edu.stanford.nlp.math
Class ArrayMath

java.lang.Object
  extended by edu.stanford.nlp.math.ArrayMath

public class ArrayMath
extends Object

Class ArrayMath

Author:
Teg Grenager

Method Summary
static double[] add(double[] a, double c)
           
static float[] add(float[] a, double c)
           
static void addInPlace(double[] a, double b)
          Increases the values in this array by b.
static void addInPlace(float[] a, double b)
          Increases the values in this array by b.
static void addMultInPlace(double[] a, double[] b, double c)
          Add c times the array b to array a.
static void addMultInto(double[] a, double[] b, double[] c, double d)
           
static int argmax_tieLast(double[] a)
           
static int argmax(double[] a)
           
static int argmax(float[] a)
           
static int argmax(int[] a)
           
static int argmin(double[] a)
           
static int argmin(float[] a)
           
static int argmin(int[] a)
           
static double average(double[] a)
           
static Double[] box(double[] assignment)
           
static Integer[] box(int[] assignment)
           
static int[][] castToInt(double[][] doubleCounts)
           
static boolean contains(int[] a, int i)
           
static boolean containsInSubarray(int[] a, int begin, int end, int i)
           
static double[] copyOf(double[] original, int newSize)
          Simulate Arrays.copyOf method provided by Java 6 When/if the JavaNLP-core code base moves past Java 5, this method can be removed
static int countCloseToZero(double[] v, double epsilon)
           
static int countInfinite(double[] v)
           
static int countNaN(double[] v)
           
static int countNegative(double[] v)
           
static int countNonZero(double[] v)
           
static int countPositive(double[] v)
           
static double[][] covariance(double[][] data)
           
static int[][] deepCopy(int[][] counts)
           
static int[] diag(int[][] a)
          Returns diagonal elements of the given (square) matrix.
static float[] doubleArrayToFloatArray(double[] a)
           
static float[][] doubleArrayToFloatArray(double[][] a)
           
static double[] exp(double[] a)
           
static void expInPlace(double[] a)
           
static double[] filterInfinite(double[] v)
           
static double[] filterNaN(double[] v)
           
static double[] filterNaNAndInfinite(double[] v)
           
static double[] floatArrayToDoubleArray(float[] a)
           
static double[][] floatArrayToDoubleArray(float[][] a)
           
static boolean hasInfinite(double[] a)
           
static boolean hasNaN(double[] a)
           
static int indexOf(int n, int[] a)
           
static double innerProduct(double[] a, double[] b)
           
static double innerProduct(float[] a, float[] b)
           
static double jensenShannonDivergence(double[] a, double[] b)
          Returns the Jensen Shannon divergence (information radius) between a and b, defined as the average of the kl divergences from a to b and from b to a.
static double klDivergence(double[] from, double[] to)
           
static double L1Norm(double[] a)
           
static void L1normalize(double[] a)
           
static double L2Norm(double[] a)
           
static double[][] load2DMatrixFromFile(String filename)
           
static double[] log(double[] a)
           
static void logInPlace(double[] a)
           
static void logNormalize(double[] a)
          Makes the values in this array sum to 1.0.
static double logSum(double[] logInputs)
          Returns the log of the sum of an array of numbers, which are themselves input in log form.
static double logSum(double[] logInputs, int fromIndex, int toIndex)
          Returns the log of the portion between fromIndex, inclusive, and toIndex, exclusive, of an array of numbers, which are themselves input in log form.
static float logSum(float[] logInputs)
          Returns the log of the sum of an array of numbers, which are themselves input in log form.
static double logSum(List<Double> logInputs)
           
static double logSum(List<Double> logInputs, int fromIndex, int toIndex)
           
static void main(String[] args)
          For testing only.
static int makeIntFromByte2(byte[] b, int offset)
           
static int makeIntFromByte4(byte[] b, int offset)
           
static double max(Collection<Double> a)
           
static double max(double[] a)
           
static float max(float[] a)
           
static int max(int[] a)
           
