-
- | Graph |
- X Axis |
- Y Axis |
- Plot Frequency
|
- Description |
-
-
- | dQdV Graph |
- Voltage (V) |
- dQdV (Ah/V) |
- per cycle |
- The differential capacity plot for each cycle
|
-
-
- | Voltage Profile |
- Continuous Capacity (mAh/g or Ah) |
- Voltage (V) |
- per cycle |
- Voltage vs. capacity plot for each cycle. Units depend if the masses are specified. |
-
-
- | Voltage vs. Time |
- Time (min) |
- Voltage (V) |
- per cycle |
- The voltage as a function of time, including all steps |
-
-
- | Discharge Capacity |
- Cycle |
- Discharge Capacity (mAh/g or Ah) |
- per cell |
- Discharge capacity for each individual cell per cycle. Coulombic efficiency is also plotted on a secondary axis. Units depend if the masses are specified. |
-
-
- | Discharge Areal Capacity |
- Cycle |
- Discharge Capacity (Ah/cm2) |
- per cell |
- Discharge areal capacity for each individual cell per cycle. Coulombic efficiency is also plotted on a secondary axis. |
-
-
- | Total Discharge Capacity |
- Cycle |
- Discharge Capacity (mAh/g or Ah) |
- per analysis |
- Discharge capacity summarized for all cells in the analysis. Coulombic efficiency is also plotted on a secondary axis. Mean is plotted as a point with error bars presenting the standard error between the cells. Units depend if the masses are specified. |
-
-
- | Average Voltage |
- Cycle |
- Voltage (V) |
- per cell |
- The average voltage vs capacity for each cycle. The charge voltage (Vcharge) and discharge voltage (Vdischarge) were calculated using the average value theorem. The average voltage is then (Vcharge + Vdischarge)/2. Charge and discharge voltages are plotted alongside the average. |
-
-
- | Delta Voltage |
- Cycle |
- Voltage (V) |
- per cell |
- The delta voltage vs capacity for each cycle. The charge voltage (Vcharge) and discharge voltage (Vdischarge) were calculated using the average value theorem. The delta voltage is then Vcharge - Vdischarge). Charge and discharge voltages are plotted alongside the average. |
-
-
- | Capacity Loss |
- Cycle |
- Capacity (mAh/g or Ah) |
- per cell |
- The discharge capacity minus the charge capacity for each cycle. Units depend if the masses are specified. |
-
-
- ')
- ),
- )}, title ="Graph Types", easyClose = TRUE)
-
- # Ensures the files imported for analysis are Excel files
- observeEvent(input$files, {
- validFile <- FALSE
-
- for (file in input$files) {
- if (file_ext(file) =="xlsx" | file_ext(file) =="xls") {
- validFile <- TRUE
- }
- }
-
- if (validFile) {
- renderTable()
- } else {
- shinyalert("That isn't right...","Please upload an Excel file.","error")
- }
- })
-
- observeEvent(input$chooseDir, {
- chosenDir = tk_choose.dir()
- dirLocation(chosenDir)
-
- if (!is.na(dirLocation())) {
- output$currDir <- renderText({paste(split_path(dirLocation())[1], "(", split_path(dirLocation())[2], ")")})
- }
- })
-
- graphbuilder <- modalDialog({
- fluidPage(
- useShinyjs(),
- useShinyalert(),
-
- tags$head(tags$style(".modal-dialog{width:80%}")),
- tags$head(tags$style(".modal-body{ min-height:1000px}")),
-
- sidebarLayout(
-
- sidebarPanel(
- fluidRow(
- headerPanel("Graph Options"),
- ),
-
- fluidRow(style = "padding:5%; border: 1px solid black;",
- strong("Basis for Plot Types"), tags$br(),
- helpText("Between Analysis requires a second dataset to be imported"), tags$br(),
- radioButtons("perType", NULL, choices = c("Within Analysis", "Between Analyses"), inline = TRUE),
- hidden(fileInput("compAnalysis", "Data to Compare"))
- ),
-
- fluidRow(style ="padding:5%; margin:5%;",
- radioButtons("typeGraph","Graph Type:", choices = c("dQdV Graphs","Voltage Profiles", "Voltage vs. Time",
- "Charge Voltage", "Discharge Voltage",
- "Average Voltage", "Delta Voltage", "Discharge Capacity", "Charge Capacity" ), inline = FALSE),
- radioButtons("plotStyle","Plot Style:", choiceNames = c("Point","Line","Both"), choiceValues = c("p","l","o"), inline = TRUE),
- checkboxGroupInput("cells","Cell to Analyze:", choices = 1, inline = FALSE),
- selectInput("renderCycles","Cycles of Interest:", choices = 1, multiple = TRUE),
- ),
-
- fluidRow(
- strong("Click to show coordinates:"), tags$br(), tags$br(),
- "X: ",
- textOutput("hoverCoordx", inline = TRUE), tags$br(),
- "Y: ",
- textOutput("hoverCoordy", inline = TRUE),
- style ="border: 1px solid black; padding: 5%; margin: 5%;"
- ),
-
- fluidRow(
- textInput("fileName","Name of graph file:"),
- actionButton("saveGraph","Save Graph", width = '100%', class = 'btn-primary'),
- style ="border: 4px double black; padding: 5%; margin: 5%;"
- ),
- ),
-
- mainPanel(
- fluidRow(
- plotOutput("outputPlot", height ="800px", click = "plot_click"),
- style = "padding: 5%;",
- ),
- fluidRow(
- h3("Graph Formatting"),
- helpText("*If left blank, they will be calculated using the min and max of the data to be plotted."),
- column(2,
- numericInput("xMin", "X Min", value = NULL),
- sliderInput("textSize", "Text Size", min = 0.1, max = 5, value = 1, ticks = FALSE),
- ),
- column(2,
- numericInput("xMax", "X Max", value = NULL),
- sliderInput("pointSize", "Point/Line Size", min = 0.1, max = 5, value = 1, ticks = FALSE),
- ),
- column(2,
- numericInput("yMin", "Y Min", value = NULL),
- ),
- column(2,
- numericInput("yMax", "Y Max", value = NULL),
- ),
- column(4,
- textInput("originalData", "Original Data Name", value = "Original Data"),
- textInput("compareData", "Comparison Data Name", value = "Comparison Data"),
- ),
- style ="border: 1px dashed black; padding: 2%;",
- )
- )
- )
- )
- }, size ="l", title ="Post-Processing Graph Builder")
-
- # Method for importing the previous R environment
- observeEvent(input$load, {
- if (is.null(input$rerun)) {
- shinyalert("Uh oh!", "It appears you haven't selected a .RData file to import.", "error")
- } else {
- load(input$rerun$datapath[[1]])
-
- validFile <- FALSE
-
- if (file_ext(input$rerun$datapath) =="RData") {
- validFile <- TRUE
- }
-
- if (validFile) {
- data <<- filter(data, grepl('Channel', sheet))
- dirLocation(dirLocation())
- numCycles <<- numCycles
- dQdVData <<- dQdVData
- total <<- total
- cycle_facts <<- cycle_facts
-
- output$channels <- renderDataTable(data, editable = FALSE, options=list(columnDefs = list(list(visible=FALSE, targets=c(4)))),
- colnames = c("File","Sheet","Mass (g)","Filepath","Limiting Electrode Area (cm^2)"))
-
- enable("graphBuilder")
- } else {
- shinyalert("That isn't right...","Please upload an RData file.","error")
- }
- }
- })
-
- # After the validation of the Arbin files, they macros (file name, and sheets) are taken and rendered in to a datatable
- renderTable <- function() {
- output$channels <- renderDataTable({
- files <- input$files
-
- if (is.null(files)) {
- return(NULL)
- }
-
- file_sheet <- data.frame()
- for (i in 1:nrow(files)) {
- sheets <- excel_sheets(files[i, 4])
- file_sheet <- rbind(file_sheet, data.frame(name = rep(files[["name"]][i], length(sheets)),"sheet" = sheets,"Mass" = rep(0, length(sheets)),
- datapath = rep(files[["datapath"]][i], length(sheets)), area = rep(input$area, length(sheets))))
- }
-
- data <<- filter(file_sheet, grepl('Channel', sheet) & !grepl('Chart', sheet))
-
- data
-
- }, editable = FALSE, options=list(columnDefs = list(list(visible=FALSE, targets=c(4)))),
- colnames = c("File","Sheet","Mass (g)","Filepath","Limiting Electrode Area (cm^2)"))
- }
-
- observeEvent(input$whatGraph, {
- showModal(graphModal)
- })
-
- # Data validation the masses imported from Excel, if valid they are placed into the datatable
- observeEvent(input$excelImport, {
- if (length(names(data)) <= 1) {
- shinyalert("Uh oh!","You need to import cells first!","error")
- removeModal()
- } else {
- tryCatch({
- masses <- lapply(strsplit(strRep(input$masses, "\n", ","), ",", fixed = TRUE), as.double)
- names(masses)[names(masses) =="V1"] <-"Mass"
- data$Mass <<- masses[[1]]
- }, error = function(cond) {
- print(cond)
- shinyalert("Something isn't right...","The number of masses imported did not match the amount of cells present or the text contained some special characters. Please try again.","error")
- removeModal()
- }, finally = {
- proxy = dataTableProxy("channels")
- replaceData(proxy, data)
-
- renderDataTable(data)
-
- removeModal()
- })
- }
- })
-
- # After some data validation, the main analysis is run on click of the"Run Analysis" button
- observeEvent(input$submit, {
- if (length(names(data)) <= 1) {
- shinyalert("Uh oh!", "You need to import cells first!", "error")
- } else if (is.na(dirLocation()) | dirLocation() == "") {
- shinyalert("Uh oh!", "You need to enter a directory name first!", "error")
- } else if (input$dirName == "") {
- shinyalert("Uh oh!", "You need to enter an analysis name first!", "error")
- } else if (sum(data$Mass) == 0) {
- shinyalert("Uh oh!", "You have not entered any masses. Do you wish to continue?",
- type ="warning", showConfirmButton = TRUE, showCancelButton = TRUE, confirmButtonText = "Continue", cancelButtonText = "Abort",
- callbackR = function(x) {
- if (x) {
- runscript()
- }
- }
- )
- } else {
- runscript()
- }
- })
-
- # This function responsible for analysis of the
- runscript <- function() {
-
- # Sets up a progress bar in which to estimate how long the execution of the code will take
- progress <- Progress$new(session, min = 0, max = nrow(data))
- progress$set(message ="Plugging and chugging...\n", detail ="Starting up...")
-
- # Closes all graphics devices that may be lingering (prevents an excess from opening and slowing down the analysis)
- while (dev.cur() != 1) {
- dev.off()
- }
-
- # Resets the variables for the graph builder so new results are concatenated to old ones
- numCycles <<- data.frame()
- dQdVData <<- data.frame()
- total <<- data.frame()
- cycle_facts <<- data.frame()
-
- # Disable all input fields to prevent errors occurring from changing values
- disable("files")
- disable("lowV")
- disable("highV")
- disable("dirLocation()")
- disable("submit")
- disable("excelImport")
- disable("gGraphs")
- disable("peakFit")
- disable("area")
- disable("perActive")
- disable("capActive")
-
- # Creates the directory in which all data will be stored
- dir.create(paste(dirLocation(), input$dirName, sep = "/"))
-
- # Update the status once all set-up functions are complete
- progress$set(detail ="Starting first cell...")
-
- # ######
- #
- # The bulk of the analysis occurs within the loop. Each iteratin of the loop corresponds to a cell.
- #
- # ######
- for (row in 1:nrow(data)) {
-
- # ######
- #
- # This is where all code that should be executed on a"per cell" basis, to prepare for analysis
- #
- # ######
-
- # Import the excel sheet corresponding to cell of interest
- tmp_excel <- read_excel(toString(data$datapath[row]), toString(data$sheet[row]))
-
- # Create an nested directory for all the data and, if applicable, then further folders for graphs of interest
- dir.create(paste(dirLocation(), "/", input$dirName, data$sheet[row], sep ="/"))
- if (is.element("dQdV Graphs", input$gGraphs)) dir.create(paste(dirLocation(), input$dirName, data$sheet[row],"dQdV Plots", sep ="/"))
- if (is.element("Voltage Profiles", input$gGraphs)) dir.create(paste(dirLocation(), input$dirName, data$sheet[row],"Voltage Profiles", sep ="/"))
- if (is.element("Voltage vs. Time", input$gGraphs)) dir.create(paste(dirLocation(), input$dirName, data$sheet[row],"Voltage v Time", sep ="/"))
-
- # Check if masses have been imported, if they have not then all future calculations will be done on a raw capacity basis
- if (sum(data$Mass) != 0) {
- ylabel <-"Capacity (mAh/g)"
-
- tmp_excel$Q.d <- as.numeric(tmp_excel$`Discharge_Capacity(Ah)` * (1000 / data$Mass[row]))
- tmp_excel$Q.c <- as.numeric(tmp_excel$`Charge_Capacity(Ah)`* (1000 / data$Mass[row]))
-
- tmp_excel$CC <- tmp_excel$Q.d - tmp_excel$Q.c
- tmp_excel$CE <- (tmp_excel$Q.d / tmp_excel$Q.c) * 100
- } else {
- ylabel <-"Capacity (Ah)"
-
- tmp_excel$CC <- tmp_excel$`Discharge_Capacity(Ah)` - tmp_excel$`Charge_Capacity(Ah)`
- tmp_excel$CE <- (tmp_excel$`Discharge_Capacity(Ah)` / tmp_excel$`Charge_Capacity(Ah)`) * 100
- }
- tmp_excel$Cell <- row
- tmp_excel$CE[is.infinite(tmp_excel$CE)|is.nan(tmp_excel$CE)|tmp_excel$CE > 200] <- 0;
-
- # ######
- #
- # This loop iterates through each cycle of the cell.
- #
- # ######
- cycles <- split(tmp_excel, tmp_excel$Cycle_Index)
- prev_c <- 0
- lastCC <- 0
- ch_dch <- TRUE
- durations <- vector(length = 4)
- caps <- vector(length = 4)
- prev <- TRUE
- dchV <- 0
- chV <- 0
- i <- 1
- for (cycle in cycles) {
-
- # ######
- #
- # Within each cycle, take out the individual steps. These include the charge, discharge, and others.
- #
- # ######
-
- progress$set(detail = paste("Analyzing cell", row,", cycle", i))
-
- steps <- split(cycle, cycle$Step_Index)
- n <- 1
-
- for (step in steps) {
-
- # ######
- #
- # Isolation of the charge and discharge cycles. The algorithm is as follows:
- #
- # If the change in voltage for the step is greater than 0.5V, it is a charge or dicharge cycle. Then, the direction (sign) of the current determines
- # if it is charge or discharge (positive current = charge step, negative current is a discharge cycle).
- #
- # ######
- if (abs(tail(step$'Voltage(V)',1) - step$'Voltage(V)'[[1]]) > 0.5) {
-
- # ######
- #
- # All code that should be executed for every charge/discharge cycles should be written here.
