Class ClampedCubicSpline represents a function determined by tabulated values. Function values are calculated using clamped cubic spline interpolation.

Class ClosedInterval represents a numeric interval with inclusive lower and upper bounds.

Class ClosedOpenInterval represents a numeric interval with an inclusive lower bound and an exclusive upper bound.

Abstract base class for all concrete convolution classes.

Abstract base class for all concrete correlation classes.

The base correlation filter which provides basic correlation services.

Class CublicSpline represents a function whose values are determined by cubic spline interpolation between tabulated values.

Double1DConvolution represents a 1D convolution, with a specified kernel and data length.

Double1DCorrelation represents a 1D correlation, with a specified kernel and data length.

DoubleComplex1DConvolution represents a 1D convolution, with a specified kernel and data length.

DoubleComplex1DCorrelation represents a 1D correlation, with a specified kernel and data length.

DoubleComplexBackward1DFFT represents the backward discrete fourier transform of a 1D complex signal vector.

DoubleComplexBackward2DFFT represents the backward discrete fourier transform of a 2D complex signal vector.

The DoubleComplexDataBlock struct defines a contiguous subset of an array of DoubleComplex numbers. A DoubleComplexDataBlock instance contains a reference to an array and an offset into the array.

DoubleComplexForward1DFFT represents the forward discrete fourier transform of a 1D complex signal vector.

DoubleComplexForward2DFFT represents the forward discrete fourier transform of a 2D complex signal vector.

Class DoubleComplexLeastSquares computes the minimum-norm solution to a linear system Ax = y.

Class DoubleComplexLUFact represents the LU factorization of a matrix of DoubleComplex numbers.

Class DoubleComplexMatrix represents a general mathematical matrix class of DoubleComplex numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.

Class DoubleComplexVector represents a mathematical vector of DoubleComplex numbers.

The DoubleDataBlock struct defines a contiguous subset of an array of double-precision floating point numbers. A DoubleDataBlock instance contains a reference to an array and an offset into the array.

DoubleForward1DFFT represents the forward discrete fourier transform of a 1D real signal vector.

DoubleForward2DFFT represents the forward discrete fourier transform of a 2D real signal vector.

Class DoubleFunctional represents a double precision functional.

Class DoubleFunctionalDelegate wraps a functional delegate specified by a delegate in a DoubleFunctional object.

General 1D FFT class assuming the behavior of the provided FFT configuration instance.

Class DoubleLeastSquares computes the minimum-norm solution to a linear system Ax = y.

Class DoubleLUFact represents the LU factorization of a matrix of double-precision floating point numbers.

Class DoubleMatrix represents a general mathematical matrix class of double-precision floating point numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.

Abstract class for representing a multi-variable function.

Class DoubleNonnegativeLeastSquares computes the minimum-norm solution to a linear system Ax = y subject to the constraint that all the elements, x[i], are nonnegative.

Class which creates a DoubleParameterizedFunction instance from delegates.

Abstract class representing a parameterized function.

Abstract class representing a parameterized functional.

Class DoubleRandomBetaDistribution generates random numbers from a beta distribution.

Class DoubleRandomCauchyDistribution generates random numbers from a Cauchy distribution.

Class DoubleRandomExponentialDistribution generates random numbers from an exponential distribution.

Class DoubleRandomGammaDistribution generates random numbers from a gamma distribution.

Class DoubleRandomGaussianDistribution generates random numbers from a Gaussian distribution.

Class DoubleRandomGumbelDistribution generates random numbers from a Gumbel distribution.

Class DoubleRandomLaplaceDistribution generates random numbers from a Laplace distribution.

Class DoubleRandomLogNormalDistribution generates random numbers from a lognormal distribution.

Class DoubleRandomRayleighDistribution generates random numbers from an Rayleigh distribution.

Class DoubleRandomUniformDistribution generates random numbers uniformly distributed over an interval.

Class DoubleRandomWeibullDistribution generates random numbers from a Weibull distribution.

Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 2D FFT's of real signals.

DoubleSymmetricBackward1DFFT represents the backward discrete fourier transform of a 1D real signal vector, and inverses packed conjugate symmetric signals back to the real domain.

Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 1D FFT's of real signals.

Class DoubleVector represents a mathematical vector of double-precision floating point numbers.

Class DoubleVectorParameterizedDelegate creates a DoubleParameterizedFunctional instance from delegates.

Abstract base class for all 2D discrete FFT transform classes. This class manages the setup and tear down of all discrete fourier resources.

Abstract base class for all 1D discrete FFT transform classes. This class manages the setup and tear down of all discrete fourier resources.

FFTConfiguration contains all of the FFT configuration state to efficiently compute a FFT. This class is typically used in conjunction with the GeneralxDFFT set of classes to configure FFT's with offset and strided signal data.

Exception thrown when MKL returns an error condition when computing as FFT

Float1DConvolution represents a 1D convolution, with a specified kernel and data length.

Float1DCorrelation represents a 1D correlation, with a specified kernel and data length.

FloatComplex1DConvolution represents a 1D convolution, with a specified kernel and data length.

FloatComplex1DCorrelation represents a 1D correlation, with a specified kernel and data length.

FloatComplexBackward1DFFT represents the backward discrete fourier transform of a 1D complex signal vector.

FloatComplexBackward2DFFT represents the backward discrete fourier transform of a 2D complex signal vector.

The FloatComplexDataBlock struct defines a contiguous subset of an array of FloatComplex numbers. A FloatComplexDataBlock instance contains a reference to an array and an offset into the array.

FloatComplexForward1DFFT represents the forward discrete fourier transform of a 1D complex signal vector.

FloatComplexForward2DFFT represents the forward discrete fourier transform of a 2D complex signal vector.

Class FloatComplexLeastSquares computes the minimum-norm solution to a linear system Ax = y.

Class FloatComplexFact represents the LU factorization of a matrix of FloatComplex numbers.

Class FloatComplexMatrix represents a general mathematical matrix class of FloatComplex numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.

Class FloatComplexVector represents a mathematical vector of FloatComplex numbers.

The FloatDataBlock struct defines a contiguous subset of an array of floating point numbers. A FloatDataBlock instance contains a reference to an array, and an offset into the array.

FloatForward1DFFT represents the forward discrete fourier transform of a 1D real signal vector.

FloatForward2DFFT represents the forward discrete fourier transform of a 2D real signal vector.

General 1D FFT class assuming the behavior of the provided FFT configuration instance.

Class FloatLeastSquares computes the minimum-norm solution to a linear system Ax = y.

Class FloatLUFact represents the LU factorization of a matrix of floating point numbers.

Class FloatMatrix represents a general mathematical matrix class of floating point numbers. Methods are provided for performing algebraic operations, data manipulation, and slicing.

Class FloatNonnegativeLeastSquares computes the minimum-norm solution to a linear system Ax = y subject to the constraint that all the elements, x[i], are nonnegative.

Class FloatRandomBetaDistribution generates random numbers from a beta distribution.

Class FloatRandomCauchyDistribution generates random numbers from a Cauchy distribution.

Class FloatRandomExponentialDistribution generates random numbers from an exponential distribution.

Class FloatRandomGammaDistribution generates random numbers from a gamma distribution.

Class FloatRandomGaussianDistribution generates random numbers from a Gaussian distribution.

Class FloatRandomGumbelDistribution generates random numbers from a Gumbel distribution.

Class FloatRandomLaplaceDistribution generates random numbers from a Laplace distribution.

Class FloatRandomLogNormalDistribution generates random numbers from a lognormal distribution.

Class FloatRandomRayleighDistribution generates random numbers from an Rayleigh distribution.

Class DoubleRandomUniformDistribution generates random numbers uniformly distributed over an interval.

Class FloatRandomWeibullDistribution generates random numbers from a Weibull distribution.

Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 2D FFT's of real signals.

