inst/shiny-examples/app/app.R
In adsteen/uvvisR: What the Package Does (One Line, Title Case)
#######
#Shiny app for analyzing ocean optics spectrophotometer
#######
library(shiny)
library(zoo)
library(DT)
library(gridExtra)
library(GMD)
library(ggdendro)
library(tidyverse)
library(ggdendro)
library(shinyjs)
library(shinyFiles)
ui <- fluidPage(
tags$head(
tags$style(
HTML(".shiny-notification {
position:fixed;
top: calc(50%);
left: calc(50%);
}
"
)
)
),
useShinyjs(),
headerPanel("Spectrophotometer Analysis GUI"),
br(),
br(),
tabsetPanel(id = "main_tab",
tabPanel("Configuration",
sidebarPanel(width = 7,
tabsetPanel(
tabPanel("General Parameters",
br(),
fluidRow(
headerPanel("Directory Input"),
column(width = 4,
shinyDirButton("dir", "Select Directory", "Upload")
),
column(width = 8,
verbatimTextOutput("dir", placeholder = TRUE)
)
),
br(),
br(),
radioButtons("data_type", "Select Spectra Type", c("Raw Spectra (requires sample/reference spectra)", "Pre-analyzed (e.g., absorbance)"), inline = TRUE),
fluidRow(
column(width = 2,
div(
textInput(inputId = "intensity_units","Spectra Units",value = "Absorption"),
style="font-size:80%;"
)
),
column(width = 2,
div(
textInput(inputId = "sample_pattern","Sample Pattern"),
style="font-size:80%;"
)
),
column(width = 2,
div(
textInput(inputId = "reference_pattern","Reference Pattern"),
style="font-size:80%;"
)
),
column(width = 2,
div(
numericInput(inputId= "id_interval","Samples per Reference",value = 1,min=1,step=1),
style="font-size:80%;"
)
),
column(width = 2,
div(
numericInput(inputId= "path_len","Pathlength (m)",value = 0.01),
style="font-size:80%;"
)
)
),
fluidRow(
column(width = 1,
actionButton("load_files", "Load/Map Files")
)
),
br(),
br(),
fluidRow(
headerPanel("Wavelength Range"),
column(width = 6,
numericInput(inputId="low.wavelength","Lower Wavelength Threshold (nm)",value=200)
),
column(width = 6,
numericInput(inputId="high.wavelength","Upper Wavelength Threshold (nm)",value=800)
)
),
fluidRow(
column(width = 3,
numericInput(inputId = "smooth_window","Running Mean Window Size", value = 1, min = 1, step = 1)
),
column(width = 3, offset = 3,
br(),
div(
checkboxInput(inputId = "write.file", "Write Output Files", FALSE),
style="font-size:150%;"
)
),
column(width = 3,
textInput(inputId = "write.header", "File Name Prefix")
)
),
br(),
br(),
actionButton(inputId = "analyze_table", "Analyze Spectra")
),
tabPanel("Spectral Slope",
br(),
checkboxInput("spec.slope", "Perform Analysis", FALSE),
fluidRow(
column(width = 4,
headerPanel("Slope 1"),
column(width = 12,
numericInput(inputId="s1.lower", "Lower Wavelength (nm)",value=275)
),
column(width = 12,
numericInput(inputId="s1.upper", "Upper Wavelength (nm)",value=295)
)
),
column(width = 4,
headerPanel("Slope 2"),
column(width = 12,
numericInput(inputId="s2.lower", "Lower Wavelength (nm)",value=350)
),
column(width = 12,
numericInput(inputId="s2.upper", "Upper Wavelength (nm)",value=400)
)
)
)
),
tabPanel("Hierarchical Clustering",
br(),
checkboxInput("cluster", "Perform Analysis", FALSE),
fluidRow(
column(width = 4,
radioButtons("cluster_norm", "Normalize Spectra for Clustering", c("Yes", "No"), inline = TRUE)
),
column(width = 4,
numericInput(inputId="cluster.threshold", "Cluster Threshold",value=0.05,max = 1)
)
)
),
tabPanel("Integrate Spectra",
br(),
checkboxInput("area.integrate", "Perform Analysis", FALSE),
fluidRow(
column(width = 4,
numericInput(inputId= "min.integrate","Lower Bound (nm)",value = 200)
),
column(width = 4,
numericInput(inputId= "max.integrate","Upper Bound (nm)",value = 800)
)
)
),
tabPanel("Inspect Spectra",
br(),
checkboxInput("inspect_spectra", "Perform Analysis", FALSE),
radioButtons("inspect_normalize", "Normalize Spectra for Inspection", c("Yes", "No"), inline = TRUE)
)
)
),
mainPanel(
fluidRow(
column(width = 6, "Reference Spectra Table", DT::dataTableOutput("fileList_reference")
),
column(width = 6,"Sample Spectra Table", DT::dataTableOutput("fileList_sample")
)
)
)
),
tabPanel(value = "figure_tab","Figure Display",
br(),
br(),
fluidRow(
column(width = 1,
br(),
actionButton("export_figures", "Export Figures")
),
column(3,
textInput(inputId = "export_header", "Figure File Prefix")
)
),
mainPanel(
plotOutput("grid.plot",width = "150%",height = "700px")
)
),
tabPanel(value = "inspect_tab","Inspect Spectra Display",
br(),
br(),
fluidRow(
column(width = 1,