- #
- # ######
- lastCC <- n
- if (step$'Current(A)'[[1]] > 0) {
- chV <- (1 / (tail(step$`Charge_Capacity(Ah)`,1) - step$`Charge_Capacity(Ah)`[[1]])) * trapz(step$`Charge_Capacity(Ah)`, step$`Voltage(V)`)
- dQCdV <- diff(step$`Charge_Capacity(Ah)`)/diff(step$`Voltage(V)`)
- dQdVData <<- rbind(dQdVData, data.frame(cycle=rep(i, length(dQCdV)+1), cell = rep(row, length(dQCdV)+1), c_d=rep(0, length(dQCdV)+1), voltage=step$`Voltage(V)`, dQdV=c(0, dQCdV), F_L=rep(0,length(dQCdV)+1)))
-
- durations[1] <- tail(step$'Test_Time(s)', 1) - step$'Test_Time(s)'[[1]]
- caps[1] <- tail(step$'Charge_Capacity(Ah)', 1) - step$'Charge_Capacity(Ah)'[[1]]
- ch_dch <- TRUE
- } else {
- dchV <- (1 / (tail(step$`Discharge_Capacity(Ah)`,1) - step$`Discharge_Capacity(Ah)`[[1]])) * trapz(step$`Discharge_Capacity(Ah)`, step$`Voltage(V)`)
- dQDdV <- diff(step$`Discharge_Capacity(Ah)`)/diff(step$`Voltage(V)`)
-
- durations[3] <- tail(step$'Test_Time(s)', 1) - step$'Test_Time(s)'[[1]]
- caps[3] <- tail(step$'Discharge_Capacity(Ah)', 1) - step$'Discharge_Capacity(Ah)'[[1]]
- ch_dch <- FALSE
- if (abs(prev_c - step$`Current(A)`[[1]]) > 0.0005) {
- dQdVData <<- rbind(dQdVData, data.frame(cycle=rep(i, length(dQDdV)+1), cell = rep(row, length(dQDdV)+1), c_d=rep(1, length(dQDdV)+1), voltage=step$`Voltage(V)`, dQdV=c(0, dQDdV), F_L=rep(1,length(dQDdV)+1)))
- prev_c = step$`Current(A)`[[1]]
- } else {
- dQdVData <<- rbind(dQdVData, data.frame(cycle=rep(i, length(dQDdV)+1), cell = rep(row, length(dQDdV)+1), c_d=rep(1, length(dQDdV)+1), voltage=step$`Voltage(V)`, dQdV=c(0, dQDdV), F_L=rep(0, length(dQDdV)+1)))
- }
- }
- } else if (n - lastCC == 1 & abs(tail(step$'Voltage(V)',1) - step$'Voltage(V)'[[1]]) < 0.001) {
- if (step$'Current(A)'[[1]] > 0) {
- durations[2] <- tail(step$'Test_Time(s)', 1) - step$'Test_Time(s)'[[1]]
- caps[2] <- tail(step$'Charge_Capacity(Ah)', 1) - step$'Charge_Capacity(Ah)'[[1]]
- } else {
- durations[4] <- tail(step$'Test_Time(s)', 1) - step$'Test_Time(s)'[[1]]
- caps[4] <- tail(step$'Discharge_Capacity(Ah)', 1) - step$'Discharge_Capacity(Ah)'[[1]]
- }
- }
- ch_dch <- FALSE
- n <- n + 1
- }
-
- # ######
- #
- # Code meant to be run on data"per cycle" should be written here
- #
- # ######
-
- dQdVData <<- dQdVData[is.finite(dQdVData$voltage),]
- dQdVData <<- dQdVData[is.finite(dQdVData$dQdV),]
-
- if (sum(data$Mass) != 0) {
- DCap <- tail(cycle$Q.d, 1)
- CCap <- tail(cycle$Q.c, 1)
- } else {
- DCap <- tail(cycle$`Discharge_Capacity(Ah)`, 1)
- CCap <- tail(cycle$`Charge_Capacity(Ah)`, 1)
- }
-
- timeCVFracCh <- durations[1] / (durations[1] + durations[2])
- timeCVFracDch <- durations[3] / (durations[3] + durations[4])
- capCVFracCh <- caps[1] / (caps[1] + caps[2])
- capCVFracDch <- caps[3] / (caps[3] + caps[4])
-
- # Record charge and discharge voltage, then calculate the delta and average voltage
- cycle_facts <<- rbind(cycle_facts, data.frame(cycle=i, cell=row, chV=chV, dchV=dchV, avgV=(dchV + chV) / 2,
- dV=chV-dchV, DCap = DCap, CCap = CCap, CE = (CCap / DCap) * 100, lostCap = CCap - DCap, cellFade = if (i == 1) 0 else {DCap - tail(cycle_facts$DCap, 1)},
- cycleTime = tail(cycle$`Test_Time(s)`, 1) - cycle$`Test_Time(s)`[[1]], timeCVFracCh = timeCVFracCh, timeCVFracDch = timeCVFracDch,
- capCVFracCh = capCVFracCh, capCVRatioDch = capCVFracDch))
-
- i <- i + 1
- }
-
- # ######
- #
- # Code meant to be run on data"per cell" should be written here
- #
- # ######
-
- cell_data <- cycle_facts[cycle_facts$cell == row,]
-
- # Discharge capacity plotting, with coulombic efficiency being plotted alongside
- if (is.element("Discharge Capacity", input$gGraphs)) {
- png(paste(dirLocation(), "/", input$dirName,"/", data$sheet[row],"/", data$sheet[row]," Discharge Capacity Plot.png", sep =""))
- eol <- cell_data$`DCap`[[1]] * 0.8
- plot(cell_data$cycle, cell_data$DCap, type ="p", main=paste("Discharge Capacity for", input$dirName), xlab=NA, ylab=paste("Discharge", ylabel), mai=c(1,1,1,1))
- abline(h=eol, lty ="dotted")
- par(new = T)
- plot(cell_data$cycle, cell_data$CE, type ="p", axes=F, col ="red", ylab=NA, xlab="Cycle", ylim = c(0, 105))
- mtext(side = 4, line = 3,"Coulombic Efficiency (%)", col = "red")
- axis(side = 4, col ="red", col.axis = "red")
- dev.off()
- }
-
- # Discharge areal capacity plotting, with coulombic efficiency being plotted alongside
- if (is.element("Discharge Areal Capacity", input$gGraphs)) {
- png(paste(dirLocation(), "/", input$dirName,"/", data$sheet[row],"/", data$sheet[row]," Discharge Areal Capacity Plot.png", sep =""))
- new_par <- old_par <- par("mar")
- new_par[4] <- old_par[2]
- par(mar = new_par)
- eol <- ((cell_data$DCap[[1]] * 1000) / data$area[row]) * 0.8
- plot(cell_data$cycle, ((cell_data$DCap * 1000) / data$area[row]), type ="p", main=paste("Discharge Areal Capacity for", input$dirName), xlab=NA, ylab="Discharge Capacity (mAh/cm^2)", mai = c(1,1,1,2))
- abline(h=eol, lty ="dotted")
- par(new = T)
- plot(cell_data$cycle, cell_data$CE, type ="p", axes=F, col ="red", ylab=NA, xlab="Cycle", ylim = c(0, 105))
- mtext(side = 4, line = 3,"Coulombic Efficiency (%)", col = "red")
- axis(side = 4, col ="red", col.axis = "red")
- dev.off()
- }
-
-
- # Average voltage plotting
- if (is.element("Average Voltage", input$gGraphs)) {
- png(paste(dirLocation(), "/", input$dirName,"/", data$sheet[row],"/", data$sheet[row]," Average Voltage Plot.png", sep =""))
- plot(cell_data$cycle, cell_data$chV, col="blue", main=paste("Average Voltage Plot for", input$dirname, data$sheet[row]), xlab="Cycle", ylab="Voltage (V)", ylim=c(min(cell_data[,2:4]), max(cell_data[,2:4])))
- points(cell_data$cycle, cell_data$dchV, col="red", main=paste("Average Voltage Plot for", input$dirName, data$sheet[row]), xlab="Cycle", ylab="Voltage (V)")
- points(cell_data$cycle, cell_data$avgV, col="black", main=paste("Average Voltage Plot for", input$dirName, data$sheet[row]), xlab="Cycle", ylab="Voltage (V)")
- legend("bottomright", c("Charge Voltage","Discharge Voltage","Average Voltage"), col=c("blue","red","black"), pch=19)
- dev.off()
- }
-
- # Delta voltage plotting
- if (is.element("Delta Voltage", input$gGraphs)) {
- png(paste(dirLocation(), "/", input$dirName,"/", data$sheet[row],"/", data$sheet[row]," Delta Voltage Plot.png", sep =""))
- plot(cell_data$cycle, cell_data$dV, main=paste("Delta Voltage Plot for", input$dirName, data$sheet[row]), xlab="Cycle", ylab="Voltage (V)", ylim =c(0, 0.5))
- dev.off()
- }
-
- # Capacity Loss plotting
- if (is.element("Capacity Loss", input$gGraphs)) {
- png(paste(dirLocation(), "/", input$dirName,"/", data$sheet[row],"/", data$sheet[row]," Capacity Loss Plot.png", sep =""))
- plot(cell_data$cycle, cell_data$lostCap, main=paste("Capacity Loss Plot for", input$dirName, data$sheet[row]), xlab="Cycle", ylab= ylabel, ylim = c(mean(cell_data$lostCap) + (2* sd(cell_data$lostCap)), mean(cell_data$lostCap) - (1.5* sd(cell_data$lostCap))))
- abline(h=median(cell_data$lostCap), lty="dotted")
- dev.off()
- }
-
- if (is.element("dQdV Plots", input$gAnim)) {
- dQdVplot <- function(){
- tmp_data <- dQdVData[dQdVData$cell == row,]
- first_cycle <- dQdVData[dQdVData$cell == row & dQdVData$cycle == 2,]
- datalist <- split(tmp_data, tmp_data$cycle)
- lapply(datalist, function(plotData){
- p <- plot(plotData$voltage, plotData$dQdV, main=paste("dQdV Plot for", input$dirName, data$sheet[row], "Cycle", plotData$cycle[[1]]), xlab="Voltage (V)", ylab= "dQdV (Ah/V)",
- xlim = c(min(tmp_data$voltage), max(tmp_data$voltage)), ylim = c(min(tmp_data$dQdV), max(tmp_data$dQdV))) +
- points(first_cycle$voltage, first_cycle$dQdV, col = rgb(red = 1, green = 0, blue = 0, alpha = 0.5))
- })
- }
- save_gif(dQdVplot(), paste(dirLocation(), input$dirName, data$sheet[row], "dQdV Animation.gif", sep = "/"), delay = 0.2)
- }
-
- if (is.element("Voltage Profiles", input$gAnim)) {
- vpPlot <- function(){
- first_cycle <- tmp_excel[tmp_excel$`Cycle_Index` == 2,]
- datalist <- split(tmp_excel, tmp_excel$`Cycle_Index`)
- lapply(datalist, function(plotData){
- p <- plot(plotData$CC, plotData$`Voltage(V)`, main=paste("Voltage Profile for", input$dirName, data$sheet[row], "Cycle", plotData$`Cycle_Index`[[1]]), xlab=ylabel, ylab= "Voltage (V)",
- xlim = c(min(tmp_excel$CC), max(tmp_excel$CC)), ylim = c(min(tmp_excel$`Voltage(V)`), max(tmp_excel$`Voltage(V)`))) +
- points(first_cycle$CC, first_cycle$`Voltage(V)`, col = rgb(red = 1, green = 0, blue = 0, alpha = 0.5))
- })
- }
- save_gif(vpPlot(), paste(dirLocation(), input$dirName, data$sheet[row], "Voltage Profile Animation.gif", sep = "/"), delay = 0.2)
- }
-
- # Save all data within the cell's directory
- write.csv(tmp_excel, file = paste(dirLocation(), "/", input$dirName,"/", data$sheet[row],"/", data$sheet[row],".csv", sep =""))
-
- # Append summation data to the larger datasets to be worked with later
- final <- rbind(final, tmp_excel)
- numCycles <<- rbind(numCycles, data.frame(sheet=data$sheet[row], cycles=nrow(cell_data)))
-
- # Update progress bar
- progress$set(value = row, detail = paste("Finished", row," of", nrow(data)," cells."))
- }
-
- # ######
- #
- # Code meant to be run on all data of all cells should be written here.
- #
- # ######
-
- # With iterations complete, final calculations are being worked
- progress$set(detail ="Wrapping up...")
-
- # Get the last status of each cycle for each cell (namely capacity)
- DCap <- cycle_facts[c("cycle","DCap")] %>% group_by(cycle) %>% summarise_each(mean)
- CE <- cycle_facts[c("cycle","CE")] %>% group_by(cycle) %>% summarise_each(mean)
- capSEs <- cycle_facts[c("cycle","DCap")] %>% group_by(cycle) %>% summarise_each(se)
- ceSEs <- cycle_facts[c("cycle","CE")] %>% group_by(cycle) %>% summarise_each(se)
- stats <- data.frame(cbind(cycle = capSEs$cycle, DCap = DCap$DCap, CE = CE$CE, capSE = capSEs$DCap, ceSE = ceSEs$CE))
-
- # Send all the data to a global variable to be used elsewhere
- total <<- final
-
- tryCatch({
- # Total dishcharge capacity plotting
- if (is.element("Total Discharge Capacity", input$gGraphs)) {
- png(paste(dirLocation(), "/", input$dirName,"/", "Total Discharge Capacity Plot.png", sep =""))
- eol <- max(stats$DCap) * 0.8
- plot(stats$cycle, stats$DCap, type ="p", main=paste("Discharge Capacity for", input$dirName), xlab=NA, ylab=paste("Discharge", ylabel), mai=c(1,1,1,1))
- arrows(stats$cycle, stats$DCap - stats$capSE, stats$cycle, stats$DCap + stats$capSE, length=0.05, angle=90, code=3)
- abline(h=eol, lty ="dotted")
- par(new = T)
- plot(stats$cycle, stats$CE, type ="p", axes=F, col ="red", ylab=NA, xlab="Cycle", ylim = c(0, 105))
- arrows(stats$cycle, stats$CE - stats$ceSE, stats$cycle, stats$CE + stats$ceSE, length=0.05, angle=90, code=3, col ="red")
- axis(side = 4, col ="red")
- mtext(side = 4, line = 2,"Coulombic Efficiency (%)")
- dev.off()
- }
- }, error = function(cond) {
- print(cond)
- })
-
- # Save total data and stats
- write.csv(stats, file = paste(dirLocation(), "/", input$dirName,"/", basename(dirLocation())," Summary.csv", sep =""))
- write.csv(final, file = paste(dirLocation(), "/", input$dirName,"/", basename(dirLocation())," Total.csv", sep =""))
- write.csv(dQdVData, file = paste(dirLocation(), "/", input$dirName,"/", basename(dirLocation())," dQdV Data.csv", sep =""))
- write.csv(cycle_facts, file = paste(dirLocation(), "/", input$dirName,"/", basename(dirLocation())," Cycle Facts.csv", sep =""))
-
- # If a histor directory does not exist, create it. Save all the data revelant to plotting to a RData file.
