---
output: html_document
runtime: shiny_prerendered
author: Environmental Cheminformatics Group, LCSB, University of Luxembourg
title: "`r paste('Shinyscreen', packageVersion('shinyscreen'))`"
---

```{r, context='setup', include='false'}
def_state <- new_state()
def_datafiles <- shinyscreen:::dtable(File=character(0),
                                      tag=character(0))
def_datatab <- shinyscreen:::dtable("tag"=factor(),
                                    "adduct"=factor(levels=shinyscreen:::DISP_ADDUCTS),
                                    "set"=factor())
## def_state$input$tab$tags <- def_datatab
rv_state <- list2rev(def_state)
compl_sets <- eventReactive(rv_state$input$tab$setid,
                            rv_state$input$tab$setid[,unique(set)])
## Reactive values to support some of the UI elements.
## rv_ui <- reactiveValues(datatab=def_tags)

```


# Configuration {.tabset}

## Inputs


<details>
<summary>Specify the project directory</summary>
This is where the output files and the state of the analysis will be
saved.
</details>
```{r, echo=FALSE}
actionButton(inputId = "project_b",
             label= "Project")

```

Current project directory is `r textOutput("project", inline=T)`



Load the config file if needed.

```{r, echo=FALSE}
actionButton(inputId = "conf_file_b",
             label= "Load config")

```

<details><summary>Load the compound list(s)</summary>
A compound list is composed of entries describing compounds. This
description is used to search for its spectrum in the data file. The
list is a table in the ***CSV*** format and contains these columns,

* ***ID*** : required column, must be filled; this is a user-defined
  ID, uniquely associated with a compound
  
* ***Name*** : this column can be left blank; if not, it should contain the
  names of the compounds
  
* ***SMILES*** : a _SMILES_ string, describing the structure of the
  compound; this entry can be left empty only if one of either
  ***Formula***, or ***mz*** entries are not
  
* ***Formula*** : a chemical formula of a compound; this field can be
  empty only if one of either ***SMILES***, or ***mz*** entries are
  not
  
* ***mz*** : mass of the ionised compound; this field can be left
  empty only if one of either ***SMILES***, or ***Formula*** is not
  
* ***CAS*** : the CAS number of the compound; it can be left empty

* ***RT*** : retention time of the MS1 peak in minutes, if known; can
  be left empty.
  
Only ***ID*** and one of ***SMILES***, ***Formula*** or ***mz*** must
be filled. When structure, or a formula of a compound is known, it is
also possible to look for various adducts in the sample. Of course,
scanning for completely unknown compounds is also supported by the
***mz*** column. In this case, ***mz*** is the mass of the ion.

It is strongly recommended to quote SMILES, names and formulas in the
CSV file used with Shinyscreen.
</details>
```{r, echo=FALSE}
actionButton(inputId = "comp_list_b",
             label= "Compound list(s)")

```

`r htmlOutput("comp_lists")`

<details><summary>Load compound set list (_setid_ table)</summary>
The compound lists can contain more entries than is necessary. Using
the _setid_ lists, it is possible to create _compound sets_ which
contain only those compounds that will actually be searched for in the
data files. A _setid table_ is a _CSV_ containing at least two
columns,

* ***ID*** : the ID entry from the compound list

* ***set*** : an user-defined set name.
</details>
```{r, echo=FALSE}
actionButton(inputId = "setid_b",
             label= "Load the setid table")

```

`r htmlOutput("setids", inline=T)`

## Data files
<details><summary>Load data files</summary>
Shinyscreen currently supports only the **mzML** file format. After
loading the files, set file tags in the file table (column
**tag**). Additionally, specify a set of compounds that is supposed
to be extracted from the file using the **set** column. Finally,
specify the **adduct** in the adduct column. In case of compounds
with unknown structure and formula, the adduct is ignored for obvious
reasons.
</details>
```{r, echo=FALSE}
actionButton(inputId = "datafiles_b",
             label= "Load data files.")

```




<details><summary>Assign tags to data files.</summary>
Each tag designates an unique file. Use the table below to assign
tags.
</details>

```{r, echo=FALSE}
rhandsontable::rHandsontableOutput("datafiles")

```




<details><summary>Assign sets to tags.</summary>
For each tag, assign a set and an adduct (if the structure information
exists, otherwise _adduct_ column is ignored).
</details>

```{r, echo=F}
rhandsontable::rHandsontableOutput("datatab")
```

## Extraction

### Spectra extraction based settings

<details><summary>MS1 coarse error</summary>

Extract all entries matching the target mass within this error in the
precursor table.
</details>
```{r, echo=F}
shinyscreen::mz_input(input_mz = "ms1_coarse",
                       input_unit = "ms1_coarse_unit",
                       def_mz = def_state$conf$tolerance[["ms1 coarse"]],
                       def_unit = "Da")
```

<details><summary>MS1 fine error</summary>

The precursor table masses can be of lower accuracy. Once there is a
match within the coarse error, it can be further checked versus the
fine error bounds directly in the mass spectrum.

