feat(calibration-step3): complete Strategy Promotion workflow and prepare Step 4 entry

Step 3 is now functionally complete and ready to hand off selected strategies
to the optimization stage (Step 4).

Main additions and improvements:

Strategy Promotion
- Added promotion engine results visualization.
- Promotion statuses supported: promote, review, review_diversity, reject.
- Diversity filter included in promotion results.

Manual Step 4 selection
- Added "Step 4" checkbox column in Promotion table.
- Default selection rules:
  - promote → selected automatically
  - review / review_diversity / reject → unselected by default
- User can manually override any selection.
- Selection source tracked (auto, manual_on, manual_off).

Step 4 selection artifact
- Implemented Step 4 selection builder.
- Generates JSON artifact with selected strategies and parameters.
- Includes promotion metadata (status, score, diversity info).
- Preview shown directly in UI.

Dataset metadata integration
- Added backend endpoint:
  GET /api/v2/calibration/strategies/data-info
- Returns dataset metadata:
  start_date, end_date, n_rows, n_days.
- UI now displays dataset information:
  Dataset: start → end | rows | days | WF windows.

Walk-forward estimation improvements
- WF windows calculated using real dataset size.
- Time estimation updated with calibrated formula:
  ~1.5 seconds per window per strategy.
- Time estimate now robust even without date inputs.

UI improvements
- Dataset info line added to calibration page.
- Promotion table extended with Step 4 controls.
- Step 4 selection summary and JSON preview added.

Architecture
- Step 3 now outputs a clean Step 4 selection artifact.
- Promotion acts as recommendation, not final decision.
- Human override supported.

This commit closes the functional implementation of Step 3
and prepares the pipeline for Step 4 (strategy parameter optimization).

src/web/api/v2/routers/calibration_strategies.py

@@ -5,8 +5,9 @@ import re
 import uuid
 from pathlib import Path
 from typing import Dict
+import pandas as pd
 
-from fastapi import APIRouter, Depends, HTTPException, Request
+from fastapi import APIRouter, Depends, HTTPException, Request, Query
 from fastapi.responses import JSONResponse, HTMLResponse
 
 from src.data.storage import StorageManager
@@ -76,6 +77,64 @@ def strategy_catalog():
     return {"strategies": enriched}
 
 
+@router.get("/status/{job_id}")
+def get_status(job_id: str):
+    return WF_JOBS.get(job_id, {"status": "unknown"})
+
+
+@router.get("/data-info")
+def get_dataset_info(
+    symbol: str = Query(...),
+    timeframe: str = Query(...),
+    storage: StorageManager = Depends(get_storage),
+):
+    df = storage.load_ohlcv(symbol=symbol, timeframe=timeframe)
+
+    if df is None or df.empty:
+        return {
+            "symbol": symbol,
+            "timeframe": timeframe,
+            "start_date": None,
+            "end_date": None,
+            "n_rows": 0,
+            "n_days": 0,
+        }
+
+    # soporta tanto índice datetime como columna timestamp/datetime
+    if hasattr(df.index, "min") and str(getattr(df.index, "dtype", "")).startswith("datetime"):
+        start_ts = df.index.min()
+        end_ts = df.index.max()
+    elif "timestamp" in df.columns:
+        ts = pd.to_datetime(df["timestamp"], errors="coerce")
+        start_ts = ts.min()
+        end_ts = ts.max()
+    elif "datetime" in df.columns:
+        ts = pd.to_datetime(df["datetime"], errors="coerce")
+        start_ts = ts.min()
+        end_ts = ts.max()
+    else:
+        start_ts = None
+        end_ts = None
+
+    if start_ts is not None and end_ts is not None and pd.notna(start_ts) and pd.notna(end_ts):
+        n_days = max(1, int((end_ts - start_ts).total_seconds() / 86400))
+        start_date = pd.Timestamp(start_ts).isoformat()
+        end_date = pd.Timestamp(end_ts).isoformat()
+    else:
+        n_days = 0
+        start_date = None
+        end_date = None
+
+    return {
+        "symbol": symbol,
+        "timeframe": timeframe,
+        "start_date": start_date,
+        "end_date": end_date,
+        "n_rows": int(len(df)),
+        "n_days": int(n_days),
+    }
+
+
 @router.post("/inspect", response_model=CalibrationStrategiesInspectResponse)
 def inspect_strategies(
     payload: CalibrationStrategiesInspectRequest,
@@ -258,8 +317,3 @@ def run_strategies_async(
     thread.start()
 
     return {"job_id": job_id}
-
-
-@router.get("/status/{job_id}")
-def get_status(job_id: str):
-    return WF_JOBS.get(job_id, {"status": "unknown"})

src/web/ui/v2/static/js/pages/calibration_strategies.js

@@ -6,6 +6,9 @@ let STRATEGY_CATALOG = [];
 let strategySlots = [];
 let selectedStrategyId = null;
 let lastValidationResult = null;
+let DATASET_INFO = null;
+let PROMOTION_RESULTS = [];
+let STEP4_SELECTION = [];
 const MAX_STRATEGIES = 10;
 