actionButton("next_spectrum", "Next Spectrum")
),
column(width = 1,
actionButton("back_spectrum", "Previous Spectrum")
)
),
br(),
br(),
fluidRow(
column(width = 1,
br(),
actionButton("find_spectrum", "Find Spectrum")
),
column(3,
textInput(inputId = "specific_spectra", "Partial Filename")
)
),
mainPanel(
plotOutput("inspect_plot",width = "150%",height = "700px")
)
)
)
)
server <- function(input, output, session) {
react.var<-reactiveValues(spectra_reference_tbl=NULL,
spectra_sample_tbl=NULL,
inspect_spectra=NULL,
plot_list=NULL,
start=1)
#Generate data tables for mapping sample and refernece spectra
observeEvent(input$load_files,{
if (is.na(input$dir[[1]][2])){
showNotification("You Need To Select a Directory")
} else {
if (input$sample_pattern %in% ""){
sample.pattern=NULL
} else{
sample.pattern=input$sample_pattern
files.sample<-list.files(path=unlist(input$dir[[1]][2]),
pattern=sample.pattern)
#calculate reference id vector
n.samples<-length(files.sample);
ref.id.vec<-sort(rep(seq(1,ceiling(n.samples/input$id_interval)),input$id_interval))[1:n.samples]
react.var[["spectra_sample_tbl"]]<-data.frame(file.name=files.sample,
reference.id=ref.id.vec,
exclude=rep(0,n.samples))
output$fileList_sample<-renderDT(react.var[["spectra_sample_tbl"]], selection = 'none', server = TRUE, editable='cell')
}
}
})
observeEvent(input$load_files,{
if (!is.na(input$dir[[1]][2])){
if (input$reference_pattern %in% ""){
reference.pattern=NULL
} else{
reference.pattern=input$reference_pattern
files.reference<-list.files(path=unlist(input$dir[[1]][2]),
pattern=reference.pattern)
react.var[["spectra_reference_tbl"]]<-data.frame(file.name=files.reference,
reference.id=seq(1,length(files.reference)),
exclude=rep(0,length(files.reference)))
output$fileList_reference<-renderDT(react.var[["spectra_reference_tbl"]], selection = 'none', server = TRUE, editable='cell')
}
}
})
#Render outputs
observeEvent(input$export_figures,{
for (f in names(react.var[["plot_list"]])){
switch(f,
"spec.slope" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"spectral_slope_figure.pdf",sep="_"),device="pdf"),
"withiness" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"withiness_figure.pdf",sep="_"),device="pdf"),
"dendrogram" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"dendrogram_figure.pdf",sep="_"),dpi=300,device="pdf"),
"integrate" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"integrate_figure.pdf",sep="_"),dpi=300,device="pdf")
)
}
})
observeEvent(input$data_type,{
if (react.var[["start"]] == 0){
if (input$data_type %in% "Raw Spectra (requires sample/reference spectra)"){
updateTextAreaInput(session,"intensity_units",value = "Absorption")
toggleState("intensity_units")
toggleState("reference_pattern")
toggleState("id_interval")
toggleState("path_len")
} else {
toggleState("intensity_units")
toggleState("id_interval")
toggleState("reference_pattern")
toggleState("path_len")
}
} else {
toggleState("intensity_units")
react.var[["start"]] <-0
}
})
# Create absorbance spectra based on data tables
observeEvent(input$fileList_sample_cell_edit,{
indx.change<-input$fileList_sample_cell_edit
i <- indx.change$row
j <- indx.change$col
v<-indx.change$value
react.var[["spectra_sample_tbl"]][i,j]<-coerceValue(v,react.var[["spectra_sample_tbl"]][i,j])
})
observeEvent(input$fileList_reference_cell_edit,{
indx.change<-input$fileList_reference_cell_edit
i <- indx.change$row
j <- indx.change$col
v<-indx.change$value
react.var[["spectra_reference_tbl"]][i,j]<-coerceValue(v,react.var[["spectra_reference_tbl"]][i,j])
})
observeEvent(input$analyze_table,{
if (is.na(input$dir[[1]][2])){
showNotification("You Need To Select a Directory")
} else if (input$spec.slope == TRUE & ((input$s1.upper > input$high.wavelength) | (input$s2.upper > input$high.wavelength) | (input$s1.lower < input$low.wavelength) | (input$s2.lower < input$low.wavelength))) {
showNotification("One of the ranges in your spectral slope analysis\n extends outside the specified wavelength range.")
} else if (input$area.integrate == TRUE & ((input$min.integrate < input$low.wavelength) | (input$max.integrate > input$high.wavelength))) {
showNotification("One of the ranges in your integration analysis\n extends outside the specified wavelength range.")
} else if(length(react.var[["spectra_sample_tbl"]]) == 0){
showNotification("You need to load in the directory.")
