DeepSeek V4.1 Flash
aca84df0ac
根因：派生预览曲线按可见采样窗口计算，代价正比于窗口采样数（弱波增强整段 2576 万采样单条约 368ms）；旧策略对超过 4M 采样的窗口不缓存，导致大跨度下每帧（含悬停重绘）重算整段曲线；拖滑块每帧改参数即每帧重算。实测弱波增强整段拖滑块单帧约 2303ms，2.5s 跨度约 89ms。 修复：1) 大窗口也进缓存并按总字节预算淘汰（静止重绘 2247ms-0.25ms）；2) 交互期间对超出预算的大窗口延迟重算、复用旧曲线（拖滑块 2303ms-18ms），小窗口仍实时重算；3) 计算缓冲改 thread_local 复用容量。仅改何时计算与是否缓存，几何与取值算法不变，逐像素比对 0 差异。 缩放等级差异：整段放大时窗口为整条信号（千万级）每帧重算故最卡；极小跨度窗口仅几千采样故不卡；中间跨度几十毫秒亦卡。
2199 lines
64 KiB
C++
2199 lines
64 KiB
C++
#include "DataModel.hpp"
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#include <algorithm>
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#include <cmath>
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#include <cstdio>
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#include <cstdlib>
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#include <cwctype>
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#include <deque>
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#include <limits>
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#include "Theme.hpp"
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#include "Utf8Util.hpp"
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namespace jdi
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{
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namespace
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{
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const double kMissing = std::numeric_limits<double>::quiet_NaN(); /**< 缺失值占位。 */
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const double kDefaultLineWidth = 1.6; /**< 默认线宽。 */
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/**
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* @brief 判断列名是否为时间轴候选列。
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* @param [IN] header 原始列名。
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* @return 可能为时间轴返回 true。
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*/
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bool LooksLikeTimeHeader(const std::wstring& header)
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{
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const std::wstring text = ToLowerAscii(Trim(header));
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if (text.empty())
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{
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return false;
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}
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if (text == L"t" || text == L"time" || text == L"timestamp" || text == L"simulation time" ||
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text == L"时间" || text == L"时间轴")
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{
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return true;
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}
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return ContainsInsensitive(text, L"time") || ContainsInsensitive(text, L"时间");
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}
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/**
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* @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）。
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* @param [IN] text 列名（已去除首尾空白）。
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* @return 单位文本，无法识别时返回空字符串。
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*/
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std::wstring ExtractUnit(const std::wstring& text)
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{
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if (text.size() < 3 || text.back() != L')')
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{
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return std::wstring();
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}
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const std::size_t open = text.rfind(L'(');
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if (open == std::wstring::npos || open + 2 >= text.size())
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{
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return std::wstring();
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}
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const std::wstring inner = Trim(text.substr(open + 1, text.size() - open - 2));
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if (inner.empty() || inner.size() > 10)
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{
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return std::wstring();
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}
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for (const wchar_t c : inner)
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{
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const bool allowed = iswalpha(c) || iswdigit(c) || c == L'%' || c == L'/' || c == L'^' ||
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c == L'-' || c == L'.' || c == L'\u00B0' || c == L'\u00B5' ||
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c == L'\u03A9' || c == L'\u00B2' || c == L'\u00B3' || c == L'\u00B7';
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if (!allowed)
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{
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return std::wstring();
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}
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}
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return inner;
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}
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/**
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* @brief 为网格范围补充留白，避免波形紧贴边界。
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* @param [IN, OUT] yMin 范围下限。