- if (!dir.exists(paste(dirLocation(), "history", sep = "/"))) {
- dir.create(paste(dirLocation(), "history", sep = "/"))
- }
-
- dirName <<- input$dirName
-
- save(dirLocation, dirName, data, dQdVData, total, cycle_facts, numCycles, file = paste(dirLocation(), "/history/", input$dirName, ".RData", sep = ""))
-
- # Modal for completed analysis
- shinyalert("Analysis Complete!", paste("All your data are now in ", dirLocation(), "/", input$dirName, sep = ""),
- type ="success", showConfirmButton = TRUE, showCancelButton = TRUE, confirmButtonText = "Generate Origin File", cancelButtonText = "Continue",
- callbackR = function(x) {
- if (x) {
- export_to_origin()
- }
- }
- )
-
- # Finish progress bar
- progress$set(value = nrow(data))
-
- # Re-enable all input fields, including graph builder
- enable("files")
- enable("lowV")
- enable("highV")
- enable("dirLocation()")
- enable("submit")
- enable("excelImport")
- enable("gGraphs")
- enable("peakFit")
- enable("area")
- enable("perActive")
- enable("capActive")
- enable("graphBuilder")
-
- # Close progress bar
- progress$close()
- }
-
- # Enable/Disable input field based on desired grph selection
- observeEvent(input$gGraphs, {
- disable("area")
- disable("perActive")
- disable("capActive")
-
- choices <- c("dQdV Graphs","Voltage Profiles","Voltage vs. Time","Discharge Capacity","Discharge Areal Capacity",
- "Total Discharge Capacity","Average Voltage","Delta Voltage")
-
- if (is.element("Discharge Areal Capacity", input$gGraphs)) {
- enable("area")
- }
- })
-
- # ######
- #
- # Graph Builder Processing
- #
- # ######
- output$outputPlot <- renderPlot({
-
- tmp_data <<- data.frame()
- normalTime <<- data.frame()
-
- bounds <<- c(input$xMin, input$xMax, input$yMin, input$yMax)
-
- # Define function to normalize Voltage vs. Time plots
- normalizeTime <- function(x) {
- return(x - x[[1]])
- }
-
- # ######
- #
- # Switch statements defining the bulk of the processing, depending on the desired graph
- #
- # ######
- if (input$perType =="Within Analysis") {
- sheetName <<- TRUE
-
- # Get the indicies in which the desired cells are in the data frame containing the number of cycles
- cellIndex <- match(input$cells, numCycles$sheet)
-
- switch(input$typeGraph,
- "dQdV Graphs" = {
- tmp_data <<- data.frame(x=dQdVData[dQdVData$cell %in% cellIndex,]$voltage, y=dQdVData[dQdVData$cell %in% cellIndex,]$dQdV, cycle=dQdVData[dQdVData$cell %in% cellIndex,]$cycle, cell=dQdVData[dQdVData$cell %in% cellIndex,]$cell)
- tmp_data <<- tmp_data[tmp_data$cycle == sort(as.numeric(input$renderCycles)),]
-
- titleLabel <<-"dQdV Plot"
- xlabel <<-"Voltage (V)"
- ylabel <<-"dQdV (mAh/V)"
- },
- "Voltage Profiles" = {
- tmp_data <<- data.frame(x=(-1) * total[total$Cell %in% cellIndex,]$CC, y=total[total$Cell %in% cellIndex,]$`Voltage(V)`, cycle=total[total$Cell %in% cellIndex,]$`Cycle_Index`, cell=total[total$Cell %in% cellIndex,]$Cell)
- tmp_data <<- tmp_data[tmp_data$cycle == sort(as.numeric(input$renderCycles)),]
-
- titleLabel <<-"Voltage Profile"
- if (sum(data$Mass) != 0) {
- xlabel <-"Continuous Capacity (mAh/g)"
- } else {
- xlabel <-"Continuous Capacity (Ah)"
- }
- ylabel <<-"Voltage (V)"
- },
- "Voltage vs. Time" = {
- tmp_data <<- data.frame(x=(total[total$Cell %in% cellIndex,]$`Test_Time(s)` / 60), y=total[total$Cell %in% cellIndex,]$`Voltage(V)`, cycle=total[total$Cell %in% cellIndex,]$`Cycle_Index`, cell=total[total$Cell %in% cellIndex,]$Cell)
- tmp_data <<- tmp_data[tmp_data$cycle %in% input$renderCycles,]
-
- x <- 0
-
- for (cell in cellIndex) {
- normalTime <<- c(normalTime, t(aggregate(tmp_data[tmp_data$cell == cell,]$x, by=list(tmp_data[tmp_data$cell == cell,]$cycle), normalizeTime)[,2]))
- }
-
- tmp_data <<- data.frame(x=unlist(normalTime), y=tmp_data$y, cycle=tmp_data$cycle, cell=tmp_data$cell)
- tmp_data <<- tmp_data[tmp_data$y >= 0.01,]
-
- titleLabel <<-"Voltge vs. Time Plot"
- xlabel <<-"Time (min)"
- ylabel <<-"Voltage (V)"
- },
- "Charge Voltage" = {
- tmp_data <<- data.frame(x=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle, y=cycle_facts[cycle_facts$cell %in% cellIndex,]$chV, cycle=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle, cell = cycle_facts[cycle_facts$cell %in% cellIndex,]$cell)
-
- titleLabel <<- "Charge Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- "Discharge Voltage" = {
- tmp_data <<- data.frame(x=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle, y=cycle_facts[cycle_facts$cell %in% cellIndex,]$dchV, cell=cycle_facts[cycle_facts$cell %in% cellIndex,]$cell, cycle=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle)
-
- titleLabel <<- "Discharge Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- "Average Voltage" = {
- tmp_data <<- data.frame(x=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle, y=cycle_facts[cycle_facts$cell %in% cellIndex,]$avgV, cell=cycle_facts[cycle_facts$cell %in% cellIndex,]$cell, cycle=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle)
-
- titleLabel <<- "Average Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- "Delta Voltage" = {
- tmp_data <<- data.frame(x=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle, y=cycle_facts[cycle_facts$cell %in% cellIndex,]$dV, cell=cycle_facts[cycle_facts$cell %in% cellIndex,]$cell, cycle=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle)
-
- titleLabel <<- "Delta Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- "Discharge Capacity" = {
- tmp_data <<- data.frame(x=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle, y=cycle_facts[cycle_facts$cell %in% cellIndex,]$DCap, cell=cycle_facts[cycle_facts$cell %in% cellIndex,]$cell, cycle=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle)
-
- titleLabel <<- "Discharge Capacity Plot "
- xlabel <<- "Cycle"
- if (sum(data$Mass) != 0) {
- ylabel <<- "Discharge Capacity (mAh/g)"
- } else {
- ylabel <<- "Discharge Capacity (Ah)"
- }
- },
- "Charge Capacity" = {
- tmp_data <<- data.frame(x=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle, y=cycle_facts[cycle_facts$cell %in% cellIndex,]$CCap, cell=cycle_facts[cycle_facts$cell %in% cellIndex,]$cell, cycle=cycle_facts[cycle_facts$cell %in% cellIndex,]$cycle)
-
- titleLabel <<- "Charge Capacity Plot "
- xlabel <<- "Cycle"
- if (sum(data$Mass) != 0) {
- ylabel <<- "Charge Capacity (mAh/g)"
- } else {
- ylabel <<- "Charge Capacity (Ah)"
- }
- }
- )
-
- tmp_data$color <<- sapply(tmp_data$cycle, function(x) {match(x, input$renderCycles, nomatch = 1)})
- tmp_data$symbol <<- sapply(tmp_data$cell, function(x) {match(x, cellIndex)})
-
- } else if (input$perType == "Between Analyses") {
-
- switch(input$typeGraph,
- "Charge Voltage" = {
- x<-0
- chV <- cycle_facts[c("cycle","chV")] %>% group_by(cycle) %>% summarise_each(mean)
- chVSE <- cycle_facts[c("cycle","chV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tryCatch({
- comp_chV <- compCycleFacts[c("cycle","chV")] %>% group_by(cycle) %>% summarise_each(mean)
- comp_chVSE <- compCycleFacts[c("cycle","chV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tmp_data <<- data.frame(x=c(chV$cycle, comp_chV$cycle), y=c(chV$chV, comp_chV$chV), se=c(chVSE$chV, comp_chVSE$chV), cell=c(rep(1, length(chV$cycle)), rep(2, length(comp_chV$cycle))), cycle=c(chV$cycle, comp_chV$cycle))
- tmp_data$symbol <<- rep(1, nrow(tmp_data))
- tmp_data$color <<- sapply(tmp_data$cell, function(x) {match(x, c(1,2))})
-
- titleLabel <<- "Charge Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- error = function(x) {
- print(x)
- })
- },
- "Discharge Voltage" = {
- x<-0
- dchV <- cycle_facts[c("cycle","dchV")] %>% group_by(cycle) %>% summarise_each(mean)
- dchVSE <- cycle_facts[c("cycle","dchV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tryCatch({
- comp_dchV <- compCycleFacts[c("cycle","dchV")] %>% group_by(cycle) %>% summarise_each(mean)
- comp_dchVSE <- compCycleFacts[c("cycle","dchV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tmp_data <<- data.frame(x=c(dchV$cycle, comp_dchV$cycle), y=c(dchV$dchV, comp_dchV$dchV), se=c(dchVSE$dchV, comp_dchVSE$dchV), cell=c(rep(1, length(dchV$cycle)), rep(2, length(comp_dchV$cycle))), cycle=c(dchV$cycle, comp_dchV$cycle))
- tmp_data$symbol <<- rep(1, nrow(tmp_data))
- tmp_data$color <<- sapply(tmp_data$cell, function(x) {match(x, c(1,2))})
-
- titleLabel <<- "Disharge Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- error = function(x) {
- print(x)
- })
- },
- "Average Voltage" = {
- avgV <- cycle_facts[c("cycle","avgV")] %>% group_by(cycle) %>% summarise_each(mean)
- avgVSE <- cycle_facts[c("cycle","avgV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tryCatch({
- comp_avgV <- compCycleFacts[c("cycle","avgV")] %>% group_by(cycle) %>% summarise_each(mean)
- comp_avgVSE <- compCycleFacts[c("cycle","avgV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tmp_data <<- data.frame(x=c(avgV$cycle, comp_avgV$cycle), y=c(avgV$avgV, comp_avgV$avgV), se=c(avgVSE$avgV, comp_avgVSE$avgV), cell=c(rep(1, length(avgV$cycle)), rep(2, length(comp_avgV$cycle))), cycle=c(avgV$cycle, comp_avgV$cycle))
- tmp_data$symbol <<- rep(1, nrow(tmp_data))
- tmp_data$color <<- sapply(tmp_data$cell, function(x) {match(x, c(1,2))})
-
- titleLabel <<- "Average Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- error = function(x) {
- print(x)
- })
- },
- "Delta Voltage" = {
- dV <- cycle_facts[c("cycle","dV")] %>% group_by(cycle) %>% summarise_each(mean)
- dVSE <- cycle_facts[c("cycle","dV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tryCatch({
- comp_dV <- compCycleFacts[c("cycle","dV")] %>% group_by(cycle) %>% summarise_each(mean)
- comp_dVSE <- compCycleFacts[c("cycle","dV")] %>% group_by(cycle) %>% summarise_each(se)
-
- tmp_data <<- data.frame(x=c(dV$cycle, comp_dV$cycle), y=c(dV$dV, comp_dV$dV), se=c(dVSE$dV, comp_dVSE$dV), cell=c(rep(1, length(dV$cycle)), rep(2, length(comp_dV$cycle))), cycle=c(dV$cycle, comp_dV$cycle))
- tmp_data$symbol <<- rep(1, nrow(tmp_data))
- tmp_data$color <<- sapply(tmp_data$cell, function(x) {match(x, c(1,2))})
-
- titleLabel <<- "Delta Voltage Plot "
- xlabel <<- "Cycle"
- ylabel <<- "Voltage (V)"
- },
- error = function(x) {
- print(x)
- })
- },
- "Discharge Capacity" = {
- DCap <- cycle_facts[c("cycle","DCap")] %>% group_by(cycle) %>% summarise_each(mean)
- DCapSE <- cycle_facts[c("cycle","DCap")] %>% group_by(cycle) %>% summarise_each(se)
-
- tryCatch({
- comp_DCap <- compCycleFacts[c("cycle","DCap")] %>% group_by(cycle) %>% summarise_each(mean)
- comp_DCapSE <- compCycleFacts[c("cycle","DCap")] %>% group_by(cycle) %>% summarise_each(se)
-
- tmp_data <<- data.frame(x=c(DCap$cycle, comp_DCap$cycle), y=c(DCap$DCap, comp_DCap$DCap), se=c(DCapSE$DCap, comp_DCapSE$DCap), cell=c(rep(1, length(DCap$cycle)), rep(2, length(comp_DCap$cycle))), cycle=c(DCap$cycle, comp_DCap$cycle))
- tmp_data$symbol <<- rep(1, nrow(tmp_data))
- tmp_data$color <<- sapply(tmp_data$cell, function(x) {match(x, c(1,2))})
-
- titleLabel <<- "Discharge Capacity Plot "
- xlabel <<- "Cycle"
- if (sum(data$Mass) != 0) {
- ylabel <<- "Discharge Capacity (mAh/g)"
- } else {
- ylabel <<- "Discharge Capacity (Ah)"
- }
- },
- error = function(x) {
- print(x)
- })
- },
- "Charge Capacity" = {
- CCap <- cycle_facts[c("cycle","CCap")] %>% group_by(cycle) %>% summarise_each(mean)
- CCapSE <- cycle_facts[c("cycle","CCap")] %>% group_by(cycle) %>% summarise_each(se)
-
- tryCatch({
- comp_CCap <- compCycleFacts[c("cycle","CCap")] %>% group_by(cycle) %>% summarise_each(mean)
- comp_CCapSE <- compCycleFacts[c("cycle","CCap")] %>% group_by(cycle) %>% summarise_each(se)
-
- tmp_data <<- data.frame(x=c(CCap$cycle, comp_CCap$cycle), y=c(CCap$CCap, comp_CCap$CCap), se=c(CCapSE$CCap, comp_CCapSE$CCap), cell=c(rep(1, length(CCap$cycle)), rep(2, length(comp_CCap$cycle))), cycle=c(CCap$cycle, comp_CCap$cycle))
- tmp_data$symbol <<- rep(1, nrow(tmp_data))
- tmp_data$color <<- sapply(tmp_data$cell, function(x) {match(x, c(1,2))})
-
- titleLabel <<- "Charge Capacity Plot "
- xlabel <<- "Cycle"
- if (sum(data$Mass) != 0) {
- ylabel <<- "Charge Capacity (mAh/g)"
- } else {
- ylabel <<- "Charge Capacity (Ah)"
- }
- },
- error = function(x) {
- print(x)
- })
- },
- "Capacity Loss" = {
- lostCap <- cycle_facts[c("cycle","lostCap")] %>% group_by(cycle) %>% summarise_each(mean)
- lostCapSE <- cycle_facts[c("cycle","lostCap")] %>% group_by(cycle) %>% summarise_each(se)
-
- tryCatch({
- comp_lostCap <- compCycleFacts[c("cycle","lostCap")] %>% group_by(cycle) %>% summarise_each(mean)
- comp_lostCapSE <- compCycleFacts[c("cycle","lostCap")] %>% group_by(cycle) %>% summarise_each(se)
-
- tmp_data <<- data.frame(x=c(lostCap$cycle, comp_lostCap$cycle), y=c(lostCap$lostCap, comp_lostCap$lostCap), se=c(lostCapSE$lostCap, comp_lostCapSE$lostCap), cell=c(rep(1, length(lostCap$cycle)), rep(2, length(comp_lostCap$cycle))), cycle=c(lostCap$cycle, comp_lostCap$cycle))
- tmp_data$symbol <<- rep(1, nrow(tmp_data))
- tmp_data$color <<- sapply(tmp_data$cell, function(x) {match(x, c(1,2))})
-
- titleLabel <<- "Charge Capacity Plot "
- xlabel <<- "Cycle"
- if (sum(data$Mass) != 0) {