}
else {
i<-1
react.var[["plot_list"]] <-NULL
withProgress(message = "Reading/Processing Spectra",value = 0, {
if (input$data_type == "Raw Spectra (requires sample/reference spectra)"){
files.sample<-react.var[["spectra_sample_tbl"]][,1]
files.reference<-react.var[["spectra_reference_tbl"]][,1]
d_all_samples<-data.frame(NULL)
d_all_references<-data.frame(NULL)
for (f in files.sample){
f_tmp<-rollmean(read.table(paste(input$dir[[1]][2],f,sep="/")),k=input$smooth_window)
colnames(f_tmp)<-c("wavelength.nm","sample.intensity")
f.split<-strsplit(f,split = "_")
name.tmp<-f#.split[[1]][1]
reference.tmp<-react.var[["spectra_sample_tbl"]][i,2]
exclude.tmp<-react.var[["spectra_sample_tbl"]][i,3]
sample.tmp<-react.var[["spectra_sample_tbl"]][i,1]
d_all_samples<-rbind(d_all_samples,data.frame(f_tmp,
sample.name=name.tmp,
reference.id=reference.tmp,
exclude=exclude.tmp))
i<-i+1
}
i<-1
for (f in files.reference){
f_tmp<-rollmean(read.table(paste(input$dir[[1]][2],f,sep="/")),k=input$smooth_window)
colnames(f_tmp)<-c("wavelength.nm","reference.intensity")
f.split<-strsplit(f,split = "_")
name.tmp<-f#.split[[1]][1]
reference.tmp<-react.var[["spectra_reference_tbl"]][i,2]
exlude.tmp<-react.var[["spectra_reference_tbl"]][i,3]
d_all_references<-rbind(d_all_references,data.frame(f_tmp,
refernece.name=name.tmp,
reference.id=reference.tmp,
exclude=exclude.tmp))
i<-i+1
}
d_all_references<-d_all_references %>%
filter(exclude==0) %>%
select(-exclude)
d_all_samples<-d_all_samples %>%
filter(exclude==0) %>%
select(-exclude)
d_merge<-merge(d_all_samples,d_all_references,by=c("reference.id","wavelength.nm"))
d_spectra <- d_merge %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$low.wavelength) %>%
filter(wavelength.nm<=input$high.wavelength) %>%
mutate(response=-log10(sample.intensity/reference.intensity)*2.303/input$path_len) %>%
mutate(response.normalize=response/max(response)) %>%
filter(!is.na(response))
} else{
files.sample<-react.var[["spectra_sample_tbl"]][,1]
d_all_samples<-data.frame(NULL)
for (f in files.sample){
f_tmp<-rollmean(read.table(paste(input$dir[[1]][2],f,sep="/")),k=input$smooth_window)
colnames(f_tmp)<-c("wavelength.nm","response")
f.split<-strsplit(f,split = "_")
name.tmp<-f#.split[[1]][1]
# reference.tmp<-react.var[["spectra_sample_tbl"]][i,3]
exclude.tmp<-react.var[["spectra_sample_tbl"]][i,3]
sample.tmp<-react.var[["spectra_sample_tbl"]][i,1]
d_all_samples<-rbind(d_all_samples,data.frame(f_tmp,
sample.name=name.tmp,
# reference.id=reference.tmp,
exclude=exclude.tmp))
i<-i+1
}
d_all_samples<-d_all_samples %>%
filter(exclude==0) %>%
select(-exclude)
d_spectra <- d_all_samples %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$low.wavelength) %>%
filter(wavelength.nm<=input$high.wavelength) %>%
mutate(response.normalize=response/max(response))
}
incProgress(1)
})
if(input$write.file == TRUE){
write.csv(d_spectra,file=paste(input$write.header,as.character(input$intensity_units),"_spectra.csv",sep="_"),quote = FALSE,row.names = FALSE)
}
if (input$inspect_spectra == TRUE){
if (input$inspect_normalize %in% "Yes"){
react.var[["inspect_spectra"]]$spectra_wide<-d_spectra %>%
group_by(sample.name) %>%
select(sample.name,wavelength.nm,response.normalize) %>%
spread(key=wavelength.nm,value=response.normalize)
} else {
react.var[["inspect_spectra"]]$spectra_wide<-d_spectra %>%
group_by(sample.name) %>%
select(sample.name,wavelength.nm,response) %>%
spread(key=wavelength.nm,value=response)
}
react.var[["inspect_spectra"]]$file.names<-as.character(unlist(react.var[["inspect_spectra"]]$spectra_wide[,1]))
react.var[["inspect_spectra"]]$spectra_wide<-react.var[["inspect_spectra"]]$spectra_wide[,-1]
react.var[["inspect_spectra"]]$wavelength<-as.numeric(colnames(react.var[["inspect_spectra"]]$spectra_wide))
react.var[["inspect_spectra"]]$max.count<-nrow(react.var[["inspect_spectra"]]$spectra_wide)
react.var[["inspect_spectra"]]$count<-1
updateTabsetPanel(session,"main_tab",selected="inspect_tab")
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
if (input$spec.slope == TRUE){
d_spectral_s1 <- d_spectra %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$s1.lower & wavelength.nm<=input$s1.upper) %>%
select(response,wavelength.nm,sample.name)
colnames(d_spectral_s1)[c(1,2)]<-c("response.s1","wavelength.nm.s1")
d_spectral_s2 <- d_spectra %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$s2.lower & wavelength.nm<=input$s2.upper) %>%
select(response,wavelength.nm,sample.name)
colnames(d_spectral_s2)[c(1,2)]<-c("response.s2","wavelength.nm.s2")
d_spectral.ratio <-
merge(d_spectral_s1,d_spectral_s2,by=c("sample.name")) %>%
group_by(sample.name) %>%
nest() %>%
mutate(slope.s2=map_dbl(data,function(df) coef(lm(log(response.s2)~wavelength.nm.s2,data=df))[2])) %>%
mutate(slope.s1=map_dbl(data,function(df) coef(lm(log(response.s1)~wavelength.nm.s1,data=df))[2])) %>%
mutate(SR=slope.s1/slope.s2)
if (input$write.file == TRUE){
write.csv(d_spectral.ratio[,c(2,4:6)],file=paste(input$write.header,"_spectral_ratio_analysis.csv",sep=""),quote = FALSE,row.names = FALSE)
}
react.var[["plot_list"]]$spec.slope <-ggplot(d_spectral.ratio,aes(x=sample.name,y=SR)) +
geom_point() +
theme_bw() +
labs(x="Sample", y = "Spectral Ratio", title = "Spectral Slope") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
