//列表
private static DataTable CreateView_T(string _selCol, string _strTestNo, int ab)
{
BLL.TestSample bllts = new HR_Test.BLL.TestSample();
DataSet dst = bllts.GetFinishList1(_selCol, " testNo = '" + _strTestNo + "' and isFinish=true ", ab);
return(dst.Tables[0]);
}
public static DataTable CreateAverageViewReport(StringBuilder _selSqlAver, StringBuilder _strSelcol, string _arrTestSample, int ab)
{
BLL.TestSample bllts = new HR_Test.BLL.TestSample();
//求平均
DataSet dsaver = bllts.GetFinishSumList1(_selSqlAver.ToString(), " testSampleNo in ('" + _arrTestSample + ") and isFinish=true ");
//获取选择试样的数量和试样编号
string selCol = _strSelcol.ToString();
selCol = selCol.Substring(0, selCol.LastIndexOf(','));
DataSet dsfinish = bllts.GetFinishList1(selCol, " testSampleNo in ('" + _arrTestSample + ") and isFinish=true ", ab);
int fcount = dsfinish.Tables[0].Rows.Count;
//变异系数 = sd/mean
StringBuilder strCV = new StringBuilder();
//中间值
StringBuilder strMid = new StringBuilder();
//创建新的数据计算结果表
DataSet dsaverto = new DataSet();
dsaverto.Tables.Add();
dsaverto.Tables[0].Columns.Add("数量(" + fcount + ")").SetOrdinal(0);
for (int i = 0; i < dsaver.Tables[0].Columns.Count; i++)
{
dsaverto.Tables[0].Columns.Add(dsaver.Tables[0].Columns[i].Caption).SetOrdinal(i + 1);
}
//给新数据表添加平均值列
List <object> objmean = new List <object>();
objmean.Add("Mean.:");
for (int i = 0; i < dsaver.Tables[0].Columns.Count; i++)
{
if (double.Parse(dsaver.Tables[0].Rows[0][i].ToString()) != 0)
{
objmean.Add(dsaver.Tables[0].Rows[0][i].ToString());
}
else
{
objmean.Add("-");
}
}
dsaverto.Tables[0].Rows.Add(objmean.ToArray());
double sumsd = 0;
double sd = 0;
double cv = 0;
double ctrue = 0;
double caver = 0;
double temp = 1000000;
double mid = 0;
List <object> objsd = new List <object>();
objsd.Add("S.D.:");
List <object> objcv = new List <object>();
objcv.Add("C.V.:");
List <object> objmid = new List <object>();
objmid.Add("Mid.:");
//计算标准偏差
for (int i = 0; i < dsaver.Tables[0].Columns.Count; i++)
{
for (int j = 0; j < dsfinish.Tables[0].Rows.Count; j++)
{
// 求和 (真实值-平均值)^2
if (ab == 2)
{
ctrue = Convert.ToDouble(dsfinish.Tables[0].Rows[j][i + 4].ToString());
caver = Convert.ToDouble(dsaver.Tables[0].Rows[0][i].ToString());
}
else
{
ctrue = Convert.ToDouble(dsfinish.Tables[0].Rows[j][i + 5].ToString());
caver = Convert.ToDouble(dsaver.Tables[0].Rows[0][i].ToString());
}
double c1 = (ctrue - caver) * (ctrue - caver);
sumsd += c1;
//查找中间值，最接近平均值的
double d_value = Math.Abs(ctrue - caver);
if (d_value < temp)
{
temp = d_value;
mid = ctrue;
}
}
if (fcount - 1 != 0)
{
sd = Math.Sqrt(sumsd / (fcount - 1));
}
else
{
sd = 0;
}
//变异系数 =( 标准偏差 / 平均值 ) *100
if (caver != 0)
{
cv = (sd / caver) * 100;
}
else
{
cv = 0;
}
if (sd != 0)
{
objsd.Add(sd.ToString("f4"));
}
else
{
objsd.Add("-");
}
if (cv != 0)
{
objcv.Add(cv.ToString("f4"));
}
else
{
objcv.Add("-");
}
if (mid != 0)
{
objmid.Add(mid.ToString("f4"));
}
else
{
objmid.Add("-");
}
temp = 1000000;
sumsd = 0;
}
//S.D.标准偏差行
if (_isSelSD)
{
dsaverto.Tables[0].Rows.Add(objsd.ToArray());
}
//变异系数行
if (_isSelCV)
{
dsaverto.Tables[0].Rows.Add(objcv.ToArray());
}
//中间值行
if (_isSelMid)
{
dsaverto.Tables[0].Rows.Add(objmid.ToArray());
}
dsfinish.Dispose();
return(dsaverto.Tables[0]);
}