- ylabel <<- "Capacity (mAh/g)"
- } else {
- ylabel <<- "Capacity (Ah)"
- }
- },
- error = function(x) {
- print(x)
- })
- },
- )
- }
-
- tmp_data <<- tmp_data[is.finite(tmp_data$x),]
- tmp_data <<- tmp_data[is.finite(tmp_data$y),]
- tmp_data <<- tmp_data[is.finite(tmp_data$cycle),]
- tmp_data <<- tmp_data[is.finite(tmp_data$cell),]
-
- if (any(sapply(bounds, is.na))) {
- if (is.na(bounds[1])) bounds[1] <<- min(tmp_data$x)
- if (is.na(bounds[2])) bounds[2] <<- max(tmp_data$x)
- if (is.na(bounds[3])) bounds[3] <<- min(tmp_data$y)
- if (is.na(bounds[4])) bounds[4] <<- max(tmp_data$y)
- }
-
- tryCatch({
- if (input$plotStyle =="o" | input$plotStyle =="p" | "se" %in% colnames(tmp_data)) {
- par(mar=c(5.1, 6.1, 4.1, 2.1))
-
- plot(tmp_data$x, tmp_data$y, type = input$plotStyle, col = tmp_data$color, pch = tmp_data$symbol, main=titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab=xlabel, ylab=ylabel, cex = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
- if ("se" %in% colnames(tmp_data)) {
- arrows(tmp_data$x, tmp_data$y - tmp_data$se, tmp_data$x, tmp_data$y + tmp_data$se, col = tmp_data$color, length=0.05, angle=90, code=3)
- legend("bottomright", legend = c(input$originalData, input$compareData), col = c(1,2), pch = 19)
- } else {
- if (input$typeGraph %in% c("dQdV Graphs", "Voltage Profiles", "Voltage vs. Time")) {
- legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), pch = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title ="Cycle", ncol=2)
- } else {
- legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), pch = c(1:length(input$cells)), title ="Cycle", ncol=2)
- }
- }
- } else if (input$plotStyle =="l") {
- newLine <- subset(tmp_data, tmp_data$color == 1 & tmp_data$symbol == 1)
- plot(newLine$x, newLine$y, type ="l", col = newLine$color, lty = newLine$symbol, main=titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab=xlabel, ylab=ylabel, lwd = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
-
- for (i in 1:length(input$renderCycles)) {
- for (n in 1:length(cellIndex)) {
- newLine <- subset(tmp_data, tmp_data$color == i & tmp_data$symbol == n)
- lines(newLine$x, newLine$y, col = newLine$color, lty = newLine$symbol, lwd = input$pointSize)
- }
- }
- if (input$typeGraph %in% c("dQdV Graphs", "Voltage Profiles", "Voltage vs. Time")) {
- legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells, if ("se" %in% colnames(tmp_data)) {c(input$dirName, compName)}), col = c(unique(tmp_data$color), rep("black", length(input$cells))), lty = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title ="Cycle", ncol=2)
- } else {
- legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells, if ("se" %in% colnames(tmp_data)) {c(input$dirName, compName)}), col = c(unique(tmp_data$color), rep("black", length(input$cells))), lty = c(1:length(input$cells)), title ="Cycle", ncol=2)
- }
- }
- },
- error=function(cond) {
- if (length(input$cells) != 0) {
- text(0.5, 0.5, labels ="This graph requires you to select a cycle!", cex = 2)
- } else {
- text(0.5, 0.5, labels ="You don messed up A-aron!\n (no data to plot)", cex = 2)
- }
- print(cond)
- return(NA)
- })
- }, res = 125)
-
- # Method for handling changes in cell selection
- observeEvent(input$cells, {
- tmp_cycles <<- input$renderCycles
- updateSelectInput(session,"renderCycles", choices = 1:max(numCycles$cycles), selected = tmp_cycles)
- })
-
- observeEvent(input$compAnalysis, {
- load(input$compAnalysis$datapath[[1]])
-
- compName <<- basename(input$compAnalysis$datapath[[1]])
- compCycleFacts <<- cycle_facts
-
- sheetName <<- !sheetName
- })
-
- # Error handling for graphBuilder and then showing modal
- observeEvent(input$graphBuilder, {
- if(dim(numCycles)[1] == 0 | dim(dQdVData)[1] == 0 | dim(cycle_facts)[1] == 0 | dim(total) == 0) {
- shinyalert("No Data!","Please run the analysis first or load a previous environment.","error")
- } else {
- updateCheckboxGroupInput(session,"cells", choices = data$sheet)
- showModal(graphbuilder)
- }
- })
-
- observeEvent(input$plot_click, {
- output$hoverCoordx <- renderText({input$plot_click$x})
- output$hoverCoordy <- renderText({input$plot_click$y})
- })
-
- observeEvent(input$perType, {
- if (input$perType == "Within Analysis") {
- updateRadioButtons(session, "typeGraph", choices = c("dQdV Graphs","Voltage Profiles", "Voltage vs. Time",
- "Charge Voltage", "Discharge Voltage",
- "Average Voltage", "Delta Voltage", "Discharge Capacity", "Charge Capacity" ))
-
- show("cells")
- show("renderCycles")
- show("plotStyle")
- hide("originalData")
- hide("compareData")
- hide("compAnalysis")
- hide("analysis")
- } else if (input$perType == "Between Analyses") {
- updateRadioButtons(session, "typeGraph", choices = c("Charge Voltage", "Discharge Voltage",
- "Average Voltage", "Delta Voltage", "Discharge Capacity", "Charge Capacity",
- "Capacity Loss"))
-
- sheetName <<- !sheetName
-
- hide("cells")
- hide("renderCycles")
- show("originalData")
- show("compareData")
- hide("plotStyle")
- show("compAnalysis")
- show("analysis")
- }
- })
-
- # Method for saving graph generated by graphBuilder
- observeEvent(input$saveGraph, {
- png(paste(input$fileName,".png"), res = 125)
-
- if (input$plotStyle =="o" | input$plotStyle =="p") {
- plot(tmp_data$x, tmp_data$y, type = input$plotStyle, col = tmp_data$color, pch = tmp_data$symbol, main=titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab=xlabel, ylab=ylabel, cex = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
- legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), pch = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title ="Cycle", ncol=2)
- } else if (input$plotStyle =="l") {
- newLine <- subset(tmp_data, tmp_data$color == 1 & tmp_data$symbol == 1)
- plot(newLine$x, newLine$y, type ="l", col = newLine$color, lty = newLine$symbol, main=titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab=xlabel, ylab=ylabel, lwd = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
-
- for (i in 1:length(input$renderCycles)) {
- for (n in 1:length(cellIndex)) {
- newLine <- subset(tmp_data, tmp_data$color == i & tmp_data$symbol == n)
- lines(newLine$x, newLine$y, col = newLine$color, lty = newLine$symbol, lwd = input$pointSize)
- }
- }
-
- legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), lty = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title ="Cycle", ncol=2)
- }
-
- dev.off()
-
- shinyalert("Success!", paste("Plot saved in working directory:\n", getwd()),"success")
- })
- }
-}
-shinyApp(ui, server)
diff --git a/global.R b/global.R
new file mode 100644
index 0000000..f762231
--- /dev/null
+++ b/global.R
@@ -0,0 +1,59 @@
+# ######
+#
+# Welcome to the Battery Analyzer Utility!
+#
+# This script aims to make it quick and efficient to analyze data exported by an Arbin battery cycler
+#
+# ######
+
+# ######
+#
+# These are all the required packages to aid in several of the processes, ranging from data analysis to plotting
+#
+# ######
+
+# options(warn = 0)
+
+list.of.packages <- c("readxl", "dplyr", "shiny", "tcltk", "DT", "shinyjs", "shinyalert", "pracma", "purrr", "zoo", "plotrix", "tools", "shinyWidgets", "gifski")
+new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[, "Package"])]
+if (length(new.packages)) install.packages(new.packages)
+lapply(list.of.packages, require, character.only = TRUE)
+
+source("ui.R", local = TRUE)
+source("server.R")
+source("info.R")
+
+# This line tests if the current R environment is interactive, RStudio makes an interactive environment by default
+if (interactive()) {
+
+ # ######
+ #
+ # All the global variables within the script, aka variables that need to be accessed by more than one
+ # function or session
+ #
+ # "Reactive Values" are ones that need to be readily changed, such as user inputs and variables to be displayed
+ #
+ # ######
+ data <- reactiveValues(data = data.frame())
+ final <- data.frame()
+ dirLocation <- vector()
+ numCycles <- data.frame()
+ dQdVData <- data.frame()
+ total <- data.frame()
+ cycle_facts <- data.frame()
+ tmp_data <- data.frame()
+ dirName <<- ""
+ tmp_cycles <- vector()
+ titleLabel <- ""
+ xlabel <- ""
+ ylabel <- ""
+ addParams <- FALSE
+ arbinCM <- FALSE
+ catMetric <<- vector()
+ legTitle <<- ""
+ sheetName <<- ""
+ bounds <<- vector()
+ compCycleFacts <<- data.frame()
+}
+
+shinyApp(ui, server)
diff --git a/info.R b/info.R
new file mode 100644
index 0000000..a0f2664
--- /dev/null
+++ b/info.R
@@ -0,0 +1,86 @@
+
+graphInfoTable <- HTML('
+
+
+
+ | Graph |
+ X Axis |
+ Y Axis |
+ Plot Frequency
|
+ Description |
+
+
+ | dQdV Graph |
+ Voltage (V) |
+ dQdV (Ah/V) |
+ per cycle |
+ The differential capacity plot for each cycle
|
+
+
+ | Voltage Profile |
+ Continuous Capacity (mAh/g or Ah) |
+ Voltage (V) |
+ per cycle |
+ Voltage vs. capacity plot for each cycle. Units depend if the masses are specified. |
+
+
+ | Voltage vs. Time |
+ Time (min) |
+ Voltage (V) |
+ per cycle |
+ The voltage as a function of time, including all steps |
+
+
+ | Discharge Capacity |
+ Cycle |
+ Discharge Capacity (mAh/g or Ah) |
+ per cell |
+ Discharge capacity for each individual cell per cycle. Coulombic efficiency is also plotted on a secondary axis. Units depend if the masses are specified. |
+
+
+ | Discharge Areal Capacity |
+ Cycle |
+ Discharge Capacity (Ah/cm2) |
+ per cell |
+ Discharge areal capacity for each individual cell per cycle. Coulombic efficiency is also plotted on a secondary axis. |
+
+
+ | Total Discharge Capacity |
+ Cycle |
+ Discharge Capacity (mAh/g or Ah) |
+ per analysis |
+ Discharge capacity summarized for all cells in the analysis. Coulombic efficiency is also plotted on a secondary axis. Mean is plotted as a point with error bars presenting the standard error between the cells. Units depend if the masses are specified. |
+
+
+ | Average Voltage |
+ Cycle |
+ Voltage (V) |
+ per cell |
+ The average voltage vs capacity for each cycle. The charge voltage (Vcharge) and discharge voltage (Vdischarge) were calculated using the average value theorem. The average voltage is then (Vcharge + Vdischarge)/2. Charge and discharge voltages are plotted alongside the average. |
+
+
+ | Delta Voltage |
+ Cycle |
+ Voltage (V) |
+ per cell |
+ The delta voltage vs capacity for each cycle. The charge voltage (Vcharge) and discharge voltage (Vdischarge) were calculated using the average value theorem. The delta voltage is then Vcharge - Vdischarge). Charge and discharge voltages are plotted alongside the average. |
+
+
+ | Capacity Loss |
+ Cycle |
+ Capacity (mAh/g or Ah) |
+ per cell |
+ The discharge capacity minus the charge capacity for each cycle. Units depend if the masses are specified. |
+
+
+ ')
diff --git a/modal.R b/modal.R
new file mode 100644
index 0000000..07cc9a3
--- /dev/null
+++ b/modal.R
@@ -0,0 +1,97 @@
+# Defines the modal in which the cell masses can be exported from Excel
+graphModal <- modalDialog(
+ {
+ fluidPage(
+ style = "font-size:15pt;",
+ tags$head(tags$style(".modal-dialog{min-width:60%}")),
+ fluidRow(align = "center", graphInfoTable),
+ )
+ },
+ title = "Graph Types",
+ easyClose = TRUE
+)
+
+graphbuilder <- modalDialog(
+ {
+ fluidPage(
+ useShinyjs(),
+ useShinyalert(),
+ tags$head(tags$style(".modal-dialog{width:80%}")),
+ tags$head(tags$style(".modal-body{ min-height:1000px}")),
+ sidebarLayout(
+ sidebarPanel(
+ fluidRow(
+ headerPanel("Graph Options"),
+ ),
+ fluidRow(
+ style = "padding:5%; border: 1px solid black;",
+ strong("Basis for Plot Types"), tags$br(),
+ helpText("Between Analysis requires a second dataset to be imported"), tags$br(),
+ radioButtons("perType", NULL, choices = c("Within Analysis", "Between Analyses"), inline = TRUE),
+ hidden(fileInput("compAnalysis", "Data to Compare"))
+ ),
+ fluidRow(
+ style = "padding:5%; margin:5%;",
+ radioButtons("typeGraph", "Graph Type:", choices = c(
+ "dQdV Graphs", "Voltage Profiles", "Voltage vs. Time",
+ "Charge Voltage", "Discharge Voltage",
+ "Average Voltage", "Delta Voltage", "Discharge Capacity", "Charge Capacity"
+ ), inline = FALSE),
+ radioButtons("plotStyle", "Plot Style:", choiceNames = c("Point", "Line", "Both"), choiceValues = c("p", "l", "o"), inline = TRUE),
+ checkboxGroupInput("cells", "Cell to Analyze:", choices = 1, inline = FALSE),
+ selectInput("renderCycles", "Cycles of Interest:", choices = 1, multiple = TRUE),
+ ),
+ fluidRow(
+ strong("Click to show coordinates:"), tags$br(), tags$br(),
+ "X: ",
+ textOutput("hoverCoordx", inline = TRUE), tags$br(),
+ "Y: ",
+ textOutput("hoverCoordy", inline = TRUE),
+ style = "border: 1px solid black; padding: 5%; margin: 5%;"
+ ),
+ fluidRow(
+ textInput("fileName", "Name of graph file:"),
+ actionButton("saveGraph", "Save Graph", width = "100%", class = "btn-primary"),
+ style = "border: 4px double black; padding: 5%; margin: 5%;"
+ ),
+ ),
+ mainPanel(
+ fluidRow(
+ plotOutput("outputPlot", height = "800px", click = "plot_click"),
+ style = "padding: 5%;",
+ ),
+ fluidRow(
+ h3("Graph Formatting"),
