backend/app/services/site_finder/velocity.py

@@ -47,6 +47,9 @@ class VelocityResult:
     period_end: str  # YYYY-MM
     sample_competitors: list[dict[str, Any]]  # top-5 для UI
     by_room_bucket: dict[str, dict[str, Any]]  # агрегат по комнатности
+    # True если ≥1 конкурент имеет маппинг в objective_complex_mapping;
+    # False → конкуренты найдены, но данных Objective нет — velocity = 0.
+    velocity_data_available: bool = True
 
     def as_dict(self) -> dict[str, Any]:
         return {
@@ -59,6 +62,7 @@ class VelocityResult:
             "period": {"start": self.period_start, "end": self.period_end},
             "sample_competitors": self.sample_competitors,
             "by_room_bucket": self.by_room_bucket,
+            "velocity_data_available": self.velocity_data_available,
         }
 
 
@@ -165,6 +169,8 @@ def compute_velocity(
     #          objective_corpus_room_month.
     # deals_total_vol_m2 = DDU + DKP м² за месяц (primary signal).
     # deals_total_count > 0 — фильтрует месяцы без сделок.
+    # LEFT JOIN с objective_complex_mapping: конкуренты без маппинга не
+    # выпадают — они включаются в список но с total_sqm=NULL (→ 0.0).
     # GROUP BY domrf_obj_id чтобы сохранить совместимость с caller (obj_id key).
     try:
         with db.begin_nested():
@@ -172,25 +178,32 @@ def compute_velocity(
                 db.execute(
                     text(
                         """
-                    WITH mapped AS (
+                    WITH all_competitors AS (
+                        SELECT unnest(CAST(:obj_ids AS int[])) AS obj_id
+                    ),
+                    mapped AS (
                         SELECT cm.domrf_obj_id AS obj_id,
                                cm.objective_complex_name
                           FROM objective_complex_mapping cm
                          WHERE cm.domrf_obj_id = ANY(:obj_ids)
                     )
                     SELECT
-                        m.obj_id,
+                        ac.obj_id,
                         SUM(COALESCE(crm.deals_total_vol_m2,
                                      crm.deals_total_count * 45.0)) AS total_sqm,
-                        COUNT(DISTINCT crm.report_month) AS months_with_data,
-                        MIN(crm.report_month)            AS period_start,
-                        MAX(crm.report_month)            AS period_end
-                      FROM objective_corpus_room_month crm
-                      JOIN mapped m
-                        ON m.objective_complex_name = crm.project_name
-                     WHERE crm.report_month >= (CURRENT_DATE - CAST(:window_interval AS interval))
-                       AND crm.deals_total_count > 0
-                     GROUP BY m.obj_id
+                        COUNT(DISTINCT crm.report_month)             AS months_with_data,
+                        MIN(crm.report_month)                        AS period_start,
+                        MAX(crm.report_month)                        AS period_end,
+                        CASE WHEN m.obj_id IS NOT NULL THEN TRUE
+                             ELSE FALSE END                          AS has_mapping
+                      FROM all_competitors ac
+                      LEFT JOIN mapped m ON m.obj_id = ac.obj_id
+                      LEFT JOIN objective_corpus_room_month crm
+                             ON crm.project_name = m.objective_complex_name
+                            AND crm.report_month >= (
+                                    CURRENT_DATE - CAST(:window_interval AS interval))
+                            AND crm.deals_total_count > 0
+                     GROUP BY ac.obj_id, m.obj_id
                     """
                     ),
                     {
@@ -209,6 +222,44 @@ def compute_velocity(
     if not sales_rows:
         return None
 
