Package gov.nih.mipav.model.algorithms

Class StochasticForests

java.lang.Object

java.lang.Thread

gov.nih.mipav.model.algorithms.AlgorithmBase

gov.nih.mipav.model.algorithms.StochasticForests

All Implemented Interfaces:

java.awt.event.ActionListener, java.awt.event.WindowListener, java.lang.Runnable, java.util.EventListener

public class StochasticForests
extends AlgorithmBase

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
private class	StochasticForests.Data
private class	StochasticForests.DataChar
private class	StochasticForests.DataDouble
private class	StochasticForests.DataFloat
private class	StochasticForests.DataSparse
private class	StochasticForests.Forest
private class	StochasticForests.ForestClassification
private class	StochasticForests.ForestProbability
private class	StochasticForests.ForestRegression
private class	StochasticForests.ForestSurvival
private static class	StochasticForests.ImportanceMode
private class	StochasticForests.indexValueComparator
private class	StochasticForests.indexValueDescendingComparator
private class	StochasticForests.indexValueItem
private static class	StochasticForests.MemoryMode
private static class	StochasticForests.PredictionType
private class	StochasticForests.SparseMatrix
private static class	StochasticForests.SplitRule
private class	StochasticForests.Tree
private class	StochasticForests.TreeClassification
private class	StochasticForests.TreeProbability
private class	StochasticForests.TreeRegression
private class	StochasticForests.TreeSurvival
private static class	StochasticForests.TreeType
private class	StochasticForests.ValuePair<K,V>

Nested classes/interfaces inherited from class java.lang.Thread

java.lang.Thread.State, java.lang.Thread.UncaughtExceptionHandler

Field Summary

Fields

Modifier and Type	Field	Description
private double	alpha
private java.util.Vector<java.lang.String>	always_split_variable_names
private java.lang.String	case_weights_file
(package private) double	DEFAULT_ALPHA
(package private) StochasticForests.ImportanceMode	DEFAULT_IMPORTANCE_MODE
(package private) int	DEFAULT_MIN_NODE_SIZE_CLASSIFICATION
(package private) int	DEFAULT_MIN_NODE_SIZE_PROBABILITY
(package private) int	DEFAULT_MIN_NODE_SIZE_REGRESSION
(package private) int	DEFAULT_MIN_NODE_SIZE_SURVIVAL
(package private) double	DEFAULT_MINPROP
(package private) int	DEFAULT_NUM_RANDOM_SPLITS
(package private) int	DEFAULT_NUM_THREADS
(package private) int	DEFAULT_NUM_TREE
(package private) StochasticForests.PredictionType	DEFAULT_PREDICTIONTYPE
(package private) StochasticForests.SplitRule	DEFAULT_SPLITRULE
private java.lang.String	dependent_variable_name
private boolean	holdout
private StochasticForests.ImportanceMode	importance_mode
private java.lang.String	input_file
private java.lang.String	load_forest_filename
static double	logprop
(package private) static int[]	mask
private StochasticForests.MemoryMode	memory_mode
private boolean	memory_saving_splitting
private int	min_node_size
private double	minprop
private int	mtry
private int	num_random_splits
private int	num_threads
private int	num_trees
(package private) static int[]	offset
private java.lang.String	output_prefix
private boolean	predict_all
private StochasticForests.PredictionType	prediction_type
private boolean	probability
(package private) double	Q_THRESHOLD
static int	RAND_MAX
private double	sample_fraction
private boolean	sample_with_replacement
private long	seed
private java.lang.String	split_select_weights_file
private StochasticForests.SplitRule	splitrule
(package private) double	STATUS_INTERVAL
private java.lang.String	status_variable_name
private boolean	testMain
private boolean	testUtility
private StochasticForests.TreeType	treetype
private java.util.Vector<java.lang.String>	unordered_variable_names
private boolean	verbose_out
private boolean	write

Fields inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

destFlag, destImage, image25D, maxProgressValue, minProgressValue, multiThreadingEnabled, nthreads, progress, progressModulus, progressStep, runningInSeparateThread, separable, srcImage, threadStopped

