Package jdistlib.math

Class VectorMath

java.lang.Object

jdistlib.math.VectorMath

public class VectorMath
extends Object

Constructor Summary

Constructors

Constructor	Description
VectorMath()

Method Summary

Modifier and Type	Method	Description
static final double	aad(double[] e)	Average Absolute Deviation (AAD) (i.e., mean(abs(e - median(e))))
static final boolean	allEq(double[] e, double v)
static final boolean	allEqual(double[] e, double[] v)
static final boolean	allEqual(double[] a, double[] b, double tol)
static final boolean	allEqualScaled(double[] a, double[] b, double tol)
static final boolean	allFinite(double[] e)
static final boolean	allGt(double[] e, double v)
static final boolean	allLt(double[] e, double v)
static final double[]	as_numeric(Collection<String> ll)
static final double[]	cumsum(double[] e)
static final int[]	cumsum(int[] e)
static final double[]	diff(double[] e)
static final double[]	diff(double[] e, int lag)
static final double[]	diff(double[] e, int lag, int order)
static final double	distance(double[] e)	Euclidian distance / Root mean square
static final double	dot(double[] e, double[] w)	Weighted sum / Dot product
static final double	dot(double[] e, int[] w)	Weighted sum / Dot product
static final double	dot(int[] e, double[] w)	Weighted sum / Dot product
static final double	dot(int[] e, int[] w)	Weighted sum / Dot product
static final double	geom_mean(double[] e)	Geometric mean
static final double	geom_sd(double[] e)	Geometric standard deviation (per Bug #34 request)
static final double	harm_mean(double[] e)	Harmonic mean
static final double	iqr(double[] e)	Inter-quartile range (i.e., Q3 - Q1)
static final boolean	isEqual(double a, double b, double tol)
static final boolean	isEqualScaled(double a, double b, double tol)
static final boolean	isSorted(double[] a, boolean ascending)
static final double	log_prod(double[] e)	Log of product of numbers.
static final double	mad(double[] e)	Compute the Median Absolute Deviation (MAD) (i.e., median(abs(e - median(e))))
static final double	max(double[] e)
static final double	maxdev(double[] e)	Maximum deviation (i.e., max(abs(e - median(e))))
static final double	mean(double[] e)
static final double	median(double[] e)	Get the median
static final double	midhinge(double[] e)	Mid hinge.
static final double	midrange(double[] e)	Mid-range of e (i.e., (max(e) + min(e)) / 2)
static final double	min(double[] e)
static final double[]	pmax(double[] a, double[] b)
static final double[]	pmin(double[] a, double[] b)
static final double	prod(double[] e)	Product of numbers.
static final double	quantile(double[] sortedData, double quantile)	Find quantile given a sorted data of array (Definition 7)
static final double[]	quantile(double[] sortedData, double[] quantile)	Find quantile given a sorted data of array (Definition 7)
static final double	quantile0(double[] e, double quantile)	Find quantile in an array (Definition 7).
static final double[]	quantile0(double[] e, double[] quantile)	Find quantile in an array (Definition 7).
static final double[]	range(double[] e)
static final double	relativeDiff(double[] a, double[] b)
static final double	sd(double[] e)
static final double[]	standardize(double[] x)	Standardize the value in x (i.e., (x - mean(x)) / sd(x))
static final double	sum(double[] e)
static final double	sum(int[] e)
static final double	sum(Map<String,Integer> e)
static final double	sum_kahan(double[] e)
static final double[]	summary(double[] e)	Return summary statistics
static final Map<String,Integer>	table(double[] e)
static final <T> Map<String,Integer>	table(T[] e)
static final double	trimean(double[] e)	Trimean (Q1 + 2Q2 + Q3) / 4
static final double	trimmed_mean(double[] e, double lower, double upper)	Trimmed mean of values.
static final double[]	vabs(double[] e)
static final double	var(double[] e)
static final double[]	vcomp(double[] e)
static final double[]	vdiv(double[] a, double b)
static final double[]	vdiv(double[] a, double[] b)
static final double[]	vdiv(double a, double[] b)
static final double[]	vexp(double[] e)
static final double[]	vlog(double[] e)
static final double[]	vlog1pComps(double[] e)
static final double[]	vmin(double[] e)
static final double[]	vmin(double[] a, double b)
static final double[]	vmin(double[] a, double[] b)
static final double[]	vmin(double a, double[] b)
static final double[]	vplus(double[] a, double b)
static final double[]	vplus(double[] a, double[] b)
static final double[]	vplus(double a, double[] b)
static final double[]	vpow(double[] x, double e)
static final double[]	vpow(double[] x, double[] e)
static final double[]	vpow(double x, double[] e)
static final double[]	vpow(double x, int[] e)
static final double[]	vpow(int[] x, int[] e)
static final int[]	vsgn(double[] e)	Vector signum.
static final int[]	vsgn(int[] e)
static final double[]	vsignif(double[] e, int digits)
static final double[]	vsq(double[] a)
static final double[]	vtimes(double[] a, double b)
static final double[]	vtimes(double[] a, double[] b)
static final double[]	vtimes(double a, double[] b)
static final int	which_max(double[] e)
static final int	which_max(int[] e)
static final int	which_min(double[] e)
static final int	which_min(int[] e)
static final double	winsor_mean(double[] e, double lower, double upper)	Winsorized mean of values.

