#include "DataModel.hpp" #include #include #include #include #include #include #include #include "Theme.hpp" #include "Utf8Util.hpp" namespace jdi { namespace { const double kMissing = std::numeric_limits::quiet_NaN(); /**< 缺失值占位。 */ const double kDefaultLineWidth = 1.6; /**< 默认线宽。 */ /** * @brief 判断列名是否为时间轴候选列。 * @param [IN] header 原始列名。 * @return 可能为时间轴返回 true。 */ bool LooksLikeTimeHeader(const std::wstring& header) { const std::wstring text = ToLowerAscii(Trim(header)); if (text.empty()) { return false; } if (text == L"t" || text == L"time" || text == L"timestamp" || text == L"simulation time" || text == L"时间" || text == L"时间轴") { return true; } return ContainsInsensitive(text, L"time") || ContainsInsensitive(text, L"时间"); } /** * @brief 从名称末尾的括号中提取单位(仅接受形如 mA / V / deg/s 的短标记)。 * @param [IN] text 列名(已去除首尾空白)。 * @return 单位文本,无法识别时返回空字符串。 */ std::wstring ExtractUnit(const std::wstring& text) { if (text.size() < 3 || text.back() != L')') { return std::wstring(); } const std::size_t open = text.rfind(L'('); if (open == std::wstring::npos || open + 2 >= text.size()) { return std::wstring(); } const std::wstring inner = Trim(text.substr(open + 1, text.size() - open - 2)); if (inner.empty() || inner.size() > 10) { return std::wstring(); } for (const wchar_t c : inner) { const bool allowed = iswalpha(c) || iswdigit(c) || c == L'%' || c == L'/' || c == L'^' || c == L'-' || c == L'.' || c == L'\u00B0' || c == L'\u00B5' || c == L'\u03A9' || c == L'\u00B2' || c == L'\u00B3' || c == L'\u00B7'; if (!allowed) { return std::wstring(); } } return inner; } /** * @brief 为网格范围补充留白,避免波形紧贴边界。 * @param [IN, OUT] yMin 范围下限。 * @param [IN, OUT] yMax 范围上限。 */ void PadRange(double& yMin, double& yMax) { if (!std::isfinite(yMin) || !std::isfinite(yMax)) { yMin = 0.0; yMax = 1.0; return; } const double span = yMax - yMin; if (span <= 0.0) { const double magnitude = std::max(1.0, std::fabs(yMin) * 0.1); yMin -= magnitude; yMax += magnitude; return; } const double pad = span * 0.06; yMin -= pad; yMax += pad; } /** * @brief 依据全部可见信号重新生成网格划分。 * @param [IN] visible 各信号的可见性(按 [文件][信号] 索引)。 * @param [IN] lanes 网格集合(原地更新)。 * @param [IN] mode 网格划分策略。 */ void RebuildLanes(const std::vector>& visible, std::vector& lanes, LaneMode mode) { // 随网格携带的“网格自身状态”(按信号继承):重建网格时不能丢。 struct LaneCarry { bool fitYToSelection = false; bool edgeCount = false; double edgeValue = 0.0; bool edgeValueValid = false; bool edgePanelOpen = true; double edgePanelX = -1.0; double edgePanelY = -1.0; bool edgeCenter = false; std::vector edgeCenterItems; bool edgeCenterPanelOpen = true; double edgeCenterPanelX = -1.0; double edgeCenterPanelY = -1.0; bool meanFilter = false; std::vector meanFilterItems; bool meanFilterPanelOpen = true; double meanFilterPanelX = -1.0; double meanFilterPanelY = -1.0; bool weakBoost = false; std::vector weakBoostItems; double weakBoostLevel = 0.5; int weakBoostIterations = 1; bool weakBoostPanelOpen = true; double weakBoostPanelX = -1.0; double weakBoostPanelY = -1.0; }; // 先记下每个信号原来所在网格的网格自身状态: // 勾选可见性会重建网格,若不携带,用户刚打开的开关会被悄悄清掉。 std::vector> previousCarry; for (const Lane& lane : lanes) { LaneCarry carry; carry.fitYToSelection = lane.fitYToSelection; carry.edgeCount = lane.edgeCount; carry.edgeValue = lane.edgeValue; carry.edgeValueValid = lane.edgeValueValid; carry.edgePanelOpen = lane.edgePanelOpen; carry.edgePanelX = lane.edgePanelX; carry.edgePanelY = lane.edgePanelY; carry.edgeCenter = lane.edgeCenter; carry.edgeCenterItems = lane.edgeCenterItems; carry.edgeCenterPanelOpen = lane.edgeCenterPanelOpen; carry.edgeCenterPanelX = lane.edgeCenterPanelX; carry.edgeCenterPanelY = lane.edgeCenterPanelY; carry.meanFilter = lane.meanFilter; carry.meanFilterItems = lane.meanFilterItems; carry.meanFilterPanelOpen = lane.meanFilterPanelOpen; carry.meanFilterPanelX = lane.meanFilterPanelX; carry.meanFilterPanelY = lane.meanFilterPanelY; carry.weakBoost = lane.weakBoost; carry.weakBoostItems = lane.weakBoostItems; carry.weakBoostLevel = lane.weakBoostLevel; carry.weakBoostIterations = lane.weakBoostIterations; carry.weakBoostPanelOpen = lane.weakBoostPanelOpen; carry.weakBoostPanelX = lane.weakBoostPanelX; carry.weakBoostPanelY = lane.weakBoostPanelY; for (const SignalRef& ref : lane.signals) { previousCarry.emplace_back(ref, carry); } } const auto inheritedCarry = [&previousCarry](const SignalRef& ref) { for (const std::pair& entry : previousCarry) { if (entry.first == ref) { return entry.second; } } return LaneCarry(); }; const auto applyCarry = [&inheritedCarry](Lane& lane, const SignalRef& ref) { const LaneCarry carry = inheritedCarry(ref); lane.fitYToSelection = carry.fitYToSelection; lane.edgeCount = carry.edgeCount; lane.edgeValue = carry.edgeValue; lane.edgeValueValid = carry.edgeValueValid; lane.edgePanelOpen = carry.edgePanelOpen; lane.edgePanelX = carry.edgePanelX; lane.edgePanelY = carry.edgePanelY; lane.edgeCenter = carry.edgeCenter; lane.edgeCenterItems = carry.edgeCenterItems; lane.edgeCenterPanelOpen = carry.edgeCenterPanelOpen; lane.edgeCenterPanelX = carry.edgeCenterPanelX; lane.edgeCenterPanelY = carry.edgeCenterPanelY; lane.meanFilter = carry.meanFilter; lane.meanFilterItems = carry.meanFilterItems; lane.meanFilterPanelOpen = carry.meanFilterPanelOpen; lane.meanFilterPanelX = carry.meanFilterPanelX; lane.meanFilterPanelY = carry.meanFilterPanelY; lane.weakBoost = carry.weakBoost; lane.weakBoostItems = carry.weakBoostItems; lane.weakBoostLevel = carry.weakBoostLevel; lane.weakBoostIterations = carry.weakBoostIterations; lane.weakBoostPanelOpen = carry.weakBoostPanelOpen; lane.weakBoostPanelX = carry.weakBoostPanelX; lane.weakBoostPanelY = carry.weakBoostPanelY; }; // 收集全部可见信号引用。 std::vector visibleRefs; for (std::size_t fileIndex = 0; fileIndex < visible.size(); ++fileIndex) { for (std::size_t signalIndex = 0; signalIndex < visible[fileIndex].size(); ++signalIndex) { if (visible[fileIndex][signalIndex]) { SignalRef ref; ref.fileIndex = static_cast(fileIndex); ref.signalIndex = static_cast(signalIndex); visibleRefs.push_back(ref); } } } // 判断某引用对应的信号是否可见(越界视为不可见)。 