- MathNet.Numerics
- MathNet.Numerics.Differentiation
- MathNet.Numerics.Distributions
- MathNet.Numerics.Financial
- MathNet.Numerics.IntegralTransforms
- MathNet.Numerics.Integration
- MathNet.Numerics.Interpolation
- MathNet.Numerics.LinearAlgebra
- MathNet.Numerics.LinearAlgebra.Complex
- MathNet.Numerics.LinearAlgebra.Complex.Solvers
- MathNet.Numerics.LinearAlgebra.Complex32
- MathNet.Numerics.LinearAlgebra.Complex32.Solvers
- MathNet.Numerics.LinearAlgebra.Double
- MathNet.Numerics.LinearAlgebra.Double.Solvers
- MathNet.Numerics.LinearAlgebra.Factorization
- MathNet.Numerics.LinearAlgebra.Single
- MathNet.Numerics.LinearAlgebra.Single.Solvers
- MathNet.Numerics.LinearAlgebra.Solvers
- MathNet.Numerics.LinearAlgebra.Storage
- MathNet.Numerics.LinearRegression
- MathNet.Numerics.OdeSolvers
- MathNet.Numerics.Properties
- MathNet.Numerics.Providers.Common.Mkl
- MathNet.Numerics.Providers.FourierTransform
- MathNet.Numerics.Providers.FourierTransform.Mkl
- MathNet.Numerics.Providers.LinearAlgebra
- MathNet.Numerics.Providers.LinearAlgebra.Cuda
- MathNet.Numerics.Providers.LinearAlgebra.Mkl
- MathNet.Numerics.Providers.LinearAlgebra.OpenBlas
- MathNet.Numerics.Random
- MathNet.Numerics.RootFinding
- MathNet.Numerics.Statistics
- MathNet.Numerics.Statistics.Mcmc

- Combinatorics
- Complex32
- ComplexExtensions
- Constants
- Control
- Differentiate
- Distance
- Euclid
- Evaluate
- ExcelFunctions
- FindRoots
- Fit
- Generate
- GoodnessOfFit
- Integrate
- Interpolate
- InvalidParameterException
- IPrecisionSupport<T>
- MemoryAllocationException
- NativeInterfaceException
- NonConvergenceException
- NumericalBreakdownException
- Permutation
- Precision
- SingularUMatrixException
- Sorting
- SpecialFunctions
- TestFunctions
- Trig
- Window

**Type** Generate

**Namespace** MathNet.Numerics

- Fibonacci
- FibonacciSequence
- Gaussian
- GaussianSequence
- Impulse
- ImpulseSequence
- LinearRange
- LinearRange
- LinearRange
- LinearRangeInt32
- LinearRangeInt32
- LinearRangeMap<T>
- LinearSpaced
- LinearSpacedMap<T>
- LogSpaced
- LogSpacedMap<T>
- Map<TA, T>
- Map2<TA, TB, T>
- Map2Sequence<TA, TB, T>
- MapSequence<TA, T>
- Normal
- NormalSequence
- Periodic
- PeriodicImpulse
- PeriodicImpulseSequence
- PeriodicMap<T>
- PeriodicMapSequence<T>
- PeriodicSequence
- Random
- Random
- RandomComplex
- RandomComplex
- RandomComplex32
- RandomComplex32
- RandomMap<T>
- RandomMap2<T>
- RandomMap2Sequence<T>
- RandomMapSequence<T>
- RandomSingle
- RandomSingle
- Repeat<T>
- RepeatSequence<T>
- Sawtooth
- SawtoothSequence
- Sinusoidal
- SinusoidalSequence
- Square
- SquareSequence
- Stable
- StableSequence
- Standard
- StandardSequence
- Step
- StepSequence
- Triangle
- TriangleSequence
- Unfold<T, TState>
- UnfoldSequence<T, TState>
- Uniform
- UniformMap<T>
- UniformMap2<T>
- UniformMap2Sequence<T>
- UniformMapSequence<T>
- UniformSequence

Generate a Fibonacci sequence, including zero as first value.

Generate an infinite Fibonacci sequence, including zero as first value.

Create samples with independent amplitudes of normal distribution and a flat spectral density.
**Obsolete:** Use Normal instead. Will be removed in v4.

Create an infinite sample sequence with independent amplitudes of normal distribution and a flat spectral density.
**Obsolete:** Use NormalSequence instead. Will be removed in v4.

Create a Kronecker Delta impulse sample vector.
##### Parameters

`int`

lengthThe number of samples to generate.

`double`

amplitudeThe maximal reached peak.

`int`

delayOffset to the time axis. Zero or positive.

Create a Kronecker Delta impulse sample vector.
##### Parameters

`double`

amplitudeThe maximal reached peak.

`int`

delayOffset to the time axis, hence the sample index of the impulse.

Generate a linearly spaced sample vector within the inclusive interval (start, stop) and step 1.
Equivalent to MATLAB colon operator (:).