static int max(int[][] matrix)
          Returns the smallest element of the matrix
static double mean(double[] a)
           
static double median(double[] a)
           
static double min(double[] a)
           
static float min(float[] a)
           
static int min(int[] a)
           
static int min(int[][] matrix)
          Returns the smallest element of the matrix
static double[] multiply(double[] a, double c)
          Scales the values in this array by c.
static float[] multiply(float[] a, float c)
          Scales the values in this array by c.
static void multiplyInPlace(double[] a, double b)
          Scales the values in this array by b.
static void multiplyInPlace(float[] a, double b)
          Scales the values in this array by b.
static void multiplyInto(double[] a, double[] b, double c)
           
static double norm_1(double[] a)
          Computes 1-norm of vector
static double norm_1(float[] a)
          Computes 1-norm of vector
static double norm_inf(double[] a)
          Computes inf-norm of vector
static double norm_inf(float[] a)
          Computes inf-norm of vector
static double norm(double[] a)
          Computes 2-norm of vector
static double norm(float[] a)
          Computes 2-norm of vector
static void normalize(double[] a)
          Makes the values in this array sum to 1.0.
static void normalize(float[] a)
          Makes the values in this array sum to 1.0.
static int numRows(double[] v)
           
static double[] pairwiseAdd(double[] a, double[] b)
           
static float[] pairwiseAdd(float[] a, float[] b)
           
static int[] pairwiseAdd(int[] a, int[] b)
           
static void pairwiseAddInPlace(double[] to, double[] from)
           
static void pairwiseAddInPlace(double[] to, int[] from)
           
static void pairwiseAddInPlace(double[] to, short[] from)
           
static double[] pairwiseMultiply(double[] a, double[] b)
          Assumes that both arrays have same length.
static void pairwiseMultiply(double[] a, double[] b, double[] result)
          Puts the result in the result array.
static float[] pairwiseMultiply(float[] a, float[] b)
          Assumes that both arrays have same length.
static void pairwiseMultiply(float[] a, float[] b, float[] result)
          Puts the result in the result array.
static double[] pairwiseScaleAdd(double[] a, double[] b, double bScale)
           
static void pairwiseScaleAddInPlace(double[] to, double[] from, double fromScale)
           
static double[] pairwiseSubtract(double[] a, double[] b)
           
static float[] pairwiseSubtract(float[] a, float[] b)
           
static void pairwiseSubtractInPlace(double[] to, double[] from)
           
static double pearsonCorrelation(double[] x, double[] y)
          Direct computation of Pearson product-moment correlation coefficient.
static double[] pow(double[] a, double c)
          raises each entry in array a by power c
static float[] pow(float[] a, float c)
          raises each entry in array a by power c
static void powInPlace(double[] a, double c)
          Scales the values in this array by c.
static void powInPlace(float[] a, float c)
          Sets the values in this array by to their value taken to cth power.
static void reverse(int[] a)
           
static double safeMax(double[] v)
          Returns the largest value in a vector of doubles.
static double safeMean(double[] v)
          Returns the mean of a vector of doubles.
static double safeMin(double[] v)
          Returns the largest value in a vector of doubles.
static double safeStdev(double[] v)
          Returns the standard deviation of a vector of doubles.
static int sampleFromDistribution(double[] d)
          Samples from the distribution over values 0 through d.length given by d.
static int sampleFromDistribution(double[] d, Random random)
          Samples from the distribution over values 0 through d.length given by d.
static int sampleFromDistribution(float[] d, Random random)
          Samples from the distribution over values 0 through d.length given by d.
static void sampleWithoutReplacement(int[] array, int numArgClasses)
          Fills the array with sample from 0 to numArgClasses-1 without replacement.
static void sampleWithoutReplacement(int[] array, int numArgClasses, Random rand)
          Fills the array with sample from 0 to numArgClasses-1 without replacement.
static void setToLogDeterministic(double[] a, int i)
           
static void setToLogDeterministic(float[] a, int i)
           
static void shuffle(int[] a)
           
