("load_second_filter_settings")
shinyjs::hide("confidence_category")
output$event_date <- renderUI({})
output$pre_event_interval <- renderUI({})
output$window_length <- renderUI({})
output$post_event_ufls_window_length <- renderUI({})
output$event_latitude <- renderUI({})
output$event_longitude <- renderUI({})
output$zone_one_radius <- renderUI({})
output$zone_two_radius <- renderUI({})
output$zone_three_radius <- renderUI({})
output$update_plots <- renderUI({})
}
reset_chart_area <- function(output) {
#' Clear all of the charts.
#' @param output
output$PlotlyTest <- renderPlotly({})
output$save_agg_power <- renderUI({})
output$save_underlying <- renderUI({})
output$save_circuit_summary <- renderUI({})
output$sample_count_table <- renderDataTable({})
output$save_sample_count <- renderUI({})
output$NormPower <- renderPlotly({})
output$ResponseCount <- renderPlotly({})
output$save_response_count <- renderUI({})
output$ZoneCount <- renderPlotly({})
output$save_zone_count <- renderUI({})
output$Frequency <- renderPlotly({})
output$Voltage <- renderPlotly({})
output$distance_response <- renderPlotly({})
output$save_distance_response <- renderUI({})
output$VoltageVisualization <- renderPlotly({})
output$save_disconnection_percentage <- renderUI({})
output$map <- renderPlotly({})
output$save_circuit_kml <- renderUI({})
}
reset_data_cleaning_tab <- function(input, output, session, stringsAsFactors) {
output$circuit_details_editor <- renderDT({})
output$site_details_editor <- renderDT({})
output$site_plot <- renderPlotly({})
}
server <- function(input, output, session) {
# Create radio button dyamically so label can be updated
output$duration <- renderUI({
radioButtons("duration", label = strong("Sampled duration (seconds), select one."),
choices = list("1","5", "30", "60"),
selected = "60",
inline = TRUE)
})
# Hide these inputs by default, they are shown once data is loaded.
hide("frequency_data")
hide("choose_frequency_data")
hide("region_to_load")
hide("duration")
hide("load_first_filter_settings")
hide("perform_clean")
hide("keep_raw")
hide("load_data")
hide("standard_agg")
hide("raw_upscale")
hide("pst_agg")
hide("grouping_agg")
hide("response_agg")
hide("manufacturer_agg")
hide("model_agg")
hide("circuit_agg")
hide("zone_agg")
hide("compliance_agg")
hide("compliance_2020_agg")
hide("reconnection_compliance_agg")
hide("v_excursion_agg")
hide("save_settings")
hide("load_second_filter_settings")
hide("norm_power_filter_off_at_t0")
hide("confidence_category")
options(DT.options = list(pageLength = 3))
# Get input from GUI
settings_file <- reactive({input$settings_file})
database_name <- reactive({input$database_name})
frequency_data_file <- reactive({input$frequency_data})
region_to_load <- reactive({input$region_to_load})
duration <- reactive({input$duration})
standards <- reactive({input$StdVersion})
responses <- reactive({input$responses})
postcodes <- reactive({input$postcodes})
manual_compliance_type <- reactive({input$manual_compliance_type})
compliance_circuits <- reactive({input$compliance_circuits})
compliance_cleaned_or_raw <- reactive({input$compliance_cleaned_or_raw})
set_c_id_compliance <- reactive({input$set_c_id_compliance})
manufacturers <- reactive({input$manufacturers})
models <- reactive({input$models})
sites <- reactive({input$sites})
circuits <- reactive({input$circuits})
zones <- reactive({input$zones})
compliance <- reactive({input$compliance})
compliance_2020 <- reactive({input$compliance_2020})
reconnection_compliance <- reactive({input$reconnection_compliance})
offsets <- reactive({input$offsets})
size_groupings <- reactive({input$size_groupings})
clean <- reactive({input$cleaned})
raw_upscale <- reactive({input$raw_upscale})
pst_agg <- reactive({input$pst_agg})
grouping_agg <- reactive({input$grouping_agg})
response_agg <- reactive({input$response_agg})
manufacturer_agg <- reactive({input$manufacturer_agg})
perform_clean <- reactive({input$perform_clean})
