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1126 lines (988 loc) · 32.4 KB
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<!doctype html><html><head>
<meta charset=utf8>
<title>orbitrap</title>
<!--llibreries TODO-->
<script src="https://unpkg.com/vue@3/dist/vue.global.prod.js"></script>
<script
src="https://cdnjs.cloudflare.com/ajax/libs/exceljs/4.4.0/exceljs.min.js"
integrity="sha512-dlPw+ytv/6JyepmelABrgeYgHI0O+frEwgfnPdXDTOIZz+eDgfW07QXG02/O8COfivBdGNINy+Vex+lYmJ5rxw=="
crossorigin="anonymous"
referrerpolicy="no-referrer"
></script>
<style>
@keyframes animacio{
from{
background-color: orange;
}
to{
background-color: yellow;
}
}
div[treballant]{
animation-name: animacio;
animation-duration: 2s;
animation-iteration-count: infinite;
}
hr{
border:none;
border-top:1px solid #ccc;
}
[center]{
text-align:center;
}
[left]{
text-align:left;
}
[number]{
text-align:right;
font-family:monospace;
}
[empty]{
color:#ccc;
text-align:center;
font-family:monospace;
}
[monospace]{
font-family:monospace;
}
[yellow=true]{
background:gold;
}
label:hover{
background:gold;
}
[hover_underline]:hover{
text-decoration:underline;
cursor:pointer;
color:blue;
}
input[type=number]{
text-align:right;
}
table.subtaula{
font-size:smaller;
border-collapse:collapse;
border-color:#ddd;
}
table.subtaula tr.subtaula_header td{
background:#fafafa;
}
[millor_regresio=true]{
background:#af0;
}
[valigntop]{
vertical-align:top;
}
</style>
</head><body>
<nav>
<a href="xlsx" target="_blank">[dev] xlsx files</a>
</nav><hr>
<div>
<b>ORBITRAP automatic file processing</b>
</div><hr>
<div id=app>
<div v-if="!treballant && sheets_processats==0">
<!--instruccions-->
<details>
<summary><b>[info] Mandatory format of the input excel</b></summary>
<ul>
<li>Format ".xlsx"</li>
<li>Column "Filename"</li>
<li>Column "Area"</li>
<li>Column "Peak Label"</li>
<li>Filenames:
<ul>
<li>"CalCurve"</li>
<li>"MM"</li>
<li>"Blank"</li>
<li>"Recovery"</li>
</ul>
Every other filename will be considered as "samples"
</li>
<li> Blank name for MM: "MM_Blank_AIF" </li>
<li> Blank name for samples: "Blank_HPLC_AIF" </li>
<li> The name of the blank for the recovery will be deduced </li>
</ul>
</details><hr>
<!--seleccionar valor peak label-->
<p>
Column "Peak Label" value to filter:
<input v-model="peak_label">
</p>
<!--boto carregar excel-->
<input type=file @change="load_excel($event)">
</div>
<div v-if="error" style="background:red">
{{error}}
</div>
<div v-if="treballant" treballant>
<div>⏳ working...</div>
</div>
<div v-if="sheets_processats">
<ul>
<li>Filtered by "Peak Label" column value = "{{peak_label}}"</li>
<li>Total number of compounds loaded: {{sheets_processats}} (each sheet represents a compound)</li>
</ul>
</div><hr>
<div v-if="sheets">
<div
style="
display:flex;
gap:5px;
"
>
<!--menú per activar/desactivar filenames visibles-->
<table border=1>
<tr>
<th colspan=2 left>
Visible filenames
<button @click="filenames_seleccionats.clear()" :disabled="filenames_seleccionats.size==0" title="unselect all">X</button>
</th>
</tr>
<tr v-for="set,i in [noms_families_fixes, get_noms_mostres]">
<td>
{{[
"Calibration",
"Samples",
][i]}}
</td>
<td>
<span v-for="fn in Array.from(set)">
<label>
<input
type=checkbox
:checked="filenames_seleccionats.has(fn)"
@change="filenames_seleccionats[!filenames_seleccionats.has(fn)?'add':'delete'](fn)"
> {{fn}}
</label>
</span>
</td>
</tr>
</table>
