diff --git a/api/MathNet.Numerics.Differentiation/FiniteDifferenceCoefficients.htm b/api/MathNet.Numerics.Differentiation/FiniteDifferenceCoefficients.htm index 8f0cef13..e3dca826 100644 --- a/api/MathNet.Numerics.Differentiation/FiniteDifferenceCoefficients.htm +++ b/api/MathNet.Numerics.Differentiation/FiniteDifferenceCoefficients.htm @@ -286,7 +286,7 @@ diff --git a/api/MathNet.Numerics.Differentiation/NumericalDerivative.htm b/api/MathNet.Numerics.Differentiation/NumericalDerivative.htm index 1fefd7d7..c2aa13b7 100644 --- a/api/MathNet.Numerics.Differentiation/NumericalDerivative.htm +++ b/api/MathNet.Numerics.Differentiation/NumericalDerivative.htm @@ -540,7 +540,7 @@ h is approximately equal to the square-root of machine accuracy, epsilon. diff --git a/api/MathNet.Numerics.Differentiation/NumericalHessian.htm b/api/MathNet.Numerics.Differentiation/NumericalHessian.htm index 8acb94e6..43b53964 100644 --- a/api/MathNet.Numerics.Differentiation/NumericalHessian.htm +++ b/api/MathNet.Numerics.Differentiation/NumericalHessian.htm @@ -314,7 +314,7 @@ The function mirrors the Hessian along the diagonal since d2f/dxdy = d2f/dydx fo diff --git a/api/MathNet.Numerics.Differentiation/NumericalJacobian.htm b/api/MathNet.Numerics.Differentiation/NumericalJacobian.htm index d54377ad..89028c91 100644 --- a/api/MathNet.Numerics.Differentiation/NumericalJacobian.htm +++ b/api/MathNet.Numerics.Differentiation/NumericalJacobian.htm @@ -363,7 +363,7 @@ added efficiency. This method also assumes that the length of vector x consisten diff --git a/api/MathNet.Numerics.Differentiation/StepType.htm b/api/MathNet.Numerics.Differentiation/StepType.htm index 1e883702..20d22b97 100644 --- a/api/MathNet.Numerics.Differentiation/StepType.htm +++ b/api/MathNet.Numerics.Differentiation/StepType.htm @@ -261,8 +261,11 @@
-

string ToString(string format)

+

string ToString(IFormatProvider provider)

+
+ Obsolete: The provider argument is not used. Please use ToString(). +
@@ -270,11 +273,8 @@
-

string ToString(IFormatProvider provider)

+

string ToString(string format)

-
- Obsolete: The provider argument is not used. Please use ToString(). -
@@ -338,7 +338,7 @@ input parameter. Although implementation may vary, an example of second order ac
diff --git a/api/MathNet.Numerics.Differentiation/index.htm b/api/MathNet.Numerics.Differentiation/index.htm index ac64dc91..23f6fa89 100644 --- a/api/MathNet.Numerics.Differentiation/index.htm +++ b/api/MathNet.Numerics.Differentiation/index.htm @@ -159,7 +159,7 @@ diff --git a/api/MathNet.Numerics.Distributions/Bernoulli.htm b/api/MathNet.Numerics.Distributions/Bernoulli.htm index 17b4af52..fb5ed55d 100644 --- a/api/MathNet.Numerics.Distributions/Bernoulli.htm +++ b/api/MathNet.Numerics.Distributions/Bernoulli.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -782,7 +791,7 @@ p specifies the probability that a 1 is generated.. diff --git a/api/MathNet.Numerics.Distributions/Beta.htm b/api/MathNet.Numerics.Distributions/Beta.htm index edf9d96c..01c445e1 100644 --- a/api/MathNet.Numerics.Distributions/Beta.htm +++ b/api/MathNet.Numerics.Distributions/Beta.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -864,7 +873,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/BetaScaled.htm b/api/MathNet.Numerics.Distributions/BetaScaled.htm index 6afbbb59..ae6f9032 100644 --- a/api/MathNet.Numerics.Distributions/BetaScaled.htm +++ b/api/MathNet.Numerics.Distributions/BetaScaled.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -948,7 +957,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/Binomial.htm b/api/MathNet.Numerics.Distributions/Binomial.htm index 8eb3aff9..16f9ea68 100644 --- a/api/MathNet.Numerics.Distributions/Binomial.htm +++ b/api/MathNet.Numerics.Distributions/Binomial.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -814,7 +823,7 @@ For details about this distribution, see.
    diff --git a/api/MathNet.Numerics.Distributions/Burr.htm b/api/MathNet.Numerics.Distributions/Burr.htm new file mode 100644 index 00000000..06390c14 --- /dev/null +++ b/api/MathNet.Numerics.Distributions/Burr.htm @@ -0,0 +1,774 @@ + + + + Burr - Math.NET Numerics Documentation + + + + + + + +
    +

    Namespaces

    +
    + +
    +
    +

    Types in MathNet.Numerics.Distributions

    +
    + +
    +
    +
    +

    Type Burr

    +

    Namespace MathNet.Numerics.Distributions

    +

    Interfaces IContinuousDistribution

    +
    +
    + +

    Constructors

    + + +

    Static Functions

    + +

    Methods

    + + + +

    Properties

    + + +
    + + +

    Public Constructors

    + +
    +

    Burr(double a, double c, double k, Random randomSource)

    +
    Initializes a new instance of the Burr Type XII class. + + +
    +
    Parameters
    + +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    Random randomSource
    +

    The random number generator which is used to draw random samples. Optional, can be null.

    +
    + + +
    +
    + +

    Public Static Functions

    + +
    +

    double CDF(double a, double c, double k, double x)

    +
    Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). + + +
    +
    Parameters
    + +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    double x
    +

    The location at which to compute the cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the cumulative distribution at location x.

    +
    + +
    +
    +
    +

    bool IsValidParameterSet(double a, double c, double k)

    +
    Tests whether the provided values are valid parameters for this distribution. + + +
    +
    Parameters
    + +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    + + +
    +
    +
    +

    double PDF(double a, double c, double k, double x)

    +
    Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. + + +
    +
    Parameters
    + +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    double x
    +

    The location at which to compute the density.

    +
    + +
    +
    Return
    +
    double
    +

    the density at x.

    +
    + +
    +
    +
    +

    double PDFLn(double a, double c, double k, double x)

    +
    Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). + + +
    +
    Parameters
    + +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    double x
    +

    The location at which to compute the log density.

    +
    + +
    +
    Return
    +
    double
    +

    the log density at x.

    +
    + +
    +
    +
    +

    double Sample(Random rnd, double a, double c, double k)

    +
    Generates a sample from the Burr distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    + +
    +
    Return
    +
    double
    +

    a sample from the distribution.

    +
    + +
    +
    +
    +

    void Samples(Random rnd, Double[] values, double a, double c, double k)

    +
    Fills an array with samples generated from the distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    Double[] values
    +

    The array to fill with the samples.

    +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    + + +
    +
    +
    +

    IEnumerable<double> Samples(Random rnd, double a, double c, double k)

    +
    Generates a sequence of samples from the Burr distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    double a
    +

    The scale parameter a of the Burr distribution. Range: a > 0.

    +
    double c
    +

    The first shape parameter c of the Burr distribution. Range: c > 0.

    +
    double k
    +

    The second shape parameter k of the Burr distribution. Range: k > 0.

    +
    + +
    +
    Return
    +
    IEnumerable<double>
    +

    a sequence of samples from the distribution.

    +
    + +
    +
    + +

    Public Methods

    + +
    +

    double CumulativeDistribution(double x)

    +
    Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the cumulative distribution at location x.

    +
    + +
    +
    +
    +

    double Density(double x)

    +
    Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the density.

    +
    + +
    +
    Return
    +
    double
    +

    the density at x.

    +
    + +
    +
    +
    +

    double DensityLn(double x)

    +
    Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the log density.

    +
    + +
    +
    Return
    +
    double
    +

    the log density at x.

    +
    + +
    +
    +
    +

    bool Equals(object obj)

    +
    + + + + +
    +
    +
    +

    int GetHashCode()

    +
    + + + + +
    +
    +
    +

    double GetMoment(double n)

    +
    Gets the n-th raw moment of the distribution. + + +
    +
    Parameters
    + +
    double n
    +

    The order (n) of the moment. Range: n ≥ 1.

    +
    + +
    +
    Return
    +
    double
    +

    the n-th moment of the distribution.

    +
    + +
    +
    +
    +

    Type GetType()

    +
    + + + + +
    +
    +
    +

    double Sample()

    +
    Generates a sample from the Burr distribution. + + + +
    +
    Return
    +
    double
    +

    a sample from the distribution.

    +
    + +
    +
    +
    +

    IEnumerable<double> Samples()

    +
    Generates a sequence of samples from the Burr distribution. + + + +
    +
    Return
    +
    IEnumerable<double>
    +

    a sequence of samples from the distribution.

    +
    + +
    +
    +
    +

    void Samples(Double[] values)

    +
    Fills an array with samples generated from the distribution. + + +
    +
    Parameters
    + +
    Double[] values
    +

    The array to fill with the samples.

    +
    + + +
    +
    +
    +

    string ToString()

    +
    A string representation of the distribution. + + + +
    +
    Return
    +
    string
    +

    a string representation of the distribution.

    +
    + +
    +
    + +

    Public Properties

    + +
    +

    double a get;

    +
    Gets the scale (a) of the distribution. Range: a > 0. + +
    +
    +
    +

    double c get;

    +
    Gets the first shape parameter (c) of the distribution. Range: c > 0. + +
    +
    +
    +

    double Entropy get;

    +
    Gets the entropy of the Burr distribution (currently not supported). + +
    +
    +
    +

    double k get;

    +
    Gets the second shape parameter (k) of the distribution. Range: k > 0. + +
    +
    +
    +

    double Maximum get;

    +
    Gets the maximum of the Burr distribution. + +
    +
    +
    +

    double Mean get;

    +
    Gets the mean of the Burr distribution. + +
    +
    +
    +

    double Median get;

    +
    Gets the median of the Burr distribution. + +
    +
    +
    +

    double Minimum get;

    +
    Gets the minimum of the Burr distribution. + +
    +
    +
    +

    double Mode get;

    +
    Gets the mode of the Burr distribution. + +
    +
    +
    +

    Random RandomSource get; set;

    +
    Gets the random number generator which is used to draw random samples. + +
    +
    +
    +

    double Skewness get;

    +
    Gets the skewness of the Burr distribution. + +
    +
    +
    +

    double StdDev get;

    +
    Gets the standard deviation of the Burr distribution. + +
    +
    +
    +

    double Variance get;

    +
    Gets the variance of the Burr distribution. + +
    +
    + + + \ No newline at end of file diff --git a/api/MathNet.Numerics.Distributions/Categorical.htm b/api/MathNet.Numerics.Distributions/Categorical.htm index 6c2870b6..b74063e3 100644 --- a/api/MathNet.Numerics.Distributions/Categorical.htm +++ b/api/MathNet.Numerics.Distributions/Categorical.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -1041,7 +1050,7 @@ at the given probability. diff --git a/api/MathNet.Numerics.Distributions/Cauchy.htm b/api/MathNet.Numerics.Distributions/Cauchy.htm index 8176a0ee..3dadeed2 100644 --- a/api/MathNet.Numerics.Distributions/Cauchy.htm +++ b/api/MathNet.Numerics.Distributions/Cauchy.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -863,7 +872,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/Chi.htm b/api/MathNet.Numerics.Distributions/Chi.htm index edafe64c..a4e94eaa 100644 --- a/api/MathNet.Numerics.Distributions/Chi.htm +++ b/api/MathNet.Numerics.Distributions/Chi.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -776,7 +785,7 @@ then have a chi distribution.. diff --git a/api/MathNet.Numerics.Distributions/ChiSquared.htm b/api/MathNet.Numerics.Distributions/ChiSquared.htm index 1898208c..09b63cad 100644 --- a/api/MathNet.Numerics.Distributions/ChiSquared.htm +++ b/api/MathNet.Numerics.Distributions/ChiSquared.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -820,7 +829,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/ContinuousUniform.htm b/api/MathNet.Numerics.Distributions/ContinuousUniform.htm index fce5379c..170362f9 100644 --- a/api/MathNet.Numerics.Distributions/ContinuousUniform.htm +++ b/api/MathNet.Numerics.Distributions/ContinuousUniform.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -863,7 +872,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/ConwayMaxwellPoisson.htm b/api/MathNet.Numerics.Distributions/ConwayMaxwellPoisson.htm index ce19f7fe..c3b94a81 100644 --- a/api/MathNet.Numerics.Distributions/ConwayMaxwellPoisson.htm +++ b/api/MathNet.Numerics.Distributions/ConwayMaxwellPoisson.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -775,7 +784,7 @@ distributions. It is parameterized by two real numbers "lambda" and "nu". For diff --git a/api/MathNet.Numerics.Distributions/Dirichlet.htm b/api/MathNet.Numerics.Distributions/Dirichlet.htm index 34cb0b6a..f0079d08 100644 --- a/api/MathNet.Numerics.Distributions/Dirichlet.htm +++ b/api/MathNet.Numerics.Distributions/Dirichlet.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -554,7 +563,7 @@ You can also leave out the last x component, and it will be compute diff --git a/api/MathNet.Numerics.Distributions/DiscreteUniform.htm b/api/MathNet.Numerics.Distributions/DiscreteUniform.htm index 298edbfe..bfa1e9af 100644 --- a/api/MathNet.Numerics.Distributions/DiscreteUniform.htm +++ b/api/MathNet.Numerics.Distributions/DiscreteUniform.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -806,7 +815,7 @@ is parameterized by a lower and upper bound (both inclusive).. diff --git a/api/MathNet.Numerics.Distributions/Erlang.htm b/api/MathNet.Numerics.Distributions/Erlang.htm index 22db65af..8783a4c3 100644 --- a/api/MathNet.Numerics.Distributions/Erlang.htm +++ b/api/MathNet.Numerics.Distributions/Erlang.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -855,7 +864,7 @@ be initialized with the default random number generator. diff --git a/api/MathNet.Numerics.Distributions/Exponential.htm b/api/MathNet.Numerics.Distributions/Exponential.htm index 2bb1b3fd..c202c174 100644 --- a/api/MathNet.Numerics.Distributions/Exponential.htm +++ b/api/MathNet.Numerics.Distributions/Exponential.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -820,7 +829,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/FisherSnedecor.htm b/api/MathNet.Numerics.Distributions/FisherSnedecor.htm index 4812d276..f10941bf 100644 --- a/api/MathNet.Numerics.Distributions/FisherSnedecor.htm +++ b/api/MathNet.Numerics.Distributions/FisherSnedecor.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -857,7 +866,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/Gamma.htm b/api/MathNet.Numerics.Distributions/Gamma.htm index 0a26cdcd..1e29eb83 100644 --- a/api/MathNet.Numerics.Distributions/Gamma.htm +++ b/api/MathNet.Numerics.Distributions/Gamma.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -910,7 +919,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/Geometric.htm b/api/MathNet.Numerics.Distributions/Geometric.htm index 3c42bca1..a7287040 100644 --- a/api/MathNet.Numerics.Distributions/Geometric.htm +++ b/api/MathNet.Numerics.Distributions/Geometric.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -747,7 +756,7 @@ This implementation of the Geometric distribution will never generate 0's.. diff --git a/api/MathNet.Numerics.Distributions/Hypergeometric.htm b/api/MathNet.Numerics.Distributions/Hypergeometric.htm index 26904dca..5e81aaa4 100644 --- a/api/MathNet.Numerics.Distributions/Hypergeometric.htm +++ b/api/MathNet.Numerics.Distributions/Hypergeometric.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -808,7 +817,7 @@ describes the number of successes for draws with replacement. diff --git a/api/MathNet.Numerics.Distributions/IContinuousDistribution.htm b/api/MathNet.Numerics.Distributions/IContinuousDistribution.htm index 5291f1d1..5ca6312c 100644 --- a/api/MathNet.Numerics.Distributions/IContinuousDistribution.htm +++ b/api/MathNet.Numerics.Distributions/IContinuousDistribution.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -386,7 +395,7 @@ diff --git a/api/MathNet.Numerics.Distributions/IDiscreteDistribution.htm b/api/MathNet.Numerics.Distributions/IDiscreteDistribution.htm index 7bfe232e..bca7a485 100644 --- a/api/MathNet.Numerics.Distributions/IDiscreteDistribution.htm +++ b/api/MathNet.Numerics.Distributions/IDiscreteDistribution.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -386,7 +395,7 @@ diff --git a/api/MathNet.Numerics.Distributions/IDistribution.htm b/api/MathNet.Numerics.Distributions/IDistribution.htm index 21c69d37..c5159d9e 100644 --- a/api/MathNet.Numerics.Distributions/IDistribution.htm +++ b/api/MathNet.Numerics.Distributions/IDistribution.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -284,7 +293,7 @@ diff --git a/api/MathNet.Numerics.Distributions/IUnivariateDistribution.htm b/api/MathNet.Numerics.Distributions/IUnivariateDistribution.htm index 2abce747..e25e0cc2 100644 --- a/api/MathNet.Numerics.Distributions/IUnivariateDistribution.htm +++ b/api/MathNet.Numerics.Distributions/IUnivariateDistribution.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -346,7 +355,7 @@ diff --git a/api/MathNet.Numerics.Distributions/InverseGamma.htm b/api/MathNet.Numerics.Distributions/InverseGamma.htm index 52f9bb6f..af65ee6e 100644 --- a/api/MathNet.Numerics.Distributions/InverseGamma.htm +++ b/api/MathNet.Numerics.Distributions/InverseGamma.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -808,7 +817,7 @@ two positive parameters.. diff --git a/api/MathNet.Numerics.Distributions/InverseGaussian.htm b/api/MathNet.Numerics.Distributions/InverseGaussian.htm new file mode 100644 index 00000000..17cdfeda --- /dev/null +++ b/api/MathNet.Numerics.Distributions/InverseGaussian.htm @@ -0,0 +1,807 @@ + + + + InverseGaussian - Math.NET Numerics Documentation + + + + + + + +
    +

    Namespaces

    +
    + +
    +
    +

    Types in MathNet.Numerics.Distributions

    +
    + +
    +
    +
    +

    Type InverseGaussian

    +

    Namespace MathNet.Numerics.Distributions

    +

    Interfaces IContinuousDistribution

    +
    +
    + +

    Constructors

    + + +

    Static Functions

    + +

    Methods

    + + + +

    Properties

    + + +
    + + +

    Public Constructors

    + +
    +

    InverseGaussian(double mu, double lambda, Random randomSource)

    +
    Initializes a new instance of the InverseGaussian class. + + +
    +
    Parameters
    + +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    Random randomSource
    +

    The random number generator which is used to draw random samples.

    +
    + + +
    +
    + +

    Public Static Functions

    + +
    +

    double CDF(double mu, double lambda, double x)

    +
    Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). + + +
    +
    Parameters
    + +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    double x
    +

    The location at which to compute the cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the cumulative distribution at location x.

    +
    + +
    +
    +
    +

    InverseGaussian Estimate(IEnumerable<double> samples, Random randomSource)

    +
    Estimates the Inverse Gaussian parameters from sample data with maximum-likelihood. + + +
    +
    Parameters
    + +
    IEnumerable<double> samples
    +

    The samples to estimate the distribution parameters from.

    +
    Random randomSource
    +

    The random number generator which is used to draw random samples. Optional, can be null.

    +
    + +
    +
    Return
    +
    InverseGaussian
    +

    An Inverse Gaussian distribution.

    +
    + +
    +
    +
    +

    double ICDF(double mu, double lambda, double p)

    +
    Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p. + + +
    +
    Parameters
    + +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    double p
    +

    The location at which to compute the inverse cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the inverse cumulative distribution at location p.

    +
    + +
    +
    +
    +

    bool IsValidParameterSet(double mu, double lambda)

    +
    Tests whether the provided values are valid parameters for this distribution. + + +
    +
    Parameters
    + +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    + + +
    +
    +
    +

    double PDF(double mu, double lambda, double x)

    +
    Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. + + +
    +
    Parameters
    + +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    double x
    +

    The location at which to compute the density.

    +
    + +
    +
    Return
    +
    double
    +

    the density at x.

    +
    + +
    +
    +
    +

    double PDFLn(double mu, double lambda, double x)

    +
    Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). + + +
    +
    Parameters
    + +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    double x
    +

    The location at which to compute the log density.

    +
    + +
    +
    Return
    +
    double
    +

    the log density at x.

    +
    + +
    +
    +
    +

    double Sample(Random rnd, double mu, double lambda)

    +
    Generates a sample from the inverse Gaussian distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    + +
    +
    Return
    +
    double
    +

    a sample from the distribution.

    +
    + +
    +
    +
    +

    void Samples(Random rnd, Double[] values, double mu, double lambda)

    +
    Fills an array with samples generated from the distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    Double[] values
    +

    The array to fill with the samples.

    +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    + + +
    +
    +
    +

    IEnumerable<double> Samples(Random rnd, double mu, double lambda)

    +
    Generates a sequence of samples from the Burr distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    double mu
    +

    The mean (μ) of the distribution. Range: μ > 0.

    +
    double lambda
    +

    The shape (λ) of the distribution. Range: λ > 0.

    +
    + +
    +
    Return
    +
    IEnumerable<double>
    +

    a sequence of samples from the distribution.

    +
    + +
    +
    + +

    Public Methods

    + +
    +

    double CumulativeDistribution(double x)

    +
    Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the cumulative distribution at location x.

    +
    + +
    +
    +
    +

    double Density(double x)

    +
    Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the density.

    +
    + +
    +
    Return
    +
    double
    +

    the density at x.

    +
    + +
    +
    +
    +

    double DensityLn(double x)

    +
    Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the log density.

    +
    + +
    +
    Return
    +
    double
    +

    the log density at x.

    +
    + +
    +
    +
    +

    bool Equals(object obj)

    +
    + + + + +
    +
    +
    +

    int GetHashCode()

    +
    + + + + +
    +
    +
    +

    Type GetType()

    +
    + + + + +
    +
    +
    +

    double InvCDF(double p)

    +
    Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p. + + +
    +
    Parameters
    + +
    double p
    +

    The location at which to compute the inverse cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the inverse cumulative distribution at location p.

    +
    + +
    +
    +
    +

    double Sample()

    +
    Generates a sample from the inverse Gaussian distribution. + + + +
    +
    Return
    +
    double
    +

    a sample from the distribution.

    +
    + +
    +
    +
    +

    void Samples(Double[] values)

    +
    Fills an array with samples generated from the distribution. + + +
    +
    Parameters
    + +
    Double[] values
    +

    The array to fill with the samples.

    +
    + + +
    +
    +
    +

    IEnumerable<double> Samples()

    +
    Generates a sequence of samples from the inverse Gaussian distribution. + + + +
    +
    Return
    +
    IEnumerable<double>
    +

    a sequence of samples from the distribution.

    +
    + +
    +
    +
    +

    string ToString()

    +
    A string representation of the distribution. + + + +
    +
    Return
    +
    string
    +

    a string representation of the distribution.

    +
    + +
    +
    + +

    Public Properties

    + +
    +

    double Entropy get;

    +
    Gets the entropy of the Inverse Gaussian distribution (currently not supported). + +
    +
    +
    +

    double Kurtosis get;

    +
    Gets the kurtosis of the Inverse Gaussian distribution. + +
    +
    +
    +

    double Lambda get;

    +
    Gets the shape (λ) of the distribution. Range: λ > 0. + +
    +
    +
    +

    double Maximum get;

    +
    Gets the maximum of the Inverse Gaussian distribution. + +
    +
    +
    +

    double Mean get;

    +
    Gets the mean of the Inverse Gaussian distribution. + +
    +
    +
    +

    double Median get;

    +
    Gets the median of the Inverse Gaussian distribution. +No closed form analytical expression exists, so this value is approximated numerically and can throw an exception. + +
    +
    +
    +

    double Minimum get;

    +
    Gets the minimum of the Inverse Gaussian distribution. + +
    +
    +
    +

    double Mode get;

    +
    Gets the mode of the Inverse Gaussian distribution. + +
    +
    +
    +

    double Mu get;

    +
    Gets the mean (μ) of the distribution. Range: μ > 0. + +
    +
    +
    +

    Random RandomSource get; set;

    +
    Gets the random number generator which is used to draw random samples. + +
    +
    +
    +

    double Skewness get;

    +
    Gets the skewness of the Inverse Gaussian distribution. + +
    +
    +
    +

    double StdDev get;

    +
    Gets the standard deviation of the Inverse Gaussian distribution. + +
    +
    +
    +

    double Variance get;

    +
    Gets the variance of the Inverse Gaussian distribution. + +
    +
    + + + \ No newline at end of file diff --git a/api/MathNet.Numerics.Distributions/InverseWishart.htm b/api/MathNet.Numerics.Distributions/InverseWishart.htm index d747398f..3c62a3dc 100644 --- a/api/MathNet.Numerics.Distributions/InverseWishart.htm +++ b/api/MathNet.Numerics.Distributions/InverseWishart.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -511,7 +520,7 @@ a Wishart random variable and inverting the matrix. diff --git a/api/MathNet.Numerics.Distributions/Laplace.htm b/api/MathNet.Numerics.Distributions/Laplace.htm index e625b193..bde91454 100644 --- a/api/MathNet.Numerics.Distributions/Laplace.htm +++ b/api/MathNet.Numerics.Distributions/Laplace.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -817,7 +826,7 @@ p(x) = \frac{1}{2 * scale} \exp{- |x - mean| / scale}.. diff --git a/api/MathNet.Numerics.Distributions/LogNormal.htm b/api/MathNet.Numerics.Distributions/LogNormal.htm index 710adda2..cf8c0c91 100644 --- a/api/MathNet.Numerics.Distributions/LogNormal.htm +++ b/api/MathNet.Numerics.Distributions/LogNormal.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -936,7 +945,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/MatrixNormal.htm b/api/MathNet.Numerics.Distributions/MatrixNormal.htm index 378a02aa..af02172e 100644 --- a/api/MathNet.Numerics.Distributions/MatrixNormal.htm +++ b/api/MathNet.Numerics.Distributions/MatrixNormal.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -499,7 +508,7 @@ for the columns (K). If the dimension of M is d-by-m then V is d-by-d and K is m diff --git a/api/MathNet.Numerics.Distributions/MeanPrecisionPair.htm b/api/MathNet.Numerics.Distributions/MeanPrecisionPair.htm index 78f376f9..07830e81 100644 --- a/api/MathNet.Numerics.Distributions/MeanPrecisionPair.htm +++ b/api/MathNet.Numerics.Distributions/MeanPrecisionPair.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -361,7 +370,7 @@ is defined. diff --git a/api/MathNet.Numerics.Distributions/Multinomial.htm b/api/MathNet.Numerics.Distributions/Multinomial.htm index d4d8f304..bb6461de 100644 --- a/api/MathNet.Numerics.Distributions/Multinomial.htm +++ b/api/MathNet.Numerics.Distributions/Multinomial.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -592,7 +601,7 @@ as this is often impossible using floating point arithmetic.

    diff --git a/api/MathNet.Numerics.Distributions/NegativeBinomial.htm b/api/MathNet.Numerics.Distributions/NegativeBinomial.htm index c6c0eaec..833815fc 100644 --- a/api/MathNet.Numerics.Distributions/NegativeBinomial.htm +++ b/api/MathNet.Numerics.Distributions/NegativeBinomial.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -777,7 +786,7 @@ when the probability of success is p.. diff --git a/api/MathNet.Numerics.Distributions/Normal.htm b/api/MathNet.Numerics.Distributions/Normal.htm index 9edf980e..29065ae8 100644 --- a/api/MathNet.Numerics.Distributions/Normal.htm +++ b/api/MathNet.Numerics.Distributions/Normal.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -984,7 +993,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/NormalGamma.htm b/api/MathNet.Numerics.Distributions/NormalGamma.htm index 32cbf6ca..de27038a 100644 --- a/api/MathNet.Numerics.Distributions/NormalGamma.htm +++ b/api/MathNet.Numerics.Distributions/NormalGamma.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -669,7 +678,7 @@ will be positive infinity. A completely degenerate NormalGamma distribution with diff --git a/api/MathNet.Numerics.Distributions/Pareto.htm b/api/MathNet.Numerics.Distributions/Pareto.htm index 1f182d89..2546fc3c 100644 --- a/api/MathNet.Numerics.Distributions/Pareto.htm +++ b/api/MathNet.Numerics.Distributions/Pareto.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -855,7 +864,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/Poisson.htm b/api/MathNet.Numerics.Distributions/Poisson.htm index 02dcd709..d901fc33 100644 --- a/api/MathNet.Numerics.Distributions/Poisson.htm +++ b/api/MathNet.Numerics.Distributions/Poisson.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -779,7 +788,7 @@ diff --git a/api/MathNet.Numerics.Distributions/Rayleigh.htm b/api/MathNet.Numerics.Distributions/Rayleigh.htm index 4bd41c6c..e632dcc0 100644 --- a/api/MathNet.Numerics.Distributions/Rayleigh.htm +++ b/api/MathNet.Numerics.Distributions/Rayleigh.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -823,7 +832,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/Stable.htm b/api/MathNet.Numerics.Distributions/Stable.htm index 42b9197a..984a8130 100644 --- a/api/MathNet.Numerics.Distributions/Stable.htm +++ b/api/MathNet.Numerics.Distributions/Stable.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -880,7 +889,7 @@ For details about this distribution, see. diff --git a/api/MathNet.Numerics.Distributions/StudentT.htm b/api/MathNet.Numerics.Distributions/StudentT.htm index cc7f8172..9b124215 100644 --- a/api/MathNet.Numerics.Distributions/StudentT.htm +++ b/api/MathNet.Numerics.Distributions/StudentT.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -915,7 +924,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/Triangular.htm b/api/MathNet.Numerics.Distributions/Triangular.htm index ddae03dc..fd1d5a89 100644 --- a/api/MathNet.Numerics.Distributions/Triangular.htm +++ b/api/MathNet.Numerics.Distributions/Triangular.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -883,7 +892,7 @@ at the given probability. This is also known as the quantile or percent point fu diff --git a/api/MathNet.Numerics.Distributions/TruncatedPareto.htm b/api/MathNet.Numerics.Distributions/TruncatedPareto.htm new file mode 100644 index 00000000..bf9f5553 --- /dev/null +++ b/api/MathNet.Numerics.Distributions/TruncatedPareto.htm @@ -0,0 +1,822 @@ + + + + TruncatedPareto - Math.NET Numerics Documentation + + + + + + + +
    +

    Namespaces

    +
    + +
    +
    +

    Types in MathNet.Numerics.Distributions

    +
    + +
    +
    +
    +

    Type TruncatedPareto

    +

    Namespace MathNet.Numerics.Distributions

    +

    Interfaces IContinuousDistribution

    +
    +
    + +

    Constructors

    + + +

    Static Functions

    + +

    Methods

    + + + +

    Properties

    + + +
    + + +

    Public Constructors

    + +
    +

    TruncatedPareto(double scale, double shape, double truncation, Random randomSource)

    +
    Initializes a new instance of the TruncatedPareto class. + + +
    +
    Parameters
    + +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    Random randomSource
    +

    The random number generator which is used to draw random samples.

    +
    + + +
    +
    + +

    Public Static Functions

    + +
    +

    double CDF(double scale, double shape, double truncation, double x)

    +
    Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). + + +
    +
    Parameters
    + +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    double x
    +

    The location at which to compute the cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the cumulative distribution at location x.

    +
    + +
    +
    +
    +

    double ICDF(double scale, double shape, double truncation, double p)

    +
    Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p. + + +
    +
    Parameters
    + +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    double p
    +

    The location at which to compute the inverse cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the inverse cumulative distribution at location p.

    +
    + +
    +
    +
    +

    bool IsValidParameterSet(double scale, double shape, double truncation)

    +
    Tests whether the provided values are valid parameters for this distribution. + + +
    +
    Parameters
    + +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    + + +
    +
    +
    +

    double PDF(double scale, double shape, double truncation, double x)

    +
    Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. + + +
    +
    Parameters
    + +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    double x
    +

    The location at which to compute the density.

    +
    + +
    +
    Return
    +
    double
    +

    the density at x.

    +
    + +
    +
    +
    +

    double PDFLn(double scale, double shape, double truncation, double x)

    +
    Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). + + +
    +
    Parameters
    + +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    double x
    +

    The location at which to compute the log density.

    +
    + +
    +
    Return
    +
    double
    +

    the log density at x.