static void shuffle(int[] a, Random rand)
           
static double sigLevelByApproxRand(boolean[] A, boolean[] B)
           
static double sigLevelByApproxRand(boolean[] A, boolean[] B, int iterations)
           
static double sigLevelByApproxRand(double[] A, double[] B)
          Computes the significance level by approximate randomization, using a default value of 1000 iterations.
static double sigLevelByApproxRand(double[] A, double[] B, int iterations)
          Takes a pair of arrays, A and B, which represent corresponding outcomes of a pair of random variables: say, results for two different classifiers on a sequence of inputs.
static double sigLevelByApproxRand(int[] A, int[] B)
           
static double sigLevelByApproxRand(int[] A, int[] B, int iterations)
           
static double standardErrorOfMean(double[] a)
           
static void standardize(double[] a)
          Standardize values in this array, i.e., subtract the mean and divide by the standard deviation.
static double stdev(double[] a)
           
static int[] subArray(int[] a, int from, int to)
           
static double sum(double[] a)
          Returns the sum of an array of numbers.
static double sum(double[] a, int fromIndex, int toIndex)
          Returns the sum of the portion of an array of numbers between fromIndex, inclusive, and toIndex, exclusive.
static float sum(float[] a)
           
static int sum(int[] a)
           
static int sum(int[][] a)
           
static double sumSquared(double[] a)
           
static double sumSquaredError(double[] a)
           
static String toBinaryString(byte[] b)
           
static String toString(byte[] a)
           
static String toString(byte[] a, NumberFormat nf)
           
static String toString(double[] a)
           
static String toString(double[][] counts)
           
static String toString(double[][] counts, int cellSize, Object[] rowLabels, Object[] colLabels, NumberFormat nf, boolean printTotals)
           
static String toString(double[] a, NumberFormat nf)
           
static String toString(float[] a)
           
static String toString(float[][] counts)
           
static String toString(float[][] counts, int cellSize, Object[] rowLabels, Object[] colLabels, NumberFormat nf, boolean printTotals)
           
static String toString(float[] a, NumberFormat nf)
           
static String toString(int[] a)
           
static String toString(int[][] counts)
           
static String toString(int[][] counts, Object[] rowLabels, Object[] colLabels, int labelSize, int cellSize, NumberFormat nf, boolean printTotals)
           
static String toString(int[] a, NumberFormat nf)
           
static double[] unbox(Collection<Double> list)
           
static int[] unboxToInt(Collection<Integer> list)
           
static double variance(double[] a)
           
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Method Detail

numRows

public static int numRows(double[] v)

doubleArrayToFloatArray

public static float[] doubleArrayToFloatArray(double[] a)

floatArrayToDoubleArray

public static double[] floatArrayToDoubleArray(float[] a)

floatArrayToDoubleArray

public static double[][] floatArrayToDoubleArray(float[][] a)

doubleArrayToFloatArray

public static float[][] doubleArrayToFloatArray(double[][] a)

makeIntFromByte4

public static int makeIntFromByte4(byte[] b,
                                   int offset)

makeIntFromByte2

public static int makeIntFromByte2(byte[] b,
                                   int offset)

exp

public static double[] exp(double[] a)

log

public static double[] log(double[] a)

expInPlace

public static void expInPlace(double[] a)

logInPlace

public static void logInPlace(double[] a)

addInPlace

public static void addInPlace(double[] a,
                              double b)
Increases the values in this array by b. Does it in place.

Parameters:
a - The array
b - The amount by which to increase each item

addInPlace

public static void addInPlace(float[] a,
                              double b)
Increases the values in this array by b. Does it in place.