+ helpText("*If left blank, they will be calculated using the min and max of the data to be plotted."),
+ column(
+ 2,
+ numericInput("xMin", "X Min", value = NULL),
+ sliderInput("textSize", "Text Size", min = 0.1, max = 5, value = 1, ticks = FALSE),
+ ),
+ column(
+ 2,
+ numericInput("xMax", "X Max", value = NULL),
+ sliderInput("pointSize", "Point/Line Size", min = 0.1, max = 5, value = 1, ticks = FALSE),
+ ),
+ column(
+ 2,
+ numericInput("yMin", "Y Min", value = NULL),
+ ),
+ column(
+ 2,
+ numericInput("yMax", "Y Max", value = NULL),
+ ),
+ column(
+ 4,
+ textInput("originalData", "Original Data Name", value = "Original Data"),
+ textInput("compareData", "Comparison Data Name", value = "Comparison Data"),
+ ),
+ style = "border: 1px dashed black; padding: 2%;",
+ )
+ )
+ )
+ )
+ },
+ size = "l",
+ title = "Post-Processing Graph Builder"
+)
diff --git a/server.R b/server.R
new file mode 100644
index 0000000..daebb77
--- /dev/null
+++ b/server.R
@@ -0,0 +1,1236 @@
+library(shiny)
+
+server <- function(input, output, session) {
+ utils <- c("modal.R")
+ lapply(utils, source)
+
+ # This sets the maximum file size Shiny will import, the default of 5Mb is not large enough to handle Arbin files
+ options(shiny.maxRequestSize = 1000 * 1024^2)
+
+ split_path <- function(x) if (dirname(x) == x) x else c(basename(x), split_path(dirname(x)))
+
+ se <- function(x) {
+ sd(x) / length(x)
+ }
+
+ proxy <- dataTableProxy("channels")
+
+ batch.elements <- c("rerun", "load", "area", "whatGraph", "gGraphs", "gAnim", "graphBuilder")
+
+ deleteButtonCol <- function(df, id, ...) {
+ f <- function(i) {
+ as.character(
+ actionButton(
+ paste(id, i, sep = "_"),
+ label = icon("trash", lib = "glyphicon"),
+ onclick = 'Shiny.setInputValue(\"deletePressed\", this.id, {priority: "event"})'
+ )
+ )
+ }
+
+ deleteCol <- unlist(lapply(seq_len(nrow(df)), f))
+
+ cbind(data, delete = deleteCol)
+ }
+
+ generateDataTable <- function(df) {
+ DT::datatable(df,
+ escape = FALSE, editable = FALSE, options = list(columnDefs = list(list(visible = FALSE, targets = c(5, 6, 7)))),
+ colnames = c("Group", "Program", "File", "Sheet", "Mass (g)", "Filepath", "Group Path", "Limiting Electrode Area (cm^2)", "Delete"), rownames = FALSE
+ )
+ }
+
+ parseDeleteEvent <- function(idstr) {
+ res <- as.integer(sub(".*_([0-9]+)", "\\1", idstr))
+ if (!is.na(res)) {
+ res
+ }
+ }
+
+ observeEvent(input$deletePressed, {
+ rowNum <- parseDeleteEvent(input$deletePressed)
+
+ data <<- data[-rowNum, ]
+
+ output$channels <- renderDataTable(generateDataTable(deleteButtonCol(data, "delete_button")))
+ })
+
+ observeEvent(input$batchProcessing, {
+ if (input$batchProcessing) {
+ lapply(batch.elements, hide)
+ } else {
+ lapply(batch.elements, show)
+ }
+ })
+
+ observeEvent(input$clearTable, {
+ shinyalert("Warning!", "Are you sure you wish to clear all cells?",
+ type = "warning", showConfirmButton = TRUE, showCancelButton = TRUE, confirmButtonText = "Continue", cancelButtonText = "Abort",
+ callbackR = function(x) {
+ if (x) {
+ data <<- data[0, ]
+ output$channels <- renderDataTable(generateDataTable(deleteButtonCol(data, "delete_button")))
+ }
+ }
+ )
+ })
+
+ export_to_origin <- function() {
+ if (!("reticulate" %in% installed.packages()[, "Package"])) {
+ install.packages("reticulate")
+ }
+ require(reticulate)
+
+ py_location <- py_config()
+
+ py_install("OriginExt", pip = TRUE)
+ py_install("pandas", pip = TRUE)
+
+ filtered_location <- shQuote(paste(dirLocation, "/", input$dirName, sep = ""))
+
+ system(paste(py_location$python, " rPyO.py ", filtered_location, sep = ""))
+ }
+
+ # Ensures the files imported for analysis are Excel files
+ observeEvent(input$files, {
+ validFile <- FALSE
+
+ for (file in 1:nrow(input$files)) {
+ if (file_ext(input$files[file, "name"]) == "xlsx" | file_ext(input$files[file, "name"]) == "xls") {
+ validFile <- TRUE
+ arbinCM <<- FALSE
+ } else if (file_ext(file) == "csv") {
+ arbinCM <<- TRUE
+ validFile <- TRUE
+ }
+ }
+
+ if (validFile) {
+ renderTable()
+ } else {
+ shinyalert("That isn't right...", "Please upload an Excel or CSV file.", "error")
+ }
+ })
+
+ observeEvent(input$chooseDir, {
+ dirLocation <<- tk_choose.dir()
+
+ internal_folders <- list.dirs(path = dirLocation, recursive = FALSE)
+ base_names <- vector()
+ for (folder in internal_folders) {
+ base_names <- append(base_names, split_path(folder)[1])
+ }
+
+ if ("history" %in% base_names) {
+ past <- new.env()
+
+ if (file.exists(paste(dirLocation, "/history/", "Formation.RData", sep = ""))) {
+ load(paste(dirLocation, "/history/", "Formation.RData", sep = ""), envir = past)
+ } else if (file.exists(paste(dirLocation, "/history/", "RateCap.RData", sep = ""))) {
+ load(paste(dirLocation, "/history/", "RateCap.RData", sep = ""), envir = past)
+ } else {
+ return(NA)
+ }
+
+ if (input$batchProcessing) {
+ data <<- rbind(data, past$data)
+ } else {
+ data <<- past$dataSubset
+ }
+
+ output$channels <- renderDataTable(generateDataTable(deleteButtonCol(data, "delete_button")))
+ }
+
+ if (!is.na(dirLocation)) {
+ output$currDir <- renderText({
+ paste(split_path(dirLocation)[1], "(", split_path(dirLocation)[2], ")")
+ })
+ }
+ })
+
+ # Method for importing the previous R environment
+ observeEvent(input$load, {
+ if (is.null(input$rerun)) {
+ shinyalert("Uh oh!", "It appears you haven't selected a .RData file to import.", "error")
+ } else {
+ load(input$rerun$datapath[[1]])
+
+
+ if (file_ext(input$rerun$datapath) == "RData") {
+ validFile <- TRUE
+ }
+
+ if (validFile) {
+ data <<- dataSubset
+ dirLocation <<- dirLocation
+ numCycles <<- numCycles
+ dQdVData <<- dQdVData
+ total <<- total
+ cycle_facts <<- cycle_facts
+
+ output$channels <- renderDataTable(generateDataTable(deleteButtonCol(data, "delete_button")))
+
+ enable("graphBuilder")
+ } else {
+ shinyalert("That isn't right...", "Please upload an RData file.", "error")
+ }
+ }
+ })
+
+ observeEvent(input$whatGraph, {
+ showModal(graphModal)
+ })
+
+ # Data validation the masses imported from Excel, if valid they are placed into the datatable
+ observeEvent(input$excelImport, {
+ if (length(names(data)) <= 1) {
+ shinyalert("Uh oh!", "You need to import cells first!", "error")
+ removeModal()
+ } else {
+ tryCatch(
+ {
+ masses <- lapply(strsplit(strRep(input$masses, "\n", ","), ",", fixed = TRUE), as.double)
+ data$Mass <<- masses[[1]]
+ },
+ error = function(cond) {
+ print(cond)
+ shinyalert("Something isn't right...", "The number of masses imported did not match the amount of cells present or the text contained some special characters. Please try again.", "error")
+ removeModal()
+ },
+ finally = {
+ output$channels <- renderDataTable(generateDataTable(deleteButtonCol(data, "delete_button")))
+ }
+ )
+ }
+ })
+
+ # After the validation of the Arbin files, they macros (file name, and sheets) are taken and rendered in to a datatable
+ renderTable <- function() {
+ files <- input$files
+
+ if (is.null(files)) {
+ return(NULL)
+ }
+
+ file_sheet <- data.frame()
+ if (arbinCM) {
+ raw_data <- data.frame(name = files[["name"]], "sheet" = 1:nrow(files), datapath = files[["datapath"]])
+ } else {
+ for (i in 1:nrow(files)) {
+ sheets <- excel_sheets(files[i, 4])
+ file_sheet <- rbind(file_sheet, data.frame(
+ group = basename(dirLocation), program = rep(input$dirName, length(sheets)), name = rep(files[["name"]][i], length(sheets)), "sheet" = sheets, "Mass" = rep(0, length(sheets)),
+ datapath = rep(files[["datapath"]][i], length(sheets)), grouppath = rep(dirLocation, length(sheets)), area = rep(input$area, length(sheets))
+ ))
+ }
+
+ raw_data <- filter(file_sheet, grepl("Channel", sheet) & !grepl("Chart", sheet))
+ }
+
+ if (!is.null(dim(data)[1]) & !is.null(size(raw_data))) {
+ new_rows <- intersect(raw_data$sheet, data[data["group"] == basename(dirLocation)]$sheet)
+ data <<- data[which(data$sheet %in% new_rows), ]
+ data$datapath <<- raw_data$datapath
+ } else {
+ if (input$batchProcessing) {
+ tryCatch(
+ {
+ data <<- rbind(data, raw_data)
+ },
+ error = function(cond) {
+ data <<- raw_data
+ }
+ )
+ } else {
+ data <<- raw_data
+ }
+ }
+
+ if (arbinCM) {
+ output$channels <- renderDataTable(data,
+ editable = TRUE, options = list(columnDefs = list(list(visible = FALSE, targets = c(3)))),
+ colnames = c("File", "Sheet", "Filepath")
+ )
+ } else {
+ output$channels <- renderDataTable(generateDataTable(deleteButtonCol(data, "delete_button")))
+ }
+ }
+
+ # After some data validation, the main analysis is run on click of the"Run Analysis" button
+ observeEvent(input$submit, {
+ if (length(names(data)) <= 1) {
+ shinyalert("Uh oh!", "You need to import cells first!", "error")
+ } else if (is.na(dirLocation) | dirLocation == "") {
+ shinyalert("Uh oh!", "You need to enter a directory name first!", "error")
+ } else if (input$dirName == "") {
+ shinyalert("Uh oh!", "You need to enter an analysis name first!", "error")
+ } else if (sum(data$Mass) == 0) {
+ shinyalert("Uh oh!", "You have not entered any masses. Do you wish to continue?",
+ type = "warning", showConfirmButton = TRUE, showCancelButton = TRUE, confirmButtonText = "Continue", cancelButtonText = "Abort",
+ callbackR = function(x) {
+ if (x) {
+ runscript()
+ }
+ }
+ )
+ } else {
+ runscript()
+ }
+ })
+
+ # This function responsible for analysis of the
+ runscript <- function() {
+ groupList <- unique(data[["group"]])
+
+ for (group in groupList) {
+ dataSubset <- data[data[["group"]] == group, ]
+ dirLocation <- dataSubset[["grouppath"]][1]
+ programName <- dataSubset[["program"]][1]
+
+ # Sets up a progress bar in which to estimate how long the execution of the code will take
+ progress <- Progress$new(session, min = 0, max = nrow(dataSubset))
+ progress$set(message = paste(group, ": Plugging and chugging...\n"), detail = "Starting up...")
+
+ # Closes all graphics devices that may be lingering (prevents an excess from opening and slowing down the analysis)
+ while (dev.cur() != 1) {
+ dev.off()
+ }
+
+ # Resets the variables for the graph builder so new results are concatenated to old ones
+ numCycles <<- data.frame()
+ dQdVData <<- data.frame()
+ total <<- data.frame()
+ cycle_facts <<- data.frame()
+
+ # Disable all input fields to prevent errors occurring from changing values
+ disable("files")
+ disable("lowV")
+ disable("highV")
+ disable("dirLocation")
+ disable("submit")
+ disable("excelImport")
+ disable("gGraphs")
+ disable("peakFit")
+ disable("area")
+ disable("perActive")
+ disable("capActive")
+
+ # Creates the directory in which all dataSubset will be stored
+ dir.create(paste(dirLocation, programName, sep = "/"))
+
+ # Update the status once all set-up functions are complete
+ progress$set(detail = "Starting first cell...")
+
+ # ######
+ #
+ # The bulk of the analysis occurs within the loop. Each iteratin of the loop corresponds to a cell.
+ #
+ # ######
+ for (row in 1:nrow(dataSubset)) {
+
+ # ######
+ #
+ # This is where all code that should be executed on a"per cell" basis, to prepare for analysis
+ #
+ # ######
+
+ # Import the excel sheet corresponding to cell of interest
+ if (arbinCM) {
+ tmp_excel <- read.csv(toString(dataSubset$dataSubsetpath[row]))
+ names(tmp_excel) <- c("Index", "Test_Time(s)", "Date_Time", "Step_Time(s)", "Step_Index", "Cycle_Index", "Current(A)", "Voltage(V)", "Charge_Capacity(Ah)", "Discharge_Capacity(Ah)", "Charge_Energy(Wh)", "Discharge_Energy(Wh)")
+ } else {
+ tmp_excel <- read_excel(toString(dataSubset$datapath[row]), toString(dataSubset$sheet[row]))
+ }
+
+ # Create an nested directory for all the dataSubset and, if applicable, then further folders for graphs of interest
+ dir.create(paste(dirLocation, "/", programName, dataSubset$sheet[row], sep = "/"))
+ if (is.element("dQdV Graphs", input$gGraphs)) dir.create(paste(dirLocation, programName, dataSubset$sheet[row], "dQdV Plots", sep = "/"))
+ if (is.element("Voltage Profiles", input$gGraphs)) dir.create(paste(dirLocation, programName, dataSubset$sheet[row], "Voltage Profiles", sep = "/"))
+ if (is.element("Voltage vs. Time", input$gGraphs)) dir.create(paste(dirLocation, programName, dataSubset$sheet[row], "Voltage v Time", sep = "/"))
+
+ # Check if masses have been imported, if they have not then all future calculations will be done on a raw capacity basis
+ if (sum(dataSubset$Mass) != 0) {
+ ylabel <- "Capacity (mAh/g)"
+
+ tmp_excel$Q.d <- as.numeric(tmp_excel$`Discharge_Capacity(Ah)` * (1000 / dataSubset$Mass[row]))
+ tmp_excel$Q.c <- as.numeric(tmp_excel$`Charge_Capacity(Ah)` * (1000 / dataSubset$Mass[row]))
+
+ tmp_excel$CC <- tmp_excel$Q.d - tmp_excel$Q.c
+ tmp_excel$CE <- (tmp_excel$Q.d / tmp_excel$Q.c) * 100
+ } else {
+ ylabel <- "Capacity (Ah)"
+
+ tmp_excel$CC <- tmp_excel$`Discharge_Capacity(Ah)` - tmp_excel$`Charge_Capacity(Ah)`
+ tmp_excel$CE <- (tmp_excel$`Discharge_Capacity(Ah)` / tmp_excel$`Charge_Capacity(Ah)`) * 100
+ }
+ tmp_excel$Cell <- row
+ tmp_excel$CE[is.infinite(tmp_excel$CE) | is.nan(tmp_excel$CE) | tmp_excel$CE > 200] <- 0
+
+ # ######
+ #
+ # This loop iterates through each cycle of the cell.