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* @param [IN, OUT] yMax 范围上限。
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*/
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void PadRange(double& yMin, double& yMax)
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{
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if (!std::isfinite(yMin) || !std::isfinite(yMax))
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{
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yMin = 0.0;
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yMax = 1.0;
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return;
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}
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const double span = yMax - yMin;
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if (span <= 0.0)
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{
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const double magnitude = std::max(1.0, std::fabs(yMin) * 0.1);
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yMin -= magnitude;
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yMax += magnitude;
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return;
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}
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const double pad = span * 0.06;
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yMin -= pad;
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yMax += pad;
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}
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/**
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* @brief 依据全部可见信号重新生成网格划分。
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* @param [IN] visible 各信号的可见性（按 [文件][信号] 索引）。
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* @param [IN] lanes 网格集合（原地更新）。
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* @param [IN] mode 网格划分策略。
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*/
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void RebuildLanes(const std::vector<std::vector<bool>>& visible, std::vector<Lane>& lanes,
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LaneMode mode)
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{
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// 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。
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struct LaneCarry
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{
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bool fitYToSelection = false;
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bool edgeCount = false;
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double edgeValue = 0.0;
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bool edgeValueValid = false;
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bool edgePanelOpen = true;
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double edgePanelX = -1.0;
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double edgePanelY = -1.0;
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bool edgeCenter = false;
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std::vector<Lane::EdgeCenterItem> edgeCenterItems;
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bool edgeCenterPanelOpen = true;
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double edgeCenterPanelX = -1.0;
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double edgeCenterPanelY = -1.0;
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bool meanFilter = false;
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std::vector<Lane::MeanFilterItem> meanFilterItems;
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bool meanFilterPanelOpen = true;
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double meanFilterPanelX = -1.0;
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double meanFilterPanelY = -1.0;
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bool weakBoost = false;
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std::vector<Lane::WeakBoostItem> weakBoostItems;
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double weakBoostLevel = 0.5;
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int weakBoostIterations = 1;
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bool weakBoostPanelOpen = true;
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double weakBoostPanelX = -1.0;
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double weakBoostPanelY = -1.0;
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};
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// 先记下每个信号原来所在网格的网格自身状态：
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// 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。
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std::vector<std::pair<SignalRef, LaneCarry>> previousCarry;
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for (const Lane& lane : lanes)
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{
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LaneCarry carry;
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carry.fitYToSelection = lane.fitYToSelection;
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carry.edgeCount = lane.edgeCount;
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carry.edgeValue = lane.edgeValue;
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carry.edgeValueValid = lane.edgeValueValid;
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carry.edgePanelOpen = lane.edgePanelOpen;
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carry.edgePanelX = lane.edgePanelX;
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carry.edgePanelY = lane.edgePanelY;
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carry.edgeCenter = lane.edgeCenter;
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carry.edgeCenterItems = lane.edgeCenterItems;
