NativeFourierMethods (FsODE)

FsODE

Documentation for 0.0.2

NativeFourierMethods Type

Namespace: Altaxo.Calc.Fourier
Assembly: AltaxoCore.Redist.dll
Base Type: obj

This class provides reference methods related to Fourier transformation that are slow and not very accurate. Do not use them except for comparism and testing purposes! The direction of the forward Fourier transform will be defined here as reference for all other Fourier methods as multiplication of f(x)*exp(iwt), i.e. as (wt) having a positive sign (forward) and wt having a negative sign (backward).

Constructors

Constructor	Description
`NativeFourierMethods()` Full Usage: `NativeFourierMethods()`

Static members

Static member	Description
`NativeFourierMethods.ConvolutionCyclic(arr1, arr2, resultarr, count)` Full Usage: `NativeFourierMethods.ConvolutionCyclic(arr1, arr2, resultarr, count)` Parameters: arr1 : `float[]` - First array. arr2 : `float[]` - Second array. resultarr : `float[]` - The array that stores the correleation result. count : `int` - Number of points to correlate.	Performes a cyclic convolution between array arr1 and arr2 and stores the result in resultarr. Resultarr must be different from the other two arrays. arr1 : `float[]` First array. arr2 : `float[]` Second array. resultarr : `float[]` The array that stores the correleation result. count : `int` Number of points to correlate.
`NativeFourierMethods.ConvolutionCyclic(src1real, src1imag, src2real, src2imag, resultreal, resultimag, n)` Full Usage: `NativeFourierMethods.ConvolutionCyclic(src1real, src1imag, src2real, src2imag, resultreal, resultimag, n)` Parameters: src1real : `float[]` - First array (real part values). src1imag : `float[]` - First array (imaginary part values). src2real : `float[]` - Second array (real part values). src2imag : `float[]` - Second array (imaginary part values). resultreal : `float[]` - The array that stores the correlation result (real part values. resultimag : `float[]` - The array that stores the correlation result (imaginary part values. n : `int` - Number of points to correlate.	Performes a cyclic convolution between splitted complex arrays and stores the result in resultarr. Resultarr must be different from the input arrays. src1real : `float[]` First array (real part values). src1imag : `float[]` First array (imaginary part values). src2real : `float[]` Second array (real part values). src2imag : `float[]` Second array (imaginary part values). resultreal : `float[]` The array that stores the correlation result (real part values. resultimag : `float[]` The array that stores the correlation result (imaginary part values. n : `int` Number of points to correlate.
`NativeFourierMethods.ConvolutionNonCyclic(arr1, arr2, resultarr)` Full Usage: `NativeFourierMethods.ConvolutionNonCyclic(arr1, arr2, resultarr)` Parameters: arr1 : `float[]` - First array. arr2 : `float[]` - Second array. resultarr : `float[]` - The array that stores the convolution result.	Performes a non-cyclic convolution between array arr1 and arr2 and stores the result in resultarr. Resultarr must be different from the other two arrays. arr1 : `float[]` First array. arr2 : `float[]` Second array. resultarr : `float[]` The array that stores the convolution result.
`NativeFourierMethods.CorrelationCyclic(arr1, arr2, resultarr, count)` Full Usage: `NativeFourierMethods.CorrelationCyclic(arr1, arr2, resultarr, count)` Parameters: arr1 : `float[]` - First array (kernel). arr2 : `float[]` - Second array (data). resultarr : `float[]` - The array that stores the correlation result. count : `int` - Number of points to correlate.	Performes a cyclic correlation between array arr1 and arr2 and stores the result in resultarr. Resultarr must be different from the other two arrays. Correlation of src1 with src2 is not the same as correlation of src2 with src1. The correlation here is defined as corr(src1,src2)(j)=SUM(k) src1(k) src2(k+j). arr1 : `float[]` First array (kernel). arr2 : `float[]` Second array (data). resultarr : `float[]` The array that stores the correlation result. count : `int` Number of points to correlate.
`NativeFourierMethods.CorrelationCyclic(src1real, src1imag, src2real, src2imag, resultreal, resultimag, n)` Full Usage: `NativeFourierMethods.CorrelationCyclic(src1real, src1imag, src2real, src2imag, resultreal, resultimag, n)` Parameters: src1real : `float[]` - First array (kernel, real part values). src1imag : `float[]` - First array (kernel, imaginary part values). src2real : `float[]` - Second array (data, real part values). src2imag : `float[]` - Second array (data, imaginary part values). resultreal : `float[]` - The array that stores the correlation result (real part values. resultimag : `float[]` - The array that stores the correlation result (imaginary part values. n : `int` - Number of points to correlate.	Performes a cyclic correlation between splitted complex arrays and stores the result in resultarr. Resultarr must be different from the input arrays. Correlation of src1 with src2 is not the same as correlation of src2 with src1. The correlation here is defined as corr(src1,src2)(j)=SUM(k) src1(k) src2(k+j). src1real : `float[]` First array (kernel, real part values). src1imag : `float[]` First array (kernel, imaginary part values). src2real : `float[]` Second array (data, real part values). src2imag : `float[]` Second array (data, imaginary part values). resultreal : `float[]` The array that stores the correlation result (real part values. resultimag : `float[]` The array that stores the correlation result (imaginary part values. n : `int` Number of points to correlate.