</details>
```{r, echo=F}
shinyscreen::mz_input(input_mz = "ms1_fine",
                      input_unit = "ms1_fine_unit",
                      def_mz = def_state$conf$tolerance[["ms1 fine"]],
                      def_unit = "ppm")
```

<details><summary>MS1 EIC window</summary>

The mz interval over which the intensities are aggregated to generate
a chromatogram.

</details>
```{r, echo=F}
shinyscreen::mz_input(input_mz = "ms1_eic",
                      input_unit = "ms1_eic_unit",
                      def_mz = def_state$conf$tolerance[["eic"]],
                      def_unit = "Da")
```

<details><summary>Retention time window</summary>

If the expected retention time has been specified for the compound,
then search for the MS1 signature inside the window defined by this
range.

</details>
```{r, echo=F}
shinyscreen::rt_input(input_rt = "ms1_rt_win",
                      input_unit = "ms1_rt_win_unit",
                      def_rt = def_state$conf$tolerance[["rt"]],
                      def_unit = "min")
```

## Prescreening

<details><summary>MS1 intensity threshold</summary>

Ignore MS1 signal below the threshold.

</details>
```{r, echo=F}

numericInput(inputId = "ms1_int_thresh",
             label = NULL,
             value = def_state$conf$prescreen$ms1_int_thresh)
```

<details><summary>MS2 intensity threshold</summary>

Ignore MS2 signal below the threshold.

</details>
```{r, echo=F}

numericInput(inputId = "ms2_int_thresh",
             label = NULL,
             value = def_state$conf$prescreen$ms2_int_thresh)
```


MS1 signal-to-noise ratio.

```{r, echo=F}

numericInput(inputId = "s2n",
             label = NULL,
             value = def_state$conf$prescreen$s2n)
```


<details><summary>MS1/MS2 retention delay.</summary>

Look for associated MS2 spectrum within this window around the MS1
peak.

</details>
```{r, echo=F}
shinyscreen::rt_input(input_rt = "ret_time_shift_tol",
                      input_unit = "ret_time_shift_tol_unit",
                      def_rt = def_state$conf$tolerance[["ret_time_shift_tol"]],
                      def_unit = "min")
```

## Filter and order the summary table
<div style= "display: flex; vertical-align:top; ">
<div>
<details><summary>Filter summary table</summary>
Selection criteria for filtering entries in the summary table
according to the QA criteria.

* **qa_pass** : entries that passed all checks

* **qa_ms1_exists** : MS1 intensity is above the MS1 threshold

* **qa_ms2_exists** : those entries for which some MS2 spectra have been found

* **qa_ms1_above_noise** : MS1 is intense enough and above the noise level

* **qa_ms2_good_int** : MS2 intensity is above the MS2 threshold

* **qa_ms2_near** : MS2 spectrum is close enough to the MS1 peak
</details>
```{r, echo=F}
checkboxGroupInput("summ_subset",
                   label=NULL,
                   choiceNames = shinyscreen:::QA_FLAGS,
                   choiceValues = shinyscreen:::QA_FLAGS)


```
</div>
<div>
<details><summary>Ordering by columns</summary>
It is possible to order the summary table using columns (keys): 
*`r paste(gsub("^-(.+)","\\1",shinyscreen:::DEF_INDEX_SUMM), collapse = ',')`*.
The sequence of columns in the table below describes the
sequence of ordering steps -- the key in the first row sorts the
entire summary table and subsequent keys break the ties.

</details>

```{r, echo=F}
rhandsontable::rHandsontableOutput("order_summ")
```

</div>

</div>




<!-- <details><summary>Order entries</summary> -->

<!-- Sequence of column a -->

<!-- </details> -->
<!-- ```{r, echo=F} -->
<!-- checkboxGroupInput("summ_subset", -->
<!--                    label=NULL, -->
<!--                    choiceNames = shinyscreen:::QA_FLAGS, -->
<!--                    choiceValues = 1:length(shinyscreen:::QA_FLAGS)) -->

<!-- ``` -->


## Plots

### Logarithmic axis

```{r, echo=F}
checkboxGroupInput("plot_log",
                   label=NULL,
                   choiceNames = c("MS1 EIC","MS2 EIC","MS2 Spectrum"),
                   choiceValues = c(F,F,F))
```

