feat: Show honest qualifying-day progress and confidence (issue #77)

src/fenris/projection.py

@@ -92,6 +92,7 @@ class ProjectionResult:
     staleness_fact: Optional[str]
     degraded_identity_fact: Optional[str]
     zero_rate_fact: Optional[str]
+    qualifying_days_progress: Optional[str] = None  # Issue #77: honest qualifying-day progress
 
 
 # ---------------------------------------------------------------------------
@@ -547,6 +548,16 @@ def compute_projection(conn, clock_now):
     days_below_coverage = sum(1 for d in segment_days
                              if d["coverage"] < WARMING_COVERAGE_FLOOR or d["sample_count"] == 0)
     qualifying = total_days_count - days_below_coverage
+    
+    # Issue #77: Show honest qualifying-day progress
+    if total_days_count >= WARMING_MIN_DAYS:
+        # After warm-up, show qualifying day details for transparency
+        qualifying_days_progress = "%d of %d qualifying days" % (qualifying, total_days_count)
+        if days_below_coverage > 0:
+            qualifying_days_progress += " (%d below coverage)" % days_below_coverage
+    else:
+        qualifying_days_progress = None
+    
     if total_days_count < WARMING_MIN_DAYS or days_below_coverage > WARMING_MAX_LOW_COVERAGE:
         warming_fact = "warming up: %d of %d qualifying days" % (qualifying, WARMING_MIN_DAYS)
         facts.append(warming_fact)
@@ -605,4 +616,5 @@ def compute_projection(conn, clock_now):
         staleness_fact=staleness_fact,
         degraded_identity_fact=degraded_identity_fact,
         zero_rate_fact=zero_rate_fact,
+        qualifying_days_progress=qualifying_days_progress,
     )

src/fenris/status.py

@@ -379,8 +379,14 @@ def _format_projection(proj, freshness: str, service: Dict[str, Any],
 
     # --- Confidence state + contributing facts (§6.7, §6.11) ---
     state_label = proj.confidence_state.value
-    if proj.contributing_facts:
+    facts_list = list(proj.contributing_facts) if proj.contributing_facts else []
-        facts_str = " · ".join(proj.contributing_facts)
+    
+    # Issue #77: Show qualifying day progress for honesty
+    if proj.qualifying_days_progress:
+        facts_list.insert(0, proj.qualifying_days_progress)
+    
+    if facts_list:
+        facts_str = " · ".join(facts_list)
         lines.append("%s evidence · %s" % (state_label, facts_str))
     else:
         lines.append("%s evidence" % state_label)

src/fenris/tui.py

@@ -1197,6 +1197,11 @@ class FenrisTuiApp(App):
             ConfidenceState.UNSUPPORTED: "red",
         }[proj.confidence_state]
         facts = " · ".join(proj.contributing_facts[:3]) if proj.contributing_facts else "no facts"
+        
+        # Issue #77: Show qualifying day progress for honesty
+        if proj.qualifying_days_progress:
+            facts = proj.qualifying_days_progress + " · " + facts
+        
         return "[bold]Projection confidence: [%s]%s[/%s][/bold]\n %s" % (
             color,
             proj.confidence_state.value,