`NativeFourierMethods.CorrelationNonCyclic(arr1, arr2, resultarr)` Full Usage: `NativeFourierMethods.CorrelationNonCyclic(arr1, arr2, resultarr)` Parameters: arr1 : `float[]` - First array. arr2 : `float[]` - Second array. resultarr : `float[]` - The array that stores the correlation result.	Performes a non-cyclic correlation between array arr1 and arr2 and stores the result in resultarr. Resultarr must be different from the other two arrays. arr1 : `float[]` First array. arr2 : `float[]` Second array. resultarr : `float[]` The array that stores the correlation result.
`NativeFourierMethods.FourierTransformation(arr, resultarr, count, direction)` Full Usage: `NativeFourierMethods.FourierTransformation(arr, resultarr, count, direction)` Parameters: arr : `float[]` - The double valued array to transform. resultarr : `Complex[]` - Used to store the result of the transformation. count : `int` - Number of points to transform. direction : `FourierDirection` - Direction of the Fourier transform.	Performs a native fouriertransformation of a real value array. arr : `float[]` The double valued array to transform. resultarr : `Complex[]` Used to store the result of the transformation. count : `int` Number of points to transform. direction : `FourierDirection` Direction of the Fourier transform.
`NativeFourierMethods.FourierTransformation(real, imag, direction)` Full Usage: `NativeFourierMethods.FourierTransformation(real, imag, direction)` Parameters: real : `float[]` - The real part of the array to transform. imag : `float[]` - The real part of the array to transform. direction : `FourierDirection` - Direction of the Fourier transform.	Performs a inline native fouriertransformation of real and imaginary part arrays. real : `float[]` The real part of the array to transform. imag : `float[]` The real part of the array to transform. direction : `FourierDirection` Direction of the Fourier transform.
`NativeFourierMethods.FourierTransformation(inputreal, inputimag, resultreal, resultimag, count, direction)` Full Usage: `NativeFourierMethods.FourierTransformation(inputreal, inputimag, resultreal, resultimag, count, direction)` Parameters: inputreal : `float[]` - The real part of the array to transform. inputimag : `float[]` - The real part of the array to transform. resultreal : `float[]` - Used to store the real part of the result of the transformation. May be equal to the input array. resultimag : `float[]` - Used to store the imaginary part of the result of the transformation. May be equal to the input array. count : `int` - Number of points to transform. direction : `FourierDirection` - Direction of the Fourier transform.	Performs a native Fourier transformation of a complex value array. inputreal : `float[]` The real part of the array to transform. inputimag : `float[]` The real part of the array to transform. resultreal : `float[]` Used to store the real part of the result of the transformation. May be equal to the input array. resultimag : `float[]` Used to store the imaginary part of the result of the transformation. May be equal to the input array. count : `int` Number of points to transform. direction : `FourierDirection` Direction of the Fourier transform.
`NativeFourierMethods.FourierTransformation(real, direction)` Full Usage: `NativeFourierMethods.FourierTransformation(real, direction)` Parameters: real : `float[]` - The real part of the array to transform. direction : `FourierDirection` - Direction of the Fourier transform.	Performs a inline native fouriertransformation of real and imaginary part arrays. real : `float[]` The real part of the array to transform. direction : `FourierDirection` Direction of the Fourier transform.
`NativeFourierMethods.FourierTransformation(inputreal, resultreal, count, direction)` Full Usage: `NativeFourierMethods.FourierTransformation(inputreal, resultreal, count, direction)` Parameters: inputreal : `float[]` - The real part of the array to transform. resultreal : `float[]` - Used to store the real part of the result of the transformation. May be equal to the input array. count : `int` - Number of points to transform. direction : `FourierDirection` - Direction of the Fourier transform.	Performs a native fouriertransformation of a real value array. inputreal : `float[]` The real part of the array to transform. resultreal : `float[]` Used to store the real part of the result of the transformation. May be equal to the input array. count : `int` Number of points to transform. direction : `FourierDirection` Direction of the Fourier transform.