 // =================================================
@@ -111,6 +114,52 @@ function sleep(ms) {
 }
 
 
+function resolveDateRange() {
+  // 1) Prioridad: configuración heredada de steps anteriores
+  const cfg =
+    window.currentConfig ||
+    window.calibrationConfig ||
+    lastValidationResult?.config ||
+    null;
+
+  const candidates = [
+    cfg?.date_from,
+    cfg?.from_date,
+    cfg?.start_date,
+    cfg?.data?.date_from,
+    cfg?.data?.from_date,
+    cfg?.data?.start_date,
+  ];
+
+  const candidatesTo = [
+    cfg?.date_to,
+    cfg?.to_date,
+    cfg?.end_date,
+    cfg?.data?.date_to,
+    cfg?.data?.to_date,
+    cfg?.data?.end_date,
+  ];
+
+  const inheritedFrom = candidates.find(v => !!v) || null;
+  const inheritedTo = candidatesTo.find(v => !!v) || null;
+
+  if (inheritedFrom && inheritedTo) {
+    return { dateFrom: inheritedFrom, dateTo: inheritedTo };
+  }
+
+  // 2) Fallback: DOM, por si existen en algún layout
+  const domFrom = str("date_from");
+  const domTo = str("date_to");
+
+  if (domFrom && domTo) {
+    return { dateFrom: domFrom, dateTo: domTo };
+  }
+
+  // 3) Sin rango explícito
+  return { dateFrom: null, dateTo: null };
+}
+
+
 // =================================================
 // FETCH CATALOG
 // =================================================
@@ -454,6 +503,7 @@ function updateTimeEstimate(globalTotal) {
   const el =
     document.getElementById("wf_time_estimate") ||
     document.getElementById("time_estimate");
+
   if (!el) return;
 
   if (!globalTotal || globalTotal <= 0) {
@@ -463,31 +513,28 @@ function updateTimeEstimate(globalTotal) {
 
   const trainDays = num("wf_train_days") || 180;
   const testDays = num("wf_test_days") || 30;
-  const stepDays = num("wf_step_days") || 30;
+  const stepDays = num("wf_step_days") || testDays;
 
-  const dateFrom = str("date_from");
+  // usar metadata real del dataset si ya se ha cargado
-  const dateTo = str("date_to");
+  let totalDays = Number(DATASET_INFO?.n_days || 0);
 
-  let totalDays = 0;
+  if (!Number.isFinite(totalDays) || totalDays <= 0) {
-  if (dateFrom && dateTo) {
+    // fallback razonable, pero ya no es el camino principal
-    const fromTs = new Date(dateFrom).getTime();
+    totalDays = 3650;
-    const toTs = new Date(dateTo).getTime();
-
-    if (Number.isFinite(fromTs) && Number.isFinite(toTs) && toTs > fromTs) {
-      totalDays = Math.max(1, Math.ceil((toTs - fromTs) / 86400000));
-    }
   }
 
-  let estimatedWindows = 1;
   const minSpan = trainDays + testDays;
+  let estimatedWindows = 1;
 
-  if (totalDays > minSpan && stepDays > 0) {
+  if (totalDays > minSpan) {
     estimatedWindows = Math.max(
       1,
       Math.floor((totalDays - minSpan) / stepDays) + 1
     );
   }
 
+  const timeframe = str("timeframe") || "1h";
+
   const barsPerDayMap = {
     "1m": 1440,
     "3m": 480,
@@ -503,24 +550,20 @@ function updateTimeEstimate(globalTotal) {
     "1d": 1
   };
 
-  const timeframe = str("timeframe") || "1h";
   const barsPerDay = barsPerDayMap[timeframe] || 24;
-
   const estimatedBars = Math.max(1, totalDays * barsPerDay);
 
