stella.util
Class FitsFinder

java.lang.Object
  stella.util.FitsFinder

public class FitsFinder
extends Object

Fits finder is a small program that searches a path recursively and collects all fits files found. The list can be further processed by various other static methods.

Nested Class Summary

static class

FitsFinder.Moment This class constructs a table of fits files versus their moments.

Constructor Summary

FitsFinder()

Method Summary

static Collection<File>	getFitsFiles(File dir, String name) Returns a list of all fits files, scanned from the named directory.
static Map<File,List<Double>>	scanFitsMoments(File dir, String pattern, int order, String path, boolean unzip) We scan for fits files, if decompress is enabled we uncompress them using imcopy, where the default path is used if not specified.

Methods inherited from class java.lang.Object

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

Constructor Detail

FitsFinder

public FitsFinder()

Method Detail

getFitsFiles

public static Collection<File> getFitsFiles(File dir,
                                            String name)

Returns a list of all fits files, scanned from the named directory. If the supplied name is null, only fits files with the extension '.fits' are returned, otherwise name is used as a wildcard pattern on all files found. If all files should be returned, either use FilteTree itself or suplly a '*' as the name pattern.

scanFitsMoments

public static Map<File,List<Double>> scanFitsMoments(File dir,
                                                     String pattern,
                                                     int order,
                                                     String path,
                                                     boolean unzip)

We scan for fits files, if decompress is enabled we uncompress them using imcopy, where the default path is used if not specified. For each fits file we calculate the n first moments and return a mapping of fits (or fitz) files to a list of seven double, where at the first index the count average, on the second the standard deviation (not variance, the root of it!), and the normalized central moments 3-7.