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Constructors

Constructor	Description
StochasticForests()
StochasticForests(StochasticForests.TreeType treetype, boolean probability, boolean verbose_out, java.lang.String dependent_variable_name, StochasticForests.MemoryMode memory_mode, java.lang.String input_file, int mtry, java.lang.String output_prefix, int num_trees, long seed, int num_threads, java.lang.String load_forest_filename, StochasticForests.ImportanceMode importance_mode, int min_node_size, java.lang.String split_select_weights_file, java.util.Vector<java.lang.String> always_split_variable_names, java.lang.String status_variable_name, boolean sample_with_replacement, java.util.Vector<java.lang.String> unordered_variable_names, boolean memory_saving_splitting, StochasticForests.SplitRule splitrule, java.lang.String case_weights_file, boolean predict_all, double sample_fraction, double alpha, double minprop, boolean holdout, StochasticForests.PredictionType prediction_type, int num_random_splits, boolean write)

Method Summary

Modifier and Type	Method	Description
private java.util.Vector<java.lang.Double>	adjustPvalues(java.util.Vector<java.lang.Double> unadjusted_pvalues)
private java.lang.String	beautifyTime(int seconds)
private boolean	checkPositiveIntegers(java.util.Vector<java.lang.Double> all_values)
private java.lang.String	checkUnorderedVariables(StochasticForests.Data data, java.util.Vector<java.lang.String> unordered_variable_names)
private double	computeConcordanceIndex(StochasticForests.Data data, java.util.Vector<java.lang.Double> sum_chf, int dependent_varID, int status_varID, java.util.Vector<java.lang.Integer> sample_IDs)
private void	drawWithoutReplacementFisherYates(java.util.Vector<java.lang.Integer> result, java.util.Random random, int max, java.util.Vector<java.lang.Integer> skip, int num_samples)
private void	drawWithoutReplacementSimple(java.util.Vector<java.lang.Integer> result, java.util.Random random, int max, java.util.Vector<java.lang.Integer> skip, int num_samples)
private void	drawWithoutReplacementSkip(java.util.Vector<java.lang.Integer> result, java.util.Random random, int max, java.util.Vector<java.lang.Integer> skip, int num_samples)
private void	drawWithoutReplacementWeighted(java.util.Vector<java.lang.Integer> result, java.util.Random random, int max_index, int num_samples, java.util.Vector<java.lang.Double> weights)
private void	drawWithoutReplacementWeighted(java.util.Vector<java.lang.Integer> result, java.util.Random random, java.util.Vector<java.lang.Integer> indices, int num_samples, java.util.Vector<java.lang.Double> weights)
private double	dstdnorm(double x)
private void	equalSplit(java.util.Vector<java.lang.Integer> result, int start, int end, int num_parts)
private boolean	equalVectorDouble(java.util.Vector<java.lang.Double> v1, java.util.Vector<java.lang.Double> v2, java.lang.String str)
private boolean	equalVectorInteger(java.util.Vector<java.lang.Integer> v1, java.util.Vector<java.lang.Integer> v2, java.lang.String str)
private boolean	equalVectorVectorDouble(java.util.Vector<java.util.Vector<java.lang.Double>> v1, java.util.Vector<java.util.Vector<java.lang.Double>> v2, java.lang.String str)
private boolean	equalVectorVectorInteger(java.util.Vector<java.util.Vector<java.lang.Integer>> v1, java.util.Vector<java.util.Vector<java.lang.Integer>> v2, java.lang.String str)
private double	erf(double x)
private boolean	expectNear(double val1, double val2, double error, java.lang.String str)
(package private) void	loadDoubleVectorFromFile(java.util.Vector<java.lang.Double> result, java.lang.String filename)
private java.util.Vector<java.lang.Double>	logrankScores(java.util.Vector<java.lang.Double> time, java.util.Vector<java.lang.Double> status)