Generate a linearly spaced sample vector within the inclusive interval (start, stop) and the provided step.
The start value is aways included as first value, but stop is only included if it stop-start is a multiple of step.
Equivalent to MATLAB double colon operator (::).

Generate a linearly spaced sample vector within the inclusive interval (start, stop) and the provide step.
The start value is aways included as first value, but stop is only included if it stop-start is a multiple of step.
Equivalent to MATLAB double colon operator (::).

Generate a linearly spaced sample vector within the inclusive interval (start, stop) and the provided step.
The start value is aways included as first value, but stop is only included if it stop-start is a multiple of step.
Equivalent to MATLAB double colon operator (::).

Generate a linearly spaced sample vector within the inclusive interval (start, stop) and step 1.
Equivalent to MATLAB colon operator (:).

Generate samples by sampling a function at linearly spaced points within the inclusive interval (start, stop) and the provide step.
The start value is aways included as first value, but stop is only included if it stop-start is a multiple of step.

Generate a linearly spaced sample vector of the given length between the specified values (inclusive).
Equivalent to MATLAB linspace but with the length as first instead of last argument.

Generate samples by sampling a function at linearly spaced points between the specified values (inclusive).

Generate a base 10 logarithmically spaced sample vector of the given length between the specified decade exponents (inclusive).
Equivalent to MATLAB logspace but with the length as first instead of last argument.

Generate samples by sampling a function at base 10 logarithmically spaced points between the specified decade exponents (inclusive).

Generate samples by sampling a function at the provided points.

Generate samples by sampling a function at the provided points.

Generate a sample sequence by sampling a function at the provided point sequence.

Generate a sample sequence by sampling a function at the provided point sequence.

Create samples with independent amplitudes of normal distribution and a flat spectral density.

Create an infinite sample sequence with independent amplitudes of normal distribution and a flat spectral density.

Create a periodic wave.
##### Parameters

`int`

lengthThe number of samples to generate.

`double`

samplingRateSamples per time unit (Hz). Must be larger than twice the frequency to satisfy the Nyquist criterion.

`double`

frequencyFrequency in periods per time unit (Hz).

`double`

amplitudeThe length of the period when sampled at one sample per time unit. This is the interval of the periodic domain, a typical value is 1.0, or 2*Pi for angular functions.

`double`

phaseOptional phase offset.

`int`

delayOptional delay, relative to the phase.

Create a periodic Kronecker Delta impulse sample vector.
##### Parameters

`int`

lengthThe number of samples to generate.

`int`

periodimpulse sequence period.

`double`

amplitudeThe maximal reached peak.

`int`

delayOffset to the time axis. Zero or positive.

Create a Kronecker Delta impulse sample vector.
##### Parameters

`int`

periodimpulse sequence period.

`double`

amplitudeThe maximal reached peak.

`int`

delayOffset to the time axis. Zero or positive.

Create a periodic wave.
##### Parameters

`int`

lengthThe number of samples to generate.

`Func<double, T>`

mapThe function to apply to each of the values and evaluate the resulting sample.

`double`

samplingRateSamples per time unit (Hz). Must be larger than twice the frequency to satisfy the Nyquist criterion.

`double`

frequencyFrequency in periods per time unit (Hz).

`double`

amplitudeThe length of the period when sampled at one sample per time unit. This is the interval of the periodic domain, a typical value is 1.0, or 2*Pi for angular functions.

`double`

phaseOptional phase offset.

`int`

delayOptional delay, relative to the phase.

Create an infinite periodic wave sequence.
##### Parameters

`Func<double, T>`

mapThe function to apply to each of the values and evaluate the resulting sample.

`double`

samplingRateSamples per time unit (Hz). Must be larger than twice the frequency to satisfy the Nyquist criterion.

`double`

frequencyFrequency in periods per time unit (Hz).

`double`

amplitudeThe length of the period when sampled at one sample per time unit. This is the interval of the periodic domain, a typical value is 1.0, or 2*Pi for angular functions.

`double`

phaseOptional phase offset.

`int`

delayOptional delay, relative to the phase.

Create an infinite periodic wave sequence.
##### Parameters

Samples per time unit (Hz). Must be larger than twice the frequency to satisfy the Nyquist criterion.

The length of the period when sampled at one sample per time unit. This is the interval of the periodic domain, a typical value is 1.0, or 2*Pi for angular functions.

`double`

samplingRate`double`

frequencyFrequency in periods per time unit (Hz).

`double`

amplitude`double`

phaseOptional phase offset.

`int`

delayOptional delay, relative to the phase.

Create random samples.

Create an infinite random sample sequence.

Create an infinite random sample sequence.

Create random samples.

Create an infinite random sample sequence.

Create random samples.

Generate samples by sampling a function at samples from a probability distribution.

Generate samples by sampling a function at sample pairs from a probability distribution.

Generate a sample sequence by sampling a function at sample pairs from a probability distribution.

Generate a sample sequence by sampling a function at samples from a probability distribution.

Create an infinite random sample sequence.

Create random samples.

Create an array with each field set to the same value.
##### Parameters

`int`

lengthThe number of samples to generate.