keep_raw <- reactive({input$keep_raw})
model_agg <- reactive({input$model_agg})
circuit_agg <- reactive({input$circuit_agg})
zone_agg <- reactive({input$zone_agg})
compliance_agg <- reactive({input$compliance_agg})
compliance_2020_agg <- reactive({input$compliance_2020_agg})
reconnection_compliance_agg <- reactive({input$reconnection_compliance_agg})
v_excursion_agg <- reactive({input$v_excursion_agg})
load_date <- reactive({
date_as_str <- as.character(input$load_date[1])
})
load_start_date <- reactive({
date_as_str <- as.character(input$load_date[1])
})
load_end_date <- reactive({
date_as_str <- as.character(input$load_date[2])
})
load_start_time <- reactive({
date_as_str <- as.character(input$load_date[1])
time_as_str <- substr(input$load_time_start, 12,19)
start_time_as_str <- paste(date_as_str, time_as_str)
})
load_end_time <- reactive({
date_as_str <- as.character(input$load_date[2])
time_as_str <- substr(input$load_time_end, 12,19)
end_time_as_str <- paste(date_as_str, time_as_str)
})
start_time <- reactive({
date_as_str <- as.character(input$date[1])
time_as_str <- substr(input$time_start, 12,19)
start_time_as_str <- paste(date_as_str, time_as_str)
start_date_time <- strptime(start_time_as_str, format = "%Y-%m-%d %H:%M:%S", tz = "Australia/Brisbane")
start_date_time
})
end_time <- reactive({
date_as_str <- as.character(input$date[2])
time_as_str <- substr(input$time_end, 12,19)
end_time_as_str <- paste(date_as_str, time_as_str)
end_date_time <- strptime(end_time_as_str, format = "%Y-%m-%d %H:%M:%S", tz = "Australia/Brisbane")
end_date_time
})
pre_event_interval <- reactive({
date_as_str <- as.character(input$event_date)
time_as_str <- substr(input$pre_event_interval, 12, 19)
date_time_as_str <- paste(date_as_str, time_as_str)
pre_event_interval_date_time <- strptime(date_time_as_str, format = "%Y-%m-%d %H:%M:%S", tz = "Australia/Brisbane")
pre_event_interval_date_time
})
agg_on_standard <- reactive({input$standard_agg})
window_length <- reactive({input$window_length})
post_event_ufls_window_length <- reactive({input$post_event_ufls_window_length})
event_latitude <- reactive({input$event_latitude})
event_longitude <- reactive({input$event_longitude})
zone_one_radius <- reactive({input$zone_one_radius})
zone_two_radius <- reactive({input$zone_two_radius})
zone_three_radius <- reactive({input$zone_three_radius})
norm_power_filter_off_at_t0 <- reactive({input$norm_power_filter_off_at_t0})
confidence_category <- reactive({input$confidence_category})
# Values from settings tab
compliance_threshold <- reactive({input$compliance_threshold})
start_buffer <- reactive({input$start_buffer})
end_buffer <- reactive({input$end_buffer})
end_buffer_responding <- reactive({input$end_buffer_responding})
compliance_threshold_2020 <- reactive({input$compliance_threshold_2020})
start_buffer_2020 <- reactive({input$start_buffer_2020})
end_buffer_2020 <- reactive({input$end_buffer_2020})
end_buffer_responding_2020 <- reactive({input$end_buffer_responding_2020})
reconnection_threshold <- reactive({input$reconnection_threshold})
reconnection_time_threshold_for_compliance <- reactive({input$reconnection_time_threshold_for_compliance})
ramp_rate_threshold <- reactive({input$ramp_rate_threshold})
total_ramp_threshold_for_compliance <- reactive({input$total_ramp_threshold_for_compliance})
total_ramp_threshold_for_non_compliance <- reactive({input$total_ramp_threshold_for_non_compliance})
ramp_rate_change_resource_limit_threshold <- reactive({input$ramp_rate_change_resource_limit_threshold})
pre_event_ufls_window_length <- reactive({input$pre_event_ufls_window_length})
pre_event_ufls_stability_threshold <- reactive({input$pre_event_ufls_stability_threshold})
NED_threshold <- reactive({input$NED_threshold})
disconnecting_threshold <- reactive({input$disconnecting_threshold})
exclude_solar_edge <- reactive({input$exclude_solar_edge})
exclude_islanded_circuits <- reactive({input$exclude_islanded_circuits})