private void	maxstat(java.util.Vector<java.lang.Double> scores, java.util.Vector<java.lang.Double> x, java.util.Vector<java.lang.Integer> indices, double[] best_maxstat, double[] best_split_value, double minprop, double maxprop)
private double	maxstatPValueLau92(double b, double minprop, double maxprop)
private double	maxstatPValueLau94(double b, double minprop, double maxprop, int N, java.util.Vector<java.lang.Integer> m)
private double	maxstatPValueUnadjusted(double b)
private int	mostFrequentClass(java.util.Vector<java.lang.Integer> class_count, java.util.Random random)	Returns the most frequent class index of a vector with counts for the classes.
private int	mostFrequentDClass(java.util.Vector<java.lang.Double> class_count, java.util.Random random)	Returns the most frequent class index of a vector with counts for the classes.
private double	mostFrequentValue(java.util.HashMap<java.lang.Double,java.lang.Integer> class_count, java.util.Random random)
private java.util.Vector<java.lang.Integer>	numSamplesLeftOfCutpoint(java.util.Vector<java.lang.Double> x, java.util.Vector<java.lang.Integer> indices)
private java.util.Vector<java.lang.Integer>	order(java.util.Vector<java.lang.Double> x, boolean decreasing)
private double	pstdnorm(double x)
(package private) java.util.Vector<java.lang.Double>	rank(java.util.Vector<java.lang.Double> values)	Sample ranks starting from 1.
private void	readBVector1D(java.util.Vector<java.lang.Boolean> result, java.io.BufferedReader br)	Read a 1d vector written by saveVector1D() from filestream.
private void	readDVector1D(java.util.Vector<java.lang.Double> result, java.io.BufferedReader br)	Read a 1d vector written by saveVector1D() from filestream.
private void	readDVector2D(java.util.Vector<java.util.Vector<java.lang.Double>> result, java.io.BufferedReader br)	Read a 2d vector written by saveVector2D() from filestream.
private void	readVector1D(java.util.Vector<java.lang.Integer> result, java.io.BufferedReader br)	Read a 1d vector written by saveVector1D() from filestream.
private void	readVector2D(java.util.Vector<java.util.Vector<java.lang.Integer>> result, java.io.BufferedReader br)	Read a 2d vector written by saveVector2D() from filestream.
private int	roundToNextMultiple(int value, int multiple)
void	runAlgorithm()	Actually runs the algorithm.
private void	saveBVector1D(java.util.Vector<java.lang.Boolean> vector, java.io.BufferedWriter bw)	Write a 1d vector to filestream.
private void	saveDVector1D(java.util.Vector<java.lang.Double> vector, java.io.BufferedWriter bw)	Write a 1d vector to filestream.
private void	saveDVector2D(java.util.Vector<java.util.Vector<java.lang.Double>> vector, java.io.BufferedWriter bw)	Write a 2d vector to filestream.
private void	saveVector1D(java.util.Vector<java.lang.Integer> vector, java.io.BufferedWriter bw)	Write a 1d vector to filestream.
private void	saveVector2D(java.util.Vector<java.util.Vector<java.lang.Integer>> vector, java.io.BufferedWriter bw)	Write a 2d vector to filestream.
private void	shuffle(java.util.Vector<java.lang.Integer> v, java.util.Random random)
private void	shuffleAndSplit(java.util.Vector<java.lang.Integer> first_part, java.util.Vector<java.lang.Integer> second_part, int n_all, int n_first, java.util.Random random)
private void	shuffleAndSplitAppend(java.util.Vector<java.lang.Integer> first_part, java.util.Vector<java.lang.Integer> second_part, int n_all, int n_first, java.util.Vector<java.lang.Integer> mapping, java.util.Random random)
private void	splitString(java.util.Vector<java.lang.String> result, java.lang.String input, java.lang.String split_string)
private java.lang.String	uintToString(int number)

