/// <summary>
/// 根据已有数据预测后面时间的数据
/// </summary>
/// <param name="models">已有数据</param>
/// <param name="time">要预测的时间长度</param>
/// <param name="interval">时间间隔</param>
/// <returns>返回预测数据加上已有数据</returns>
public List <DaoGuZhiLiangTeXingModel> getPredictDataAfterTime(List <DaoGuZhiLiangTeXingModel> models, int time, int interval)
{
string xLabel = models[0].xLabel;
string yLabel = models[0].canShuName;
double[] douX = new double[models.Count];
List <double> predictX = new List <double>();
double[] douY = new double[models.Count];
for (int i = 0; i < models.Count; i++)
{
douX[i] = Convert.ToDouble(models[i].xData);
douY[i] = Convert.ToDouble(models[i].yData);
}
int count = time / interval;
int flag = time % interval;
double xLast = douX[douX.Length - 1];
for (int i = 0; i < count; i++)
{
xLast = xLast + interval;
predictX.Add(xLast);
}
if (flag != 0)
{
xLast = xLast + flag;
predictX.Add(xLast);
}
Lagrange lan = new Lagrange(douX, douY);
List <double> predictY = lan.InsertDatas(predictX);
for (int i = 0; i < predictY.Count; i++)
{
DaoGuZhiLiangTeXingModel model = new DaoGuZhiLiangTeXingModel();
model.xData = predictX[i].ToString();
model.yData = predictY[i].ToString();
models.Add(model);
}
for (int i = 0; i < models.Count; i++)
{
models[i].high = getMax(convert(models));
models[i].low = getMin(convert(models));
models[i].media = getMedia(convert(models));
models[i].xLabel = xLabel;
models[i].canShuName = yLabel;
}
return(models);
}
public List <DaoGuZhiLiangTeXingModel> getAllPredictData(List <DaoGuZhiLiangTeXingModel> models)
{
string xLabel = models[0].xLabel;
string yLabel = models[0].canShuName;
List <DaoGuZhiLiangTeXingModel> allModels = getAllData(models);
double[] douY = new double[allModels.Count];
double[] douX = new double[allModels.Count];
List <double> douAllX = new List <double>();
//double[] douAllY;
for (int i = 0; i < allModels.Count; i++)
{
douX[i] = Convert.ToDouble(allModels[i].xData);
douY[i] = Convert.ToDouble(allModels[i].yData);
}
for (double i = douX[0]; i <= douX[allModels.Count - 1]; i++)
{
douAllX.Add(i);
}
MatrixEquation mart = new MatrixEquation();
double[] xiShu = mart.MultiLine(douX, douY, douY.Length, 3);
List <DaoGuZhiLiangTeXingModel> allPredictModels = new List <DaoGuZhiLiangTeXingModel>();
for (int i = 0; i < douAllX.Count; i++)
{
DaoGuZhiLiangTeXingModel model = new DaoGuZhiLiangTeXingModel();
double y = xiShu[0] + xiShu[1] * douAllX[i] + xiShu[2] * douAllX[i] * douAllX[i] + xiShu[3] * douAllX[i] * douAllX[i] * douAllX[i];
model.xData = douAllX[i].ToString();
model.yData = y.ToString();
allPredictModels.Add(model);
}
for (int i = 0; i < allPredictModels.Count; i++)
{
allPredictModels[i].high = getMax(convert(allPredictModels));
allPredictModels[i].low = getMin(convert(allPredictModels));
allPredictModels[i].predictChaValue = Convert.ToDouble(allModels[i].yData) - Convert.ToDouble(allPredictModels[i].yData);
allPredictModels[i].xLabel = xLabel;
allPredictModels[i].canShuName = yLabel;
}
return(allPredictModels);
}
public List <DaoGuZhiLiangTeXingModel> getLagPredictValue(List <DaoGuZhiLiangTeXingModel> models, int time)
{
string xLabel = models[0].xLabel;
string yLabel = models[0].canShuName;
List <DaoGuZhiLiangTeXingModel> allModels = getAllData(models);
double[] ownX = new double[time];
double[] ownY = new double[time];
List <double> douX = new List <double>();
List <double> douY;
for (int i = 0; i < allModels.Count; i++)
{
if (i < time)
{
ownX[i] = Convert.ToDouble(allModels[i].xData);
ownY[i] = Convert.ToDouble(allModels[i].yData);
}
douX.Add(Convert.ToDouble(allModels[i].xData));
}
Lagrange lan1 = new Lagrange(ownX, ownY);
douY = lan1.InsertDatas(douX);
List <DaoGuZhiLiangTeXingModel> predictModels = new List <DaoGuZhiLiangTeXingModel>();
for (int i = 0; i < douY.Count; i++)
{
DaoGuZhiLiangTeXingModel model = new DaoGuZhiLiangTeXingModel();
model.xData = douX[i].ToString();
model.yData = douY[i].ToString();
predictModels.Add(model);
}
for (int i = 0; i < predictModels.Count; i++)
{
predictModels[i].high = getMax(convert(predictModels));
predictModels[i].low = getMin(convert(predictModels));
predictModels[i].predictChaValue = Convert.ToDouble(allModels[i].yData) - Convert.ToDouble(predictModels[i].yData);