# Store the main data table in a reactive value so it is accessable outside
# the observe event that creates it.
v <- reactiveValues(
combined_data = data.frame(),
combined_data_no_ac_filter = data.frame(),
agg_power = data.frame(),
agg_norm_power = data.frame(),
install_data = data.frame(),
site_details = data.frame(),
circuit_details = data.frame(),
circuit_details_for_editing = data.frame(),
site_details_raw = data.frame(),
site_details_for_editing = data.frame(),
proxy_site_details_editor = 1,
proxy_circuit_details_editor = 1,
combined_data_after_clean = data.frame(),
time_series_data = data.frame(),
sample_count_table = data.frame(),
combined_data_f = data.frame(),
performance_factors = data.frame(),
postcode_data = data.frame(),
response_count = data.frame(),
zone_count = data.frame(),
disconnection_percentage = data.frame(),
distance_response = data.frame(),
frequency_data = data.frame(),
unique_offsets = c(),
circuit_summary = data.frame(),
region_frequency = data.frame(),
trigger_update_manual_compliance_tab = FALSE
)
observeEvent(input$connect_to_database, {
v$db <- DBInterface$new()
good_connection = FALSE
tryCatch(
{
v$db$connect_to_existing_database(database_name())
good_connection = TRUE
},
error = function(cond) {
shinyalert("An error occured while connecting to the database.", cond$message)
})
if (good_connection) {
min_timestamp <- v$db$get_min_timestamp()
max_timestamp <- v$db$get_max_timestamp()
output$load_time_start <- renderUI({
timeInput("load_time_start", label = strong("Enter start time"), value = min_timestamp)
})
output$load_time_end <- renderUI({
timeInput("load_time_end", label = strong("Enter end time"), value = max_timestamp)
})
output$load_date <- renderUI({
dateRangeInput(
"load_date",
label = strong("Date range (yyyy-mm-dd):"),
start = strftime(min_timestamp, format = "%Y-%m-%d"),
end = strftime(min_timestamp, format = "%Y-%m-%d"),
min = strftime(min_timestamp, format = "%Y-%m-%d"),
max = strftime(max_timestamp, format = "%Y-%m-%d"),
startview = "year"
)
})
shinyjs::show("frequency_data")
shinyjs::show("choose_frequency_data")
shinyjs::show("region_to_load")
shinyjs::show("duration")
shinyjs::show("load_data")
shinyjs::show("load_first_filter_settings")
}
})