    +
    + +
    +
    +
    +

    double Sample(Random rnd, double scale, double shape, double truncation)

    +
    Generates a sample from the truncated Pareto distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    + +
    +
    Return
    +
    double
    +

    a sample from the distribution.

    +
    + +
    +
    +
    +

    void Samples(Random rnd, Double[] values, double scale, double shape, double truncation)

    +
    Fills an array with samples generated from the distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    Double[] values
    +

    The array to fill with the samples.

    +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    + + +
    +
    +
    +

    IEnumerable<double> Samples(Random rnd, double scale, double shape, double truncation)

    +
    Generates a sequence of samples from the truncated Pareto distribution. + + +
    +
    Parameters
    + +
    Random rnd
    +

    The random number generator to use.

    +
    double scale
    +

    The scale (xm) of the distribution. Range: xm > 0.

    +
    double shape
    +

    The shape (α) of the distribution. Range: α > 0.

    +
    double truncation
    +

    The truncation (T) of the distribution. Range: T > xm.

    +
    + +
    +
    Return
    +
    IEnumerable<double>
    +

    a sequence of samples from the distribution.

    +
    + +
    +
    + +

    Public Methods

    + +
    +

    double CumulativeDistribution(double x)

    +
    Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the cumulative distribution at location x.

    +
    + +
    +
    +
    +

    double Density(double x)

    +
    Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the density.

    +
    + +
    +
    Return
    +
    double
    +

    the density at x.

    +
    + +
    +
    +
    +

    double DensityLn(double x)

    +
    Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). + + +
    +
    Parameters
    + +
    double x
    +

    The location at which to compute the log density.

    +
    + +
    +
    Return
    +
    double
    +

    the log density at x.

    +
    + +
    +
    +
    +

    bool Equals(object obj)

    +
    + + + + +
    +
    +
    +

    int GetHashCode()

    +
    + + + + +
    +
    +
    +

    double GetMoment(int n)

    +
    Gets the n-th raw moment of the distribution. + + +
    +
    Parameters
    + +
    int n
    +

    The order (n) of the moment. Range: n ≥ 1.

    +
    + +
    +
    Return
    +
    double
    +

    the n-th moment of the distribution.

    +
    + +
    +
    +
    +

    Type GetType()

    +
    + + + + +
    +
    +
    +

    double InvCDF(double p)

    +
    Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p. + + +
    +
    Parameters
    + +
    double p
    +

    The location at which to compute the inverse cumulative distribution function.

    +
    + +
    +
    Return
    +
    double
    +

    the inverse cumulative distribution at location p.

    +
    + +
    +
    +
    +

    double Sample()

    +
    Generates a sample from the truncated Pareto distribution. + + + +
    +
    Return
    +
    double
    +

    a sample from the distribution.

    +
    + +
    +
    +
    +

    IEnumerable<double> Samples()

    +
    Generates a sequence of samples from the truncated Pareto distribution. + + + +
    +
    Return
    +
    IEnumerable<double>
    +

    a sequence of samples from the distribution.

    +
    + +
    +
    +
    +

    void Samples(Double[] values)

    +
    Fills an array with samples generated from the distribution. + + +
    +
    Parameters
    + +
    Double[] values
    +

    The array to fill with the samples.

    +
    + + +
    +
    +
    +

    string ToString()

    +
    A string representation of the distribution. + + + +
    +
    Return
    +
    string
    +

    a string representation of the distribution.

    +
    + +
    +
    + +

    Public Properties

    + +
    +

    double Entropy get;

    +
    Gets the entropy of the truncated Pareto distribution (not supported). + +
    +
    +
    +

    double Maximum get;

    +
    Gets the maximum of the truncated Pareto distribution. + +
    +
    +
    +

    double Mean get;

    +
    Gets the mean of the truncated Pareto distribution. + +
    +
    +
    +

    double Median get;

    +
    Gets the median of the truncated Pareto distribution. + +
    +
    +
    +

    double Minimum get;

    +
    Gets the minimum of the truncated Pareto distribution. + +
    +
    +
    +

    double Mode get;

    +
    Gets the mode of the truncated Pareto distribution (not supported). + +
    +
    +
    +

    Random RandomSource get; set;

    +
    Gets the random number generator which is used to draw random samples. + +
    +
    +
    +

    double Scale get;

    +
    Gets the scale (xm) of the distribution. Range: xm > 0. + +
    +
    +
    +

    double Shape get;

    +
    Gets the shape (α) of the distribution. Range: α > 0. + +
    +
    +
    +

    double Skewness get;

    +
    Gets the skewness of the truncated Pareto distribution. + +
    +
    +
    +

    double StdDev get;

    +
    Gets the standard deviation of the truncated Pareto distribution. + +
    +
    +
    +

    double Truncation get;

    +
    Gets the truncation (T) of the distribution. Range: T > 0. + +
    +
    +
    +

    double Variance get;

    +
    Gets the variance of the truncated Pareto distribution. + +
    +
    + + + \ No newline at end of file diff --git a/api/MathNet.Numerics.Distributions/Weibull.htm b/api/MathNet.Numerics.Distributions/Weibull.htm index eab84e73..d971b6b2 100644 --- a/api/MathNet.Numerics.Distributions/Weibull.htm +++ b/api/MathNet.Numerics.Distributions/Weibull.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -822,7 +831,7 @@ For details about this distribution, see.
    diff --git a/api/MathNet.Numerics.Distributions/Wishart.htm b/api/MathNet.Numerics.Distributions/Wishart.htm index 04864455..d1fa1cb6 100644 --- a/api/MathNet.Numerics.Distributions/Wishart.htm +++ b/api/MathNet.Numerics.Distributions/Wishart.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -512,7 +521,7 @@ Applied Statistics, Vol. 21, No. 3 (1972), pp. 341-345 diff --git a/api/MathNet.Numerics.Distributions/Zipf.htm b/api/MathNet.Numerics.Distributions/Zipf.htm index 17e7f718..9c71af43 100644 --- a/api/MathNet.Numerics.Distributions/Zipf.htm +++ b/api/MathNet.Numerics.Distributions/Zipf.htm @@ -138,6 +138,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -192,6 +195,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -240,6 +246,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -778,7 +787,7 @@ For details about this distribution, see. diff --git a/api/MathNet.Numerics.Distributions/index.htm b/api/MathNet.Numerics.Distributions/index.htm index 7fa9f0a8..d4899494 100644 --- a/api/MathNet.Numerics.Distributions/index.htm +++ b/api/MathNet.Numerics.Distributions/index.htm @@ -137,6 +137,9 @@
  • Binomial +
    • +
  • + Burr
  • Categorical @@ -191,6 +194,9 @@
  • InverseGamma +
    • +
  • + InverseGaussian
  • InverseWishart @@ -239,6 +245,9 @@
  • Triangular +
    • +
  • + TruncatedPareto
  • Weibull @@ -262,6 +271,7 @@
  • Beta
  • BetaScaled
  • Binomial
    • +
  • Burr
  • Categorical
  • Cauchy
  • Chi
    • @@ -277,6 +287,7 @@
  • Geometric
  • Hypergeometric
  • InverseGamma
    • +
  • InverseGaussian
  • InverseWishart
  • Laplace
  • LogNormal
    • @@ -292,6 +303,7 @@
  • Stable
  • StudentT
  • Triangular
    • +
  • TruncatedPareto
  • Weibull
  • Wishart
  • Zipf
    • @@ -306,7 +318,7 @@ diff --git a/api/MathNet.Numerics.Financial/AbsoluteReturnMeasures.htm b/api/MathNet.Numerics.Financial/AbsoluteReturnMeasures.htm index 9a0a2314..05c81f9f 100644 --- a/api/MathNet.Numerics.Financial/AbsoluteReturnMeasures.htm +++ b/api/MathNet.Numerics.Financial/AbsoluteReturnMeasures.htm @@ -196,7 +196,7 @@ and then dividing the total by the number of loss periods.
    -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm b/api/MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm index bb17e5ea..db4a8cc5 100644 --- a/api/MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm +++ b/api/MathNet.Numerics.Financial/AbsoluteRiskMeasures.htm @@ -219,7 +219,7 @@ looks at periods where the investment return was less than average return. diff --git a/api/MathNet.Numerics.Financial/index.htm b/api/MathNet.Numerics.Financial/index.htm index d6985221..196d3747 100644 --- a/api/MathNet.Numerics.Financial/index.htm +++ b/api/MathNet.Numerics.Financial/index.htm @@ -147,7 +147,7 @@ diff --git a/api/MathNet.Numerics.IntegralTransforms/Fourier.htm b/api/MathNet.Numerics.IntegralTransforms/Fourier.htm index d98531c0..39d2a951 100644 --- a/api/MathNet.Numerics.IntegralTransforms/Fourier.htm +++ b/api/MathNet.Numerics.IntegralTransforms/Fourier.htm @@ -203,7 +203,7 @@

    Public Static Functions

    -

    void BluesteinForward(Complex[] samples, FourierOptions options)

    +

    void BluesteinForward(Complex32[] samples, FourierOptions options)

    Bluestein forward FFT for arbitrary sized sample vectors.
    Obsolete: Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then. @@ -213,7 +213,7 @@
    Parameters
    -
    Complex[] samples
    +
    Complex32[] samples

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -223,7 +223,7 @@
    -

    void BluesteinForward(Complex32[] samples, FourierOptions options)

    +

    void BluesteinForward(Complex[] samples, FourierOptions options)

    Bluestein forward FFT for arbitrary sized sample vectors.
    Obsolete: Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then. @@ -233,7 +233,7 @@
    Parameters
    -
    Complex32[] samples
    +
    Complex[] samples

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -313,15 +313,17 @@
    -

    void Forward(Complex32[] samples, FourierOptions options)

    +

    void Forward(Single[] real, Single[] imaginary, FourierOptions options)

    Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
    Parameters
    -
    Complex32[] samples
    -

    Sample vector, where the FFT is evaluated in place.

    +
    Single[] real
    +

    Real part of the sample vector, where the FFT is evaluated in place.

    +
    Single[] imaginary
    +

    Imaginary part of the sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -330,14 +332,14 @@
    -

    void Forward(Complex[] samples, FourierOptions options)

    +

    void Forward(Complex32[] samples, FourierOptions options)

    Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
    Parameters
    -
    Complex[] samples
    +
    Complex32[] samples

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -347,16 +349,16 @@
    -

    void Forward(Single[] real, Single[] imaginary, FourierOptions options)

    +

    void Forward(Double[] real, Double[] imaginary, FourierOptions options)

    Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
    Parameters
    -
    Single[] real
    +
    Double[] real

    Real part of the sample vector, where the FFT is evaluated in place.

    -
    Single[] imaginary
    +
    Double[] imaginary

    Imaginary part of the sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -366,17 +368,15 @@
    -

    void Forward(Double[] real, Double[] imaginary, FourierOptions options)

    +

    void Forward(Complex[] samples, FourierOptions options)

    Applies the forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors.
    Parameters
    -
    Double[] real
    -

    Real part of the sample vector, where the FFT is evaluated in place.

    -
    Double[] imaginary
    -

    Imaginary part of the sample vector, where the FFT is evaluated in place.

    +
    Complex[] samples
    +

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -448,14 +448,14 @@
    -

    void ForwardMultiDim(Complex[] samples, Int32[] dimensions, FourierOptions options)

    +

    void ForwardMultiDim(Complex32[] samples, Int32[] dimensions, FourierOptions options)

    Applies the forward Fast Fourier Transform (FFT) to multiple dimensional sample data.
    Parameters
    -
    Complex[] samples
    +
    Complex32[] samples

    Sample data, where the FFT is evaluated in place.

    Int32[] dimensions

    The data size per dimension. The first dimension is the major one. @@ -468,14 +468,14 @@ For example, with two dimensions "rows" and "columns" the samples are assumed to

    -

    void ForwardMultiDim(Complex32[] samples, Int32[] dimensions, FourierOptions options)

    +

    void ForwardMultiDim(Complex[] samples, Int32[] dimensions, FourierOptions options)

    Applies the forward Fast Fourier Transform (FFT) to multiple dimensional sample data.
    Parameters
    -
    Complex32[] samples
    +
    Complex[] samples

    Sample data, where the FFT is evaluated in place.

    Int32[] dimensions

    The data size per dimension. The first dimension is the major one. @@ -488,17 +488,17 @@ For example, with two dimensions "rows" and "columns" the samples are assumed to

    -

    void ForwardReal(Double[] data, int n, FourierOptions options)

    +

    void ForwardReal(Single[] data, int n, FourierOptions options)

    Packed Real-Complex forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors. Since for real-valued time samples the complex spectrum is conjugate-even (symmetry), -the spectrum can be fully reconstructed form the positive frequencies only (first half). +the spectrum can be fully reconstructed from the positive frequencies only (first half). The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order to support such a packed spectrum.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Data array of length N+2 (if N is even) or N+1 (if N is odd).

    int n

    The number of samples.

    @@ -510,17 +510,17 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    -

    void ForwardReal(Single[] data, int n, FourierOptions options)

    +

    void ForwardReal(Double[] data, int n, FourierOptions options)

    Packed Real-Complex forward Fast Fourier Transform (FFT) to arbitrary-length sample vectors. Since for real-valued time samples the complex spectrum is conjugate-even (symmetry), -the spectrum can be fully reconstructed from the positive frequencies only (first half). +the spectrum can be fully reconstructed form the positive frequencies only (first half). The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order to support such a packed spectrum.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Data array of length N+2 (if N is even) or N+1 (if N is odd).

    int n

    The number of samples.

    @@ -553,22 +553,26 @@ followed by the negative frequencies wrapped around.
    -

    void Inverse(Complex32[] spectrum)

    +

    void Inverse(Single[] real, Single[] imaginary, FourierOptions options)

    Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
    Parameters
    -
    Complex32[] spectrum
    -

    Spectrum data, where the iFFT is evaluated in place.

    +
    Single[] real
    +

    Real part of the sample vector, where the iFFT is evaluated in place.

    +
    Single[] imaginary
    +

    Imaginary part of the sample vector, where the iFFT is evaluated in place.

    +
    FourierOptions options
    +

    Fourier Transform Convention Options.

    -

    void Inverse(Complex[] spectrum)

    +

    void Inverse(Complex[] spectrum, FourierOptions options)

    Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors. @@ -577,6 +581,8 @@ followed by the negative frequencies wrapped around.
    Complex[] spectrum

    Spectrum data, where the iFFT is evaluated in place.

    +
    FourierOptions options
    +

    Fourier Transform Convention Options.

    @@ -600,33 +606,31 @@ followed by the negative frequencies wrapped around.
    -

    void Inverse(Complex[] spectrum, FourierOptions options)

    +

    void Inverse(Complex32[] spectrum)

    Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
    Parameters
    -
    Complex[] spectrum
    +
    Complex32[] spectrum

    Spectrum data, where the iFFT is evaluated in place.

    -
    FourierOptions options
    -

    Fourier Transform Convention Options.

    -

    void Inverse(Single[] real, Single[] imaginary, FourierOptions options)

    +

    void Inverse(Double[] real, Double[] imaginary, FourierOptions options)

    Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
    Parameters
    -
    Single[] real
    +
    Double[] real

    Real part of the sample vector, where the iFFT is evaluated in place.

    -
    Single[] imaginary
    +
    Double[] imaginary

    Imaginary part of the sample vector, where the iFFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -636,19 +640,15 @@ followed by the negative frequencies wrapped around.
    -

    void Inverse(Double[] real, Double[] imaginary, FourierOptions options)

    +

    void Inverse(Complex[] spectrum)

    Applies the inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors.
    Parameters
    -
    Double[] real
    -

    Real part of the sample vector, where the iFFT is evaluated in place.

    -
    Double[] imaginary
    -

    Imaginary part of the sample vector, where the iFFT is evaluated in place.

    -
    FourierOptions options
    -

    Fourier Transform Convention Options.

    +
    Complex[] spectrum
    +

    Spectrum data, where the iFFT is evaluated in place.

    @@ -758,7 +758,7 @@ For example, with two dimensions "rows" and "columns" the samples are assumed to
    -

    void InverseReal(Single[] data, int n, FourierOptions options)

    +

    void InverseReal(Double[] data, int n, FourierOptions options)

    Packed Real-Complex inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors. Since for real-valued time samples the complex spectrum is conjugate-even (symmetry), the spectrum can be fully reconstructed form the positive frequencies only (first half). @@ -768,7 +768,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    Parameters
    -
    Single[] data
    +
    Double[] data

    Data array of length N+2 (if N is even) or N+1 (if N is odd).

    int n

    The number of samples.

    @@ -780,7 +780,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    -

    void InverseReal(Double[] data, int n, FourierOptions options)

    +

    void InverseReal(Single[] data, int n, FourierOptions options)

    Packed Real-Complex inverse Fast Fourier Transform (iFFT) to arbitrary-length sample vectors. Since for real-valued time samples the complex spectrum is conjugate-even (symmetry), the spectrum can be fully reconstructed form the positive frequencies only (first half). @@ -790,7 +790,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    Parameters
    -
    Double[] data
    +
    Single[] data

    Data array of length N+2 (if N is even) or N+1 (if N is odd).

    int n

    The number of samples.

    @@ -902,7 +902,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    -

    void Radix2Forward(Complex32[] samples, FourierOptions options)

    +

    void Radix2Forward(Complex[] samples, FourierOptions options)

    Radix-2 forward FFT for power-of-two sized sample vectors.
    Obsolete: Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then. @@ -912,7 +912,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    Parameters
    -
    Complex32[] samples
    +
    Complex[] samples

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -922,7 +922,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    -

    void Radix2Forward(Complex[] samples, FourierOptions options)

    +

    void Radix2Forward(Complex32[] samples, FourierOptions options)

    Radix-2 forward FFT for power-of-two sized sample vectors.
    Obsolete: Use Forward instead. Will be dropped in version 5.0 and behave like Forward until then. @@ -932,7 +932,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    Parameters
    -
    Complex[] samples
    +
    Complex32[] samples

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -942,7 +942,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    -

    void Radix2Inverse(Complex[] spectrum, FourierOptions options)

    +

    void Radix2Inverse(Complex32[] spectrum, FourierOptions options)

    Radix-2 inverse FFT for power-of-two sized sample vectors.
    Obsolete: Use Inverse instead. Will be dropped in version 5.0 and behave like Inverse until then. @@ -952,7 +952,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    Parameters
    -
    Complex[] spectrum
    +
    Complex32[] spectrum

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -962,7 +962,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    -

    void Radix2Inverse(Complex32[] spectrum, FourierOptions options)

    +

    void Radix2Inverse(Complex[] spectrum, FourierOptions options)

    Radix-2 inverse FFT for power-of-two sized sample vectors.
    Obsolete: Use Inverse instead. Will be dropped in version 5.0 and behave like Inverse until then. @@ -972,7 +972,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order
    Parameters
    -
    Complex32[] spectrum
    +
    Complex[] spectrum

    Sample vector, where the FFT is evaluated in place.

    FourierOptions options

    Fourier Transform Convention Options.

    @@ -984,7 +984,7 @@ The data array needs to be N+2 (if N is even) or N+1 (if N is odd) long in order diff --git a/api/MathNet.Numerics.IntegralTransforms/FourierOptions.htm b/api/MathNet.Numerics.IntegralTransforms/FourierOptions.htm index a800716c..30e5bf3d 100644 --- a/api/MathNet.Numerics.IntegralTransforms/FourierOptions.htm +++ b/api/MathNet.Numerics.IntegralTransforms/FourierOptions.htm @@ -261,8 +261,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -270,11 +273,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -369,7 +369,7 @@
    diff --git a/api/MathNet.Numerics.IntegralTransforms/Hartley.htm b/api/MathNet.Numerics.IntegralTransforms/Hartley.htm index 433fbc8c..05b4db04 100644 --- a/api/MathNet.Numerics.IntegralTransforms/Hartley.htm +++ b/api/MathNet.Numerics.IntegralTransforms/Hartley.htm @@ -212,7 +212,7 @@ diff --git a/api/MathNet.Numerics.IntegralTransforms/HartleyOptions.htm b/api/MathNet.Numerics.IntegralTransforms/HartleyOptions.htm index 3fdd707b..c31c220d 100644 --- a/api/MathNet.Numerics.IntegralTransforms/HartleyOptions.htm +++ b/api/MathNet.Numerics.IntegralTransforms/HartleyOptions.htm @@ -258,8 +258,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -267,11 +270,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -330,7 +330,7 @@
    diff --git a/api/MathNet.Numerics.IntegralTransforms/index.htm b/api/MathNet.Numerics.IntegralTransforms/index.htm index 2ebcd3f1..c0b7f3bd 100644 --- a/api/MathNet.Numerics.IntegralTransforms/index.htm +++ b/api/MathNet.Numerics.IntegralTransforms/index.htm @@ -155,7 +155,7 @@
    diff --git a/api/MathNet.Numerics.Integration/DoubleExponentialTransformation.htm b/api/MathNet.Numerics.Integration/DoubleExponentialTransformation.htm index 738e37a1..b971b40d 100644 --- a/api/MathNet.Numerics.Integration/DoubleExponentialTransformation.htm +++ b/api/MathNet.Numerics.Integration/DoubleExponentialTransformation.htm @@ -129,6 +129,9 @@
    • DoubleExponentialTransformation +
      • +
    • + GaussKronrodRule
    • GaussLegendreRule @@ -154,6 +157,7 @@ or derivative discontinuities and no poles inside the interval.

      Static Functions

      @@ -165,6 +169,32 @@ or derivative discontinuities and no poles inside the interval.

      Public Static Functions

      +
      +

      Complex ContourIntegrate(Func<double, Complex> f, double intervalBegin, double intervalEnd, double targetRelativeError)

      +
      Approximate the integral by the double exponential transformation + + +
      +
      Parameters
      + +
      Func<double, Complex> f
      +

      The analytic smooth complex function to integrate, defined on the real domain.

      +
      double intervalBegin
      +

      Where the interval starts, inclusive and finite.

      +
      double intervalEnd
      +

      Where the interval stops, inclusive and finite.

      +
      double targetRelativeError
      +

      The expected relative accuracy of the approximation.

      +
      + +
      +
      Return
      +
      Complex
      +

      Approximation of the finite integral in the given interval.

      +
      + +
      +

      double Integrate(Func<double, double> f, double intervalBegin, double intervalEnd, double targetRelativeError)

      Approximate the integral by the double exponential transformation @@ -194,7 +224,7 @@ or derivative discontinuities and no poles inside the interval. diff --git a/api/MathNet.Numerics.Integration/GaussKronrodRule.htm b/api/MathNet.Numerics.Integration/GaussKronrodRule.htm new file mode 100644 index 00000000..b9ebc532 --- /dev/null +++ b/api/MathNet.Numerics.Integration/GaussKronrodRule.htm @@ -0,0 +1,287 @@ + + + + GaussKronrodRule - Math.NET Numerics Documentation + + + + + + + +
      +

      Namespaces

      +
      + +
      +
      +

      Types in MathNet.Numerics.Integration

      +
      + +
      +
      +
      +

      Type GaussKronrodRule

      +

      Namespace MathNet.Numerics.Integration

      +
      +
      + +

      Constructors

      + + +

      Static Functions

      + +

      Methods

      + + + +

      Properties

      + + +
      + + +

      Public Constructors

      + +
      +

      GaussKronrodRule(int order)

      +
      + + + + +
      +
      + +

      Public Static Functions

      + +
      +

      Complex ContourIntegrate(Func<double, Complex> f, double intervalBegin, double intervalEnd, Double& error, Double& L1Norm, double targetRelativeError, int maximumDepth, int order)

      +
      + + + + +
      +
      +
      +

      double Integrate(Func<double, double> f, double intervalBegin, double intervalEnd, Double& error, Double& L1Norm, double targetRelativeError, int maximumDepth, int order)

      +
      + + + + +
      +
      + +

      Public Methods

      + +
      +

      bool Equals(object obj)

      +
      + + + + +
      +
      +
      +

      int GetHashCode()

      +
      + + + + +
      +
      +
      +

      Type GetType()

      +
      + + + + +
      +
      +
      +

      string ToString()

      +
      + + + + +
      +
      + +

      Public Properties

      + +
      +

      Double[] GaussWeights get;

      +
      Getter that returns a clone of the array containing the Gauss weights. + +
      +
      +
      +

      Double[] KronrodAbscissas get;

      +
      Getter that returns a clone of the array containing the Kronrod abscissas. + +
      +
      +
      +

      Double[] KronrodWeights get;

      +
      Getter that returns a clone of the array containing the Kronrod weights. + +
      +
      +
      +

      int Order get;

      +
      Getter for the order. + +
      +
      + + + \ No newline at end of file diff --git a/api/MathNet.Numerics.Integration/GaussLegendreRule.htm b/api/MathNet.Numerics.Integration/GaussLegendreRule.htm index a85604ca..8f434fd0 100644 --- a/api/MathNet.Numerics.Integration/GaussLegendreRule.htm +++ b/api/MathNet.Numerics.Integration/GaussLegendreRule.htm @@ -129,6 +129,9 @@
      • DoubleExponentialTransformation +
        • +
      • + GaussKronrodRule
      • GaussLegendreRule @@ -157,6 +160,7 @@

        Static Functions

        @@ -207,6 +211,32 @@

        Public Static Functions

        +
        +

        Complex ContourIntegrate(Func<double, Complex> f, double invervalBegin, double invervalEnd, int order)

        +
        Approximates a definite integral using an Nth order Gauss-Legendre rule. + + +
        +
        Parameters
        + +
        Func<double, Complex> f
        +

        The analytic smooth complex function to integrate, defined on the real domain.

        +
        double invervalBegin
        +

        Where the interval starts, exclusive and finite.

        +
        double invervalEnd
        +

        Where the interval ends, exclusive and finite.

        +
        int order
        +

        Defines an Nth order Gauss-Legendre rule. The order also defines the number of abscissas and weights for the rule. Precomputed Gauss-Legendre abscissas/weights for orders 2-20, 32, 64, 96, 100, 128, 256, 512, 1024 are used, otherwise they're calculated on the fly.

        +
        + +
        +
        Return
        +
        Complex
        +

        Approximation of the finite integral in the given interval.

        +
        + +
        +

        double Integrate(Func<double, double> f, double invervalBegin, double invervalEnd, int order)

        Approximates a definite integral using an Nth order Gauss-Legendre rule. @@ -376,7 +406,7 @@
        diff --git a/api/MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm b/api/MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm index cb6e36cd..f4d9ca69 100644 --- a/api/MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm +++ b/api/MathNet.Numerics.Integration/NewtonCotesTrapeziumRule.htm @@ -129,6 +129,9 @@
        • DoubleExponentialTransformation +
          • +
        • + GaussKronrodRule
        • GaussLegendreRule @@ -153,6 +156,10 @@

          Static Functions

            +
          • ContourIntegrateAdaptive
            • +
          • ContourIntegrateAdaptiveTransformedOdd
            • +
          • ContourIntegrateComposite
            • +
          • ContourIntegrateTwoPoint
          • IntegrateAdaptive
          • IntegrateAdaptiveTransformedOdd
          • IntegrateComposite
            • @@ -167,6 +174,114 @@

            Public Static Functions

            +
            +

            Complex ContourIntegrateAdaptive(Func<double, Complex> f, double intervalBegin, double intervalEnd, double targetError)

            +
            Adaptive approximation of the definite integral in the provided interval by the trapezium rule. + + +
            +
            Parameters
            + +
            Func<double, Complex> f
            +

            The analytic smooth complex function to integrate, define don real domain.

            +
            double intervalBegin
            +

            Where the interval starts, inclusive and finite.

            +
            double intervalEnd
            +

            Where the interval stops, inclusive and finite.

            +
            double targetError
            +

            The expected accuracy of the approximation.

            +
            + +
            +
            Return
            +
            Complex
            +

            Approximation of the finite integral in the given interval.

            +
            + +
            +
            +
            +

            Complex ContourIntegrateAdaptiveTransformedOdd(Func<double, Complex> f, double intervalBegin, double intervalEnd, IEnumerable<Double[]> levelAbscissas, IEnumerable<Double[]> levelWeights, double levelOneStep, double targetRelativeError)

            +
            Adaptive approximation of the definite integral by the trapezium rule. + + +
            +
            Parameters
            + +
            Func<double, Complex> f
            +

            The analytic smooth complex function to integrate, defined on the real domain.

            +
            double intervalBegin
            +

            Where the interval starts, inclusive and finite.

            +
            double intervalEnd
            +

            Where the interval stops, inclusive and finite.

            +
            IEnumerable<Double[]> levelAbscissas
            +

            Abscissa vector per level provider.

            +
            IEnumerable<Double[]> levelWeights
            +

            Weight vector per level provider.

            +
            double levelOneStep
            +

            First Level Step

            +
            double targetRelativeError
            +

            The expected relative accuracy of the approximation.

            +
            + +
            +
            Return
            +
            Complex
            +

            Approximation of the finite integral in the given interval.

            +
            + +
            +
            +
            +

            Complex ContourIntegrateComposite(Func<double, Complex> f, double intervalBegin, double intervalEnd, int numberOfPartitions)

            +
            Composite N-point approximation of the definite integral in the provided interval by the trapezium rule. + + +
            +
            Parameters
            + +
            Func<double, Complex> f
            +

            The analytic smooth complex function to integrate, defined on real domain.

            +
            double intervalBegin
            +

            Where the interval starts, inclusive and finite.

            +
            double intervalEnd
            +

            Where the interval stops, inclusive and finite.

            +
            int numberOfPartitions
            +

            Number of composite subdivision partitions.

            +
            + +
            +
            Return
            +
            Complex
            +

            Approximation of the finite integral in the given interval.

            +
            + +
            +
            +
            +

            Complex ContourIntegrateTwoPoint(Func<double, Complex> f, double intervalBegin, double intervalEnd)

            +
            Direct 2-point approximation of the definite integral in the provided interval by the trapezium rule. + + +
            +
            Parameters
            + +
            Func<double, Complex> f
            +

            The analytic smooth complex function to integrate, defined on real domain.

            +
            double intervalBegin
            +

            Where the interval starts, inclusive and finite.

            +
            double intervalEnd
            +

            Where the interval stops, inclusive and finite.

            +
            + +
            +
            Return
            +
            Complex
            +

            Approximation of the finite integral in the given interval.