FloatSymmetricBackward1DFFT represents the backward discrete fourier transform of a 1D real signal vector, and inverses packed conjugate symmetric signals back to the real domain.

Provides symmetric complex conjugate signal unpacking services. Typically used for unpacking 1D FFT's of real signals.

Class FloatVector represents a mathematical vector of floating point numbers.

Class GaussKronrod21Integrator calculates an approximation of the integral of a function over a finite interval using the Gauss 10-point and the Kronrod 21-point rule.

Class GaussKronrod43Integrator calculates an approximation of the integral of a function over a finite interval using the Gauss 21-point and the Kronrod 43-point rule.

Class GaussKronrod87Integrator calculates an approximation of the integral of a function over a finite interval using the Gauss 43-point and the Kronrod 87-point rule.

Class GaussKronrodIntegrator calculates an approximation of the integral of a function over a finite interval using Gauss-Kronrod rules.

Class Histogram constructs and maintains a histogram of input data. Input data is sorted into bins and a count is kept of how many data points fall into each bin.

Base class for creating streams of independent random numbers. Deriving classes must construct the streams_ array.

Exception thrown when an out of range index is passed to an NMath function.

Class Interval represents a numeric interval with inclusive or exclusive lower and upper bounds.

Class IntRandomBernoulliDistribution generates random numbers from a discrete binomial distribution.

Class IntRandomBinomialDistribution generates random numbers from a discrete binomial distribution.

Class IntRandomGeometricDistribution generates random numbers from a discrete geometric distribution.

Class IntRandomHypergeometricDistribution generates random numbers from a discrete hypergeometric distribution.

Class IntRandomNegativeBinomialDistribution generates random numbers from a discrete negative binomial distribution.

Class IntRandomPoissonDistribution generates random numbers from a discrete Poisson distribution.

Class IntRandomPoissonVaryingMeanDistribution generates random numbers from a discrete Poisson distribution with varying mean.

Class IntRandomUniformBitsDistribution generates integer values with uniform bit distribution.

Class IntRandomUniformDistribution generates random numbers uniformly distributed over an interval.

Exception thrown when an invalid argument is passed to an NMath function.

Exception thrown when a histogram operation results in invalid bin boundaries.

Exception thrown when NMath cannot load a kernel assembly.

Class LeapfrogRandomStreams creates several independent streams of random numbers using the method know as leapfrogging.

Class LeapfrogStream represents a single leapfrog stream.

Class LinearSpline represents a function whose values are determined by linear interpolation between tabulated values.

Exception thrown when a matrix operation requiring a square matrix is presented with a non-square one.

Exception thrown when an operation is performed with operands whose sizes are incompatible with the operation.

Class implementing data filtering by replacing data points f(i) with a linear combination of the data points immediately to the left and right of f(i). The user provides the coefficients to use in the linear combination. Static class methods are provided for generating coefficients to implement a moving average filter and a Savitzky-Golay smoothing filter.

Class NaturalCubicSpline represents a function determined by tabulated values. Function values are calculated using natural cubic spline interpolation.

Class NiederreiterQuasiRandomGenerator is a quasi-random number generator which can be used for generating sequences of quasi-random point in n-dimensional space.

Base class for exceptions thrown by the NMath product suite.

Exception thrown when a method encounters a faulty text representation.

Class NMathFunctions provides standard mathematical functions for NMath types. Trigonometric functions, exponents, logarithms, powers, and square roots are provided for vector, matrix, and complex number types.

Class OneVariableFunction represents functions of one variable.

Class OpenClosedInterval represents a numeric interval with an exclusive lower bound and an inclusive upper bound.

Class OpenInterval represents a numeric interval with exclusive lower and upper bounds.

Abstract base class for all peak finding algorithms. The class is an enumerable collection of all found peaks.

Class PeakFinderSavitzkyGolay uses smooth Savitzky-Golay derivatives to find peaks in data and acts as a collection for the found peaks.

Class Polynomial represents a polynomial function as a vector of coefficients.