+ #
+ # ######
+ cycles <- split(tmp_excel, tmp_excel$Cycle_Index)
+ prev_c <- 0
+ lastCC <- 0
+ ch_dch <- TRUE
+ durations <- vector(length = 4)
+ caps <- vector(length = 4)
+ prev <- TRUE
+ dchV <- 0
+ chV <- 0
+ i <- 1
+ for (cycle in cycles) {
+
+ # ######
+ #
+ # Within each cycle, take out the individual steps. These include the charge, discharge, and others.
+ #
+ # ######
+
+ progress$set(detail = paste("Analyzing cell", row, ", cycle", i))
+
+ steps <- split(cycle, cycle$Step_Index)
+ n <- 1
+
+ for (step in steps) {
+
+ # ######
+ #
+ # Isolation of the charge and discharge cycles. The algorithm is as follows:
+ #
+ # If the change in voltage for the step is greater than 0.5V, it is a charge or dicharge cycle. Then, the direction (sign) of the current determines
+ # if it is charge or discharge (positive current = charge step, negative current is a discharge cycle).
+ #
+ # ######
+ if (abs(tail(step$"Voltage(V)", 1) - step$"Voltage(V)"[[1]]) > 0.5) {
+
+ # ######
+ #
+ # All code that should be executed for every charge/discharge cycles should be written here.
+ #
+ # ######
+ lastCC <- n
+ if (step$"Current(A)"[[1]] > 0) {
+ chV <- (1 / (tail(step$`Charge_Capacity(Ah)`, 1) - step$`Charge_Capacity(Ah)`[[1]])) * trapz(step$`Charge_Capacity(Ah)`, step$`Voltage(V)`)
+ dQCdV <- diff(step$`Charge_Capacity(Ah)`) / diff(step$`Voltage(V)`)
+ dQdVData <<- rbind(dQdVData, data.frame(cycle = rep(i, length(dQCdV) + 1), cell = rep(row, length(dQCdV) + 1), c_d = rep(0, length(dQCdV) + 1), voltage = step$`Voltage(V)`, dQdV = c(0, dQCdV), F_L = rep(0, length(dQCdV) + 1), CC = step[["CC"]][1:nrow(step)]))
+
+ durations[1] <- tail(step$"Test_Time(s)", 1) - step$"Test_Time(s)"[[1]]
+ caps[1] <- tail(step$"Charge_Capacity(Ah)", 1) - step$"Charge_Capacity(Ah)"[[1]]
+ ch_dch <- TRUE
+ } else {
+ dchV <- (1 / (tail(step$`Discharge_Capacity(Ah)`, 1) - step$`Discharge_Capacity(Ah)`[[1]])) * trapz(step$`Discharge_Capacity(Ah)`, step$`Voltage(V)`)
+ dQDdV <- diff(step$`Discharge_Capacity(Ah)`) / diff(step$`Voltage(V)`)
+
+ durations[3] <- tail(step$"Test_Time(s)", 1) - step$"Test_Time(s)"[[1]]
+ caps[3] <- tail(step$"Discharge_Capacity(Ah)", 1) - step$"Discharge_Capacity(Ah)"[[1]]
+ ch_dch <- FALSE
+ if (abs(prev_c - step$`Current(A)`[[1]]) > 0.0005) {
+ if (!arbinCM) dQdVData <<- rbind(dQdVData, data.frame(cycle = rep(i, length(dQDdV) + 1), cell = rep(row, length(dQDdV) + 1), c_d = rep(1, length(dQDdV) + 1), voltage = step$`Voltage(V)`, dQdV = c(0, dQDdV), F_L = rep(1, length(dQDdV) + 1), CC = step[["CC"]][1:nrow(step)]))
+ prev_c <- step$`Current(A)`[[1]]
+ } else {
+ if (!arbinCM) dQdVData <<- rbind(dQdVData, data.frame(cycle = rep(i, length(dQDdV) + 1), cell = rep(row, length(dQDdV) + 1), c_d = rep(1, length(dQDdV) + 1), voltage = step$`Voltage(V)`, dQdV = c(0, dQDdV), F_L = rep(0, length(dQDdV) + 1), CC = step[["CC"]][1:nrow(step)]))
+ }
+ }
+ } else if (n - lastCC == 1 & abs(tail(step$"Voltage(V)", 1) - step$"Voltage(V)"[[1]]) < 0.001) {
+ if (step$"Current(A)"[[1]] > 0) {
+ durations[2] <- tail(step$"Test_Time(s)", 1) - step$"Test_Time(s)"[[1]]
+ caps[2] <- tail(step$"Charge_Capacity(Ah)", 1) - step$"Charge_Capacity(Ah)"[[1]]
+ } else {
+ durations[4] <- tail(step$"Test_Time(s)", 1) - step$"Test_Time(s)"[[1]]
+ caps[4] <- tail(step$"Discharge_Capacity(Ah)", 1) - step$"Discharge_Capacity(Ah)"[[1]]
+ }
+ }
+ ch_dch <- FALSE
+ n <- n + 1
+ }
+
+ # ######
+ #
+ # Code meant to be run on dataSubset"per cycle" should be written here
+ #
+ # ######
+
+ dQdVData <<- dQdVData[is.finite(dQdVData$voltage), ]
+ dQdVData <<- dQdVData[is.finite(dQdVData$dQdV), ]
+
+ if (sum(dataSubset$Mass) != 0) {
+ DCap <- tail(cycle$Q.d, 1)
+ CCap <- tail(cycle$Q.c, 1)
+ } else {
+ DCap <- tail(cycle$`Discharge_Capacity(Ah)`, 1)
+ CCap <- tail(cycle$`Charge_Capacity(Ah)`, 1)
+ }
+
+ timeCVFracCh <- durations[1] / (durations[1] + durations[2])
+ timeCVFracDch <- durations[3] / (durations[3] + durations[4])
+ capCVFracCh <- caps[1] / (caps[1] + caps[2])
+ capCVFracDch <- caps[3] / (caps[3] + caps[4])
+
+ if (max(tmp_excel$voltage) > 2) {
+ CE <- DCap / CCap
+ } else {
+ CE <- CCap / DCap
+ }
+
+ # Record charge and discharge voltage, then calculate the delta and average voltage
+ cycle_facts <<- rbind(cycle_facts, data.frame(
+ cycle = i, cell = row, chV = chV, dchV = dchV, avgV = (dchV + chV) / 2,
+ dV = chV - dchV, DCap = DCap, raw_DCap = tail(cycle$"Discharge_Capacity(Ah)", 1), raw_CCap = tail(cycle$"Charge_Capacity(Ah)", 1), CCap = CCap, CE = CE * 100, lostCap = CCap - DCap, cellFade = if (i == 1) {
+ 0
+ } else {
+ DCap - tail(cycle_facts$DCap, 1)
+ },
+ cycleTime = tail(cycle$`Test_Time(s)`, 1) - cycle$`Test_Time(s)`[[1]], timeCVFracCh = timeCVFracCh, timeCVFracDch = timeCVFracDch,
+ capCVFracCh = capCVFracCh, capCVRatioDch = capCVFracDch
+ ))
+
+ i <- i + 1
+ }
+
+ # ######
+ #
+ # Code meant to be run on dataSubset"per cell" should be written here
+ #
+ # ######
+
+ cell_dataSubset <- cycle_facts[cycle_facts$cell == row, ]
+
+ # Discharge capacity plotting, with coulombic efficiency being plotted alongside
+ if (is.element("Discharge Capacity", input$gGraphs)) {
+ png(paste(dirLocation, "/", programName, "/", dataSubset$sheet[row], "/", dataSubset$sheet[row], " Discharge Capacity Plot.png", sep = ""))
+ eol <- cell_dataSubset$`DCap`[[1]] * 0.8
+ plot(cell_dataSubset$cycle, cell_dataSubset$DCap, type = "p", main = paste("Discharge Capacity for", programName), xlab = NA, ylab = paste("Discharge", ylabel), mai = c(1, 1, 1, 1))
+ abline(h = eol, lty = "dotted")
+ par(new = T)
+ plot(cell_dataSubset$cycle, cell_dataSubset$CE, type = "p", axes = F, col = "red", ylab = NA, xlab = "Cycle", ylim = c(0, 105))
+ mtext(side = 4, line = 3, "Coulombic Efficiency (%)", col = "red")
+ axis(side = 4, col = "red", col.axis = "red")
+ dev.off()
+ }
+
+ # Discharge areal capacity plotting, with coulombic efficiency being plotted alongside
+ if (is.element("Discharge Areal Capacity", input$gGraphs)) {
+ png(paste(dirLocation, "/", programName, "/", dataSubset$sheet[row], "/", dataSubset$sheet[row], " Discharge Areal Capacity Plot.png", sep = ""))
+ new_par <- old_par <- par("mar")
+ new_par[4] <- old_par[2]
+ par(mar = new_par)
+ eol <- ((cell_dataSubset$DCap[[1]] * 1000) / dataSubset$area[row]) * 0.8
+ plot(cell_dataSubset$cycle, ((cell_dataSubset$DCap * 1000) / dataSubset$area[row]), type = "p", main = paste("Discharge Areal Capacity for", programName), xlab = NA, ylab = "Discharge Capacity (mAh/cm^2)", mai = c(1, 1, 1, 2))
+ abline(h = eol, lty = "dotted")
+ par(new = T)
+ plot(cell_dataSubset$cycle, cell_dataSubset$CE, type = "p", axes = F, col = "red", ylab = NA, xlab = "Cycle", ylim = c(0, 105))
+ mtext(side = 4, line = 3, "Coulombic Efficiency (%)", col = "red")
+ axis(side = 4, col = "red", col.axis = "red")
+ dev.off()
+ }
+
+
+ # Average voltage plotting
+ if (is.element("Average Voltage", input$gGraphs)) {
+ png(paste(dirLocation, "/", programName, "/", dataSubset$sheet[row], "/", dataSubset$sheet[row], " Average Voltage Plot.png", sep = ""))
+ plot(cell_dataSubset$cycle, cell_dataSubset$chV, col = "blue", main = paste("Average Voltage Plot for", programName, dataSubset$sheet[row]), xlab = "Cycle", ylab = "Voltage (V)", ylim = c(min(cell_dataSubset[, 2:4]), max(cell_dataSubset[, 2:4])))
+ points(cell_dataSubset$cycle, cell_dataSubset$dchV, col = "red", main = paste("Average Voltage Plot for", programName, dataSubset$sheet[row]), xlab = "Cycle", ylab = "Voltage (V)")
+ points(cell_dataSubset$cycle, cell_dataSubset$avgV, col = "black", main = paste("Average Voltage Plot for", programName, dataSubset$sheet[row]), xlab = "Cycle", ylab = "Voltage (V)")
+ legend("bottomright", c("Charge Voltage", "Discharge Voltage", "Average Voltage"), col = c("blue", "red", "black"), pch = 19)
+ dev.off()
+ }
+
+ # Delta voltage plotting
+ if (is.element("Delta Voltage", input$gGraphs)) {
+ png(paste(dirLocation, "/", programName, "/", dataSubset$sheet[row], "/", dataSubset$sheet[row], " Delta Voltage Plot.png", sep = ""))
+ plot(cell_dataSubset$cycle, cell_dataSubset$dV, main = paste("Delta Voltage Plot for", programName, dataSubset$sheet[row]), xlab = "Cycle", ylab = "Voltage (V)", ylim = c(0, 0.5))
+ dev.off()
+ }
+
+ # Capacity Loss plotting
+ if (is.element("Capacity Loss", input$gGraphs)) {
+ png(paste(dirLocation, "/", programName, "/", dataSubset$sheet[row], "/", dataSubset$sheet[row], " Capacity Loss Plot.png", sep = ""))
+ plot(cell_dataSubset$cycle, cell_dataSubset$lostCap, main = paste("Capacity Loss Plot for", programName, dataSubset$sheet[row]), xlab = "Cycle", ylab = ylabel, ylim = c(mean(cell_dataSubset$lostCap) + (2 * sd(cell_dataSubset$lostCap)), mean(cell_dataSubset$lostCap) - (1.5 * sd(cell_dataSubset$lostCap))))
+ abline(h = median(cell_dataSubset$lostCap), lty = "dotted")
+ dev.off()
+ }
+
+ if (is.element("dQdV Plots", input$gAnim)) {
+ dQdVplot <- function() {
+ tmp_dataSubset <- dQdVData[dQdVData$cell == row, ]
+ first_cycle <- dQdVData[dQdVData$cell == row & dQdVData$cycle == 2, ]
+ dataSubsetlist <- split(tmp_dataSubset, tmp_dataSubset$cycle)
+ lapply(dataSubsetlist, function(plotdataSubset) {
+ p <- plot(plotdataSubset$voltage, plotdataSubset$dQdV,
+ main = paste("dQdV Plot for", programName, dataSubset$sheet[row], "Cycle", plotdataSubset$cycle[[1]]), xlab = "Voltage (V)", ylab = "dQdV (Ah/V)",
+ xlim = c(min(tmp_dataSubset$voltage), max(tmp_dataSubset$voltage)), ylim = c(min(tmp_dataSubset$dQdV), max(tmp_dataSubset$dQdV))
+ ) +
+ points(first_cycle$voltage, first_cycle$dQdV, col = rgb(red = 1, green = 0, blue = 0, alpha = 0.5))
+ })
+ }
+ save_gif(dQdVplot(), paste(dirLocation, programName, dataSubset$sheet[row], "dQdV Animation.gif", sep = "/"), delay = 0.2)
+ }
+
+ if (is.element("Voltage Profiles", input$gAnim)) {
+ vpPlot <- function() {
+ first_cycle <- tmp_excel[tmp_excel$`Cycle_Index` == 2, ]
+ dataSubsetlist <- split(tmp_excel, tmp_excel$`Cycle_Index`)
+ lapply(dataSubsetlist, function(plotdataSubset) {
+ p <- plot(plotdataSubset$CC, plotdataSubset$`Voltage(V)`,
+ main = paste("Voltage Profile for", programName, dataSubset$sheet[row], "Cycle", plotdataSubset$`Cycle_Index`[[1]]), xlab = ylabel, ylab = "Voltage (V)",
+ xlim = c(min(tmp_excel$CC), max(tmp_excel$CC)), ylim = c(min(tmp_excel$`Voltage(V)`), max(tmp_excel$`Voltage(V)`))
+ ) +
+ points(first_cycle$CC, first_cycle$`Voltage(V)`, col = rgb(red = 1, green = 0, blue = 0, alpha = 0.5))
+ })
+ }
+ save_gif(vpPlot(), paste(dirLocation, programName, dataSubset$sheet[row], "Voltage Profile Animation.gif", sep = "/"), delay = 0.2)
+ }
+
+ # Save all dataSubset within the cell's directory
+ write.csv(tmp_excel, file = paste(dirLocation, "/", programName, "/", dataSubset$sheet[row], "/", dataSubset$sheet[row], ".csv", sep = ""))
+
+ # Append summation dataSubset to the larger dataSubsetsets to be worked with later
+ final <- rbind(final, tmp_excel)
+ numCycles <<- rbind(numCycles, data.frame(sheet = dataSubset$sheet[row], cycles = nrow(cell_dataSubset)))
+
+ # Update progress bar
+ progress$set(value = row, detail = paste("Finished", row, " of", nrow(dataSubset), " cells."))