-  // Heurística V1:
+  const overheadSeconds = 3;
-  // - overhead fijo de arranque
+  const perWindowPerStrategySeconds = 0.25;
-  // - coste por estrategia
+  const dataSeconds = estimatedBars * globalTotal * 0.00005;
-  // - coste por ventana
-  // - pequeño coste por volumen de datos
-  const baseSeconds = 1.5;
-  const perStrategySeconds = 0.9 * globalTotal;
-  const perWindowSeconds = 0.35 * estimatedWindows * globalTotal;
-  const dataSeconds = estimatedBars * globalTotal * 0.00003;
 
   const totalSeconds = Math.max(
     1,
-    Math.round(baseSeconds + perStrategySeconds + perWindowSeconds + dataSeconds)
+    Math.round(
+      overheadSeconds +
+      (estimatedWindows * globalTotal * perWindowPerStrategySeconds) +
+      dataSeconds
+    )
   );
 
   if (totalSeconds < 60) {
@@ -542,6 +585,27 @@ function updateTimeEstimate(globalTotal) {
 }
 
 
+function estimateWFWindows() {
+
+  if (!DATASET_INFO) return 0;
+
+  const trainDays = num("wf_train_days") || 180;
+  const testDays = num("wf_test_days") || 30;
+  const stepDays = num("wf_step_days") || testDays;
+
+  const totalDays = Number(DATASET_INFO.n_days || 0);
+
+  const minSpan = trainDays + testDays;
+
+  if (totalDays <= minSpan) return 1;
+
+  const windows =
+    Math.floor((totalDays - minSpan) / stepDays) + 1;
+
+  return Math.max(1, windows);
+}
+
+
 function removeStrategySlot(index) {
 
   strategySlots.splice(index, 1);
@@ -550,6 +614,32 @@ function removeStrategySlot(index) {
 }
 
 
+function renderDatasetInfo() {
+
+  const el = document.getElementById("dataset_info");
+  if (!el) return;
+
+  if (!DATASET_INFO) {
+    el.textContent = "";
+    return;
+  }
+
+  const start = DATASET_INFO.start_date
+    ? new Date(DATASET_INFO.start_date).toISOString().slice(0, 10)
+    : "?";
+
+  const end = DATASET_INFO.end_date
+    ? new Date(DATASET_INFO.end_date).toISOString().slice(0, 10)
+    : "?";
+
+  const rows = Number(DATASET_INFO.n_rows || 0).toLocaleString();
+  const days = Number(DATASET_INFO.n_days || 0).toLocaleString();
+  const windows = estimateWFWindows().toLocaleString();
+
+  el.textContent = `Dataset: ${start} → ${end} | ${rows} rows | ${days} days | ${windows} WF windows`;
+}
+
+
 // =================================================
 // PAYLOAD
 // =================================================
@@ -675,6 +765,30 @@ async function fetchAvailableStrategies() {
 }
 
 
+async function fetchDatasetInfo() {
+  const symbol = str("symbol");
+  const timeframe = str("timeframe");
+
+  if (!symbol || !timeframe) {
+    DATASET_INFO = null;
+    return null;
+  }
+
+  const qs = new URLSearchParams({ symbol, timeframe });
+
+  const res = await fetch(`/api/v2/calibration/strategies/data-info?${qs.toString()}`);
+  if (!res.ok) {
+    DATASET_INFO = null;
+    return null;
+  }
+
+  const data = await res.json();
+  DATASET_INFO = data;
+  renderDatasetInfo();
+  return data;
+}
+
+
 function loadFromStep2() {
 
   document.getElementById("risk_fraction").value =
@@ -1768,8 +1882,10 @@ function wireButtons() {
     renderStrategiesList(strategies);
   });
 
-  document.getElementById("load_step2_btn")?.addEventListener("click", () => {
+  document.getElementById("load_step2_btn")?.addEventListener("click", async () => {
     loadContextFromLocalStorage();
+    await fetchDatasetInfo();
+    updateCombinationCounter();
   });
 
   document.getElementById("close_pdf_btn")?.addEventListener("click", () => {
@@ -1804,24 +1920,44 @@ async function init() {
   loadFromStep2();
   applyInheritedLock();
 
+  await fetchDatasetInfo();
+
   document.getElementById("stop_type")
     .addEventListener("change", updateStopUI);
 
   wireButtons();
+
   [
-    "date_from",
-    "date_to",
     "timeframe",
     "wf_train_days",
     "wf_test_days",
     "wf_step_days"
   ].forEach(id => {
     const el = document.getElementById(id);
-    if (el) {
+    if (!el) return;
-      el.addEventListener("change", updateCombinationCounter);
+
-      el.addEventListener("input", updateCombinationCounter);
+    if (id === "timeframe") {
+      el.addEventListener("change", async () => {
+        await fetchDatasetInfo();
+        updateCombinationCounter();
+        renderDatasetInfo();
+      });
+      el.addEventListener("input", async () => {
+        await fetchDatasetInfo();
+        updateCombinationCounter();
+        renderDatasetInfo();
+      });
+    } else {
+      el.addEventListener("change", () => {
+        updateCombinationCounter();
+        renderDatasetInfo();
+      });
+      el.addEventListener("input", () => {
+        updateCombinationCounter();
+      });
     }
   });
+
   wirePromotionUI();
 
   document.getElementById("plot_strategy_select").addEventListener("change", function() {
@@ -2076,6 +2212,81 @@ function renderRegimeSummary(strategyId, s, data) {
 // =================================================
 
