/// <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;
InputFormat = format;
Analyzed = true;
_analyst = theAnalyst;
if (OutputFormat == null)
{
OutputFormat = InputFormat;
}
_data = new BasicMLDataSet();
ResetStatus();
int recordCount = 0;
int outputLength = _analyst.DetermineTotalColumns();
var csv = new ReadCSV(InputFilename.ToString(),
ExpectInputHeaders, InputFormat);
ReadHeaders(csv);
_analystHeaders = new CSVHeaders(InputHeadings);
while (csv.Next() && !ShouldStop())
{
UpdateStatus(true);
var row = new LoadedRow(csv, 1);
double[] inputArray = AnalystNormalizeCSV.ExtractFields(
_analyst, _analystHeaders, csv, outputLength, true);
var input = new ClusterRow(inputArray, row);
_data.Add(input);
recordCount++;
}
RecordCount = recordCount;
Count = csv.ColumnCount;
ReadHeaders(csv);
csv.Close();
ReportDone(true);
}
/// <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);
var row = new LoadedRow(csv, 1);
double[] inputArray = AnalystNormalizeCSV.ExtractFields(
_analyst, _analystHeaders, csv, outputLength, true);
var input = new ClusterRow(inputArray, row);
_data.Add(input);
recordCount++;
}
RecordCount = recordCount;
Count = csv.ColumnCount;
ReadHeaders(csv);
csv.Close();
ReportDone(true);
}
public void Analyze(EncogAnalyst theAnalyst, FileInfo inputFile, bool headers, CSVFormat format)
{
int num;
int num2;
ReadCSV dcsv;
base.InputFilename = inputFile;
if (0 == 0)
{
if ((((uint) headers) + ((uint) num2)) < 0)
{
goto Label_00CC;
}
base.ExpectInputHeaders = headers;
base.InputFormat = format;
if ((((uint) num) + ((uint) headers)) >= 0)
{
base.Analyzed = true;
this._x554f16462d8d4675 = theAnalyst;
if (base.OutputFormat == null)
{
base.OutputFormat = base.InputFormat;
if (((uint) num2) < 0)
{
goto Label_007E;
}
}
}
}
goto Label_0184;
Label_0044:
base.RecordCount = num;
base.Count = dcsv.ColumnCount;
base.ReadHeaders(dcsv);
dcsv.Close();
base.ReportDone(true);
if ((((uint) num2) | 0xfffffffe) != 0)
{
return;
}
goto Label_0184;
Label_0074:
if (!base.ShouldStop())
{
base.UpdateStatus(true);
LoadedRow theRow = new LoadedRow(dcsv, 1);
double[] input = AnalystNormalizeCSV.ExtractFields(this._x554f16462d8d4675, this._xc5416b6511261016, dcsv, num2, true);
if ((((uint) num2) + ((uint) num)) >= 0)
{
ClusterRow inputData = new ClusterRow(input, theRow);
this._x4a3f0a05c02f235f.Add(inputData);
if ((((uint) num2) + ((uint) num2)) >= 0)
{
num++;
if ((((uint) num2) & 0) == 0)
{
goto Label_007E;
}
goto Label_0074;
}
goto Label_00C5;
}
goto Label_011C;
}
goto Label_0044;
Label_007E:
if (dcsv.Next())
{
goto Label_0074;
}
goto Label_0044;
Label_00C5:
if (2 == 0)
{
goto Label_0074;
}
Label_00CC:
this._xc5416b6511261016 = new CSVHeaders(base.InputHeadings);
goto Label_007E;
Label_011C:
num2 = this._x554f16462d8d4675.DetermineTotalColumns();
dcsv = new ReadCSV(base.InputFilename.ToString(), base.ExpectInputHeaders, base.InputFormat);
base.ReadHeaders(dcsv);
goto Label_00C5;
Label_0184:
this._x4a3f0a05c02f235f = new BasicMLDataSet();
base.ResetStatus();
if ((((uint) headers) - ((uint) num)) > uint.MaxValue)
{
goto Label_0044;
}
num = 0;
goto Label_011C;
}