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carry.edgeCenterPanelOpen = lane.edgeCenterPanelOpen;
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carry.edgeCenterPanelX = lane.edgeCenterPanelX;
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carry.edgeCenterPanelY = lane.edgeCenterPanelY;
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carry.meanFilter = lane.meanFilter;
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carry.meanFilterItems = lane.meanFilterItems;
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carry.meanFilterPanelOpen = lane.meanFilterPanelOpen;
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carry.meanFilterPanelX = lane.meanFilterPanelX;
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carry.meanFilterPanelY = lane.meanFilterPanelY;
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carry.weakBoost = lane.weakBoost;
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carry.weakBoostItems = lane.weakBoostItems;
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carry.weakBoostLevel = lane.weakBoostLevel;
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carry.weakBoostIterations = lane.weakBoostIterations;
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carry.weakBoostPanelOpen = lane.weakBoostPanelOpen;
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carry.weakBoostPanelX = lane.weakBoostPanelX;
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carry.weakBoostPanelY = lane.weakBoostPanelY;
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for (const SignalRef& ref : lane.signals)
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{
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previousCarry.emplace_back(ref, carry);
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}
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}
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const auto inheritedCarry = [&previousCarry](const SignalRef& ref)
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{
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for (const std::pair<SignalRef, LaneCarry>& entry : previousCarry)
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{
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if (entry.first == ref)
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{
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return entry.second;
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}
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}
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return LaneCarry();
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};
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const auto applyCarry = [&inheritedCarry](Lane& lane, const SignalRef& ref)
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{
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const LaneCarry carry = inheritedCarry(ref);
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lane.fitYToSelection = carry.fitYToSelection;
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lane.edgeCount = carry.edgeCount;
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lane.edgeValue = carry.edgeValue;
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lane.edgeValueValid = carry.edgeValueValid;
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lane.edgePanelOpen = carry.edgePanelOpen;
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lane.edgePanelX = carry.edgePanelX;
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lane.edgePanelY = carry.edgePanelY;
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lane.edgeCenter = carry.edgeCenter;
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lane.edgeCenterItems = carry.edgeCenterItems;
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lane.edgeCenterPanelOpen = carry.edgeCenterPanelOpen;
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lane.edgeCenterPanelX = carry.edgeCenterPanelX;
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lane.edgeCenterPanelY = carry.edgeCenterPanelY;
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lane.meanFilter = carry.meanFilter;
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lane.meanFilterItems = carry.meanFilterItems;
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lane.meanFilterPanelOpen = carry.meanFilterPanelOpen;
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lane.meanFilterPanelX = carry.meanFilterPanelX;
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lane.meanFilterPanelY = carry.meanFilterPanelY;
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lane.weakBoost = carry.weakBoost;
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lane.weakBoostItems = carry.weakBoostItems;
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lane.weakBoostLevel = carry.weakBoostLevel;
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lane.weakBoostIterations = carry.weakBoostIterations;
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lane.weakBoostPanelOpen = carry.weakBoostPanelOpen;
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lane.weakBoostPanelX = carry.weakBoostPanelX;
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lane.weakBoostPanelY = carry.weakBoostPanelY;
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};
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// 收集全部可见信号引用。
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std::vector<SignalRef> visibleRefs;
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for (std::size_t fileIndex = 0; fileIndex < visible.size(); ++fileIndex)
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{
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for (std::size_t signalIndex = 0; signalIndex < visible[fileIndex].size(); ++signalIndex)
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{