            +
            + +
            +

            double IntegrateAdaptive(Func<double, double> f, double intervalBegin, double intervalEnd, double targetError)

            Adaptive approximation of the definite integral in the provided interval by the trapezium rule. @@ -278,7 +393,7 @@ diff --git a/api/MathNet.Numerics.Integration/SimpsonRule.htm b/api/MathNet.Numerics.Integration/SimpsonRule.htm index 061c1d30..7cd7a7dd 100644 --- a/api/MathNet.Numerics.Integration/SimpsonRule.htm +++ b/api/MathNet.Numerics.Integration/SimpsonRule.htm @@ -129,6 +129,9 @@
            diff --git a/api/MathNet.Numerics.Interpolation/Barycentric.htm b/api/MathNet.Numerics.Interpolation/Barycentric.htm index e4a23724..da435512 100644 --- a/api/MathNet.Numerics.Interpolation/Barycentric.htm +++ b/api/MathNet.Numerics.Interpolation/Barycentric.htm @@ -443,7 +443,7 @@ The values are assumed to be sorted ascendingly by x.
            diff --git a/api/MathNet.Numerics.Interpolation/BulirschStoerRationalInterpolation.htm b/api/MathNet.Numerics.Interpolation/BulirschStoerRationalInterpolation.htm index 2b5635b5..707f45e5 100644 --- a/api/MathNet.Numerics.Interpolation/BulirschStoerRationalInterpolation.htm +++ b/api/MathNet.Numerics.Interpolation/BulirschStoerRationalInterpolation.htm @@ -310,7 +310,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
      diff --git a/api/MathNet.Numerics.Interpolation/CubicSpline.htm b/api/MathNet.Numerics.Interpolation/CubicSpline.htm index 3c94b41a..087038ca 100644 --- a/api/MathNet.Numerics.Interpolation/CubicSpline.htm +++ b/api/MathNet.Numerics.Interpolation/CubicSpline.htm @@ -492,7 +492,7 @@ and zero second derivatives at the two boundaries, sorted ascendingly by x.
      diff --git a/api/MathNet.Numerics.Interpolation/IInterpolation.htm b/api/MathNet.Numerics.Interpolation/IInterpolation.htm index 98a438e8..0888c966 100644 --- a/api/MathNet.Numerics.Interpolation/IInterpolation.htm +++ b/api/MathNet.Numerics.Interpolation/IInterpolation.htm @@ -303,7 +303,7 @@
    diff --git a/api/MathNet.Numerics.Interpolation/LinearSpline.htm b/api/MathNet.Numerics.Interpolation/LinearSpline.htm index e9c3ccc6..3c124f5b 100644 --- a/api/MathNet.Numerics.Interpolation/LinearSpline.htm +++ b/api/MathNet.Numerics.Interpolation/LinearSpline.htm @@ -388,7 +388,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
    diff --git a/api/MathNet.Numerics.Interpolation/LogLinear.htm b/api/MathNet.Numerics.Interpolation/LogLinear.htm index 3f931a6f..1c9dcf06 100644 --- a/api/MathNet.Numerics.Interpolation/LogLinear.htm +++ b/api/MathNet.Numerics.Interpolation/LogLinear.htm @@ -352,7 +352,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered and m
    diff --git a/api/MathNet.Numerics.Interpolation/NevillePolynomialInterpolation.htm b/api/MathNet.Numerics.Interpolation/NevillePolynomialInterpolation.htm index d0cc53e9..b7ae6000 100644 --- a/api/MathNet.Numerics.Interpolation/NevillePolynomialInterpolation.htm +++ b/api/MathNet.Numerics.Interpolation/NevillePolynomialInterpolation.htm @@ -354,7 +354,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
    diff --git a/api/MathNet.Numerics.Interpolation/QuadraticSpline.htm b/api/MathNet.Numerics.Interpolation/QuadraticSpline.htm index f22ffb1f..3b7dab89 100644 --- a/api/MathNet.Numerics.Interpolation/QuadraticSpline.htm +++ b/api/MathNet.Numerics.Interpolation/QuadraticSpline.htm @@ -354,7 +354,7 @@
    diff --git a/api/MathNet.Numerics.Interpolation/SplineBoundaryCondition.htm b/api/MathNet.Numerics.Interpolation/SplineBoundaryCondition.htm index c5119630..38a31bff 100644 --- a/api/MathNet.Numerics.Interpolation/SplineBoundaryCondition.htm +++ b/api/MathNet.Numerics.Interpolation/SplineBoundaryCondition.htm @@ -280,8 +280,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -289,11 +292,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -364,7 +364,7 @@
    diff --git a/api/MathNet.Numerics.Interpolation/StepInterpolation.htm b/api/MathNet.Numerics.Interpolation/StepInterpolation.htm index 44b2bb82..131cba8b 100644 --- a/api/MathNet.Numerics.Interpolation/StepInterpolation.htm +++ b/api/MathNet.Numerics.Interpolation/StepInterpolation.htm @@ -388,7 +388,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered.
    diff --git a/api/MathNet.Numerics.Interpolation/TransformedInterpolation.htm b/api/MathNet.Numerics.Interpolation/TransformedInterpolation.htm index 0b52d2fc..ee3e0658 100644 --- a/api/MathNet.Numerics.Interpolation/TransformedInterpolation.htm +++ b/api/MathNet.Numerics.Interpolation/TransformedInterpolation.htm @@ -302,7 +302,7 @@ WARNING: Works in-place and can thus causes the data array to be reordered and m
    diff --git a/api/MathNet.Numerics.Interpolation/index.htm b/api/MathNet.Numerics.Interpolation/index.htm index 6c35e443..67d7fab7 100644 --- a/api/MathNet.Numerics.Interpolation/index.htm +++ b/api/MathNet.Numerics.Interpolation/index.htm @@ -186,7 +186,7 @@
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/BiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/BiCgStab.htm index 6a959b04..a174b0f5 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/BiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/BiCgStab.htm @@ -271,7 +271,7 @@ solution vector and x is the unknown vector.
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/CompositeSolver.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/CompositeSolver.htm index 25fc3229..111a3033 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/CompositeSolver.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/CompositeSolver.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector.
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/DiagonalPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/DiagonalPreconditioner.htm index 6cff0c70..f5900845 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/DiagonalPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/DiagonalPreconditioner.htm @@ -272,7 +272,7 @@ of the matrix diagonal as preconditioning values.
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/GpBiCg.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/GpBiCg.htm index b250dc0f..7fc9ae05 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/GpBiCg.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/GpBiCg.htm @@ -291,7 +291,7 @@ before switching over to the BiCgStab algorithm.
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILU0Preconditioner.htm index 97528fe2..90777bc2 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILU0Preconditioner.htm @@ -273,7 +273,7 @@
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILUTPPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILUTPPreconditioner.htm index e27cfde2..3b9ebb4e 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILUTPPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/ILUTPPreconditioner.htm @@ -384,7 +384,7 @@ the preconditioner.

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MILU0Preconditioner.htm index 16c32deb..49cdbcde 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MILU0Preconditioner.htm @@ -298,7 +298,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MlkBiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MlkBiCgStab.htm index 7354f0e6..e7b138f1 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MlkBiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/MlkBiCgStab.htm @@ -299,7 +299,7 @@ Krylov sub-space. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/TFQMR.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/TFQMR.htm index 471b76ec..15258c1e 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/TFQMR.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/TFQMR.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/index.htm b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/index.htm index 34b3578e..e8a360ce 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex.Solvers/index.htm @@ -175,7 +175,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/DenseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/DenseMatrix.htm index 1219cd15..1f8679f8 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/DenseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/DenseMatrix.htm @@ -4601,7 +4601,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/DenseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/DenseVector.htm index 267ac04c..51cbeead 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/DenseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/DenseVector.htm @@ -2637,7 +2637,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/DiagonalMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/DiagonalMatrix.htm index d96d50bf..a79d74e8 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/DiagonalMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/DiagonalMatrix.htm @@ -4400,7 +4400,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/Matrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/Matrix.htm index 4b75ed06..9abfa591 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/Matrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/Matrix.htm @@ -4237,7 +4237,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/SparseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/SparseMatrix.htm index b27e6ede..a1f5cd09 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/SparseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/SparseMatrix.htm @@ -4584,7 +4584,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/SparseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/SparseVector.htm index aabd9a44..5d378f20 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/SparseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/SparseVector.htm @@ -2605,7 +2605,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/Vector.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/Vector.htm index 522ac7ae..0fedbb64 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/Vector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/Vector.htm @@ -2458,7 +2458,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex/index.htm b/api/MathNet.Numerics.LinearAlgebra.Complex/index.htm index 47be29d1..6e86938c 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex/index.htm @@ -167,7 +167,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/BiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/BiCgStab.htm index 7fde80f7..45954162 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/BiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/BiCgStab.htm @@ -271,7 +271,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/CompositeSolver.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/CompositeSolver.htm index a28ff0fd..0af2df6e 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/CompositeSolver.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/CompositeSolver.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/DiagonalPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/DiagonalPreconditioner.htm index e3714f49..e29aec34 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/DiagonalPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/DiagonalPreconditioner.htm @@ -272,7 +272,7 @@ of the matrix diagonal as preconditioning values. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/GpBiCg.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/GpBiCg.htm index 00fce67f..75185ebb 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/GpBiCg.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/GpBiCg.htm @@ -291,7 +291,7 @@ before switching over to the BiCgStab algorithm. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILU0Preconditioner.htm index 94be15f4..f2c6c527 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILU0Preconditioner.htm @@ -273,7 +273,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILUTPPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILUTPPreconditioner.htm index bfca9e45..d385c179 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILUTPPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/ILUTPPreconditioner.htm @@ -384,7 +384,7 @@ the preconditioner.

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MILU0Preconditioner.htm index 9b2be02b..f7b8aacc 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MILU0Preconditioner.htm @@ -298,7 +298,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MlkBiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MlkBiCgStab.htm index 3cf21f56..375e9d6f 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MlkBiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/MlkBiCgStab.htm @@ -299,7 +299,7 @@ Krylov sub-space. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/TFQMR.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/TFQMR.htm index 3d5f826d..ffb90778 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/TFQMR.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/TFQMR.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/index.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/index.htm index cfa5364d..28e131f3 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32.Solvers/index.htm @@ -175,7 +175,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseMatrix.htm index 71086aa3..6068632d 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseMatrix.htm @@ -4601,7 +4601,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseVector.htm index 75f329a0..b7acec41 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/DenseVector.htm @@ -2637,7 +2637,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/DiagonalMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/DiagonalMatrix.htm index ca7459aa..490d5d4c 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/DiagonalMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/DiagonalMatrix.htm @@ -4400,7 +4400,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/Matrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/Matrix.htm index d5aea3fa..f936e39e 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/Matrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/Matrix.htm @@ -4237,7 +4237,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseMatrix.htm index 1cb93146..ad702c04 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseMatrix.htm @@ -4584,7 +4584,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseVector.htm index e1198769..9d2fbc46 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/SparseVector.htm @@ -2605,7 +2605,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/Vector.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/Vector.htm index 3d92ca6d..fa05cbab 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/Vector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/Vector.htm @@ -2458,7 +2458,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Complex32/index.htm b/api/MathNet.Numerics.LinearAlgebra.Complex32/index.htm index 74bac865..7d1fc113 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Complex32/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Complex32/index.htm @@ -167,7 +167,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/BiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/BiCgStab.htm index 0b21682a..dc239a77 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/BiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/BiCgStab.htm @@ -271,7 +271,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/CompositeSolver.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/CompositeSolver.htm index c02b434d..cb007141 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/CompositeSolver.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/CompositeSolver.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/DiagonalPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/DiagonalPreconditioner.htm index 745b5909..7d9eeac6 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/DiagonalPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/DiagonalPreconditioner.htm @@ -272,7 +272,7 @@ of the matrix diagonal as preconditioning values. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/GpBiCg.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/GpBiCg.htm index 1a6537be..ccbdb954 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/GpBiCg.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/GpBiCg.htm @@ -291,7 +291,7 @@ before switching over to the BiCgStab algorithm. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILU0Preconditioner.htm index 56c2a073..233e7222 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILU0Preconditioner.htm @@ -273,7 +273,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILUTPPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILUTPPreconditioner.htm index 6c1cad50..346708d4 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILUTPPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/ILUTPPreconditioner.htm @@ -384,7 +384,7 @@ the preconditioner.

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MILU0Preconditioner.htm index 33453011..c92c4da7 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MILU0Preconditioner.htm @@ -298,7 +298,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MlkBiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MlkBiCgStab.htm index 0252e0d4..7deabe16 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MlkBiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/MlkBiCgStab.htm @@ -299,7 +299,7 @@ Krylov sub-space. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/TFQMR.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/TFQMR.htm index 080713af..972109d2 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/TFQMR.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/TFQMR.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/index.htm b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/index.htm index 206e9efa..573cc8bb 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double.Solvers/index.htm @@ -175,7 +175,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/DenseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Double/DenseMatrix.htm index ff6b7d84..3c24a9c4 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/DenseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/DenseMatrix.htm @@ -4601,7 +4601,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/DenseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Double/DenseVector.htm index 7f4c7c47..7b493608 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/DenseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/DenseVector.htm @@ -2637,7 +2637,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/DiagonalMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Double/DiagonalMatrix.htm index 1decbb51..61c9249c 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/DiagonalMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/DiagonalMatrix.htm @@ -4400,7 +4400,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/Matrix.htm b/api/MathNet.Numerics.LinearAlgebra.Double/Matrix.htm index 73e85900..be4b5390 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/Matrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/Matrix.htm @@ -4237,7 +4237,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/SparseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Double/SparseMatrix.htm index d6f35ace..4b6f2c5b 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/SparseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/SparseMatrix.htm @@ -4584,7 +4584,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/SparseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Double/SparseVector.htm index b9492952..8560d24b 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/SparseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/SparseVector.htm @@ -2605,7 +2605,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/Vector.htm b/api/MathNet.Numerics.LinearAlgebra.Double/Vector.htm index e2005a89..e7cb3149 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/Vector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/Vector.htm @@ -2458,7 +2458,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Double/index.htm b/api/MathNet.Numerics.LinearAlgebra.Double/index.htm index 7c429ed8..c317eb8d 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Double/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Double/index.htm @@ -167,7 +167,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/Cholesky`1.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/Cholesky`1.htm index bed9e3a2..8a601d0f 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/Cholesky`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/Cholesky`1.htm @@ -343,7 +343,7 @@ or positive definite, the constructor will throw an exception. diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/Evd`1.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/Evd`1.htm index 4753099a..c2dff9fe 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/Evd`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/Evd`1.htm @@ -366,7 +366,7 @@ A = V*D*Inverse(V) depends upon V.Condition(). diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/GramSchmidt`1.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/GramSchmidt`1.htm index 8604c8f4..932ccb26 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/GramSchmidt`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/GramSchmidt`1.htm @@ -332,7 +332,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/ISolver`1.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/ISolver`1.htm index 50b5c229..893c9209 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/ISolver`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/ISolver`1.htm @@ -256,7 +256,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/LU`1.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/LU`1.htm index 1ee1c04a..3eb1d216 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/LU`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/LU`1.htm @@ -349,7 +349,7 @@ numerical stability. The pivot elements encode a permutation matrix P such that diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/QRMethod.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/QRMethod.htm index 19c07d04..23865437 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/QRMethod.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/QRMethod.htm @@ -269,8 +269,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -278,11 +281,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -329,7 +329,7 @@
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/QR`1.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/QR`1.htm index a0a12038..4c166806 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/QR`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/QR`1.htm @@ -339,7 +339,7 @@ resulting Q matrix is an m x n matrix and the R matrix is an n x n matrix. diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/Svd`1.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/Svd`1.htm index 50efda17..dd724ecf 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/Svd`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/Svd`1.htm @@ -369,7 +369,7 @@ by M (though the matrices U and V are not). The diagonal entries of Σ are known diff --git a/api/MathNet.Numerics.LinearAlgebra.Factorization/index.htm b/api/MathNet.Numerics.LinearAlgebra.Factorization/index.htm index 37a18260..58278a8d 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Factorization/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Factorization/index.htm @@ -174,7 +174,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/BiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/BiCgStab.htm index ed91253d..d419257a 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/BiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/BiCgStab.htm @@ -271,7 +271,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/CompositeSolver.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/CompositeSolver.htm index b3d32b09..31ba886b 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/CompositeSolver.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/CompositeSolver.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/DiagonalPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/DiagonalPreconditioner.htm index 42927d8c..20e66484 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/DiagonalPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/DiagonalPreconditioner.htm @@ -272,7 +272,7 @@ of the matrix diagonal as preconditioning values. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/GpBiCg.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/GpBiCg.htm index c2fce102..4fbe2434 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/GpBiCg.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/GpBiCg.htm @@ -291,7 +291,7 @@ before switching over to the BiCgStab algorithm. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILU0Preconditioner.htm index b50c7e77..6c72e963 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILU0Preconditioner.htm @@ -273,7 +273,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILUTPPreconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILUTPPreconditioner.htm index 997454da..e3c44ad7 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILUTPPreconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/ILUTPPreconditioner.htm @@ -384,7 +384,7 @@ the preconditioner.

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MILU0Preconditioner.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MILU0Preconditioner.htm index 86da5bb4..2ac892db 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MILU0Preconditioner.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MILU0Preconditioner.htm @@ -298,7 +298,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MlkBiCgStab.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MlkBiCgStab.htm index 1dcc25e3..5d810af4 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MlkBiCgStab.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/MlkBiCgStab.htm @@ -299,7 +299,7 @@ Krylov sub-space. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/TFQMR.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/TFQMR.htm index 0d8f04bb..2b095d0e 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/TFQMR.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/TFQMR.htm @@ -265,7 +265,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/index.htm b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/index.htm index f345193c..7b11f81c 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single.Solvers/index.htm @@ -175,7 +175,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/DenseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Single/DenseMatrix.htm index 87e019cd..53a0e455 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/DenseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/DenseMatrix.htm @@ -4601,7 +4601,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/DenseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Single/DenseVector.htm index 9be20cdb..de3454ac 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/DenseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/DenseVector.htm @@ -2637,7 +2637,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/DiagonalMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Single/DiagonalMatrix.htm index 478c830f..18ff0e0d 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/DiagonalMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/DiagonalMatrix.htm @@ -4400,7 +4400,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/Matrix.htm b/api/MathNet.Numerics.LinearAlgebra.Single/Matrix.htm index add19415..259bc239 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/Matrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/Matrix.htm @@ -4237,7 +4237,7 @@ The maximum number of cells can be configured in the -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/SparseMatrix.htm b/api/MathNet.Numerics.LinearAlgebra.Single/SparseMatrix.htm index 2709c953..756d75c0 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/SparseMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/SparseMatrix.htm @@ -4584,7 +4584,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/SparseVector.htm b/api/MathNet.Numerics.LinearAlgebra.Single/SparseVector.htm index 262aec3d..ce2a1cd6 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/SparseVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/SparseVector.htm @@ -2605,7 +2605,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/Vector.htm b/api/MathNet.Numerics.LinearAlgebra.Single/Vector.htm index 6b507bb9..e3a019bb 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/Vector.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/Vector.htm @@ -2458,7 +2458,7 @@ The format string is ignored. diff --git a/api/MathNet.Numerics.LinearAlgebra.Single/index.htm b/api/MathNet.Numerics.LinearAlgebra.Single/index.htm index e4496638..c16cb1cf 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Single/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Single/index.htm @@ -167,7 +167,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/CancellationStopCriterion`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/CancellationStopCriterion`1.htm index 4bf3ad6e..3efd3218 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/CancellationStopCriterion`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/CancellationStopCriterion`1.htm @@ -336,7 +336,7 @@ calculation has moved forwards at least one step. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/DelegateStopCriterion`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/DelegateStopCriterion`1.htm index c0d48f9d..4de62d14 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/DelegateStopCriterion`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/DelegateStopCriterion`1.htm @@ -317,7 +317,7 @@ calculation has moved forwards at least one step. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/DivergenceStopCriterion`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/DivergenceStopCriterion`1.htm index aa8cbf4e..843cc6e9 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/DivergenceStopCriterion`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/DivergenceStopCriterion`1.htm @@ -340,7 +340,7 @@ issuing a divergence warning. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/FailureStopCriterion`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/FailureStopCriterion`1.htm index 7038872d..75bee4b7 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/FailureStopCriterion`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/FailureStopCriterion`1.htm @@ -316,7 +316,7 @@ calculation has moved forwards at least one step. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterationStopCriterion`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterationStopCriterion`1.htm index 55aded3f..4868a1a5 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterationStopCriterion`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterationStopCriterion`1.htm @@ -261,7 +261,7 @@ calculation. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolverSetup`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolverSetup`1.htm index cf2e75f3..84048b44 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolverSetup`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolverSetup`1.htm @@ -255,7 +255,7 @@ setup information around. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolver`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolver`1.htm index dffb880a..454c08c0 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolver`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/IIterativeSolver`1.htm @@ -222,7 +222,7 @@ solution vector and x is the unknown vector. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/IPreconditioner`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/IPreconditioner`1.htm index 4f5a20f6..03addc25 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/IPreconditioner`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/IPreconditioner`1.htm @@ -239,7 +239,7 @@ if the changes occur after creating the preconditioner.

    diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationCountStopCriterion`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationCountStopCriterion`1.htm index dfe83d96..690a0567 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationCountStopCriterion`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationCountStopCriterion`1.htm @@ -371,7 +371,7 @@ to perform. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationStatus.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationStatus.htm index c39a3370..57614728 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationStatus.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/IterationStatus.htm @@ -291,8 +291,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -300,11 +303,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -399,7 +399,7 @@
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/Iterator`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/Iterator`1.htm index 6cf3bf62..9562cea0 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/Iterator`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/Iterator`1.htm @@ -354,7 +354,7 @@ calculation has moved forwards at least one step. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/ResidualStopCriterion`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/ResidualStopCriterion`1.htm index 6da2fc62..546ccfce 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/ResidualStopCriterion`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/ResidualStopCriterion`1.htm @@ -342,7 +342,7 @@ below the maximum before the calculation is considered converged. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/SolverSetup`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/SolverSetup`1.htm index d18facae..0273c67f 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/SolverSetup`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/SolverSetup`1.htm @@ -280,7 +280,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/UnitPreconditioner`1.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/UnitPreconditioner`1.htm index 3f8bf06b..2734132e 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/UnitPreconditioner`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/UnitPreconditioner`1.htm @@ -288,7 +288,7 @@ a preconditioner. diff --git a/api/MathNet.Numerics.LinearAlgebra.Solvers/index.htm b/api/MathNet.Numerics.LinearAlgebra.Solvers/index.htm index 111537a5..48fc2c0f 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Solvers/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Solvers/index.htm @@ -198,7 +198,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/DenseColumnMajorMatrixStorage`1.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/DenseColumnMajorMatrixStorage`1.htm index 308854fe..cabfc05c 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/DenseColumnMajorMatrixStorage`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/DenseColumnMajorMatrixStorage`1.htm @@ -882,7 +882,7 @@ False if some fields are fixed, like on a diagonal matrix. diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/DenseVectorStorage`1.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/DenseVectorStorage`1.htm index 7a28e291..85656b7a 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/DenseVectorStorage`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/DenseVectorStorage`1.htm @@ -402,41 +402,41 @@
    -

    bool Equals(VectorStorage<T> other)

    -
    Indicates whether the current object is equal to another object of the same type. +

    bool Equals(object obj)

    +
    Determines whether the specified Object is equal to the current Object.
    Parameters
    -
    VectorStorage<T> other
    -

    An object to compare with this object.

    +
    object obj
    +

    The Object to compare with the current Object.

    Return
    bool
    -

    true if the current object is equal to the other parameter; otherwise, false.

    +

    true if the specified Object is equal to the current Object ; otherwise, false.

    -

    bool Equals(object obj)

    -
    Determines whether the specified Object is equal to the current Object. +

    bool Equals(VectorStorage<T> other)

    +
    Indicates whether the current object is equal to another object of the same type.
    Parameters
    -
    object obj
    -

    The Object to compare with the current Object.

    +
    VectorStorage<T> other
    +

    An object to compare with this object.

    Return
    bool
    -

    true if the specified Object is equal to the current Object ; otherwise, false.

    +

    true if the current object is equal to the other parameter; otherwise, false.

    @@ -596,7 +596,7 @@
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/DiagonalMatrixStorage`1.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/DiagonalMatrixStorage`1.htm index 6428b16e..836aca2e 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/DiagonalMatrixStorage`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/DiagonalMatrixStorage`1.htm @@ -782,7 +782,7 @@ False if some fields are fixed, like on a diagonal matrix.
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/MatrixStorage`1.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/MatrixStorage`1.htm index 830dd390..c6b8ecea 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/MatrixStorage`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/MatrixStorage`1.htm @@ -735,7 +735,7 @@ False if some fields are fixed, like on a diagonal matrix. diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/SparseCompressedRowMatrixStorage`1.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/SparseCompressedRowMatrixStorage`1.htm index bd11fadb..d9356763 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/SparseCompressedRowMatrixStorage`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/SparseCompressedRowMatrixStorage`1.htm @@ -471,7 +471,7 @@
    -

    void Clear()

    +

    void Clear(int rowIndex, int rowCount, int columnIndex, int columnCount)

    @@ -480,7 +480,7 @@
    -

    void Clear(int rowIndex, int rowCount, int columnIndex, int columnCount)

    +

    void Clear()

    @@ -984,7 +984,7 @@ array using the row-major storage mapping described in a compressed sparse row (
    diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/SparseVectorStorage`1.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/SparseVectorStorage`1.htm index e75b218c..90243529 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/SparseVectorStorage`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/SparseVectorStorage`1.htm @@ -611,7 +611,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/VectorStorage`1.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/VectorStorage`1.htm index 489c4ac9..507e25dd 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/VectorStorage`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/VectorStorage`1.htm @@ -555,7 +555,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra.Storage/index.htm b/api/MathNet.Numerics.LinearAlgebra.Storage/index.htm index 0fd16ee5..d4b793c6 100644 --- a/api/MathNet.Numerics.LinearAlgebra.Storage/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra.Storage/index.htm @@ -167,7 +167,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra/CreateMatrix.htm b/api/MathNet.Numerics.LinearAlgebra/CreateMatrix.htm index 4175ee0c..6ac179de 100644 --- a/api/MathNet.Numerics.LinearAlgebra/CreateMatrix.htm +++ b/api/MathNet.Numerics.LinearAlgebra/CreateMatrix.htm @@ -269,10 +269,11 @@

    Public Static Functions

    -

    Matrix<T> Dense<T>(int rows, int columns, T[] storage)

    -
    Create a new dense matrix with the given number of rows and columns directly binding to a raw array. -The array is assumed to be in column-major order (column by column) and is used directly without copying. -Very efficient, but changes to the array and the matrix will affect each other. +

    Matrix<T> Dense<T>(DenseColumnMajorMatrixStorage<T> storage)

    +
    Create a new dense matrix straight from an initialized matrix storage instance. +The storage is used directly without copying. +Intended for advanced scenarios where you're working directly with +storage for performance or interop reasons. @@ -280,8 +281,10 @@ Very efficient, but changes to the array and the matrix will affect each other.
    -

    Matrix<T> Dense<T>(int rows, int columns, Func<int, int, T> init)

    -
    Create a new dense matrix and initialize each value using the provided init function. +

    Matrix<T> Dense<T>(int rows, int columns, T[] storage)

    +
    Create a new dense matrix with the given number of rows and columns directly binding to a raw array. +The array is assumed to be in column-major order (column by column) and is used directly without copying. +Very efficient, but changes to the array and the matrix will affect each other. @@ -298,10 +301,8 @@ Very efficient, but changes to the array and the matrix will affect each other.
    -

    Matrix<T> Dense<T>(int rows, int columns)

    -
    Create a new dense matrix with the given number of rows and columns. -All cells of the matrix will be initialized to zero. -Zero-length matrices are not supported. +

    Matrix<T> Dense<T>(int rows, int columns, Func<int, int, T> init)

    +
    Create a new dense matrix and initialize each value using the provided init function. @@ -309,11 +310,10 @@ Zero-length matrices are not supported.
    -

    Matrix<T> Dense<T>(DenseColumnMajorMatrixStorage<T> storage)

    -
    Create a new dense matrix straight from an initialized matrix storage instance. -The storage is used directly without copying. -Intended for advanced scenarios where you're working directly with -storage for performance or interop reasons. +

    Matrix<T> Dense<T>(int rows, int columns)

    +
    Create a new dense matrix with the given number of rows and columns. +All cells of the matrix will be initialized to zero. +Zero-length matrices are not supported. @@ -321,8 +321,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseDiagonal<T>(int rows, int columns, Func<int, T> init)

    -
    Create a new diagonal dense matrix and initialize each diagonal value using the provided init function. +

    Matrix<T> DenseDiagonal<T>(int rows, int columns, T value)

    +
    Create a new diagonal dense matrix and initialize each diagonal value to the same provided value. @@ -339,8 +339,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseDiagonal<T>(int rows, int columns, T value)

    -
    Create a new diagonal dense matrix and initialize each diagonal value to the same provided value. +

    Matrix<T> DenseDiagonal<T>(int rows, int columns, Func<int, T> init)

    +
    Create a new diagonal dense matrix and initialize each diagonal value using the provided init function. @@ -348,7 +348,7 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseIdentity<T>(int rows, int columns)

    +

    Matrix<T> DenseIdentity<T>(int order)

    Create a new diagonal dense identity matrix with a one-diagonal. @@ -357,7 +357,7 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseIdentity<T>(int order)

    +

    Matrix<T> DenseIdentity<T>(int rows, int columns)

    Create a new diagonal dense identity matrix with a one-diagonal. @@ -375,10 +375,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseOfColumnArrays<T>(IEnumerable<T[]> columns)

    -
    Create a new dense matrix of T as a copy of the given column arrays. -This new matrix will be independent from the arrays. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> DenseOfColumnArrays<T>(T[][] columns)

    +
    @@ -386,8 +384,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumnArrays<T>(T[][] columns)

    -
    +

    Matrix<T> DenseOfColumnArrays<T>(IEnumerable<T[]> columns)

    +
    Create a new dense matrix of T as a copy of the given column arrays. +This new matrix will be independent from the arrays. +A new memory block will be allocated for storing the matrix. @@ -407,7 +407,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumns<T>(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> DenseOfColumns<T>(IEnumerable<IEnumerable<T>> data)

    Create a new dense matrix as a copy of the given enumerable of enumerable columns. Each enumerable in the master enumerable specifies a column. This new matrix will be independent from the enumerables. @@ -419,7 +419,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumns<T>(IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> DenseOfColumns<T>(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    Create a new dense matrix as a copy of the given enumerable of enumerable columns. Each enumerable in the master enumerable specifies a column. This new matrix will be independent from the enumerables. @@ -431,10 +431,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumnVectors<T>(IEnumerable<Vector<T>> columns)

    -
    Create a new dense matrix as a copy of the given column vectors. -This new matrix will be independent from the vectors. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> DenseOfColumnVectors<T>(Vector`1[] columns)

    +
    @@ -442,8 +440,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumnVectors<T>(Vector`1[] columns)

    -
    +

    Matrix<T> DenseOfColumnVectors<T>(IEnumerable<Vector<T>> columns)

    +
    Create a new dense matrix as a copy of the given column vectors. +This new matrix will be independent from the vectors. +A new memory block will be allocated for storing the matrix. @@ -527,8 +527,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRowArrays<T>(T[][] rows)

    -
    +

    Matrix<T> DenseOfRowArrays<T>(IEnumerable<T[]> rows)

    +
    Create a new dense matrix of T as a copy of the given row arrays. +This new matrix will be independent from the arrays. +A new memory block will be allocated for storing the matrix. @@ -536,10 +538,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRowArrays<T>(IEnumerable<T[]> rows)

    -
    Create a new dense matrix of T as a copy of the given row arrays. -This new matrix will be independent from the arrays. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> DenseOfRowArrays<T>(T[][] rows)

    +
    @@ -547,7 +547,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRows<T>(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> DenseOfRows<T>(IEnumerable<IEnumerable<T>> data)

    Create a new dense matrix as a copy of the given enumerable of enumerable rows. Each enumerable in the master enumerable specifies a row. This new matrix will be independent from the enumerables. @@ -559,7 +559,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRows<T>(IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> DenseOfRows<T>(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    Create a new dense matrix as a copy of the given enumerable of enumerable rows. Each enumerable in the master enumerable specifies a row. This new matrix will be independent from the enumerables. @@ -568,6 +568,15 @@ A new memory block will be allocated for storing the matrix. +
    +
    +
    +

    Matrix<T> DenseOfRowVectors<T>(Vector`1[] rows)

    +
    + + + +
    @@ -581,9 +590,9 @@ A new memory block will be allocated for storing the matrix.
    -
    -

    Matrix<T> DenseOfRowVectors<T>(Vector`1[] rows)

    -
    +
    +

    Matrix<T> Diagonal<T>(int rows, int columns, Func<int, T> init)

    +
    Create a new diagonal matrix and initialize each diagonal value using the provided init function. @@ -633,15 +642,6 @@ Very efficient, but changes to the array and the matrix will affect each other. -
    -
    -
    -

    Matrix<T> Diagonal<T>(int rows, int columns, Func<int, T> init)

    -
    Create a new diagonal matrix and initialize each diagonal value using the provided init function. - - - -
    @@ -694,7 +694,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DiagonalOfDiagonalVector<T>(Vector<T> diagonal)

    +

    Matrix<T> DiagonalOfDiagonalVector<T>(int rows, int columns, Vector<T> diagonal)

    Create a new diagonal matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -705,7 +705,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DiagonalOfDiagonalVector<T>(int rows, int columns, Vector<T> diagonal)

    +

    Matrix<T> DiagonalOfDiagonalVector<T>(Vector<T> diagonal)

    Create a new diagonal matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -716,8 +716,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> Random<T>(int rows, int columns, int seed)

    -
    Create a new dense matrix with values sampled from the standard distribution with a system random source. +

    Matrix<T> Random<T>(int rows, int columns, IContinuousDistribution distribution)

    +
    Create a new dense matrix with values sampled from the provided random distribution. @@ -725,7 +725,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> Random<T>(int rows, int columns)

    +

    Matrix<T> Random<T>(int rows, int columns, int seed)

    Create a new dense matrix with values sampled from the standard distribution with a system random source. @@ -734,8 +734,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> Random<T>(int rows, int columns, IContinuousDistribution distribution)

    -
    Create a new dense matrix with values sampled from the provided random distribution. +

    Matrix<T> Random<T>(int rows, int columns)

    +
    Create a new dense matrix with values sampled from the standard distribution with a system random source. @@ -743,9 +743,9 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> RandomPositiveDefinite<T>(int order)

