本文整理汇总了C#中Encog.Util.CSV.CSVFormat类的典型用法代码示例。如果您正苦于以下问题:C# CSVFormat类的具体用法?C# CSVFormat怎么用?C# CSVFormat使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
CSVFormat类属于Encog.Util.CSV命名空间,在下文中一共展示了CSVFormat类的15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: CSVDataSource
/// <summary>
/// Construct a CSV source from a filename. Allows a delimiter character to
/// be specified.
/// </summary>
/// <param name="file">The filename.</param>
/// <param name="headers">The headers.</param>
/// <param name="format">The format.</param>
public CSVDataSource(string file, bool headers,
CSVFormat format)
{
_file = file;
_headers = headers;
_format = format;
}
示例2: Analyze
public void Analyze(EncogAnalyst theAnalyst, FileInfo inputFile, bool headers, CSVFormat format)
{
base.InputFilename = inputFile;
if ((((uint) headers) & 0) != 0)
{
goto Label_0063;
}
Label_005C:
base.ExpectInputHeaders = headers;
Label_0063:
base.InputFormat = format;
base.Analyzed = true;
this._x554f16462d8d4675 = theAnalyst;
base.PerformBasicCounts();
if (((uint) headers) >= 0)
{
this._x146688677da5adf5 = base.InputHeadings.Length;
this._x1402a42b31a31090 = this._x554f16462d8d4675.DetermineOutputFieldCount();
this._xc5416b6511261016 = new CSVHeaders(base.InputHeadings);
this._x7acb8518c8ed6133 = new TimeSeriesUtil(this._x554f16462d8d4675, false, this._xc5416b6511261016.Headers);
if (0 != 0)
{
goto Label_005C;
}
}
}
示例3: 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.</param>
/// <param name="headers">True if headers are present.</param>
/// <param name="format">The format the file is in.</param>
public void Analyze(EncogAnalyst theAnalyst,
FileInfo inputFile, bool headers, CSVFormat format)
{
InputFilename = inputFile;
ExpectInputHeaders = headers;
Format = format;
_analyst = theAnalyst;
Analyzed = true;
PerformBasicCounts();
_inputCount = _analyst.DetermineInputCount();
_outputCount = _analyst.DetermineOutputCount();
_idealCount = InputHeadings.Length - _inputCount;
if ((InputHeadings.Length != _inputCount)
&& (InputHeadings.Length != (_inputCount + _outputCount)))
{
throw new AnalystError("Invalid number of columns("
+ InputHeadings.Length + "), must match input("
+ _inputCount + ") count or input+output("
+ (_inputCount + _outputCount) + ") count.");
}
}
示例4: CSVDataCODEC
public CSVDataCODEC(string file, CSVFormat format, bool headers, int inputCount, int idealCount, bool significance)
{
if ((((uint) inputCount) - ((uint) significance)) < 0)
{
}
Label_0063:
if (this._x43f451310e815b76 != 0)
{
throw new BufferedDataError("To export CSV, you must use the CSVDataCODEC constructor that does not specify input or ideal sizes.");
}
Label_006B:
this._xb44380e048627945 = file;
if ((((uint) inputCount) - ((uint) inputCount)) <= uint.MaxValue)
{
this._x5786461d089b10a0 = format;
this._x43f451310e815b76 = inputCount;
this._xb52d4a98fad404da = idealCount;
this._x94e6ca5ac178dbd0 = headers;
this._x2602a84fb5c05ca2 = significance;
if ((((uint) headers) - ((uint) inputCount)) > uint.MaxValue)
{
goto Label_0063;
if ((((uint) significance) + ((uint) headers)) >= 0)
{
goto Label_006B;
}
goto Label_0063;
}
}
}
示例5: ReadCSV
public ReadCSV(string filename, bool headers, CSVFormat format)
{
this._x44b48f93f08f9199 = new List<string>();
this._x26c511b92db96554 = new Dictionary<string, int>();
this._xe134235b3526fa75 = new StreamReader(filename);
this.x5e9e6297e1dda8c2(headers, format);
}
示例6: FromListInt
/// <summary>
/// Get an array of ints's from a string of comma separated text.
/// </summary>
/// <param name="format">The way to format this list.</param>
/// <param name="str">The string that contains a list of numbers.</param>
/// <returns>An array of ints parsed from the string.</returns>
public static int[] FromListInt(CSVFormat format, String str)
{
if (str.Trim().Length == 0)
{
return new int[0];
}
// first count the numbers
String[] tok = str.Split(format.Separator);
int count = tok.Length;
// now allocate an object to hold that many numbers
var result = new int[count];
// and finally parse the numbers
for (int index = 0; index < tok.Length; index++)
{
try
{
String num = tok[index];
int value = int.Parse(num);
result[index] = value;
}
catch (Exception e)
{
throw new PersistError(e);
}
}
return result;
}
示例7: FromList
/// <summary>
/// Get an array of double's from a string of comma separated text.
/// </summary>
/// <param name="format">The way to format this list.</param>
/// <param name="str">The string that contains a list of numbers.</param>
/// <returns>An array of doubles parsed from the string.</returns>
public static double[] FromList(CSVFormat format, String str)
{
// first count the numbers
String[] tok = str.Split(format.Separator);
int count = tok.Length;
// now allocate an object to hold that many numbers
double[] result = new double[count];
// and finally parse the numbers
for (int index = 0; index < tok.Length; index++)
{
try
{
String num = tok[index];
double value = format.Parse(num);
result[index] = value;
}
catch (Exception e)
{
throw new PersistError(e);
}
}
return result;
}
示例8: LoadCSVTOMemory
/// <summary>
/// Load a CSV file into a memory dataset.