const auto isVisibleRef = [&visible](const SignalRef& ref) { if (ref.fileIndex < 0 || static_cast(ref.fileIndex) >= visible.size()) { return false; } const std::vector& fileVisible = visible[static_cast(ref.fileIndex)]; if (ref.signalIndex < 0 || static_cast(ref.signalIndex) >= fileVisible.size()) { return false; } return fileVisible[static_cast(ref.signalIndex)]; }; // 某信号当前所属的网格下标(-1 表示尚未分配网格)。 const auto laneIndexOf = [&lanes](const SignalRef& ref) { for (std::size_t index = 0; index < lanes.size(); ++index) { const std::vector& refs = lanes[index].signals; if (std::find(refs.begin(), refs.end(), ref) != refs.end()) { return static_cast(index); } } return -1; }; if (mode == LaneMode::PER_SIGNAL) { // 每条可见信号独占一个网格:网格数量严格跟随可见信号数量。 // **顺序按"原有网格位置"优先**:已经分配过网格的信号保持其相对次序, // 新勾选(此前没有网格)的信号统一追加到最下方。 // 若直接按 visibleRefs(文件/列序)重建,新勾选的信号会按其列序 // 插到中间,位置看起来"不确定"。 std::vector ordered; ordered.reserve(visibleRefs.size()); for (const SignalRef& ref : visibleRefs) { if (laneIndexOf(ref) >= 0) { ordered.push_back(ref); } } std::stable_sort(ordered.begin(), ordered.end(), [&laneIndexOf](const SignalRef& a, const SignalRef& b) { return laneIndexOf(a) < laneIndexOf(b); }); for (const SignalRef& ref : visibleRefs) { if (laneIndexOf(ref) < 0) { ordered.push_back(ref); } } lanes.clear(); lanes.reserve(ordered.size()); for (const SignalRef& ref : ordered) { Lane lane; lane.autoRange = true; applyCarry(lane, ref); lane.signals.push_back(ref); lanes.push_back(std::move(lane)); } } else if (mode == LaneMode::MERGED) { // 全部可见信号合并到同一网格;无可见信号时不保留空网格。 bool previousAutoRange = true; double previousYMin = -1.0; double previousYMax = 1.0; if (lanes.size() == 1) { previousAutoRange = lanes[0].autoRange; previousYMin = lanes[0].yMin; previousYMax = lanes[0].yMax; } lanes.clear(); if (!visibleRefs.empty()) { Lane lane; lane.autoRange = previousAutoRange; lane.yMin = previousYMin; lane.yMax = previousYMax; applyCarry(lane, visibleRefs.front()); lane.signals = visibleRefs; lanes.push_back(std::move(lane)); } } else { // 自定义划分:仅移除不可见信号与由此产生的空网格,保持用户排布。 for (Lane& lane : lanes) { std::vector& refs = lane.signals; refs.erase(std::remove_if(refs.begin(), refs.end(), [&isVisibleRef](const SignalRef& ref) { return !isVisibleRef(ref); }), refs.end()); } lanes.erase(std::remove_if(lanes.begin(), lanes.end(), [](const Lane& lane) { return lane.signals.empty(); }), lanes.end()); // 未分配网格的可见信号各自独占一个新网格。 // 注意:不能把它们塞进已有的第一个网格——那会导致“拖拽合并后新勾选的信号 // 被悄悄并入合并网格”,用户看不到新增的独立泳道。 for (const SignalRef& ref : visibleRefs) { bool placed = false; for (const Lane& lane : lanes) { if (std::find(lane.signals.begin(), lane.signals.end(), ref) != lane.signals.end()) { placed = true; break; } } if (placed) { continue; } Lane lane; lane.autoRange = true; applyCarry(lane, ref); lane.signals.push_back(ref); lanes.push_back(std::move(lane)); } } // 统一重命名,保证编号连续。 for (std::size_t index = 0; index < lanes.size(); ++index) { lanes[index].name = L"网格 " + std::to_wstring(index + 1); } } } const wchar_t* DrawModeName(DrawMode mode) { switch (mode) { case DrawMode::LINE: return L"线段"; case DrawMode::SCATTER: return L"散点"; case DrawMode::LINE_SCATTER: return L"点线"; default: return L"线段"; } } // ============================ DataFile 构建 ============================ /** * @brief 粗粒度包络层每个分组覆盖的采样数。 * * 16KB 的双精度分组可覆盖 1024 个采样(内存开销 = 采样数的 1.6%), * 但会让"每列采样数略多于分组跨度"的场景退化为逐点扫描。 * 取 256 时:额外内存约为采样数的 0.8%,最坏情况的扫描量也能压低到 * 每列 ≤256 个采样(2400 列 ≈ 0.6M 次读取,约 1ms)。 */ const std::size_t kCoarseStride = 256; /** * @brief 单条信号的取值范围统计结果。 */ struct SignalStats { double minValue = 0.0; /**< 有限采样值最小值。 */ double maxValue = 0.0; /**< 有限采样值最大值。 */ std::size_t finiteCount = 0; /**< 有限采样点数量。 */ }; /** * @brief 统计一列采样的最小/最大值与有效点数量,并顺带构建粗粒度包络层。 * * 两者在同一个循环内完成,避免为粗粒度层多扫一遍数据(大文件下那是一整趟内存遍历)。 * * @param [IN] values 采样列。 * @param [OUT] coarseMin 粗粒度分组最小值输出。 * @param [OUT] coarseMax 粗粒度分组最大值输出。 * @return 统计结果。 */ SignalStats ComputeStats(const std::vector& values, std::vector& coarseMin, std::vector& coarseMax) { SignalStats stats; double low = std::numeric_limits::infinity(); double high = -std::numeric_limits::infinity(); const std::size_t count = values.size(); const std::size_t buckets = (count + kCoarseStride - 1) / kCoarseStride; coarseMin.assign(buckets, std::numeric_limits::infinity()); coarseMax.assign(buckets, -std::numeric_limits::infinity()); std::size_t bucket = 0; std::size_t bucketEnd = kCoarseStride; for (std::size_t index = 0; index < count; ++index) { if (index >= bucketEnd) { ++bucket; bucketEnd += kCoarseStride; } const double value = values[index]; if (std::isfinite(value)) { ++stats.finiteCount; low = std::min(low, value); high = std::max(high, value); if (value < coarseMin[bucket]) { coarseMin[bucket] = value; } if (value > coarseMax[bucket]) { coarseMax[bucket] = value; } } } if (stats.finiteCount == 0) { stats.minValue = 0.0; stats.maxValue = 0.0; } else { stats.minValue = low; stats.maxValue = high; } return stats; } bool BuildDataFile(CsvTable&& table, const std::wstring& filePath, std::size_t paletteBase, DataFile& file, std::wstring& error, const CsvProgress& progress) { error.clear(); file = DataFile(); if (!table.HasData()) { error = L"数据表为空。"; return false; } const std::size_t columnCount = table.headers.size(); if (table.columns.size() < columnCount) { error = L"数据表列结构不完整。"; return false; } // 1. 识别时间轴列:优先取列名匹配的列,否则回退到第一列。 int timeColumn = -1; for (std::size_t column = 0; column < columnCount; ++column) { if (LooksLikeTimeHeader(table.headers[column])) { timeColumn = static_cast(column); break; } } if (timeColumn < 0) { timeColumn = 0; } // 时间列整列移动,不做逐元素拷贝。 file.time = std::move(table.columns[static_cast(timeColumn)]); std::size_t finiteTimeCount = 0; bool monotonic = true; double previousTime = 0.0; bool hasPrevious = false; for (const double value : file.time) { if (std::isfinite(value)) { ++finiteTimeCount; if (hasPrevious && value < previousTime) { monotonic = false; } previousTime = value; hasPrevious = true; } } if (finiteTimeCount < 2) { error = L"时间轴列(" + table.headers[static_cast(timeColumn)] + L")有效数值不足。"