    +

    Matrix<T> RandomPositiveDefinite<T>(int order, int seed)

    Create a new positive definite dense matrix where each value is the product -of two samples from the standard distribution. +of two samples from the provided random distribution. @@ -753,9 +753,9 @@ of two samples from the standard distribution.
    -

    Matrix<T> RandomPositiveDefinite<T>(int order, IContinuousDistribution distribution)

    +

    Matrix<T> RandomPositiveDefinite<T>(int order)

    Create a new positive definite dense matrix where each value is the product -of two samples from the provided random distribution. +of two samples from the standard distribution. @@ -763,7 +763,7 @@ of two samples from the provided random distribution.
    -

    Matrix<T> RandomPositiveDefinite<T>(int order, int seed)

    +

    Matrix<T> RandomPositiveDefinite<T>(int order, IContinuousDistribution distribution)

    Create a new positive definite dense matrix where each value is the product of two samples from the provided random distribution. @@ -773,8 +773,8 @@ of two samples from the provided random distribution.
    -

    Matrix<T> SameAs<T>(Matrix<T> example, Matrix<T> otherExample)

    -
    Create a new matrix with a type that can represent and is closest to both provided samples and the dimensions of example. +

    Matrix<T> SameAs<T>(Matrix<T> example, Matrix<T> otherExample, int rows, int columns, bool fullyMutable)

    +
    Create a new matrix with a type that can represent and is closest to both provided samples. @@ -782,8 +782,8 @@ of two samples from the provided random distribution.
    -

    Matrix<T> SameAs<T>(Matrix<T> example, Matrix<T> otherExample, int rows, int columns, bool fullyMutable)

    -
    Create a new matrix with a type that can represent and is closest to both provided samples. +

    Matrix<T> SameAs<T>(Matrix<T> example, Matrix<T> otherExample)

    +
    Create a new matrix with a type that can represent and is closest to both provided samples and the dimensions of example. @@ -818,8 +818,11 @@ of two samples from the provided random distribution.
    -

    Matrix<T> Sparse<T>(int rows, int columns, Func<int, int, T> init)

    -
    Create a new sparse matrix and initialize each value using the provided init function. +

    Matrix<T> Sparse<T>(SparseCompressedRowMatrixStorage<T> storage)

    +
    Create a new sparse matrix straight from an initialized matrix storage instance. +The storage is used directly without copying. +Intended for advanced scenarios where you're working directly with +storage for performance or interop reasons. @@ -844,11 +847,8 @@ of two samples from the provided random distribution.
    -

    Matrix<T> Sparse<T>(SparseCompressedRowMatrixStorage<T> storage)

    -
    Create a new sparse matrix straight from an initialized matrix storage instance. -The storage is used directly without copying. -Intended for advanced scenarios where you're working directly with -storage for performance or interop reasons. +

    Matrix<T> Sparse<T>(int rows, int columns, T value)

    +
    Create a new sparse matrix and initialize each value to the same provided value. @@ -856,8 +856,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> Sparse<T>(int rows, int columns, T value)

    -
    Create a new sparse matrix and initialize each value to the same provided value. +

    Matrix<T> Sparse<T>(int rows, int columns, Func<int, int, T> init)

    +
    Create a new sparse matrix and initialize each value using the provided init function. @@ -865,7 +865,7 @@ storage for performance or interop reasons.
    -

    Matrix<T> SparseDiagonal<T>(int rows, int columns, T value)

    +

    Matrix<T> SparseDiagonal<T>(int order, T value)

    Create a new diagonal sparse matrix and initialize each diagonal value to the same provided value. @@ -874,7 +874,7 @@ storage for performance or interop reasons.
    -

    Matrix<T> SparseDiagonal<T>(int order, T value)

    +

    Matrix<T> SparseDiagonal<T>(int rows, int columns, T value)

    Create a new diagonal sparse matrix and initialize each diagonal value to the same provided value. @@ -892,7 +892,7 @@ storage for performance or interop reasons.
    -

    Matrix<T> SparseIdentity<T>(int rows, int columns)

    +

    Matrix<T> SparseIdentity<T>(int order)

    Create a new diagonal dense identity matrix with a one-diagonal. @@ -901,7 +901,7 @@ storage for performance or interop reasons.
    -

    Matrix<T> SparseIdentity<T>(int order)

    +

    Matrix<T> SparseIdentity<T>(int rows, int columns)

    Create a new diagonal dense identity matrix with a one-diagonal. @@ -995,7 +995,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalArray<T>(T[] diagonal)

    +

    Matrix<T> SparseOfDiagonalArray<T>(int rows, int columns, T[] diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -1006,7 +1006,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalArray<T>(int rows, int columns, T[] diagonal)

    +

    Matrix<T> SparseOfDiagonalArray<T>(T[] diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -1017,7 +1017,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalVector<T>(Vector<T> diagonal)

    +

    Matrix<T> SparseOfDiagonalVector<T>(int rows, int columns, Vector<T> diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -1028,7 +1028,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalVector<T>(int rows, int columns, Vector<T> diagonal)

    +

    Matrix<T> SparseOfDiagonalVector<T>(Vector<T> diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -1071,10 +1071,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfRowArrays<T>(IEnumerable<T[]> rows)

    -
    Create a new sparse matrix as a copy of the given row arrays. -This new matrix will be independent from the arrays. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> SparseOfRowArrays<T>(T[][] rows)

    +
    @@ -1082,8 +1080,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfRowArrays<T>(T[][] rows)

    -
    +

    Matrix<T> SparseOfRowArrays<T>(IEnumerable<T[]> rows)

    +
    Create a new sparse matrix as a copy of the given row arrays. +This new matrix will be independent from the arrays. +A new memory block will be allocated for storing the matrix. @@ -1127,8 +1127,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfRowVectors<T>(Vector`1[] rows)

    -
    +

    Matrix<T> SparseOfRowVectors<T>(IEnumerable<Vector<T>> rows)

    +
    Create a new sparse matrix as a copy of the given row vectors. +This new matrix will be independent from the vectors. +A new memory block will be allocated for storing the matrix. @@ -1136,10 +1138,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfRowVectors<T>(IEnumerable<Vector<T>> rows)

    -
    Create a new sparse matrix as a copy of the given row vectors. -This new matrix will be independent from the vectors. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> SparseOfRowVectors<T>(Vector`1[] rows)

    +
    @@ -1159,7 +1159,7 @@ If you have an instance of a discrete storage type instead, use their direct met diff --git a/api/MathNet.Numerics.LinearAlgebra/CreateVector.htm b/api/MathNet.Numerics.LinearAlgebra/CreateVector.htm index 4ef8f90f..b5538fc2 100644 --- a/api/MathNet.Numerics.LinearAlgebra/CreateVector.htm +++ b/api/MathNet.Numerics.LinearAlgebra/CreateVector.htm @@ -318,8 +318,8 @@ A new memory block will be allocated for storing the vector.
    -

    Vector<T> Random<T>(int length, IContinuousDistribution distribution)

    -
    Create a new dense vector with values sampled from the provided random distribution. +

    Vector<T> Random<T>(int length, int seed)

    +
    Create a new dense vector with values sampled from the standard distribution with a system random source. @@ -327,8 +327,8 @@ A new memory block will be allocated for storing the vector.
    -

    Vector<T> Random<T>(int length, int seed)

    -
    Create a new dense vector with values sampled from the standard distribution with a system random source. +

    Vector<T> Random<T>(int length, IContinuousDistribution distribution)

    +
    Create a new dense vector with values sampled from the provided random distribution. @@ -336,8 +336,8 @@ A new memory block will be allocated for storing the vector.
    -

    Vector<T> SameAs<T>(Matrix<T> matrix, Vector<T> vector, int length)

    -
    Create a new vector with a type that can represent and is closest to both provided samples. +

    Vector<T> SameAs<T>(Vector<T> example, Vector<T> otherExample)

    +
    Create a new vector with a type that can represent and is closest to both provided samples and the dimensions of example. @@ -345,8 +345,8 @@ A new memory block will be allocated for storing the vector.
    -

    Vector<T> SameAs<T>(Vector<T> example, Vector<T> otherExample)

    -
    Create a new vector with a type that can represent and is closest to both provided samples and the dimensions of example. +

    Vector<T> SameAs<T>(Matrix<T> matrix, Vector<T> vector, int length)

    +
    Create a new vector with a type that can represent and is closest to both provided samples. @@ -390,8 +390,11 @@ A new memory block will be allocated for storing the vector.
    -

    Vector<T> Sparse<T>(int length, Func<int, T> init)

    -
    Create a new sparse vector and initialize each value using the provided init function. +

    Vector<T> Sparse<T>(SparseVectorStorage<T> storage)

    +
    Create a new sparse vector straight from an initialized vector storage instance. +The storage is used directly without copying. +Intended for advanced scenarios where you're working directly with +storage for performance or interop reasons. @@ -399,20 +402,23 @@ A new memory block will be allocated for storing the vector.
    -

    Vector<T> Sparse<T>(int length, T value)

    -
    Create a new sparse vector and initialize each value using the provided value. +

    Vector<T> Sparse<T>(int size)

    +
    Create a sparse vector of T with the given size. +
    +
    Parameters
    + +
    int size
    +

    The size of the vector.

    +
    -

    Vector<T> Sparse<T>(SparseVectorStorage<T> storage)

    -
    Create a new sparse vector straight from an initialized vector storage instance. -The storage is used directly without copying. -Intended for advanced scenarios where you're working directly with -storage for performance or interop reasons. +

    Vector<T> Sparse<T>(int length, T value)

    +
    Create a new sparse vector and initialize each value using the provided value. @@ -420,16 +426,10 @@ storage for performance or interop reasons.
    -

    Vector<T> Sparse<T>(int size)

    -
    Create a sparse vector of T with the given size. - +

    Vector<T> Sparse<T>(int length, Func<int, T> init)

    +
    Create a new sparse vector and initialize each value using the provided init function. -
    -
    Parameters
    -
    int size
    -

    The size of the vector.

    -
    @@ -492,7 +492,7 @@ If you have an instance of a discrete storage type instead, use their direct met diff --git a/api/MathNet.Numerics.LinearAlgebra/ExistingData.htm b/api/MathNet.Numerics.LinearAlgebra/ExistingData.htm index f23b7097..df290805 100644 --- a/api/MathNet.Numerics.LinearAlgebra/ExistingData.htm +++ b/api/MathNet.Numerics.LinearAlgebra/ExistingData.htm @@ -276,8 +276,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -285,11 +288,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -338,7 +338,7 @@ clearing it may be skipped if applicable.
    diff --git a/api/MathNet.Numerics.LinearAlgebra/MatrixBuilder`1.htm b/api/MathNet.Numerics.LinearAlgebra/MatrixBuilder`1.htm index c186eec0..29835eae 100644 --- a/api/MathNet.Numerics.LinearAlgebra/MatrixBuilder`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra/MatrixBuilder`1.htm @@ -337,8 +337,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseDiagonal(int rows, int columns, Func<int, T> init)

    -
    Create a new diagonal dense matrix and initialize each diagonal value using the provided init function. +

    Matrix<T> DenseDiagonal(int rows, int columns, T value)

    +
    Create a new diagonal dense matrix and initialize each diagonal value to the same provided value. @@ -346,8 +346,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseDiagonal(int order, T value)

    -
    Create a new diagonal dense matrix and initialize each diagonal value to the same provided value. +

    Matrix<T> DenseDiagonal(int rows, int columns, Func<int, T> init)

    +
    Create a new diagonal dense matrix and initialize each diagonal value using the provided init function. @@ -355,7 +355,7 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseDiagonal(int rows, int columns, T value)

    +

    Matrix<T> DenseDiagonal(int order, T value)

    Create a new diagonal dense matrix and initialize each diagonal value to the same provided value. @@ -391,10 +391,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> DenseOfColumnArrays(IEnumerable<T[]> columns)

    -
    Create a new dense matrix of T as a copy of the given column arrays. -This new matrix will be independent from the arrays. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> DenseOfColumnArrays(T[][] columns)

    +
    @@ -402,8 +400,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumnArrays(T[][] columns)

    -
    +

    Matrix<T> DenseOfColumnArrays(IEnumerable<T[]> columns)

    +
    Create a new dense matrix of T as a copy of the given column arrays. +This new matrix will be independent from the arrays. +A new memory block will be allocated for storing the matrix. @@ -447,8 +447,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumnVectors(Vector`1[] columns)

    -
    +

    Matrix<T> DenseOfColumnVectors(IEnumerable<Vector<T>> columns)

    +
    Create a new dense matrix as a copy of the given column vectors. +This new matrix will be independent from the vectors. +A new memory block will be allocated for storing the matrix. @@ -456,10 +458,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfColumnVectors(IEnumerable<Vector<T>> columns)

    -
    Create a new dense matrix as a copy of the given column vectors. -This new matrix will be independent from the vectors. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> DenseOfColumnVectors(Vector`1[] columns)

    +
    @@ -467,7 +467,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfDiagonalArray(int rows, int columns, T[] diagonal)

    +

    Matrix<T> DenseOfDiagonalArray(T[] diagonal)

    Create a new dense matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -478,7 +478,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfDiagonalArray(T[] diagonal)

    +

    Matrix<T> DenseOfDiagonalArray(int rows, int columns, T[] diagonal)

    Create a new dense matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -489,7 +489,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfDiagonalVector(int rows, int columns, Vector<T> diagonal)

    +

    Matrix<T> DenseOfDiagonalVector(Vector<T> diagonal)

    Create a new dense matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -500,7 +500,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfDiagonalVector(Vector<T> diagonal)

    +

    Matrix<T> DenseOfDiagonalVector(int rows, int columns, Vector<T> diagonal)

    Create a new dense matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -543,8 +543,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRowArrays(T[][] rows)

    -
    +

    Matrix<T> DenseOfRowArrays(IEnumerable<T[]> rows)

    +
    Create a new dense matrix of T as a copy of the given row arrays. +This new matrix will be independent from the arrays. +A new memory block will be allocated for storing the matrix. @@ -552,10 +554,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRowArrays(IEnumerable<T[]> rows)

    -
    Create a new dense matrix of T as a copy of the given row arrays. -This new matrix will be independent from the arrays. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> DenseOfRowArrays(T[][] rows)

    +
    @@ -599,10 +599,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRowVectors(IEnumerable<Vector<T>> rows)

    -
    Create a new dense matrix as a copy of the given row vectors. -This new matrix will be independent from the vectors. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> DenseOfRowVectors(Vector`1[] rows)

    +
    @@ -610,8 +608,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DenseOfRowVectors(Vector`1[] rows)

    -
    +

    Matrix<T> DenseOfRowVectors(IEnumerable<Vector<T>> rows)

    +
    Create a new dense matrix as a copy of the given row vectors. +This new matrix will be independent from the vectors. +A new memory block will be allocated for storing the matrix. @@ -619,8 +619,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> Diagonal(int rows, int columns, T[] storage)

    -
    Create a new diagonal matrix with the given number of rows and columns directly binding to a raw array. +

    Matrix<T> Diagonal(T[] storage)

    +
    Create a new square diagonal matrix directly binding to a raw array. The array is assumed to represent the diagonal values and is used directly without copying. Very efficient, but changes to the array and the matrix will affect each other. @@ -630,11 +630,10 @@ Very efficient, but changes to the array and the matrix will affect each other.
    -

    Matrix<T> Diagonal(DiagonalMatrixStorage<T> storage)

    -
    Create a new diagonal matrix straight from an initialized matrix storage instance. -The storage is used directly without copying. -Intended for advanced scenarios where you're working directly with -storage for performance or interop reasons. +

    Matrix<T> Diagonal(int rows, int columns, T[] storage)

    +
    Create a new diagonal matrix with the given number of rows and columns directly binding to a raw array. +The array is assumed to represent the diagonal values and is used directly without copying. +Very efficient, but changes to the array and the matrix will affect each other. @@ -642,10 +641,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> Diagonal(T[] storage)

    -
    Create a new square diagonal matrix directly binding to a raw array. -The array is assumed to represent the diagonal values and is used directly without copying. -Very efficient, but changes to the array and the matrix will affect each other. +

    Matrix<T> Diagonal(int rows, int columns, T value)

    +
    Create a new diagonal matrix and initialize each diagonal value to the same provided value. @@ -653,8 +650,8 @@ Very efficient, but changes to the array and the matrix will affect each other.
    -

    Matrix<T> Diagonal(int rows, int columns, T value)

    -
    Create a new diagonal matrix and initialize each diagonal value to the same provided value. +

    Matrix<T> Diagonal(int rows, int columns, Func<int, T> init)

    +
    Create a new diagonal matrix and initialize each diagonal value using the provided init function. @@ -662,8 +659,11 @@ Very efficient, but changes to the array and the matrix will affect each other.
    -

    Matrix<T> Diagonal(int rows, int columns, Func<int, T> init)

    -
    Create a new diagonal matrix and initialize each diagonal value using the provided init function. +

    Matrix<T> Diagonal(DiagonalMatrixStorage<T> storage)

    +
    Create a new diagonal matrix straight from an initialized matrix storage instance. +The storage is used directly without copying. +Intended for advanced scenarios where you're working directly with +storage for performance or interop reasons. @@ -700,7 +700,7 @@ Zero-length matrices are not supported.
    -

    Matrix<T> DiagonalOfDiagonalArray(T[] diagonal)

    +

    Matrix<T> DiagonalOfDiagonalArray(int rows, int columns, T[] diagonal)

    Create a new diagonal matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -711,7 +711,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> DiagonalOfDiagonalArray(int rows, int columns, T[] diagonal)

    +

    Matrix<T> DiagonalOfDiagonalArray(T[] diagonal)

    Create a new diagonal matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -847,8 +847,8 @@ of two samples from the provided random distribution.
    -

    Matrix<T> SameAs(Vector<T> example, int rows, int columns)

    -
    Create a new matrix with the same kind of the provided example. +

    Matrix<T> SameAs(Matrix<T> example, Matrix<T> otherExample, int rows, int columns, bool fullyMutable)

    +
    Create a new matrix with a type that can represent and is closest to both provided samples. @@ -856,8 +856,8 @@ of two samples from the provided random distribution.
    -

    Matrix<T> SameAs(Matrix<T> example, Matrix<T> otherExample, int rows, int columns, bool fullyMutable)

    -
    Create a new matrix with a type that can represent and is closest to both provided samples. +

    Matrix<T> SameAs(Vector<T> example, int rows, int columns)

    +
    Create a new matrix with the same kind of the provided example. @@ -874,8 +874,8 @@ of two samples from the provided random distribution.
    -

    Matrix<T> SameAs<TU>(Matrix<T> example, int rows, int columns, bool fullyMutable)

    -
    Create a new matrix with the same kind of the provided example. +

    Matrix<T> SameAs<TU>(Matrix<T> example)

    +
    Create a new matrix with the same kind and dimensions of the provided example. @@ -883,8 +883,8 @@ of two samples from the provided random distribution.
    -

    Matrix<T> SameAs<TU>(Matrix<T> example)

    -
    Create a new matrix with the same kind and dimensions of the provided example. +

    Matrix<T> SameAs<TU>(Matrix<T> example, int rows, int columns, bool fullyMutable)

    +
    Create a new matrix with the same kind of the provided example. @@ -993,8 +993,10 @@ storage for performance or interop reasons.
    -

    Matrix<T> SparseOfColumnArrays(T[][] columns)

    -
    +

    Matrix<T> SparseOfColumnArrays(IEnumerable<T[]> columns)

    +
    Create a new sparse matrix as a copy of the given column arrays. +This new matrix will be independent from the arrays. +A new memory block will be allocated for storing the matrix. @@ -1002,10 +1004,8 @@ storage for performance or interop reasons.
    -

    Matrix<T> SparseOfColumnArrays(IEnumerable<T[]> columns)

    -
    Create a new sparse matrix as a copy of the given column arrays. -This new matrix will be independent from the arrays. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> SparseOfColumnArrays(T[][] columns)

    +
    @@ -1025,7 +1025,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfColumns(IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> SparseOfColumns(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    Create a new sparse matrix as a copy of the given enumerable of enumerable columns. Each enumerable in the master enumerable specifies a column. This new matrix will be independent from the enumerables. @@ -1037,7 +1037,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfColumns(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> SparseOfColumns(IEnumerable<IEnumerable<T>> data)

    Create a new sparse matrix as a copy of the given enumerable of enumerable columns. Each enumerable in the master enumerable specifies a column. This new matrix will be independent from the enumerables. @@ -1049,10 +1049,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfColumnVectors(IEnumerable<Vector<T>> columns)

    -
    Create a new sparse matrix as a copy of the given column vectors. -This new matrix will be independent from the vectors. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> SparseOfColumnVectors(Vector`1[] columns)

    +
    @@ -1060,8 +1058,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfColumnVectors(Vector`1[] columns)

    -
    +

    Matrix<T> SparseOfColumnVectors(IEnumerable<Vector<T>> columns)

    +
    Create a new sparse matrix as a copy of the given column vectors. +This new matrix will be independent from the vectors. +A new memory block will be allocated for storing the matrix. @@ -1069,7 +1069,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalArray(T[] diagonal)

    +

    Matrix<T> SparseOfDiagonalArray(int rows, int columns, T[] diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -1080,7 +1080,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalArray(int rows, int columns, T[] diagonal)

    +

    Matrix<T> SparseOfDiagonalArray(T[] diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given array. This new matrix will be independent from the array. A new memory block will be allocated for storing the matrix. @@ -1091,7 +1091,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalVector(Vector<T> diagonal)

    +

    Matrix<T> SparseOfDiagonalVector(int rows, int columns, Vector<T> diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -1102,7 +1102,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfDiagonalVector(int rows, int columns, Vector<T> diagonal)

    +

    Matrix<T> SparseOfDiagonalVector(Vector<T> diagonal)

    Create a new sparse matrix with the diagonal as a copy of the given vector. This new matrix will be independent from the vector. A new memory block will be allocated for storing the matrix. @@ -1177,7 +1177,7 @@ A new memory block will be allocated for storing the vector.
    -

    Matrix<T> SparseOfRows(IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> SparseOfRows(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    Create a new sparse matrix as a copy of the given enumerable of enumerable rows. Each enumerable in the master enumerable specifies a row. This new matrix will be independent from the enumerables. @@ -1189,7 +1189,7 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfRows(int rows, int columns, IEnumerable<IEnumerable<T>> data)

    +

    Matrix<T> SparseOfRows(IEnumerable<IEnumerable<T>> data)

    Create a new sparse matrix as a copy of the given enumerable of enumerable rows. Each enumerable in the master enumerable specifies a row. This new matrix will be independent from the enumerables. @@ -1201,10 +1201,8 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfRowVectors(IEnumerable<Vector<T>> rows)

    -
    Create a new sparse matrix as a copy of the given row vectors. -This new matrix will be independent from the vectors. -A new memory block will be allocated for storing the matrix. +

    Matrix<T> SparseOfRowVectors(Vector`1[] rows)

    +
    @@ -1212,8 +1210,10 @@ A new memory block will be allocated for storing the matrix.
    -

    Matrix<T> SparseOfRowVectors(Vector`1[] rows)

    -
    +

    Matrix<T> SparseOfRowVectors(IEnumerable<Vector<T>> rows)

    +
    Create a new sparse matrix as a copy of the given row vectors. +This new matrix will be independent from the vectors. +A new memory block will be allocated for storing the matrix. @@ -1245,7 +1245,7 @@ A new memory block will be allocated for storing the matrix.
    diff --git a/api/MathNet.Numerics.LinearAlgebra/MatrixExtensions.htm b/api/MathNet.Numerics.LinearAlgebra/MatrixExtensions.htm index 5b2ddb94..ba65c579 100644 --- a/api/MathNet.Numerics.LinearAlgebra/MatrixExtensions.htm +++ b/api/MathNet.Numerics.LinearAlgebra/MatrixExtensions.htm @@ -245,7 +245,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra/Matrix`1.htm b/api/MathNet.Numerics.LinearAlgebra/Matrix`1.htm index 6401417c..b02c23f2 100644 --- a/api/MathNet.Numerics.LinearAlgebra/Matrix`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra/Matrix`1.htm @@ -4924,7 +4924,7 @@ The format string is ignored.
    diff --git a/api/MathNet.Numerics.LinearAlgebra/Symmetricity.htm b/api/MathNet.Numerics.LinearAlgebra/Symmetricity.htm index 0bef2c3f..241f92f1 100644 --- a/api/MathNet.Numerics.LinearAlgebra/Symmetricity.htm +++ b/api/MathNet.Numerics.LinearAlgebra/Symmetricity.htm @@ -278,8 +278,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -287,11 +290,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -362,7 +362,7 @@
    diff --git a/api/MathNet.Numerics.LinearAlgebra/VectorBuilder`1.htm b/api/MathNet.Numerics.LinearAlgebra/VectorBuilder`1.htm index 77dc2dc2..aa9db897 100644 --- a/api/MathNet.Numerics.LinearAlgebra/VectorBuilder`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra/VectorBuilder`1.htm @@ -248,6 +248,18 @@ required in normal user code. +
    +
    +
    +

    Vector<T> Dense(DenseVectorStorage<T> storage)

    +
    Create a new dense vector straight from an initialized vector storage instance. +The storage is used directly without copying. +Intended for advanced scenarios where you're working directly with +storage for performance or interop reasons. + + + +
    @@ -263,18 +275,6 @@ required in normal user code.
    -
    -
    -
    -

    Vector<T> Dense(DenseVectorStorage<T> storage)

    -
    Create a new dense vector straight from an initialized vector storage instance. -The storage is used directly without copying. -Intended for advanced scenarios where you're working directly with -storage for performance or interop reasons. - - - -
    @@ -360,7 +360,7 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> Random(int length, int seed)

    +

    Vector<T> Random(int length)

    Create a new dense vector with values sampled from the standard distribution with a system random source. @@ -369,8 +369,8 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> Random(int length)

    -
    Create a new dense vector with values sampled from the standard distribution with a system random source. +

    Vector<T> Random(int length, IContinuousDistribution distribution)

    +
    Create a new dense vector with values sampled from the provided random distribution. @@ -378,8 +378,8 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> Random(int length, IContinuousDistribution distribution)

    -
    Create a new dense vector with values sampled from the provided random distribution. +

    Vector<T> Random(int length, int seed)

    +
    Create a new dense vector with values sampled from the standard distribution with a system random source. @@ -387,8 +387,8 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> SameAs(Vector<T> example, Vector<T> otherExample)

    -
    Create a new vector with a type that can represent and is closest to both provided samples and the dimensions of example. +

    Vector<T> SameAs(Matrix<T> matrix, Vector<T> vector, int length)

    +
    Create a new vector with a type that can represent and is closest to both provided samples. @@ -396,8 +396,8 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> SameAs(Vector<T> example, Vector<T> otherExample, int length)

    -
    Create a new vector with a type that can represent and is closest to both provided samples. +

    Vector<T> SameAs(Vector<T> example, Vector<T> otherExample)

    +
    Create a new vector with a type that can represent and is closest to both provided samples and the dimensions of example. @@ -405,7 +405,7 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> SameAs(Matrix<T> matrix, Vector<T> vector, int length)

    +

    Vector<T> SameAs(Vector<T> example, Vector<T> otherExample, int length)

    Create a new vector with a type that can represent and is closest to both provided samples. @@ -423,8 +423,8 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> SameAs<TU>(Vector<T> example)

    -
    Create a new vector with the same kind and dimension of the provided example. +

    Vector<T> SameAs<TU>(Vector<T> example, int length)

    +
    Create a new vector with the same kind of the provided example. @@ -432,8 +432,8 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> SameAs<TU>(Vector<T> example, int length)

    -
    Create a new vector with the same kind of the provided example. +

    Vector<T> SameAs<TU>(Vector<T> example)

    +
    Create a new vector with the same kind and dimension of the provided example. @@ -441,11 +441,8 @@ If you have an instance of a discrete storage type instead, use their direct met
    -

    Vector<T> Sparse(SparseVectorStorage<T> storage)

    -
    Create a new sparse vector straight from an initialized vector storage instance. -The storage is used directly without copying. -Intended for advanced scenarios where you're working directly with -storage for performance or interop reasons. +

    Vector<T> Sparse(int length, T value)

    +
    Create a new sparse vector and initialize each value using the provided value. @@ -468,8 +465,11 @@ storage for performance or interop reasons.
    -

    Vector<T> Sparse(int length, Func<int, T> init)

    -
    Create a new sparse vector and initialize each value using the provided init function. +

    Vector<T> Sparse(SparseVectorStorage<T> storage)

    +
    Create a new sparse vector straight from an initialized vector storage instance. +The storage is used directly without copying. +Intended for advanced scenarios where you're working directly with +storage for performance or interop reasons. @@ -477,8 +477,8 @@ storage for performance or interop reasons.
    -

    Vector<T> Sparse(int length, T value)

    -
    Create a new sparse vector and initialize each value using the provided value. +

    Vector<T> Sparse(int length, Func<int, T> init)

    +
    Create a new sparse vector and initialize each value using the provided init function. @@ -555,7 +555,7 @@ A new memory block will be allocated for storing the vector.
    diff --git a/api/MathNet.Numerics.LinearAlgebra/VectorExtensions.htm b/api/MathNet.Numerics.LinearAlgebra/VectorExtensions.htm index d4911cd2..e2d16023 100644 --- a/api/MathNet.Numerics.LinearAlgebra/VectorExtensions.htm +++ b/api/MathNet.Numerics.LinearAlgebra/VectorExtensions.htm @@ -245,7 +245,7 @@ diff --git a/api/MathNet.Numerics.LinearAlgebra/Vector`1.htm b/api/MathNet.Numerics.LinearAlgebra/Vector`1.htm index 602116ca..15e15133 100644 --- a/api/MathNet.Numerics.LinearAlgebra/Vector`1.htm +++ b/api/MathNet.Numerics.LinearAlgebra/Vector`1.htm @@ -3083,7 +3083,7 @@ The format string is ignored.
    diff --git a/api/MathNet.Numerics.LinearAlgebra/Zeros.htm b/api/MathNet.Numerics.LinearAlgebra/Zeros.htm index f3b8eefa..13edda17 100644 --- a/api/MathNet.Numerics.LinearAlgebra/Zeros.htm +++ b/api/MathNet.Numerics.LinearAlgebra/Zeros.htm @@ -276,8 +276,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -285,11 +288,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -337,7 +337,7 @@ When enumerating sparse matrices this can significantly speed up operations.
    diff --git a/api/MathNet.Numerics.LinearAlgebra/index.htm b/api/MathNet.Numerics.LinearAlgebra/index.htm index 762578d7..ec610d28 100644 --- a/api/MathNet.Numerics.LinearAlgebra/index.htm +++ b/api/MathNet.Numerics.LinearAlgebra/index.htm @@ -183,7 +183,7 @@
    diff --git a/api/MathNet.Numerics.LinearRegression/DirectRegressionMethod.htm b/api/MathNet.Numerics.LinearRegression/DirectRegressionMethod.htm index 7b53f652..8af154b7 100644 --- a/api/MathNet.Numerics.LinearRegression/DirectRegressionMethod.htm +++ b/api/MathNet.Numerics.LinearRegression/DirectRegressionMethod.htm @@ -256,8 +256,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -265,11 +268,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -328,7 +328,7 @@
    diff --git a/api/MathNet.Numerics.LinearRegression/MultipleRegression.htm b/api/MathNet.Numerics.LinearRegression/MultipleRegression.htm index b5ff4ea2..16b0c826 100644 --- a/api/MathNet.Numerics.LinearRegression/MultipleRegression.htm +++ b/api/MathNet.Numerics.LinearRegression/MultipleRegression.htm @@ -260,24 +260,24 @@ Uses the cholesky decomposition of the normal equations.
    -

    T[] NormalEquations<T>(IEnumerable<Tuple<T[], T>> samples, bool intercept)

    -
    Find the model parameters β such that their linear combination with all predictor-arrays in X become as close to their response in Y as possible, with least squares residuals. +

    Vector<T> NormalEquations<T>(Matrix<T> x, Vector<T> y)

    +
    Find the model parameters β such that X*β with predictor X becomes as close to response Y as possible, with least squares residuals. Uses the cholesky decomposition of the normal equations.
    Parameters
    -
    IEnumerable<Tuple<T[], T>> samples
    -

    Sequence of predictor-arrays and their response.

    -
    bool intercept
    -

    True if an intercept should be added as first artificial predictor value. Default = false.