 
+function defaultStep4SelectionForStatus(status) {
+  return status === "promote";
+}
+
+
+function normalizePromotionResults(results) {
+  return (results || []).map(r => ({
+    ...r,
+    selected_for_step4: defaultStep4SelectionForStatus(r.status),
+    selection_source: defaultStep4SelectionForStatus(r.status) ? "auto" : "manual_off"
+  }));
+}
+
+
+function getStrategyConfigFromSlots(strategyId) {
+  const slot = (strategySlots || []).find(s => s.strategy_id === strategyId);
+  if (!slot) return null;
+
+  return {
+    strategy_id: slot.strategy_id,
+    parameters: { ...(slot.parameters || {}) }
+  };
+}
+
+
+function collectStep4Selection() {
+  return (PROMOTION_RESULTS || [])
+    .filter(r => r.selected_for_step4)
+    .map(r => {
+      const cfg = getStrategyConfigFromSlots(r.strategy_id);
+
+      return {
+        strategy_id: r.strategy_id,
+        promotion_status: r.status,
+        promotion_score: r.score,
+        selection_source: r.selection_source,
+        diversity_blocked_by: r.diversity_blocked_by ?? null,
+        diversity_correlation: r.diversity_correlation ?? null,
+        parameters: cfg?.parameters || {}
+      };
+    });
+}
+
+
+function updateStep4SelectionSummary() {
+  const el = document.getElementById("step4SelectionSummary");
+  if (!el) return;
+
+  const selected = (PROMOTION_RESULTS || []).filter(r => r.selected_for_step4).length;
+  const total = (PROMOTION_RESULTS || []).length;
+
+  el.textContent = `Selected for Step 4: ${selected} / ${total}`;
+}
+
+
+function buildStep4SelectionArtifact() {
+  STEP4_SELECTION = collectStep4Selection();
+
+  const previewEl = document.getElementById("step4SelectionPreview");
+  if (!previewEl) return;
+
+  const artifact = {
+    created_at: new Date().toISOString(),
+    symbol: str("symbol"),
+    timeframe: str("timeframe"),
+    selected_strategies: STEP4_SELECTION
+  };
+
+  previewEl.textContent = JSON.stringify(artifact, null, 2);
+  previewEl.classList.remove("d-none");
+
+  updateStep4SelectionSummary();
+}
+
+
 async function runPromotion() {
 
   if (!Array.isArray(window.lastStrategiesResult) || window.lastStrategiesResult.length === 0) {
@@ -2105,7 +2316,10 @@ async function runPromotion() {
     }
 
     const data = await res.json();
-    renderPromotionResults(data.results || []);
+
+    PROMOTION_RESULTS = normalizePromotionResults(data.results || []);
+    renderPromotionResults(PROMOTION_RESULTS);
+    updateStep4SelectionSummary();
 
   } catch (err) {
     console.error(err);
@@ -2119,7 +2333,7 @@ function renderPromotionResults(results) {
   const table = document.querySelector("#promotionTable tbody");
   table.innerHTML = "";
 
-  results.forEach(r => {
+  results.forEach((r, idx) => {
 
     const tr = document.createElement("tr");
 
@@ -2128,13 +2342,39 @@ function renderPromotionResults(results) {
       ? "—"
       : Number(r.diversity_correlation).toFixed(4);
 
+    const checked = r.selected_for_step4 ? "checked" : "";
+
+    let statusBadge = "bg-secondary-lt text-secondary";
+    if (r.status === "promote") statusBadge = "bg-success-lt text-success";
+    else if (r.status === "review") statusBadge = "bg-warning-lt text-warning";
+    else if (r.status === "review_diversity") statusBadge = "bg-orange-lt text-orange";
+    else if (r.status === "reject") statusBadge = "bg-danger-lt text-danger";
+
+    let sourceBadge = "bg-secondary-lt text-secondary";
+    let sourceLabel = r.selection_source || "manual_off";
+
+    if (sourceLabel === "auto") sourceBadge = "bg-success-lt text-success";
+    else if (sourceLabel === "manual_on") sourceBadge = "bg-blue-lt text-blue";
+    else if (sourceLabel === "manual_off") sourceBadge = "bg-secondary-lt text-secondary";
+
     tr.innerHTML = `
       <td>${r.rank}</td>
       <td>${r.strategy_id}</td>
       <td>${r.score}</td>
-      <td>${r.status}</td>
+      <td><span class="badge ${statusBadge}">${r.status}</span></td>
       <td>${blockedBy}</td>
       <td>${corr}</td>
+      <td>
+        <label class="form-check m-0">
+          <input
+            class="form-check-input promotion-step4-checkbox"
+            type="checkbox"
+            data-index="${idx}"
+            ${checked}
+          >
+        </label>
+      </td>
+      <td><span class="badge ${sourceBadge}">${sourceLabel}</span></td>
     `;
 