Class PolynomialDifferentiator encapsulates exact differentiation of polynomials.

Class PolynomialIntegration encapsulates exact integration of polynomials.

Abstract base class for generating sequences of quasirandom points. A quasirandom sequence is a sequence of n-tuples that fills n-space more uniformly than uncorrelated random points.

Class RandGenBeta generates random numbers from a beta distribution.

Class RandGenBinomial generates random numbers from a binomial distribution.

Class RandGenExponential generates random numbers from an exponential distribution.

Class RandGenGamma generates random numbers from an gamma distribution.

Class RandGenGeometric generaties random numbers from a Geometric distribution.

Class RandGenJohnson generates random numbers from a Johnson distribution.

Class RandGenLogNormal generates random numbers from a lognormal distribution.

Class RandGenMTwist generates random numbers from a uniform distribution using the Mersenne Twister algorithm.

Class RandGenNormal generates random numbers from a normal distribution.

Class RandGenPareto generates random numbers from a Pareto distribution.

Class RandGenPoisson generates random numbers from an Poisson distribution.

Class RandGenTriangular generates random numbers from a triangular distribution.

Class RandGenUniform generates random numbers from a uniform distribution.

Class RandGenWeibull generates random numbers from a Weibull distribution.

Abstract base class for NMath random number generators.

Class RandomNumbers is an adapter for the RandomNumberStream class to give the same behavior as a scalar-type random number generator.

Class RandomNumberStream is a vectorized random number generator which yields a stream of random numbers from various probability distributions.

Class Range represents a collection of indices that can be used to view a subset of data from another data structure. A Range is defined by a starting index, an ending index or enumerated Position value, and a step increment called the stride.

Class RidderDifferentiator encapsulates numerical differentiation of functions.

Class RombergIntegrator approximates integrals of functions over a given interval using the Romberg method.

Class generates the Savitzy-Golay filter coefficients for smoothing data or computing smoothed derivatives. Smoothed derivatives can be found up to the order of the fitting polynomial.

Class SavitzkyGolayFilter is a correlation filter specialized for filtering with Savitzky-Golay coefficients with additional boundary options for better edge continuity. The default boundary option ShiftFilterCenter provides data smoothing all the way boundary ends.

Exception thrown when a matrix operation requiring a non-singular matrix is presented with a singular one.

Class for creating several independent streams of random numbers using the method know as skip-ahead, or block-splitting.

Class SkipAheadStream represents a single skip-ahead stream.

Class Slice represents a collection of indices that can be used to view a subset of data from another data structure. A slice is defined by a starting index, a total number of elements, and a step increment called the stride.

Class SobolQuasiRandomGenerator is quasi-random number generator which can be used for generating sequences of quasi-random point in n-dimensional space.

Class TabulatedFunction is an abstract class representing a function determined by tabulated values.

The DoubleComplex struct represents a complex number, consisting of a real part and an imaginary part.

Represents an imutable extrema of a function in two dimensions.

The FloatComplex struct represents a complex number, consisting of a real part and an imaginary part.

Interface to the correlation and convolution task manager. This is used to maintain the state of an instance of a MKL convolution or correlation task.

Interface for classes that perform differentiation of a function at a point.

Classes that implement the IDoubleComplexEnumerator interface behave like regular IEnumerator implementations except that they return a DoubleComplex instead of an object. They avoid casting and are therefore much faster.

Classes that implement the IDoubleEnumerator interface behave like regular IEnumerator implementations except that they return a double instead of an object. They avoid casting and are therefore much faster.

Classes that implement the IFloatComplexEnumerator interface behave like regular IEnumerator implementations except that they return a FloatComplex instead of an object. They avoid casting and are therefore much faster.

Classes that implement the IFloatEnumerator interface behave like regular IEnumerator implementations except that they return a float instead of an object. They avoid casting and are therefore much faster.

Interface for classes that perform integration of a function over an interval.

Interface for random number distributions.

