#include "harness.hpp" #include #include #include #include #include #include #include #include #include #include #include using plot::data::kBucket; PLOT_TEST(array_series_bounds_and_gather) { std::vector y{1, 5, -2, 3}; plot::data::ArraySeries s(std::move(y), /*x0=*/10.0, /*dx=*/0.5); PLOT_CHECK(s.size() == 4); PLOT_CHECK_NEAR(s.x_bounds().min, 10.0, 1e-9); PLOT_CHECK_NEAR(s.x_bounds().max, 11.5, 1e-9); PLOT_CHECK_NEAR(s.y_bounds().min, -2.0, 1e-6); std::vector out; s.gather(0, 0, 4, out); PLOT_CHECK(out.size() == 8); // interleaved x,y PLOT_CHECK_NEAR(out[0], 10.0, 1e-6); PLOT_CHECK_NEAR(out[1], 1.0, 1e-6); PLOT_CHECK_NEAR(out[6], 11.5, 1e-6); } PLOT_TEST(stream_series_acquire_publishes_snapshot) { plot::data::StreamSeries s(1 << 12, /*x0=*/0.0, /*dx=*/1e-6); for (int i = 0; i < 100; ++i) s.push(f32(i)); PLOT_CHECK(s.produced() == 100); s.acquire(); PLOT_CHECK(s.size() == 100); // Pyramid must track the published samples. PLOT_CHECK_NEAR(s.reduce(0, 100).max, 99.0, 1e-4); for (int i = 100; i < 250; ++i) s.push(f32(i)); s.acquire(); PLOT_CHECK(s.size() == 250); } PLOT_TEST(stream_series_drops_oldest_when_full) { plot::data::StreamSeries s(256, 0.0, 1.0); for (int i = 0; i < 1000; ++i) s.push(f32(i)); s.acquire(); PLOT_CHECK(s.size() <= 256); PLOT_CHECK_NEAR(s.y_bounds().max, 999.0, 1e-4); } PLOT_TEST(array_series_exact_range_queries_match_bruteforce) { // The strong test for the exactness split: arbitrary, deliberately // unaligned ranges must match a brute-force scan of the raw samples. std::mt19937 rng(7); std::uniform_real_distribution d(-5.0f, 5.0f); std::vector y(4000); for (auto& v : y) v = d(rng); plot::data::ArraySeries s(y, 0.0, 1.0); for (u64 a = 0; a < 4000; a += 173) { for (u64 b = a + 1; b <= 4000; b += 331) { float lo = y[a], hi = y[a]; double sum = 0.0, sq = 0.0; for (u64 i = a; i < b; ++i) { lo = std::min(lo, y[i]); hi = std::max(hi, y[i]); sum += y[i]; sq += double(y[i]) * double(y[i]); } const plot::Range r = s.reduce(a, b); PLOT_CHECK_NEAR(r.min, lo, 1e-4); PLOT_CHECK_NEAR(r.max, hi, 1e-4); PLOT_CHECK_NEAR(s.sum(a, b), sum, 1e-2); PLOT_CHECK_NEAR(s.sumsq(a, b), sq, 1e-1); } } } PLOT_TEST(stream_series_exact_queries_survive_ring_wrap) { plot::data::StreamSeries s(1u << 10, 0.0, 1.0); constexpr u64 kPushes = 3000; constexpr u64 kFirstRetained = kPushes - (1u << 10); // 1976 for (u64 i = 0; i < kPushes; ++i) s.push(f32(i % 97)); // wraps the ring twice s.acquire(); const u64 n = s.size(); PLOT_CHECK(n == 1u << 10); PLOT_CHECK_NEAR(s.x0(), 1976.0, 1e-9); PLOT_CHECK(s.x_bounds().min == s.x0()); PLOT_CHECK(s.pyramid().size() == n); const plot::Range r = s.reduce(0, n); // retained window, wrapped PLOT_CHECK_NEAR(r.max, 96.0, 1e-4); PLOT_CHECK_NEAR(r.min, 0.0, 1e-4); double sum = 0.0, sumsq = 0.0; for (u64 i = kFirstRetained; i < kPushes; ++i) { const double v = static_cast(i % 97); sum += v; sumsq += v * v; } PLOT_CHECK_NEAR(s.sum(0, n), sum, 1e-2); PLOT_CHECK_NEAR(s.sumsq(0, n), sumsq, 1e-1); std::vector out; s.gather(0, 0, n, out); // level 0: raw samples PLOT_CHECK(out.size() == 2 * n); PLOT_CHECK_NEAR(out[0], s.x0(), 1e-6); PLOT_CHECK_NEAR(out[1], f32(kFirstRetained % 97), 1e-6); PLOT_CHECK_NEAR(out[2 * n - 2], s.x0() + f64(n - 1), 1e-6); } PLOT_TEST(stream_series_push_and_read_are_race_free) { // The ring overwrites, so the producer reuses the slot of the snapshot's oldest // retained sample while the consumer may still be reading it. Relaxed atomic // slots make that defined; nothing else in the suite has two threads, so this is // the case ThreadSanitizer actually flags when the slots are plain. // // The two flags make the overlap structural, not scheduling luck: the reader // waits until the producer is already pushing, acknowledges, and only then does // the producer push the rest -- so the reader's window spans pushes that are in // flight by construction. The reader then loops until the producer reports done, // which also makes "at least one read" true by construction instead of by // winning a race with a fast producer. plot::data::StreamSeries s(1u << 8, 0.0, 1.0); // one read spans reused slots constexpr u64 kStride = 512; // pushes before the reader starts constexpr u64 kPushes = 4'096; // total: a few thousand only std::atomic started{false}; std::atomic reading{false}; std::atomic done{false}; std::thread producer([&] { for (u64 i = 0; i < kStride; ++i) s.push(f32(i % 971)); started.store(true, std::memory_order_release); while (!reading.load(std::memory_order_acquire)) { } for (u64 i = kStride; i < kPushes; ++i) s.push(f32(i % 971)); done.store(true, std::memory_order_release); }); while (!started.load(std::memory_order_acquire)) { } reading.store(true, std::memory_order_release); u64 reads = 0; bool sizes_ok = true; bool finished = false; do { finished = done.load(std::memory_order_acquire); s.acquire(); const u64 n = s.size(); if (n > 0) { (void)s.reduce(0, n); (void)s.sum(0, n); (void)s.sumsq(0, n); std::vector out; s.gather(0, 0, n, out); // reads the oldest edge if (out.size() != 2 * n) sizes_ok = false; } ++reads; } while (!finished); producer.join(); // Checked only after the join: a throw while the producer is joinable would // std::terminate instead of reporting the failure. PLOT_CHECK(s.produced() == kPushes); PLOT_CHECK(reads >= 1); PLOT_CHECK(sizes_ok); } namespace { /// Buckets the pyramid holds across every level: its footprint, not its window. u64 pyramid_entries(const plot::data::MinMaxPyramid& p) { u64 total = 0; for (u32 l = 0; l < p.level_count(); ++l) total += p.level_size(l); return total; } } // namespace PLOT_TEST(stream_series_sliding_window_queries_match_bruteforce) { // After the base has moved many times, an exact query must still match a scan // of exactly the retained samples. The pyramid's buckets live in absolute // sample space while the window's base is arbitrary, and that meeting point is // where an off-by-one hides -- so test the sliding case, not just the static // ArraySeries one. constexpr u64 kCapacity = 1u << 14; constexpr u64 kPushes = 60'000; const auto value = [](u64 i) { return f32((i * 29u) % 173u) - 86.0f; }; plot::data::StreamSeries s(kCapacity, 0.0, 1e-6); for (u64 i = 0; i < kPushes; i += 337) { const u64 n = std::min(337, kPushes - i); for (u64 k = 0; k < n; ++k) s.push(value(i + k)); s.acquire(); // the window's base moves on every one of these } const u64 n = s.size(); const u64 base = s.produced() - n; PLOT_CHECK(n == kCapacity); PLOT_CHECK(base > 2 * kCapacity); // the window really did slide PLOT_CHECK(s.pyramid().size() == n); // pyramid() indexes the window PLOT_CHECK(s.pyramid().window_base() == base); PLOT_CHECK(s.pyramid().window_end() == s.produced()); PLOT_CHECK_NEAR(s.x0(), f64(base) * 1e-6, 1e-12); PLOT_CHECK(s.x_bounds().min == s.x0()); PLOT_CHECK_NEAR(s.x_bounds().max, f64(base + n - 1) * 1e-6, 1e-9); // Brute force in window coordinates over the retained samples only. const auto brute = [&](u64 a, u64 b) { f64 lo = f64(value(base + a)), hi = lo; f64 sum = 0.0, sq = 0.0; for (u64 i = a; i < b; ++i) { const f64 v = f64(value(base + i)); lo = std::min(lo, v); hi = std::max(hi, v); sum += v; sq += v * v; } return std::array{lo, hi, sum, sq}; }; const u64 starts[] = {0, 1, 63, 64, 65, 1000, 7919, n - 200}; for (const u64 a : starts) { for (u64 b = a + 1; b <= n; b += 1301) { const std::array want = brute(a, b); const plot::Range r = s.reduce(a, b); PLOT_CHECK_NEAR(r.min, want[0], 1e-4); PLOT_CHECK_NEAR(r.max, want[1], 1e-4); PLOT_CHECK_NEAR(s.sum(a, b), want[2], 1e-2); PLOT_CHECK_NEAR(s.sumsq(a, b), want[3], 1e-1); } } const std::array whole = brute(0, n); PLOT_CHECK_NEAR(s.y_bounds().min, whole[0], 1e-6); PLOT_CHECK_NEAR(s.y_bounds().max, whole[1], 1e-6); // The level accessors are in absolute bucket coordinates: a stored bucket must // aggregate its own absolute span, the sliding window included. const u64 span = u64{kBucket} << 1; const u64 lbase = s.pyramid().level_base(1); const u64 lsize = s.pyramid().level_size(1); PLOT_CHECK(lsize >= 2); for (u64 b = lbase; b < lbase + std::min(lsize, 4); ++b) { const std::array want = brute(b * span - base, (b + 1) * span - base); const plot::data::MinMax m = s.pyramid().bucket(1, b); PLOT_CHECK_NEAR(m.min, want[0], 1e-6); PLOT_CHECK_NEAR(m.max, want[1], 1e-6); } // level-1 gather: the envelope pairs of the retained buckets, bracketed by the // two partial edge buckets as raw samples, so the geometry spans the range // exactly. This is the mapping the renderer draws from. std::vector out; s.gather(1, 0, n, out); const u64 first = std::max(base / span, lbase); const u64 last = std::min((base + n - 1) / span + 1, lbase + lsize); const u64 lead = first * span - base; // raw pairs before the first whole bucket const u64 trail = last * span - base; // first window index after the last one const u64 tail = trail < n ? n - trail : 0; const u64 env = last - first; PLOT_CHECK(out.size() == 2 * (lead + 2 * env + tail)); // each bucket is two pairs for (u64 i = 0; i < lead; ++i) { // the partial leading bucket, raw PLOT_CHECK_NEAR(out[2 * i], f32(f64(base + i) * 1e-6), 1e-9); PLOT_CHECK_NEAR(out[2 * i + 1], value(base + i), 1e-6); } for (u64 j = 0; j < env; ++j) { // Each whole bucket contributes two pairs: (first sample, min) and (last // sample, max). x is in data coordinates -- x0() is the retained window's // first sample -- so window index i plots at (base + i) * dx. const u64 bi = first + j; const std::array want = brute(bi * span - base, (bi + 1) * span - base); const u64 first_sample = bi * span - base; const u64 last_sample = std::min((bi + 1) * span, base + n) - 1 - base; const