Qt历史数据使用线性回归算法预测未来数据趋势

#include <QWidget>
#include <QtCharts>

QT_CHARTS_USE_NAMESPACE

namespace Ui {
class WindowTrend_INS;
}

class WindowTrend_INS : public QWidget
{
    Q_OBJECT

public:
    explicit WindowTrend_INS(QWidget *parent = nullptr);
    ~WindowTrend_INS();

private slots:
    void on_pushButton_eva_trend_clicked();

private:
    Ui::WindowTrend_INS *ui;

    QSplineSeries *historicSeries,*predictSeries;
    QLineSeries *trendSeries;
    QChart *chart;
    QDateTimeAxis * axisX;
    QValueAxis * axisY;
    QDateTime datetimeNow,datetimeFuture30Days;

    QList<QPointF> listHistoric,listPredict;

    void initData();


    // 计算线性回归的趋势线
    QLineSeries* calculateTrendLine(const QList<QPointF>& dataPoints,double &slope,double &intercept) {
        QLineSeries *trendLineSeries = new QLineSeries();
        trendLineSeries->setName("趋势");

        if (dataPoints.isEmpty()) {
            return trendLineSeries;
        }

        // 计算线性回归的斜率和截距
        double sumX = 0, sumY = 0, sumXY = 0, sumX2 = 0;
        int n = dataPoints.size();

        for (const QPointF& point : dataPoints) {
            sumX += point.x();
            sumY += point.y();
            sumXY += point.x() * point.y();
            sumX2 += point.x() * point.x();
        }

        slope = (n * sumXY - sumX * sumY) / (n * sumX2 - sumX * sumX); // 斜率
        intercept = (sumY - slope * sumX) / n; // 截距

        // 生成趋势线的起点和终点
        double x1 = dataPoints.first().x();
        double y1 = slope * x1 + intercept;
        double x2 = dataPoints.last().x();
        double y2 = slope * x2 + intercept;

        *trendLineSeries << QPointF(x1, y1) << QPointF(x2, y2);
        return trendLineSeries;
    }

};

#include "WindowTrend_INS.h"
#include "ui_WindowTrend_INS.h"

WindowTrend_INS::WindowTrend_INS(QWidget *parent) :
    QWidget(parent),
    ui(new Ui::WindowTrend_INS)
{
    ui->setupUi(this);
    initData();
}

WindowTrend_INS::~WindowTrend_INS()
{
    delete ui;
}

void WindowTrend_INS::initData()
{
    datetimeNow = QDateTime::currentDateTime();
    datetimeFuture30Days = datetimeNow.addDays(30);

    ui->timefrom->setDateTime(datetimeNow);
    ui->timeto->setDateTime(datetimeFuture30Days);

    chart = new QChart();
    ui->chart_trend->setRenderHint(QPainter::Antialiasing);

    // 创建历史数据曲线
    historicSeries = new QSplineSeries();
    historicSeries->setName("历史数据");

    // historicSeries->setPointLabelsVisible(true); // 显示标签
    // historicSeries->setPointLabelsFormat("(@xPoint, @yPoint)"); // 设置标签格式
    // historicSeries->setPointLabelsColor(Qt::blue); // 设置标签颜色
    // historicSeries->setPointLabelsFont(QFont("Arial", 10)); // 设置标签字体

    // 创建图表
    chart->addSeries(historicSeries);
    chart->setTitle("惯性元件性能预测");
    chart->setTitleFont(QFont("黑体",14));

    // 设置X轴和Y轴的范围
    axisX = new QDateTimeAxis(this);
    axisX -> setTitleText("预测时间"); 	//设置轴的标题
    axisX -> setRange(datetimeNow,datetimeFuture30Days); //设置时间轴的范围,参数是两个时期时间QDateTime

    axisX -> setFormat("MM-dd HH:mm"); //设置刻度值的格式，和格式化时间字符串一样
    axisX -> setLabelsAngle(15);
    chart -> addAxis(axisX, Qt::AlignBottom); //添加轴

    axisY = new QValueAxis(this);
    axisY->setMin(-1);
    axisY->setMax(1);
    axisY->setRange(-0.1, 0.1);
    axisY->setTickAnchor(0.1);
    axisY->setTickInterval(0.01);
    axisY->setTickType(QValueAxis::TicksDynamic);
    axisY->setTitleText("误差值");
    chart->addAxis(axisY, Qt::AlignLeft);

    historicSeries->attachAxis(axisX);
    historicSeries->attachAxis(axisY);

    ui->chart_trend->setChart(chart);

    //生成默认数据，将从数据库提取
    listHistoric.clear();
    for(int i=1;i<30;i++){
        // 生成 [0, 1) 范围内的随机数
        double randomValue = QRandomGenerator::global()->generateDouble()*0.05-0.01;
        listHistoric.append(QPointF(QDateTime::currentDateTime().addDays(i).toMSecsSinceEpoch(), randomValue));
    }

    historicSeries->clear();
    historicSeries->append(listHistoric);

}

void WindowTrend_INS::on_pushButton_eva_trend_clicked()
{
    // 计算趋势线
    if(!chart->series().contains(trendSeries)){
        double slope,intercept;
        trendSeries = calculateTrendLine(listHistoric,slope,intercept);
        trendSeries->setPen(QPen(QBrush(Qt::red),2,Qt::DotLine));
        trendSeries->setName("趋势");
        trendSeries->setPointLabelsVisible(true);
        chart->addSeries(trendSeries);
        trendSeries->attachAxis(axisX);
        trendSeries->attachAxis(axisY);
    }

    //计算预测数据
    if(!chart->series().contains(predictSeries)){
        predictSeries = new QSplineSeries();
        predictSeries->setPen(QPen(QBrush(Qt::green),2,Qt::DashDotDotLine));
        predictSeries->setName("预测数据");
        predictSeries->setPointLabelsVisible(true);
        chart->addSeries(predictSeries);
        predictSeries->attachAxis(axisX);
        predictSeries->attachAxis(axisY);

        //强调一下连接点joint
        listPredict.append(listHistoric.last());
        listPredict.append(listHistoric.last());
        listPredict.append(listHistoric.last());
        listPredict.append(listHistoric.last());
        listPredict.append(listHistoric.last());

        for(int i=1;i<30;i++){
            // 生成 [0, 1) 范围内的随机数
            double randomValue = QRandomGenerator::global()->generateDouble()*0.05-0.01;
            // listPredict.append(QPointF(QDateTime::currentDateTime().addDays(i).toMSecsSinceEpoch(), randomValue));

            QPointF p = QPointF(QDateTime::fromMSecsSinceEpoch(listHistoric.last().x()).addDays(i).toMSecsSinceEpoch(),
                    randomValue);

            qDebug()<<""<< p;
            listPredict.append(p);

        }

        predictSeries->clear();
        predictSeries->append(listPredict);

        //延长x轴
        datetimeFuture30Days = datetimeFuture30Days.addDays(30);
        axisX -> setRange(datetimeNow,datetimeFuture30Days); //设置时间轴的范围,参数是两个时期时间QDateTime

    }

}

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