Codex upgrade

Author: ElektrikAkar

.claude/reports/memory-and-design-audit.md

@@ -48,6 +48,40 @@ static dtwc::Data make_random_data(int N, int L, unsigned base_seed = 100)
   return dtwc::Data(std::move(vecs), std::move(names));
 }
 
+static void configure_problem_variant(dtwc::Problem &prob, int variant_code)
+{
+  dtwc::core::DTWVariantParams params;
+  switch (variant_code) {
+  case 1:
+    params.variant = dtwc::core::DTWVariant::WDTW;
+    params.wdtw_g = 0.05;
+    break;
+  case 2:
+    params.variant = dtwc::core::DTWVariant::DDTW;
+    break;
+  case 3:
+    params.variant = dtwc::core::DTWVariant::ADTW;
+    params.adtw_penalty = 1.0;
+    break;
+  case 0:
+  default:
+    params.variant = dtwc::core::DTWVariant::Standard;
+    break;
+  }
+  prob.set_variant(params);
+}
+
+static const char *variant_name(int variant_code)
+{
+  switch (variant_code) {
+  case 1: return "WDTW";
+  case 2: return "DDTW";
+  case 3: return "ADTW";
+  case 0:
+  default: return "Standard";
+  }
+}
+
 // ---------------------------------------------------------------------------
 // BM_dtwFull — full O(n*m) DTW for varying series lengths
 // ---------------------------------------------------------------------------
@@ -135,6 +169,135 @@ BENCHMARK(BM_dtwBanded_fullFallback)
   ->Arg(1000)
   ->Unit(benchmark::kMicrosecond);
 