<!--menú per activar/desactivar blancs-->
<table border=1>
<tr>
<th left>Subtract blank from</th>
<th left>Filename</th>
<th left></th>
</tr>
<tr>
<td>MM</td>
<td><code>"{{nom_blanc_MM}}"</code></td>
<td>
<label><input type=radio v-model="restar_blancs.MM" :value="true" > sí</label>
<label><input type=radio v-model="restar_blancs.MM" :value="false"> no</label>
</td>
</tr>
<tr>
<td>Recovery</td>
<td><code>"{{nom_blanc_recovery}}"</code></td>
<td>
<label><input type=radio v-model="restar_blancs.recovery" :value="true" > sí</label>
<label><input type=radio v-model="restar_blancs.recovery" :value="false"> no</label>
</td>
</tr>
<tr>
<td>Samples</td>
<td>
<code>"{{nom_blanc_mostres}}"</code>
<div>
<table>
<tr v-for="val in Object.values(blanks_de_mostres_detectats)" style="font-size:smaller">
<td><code>"{{val}}"</code></td>
</tr>
</table>
</div>
</td>
<td>
<label><input type=radio v-model="restar_blancs.mostres" :value="true" > sí</label>
<label><input type=radio v-model="restar_blancs.mostres" :value="false"> no</label>
</td>
</tr>
</table>
<table border=1>
<tr>
<th left>Choose Regression to compute PPB</th>
</tr>
<tr>
<td>
<label><input type=radio v-model=regressió_utilitzada value="CC">CalCurve</label><br>
<label><input type=radio v-model=regressió_utilitzada value="MM">MM</label><br>
<label><input type=radio v-model=regressió_utilitzada value="best">Best r<sup>2</sup> (CalCurve or MM)</label>
</td>
</tr>
</table>
</div><hr>
<!--filtres-->
<div
style="
display:grid;
grid-template-columns:repeat(4,1fr);
grid-gap:5px;
"
>
<!--filtre_nom_compost-->
<div>
<label>
Search compound name<br>
<input v-model="filtre_nom_compost"
style="
field-sizing: content;
min-width:150px;
padding:1px 5px;
"
:yellow="filtre_nom_compost!=''"
placeholder="compound name"
>
<button @click="filtre_nom_compost=''" :disabled="filtre_nom_compost==''">X</button>
</label><br>
</div>
<!--checkbox filtres regressio-->
<div>
<label>
<input type=checkbox v-model="veure_nomes_sheets_amb_regressio">
Filter by r<sup>2</sup>
</label><br>
<label>
r<sup>2</sup> >
<input type=number :disabled="veure_nomes_sheets_amb_regressio==false" v-model="r_squared_threshold"
min=0 max=9 step=0.01
>
</label>
</div>
<!--limits recovery-->
<div>
<table border=1 style="border-collapse:collapse">
<tr>
<td rowspan=3 center>
<label>
<input type=checkbox v-model="recovery_thresholds">
Filter by Recovery
</label>
</td>
</tr>
<tr>
<td>low</td>
<td>
<label>
<input type=number v-model="recovery_threshold_lo" :disabled="!recovery_thresholds" placeholder="Recovery threshold low" min=0 max=999>%
</label>
</td>
</tr>
<tr>
<td>high</td>
<td>
<label>
<input type=number v-model="recovery_threshold_hi" :disabled="!recovery_thresholds" placeholder="Recovery threshold high" min=0 max=999>%
</label>
</td>
</tr>
</table>
</div>
<div>
<label>
<input type=checkbox v-model="mostrar_area_NF">
Show rows with area "N/F"
</label><br>
</div>
</div><hr>
<div style="margin-top:5px">
<b>Results ({{get_sheets_filtrats.length}}/{{sheets.length}})</b>
</div>
<div v-if="get_sheets_filtrats.length==0" style="font-size:larger;color:#666">~No results</div>
<div v-if="get_sheets_filtrats">
<p>
<button @click="descarregar_fitxer_final()" :disabled="get_sheets_filtrats.length==0">
export results xlsx
</button>
</p>
</div>
<table border=1 style="border-collapse:collapse">
<tbody v-for="sheet in get_sheets_filtrats">
<tr>