Implement this interface to indicate support of range slicing in an vector.

Functor that takes two booleans and returns a boolean.

Functor that takes no arguments and returns a boolean.

Functor that takes a boolean and returns a boolean.

Functor that takes two DateTimes and returns a DateTime.

Functor that takes no arguments and returns a DateTime.

Functor that takes a DateTime and returns a DateTime.

Functor that takes an array of double-precision numbers and returns an array of double-precision numbers.

Functor that takes two double-precision floating point numbers, and returns a double-precision floating point number.

Functor that takes two DoubleComplex instances, and returns a DoubleComplex instance.

Functor that takes no arguments and returns a DoubleComplex instance.

Functor that takes a double-precision complex number and an integer and returns a double-precision complex number.

Functor that takes a DoubleComplex instance, and returns a DoubleComplex instance.

Functor that taks a DoubleComplex instance and returns a double.

Functor that takes a DoubleComplexVector instance and returns a DoubleComplex instance.

Functor that takes no arguments and returns a double-precision floating point number.

Functor that takes a double-precision floating point number and an integer and returns a double-precision floating point number.

Functor that takes a double-precision floating point number, and returns a double-precision floating point number.

Functor that takes a double-precision vector and returns a double-precision number.

Functor that takes a double-precision vector and returns a double-precision vector.

Functor that takes two floating point numbers, and returns a floating point number.

Functor that takes two FloatComplex instances, and returns a FloatComplex instance.

Functor that takes no arguments and returns a FloatComplex instance.

Functor that takes a single-precision complex number and an integer and returns a single-precision complex number.

Functor that takes a FloatComplex instance, and returns a FloatComplex instance.

Functor that takes a FloatComplex instance, and returns a float.

Functor that takes a FloatComplexVector instance and returns a FloatComplex instance.

Functor that takes no arguments and returns a floating point number.

Functor that takes a floating point number and an integer and returns a floating point number.

Functor that takes a floating point number, and returns a floating point number.

Functor that takes a single-precision vector and returns a single-precision number.

Functor that takes a single-precision vector and returns a single-precision vector.

Functor representing a generalized version of a DoubleUnaryFunction. Takes a vector of function parameters in addition to the point at which to evaluate the function.

Functor representing a generalized version of a DoubleVectorDoubleFunction. Takes a vector of function parameters in addition to the point at which to evaluate the function.

Functor that takes two integer values and returns an integer value.

Functor that takes no arguments and returns an integer value.

Functor that takes an integer value and returns an integer value.

Functor that takes two objects and returns an object.

Functor that takes no arguments and returns an object.

Functor that takes an object and returns an object.

Functor that takes two strings and returns a string.

Functor that takes no arguments and returns a string.

Functor that takes a string and returns a string.

Functor that takes a type T and returns a type T

Functor for generating uniform deviates between zero and one.

Enum specifying a particualr conjugate transpose option.

Options for handling the various convolution/correlation result boundaries.

Controls internal funtion of convolution class.

Options for handling the various convolution/correlation result boundaries.

Controls internal funtion of correlation class.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Direction of FFT. Used for building FFTConfiguration types.

Forward Domain of FFT. Used for building FFTConfiguration types.

Precision of FFT transform. Used for building FFTConfiguration types.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

An enumeration representing the possible interval types classified according to whether or not the endpoints are included in the interval.

Enumeration specifying different methods of random number generation.

Enumeration specifying different methods of random number generation.

Enumeration for specifying the type of transformation of a normal random variate in the Johnson system.

Options for handling the boundaries in a moving window filter.

Enumeration for specifying different types of norms.

Enumeration for specifying different view positions of underlying data.

Enum for specifying transpose operations to be performed on the operands of a matrix-matrix multiply opertion.

Enumeration for the various algorithms available for generating random numbers uniformly dstributed in the interval [0, 1]

Enum indicating the status of a random number stream.

Enumeration specifying Savitsky-Golay boundary options.

Enumeration for specifying the storage scheme of a matrix.