public async Task FitSingleProfile(FittingProfile profile)
{
var d_data = WideScan.GetRestrictedData(profile.RangeBegin, profile.RangeEnd).Differentiate(_differentialWindow);
var fitting_results = new FittingProfile.FittingResult();
// キーはサイクル数．
EqualIntervalData target_data = new EqualIntervalData();
// 1.まず，フィッティングの計算を行う．
{
#region 固定参照スペクトルを取得する。(一時的にコメントアウト中)
/*
* List<decimal> fixed_data = new List<decimal>();
* if (FixedSpectra.Count > 0)
* {
* var v_data = await FixedSpectra.ForEachAsync(
* async sp => await sp.GetShiftedDataAsync(d_data.Parameter, 3), 10);
*
* for (int j = 0; j < v_data.First().Count; j++)
* {
* fixed_data.Add(v_data.Sum(one => one[j]));
* }
* }
*/
#endregion
/// フィッティング対象となるデータ。すなわち、もとのデータからFixされた分を差し引いたデータ。
//var target_data = fixed_data.Count > 0 ? data.Substract(fixed_data) : data;
// なんだけど、とりあえずはFixedを考慮しない。
target_data = d_data.Data;
//fitting_tasks.Add(i, profile.FitOneCycle(i, target_data[i], d_data.Parameter));
fitting_results = profile.FitOneCycle(-1, target_data, d_data.Parameter);
}
// 2.その後に，チャート出力を行う？
Gnuplot charts = await Output(d_data.Parameter, profile, target_data, fitting_results);
// pltファイルも出力してみる。
using (var writer = new StreamWriter(GetCsvFileName(profile.Name, -1) + ".plt"))
{
await charts.OutputPltFileAsync(writer);
}
// チャートを描画する。
await charts.Draw();
}
/// <summary>
/// 具体的なチャートの設定を行います．
/// </summary>
/// <param name="cycle"></param>
/// <param name="result"></param>
/// <param name="profile"></param>
/// <param name="outputConvolution"></param>
/// <returns></returns>
public Gnuplot ConfigureChart(FittingProfile.FittingResult result, FittingProfile profile, bool outputConvolution, int cycle = -1)
{
string chart_ext = string.Empty;
switch (FittingCondition.ChartFormat)
{
case ChartFormat.Png:
chart_ext = ".png";
break;
case ChartFormat.Svg:
chart_ext = ".svg";
break;
}
var chart_destination = Path.Combine(FittingCondition.OutputDestination, $"{profile.Name}{(cycle >= 0 ? string.Format("_{0}", cycle) : string.Empty)}{chart_ext}");
#region チャート設定
var gnuplot = new Gnuplot
{
Format = FittingCondition.ChartFormat,
Width = 800,
Height = 600,
FontScale = 1.6,
Destination = chart_destination,
XTitle = "Kinetic Energy / eV",
YTitle = "dN(E)/dE",
Title = (cycle >= 0 ? $"Cycle {cycle} , " : string.Empty) + $"Shift {result.Shift} eV"
};
var source_csv = GetCsvFileName(profile.Name, cycle);
gnuplot.DataSeries.Add(new LineChartSeries
{
SourceFile = source_csv,
XColumn = 1,
YColumn = 2,
Title = "data",
Style = new LineChartSeriesStyle(LineChartStyle.Lines)
{
Style = new LinePointStyle
{
LineColor = "#FF0000",
LineWidth = 3,
}
}
});
var reference_names = profile.ReferenceSpectra.Select(r => r.Name).ToList();
for (int j = 0; j < reference_names.Count; j++)
{
gnuplot.DataSeries.Add(new LineChartSeries
{
SourceFile = source_csv,
XColumn = 1,
YColumn = j + 3,
Title = $"{result.Gains[j].ToString("f3")} * {reference_names[j]}",
Style = new LineChartSeriesStyle(LineChartStyle.Lines)
{
Style = new LinePointStyle
{
LineColorIndex = j,
LineWidth = 2,
}
}
});
}
if (outputConvolution)
{
gnuplot.DataSeries.Add(new LineChartSeries
{
SourceFile = source_csv,
XColumn = 1,
YColumn = reference_names.Count + 3,
Title = "Convolution",
Style = new LineChartSeriesStyle(LineChartStyle.Lines)
{
Style = new LinePointStyle
{
LineColor = "#0000FF",
LineWidth = 3,
}
}
});
}
#endregion
gnuplot.PreConfigureAxis();
return(gnuplot);
}