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if (visible[fileIndex][signalIndex])
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{
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SignalRef ref;
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ref.fileIndex = static_cast<int>(fileIndex);
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ref.signalIndex = static_cast<int>(signalIndex);
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visibleRefs.push_back(ref);
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}
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}
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}
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// 判断某引用对应的信号是否可见（越界视为不可见）。
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const auto isVisibleRef = [&visible](const SignalRef& ref)
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{
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if (ref.fileIndex < 0 || static_cast<std::size_t>(ref.fileIndex) >= visible.size())
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{
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return false;
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}
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const std::vector<bool>& fileVisible = visible[static_cast<std::size_t>(ref.fileIndex)];
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if (ref.signalIndex < 0 || static_cast<std::size_t>(ref.signalIndex) >= fileVisible.size())
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{
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return false;
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}
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return fileVisible[static_cast<std::size_t>(ref.signalIndex)];
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};
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// 某信号当前所属的网格下标（-1 表示尚未分配网格）。
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const auto laneIndexOf = [&lanes](const SignalRef& ref)
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{
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for (std::size_t index = 0; index < lanes.size(); ++index)
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{
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const std::vector<SignalRef>& refs = lanes[index].signals;
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if (std::find(refs.begin(), refs.end(), ref) != refs.end())
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{
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return static_cast<int>(index);
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}
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}
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return -1;
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};
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if (mode == LaneMode::PER_SIGNAL)
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{
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// 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。
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// **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，
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// 新勾选（此前没有网格）的信号统一追加到最下方。
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// 若直接按 visibleRefs（文件/列序）重建，新勾选的信号会按其列序
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// 插到中间，位置看起来"不确定"。
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std::vector<SignalRef> ordered;
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ordered.reserve(visibleRefs.size());
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for (const SignalRef& ref : visibleRefs)
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{
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if (laneIndexOf(ref) >= 0)
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{
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ordered.push_back(ref);
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}
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}
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std::stable_sort(ordered.begin(), ordered.end(),
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[&laneIndexOf](const SignalRef& a, const SignalRef& b)
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{ return laneIndexOf(a) < laneIndexOf(b); });
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for (const SignalRef& ref : visibleRefs)
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{
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if (laneIndexOf(ref) < 0)
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{
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ordered.push_back(ref);
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}
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}
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lanes.clear();
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lanes.reserve(ordered.size());
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for (const SignalRef& ref : ordered)
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{
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Lane lane;
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lane.autoRange = true;
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applyCarry(lane, ref);
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lane.signals.push_back(ref);
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lanes.push_back(std::move(lane));
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}
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}
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else if (mode == LaneMode::MERGED)
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{