Parameters:
a - The array
b - The amount by which to increase each item

addMultInPlace

public static void addMultInPlace(double[] a,
                                  double[] b,
                                  double c)
Add c times the array b to array a. Does it in place.


multiplyInPlace

public static void multiplyInPlace(double[] a,
                                   double b)
Scales the values in this array by b. Does it in place.


multiplyInPlace

public static void multiplyInPlace(float[] a,
                                   double b)
Scales the values in this array by b. Does it in place.


powInPlace

public static void powInPlace(double[] a,
                              double c)
Scales the values in this array by c.


powInPlace

public static void powInPlace(float[] a,
                              float c)
Sets the values in this array by to their value taken to cth power.


add

public static double[] add(double[] a,
                           double c)

add

public static float[] add(float[] a,
                          double c)

multiply

public static double[] multiply(double[] a,
                                double c)
Scales the values in this array by c.


multiply

public static float[] multiply(float[] a,
                               float c)
Scales the values in this array by c.


pow

public static double[] pow(double[] a,
                           double c)
raises each entry in array a by power c


pow

public static float[] pow(float[] a,
                          float c)
raises each entry in array a by power c


pairwiseAddInPlace

public static void pairwiseAddInPlace(double[] to,
                                      double[] from)

pairwiseAddInPlace

public static void pairwiseAddInPlace(double[] to,
                                      int[] from)

pairwiseAddInPlace

public static void pairwiseAddInPlace(double[] to,
                                      short[] from)

pairwiseSubtractInPlace

public static void pairwiseSubtractInPlace(double[] to,
                                           double[] from)

pairwiseScaleAddInPlace

public static void pairwiseScaleAddInPlace(double[] to,
                                           double[] from,
                                           double fromScale)

pairwiseAdd

public static int[] pairwiseAdd(int[] a,
                                int[] b)

pairwiseAdd

public static double[] pairwiseAdd(double[] a,
                                   double[] b)

pairwiseAdd

public static float[] pairwiseAdd(float[] a,
                                  float[] b)

pairwiseScaleAdd

public static double[] pairwiseScaleAdd(double[] a,
                                        double[] b,
                                        double bScale)

pairwiseSubtract

public static double[] pairwiseSubtract(double[] a,
                                        double[] b)

pairwiseSubtract

public static float[] pairwiseSubtract(float[] a,
                                       float[] b)

pairwiseMultiply

public static double[] pairwiseMultiply(double[] a,
                                        double[] b)
Assumes that both arrays have same length.


pairwiseMultiply

public static float[] pairwiseMultiply(float[] a,
                                       float[] b)
Assumes that both arrays have same length.


pairwiseMultiply

public static void pairwiseMultiply(double[] a,
                                    double[] b,
                                    double[] result)
Puts the result in the result array. Assumes that all arrays have same length.


pairwiseMultiply

public static void pairwiseMultiply(float[] a,
                                    float[] b,
                                    float[] result)
Puts the result in the result array. Assumes that all arrays have same length.


hasNaN

public static boolean hasNaN(double[] a)

hasInfinite

public static boolean hasInfinite(double[] a)

countNaN

public static int countNaN(double[] v)

filterNaN

public static double[] filterNaN(double[] v)

countInfinite

public static int countInfinite(double[] v)

countNonZero

public static int countNonZero(double[] v)

countCloseToZero

public static int countCloseToZero(double[] v,
                                   double epsilon)

countPositive

public static int countPositive(double[] v)

countNegative

public static int countNegative(double[] v)

filterInfinite

public static double[] filterInfinite(double[] v)

filterNaNAndInfinite

public static double[] filterNaNAndInfinite(double[] v)

sum

public static double sum(double[] a)
Returns the sum of an array of numbers.


sum

public static double sum(double[] a,
                         int fromIndex,
                         int toIndex)
Returns the sum of the portion of an array of numbers between fromIndex, inclusive, and toIndex, exclusive. Returns 0 if fromIndex >= toIndex.


sum

public static int sum(int[] a)

sum

public static float sum(float[] a)

sum

public static int sum(int[][] a)

diag

public static int[] diag(int[][] a)
Returns diagonal elements of the given (square) matrix.