; return false; } file.timeColumnName = table.headers[static_cast(timeColumn)]; file.timeMonotonic = monotonic; file.filePath = filePath; const std::size_t slashPos = filePath.find_last_of(L"\\/"); file.fileName = (slashPos == std::wstring::npos) ? filePath : filePath.substr(slashPos + 1); // 2. 构建信号列:每列整块移动,随后就地统计取值范围。 int paletteCount = 0; const std::uint32_t* palette = SignalPalette(paletteCount); file.signals.reserve(columnCount); for (std::size_t column = 0; column < columnCount; ++column) { if (static_cast(column) == timeColumn) { continue; } SignalData signal; signal.rawHeader = table.headers[column]; { // 名称完整保留文件内的列名(含 "[n]" 序号与括号描述),仅用于展示不做改写。 signal.name = Trim(signal.rawHeader); signal.unit = ExtractUnit(signal.name); } signal.values = std::move(table.columns[column]); const SignalStats stats = ComputeStats(signal.values, signal.coarseMin, signal.coarseMax); signal.coarseStride = kCoarseStride; signal.minValue = stats.minValue; signal.maxValue = stats.maxValue; signal.finiteCount = stats.finiteCount; // 显示外观随信号一起初始化:调色板按「全局信号序号」取色, // 使同一信号在任意标签页中都保持同一默认颜色。 { const std::size_t globalIndex = paletteBase + file.signals.size(); if (palette != nullptr && paletteCount > 0) { const std::size_t count = static_cast(paletteCount); const std::size_t slot = globalIndex % count; signal.style.color = palette[slot]; // 自定义色初值取调色板中「向后递进」的下一个颜色。 // 若初值等于本信号自身的预设色,样式区里点击该预设色块会被判定成 // “当前用的是自定义色”,高亮会直接跳到自定义色块上(此前的缺陷)。 signal.style.customColor = palette[(slot + 1) % count]; } else { signal.style.color = 0xFF268BD2u; signal.style.customColor = 0xFF859900u; } signal.style.opacity = 1.0f; signal.style.lineWidth = 1.0f; signal.style.mode = DrawMode::LINE; } file.signals.push_back(std::move(signal)); if (progress) { CsvProgressInfo info; info.ratio = 0.75 + 0.25 * static_cast(column + 1) / static_cast(columnCount); if (!progress(info)) { error = L"已取消加载。"; return false; } } } if (file.signals.empty()) { error = L"除时间轴外未发现任何数据列。"; return false; } // 3. 统计时间范围(时间列为空或全部无效时回退到行数上界)。 double tMin = std::numeric_limits::infinity(); double tMax = -std::numeric_limits::infinity(); for (const double value : file.time) { if (std::isfinite(value)) { tMin = std::min(tMin, value); tMax = std::max(tMax, value); } } file.minTime = tMin; file.maxTime = tMax; return true; } // ============================ DataSet ============================ bool DataSet::AddDataFile(DataFile&& file, int& fileIndex) { fileIndex = -1; if (file.signals.empty()) { return false; } m_files.push_back(std::move(file)); fileIndex = static_cast(m_files.size()) - 1; return true; } bool DataSet::InsertDerivedSignal(int fileIndex, int afterSignalIndex, SignalData&& signal, int& newSignalIndex) { newSignalIndex = -1; if (fileIndex < 0 || fileIndex >= static_cast(m_files.size())) { return false; } DataFile& file = m_files[static_cast(fileIndex)]; if (afterSignalIndex < -1 || afterSignalIndex >= static_cast(file.signals.size())) { return false; } // 1. 采样值统计与粗粒度包络层:与正常加载路径使用同一套统计逻辑, // 否则派生信号在大文件下会退化成逐点扫描(包络构建变慢)。 const SignalStats stats = ComputeStats(signal.values, signal.coarseMin, signal.coarseMax); signal.coarseStride = kCoarseStride; signal.minValue = stats.minValue; signal.maxValue = stats.maxValue; signal.finiteCount = stats.finiteCount; // 2. 显示外观按「全局信号序号」取调色板颜色(与普通新信号完全一致的规则)。 const int insertPos = afterSignalIndex + 1; { // 新信号的全局序号 = 本文件之前的信号总数 + 它在文件内的下标。 std::size_t globalIndex = static_cast(insertPos); for (int index = 0; index < fileIndex; ++index) { globalIndex += m_files[static_cast(index)].signals.size(); } int paletteCount = 0; const std::uint32_t* palette = SignalPalette(paletteCount); if (palette != nullptr && paletteCount > 0) { const std::size_t count = static_cast(paletteCount); const std::size_t slot = globalIndex % count; signal.style.color = palette[slot]; signal.style.customColor = palette[(slot + 1) % count]; } } file.signals.insert(file.signals.begin() + insertPos, std::move(signal)); // 3. 全局选中引用:同一文件内位于插入点之后的信号下标整体后移。 if (m_selected.fileIndex == fileIndex && m_selected.signalIndex >= insertPos) { ++m_selected.signalIndex; } newSignalIndex = insertPos; return true; } bool DataSet::RemoveFile(int fileIndex) { if (fileIndex < 0 || fileIndex >= static_cast(m_files.size())) { return false; } // 用移动到末位后弹出的方式移除,使被移除文件的时间轴与全部信号缓冲区在本调用内 // 立即析构归还操作系统,不再等待后续插入覆盖;最后收缩容量,避免残留空闲块。 const std::size_t position = static_cast(fileIndex); for (std::size_t index = position; index + 1 < m_files.size(); ++index) { m_files[index] = std::move(m_files[index + 1]); } m_files.pop_back(); m_files.shrink_to_fit(); return true; } bool DataSet::RemoveSignal(int fileIndex, int signalIndex) { if (fileIndex < 0 || fileIndex >= static_cast(m_files.size())) { return false; } DataFile& file = m_files[static_cast(fileIndex)]; if (signalIndex < 0 || signalIndex >= static_cast(file.signals.size())) { return false; } // 与 RemoveFile 同一思路:先把待移除项移到末位(move 赋值时其原有缓冲当场析构), // 再 pop_back + shrink_to_fit,使该信号的全部采样内存在本调用内立即归还给系统, // 而不是留在容量里等后续插入覆盖。 std::vector& signals = file.signals; const std::size_t position = static_cast(signalIndex); for (std::size_t index = position; index + 1 < signals.size(); ++index) { signals[index] = std::move(signals[index + 1]); } signals.pop_back(); signals.shrink_to_fit(); return true; } void DataSet::RemapSelectionAfterSignalRemoval(int fileIndex, int signalIndex) { if (fileIndex < 0 || signalIndex < 0 || m_selected.fileIndex != fileIndex) { return; } if (m_selected.signalIndex == signalIndex) { // 选中的信号本身被移除:取消选中。 m_selected = SignalRef(); } else if (m_selected.signalIndex > signalIndex) { // 其后信号整体前移一位。 --m_selected.signalIndex; } } std::size_t DataSet::SignalCount() const { std::size_t count = 0; for (const DataFile& file : m_files) { count += file.signals.size(); } return count; } const DataFile* DataSet::FileAt(int fileIndex) const { if (fileIndex < 0 || fileIndex >= static_cast(m_files.size())) { return nullptr; } return &m_files[static_cast(fileIndex)]; } bool DataSet::SetSignalDisplayName(int fileIndex, int signalIndex, const std::wstring& name) { if (fileIndex < 0 || fileIndex >= static_cast(m_files.size())) { return false; } DataFile& file = m_files[static_cast(fileIndex)]; if (signalIndex < 0 || signalIndex >= static_cast(file.signals.size())) { return false; } // 统一去除首尾空白;结果为空则视为恢复原始列名。 