}
if (input$cluster == TRUE){
if (input$cluster_norm %in% "Yes"){
d_spectra_wide<-d_spectra %>%
select(response.normalize,wavelength.nm,sample.name) %>%
group_by(sample.name) %>%
spread(key=wavelength.nm,value=response.normalize)
} else {
d_spectra_wide<-d_spectra %>%
select(response,sample.name,wavelength.nm) %>%
group_by(sample.name) %>%
spread(key=wavelength.nm,value=response)
}
id_list<-d_spectra_wide[,1]
d_spectra_dist<-d_spectra_wide[,-1]
rownames(d_spectra_dist)<-as.character(unlist(id_list))
dist_mat<-dist(d_spectra_dist,method="euclidean")
if (nrow(id_list) > 10){
k.max<-10
} else {
k.max<-nrow(id_list)
}
ss<-rep(0,k.max)
o_clust<-hclust(dist_mat, method="ward.D")
for(i in 1:k.max) {
o_cut_clust<-cutree(o_clust, k=i)
o_cluster_quality<-css(dist.obj=dist_mat, clusters=o_cut_clust)
ss[i]<-o_cluster_quality$totwss
}
delta.ss<-(ss[1:k.max-1]/ss[1])-(ss[2:k.max]/ss[1])
n.cluster<-min(which(delta.ss < input$cluster.threshold))
p_dend<-dendro_data(o_clust,type="rectangle")
cluster.vec<-merge(label(p_dend),data.frame(cluster=cutree(o_clust, k=n.cluster),label=unlist(id_list[1]),by="label"))
if (input$write.file == TRUE){
write.csv(cluster.vec[,c(5,4)],file=paste(input$write.header,"_cluster_analysis.csv",sep=""),quote = FALSE,row.names = FALSE)
}
# react.var[["plot_list"]]$cluster$cluster_ids<-cluster.vec
react.var[["plot_list"]]$withiness<-ggplot(data=data.frame(withiness=ss,cluster=1:k.max),aes(x=cluster,y=withiness)) +
geom_point() +
theme_bw() +
labs(x = "Number of Clusters", y = "Withiness", title = "Withiness as a Function of Clusters")
cluster.vec<-cluster.vec[order(cluster.vec$x),][,4]
react.var[["plot_list"]]$dendrogram <-ggplot() +
geom_segment(data=segment(p_dend), aes(x=x, y=y, xend=xend, yend=yend)) +
geom_text(data=label(p_dend), aes(x=x, y=y, label=label, hjust=0,color=as.factor(cluster.vec)), size=3) +
coord_flip() + scale_y_reverse(expand=c(0.2, 0)) +
labs(x="Distance",y="Sample",color="Cluster",title = "Spectra Dendrogram") +
theme(axis.line.y=element_blank(),
axis.ticks.y=element_blank(),
axis.text.y=element_blank(),
axis.title.y=element_blank(),
panel.background=element_rect(fill="white"),
panel.grid=element_blank())
}
if (input$area.integrate == TRUE){
d_spectra_integrate <- d_spectra %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$min.integrate) %>%
filter(wavelength.nm<=input$max.integrate) %>%
summarize(area.integrate=sum(response))
if (input$write.file == TRUE){
write.csv(d_spectra_integrate[,c(2,3)],file=paste(input$write.header,"_",as.character(input$min.integrate),"_",as.character(input$max.integrate),"_integration_analysis.csv",sep=""),quote = FALSE,row.names = FALSE)
}
react.var[["plot_list"]]$integrate <-ggplot(d_spectra_integrate,aes(x=sample.name,y=area.integrate)) +
geom_point() +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
labs(x="Sample", y = paste("Integrated ",input$intensity_units), title = "Integrated Spectra")
}
if (length(names(react.var[["plot_list"]])>0)){
updateTabsetPanel(session,"main_tab",selected="figure_tab")
output$grid.plot <- renderPlot({
do.call("grid.arrange",c(react.var[["plot_list"]],ncol=2))
})
}
}
})
observeEvent(input$next_spectrum, {
if (length(react.var[["inspect_spectra"]])>0){
if(react.var[["inspect_spectra"]]$count<react.var[["inspect_spectra"]]$max.count){
react.var[["inspect_spectra"]]$count <<- react.var[["inspect_spectra"]]$count + 1 # Increment the counter by 1 when button is click
}
else{
react.var[["inspect_spectra"]]$count <- 1 # Increment the counter by 1 when button is click
}
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
})
observeEvent(input$back_spectrum, {
if (length(react.var[["inspect_spectra"]])>0){
if(react.var[["inspect_spectra"]]$count>1){
react.var[["inspect_spectra"]]$count <<- react.var[["inspect_spectra"]]$count - 1 # Increment the counter by 1 when button is click
}
else{
react.var[["inspect_spectra"]]$count <- react.var[["inspect_spectra"]]$max.count # Increment the counter by 1 when button is click
}
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
})
observeEvent(input$find_spectrum, {
if (length(react.var[["inspect_spectra"]])>0){
file.name.match.indx<-grep(input$specific_spectra,react.var[["inspect_spectra"]]$file.names)
if (length(file.name.match.indx) == 0){
showNotification("There are no filenames matching this pattern.")
} else {
if (length(file.name.match.indx) > 1){
showNotification("There are multiple filenames matching this pattern. The first match was used by default.")
}
react.var[["inspect_spectra"]]$count <- file.name.match.indx[1]
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
}
})
#Select directory for analysis
dir_load<-shinyDirChoose(
input,
'dir',
roots = c(wd = '.'),
filetypes = c("tsv", "csv")
)
global <- reactiveValues(datapath = getwd())
dir <- reactive(input$dir)
output$dir <- renderText({
global$datapath
})
observeEvent(ignoreNULL = TRUE,
eventExpr = {
input$dir
},
handlerExpr = {
if (!"path" %in% names(dir())) return()
home <- normalizePath(".")
global$datapath <-
file.path(home, paste(unlist(dir()$path[-1]), collapse = .Platform$file.sep))
})
}
shinyApp(ui = ui, server = server)
adsteen/uvvisR documentation built on Jan. 25, 2020, 12:42 a.m.