Methods inherited from class gov.nih.mipav.model.algorithms.AlgorithmBase

actionPerformed, addListener, addProgressChangeListener, calculateImageSize, calculatePrincipleAxis, computeElapsedTime, computeElapsedTime, convertIntoFloat, delinkProgressToAlgorithm, delinkProgressToAlgorithmMulti, displayError, errorCleanUp, finalize, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, fireProgressStateChanged, generateProgressValues, getDestImage, getElapsedTime, getMask, getMaxProgressValue, getMinProgressValue, getNumberOfThreads, getProgress, getProgressChangeListener, getProgressChangeListeners, getProgressModulus, getProgressStep, getProgressValues, getSrcImage, isCompleted, isImage25D, isMultiThreadingEnabled, isRunningInSeparateThread, isThreadStopped, linkProgressToAlgorithm, linkProgressToAlgorithm, makeProgress, notifyListeners, removeListener, removeProgressChangeListener, run, setCompleted, setImage25D, setMask, setMaxProgressValue, setMinProgressValue, setMultiThreadingEnabled, setNumberOfThreads, setProgress, setProgressModulus, setProgressStep, setProgressValues, setProgressValues, setRunningInSeparateThread, setSrcImage, setStartTime, setThreadStopped, startMethod, windowActivated, windowClosed, windowClosing, windowDeactivated, windowDeiconified, windowIconified, windowOpened

Methods inherited from class java.lang.Thread

activeCount, checkAccess, clone, countStackFrames, currentThread, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, join, join, join, onSpinWait, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, start, stop, suspend, toString, yield

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

mask

static final int[] mask

offset

static final int[] offset

DEFAULT_NUM_TREE

final int DEFAULT_NUM_TREE

See Also:

Constant Field Values

DEFAULT_NUM_THREADS

final int DEFAULT_NUM_THREADS

See Also:

Constant Field Values

DEFAULT_IMPORTANCE_MODE

final StochasticForests.ImportanceMode DEFAULT_IMPORTANCE_MODE

DEFAULT_MIN_NODE_SIZE_CLASSIFICATION

final int DEFAULT_MIN_NODE_SIZE_CLASSIFICATION

See Also:

Constant Field Values

DEFAULT_MIN_NODE_SIZE_REGRESSION

final int DEFAULT_MIN_NODE_SIZE_REGRESSION

See Also:

Constant Field Values

DEFAULT_MIN_NODE_SIZE_SURVIVAL

final int DEFAULT_MIN_NODE_SIZE_SURVIVAL

See Also:

Constant Field Values

DEFAULT_MIN_NODE_SIZE_PROBABILITY

final int DEFAULT_MIN_NODE_SIZE_PROBABILITY

See Also:

Constant Field Values

DEFAULT_SPLITRULE

final StochasticForests.SplitRule DEFAULT_SPLITRULE

DEFAULT_ALPHA

final double DEFAULT_ALPHA

See Also:

Constant Field Values

DEFAULT_MINPROP

final double DEFAULT_MINPROP

See Also:

Constant Field Values

DEFAULT_PREDICTIONTYPE

final StochasticForests.PredictionType DEFAULT_PREDICTIONTYPE

DEFAULT_NUM_RANDOM_SPLITS

final int DEFAULT_NUM_RANDOM_SPLITS

See Also:

Constant Field Values

STATUS_INTERVAL

final double STATUS_INTERVAL

See Also:

Constant Field Values

Q_THRESHOLD

final double Q_THRESHOLD

See Also:

Constant Field Values

RAND_MAX

public static int RAND_MAX

logprop

public static double logprop

testUtility

private boolean testUtility

testMain

private boolean testMain

treetype

private StochasticForests.TreeType treetype

probability

private boolean probability

verbose_out

private boolean verbose_out

dependent_variable_name

private java.lang.String dependent_variable_name

memory_mode

private StochasticForests.MemoryMode memory_mode

input_file

private java.lang.String input_file

mtry

private int mtry

output_prefix

private java.lang.String output_prefix

num_trees

private int num_trees

seed

private long seed

num_threads

private int num_threads

load_forest_filename

private java.lang.String load_forest_filename

importance_mode

private StochasticForests.ImportanceMode importance_mode

min_node_size

private int min_node_size

split_select_weights_file

private java.lang.String split_select_weights_file

always_split_variable_names

private java.util.Vector<java.lang.String> always_split_variable_names

status_variable_name

private java.lang.String status_variable_name

sample_with_replacement

private boolean sample_with_replacement

unordered_variable_names

private java.util.Vector<java.lang.String> unordered_variable_names

memory_saving_splitting

private boolean memory_saving_splitting

splitrule

private StochasticForests.SplitRule splitrule

case_weights_file

private java.lang.String case_weights_file

predict_all

private boolean predict_all

sample_fraction

private double sample_fraction

alpha

private double alpha

minprop

private double minprop

holdout

private boolean holdout

prediction_type

private StochasticForests.PredictionType prediction_type

num_random_splits

private int num_random_splits

write

private boolean write

Constructor Detail

StochasticForests

public StochasticForests()

StochasticForests

public StochasticForests(StochasticForests.TreeType treetype,
                         boolean probability,
                         boolean verbose_out,
                         java.lang.String dependent_variable_name,
                         StochasticForests.MemoryMode memory_mode,
                         java.lang.String input_file,
                         int mtry,
                         java.lang.String output_prefix,
                         int num_trees,
                         long seed,
                         int num_threads,
                         java.lang.String load_forest_filename,
                         StochasticForests.ImportanceMode importance_mode,
                         int min_node_size,
                         java.lang.String split_select_weights_file,
                         java.util.Vector<java.lang.String> always_split_variable_names,
                         java.lang.String status_variable_name,
                         boolean sample_with_replacement,
                         java.util.Vector<java.lang.String> unordered_variable_names,
                         boolean memory_saving_splitting,
                         StochasticForests.SplitRule splitrule,
                         java.lang.String case_weights_file,
                         boolean predict_all,
                         double sample_fraction,
                         double alpha,
                         double minprop,
                         boolean holdout,
                         StochasticForests.PredictionType prediction_type,
                         int num_random_splits,
                         boolean write)

Method Detail

order

private java.util.Vector<java.lang.Integer> order(java.util.Vector<java.lang.Double> x,
                                                  boolean decreasing)

rank

java.util.Vector<java.lang.Double> rank(java.util.Vector<java.lang.Double> values)

Sample ranks starting from 1. Ties are given the average rank.

Parameters:

values - Values to rank

Returns:

Ranks of input values

roundToNextMultiple

private int roundToNextMultiple(int value,
                                int multiple)

shuffle

private void shuffle(java.util.Vector<java.lang.Integer> v,
                     java.util.Random random)

equalSplit

private void equalSplit(java.util.Vector<java.lang.Integer> result,
                        int start,
                        int end,
                        int num_parts)

loadDoubleVectorFromFile

void loadDoubleVectorFromFile(java.util.Vector<java.lang.Double> result,
                              java.lang.String filename)

drawWithoutReplacementSkip

private void drawWithoutReplacementSkip(java.util.Vector<java.lang.Integer> result,
                                        java.util.Random random,
                                        int max,
                                        java.util.Vector<java.lang.Integer> skip,
                                        int num_samples)

drawWithoutReplacementSimple

private void drawWithoutReplacementSimple(java.util.Vector<java.lang.Integer> result,
                                          java.util.Random random,
                                          int max,
                                          java.util.Vector<java.lang.Integer> skip,
                                          int num_samples)

drawWithoutReplacementFisherYates

private void drawWithoutReplacementFisherYates(java.util.Vector<java.lang.Integer> result,
                                               java.util.Random random,
                                               int max,
                                               java.util.Vector<java.lang.Integer> skip,
                                               int num_samples)

drawWithoutReplacementWeighted

private void drawWithoutReplacementWeighted(java.util.Vector<java.lang.Integer> result,
                                            java.util.Random random,
                                            java.util.Vector<java.lang.Integer> indices,
                                            int num_samples,
                                            java.util.Vector<java.lang.Double> weights)

drawWithoutReplacementWeighted

private void drawWithoutReplacementWeighted(java.util.Vector<java.lang.Integer> result,
                                            java.util.Random random,
                                            int max_index,
                                            int num_samples,
                                            java.util.Vector<java.lang.Double> weights)

mostFrequentClass

private int mostFrequentClass(java.util.Vector<java.lang.Integer> class_count,
                              java.util.Random random)

Returns the most frequent class index of a vector with counts for the classes. Returns a random class if counts are equal.