std::wstring trimmed = Trim(name); SignalData& signal = file.signals[static_cast(signalIndex)]; if (trimmed == signal.displayName) { return false; } signal.displayName = std::move(trimmed); return true; } bool DataSet::SetFileDisplayName(int fileIndex, const std::wstring& name) { if (fileIndex < 0 || fileIndex >= static_cast(m_files.size())) { return false; } std::wstring trimmed = Trim(name); DataFile& file = m_files[static_cast(fileIndex)]; if (trimmed == file.displayName) { return false; } file.displayName = std::move(trimmed); return true; } const SignalData* DataSet::Resolve(const SignalRef& ref) const { const DataFile* file = FileAt(ref.fileIndex); if (file == nullptr) { return nullptr; } if (ref.signalIndex < 0 || ref.signalIndex >= static_cast(file->signals.size())) { return nullptr; } return &file->signals[static_cast(ref.signalIndex)]; } const SignalStyle* DataSet::Style(const SignalRef& ref) const { const SignalData* signal = Resolve(ref); return (signal != nullptr) ? &signal->style : nullptr; } SignalStyle* DataSet::Style(const SignalRef& ref) { const DataFile* file = FileAt(ref.fileIndex); if (file == nullptr) { return nullptr; } if (ref.signalIndex < 0 || ref.signalIndex >= static_cast(file->signals.size())) { return nullptr; } // 这里需要写入,因此借助非 const 路径重新定位信号。 DataFile& mutableFile = m_files[static_cast(ref.fileIndex)]; return &mutableFile.signals[static_cast(ref.signalIndex)].style; } double DataSet::MinTime() const { double value = std::numeric_limits::infinity(); for (const DataFile& file : m_files) { if (std::isfinite(file.minTime)) { value = std::min(value, file.minTime); } } return std::isfinite(value) ? value : 0.0; } double DataSet::MaxTime() const { double value = -std::numeric_limits::infinity(); for (const DataFile& file : m_files) { if (std::isfinite(file.maxTime)) { value = std::max(value, file.maxTime); } } return std::isfinite(value) ? value : 1.0; } void DataSet::RemapSelectionAfterFileRemoval(int fileIndex) { if (fileIndex < 0) { return; } if (m_selected.fileIndex == fileIndex) { m_selected = SignalRef(); } else if (m_selected.fileIndex > fileIndex) { --m_selected.fileIndex; } } bool DataSet::ValidateSelection() { if (!m_selected.IsValid()) { return false; } if (Resolve(m_selected) != nullptr) { return false; } m_selected = SignalRef(); return true; } // ============================ 采样辅助 ============================ namespace { /** * @brief 滑动平均的共用实现(输入只要可转成 double)。 * * 窗口 = [max(0,i-N), min(count-1,i+N)],每前进一步只增减边界处的两个采样点, * 整体 O(n),不额外占用前缀和内存。 */ template void MovingAverageImpl(const std::vector& values, int radius, std::vector& out); } // namespace void ComputeMovingAverage(const std::vector& values, int radius, std::vector& out) { MovingAverageImpl(values, radius, out); } namespace { template void MovingAverageImpl(const std::vector& values, int radius, std::vector& out) { const int window = std::max(0, radius); const std::size_t count = values.size(); out.assign(count, std::numeric_limits::quiet_NaN()); if (count == 0 || window == 0) { // 半径 0 表示不平滑:原样复制(中心点无效处仍为 NaN)。 for (std::size_t index = 0; index < count; ++index) { const double value = static_cast(values[index]); if (std::isfinite(value)) { out[index] = static_cast(value); } } return; } // 滑动窗口求和:每前进一步只增减边界处的两个采样点,整体 O(n)。 double sum = 0.0; std::size_t finiteCount = 0; std::size_t windowLow = 0; std::size_t windowHigh = 0; // 闭区间右端。 const auto addValue = [&sum, &finiteCount](double value) { if (std::isfinite(value)) { sum += value; ++finiteCount; } }; const auto removeValue = [&sum, &finiteCount](double value) { if (std::isfinite(value)) { sum -= value; --finiteCount; } }; for (std::size_t index = 0; index < count; ++index) { const std::size_t low = (index > static_cast(window)) ? (index - static_cast(window)) : 0; const std::size_t high = std::min(count - 1, index + static_cast(window)); if (index == 0) { windowLow = low; windowHigh = high; for (std::size_t i = windowLow; i <= windowHigh; ++i) { addValue(static_cast(values[i])); } } else { while (windowLow < low) { removeValue(static_cast(values[windowLow])); ++windowLow; } while (windowHigh < high) { ++windowHigh; addValue(static_cast(values[windowHigh])); } } // 中心点本身无效(NaN)时该处不产生有效结果。 const double center = static_cast(values[index]); if (finiteCount > 0 && std::isfinite(center)) { out[index] = static_cast(sum / static_cast(finiteCount)); } } } } // namespace void ComputeMovingAverageIterated(const std::vector& values, int radius, int iterations, std::vector& out) { const int stages = std::max(1, iterations); // 第 1 阶:从原始采样值出发。 ComputeMovingAverage(values, radius, out); if (stages == 1) { return; } // 后续各阶以上一阶的结果为输入(double 中转,避免 float→double 的精度损失累积)。 std::vector buffer(values.size(), std::numeric_limits::quiet_NaN()); std::vector stage; for (int iteration = 1; iteration < stages; ++iteration) { for (std::size_t index = 0; index < out.size(); ++index) { buffer[index] = std::isfinite(out[index]) ? static_cast(out[index]) : std::numeric_limits::quiet_NaN(); } ComputeMovingAverage(buffer, radius, stage); out.swap(stage); } } namespace { /** * @brief 「弱波增强」内部使用的极值点(波峰 / 波谷)。 */ struct BoostExtremum { std::size_t index = 0; /**< 采样下标。 */ double value = 0.0; /**< 采样值。 */ int type = 0; /**< +1 = 波峰,-1 = 波谷。 */ }; /** * @brief 「弱波增强」的单阶处理:把偏弱的波峰上拉、偏弱的波谷下拉。 * * **不做任何前置滤波**(需要平滑时用户可以先用「均值滤波」构建一条滤波后的信号): * 极值点直接在输入采样上通过单调段的方向翻转识别。 * * @param [IN] input 本阶的输入采样值。 * @param [IN] strength 弱波增强等级(0–1,已夹取)。 * @param [OUT] output 本阶的输出(长度与 input 相同;原值为 NaN 处保持 NaN)。 * @return 确实有采样点被改动返回 true;完全无弱波时返回 false。 */ bool ApplyWeakBoostStage(const std::vector& input, double strength, std::vector& output) { const std::size_t count = input.size(); output.assign(count, std::numeric_limits::quiet_NaN()); if (count == 0) { return false; } // 先把有效采样原样拷入输出,之后按“极值点之间的平滑偏移”逐点叠加。 for (std::size_t index = 0; index < count; ++index) { const float value = input[index]; if (std::isfinite(value)) { output[index] = value; } } // 1) 识别波峰 / 波谷:扫描单调段,方向翻转处的上一个采样点即为极值点。 // 波峰(先升后降)与波谷(先降后升)必然交替出现, // 因此同类极值就是极值序列里下标 ±2 的两个。 std::vector extremes; { int direction = 0; // 当前单调段方向(+1 上升、-1 下降)。 bool hasPrevious = false; std::size_t previousIndex = 0; double previousValue = 0.0; for (std::size_t index = 0; index < count; ++index) { const double value = static_cast(input[index]); if (!std::isfinite(value)) { // 无效采样作为断点:不跨越它判定极值。 hasPrevious = false; continue; } if (!hasPrevious) { hasPrevious = true; previousIndex = index; previousValue = value; continue; } const int step = (value > previousValue) ? 1 : ((value < previousValue) ? -1 : 0); if (step != 0) { if (direction == 0) { direction = step; } else if (step != direction) { // 方向在此翻转:上一个采样点就是极值(原方向向上则为波峰)。 BoostExtremum extreme; extreme.index = previousIndex; extreme.value = previousValue; extreme.type = direction; extremes.push_back(extreme); direction = step; } } previousIndex = index; previousValue = value; } } // 识别不到足够多的极值(常量 / 单调 / 采样点太少):本阶无需任何改动。 if (extremes.size() < 5) { return false; } // 2) 逐个极值点判定“是否偏弱”,并算出它自己的目标偏移量。 const std::size_t extremeCount = extremes.size(); std::vector shift(extremeCount, 0.0); for (std::size_t k = 2; k + 2 < extremeCount; ++k) { const BoostExtremum& current = extremes[k]; const BoostExtremum& left = extremes[k - 2]; const BoostExtremum& right = extremes[k + 2]; if (left.type != current.type || right.type != current.type) { continue; } if (!std::isfinite(current.value) || !std::isfinite(left.value) || !std::isfinite(right.value)) { continue; } const double mean = (left.value + right.value) * 0.5; const double lower = std::min(left.value, right.value); const double upper = std::max(left.value, right.value); double destination = 0.0; if (current.type > 0) { // 波峰:低于左右两个波峰的均值 → 判定为弱波,上拉到等级对应的目标值。 if (!(current.value < mean)) { continue; } destination = lower + strength * (upper - lower); } else { // 波谷:高于左右两个波谷的均值 → 判定为弱波,下拉到等级对应的目标值。 if (!(current.value > mean)) { continue; } destination = upper - strength * (upper - lower); } shift[k] = destination - current.value; } // 3) 把偏移量平滑地摊到极值点之间的数据点上: // 相邻两个极值点之间用平滑步进过渡(两端导数为 0,波形不会出现折角), // 数据首尾则从 0 渐变到最近的极值点偏移。 // 注意:极值序列的首尾各两个元素的偏移量恒为 0(缺少同类的左右邻居), // 因此这里只需要填充 shift 非零的区间。 bool changed = false; const auto applySpan = [&input, &output, count](std::size_t begin, std::size_t end, double beginShift, double endShift) { if (end <= begin) { if (begin < count && std::isfinite(input[begin])) { output[begin] = static_cast(input[begin] + beginShift); } return; } const double span = static_cast(end - begin); for (std::size_t index = begin; index <= end; ++index) { const float value = input[index]; if (!std::isfinite(value)) { continue; } const double t = static_cast(index - begin) / span; const double weight = t * t * (3.0 - 2.0 * t); output[index] = static_cast(value + beginShift * (1.0 - weight) + endShift * weight); } }; for (std::size_t k = 0; k + 1 < extremeCount; ++k) { if (shift[k] == 0.0 && shift[k + 1] == 0.0) { continue; } applySpan(extremes[k].index, extremes[k + 1].index, shift[k], shift[k + 1]); changed = true; } return changed; } } // namespace void ComputeWeakWaveBoost(const std::vector& values, double level, int iterations, std::vector& out) { const std::size_t count = values.size(); out.assign(count, std::numeric_limits::quiet_NaN()); if (count == 0) { return; } // 第 1 阶:从原始采样值出发(非有限值保持 NaN)。 std::vector current(count, std::numeric_limits::quiet_NaN()); for (std::size_t index = 0; index < count; ++index) { const double value = values[index]; if (std::isfinite(value)) { current[index] = static_cast(value); } } // 「迭代次数 N」与「均值滤波」的迭代次数语义一致:把同一处理**重复应用 N 次**, // 每一阶以上一阶的结果为输入。一阶时改定量已严格等于「等级」对应的目标值; // 多次迭代时相邻的弱波会互相抬高彼此的基准,从而把较宽的弱波区逐步恢复。 const int stages = std::max(1, std::min(iterations, 1000)); const double strength = std::max(0.0, std::min(1.0, level)); std::vector next; for (int stage = 0; stage < stages; ++stage) { if (!ApplyWeakBoostStage(current, strength, next)) { // 这一阶没有任何采样点需要调整:后续迭代次数也不会再有变化,提前结束。 break; } current.swap(next); } out.swap(current); } const Lane::MeanFilterItem* Lane::FindMeanFilterItem(const SignalRef& ref) const { for (const MeanFilterItem& item : meanFilterItems) { if (item.ref == ref) { return &item; } } return nullptr; } Lane::MeanFilterItem& Lane::EnsureMeanFilterItem(const SignalRef& ref) { for (MeanFilterItem& item : meanFilterItems) { if (item.ref == ref) { return item; } } MeanFilterItem item; item.ref = ref; meanFilterItems.push_back(item); return meanFilterItems.back(); } void Lane::RemoveMeanFilterItem(const SignalRef& ref) { meanFilterItems.erase( std::remove_if(meanFilterItems.begin(), meanFilterItems.end(), [&ref](const MeanFilterItem& item) { return item.ref == ref; }), meanFilterItems.end()); } const Lane::EdgeCenterItem* Lane::FindEdgeCenterItem(const SignalRef& ref) const { for (const EdgeCenterItem& item : edgeCenterItems) { if (item.ref == ref) { return &item; } } return nullptr; } Lane::EdgeCenterItem& Lane::EnsureEdgeCenterItem(const SignalRef& ref) { for (EdgeCenterItem& item : edgeCenterItems) { if (item.ref == ref) { return item; } } EdgeCenterItem item; item.ref = ref; edgeCenterItems.push_back(item); return edgeCenterItems.back(); } void Lane::RemoveEdgeCenterItem(const SignalRef& ref) { edgeCenterItems.erase( std::remove_if(edgeCenterItems.begin(), edgeCenterItems.end(), [&ref](const EdgeCenterItem& item) { return item.ref == ref; }), edgeCenterItems.end()); } const Lane::WeakBoostItem* Lane::FindWeakBoostItem(const SignalRef& ref) const { for (const WeakBoostItem& item : weakBoostItems) { if (item.ref == ref) { return &item; } } return nullptr; } Lane::WeakBoostItem& Lane::EnsureWeakBoostItem(const SignalRef& ref) { for (WeakBoostItem& item : weakBoostItems) { if (item.ref == ref) { return item; } } WeakBoostItem item; item.ref = ref; weakBoostItems.push_back(item); return weakBoostItems.back(); } void Lane::RemoveWeakBoostItem(const SignalRef& ref) { weakBoostItems.erase( std::remove_if(weakBoostItems.begin(), weakBoostItems.end(), [&ref](const WeakBoostItem& item) { return item.ref == ref; }), weakBoostItems.end()); } int FindNearestSample(const DataFile& file, double