### Global retention time range
```{r, echo=F}
shinyscreen::rt_input(input_rt = "plot_rt_min",
                      input_unit = "plot_rt_min_unit",
                      def_rt = NA_real_,
                      def_unit = "min",
                      pref = "min:")

shinyscreen::rt_input(input_rt = "plot_rt_max",
                      input_unit = "plot_rt_max_unit",
                      def_rt = NA_real_,
                      def_unit = "min",
                      pref = "max:")
```

## Report

```{r, echo=F}
shiny::textInput(inputId = "rep_aut", label = "Report author", value = def_state$conf$report$author)
shiny::textInput(inputId = "rep_tit", label = "Report title", value = def_state$conf$report$title)
```

# View compound Lists and Sets {.tabset}

## Compound List

```{r, echo=F}
DT::dataTableOutput("comp_table")
```

## Setid Table
```{r, echo=F}
DT::dataTableOutput("setid_table")
```

# Extract Data and Prescreen

<details><summary>Extract spectra from data files.</summary>

After Shinyscreen is configured, the compound and setid lists loaded, it
is possible to proceed with extracting the data. This is potentially a
time-intensive step, so some patience might be needed.

Once the data is extracted, it will be possible to quality check the
spectra associated with the compounds specified in the _setid_ list,
to subset that data, look at the plots and publish a report.

</details>
```{r, echo=FALSE}
actionButton(inputId = "extract",
             label = "Extract")
```


# Browse Results

<!-- Setup is here  -->

```{r, include="false", context='setup'}

ord_nms <- gsub("^-(.+)","\\1",shinyscreen:::DEF_INDEX_SUMM)
ord_asc <- grepl("^-.+",shinyscreen:::DEF_INDEX_SUMM)
ord_asc <- factor(ifelse(ord_asc, "descending", "ascending"),levels = c("ascending","descending"))
def_ord_summ <- shinyscreen:::dtable("Column names"=ord_nms,"Direction"=ord_asc)

```

```{r, include="false", context='server'}
## reactive functions

rf_compound_input_state <- reactive({
    sets <- rv_state$conf$compounds$sets
    lst <- as.list(rv_state$conf$compounds$lists)
    validate(need(length(lst)>0,
                  message = "Load the compound lists(s) first."))
    validate(need(nchar(sets)>0,
                  message = "Load the setid table first."))
    isolate({
        state <- rev2list(rv_state)
        m <- load_compound_input(state)
        ## Side effect! This is because my pipeline logic does not
        ## work nicely with reactive stuff.
        rv_state$input$tab$cmpds <- list2rev(m$input$tab$cmpds)
        rv_state$input$tab$setid <- m$input$tab$setid
        m
        })
})

rf_get_dfiles <- reactive({
    input$datafiles_b
    if (input$datafiles_b > 0) {
        filters <- matrix(c("mzML files", ".mzML",
                            "All files", "*"),
                          2, 2, byrow = TRUE)
        mzMLs <- tcltk::tk_choose.files(filters=filters)
        message("(config) Selected data files: ", paste(mzMLs,collapse = ","))
        mzMLs
    } else character(0)
})

rf_dfiles_tab <- reactive({
    mzMLs <- rf_get_dfiles()
    isolate({oldtab <- data.table::as.data.table(rhandsontable::hot_to_r(input$datafiles))})
    newf <- setdiff(mzMLs,oldtab$File)
    nr <- NROW(oldtab)
    tmp <- if (length(newf)>0) shinyscreen:::dtable(File=newf,tag=paste0('F',(nr+1):(nr + length(newf)))) else shinyscreen:::dtable(File=character(),tag=character())
    rbind(oldtab,
          tmp)
})
rf_tag_tab <- reactive({
    state <- rf_compound_input_state()
    isolate({oldtab <- rhandsontable::hot_to_r(input$datatab)})
    oldt <- oldtab$tag
    sets <- compl_sets()
    sets <- if (length(sets)==1) sets <- c(sets,"invalid") #Just
                                                           #because
                                                           #when one
                                                           #level,
                                                           #rhandsontable
                                                           #has issues
                                                           #displaying
                                                           #it.

    otagch <- as.character(oldt)
    df_tab <- rhandsontable::hot_to_r(input$datafiles)
    tagl <- df_tab$tag
    diff <- setdiff(tagl,
                    otagch)
    if (length(diff)!=0) {
        ## Only change the tag names in the old ones.
        pos_tag <- 1:length(tagl)
        pos_old <- 1:NROW(oldtab)
        pos_mod <- intersect(pos_tag,pos_old)
        new_tag <- tagl[pos_mod]
        if (NROW(oldtab)>0) oldtab[pos_mod,tag := ..new_tag]

        ## Now add tags for completely new files, if any.
        rest_new <- if (NROW(oldtab) > 0) setdiff(diff,new_tag) else diff
        tmp <- shinyscreen:::dtable(tag=factor(rest_new,levels=tagl),
                                    adduct=factor(levels = shinyscreen:::DISP_ADDUCTS),
                                    set=factor(levels = sets))

        dt <-data.table::as.data.table(rbind(as.data.frame(oldtab),
                                             as.data.frame(tmp)))
        dt[tag %in% df_tab$tag,]
    } else oldtab
})
```

```{r, include="false", context='server'}

observeEvent(input$project_b,{
    wd <- tcltk::tk_choose.dir(default = getwd(),
                               caption = "Choose project directory")
    message("Set project dir to ", wd)
    rv_state$conf$project <- wd
})

observeEvent(input$comp_list_b, {
    filters <- matrix(c("CSV files", ".csv",
                        "All files", "*"),
                       2, 2, byrow = TRUE)
    compfiles <- tcltk::tk_choose.files(filters=filters)
    message("(config) Selected compound lists: ", paste(compfiles,collapse = ","))
    rv_state$conf$compounds$lists <- if (length(compfiles)>0 && nchar(compfiles[[1]])>0) compfiles else "Nothing selected."
})

observeEvent(input$setid_b, {
    filters <- matrix(c("CSV files", ".csv",
                        "All files", "*"),
                       2, 2, byrow = TRUE)
    setids <- tcltk::tk_choose.files(filters=filters)
    message("(config) Selected compound sets (setid): ", paste(setids,collapse = ","))
    rv_state$conf$compounds$sets <- if (length(setids)>0 && nchar(setids[[1]])>0) setids else "Nothing selected."
})

observeEvent(input$extract,{
    tmp <- rev2list(rv_state)
    fn_c_state <- file.path(tmp$conf$project,
                            shinyscreen:::FN_CONF)
    yaml::write_yaml(x=tmp$conf,file=fn_c_state)
    message("(extract) Config written to ", fn_c_state)
})



