本文整理汇总了C#中EncogAnalyst.DetermineTotalColumns方法的典型用法代码示例。如果您正苦于以下问题：C# EncogAnalyst.DetermineTotalColumns方法的具体用法？C# EncogAnalyst.DetermineTotalColumns怎么用？C# EncogAnalyst.DetermineTotalColumns使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类EncogAnalyst的用法示例。
在下文中一共展示了EncogAnalyst.DetermineTotalColumns方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: Analyze
/// <summary>
/// Analyze the data. This counts the records and prepares the data to be
/// processed.
/// </summary>
/// <param name="theAnalyst">The analyst to use.</param>
/// <param name="inputFile">The input file to analyze.</param>
/// <param name="headers">True, if the input file has headers.</param>
/// <param name="format">The format of the input file.</param>
public void Analyze(EncogAnalyst theAnalyst,
FileInfo inputFile, bool headers, CSVFormat format)
{
InputFilename = inputFile;
ExpectInputHeaders = headers;
Format = format;
Analyzed = true;
_analyst = theAnalyst;
_data = new BasicMLDataSet();
ResetStatus();
int recordCount = 0;
int outputLength = _analyst.DetermineTotalColumns();
var csv = new ReadCSV(InputFilename.ToString(),
ExpectInputHeaders, Format);
ReadHeaders(csv);
_analystHeaders = new CSVHeaders(InputHeadings);
while (csv.Next() && !ShouldStop())
{
UpdateStatus(true);
double[] inputArray = AnalystNormalizeCSV.ExtractFields(
_analyst, _analystHeaders, csv, outputLength, true);
IMLData input = new BasicMLData(inputArray);
_data.Add(new BasicMLDataPair(input));
recordCount++;
}
RecordCount = recordCount;
Count = csv.ColumnCount;
ReadHeaders(csv);
csv.Close();
ReportDone(true);
}示例2: TimeSeriesUtil
/// <summary>
/// Construct the time-series utility.
/// </summary>
/// <param name="theAnalyst">The analyst to use.</param>
/// <param name="includeOutput">Should output fields be included.</param>
/// <param name="headings">The column headings.</param>
public TimeSeriesUtil(EncogAnalyst theAnalyst, bool includeOutput,
IEnumerable<string> headings)
{
_buffer = new List<double[]>();
_headingMap = new Dictionary<String, Int32>();
_analyst = theAnalyst;
_lagDepth = _analyst.LagDepth;
_leadDepth = _analyst.LeadDepth;
_totalDepth = _lagDepth + _leadDepth + 1;
_inputSize = includeOutput ? _analyst.DetermineTotalColumns() : _analyst.DetermineTotalInputFieldCount();
_outputSize = _analyst.DetermineInputCount()
+ _analyst.DetermineOutputCount();
int headingIndex = 0;
foreach (String column in headings)
{
_headingMap[column.ToUpper()] = headingIndex++;
}
}