Methods inherited from class java.lang.Object

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

Constructor Details

VectorMath

public VectorMath()

Method Details

vpow

public static final double[] vpow(double x,
 double[] e)

vpow

public static final double[] vpow(double[] x,
 double e)

vpow

public static final double[] vpow(double[] x,
 double[] e)

vpow

public static final double[] vpow(int[] x,
 int[] e)

vpow

public static final double[] vpow(double x,
 int[] e)

vplus

public static final double[] vplus(double[] a,
 double[] b)

vplus

public static final double[] vplus(double a,
 double[] b)

vplus

public static final double[] vplus(double[] a,
 double b)

vmin

public static final double[] vmin(double[] e)

vmin

public static final double[] vmin(double[] a,
 double[] b)

vmin

public static final double[] vmin(double[] a,
 double b)

vmin

public static final double[] vmin(double a,
 double[] b)

vtimes

public static final double[] vtimes(double a,
 double[] b)

vtimes

public static final double[] vtimes(double[] a,
 double b)

vtimes

public static final double[] vtimes(double[] a,
 double[] b)

vsq

public static final double[] vsq(double[] a)

vdiv

public static final double[] vdiv(double[] a,
 double b)

vdiv

public static final double[] vdiv(double a,
 double[] b)

vdiv

public static final double[] vdiv(double[] a,
 double[] b)

vcomp

public static final double[] vcomp(double[] e)

vabs

public static final double[] vabs(double[] e)

vexp

public static final double[] vexp(double[] e)

vlog

public static final double[] vlog(double[] e)

vlog1pComps

public static final double[] vlog1pComps(double[] e)

vsignif

public static final double[] vsignif(double[] e,
 int digits)

vsgn

public static final int[] vsgn(double[] e)

Vector signum.

Parameters:

e -

Returns:

-1 if e[i] < 0; 0 if e[i] == 0; 1 if e[i] > 0

vsgn

public static final int[] vsgn(int[] e)

diff

public static final double[] diff(double[] e,
 int lag,
 int order)

diff

public static final double[] diff(double[] e,
 int lag)

diff

public static final double[] diff(double[] e)

allFinite

public static final boolean allFinite(double[] e)

allLt

public static final boolean allLt(double[] e,
 double v)

allGt

public static final boolean allGt(double[] e,
 double v)

allEq

public static final boolean allEq(double[] e,
 double v)

allEqual

public static final boolean allEqual(double[] e,
 double[] v)

quantile

public static final double quantile(double[] sortedData,
 double quantile)

Find quantile given a sorted data of array (Definition 7)

Parameters:

sortedData - This data is assumed to be presorted! Use quantile0 if you want to use unsorted data!

quantile - must be 0 <= quantile <= 1

Returns:

quantile value

quantile

public static final double[] quantile(double[] sortedData,
 double[] quantile)

Find quantile given a sorted data of array (Definition 7)

Parameters:

sortedData - This data is assumed to be presorted!

quantile -

Returns:

quantile values

quantile0

public static final double quantile0(double[] e,
 double quantile)

Find quantile in an array (Definition 7). Data is assumed to be unsorted

Parameters:

e -

quantile - must be 0 <= quantile <= 1

Returns:

quantile value

quantile0

public static final double[] quantile0(double[] e,
 double[] quantile)

Find quantile in an array (Definition 7). Data is assumed to be unsorted

Parameters:

e -

quantile - must be 0 <= quantile <= 1

Returns:

quantile values

mean

public static final double mean(double[] e)

distance

public static final double distance(double[] e)

Euclidian distance / Root mean square

Parameters:

e -

Returns:

sqrt(mean(e * e))

summary

public static final double[] summary(double[] e)

Return summary statistics

Parameters:

e -

Returns:

an array of 6 elements: Min, Q1, Median, Mean, Q3, Max

median

public static final double median(double[] e)

Get the median

Parameters:

e - does not need to be sorted

Returns:

median value

sd

public static final double sd(double[] e)

var

public static final double var(double[] e)

sum

public static final double sum(double[] e)

sum

public static final double sum(int[] e)

prod

public static final double prod(double[] e)

Product of numbers. Implemented as exp(sum(log(e))).