+    # Проверяем: есть ли хотя бы один конкурент с маппингом (has_mapping=True).
+    # Если нет — возвращаем velocity=0 с явным флагом velocity_data_available=False,
+    # вместо того чтобы отбросить всех конкурентов (старый INNER JOIN поведение).
+    has_any_mapping = any(bool(r["has_mapping"]) for r in sales_rows)
+    if not has_any_mapping:
+        logger.info(
+            "velocity: %d competitors found but none mapped in objective_complex_mapping;"
+            " returning velocity=0 with data_available=False",
+            len(obj_ids),
+        )
+        ekb_median = (
+            _get_ekb_median(db, months_window=months_window) or _EKB_MEDIAN_FALLBACK_SQM_PER_MONTH
+        )
+        n_comps = len(comp_rows)
+        sample = [
+            {
+                "obj_id": oid,
+                **competitor_meta[oid],
+                "total_sqm_period": 0.0,
+                "by_room_bucket": {},
+            }
+            for oid in obj_ids[:5]
+            if oid in competitor_meta
+        ]
+        return VelocityResult(
+            competitors_count=n_comps,
+            monthly_velocity_sqm=0.0,
+            ekb_median_sqm=ekb_median,
+            velocity_score=0.0,
+            confidence="low",
+            months_observed=0,
+            period_start="",
+            period_end="",
+            sample_competitors=sample,
+            by_room_bucket={},
+            velocity_data_available=False,
+        )
+
     # ── Step 2b: разбивка по комнатности (room_bucket) ───────────────────────
     # Тот же маппинг domrf_obj_id → project_name. Агрегируем по room_bucket
     # для отображения структуры спроса в UI.
@@ -278,46 +329,85 @@ def compute_velocity(
         for bucket, data in by_bucket_agg.items()
     }
 
-    total_sqm = sum(float(r["total_sqm"] or 0.0) for r in sales_rows)
-    months_observed = max((int(r["months_with_data"] or 0) for r in sales_rows), default=0)
-    period_start_dates = [r["period_start"] for r in sales_rows if r["period_start"]]
-    period_end_dates = [r["period_end"] for r in sales_rows if r["period_end"]]
+    # Считаем только по строкам с маппингом — unmapped строки дают total_sqm=NULL.
+    mapped_sales_rows = [r for r in sales_rows if bool(r["has_mapping"])]
+
+    total_sqm = sum(float(r["total_sqm"] or 0.0) for r in mapped_sales_rows)
+    months_observed = max((int(r["months_with_data"] or 0) for r in mapped_sales_rows), default=0)
+    period_start_dates = [r["period_start"] for r in mapped_sales_rows if r["period_start"]]
+    period_end_dates = [r["period_end"] for r in mapped_sales_rows if r["period_end"]]
     period_start = min(period_start_dates).strftime("%Y-%m") if period_start_dates else ""
     period_end = max(period_end_dates).strftime("%Y-%m") if period_end_dates else ""
 
-    if months_observed == 0 or total_sqm <= 0:
-        return None
-
-    # Среднемесячный объём в расчёте: суммарный по всем конкурентам / месяцев.
-    # Чем больше конкурентов с данными — тем весомее результат.
-    monthly_velocity = total_sqm / months_observed
-
     # ── Step 3: ЕКБ-медиана ──────────────────────────────────────────────────
     ekb_median = (
         _get_ekb_median(db, months_window=months_window) or _EKB_MEDIAN_FALLBACK_SQM_PER_MONTH
     )
 
+    n_comps = len(comp_rows)
+
+    # Если mapped-конкурентов нет данных — partial coverage → velocity=0.
+    if months_observed == 0 or total_sqm <= 0:
+        logger.info(
+            "velocity: %d competitors found, %d mapped, but no sales data in window;"
+            " returning velocity=0 with data_available=False",
+            len(obj_ids),
+            len(mapped_sales_rows),
+        )
+        sample_partial = sorted(
+            [
+                {
+                    "obj_id": oid,
+                    **competitor_meta[oid],
+                    "total_sqm_period": 0.0,
+                    "by_room_bucket": {},
+                }
+                for oid in obj_ids
+                if oid in competitor_meta
+            ],
+            key=lambda x: x["total_sqm_period"],  # type: ignore[arg-type]
+            reverse=True,
+        )[:5]
+        return VelocityResult(
+            competitors_count=n_comps,
+            monthly_velocity_sqm=0.0,
+            ekb_median_sqm=ekb_median,
+            velocity_score=0.0,
+            confidence="low",
+            months_observed=0,
+            period_start="",
+            period_end="",
+            sample_competitors=sample_partial,
+            by_room_bucket={},
+            velocity_data_available=False,
+        )
+
+    # Среднемесячный объём в расчёте: суммарный по всем конкурентам / месяцев.
+    # Чем больше конкурентов с данными — тем весомее результат.
+    monthly_velocity = total_sqm / months_observed
+
     # ── Step 4: нормализация → score 0..1 ────────────────────────────────────
     # Логика: сравниваем суммарный velocity радиуса с «нормой» одного ЖК.
     # Если в радиусе продаётся N × ekb_median → рынок горячий.
     # Нормируем: score = min(1.0, total_velocity / (n_competitors × ekb_median × 2))
     # Cap 2×median = «насыщен». Итоговый score 0..1.
-    n_with_sales = len(sales_rows)
+    # n_with_sales — только mapped конкуренты (у unmapped данных нет).
+    n_with_sales = len(mapped_sales_rows)
     denominator = n_with_sales * ekb_median * 2.0 if n_with_sales > 0 else ekb_median * 2.0
     velocity_score = min(1.0, max(0.0, monthly_velocity / denominator))
 