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// 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。
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bool previousAutoRange = true;
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double previousYMin = -1.0;
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double previousYMax = 1.0;
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if (lanes.size() == 1)
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{
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previousAutoRange = lanes[0].autoRange;
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previousYMin = lanes[0].yMin;
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previousYMax = lanes[0].yMax;
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}
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lanes.clear();
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if (!visibleRefs.empty())
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{
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Lane lane;
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lane.autoRange = previousAutoRange;
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lane.yMin = previousYMin;
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lane.yMax = previousYMax;
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applyCarry(lane, visibleRefs.front());
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lane.signals = visibleRefs;
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lanes.push_back(std::move(lane));
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}
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}
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else
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{
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// 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。
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for (Lane& lane : lanes)
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{
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std::vector<SignalRef>& refs = lane.signals;
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refs.erase(std::remove_if(refs.begin(), refs.end(),
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[&isVisibleRef](const SignalRef& ref)
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{ return !isVisibleRef(ref); }),
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refs.end());
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}
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lanes.erase(std::remove_if(lanes.begin(), lanes.end(),
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[](const Lane& lane) { return lane.signals.empty(); }),
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lanes.end());
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// 未分配网格的可见信号各自独占一个新网格。
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// 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
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// 被悄悄并入合并网格”，用户看不到新增的独立泳道。
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for (const SignalRef& ref : visibleRefs)
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{
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bool placed = false;
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for (const Lane& lane : lanes)
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{
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if (std::find(lane.signals.begin(), lane.signals.end(), ref) != lane.signals.end())
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{
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placed = true;
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break;
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}
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}
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if (placed)
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{
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continue;
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}
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Lane lane;
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lane.autoRange = true;
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applyCarry(lane, ref);
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lane.signals.push_back(ref);
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lanes.push_back(std::move(lane));
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}
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}
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// 统一重命名，保证编号连续。
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for (std::size_t index = 0; index < lanes.size(); ++index)
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{
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lanes[index].name = L"网格 " + std::to_wstring(index + 1);
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}
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}
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}
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const wchar_t* DrawModeName(DrawMode mode)
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{
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switch (mode)
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{
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case DrawMode::LINE:
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return L"线段";
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case DrawMode::SCATTER:
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return L"散点";
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case DrawMode::LINE_SCATTER:
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return L"点线";
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default:
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return L"线段";