predictModels[i].xLabel = xLabel;
predictModels[i].canShuName = yLabel;
}
return(predictModels);
}
public List <DaoGuZhiLiangTeXingModel> getAllData(List <DaoGuZhiLiangTeXingModel> models)
{
string xLabel = models[0].xLabel;
string yLabel = models[0].canShuName;
double[] douY = new double[models.Count];
double[] douX = new double[models.Count];
List <double> douAllX = new List <double>();
double[] douAllY;
for (int i = 0; i < models.Count; i++)
{
douX[i] = Convert.ToDouble(models[i].xData);
douY[i] = Convert.ToDouble(models[i].yData);
}
for (double i = douX[0]; i <= douX[models.Count - 1]; i++)
{
douAllX.Add(i);
}
douAllY = spline.setSplineData(douX, douY, douAllX.ToArray());
List <DaoGuZhiLiangTeXingModel> allModels = new List <DaoGuZhiLiangTeXingModel>();
for (int i = 0; i < douAllX.Count; i++)
{
DaoGuZhiLiangTeXingModel model = new DaoGuZhiLiangTeXingModel();
model.xData = douAllX[i].ToString();
model.yData = douAllY[i].ToString();
allModels.Add(model);
}
for (int i = 0; i < allModels.Count; i++)
{
allModels[i].high = getMax(convert(allModels));
allModels[i].low = getMin(convert(allModels));
allModels[i].xLabel = xLabel;
allModels[i].canShuName = yLabel;
}
return(allModels);
}
public List <DaoGuZhiLiangTeXingModel> getDaoGuZhiLiangTeXingData(string shiYanHao)
{
List <DaoGuZhiLiangTeXingModel> daoGuModel = new List <DaoGuZhiLiangTeXingModel>();
DaoGuZhiLiangTeXingModel model = new DaoGuZhiLiangTeXingModel();
try
{
SqlConnection();
}
catch (Exception e)
{
throw e;
}
sqlStr = "select * from 稻谷质量特性参数实验信息表 where 实验号 = '" + shiYanHao + "'";
try
{
dataControl = new DataControl();
reader = dataControl.controlSql(sqlCon, sqlStr);
}
catch (Exception e)
{
throw e;
}
reader.Read();
model.shiYanHao = Convert.ToString(reader["实验号"]);
model.canShuHao = Convert.ToString(reader["参数号"]);
model.startCanShuValue = Convert.ToString(reader["起始参数值"]);
model.endCanShuValue = Convert.ToString(reader["终点参数值"]);
try
{
model.startTime = Convert.ToDateTime(reader["开始时间"]);
}
catch (Exception)
{
}
try
{
model.endTime = Convert.ToDateTime(reader["结束时间"]);
}
catch (Exception)
{ }
reader.Close();
sqlStr = "select * from 稻谷质量特性参数信息表 where 参数号 = '" + model.canShuHao + "'";
try
{
dataControl = new DataControl();
reader = dataControl.controlSql(sqlCon, sqlStr);
}
catch (Exception e)
{
throw e;
}
reader.Read();
model.canShuName = Convert.ToString(reader["参数名"]);
reader.Close();
sqlStr = "select * from 稻谷质量特性参数实验数据表 where 实验号 = '" + shiYanHao + "'";
try
{
dataControl = new DataControl();
reader = dataControl.controlSql(sqlCon, sqlStr);
}
catch (Exception e)
{
throw e;
}
while (reader.Read())
{
DaoGuZhiLiangTeXingModel model1 = new DaoGuZhiLiangTeXingModel();
model1.shiYanHao = model.shiYanHao;
model1.canShuHao = model.canShuHao;
model1.startCanShuValue = model.startCanShuValue;
model1.endCanShuValue = model.endCanShuValue;
if (model.startTime != null && model.endTime != null)
{
model1.startTime = model.startTime;
model1.endTime = model.endTime;
}
model1.canShuName = model.canShuName;
model1.xData = Convert.ToString(reader["消耗时间(/d)"]);
model1.xLabel = "消耗时间:";
model1.yData = Convert.ToString(reader["参数值"]);
if (model1.rData < 5)
{
model1.rData = 10;
}
try
{
model1.checkTime = Convert.ToDateTime(reader["检测日期"]);
}
catch (Exception)
{ }
model.tem = Convert.ToString(reader["粮温"]);
model.water = Convert.ToString(reader["水分"]);
daoGuModel.Add(model1);
}
reader.Close();
try
{
SqlClose();
}
catch (Exception e)
{
throw e;
}
for (int i = 0; i < daoGuModel.Count; i++)
{
if (i == 0)
{
daoGuModel[i].addToSpeed = 0.0;
}
else
{
daoGuModel[i].addToSpeed = ((Convert.ToDouble(daoGuModel[i].yData) - Convert.ToDouble(daoGuModel[i - 1].yData)) * 1.0 / (Convert.ToDouble(daoGuModel[i].xData) - Convert.ToDouble(daoGuModel[i - 1].xData)));
}
}
for (int i = 0; i < daoGuModel.Count; i++)
{
daoGuModel[i].high = getMax(convert(daoGuModel));
daoGuModel[i].low = getMin(convert(daoGuModel));
daoGuModel[i].media = getMedia(convert(daoGuModel));
daoGuModel[i].addToSpeedHigh = getAddToSpeedMax(convert(daoGuModel));
daoGuModel[i].addToSpeedLow = getAddToSpeedMin(convert(daoGuModel));
}
return(daoGuModel);
}