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#######
#Shiny app for analyzing ocean optics spectrophotometer
#######
library(shiny)
library(zoo)
library(DT)
library(gridExtra)
library(GMD)
library(ggdendro)
library(tidyverse)
library(ggdendro)
library(shinyjs)
library(shinyFiles)
ui <- fluidPage(
tags$head(
tags$style(
HTML(".shiny-notification {
position:fixed;
top: calc(50%);
left: calc(50%);
}
"
)
)
),
useShinyjs(),
headerPanel("Spectrophotometer Analysis GUI"),
br(),
br(),
tabsetPanel(id = "main_tab",
tabPanel("Configuration",
sidebarPanel(width = 7,
tabsetPanel(
tabPanel("General Parameters",
br(),
fluidRow(
headerPanel("Directory Input"),
column(width = 4,
shinyDirButton("dir", "Select Directory", "Upload")
),
column(width = 8,
verbatimTextOutput("dir", placeholder = TRUE)
)
),
br(),
br(),
radioButtons("data_type", "Select Spectra Type", c("Raw Spectra (requires sample/reference spectra)", "Pre-analyzed (e.g., absorbance)"), inline = TRUE),
fluidRow(
column(width = 2,
div(
textInput(inputId = "intensity_units","Spectra Units",value = "Absorption"),
style="font-size:80%;"
)
),
column(width = 2,
div(
textInput(inputId = "sample_pattern","Sample Pattern"),
style="font-size:80%;"
)
),
column(width = 2,
div(
textInput(inputId = "reference_pattern","Reference Pattern"),
style="font-size:80%;"
)
),
column(width = 2,
div(
numericInput(inputId= "id_interval","Samples per Reference",value = 1,min=1,step=1),
style="font-size:80%;"
)
),
column(width = 2,
div(
numericInput(inputId= "path_len","Pathlength (m)",value = 0.01),
style="font-size:80%;"
)
)
),
fluidRow(
column(width = 1,
actionButton("load_files", "Load/Map Files")
)
),
br(),
br(),
fluidRow(
headerPanel("Wavelength Range"),
column(width = 6,
numericInput(inputId="low.wavelength","Lower Wavelength Threshold (nm)",value=200)
),
column(width = 6,
numericInput(inputId="high.wavelength","Upper Wavelength Threshold (nm)",value=800)
)
),
fluidRow(
column(width = 3,
numericInput(inputId = "smooth_window","Running Mean Window Size", value = 1, min = 1, step = 1)
),
column(width = 3, offset = 3,
br(),
div(
checkboxInput(inputId = "write.file", "Write Output Files", FALSE),
style="font-size:150%;"
)
),
column(width = 3,
textInput(inputId = "write.header", "File Name Prefix")
)
),
br(),
br(),
actionButton(inputId = "analyze_table", "Analyze Spectra")
),
tabPanel("Spectral Slope",
br(),
checkboxInput("spec.slope", "Perform Analysis", FALSE),
fluidRow(
column(width = 4,
headerPanel("Slope 1"),
column(width = 12,
numericInput(inputId="s1.lower", "Lower Wavelength (nm)",value=275)
),
column(width = 12,
numericInput(inputId="s1.upper", "Upper Wavelength (nm)",value=295)
)
),
column(width = 4,
headerPanel("Slope 2"),
column(width = 12,
numericInput(inputId="s2.lower", "Lower Wavelength (nm)",value=350)
),
column(width = 12,
numericInput(inputId="s2.upper", "Upper Wavelength (nm)",value=400)
)
)
)
),
tabPanel("Hierarchical Clustering",
br(),
checkboxInput("cluster", "Perform Analysis", FALSE),
fluidRow(
column(width = 4,
radioButtons("cluster_norm", "Normalize Spectra for Clustering", c("Yes", "No"), inline = TRUE)
),
column(width = 4,
numericInput(inputId="cluster.threshold", "Cluster Threshold",value=0.05,max = 1)
)
)
),
tabPanel("Integrate Spectra",
br(),
checkboxInput("area.integrate", "Perform Analysis", FALSE),
fluidRow(
column(width = 4,
numericInput(inputId= "min.integrate","Lower Bound (nm)",value = 200)
),
column(width = 4,
numericInput(inputId= "max.integrate","Upper Bound (nm)",value = 800)
)
)
),
tabPanel("Inspect Spectra",
br(),
checkboxInput("inspect_spectra", "Perform Analysis", FALSE),
radioButtons("inspect_normalize", "Normalize Spectra for Inspection", c("Yes", "No"), inline = TRUE)
)
)
),
mainPanel(
fluidRow(
column(width = 6, "Reference Spectra Table", DT::dataTableOutput("fileList_reference")
),
column(width = 6,"Sample Spectra Table", DT::dataTableOutput("fileList_sample")
)
)
)
),
tabPanel(value = "figure_tab","Figure Display",
br(),
br(),
fluidRow(
column(width = 1,
br(),
actionButton("export_figures", "Export Figures")
),
column(3,
textInput(inputId = "export_header", "Figure File Prefix")
)
),
mainPanel(
plotOutput("grid.plot",width = "150%",height = "700px")
)
),
tabPanel(value = "inspect_tab","Inspect Spectra Display",
br(),
br(),
fluidRow(
column(width = 1,
actionButton("next_spectrum", "Next Spectrum")
),
column(width = 1,
actionButton("back_spectrum", "Previous Spectrum")
)
),
br(),
br(),
fluidRow(
column(width = 1,
br(),
actionButton("find_spectrum", "Find Spectrum")
),
column(3,
textInput(inputId = "specific_spectra", "Partial Filename")
)
),
mainPanel(
plotOutput("inspect_plot",width = "150%",height = "700px")
)
)
)
)
server <- function(input, output, session) {
react.var<-reactiveValues(spectra_reference_tbl=NULL,
spectra_sample_tbl=NULL,
inspect_spectra=NULL,
plot_list=NULL,
start=1)
#Generate data tables for mapping sample and refernece spectra