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}
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}
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// ============================ DataFile 构建 ============================
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/**
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* @brief 粗粒度包络层每个分组覆盖的采样数。
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*
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* 16KB 的双精度分组可覆盖 1024 个采样（内存开销 = 采样数的 1.6%），
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* 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。
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* 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
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* 每列 ≤256 个采样（2400 列 ≈ 0.6M 次读取，约 1ms）。
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*/
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const std::size_t kCoarseStride = 256;
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/**
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* @brief 单条信号的取值范围统计结果。
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*/
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struct SignalStats
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{
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double minValue = 0.0; /**< 有限采样值最小值。 */
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double maxValue = 0.0; /**< 有限采样值最大值。 */
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std::size_t finiteCount = 0; /**< 有限采样点数量。 */
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};
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/**
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* @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。
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*
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* 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）。
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*
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* @param [IN] values 采样列。
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* @param [OUT] coarseMin 粗粒度分组最小值输出。
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* @param [OUT] coarseMax 粗粒度分组最大值输出。
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* @return 统计结果。
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*/
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SignalStats ComputeStats(const std::vector<double>& values, std::vector<double>& coarseMin,
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std::vector<double>& coarseMax)
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{
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SignalStats stats;
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double low = std::numeric_limits<double>::infinity();
|
|
double high = -std::numeric_limits<double>::infinity();
|
|
|
|
const std::size_t count = values.size();
|
|
const std::size_t buckets = (count + kCoarseStride - 1) / kCoarseStride;
|
|
coarseMin.assign(buckets, std::numeric_limits<double>::infinity());
|
|
coarseMax.assign(buckets, -std::numeric_limits<double>::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<int>(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<std::size_t>(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<std::size_t>(timeColumn)] + L"）有效数值不足。";
|
|
return false;
|
|
}
|
|
|
|
file.timeColumnName = table.headers[static_cast<std::size_t>(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<int>(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<std::size_t>(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<double>(column + 1) / static_cast<double>(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<double>::infinity();
|
|
double tMax = -std::numeric_limits<double>::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<int>(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<int>(m_files.size()))
|
|
{
|
|
return false;
|
|
}
|
|
|
|
DataFile& file = m_files[static_cast<std::size_t>(fileIndex)];
|
|
if (afterSignalIndex < -1 || afterSignalIndex >= static_cast<int>(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<std::size_t>(insertPos);
|
|
for (int index = 0; index < fileIndex; ++index)
|
|
{
|
|
globalIndex += m_files[static_cast<std::size_t>(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<std::size_t>(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<int>(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<std::size_t>(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<int>(m_files.size()))
|
|
{
|
|
return false;
|
|
}
|
|
DataFile& file = m_files[static_cast<std::size_t>(fileIndex)];
|
|
if (signalIndex < 0 || signalIndex >= static_cast<int>(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<SignalData>& signals = file.signals;
|
|
const std::size_t position = static_cast<std::size_t>(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<int>(m_files.size()))
|
|
{
|
|
return nullptr;
|
|
}
|
|
return &m_files[static_cast<std::size_t>(fileIndex)];
|
|
}
|
|
|
|
bool DataSet::SetSignalDisplayName(int fileIndex, int signalIndex, const std::wstring& name)
|
|
{
|
|
if (fileIndex < 0 || fileIndex >= static_cast<int>(m_files.size()))
|
|
{
|
|
return false;
|
|
}
|
|
|
|
DataFile& file = m_files[static_cast<std::size_t>(fileIndex)];
|
|
if (signalIndex < 0 || signalIndex >= static_cast<int>(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<std::size_t>(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<int>(m_files.size()))
|
|
{
|
|
return false;
|
|
}
|
|
|
|
std::wstring trimmed = Trim(name);
|
|
DataFile& file = m_files[static_cast<std::size_t>(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<int>(file->signals.size()))
|
|
{
|
|
return nullptr;
|
|
}
|
|