time) { const std::size_t count = file.time.size(); if (count == 0) { return -1; } if (file.timeMonotonic) { const std::vector::const_iterator lower = std::lower_bound(file.time.begin(), file.time.end(), time); if (lower == file.time.begin()) { return 0; } if (lower == file.time.end()) { return static_cast(count - 1); } const std::size_t rightIndex = static_cast(lower - file.time.begin()); const std::size_t leftIndex = rightIndex - 1; const double leftDistance = std::fabs(time - file.time[leftIndex]); const double rightDistance = std::fabs(file.time[rightIndex] - time); return (leftDistance <= rightDistance) ? static_cast(leftIndex) : static_cast(rightIndex); } int best = 0; double bestDistance = std::numeric_limits::infinity(); for (std::size_t index = 0; index < count; ++index) { if (!std::isfinite(file.time[index])) { continue; } const double distance = std::fabs(file.time[index] - time); if (distance < bestDistance) { bestDistance = distance; best = static_cast(index); } } return best; } bool SampleSignalAt(const DataFile& file, const SignalData& signal, double time, bool interpolate, double& value) { value = kMissing; if (file.time.empty() || signal.values.empty()) { return false; } if (time < file.minTime || time > file.maxTime) { return false; } const std::vector& values = signal.values; if (!file.timeMonotonic) { const int nearest = FindNearestSample(file, time); if (nearest < 0 || static_cast(nearest) >= values.size()) { return false; } value = values[static_cast(nearest)]; return std::isfinite(value); } const std::vector::const_iterator lower = std::lower_bound(file.time.begin(), file.time.end(), time); const std::size_t rightIndex = static_cast(lower - file.time.begin()); if (rightIndex == 0) { value = values[0]; return std::isfinite(value); } if (rightIndex >= file.time.size()) { value = values.back(); return std::isfinite(value); } const std::size_t leftIndex = rightIndex - 1; if (rightIndex >= values.size() || leftIndex >= values.size()) { return false; } const double t0 = file.time[leftIndex]; const double t1 = file.time[rightIndex]; const double v0 = values[leftIndex]; const double v1 = values[rightIndex]; if (!interpolate || !std::isfinite(v0) || !std::isfinite(v1) || !(t1 > t0)) { const double leftDistance = std::fabs(time - t0); const double rightDistance = std::fabs(t1 - time); value = (leftDistance <= rightDistance) ? v0 : v1; return std::isfinite(value); } const double ratio = (time - t0) / (t1 - t0); value = v0 + (v1 - v0) * ratio; return true; } // ============================ TabConfig ============================ TabConfig::TabConfig() : m_name(L"视图 1") { } void TabConfig::SyncToDataSet(const DataSet& dataSet) { const std::size_t fileCount = dataSet.FileCount(); m_visible.resize(fileCount); m_collapsed.resize(fileCount, false); for (std::size_t fileIndex = 0; fileIndex < fileCount; ++fileIndex) { const DataFile* file = dataSet.FileAt(static_cast(fileIndex)); if (file == nullptr) { continue; } // 新增信号默认为未勾选(由用户自行决定查看哪些信号), // 其显示外观已在 DataSet 中初始化完毕。 m_visible[fileIndex].resize(file->signals.size(), false); } // 清理已失效的网格引用(选中状态由 DataSet 统一维护)。 for (Lane& lane : m_lanes) { std::vector& refs = lane.signals; refs.erase(std::remove_if(refs.begin(), refs.end(), [&dataSet](const SignalRef& ref) { return dataSet.Resolve(ref) == nullptr; }), refs.end()); } m_lanes.erase(std::remove_if(m_lanes.begin(), m_lanes.end(), [](const Lane& lane) { return lane.signals.empty(); }), m_lanes.end()); SyncLanes(); } void TabConfig::RemapAfterFileRemoval(int fileIndex) { if (fileIndex < 0) { return; } const std::size_t slot = static_cast(fileIndex); if (slot < m_visible.size()) { m_visible.erase(m_visible.begin() + fileIndex); } if (slot < m_collapsed.size()) { m_collapsed.erase(m_collapsed.begin() + fileIndex); } for (Lane& lane : m_lanes) { std::vector& refs = lane.signals; refs.erase(std::remove_if(refs.begin(), refs.end(), [fileIndex](const SignalRef& ref) { return ref.fileIndex == fileIndex; }), refs.end()); for (SignalRef& ref : refs) { if (ref.fileIndex > fileIndex) { --ref.fileIndex; } } } m_lanes.erase(std::remove_if(m_lanes.begin(), m_lanes.end(), [](const Lane& lane) { return lane.signals.empty(); }), m_lanes.end()); } void TabConfig::RemapAfterSignalRemoval(int fileIndex, int signalIndex) { if (fileIndex < 0 || signalIndex < 0) { return; } // 可见性表:删掉该信号对应的那一列。 const std::size_t slot = static_cast(fileIndex); if (slot < m_visible.size()) { std::vector& fileVisible = m_visible[slot]; if (static_cast(signalIndex) < fileVisible.size()) { fileVisible.erase(fileVisible.begin() + signalIndex); } } // 网格归属:删掉该信号本身,并把同一文件内位于其后的引用下标前移一位。 for (Lane& lane : m_lanes) { std::vector& refs = lane.signals; refs.erase(std::remove_if(refs.begin(), refs.end(), [fileIndex, signalIndex](const SignalRef& ref) { return ref.fileIndex == fileIndex && ref.signalIndex == signalIndex; }), refs.end()); for (SignalRef& ref : refs) { if (ref.fileIndex == fileIndex && ref.signalIndex > signalIndex) { --ref.signalIndex; } } // 均值滤波 / 中心轴边沿计数的条目同样持有信号引用,必须一起删除/前移。 const auto purgeRefs = [fileIndex, signalIndex](std::vector& items) { items.erase(std::remove_if(items.begin(), items.end(), [fileIndex, signalIndex](const Lane::MeanFilterItem& item) { return item.ref.fileIndex == fileIndex && item.ref.signalIndex == signalIndex; }), items.end()); for (Lane::MeanFilterItem& item : items) { if (item.ref.fileIndex == fileIndex && item.ref.signalIndex > signalIndex) { --item.ref.signalIndex; } } }; purgeRefs(lane.meanFilterItems); purgeRefs(lane.edgeCenterItems); purgeRefs(lane.weakBoostItems); } // 被移除信号若独占了某个网格,该网格随之消失(与取消勾选的行为一致)。 