<td monospace valigntop style="color:blue">
<span hover_underline @click="filtre_nom_compost=sheet.nom">
<span style="font-size:larger">{{sheet.nom}}</span>
</span>
<!--taula blanks-->
<div v-if="Object.values(sheet.blanks).length">
<br>
<table border=1 style="font-size:smaller;color:black">
<tr>
<th>blank</th>
<th>area</th>
</tr>
<tr v-for="[key,val] in Object.entries(sheet.blanks)">
<td>{{key}}</td>
<td>{{val}}</td>
</tr>
</table>
</div>
</td>
<td valigntop>
<table border=1 class=subtaula>
<tr class=subtaula_header>
<td>type</td>
<td>filename</td>
<td>area (raw)</td>
<td>area (-blank)</td>
<td>ppb theoric</td>
<td>ppb computed</td>
<td>
<div>ppb computed</div>
<div><small>(appl. recovery)</small></div>
</td>
<td title="exclude for linear regression calculation">
exclude
</td>
</tr>
<!--calibration-->
<tbody v-for="row in sheet.rows" v-if="cal_mostrar_taula_calibracio">
<tr
v-if="
filenames_seleccionats.has(row.family) && noms_families_fixes.has(row.family)
&& (mostrar_area_NF||row.area!='N/F')
"
v-for="area_blanked in [calcula_area_minus_blank(sheet, row.family, row.area)]"
>
<td style="color:#aaa">calibration</td>
<td monospace>
{{row.filename}}
</td>
<td number>
<div v-if="row.area=='N/F'" empty>
{{row.area}}
</div>
<div v-else>
{{row.area}}
</div>
</td>
<td number>
<div v-if="row.area!=area_blanked">
{{area_blanked}}
</div>
</td>
<td number>
<div v-if="row.ppb_teoric!=null" center>
{{row.ppb_teoric}}
</div>
<div v-else empty>∅</div>
</td>
<td number>
<div v-for="ppb_computed in [quantifica_area(sheet, area_blanked)]">
<div v-if="ppb_computed">
{{ppb_computed}}
</div>
<div v-else empty>∅</div>
</div>
</td>
<td empty>∅</td>
<td v-if="['CalCurve','MM','Recovery'].includes(row.family)" center>
<input type=checkbox v-model="row.exclude">
</td>
</tr>
</tbody>
<!--samples-->
<tbody v-for="row in sheet.rows" v-if="cal_mostrar_taula_mostres">
<tr
v-if="
filenames_seleccionats.has(row.family) && get_noms_mostres.has(row.family)
&& (mostrar_area_NF||row.area!='N/F')
"
v-for="area_blanked in [calcula_area_minus_blank(sheet, row.family, row.area)]"
>
<td style="color:#aaa">sample</td>
<td monospace>
{{row.filename}}
</td>
<td number>
<div v-if="row.area=='N/F'" empty>
{{row.area}}
</div>
<div v-else>
{{row.area}}
</div>
</td>
<td number>
<div v-if="row.area!=area_blanked">
{{area_blanked}}
</div>
</td>
<td empty>∅</td>
<td number>
<div v-for="ppb_computed in [quantifica_area(sheet, area_blanked)]">
<div v-if="ppb_computed">
{{ppb_computed}}
</div>
<div v-else empty>∅</div>
</div>
</td>
<td number >
<div v-for="rec in [sheet.recovery]">
<div v-if="rec">
{{quantifica_area(sheet, area_blanked)*100/rec}}
</div>
</div>
</td>
</tr>
</tbody>
</table>
</td>
<!--taules regressio i recovery-->
<td valigntop>
<div style="display:flex">
<div v-for="tipus_regressio in ['CC','MM']">
<div v-if="sheet.regressio[tipus_regressio]">
<table border=1 class=subtaula
v-if="regressió_utilitzada=='best' || regressió_utilitzada==tipus_regressio"
style="margin-bottom:2px"
>
<tr>
<th colspan=2
:millor_regresio="calcula_millor_regressio(sheet)==tipus_regressio"
>
<small>
Regression {{tipus_regressio=='CC'?'CalCurve':tipus_regressio}} (ppb = m·area + n)
</small>
</th>
</tr>
<tr>
<th>m</th>
<td number>{{sheet.regressio[tipus_regressio].m}}</td>
</tr>
<tr>
<th>n</th>
<td number>{{sheet.regressio[tipus_regressio].n}}</td>
</tr>
<tr>
<th>r<sup>2</sup></th>
<td number>{{sheet.regressio[tipus_regressio].r_squared}}</td>