    +
    Matrix<T> x
    +

    Predictor matrix X

    +
    Vector<T> y
    +

    Response vector Y

    Return
    -
    T[]
    -

    Best fitting list of model parameters β for each element in the predictor-arrays.

    +
    Vector<T>
    +

    Best fitting vector for model parameters β

    @@ -306,39 +306,39 @@ Uses the cholesky decomposition of the normal equations.
    -

    Vector<T> NormalEquations<T>(Matrix<T> x, Vector<T> y)

    -
    Find the model parameters β such that X*β with predictor X becomes as close to response Y as possible, with least squares residuals. +

    T[] NormalEquations<T>(T[][] x, T[] y, bool intercept)

    +
    + + + + +
    +
    +
    +

    T[] NormalEquations<T>(IEnumerable<Tuple<T[], T>> samples, bool intercept)

    +
    Find the model parameters β such that their linear combination with all predictor-arrays in X become as close to their response in Y as possible, with least squares residuals. Uses the cholesky decomposition of the normal equations.
    Parameters
    -
    Matrix<T> x
    -

    Predictor matrix X

    -
    Vector<T> y
    -

    Response vector Y

    +
    IEnumerable<Tuple<T[], T>> samples
    +

    Sequence of predictor-arrays and their response.

    +
    bool intercept
    +

    True if an intercept should be added as first artificial predictor value. Default = false.

    Return
    -
    Vector<T>
    -

    Best fitting vector for model parameters β

    +
    T[]
    +

    Best fitting list of model parameters β for each element in the predictor-arrays.

    -
    -
    -
    -

    T[] NormalEquations<T>(T[][] x, T[] y, bool intercept)

    -
    - - - -
    -

    Vector<T> QR<T>(Matrix<T> x, Vector<T> y)

    +

    Matrix<T> QR<T>(Matrix<T> x, Matrix<T> y)

    Find the model parameters β such that X*β with predictor X becomes as close to response Y as possible, with least squares residuals. Uses an orthogonal decomposition and is therefore more numerically stable than the normal equations but also slower. @@ -348,13 +348,13 @@ Uses an orthogonal decomposition and is therefore more numerically stable than t
    Matrix<T> x

    Predictor matrix X

    -
    Vector<T> y
    -

    Response vector Y

    +
    Matrix<T> y
    +

    Response matrix Y

    Return
    -
    Vector<T>
    +
    Matrix<T>

    Best fitting vector for model parameters β

    @@ -370,47 +370,47 @@ Uses an orthogonal decomposition and is therefore more numerically stable than t
    -

    T[] QR<T>(IEnumerable<Tuple<T[], T>> samples, bool intercept)

    -
    Find the model parameters β such that their linear combination with all predictor-arrays in X become as close to their response in Y as possible, with least squares residuals. +

    Vector<T> QR<T>(Matrix<T> x, Vector<T> y)

    +
    Find the model parameters β such that X*β with predictor X becomes as close to response Y as possible, with least squares residuals. Uses an orthogonal decomposition and is therefore more numerically stable than the normal equations but also slower.
    Parameters
    -
    IEnumerable<Tuple<T[], T>> samples
    -

    Sequence of predictor-arrays and their response.

    -
    bool intercept
    -

    True if an intercept should be added as first artificial predictor value. Default = false.

    +
    Matrix<T> x
    +

    Predictor matrix X

    +
    Vector<T> y
    +

    Response vector Y

    Return
    -
    T[]
    -

    Best fitting list of model parameters β for each element in the predictor-arrays.

    +
    Vector<T>
    +

    Best fitting vector for model parameters β

    -

    Matrix<T> QR<T>(Matrix<T> x, Matrix<T> y)

    -
    Find the model parameters β such that X*β with predictor X becomes as close to response Y as possible, with least squares residuals. +

    T[] QR<T>(IEnumerable<Tuple<T[], T>> samples, bool intercept)

    +
    Find the model parameters β such that their linear combination with all predictor-arrays in X become as close to their response in Y as possible, with least squares residuals. Uses an orthogonal decomposition and is therefore more numerically stable than the normal equations but also slower.
    Parameters
    -
    Matrix<T> x
    -

    Predictor matrix X

    -
    Matrix<T> y
    -

    Response matrix Y

    +
    IEnumerable<Tuple<T[], T>> samples
    +

    Sequence of predictor-arrays and their response.

    +
    bool intercept
    +

    True if an intercept should be added as first artificial predictor value. Default = false.

    Return
    -
    Matrix<T>
    -

    Best fitting vector for model parameters β

    +
    T[]
    +

    Best fitting list of model parameters β for each element in the predictor-arrays.

    @@ -496,7 +496,7 @@ Uses a singular value decomposition and is therefore more numerically stable (es diff --git a/api/MathNet.Numerics.LinearRegression/SimpleRegression.htm b/api/MathNet.Numerics.LinearRegression/SimpleRegression.htm index 8fda6353..d825a3be 100644 --- a/api/MathNet.Numerics.LinearRegression/SimpleRegression.htm +++ b/api/MathNet.Numerics.LinearRegression/SimpleRegression.htm @@ -240,7 +240,7 @@ where the intercept is zero and b the slope. diff --git a/api/MathNet.Numerics.LinearRegression/WeightedRegression.htm b/api/MathNet.Numerics.LinearRegression/WeightedRegression.htm index becc0336..666c567a 100644 --- a/api/MathNet.Numerics.LinearRegression/WeightedRegression.htm +++ b/api/MathNet.Numerics.LinearRegression/WeightedRegression.htm @@ -273,7 +273,7 @@ diff --git a/api/MathNet.Numerics.LinearRegression/index.htm b/api/MathNet.Numerics.LinearRegression/index.htm index 58b13794..c135de82 100644 --- a/api/MathNet.Numerics.LinearRegression/index.htm +++ b/api/MathNet.Numerics.LinearRegression/index.htm @@ -155,7 +155,7 @@
    diff --git a/api/MathNet.Numerics.OdeSolvers/AdamsBashforth.htm b/api/MathNet.Numerics.OdeSolvers/AdamsBashforth.htm index 4ff0a19e..d67bfa86 100644 --- a/api/MathNet.Numerics.OdeSolvers/AdamsBashforth.htm +++ b/api/MathNet.Numerics.OdeSolvers/AdamsBashforth.htm @@ -274,7 +274,7 @@ diff --git a/api/MathNet.Numerics.OdeSolvers/RungeKutta.htm b/api/MathNet.Numerics.OdeSolvers/RungeKutta.htm index 7e77f35a..73dc2483 100644 --- a/api/MathNet.Numerics.OdeSolvers/RungeKutta.htm +++ b/api/MathNet.Numerics.OdeSolvers/RungeKutta.htm @@ -276,7 +276,7 @@ diff --git a/api/MathNet.Numerics.OdeSolvers/index.htm b/api/MathNet.Numerics.OdeSolvers/index.htm index 1a373f1f..a4d6fa19 100644 --- a/api/MathNet.Numerics.OdeSolvers/index.htm +++ b/api/MathNet.Numerics.OdeSolvers/index.htm @@ -147,7 +147,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.LineSearch/LineSearchResult.htm b/api/MathNet.Numerics.Optimization.LineSearch/LineSearchResult.htm index eeff98dc..8039991b 100644 --- a/api/MathNet.Numerics.Optimization.LineSearch/LineSearchResult.htm +++ b/api/MathNet.Numerics.Optimization.LineSearch/LineSearchResult.htm @@ -260,7 +260,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.LineSearch/StrongWolfeLineSearch.htm b/api/MathNet.Numerics.Optimization.LineSearch/StrongWolfeLineSearch.htm index 0e569b37..ef0e27c3 100644 --- a/api/MathNet.Numerics.Optimization.LineSearch/StrongWolfeLineSearch.htm +++ b/api/MathNet.Numerics.Optimization.LineSearch/StrongWolfeLineSearch.htm @@ -262,7 +262,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.LineSearch/WeakWolfeLineSearch.htm b/api/MathNet.Numerics.Optimization.LineSearch/WeakWolfeLineSearch.htm index 9067f8c8..53118ad3 100644 --- a/api/MathNet.Numerics.Optimization.LineSearch/WeakWolfeLineSearch.htm +++ b/api/MathNet.Numerics.Optimization.LineSearch/WeakWolfeLineSearch.htm @@ -272,7 +272,7 @@ http://www.math.washington.edu/~burke/crs/408/lectures/L9-weak-Wolfe.pdf
    diff --git a/api/MathNet.Numerics.Optimization.LineSearch/WolfeLineSearch.htm b/api/MathNet.Numerics.Optimization.LineSearch/WolfeLineSearch.htm index c9902626..3607d616 100644 --- a/api/MathNet.Numerics.Optimization.LineSearch/WolfeLineSearch.htm +++ b/api/MathNet.Numerics.Optimization.LineSearch/WolfeLineSearch.htm @@ -261,7 +261,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.LineSearch/index.htm b/api/MathNet.Numerics.Optimization.LineSearch/index.htm index ada68411..e6f639fe 100644 --- a/api/MathNet.Numerics.Optimization.LineSearch/index.htm +++ b/api/MathNet.Numerics.Optimization.LineSearch/index.htm @@ -155,7 +155,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ForwardDifferenceGradientObjectiveFunction.htm b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ForwardDifferenceGradientObjectiveFunction.htm index 797709c8..fd7f25b4 100644 --- a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ForwardDifferenceGradientObjectiveFunction.htm +++ b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ForwardDifferenceGradientObjectiveFunction.htm @@ -323,7 +323,7 @@ functions's number of input parameters.
    diff --git a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/LazyObjectiveFunctionBase.htm b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/LazyObjectiveFunctionBase.htm index 8af631b0..713b4ed7 100644 --- a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/LazyObjectiveFunctionBase.htm +++ b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/LazyObjectiveFunctionBase.htm @@ -279,7 +279,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ObjectiveFunctionBase.htm b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ObjectiveFunctionBase.htm index 710ce6c8..81d8829b 100644 --- a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ObjectiveFunctionBase.htm +++ b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/ObjectiveFunctionBase.htm @@ -279,7 +279,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/index.htm b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/index.htm index 6cb585e6..808d753b 100644 --- a/api/MathNet.Numerics.Optimization.ObjectiveFunctions/index.htm +++ b/api/MathNet.Numerics.Optimization.ObjectiveFunctions/index.htm @@ -151,7 +151,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.TrustRegion/ITrustRegionSubproblem.htm b/api/MathNet.Numerics.Optimization.TrustRegion/ITrustRegionSubproblem.htm index e570f87f..52d37638 100644 --- a/api/MathNet.Numerics.Optimization.TrustRegion/ITrustRegionSubproblem.htm +++ b/api/MathNet.Numerics.Optimization.TrustRegion/ITrustRegionSubproblem.htm @@ -196,7 +196,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionDogLegMinimizer.htm b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionDogLegMinimizer.htm index 6b1a4833..e5262bc0 100644 --- a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionDogLegMinimizer.htm +++ b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionDogLegMinimizer.htm @@ -243,7 +243,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionMinimizerBase.htm b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionMinimizerBase.htm index 4d44ddf4..cc99a0b5 100644 --- a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionMinimizerBase.htm +++ b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionMinimizerBase.htm @@ -312,7 +312,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionNewtonCGMinimizer.htm b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionNewtonCGMinimizer.htm index 4a959154..250a976b 100644 --- a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionNewtonCGMinimizer.htm +++ b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionNewtonCGMinimizer.htm @@ -243,7 +243,7 @@
    diff --git a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionSubproblem.htm b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionSubproblem.htm index 4d94d1a9..09111239 100644 --- a/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionSubproblem.htm +++ b/api/MathNet.Numerics.Optimization.TrustRegion/TrustRegionSubproblem.htm @@ -187,7 +187,7 @@ diff --git a/api/MathNet.Numerics.Optimization.TrustRegion/index.htm b/api/MathNet.Numerics.Optimization.TrustRegion/index.htm index 36ae19c0..c9925b94 100644 --- a/api/MathNet.Numerics.Optimization.TrustRegion/index.htm +++ b/api/MathNet.Numerics.Optimization.TrustRegion/index.htm @@ -162,7 +162,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/BfgsBMinimizer.htm b/api/MathNet.Numerics.Optimization/BfgsBMinimizer.htm index 9b98f0a2..528af11f 100644 --- a/api/MathNet.Numerics.Optimization/BfgsBMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/BfgsBMinimizer.htm @@ -367,7 +367,7 @@ http://www.ece.northwestern.edu/~nocedal/PSfiles/limited.ps.gz
    diff --git a/api/MathNet.Numerics.Optimization/BfgsMinimizer.htm b/api/MathNet.Numerics.Optimization/BfgsMinimizer.htm index 7aee002c..b8de8647 100644 --- a/api/MathNet.Numerics.Optimization/BfgsMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/BfgsMinimizer.htm @@ -375,7 +375,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/BfgsMinimizerBase.htm b/api/MathNet.Numerics.Optimization/BfgsMinimizerBase.htm index 2a2cc46e..d07e2721 100644 --- a/api/MathNet.Numerics.Optimization/BfgsMinimizerBase.htm +++ b/api/MathNet.Numerics.Optimization/BfgsMinimizerBase.htm @@ -322,7 +322,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/BfgsSolver.htm b/api/MathNet.Numerics.Optimization/BfgsSolver.htm index d3033f54..3a6f14d2 100644 --- a/api/MathNet.Numerics.Optimization/BfgsSolver.htm +++ b/api/MathNet.Numerics.Optimization/BfgsSolver.htm @@ -278,7 +278,7 @@ This uses the function and it's gradient (partial derivatives in each direction) diff --git a/api/MathNet.Numerics.Optimization/ConjugateGradientMinimizer.htm b/api/MathNet.Numerics.Optimization/ConjugateGradientMinimizer.htm index 14bb7b97..b8909d6e 100644 --- a/api/MathNet.Numerics.Optimization/ConjugateGradientMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/ConjugateGradientMinimizer.htm @@ -348,7 +348,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/EvaluationException.htm b/api/MathNet.Numerics.Optimization/EvaluationException.htm index f29d1ccd..e9d68256 100644 --- a/api/MathNet.Numerics.Optimization/EvaluationException.htm +++ b/api/MathNet.Numerics.Optimization/EvaluationException.htm @@ -402,7 +402,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/ExitCondition.htm b/api/MathNet.Numerics.Optimization/ExitCondition.htm index c3930301..9972ec33 100644 --- a/api/MathNet.Numerics.Optimization/ExitCondition.htm +++ b/api/MathNet.Numerics.Optimization/ExitCondition.htm @@ -349,8 +349,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -358,11 +361,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -529,7 +529,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/GoldenSectionMinimizer.htm b/api/MathNet.Numerics.Optimization/GoldenSectionMinimizer.htm index 4344ea99..c2be5855 100644 --- a/api/MathNet.Numerics.Optimization/GoldenSectionMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/GoldenSectionMinimizer.htm @@ -368,7 +368,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/GradientProjectionResult.htm b/api/MathNet.Numerics.Optimization/GradientProjectionResult.htm index ff40efee..8dbb7925 100644 --- a/api/MathNet.Numerics.Optimization/GradientProjectionResult.htm +++ b/api/MathNet.Numerics.Optimization/GradientProjectionResult.htm @@ -330,7 +330,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/IObjectiveFunction.htm b/api/MathNet.Numerics.Optimization/IObjectiveFunction.htm index 430b81c1..b11a3549 100644 --- a/api/MathNet.Numerics.Optimization/IObjectiveFunction.htm +++ b/api/MathNet.Numerics.Optimization/IObjectiveFunction.htm @@ -271,7 +271,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/IObjectiveFunctionEvaluation.htm b/api/MathNet.Numerics.Optimization/IObjectiveFunctionEvaluation.htm index 8311a1fc..dcfed0d6 100644 --- a/api/MathNet.Numerics.Optimization/IObjectiveFunctionEvaluation.htm +++ b/api/MathNet.Numerics.Optimization/IObjectiveFunctionEvaluation.htm @@ -307,7 +307,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/IObjectiveModel.htm b/api/MathNet.Numerics.Optimization/IObjectiveModel.htm index c8e2d8b0..7b91d47a 100644 --- a/api/MathNet.Numerics.Optimization/IObjectiveModel.htm +++ b/api/MathNet.Numerics.Optimization/IObjectiveModel.htm @@ -289,7 +289,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/IObjectiveModelEvaluation.htm b/api/MathNet.Numerics.Optimization/IObjectiveModelEvaluation.htm index 464abceb..f1f8b0e0 100644 --- a/api/MathNet.Numerics.Optimization/IObjectiveModelEvaluation.htm +++ b/api/MathNet.Numerics.Optimization/IObjectiveModelEvaluation.htm @@ -347,7 +347,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/IScalarObjectiveFunction.htm b/api/MathNet.Numerics.Optimization/IScalarObjectiveFunction.htm index d19d4b33..6cf5a6f3 100644 --- a/api/MathNet.Numerics.Optimization/IScalarObjectiveFunction.htm +++ b/api/MathNet.Numerics.Optimization/IScalarObjectiveFunction.htm @@ -277,7 +277,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/IScalarObjectiveFunctionEvaluation.htm b/api/MathNet.Numerics.Optimization/IScalarObjectiveFunctionEvaluation.htm index 46a37dc4..82997dfa 100644 --- a/api/MathNet.Numerics.Optimization/IScalarObjectiveFunctionEvaluation.htm +++ b/api/MathNet.Numerics.Optimization/IScalarObjectiveFunctionEvaluation.htm @@ -276,7 +276,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/IUnconstrainedMinimizer.htm b/api/MathNet.Numerics.Optimization/IUnconstrainedMinimizer.htm index b22e307e..bac1f780 100644 --- a/api/MathNet.Numerics.Optimization/IUnconstrainedMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/IUnconstrainedMinimizer.htm @@ -258,7 +258,7 @@ diff --git a/api/MathNet.Numerics.Optimization/IncompatibleObjectiveException.htm b/api/MathNet.Numerics.Optimization/IncompatibleObjectiveException.htm index 8ea8eb96..0a3c81ca 100644 --- a/api/MathNet.Numerics.Optimization/IncompatibleObjectiveException.htm +++ b/api/MathNet.Numerics.Optimization/IncompatibleObjectiveException.htm @@ -385,7 +385,7 @@ diff --git a/api/MathNet.Numerics.Optimization/InnerOptimizationException.htm b/api/MathNet.Numerics.Optimization/InnerOptimizationException.htm index fda1ec3c..6a88927b 100644 --- a/api/MathNet.Numerics.Optimization/InnerOptimizationException.htm +++ b/api/MathNet.Numerics.Optimization/InnerOptimizationException.htm @@ -395,7 +395,7 @@ diff --git a/api/MathNet.Numerics.Optimization/LevenbergMarquardtMinimizer.htm b/api/MathNet.Numerics.Optimization/LevenbergMarquardtMinimizer.htm index d8592aa1..b48925f3 100644 --- a/api/MathNet.Numerics.Optimization/LevenbergMarquardtMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/LevenbergMarquardtMinimizer.htm @@ -378,7 +378,7 @@ diff --git a/api/MathNet.Numerics.Optimization/LimitedMemoryBfgsMinimizer.htm b/api/MathNet.Numerics.Optimization/LimitedMemoryBfgsMinimizer.htm index 83c38e7a..d6589ccc 100644 --- a/api/MathNet.Numerics.Optimization/LimitedMemoryBfgsMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/LimitedMemoryBfgsMinimizer.htm @@ -380,7 +380,7 @@ diff --git a/api/MathNet.Numerics.Optimization/MaximumIterationsException.htm b/api/MathNet.Numerics.Optimization/MaximumIterationsException.htm index cb89b930..d1c96ab9 100644 --- a/api/MathNet.Numerics.Optimization/MaximumIterationsException.htm +++ b/api/MathNet.Numerics.Optimization/MaximumIterationsException.htm @@ -385,7 +385,7 @@ diff --git a/api/MathNet.Numerics.Optimization/MinimizationResult.htm b/api/MathNet.Numerics.Optimization/MinimizationResult.htm index b62eb767..4c8244ba 100644 --- a/api/MathNet.Numerics.Optimization/MinimizationResult.htm +++ b/api/MathNet.Numerics.Optimization/MinimizationResult.htm @@ -336,7 +336,7 @@ diff --git a/api/MathNet.Numerics.Optimization/MinimizationWithLineSearchResult.htm b/api/MathNet.Numerics.Optimization/MinimizationWithLineSearchResult.htm index 4ac65d26..c3390658 100644 --- a/api/MathNet.Numerics.Optimization/MinimizationWithLineSearchResult.htm +++ b/api/MathNet.Numerics.Optimization/MinimizationWithLineSearchResult.htm @@ -351,7 +351,7 @@ diff --git a/api/MathNet.Numerics.Optimization/MinimizerBase.htm b/api/MathNet.Numerics.Optimization/MinimizerBase.htm index c2cf897a..9d2c3d14 100644 --- a/api/MathNet.Numerics.Optimization/MinimizerBase.htm +++ b/api/MathNet.Numerics.Optimization/MinimizerBase.htm @@ -321,7 +321,7 @@ diff --git a/api/MathNet.Numerics.Optimization/NelderMeadSimplex.htm b/api/MathNet.Numerics.Optimization/NelderMeadSimplex.htm index 449e291b..2faf217e 100644 --- a/api/MathNet.Numerics.Optimization/NelderMeadSimplex.htm +++ b/api/MathNet.Numerics.Optimization/NelderMeadSimplex.htm @@ -438,7 +438,7 @@ http://se.mathworks.com/help/matlab/math/optimizing-nonlinear-functions.html#bsg diff --git a/api/MathNet.Numerics.Optimization/NewtonMinimizer.htm b/api/MathNet.Numerics.Optimization/NewtonMinimizer.htm index f2125dfb..38b0d4af 100644 --- a/api/MathNet.Numerics.Optimization/NewtonMinimizer.htm +++ b/api/MathNet.Numerics.Optimization/NewtonMinimizer.htm @@ -355,7 +355,7 @@ diff --git a/api/MathNet.Numerics.Optimization/NonlinearMinimizationResult.htm b/api/MathNet.Numerics.Optimization/NonlinearMinimizationResult.htm index 53c61c93..d436dcc0 100644 --- a/api/MathNet.Numerics.Optimization/NonlinearMinimizationResult.htm +++ b/api/MathNet.Numerics.Optimization/NonlinearMinimizationResult.htm @@ -364,7 +364,7 @@ diff --git a/api/MathNet.Numerics.Optimization/NonlinearMinimizerBase.htm b/api/MathNet.Numerics.Optimization/NonlinearMinimizerBase.htm index 92d8e362..1e268832 100644 --- a/api/MathNet.Numerics.Optimization/NonlinearMinimizerBase.htm +++ b/api/MathNet.Numerics.Optimization/NonlinearMinimizerBase.htm @@ -342,7 +342,7 @@ diff --git a/api/MathNet.Numerics.Optimization/ObjectiveFunction.htm b/api/MathNet.Numerics.Optimization/ObjectiveFunction.htm index 26208332..4b5667a0 100644 --- a/api/MathNet.Numerics.Optimization/ObjectiveFunction.htm +++ b/api/MathNet.Numerics.Optimization/ObjectiveFunction.htm @@ -314,9 +314,8 @@
    -

    IObjectiveFunction NonlinearFunction(Func<Vector<double>, Vector<double>, Vector<double>> function, Vector<T> observedX, Vector<T> observedY, Vector<T> weight, int accuracyOrder)

    -
    Objective function for nonlinear least squares regression. -The numerical jacobian with accuracy order is used. +

    IObjectiveFunction NonlinearFunction(Func<Vector<double>, Vector<double>, Vector<double>> function, Func<Vector<double>, Vector<double>, Matrix<double>> derivatives, Vector<T> observedX, Vector<T> observedY, Vector<T> weight)

    +
    Objective function with a user supplied jacobian for nonlinear least squares regression. @@ -324,8 +323,9 @@ The numerical jacobian with accuracy order is used.
    -

    IObjectiveFunction NonlinearFunction(Func<Vector<double>, Vector<double>, Vector<double>> function, Func<Vector<double>, Vector<double>, Matrix<double>> derivatives, Vector<T> observedX, Vector<T> observedY, Vector<T> weight)

    -
    Objective function with a user supplied jacobian for nonlinear least squares regression. +

    IObjectiveFunction NonlinearFunction(Func<Vector<double>, Vector<double>, Vector<double>> function, Vector<T> observedX, Vector<T> observedY, Vector<T> weight, int accuracyOrder)

    +
    Objective function for nonlinear least squares regression. +The numerical jacobian with accuracy order is used. @@ -389,7 +389,7 @@ The numerical jacobian with accuracy order is used. diff --git a/api/MathNet.Numerics.Optimization/OptimizationException.htm b/api/MathNet.Numerics.Optimization/OptimizationException.htm index a922148c..5b0673c4 100644 --- a/api/MathNet.Numerics.Optimization/OptimizationException.htm +++ b/api/MathNet.Numerics.Optimization/OptimizationException.htm @@ -395,7 +395,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/QuadraticGradientProjectionSearch.htm b/api/MathNet.Numerics.Optimization/QuadraticGradientProjectionSearch.htm index 884217bb..a68797af 100644 --- a/api/MathNet.Numerics.Optimization/QuadraticGradientProjectionSearch.htm +++ b/api/MathNet.Numerics.Optimization/QuadraticGradientProjectionSearch.htm @@ -258,7 +258,7 @@ diff --git a/api/MathNet.Numerics.Optimization/ScalarMinimizationResult.htm b/api/MathNet.Numerics.Optimization/ScalarMinimizationResult.htm index d86a4b35..2ed82b71 100644 --- a/api/MathNet.Numerics.Optimization/ScalarMinimizationResult.htm +++ b/api/MathNet.Numerics.Optimization/ScalarMinimizationResult.htm @@ -336,7 +336,7 @@
    diff --git a/api/MathNet.Numerics.Optimization/index.htm b/api/MathNet.Numerics.Optimization/index.htm index 3f0f2bb2..d61c753b 100644 --- a/api/MathNet.Numerics.Optimization/index.htm +++ b/api/MathNet.Numerics.Optimization/index.htm @@ -270,7 +270,7 @@ diff --git a/api/MathNet.Numerics.Properties/Resources.htm b/api/MathNet.Numerics.Properties/Resources.htm index 89619c4b..667e3c76 100644 --- a/api/MathNet.Numerics.Properties/Resources.htm +++ b/api/MathNet.Numerics.Properties/Resources.htm @@ -241,6 +241,7 @@
  • NameCannotContainASpace
  • NotSupportedType
  • NumericalBreakdown
    • +
  • NumericalEstimationFailed
  • PartialOrderException
  • PermutationAsIntArrayInvalid
  • ProposalDistributionNoUpperBound
    • @@ -843,6 +844,12 @@ resource lookups using this strongly typed resource class. +
    +

    string NumericalEstimationFailed get;

    +
    Looks up a localized string similar to: Numerical estimation of the statistic has failed. + +
    +

    string PartialOrderException get;

    Looks up a localized string similar to The two arguments can't be compared (maybe they are part of a partial ordering?). @@ -988,7 +995,7 @@ resource lookups using this strongly typed resource class.
    diff --git a/api/MathNet.Numerics.Properties/index.htm b/api/MathNet.Numerics.Properties/index.htm index 4ff0a5f0..fb47dde7 100644 --- a/api/MathNet.Numerics.Properties/index.htm +++ b/api/MathNet.Numerics.Properties/index.htm @@ -143,7 +143,7 @@ diff --git a/api/MathNet.Numerics.Providers.Common.Cuda/CudaProvider.htm b/api/MathNet.Numerics.Providers.Common.Cuda/CudaProvider.htm index 8a5e4f4d..dc57fb38 100644 --- a/api/MathNet.Numerics.Providers.Common.Cuda/CudaProvider.htm +++ b/api/MathNet.Numerics.Providers.Common.Cuda/CudaProvider.htm @@ -202,7 +202,7 @@ This method is safe to call, even if the provider is not loaded. diff --git a/api/MathNet.Numerics.Providers.Common.Cuda/index.htm b/api/MathNet.Numerics.Providers.Common.Cuda/index.htm index c73d02d7..d66cae8e 100644 --- a/api/MathNet.Numerics.Providers.Common.Cuda/index.htm +++ b/api/MathNet.Numerics.Providers.Common.Cuda/index.htm @@ -143,7 +143,7 @@ diff --git a/api/MathNet.Numerics.Providers.Common.Mkl/MklAccuracy.htm b/api/MathNet.Numerics.Providers.Common.Mkl/MklAccuracy.htm index a9b811ad..66a0b8f7 100644 --- a/api/MathNet.Numerics.Providers.Common.Mkl/MklAccuracy.htm +++ b/api/MathNet.Numerics.Providers.Common.Mkl/MklAccuracy.htm @@ -255,8 +255,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -264,11 +267,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -315,7 +315,7 @@
    diff --git a/api/MathNet.Numerics.Providers.Common.Mkl/MklConsistency.htm b/api/MathNet.Numerics.Providers.Common.Mkl/MklConsistency.htm index dbc20ca1..af8cf07b 100644 --- a/api/MathNet.Numerics.Providers.Common.Mkl/MklConsistency.htm +++ b/api/MathNet.Numerics.Providers.Common.Mkl/MklConsistency.htm @@ -261,8 +261,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -270,11 +273,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -369,7 +369,7 @@
    diff --git a/api/MathNet.Numerics.Providers.Common.Mkl/MklPrecision.htm b/api/MathNet.Numerics.Providers.Common.Mkl/MklPrecision.htm index 4a7591dd..e0c8ea23 100644 --- a/api/MathNet.Numerics.Providers.Common.Mkl/MklPrecision.htm +++ b/api/MathNet.Numerics.Providers.Common.Mkl/MklPrecision.htm @@ -255,8 +255,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -264,11 +267,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -315,7 +315,7 @@
    diff --git a/api/MathNet.Numerics.Providers.Common.Mkl/MklProvider.htm b/api/MathNet.Numerics.Providers.Common.Mkl/MklProvider.htm index 0ad0ef63..f64692e1 100644 --- a/api/MathNet.Numerics.Providers.Common.Mkl/MklProvider.htm +++ b/api/MathNet.Numerics.Providers.Common.Mkl/MklProvider.htm @@ -307,7 +307,7 @@ This method is safe to call, even if the provider is not loaded. diff --git a/api/MathNet.Numerics.Providers.Common.Mkl/index.htm b/api/MathNet.Numerics.Providers.Common.Mkl/index.htm index 5e63d3f6..ff899bb5 100644 --- a/api/MathNet.Numerics.Providers.Common.Mkl/index.htm +++ b/api/MathNet.Numerics.Providers.Common.Mkl/index.htm @@ -155,7 +155,7 @@ diff --git a/api/MathNet.Numerics.Providers.Common.OpenBlas/OpenBlasProvider.htm b/api/MathNet.Numerics.Providers.Common.OpenBlas/OpenBlasProvider.htm index c39acbeb..0390ce96 100644 --- a/api/MathNet.Numerics.Providers.Common.OpenBlas/OpenBlasProvider.htm +++ b/api/MathNet.Numerics.Providers.Common.OpenBlas/OpenBlasProvider.htm @@ -202,7 +202,7 @@ This method is safe to call, even if the provider is not loaded. diff --git a/api/MathNet.Numerics.Providers.Common.OpenBlas/index.htm b/api/MathNet.Numerics.Providers.Common.OpenBlas/index.htm index 2f6e1830..5bc7a491 100644 --- a/api/MathNet.Numerics.Providers.Common.OpenBlas/index.htm +++ b/api/MathNet.Numerics.Providers.Common.OpenBlas/index.htm @@ -143,7 +143,7 @@ diff --git a/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformControl.htm b/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformControl.htm index 7619061a..c696f49a 100644 --- a/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformControl.htm +++ b/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformControl.htm @@ -276,7 +276,7 @@ If not set, Numerics will fall back to the environment variable diff --git a/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformScaling.htm b/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformScaling.htm index d9628837..3ecef4bc 100644 --- a/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformScaling.htm +++ b/api/MathNet.Numerics.Providers.FourierTransform/FourierTransformScaling.htm @@ -254,8 +254,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -263,11 +266,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -338,7 +338,7 @@
    diff --git a/api/MathNet.Numerics.Providers.FourierTransform/IFourierTransformProvider.htm b/api/MathNet.Numerics.Providers.FourierTransform/IFourierTransformProvider.htm index 0ca7c535..e4f3f5c7 100644 --- a/api/MathNet.Numerics.Providers.FourierTransform/IFourierTransformProvider.htm +++ b/api/MathNet.Numerics.Providers.FourierTransform/IFourierTransformProvider.htm @@ -313,7 +313,7 @@ Verification may still fail if available, but it will certainly fail if unavaila diff --git a/api/MathNet.Numerics.Providers.FourierTransform/index.htm b/api/MathNet.Numerics.Providers.FourierTransform/index.htm index 35d0dfce..c785cae2 100644 --- a/api/MathNet.Numerics.Providers.FourierTransform/index.htm +++ b/api/MathNet.Numerics.Providers.FourierTransform/index.htm @@ -154,7 +154,7 @@ diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/NativeError.htm b/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/NativeError.htm index d54b9c32..276fe352 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/NativeError.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/NativeError.htm @@ -247,8 +247,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -256,11 +259,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -295,7 +295,7 @@
    diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/index.htm b/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/index.htm index 2e515872..c60eb3f5 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/index.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra.OpenBlas/index.htm @@ -143,7 +143,7 @@ diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider.htm b/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider.htm index 5596a0bb..deb88293 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider.htm @@ -202,7 +202,7 @@ Verification may still fail if available, but it will certainly fail if unavaila diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider`1.htm b/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider`1.htm index acc9bb1d..1141ed5f 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider`1.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra/ILinearAlgebraProvider`1.htm @@ -899,7 +899,7 @@ to be used by the QR solve routine.

    diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra/LinearAlgebraControl.htm b/api/MathNet.Numerics.Providers.LinearAlgebra/LinearAlgebraControl.htm index ee225a65..f45d76ed 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra/LinearAlgebraControl.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra/LinearAlgebraControl.htm @@ -343,7 +343,7 @@ Consider to use UseNativeMKL or UseManaged instead. diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra/Norm.htm b/api/MathNet.Numerics.Providers.LinearAlgebra/Norm.htm index ec1f2688..da8f2b08 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra/Norm.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra/Norm.htm @@ -262,8 +262,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -271,11 +274,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -346,7 +346,7 @@
    diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra/Transpose.htm b/api/MathNet.Numerics.Providers.LinearAlgebra/Transpose.htm index 66a958c4..2b7c2b8e 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra/Transpose.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra/Transpose.htm @@ -261,8 +261,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -270,11 +273,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -335,7 +335,7 @@
    diff --git a/api/MathNet.Numerics.Providers.LinearAlgebra/index.htm b/api/MathNet.Numerics.Providers.LinearAlgebra/index.htm index 4d4207c7..ed5c551e 100644 --- a/api/MathNet.Numerics.Providers.LinearAlgebra/index.htm +++ b/api/MathNet.Numerics.Providers.LinearAlgebra/index.htm @@ -162,7 +162,7 @@ diff --git a/api/MathNet.Numerics.Random/CryptoRandomSource.htm b/api/MathNet.Numerics.Random/CryptoRandomSource.htm index fef3d6b5..76223c52 100644 --- a/api/MathNet.Numerics.Random/CryptoRandomSource.htm +++ b/api/MathNet.Numerics.Random/CryptoRandomSource.htm @@ -618,7 +618,7 @@ diff --git a/api/MathNet.Numerics.Random/Mcg31m1.htm b/api/MathNet.Numerics.Random/Mcg31m1.htm index f1e4edb6..e3224811 100644 --- a/api/MathNet.Numerics.Random/Mcg31m1.htm +++ b/api/MathNet.Numerics.Random/Mcg31m1.htm @@ -607,7 +607,7 @@ set whether the instance is thread safe. diff --git a/api/MathNet.Numerics.Random/Mcg59.htm b/api/MathNet.Numerics.Random/Mcg59.htm index 93dd70ff..c7e569ee 100644 --- a/api/MathNet.Numerics.Random/Mcg59.htm +++ b/api/MathNet.Numerics.Random/Mcg59.htm @@ -609,7 +609,7 @@ set whether the instance is thread safe. diff --git a/api/MathNet.Numerics.Random/MersenneTwister.htm b/api/MathNet.Numerics.Random/MersenneTwister.htm index d3f54f47..3664876d 100644 --- a/api/MathNet.Numerics.Random/MersenneTwister.htm +++ b/api/MathNet.Numerics.Random/MersenneTwister.htm @@ -622,7 +622,7 @@ set whether the instance is thread safe. diff --git a/api/MathNet.Numerics.Random/Mrg32k3a.htm b/api/MathNet.Numerics.Random/Mrg32k3a.htm index ce999d42..8c8df05d 100644 --- a/api/MathNet.Numerics.Random/Mrg32k3a.htm +++ b/api/MathNet.Numerics.Random/Mrg32k3a.htm @@ -613,7 +613,7 @@ set whether the instance is thread safe. diff --git a/api/MathNet.Numerics.Random/Palf.htm b/api/MathNet.Numerics.Random/Palf.htm index 13d07a4b..7ce1d131 100644 --- a/api/MathNet.Numerics.Random/Palf.htm +++ b/api/MathNet.Numerics.Random/Palf.htm @@ -655,7 +655,7 @@ set whether the instance is thread safe. diff --git a/api/MathNet.Numerics.Random/RandomExtensions.htm b/api/MathNet.Numerics.Random/RandomExtensions.htm index 313e4202..795a08f9 100644 --- a/api/MathNet.Numerics.Random/RandomExtensions.htm +++ b/api/MathNet.Numerics.Random/RandomExtensions.htm @@ -449,7 +449,7 @@ the range of return values includes 0 but not -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    diff --git a/api/MathNet.Numerics.Random/RandomSeed.htm b/api/MathNet.Numerics.Random/RandomSeed.htm index 4437472b..46d901cf 100644 --- a/api/MathNet.Numerics.Random/RandomSeed.htm +++ b/api/MathNet.Numerics.Random/RandomSeed.htm @@ -230,7 +230,7 @@ the same seed value. Do not use for cryptography! diff --git a/api/MathNet.Numerics.Random/RandomSource.htm b/api/MathNet.Numerics.Random/RandomSource.htm index 52bd578f..48332f1a 100644 --- a/api/MathNet.Numerics.Random/RandomSource.htm +++ b/api/MathNet.Numerics.Random/RandomSource.htm @@ -358,8 +358,8 @@ When used directly it use the System.Random as random number source.
    -

    Int32[] NextInt32s(int count)

    -
    Returns an array with random 32-bit signed integers greater than or equal to zero and less than MaxValue. +

    Int32[] NextInt32s(int count, int maxExclusive)

    +
    Returns an array with random 32-bit signed integers within the specified range.
    @@ -367,6 +367,8 @@ When used directly it use the System.Random as random number source.
    int count

    The size of the array to fill.

    +
    int maxExclusive
    +

    The exclusive upper bound of the random number returned. Range: maxExclusive ≥ 1.

    @@ -392,42 +394,40 @@ When used directly it use the System.Random as random number source.
    -

    Int32[] NextInt32s(int count, int minInclusive, int maxExclusive)

    -
    Returns an array with random 32-bit signed integers within the specified range. +

    void NextInt32s(Int32[] values, int maxExclusive)

    +
    Fills an array with random numbers within a specified range.
    Parameters
    -
    int count
    -

    The size of the array to fill.

    -
    int minInclusive
    -

    The inclusive lower bound of the random number returned.

    +
    Int32[] values
    +

    The array to fill with random values.

    int maxExclusive
    -

    The exclusive upper bound of the random number returned. Range: maxExclusive > minExclusive.

    +

    The exclusive upper bound of the random number returned. Range: maxExclusive ≥ 1.

    -

    void NextInt32s(Int32[] values)

    -
    Fills an array with random 32-bit signed integers greater than or equal to zero and less than MaxValue. +

    Int32[] NextInt32s(int count)

    +
    Returns an array with random 32-bit signed integers greater than or equal to zero and less than MaxValue.
    Parameters
    -
    Int32[] values
    -

    The array to fill with random values.

    +
    int count
    +

    The size of the array to fill.

    -

    void NextInt32s(Int32[] values, int maxExclusive)

    -
    Fills an array with random numbers within a specified range. +

    void NextInt32s(Int32[] values)

    +
    Fills an array with random 32-bit signed integers greater than or equal to zero and less than MaxValue.
    @@ -435,15 +435,13 @@ When used directly it use the System.Random as random number source.
    Int32[] values

    The array to fill with random values.

    -
    int maxExclusive
    -

    The exclusive upper bound of the random number returned. Range: maxExclusive ≥ 1.

    -

    Int32[] NextInt32s(int count, int maxExclusive)

    +

    Int32[] NextInt32s(int count, int minInclusive, int maxExclusive)

    Returns an array with random 32-bit signed integers within the specified range. @@ -452,8 +450,10 @@ When used directly it use the System.Random as random number source.
    int count

    The size of the array to fill.

    +
    int minInclusive
    +

    The inclusive lower bound of the random number returned.

    int maxExclusive
    -

    The exclusive upper bound of the random number returned. Range: maxExclusive ≥ 1.

    +

    The exclusive upper bound of the random number returned. Range: maxExclusive > minExclusive.

    @@ -496,7 +496,7 @@ When used directly it use the System.Random as random number source.
    diff --git a/api/MathNet.Numerics.Random/SystemRandomSource.htm b/api/MathNet.Numerics.Random/SystemRandomSource.htm index 10439625..4c3ff6ff 100644 --- a/api/MathNet.Numerics.Random/SystemRandomSource.htm +++ b/api/MathNet.Numerics.Random/SystemRandomSource.htm @@ -651,7 +651,7 @@ WARNING: potentially very short random sequence length, can generate repeated pa
    diff --git a/api/MathNet.Numerics.Random/WH1982.htm b/api/MathNet.Numerics.Random/WH1982.htm index 22583923..8c1d1f7b 100644 --- a/api/MathNet.Numerics.Random/WH1982.htm +++ b/api/MathNet.Numerics.Random/WH1982.htm @@ -612,7 +612,7 @@ set whether the instance is thread safe.
    diff --git a/api/MathNet.Numerics.Random/WH2006.htm b/api/MathNet.Numerics.Random/WH2006.htm index 2a08b2f1..0cec1df7 100644 --- a/api/MathNet.Numerics.Random/WH2006.htm +++ b/api/MathNet.Numerics.Random/WH2006.htm @@ -612,7 +612,7 @@ set whether the instance is thread safe.
    diff --git a/api/MathNet.Numerics.Random/Xorshift.htm b/api/MathNet.Numerics.Random/Xorshift.htm index 9ee0e344..f2046396 100644 --- a/api/MathNet.Numerics.Random/Xorshift.htm +++ b/api/MathNet.Numerics.Random/Xorshift.htm @@ -476,52 +476,52 @@ Uses the default values of:
    - diff --git a/api/MathNet.Numerics.Statistics.Mcmc/Density`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/Density`1.htm index 1961f04a..3c69a107 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/Density`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/Density`1.htm @@ -344,7 +344,7 @@ diff --git a/api/MathNet.Numerics.Statistics.Mcmc/DiffMethod.htm b/api/MathNet.Numerics.Statistics.Mcmc/DiffMethod.htm index aa2de827..2692173b 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/DiffMethod.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/DiffMethod.htm @@ -342,7 +342,7 @@ diff --git a/api/MathNet.Numerics.Statistics.Mcmc/GlobalProposalSampler`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/GlobalProposalSampler`1.htm index e0128bb1..75e0a5c2 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/GlobalProposalSampler`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/GlobalProposalSampler`1.htm @@ -346,7 +346,7 @@ variables from the whole domain. diff --git a/api/MathNet.Numerics.Statistics.Mcmc/HybridMC.htm b/api/MathNet.Numerics.Statistics.Mcmc/HybridMC.htm index 7b51048f..3602acc0 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/HybridMC.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/HybridMC.htm @@ -426,7 +426,7 @@ momentum. diff --git a/api/MathNet.Numerics.Statistics.Mcmc/HybridMCGeneric`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/HybridMCGeneric`1.htm index 8841cf55..bd237b4c 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/HybridMCGeneric`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/HybridMCGeneric`1.htm @@ -315,7 +315,7 @@ to sample the distribution. This can result in a faster convergence than the ran diff --git a/api/MathNet.Numerics.Statistics.Mcmc/LocalProposalSampler`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/LocalProposalSampler`1.htm index 2561e8ba..04607e0c 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/LocalProposalSampler`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/LocalProposalSampler`1.htm @@ -346,7 +346,7 @@ makes a small local move rather than producing a global sample from the proposal diff --git a/api/MathNet.Numerics.Statistics.Mcmc/MCMCDiagnostics.htm b/api/MathNet.Numerics.Statistics.Mcmc/MCMCDiagnostics.htm index edd868eb..c8e9d3a2 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/MCMCDiagnostics.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/MCMCDiagnostics.htm @@ -248,7 +248,7 @@ a . diff --git a/api/MathNet.Numerics.Statistics.Mcmc/McmcSampler`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/McmcSampler`1.htm index d402c794..db6a7120 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/McmcSampler`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/McmcSampler`1.htm @@ -289,7 +289,7 @@ diff --git a/api/MathNet.Numerics.Statistics.Mcmc/MetropolisHastingsSampler`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/MetropolisHastingsSampler`1.htm index 7bc698f3..1ee8b213 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/MetropolisHastingsSampler`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/MetropolisHastingsSampler`1.htm @@ -332,7 +332,7 @@ constructor will set the burn interval. diff --git a/api/MathNet.Numerics.Statistics.Mcmc/MetropolisSampler`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/MetropolisSampler`1.htm index 37b17b14..bea42bf5 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/MetropolisSampler`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/MetropolisSampler`1.htm @@ -328,7 +328,7 @@ of the distribution P. diff --git a/api/MathNet.Numerics.Statistics.Mcmc/RejectionSampler`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/RejectionSampler`1.htm index 22479e59..9da76e18 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/RejectionSampler`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/RejectionSampler`1.htm @@ -317,7 +317,7 @@ to be normalized, but we do need that for each x, P(x) < Q(x). diff --git a/api/MathNet.Numerics.Statistics.Mcmc/TransitionKernelLn`1.htm b/api/MathNet.Numerics.Statistics.Mcmc/TransitionKernelLn`1.htm index 416a43c7..af62c0e9 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/TransitionKernelLn`1.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/TransitionKernelLn`1.htm @@ -344,7 +344,7 @@ diff --git a/api/MathNet.Numerics.Statistics.Mcmc/UnivariateHybridMC.htm b/api/MathNet.Numerics.Statistics.Mcmc/UnivariateHybridMC.htm index 912fd838..6462a6f4 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/UnivariateHybridMC.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/UnivariateHybridMC.htm @@ -398,7 +398,7 @@ momentum. diff --git a/api/MathNet.Numerics.Statistics.Mcmc/UnivariateSliceSampler.htm b/api/MathNet.Numerics.Statistics.Mcmc/UnivariateSliceSampler.htm index c421aae5..207a97ad 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/UnivariateSliceSampler.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/UnivariateSliceSampler.htm @@ -356,7 +356,7 @@ will set the number of burnInterval iterations and run a burnInterval phase. diff --git a/api/MathNet.Numerics.Statistics.Mcmc/index.htm b/api/MathNet.Numerics.Statistics.Mcmc/index.htm index 1256be52..12ec5f3d 100644 --- a/api/MathNet.Numerics.Statistics.Mcmc/index.htm +++ b/api/MathNet.Numerics.Statistics.Mcmc/index.htm @@ -199,7 +199,7 @@ diff --git a/api/MathNet.Numerics.Statistics/ArrayStatistics.htm b/api/MathNet.Numerics.Statistics/ArrayStatistics.htm index f3a8ad6d..4578c3bb 100644 --- a/api/MathNet.Numerics.Statistics/ArrayStatistics.htm +++ b/api/MathNet.Numerics.Statistics/ArrayStatistics.htm @@ -281,7 +281,7 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    -

    double Covariance(Double[] samples1, Double[] samples2)

    +

    double Covariance(Int32[] samples1, Int32[] samples2)

    Estimates the unbiased population covariance from the provided two sample arrays. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN. @@ -290,9 +290,9 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    Parameters
    -
    Double[] samples1
    +
    Int32[] samples1

    First sample array.

    -
    Double[] samples2
    +
    Int32[] samples2

    Second sample array.

    @@ -300,7 +300,7 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    -

    double Covariance(Int32[] samples1, Int32[] samples2)

    +

    double Covariance(Double[] samples1, Double[] samples2)

    Estimates the unbiased population covariance from the provided two sample arrays. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN. @@ -309,9 +309,9 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    Parameters
    -
    Int32[] samples1
    +
    Double[] samples1

    First sample array.

    -
    Int32[] samples2
    +
    Double[] samples2

    Second sample array.

    @@ -319,7 +319,7 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    -

    Double[] FiveNumberSummaryInplace(Double[] data)

    +

    Single[] FiveNumberSummaryInplace(Single[] data)

    Estimates {min, lower-quantile, median, upper-quantile, max} from the unsorted data array. Approximately median-unbiased regardless of the sample distribution (R8). WARNING: Works inplace and can thus causes the data array to be reordered. @@ -328,7 +328,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -336,7 +336,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    Single[] FiveNumberSummaryInplace(Single[] data)

    +

    Double[] FiveNumberSummaryInplace(Double[] data)

    Estimates {min, lower-quantile, median, upper-quantile, max} from the unsorted data array. Approximately median-unbiased regardless of the sample distribution (R8). WARNING: Works inplace and can thus causes the data array to be reordered. @@ -345,7 +345,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -353,7 +353,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double GeometricMean(Single[] data)

    +

    double GeometricMean(Int32[] data)

    Evaluates the geometric mean of the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -361,7 +361,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Single[] data
    +
    Int32[] data

    Sample array, no sorting is assumed.

    @@ -369,7 +369,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double GeometricMean(Int32[] data)

    +

    double GeometricMean(Single[] data)

    Evaluates the geometric mean of the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -377,7 +377,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Int32[] data
    +
    Single[] data

    Sample array, no sorting is assumed.

    @@ -401,7 +401,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double HarmonicMean(Int32[] data)

    +

    double HarmonicMean(Single[] data)

    Evaluates the harmonic mean of the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -409,7 +409,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Int32[] data
    +
    Single[] data

    Sample array, no sorting is assumed.

    @@ -417,7 +417,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double HarmonicMean(Single[] data)

    +

    double HarmonicMean(Int32[] data)

    Evaluates the harmonic mean of the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -425,7 +425,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Single[] data
    +
    Int32[] data

    Sample array, no sorting is assumed.

    @@ -449,7 +449,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    float InterquartileRangeInplace(Single[] data)

    +

    double InterquartileRangeInplace(Double[] data)

    Estimates the inter-quartile range from the unsorted data array. Approximately median-unbiased regardless of the sample distribution (R8). WARNING: Works inplace and can thus causes the data array to be reordered. @@ -458,7 +458,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -466,7 +466,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double InterquartileRangeInplace(Double[] data)

    +

    float InterquartileRangeInplace(Single[] data)

    Estimates the inter-quartile range from the unsorted data array. Approximately median-unbiased regardless of the sample distribution (R8). WARNING: Works inplace and can thus causes the data array to be reordered. @@ -475,7 +475,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -483,7 +483,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double LowerQuartileInplace(Double[] data)

    +

    float LowerQuartileInplace(Single[] data)

    Estimates the first quartile value from the unsorted data array. Approximately median-unbiased regardless of the sample distribution (R8). WARNING: Works inplace and can thus causes the data array to be reordered. @@ -492,7 +492,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -500,7 +500,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    float LowerQuartileInplace(Single[] data)

    +

    double LowerQuartileInplace(Double[] data)

    Estimates the first quartile value from the unsorted data array. Approximately median-unbiased regardless of the sample distribution (R8). WARNING: Works inplace and can thus causes the data array to be reordered. @@ -509,7 +509,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -581,7 +581,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    Complex32 MaximumMagnitudePhase(Complex32[] data)

    +

    Complex MaximumMagnitudePhase(Complex[] data)

    Returns the largest absolute value from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -589,7 +589,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Complex32[] data
    +
    Complex[] data

    Sample array, no sorting is assumed.

    @@ -597,7 +597,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    Complex MaximumMagnitudePhase(Complex[] data)

    +

    Complex32 MaximumMagnitudePhase(Complex32[] data)

    Returns the largest absolute value from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -605,7 +605,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Complex[] data
    +
    Complex32[] data

    Sample array, no sorting is assumed.

    @@ -613,7 +613,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double Mean(Double[] data)

    +

    double Mean(Int32[] data)

    Estimates the arithmetic sample mean from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -621,7 +621,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Double[] data
    +
    Int32[] data

    Sample array, no sorting is assumed.

    @@ -629,7 +629,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double Mean(Int32[] data)

    +

    double Mean(Double[] data)

    Estimates the arithmetic sample mean from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -637,7 +637,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Int32[] data
    +
    Double[] data

    Sample array, no sorting is assumed.

    @@ -763,7 +763,7 @@ Returns NaN for mean if data is empty or any entry is NaN and NaN for variance i
    -

    float MedianInplace(Single[] data)

    +

    double MedianInplace(Double[] data)

    Estimates the median value from the unsorted data array. WARNING: Works inplace and can thus causes the data array to be reordered. @@ -771,7 +771,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -779,7 +779,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double MedianInplace(Double[] data)

    +

    float MedianInplace(Single[] data)

    Estimates the median value from the unsorted data array. WARNING: Works inplace and can thus causes the data array to be reordered. @@ -787,7 +787,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, no sorting is assumed. Will be reordered.

    @@ -827,7 +827,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    float MinimumAbsolute(Single[] data)

    +

    double MinimumAbsolute(Double[] data)

    Returns the smallest absolute value from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -835,7 +835,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, no sorting is assumed.

    @@ -843,7 +843,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double MinimumAbsolute(Double[] data)

    +

    float MinimumAbsolute(Single[] data)

    Returns the smallest absolute value from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -851,7 +851,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, no sorting is assumed.

    @@ -967,7 +967,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double PopulationCovariance(Double[] population1, Double[] population2)

    +

    double PopulationCovariance(Int32[] population1, Int32[] population2)

    Evaluates the population covariance from the full population provided as two arrays. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. @@ -976,9 +976,9 @@ Returns NaN if data is empty or if any entry is NaN.
    Parameters
    -
    Double[] population1
    +
    Int32[] population1

    First population array.

    -
    Double[] population2
    +
    Int32[] population2

    Second population array.

    @@ -986,7 +986,7 @@ Returns NaN if data is empty or if any entry is NaN.
    -

    double PopulationCovariance(Int32[] population1, Int32[] population2)

    +

    double PopulationCovariance(Double[] population1, Double[] population2)

    Evaluates the population covariance from the full population provided as two arrays. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. @@ -995,9 +995,9 @@ Returns NaN if data is empty or if any entry is NaN.
    Parameters
    -
    Int32[] population1
    +
    Double[] population1

    First population array.

    -
    Int32[] population2
    +
    Double[] population2

    Second population array.

    @@ -1041,7 +1041,7 @@ Returns NaN if data is empty or if any entry is NaN.
    -

    double PopulationStandardDeviation(Int32[] population)

    +

    double PopulationStandardDeviation(Single[] population)

    Evaluates the population standard deviation from the full population provided as unsorted array. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. @@ -1050,7 +1050,7 @@ Returns NaN if data is empty or if any entry is NaN.
    Parameters
    -
    Int32[] population
    +
    Single[] population

    Sample array, no sorting is assumed.

    @@ -1058,7 +1058,7 @@ Returns NaN if data is empty or if any entry is NaN.
    -

    double PopulationStandardDeviation(Single[] population)

    +

    double PopulationStandardDeviation(Int32[] population)

    Evaluates the population standard deviation from the full population provided as unsorted array. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. @@ -1067,7 +1067,7 @@ Returns NaN if data is empty or if any entry is NaN.
    Parameters
    -
    Single[] population
    +
    Int32[] population

    Sample array, no sorting is assumed.

    @@ -1075,7 +1075,7 @@ Returns NaN if data is empty or if any entry is NaN.
    -

    double PopulationVariance(Double[] population)

    +

    double PopulationVariance(Single[] population)

    Evaluates the population variance from the full population provided as unsorted array. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. @@ -1084,7 +1084,7 @@ Returns NaN if data is empty or if any entry is NaN.
    Parameters
    -
    Double[] population
    +
    Single[] population

    Sample array, no sorting is assumed.

    @@ -1092,7 +1092,7 @@ Returns NaN if data is empty or if any entry is NaN.
    -

    double PopulationVariance(Int32[] population)

    +

    double PopulationVariance(Double[] population)

    Evaluates the population variance from the full population provided as unsorted array. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. @@ -1101,7 +1101,7 @@ Returns NaN if data is empty or if any entry is NaN.
    Parameters
    -
    Int32[] population
    +
    Double[] population

    Sample array, no sorting is assumed.

    @@ -1109,7 +1109,7 @@ Returns NaN if data is empty or if any entry is NaN.
    -

    double PopulationVariance(Single[] population)

    +

    double PopulationVariance(Int32[] population)

    Evaluates the population variance from the full population provided as unsorted array. On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset. Returns NaN if data is empty or if any entry is NaN. @@ -1118,7 +1118,7 @@ Returns NaN if data is empty or if any entry is NaN.
    Parameters
    -
    Single[] population
    +
    Int32[] population

    Sample array, no sorting is assumed.

    @@ -1230,7 +1230,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double QuantileInplace(Double[] data, double tau)

    +

    float QuantileInplace(Single[] data, double tau)

    Estimates the tau-th quantile from the unsorted data array. The tau-th quantile is the data value where the cumulative distribution function crosses tau. @@ -1245,7 +1245,7 @@ When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, no sorting is assumed. Will be reordered.

    double tau

    Quantile selector, between 0.0 and 1.0 (inclusive).

    @@ -1255,7 +1255,7 @@ When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
    -

    float QuantileInplace(Single[] data, double tau)

    +

    double QuantileInplace(Double[] data, double tau)

    Estimates the tau-th quantile from the unsorted data array. The tau-th quantile is the data value where the cumulative distribution function crosses tau. @@ -1270,7 +1270,7 @@ When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, no sorting is assumed. Will be reordered.

    double tau

    Quantile selector, between 0.0 and 1.0 (inclusive).

    @@ -1304,7 +1304,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double RootMeanSquare(Int32[] data)

    +

    double RootMeanSquare(Double[] data)

    Estimates the root mean square (RMS) also known as quadratic mean from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -1312,7 +1312,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Int32[] data
    +
    Double[] data

    Sample array, no sorting is assumed.

    @@ -1320,7 +1320,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double RootMeanSquare(Double[] data)

    +

    double RootMeanSquare(Single[] data)

    Estimates the root mean square (RMS) also known as quadratic mean from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -1328,7 +1328,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, no sorting is assumed.

    @@ -1336,7 +1336,7 @@ Returns NaN if data is empty or any entry is NaN.
    -

    double RootMeanSquare(Single[] data)

    +

    double RootMeanSquare(Int32[] data)

    Estimates the root mean square (RMS) also known as quadratic mean from the unsorted data array. Returns NaN if data is empty or any entry is NaN. @@ -1344,7 +1344,7 @@ Returns NaN if data is empty or any entry is NaN.
    Parameters
    -
    Single[] data
    +
    Int32[] data

    Sample array, no sorting is assumed.

    @@ -1437,7 +1437,7 @@ WARNING: Works inplace and can thus causes the data array to be reordered.
    -

    double Variance(Int32[] samples)

    +

    double Variance(Single[] samples)

    Estimates the unbiased population variance from the provided samples as unsorted array. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN. @@ -1446,7 +1446,7 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    Parameters
    -
    Int32[] samples
    +
    Single[] samples

    Sample array, no sorting is assumed.

    @@ -1454,7 +1454,7 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    -

    double Variance(Single[] samples)

    +

    double Variance(Int32[] samples)

    Estimates the unbiased population variance from the provided samples as unsorted array. On a dataset of size N will use an N-1 normalizer (Bessel's correction). Returns NaN if data has less than two entries or if any entry is NaN. @@ -1463,7 +1463,7 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    Parameters
    -
    Single[] samples
    +
    Int32[] samples

    Sample array, no sorting is assumed.

    @@ -1490,7 +1490,7 @@ Returns NaN if data has less than two entries or if any entry is NaN. diff --git a/api/MathNet.Numerics.Statistics/Bucket.htm b/api/MathNet.Numerics.Statistics/Bucket.htm index 6d5a8973..07ec9fd1 100644 --- a/api/MathNet.Numerics.Statistics/Bucket.htm +++ b/api/MathNet.Numerics.Statistics/Bucket.htm @@ -371,7 +371,7 @@ difference in Count given by .
    diff --git a/api/MathNet.Numerics.Statistics/Correlation.htm b/api/MathNet.Numerics.Statistics/Correlation.htm index 1f41ce04..3604f4ef 100644 --- a/api/MathNet.Numerics.Statistics/Correlation.htm +++ b/api/MathNet.Numerics.Statistics/Correlation.htm @@ -395,7 +395,7 @@ diff --git a/api/MathNet.Numerics.Statistics/DescriptiveStatistics.htm b/api/MathNet.Numerics.Statistics/DescriptiveStatistics.htm index d77d14da..5269b856 100644 --- a/api/MathNet.Numerics.Statistics/DescriptiveStatistics.htm +++ b/api/MathNet.Numerics.Statistics/DescriptiveStatistics.htm @@ -350,7 +350,7 @@ Increased accuracy mode uses Decimal types
    diff --git a/api/MathNet.Numerics.Statistics/Histogram.htm b/api/MathNet.Numerics.Statistics/Histogram.htm index ace3b5e1..e1f3c1f2 100644 --- a/api/MathNet.Numerics.Statistics/Histogram.htm +++ b/api/MathNet.Numerics.Statistics/Histogram.htm @@ -415,7 +415,7 @@ the lowerbound or upperbound will automatically adapt. diff --git a/api/MathNet.Numerics.Statistics/KernelDensity.htm b/api/MathNet.Numerics.Statistics/KernelDensity.htm index 7107b581..d0ea001d 100644 --- a/api/MathNet.Numerics.Statistics/KernelDensity.htm +++ b/api/MathNet.Numerics.Statistics/KernelDensity.htm @@ -290,7 +290,7 @@ x => Math.Abs(x) <= 1.0 ? 1.0/2.0 : 0.0 diff --git a/api/MathNet.Numerics.Statistics/MovingStatistics.htm b/api/MathNet.Numerics.Statistics/MovingStatistics.htm index af3fb43e..892bcea1 100644 --- a/api/MathNet.Numerics.Statistics/MovingStatistics.htm +++ b/api/MathNet.Numerics.Statistics/MovingStatistics.htm @@ -357,7 +357,7 @@ Returns NaN if data has less than two entries or if any entry is NaN. diff --git a/api/MathNet.Numerics.Statistics/QuantileDefinition.htm b/api/MathNet.Numerics.Statistics/QuantileDefinition.htm index c637d5e7..bfecfee3 100644 --- a/api/MathNet.Numerics.Statistics/QuantileDefinition.htm +++ b/api/MathNet.Numerics.Statistics/QuantileDefinition.htm @@ -309,8 +309,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -318,11 +321,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -693,7 +693,7 @@
    diff --git a/api/MathNet.Numerics.Statistics/RankDefinition.htm b/api/MathNet.Numerics.Statistics/RankDefinition.htm index 3498dd08..b7b7cb15 100644 --- a/api/MathNet.Numerics.Statistics/RankDefinition.htm +++ b/api/MathNet.Numerics.Statistics/RankDefinition.htm @@ -287,8 +287,11 @@
    -

    string ToString(string format)

    +

    string ToString(IFormatProvider provider)

    +
    + Obsolete: The provider argument is not used. Please use ToString(). +
    @@ -296,11 +299,8 @@
    -

    string ToString(IFormatProvider provider)

    +

    string ToString(string format)

    -
    - Obsolete: The provider argument is not used. Please use ToString(). -
    @@ -407,7 +407,7 @@
    diff --git a/api/MathNet.Numerics.Statistics/RunningStatistics.htm b/api/MathNet.Numerics.Statistics/RunningStatistics.htm index 0b2c9a1b..01c6ebc7 100644 --- a/api/MathNet.Numerics.Statistics/RunningStatistics.htm +++ b/api/MathNet.Numerics.Statistics/RunningStatistics.htm @@ -407,7 +407,7 @@ Returns NaN if data has less than two entries or if any entry is NaN. diff --git a/api/MathNet.Numerics.Statistics/SortedArrayStatistics.htm b/api/MathNet.Numerics.Statistics/SortedArrayStatistics.htm index 8daa200f..db456f22 100644 --- a/api/MathNet.Numerics.Statistics/SortedArrayStatistics.htm +++ b/api/MathNet.Numerics.Statistics/SortedArrayStatistics.htm @@ -255,7 +255,7 @@
    -

    Single[] FiveNumberSummary(Single[] data)

    +

    Double[] FiveNumberSummary(Double[] data)

    Estimates {min, lower-quantile, median, upper-quantile, max} from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8). @@ -263,7 +263,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, must be sorted ascendingly.