m_lanes.erase(std::remove_if(m_lanes.begin(), m_lanes.end(), [](const Lane& lane) { return lane.signals.empty(); }), m_lanes.end()); } bool TabConfig::IsVisible(const SignalRef& ref) const { if (ref.fileIndex < 0 || static_cast(ref.fileIndex) >= m_visible.size()) { return false; } const std::vector& fileVisible = m_visible[static_cast(ref.fileIndex)]; if (ref.signalIndex < 0 || static_cast(ref.signalIndex) >= fileVisible.size()) { return false; } return fileVisible[static_cast(ref.signalIndex)]; } void TabConfig::SetVisible(const SignalRef& ref, bool visible) { if (ref.fileIndex < 0 || static_cast(ref.fileIndex) >= m_visible.size()) { return; } std::vector& fileVisible = m_visible[static_cast(ref.fileIndex)]; if (ref.signalIndex < 0 || static_cast(ref.signalIndex) >= fileVisible.size()) { return; } if (fileVisible[static_cast(ref.signalIndex)] == visible) { return; } fileVisible[static_cast(ref.signalIndex)] = visible; // 合并模式下新勾选的信号独占一个新网格:切到自定义划分后, // RebuildLanes 会把尚未分配网格的可见信号各自放入新网格。 if (visible && m_laneMode == LaneMode::MERGED) { m_laneMode = LaneMode::CUSTOM; } SyncLanes(); } void TabConfig::ToggleVisible(const SignalRef& ref) { SetVisible(ref, !IsVisible(ref)); } void TabConfig::SetFileVisible(int fileIndex, bool visible) { if (fileIndex < 0 || static_cast(fileIndex) >= m_visible.size()) { return; } std::vector& fileVisible = m_visible[static_cast(fileIndex)]; // 合并模式下“新增”的信号同样应各自独占网格(与 SetVisible 一致): // 先切到自定义划分,RebuildLanes 会把尚未分配网格的可见信号追加到最下方。 // 只有确实存在“原本不可见”的信号时才切模式,避免重复点击默默改掉划分策略。 const bool anyHidden = std::find(fileVisible.begin(), fileVisible.end(), false) != fileVisible.end(); if (visible && anyHidden && m_laneMode == LaneMode::MERGED) { m_laneMode = LaneMode::CUSTOM; } std::fill(fileVisible.begin(), fileVisible.end(), visible); SyncLanes(); } void TabConfig::SetAllVisible(bool visible) { bool anyHidden = false; for (const std::vector& fileVisible : m_visible) { if (std::find(fileVisible.begin(), fileVisible.end(), false) != fileVisible.end()) { anyHidden = true; break; } } // 同上:合并模式下新增的信号各自独占网格,且排列在最下方。 if (visible && anyHidden && m_laneMode == LaneMode::MERGED) { m_laneMode = LaneMode::CUSTOM; } for (std::vector& fileVisible : m_visible) { std::fill(fileVisible.begin(), fileVisible.end(), visible); } SyncLanes(); } void TabConfig::SoloSignal(const SignalRef& ref) { for (std::vector& fileVisible : m_visible) { std::fill(fileVisible.begin(), fileVisible.end(), false); } SetVisible(ref, true); } bool TabConfig::FileHasVisible(int fileIndex) const { if (fileIndex < 0 || static_cast(fileIndex) >= m_visible.size()) { return false; } const std::vector& fileVisible = m_visible[static_cast(fileIndex)]; return std::find(fileVisible.begin(), fileVisible.end(), true) != fileVisible.end(); } bool TabConfig::FileAllVisible(int fileIndex) const { if (fileIndex < 0 || static_cast(fileIndex) >= m_visible.size()) { return false; } const std::vector& fileVisible = m_visible[static_cast(fileIndex)]; if (fileVisible.empty()) { return false; } return std::find(fileVisible.begin(), fileVisible.end(), false) == fileVisible.end(); } bool TabConfig::AnyVisible() const { for (const std::vector& fileVisible : m_visible) { if (std::find(fileVisible.begin(), fileVisible.end(), true) != fileVisible.end()) { return true; } } return false; } int TabConfig::VisibleCount() const { int count = 0; for (const std::vector& fileVisible : m_visible) { count += static_cast(std::count(fileVisible.begin(), fileVisible.end(), true)); } return count; } void TabConfig::SetMode(LaneMode mode) { m_laneMode = mode; SyncLanes(); } void TabConfig::SyncLanes() { RebuildLanes(m_visible, m_lanes, m_laneMode); } int TabConfig::LaneOfSignal(const SignalRef& ref) const { for (std::size_t lane = 0; lane < m_lanes.size(); ++lane) { const std::vector& refs = m_lanes[lane].signals; if (std::find(refs.begin(), refs.end(), ref) != refs.end()) { return static_cast(lane); } } return -1; } int TabConfig::MoveSignalToLane(const DataSet& dataSet, const SignalRef& ref, int laneIndex) { if (dataSet.Resolve(ref) == nullptr) { return -1; } const int sourceLane = LaneOfSignal(ref); if (laneIndex >= 0 && laneIndex == sourceLane) { // 拖回原网格:无需变动,避免因网格回收导致顺序抖动。 return sourceLane; } // 先把目标网格的“锚信号”固定下来:移除信号后空网格会被回收, // 下标随之变化,必须用不依赖下标的引用找回真正的目标网格 // (否则会变成“与原网格交换位置”而不是合并进去)。 SignalRef targetAnchor; bool hasTarget = (laneIndex >= 0 && laneIndex < static_cast(m_lanes.size())); if (hasTarget) { const std::vector& targetSignals = m_lanes[static_cast(laneIndex)].signals; for (const SignalRef& candidate : targetSignals) { if (!(candidate == ref)) { targetAnchor = candidate; break; } } } // 手动指定归属意味着切换到自定义划分策略。 m_laneMode = LaneMode::CUSTOM; for (Lane& lane : m_lanes) { std::vector& refs = lane.signals; refs.erase(std::remove(refs.begin(), refs.end(), ref), refs.end()); } m_lanes.erase(std::remove_if(m_lanes.begin(), m_lanes.end(), [](const Lane& lane) { return lane.signals.empty(); }), m_lanes.end()); int destination = -1; if (hasTarget && targetAnchor.IsValid()) { for (std::size_t index = 0; index < m_lanes.size(); ++index) { const std::vector& refs = m_lanes[index].signals; if (std::find(refs.begin(), refs.end(), targetAnchor) != refs.end()) { destination = static_cast(index); break; } } } if (destination >= 0) { m_lanes[static_cast(destination)].signals.push_back(ref); } else { Lane lane; lane.autoRange = true; lane.signals.push_back(ref); m_lanes.push_back(std::move(lane)); } for (std::size_t index = 0; index < m_lanes.size(); ++index) { m_lanes[index].name = L"网格 " + std::to_wstring(index + 1); } return LaneOfSignal(ref); } int TabConfig::SplitLane(int laneIndex) { if (laneIndex < 0 || laneIndex >= static_cast(m_lanes.size())) { return -1; } const std::vector signals = m_lanes[static_cast(laneIndex)].signals; if (signals.size() <= 1) { // 只有一条信号时无需拆分(本就独占一个网格)。 return -1; } // 手动排布 → 切换到自定义划分策略。 m_laneMode = LaneMode::CUSTOM; // 用原网格的“网格自身状态”(Y 轴自适应/边沿计数等)作为每一份的初始状态, // 这样拆分出来的网格保持原网格的显示设置。 const Lane source = m_lanes[static_cast(laneIndex)]; std::vector pieces; pieces.reserve(signals.size()); for (const SignalRef& ref : signals) { Lane lane; lane.autoRange = source.autoRange; lane.yMin = source.yMin; lane.yMax = source.yMax; lane.fitYToSelection = source.fitYToSelection; lane.edgeCount = source.edgeCount; lane.edgeValue = source.edgeValue; lane.edgeValueValid = source.edgeValueValid; lane.edgePanelOpen = source.edgePanelOpen; lane.edgePanelX = source.edgePanelX; lane.edgePanelY = source.edgePanelY; lane.edgeCenter = source.edgeCenter; lane.edgeCenterPanelOpen = source.edgeCenterPanelOpen; lane.edgeCenterPanelX = source.edgeCenterPanelX; lane.edgeCenterPanelY = source.edgeCenterPanelY; lane.weakBoost = source.weakBoost; lane.weakBoostLevel = source.weakBoostLevel; lane.weakBoostIterations = source.weakBoostIterations; lane.weakBoostPanelOpen = source.weakBoostPanelOpen; lane.weakBoostPanelX = source.weakBoostPanelX; lane.weakBoostPanelY = source.weakBoostPanelY; lane.meanFilter = source.meanFilter; lane.meanFilterPanelOpen = source.meanFilterPanelOpen; lane.meanFilterPanelX = source.meanFilterPanelX; lane.meanFilterPanelY = source.meanFilterPanelY; // 拆分后每个子网格只保留自己那个信号的均值滤波 / 中心轴 / 弱波增强条目。 