Parameters:

e -

Returns:

e[0] * e[1] * ... * e[n-1]

log_prod

public static final double log_prod(double[] e)

Log of product of numbers. Implemented as sum(log(e)).

Parameters:

e -

Returns:

log(e[0]) + log(e[1]) + ... + log(e[n-1])

geom_mean

public static final double geom_mean(double[] e)

Geometric mean

Parameters:

e -

geom_sd

public static final double geom_sd(double[] e)

Geometric standard deviation (per Bug #34 request)

Parameters:

e -

harm_mean

public static final double harm_mean(double[] e)

Harmonic mean

Parameters:

e -

dot

public static final double dot(double[] e,
 double[] w)

Weighted sum / Dot product

Parameters:

e -

w -

Returns:

sum(e * w)

dot

public static final double dot(int[] e,
 double[] w)

Weighted sum / Dot product

Parameters:

e -

w -

Returns:

sum(e * w)

dot

public static final double dot(double[] e,
 int[] w)

Weighted sum / Dot product

Parameters:

e -

w -

Returns:

sum(e * w)

dot

public static final double dot(int[] e,
 int[] w)

Weighted sum / Dot product

Parameters:

e -

w -

Returns:

sum(e * w)

trimmed_mean

public static final double trimmed_mean(double[] e,
 double lower,
 double upper)

Trimmed mean of values. Lower and upper are the percentile. For example: trimmed_mean(e, 0.25, 0.75) means average all values between 0.25 and 0.75 percentile inclusive.

Parameters:

e -

lower - must be between 0 and 1

upper - must be between 0 and 1

Returns:

trimmed mean.

winsor_mean

public static final double winsor_mean(double[] e,
 double lower,
 double upper)

Winsorized mean of values. Lower and upper are the percentile. For example: winsor_mean(e, 0.25, 0.75) means average all values between 0.25 and 0.75 percentile inclusive, the rest will be replaced by the boundary value (i.e., values lower than 0.25 percentile will be capped at 0.25 percentile and values higher than 0.75 percentile will be capped at 0.75 percentile).

Parameters:

e -

lower - must be between 0 and 1

upper - must be between 0 and 1

Returns:

winsorized mean.

sum_kahan

public static final double sum_kahan(double[] e)

sum

public static final double sum(Map<String,Integer> e)

mad

public static final double mad(double[] e)

Compute the Median Absolute Deviation (MAD) (i.e., median(abs(e - median(e))))

Parameters:

e - does not need to be sorted

Returns:

MAD value

aad

public static final double aad(double[] e)

Average Absolute Deviation (AAD) (i.e., mean(abs(e - median(e))))

Parameters:

e - does not need to be sorted

Returns:

AAD value

maxdev

public static final double maxdev(double[] e)

Maximum deviation (i.e., max(abs(e - median(e))))

Parameters:

e -

standardize

public static final double[] standardize(double[] x)

Standardize the value in x (i.e., (x - mean(x)) / sd(x))

Parameters:

x -

Returns:

standardized values

table

public static final Map<String,Integer> table(double[] e)

table

public static final <T> Map<String,Integer> table(T[] e)

as_numeric

public static final double[] as_numeric(Collection<String> ll)

cumsum

public static final double[] cumsum(double[] e)

cumsum

public static final int[] cumsum(int[] e)

max

public static final double max(double[] e)

min

public static final double min(double[] e)

midrange

public static final double midrange(double[] e)

Mid-range of e (i.e., (max(e) + min(e)) / 2)

Parameters:

e -

which_max

public static final int which_max(double[] e)

which_min

public static final int which_min(double[] e)

which_max

public static final int which_max(int[] e)

which_min

public static final int which_min(int[] e)

pmax

public static final double[] pmax(double[] a,
 double[] b)

pmin

public static final double[] pmin(double[] a,
 double[] b)

range

public static final double[] range(double[] e)

iqr

public static final double iqr(double[] e)

Inter-quartile range (i.e., Q3 - Q1)

Parameters:

e -

midhinge

public static final double midhinge(double[] e)

Mid hinge. (Q1 + Q3) / 2.0

Parameters:

e -

trimean

public static final double trimean(double[] e)

Trimean (Q1 + 2Q2 + Q3) / 4

Parameters:

e -

isEqual

public static final boolean isEqual(double a,
 double b,
 double tol)

isEqualScaled

public static final boolean isEqualScaled(double a,
 double b,
 double tol)

relativeDiff

public static final double relativeDiff(double[] a,
 double[] b)

allEqual

public static final boolean allEqual(double[] a,
 double[] b,
 double tol)

allEqualScaled

public static final boolean allEqualScaled(double[] a,
 double[] b,
 double tol)

isSorted

public static final boolean isSorted(double[] a,
 boolean ascending)