+ }
+
+ # ######
+ #
+ # Code meant to be run on all dataSubset of all cells should be written here.
+ #
+ # ######
+
+ # With iterations complete, final calculations are being worked
+ progress$set(detail = "Wrapping up...")
+
+ # Get the last status of each cycle for each cell (namely capacity)
+ DCap <- cycle_facts[c("cycle", "DCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ CE <- cycle_facts[c("cycle", "CE")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ capSEs <- cycle_facts[c("cycle", "DCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+ ceSEs <- cycle_facts[c("cycle", "CE")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+ stats <- data.frame(cbind(cycle = capSEs$cycle, DCap = DCap$DCap, CE = CE$CE, capSE = capSEs$DCap, ceSE = ceSEs$CE))
+
+ # Send all the dataSubset to a global variable to be used elsewhere
+ total <<- final
+
+ tryCatch(
+ {
+ # Total dishcharge capacity plotting
+ if (is.element("Total Discharge Capacity", input$gGraphs)) {
+ png(paste(dirLocation, "/", programName, "/", "Total Discharge Capacity Plot.png", sep = ""))
+ eol <- max(stats$DCap) * 0.8
+ plot(stats$cycle, stats$DCap, type = "p", main = paste("Discharge Capacity for", programName), xlab = NA, ylab = paste("Discharge", ylabel), mai = c(1, 1, 1, 1))
+ arrows(stats$cycle, stats$DCap - stats$capSE, stats$cycle, stats$DCap + stats$capSE, length = 0.05, angle = 90, code = 3)
+ abline(h = eol, lty = "dotted")
+ par(new = T)
+ plot(stats$cycle, stats$CE, type = "p", axes = F, col = "red", ylab = NA, xlab = "Cycle", ylim = c(0, 105))
+ arrows(stats$cycle, stats$CE - stats$ceSE, stats$cycle, stats$CE + stats$ceSE, length = 0.05, angle = 90, code = 3, col = "red")
+ axis(side = 4, col = "red")
+ mtext(side = 4, line = 2, "Coulombic Efficiency (%)")
+ dev.off()
+ }
+ },
+ error = function(cond) {
+ print(cond)
+ }
+ )
+
+ # Save total dataSubset and stats
+ write.csv(stats, file = paste(dirLocation, "/", programName, "/", basename(dirLocation), " Summary.csv", sep = ""))
+ if (!arbinCM) write.csv(dQdVData, file = paste(dirLocation, "/", programName, "/", basename(dirLocation), " dQdV data.csv", sep = ""))
+ write.csv(cycle_facts, file = paste(dirLocation, "/", programName, "/", basename(dirLocation), " Cycle Facts.csv", sep = ""))
+
+ # If a histor directory does not exist, create it. Save all the dataSubset revelant to plotting to a RdataSubset file.
+ if (!dir.exists(paste(dirLocation, "history", sep = "/"))) {
+ dir.create(paste(dirLocation, "history", sep = "/"))
+ }
+
+ dirName <<- programName
+ data <- dataSubset
+
+ save(dirLocation, dirName, data, dQdVData, total, cycle_facts, numCycles, file = paste(dirLocation, "/history/", programName, ".Rdata", sep = ""))
+ }
+
+ # Modal for completed analysis
+ shinyalert("Analysis Complete!", paste("All your data are now in ", dirLocation, "/", programName, sep = ""),
+ type = "success", showConfirmButton = TRUE, showCancelButton = TRUE, confirmButtonText = "Generate Origin File", cancelButtonText = "Continue",
+ callbackR = function(x) {
+ if (x) {
+ export_to_origin()
+ }
+ }
+ )
+
+ # Finish progress bar
+ progress$set(value = nrow(data))
+
+ # Re-enable all input fields, including graph builder
+ enable("files")
+ enable("lowV")
+ enable("highV")
+ enable("dirLocation")
+ enable("submit")
+ enable("excelImport")
+ enable("gGraphs")
+ enable("peakFit")
+ enable("area")
+ enable("perActive")
+ enable("capActive")
+ enable("graphBuilder")
+
+
+ for (num in 1:size(groupList)[2]) {
+ # Close progress bar
+ progress$close()
+ }
+ }
+
+ # ######
+ #
+ # Graph Builder Processing
+ #
+ # ######
+ output$outputPlot <- renderPlot(
+ {
+ tmp_data <<- data.frame()
+ normalTime <<- data.frame()
+
+ bounds <<- c(input$xMin, input$xMax, input$yMin, input$yMax)
+
+ # Define function to normalize Voltage vs. Time plots
+ normalizeTime <- function(x) {
+ return(x - x[[1]])
+ }
+
+ # ######
+ #
+ # Switch statements defining the bulk of the processing, depending on the desired graph
+ #
+ # ######
+ if (input$perType == "Within Analysis") {
+ sheetName <<- TRUE
+
+ # Get the indicies in which the desired cells are in the data frame containing the number of cycles
+ cellIndex <- match(input$cells, numCycles$sheet)
+
+ switch(input$typeGraph,
+ "dQdV Graphs" = {
+ tmp_data <<- data.frame(x = dQdVData[dQdVData$cell %in% cellIndex, ]$voltage, y = dQdVData[dQdVData$cell %in% cellIndex, ]$dQdV, cycle = dQdVData[dQdVData$cell %in% cellIndex, ]$cycle, cell = dQdVData[dQdVData$cell %in% cellIndex, ]$cell)
+ tmp_data <<- tmp_data[tmp_data$cycle == sort(as.numeric(input$renderCycles)), ]
+
+ titleLabel <<- "dQdV Plot"
+ xlabel <<- "Voltage (V)"
+ ylabel <<- "dQdV (mAh/V)"
+ },
+ "Voltage Profiles" = {
+ tmp_data <<- data.frame(x = total[total$Cell %in% cellIndex, ]$CC, y = total[total$Cell %in% cellIndex, ]$`Voltage(V)`, cycle = total[total$Cell %in% cellIndex, ]$`Cycle_Index`, cell = total[total$Cell %in% cellIndex, ]$Cell)
+ tmp_data <<- tmp_data[tmp_data$cycle == sort(as.numeric(input$renderCycles)), ]
+
+ titleLabel <<- "Voltage Profile"
+ if (sum(data$Mass) != 0) {
+ xlabel <- "Continuous Capacity (mAh/g)"
+ } else {
+ xlabel <- "Continuous Capacity (Ah)"
+ }
+ ylabel <<- "Voltage (V)"
+ },
+ "Voltage vs. Time" = {
+ tmp_data <<- data.frame(x = (total[total$Cell %in% cellIndex, ]$`Test_Time(s)` / 60), y = total[total$Cell %in% cellIndex, ]$`Voltage(V)`, cycle = total[total$Cell %in% cellIndex, ]$`Cycle_Index`, cell = total[total$Cell %in% cellIndex, ]$Cell)
+ tmp_data <<- tmp_data[tmp_data$cycle %in% input$renderCycles, ]
+
+ x <- 0
+
+ for (cell in cellIndex) {
+ normalTime <<- c(normalTime, t(aggregate(tmp_data[tmp_data$cell == cell, ]$x, by = list(tmp_data[tmp_data$cell == cell, ]$cycle), normalizeTime)[, 2]))
+ }
+
+ tmp_data <<- data.frame(x = unlist(normalTime), y = tmp_data$y, cycle = tmp_data$cycle, cell = tmp_data$cell)
+ tmp_data <<- tmp_data[tmp_data$y >= 0.01, ]
+
+ titleLabel <<- "Voltge vs. Time Plot"
+ xlabel <<- "Time (min)"
+ ylabel <<- "Voltage (V)"
+ },
+ "Charge Voltage" = {
+ tmp_data <<- data.frame(x = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle, y = cycle_facts[cycle_facts$cell %in% cellIndex, ]$chV, cycle = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle, cell = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cell)
+
+ titleLabel <<- "Charge Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ "Discharge Voltage" = {
+ tmp_data <<- data.frame(x = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle, y = cycle_facts[cycle_facts$cell %in% cellIndex, ]$dchV, cell = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cell, cycle = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle)
+
+ titleLabel <<- "Discharge Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ "Average Voltage" = {
+ tmp_data <<- data.frame(x = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle, y = cycle_facts[cycle_facts$cell %in% cellIndex, ]$avgV, cell = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cell, cycle = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle)
+
+ titleLabel <<- "Average Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ "Delta Voltage" = {
+ tmp_data <<- data.frame(x = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle, y = cycle_facts[cycle_facts$cell %in% cellIndex, ]$dV, cell = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cell, cycle = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle)
+
+ titleLabel <<- "Delta Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ "Discharge Capacity" = {
+ tmp_data <<- data.frame(x = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle, y = cycle_facts[cycle_facts$cell %in% cellIndex, ]$DCap, cell = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cell, cycle = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle)
+
+ titleLabel <<- "Discharge Capacity Plot "
+ xlabel <<- "Cycle"
+ if (sum(data$Mass) != 0) {
+ ylabel <<- "Discharge Capacity (mAh/g)"
+ } else {
+ ylabel <<- "Discharge Capacity (Ah)"
+ }
+ },
+ "Charge Capacity" = {
+ tmp_data <<- data.frame(x = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle, y = cycle_facts[cycle_facts$cell %in% cellIndex, ]$CCap, cell = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cell, cycle = cycle_facts[cycle_facts$cell %in% cellIndex, ]$cycle)
+
+ titleLabel <<- "Charge Capacity Plot "
+ xlabel <<- "Cycle"
+ if (sum(data$Mass) != 0) {
+ ylabel <<- "Charge Capacity (mAh/g)"
+ } else {
+ ylabel <<- "Charge Capacity (Ah)"
+ }
+ }
+ )
+
+ tmp_data$color <<- sapply(tmp_data$cycle, function(x) {
+ match(x, input$renderCycles, nomatch = 1)
+ })
+ tmp_data$symbol <<- sapply(tmp_data$cell, function(x) {
+ match(x, cellIndex)
+ })
+ } else if (input$perType == "Between Analyses") {
+ switch(input$typeGraph,
+ "Charge Voltage" = {
+ x <- 0
+ chV <- cycle_facts[c("cycle", "chV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ chVSE <- cycle_facts[c("cycle", "chV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tryCatch(
+ {
+ comp_chV <- compCycleFacts[c("cycle", "chV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ comp_chVSE <- compCycleFacts[c("cycle", "chV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tmp_data <<- data.frame(x = c(chV$cycle, comp_chV$cycle), y = c(chV$chV, comp_chV$chV), se = c(chVSE$chV, comp_chVSE$chV), cell = c(rep(1, length(chV$cycle)), rep(2, length(comp_chV$cycle))), cycle = c(chV$cycle, comp_chV$cycle))
+ tmp_data$symbol <<- rep(1, nrow(tmp_data))
+ tmp_data$color <<- sapply(tmp_data$cell, function(x) {
+ match(x, c(1, 2))
+ })
+
+ titleLabel <<- "Charge Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ error = function(x) {
+ print(x)
+ }
+ )
+ },
+ "Discharge Voltage" = {
+ x <- 0
+ dchV <- cycle_facts[c("cycle", "dchV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ dchVSE <- cycle_facts[c("cycle", "dchV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tryCatch(
+ {
+ comp_dchV <- compCycleFacts[c("cycle", "dchV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ comp_dchVSE <- compCycleFacts[c("cycle", "dchV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tmp_data <<- data.frame(x = c(dchV$cycle, comp_dchV$cycle), y = c(dchV$dchV, comp_dchV$dchV), se = c(dchVSE$dchV, comp_dchVSE$dchV), cell = c(rep(1, length(dchV$cycle)), rep(2, length(comp_dchV$cycle))), cycle = c(dchV$cycle, comp_dchV$cycle))
+ tmp_data$symbol <<- rep(1, nrow(tmp_data))
+ tmp_data$color <<- sapply(tmp_data$cell, function(x) {
+ match(x, c(1, 2))
+ })
+
+ titleLabel <<- "Disharge Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ error = function(x) {
+ print(x)
+ }
+ )
+ },
+ "Average Voltage" = {
+ avgV <- cycle_facts[c("cycle", "avgV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ avgVSE <- cycle_facts[c("cycle", "avgV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tryCatch(
+ {
+ comp_avgV <- compCycleFacts[c("cycle", "avgV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ comp_avgVSE <- compCycleFacts[c("cycle", "avgV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tmp_data <<- data.frame(x = c(avgV$cycle, comp_avgV$cycle), y = c(avgV$avgV, comp_avgV$avgV), se = c(avgVSE$avgV, comp_avgVSE$avgV), cell = c(rep(1, length(avgV$cycle)), rep(2, length(comp_avgV$cycle))), cycle = c(avgV$cycle, comp_avgV$cycle))
+ tmp_data$symbol <<- rep(1, nrow(tmp_data))
+ tmp_data$color <<- sapply(tmp_data$cell, function(x) {
+ match(x, c(1, 2))
+ })
+
+ titleLabel <<- "Average Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ error = function(x) {
+ print(x)
+ }
+ )
+ },
+ "Delta Voltage" = {
+ dV <- cycle_facts[c("cycle", "dV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ dVSE <- cycle_facts[c("cycle", "dV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tryCatch(
+ {
+ comp_dV <- compCycleFacts[c("cycle", "dV")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ comp_dVSE <- compCycleFacts[c("cycle", "dV")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tmp_data <<- data.frame(x = c(dV$cycle, comp_dV$cycle), y = c(dV$dV, comp_dV$dV), se = c(dVSE$dV, comp_dVSE$dV), cell = c(rep(1, length(dV$cycle)), rep(2, length(comp_dV$cycle))), cycle = c(dV$cycle, comp_dV$cycle))
+ tmp_data$symbol <<- rep(1, nrow(tmp_data))
+ tmp_data$color <<- sapply(tmp_data$cell, function(x) {
+ match(x, c(1, 2))
+ })
+
+ titleLabel <<- "Delta Voltage Plot "
+ xlabel <<- "Cycle"
+ ylabel <<- "Voltage (V)"
+ },
+ error = function(x) {
+ print(x)
+ }
+ )
+ },
+ "Discharge Capacity" = {
+ DCap <- cycle_facts[c("cycle", "DCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ DCapSE <- cycle_facts[c("cycle", "DCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tryCatch(
+ {
