LitDev Extension API

LD3DView LDArray LDBits LDBlueTooth LDCall
LDChart LDClient LDClipboard LDColours LDCommPort
LDController LDControls LDCursors LDDataBase LDDateTime
LDDebug LDDialogs LDDictionary LDEffect LDEmail
LDEncryption LDEvents LDFastArray LDFastShapes LDFigures
LDFile LDFocus LDftp LDGraph LDGraphicsWindow
LDHID LDImage LDInline LDIOWarrior LDList
LDLogic LDMath LDMathX LDMatrix LDMusic
LDNetwork LDPhysics LDProcess LDQueue LDRegex
LDResources LDScrollBars LDSearch LDServer LDSettings
LDShapes LDShell LDSort LDSound LDSpeech
LDStatistics LDStopwatch LDText LDTextWindow LDTimer
LDTranslate LDUnits LDUtilities LDVector LDWaveForm
LDWebCam LDWindows LDxml LDZip

LDStatistics
Performs statistics on a 1D array of data.

Count Differentiate DistBinomial
DistNormal DistTriangular DistUniform
Frequency GeometricMean HarmonicMean
Integrate InterpolateX InterpolateY
Max Mean Median
Min Mode PDev
SDev SetArray Sum
Sum2

Count
The number of data points.

Differentiate(array)
Calculate the derivative of a 1D data array.
array The array to differentiate (array[x]=y).
returns A 1D array of the Derivative of the input array.

DistBinomial(n,p)
Create an array with a Binomial distribution.

This is like the probablity of getting k heads from 20 (n) coin tosses, with a probablity for each toss getting a heads of 0.5 (p).

n The number of tries.
p The probablity of success for each try.
returns A 1D array of the Binomial distribution, probablity of k successes (Array[k] = y).

DistNormal(distMean,distSTD,size)
Create an array with a Normal distribution.
distMean The mean of the distribution.
distSTD The standard deviation of the distribution.
size The number of points.
returns A 1D array of the Normal distribution (Array[x] = y).

DistTriangular(rangeMin,rangeMax,size)
Create an array with a Triangular distribution.
rangeMin The minimum value.
rangeMax The maximum value.
size The number of points.
returns A 1D array of the Triangular distribution (Array[x] = y).

DistUniform(rangeMin,rangeMax,size)
Create an array with a Uniform distribution.
rangeMin The minimum value.
rangeMax The maximum value.
size The number of points.
returns A 1D array of the Uniform distribution (Array[x] = y).

Frequency(array,bins,normalised)
Calculate a frequency distribution from array of data.
array The array to create the frequency distribution from.
bins The number of bins spanning the data.
normalised Is the frequency normalised to integrate to 1 ("True" or "False").
returns Frequency distribution as an array (array[bin]=frequency).

GeometricMean
The geometric mean of the data points (all points > 0).

HarmonicMean
The harmonic mean of the data points (all points > 0).

Integrate(array)
Calculate the integral of a 1D data array.
array The array to integrate (array[x]=y).
returns A 1D array of the Integral of the input array.

InterpolateX(array,y)
Interpolate a 1D data array to find the value of x(y).

The values of y should be monotonically increasing with x.

array The array to interpolate (array[x]=y).
y The value of y (may be an array of y values).
returns The interpolated value x or an array of x values.

InterpolateY(array,x)
Interpolate a 1D data array to find the value of y(x).

The values of x should be monotonically increasing.

array The array to interpolate (array[x]=y).
x The value of x (may be an array of x values).
returns The interpolated value y or an array of y values.

Max
The maximum value of the data points.

Mean
The arithmetic mean of the data points.

Median
The median of the data points.

Min
The minimum value of the data points.

Mode
The mode of the data points.

PDev
The population deviation of the data points.

SDev
The standard deviation of the data points.

SetArray(array)
Set a 1D array of numbers to perform some statistics on.

This command must be called before any statistics are calculated.

array The array to perform statistics on.
returns An array of the data sorted.

Sum
The sum of data points.

Sum2
The sum of the squares of the data points.