lane.meanFilterItems.clear(); lane.edgeCenterItems.clear(); lane.weakBoostItems.clear(); for (const Lane::MeanFilterItem& item : source.meanFilterItems) { if (item.ref == ref) { lane.meanFilterItems.push_back(item); } } for (const Lane::EdgeCenterItem& item : source.edgeCenterItems) { if (item.ref == ref) { lane.edgeCenterItems.push_back(item); } } for (const Lane::WeakBoostItem& item : source.weakBoostItems) { if (item.ref == ref) { lane.weakBoostItems.push_back(item); } } lane.signals.push_back(ref); pieces.push_back(std::move(lane)); } // 用 pieces 替换原网格(插入到原位置,因此其后方的网格整体顺次后移)。 m_lanes.erase(m_lanes.begin() + laneIndex); m_lanes.insert(m_lanes.begin() + laneIndex, pieces.begin(), pieces.end()); // 统一重命名,保证编号连续(GX 编号在各显示位置均由此位置推导)。 for (std::size_t index = 0; index < m_lanes.size(); ++index) { m_lanes[index].name = L"网格 " + std::to_wstring(index + 1); } return laneIndex; } void TabConfig::RemapAfterSignalInsert(int fileIndex, int insertPos) { if (fileIndex < 0 || insertPos < 0) { return; } // 可见性表:在插入点补一列(新信号默认不可见,由调用方按需勾选)。 const std::size_t slot = static_cast(fileIndex); if (slot < m_visible.size() && static_cast(insertPos) <= m_visible[slot].size()) { m_visible[slot].insert(m_visible[slot].begin() + insertPos, false); } // 网格内的信号引用:同一文件中位于插入点之后的引用下标整体后移。 for (Lane& lane : m_lanes) { for (SignalRef& ref : lane.signals) { if (ref.fileIndex == fileIndex && ref.signalIndex >= insertPos) { ++ref.signalIndex; } } // 均值滤波 / 中心轴条目同样持有信号引用,必须一起后移。 for (Lane::MeanFilterItem& item : lane.meanFilterItems) { if (item.ref.fileIndex == fileIndex && item.ref.signalIndex >= insertPos) { ++item.ref.signalIndex; } } for (Lane::EdgeCenterItem& item : lane.edgeCenterItems) { if (item.ref.fileIndex == fileIndex && item.ref.signalIndex >= insertPos) { ++item.ref.signalIndex; } } for (Lane::WeakBoostItem& item : lane.weakBoostItems) { if (item.ref.fileIndex == fileIndex && item.ref.signalIndex >= insertPos) { ++item.ref.signalIndex; } } } } bool TabConfig::MoveLaneOfSignalBelow(const SignalRef& moved, const SignalRef& anchor) { const int from = LaneOfSignal(moved); if (from < 0 || LaneOfSignal(anchor) < 0) { return false; } Lane lane = std::move(m_lanes[static_cast(from)]); m_lanes.erase(m_lanes.begin() + from); // erase 之后锚点网格的下标可能变化,必须用信号引用重新定位。 const int target = LaneOfSignal(anchor); if (target < 0) { m_lanes.push_back(std::move(lane)); } else { m_lanes.insert(m_lanes.begin() + target + 1, std::move(lane)); } // 手动排布 → 切换到自定义划分策略,避免后续重建网格时顺序被还原。 m_laneMode = LaneMode::CUSTOM; RenameLanes(); return true; } bool TabConfig::MoveLane(int from, int target) { const int count = static_cast(m_lanes.size()); if (from < 0 || from >= count || target < 0 || target > count) { return false; } // `target` 语义 = 「插入到该下标之前」;向后拖时扣除自身占位后再比较, // 保证"拖到自己原来的位置"不会产生无意义的移动。 int destination = target; if (destination > from) { --destination; } destination = std::max(0, std::min(destination, count - 1)); if (destination == from) { return false; } Lane moved = std::move(m_lanes[static_cast(from)]); m_lanes.erase(m_lanes.begin() + from); m_lanes.insert(m_lanes.begin() + destination, std::move(moved)); // 手动排布 → 切换到自定义划分策略,避免后续重建网格时顺序被还原。 m_laneMode = LaneMode::CUSTOM; RenameLanes(); return true; } void TabConfig::RenameLanes() { for (std::size_t index = 0; index < m_lanes.size(); ++index) { m_lanes[index].name = L"网格 " + std::to_wstring(index + 1); } } bool TabConfig::IsCollapsed(int fileIndex) const { if (fileIndex < 0 || static_cast(fileIndex) >= m_collapsed.size()) { return false; } return m_collapsed[static_cast(fileIndex)]; } void TabConfig::ToggleCollapsed(int fileIndex) { if (fileIndex < 0) { return; } if (static_cast(fileIndex) >= m_collapsed.size()) { m_collapsed.resize(static_cast(fileIndex) + 1, false); } m_collapsed[static_cast(fileIndex)] = !m_collapsed[static_cast(fileIndex)]; } void TabConfig::ComputeLaneRange(const DataSet& dataSet, int laneIndex, double& yMin, double& yMax) const { if (laneIndex < 0 || laneIndex >= static_cast(m_lanes.size())) { yMin = 0.0; yMax = 1.0; return; } const Lane& lane = m_lanes[static_cast(laneIndex)]; if (!lane.autoRange) { yMin = lane.yMin; yMax = lane.yMax; if (!(yMax > yMin)) { yMin = 0.0; yMax = 1.0; } return; } double low = std::numeric_limits::infinity(); double high = -std::numeric_limits::infinity(); for (const SignalRef& ref : lane.signals) { if (!IsVisible(ref)) { continue; } const SignalData* signal = dataSet.Resolve(ref); if (signal == nullptr || signal->finiteCount == 0) { continue; } low = std::min(low, signal->minValue); high = std::max(high, signal->maxValue); } if (!std::isfinite(low) || !std::isfinite(high)) { low = 0.0; high = 1.0; } PadRange(low, high); yMin = low; yMax = high; } bool TabConfig::ComputeVisibleTimeBounds(const DataSet& dataSet, double& minTime, double& maxTime) const { double low = std::numeric_limits::infinity(); double high = -std::numeric_limits::infinity(); for (std::size_t fileIndex = 0; fileIndex < m_visible.size(); ++fileIndex) { const std::vector& fileVisible = m_visible[fileIndex]; if (std::find(fileVisible.begin(), fileVisible.end(), true) == fileVisible.end()) { continue; } const DataFile* file = dataSet.FileAt(static_cast(fileIndex)); if (file == nullptr) { continue; } if (std::isfinite(file->minTime)) { low = std::min(low, file->minTime); } if (std::isfinite(file->maxTime)) { high = std::max(high, file->maxTime); } } if (!std::isfinite(low) || !std::isfinite(high) || !(high > low)) { return false; } minTime = low; maxTime = high; return true; } } // namespace jdi