﻿ LitDev API

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 LDIcon 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.