return &file->signals[static_cast<std::size_t>(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<int>(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<std::size_t>(ref.fileIndex)];
|
|
return &mutableFile.signals[static_cast<std::size_t>(ref.signalIndex)].style;
|
|
}
|
|
|
|
double DataSet::MinTime() const
|
|
{
|
|
double value = std::numeric_limits<double>::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<double>::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 <typename T>
|
|
void MovingAverageImpl(const std::vector<T>& values, int radius, std::vector<float>& out);
|
|
} // namespace
|
|
|
|
void ComputeMovingAverage(const std::vector<double>& values, int radius, std::vector<float>& out)
|
|
{
|
|
MovingAverageImpl(values, radius, out);
|
|
}
|
|
|
|
namespace
|
|
{
|
|
template <typename T>
|
|
void MovingAverageImpl(const std::vector<T>& values, int radius, std::vector<float>& out)
|
|
{
|
|
const int window = std::max(0, radius);
|
|
const std::size_t count = values.size();
|
|
out.assign(count, std::numeric_limits<float>::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<double>(values[index]);
|
|
if (std::isfinite(value))
|
|
{
|
|
out[index] = static_cast<float>(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<std::size_t>(window))
|
|
? (index - static_cast<std::size_t>(window))
|
|
: 0;
|
|
const std::size_t high =
|
|
std::min(count - 1, index + static_cast<std::size_t>(window));
|
|
|
|
if (index == 0)
|
|
{
|
|
windowLow = low;
|
|
windowHigh = high;
|
|
for (std::size_t i = windowLow; i <= windowHigh; ++i)
|
|
{
|
|
addValue(static_cast<double>(values[i]));
|
|
}
|
|
}
|
|
else
|
|
{
|
|
while (windowLow < low)
|
|
{
|
|
removeValue(static_cast<double>(values[windowLow]));
|
|
++windowLow;
|
|
}
|
|
while (windowHigh < high)
|
|
{
|
|
++windowHigh;
|
|
addValue(static_cast<double>(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<double>(values[index]);
|
|
if (finiteCount > 0 && std::isfinite(center))
|
|
{
|
|
out[index] = static_cast<float>(sum / static_cast<double>(finiteCount));
|
|
}
|
|
}
|
|
}
|
|
} // namespace
|
|
|
|
void ComputeMovingAverageIterated(const std::vector<double>& values, int radius, int iterations,
|
|
std::vector<float>& 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）。
|
|
// 中转缓冲复用容量（线程本地），避免每阶重新分配上千万元素的向量。
|
|
thread_local std::vector<double> bufferBuffer;
|
|
std::vector<double>& buffer = bufferBuffer;
|
|
buffer.assign(values.size(), std::numeric_limits<double>::quiet_NaN());
|
|
std::vector<float> 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<double>(out[index])
|
|
: std::numeric_limits<double>::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<float>& input, double strength,
|
|
std::vector<float>& output, std::vector<BoostExtremum>& extremes)
|
|
{
|
|
const std::size_t count = input.size();
|
|
output.assign(count, std::numeric_limits<float>::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。
|
|
extremes.clear();
|
|
{
|
|
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<double>(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();
|
|
thread_local std::vector<double> shiftBuffer;
|
|
std::vector<double>& shift = shiftBuffer;
|
|
shift.assign(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<float>(input[begin] + beginShift);
|
|
}
|
|
return;
|
|
}
|
|
const double span = static_cast<double>(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<double>(index - begin) / span;
|
|
const double weight = t * t * (3.0 - 2.0 * t);
|
|
output[index] = static_cast<float>(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<double>& values, double level, int iterations,
|
|
std::vector<float>& out)
|
|
{
|
|
const std::size_t count = values.size();
|
|
out.assign(count, std::numeric_limits<float>::quiet_NaN());
|
|
if (count == 0)
|
|
{
|
|
return;
|
|
}
|
|
|
|
// 第 1 阶：从原始采样值出发（非有限值保持 NaN）。
|
|
// 工作缓冲用线程本地变量复用容量：单条曲线动辄上千万采样，若每次调用都重新分配
|
|
// 并零初始化，单条「弱波增强」的耗时会被明显放大（内存分配 + page fault）。
|
|
thread_local std::vector<float> currentBuffer;
|
|
thread_local std::vector<float> nextBuffer;
|
|
thread_local std::vector<BoostExtremum> extremesBuffer;
|
|
std::vector<float>& current = currentBuffer;
|
|
current.assign(count, std::numeric_limits<float>::quiet_NaN());
|
|
for (std::size_t index = 0; index < count; ++index)
|
|
{
|
|
const double value = values[index];
|
|
if (std::isfinite(value))
|
|
{
|
|
current[index] = static_cast<float>(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<float>& next = nextBuffer;
|
|
for (int stage = 0; stage < stages; ++stage)
|
|
{
|
|
if (!ApplyWeakBoostStage(current, strength, next, extremesBuffer))
|
|
{
|
|
// 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<double>::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<int>(count - 1);
|
|
}
|
|
const std::size_t rightIndex = static_cast<std::size_t>(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<int>(leftIndex) : static_cast<int>(rightIndex);
|
|
}
|
|
|
|
int best = 0;
|
|
double bestDistance = std::numeric_limits<double>::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<int>(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<double>& values = signal.values;
|
|
|
|
if (!file.timeMonotonic)
|
|
{
|
|
const int nearest = FindNearestSample(file, time);
|
|
if (nearest < 0 || static_cast<std::size_t>(nearest) >= values.size())
|
|
{
|
|
return false;
|
|
}
|
|
value = values[static_cast<std::size_t>(nearest)];
|
|
return std::isfinite(value);
|
|
}
|
|
|
|
const std::vector<double>::const_iterator lower = std::lower_bound(file.time.begin(), file.time.end(), time);
|
|
const std::size_t rightIndex = static_cast<std::size_t>(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<int>(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<SignalRef>& 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<std::size_t>(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<SignalRef>& 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<std::size_t>(fileIndex);