+// ---------------------------------------------------------------------------
+// BM_wdtwBanded_g — WDTW banded path that recomputes weights every call
+// ---------------------------------------------------------------------------
+static void BM_wdtwBanded_g(benchmark::State &state)
+{
+  const auto len = static_cast<size_t>(state.range(0));
+  const int band = static_cast<int>(state.range(1));
+  constexpr double g = 0.05;
+  auto x = random_series(len, 42);
+  auto y = random_series(len, 43);
+  for (auto _ : state) {
+    benchmark::DoNotOptimize(dtwc::wdtwBanded<double>(x, y, band, g));
+  }
+  state.SetItemsProcessed(static_cast<int64_t>(state.iterations()));
+}
+BENCHMARK(BM_wdtwBanded_g)
+  ->Args({1000, 10})
+  ->Args({1000, 50})
+  ->Args({4000, 50})
+  ->Unit(benchmark::kMicrosecond);
+
+// ---------------------------------------------------------------------------
+// BM_wdtwBanded_precomputed — WDTW banded path with reused weight vector
+// ---------------------------------------------------------------------------
+static void BM_wdtwBanded_precomputed(benchmark::State &state)
+{
+  const auto len = static_cast<size_t>(state.range(0));
+  const int band = static_cast<int>(state.range(1));
+  constexpr double g = 0.05;
+  auto x = random_series(len, 42);
+  auto y = random_series(len, 43);
+  const int max_dev = static_cast<int>(std::max(x.size(), y.size()));
+  const auto weights = dtwc::wdtw_weights<double>(max_dev, g);
+  for (auto _ : state) {
+    benchmark::DoNotOptimize(dtwc::wdtwBanded<double>(x, y, weights, band));
+  }
+  state.SetItemsProcessed(static_cast<int64_t>(state.iterations()));
+}
+BENCHMARK(BM_wdtwBanded_precomputed)
+  ->Args({1000, 10})
+  ->Args({1000, 50})
+  ->Args({4000, 50})
+  ->Unit(benchmark::kMicrosecond);
+
+// ---------------------------------------------------------------------------
+// BM_ddtwBanded — DDTW banded path including derivative preprocessing
+// ---------------------------------------------------------------------------
+static void BM_ddtwBanded(benchmark::State &state)
+{
+  const auto len = static_cast<size_t>(state.range(0));
+  const int band = static_cast<int>(state.range(1));
+  auto x = random_series(len, 42);
+  auto y = random_series(len, 43);
+  for (auto _ : state) {
+    benchmark::DoNotOptimize(dtwc::ddtwBanded<double>(x, y, band));
+  }
+  state.SetItemsProcessed(static_cast<int64_t>(state.iterations()));
+}
+BENCHMARK(BM_ddtwBanded)
+  ->Args({1000, 10})
+  ->Args({1000, 50})
+  ->Args({4000, 50})
+  ->Unit(benchmark::kMicrosecond);
+
+// ---------------------------------------------------------------------------
+// BM_adtwBanded — ADTW banded path
+// ---------------------------------------------------------------------------
+static void BM_adtwBanded(benchmark::State &state)
+{
+  const auto len = static_cast<size_t>(state.range(0));
+  const int band = static_cast<int>(state.range(1));
+  constexpr double penalty = 1.0;
+  auto x = random_series(len, 42);
+  auto y = random_series(len, 43);
+  for (auto _ : state) {
+    benchmark::DoNotOptimize(dtwc::adtwBanded<double>(x, y, band, penalty));
+  }
+  state.SetItemsProcessed(static_cast<int64_t>(state.iterations()));
+}
+BENCHMARK(BM_adtwBanded)
+  ->Args({1000, 10})
+  ->Args({1000, 50})
+  ->Args({4000, 50})
+  ->Unit(benchmark::kMicrosecond);
+
+// ---------------------------------------------------------------------------
+// BM_wdtwBanded_mv_ndim1 — MV WDTW ndim==1 scalar fallback path
+// ---------------------------------------------------------------------------
+static void BM_wdtwBanded_mv_ndim1(benchmark::State &state)
+{
+  const auto len = static_cast<size_t>(state.range(0));
+  const int band = static_cast<int>(state.range(1));
+  constexpr double g = 0.05;
+  auto x = random_series(len, 42);
+  auto y = random_series(len, 43);
+  for (auto _ : state) {
+    benchmark::DoNotOptimize(
+      dtwc::wdtwBanded_mv<double>(x.data(), x.size(), y.data(), y.size(), 1, band, g));
+  }
+  state.SetItemsProcessed(static_cast<int64_t>(state.iterations()));
+}
+BENCHMARK(BM_wdtwBanded_mv_ndim1)
+  ->Args({1000, 10})
+  ->Args({1000, 50})
+  ->Args({4000, 50})
+  ->Unit(benchmark::kMicrosecond);
+
+// ---------------------------------------------------------------------------
+// BM_adtwBanded_mv_ndim1 — MV ADTW ndim==1 scalar fallback path
+// ---------------------------------------------------------------------------
+static void BM_adtwBanded_mv_ndim1(benchmark::State &state)
+{
+  const auto len = static_cast<size_t>(state.range(0));
+  const int band = static_cast<int>(state.range(1));
+  constexpr double penalty = 1.0;
+  auto x = random_series(len, 42);
+  auto y = random_series(len, 43);
+  for (auto _ : state) {
+    benchmark::DoNotOptimize(
+      dtwc::adtwBanded_mv<double>(x.data(), x.size(), y.data(), y.size(), 1, band, penalty));
+  }
+  state.SetItemsProcessed(static_cast<int64_t>(state.iterations()));
+}
+BENCHMARK(BM_adtwBanded_mv_ndim1)
+  ->Args({1000, 10})
+  ->Args({1000, 50})
+  ->Args({4000, 50})
+  ->Unit(benchmark::kMicrosecond);
+
 // ---------------------------------------------------------------------------
 // BM_fillDistanceMatrix — end-to-end distance matrix build
 // Args: (N_series, series_length, band)  where band=-1 means full DTW
@@ -170,6 +333,39 @@ BENCHMARK(BM_fillDistanceMatrix)
   ->Args({100, 1000, -1})
   ->Unit(benchmark::kMillisecond);
 
+// ---------------------------------------------------------------------------
+// BM_fillDistanceMatrix_variant — end-to-end Problem path by variant
+// Args: (N_series, series_length, band, variant_code)
+// ---------------------------------------------------------------------------
+static void BM_fillDistanceMatrix_variant(benchmark::State &state)
+{
+  const int N = static_cast<int>(state.range(0));
+  const int L = static_cast<int>(state.range(1));
+  const int band = static_cast<int>(state.range(2));
+  const int variant = static_cast<int>(state.range(3));
+  state.SetLabel(variant_name(variant));
+
+  for (auto _ : state) {
+    state.PauseTiming();
+    dtwc::Problem prob("bench_variant");
+    prob.set_data(make_random_data(N, L));
+    prob.band = band;
+    configure_problem_variant(prob, variant);
+    state.ResumeTiming();
+
+    prob.fillDistanceMatrix();
+  }
+
+  state.SetItemsProcessed(static_cast<int64_t>(state.iterations())
+                          * static_cast<int64_t>(N) * (N - 1) / 2);
+}
+BENCHMARK(BM_fillDistanceMatrix_variant)
+  ->Args({50, 500, 50, 0})
+  ->Args({50, 500, 50, 1})
+  ->Args({50, 500, 50, 2})
+  ->Args({50, 500, 50, 3})
+  ->Unit(benchmark::kMillisecond);
+
 // ---------------------------------------------------------------------------
 // BM_lb_keogh — LB_Keogh lower bound for varying lengths
 // ---------------------------------------------------------------------------