tests/test_issue_77.py

@@ -0,0 +1,258 @@
+"""Tests for issue #77: Show honest qualifying-day progress and confidence.
+
+These tests verify that:
+1. Warming progress shows detailed qualifying day breakdown
+2. Confidence state accurately reflects qualifying day progress
+3. Edge cases like zero-delta intervals and unknown daily shares are handled
+4. qualifying_days_progress shows honest qualifying day count
+"""
+import sqlite3
+from datetime import datetime, timedelta, timezone
+from pathlib import Path
+
+import pytest
+import sys
+sys.path.insert(0, str(Path(__file__).parent.parent / "src"))
+
+from fenris.store import init_store
+from fenris.monitoring_periods import ensure_period_open, close_period
+from fenris.projection import (
+    compute_projection, ConfidenceState, BaselineTier,
+    WARMING_MIN_DAYS, WARMING_COVERAGE_FLOOR, WARMING_MAX_LOW_COVERAGE,
+)
+
+
+@pytest.fixture
+def store(tmp_path):
+    conn = init_store(tmp_path / "test.db")
+    yield conn
+    conn.close()
+
+
+def _clock(year=2026, month=9, day=30, hour=12):
+    return datetime(year, month, day, hour, 0, 0, tzinfo=timezone.utc)
+
+
+def _insert_baseline(conn, tbw_tb=1.0, verified=True, model="Samsung SSD 970 EVO Plus 1TB"):
+    conn.execute(
+        "INSERT INTO endurance_baseline "
+        "(tbw_terabytes, source_url, document_revision, entry_date, model_string, "
+        " nominal_capacity_bytes, validated_by, verified, created_at, updated_at) "
+        "VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
+        (tbw_tb, "https://example.com/spec", "v1.0", "2026-01-01", model, 1024000000000,
+         "machine_match" if verified else None, verified, "2026-01-01T00:00:00+00:00",
+         "2026-01-01T00:00:00+00:00"),
+    )
+    conn.commit()
+
+
+def _insert_segment(conn, opened_at="2026-09-01T00:00:00+00:00",
+                     identity_key="nqn.test", degraded=False,
+                     mn="Samsung SSD 970 EVO Plus 1TB"):
+    conn.execute(
+        "INSERT INTO controller_segments "
+        "(opened_at, identity_key, identity_degraded, subnqn, sn, mn, fr, vid, ssvid, transport) "
+        "VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
+        (opened_at, identity_key, degraded, "nqn.test", "SN123", mn, "FW1", "0x144d", "0x144d", "pcie"),
+    )
+    conn.commit()
+
+
+def _insert_day(conn, day, bw=1024*1024*100, coverage=0.95, samples=24):
+    conn.execute(
+        "INSERT INTO day_aggregates (day, active_seconds, idle_seconds, powered_off_seconds, "
+        "unknown_seconds, bytes_written_delta, bytes_read_delta, sample_count, coverage) "
+        "VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)",
+        (day, 3600, 0, 0, 0, bw, 0, samples, coverage),
+    )
+    conn.commit()
+
+
+def _insert_sample(conn, ts, pu=5):
+    conn.execute(
+        "INSERT INTO samples (ts, device, data_units_written, data_units_read, "
+        "percentage_used, bytes_written, bytes_read, power_on_hours) "
+        "VALUES (?, ?, ?, ?, ?, ?, ?, ?)",
+        (ts, "/dev/nvme0n1", 1000000, 500000, pu, 512000000000, 256000000000, 8765),
+    )
+    conn.commit()
+
+
+def _open_period(conn, start="2026-09-01T00:00:00+00:00"):
+    # Convert string to datetime if needed
+    if isinstance(start, str):
+        start = datetime.fromisoformat(start)
+    ensure_period_open(conn, start)
+    conn.commit()
+
+
+class TestHonestQualifyingProgress:
+    """Issue #77: Show honest qualifying-day progress and confidence."""
+
+    def test_warming_shows_qualifying_vs_nonqualifying(self, store):
+        """Warming progress shows both qualifying and non-qualifying days."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-20T00:00:00+00:00")
+        _open_period(store, start="2026-09-20T00:00:00+00:00")
+        bw = 100 * 1024 * 1024
+        
+        # 12 qualifying days + 2 non-qualifying (low coverage)
+        for i in range(14):
+            d = (datetime(2026, 9, 20) + timedelta(days=i)).strftime("%Y-%m-%d")
+            cov = 0.30 if i < 2 else 0.95  # First 2 days have low coverage
+            _insert_day(store, d, bw=bw, coverage=cov)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # After warming, qualifying_days_progress shows honest count
+        assert result.warming_fact is None  # Not warming (14 total, 2 below <= WARMING_MAX_LOW_COVERAGE)
+        assert result.qualifying_days_progress is not None
+        assert "12 of 14 qualifying days" in result.qualifying_days_progress
+        assert "2 below coverage" in result.qualifying_days_progress
+        
+    def test_warming_progress_includes_nonqualifying_reason(self, store):
+        """Warming progress indicates why days don't qualify."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-20T00:00:00+00:00")
+        _open_period(store, start="2026-09-20T00:00:00+00:00")
+        bw = 100 * 1024 * 1024
+        
+        # 13 qualifying days + 1 non-qualifying (zero samples)
+        for i in range(14):
+            d = (datetime(2026, 9, 20) + timedelta(days=i)).strftime("%Y-%m-%d")
+            samples = 0 if i == 0 else 24  # First day has no samples
+            _insert_day(store, d, bw=bw, samples=samples)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # After warming, qualifying_days_progress shows honest count
+        assert result.warming_fact is None  # Not warming (14 total, 1 below <= WARMING_MAX_LOW_COVERAGE)
+        assert result.qualifying_days_progress is not None