average

public static double average(double[] a)

norm_inf

public static double norm_inf(double[] a)
Computes inf-norm of vector

Parameters:
a - Array of double
Returns:
inf-norm of a

norm_inf

public static double norm_inf(float[] a)
Computes inf-norm of vector

Returns:
inf-norm of a

norm_1

public static double norm_1(double[] a)
Computes 1-norm of vector

Parameters:
a - A vector of double
Returns:
1-norm of a

norm_1

public static double norm_1(float[] a)
Computes 1-norm of vector

Parameters:
a - A vector of floats
Returns:
1-norm of a

norm

public static double norm(double[] a)
Computes 2-norm of vector

Parameters:
a - A vector of double
Returns:
Euclidean norm of a

norm

public static double norm(float[] a)
Computes 2-norm of vector

Parameters:
a - A vector of floats
Returns:
Euclidean norm of a

argmax

public static int argmax(double[] a)
Returns:
the index of the max value; if max is a tie, returns the first one.

argmax_tieLast

public static int argmax_tieLast(double[] a)
Returns:
the index of the max value; if max is a tie, returns the last one.

max

public static double max(double[] a)

max

public static double max(Collection<Double> a)

argmax

public static int argmax(float[] a)
Returns:
the index of the max value; if max is a tie, returns the first one.

max

public static float max(float[] a)

argmin

public static int argmin(double[] a)
Returns:
the index of the max value; if max is a tie, returns the first one.

min

public static double min(double[] a)

safeMin

public static double safeMin(double[] v)
Returns the largest value in a vector of doubles. Any values which are NaN or infinite are ignored. If the vector is empty, 0.0 is returned.


argmin

public static int argmin(float[] a)
Returns:
the index of the max value; if max is a tie, returns the first one.

min

public static float min(float[] a)

argmin

public static int argmin(int[] a)
Returns:
the index of the max value; if max is a tie, returns the first one.

min

public static int min(int[] a)

argmax

public static int argmax(int[] a)
Returns:
the index of the max value; if max is a tie, returns the first one.

max

public static int max(int[] a)

min

public static int min(int[][] matrix)
Returns the smallest element of the matrix


max

public static int max(int[][] matrix)
Returns the smallest element of the matrix


safeMax

public static double safeMax(double[] v)
Returns the largest value in a vector of doubles. Any values which are NaN or infinite are ignored. If the vector is empty, 0.0 is returned.


logSum

public static double logSum(double[] logInputs)
Returns the log of the sum of an array of numbers, which are themselves input in log form. This is all natural logarithms. Reasonable care is taken to do this as efficiently as possible (under the assumption that the numbers might differ greatly in magnitude), with high accuracy, and without numerical overflow.

Parameters:
logInputs - An array of numbers [log(x1), ..., log(xn)]
Returns:
log(x1 + ... + xn)

logSum

public static double logSum(double[] logInputs,
                            int fromIndex,
                            int toIndex)
Returns the log of the portion between fromIndex, inclusive, and toIndex, exclusive, of an array of numbers, which are themselves input in log form. This is all natural logarithms. Reasonable care is taken to do this as efficiently as possible (under the assumption that the numbers might differ greatly in magnitude), with high accuracy, and without numerical overflow. Throws an IllegalArgumentException if logInputs is of length zero. Otherwise, returns Double.NEGATIVE_INFINITY if fromIndex >= toIndex.

Parameters:
logInputs - An array of numbers [log(x1), ..., log(xn)]
fromIndex - the
Returns:
log(x1 + ... + xn)

logSum

public static double logSum(List<Double> logInputs)

logSum

public static double logSum(List<Double> logInputs,
                            int fromIndex,
                            int toIndex)

logSum

public static float logSum(float[] logInputs)
Returns the log of the sum of an array of numbers, which are themselves input in log form. This is all natural logarithms. Reasonable care is taken to do this as efficiently as possible (under the assumption that the numbers might differ greatly in magnitude), with high accuracy, and without numerical overflow.