     # ── Step 5: confidence ───────────────────────────────────────────────────
-    n_comps = len(comp_rows)
+    mapped_conf: Literal["high", "medium", "low"]
     if n_comps >= 10 and months_observed >= 5:
-        confidence: Literal["high", "medium", "low"] = "high"
+        mapped_conf = "high"
     elif n_comps >= 5 and months_observed >= 3:
-        confidence = "medium"
+        mapped_conf = "medium"
     else:
-        confidence = "low"
+        mapped_conf = "low"
 
     # ── Step 6: top-5 конкурентов по объёму продаж ───────────────────────────
     sales_by_id: dict[int, float] = {
-        int(r["obj_id"]): float(r["total_sqm"] or 0.0) for r in sales_rows
+        int(r["obj_id"]): float(r["total_sqm"] or 0.0) for r in mapped_sales_rows
     }
     sample = sorted(
         [
@@ -339,12 +429,13 @@ def compute_velocity(
         monthly_velocity_sqm=monthly_velocity,
         ekb_median_sqm=ekb_median,
         velocity_score=velocity_score,
-        confidence=confidence,
+        confidence=mapped_conf,
         months_observed=months_observed,
         period_start=period_start,
         period_end=period_end,
         sample_competitors=sample,
         by_room_bucket=by_room_bucket,
+        velocity_data_available=True,
     )
 
 

frontend/src/components/site-finder/VelocityBlock.tsx

@@ -49,6 +49,7 @@ export function VelocityBlock({ velocity }: VelocityBlockProps) {
     );
   }
 
+  const dataAvailable = velocity.velocity_data_available !== false;
   const confColor = CONFIDENCE_COLOR[velocity.confidence];
   const scorePct = formatPercent(velocity.velocity_score);
   const ratio = velocity.monthly_velocity_sqm / velocity.ekb_median_sqm;
@@ -64,72 +65,89 @@ export function VelocityBlock({ velocity }: VelocityBlockProps) {
         }}
       >
         <SectionLabel>Темп продаж конкурентов</SectionLabel>
-        <span
-          style={{
-            padding: "2px 8px",
-            background: confColor.bg,
-            color: confColor.fg,
-            borderRadius: 4,
-            fontSize: 11,
-            fontWeight: 600,
-          }}
-          title={`Уверенность: ${CONFIDENCE_LABEL[velocity.confidence]}`}
-        >
-          {CONFIDENCE_LABEL[velocity.confidence]}
-        </span>
+        <div style={{ display: "flex", alignItems: "center", gap: 6 }}>
+          {!dataAvailable && (
+            <span className="bg-slate-100 text-slate-500 text-xs px-2 py-0.5 rounded">
+              нет данных velocity
+            </span>
+          )}
+          <span
+            style={{
+              padding: "2px 8px",
+              background: confColor.bg,
+              color: confColor.fg,
+              borderRadius: 4,
+              fontSize: 11,
+              fontWeight: 600,
+            }}
+            title={`Уверенность: ${CONFIDENCE_LABEL[velocity.confidence]}`}
+          >
+            {CONFIDENCE_LABEL[velocity.confidence]}
+          </span>
+        </div>
       </div>
 