# This is the event that runs when the "Load data" button on the GUI is
# Clicked.
observeEvent(input$load_data, {
id <- showNotification("Loading data", duration = 1000)
# setup loading inputs
data <- reactiveValuesToList(v)
settings <- get_current_settings()
# load data
loaded <- load_data(data, settings)
data <- loaded$data
errors <- loaded$errors
rm(loaded)
for (d_name in names(data)) {
v[[d_name]] <- data[[d_name]]
}
removeNotification(id)
# -------- UI Code --------
# show errors and warnings on tool dash
if (length(errors$warnings) > 0) {
for (warning in errors$warnings) {
shinyalert(warning$title, warning$body)
logging::logwarn(paste(warning$title, warning$body), logger = app_logger)
}
}
# do not proceed if errors have been raised
if (length(errors$errors) > 0) {
for (error in errors$errors) {
shinyalert(error$title, error$body)
logging::logerror(paste(error$title, error$body), logger = app_logger)
}
} else {
if (v$db$check_if_table_exists("site_details_cleaned")) {
v$site_details_for_editing <- v$db$get_site_details_cleaning_report()
v$site_details_for_editing <- filter(v$site_details_for_editing, s_state == settings$region_to_load)
output$site_details_editor <- renderDT(
isolate(v$site_details_for_editing),
selection = "single",
rownames = FALSE,
editable = TRUE
)
v$proxy_site_details_editor <- dataTableProxy("site_details_editor")
}
if (v$db$check_if_table_exists("circuit_details_cleaned")) {
v$circuit_details_for_editing <- v$db$get_circuit_details_cleaning_report()
v$circuit_details_for_editing <- filter(
v$circuit_details_for_editing, site_id %in% v$site_details_for_editing$site_id
)
output$circuit_details_editor <- renderDT(
isolate(v$circuit_details_for_editing),
selection = "single",
rownames = FALSE,
editable = TRUE
)
v$proxy_circuit_details_editor <- dataTableProxy("circuit_details_editor")
}
# Filtering option widgets are rendered after the data is loaded, this is
# because they are only usable once there is data to filter. Additionally
# The data loaded can then be used to create the appropraite options for
# filtering.
output$postcodes <- renderUI({
selectizeInput(
"postcodes",
label = strong("Select postcodes"),
choices = sort(unique(v$site_details$s_postcode)),
multiple = TRUE
)
})
output$manufacturers <- renderUI({
selectizeInput(
"manufacturers",
label = strong("Select manufacturers"),
choices = sort(unique(v$site_details$manufacturer)),
multiple = TRUE
)
})
output$models <- renderUI({
selectizeInput(
"models",
label = strong("Select models"),
choices = sort(unique(v$site_details$model)),
multiple = TRUE
)
})
output$sites <- renderUI({
selectizeInput(
"sites",
label = strong("Select Sites"),
choices = sort(unique(v$site_details$site_id)),
multiple = TRUE
)
})
output$circuits <- renderUI({
selectizeInput(
"circuits",
label = strong("Select Circuits"),
choices = sort(unique(v$circuit_details$c_id)),
multiple = TRUE
)
})
shinyjs::show("standard_agg")
output$size_groupings <- renderUI({
checkboxGroupButtons(
inputId = "size_groupings",
label = strong("Size Groupings"),
choices = list("30-100kW", "<30 kW"),
selected = list("30-100kW", "<30 kW"),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
output$cleaned <- renderUI({
checkboxGroupButtons(
inputId = "cleaned",
label = strong("Data sets"),
choices = list("clean", "raw"),
selected = list("clean"),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
output$StdVersion <- renderUI({
checkboxGroupButtons(
inputId = "StdVersion",
label = strong("AS47777 Version:"),
choices = list(
"AS4777.3:2005",
"Transition",
"AS4777.2:2015",
"AS4777.2:2015 VDRT",
"Transition 2020-21",
"AS4777.2:2020"
),
selected = list(
"AS4777.3:2005",
"Transition",
"AS4777.2:2015",
"AS4777.2:2015 VDRT",
"Transition 2020-21",
"AS4777.2:2020"
),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