</tr>
<tr>
<td>#points</td>
<td center monospace>{{sheet.regressio[tipus_regressio].N}}</td>
</tr>
</table>
</div>
</div>
</div>
<table
border=1
class=subtaula
v-if="sheet.recovery"
>
<tr>
<th>
<small>Recovery (%)</small>
</th>
<td>{{sheet.recovery}}</td>
</tr>
</table>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<script>
//mòdul per regressió lineal
function linear_regression(points){
//points: [{x,y},{x,y},...{x,y}]
let N = points.length; //number of points
if(N<3){ throw new Error("N<3 points"); }
//arrays of points
let xi = points.map(p=>p.x); //array x
let yi = points.map(p=>p.y); //array y
let xi_sq = xi.map(x=>x*x); //array x squared
let yi_sq = yi.map(y=>y*y); //array y squared
let xiyi = points.map(p=>{ //array x·y
return p.x*p.y;
});
//sums of arrays
let xi_sum = xi.reduce((p,c)=>p+c,0); //sum of x array
let yi_sum = yi.reduce((p,c)=>p+c,0); //sum of y array
let xi_sq_sum = xi_sq.reduce((p,c)=>p+c,0); //sum of x squared array
let yi_sq_sum = yi_sq.reduce((p,c)=>p+c,0); //sum of y squared array
let xiyi_sum = xiyi.reduce((p,c)=>p+c,0); //sum of x·y array
//compute m (slope) and n (intercept) as (y = mx + n)
let m = (N*(xiyi_sum) - yi_sum*xi_sum)/(N*xi_sq_sum - xi_sum*xi_sum);
let n = (yi_sum - m*xi_sum)/N;
//compute r squared
let r_squared = Math.pow(N*xiyi_sum - xi_sum*yi_sum, 2)/((N*xi_sq_sum - Math.pow(xi_sum,2))*(N*yi_sq_sum - Math.pow(yi_sum,2)));
//end
return {m, n, r_squared, N};
}
</script>
<script>
let app = Vue.createApp({
data(){return{
//valor "T1" a la columna "Peak Label" per filtrar al carregar l'excel
peak_label:"T1",
treballant:false,
err:"", //missatge error
wb:null, //objecte workbook que ha sigut carregat
//main array
sheets:null, //array sheets processats
sheets_processats:0, //number
//filenames fixes visibles
filenames_seleccionats: new Set(["CalCurve","MM","Blank","Recovery"]),
//regressio
veure_nomes_sheets_amb_regressio:true,
r_squared_threshold:0.9,
//recovery thresholds
recovery_thresholds:true,
recovery_threshold_lo:60,
recovery_threshold_hi:120,
//filtre nom compost
filtre_nom_compost:"",
//filenames que NO són mostres
//aquests noms surten a tots els excels, són fixos
noms_families_fixes:new Set([
"CalCurve", //"calibration curve"
"MM", //"matrix match"
"Blank", //blancs mostres
"Recovery", //recovery
]),
//restar blancs
restar_blancs:{
MM : true,
mostres : true,
recovery : true,
},
//forçar regressió utilitzada
regressió_utilitzada:"best",
//noms blancs
nom_blanc_MM:"MM_Blank_AIF",
nom_blanc_recovery:"Blank_recovery_AIF",
nom_blanc_mostres:"Blank_HPLC_AIF",
//configuracio mostrar "NFs" (valors àrea que no han sortit bé)
mostrar_area_NF:true,
//blanks de mostres detectats (family=>filename)
blanks_de_mostres_detectats:{},
}},
methods:{
async load_excel(event){
this.treballant = true;
this.error = "";
let file = event.target.files[0];
let wb = new ExcelJS.Workbook();
this.wb = wb;
try{
await wb.xlsx.load(file);
this.sheets = wb.worksheets.map(sheet=>{
return this.processa_sheet(sheet);
});
this.treballant=false;
}catch(err){
this.error=err;
this.treballant=false;
}
},
processa_sheet(sheet){
//sheet: objecte
/*
per cada sheet necessitem:
- nom compost
- array filename
- array area
- array peak label (i filtrar per valor=="T1")
*/
let nom = sheet.name;
try{
nom = sheet.columns[0].values[2];
}catch(err){}
//busca index columna "Filename"