-      {/* Score gauge */}
-      <div style={{ marginBottom: 12 }}>
-        <div
-          style={{
-            display: "flex",
-            justifyContent: "space-between",
-            fontSize: 12,
-            color: "#6b7280",
-            marginBottom: 4,
-          }}
-        >
-          <span>Velocity-score</span>
-          <span style={{ fontWeight: 600, color: "#111827" }}>{scorePct}</span>
-        </div>
-        <div
-          style={{
-            background: "#e5e7eb",
-            borderRadius: 4,
-            height: 8,
-            overflow: "hidden",
-          }}
-        >
+      {/* Score gauge — показываем только если данные есть */}
+      {dataAvailable && (
+        <div style={{ marginBottom: 12 }}>
           <div
             style={{
-              background:
-                velocity.velocity_score >= 0.66
-                  ? "#10b981"
-                  : velocity.velocity_score >= 0.33
-                    ? "#f59e0b"
-                    : "#ef4444",
-              width: `${velocity.velocity_score * 100}%`,
-              height: "100%",
+              display: "flex",
+              justifyContent: "space-between",
+              fontSize: 12,
+              color: "#6b7280",
+              marginBottom: 4,
             }}
-          />
+          >
+            <span>Velocity-score</span>
+            <span style={{ fontWeight: 600, color: "#111827" }}>
+              {scorePct}
+            </span>
+          </div>
+          <div
+            style={{
+              background: "#e5e7eb",
+              borderRadius: 4,
+              height: 8,
+              overflow: "hidden",
+            }}
+          >
+            <div
+              style={{
+                background:
+                  velocity.velocity_score >= 0.66
+                    ? "#10b981"
+                    : velocity.velocity_score >= 0.33
+                      ? "#f59e0b"
+                      : "#ef4444",
+                width: `${velocity.velocity_score * 100}%`,
+                height: "100%",
+              }}
+            />
+          </div>
+          <div style={{ fontSize: 11, color: "#9ca3af", marginTop: 4 }}>
+            {Math.round(velocity.monthly_velocity_sqm)} м²/мес vs{" "}
+            {Math.round(velocity.ekb_median_sqm)} м²/мес (медиана ЕКБ) &middot;{" "}
+            {ratio >= 1
+              ? `x${ratio.toFixed(1)} выше`
+              : `${formatPercent(ratio)} от среднего`}
+          </div>
         </div>
-        <div style={{ fontSize: 11, color: "#9ca3af", marginTop: 4 }}>
-          {Math.round(velocity.monthly_velocity_sqm)} м²/мес vs{" "}
-          {Math.round(velocity.ekb_median_sqm)} м²/мес (медиана ЕКБ) &middot;{" "}
-          {ratio >= 1
-            ? `x${ratio.toFixed(1)} выше`
-            : `${formatPercent(ratio)} от среднего`}
-        </div>
-      </div>
+      )}
 
       {/* Period + competitors meta */}
       <div style={{ fontSize: 12, color: "#6b7280", marginBottom: 8 }}>
-        В радиусе 3 км: <b>{velocity.competitors_count}</b> ЖК &middot; период{" "}
-        <b>
-          {velocity.period.start} &rarr; {velocity.period.end}
-        </b>{" "}
-        ({velocity.months_observed} мес)
+        В радиусе 3 км: <b>{velocity.competitors_count}</b> ЖК
+        {dataAvailable && (
+          <>
+            {" "}
+            &middot; период{" "}
+            <b>
+              {velocity.period.start} &rarr; {velocity.period.end}
+            </b>{" "}
+            ({velocity.months_observed} мес)
+          </>
+        )}
       </div>
 
       {/* By room bucket aggregate */}

frontend/src/types/site-finder.ts

@@ -241,6 +241,9 @@ export interface Velocity {
   period: VelocityPeriod;
   sample_competitors: VelocityCompetitor[];
   by_room_bucket?: Record<string, VelocityBucketStat>;
+  // True если ≥1 конкурент имеет маппинг в objective_complex_mapping.
+  // False → конкуренты найдены, velocity=0, данных Objective нет.
+  velocity_data_available?: boolean;
 }
 
 // G5 (#32) — Gate verdict: can_build_mkd