    @@ -271,7 +271,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    Double[] FiveNumberSummary(Double[] data)

    +

    Single[] FiveNumberSummary(Single[] data)

    Estimates {min, lower-quantile, median, upper-quantile, max} from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8). @@ -279,7 +279,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, must be sorted ascendingly.

    @@ -287,7 +287,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    float InterquartileRange(Single[] data)

    +

    double InterquartileRange(Double[] data)

    Estimates the inter-quartile range from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8). @@ -295,7 +295,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, must be sorted ascendingly.

    @@ -303,7 +303,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    double InterquartileRange(Double[] data)

    +

    float InterquartileRange(Single[] data)

    Estimates the inter-quartile range from the sorted data array (ascending). Approximately median-unbiased regardless of the sample distribution (R8). @@ -311,7 +311,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, must be sorted ascendingly.

    @@ -443,14 +443,14 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    double OrderStatistic(Double[] data, int order)

    +

    float OrderStatistic(Single[] data, int order)

    Returns the order statistic (order 1..N) from the sorted data array (ascending).
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, must be sorted ascendingly.

    int order

    One-based order of the statistic, must be between 1 and N (inclusive).

    @@ -460,14 +460,14 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    float OrderStatistic(Single[] data, int order)

    +

    double OrderStatistic(Double[] data, int order)

    Returns the order statistic (order 1..N) from the sorted data array (ascending).
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, must be sorted ascendingly.

    int order

    One-based order of the statistic, must be between 1 and N (inclusive).

    @@ -477,7 +477,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    double Percentile(Double[] data, int p)

    +

    float Percentile(Single[] data, int p)

    Estimates the p-Percentile value from the sorted data array (ascending). If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8). @@ -486,7 +486,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, must be sorted ascendingly.

    int p

    Percentile selector, between 0 and 100 (inclusive).

    @@ -496,7 +496,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    float Percentile(Single[] data, int p)

    +

    double Percentile(Double[] data, int p)

    Estimates the p-Percentile value from the sorted data array (ascending). If a non-integer Percentile is needed, use Quantile instead. Approximately median-unbiased regardless of the sample distribution (R8). @@ -505,7 +505,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, must be sorted ascendingly.

    int p

    Percentile selector, between 0 and 100 (inclusive).

    @@ -515,7 +515,7 @@ Approximately median-unbiased regardless of the sample distribution (R8).
    -

    double Quantile(Double[] data, double tau)

    +

    float Quantile(Single[] data, double tau)

    Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. @@ -529,7 +529,7 @@ When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, must be sorted ascendingly.

    double tau

    Quantile selector, between 0.0 and 1.0 (inclusive).

    @@ -539,7 +539,7 @@ When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
    -

    float Quantile(Single[] data, double tau)

    +

    double Quantile(Double[] data, double tau)

    Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. @@ -553,7 +553,7 @@ When tau < (2/3) / (N + 1/3), use x1. When tau >= (N - 1/3) / (N + 1/3), use xN.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, must be sorted ascendingly.

    double tau

    Quantile selector, between 0.0 and 1.0 (inclusive).

    @@ -585,7 +585,7 @@ with an existing system.
    -

    float QuantileCustom(Single[] data, double tau, double a, double b, double c, double d)

    +

    double QuantileCustom(Double[] data, double tau, double a, double b, double c, double d)

    Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile definition can be specified @@ -595,7 +595,7 @@ by 4 parameters a, b, c and d, consistent with Mathematica.
    Parameters
    -
    Single[] data
    +
    Double[] data

    Sample array, must be sorted ascendingly.

    double tau

    Quantile selector, between 0.0 and 1.0 (inclusive).

    @@ -613,11 +613,11 @@ by 4 parameters a, b, c and d, consistent with Mathematica.
    -

    float QuantileCustom(Single[] data, double tau, QuantileDefinition definition)

    +

    float QuantileCustom(Single[] data, double tau, double a, double b, double c, double d)

    Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution -function crosses tau. The quantile definition can be specified to be compatible -with an existing system. +function crosses tau. The quantile definition can be specified +by 4 parameters a, b, c and d, consistent with Mathematica.
    @@ -627,43 +627,43 @@ with an existing system.

    Sample array, must be sorted ascendingly.

    double tau

    Quantile selector, between 0.0 and 1.0 (inclusive).

    -
    QuantileDefinition definition
    -

    Quantile definition, to choose what product/definition it should be consistent with

    +
    double a
    +

    a-parameter

    +
    double b
    +

    b-parameter

    +
    double c
    +

    c-parameter

    +
    double d
    +

    d-parameter

    -

    double QuantileCustom(Double[] data, double tau, double a, double b, double c, double d)

    +

    float QuantileCustom(Single[] data, double tau, QuantileDefinition definition)

    Estimates the tau-th quantile from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution -function crosses tau. The quantile definition can be specified -by 4 parameters a, b, c and d, consistent with Mathematica. +function crosses tau. The quantile definition can be specified to be compatible +with an existing system.
    Parameters
    -
    Double[] data
    +
    Single[] data

    Sample array, must be sorted ascendingly.

    double tau

    Quantile selector, between 0.0 and 1.0 (inclusive).

    -
    double a
    -

    a-parameter

    -
    double b
    -

    b-parameter

    -
    double c
    -

    c-parameter

    -
    double d
    -

    d-parameter

    +
    QuantileDefinition definition
    +

    Quantile definition, to choose what product/definition it should be consistent with

    -

    double QuantileRank(Single[] data, float x, RankDefinition definition)

    +

    double QuantileRank(Double[] data, double x, RankDefinition definition)

    Estimates the quantile tau from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile definition can be specified to be compatible @@ -673,9 +673,9 @@ with an existing system.
    Parameters
    -
    Single[] data
    +
    Double[] data

    The data sample sequence.

    -
    float x
    +
    double x

    Quantile value.

    RankDefinition definition

    Rank definition, to choose how ties should be handled and what product/definition it should be consistent with

    @@ -685,7 +685,7 @@ with an existing system.
    -

    double QuantileRank(Double[] data, double x, RankDefinition definition)

    +

    double QuantileRank(Single[] data, float x, RankDefinition definition)

    Estimates the quantile tau from the sorted data array (ascending). The tau-th quantile is the data value where the cumulative distribution function crosses tau. The quantile definition can be specified to be compatible @@ -695,9 +695,9 @@ with an existing system.
    Parameters
    -
    Double[] data
    +
    Single[] data

    The data sample sequence.

    -
    double x
    +
    float x

    Quantile value.

    RankDefinition definition

    Rank definition, to choose how ties should be handled and what product/definition it should be consistent with

    @@ -763,7 +763,7 @@ Approximately median-unbiased regardless of the sample distribution (R8). diff --git a/api/MathNet.Numerics.Statistics/Statistics.htm b/api/MathNet.Numerics.Statistics/Statistics.htm index b34ccb8d..6f458a74 100644 --- a/api/MathNet.Numerics.Statistics/Statistics.htm +++ b/api/MathNet.Numerics.Statistics/Statistics.htm @@ -258,16 +258,16 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    -

    double EmpiricalCDF(this IEnumerable<double> data, double x)

    +

    double EmpiricalCDF(this IEnumerable<float> data, float x)

    Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
    Parameters
    -
    IEnumerable<double> data
    +
    IEnumerable<float> data

    The data sample sequence.

    -
    double x
    +
    float x

    The value where to estimate the CDF at.

    @@ -275,16 +275,16 @@ Returns NaN if data has less than two entries or if any entry is NaN.
    -

    double EmpiricalCDF(this IEnumerable<float> data, float x)

    +

    double EmpiricalCDF(this IEnumerable<double> data, double x)

    Estimates the empirical cumulative distribution function (CDF) at x from the provided samples.
    Parameters
    -
    IEnumerable<float> data
    +
    IEnumerable<double> data

    The data sample sequence.

    -
    float x
    +
    double x

    The value where to estimate the CDF at.

    @@ -1121,7 +1121,7 @@ Returns NaN if data has less than two entries or if any entry is NaN. diff --git a/api/MathNet.Numerics.Statistics/StreamingStatistics.htm b/api/MathNet.Numerics.Statistics/StreamingStatistics.htm index 0ea3be8b..289a2c6a 100644 --- a/api/MathNet.Numerics.Statistics/StreamingStatistics.htm +++ b/api/MathNet.Numerics.Statistics/StreamingStatistics.htm @@ -529,7 +529,7 @@ Returns NaN if data has less than two entries or if any entry is NaN. diff --git a/api/MathNet.Numerics.Statistics/index.htm b/api/MathNet.Numerics.Statistics/index.htm index 97eb02ab..bac6426a 100644 --- a/api/MathNet.Numerics.Statistics/index.htm +++ b/api/MathNet.Numerics.Statistics/index.htm @@ -191,7 +191,7 @@
    diff --git a/api/MathNet.Numerics/Combinatorics.htm b/api/MathNet.Numerics/Combinatorics.htm index 2eae8d08..47141b1a 100644 --- a/api/MathNet.Numerics/Combinatorics.htm +++ b/api/MathNet.Numerics/Combinatorics.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -311,8 +314,8 @@ The order does not matter and an object can be chosen more than once.
    • -

    Boolean[] GenerateCombination(int n, Random randomSource)

    -
    Generate a random combination, without repetition, by randomly selecting some of N elements. +

    Boolean[] GenerateCombination(int n, int k, Random randomSource)

    +
    Generate a random combination, without repetition, by randomly selecting k of N elements.
    @@ -320,6 +323,8 @@ The order does not matter and an object can be chosen more than once.
    int n

    Number of elements in the set.

    +
    int k
    +

    Number of elements to choose from the set. Each element is chosen at most once.

    Random randomSource

    The random number generator to use. Optional; the default random source will be used if null.

    @@ -333,8 +338,8 @@ The order does not matter and an object can be chosen more than once.
    -

    Boolean[] GenerateCombination(int n, int k, Random randomSource)

    -
    Generate a random combination, without repetition, by randomly selecting k of N elements. +

    Boolean[] GenerateCombination(int n, Random randomSource)

    +
    Generate a random combination, without repetition, by randomly selecting some of N elements.
    @@ -342,8 +347,6 @@ The order does not matter and an object can be chosen more than once.
    int n

    Number of elements in the set.

    -
    int k
    -

    Number of elements to choose from the set. Each element is chosen at most once.

    Random randomSource

    The random number generator to use. Optional; the default random source will be used if null.

    @@ -654,7 +657,7 @@ The order matters and each object can be chosen more than once. diff --git a/api/MathNet.Numerics/Complex32.htm b/api/MathNet.Numerics/Complex32.htm index 2af6b828..231dd675 100644 --- a/api/MathNet.Numerics/Complex32.htm +++ b/api/MathNet.Numerics/Complex32.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -1463,7 +1466,7 @@ with real and imaginary numbers not a number.
    • diff --git a/api/MathNet.Numerics/ComplexExtensions.htm b/api/MathNet.Numerics/ComplexExtensions.htm index 05ddcfe1..0cb5574f 100644 --- a/api/MathNet.Numerics/ComplexExtensions.htm +++ b/api/MathNet.Numerics/ComplexExtensions.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -588,7 +591,7 @@ close this value is to zero.
    • -

    double NormOfDifference(this Complex32 complex, Complex32 otherValue)

    +

    double NormOfDifference(this Complex complex, Complex otherValue)

    Returns a Norm of the difference of two values of this type, which is appropriate for measuring how close together these two values are. @@ -598,7 +601,7 @@ appropriate for measuring how close together these two values are.
    -

    double NormOfDifference(this Complex complex, Complex otherValue)

    +

    double NormOfDifference(this Complex32 complex, Complex32 otherValue)

    Returns a Norm of the difference of two values of this type, which is appropriate for measuring how close together these two values are. @@ -724,7 +727,7 @@ appropriate for measuring how close together these two values are.
    -

    Complex ToComplex(this string value)

    +

    Complex ToComplex(this string value, IFormatProvider formatProvider)

    Creates a complex number based on a string. The string can be in the following formats (without the quotes): 'n', 'ni', 'n +/- ni', 'ni +/- n', 'n,n', 'n,ni,' '(n,n)', or '(n,ni)', where n is a double. @@ -734,7 +737,10 @@ following formats (without the quotes): 'n', 'ni', 'n +/- ni',
    Parameters
    string value
    -

    The string to parse.

    +

    the string to parse.

    +
    IFormatProvider formatProvider
    +

    An IFormatProvider that supplies culture-specific +formatting information.

    @@ -746,7 +752,7 @@ following formats (without the quotes): 'n', 'ni', 'n +/- ni',
    -

    Complex ToComplex(this string value, IFormatProvider formatProvider)

    +

    Complex ToComplex(this string value)

    Creates a complex number based on a string. The string can be in the following formats (without the quotes): 'n', 'ni', 'n +/- ni', 'ni +/- n', 'n,n', 'n,ni,' '(n,n)', or '(n,ni)', where n is a double. @@ -756,10 +762,7 @@ following formats (without the quotes): 'n', 'ni', 'n +/- ni',
    Parameters
    string value
    -

    the string to parse.

    -
    IFormatProvider formatProvider
    -

    An IFormatProvider that supplies culture-specific -formatting information.

    +

    The string to parse.

    @@ -818,7 +821,7 @@ formatting information.

    -

    bool TryToComplex(this string value, IFormatProvider formatProvider, Complex& result)

    +

    bool TryToComplex(this string value, Complex& result)

    @@ -827,7 +830,7 @@ formatting information.

    -

    bool TryToComplex(this string value, Complex& result)

    +

    bool TryToComplex(this string value, IFormatProvider formatProvider, Complex& result)

    @@ -856,7 +859,7 @@ formatting information.

    diff --git a/api/MathNet.Numerics/Constants.htm b/api/MathNet.Numerics/Constants.htm index ea71cdb7..1af859b3 100644 --- a/api/MathNet.Numerics/Constants.htm +++ b/api/MathNet.Numerics/Constants.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -1974,7 +1977,7 @@
    • diff --git a/api/MathNet.Numerics/ContourIntegrate.htm b/api/MathNet.Numerics/ContourIntegrate.htm new file mode 100644 index 00000000..12a57ddf --- /dev/null +++ b/api/MathNet.Numerics/ContourIntegrate.htm @@ -0,0 +1,355 @@ + + + + ContourIntegrate - Math.NET Numerics Documentation + + + + + + + +
    +

    Namespaces

    +
    + +
    +
    +
    +

    Type ContourIntegrate

    +

    Namespace MathNet.Numerics

    +
    +
    +
    Numerical Contour Integration of a complex-valued function over a real variable,. +
    + + +

    Static Functions

    + + + + +
    + + + +

    Public Static Functions

    + +
    +

    Complex DoubleExponential(Func<double, Complex> f, double intervalBegin, double intervalEnd, double targetAbsoluteError)

    +
    Approximation of the definite integral of an analytic smooth complex function by double-exponential quadrature. When either or both limits are infinite, the integrand is assumed rapidly decayed to zero as x -> infinity. + + +
    +
    Parameters
    + +
    Func<double, Complex> f
    +

    The analytic smooth complex function to integrate, defined on the real domain.

    +
    double intervalBegin
    +

    Where the interval starts.

    +
    double intervalEnd
    +

    Where the interval stops.

    +
    double targetAbsoluteError
    +

    The expected relative accuracy of the approximation.

    +
    + +
    +
    Return
    +
    Complex
    +

    Approximation of the finite integral in the given interval.

    +
    + +
    +
    +
    +

    Complex GaussKronrod(Func<double, Complex> f, double intervalBegin, double intervalEnd, double targetRelativeError, int maximumDepth, int order)

    +
    Approximation of the definite integral of an analytic smooth function by Gauss-Kronrod quadrature. When either or both limits are infinite, the integrand is assumed rapidly decayed to zero as x -> infinity. + + +
    +
    Parameters
    + +
    Func<double, Complex> f
    +

    The analytic smooth complex function to integrate, defined on the real domain.

    +
    double intervalBegin
    +

    Where the interval starts.

    +
    double intervalEnd
    +

    Where the interval stops.

    +
    double targetRelativeError
    +

    The expected relative accuracy of the approximation.

    +
    int maximumDepth
    +

    The maximum number of interval splittings permitted before stopping

    +
    int order
    +

    The number of Gauss-Kronrod points. Pre-computed for 15, 21, 31, 41, 51 and 61 points

    +
    + +
    +
    Return
    +
    Complex
    +

    Approximation of the finite integral in the given interval.

    +
    + +
    +
    +
    +

    Complex GaussKronrod(Func<double, Complex> f, double intervalBegin, double intervalEnd, Double& error, Double& L1Norm, double targetRelativeError, int maximumDepth, int order)

    +
    + + + + +
    +
    +
    +

    Complex GaussLegendre(Func<double, Complex> f, double intervalBegin, double intervalEnd, int order)

    +
    Approximation of the definite integral of an analytic smooth complex function by double-exponential quadrature. When either or both limits are infinite, the integrand is assumed rapidly decayed to zero as x -> infinity. + + +
    +
    Parameters
    + +
    Func<double, Complex> f
    +

    The analytic smooth complex function to integrate, defined on the real domain.

    +
    double intervalBegin
    +

    Where the interval starts.

    +
    double intervalEnd
    +

    Where the interval stops.

    +
    int order
    +

    Defines an Nth order Gauss-Legendre rule. The order also defines the number of abscissas and weights for the rule. Precomputed Gauss-Legendre abscissas/weights for orders 2-20, 32, 64, 96, 100, 128, 256, 512, 1024 are used, otherwise they're calculated on the fly.

    +
    + +
    +
    Return
    +
    Complex
    +

    Approximation of the finite integral in the given interval.

    +
    + +
    +
    + + + + + \ No newline at end of file diff --git a/api/MathNet.Numerics/Control.htm b/api/MathNet.Numerics/Control.htm index 0df779b6..5856779e 100644 --- a/api/MathNet.Numerics/Control.htm +++ b/api/MathNet.Numerics/Control.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -416,8 +419,8 @@ Throws if it is not available or failed to initialize, in which case the previou
    • -

    void UseNativeMKL(MklConsistency consistency, MklPrecision precision, MklAccuracy accuracy)

    -
    Use the Intel MKL native provider for linear algebra, with the specified configuration parameters. +

    void UseNativeMKL()

    +
    Use the Intel MKL native provider for linear algebra. Throws if it is not available or failed to initialize, in which case the previous provider is still active. @@ -426,8 +429,8 @@ Throws if it is not available or failed to initialize, in which case the previou
    -

    void UseNativeMKL()

    -
    Use the Intel MKL native provider for linear algebra. +

    void UseNativeMKL(MklConsistency consistency, MklPrecision precision, MklAccuracy accuracy)

    +
    Use the Intel MKL native provider for linear algebra, with the specified configuration parameters. Throws if it is not available or failed to initialize, in which case the previous provider is still active. @@ -497,7 +500,7 @@ Thread safe RNG about two and half time slower than non-thread safe RNG.
    diff --git a/api/MathNet.Numerics/Differentiate.htm b/api/MathNet.Numerics/Differentiate.htm index 74f5e918..a5718d6f 100644 --- a/api/MathNet.Numerics/Differentiate.htm +++ b/api/MathNet.Numerics/Differentiate.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -540,7 +543,7 @@ diff --git a/api/MathNet.Numerics/Distance.htm b/api/MathNet.Numerics/Distance.htm index 52ef3b15..e7e2d20d 100644 --- a/api/MathNet.Numerics/Distance.htm +++ b/api/MathNet.Numerics/Distance.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -344,7 +347,7 @@
    • -

    float Euclidean(Single[] a, Single[] b)

    +

    double Euclidean(Double[] a, Double[] b)

    Euclidean Distance, i.e. the L2-norm of the difference. @@ -353,7 +356,7 @@
    -

    double Euclidean(Double[] a, Double[] b)

    +

    float Euclidean(Single[] a, Single[] b)

    Euclidean Distance, i.e. the L2-norm of the difference. @@ -389,7 +392,7 @@
    -

    double Jaccard(Single[] a, Single[] b)

    +

    double Jaccard(Double[] a, Double[] b)

    Jaccard distance, i.e. 1 - the Jaccard index. @@ -403,7 +406,7 @@
    -

    double Jaccard(Double[] a, Double[] b)

    +

    double Jaccard(Single[] a, Single[] b)

    Jaccard distance, i.e. 1 - the Jaccard index. @@ -498,7 +501,7 @@
    -

    double MSE(Double[] a, Double[] b)

    +

    float MSE(Single[] a, Single[] b)

    Mean-Squared Error (MSE), i.e. the normalized squared L2-norm (Euclidean) of the difference. @@ -507,7 +510,7 @@
    -

    float MSE(Single[] a, Single[] b)

    +

    double MSE(Double[] a, Double[] b)

    Mean-Squared Error (MSE), i.e. the normalized squared L2-norm (Euclidean) of the difference. @@ -590,7 +593,7 @@ diff --git a/api/MathNet.Numerics/Euclid.htm b/api/MathNet.Numerics/Euclid.htm index a1f33d8f..41d008c0 100644 --- a/api/MathNet.Numerics/Euclid.htm +++ b/api/MathNet.Numerics/Euclid.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -283,49 +286,49 @@

    Public Static Functions

    -

    long CeilingToPowerOfTwo(this long number)

    +

    int CeilingToPowerOfTwo(this int number)

    Find the closest perfect power of two that is larger or equal to the provided -64 bit integer. +32 bit integer.
    Parameters
    -
    long number
    +
    int number

    The number of which to find the closest upper power of two.

    Return
    -
    long
    +
    int

    A power of two.

    -

    int CeilingToPowerOfTwo(this int number)

    +

    long CeilingToPowerOfTwo(this long number)

    Find the closest perfect power of two that is larger or equal to the provided -32 bit integer. +64 bit integer.
    Parameters
    -
    int number
    +
    long number

    The number of which to find the closest upper power of two.

    Return
    -
    int
    +
    long

    A power of two.

    -

    BigInteger ExtendedGreatestCommonDivisor(BigInteger a, BigInteger b, BigInteger& x, BigInteger& y)

    +

    long ExtendedGreatestCommonDivisor(long a, long b, Int64& x, Int64& y)

    @@ -334,7 +337,7 @@
    -

    long ExtendedGreatestCommonDivisor(long a, long b, Int64& x, Int64& y)

    +

    BigInteger ExtendedGreatestCommonDivisor(BigInteger a, BigInteger b, BigInteger& x, BigInteger& y)

    @@ -343,105 +346,105 @@
    -

    long GreatestCommonDivisor(long a, long b)

    -
    Returns the greatest common divisor ( gcd ) of two integers using Euclid's algorithm. +

    BigInteger GreatestCommonDivisor(BigInteger[] integers)

    +
    Returns the greatest common divisor ( gcd ) of a set of big integers.
    Parameters
    -
    long a
    -

    First Integer: a.

    -
    long b
    -

    Second Integer: b.

    +
    BigInteger[] integers
    +

    List of Integers.

    Return
    -
    long
    -

    Greatest common divisor gcd (a,b)

    +
    BigInteger
    +

    Greatest common divisor gcd (list of integers)

    -

    long GreatestCommonDivisor(IList<long> integers)

    -
    Returns the greatest common divisor ( gcd ) of a set of integers using Euclid's -algorithm. +

    BigInteger GreatestCommonDivisor(BigInteger a, BigInteger b)

    +
    Returns the greatest common divisor ( gcd ) of two big integers.
    Parameters
    -
    IList<long> integers
    -

    List of Integers.

    +
    BigInteger a
    +

    First Integer: a.

    +
    BigInteger b
    +

    Second Integer: b.

    Return
    -
    long
    -

    Greatest common divisor gcd (list of integers)

    +
    BigInteger
    +

    Greatest common divisor gcd (a,b)

    -

    long GreatestCommonDivisor(Int64[] integers)

    -
    Returns the greatest common divisor ( gcd ) of a set of integers using Euclid's algorithm. +

    long GreatestCommonDivisor(long a, long b)

    +
    Returns the greatest common divisor ( gcd ) of two integers using Euclid's algorithm.
    Parameters
    -
    Int64[] integers
    -

    List of Integers.

    +
    long a
    +

    First Integer: a.

    +
    long b
    +

    Second Integer: b.

    Return
    long
    -

    Greatest common divisor gcd (list of integers)

    +

    Greatest common divisor gcd (a,b)

    -

    BigInteger GreatestCommonDivisor(BigInteger a, BigInteger b)

    -
    Returns the greatest common divisor ( gcd ) of two big integers. +

    long GreatestCommonDivisor(IList<long> integers)

    +
    Returns the greatest common divisor ( gcd ) of a set of integers using Euclid's +algorithm.
    Parameters
    -
    BigInteger a
    -

    First Integer: a.

    -
    BigInteger b
    -

    Second Integer: b.

    +
    IList<long> integers
    +

    List of Integers.

    Return
    -
    BigInteger
    -

    Greatest common divisor gcd (a,b)

    +
    long
    +

    Greatest common divisor gcd (list of integers)

    -

    BigInteger GreatestCommonDivisor(BigInteger[] integers)

    -
    Returns the greatest common divisor ( gcd ) of a set of big integers. +

    long GreatestCommonDivisor(Int64[] integers)

    +
    Returns the greatest common divisor ( gcd ) of a set of integers using Euclid's algorithm.
    Parameters
    -
    BigInteger[] integers
    +
    Int64[] integers

    List of Integers.

    Return
    -
    BigInteger
    +
    long

    Greatest common divisor gcd (list of integers)

    @@ -488,14 +491,14 @@ algorithm.
    -

    bool IsOdd(this long number)

    -
    Find out whether the provided 64 bit integer is an odd number. +

    bool IsOdd(this int number)

    +
    Find out whether the provided 32 bit integer is an odd number.
    Parameters
    -
    long number
    +
    int number

    The number to very whether it's odd.

    @@ -508,14 +511,14 @@ algorithm.
    -

    bool IsOdd(this int number)

    -
    Find out whether the provided 32 bit integer is an odd number. +

    bool IsOdd(this long number)

    +
    Find out whether the provided 64 bit integer is an odd number.
    Parameters
    -
    int number
    +
    long number

    The number to very whether it's odd.

    @@ -568,14 +571,14 @@ algorithm.
    -

    bool IsPowerOfTwo(this int number)

    -
    Find out whether the provided 32 bit integer is a perfect power of two. +

    bool IsPowerOfTwo(this long number)

    +
    Find out whether the provided 64 bit integer is a perfect power of two.
    Parameters
    -
    int number
    +
    long number

    The number to very whether it's a power of two.

    @@ -588,14 +591,14 @@ algorithm.
    -

    bool IsPowerOfTwo(this long number)

    -
    Find out whether the provided 64 bit integer is a perfect power of two. +

    bool IsPowerOfTwo(this int number)

    +
    Find out whether the provided 32 bit integer is a perfect power of two.
    Parameters
    -
    long number
    +
    int number

    The number to very whether it's a power of two.

    @@ -608,105 +611,105 @@ algorithm.
    -

    long LeastCommonMultiple(IList<long> integers)

    -
    Returns the least common multiple ( lcm ) of a set of integers using Euclid's algorithm. +

    BigInteger LeastCommonMultiple(BigInteger a, BigInteger b)

    +
    Returns the least common multiple ( lcm ) of two big integers.
    Parameters
    -
    IList<long> integers
    -

    List of Integers.

    +
    BigInteger a
    +

    First Integer: a.

    +
    BigInteger b
    +

    Second Integer: b.

    Return
    -
    long
    -

    Least common multiple lcm (list of integers)

    +
    BigInteger
    +

    Least common multiple lcm (a,b)

    -

    long LeastCommonMultiple(Int64[] integers)

    -
    Returns the least common multiple ( lcm ) of a set of integers using Euclid's algorithm. +

    BigInteger LeastCommonMultiple(BigInteger[] integers)

    +
    Returns the least common multiple ( lcm ) of a set of big integers.
    Parameters
    -
    Int64[] integers
    +
    BigInteger[] integers

    List of Integers.

    Return
    -
    long
    +
    BigInteger

    Least common multiple lcm (list of integers)

    -

    BigInteger LeastCommonMultiple(BigInteger a, BigInteger b)

    -
    Returns the least common multiple ( lcm ) of two big integers. +

    long LeastCommonMultiple(long a, long b)

    +
    Returns the least common multiple ( lcm ) of two integers using Euclid's algorithm.
    Parameters
    -
    BigInteger a
    +
    long a

    First Integer: a.

    -
    BigInteger b
    +
    long b

    Second Integer: b.

    Return
    -
    BigInteger
    +
    long

    Least common multiple lcm (a,b)

    -

    BigInteger LeastCommonMultiple(BigInteger[] integers)

    -
    Returns the least common multiple ( lcm ) of a set of big integers. +

    long LeastCommonMultiple(IList<long> integers)

    +
    Returns the least common multiple ( lcm ) of a set of integers using Euclid's algorithm.
    Parameters
    -
    BigInteger[] integers
    +
    IList<long> integers

    List of Integers.

    Return
    -
    BigInteger
    +
    long

    Least common multiple lcm (list of integers)

    -

    long LeastCommonMultiple(long a, long b)

    -
    Returns the least common multiple ( lcm ) of two integers using Euclid's algorithm. +

    long LeastCommonMultiple(Int64[] integers)

    +
    Returns the least common multiple ( lcm ) of a set of integers using Euclid's algorithm.
    Parameters
    -
    long a
    -

    First Integer: a.

    -
    long b
    -

    Second Integer: b.

    +
    Int64[] integers
    +

    List of Integers.

    Return
    long
    -

    Least common multiple lcm (a,b)

    +

    Least common multiple lcm (list of integers)

    @@ -723,7 +726,7 @@ algorithm.
    -

    double Modulus(double dividend, double divisor)

    +

    BigInteger Modulus(BigInteger dividend, BigInteger divisor)

    Canonical Modulus. The result has the sign of the divisor. @@ -732,7 +735,7 @@ algorithm.
    -

    BigInteger Modulus(BigInteger dividend, BigInteger divisor)

    +

    long Modulus(long dividend, long divisor)

    Canonical Modulus. The result has the sign of the divisor. @@ -741,7 +744,7 @@ algorithm.
    -

    long Modulus(long dividend, long divisor)

    +

    int Modulus(int dividend, int divisor)

    Canonical Modulus. The result has the sign of the divisor. @@ -750,7 +753,7 @@ algorithm.
    -

    int Modulus(int dividend, int divisor)

    +

    float Modulus(float dividend, float divisor)

    Canonical Modulus. The result has the sign of the divisor. @@ -759,7 +762,7 @@ algorithm.
    -

    float Modulus(float dividend, float divisor)

    +

    double Modulus(double dividend, double divisor)

    Canonical Modulus. The result has the sign of the divisor. @@ -768,40 +771,40 @@ algorithm.
    -

    int PowerOfTwo(this int exponent)

    -
    Raises 2 to the provided integer exponent (0 <= exponent < 31). +

    long PowerOfTwo(this long exponent)

    +
    Raises 2 to the provided integer exponent (0 <= exponent < 63).
    Parameters
    -
    int exponent
    +
    long exponent

    The exponent to raise 2 up to.

    Return
    -
    int
    +
    long

    2 ^ exponent.

    -

    long PowerOfTwo(this long exponent)

    -
    Raises 2 to the provided integer exponent (0 <= exponent < 63). +

    int PowerOfTwo(this int exponent)

    +
    Raises 2 to the provided integer exponent (0 <= exponent < 31).
    Parameters
    -
    long exponent
    +
    int exponent

    The exponent to raise 2 up to.

    Return
    -
    long
    +
    int

    2 ^ exponent.