Parameters:
logInputs - An array of numbers [log(x1), ..., log(xn)]
Returns:
log(x1 + ... + xn)

innerProduct

public static double innerProduct(double[] a,
                                  double[] b)

innerProduct

public static double innerProduct(float[] a,
                                  float[] b)

subArray

public static int[] subArray(int[] a,
                             int from,
                             int to)

load2DMatrixFromFile

public static double[][] load2DMatrixFromFile(String filename)
                                       throws IOException
Throws:
IOException

box

public static Integer[] box(int[] assignment)

unboxToInt

public static int[] unboxToInt(Collection<Integer> list)

box

public static Double[] box(double[] assignment)

unbox

public static double[] unbox(Collection<Double> list)

indexOf

public static int indexOf(int n,
                          int[] a)

castToInt

public static int[][] castToInt(double[][] doubleCounts)

normalize

public static void normalize(double[] a)
Makes the values in this array sum to 1.0. Does it in place. If the total is 0.0 or NaN, throws an RuntimeException.


L1normalize

public static void L1normalize(double[] a)

normalize

public static void normalize(float[] a)
Makes the values in this array sum to 1.0. Does it in place. If the total is 0.0 or NaN, throws an RuntimeException.


standardize

public static void standardize(double[] a)
Standardize values in this array, i.e., subtract the mean and divide by the standard deviation. If standard deviation is 0.0, throws an RuntimeException.


L2Norm

public static double L2Norm(double[] a)

L1Norm

public static double L1Norm(double[] a)

logNormalize

public static void logNormalize(double[] a)
Makes the values in this array sum to 1.0. Does it in place. If the total is 0.0, throws a RuntimeException. If the total is Double.NEGATIVE_INFINITY, then it replaces the array with a normalized uniform distribution. CDM: This last bit is weird! Do we really want that?


sampleFromDistribution

public static int sampleFromDistribution(double[] d)
Samples from the distribution over values 0 through d.length given by d. Assumes that the distribution sums to 1.0.

Parameters:
d - the distribution to sample from
Returns:
a value from 0 to d.length

sampleFromDistribution

public static int sampleFromDistribution(double[] d,
                                         Random random)
Samples from the distribution over values 0 through d.length given by d. Assumes that the distribution sums to 1.0.

Parameters:
d - the distribution to sample from
Returns:
a value from 0 to d.length

sampleFromDistribution

public static int sampleFromDistribution(float[] d,
                                         Random random)
Samples from the distribution over values 0 through d.length given by d. Assumes that the distribution sums to 1.0.

Parameters:
d - the distribution to sample from
Returns:
a value from 0 to d.length

klDivergence

public static double klDivergence(double[] from,
                                  double[] to)

jensenShannonDivergence

public static double jensenShannonDivergence(double[] a,
                                             double[] b)
Returns the Jensen Shannon divergence (information radius) between a and b, defined as the average of the kl divergences from a to b and from b to a.


setToLogDeterministic

public static void setToLogDeterministic(float[] a,
                                         int i)

setToLogDeterministic

public static void setToLogDeterministic(double[] a,
                                         int i)

mean

public static double mean(double[] a)

median

public static double median(double[] a)

safeMean

public static double safeMean(double[] v)
Returns the mean of a vector of doubles. Any values which are NaN or infinite are ignored. If the vector is empty, 0.0 is returned.


sumSquaredError

public static double sumSquaredError(double[] a)

sumSquared

public static double sumSquared(double[] a)

variance

public static double variance(double[] a)

stdev

public static double stdev(double[] a)

safeStdev

public static double safeStdev(double[] v)
Returns the standard deviation of a vector of doubles. Any values which are NaN or infinite are ignored. If the vector contains fewer than two values, 1.0 is returned.


standardErrorOfMean

public static double standardErrorOfMean(double[] a)

sampleWithoutReplacement

public static void sampleWithoutReplacement(int[] array,
                                            int numArgClasses)
Fills the array with sample from 0 to numArgClasses-1 without replacement.


sampleWithoutReplacement

public static void sampleWithoutReplacement(int[] array,
                                            int numArgClasses,
                                            Random rand)
Fills the array with sample from 0 to numArgClasses-1 without replacement.