/// </summary>
///
/// <param name="format">The CSV format to use.</param>
/// <param name="filename">The filename to load.</param>
/// <param name="headers">True if there is a header line.</param>
/// <param name="inputSize">The input size. Input always comes first in a file.</param>
/// <param name="idealSize">The ideal size, 0 for unsupervised.</param>
/// <returns>A NeuralDataSet that holds the contents of the CSV file.</returns>
public static IMLDataSet LoadCSVTOMemory(CSVFormat format, String filename,
bool headers, int inputSize, int idealSize)
{
var result = new BasicMLDataSet();
var csv = new ReadCSV(filename, headers, format);
while (csv.Next())
{
BasicMLData ideal = null;
int index = 0;
var input = new BasicMLData(inputSize);
for (int i = 0; i < inputSize; i++)
{
double d = csv.GetDouble(index++);
input[i] = d;
}
if (idealSize > 0)
{
ideal = new BasicMLData(idealSize);
for (int i = 0; i < idealSize; i++)
{
double d = csv.GetDouble(index++);
ideal[i] = d;
}
}
IMLDataPair pair = new BasicMLDataPair(input, ideal);
result.Add(pair);
}
return result;
}
示例9: ReadCSV
/// <summary>
/// Construct a CSV reader from an input stream.
/// </summary>
/// <param name="istream">The InputStream to read from.</param>
/// <param name="headers">Are headers present?</param>
/// <param name="delim">What is the delimiter.</param>
public ReadCSV(Stream istream, bool headers,
char delim)
{
var format = new CSVFormat(CSVFormat.DecimalCharacter, delim);
_reader = new StreamReader(istream);
_delim = delim;
Begin(headers, format);
}
示例10: Analyze
public void Analyze(FileInfo inputFile, bool headers, CSVFormat format)
{
base.InputFilename = inputFile;
base.ExpectInputHeaders = headers;
base.InputFormat = format;
base.Analyzed = true;
base.PerformBasicCounts();
}
示例11: LoadedRow
/// <summary>
/// Construct a loaded row from an IMLData.
/// </summary>
/// <param name="format">The format to store the numbers in.</param>
/// <param name="data">The data to use.</param>
/// <param name="extra">The extra positions to allocate.</param>
public LoadedRow(CSVFormat format, IMLData data, int extra)
{
int count = data.Count;
_data = new String[count + extra];
for (int i = 0; i < count; i++)
{
_data[i] = format.Format(data[i], 5);
}
}
示例12: LoadedRow
/// <summary>
/// Construct a loaded row from an array.
/// </summary>
/// <param name="format">The format to store the numbers in.</param>
/// <param name="data">The data to use.</param>
/// <param name="extra">The extra positions to allocate.</param>
public LoadedRow(CSVFormat format, double[] data, int extra)
{
int count = data.Length;
_data = new String[count + extra];
for (int i = 0; i < count; i++)
{
_data[i] = format.Format(data[i], 5);
}
}
示例13: Analyze
public void Analyze(IMLRegression method, FileInfo inputFile, bool headers, CSVFormat format)
{
object[] objArray;
base.InputFilename = inputFile;
base.ExpectInputHeaders = headers;
base.InputFormat = format;
if (((uint) headers) >= 0)
{
base.Analyzed = true;
}
base.PerformBasicCounts();
this._x43f451310e815b76 = method.InputCount;
this._x98cf41c6b0eaf6ab = method.OutputCount;
this._xb52d4a98fad404da = Math.Max(base.InputHeadings.Length - this._x43f451310e815b76, 0);
if (0x7fffffff == 0)
{
goto Label_00E0;
}
if ((((uint) headers) & 0) != 0)
{
goto Label_0084;
}
if ((((uint) headers) - ((uint) headers)) >= 0)
{
if (base.InputHeadings.Length == this._x43f451310e815b76)
{
return;
}
if (3 == 0)
{
return;
}
}
Label_000C:
if (base.InputHeadings.Length != (this._x43f451310e815b76 + this._x98cf41c6b0eaf6ab))
{
objArray = new object[7];
goto Label_00E0;
}
return;
Label_0084:
objArray[3] = this._x43f451310e815b76;
if ((((uint) headers) + ((uint) headers)) < 0)
{
goto Label_000C;
}
objArray[4] = ") count or input+output(";
objArray[5] = this._x43f451310e815b76 + this._x98cf41c6b0eaf6ab;
objArray[6] = ") count.";
throw new AnalystError(string.Concat(objArray));
Label_00E0:
objArray[0] = "Invalid number of columns(";
objArray[1] = base.InputHeadings.Length;
objArray[2] = "), must match input(";
goto Label_0084;
}
示例14: QuickParseCSV
/// <summary>
/// parses one column of a csv and returns an array of doubles.
/// you can only return one double array with this method.
/// </summary>
/// <param name="file">The file.</param>
/// <param name="formatused">The formatused.</param>
/// <param name="Name">The name of the column to parse..</param>
/// <returns></returns>
public static List<double> QuickParseCSV(string file, CSVFormat formatused, string Name)
{
List<double> returnedArrays = new List<double>();
ReadCSV csv = new ReadCSV(file, true, formatused);
while (csv.Next())
{
returnedArrays.Add(csv.GetDouble(Name));
}
return returnedArrays;
}
示例15: Process
/// <summary>
/// Process, and sort the files.
/// </summary>
///
/// <param name="inputFile">The input file.</param>
/// <param name="outputFile">The output file.</param>
/// <param name="headers">True, if headers are to be used.</param>
/// <param name="format">The format of the file.</param>
public void Process(FileInfo inputFile, FileInfo outputFile,
bool headers, CSVFormat format)
{
InputFilename = inputFile;
ExpectInputHeaders = headers;
InputFormat = format;
ReadInputFile();
SortData();
WriteOutputFile(outputFile);
}