let index_col_filename = sheet.columns.find(c=>c.values[1]=="Filename")._number;
//busca index columna "Area"
let index_col_area = sheet.columns.find(c=>c.values[1]=="Area")._number;
//busca index columna "Peak Label"
let index_col_peak_label = sheet.columns.find(c=>c.values[1]=="Peak Label")._number;
//blank per família (area=number)
let blanks={}; //{"family"=>area}
//filtra per "Peak Label"=="T1"
//i retorna [filename, area, peak_label]
let rows = sheet._rows.filter(r=>{
if(this.peak_label==""){
return true;
}else{
return r.values[index_col_peak_label] == this.peak_label;
}
}).map(r=>{
let filename = r.values[index_col_filename];
let family = filename.split("_")[0];
let area = r.values[index_col_area];
let peak_label = r.values[index_col_peak_label];
let ppb_teoric = null;
//comprova si aquesta dada correspon a un blank
//sino, assigna'l a recovery
if(family=="Blank" && filename!=this.nom_blanc_mostres){
this.nom_blanc_recovery=filename;
}
//calcula ppb_teoric
if(family=="CalCurve"||family=="MM"||family=="Recovery"){
ppb_teoric=0;//diferencia de null
let filename_split = filename.split("_");
for(let i=1;i<filename_split.length;i++){
let token = filename_split[i];
let token_parsed = parseInt(token);
if(!isNaN(token_parsed)){
ppb_teoric = token_parsed;
break;
}
}
}
if(family=="Blank"){
ppb_teoric=0;
}
//estableix valors dels blancs
if(filename==this.nom_blanc_MM){
if(area!="N/F"){
blanks.MM = area;
}
}
if(filename==this.nom_blanc_mostres){
if(area!="N/F"){
blanks.Samples = area;
}
}
if(filename==this.nom_blanc_recovery){
if(area!="N/F"){
blanks.Recovery = area;
}
}
if(!this.noms_families_fixes.has(family) && filename.toLowerCase().includes("blank")){
this.blanks_de_mostres_detectats[family]=filename;
if(area=="N/F"){
blanks[family]=0;
}else{
blanks[family]=area;
}
}
//exclude for linear regression
let exclude=false;
return {family,filename,area,peak_label,exclude,ppb_teoric};
});
this.sheets_processats++;
return {
nom, rows, blanks,
regressio:null,
recovery:null,
};
},
//adapta les dades per poder cridar "linear_regression()"
calcula_regressio(sheet, family){
family = family || "MM"; //"MM" || "CalCurve"
let rows = sheet.rows.filter(r=>r.family==family);
let punts = rows.filter(r=>!r.exclude).map(r=>{
let x = r.area;
if(family=="MM"){
x = this.calcula_area_minus_blank(sheet,family,r.area);
}
let y = 0;
let filename_split = r.filename.split("_");
for(let i=1;i<filename_split.length;i++){
let token = filename_split[i];
let token_parsed = parseInt(token);
if(!isNaN(token_parsed)){
y = token_parsed;
break;
}
}
return {x,y};
}).filter(p=>p.x!="N/F");
//result: {m,n,r2}
let result;
try{
result = linear_regression(punts);
}catch(err){
result = null;
}
return result;
},
calcula_recovery(sheet){
//mitjana dels recoveries
let recovery=[];//init empty array
let rows = sheet.rows.filter(r=>r.family=="Recovery"&&!r.exclude);
rows.forEach(row=>{
let area = row.area; //number | string ("N/F")
if(area=="N/F") return;
//restar blanc recovery
if(this.restar_blancs.recovery){
let blank=0;
let bl = sheet.blanks.Recovery;
if(bl) blank=bl;
area -= blank;
}
let ppb = this.quantifica_area(sheet,area); //number or NaN
if(ppb===false) return;
let teoric = 100;
let filename_split = row.filename.split("_");
for(let i=1;i<filename_split.length;i++){
let token = filename_split[i];
let token_parsed = parseInt(token);
if(!isNaN(token_parsed)){
teoric = token_parsed;
break;
}
}
let rec = 100*ppb/teoric; //percentatge
if(rec>0){
recovery.push(rec);
}
});
let N = recovery.length;
if(N==0) return false;
return recovery.reduce((p,c)=>p+c,0)/N;
},
//calcula PPB a partir d'àrea, fent servir regressions lineals (CC i MM)
// PPB = m·area + n
quantifica_area(sheet, area){
//sheet:object
//area:number
let CC = sheet.regressio.CC;
let MM = sheet.regressio.MM;
//tria quina de les dues regressions es farà servir: CC ò MM
let reg = null; //regressio triada (objecte)
if(this.regressió_utilitzada=="best"){
if(CC && MM){
if(CC.r_squared > MM.r_squared){
reg = CC;
}else{
reg = MM;
}
}else if(!CC && MM){
reg = MM;
}else if(!MM && CC){
reg = CC;
}else{
reg = false;
}
}
if(this.regressió_utilitzada=="CC"){
reg = CC;
}
if(this.regressió_utilitzada=="MM"){
reg = MM;
}
if(!reg) return false;
//aplica formula recta (y=mx+n)
let y = reg.m*area + reg.n;
//if(y<0) y=0;
return y;
},
calcula_area_minus_blank(sheet, family, area){
//sheet: object
//family: string
//area: number
if(area=="N/F") return "N/F";
let blank = 0;
//MM
if(family=="MM"){
if(this.restar_blancs.MM){
let bl = sheet.blanks.MM;
if(bl) blank=bl;
}
return area-blank;
}
//Recovery
if(family=="Recovery"){
if(this.restar_blancs.recovery){
let bl = sheet.blanks.Recovery;
if(bl) blank=bl;
}
return area-blank;
}
if(this.get_noms_mostres.has(family)){
if(this.restar_blancs.mostres){
let bl = sheet.blanks[family];
if(bl===undefined){
bl = sheet.blanks.Samples;
if(bl) blank=bl;
}else{
blank=bl;
}
}
return area-blank;
}
return area;
},
//wip TODO
descarregar_fitxer_final(){
let wb = new ExcelJS.Workbook();
//una fulla per cada compost
this.get_sheets_filtrats.forEach((sheet,i)=>{
let sh = wb.addWorksheet(`Compound ${i+1}`);
//regressions info
sh.addRow(['Regression','m','n','r2','#points']);
if(sheet.regressio.CC){
let reg = sheet.regressio.CC;
sh.addRow(['CalCurve', reg.m, reg.n, reg.r_squared, reg.N]);
}
if(sheet.regressio.MM){
let reg = sheet.regressio.MM;
sh.addRow(['MM', reg.m, reg.n, reg.r_squared, reg.N]);
}
sh.addRow(['']); //espai
//recovery info
if(sheet.recovery){
sh.addRow(['Recovery (%)', sheet.recovery]);
sh.addRow(['']); //espai
}
//lectures
sh.addRow(['Compound','Filename','area(raw)','area(-blank)','ppb theoric','ppb computed','ppb computed (+recovery)']);
//agafa files
let rows = [...sheet.rows];
//filtra per exclude
rows = rows.filter(r=>!r.exclude);
//filtra per area=="N/F"
if(this.mostrar_area_NF==false){
rows = rows.filter(r=>r.area!="N/F");
}
//filtra per filenames seleccionats
rows = rows.filter(r=>{
return this.filenames_seleccionats.has(r.family);
});
//processa rows
rows.forEach(row=>{
let family = row.family;
let area = row.area;
let area_blanked = this.calcula_area_minus_blank(sheet,family,area);
let ppb_teoric = row.ppb_teoric;
let ppb = this.quantifica_area(sheet,area_blanked);
let rec = sheet.recovery || 0;
let ppb_rec = null;
if(this.get_noms_mostres.has(family) && rec){
ppb_rec = ppb*100/rec;
}
sh.addRow([
sheet.nom,
row.filename,
area,
area_blanked,
ppb_teoric,
ppb,
ppb_rec,
]);
});
});
//export workbook to xlsx file
let fileType='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet';
wb.xlsx.writeBuffer().then(buffer=>{
let blob = new Blob([buffer],{type:fileType});
saveFile(blob);
}).catch(err=>{
console.log('Error writing excel file',err);
});
},
//calcula si és millor MM o CC
calcula_millor_regressio(sheet){
let millor = false; //return value