     table.appendChild(tr);
@@ -2144,16 +2384,49 @@ function renderPromotionResults(results) {
   const review = results.filter(r => r.status === "review").length;
   const reviewDiversity = results.filter(r => r.status === "review_diversity").length;
   const reject = results.filter(r => r.status === "reject").length;
+  const selected = results.filter(r => r.selected_for_step4).length;
 
   document.getElementById("promotionSummary").innerHTML =
-    `Promoted: ${promoted} | Review: ${review} | Review diversity: ${reviewDiversity} | Rejected: ${reject}`;
+    `Promoted: ${promoted} | Review: ${review} | Review diversity: ${reviewDiversity} | Rejected: ${reject} | Step 4 selected: ${selected}`;
+
+  updateStep4SelectionSummary();
+}
+
+
+function handlePromotionStep4Toggle(event) {
+  const target = event.target;
+  if (!target || !target.classList.contains("promotion-step4-checkbox")) return;
+
+  const index = Number(target.dataset.index);
+  if (!Number.isInteger(index) || !PROMOTION_RESULTS[index]) return;
+
+  const row = PROMOTION_RESULTS[index];
+  row.selected_for_step4 = !!target.checked;
+
+  if (row.selected_for_step4) {
+    row.selection_source = row.status === "promote" ? "auto" : "manual_on";
+  } else {
+    row.selection_source = "manual_off";
+  }
+
+  renderPromotionResults(PROMOTION_RESULTS);
 }
 
 
 function wirePromotionUI() {
-  const btn = document.getElementById("btnRunPromotion");
+  const btnRun = document.getElementById("btnRunPromotion");
-  if (btn) {
+  if (btnRun) {
-    btn.addEventListener("click", runPromotion);
+    btnRun.addEventListener("click", runPromotion);
+  }
+
+  const table = document.querySelector("#promotionTable");
+  if (table) {
+    table.addEventListener("change", handlePromotionStep4Toggle);
+  }
+
+  const btnBuild = document.getElementById("btnBuildStep4Selection");
+  if (btnBuild) {
+    btnBuild.addEventListener("click", buildStep4SelectionArtifact);
   }
 }
 

src/web/ui/v2/templates/pages/calibration/calibration_strategies.html

@@ -24,7 +24,7 @@
 
     <div class="flex-grow-1 text-center">
       <h2 class="mb-0">Calibración · Paso 3 · Strategies</h2>
-      <div class="text-secondary">Optimización + Walk Forward (OOS)</div>
+      <div class="text-secondary">Strategy Selector</div>
     </div>
 
     <!-- Forward arrow (disabled until OK) -->
@@ -245,6 +245,11 @@
           <span id="wf_time_estimate">~ 0 sec</span>
         </small>
       </div>
+      <div class="mt-2 text-end">
+        <small class="text-muted">
+          <span id="dataset_info"></span>
+        </small>
+      </div>
       <div class="mt-3 text-secondary">
         Cada estrategia utiliza parámetros fijos (validación OOS sin grid).
       </div>
@@ -306,6 +311,17 @@
 
       <div id="promotionSummary" class="mt-3"></div>
 
+      <div class="mt-2 d-flex gap-2 flex-wrap">
+        <button id="btnBuildStep4Selection" class="btn btn-success btn-sm">
+          Build Step 4 Selection
+        </button>
+      </div>
+
+      <div id="step4SelectionSummary" class="mt-2 text-secondary small"></div>
+
+      <pre id="step4SelectionPreview" class="mt-2 p-2 bg-light border rounded d-none"
+          style="max-height: 280px; overflow:auto;"></pre>
+
       <table class="table mt-3" id="promotionTable">
         <thead>
           <tr>
@@ -315,6 +331,8 @@
             <th>Status</th>
             <th>Blocked by</th>
             <th>Corr</th>
+            <th>Step 4</th>
+            <th>Source</th>
           </tr>
         </thead>
         <tbody></tbody>