Parameters:

class_count - Vector with class counts

random_number_generator - Random number generator

Returns:

Most frequent class index. Out of range index if all 0.

mostFrequentDClass

private int mostFrequentDClass(java.util.Vector<java.lang.Double> class_count,
                               java.util.Random random)

Returns the most frequent class index of a vector with counts for the classes. Returns a random class if counts are equal.

Parameters:

class_count - Vector with class counts

random_number_generator - Random number generator

Returns:

Most frequent class index. Out of range index if all 0.

mostFrequentValue

private double mostFrequentValue(java.util.HashMap<java.lang.Double,java.lang.Integer> class_count,
                                 java.util.Random random)

computeConcordanceIndex

private double computeConcordanceIndex(StochasticForests.Data data,
                                       java.util.Vector<java.lang.Double> sum_chf,
                                       int dependent_varID,
                                       int status_varID,
                                       java.util.Vector<java.lang.Integer> sample_IDs)

uintToString

private java.lang.String uintToString(int number)

beautifyTime

private java.lang.String beautifyTime(int seconds)

splitString

private void splitString(java.util.Vector<java.lang.String> result,
                         java.lang.String input,
                         java.lang.String split_string)

shuffleAndSplit

private void shuffleAndSplit(java.util.Vector<java.lang.Integer> first_part,
                             java.util.Vector<java.lang.Integer> second_part,
                             int n_all,
                             int n_first,
                             java.util.Random random)

shuffleAndSplitAppend

private void shuffleAndSplitAppend(java.util.Vector<java.lang.Integer> first_part,
                                   java.util.Vector<java.lang.Integer> second_part,
                                   int n_all,
                                   int n_first,
                                   java.util.Vector<java.lang.Integer> mapping,
                                   java.util.Random random)

checkUnorderedVariables

private java.lang.String checkUnorderedVariables(StochasticForests.Data data,
                                                 java.util.Vector<java.lang.String> unordered_variable_names)

checkPositiveIntegers

private boolean checkPositiveIntegers(java.util.Vector<java.lang.Double> all_values)

maxstatPValueLau92

private double maxstatPValueLau92(double b,
                                  double minprop,
                                  double maxprop)

maxstatPValueLau94

private double maxstatPValueLau94(double b,
                                  double minprop,
                                  double maxprop,
                                  int N,
                                  java.util.Vector<java.lang.Integer> m)

maxstatPValueUnadjusted

private double maxstatPValueUnadjusted(double b)

dstdnorm

private double dstdnorm(double x)

pstdnorm

private double pstdnorm(double x)

erf

private double erf(double x)

adjustPvalues

private java.util.Vector<java.lang.Double> adjustPvalues(java.util.Vector<java.lang.Double> unadjusted_pvalues)

logrankScores

private java.util.Vector<java.lang.Double> logrankScores(java.util.Vector<java.lang.Double> time,
                                                         java.util.Vector<java.lang.Double> status)

maxstat

private void maxstat(java.util.Vector<java.lang.Double> scores,
                     java.util.Vector<java.lang.Double> x,
                     java.util.Vector<java.lang.Integer> indices,
                     double[] best_maxstat,
                     double[] best_split_value,
                     double minprop,
                     double maxprop)

numSamplesLeftOfCutpoint

private java.util.Vector<java.lang.Integer> numSamplesLeftOfCutpoint(java.util.Vector<java.lang.Double> x,
                                                                     java.util.Vector<java.lang.Integer> indices)

saveVector1D

private void saveVector1D(java.util.Vector<java.lang.Integer> vector,
                          java.io.BufferedWriter bw)

Write a 1d vector to filestream. First the size is written, then all vector elements.