```

<!-- Render -->
```{r, include="false", context="server"}
output$project <- renderText(rv_state$conf$project)

output$comp_lists <- renderText({
    lsts <- rev2list(rv_state$conf$compounds$lists)
    if (length(lsts) > 0 &&
        isTruthy(lsts) &&
        lsts != "Nothing selected.") {
        paste(c("<ul>",
                sapply(lsts,
                       function (x) paste("<li>",x,"</li>")),
                "</ul>"))
    } else "No compound list selected yet."
})

output$setids <- renderText({
    sets <- rv_state$conf$compounds$sets
    if (isTruthy(sets) && sets != "Nothing selected.")
        paste("selected <em>setid</em> table:",
              sets) else "No <em>setid</em> table selected."
})

output$order_summ <- rhandsontable::renderRHandsontable(rhandsontable::rhandsontable(def_ord_summ,
                                                                                     manualRowMove = T))

output$datafiles <- rhandsontable::renderRHandsontable(
{
    res <- if (length(rf_get_dfiles())>0) {
               rf_dfiles_tab()

           } else def_datafiles
    rhandsontable::rhandsontable(as.data.frame(res),
                                 width = "50%",
                                 height = "25%",
                                 allowInvalid=F)
})

output$datatab <- rhandsontable::renderRHandsontable(
{
    df <- rhandsontable::hot_to_r(input$datafiles)
    res <- if (NROW(rv_state$input$tab$setid) > 0 &&
               NROW(df) > 0) rf_tag_tab() else def_datatab

    rhandsontable::rhandsontable(res,stretchH="all",
                                 allowInvalid=F)
})

output$comp_table <- DT::renderDataTable({
    state <- rf_compound_input_state()


    DT::datatable(state$input$tab$cmpds,
                  style = 'bootstrap',
                  class = 'table-condensed',
                  extensions = 'Scroller',
                  options = list(scrollX = T,
                                 scrollY = 200,
                                 deferRender = T,
                                 scroller = T))
})

output$setid_table <- DT::renderDataTable({
    state <- rf_compound_input_state()

    DT::datatable(state$input$tab$setid,
                  style = 'bootstrap',
                  class = 'table-condensed',
                  extensions = 'Scroller',
                  options = list(scrollX = T,
                                 scrollY = 200,
                                 deferRender = T,
                                 scroller = T))
})
```

```{r, echo=F, context = 'server'}
session$onSessionEnded(function () stopApp())
```