|
|
if (slot < m_visible.size())
|
|
{
|
|
std::vector<bool>& fileVisible = m_visible[slot];
|
|
if (static_cast<std::size_t>(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<SignalRef>& 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<Lane::MeanFilterItem>& 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<std::size_t>(ref.fileIndex) >= m_visible.size())
|
|
{
|
|
return false;
|
|
}
|
|
const std::vector<bool>& fileVisible = m_visible[static_cast<std::size_t>(ref.fileIndex)];
|
|
if (ref.signalIndex < 0 || static_cast<std::size_t>(ref.signalIndex) >= fileVisible.size())
|
|
{
|
|
return false;
|
|
}
|
|
return fileVisible[static_cast<std::size_t>(ref.signalIndex)];
|
|
}
|
|
|
|
void TabConfig::SetVisible(const SignalRef& ref, bool visible)
|
|
{
|
|
if (ref.fileIndex < 0 || static_cast<std::size_t>(ref.fileIndex) >= m_visible.size())
|
|
{
|
|
return;
|
|
}
|
|
std::vector<bool>& fileVisible = m_visible[static_cast<std::size_t>(ref.fileIndex)];
|
|
if (ref.signalIndex < 0 || static_cast<std::size_t>(ref.signalIndex) >= fileVisible.size())
|
|
{
|
|
return;
|
|
}
|
|
if (fileVisible[static_cast<std::size_t>(ref.signalIndex)] == visible)
|
|
{
|
|
return;
|
|
}
|
|
fileVisible[static_cast<std::size_t>(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<std::size_t>(fileIndex) >= m_visible.size())
|
|
{
|
|
return;
|
|
}
|
|
std::vector<bool>& fileVisible = m_visible[static_cast<std::size_t>(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<bool>& 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<bool>& fileVisible : m_visible)
|
|
{
|
|
std::fill(fileVisible.begin(), fileVisible.end(), visible);
|
|
}
|
|
SyncLanes();
|
|
}
|
|
|
|
void TabConfig::SoloSignal(const SignalRef& ref)
|
|
{
|
|
for (std::vector<bool>& fileVisible : m_visible)
|
|
{
|
|
std::fill(fileVisible.begin(), fileVisible.end(), false);
|
|
}
|
|
SetVisible(ref, true);
|
|
}
|
|
|
|
bool TabConfig::FileHasVisible(int fileIndex) const
|
|
{
|
|
if (fileIndex < 0 || static_cast<std::size_t>(fileIndex) >= m_visible.size())
|
|
{
|
|
return false;
|
|
}
|
|
const std::vector<bool>& fileVisible = m_visible[static_cast<std::size_t>(fileIndex)];
|
|
return std::find(fileVisible.begin(), fileVisible.end(), true) != fileVisible.end();
|
|
}
|
|
|
|
bool TabConfig::FileAllVisible(int fileIndex) const
|
|
{
|
|
if (fileIndex < 0 || static_cast<std::size_t>(fileIndex) >= m_visible.size())
|
|
{
|
|
return false;
|
|
}
|
|
const std::vector<bool>& fileVisible = m_visible[static_cast<std::size_t>(fileIndex)];
|
|
if (fileVisible.empty())
|
|
{
|
|
return false;
|
|
}
|
|
return std::find(fileVisible.begin(), fileVisible.end(), false) == fileVisible.end();
|
|
}
|
|
|
|
bool TabConfig::AnyVisible() const
|
|
{
|
|
for (const std::vector<bool>& 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<bool>& fileVisible : m_visible)
|
|
{
|
|
count += static_cast<int>(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<SignalRef>& refs = m_lanes[lane].signals;
|
|
if (std::find(refs.begin(), refs.end(), ref) != refs.end())
|
|
{
|
|
return static_cast<int>(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<int>(m_lanes.size()));
|
|
if (hasTarget)
|
|
{
|
|
const std::vector<SignalRef>& targetSignals = m_lanes[static_cast<std::size_t>(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<SignalRef>& 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<SignalRef>& refs = m_lanes[index].signals;
|
|
if (std::find(refs.begin(), refs.end(), targetAnchor) != refs.end())
|
|
{
|
|
destination = static_cast<int>(index);
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
if (destination >= 0)
|
|
{
|
|
m_lanes[static_cast<std::size_t>(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<int>(m_lanes.size()))
|
|
{
|
|
return -1;
|
|
}
|
|
const std::vector<SignalRef> signals = m_lanes[static_cast<std::size_t>(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<std::size_t>(laneIndex)];
|
|
|
|
std::vector<Lane> 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<std::size_t>(fileIndex);
|
|
if (slot < m_visible.size() && static_cast<std::size_t>(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<std::size_t>(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<int>(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<std::size_t>(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<std::size_t>(fileIndex) >= m_collapsed.size())
|
|
{
|
|
return false;
|
|
}
|
|
return m_collapsed[static_cast<std::size_t>(fileIndex)];
|
|
}
|
|
|
|
void TabConfig::ToggleCollapsed(int fileIndex)
|
|
{
|
|
if (fileIndex < 0)
|
|
{
|
|
return;
|
|
}
|
|
if (static_cast<std::size_t>(fileIndex) >= m_collapsed.size())
|
|
{
|
|
m_collapsed.resize(static_cast<std::size_t>(fileIndex) + 1, false);
|
|
}
|
|
m_collapsed[static_cast<std::size_t>(fileIndex)] = !m_collapsed[static_cast<std::size_t>(fileIndex)];
|
|
}
|
|
|
|
void TabConfig::ComputeLaneRange(const DataSet& dataSet, int laneIndex, double& yMin, double& yMax) const
|
|
{
|
|
if (laneIndex < 0 || laneIndex >= static_cast<int>(m_lanes.size()))
|
|
{
|
|
yMin = 0.0;
|
|
yMax = 1.0;
|
|
return;
|
|
}
|
|
|
|
const Lane& lane = m_lanes[static_cast<std::size_t>(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<double>::infinity();
|
|
double high = -std::numeric_limits<double>::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<double>::infinity();
|
|
double high = -std::numeric_limits<double>::infinity();
|
|
|
|
for (std::size_t fileIndex = 0; fileIndex < m_visible.size(); ++fileIndex)
|
|
{
|
|
const std::vector<bool>& fileVisible = m_visible[fileIndex];
|
|
if (std::find(fileVisible.begin(), fileVisible.end(), true) == fileVisible.end())
|
|
{
|
|
continue;
|
|
}
|
|
|
|
const DataFile* file = dataSet.FileAt(static_cast<int>(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
|