Parameters:

vector - Vector of type T to save

file - ofstream object to write to.

saveBVector1D

private void saveBVector1D(java.util.Vector<java.lang.Boolean> vector,
                           java.io.BufferedWriter bw)

Write a 1d vector to filestream. First the size is written, then all vector elements.

Parameters:

vector - Vector of type T to save

file - ofstream object to write to.

readVector1D

private void readVector1D(java.util.Vector<java.lang.Integer> result,
                          java.io.BufferedReader br)

Read a 1d vector written by saveVector1D() from filestream.

Parameters:

result - Result vector with elements of type T.

file - ifstream object to read from.

readBVector1D

private void readBVector1D(java.util.Vector<java.lang.Boolean> result,
                           java.io.BufferedReader br)

Read a 1d vector written by saveVector1D() from filestream.

Parameters:

result - Result vector with elements of type T.

file - ifstream object to read from.

saveDVector1D

private void saveDVector1D(java.util.Vector<java.lang.Double> vector,
                           java.io.BufferedWriter bw)

Write a 1d vector to filestream. First the size is written, then all vector elements.

Parameters:

vector - Vector of type T to save

file - ofstream object to write to.

readDVector1D

private void readDVector1D(java.util.Vector<java.lang.Double> result,
                           java.io.BufferedReader br)

Read a 1d vector written by saveVector1D() from filestream.

Parameters:

result - Result vector with elements of type T.

file - ifstream object to read from.

saveVector2D

private void saveVector2D(java.util.Vector<java.util.Vector<java.lang.Integer>> vector,
                          java.io.BufferedWriter bw)

Write a 2d vector to filestream. First the size of the first dim is written as size_t, then for all inner vectors the size and elements.

Parameters:

vector - Vector of vectors of type T to write to file.

file - ofstream object to write to.

readVector2D

private void readVector2D(java.util.Vector<java.util.Vector<java.lang.Integer>> result,
                          java.io.BufferedReader br)

Read a 2d vector written by saveVector2D() from filestream.

Parameters:

result - Result vector of vectors with elements of type T.

file - ifstream object to read from.

saveDVector2D

private void saveDVector2D(java.util.Vector<java.util.Vector<java.lang.Double>> vector,
                           java.io.BufferedWriter bw)

Write a 2d vector to filestream. First the size of the first dim is written as size_t, then for all inner vectors the size and elements.

Parameters:

vector - Vector of vectors of type T to write to file.

file - ofstream object to write to.

readDVector2D

private void readDVector2D(java.util.Vector<java.util.Vector<java.lang.Double>> result,
                           java.io.BufferedReader br)

Read a 2d vector written by saveVector2D() from filestream.

Parameters:

result - Result vector of vectors with elements of type T.

file - ifstream object to read from.

equalVectorInteger

private boolean equalVectorInteger(java.util.Vector<java.lang.Integer> v1,
                                   java.util.Vector<java.lang.Integer> v2,
                                   java.lang.String str)

equalVectorVectorInteger

private boolean equalVectorVectorInteger(java.util.Vector<java.util.Vector<java.lang.Integer>> v1,
                                         java.util.Vector<java.util.Vector<java.lang.Integer>> v2,
                                         java.lang.String str)

equalVectorDouble

private boolean equalVectorDouble(java.util.Vector<java.lang.Double> v1,
                                  java.util.Vector<java.lang.Double> v2,
                                  java.lang.String str)

equalVectorVectorDouble

private boolean equalVectorVectorDouble(java.util.Vector<java.util.Vector<java.lang.Double>> v1,
                                        java.util.Vector<java.util.Vector<java.lang.Double>> v2,
                                        java.lang.String str)

expectNear

private boolean expectNear(double val1,
                           double val2,
                           double error,
                           java.lang.String str)

runAlgorithm

public void runAlgorithm()

Description copied from class: AlgorithmBase

Actually runs the algorithm. Implemented by inheriting algorithms.

Specified by:

runAlgorithm in class AlgorithmBase