observeEvent(input$load_files,{
if (is.na(input$dir[[1]][2])){
showNotification("You Need To Select a Directory")
} else {
if (input$sample_pattern %in% ""){
sample.pattern=NULL
} else{
sample.pattern=input$sample_pattern
files.sample<-list.files(path=unlist(input$dir[[1]][2]),
pattern=sample.pattern)
#calculate reference id vector
n.samples<-length(files.sample);
ref.id.vec<-sort(rep(seq(1,ceiling(n.samples/input$id_interval)),input$id_interval))[1:n.samples]
react.var[["spectra_sample_tbl"]]<-data.frame(file.name=files.sample,
reference.id=ref.id.vec,
exclude=rep(0,n.samples))
output$fileList_sample<-renderDT(react.var[["spectra_sample_tbl"]], selection = 'none', server = TRUE, editable='cell')
}
}
})
observeEvent(input$load_files,{
if (!is.na(input$dir[[1]][2])){
if (input$reference_pattern %in% ""){
reference.pattern=NULL
} else{
reference.pattern=input$reference_pattern
files.reference<-list.files(path=unlist(input$dir[[1]][2]),
pattern=reference.pattern)
react.var[["spectra_reference_tbl"]]<-data.frame(file.name=files.reference,
reference.id=seq(1,length(files.reference)),
exclude=rep(0,length(files.reference)))
output$fileList_reference<-renderDT(react.var[["spectra_reference_tbl"]], selection = 'none', server = TRUE, editable='cell')
}
}
})
#Render outputs
observeEvent(input$export_figures,{
for (f in names(react.var[["plot_list"]])){
switch(f,
"spec.slope" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"spectral_slope_figure.pdf",sep="_"),device="pdf"),
"withiness" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"withiness_figure.pdf",sep="_"),device="pdf"),
"dendrogram" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"dendrogram_figure.pdf",sep="_"),dpi=300,device="pdf"),
"integrate" = ggsave(plot=react.var[["plot_list"]]$f, paste(input$export_header,"integrate_figure.pdf",sep="_"),dpi=300,device="pdf")
)
}
})
observeEvent(input$data_type,{
if (react.var[["start"]] == 0){
if (input$data_type %in% "Raw Spectra (requires sample/reference spectra)"){
updateTextAreaInput(session,"intensity_units",value = "Absorption")
toggleState("intensity_units")
toggleState("reference_pattern")
toggleState("id_interval")
toggleState("path_len")
} else {
toggleState("intensity_units")
toggleState("id_interval")
toggleState("reference_pattern")
toggleState("path_len")
}
} else {
toggleState("intensity_units")
react.var[["start"]] <-0
}
})
# Create absorbance spectra based on data tables
observeEvent(input$fileList_sample_cell_edit,{
indx.change<-input$fileList_sample_cell_edit
i <- indx.change$row
j <- indx.change$col
v<-indx.change$value
react.var[["spectra_sample_tbl"]][i,j]<-coerceValue(v,react.var[["spectra_sample_tbl"]][i,j])
})
observeEvent(input$fileList_reference_cell_edit,{
indx.change<-input$fileList_reference_cell_edit
i <- indx.change$row
j <- indx.change$col
v<-indx.change$value
react.var[["spectra_reference_tbl"]][i,j]<-coerceValue(v,react.var[["spectra_reference_tbl"]][i,j])
})
observeEvent(input$analyze_table,{
if (is.na(input$dir[[1]][2])){
showNotification("You Need To Select a Directory")
} else if (input$spec.slope == TRUE & ((input$s1.upper > input$high.wavelength) | (input$s2.upper > input$high.wavelength) | (input$s1.lower < input$low.wavelength) | (input$s2.lower < input$low.wavelength))) {
showNotification("One of the ranges in your spectral slope analysis\n extends outside the specified wavelength range.")
} else if (input$area.integrate == TRUE & ((input$min.integrate < input$low.wavelength) | (input$max.integrate > input$high.wavelength))) {
showNotification("One of the ranges in your integration analysis\n extends outside the specified wavelength range.")
} else if(length(react.var[["spectra_sample_tbl"]]) == 0){
showNotification("You need to load in the directory.")
}
else {
i<-1
react.var[["plot_list"]] <-NULL
withProgress(message = "Reading/Processing Spectra",value = 0, {
if (input$data_type == "Raw Spectra (requires sample/reference spectra)"){
files.sample<-react.var[["spectra_sample_tbl"]][,1]
files.reference<-react.var[["spectra_reference_tbl"]][,1]
d_all_samples<-data.frame(NULL)
d_all_references<-data.frame(NULL)
for (f in files.sample){
f_tmp<-rollmean(read.table(paste(input$dir[[1]][2],f,sep="/")),k=input$smooth_window)
colnames(f_tmp)<-c("wavelength.nm","sample.intensity")
f.split<-strsplit(f,split = "_")
name.tmp<-f#.split[[1]][1]
reference.tmp<-react.var[["spectra_sample_tbl"]][i,2]
exclude.tmp<-react.var[["spectra_sample_tbl"]][i,3]
sample.tmp<-react.var[["spectra_sample_tbl"]][i,1]
d_all_samples<-rbind(d_all_samples,data.frame(f_tmp,
sample.name=name.tmp,
reference.id=reference.tmp,
exclude=exclude.tmp))
i<-i+1
}
i<-1
for (f in files.reference){
f_tmp<-rollmean(read.table(paste(input$dir[[1]][2],f,sep="/")),k=input$smooth_window)
colnames(f_tmp)<-c("wavelength.nm","reference.intensity")
f.split<-strsplit(f,split = "_")
name.tmp<-f#.split[[1]][1]
reference.tmp<-react.var[["spectra_reference_tbl"]][i,2]