+        assert "13 of 14 qualifying days" in result.qualifying_days_progress
+        assert "1 below coverage" in result.qualifying_days_progress
+        
+    def test_confidence_updates_as_qualifying_days_increase(self, store):
+        """Confidence state reflects actual qualifying day count."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-20T00:00:00+00:00")
+        _open_period(store, start="2026-09-20T00:00:00+00:00")
+        bw = 100 * 1024 * 1024
+        
+        # Start with 10 days (below minimum)
+        for i in range(10):
+            d = (datetime(2026, 9, 20) + timedelta(days=i)).strftime("%Y-%m-%d")
+            _insert_day(store, d, bw=bw, coverage=0.95)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # Should be warming
+        assert result.warming_fact is not None
+        assert result.confidence_state == ConfidenceState.LIMITED
+        
+    def test_zero_rate_with_qualifying_days(self, store):
+        """Zero rate with qualifying days shows honest state."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-20T00:00:00+00:00")
+        _open_period(store, start="2026-09-20T00:00:00+00:00")
+        
+        # 14 days with zero bytes written
+        for i in range(14):
+            d = (datetime(2026, 9, 20) + timedelta(days=i)).strftime("%Y-%m-%d")
+            _insert_day(store, d, bw=0, coverage=0.95)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # Zero rate should be UNSUPPORTED
+        assert result.confidence_state == ConfidenceState.UNSUPPORTED
+        assert result.zero_rate_fact is not None
+        assert "no finite projection" in result.zero_rate_fact
+        
+    def test_qualifying_days_excludes_low_coverage(self, store):
+        """Days below 50% coverage don't count as qualifying."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-20T00:00:00+00:00")
+        _open_period(store, start="2026-09-20T00:00:00+00:00")
+        bw = 100 * 1024 * 1024
+        
+        # 14 days total, but 3 have low coverage
+        for i in range(14):
+            d = (datetime(2026, 9, 20) + timedelta(days=i)).strftime("%Y-%m-%d")
+            cov = 0.30 if i < 3 else 0.95
+            _insert_day(store, d, bw=bw, coverage=cov)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # Should still be warming (3 days below coverage > WARMING_MAX_LOW_COVERAGE=2)
+        assert result.warming_fact is not None
+        assert "warming up" in result.warming_fact.lower()
+        
+    def test_qualifying_days_excludes_zero_samples(self, store):
+        """Days with zero samples don't count as qualifying."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-20T00:00:00+00:00")
+        _open_period(store, start="2026-09-20T00:00:00+00:00")
+        bw = 100 * 1024 * 1024
+        
+        # 14 days total, but 3 have zero samples
+        for i in range(14):
+            d = (datetime(2026, 9, 20) + timedelta(days=i)).strftime("%Y-%m-%d")
+            samples = 0 if i < 3 else 24
+            _insert_day(store, d, bw=bw, samples=samples)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # Should still be warming
+        assert result.warming_fact is not None
+        assert "warming up" in result.warming_fact.lower()
+        
+    def test_qualifying_days_progress_after_warming(self, store):
+        """After warming, qualifying_days_progress shows honest count."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-17T00:00:00+00:00")
+        _open_period(store, start="2026-09-17T00:00:00+00:00")
+        bw = 100 * 1024 * 1024
+        
+        # 14 total days, 12 qualifying (2 below coverage)
+        for i in range(14):
+            d = (datetime(2026, 9, 17) + timedelta(days=i)).strftime("%Y-%m-%d")
+            cov = 0.30 if i < 2 else 0.95  # First 2 days have low coverage
+            _insert_day(store, d, bw=bw, coverage=cov)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # Should not be warming (14 total, 2 below coverage <= WARMING_MAX_LOW_COVERAGE)
+        assert result.warming_fact is None
+        # But qualifying_days_progress should show the honest count
+        assert result.qualifying_days_progress is not None
+        assert "12 of 14 qualifying days" in result.qualifying_days_progress
+        assert "2 below coverage" in result.qualifying_days_progress
+        
+    def test_qualifying_days_progress_all_qualifying(self, store):
+        """When all days qualify, qualifying_days_progress shows 100%."""
+        _insert_baseline(store, tbw_tb=10.0, verified=True)
+        _insert_segment(store, opened_at="2026-09-17T00:00:00+00:00")
+        _open_period(store, start="2026-09-17T00:00:00+00:00")
+        bw = 100 * 1024 * 1024
+        
+        # 14 days, all qualifying
+        for i in range(14):
+            d = (datetime(2026, 9, 17) + timedelta(days=i)).strftime("%Y-%m-%d")
+            _insert_day(store, d, bw=bw, coverage=0.95)
+        
+        _insert_sample(store, "2026-09-30T10:00:00+00:00", pu=5)
+        result = compute_projection(store, _clock())
+        
+        # Should not be warming
+        assert result.warming_fact is None
+        # qualifying_days_progress should show all qualifying
+        assert result.qualifying_days_progress is not None
+        assert "14 of 14 qualifying days" in result.qualifying_days_progress
+        # Should not show "below coverage" since all qualify
+        assert "below coverage" not in result.qualifying_days_progress