shuffle

public static void shuffle(int[] a)

shuffle

public static void shuffle(int[] a,
                           Random rand)

reverse

public static void reverse(int[] a)

contains

public static boolean contains(int[] a,
                               int i)

containsInSubarray

public static boolean containsInSubarray(int[] a,
                                         int begin,
                                         int end,
                                         int i)

pearsonCorrelation

public static double pearsonCorrelation(double[] x,
                                        double[] y)
Direct computation of Pearson product-moment correlation coefficient. Note that if x and y are involved in several computations of pearsonCorrelation, it is perhaps more advisable to first standardize x and y, then compute innerProduct(x,y)/(x.length-1).


sigLevelByApproxRand

public static double sigLevelByApproxRand(double[] A,
                                          double[] B)
Computes the significance level by approximate randomization, using a default value of 1000 iterations. See documentation for other version of method.


sigLevelByApproxRand

public static double sigLevelByApproxRand(double[] A,
                                          double[] B,
                                          int iterations)
Takes a pair of arrays, A and B, which represent corresponding outcomes of a pair of random variables: say, results for two different classifiers on a sequence of inputs. Returns the estimated probability that the difference between the means of A and B is not significant, that is, the significance level. This is computed by "approximate randomization". The test statistic is the absolute difference between the means of the two arrays. A randomized test statistic is computed the same way after initially randomizing the arrays by swapping each pair of elements with 50% probability. For the given number of iterations, we generate a randomized test statistic and compare it to the actual test statistic. The return value is the proportion of iterations in which a randomized test statistic was found to exceed the actual test statistic.

Parameters:
A - Outcome of one r.v.
B - Outcome of another r.v.
Returns:
Significance level by randomization

sigLevelByApproxRand

public static double sigLevelByApproxRand(int[] A,
                                          int[] B)

sigLevelByApproxRand

public static double sigLevelByApproxRand(int[] A,
                                          int[] B,
                                          int iterations)

sigLevelByApproxRand

public static double sigLevelByApproxRand(boolean[] A,
                                          boolean[] B)

sigLevelByApproxRand

public static double sigLevelByApproxRand(boolean[] A,
                                          boolean[] B,
                                          int iterations)

toBinaryString

public static String toBinaryString(byte[] b)

toString

public static String toString(double[] a)

toString

public static String toString(double[] a,
                              NumberFormat nf)

toString

public static String toString(float[] a)

toString

public static String toString(float[] a,
                              NumberFormat nf)

toString

public static String toString(int[] a)

toString

public static String toString(int[] a,
                              NumberFormat nf)

toString

public static String toString(byte[] a)

toString

public static String toString(byte[] a,
                              NumberFormat nf)

toString

public static String toString(int[][] counts)

toString

public static String toString(int[][] counts,
                              Object[] rowLabels,
                              Object[] colLabels,
                              int labelSize,
                              int cellSize,
                              NumberFormat nf,
                              boolean printTotals)

toString

public static String toString(double[][] counts)

toString

public static String toString(double[][] counts,
                              int cellSize,
                              Object[] rowLabels,
                              Object[] colLabels,
                              NumberFormat nf,
                              boolean printTotals)

toString

public static String toString(float[][] counts)

toString

public static String toString(float[][] counts,
                              int cellSize,
                              Object[] rowLabels,
                              Object[] colLabels,
                              NumberFormat nf,
                              boolean printTotals)

main

public static void main(String[] args)
For testing only.

Parameters:
args - Ignored

deepCopy

public static int[][] deepCopy(int[][] counts)

covariance

public static double[][] covariance(double[][] data)

addMultInto

public static void addMultInto(double[] a,
                               double[] b,
                               double[] c,
                               double d)

multiplyInto

public static void multiplyInto(double[] a,
                                double[] b,
                                double c)

copyOf

public static double[] copyOf(double[] original,
                              int newSize)
Simulate Arrays.copyOf method provided by Java 6 When/if the JavaNLP-core code base moves past Java 5, this method can be removed

Parameters:
original -
newSize -


Stanford NLP Group