plot::usize lo = static_cast(2 * (lead + 2 * j)); const plot::usize hi = lo + 2; PLOT_CHECK_NEAR(out[lo], f32(f64(base + first_sample) * 1e-6), 1e-9); PLOT_CHECK_NEAR(out[lo + 1], want[0], 1e-6); PLOT_CHECK_NEAR(out[hi], f32(f64(base + last_sample) * 1e-6), 1e-9); PLOT_CHECK_NEAR(out[hi + 1], want[1], 1e-6); } for (u64 i = 0; i < tail; ++i) { // the partial trailing bucket: the newest samples const plot::usize k = static_cast(2 * (lead + 2 * env + i)); PLOT_CHECK_NEAR(out[k], f32(f64(base + trail + i) * 1e-6), 1e-9); PLOT_CHECK_NEAR(out[k + 1], value(base + trail + i), 1e-6); } } PLOT_TEST(stream_series_steady_state_acquire_is_proportional_to_produced) { // The defect this pins: a saturated ring whose base moved every frame used to // rebuild the whole window, costing O(capacity * live_levels) merges per // acquire. It must cost O(samples produced since the last acquire) instead, so // the same production through a 16x larger window must cost the same. const auto merges_for = [](u64 capacity) { plot::data::StreamSeries s(capacity, 0.0, 1.0); constexpr u64 kSaturate = 1u << 20; for (u64 i = 0; i < kSaturate; ++i) s.push(f32(i % 977)); s.acquire(); PLOT_CHECK(s.size() == capacity); constexpr u64 kFrames = 64; constexpr u64 kFrame = 1u << 13; // 8192 samples: 1 MS/s at ~122 fps plot::data::detail::merge_count().store(0, std::memory_order_relaxed); for (u64 f = 0; f < kFrames; ++f) { for (u64 k = 0; k < kFrame; ++k) s.push(f32((kSaturate + f * kFrame + k) % 977)); s.acquire(); } return plot::data::detail::merge_count().load(std::memory_order_relaxed); }; constexpr u64 kProduced = 64 * (1u << 13); const u64 small = merges_for(1u << 16); // 64k-sample window const u64 big = merges_for(1u << 20); // 1M-sample window: 16x to rebuild // ~kProduced/32 in practice; rebuilding the 1M window alone would merge // kCapacity/64 * live_levels ~ 245'000 buckets per acquire. PLOT_CHECK(small <= kProduced / 16); PLOT_CHECK(big <= kProduced / 16); PLOT_CHECK(big <= 2 * small + kBucket); } PLOT_TEST(stream_series_steady_state_acquire_is_fast) { // Wall-clock backstop for the merge count above: rebuilding the 1M-sample // window measured ~44 ms, so 128 such frames would need ~5.6 s. The sliding // path does the same work in a few milliseconds; the bound is two orders of // magnitude clear of both, so it is not a thin timing margin. plot::data::StreamSeries s(1u << 20, 0.0, 1.0); constexpr u64 kSaturate = 1u << 20; for (u64 i = 0; i < kSaturate; ++i) s.push(f32(i % 977)); s.acquire(); constexpr u64 kFrames = 128; constexpr u64 kFrame = 1u << 13; const auto t0 = std::chrono::steady_clock::now(); for (u64 f = 0; f < kFrames; ++f) { for (u64 k = 0; k < kFrame; ++k) s.push(f32((kSaturate + f * kFrame + k) % 977)); s.acquire(); } const f64 ms = std::chrono::duration(std::chrono::steady_clock::now() - t0).count() * 1.0e3; PLOT_CHECK(s.size() == 1u << 20); PLOT_CHECK(ms < 250.0); } PLOT_TEST(stream_series_pyramid_memory_is_bounded_by_the_window) { // 50M samples through a 1M-sample ring: the pyramid's footprint must track the // retained window (n/64 level-0 buckets plus the levels over them), not the // samples ever pushed. constexpr u64 kCapacity = 1u << 20; constexpr