org.encog.app.analyst.csv.normalize

Class AnalystNormalizeCSV

java.lang.Object

org.encog.app.analyst.csv.basic.BasicFile

org.encog.app.analyst.csv.normalize.AnalystNormalizeCSV

All Implemented Interfaces:

QuantTask

public class AnalystNormalizeCSV
extends BasicFile

Normalize, or denormalize, a CSV file.

Field Summary

Fields inherited from class org.encog.app.analyst.csv.basic.BasicFile

REPORT_INTERVAL

Constructor Summary

Constructors

Constructor and Description
AnalystNormalizeCSV()

Method Summary

Modifier and Type	Method and Description
void	analyze(java.io.File inputFilename, boolean expectInputHeaders, CSVFormat inputFormat, EncogAnalyst theAnalyst) Analyze the file.
static double[]	extractFields(EncogAnalyst analyst, CSVHeaders headers, ReadCSV csv, int outputLength, boolean skipOutput) Extract fields from a file into a numeric array for machine learning.
void	normalize(java.io.File file) Normalize the input file.
void	setSourceFile(java.io.File file, boolean headers, CSVFormat format) Set the source file.

Methods inherited from class org.encog.app.analyst.csv.basic.BasicFile

appendSeparator, getColumnCount, getFormat, getInputFilename, getInputHeadings, getPrecision, getRecordCount, getReport, getReportInterval, getScript, isAnalyzed, isExpectInputHeaders, isProduceOutputHeaders, performBasicCounts, prepareOutputFile, readHeaders, reportDone, reportDone, requestStop, resetStatus, setAnalyzed, setColumnCount, setExpectInputHeaders, setInputFilename, setInputFormat, setInputHeadings, setPrecision, setProduceOutputHeaders, setRecordCount, setReport, setReportInterval, setScript, shouldStop, toString, updateStatus, updateStatus, validateAnalyzed, writeRow

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

AnalystNormalizeCSV

public AnalystNormalizeCSV()

Method Detail

extractFields

public static final double[] extractFields(EncogAnalyst analyst,
                                           CSVHeaders headers,
                                           ReadCSV csv,
                                           int outputLength,
                                           boolean skipOutput)

Extract fields from a file into a numeric array for machine learning.

Parameters:

analyst - The analyst to use.

headers - The headers for the input data.

csv - The CSV that holds the input data.

outputLength - The length of the returned array.

skipOutput - True if the output should be skipped.

Returns:

The encoded data.

analyze

public void analyze(java.io.File inputFilename,
                    boolean expectInputHeaders,
                    CSVFormat inputFormat,
                    EncogAnalyst theAnalyst)

Analyze the file.

Parameters:

inputFilename - The input file.

expectInputHeaders - True, if input headers are present.

inputFormat - The format.

theAnalyst - The analyst to use.

normalize

public void normalize(java.io.File file)

Normalize the input file. Write to the specified file.

Parameters:

file - The file to write to.

setSourceFile

public void setSourceFile(java.io.File file,
                          boolean headers,
                          CSVFormat format)

Set the source file. This is useful if you want to use pre-existing stats to normalize something and skip the analyze step.

Parameters:

file - The file to use.

headers - True, if headers are to be expected.

format - The format of the CSV file.