exlude.tmp<-react.var[["spectra_reference_tbl"]][i,3]
d_all_references<-rbind(d_all_references,data.frame(f_tmp,
refernece.name=name.tmp,
reference.id=reference.tmp,
exclude=exclude.tmp))
i<-i+1
}
d_all_references<-d_all_references %>%
filter(exclude==0) %>%
select(-exclude)
d_all_samples<-d_all_samples %>%
filter(exclude==0) %>%
select(-exclude)
d_merge<-merge(d_all_samples,d_all_references,by=c("reference.id","wavelength.nm"))
d_spectra <- d_merge %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$low.wavelength) %>%
filter(wavelength.nm<=input$high.wavelength) %>%
mutate(response=-log10(sample.intensity/reference.intensity)*2.303/input$path_len) %>%
mutate(response.normalize=response/max(response)) %>%
filter(!is.na(response))
} else{
files.sample<-react.var[["spectra_sample_tbl"]][,1]
d_all_samples<-data.frame(NULL)
for (f in files.sample){
f_tmp<-rollmean(read.table(paste(input$dir[[1]][2],f,sep="/")),k=input$smooth_window)
colnames(f_tmp)<-c("wavelength.nm","response")
f.split<-strsplit(f,split = "_")
name.tmp<-f#.split[[1]][1]
# reference.tmp<-react.var[["spectra_sample_tbl"]][i,3]
exclude.tmp<-react.var[["spectra_sample_tbl"]][i,3]
sample.tmp<-react.var[["spectra_sample_tbl"]][i,1]
d_all_samples<-rbind(d_all_samples,data.frame(f_tmp,
sample.name=name.tmp,
# reference.id=reference.tmp,
exclude=exclude.tmp))
i<-i+1
}
d_all_samples<-d_all_samples %>%
filter(exclude==0) %>%
select(-exclude)
d_spectra <- d_all_samples %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$low.wavelength) %>%
filter(wavelength.nm<=input$high.wavelength) %>%
mutate(response.normalize=response/max(response))
}
incProgress(1)
})
if(input$write.file == TRUE){
write.csv(d_spectra,file=paste(input$write.header,as.character(input$intensity_units),"_spectra.csv",sep="_"),quote = FALSE,row.names = FALSE)
}
if (input$inspect_spectra == TRUE){
if (input$inspect_normalize %in% "Yes"){
react.var[["inspect_spectra"]]$spectra_wide<-d_spectra %>%
group_by(sample.name) %>%
select(sample.name,wavelength.nm,response.normalize) %>%
spread(key=wavelength.nm,value=response.normalize)
} else {
react.var[["inspect_spectra"]]$spectra_wide<-d_spectra %>%
group_by(sample.name) %>%
select(sample.name,wavelength.nm,response) %>%
spread(key=wavelength.nm,value=response)
}
react.var[["inspect_spectra"]]$file.names<-as.character(unlist(react.var[["inspect_spectra"]]$spectra_wide[,1]))
react.var[["inspect_spectra"]]$spectra_wide<-react.var[["inspect_spectra"]]$spectra_wide[,-1]
react.var[["inspect_spectra"]]$wavelength<-as.numeric(colnames(react.var[["inspect_spectra"]]$spectra_wide))
react.var[["inspect_spectra"]]$max.count<-nrow(react.var[["inspect_spectra"]]$spectra_wide)
react.var[["inspect_spectra"]]$count<-1
updateTabsetPanel(session,"main_tab",selected="inspect_tab")
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
if (input$spec.slope == TRUE){
d_spectral_s1 <- d_spectra %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$s1.lower & wavelength.nm<=input$s1.upper) %>%
select(response,wavelength.nm,sample.name)
colnames(d_spectral_s1)[c(1,2)]<-c("response.s1","wavelength.nm.s1")
d_spectral_s2 <- d_spectra %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$s2.lower & wavelength.nm<=input$s2.upper) %>%
select(response,wavelength.nm,sample.name)
colnames(d_spectral_s2)[c(1,2)]<-c("response.s2","wavelength.nm.s2")
d_spectral.ratio <-
merge(d_spectral_s1,d_spectral_s2,by=c("sample.name")) %>%
group_by(sample.name) %>%
nest() %>%
mutate(slope.s2=map_dbl(data,function(df) coef(lm(log(response.s2)~wavelength.nm.s2,data=df))[2])) %>%
mutate(slope.s1=map_dbl(data,function(df) coef(lm(log(response.s1)~wavelength.nm.s1,data=df))[2])) %>%
mutate(SR=slope.s1/slope.s2)
if (input$write.file == TRUE){
write.csv(d_spectral.ratio[,c(2,4:6)],file=paste(input$write.header,"_spectral_ratio_analysis.csv",sep=""),quote = FALSE,row.names = FALSE)
}
react.var[["plot_list"]]$spec.slope <-ggplot(d_spectral.ratio,aes(x=sample.name,y=SR)) +
geom_point() +
theme_bw() +
labs(x="Sample", y = "Spectral Ratio", title = "Spectral Slope") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
}
if (input$cluster == TRUE){
if (input$cluster_norm %in% "Yes"){
d_spectra_wide<-d_spectra %>%
select(response.normalize,wavelength.nm,sample.name) %>%
group_by(sample.name) %>%
spread(key=wavelength.nm,value=response.normalize)
} else {
d_spectra_wide<-d_spectra %>%
select(response,sample.name,wavelength.nm) %>%
group_by(sample.name) %>%
spread(key=wavelength.nm,value=response)
}
id_list<-d_spectra_wide[,1]
d_spectra_dist<-d_spectra_wide[,-1]
rownames(d_spectra_dist)<-as.character(unlist(id_list))
dist_mat<-dist(d_spectra_dist,method="euclidean")
if (nrow(id_list) > 10){
k.max<-10
} else {
k.max<-nrow(id_list)
}
ss<-rep(0,k.max)
o_clust<-hclust(dist_mat, method="ward.D")
for(i in 1:k.max) {
o_cut_clust<-cutree(o_clust, k=i)
o_cluster_quality<-css(dist.obj=dist_mat, clusters=o_cut_clust)
ss[i]<-o_cluster_quality$totwss