`T`

valueThe value that each field should be set to.

Create an infinite sequence where each element has the same value.
##### Parameters

`T`

valueThe value that each element should be set to.

Create a periodic sawtooth wave, starting with the lowest sample.
##### Parameters

`int`

lengthThe number of samples to generate.

`int`

periodNumber of samples a full sawtooth period.

`double`

lowValueLowest sample value.

`double`

highValueHighest sample value.

`int`

delayOptional delay.

Create an infinite periodic sawtooth wave sequence, starting with the lowest sample.
##### Parameters

`int`

periodNumber of samples a full sawtooth period.

`double`

lowValueLowest sample value.

`double`

highValueHighest sample value.

`int`

delayOptional delay.

Create a Sine wave.
##### Parameters

Samples per time unit (Hz). Must be larger than twice the frequency to satisfy the Nyquist criterion.

`int`

lengthThe number of samples to generate.

`double`

samplingRate`double`

frequencyFrequency in periods per time unit (Hz).

`double`

amplitudeThe maximal reached peak.

`double`

meanThe mean, or DC part, of the signal.

`double`

phaseOptional phase offset.

`int`

delayOptional delay, relative to the phase.

Create an infinite Sine wave sequence.
##### Parameters

`double`

samplingRateSamples per unit.

`double`

frequencyFrequency in samples per unit.

`double`

amplitudeThe maximal reached peak.

`double`

meanThe mean, or DC part, of the signal.

`double`

phaseOptional phase offset.

`int`

delayOptional delay, relative to the phase.

Create a periodic square wave, starting with the high phase.
##### Parameters

`int`

lengthThe number of samples to generate.

`int`

highDurationNumber of samples of the high phase.

`int`

lowDurationNumber of samples of the low phase.

`double`

lowValueSample value to be emitted during the low phase.

`double`

highValueSample value to be emitted during the high phase.

`int`

delayOptional delay.

Create an infinite periodic square wave sequence, starting with the high phase.
##### Parameters

`int`

highDurationNumber of samples of the high phase.

`int`

lowDurationNumber of samples of the low phase.

`double`

lowValueSample value to be emitted during the low phase.

`double`

highValueSample value to be emitted during the high phase.

`int`

delayOptional delay.

Create skew alpha stable samples.
**Obsolete:** Will be removed in v4.
##### Parameters

`int`

lengthThe number of samples to generate.

`double`

alphaStability alpha-parameter of the stable distribution

`double`

betaSkewness beta-parameter of the stable distribution

`double`

scaleScale c-parameter of the stable distribution

`double`

locationLocation mu-parameter of the stable distribution

Create skew alpha stable samples.
**Obsolete:** Will be removed in v4.
##### Parameters

`double`

alphaStability alpha-parameter of the stable distribution

`double`

betaSkewness beta-parameter of the stable distribution

`double`

scaleScale c-parameter of the stable distribution

`double`

locationLocation mu-parameter of the stable distribution

Create samples with independent amplitudes of standard distribution.

Create an infinite sample sequence with independent amplitudes of standard distribution.

Create a Heaviside Step sample vector.
##### Parameters

`int`

lengthThe number of samples to generate.

`double`

amplitudeThe maximal reached peak.

`int`

delayOffset to the time axis.

Create an infinite Heaviside Step sample sequence.
##### Parameters

`double`

amplitudeThe maximal reached peak.

`int`

delayOffset to the time axis.

Create a periodic triangle wave, starting with the raise phase from the lowest sample.
##### Parameters

`int`

lengthThe number of samples to generate.

`int`

raiseDurationNumber of samples of the raise phase.

`int`

fallDurationNumber of samples of the fall phase.

`double`

lowValueLowest sample value.

`double`

highValueHighest sample value.

`int`

delayOptional delay.

Create an infinite periodic triangle wave sequence, starting with the raise phase from the lowest sample.
##### Parameters

`int`

raiseDurationNumber of samples of the raise phase.

`int`

fallDurationNumber of samples of the fall phase.

`double`

lowValueLowest sample value.

`double`

highValueHighest sample value.

`int`

delayOptional delay.

Generate samples generated by the given computation.

Generate an infinite sequence generated by the given computation.

Create random samples, uniform between 0 and 1.
Faster than other methods but with reduced guarantees on randomness.

Generate samples by sampling a function at samples from a probability distribution, uniform between 0 and 1.
Faster than other methods but with reduced guarantees on randomness.

Generate samples by sampling a function at sample pairs from a probability distribution, uniform between 0 and 1.
Faster than other methods but with reduced guarantees on randomness.

Generate a sample sequence by sampling a function at sample pairs from a probability distribution, uniform between 0 and 1.
Faster than other methods but with reduced guarantees on randomness.

Generate a sample sequence by sampling a function at samples from a probability distribution, uniform between 0 and 1.
Faster than other methods but with reduced guarantees on randomness.

Create an infinite random sample sequence, uniform between 0 and 1.
Faster than other methods but with reduced guarantees on randomness.