output$responses <- renderUI({
checkboxGroupButtons(
inputId = "responses",
label = strong("Select Responses:"),
choices = list(
"1 Ride Through",
"2 Curtail",
"3 Drop to Zero",
"4 Disconnect",
"5 Off at t0",
"6 Not enough data",
"7 UFLS Dropout",
"Undefined",
NA
),
selected = list(
"1 Ride Through",
"2 Curtail",
"3 Drop to Zero",
"4 Disconnect",
"5 Off at t0",
"6 Not enough data",
"7 UFLS Dropout",
"Undefined",
NA
),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
output$zones <- renderUI({
checkboxGroupButtons(
inputId = "zones",
label = strong("Zones"),
choices = list("1 Zone", "2 Zone", "3 Zone", "Undefined", NA),
selected = list("1 Zone", "2 Zone", "3 Zone", "Undefined", NA),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
output$compliance <- renderUI({
checkboxGroupButtons(
inputId = "compliance",
label = strong("Compliance"),
choices = list(
"Compliant",
"Non-compliant Responding",
"Non-compliant",
"UFLS Dropout",
"Disconnect/Drop to Zero",
"Off at t0",
"Not enough data",
"Undefined",
NA
),
selected = list(
"Compliant",
"Non-compliant Responding",
"Non-compliant",
"UFLS Dropout",
"Disconnect/Drop to Zero",
"Off at t0",
"Not enough data",
"Undefined",
NA
),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
output$compliance_2020 <- renderUI({
checkboxGroupButtons(
inputId = "compliance_2020",
label = strong("Compliance 2020"),
choices = list(
"Compliant",
"Non-compliant Responding",
"Non-compliant",
"UFLS Dropout",
"Disconnect/Drop to Zero",
"Off at t0",
"Not enough data",
"Undefined",
NA
),
selected = list(
"Compliant",
"Non-compliant Responding",
"Non-compliant",
"UFLS Dropout",
"Disconnect/Drop to Zero",
"Off at t0",
"Not enough data",
"Undefined",
NA
),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
output$reconnection_compliance <- renderUI({
checkboxGroupButtons(
inputId = "reconnection_compliance",
label = strong("Reconnection Compliance"),
choices = list("Compliant", "Non Compliant", "Unsure", "Cannot be set", NA),
selected = list("Compliant", "Non Compliant", "Unsure", "Cannot be set", NA),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
sample_counts <- get_offset_sample_counts(v$combined_data, v$unique_offsets)
unique_offsets_filter_label <- make_offset_filter_label(sample_counts, v$unique_offsets)
output$offsets <- renderUI({
checkboxGroupButtons(
inputId = "offsets",
label = unique_offsets_filter_label,
choices = v$unique_offsets,
selected = c(v$unique_offsets[which.max(sample_counts)]),
justified = TRUE,
status = "primary",
individual = TRUE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"), no = icon("remove", lib = "glyphicon")),
direction = "vertical"
)
})
shinyjs::show("raw_upscale")
shinyjs::show("pst_agg")
shinyjs::show("grouping_agg")
shinyjs::show("grouping_agg")
shinyjs::show("manufacturer_agg")
shinyjs::show("response_agg")
shinyjs::show("circuit_agg")
shinyjs::show("zone_agg")
shinyjs::show("compliance_agg")
shinyjs::show("compliance_2020_agg")
shinyjs::show("reconnection_compliance_agg")
shinyjs::show("v_excursion_agg")
shinyjs::show("save_settings")
shinyjs::show("load_second_filter_settings")
shinyjs::show("norm_power_filter_off_at_t0")
shinyjs::show("confidence_category")
output$event_date <- renderUI({
dateInput(
"event_date",
label = strong("Event date (yyyy-mm-dd):"),
value = strftime(floor_date(get_mode(v$combined_data$ts), "day"), format = "%Y-%m-%d"),
startview = "year"
)
})
output$pre_event_interval <- renderUI({
timeInput(
"pre_event_interval",
label = strong("Pre-event time interval"),
value = as.POSIXct("12:13:55", format = "%H:%M:%S")
)
})
output$window_length <- renderUI({
numericInput(
"window_length",
label = strong("Set window length (min), Only data in this window is used for response analysis."),
value = 5,
min = 1,
max = 100,
step = 1
)