}
delta.ss<-(ss[1:k.max-1]/ss[1])-(ss[2:k.max]/ss[1])
n.cluster<-min(which(delta.ss < input$cluster.threshold))
p_dend<-dendro_data(o_clust,type="rectangle")
cluster.vec<-merge(label(p_dend),data.frame(cluster=cutree(o_clust, k=n.cluster),label=unlist(id_list[1]),by="label"))
if (input$write.file == TRUE){
write.csv(cluster.vec[,c(5,4)],file=paste(input$write.header,"_cluster_analysis.csv",sep=""),quote = FALSE,row.names = FALSE)
}
# react.var[["plot_list"]]$cluster$cluster_ids<-cluster.vec
react.var[["plot_list"]]$withiness<-ggplot(data=data.frame(withiness=ss,cluster=1:k.max),aes(x=cluster,y=withiness)) +
geom_point() +
theme_bw() +
labs(x = "Number of Clusters", y = "Withiness", title = "Withiness as a Function of Clusters")
cluster.vec<-cluster.vec[order(cluster.vec$x),][,4]
react.var[["plot_list"]]$dendrogram <-ggplot() +
geom_segment(data=segment(p_dend), aes(x=x, y=y, xend=xend, yend=yend)) +
geom_text(data=label(p_dend), aes(x=x, y=y, label=label, hjust=0,color=as.factor(cluster.vec)), size=3) +
coord_flip() + scale_y_reverse(expand=c(0.2, 0)) +
labs(x="Distance",y="Sample",color="Cluster",title = "Spectra Dendrogram") +
theme(axis.line.y=element_blank(),
axis.ticks.y=element_blank(),
axis.text.y=element_blank(),
axis.title.y=element_blank(),
panel.background=element_rect(fill="white"),
panel.grid=element_blank())
}
if (input$area.integrate == TRUE){
d_spectra_integrate <- d_spectra %>%
group_by(sample.name) %>%
filter(wavelength.nm>=input$min.integrate) %>%
filter(wavelength.nm<=input$max.integrate) %>%
summarize(area.integrate=sum(response))
if (input$write.file == TRUE){
write.csv(d_spectra_integrate[,c(2,3)],file=paste(input$write.header,"_",as.character(input$min.integrate),"_",as.character(input$max.integrate),"_integration_analysis.csv",sep=""),quote = FALSE,row.names = FALSE)
}
react.var[["plot_list"]]$integrate <-ggplot(d_spectra_integrate,aes(x=sample.name,y=area.integrate)) +
geom_point() +
theme_bw() +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
labs(x="Sample", y = paste("Integrated ",input$intensity_units), title = "Integrated Spectra")
}
if (length(names(react.var[["plot_list"]])>0)){
updateTabsetPanel(session,"main_tab",selected="figure_tab")
output$grid.plot <- renderPlot({
do.call("grid.arrange",c(react.var[["plot_list"]],ncol=2))
})
}
}
})
observeEvent(input$next_spectrum, {
if (length(react.var[["inspect_spectra"]])>0){
if(react.var[["inspect_spectra"]]$count<react.var[["inspect_spectra"]]$max.count){
react.var[["inspect_spectra"]]$count <<- react.var[["inspect_spectra"]]$count + 1 # Increment the counter by 1 when button is click
}
else{
react.var[["inspect_spectra"]]$count <- 1 # Increment the counter by 1 when button is click
}
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
})
observeEvent(input$back_spectrum, {
if (length(react.var[["inspect_spectra"]])>0){
if(react.var[["inspect_spectra"]]$count>1){
react.var[["inspect_spectra"]]$count <<- react.var[["inspect_spectra"]]$count - 1 # Increment the counter by 1 when button is click
}
else{
react.var[["inspect_spectra"]]$count <- react.var[["inspect_spectra"]]$max.count # Increment the counter by 1 when button is click
}
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
})
observeEvent(input$find_spectrum, {
if (length(react.var[["inspect_spectra"]])>0){
file.name.match.indx<-grep(input$specific_spectra,react.var[["inspect_spectra"]]$file.names)
if (length(file.name.match.indx) == 0){
showNotification("There are no filenames matching this pattern.")
} else {
if (length(file.name.match.indx) > 1){
showNotification("There are multiple filenames matching this pattern. The first match was used by default.")
}
react.var[["inspect_spectra"]]$count <- file.name.match.indx[1]
if (input$inspect_normalize %in% "Yes"){
y.label<- paste("Normalized",input$intensity_units, sep = " ")
} else {
y.label<- paste(input$intensity_units,"")
}
output$inspect_plot <- renderPlot({
d_spectra_inspect_tmp <- data.frame(wavelength=react.var[["inspect_spectra"]]$wavelength,
response=as.numeric(react.var[["inspect_spectra"]]$spectra_wide[react.var[["inspect_spectra"]]$count,]))
ggplot() +
geom_line(data=d_spectra_inspect_tmp,aes(x=wavelength,y=response)) +
theme_bw() +
labs(x="Wavelength (nm)", y = y.label,title = react.var[["inspect_spectra"]]$file.names[react.var[["inspect_spectra"]]$count])
})
}
}
})
#Select directory for analysis
dir_load<-shinyDirChoose(
input,
'dir',
roots = c(wd = '.'),
filetypes = c("tsv", "csv")
)
global <- reactiveValues(datapath = getwd())
dir <- reactive(input$dir)
output$dir <- renderText({
global$datapath
})
observeEvent(ignoreNULL = TRUE,
eventExpr = {
input$dir
},
handlerExpr = {
if (!"path" %in% names(dir())) return()
home <- normalizePath(".")
global$datapath <-
file.path(home, paste(unlist(dir()$path[-1]), collapse = .Platform$file.sep))
})
}
shinyApp(ui = ui, server = server)
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