u64 kTotal = 50u * (1u << 20); constexpr u64 kChunk = 1u << 19; plot::data::StreamSeries s(kCapacity, 0.0, 1.0); u64 entries_after_10m = 0; for (u64 p = 0; p < kTotal; p += kChunk) { for (u64 i = 0; i < kChunk; ++i) s.push(f32((p + i) % 251)); s.acquire(); if (p + kChunk == 10u * (1u << 20)) entries_after_10m = pyramid_entries(s.pyramid()); } const u64 entries = pyramid_entries(s.pyramid()); const u64 bound = 2 * (kCapacity / kBucket) + kBucket; PLOT_CHECK(s.produced() == kTotal); PLOT_CHECK(s.size() == kCapacity); PLOT_CHECK(entries <= bound); // 5x the samples pushed, same footprint: levels deeper than one chunk can // differ by a bucket each, hence the slack. PLOT_CHECK(entries <= entries_after_10m + kBucket); } PLOT_TEST(gather_at_a_lod_level_reaches_both_ends_of_the_window) { // The pyramid stores complete buckets only, so its envelope stops at bucket // boundaries. Without the two partial edge buckets drawn from raw samples the // geometry would stop short of the newest samples -- the ones a live trace is // watched for -- and of the oldest retained ones. constexpr u64 kCapacity = 1u << 13; constexpr u64 kPushes = 40013; constexpr u64 kBase = kPushes - kCapacity; // 31821: not a multiple of kBucket const auto value = [](u64 i) { if (i == kBase) return 25.0f; // the oldest retained sample if (i == kPushes - 1) return -25.0f; // the newest retained sample return f32(i % 97) * 0.25f - 12.0f; // inside [-12, 12], so a bucket's }; // envelope can never equal either spike plot::data::StreamSeries s(kCapacity, 0.0, 1e-6); for (u64 i = 0; i < kPushes; ++i) s.push(value(i)); s.acquire(); const u64 n = s.size(); PLOT_CHECK(n == kCapacity); PLOT_CHECK((kBase % kBucket) != 0); // both edges off the grid PLOT_CHECK((kPushes % (u64{kBucket} << 1)) != 0); const auto check_ends = [&](u32 level) { std::vector out; s.gather(level, 0, n, out); PLOT_CHECK(out.size() >= 8u); // Oldest: the first emitted pair is the retained sample at index 0, not the // first whole bucket (which starts `lead` samples later). PLOT_CHECK_NEAR(out[0], f32(s.x0()), 1e-9); PLOT_CHECK_NEAR(out[1], 25.0, 1e-6); // Newest: the last emitted pair is the sample at index n-1, not the last // complete bucket. PLOT_CHECK_NEAR(out[out.size() - 2], f32(s.x0() + f64(n - 1) * 1e-6), 1e-9); PLOT_CHECK_NEAR(out[out.size() - 1], -25.0, 1e-6); }; PLOT_CHECK(s.pyramid().level_size(1) >= 2); check_ends(1); const u32 dense = s.pyramid().level_for(n, 1024.0); PLOT_CHECK(dense > 0u); check_ends(dense); // A static series whose window starts on the grid: only the trailing partial // bucket is at stake, and that is exactly what level_for() picks when a pixel // covers hundreds of samples. std::vector y(5000); for (u64 i = 0; i < y.size(); ++i) y[i] = value(i); y[0] = 25.0f; y[y.size() - 1] = -25.0f; const u64 ny = static_cast(y.size()); PLOT_CHECK((ny % 256u) != 0u); // 5000 = 19 * 256 + 136 at level 2 plot::data::ArraySeries a(y, 0.0, 1e-6); std::vector out; a.gather(2, 0, ny, out); PLOT_CHECK(out.size() >= 8u); PLOT_CHECK_NEAR(out[0], 0.0, 1e-9); // level 2 starts on the grid PLOT_CHECK_NEAR(out[out.size() - 2], f32(f64(ny - 1) * 1e-6), 1e-9); PLOT_CHECK_NEAR(out[out.size() - 1], -25.0, 1e-6); }