+ comp_DCap <- compCycleFacts[c("cycle", "DCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ comp_DCapSE <- compCycleFacts[c("cycle", "DCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tmp_data <<- data.frame(x = c(DCap$cycle, comp_DCap$cycle), y = c(DCap$DCap, comp_DCap$DCap), se = c(DCapSE$DCap, comp_DCapSE$DCap), cell = c(rep(1, length(DCap$cycle)), rep(2, length(comp_DCap$cycle))), cycle = c(DCap$cycle, comp_DCap$cycle))
+ tmp_data$symbol <<- rep(1, nrow(tmp_data))
+ tmp_data$color <<- sapply(tmp_data$cell, function(x) {
+ match(x, c(1, 2))
+ })
+
+ titleLabel <<- "Discharge Capacity Plot "
+ xlabel <<- "Cycle"
+ if (sum(data$Mass) != 0) {
+ ylabel <<- "Discharge Capacity (mAh/g)"
+ } else {
+ ylabel <<- "Discharge Capacity (Ah)"
+ }
+ },
+ error = function(x) {
+ print(x)
+ }
+ )
+ },
+ "Charge Capacity" = {
+ CCap <- cycle_facts[c("cycle", "CCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ CCapSE <- cycle_facts[c("cycle", "CCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tryCatch(
+ {
+ comp_CCap <- compCycleFacts[c("cycle", "CCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ comp_CCapSE <- compCycleFacts[c("cycle", "CCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tmp_data <<- data.frame(x = c(CCap$cycle, comp_CCap$cycle), y = c(CCap$CCap, comp_CCap$CCap), se = c(CCapSE$CCap, comp_CCapSE$CCap), cell = c(rep(1, length(CCap$cycle)), rep(2, length(comp_CCap$cycle))), cycle = c(CCap$cycle, comp_CCap$cycle))
+ tmp_data$symbol <<- rep(1, nrow(tmp_data))
+ tmp_data$color <<- sapply(tmp_data$cell, function(x) {
+ match(x, c(1, 2))
+ })
+
+ titleLabel <<- "Charge Capacity Plot "
+ xlabel <<- "Cycle"
+ if (sum(data$Mass) != 0) {
+ ylabel <<- "Charge Capacity (mAh/g)"
+ } else {
+ ylabel <<- "Charge Capacity (Ah)"
+ }
+ },
+ error = function(x) {
+ print(x)
+ }
+ )
+ },
+ "Capacity Loss" = {
+ lostCap <- cycle_facts[c("cycle", "lostCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ lostCapSE <- cycle_facts[c("cycle", "lostCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tryCatch(
+ {
+ comp_lostCap <- compCycleFacts[c("cycle", "lostCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(mean)
+ comp_lostCapSE <- compCycleFacts[c("cycle", "lostCap")] %>%
+ group_by(cycle) %>%
+ summarise_each(se)
+
+ tmp_data <<- data.frame(x = c(lostCap$cycle, comp_lostCap$cycle), y = c(lostCap$lostCap, comp_lostCap$lostCap), se = c(lostCapSE$lostCap, comp_lostCapSE$lostCap), cell = c(rep(1, length(lostCap$cycle)), rep(2, length(comp_lostCap$cycle))), cycle = c(lostCap$cycle, comp_lostCap$cycle))
+ tmp_data$symbol <<- rep(1, nrow(tmp_data))
+ tmp_data$color <<- sapply(tmp_data$cell, function(x) {
+ match(x, c(1, 2))
+ })
+
+ titleLabel <<- "Charge Capacity Plot "
+ xlabel <<- "Cycle"
+ if (sum(data$Mass) != 0) {
+ ylabel <<- "Capacity (mAh/g)"
+ } else {
+ ylabel <<- "Capacity (Ah)"
+ }
+ },
+ error = function(x) {
+ print(x)
+ }
+ )
+ },
+ )
+ }
+
+ tmp_data <<- tmp_data[is.finite(tmp_data$x), ]
+ tmp_data <<- tmp_data[is.finite(tmp_data$y), ]
+ tmp_data <<- tmp_data[is.finite(tmp_data$cycle), ]
+ tmp_data <<- tmp_data[is.finite(tmp_data$cell), ]
+
+ if (any(sapply(bounds, is.na))) {
+ if (is.na(bounds[1])) bounds[1] <<- min(tmp_data$x)
+ if (is.na(bounds[2])) bounds[2] <<- max(tmp_data$x)
+ if (is.na(bounds[3])) bounds[3] <<- min(tmp_data$y)
+ if (is.na(bounds[4])) bounds[4] <<- max(tmp_data$y)
+ }
+
+ tryCatch(
+ {
+ if (input$plotStyle == "o" | input$plotStyle == "p" | "se" %in% colnames(tmp_data)) {
+ par(mar = c(5.1, 6.1, 4.1, 2.1))
+
+ plot(tmp_data$x, tmp_data$y, type = input$plotStyle, col = tmp_data$color, pch = tmp_data$symbol, main = titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab = xlabel, ylab = ylabel, cex = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
+ if ("se" %in% colnames(tmp_data)) {
+ arrows(tmp_data$x, tmp_data$y - tmp_data$se, tmp_data$x, tmp_data$y + tmp_data$se, col = tmp_data$color, length = 0.05, angle = 90, code = 3)
+ # legend("bottomright", legend = c(input$originalData, input$compareData), col = c(1,2), pch = 19)
+ } else {
+ if (input$typeGraph %in% c("dQdV Graphs", "Voltage Profiles", "Voltage vs. Time")) {
+ # legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), pch = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title ="Cycle", ncol=2)
+ } else {
+ # legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), pch = c(1:length(input$cells)), title ="Cycle", ncol=2)
+ }
+ }
+ } else if (input$plotStyle == "l") {
+ newLine <- subset(tmp_data, tmp_data$color == 1 & tmp_data$symbol == 1)
+ plot(newLine$x, newLine$y, type = "l", col = newLine$color, lty = newLine$symbol, main = titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab = xlabel, ylab = ylabel, lwd = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
+
+ for (i in 1:length(input$renderCycles)) {
+ for (n in 1:length(cellIndex)) {
+ newLine <- subset(tmp_data, tmp_data$color == i & tmp_data$symbol == n)
+ lines(newLine$x, newLine$y, col = newLine$color, lty = newLine$symbol, lwd = input$pointSize)
+ }
+ }
+ if (input$typeGraph %in% c("dQdV Graphs", "Voltage Profiles", "Voltage vs. Time")) {
+ legend("topright", legend = c(sort(as.numeric(input$renderCycles)), if ("se" %in% colnames(tmp_data)) {
+ c(input$dirName, compName)
+ }), col = c(unique(tmp_data$color), rep("black", length(input$cells))), lty = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title = "Cycle", ncol = 2)
+ } else {
+ legend("topright", legend = c(sort(as.numeric(input$renderCycles)), input$cells, if ("se" %in% colnames(tmp_data)) {
+ c(input$dirName, compName)
+ }), col = c(unique(tmp_data$color), rep("black", length(input$cells))), lty = c(1:length(input$cells)), title = "Cycle", ncol = 2)
+ }
+ }
+ },
+ error = function(cond) {
+ if (length(input$cells) != 0) {
+ text(0.5, 0.5, labels = "This graph requires you to select a cycle!", cex = 2)
+ } else {
+ text(0.5, 0.5, labels = "You don messed up A-aron!\n (no data to plot)", cex = 2)
+ }
+ print(cond)
+ return(NA)
+ }
+ )
+ },
+ res = 125
+ )
+
+ # Enable/Disable input field based on desired grph selection
+ observeEvent(input$gGraphs, {
+ disable("area")
+ disable("perActive")
+ disable("capActive")
+
+ choices <- c(
+ "dQdV Graphs", "Voltage Profiles", "Voltage vs. Time", "Discharge Capacity", "Discharge Areal Capacity",
+ "Total Discharge Capacity", "Average Voltage", "Delta Voltage"
+ )
+
+ if (is.element("Discharge Areal Capacity", input$gGraphs)) {
+ enable("area")
+ }
+ })
+
+ # Method for handling changes in cell selection
+ observeEvent(input$cells, {
+ tmp_cycles <<- input$renderCycles
+ updateSelectInput(session, "renderCycles", choices = 1:max(numCycles$cycles), selected = tmp_cycles)
+ })
+
+ observeEvent(input$compAnalysis, {
+ load(input$compAnalysis$datapath[[1]])
+
+ compName <<- basename(input$compAnalysis$datapath[[1]])
+ compCycleFacts <<- cycle_facts
+
+ sheetName <<- !sheetName
+ })
+
+ # Error handling for graphBuilder and then showing modal
+ observeEvent(input$graphBuilder, {
+ if (dim(numCycles)[1] == 0 | dim(dQdVData)[1] == 0 | dim(cycle_facts)[1] == 0) {
+ shinyalert("No Data!", "Please run the analysis first or load a previous environment.", "error")
+ } else {
+ updateCheckboxGroupInput(session, "cells", choices = data$sheet)
+ showModal(graphbuilder)
+ }
+ })
+
+ observeEvent(input$plot_click, {
+ output$hoverCoordx <- renderText({
+ input$plot_click$x
+ })
+ output$hoverCoordy <- renderText({
+ input$plot_click$y
+ })
+ })
+
+ observeEvent(input$perType, {
+ if (input$perType == "Within Analysis") {
+ updateRadioButtons(session, "typeGraph", choices = c(
+ "dQdV Graphs", "Voltage Profiles", "Voltage vs. Time",
+ "Charge Voltage", "Discharge Voltage",
+ "Average Voltage", "Delta Voltage", "Discharge Capacity", "Charge Capacity"
+ ))
+
+ show("cells")
+ show("renderCycles")
+ show("plotStyle")
+ hide("originalData")
+ hide("compareData")
+ hide("compAnalysis")
+ hide("analysis")
+ } else if (input$perType == "Between Analyses") {
+ updateRadioButtons(session, "typeGraph", choices = c(
+ "Charge Voltage", "Discharge Voltage",
+ "Average Voltage", "Delta Voltage", "Discharge Capacity", "Charge Capacity",
+ "Capacity Loss"
+ ))
+
+ sheetName <<- !sheetName
+
+ hide("cells")
+ hide("renderCycles")
+ show("originalData")
+ show("compareData")
+ hide("plotStyle")
+ show("compAnalysis")
+ show("analysis")
+ }
+ })
+
+ # Method for saving graph generated by graphBuilder
+ observeEvent(input$saveGraph, {
+ png(paste(input$fileName, ".png"), res = 125)
+
+ if (input$plotStyle == "o" | input$plotStyle == "p") {
+ plot(tmp_data$x, tmp_data$y, type = input$plotStyle, col = tmp_data$color, pch = tmp_data$symbol, main = titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab = xlabel, ylab = ylabel, cex = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
+ # legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), pch = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title ="Cycle", ncol=2)
+ } else if (input$plotStyle == "l") {
+ newLine <- subset(tmp_data, tmp_data$color == 1 & tmp_data$symbol == 1)
+ plot(newLine$x, newLine$y, type = "l", col = newLine$color, lty = newLine$symbol, main = titleLabel, xlim = c(bounds[1], bounds[2]), ylim = c(bounds[3], bounds[4]), xlab = xlabel, ylab = ylabel, lwd = input$pointSize, cex.axis = input$textSize, cex.lab = input$textSize, cex.main = input$textSize)
+
+ for (i in 1:length(input$renderCycles)) {
+ for (n in 1:length(cellIndex)) {
+ newLine <- subset(tmp_data, tmp_data$color == i & tmp_data$symbol == n)
+ lines(newLine$x, newLine$y, col = newLine$color, lty = newLine$symbol, lwd = input$pointSize)
+ }
+ }
+
+ # legend("bottomright", legend = c(sort(as.numeric(input$renderCycles)), input$cells), col = c(unique(tmp_data$color), rep("black", length(input$cells))), lty = c(rep(19, length(unique(tmp_data$color))), 1:length(input$cells)), title ="Cycle", ncol=2)
+ }
+
+ dev.off()
+
+ shinyalert("Success!", paste("Plot saved in working directory:\n", getwd()), "success")
+ })
+}
diff --git a/ui.R b/ui.R
new file mode 100644
index 0000000..11fa0d4
--- /dev/null
+++ b/ui.R
@@ -0,0 +1,111 @@
+library(shiny)
+
+ui <- shinyUI({
+ fluidPage(
+
+ # Utilizing javascript within Shiny allows for added features such as enable/disable of inputs
+ useShinyjs(),
+
+ # Shinyalert is a package that makes interactive"pop-ups" (modals) easy to generate
+ useShinyalert(),
+ setBackgroundColor(
+ color = c("ghostwhite", "lightgrey"),
+ gradient = "linear",
+ direction = "bottom",
+ shinydashboard = FALSE
+ ),
+ fluidRow(headerPanel("Electrochemical Data Processing Tool (EcDPT)")),
+ fluidRow("Analysis Mode",
+ switchInput("batchProcessing", onLabel = "Batch Processing", offLabel = "Single Analysis", handleWidth = "200px"),
+ align = "center", style = "margin: 0%;"
+ ),
+
+ # This first column is where most user inputs are, with the exception of the directory name
+ column(4,
+ align = "center",
+
+ # This generates the optional block in which the user can import a previous R environment
+ fluidRow(
+ strong("Start Here"), tags$br(),
+ "Current Cell Group: ", textOutput("currDir", inline = TRUE), tags$br(),
+ actionButton("chooseDir", "Cell Group Location*", class = "btn-secondary", style = "width: 80%; margin: 5%; font-size: 100%;"), tags$br(),
+ helpText("The analysis will create a folder within the selected folder."),
+ style = "border: 1px solid black; padding: 5%; margin: 5%;"
+ ),
+ fluidRow(
+ fileInput("rerun", "Optional: Import Previous R Environment", multiple = FALSE, accept = ".RData"),
+ actionButton("load", "Load"),
+ style = "border: 1px dashed black; margin: 5%; padding: 5%;"
+ ),
+
+ # These are the"optional" parameters that need to be filled out if select graphs are selected
+ fluidRow(
+ strong("Optional Parameters"), tags$br(),
+ "Parameters responsible for certain graphs.", tags$br(), tags$br(),
+
+ # Used for dishcharge areal capacity graphs
+ numericInput("area", "Limiting Electrode Area (cm^2)", 2.74, min = 0),
+
+ # Used for C-Rate calculations
+ # numericInput("perActive","Active Loading of Limiting Electrode (wt%)", 96, min = 0, max = 100),
+ # numericInput("capActive","Capacity of Limiting Active Material (mAh/g)", 155, min = 0, max = 100),
+ style = "border: 1px dashed black; padding: 5%; margin: 5%;"
+ ),
+ ),
+
+ # The second column is where selection of graphs and further features are selected
+ column(4,
+ align = "left",
+ fluidRow(
+ # Presents options for graphs to be generated
+ "Choose graphs to be generated: ",
+ actionButton("whatGraph", "What's this?", class = "btn-link"),
+ checkboxGroupInput("gGraphs", NULL, choices = c(
+ "Discharge Capacity", "Discharge Areal Capacity",
+ "Total Discharge Capacity", "Average Voltage", "Delta Voltage", "Capacity Loss"
+ ), inline = FALSE),
+ "Choose graphs to animate: ",
+ checkboxGroupInput("gAnim", NULL, choices = c("dQdV Plots", "Voltage Profiles"), inline = FALSE),
+ # "Advanced Analysis",
+ # radioButtons("advCalc", NULL, choices = c("No", "Yes"), inline = TRUE),
+ # helpText(HTML("Advanced Analysis includes: