{% extends "op_zz_frame.html" %}
{% block centercontent %}


  <style>
:root{--bg:#006B52;--panel:#FFFFFF;--border:#D5D5D5;--text:#0b110f;--muted:#3a4a46;--accent:#008143}
*{box-sizing:border-box}
body{margin:0;background:var(--bg);color:var(--text);font-family:system-ui,-apple-system,Segoe UI,Roboto,Ubuntu,Arial,sans-serif}
.header{display:flex;align-items:center;gap:10px;padding:14px 20px;background:linear-gradient(180deg,#006B52,#008143);color:#fff;border-bottom:1px solid rgba(255,255,255,.2)}
.header .brand{font-weight:800}
.container{max-width:1140px;margin:0 auto;padding:20px}
.card{background:var(--panel);border:1px solid var(--border);border-radius:12px;padding:14px;margin-top:14px;box-shadow:0 2px 8px rgba(0,0,0,.05)}
.grid{display:grid;grid-template-columns:2.1fr 2.9fr;gap:14px}
.controls .row{display:flex;gap:12px;align-items:center;flex-wrap:wrap;margin:8px 0}
.controls label{font-size:14px;color:var(--muted)}
.controls input[type='range']{width:220px}
.pill{padding:6px 10px;border-radius:999px;background:#f5f8f7;border:1px solid var(--border);font-size:12px;margin-right:8px}
.figure-wrap{position:relative}
.figure-wrap img{width:100%;height:auto;display:block;border:1px solid var(--border);border-radius:10px}
.overlay{position:absolute;left:0;top:0;right:0;bottom:0;pointer-events:none}
.kpi-grid{display:grid;grid-template-columns:repeat(3,1fr);gap:12px;margin-top:10px}
.kpi .lbl{font-size:12px;color:var(--muted);text-transform:uppercase;letter-spacing:.08em}
.kpi .val{font-size:22px;font-weight:800;margin-top:4px}
.btn{display:inline-block;padding:8px 10px;border:1px solid var(--border);border-radius:8px;background:#f5f8f7;color:#0f2b23;font-size:14px;text-decoration:none}
.btn:hover{border-color:#b8d2c5}
select, input[type='number']{padding:6px 8px;border:1px solid var(--border);border-radius:8px}
.small{font-size:12px;color:var(--muted)}
</style>

  <div class="header">
    <div class="brand">Degradation & Range Tool</div>
    <div style="margin-left:auto">
      <a class="btn" href="bhi_dashboard.html">Back to dashboard</a>
      <a class="btn" href="bhi_methodology.html#refs">Methodology</a>
    </div>
  </div>
  <div class="container">
    <div class="grid">
      <div class="card controls">
        <h3 style="margin:0 0 8px 0">Vehicle & inputs</h3>
        <div class="row">
          <label>Vehicle</label>
          <select id="vehSel"></select>
          <a class="btn" id="useOEM">Set SoH = latest OEM</a>
          <a class="btn" id="useManual">Set SoH = latest Manual</a>
        </div>
        <div class="row"><span class="pill" id="capPill">Nominal capacity: –</span><span class="pill" id="odoPill">Odometer: – km</span><span class="pill" id="consPill">Base consumption: – kWh/100km</span><span class="pill" id="refPill">Last ref: –</span></div>
        <hr style="border:0;border-top:1px solid var(--border)"/>
        <div class="row">
          <label>Model</label>
          <select id="modelSel">
            <option value="typical">Typical curve</option>
            <option value="oem">OEM-calibrated (this vehicle)</option>
            <option value="fleet">Fleet regression</option>
          </select>
          <span class="small">Switch to compare different degradation assumptions.</span>
        </div>
        <div class="row">
          <label>Climate sensitivity</label>
          <input type="range" min="-1" max="1" value="0" step="1" id="climateRange"/>
          <span id="climateLbl" class="pill">Neutral</span>
          <span class="small">Cold → faster degradation & wider CI; Warm → slower & narrower.</span>
        </div>
        <div class="row">
          <label>SoH (%)</label>
          <input type="range" min="60" max="100" value="90" step="0.5" id="sohRange"/>
          <input type="number" id="sohNum" min="60" max="100" step="0.5" style="width:90px"/>
        </div>
        <div class="row">
          <label>EoL SoH (%)</label>
          <input type="range" min="60" max="90" value="70" step="0.5" id="eolRange"/>
          <input type="number" id="eolNum" min="60" max="90" step="0.5" style="width:90px"/>
          <label>Duty</label>
          <select id="dutySel">
            <option value="70">Delivery / logistics (70%)</option>
            <option value="75">Ride-hailing / taxi (75%)</option>
            <option value="80">Private / pool (80%)</option>
          </select>
          <a class="btn" id="applyDuty">Apply EoL suggestion</a>
        </div>
        <div class="row">
          <label>Month</label>
          <select id="monthSel"></select>
          <span class="small">Affects consumption & charging losses for the range band.</span>
        </div>
      </div>

      <div class="card">
        <h3 style="margin:0 0 8px 0">Degradation curve & uncertainty</h3>
        <div class="figure-wrap" id="figWrap" data-left="0.125" data-bottom="0.10999999999999999" data-width="0.775" data-height="0.77" data-xmin="0" data-xmax="300000" data-ymin="60" data-ymax="100">
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"/>
          <canvas class="overlay" id="overlay"></canvas>
        </div>
        <small>The shaded area indicates the confidence band around the selected model. The dot shows (odometer, SoH). The dashed line marks the EoL km.</small>
      </div>
    </div>

    <div class="card">
      <h3 style="margin:0 0 8px 0">Computed results</h3>
      <div class="kpi-grid">
        <div class="card kpi"><div class="lbl">Range per full charge (this month)</div><div class="val"><span id="rangeThis">–</span></div></div>
        <div class="card kpi"><div class="lbl">Seasonal range band (min–max)</div><div class="val"><span id="rangeBand">–</span></div></div>
        <div class="card kpi"><div class="lbl">Predicted total lifetime</div><div class="val"><span id="lifeTotal">–</span> km</div></div>
      </div>
      <div class="kpi-grid">
        <div class="card kpi"><div class="lbl">Remaining to EoL</div><div class="val"><span id="lifeRemain">–</span> km</div></div>
        <div class="card kpi"><div class="lbl">EoL km (selected model)</div><div class="val"><span id="lifeEoL">–</span> km</div></div>
        <div class="card kpi"><div class="lbl">Current position on curve</div><div class="val"><span id="posLbl">–</span></div></div>
      </div>
    </div>

    <div class="card">
      <h3 style="margin:0 0 8px 0">Model notes</h3>
      <ul>
        <li><b>Typical curve:</b> 100%→95% by 30k km, 95%→80% by 200k km, 70% by 300k km (piecewise linear).</li>
        <li><b>OEM‑calibrated:</b> typical shape adjusted to pass through the last reference SoH at the vehicle's odometer.</li>
        <li><b>Fleet regression:</b> straight‑line fit of SoH vs km across the current fleet; CI from residual stddev.</li>
        <li><b>Climate:</b> Cold widens CI and slightly steepens slope; Warm narrows CI and slightly flattens slope.</li>
        <li><b>Range:</b> Uses nominal capacity × SoH; month adjusts consumption and charging losses; "band" spans worst↔best months.</li>
      </ul>
    </div>
  </div>

  <script>
  const vehicles = [{"id": "DEK-001", "alias": "Vehicle 1", "cap_nom": 62.0, "odometer_km": 200818, "consumption_kwh_per_100km": 19.3, "last_ref_soh": 86.1, "last_ref_type": "OEM"}, {"id": "DEK-002", "alias": "Vehicle 2", "cap_nom": 72.0, "odometer_km": 222877, "consumption_kwh_per_100km": 18.1, "last_ref_soh": 93.0, "last_ref_type": "OEM"}, {"id": "DEK-003", "alias": "Vehicle 3", "cap_nom": 72.0, "odometer_km": 39951, "consumption_kwh_per_100km": 15.0, "last_ref_soh": 89.4, "last_ref_type": "OEM"}, {"id": "DEK-004", "alias": "Vehicle 4", "cap_nom": 62.0, "odometer_km": 169627, "consumption_kwh_per_100km": 18.5, "last_ref_soh": 87.5, "last_ref_type": "OEM"}, {"id": "DEK-005", "alias": "Vehicle 5", "cap_nom": 62.0, "odometer_km": 27077, "consumption_kwh_per_100km": 21.7, "last_ref_soh": 87.3, "last_ref_type": "OEM"}];
  const typical = {"x1": 30000, "soh1": 95.0, "x2": 200000, "soh2": 80.0, "xMax": 300000, "soh0": 100.0, "sohEnd": 70.0};
  const fleetReg = {"slope": 7.3516632454172025e-06, "intercept": 87.68906583517774, "sigma": 2.3366742027698906};
  const season = [{"m": "Jan", "cons": 1.15, "loss": 0.1}, {"m": "Feb", "cons": 1.12, "loss": 0.09}, {"m": "Mar", "cons": 1.06, "loss": 0.06}, {"m": "Apr", "cons": 1.02, "loss": 0.04}, {"m": "May", "cons": 0.98, "loss": 0.03}, {"m": "Jun", "cons": 0.97, "loss": 0.02}, {"m": "Jul", "cons": 0.97, "loss": 0.02}, {"m": "Aug", "cons": 0.98, "loss": 0.02}, {"m": "Sep", "cons": 1.0, "loss": 0.03}, {"m": "Oct", "cons": 1.03, "loss": 0.05}, {"m": "Nov", "cons": 1.08, "loss": 0.07}, {"m": "Dec", "cons": 1.13, "loss": 0.1}];

  function modelTypical(km, climate=0){
    // piecewise with optional slope factor by climate
    const p = typical;
    const f = (climate===-1)? 1.05 : (climate===1? 0.95 : 1.0); // cold=steeper, warm=flatter
    function seg(xa, ya, xb, yb, x){
      return ya + (yb-ya) * ((x-xa)/(xb-xa));
    }
    if(km <= p.x1) return seg(0, p.soh0, p.x1, p.soh1 + (p.soh1- p.soh0)*(1-f), km);
    if(km <= p.x2) return seg(p.x1, p.soh1, p.x2, p.soh2 + (p.soh2- p.soh1)*(1-f), km);
    return seg(p.x2, p.soh2, p.xMax, p.sohEnd + (p.sohEnd- p.soh2)*(1-f), km);
  }

  function modelOEM(km, veh, climate=0){
    // shift typical vertically so that model(odo)=veh.last_ref_soh
    const baseAtOdo = modelTypical(veh.odometer_km, 0);
    const shift = veh.last_ref_soh - baseAtOdo;
    const base = modelTypical(km, climate);
    return Math.max(60, Math.min(100, base + shift));
  }

  function modelFleet(km, climate=0){
    const a = fleetReg.intercept;
    let b = fleetReg.slope;
    // climate: slight slope tweak
    b = b * (climate===-1? 1.1 : (climate===1? 0.9 : 1.0));
    return Math.max(60, Math.min(100, a + b*km));
  }

  function bandWidth(model, km, climate=0){
    // base ± CI in pp; widen/narrow with climate and model type
    let base = 3.0;
    if(model==='fleet') base = Math.max(2.0, fleetReg.sigma*2.0);
    if(model==='oem') base = 3.0;
    if(climate===-1) base += 1.5;
    if(climate===1) base -= 0.8;
    return Math.max(1.5, base);
  }

  function kmAtSoH_target(model, veh, targetSoH, climate){
    // invert numerically (bisection)
    let lo=0, hi=typical.xMax;
    for(let i=0;i<40;i++){
      const mid=(lo+hi)/2;
      const y = (model==='typical')? modelTypical(mid, climate)
               : (model==='oem')? modelOEM(mid, veh, climate)
               : modelFleet(mid, climate);
      if(y > targetSoH) lo = mid; else hi = mid;
    }
    return (lo+hi)/2;
  }

  // Axes mapping
  const wrap = document.getElementById('figWrap');
  const axesImg = document.getElementById('axesImg');
  const canvas = document.getElementById('overlay');
  const ctx = canvas.getContext('2d');

  function mapInit(){
    canvas.width = axesImg.clientWidth;
    canvas.height = axesImg.clientHeight;
  }
  function mapX(x){
    const left = parseFloat(wrap.dataset.left);
    const width = parseFloat(wrap.dataset.width);
    const xmin = parseFloat(wrap.dataset.xmin);
    const xmax = parseFloat(wrap.dataset.xmax);
    const W = axesImg.clientWidth;
    const fx = (x - xmin) / (xmax - xmin);
    return (left + fx * width) * W;
  }
  function mapY(y){
    const bottom = parseFloat(wrap.dataset.bottom);
    const height = parseFloat(wrap.dataset.height);
    const ymin = parseFloat(wrap.dataset.ymin);
    const ymax = parseFloat(wrap.dataset.ymax);
    const H = axesImg.clientHeight;
    const fy = (y - ymin) / (ymax - ymin);
    const figY = bottom + fy * height;
    return (1 - figY) * H;
  }

  // UI elements
  const vehSel = document.getElementById('vehSel');
  const sohR = document.getElementById('sohRange');
  const sohN = document.getElementById('sohNum');
  const eolR = document.getElementById('eolRange');
  const eolN = document.getElementById('eolNum');
  const capPill = document.getElementById('capPill');
  const odoPill = document.getElementById('odoPill');
  const consPill = document.getElementById('consPill');
  const refPill = document.getElementById('refPill');
  const modelSel = document.getElementById('modelSel');
  const climateRange = document.getElementById('climateRange');
  const climateLbl = document.getElementById('climateLbl');
  const dutySel = document.getElementById('dutySel');
  const applyDuty = document.getElementById('applyDuty');
  const monthSel = document.getElementById('monthSel');

  const rangeThis = document.getElementById('rangeThis');
  const rangeBand = document.getElementById('rangeBand');
  const lifeTotal = document.getElementById('lifeTotal');
  const lifeRemain = document.getElementById('lifeRemain');
  const lifeEoL = document.getElementById('lifeEoL');
  const posLbl = document.getElementById('posLbl');

  // Populate selectors
  vehicles.forEach(v=>{
    const opt = document.createElement('option');
    opt.value = v.id;
    opt.textContent = v.id + ' – ' + v.alias;
    vehSel.appendChild(opt);
  });
  season.forEach((s, idx)=>{
    const opt = document.createElement('option');
    opt.value = idx;
    opt.textContent = s.m;
    monthSel.appendChild(opt);
  });
  monthSel.value = new Date().getMonth().toString();

  // Preselect vehicle via ?vid=
  const params = new URLSearchParams(window.location.search);
  const qvid = params.get('vid');
  if(qvid && vehicles.some(v => v.id === qvid)) vehSel.value = qvid;

  function setSoH(val){ sohR.value = val; sohN.value = val; }
  function setEoL(val){ eolR.value = val; eolN.value = val; }

  const v0 = vehicles.find(x => x.id === vehSel.value) || vehicles[0];
  setSoH(v0.last_ref_soh.toFixed(1));
  setEoL(70);

  function climateText(v){
    return v==="-1"||v===-1? "Cold" : (v==="1"||v===1? "Warm" : "Neutral");
  }

  function recompute(){
    const v = vehicles.find(x => x.id === vehSel.value);
    if(!v) return;
    const climate = parseInt(climateRange.value);
    climateLbl.textContent = climateText(climate);

    capPill.textContent = 'Nominal capacity: ' + v.cap_nom + ' kWh';
    odoPill.textContent = 'Odometer: ' + Number(v.odometer_km).toLocaleString() + ' km';
    consPill.textContent = 'Base consumption: ' + v.consumption_kwh_per_100km.toFixed(1) + ' kWh/100km';
    refPill.textContent = 'Last ref (' + v.last_ref_type + '): ' + v.last_ref_soh.toFixed(1) + '%';

    const model = modelSel.value;
    const soh = parseFloat(sohR.value);
    const eol = parseFloat(eolR.value);

    // Lifetime (km) at EoL
    const kmEoL = kmAtSoH_target(model, v, eol, climate);
    lifeEoL.textContent = Math.round(kmEoL).toLocaleString();
    lifeTotal.textContent = Math.round(kmEoL).toLocaleString();
    const remain = Math.max(0, kmEoL - v.odometer_km);
    lifeRemain.textContent = Math.round(remain).toLocaleString();

    // Range this month & seasonal band
    const m = season[parseInt(monthSel.value)];
    const usable = v.cap_nom * (soh/100.0) * (1 - m.loss);
    const cons_this = v.consumption_kwh_per_100km * m.cons;
    const range_this = (usable / cons_this) * 100.0;
    rangeThis.textContent = Math.round(range_this).toLocaleString() + ' km';

    // Seasonal min/max across months
    let rmin=1e9, rmax=0;
    season.forEach(s=>{
      const u = v.cap_nom * (soh/100.0) * (1 - s.loss);
      const c = v.consumption_kwh_per_100km * s.cons;
      const r = (u / c) * 100.0;
      if(r<rmin) rmin=r;
      if(r>rmax) rmax=r;
    });
    rangeBand.textContent = Math.round(rmin).toLocaleString() + '–' + Math.round(rmax).toLocaleString() + ' km';

    // Position label
    posLbl.textContent = Number(v.odometer_km).toLocaleString() + ' km @ ' + soh.toFixed(1) + '% SoH';

    // Draw overlay
    drawOverlay(v, model, climate, soh, eol, kmEoL);
  }

  function drawOverlay(v, model, climate, soh, eol, kmEoL){
    mapInit();
    ctx.clearRect(0,0,canvas.width,canvas.height);

    // Curve + CI band
    const N=200;
    const xmin=0, xmax=typical.xMax;
    const xs=[], ys=[], yL=[], yU=[];
    for(let i=0;i<N;i++){
      const x = xmin + (xmax-xmin)*i/(N-1);
      let y = (model==='typical')? modelTypical(x, climate)
            : (model==='oem')? modelOEM(x, v, climate)
            : modelFleet(x, climate);
      const bw = bandWidth(model, x, climate);
      xs.push(x); ys.push(y); yL.push(Math.max(60,y-bw)); yU.push(Math.min(100,y+bw));
    }
    // band
    ctx.globalAlpha = 0.12;
    ctx.beginPath();
    for(let i=0;i<N;i++){
      const x = mapX(xs[i]); const y = mapY(yU[i]);
      if(i===0) ctx.moveTo(x,y); else ctx.lineTo(x,y);
    }
    for(let i=N-1;i>=0;i--){
      const x = mapX(xs[i]); const y = mapY(yL[i]);
      ctx.lineTo(x,y);
    }
    ctx.closePath();
    ctx.fillStyle = "#000000"; // default black with low alpha; UI colors handled by CSS
    ctx.fill();
    ctx.globalAlpha = 1.0;

    // curve
    ctx.beginPath();
    for(let i=0;i<N;i++){
      const x = mapX(xs[i]); const y = mapY(ys[i]);
      if(i===0) ctx.moveTo(x,y); else ctx.lineTo(x,y);
    }
    ctx.lineWidth = 2;
    ctx.strokeStyle = "#000000";
    ctx.stroke();

    // marker at (odo, SoH)
    const px = mapX(v.odometer_km);
    const py = mapY(soh);
    ctx.beginPath();
    ctx.arc(px, py, 4.5, 0, Math.PI*2);
    ctx.fillStyle = "#FFFFFF";
    ctx.fill();
    ctx.lineWidth = 2;
    ctx.strokeStyle = "#000000";
    ctx.stroke();

    // EoL vertical dashed line
    const ex = mapX(kmEoL);
    const yTop = mapY(100);
    const yBot = mapY(60);
    ctx.setLineDash([5,4]);
    ctx.beginPath();
    ctx.moveTo(ex, yTop);
    ctx.lineTo(ex, yBot);
    ctx.strokeStyle = "#000000";
    ctx.lineWidth = 1.5;
    ctx.stroke();
    ctx.setLineDash([]);
  }

  // Sync & handlers
  function syncInputs(src){
    if(src==='sohR') sohN.value = sohR.value;
    if(src==='sohN') sohR.value = sohN.value;
    if(src==='eolR') eolN.value = eolR.value;
    if(src==='eolN') eolR.value = eolN.value;
    recompute();
  }

  vehSel.addEventListener('change', ()=>{ setSoH(vehicles.find(x=>x.id===vehSel.value).last_ref_soh.toFixed(1)); recompute(); });
  sohR.addEventListener('input', ()=>syncInputs('sohR'));
  sohN.addEventListener('input', ()=>syncInputs('sohN'));
  eolR.addEventListener('input', ()=>syncInputs('eolR'));
  eolN.addEventListener('input', ()=>syncInputs('eolN'));
  modelSel.addEventListener('change', recompute);
  climateRange.addEventListener('input', recompute);
  monthSel.addEventListener('change', recompute);
  window.addEventListener('resize', recompute);
  document.getElementById('useOEM').addEventListener('click', (e)=>{ e.preventDefault(); const v=vehicles.find(x=>x.id===vehSel.value); setSoH(v.last_ref_soh.toFixed(1)); recompute(); });
  document.getElementById('useManual').addEventListener('click', (e)=>{ e.preventDefault(); /* if no manual, leaves as is */ recompute(); });
  document.getElementById('applyDuty').addEventListener('click', (e)=>{ e.preventDefault(); setEoL(dutySel.value); recompute(); });

  // Init after image load
  if(axesImg.complete) recompute();
  else axesImg.onload = recompute;
  </script>


<p>Total sessions: {{ stats.total_sessions or 0 }}</p>
<p>Total messages: {{ stats.total_msgs or 0 }}</p>
{% endblock %}