    @@ -855,7 +858,7 @@ algorithm. diff --git a/api/MathNet.Numerics/Evaluate.htm b/api/MathNet.Numerics/Evaluate.htm index 6815eb33..39d892c7 100644 --- a/api/MathNet.Numerics/Evaluate.htm +++ b/api/MathNet.Numerics/Evaluate.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -319,7 +322,7 @@ Example: coefficients [3,-1,2] represent y=2x^2-x+3. diff --git a/api/MathNet.Numerics/ExcelFunctions.htm b/api/MathNet.Numerics/ExcelFunctions.htm index 15ea74cb..fc645de0 100644 --- a/api/MathNet.Numerics/ExcelFunctions.htm +++ b/api/MathNet.Numerics/ExcelFunctions.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -403,7 +406,7 @@ porting over solutions previously implemented in Excel. diff --git a/api/MathNet.Numerics/FindMinimum.htm b/api/MathNet.Numerics/FindMinimum.htm index cd62a8de..3206577e 100644 --- a/api/MathNet.Numerics/FindMinimum.htm +++ b/api/MathNet.Numerics/FindMinimum.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -383,7 +386,7 @@ For more options and diagnostics consider to use -

    Based on v4.8.1.0 of MathNet.Numerics (Math.NET Numerics)

    +

    Based on v4.9.0.0 of MathNet.Numerics (Math.NET Numerics)

    Generated by docu

    • diff --git a/api/MathNet.Numerics/FindRoots.htm b/api/MathNet.Numerics/FindRoots.htm index c5d0613c..e213543a 100644 --- a/api/MathNet.Numerics/FindRoots.htm +++ b/api/MathNet.Numerics/FindRoots.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -412,7 +415,7 @@ Note the special coefficient order ascending by exponent (consistent with polyno diff --git a/api/MathNet.Numerics/Fit.htm b/api/MathNet.Numerics/Fit.htm index 07541e50..6dddd9bb 100644 --- a/api/MathNet.Numerics/Fit.htm +++ b/api/MathNet.Numerics/Fit.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -282,9 +285,9 @@

    Public Static Functions

    -

    Tuple<double, double, double> Curve(Double[] x, Double[] y, Func<double, double, double, double, double> f, double initialGuess0, double initialGuess1, double initialGuess2, double tolerance, int maxIterations)

    -
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p0, p1, p2, x), -returning its best fitting parameter p0, p1 and p2. +

    Tuple<double, double> Curve(Double[] x, Double[] y, Func<double, double, double, double> f, double initialGuess0, double initialGuess1, double tolerance, int maxIterations)

    +
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p0, p1, x), +returning its best fitting parameter p0 and p1. @@ -292,9 +295,9 @@ returning its best fitting parameter p0, p1 and p2.
    -

    Tuple<double, double> Curve(Double[] x, Double[] y, Func<double, double, double, double> f, double initialGuess0, double initialGuess1, double tolerance, int maxIterations)

    -
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p0, p1, x), -returning its best fitting parameter p0 and p1. +

    Tuple<double, double, double> Curve(Double[] x, Double[] y, Func<double, double, double, double, double> f, double initialGuess0, double initialGuess1, double initialGuess2, double tolerance, int maxIterations)

    +
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p0, p1, p2, x), +returning its best fitting parameter p0, p1 and p2. @@ -312,8 +315,8 @@ returning its best fitting parameter p.
    -

    Func<double, double> CurveFunc(Double[] x, Double[] y, Func<double, double, double, double, double> f, double initialGuess0, double initialGuess1, double initialGuess2, double tolerance, int maxIterations)

    -
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p0, p1, p2, x), +

    Func<double, double> CurveFunc(Double[] x, Double[] y, Func<double, double, double> f, double initialGuess, double tolerance, int maxIterations)

    +
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p, x), returning a function y' for the best fitting curve. @@ -332,8 +335,8 @@ returning a function y' for the best fitting curve.
    -

    Func<double, double> CurveFunc(Double[] x, Double[] y, Func<double, double, double> f, double initialGuess, double tolerance, int maxIterations)

    -
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p, x), +

    Func<double, double> CurveFunc(Double[] x, Double[] y, Func<double, double, double, double, double> f, double initialGuess0, double initialGuess1, double initialGuess2, double tolerance, int maxIterations)

    +
    Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p0, p1, p2, x), returning a function y' for the best fitting curve. @@ -409,7 +412,7 @@ where a is the intercept and b the slope.
    -

    Double[] LinearGeneric<T>(T[] x, Double[] y, Func`2[] functions)

    +

    Double[] LinearGeneric<T>(T[] x, Double[] y, DirectRegressionMethod method, Func`2[] functions)

    @@ -418,7 +421,7 @@ where a is the intercept and b the slope.
    -

    Double[] LinearGeneric<T>(T[] x, Double[] y, DirectRegressionMethod method, Func`2[] functions)

    +

    Double[] LinearGeneric<T>(T[] x, Double[] y, Func`2[] functions)

    @@ -614,7 +617,7 @@ returning a function y' for the best fitting line. diff --git a/api/MathNet.Numerics/Generate.htm b/api/MathNet.Numerics/Generate.htm index c256e803..bac01f5b 100644 --- a/api/MathNet.Numerics/Generate.htm +++ b/api/MathNet.Numerics/Generate.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -360,9 +363,10 @@
    • -

    Double[] LinearRange(int start, int stop)

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

    Double[] LinearRange(int start, int step, int stop)

    +
    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 (::). @@ -370,8 +374,8 @@ Equivalent to MATLAB colon operator (:).
    -

    Double[] LinearRange(int start, int step, int stop)

    -
    Generate a linearly spaced sample vector within the inclusive interval (start, stop) and the provided step. +

    Double[] LinearRange(double start, double step, double stop)

    +
    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 (::). @@ -381,10 +385,9 @@ Equivalent to MATLAB double colon operator (::).
    -

    Double[] LinearRange(double start, double step, double stop)

    -
    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 (::). +

    Double[] LinearRange(int start, int stop)

    +
    Generate a linearly spaced sample vector within the inclusive interval (start, stop) and step 1. +Equivalent to MATLAB colon operator (:). @@ -745,8 +748,8 @@ Equivalent to MATLAB logspace but with the length as first instead of last argum
    -

    IEnumerable<float> RandomSingle(IContinuousDistribution distribution)

    -
    Create an infinite random sample sequence. +

    Single[] RandomSingle(int length, IContinuousDistribution distribution)

    +
    Create random samples. @@ -754,8 +757,8 @@ Equivalent to MATLAB logspace but with the length as first instead of last argum
    -

    Single[] RandomSingle(int length, IContinuousDistribution distribution)

    -
    Create random samples. +

    IEnumerable<float> RandomSingle(IContinuousDistribution distribution)

    +
    Create an infinite random sample sequence. @@ -1121,7 +1124,7 @@ Faster than other methods but with reduced guarantees on randomness. diff --git a/api/MathNet.Numerics/GoodnessOfFit.htm b/api/MathNet.Numerics/GoodnessOfFit.htm index d4b01fb6..8d93e574 100644 --- a/api/MathNet.Numerics/GoodnessOfFit.htm +++ b/api/MathNet.Numerics/GoodnessOfFit.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -372,7 +375,7 @@ number of samples is reduced for performing the Standard Error calculation

    diff --git a/api/MathNet.Numerics/IPrecisionSupport`1.htm b/api/MathNet.Numerics/IPrecisionSupport`1.htm index b9749416..9b9a016c 100644 --- a/api/MathNet.Numerics/IPrecisionSupport`1.htm +++ b/api/MathNet.Numerics/IPrecisionSupport`1.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -288,7 +291,7 @@ appropriate for measuring how close together these two values are.
    • diff --git a/api/MathNet.Numerics/Integrate.htm b/api/MathNet.Numerics/Integrate.htm index db9e5df3..f803c3da 100644 --- a/api/MathNet.Numerics/Integrate.htm +++ b/api/MathNet.Numerics/Integrate.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -237,6 +240,10 @@

    Static Functions

      +
    • DoubleExponential
      • +
    • GaussKronrod
      • +
    • GaussKronrod
      • +
    • GaussLegendre
    • OnClosedInterval
    • OnClosedInterval
    • OnRectangle
      • @@ -251,6 +258,97 @@

      Public Static Functions

      +
      +

      double DoubleExponential(Func<double, double> f, double intervalBegin, double intervalEnd, double targetAbsoluteError)

      +
      Approximation of the definite integral of an analytic smooth function by double-exponential quadrature. When either or both limits are infinite, the integrand is assumed rapidly decayed to zero as x -> infinity. + + +
      +
      Parameters
      + +
      Func<double, double> f
      +

      The analytic smooth function to integrate.

      +
      double intervalBegin
      +

      Where the interval starts.

      +
      double intervalEnd
      +

      Where the interval stops.

      +
      double targetAbsoluteError
      +

      The expected relative accuracy of the approximation.

      +
      + +
      +
      Return
      +
      double
      +

      Approximation of the finite integral in the given interval.

      +
      + +
      +
      +
      +

      double GaussKronrod(Func<double, double> f, double intervalBegin, double intervalEnd, double targetRelativeError, int maximumDepth, int order)

      +
      Approximation of the definite integral of an analytic smooth function by Gauss-Kronrod quadrature. When either or both limits are infinite, the integrand is assumed rapidly decayed to zero as x -> infinity. + + +
      +
      Parameters
      + +
      Func<double, double> f
      +

      The analytic smooth function to integrate.

      +
      double intervalBegin
      +

      Where the interval starts.

      +
      double intervalEnd
      +

      Where the interval stops.

      +
      double targetRelativeError
      +

      The expected relative accuracy of the approximation.

      +
      int maximumDepth
      +

      The maximum number of interval splittings permitted before stopping.

      +
      int order
      +

      The number of Gauss-Kronrod points. Pre-computed for 15, 31, 41, 51 and 61 points.

      +
      + +
      +
      Return
      +
      double
      +

      Approximation of the finite integral in the given interval.

      +
      + +
      +
      +
      +

      double GaussKronrod(Func<double, double> f, double intervalBegin, double intervalEnd, Double& error, Double& L1Norm, double targetRelativeError, int maximumDepth, int order)

      +
      + + + + +
      +
      +
      +

      double GaussLegendre(Func<double, double> f, double intervalBegin, double intervalEnd, int order)

      +
      Approximation of the definite integral of an analytic smooth function by Gauss-Legendre quadrature. When either or both limits are infinite, the integrand is assumed rapidly decayed to zero as x -> infinity. + + +
      +
      Parameters
      + +
      Func<double, double> f
      +

      The analytic smooth function to integrate.

      +
      double intervalBegin
      +

      Where the interval starts.

      +
      double intervalEnd
      +

      Where the interval stops.

      +
      int order
      +

      Defines an Nth order Gauss-Legendre rule. The order also defines the number of abscissas and weights for the rule. Precomputed Gauss-Legendre abscissas/weights for orders 2-20, 32, 64, 96, 100, 128, 256, 512, 1024 are used, otherwise they're calculated on the fly.

      +
      + +
      +
      Return
      +
      double
      +

      Approximation of the finite integral in the given interval.

      +
      + +
      +

      double OnClosedInterval(Func<double, double> f, double intervalBegin, double intervalEnd, double targetAbsoluteError)

      Approximation of the definite integral of an analytic smooth function on a closed interval. @@ -362,7 +460,7 @@ diff --git a/api/MathNet.Numerics/Interpolate.htm b/api/MathNet.Numerics/Interpolate.htm index e0ce7008..c57f5423 100644 --- a/api/MathNet.Numerics/Interpolate.htm +++ b/api/MathNet.Numerics/Interpolate.htm @@ -138,6 +138,9 @@
    • Constants +
      • +
    • + ContourIntegrate
    • Control @@ -576,7 +579,7 @@ on arbitrary points.

      diff --git a/api/MathNet.Numerics/InvalidParameterException.htm b/api/MathNet.Numerics/InvalidParameterException.htm index 2c0b8684..aba6926e 100644 --- a/api/MathNet.Numerics/InvalidParameterException.htm +++ b/api/MathNet.Numerics/InvalidParameterException.htm @@ -138,6 +138,9 @@
    • Constants +
      • +
    • + ContourIntegrate
    • Control @@ -407,7 +410,7 @@
      • diff --git a/api/MathNet.Numerics/MemoryAllocationException.htm b/api/MathNet.Numerics/MemoryAllocationException.htm index 6926adda..e55c3c05 100644 --- a/api/MathNet.Numerics/MemoryAllocationException.htm +++ b/api/MathNet.Numerics/MemoryAllocationException.htm @@ -138,6 +138,9 @@
    • Constants +
      • +
    • + ContourIntegrate
    • Control @@ -397,7 +400,7 @@
    • diff --git a/api/MathNet.Numerics/NativeInterfaceException.htm b/api/MathNet.Numerics/NativeInterfaceException.htm index 96830532..8b7ab933 100644 --- a/api/MathNet.Numerics/NativeInterfaceException.htm +++ b/api/MathNet.Numerics/NativeInterfaceException.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -372,7 +375,7 @@
    • diff --git a/api/MathNet.Numerics/NonConvergenceException.htm b/api/MathNet.Numerics/NonConvergenceException.htm index 79129f8e..577d12a7 100644 --- a/api/MathNet.Numerics/NonConvergenceException.htm +++ b/api/MathNet.Numerics/NonConvergenceException.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -407,7 +410,7 @@
    • diff --git a/api/MathNet.Numerics/NumericalBreakdownException.htm b/api/MathNet.Numerics/NumericalBreakdownException.htm index b1499135..dea07f2b 100644 --- a/api/MathNet.Numerics/NumericalBreakdownException.htm +++ b/api/MathNet.Numerics/NumericalBreakdownException.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -407,7 +410,7 @@
    • diff --git a/api/MathNet.Numerics/Permutation.htm b/api/MathNet.Numerics/Permutation.htm index 00997af2..f462dbb4 100644 --- a/api/MathNet.Numerics/Permutation.htm +++ b/api/MathNet.Numerics/Permutation.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -395,7 +398,7 @@ encoded using the array [22244].
    • diff --git a/api/MathNet.Numerics/Polynomial.htm b/api/MathNet.Numerics/Polynomial.htm index efa241f6..40c82d59 100644 --- a/api/MathNet.Numerics/Polynomial.htm +++ b/api/MathNet.Numerics/Polynomial.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -927,7 +930,7 @@ The null-polynomial returns degree -1 because the correct degree, negative infin
    • diff --git a/api/MathNet.Numerics/Precision.htm b/api/MathNet.Numerics/Precision.htm index 3427d192..db41f06f 100644 --- a/api/MathNet.Numerics/Precision.htm +++ b/api/MathNet.Numerics/Precision.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -294,6 +297,7 @@
  • EpsilonOf
  • EpsilonOf
  • Increment
    • +
  • IsFinite
  • IsLarger
  • IsLarger
  • IsLarger
    • @@ -352,27 +356,29 @@

    Public Static Functions

    -

    bool AlmostEqual(this double a, double b, double maximumAbsoluteError)

    -
    Compares two doubles and determines if they are equal within -the specified maximum error. +

    bool AlmostEqual(this double a, double b)

    +
    Checks whether two real numbers are almost equal.
    Parameters
    double a
    -

    The first value.

    +

    The first number

    double b
    -

    The second value.

    -
    double maximumAbsoluteError
    -

    The accuracy required for being almost equal.

    +

    The second number

    +
    +
    Return
    +
    bool
    +

    true if the two values differ by no more than 10 * 2^(-52); false otherwise.

    +
    -

    bool AlmostEqual(this float a, float b, int decimalPlaces)

    +

    bool AlmostEqual(this Complex a, Complex b, int decimalPlaces)

    Compares two doubles and determines if they are equal to within the specified number of decimal places or not, using the number of decimal places as an absolute measure. @@ -380,9 +386,9 @@ number of decimal places as an absolute measure.
    Parameters
    -
    float a
    +
    Complex a

    The first value.

    -
    float b
    +
    Complex b

    The second value.

    int decimalPlaces

    The number of decimal places.

    @@ -392,7 +398,7 @@ number of decimal places as an absolute measure.
    -

    bool AlmostEqual(this double a, double b, int decimalPlaces)

    +

    bool AlmostEqual(this Complex32 a, Complex32 b, int decimalPlaces)

    Compares two doubles and determines if they are equal to within the specified number of decimal places or not, using the number of decimal places as an absolute measure. @@ -400,9 +406,9 @@ number of decimal places as an absolute measure.
    Parameters
    -
    double a
    +
    Complex32 a

    The first value.

    -
    double b
    +
    Complex32 b

    The second value.

    int decimalPlaces

    The number of decimal places.

    @@ -478,29 +484,27 @@ number of decimal places as an absolute measure.
    -

    bool AlmostEqual(this double a, double b)

    -
    Checks whether two real numbers are almost equal. +

    bool AlmostEqual(this float a, float b, int decimalPlaces)

    +
    Compares two doubles and determines if they are equal to within the specified number of decimal places or not, using the +number of decimal places as an absolute measure.
    Parameters
    -
    double a
    -

    The first number

    -
    double b
    -

    The second number

    +
    float a
    +

    The first value.

    +
    float b
    +

    The second value.

    +
    int decimalPlaces
    +

    The number of decimal places.

    -
    -
    Return
    -
    bool
    -

    true if the two values differ by no more than 10 * 2^(-52); false otherwise.

    -
    -

    bool AlmostEqual(this Complex32 a, Complex32 b, int decimalPlaces)

    +

    bool AlmostEqual(this double a, double b, int decimalPlaces)

    Compares two doubles and determines if they are equal to within the specified number of decimal places or not, using the number of decimal places as an absolute measure. @@ -508,9 +512,9 @@ number of decimal places as an absolute measure.
    Parameters
    -
    Complex32 a
    +
    double a

    The first value.

    -
    Complex32 b
    +
    double b

    The second value.

    int decimalPlaces

    The number of decimal places.

    @@ -520,9 +524,9 @@ number of decimal places as an absolute measure.
    -

    bool AlmostEqual(this Complex a, Complex b, int decimalPlaces)

    -
    Compares two doubles and determines if they are equal to within the specified number of decimal places or not, using the -number of decimal places as an absolute measure. +

    bool AlmostEqual(this Complex a, Complex b, double maximumAbsoluteError)

    +
    Compares two complex and determines if they are equal within +the specified maximum error.
    @@ -532,15 +536,15 @@ number of decimal places as an absolute measure.

    The first value.

    Complex b

    The second value.

    -
    int decimalPlaces
    -

    The number of decimal places.

    +
    double maximumAbsoluteError
    +

    The accuracy required for being almost equal.

    -

    bool AlmostEqual(this Complex a, Complex b, double maximumAbsoluteError)

    +

    bool AlmostEqual(this float a, float b, double maximumAbsoluteError)

    Compares two complex and determines if they are equal within the specified maximum error. @@ -548,9 +552,9 @@ the specified maximum error.
    Parameters
    -
    Complex a
    +
    float a

    The first value.

    -
    Complex b
    +
    float b

    The second value.

    double maximumAbsoluteError

    The accuracy required for being almost equal.

    @@ -560,17 +564,17 @@ the specified maximum error.
    -

    bool AlmostEqual(this float a, float b, double maximumAbsoluteError)

    -
    Compares two complex and determines if they are equal within +

    bool AlmostEqual(this double a, double b, double maximumAbsoluteError)

    +
    Compares two doubles and determines if they are equal within the specified maximum error.
    Parameters
    -
    float a
    +
    double a

    The first value.

    -
    float b
    +
    double b

    The second value.

    double maximumAbsoluteError

    The accuracy required for being almost equal.

    @@ -597,6 +601,25 @@ the specified maximum error.
    +
    +
    +
    +

    bool AlmostEqual<T>(this Vector<T> a, Vector<T> b, double maximumAbsoluteError)

    +
    Compares two vectors and determines if they are equal within the specified maximum error. + + +
    +
    Parameters
    + +
    Vector<T> a
    +

    The first value.

    +
    Vector<T> b
    +

    The second value.

    +
    double maximumAbsoluteError
    +

    The accuracy required for being almost equal.

    +
    + +
    @@ -656,25 +679,6 @@ of decimal places or not, using the number of decimal places as an absolute meas
    -
    -
    -
    -

    bool AlmostEqual<T>(this Vector<T> a, Vector<T> b, double maximumAbsoluteError)

    -
    Compares two vectors and determines if they are equal within the specified maximum error. - - -
    -
    Parameters
    - -
    Vector<T> a
    -

    The first value.

    -
    Vector<T> b
    -

    The second value.

    -
    double maximumAbsoluteError
    -

    The accuracy required for being almost equal.

    -
    - -
    @@ -780,9 +784,13 @@ within the specified maximum absolute error.
    -

    bool AlmostEqualNormRelative(this double a, double b, double diff, double maximumError)

    -
    Compares two doubles and determines if they are equal -within the specified maximum error. +

    bool AlmostEqualNormRelative(this double a, double b, double diff, int decimalPlaces)

    +
    Compares two doubles and determines if they are equal to within the specified number of decimal places or not. If the numbers +are very close to zero an absolute difference is compared, otherwise the relative difference is compared.
    +

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by +two so that we have half the range on each side of the numbers, e.g. if decimalPlaces == 2, then 0.01 will equal between +0.005 and 0.015, but not 0.02 and not 0.00

    +
    @@ -794,26 +802,17 @@ within the specified maximum error.

    The norm of the second value (can be negative).

    double diff

    The norm of the difference of the two values (can be negative).

    -
    double maximumError
    -

    The accuracy required for being almost equal.

    +
    int decimalPlaces
    +

    The number of decimal places.

    -
    -
    Return
    -
    bool
    -

    True if both doubles are almost equal up to the specified maximum error, false otherwise.

    -
    -

    bool AlmostEqualNormRelative(this double a, double b, double diff, int decimalPlaces)

    -
    Compares two doubles and determines if they are equal to within the specified number of decimal places or not. If the numbers -are very close to zero an absolute difference is compared, otherwise the relative difference is compared.
    -

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by -two so that we have half the range on each side of the numbers, e.g. if decimalPlaces == 2, then 0.01 will equal between -0.005 and 0.015, but not 0.02 and not 0.00

    -
    +

    bool AlmostEqualNormRelative(this double a, double b, double diff, double maximumError)

    +
    Compares two doubles and determines if they are equal +within the specified maximum error.
    @@ -825,10 +824,15 @@ two so that we have half the range on each side of the numbers, e.g. if de

    The norm of the second value (can be negative).

    double diff

    The norm of the difference of the two values (can be negative).

    -
    int decimalPlaces
    -

    The number of decimal places.

    +
    double maximumError
    +

    The accuracy required for being almost equal.

    +
    +
    Return
    +
    bool
    +

    True if both doubles are almost equal up to the specified maximum error, false otherwise.

    +
    @@ -879,6 +883,32 @@ within the specified maximum error.

    True if both doubles are almost equal up to the specified maximum error, false otherwise.

    +
    +
    +
    +

    bool AlmostEqualNumbersBetween(this double a, double b, long maxNumbersBetween)

    +
    Compares two doubles and determines if they are equal to within the tolerance or not. Equality comparison is based on the binary representation.
    +

    Determines the 'number' of floating point numbers between two values (i.e. the number of discrete steps +between the two numbers) and then checks if that is within the specified tolerance. So if a tolerance +of 1 is passed then the result will be true only if the two numbers have the same binary representation +OR if they are two adjacent numbers that only differ by one step.

    The comparison method used is explained in http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm. The article +at http://www.extremeoptimization.com/resources/Articles/FPDotNetConceptsAndFormats.aspx explains how to transform the C code to +.NET enabled code without using pointers and unsafe code.

    +
    + + +
    +
    Parameters
    + +
    double a
    +

    The first value.

    +
    double b
    +

    The second value.

    +
    long maxNumbersBetween
    +

    The maximum number of floating point values between the two values. Must be 1 or larger.

    +
    + +
    @@ -900,29 +930,25 @@ within the specified maximum error.
    -
    -

    bool AlmostEqualNumbersBetween(this double a, double b, long maxNumbersBetween)

    -
    Compares two doubles and determines if they are equal to within the tolerance or not. Equality comparison is based on the binary representation.
    -

    Determines the 'number' of floating point numbers between two values (i.e. the number of discrete steps -between the two numbers) and then checks if that is within the specified tolerance. So if a tolerance -of 1 is passed then the result will be true only if the two numbers have the same binary representation -OR if they are two adjacent numbers that only differ by one step.

    The comparison method used is explained in http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm. The article -at http://www.extremeoptimization.com/resources/Articles/FPDotNetConceptsAndFormats.aspx explains how to transform the C code to -.NET enabled code without using pointers and unsafe code.

    -
    +
    +

    bool AlmostEqualRelative(this Complex a, Complex b)

    +
    Checks whether two Complex numbers are almost equal.
    Parameters
    -
    double a
    -

    The first value.

    -
    double b
    -

    The second value.

    -
    long maxNumbersBetween
    -

    The maximum number of floating point values between the two values. Must be 1 or larger.

    +
    Complex a
    +

    The first number

    +
    Complex b
    +

    The second number

    +
    +
    Return
    +
    bool
    +

    true if the two values differ by no more than 10 * 2^(-52); false otherwise.

    +
    @@ -1007,7 +1033,29 @@ the specified maximum error.
    -

    bool AlmostEqualRelative(this double a, double b, int decimalPlaces)

    +

    bool AlmostEqualRelative(this Complex32 a, Complex32 b)

    +
    Checks whether two Complex numbers are almost equal. + + +
    +
    Parameters
    + +
    Complex32 a
    +

    The first number

    +
    Complex32 b
    +

    The second number

    +
    + +
    +
    Return
    +
    bool
    +

    true if the two values differ by no more than 10 * 2^(-52); false otherwise.

    +
    + +
    +
    +
    +

    bool AlmostEqualRelative(this float a, float b, int decimalPlaces)

    Compares two doubles and determines if they are equal to within the specified number of decimal places or not. If the numbers are very close to zero an absolute difference is compared, otherwise the relative difference is compared. @@ -1015,9 +1063,9 @@ are very close to zero an absolute difference is compared, otherwise the relativ
    Parameters
    -
    double a
    +
    float a

    The first value.

    -
    double b
    +
    float b

    The second value.

    int decimalPlaces

    The number of decimal places.

    @@ -1027,7 +1075,7 @@ are very close to zero an absolute difference is compared, otherwise the relativ
    -

    bool AlmostEqualRelative(this float a, float b, int decimalPlaces)

    +

    bool AlmostEqualRelative(this double a, double b, int decimalPlaces)

    Compares two doubles and determines if they are equal to within the specified number of decimal places or not. If the numbers are very close to zero an absolute difference is compared, otherwise the relative difference is compared. @@ -1035,9 +1083,9 @@ are very close to zero an absolute difference is compared, otherwise the relativ
    Parameters
    -
    float a
    +
    double a

    The first value.

    -
    float b
    +
    double b

    The second value.

    int decimalPlaces

    The number of decimal places.

    @@ -1130,47 +1178,23 @@ are very close to zero an absolute difference is compared, otherwise the relativ
    -
    -

    bool AlmostEqualRelative(this Complex a, Complex b)

    -
    Checks whether two Complex numbers are almost equal. - - -
    -
    Parameters
    - -
    Complex a
    -

    The first number

    -
    Complex b
    -

    The second number

    -
    - -
    -
    Return
    -
    bool
    -

    true if the two values differ by no more than 10 * 2^(-52); false otherwise.

    -
    - -
    -
    -
    -

    bool AlmostEqualRelative(this Complex32 a, Complex32 b)

    -
    Checks whether two Complex numbers are almost equal. +
    +

    bool AlmostEqualRelative<T>(this Matrix<T> a, Matrix<T> b, int decimalPlaces)

    +
    Compares two matrices and determines if they are equal to within the specified number of decimal places or not. +If the numbers are very close to zero an absolute difference is compared, otherwise the relative difference is compared.
    Parameters
    -
    Complex32 a
    -

    The first number

    -
    Complex32 b
    -

    The second number

    +
    Matrix<T> a
    +

    The first value.

    +
    Matrix<T> b
    +

    The second value.

    +
    int decimalPlaces
    +

    The number of decimal places.

    -
    -
    Return
    -
    bool
    -

    true if the two values differ by no more than 10 * 2^(-52); false otherwise.

    -
    @@ -1230,31 +1254,11 @@ If the numbers are very close to zero an absolute difference is compared, otherw
    -
    -
    -
    -

    bool AlmostEqualRelative<T>(this Matrix<T> a, Matrix<T> b, int decimalPlaces)

    -
    Compares two matrices and determines if they are equal to within the specified number of decimal places or not. -If the numbers are very close to zero an absolute difference is compared, otherwise the relative difference is compared. - - -
    -
    Parameters
    - -
    Matrix<T> a
    -

    The first value.

    -
    Matrix<T> b
    -

    The second value.

    -
    int decimalPlaces
    -

    The number of decimal places.

    -
    - -
    -

    double CoerceZero(this double a, double maximumAbsoluteError)

    -
    Forces small numbers near zero to zero, according to the specified absolute accuracy. +

    double CoerceZero(this double a)

    +
    Forces small numbers near zero to zero.
    @@ -1262,21 +1266,19 @@ If the numbers are very close to zero an absolute difference is compared, otherw
    double a

    The real number to coerce to zero, if it is almost zero.

    -
    double maximumAbsoluteError
    -

    The absolute threshold for a to consider it as zero.

    Return
    double
    -

    Zero if | a | is smaller than maximumAbsoluteError , a otherwise.

    +

    Zero if | a | is smaller than 2^(-53) = 1.11e-16, a otherwise.

    -

    double CoerceZero(this double a)

    -
    Forces small numbers near zero to zero. +

    double CoerceZero(this double a, int maxNumbersBetween)

    +
    Forces small numbers near zero to zero, according to the specified absolute accuracy.
    @@ -1284,18 +1286,20 @@ If the numbers are very close to zero an absolute difference is compared, otherw
    double a

    The real number to coerce to zero, if it is almost zero.

    +
    int maxNumbersBetween
    +

    The maximum count of numbers between the zero and the number a.

    Return
    double
    -

    Zero if | a | is smaller than 2^(-53) = 1.11e-16, a otherwise.

    +

    Zero if | a | is fewer than maxNumbersBetween numbers from zero, a otherwise.

    -

    double CoerceZero(this double a, int maxNumbersBetween)

    +

    double CoerceZero(this double a, double maximumAbsoluteError)

    Forces small numbers near zero to zero, according to the specified absolute accuracy. @@ -1304,14 +1308,14 @@ If the numbers are very close to zero an absolute difference is compared, otherw
    double a

    The real number to coerce to zero, if it is almost zero.

    -
    int maxNumbersBetween
    -

    The maximum count of numbers between the zero and the number a.

    +
    double maximumAbsoluteError
    +

    The absolute threshold for a to consider it as zero.

    Return
    double
    -

    Zero if | a | is fewer than maxNumbersBetween numbers from zero, a otherwise.

    +

    Zero if | a | is smaller than maximumAbsoluteError , a otherwise.

    @@ -1530,6 +1534,45 @@ Increment(double.MaxValue) will return positive infinity.

    The next larger floating point value.

    +
    +
    +
    +

    bool IsFinite(this double value)

    +
    Checks if a given double values is finite, i.e. neither NaN nor inifnity + + +
    +
    Parameters
    + +
    double value
    +

    The value to be checked fo finitenes.

    +
    + + +
    +
    +
    +

    bool IsLarger(this float a, float b, double maximumAbsoluteError)

    +
    Compares two doubles and determines if the first value is larger than the second value to within the specified number of decimal places or not. + + +
    +
    Parameters
    + +
    float a
    +

    The first value.

    +
    float b
    +

    The second value.

    +
    double maximumAbsoluteError
    +

    The absolute accuracy required for being almost equal.

    +
    + +
    +
    Return
    +
    bool
    +

    true if the first value is larger than the second value; otherwise false.

    +
    +
    @@ -1612,9 +1655,9 @@ two so that we have half the range on each side of the numbers, e.g. if de
    -
    -

    bool IsLarger(this float a, float b, double maximumAbsoluteError)

    -
    Compares two doubles and determines if the first value is larger than the second value to within the specified number of decimal places or not. +
    +

    bool IsLargerNumbersBetween(this float a, float b, long maxNumbersBetween)

    +
    Compares two doubles and determines if the first value is larger than the second value to within the tolerance or not. Equality comparison is based on the binary representation.
    @@ -1624,8 +1667,8 @@ two so that we have half the range on each side of the numbers, e.g. if de

    The first value.

    float b

    The second value.

    -
    double maximumAbsoluteError
    -

    The absolute accuracy required for being almost equal.

    +
    long maxNumbersBetween
    +

    The maximum number of floating point values for which the two values are considered equal. Must be 1 or larger.

    @@ -1660,20 +1703,24 @@ two so that we have half the range on each side of the numbers, e.g. if de
    -
    -

    bool IsLargerNumbersBetween(this float a, float b, long maxNumbersBetween)

    -
    Compares two doubles and determines if the first value is larger than the second value to within the tolerance or not. Equality comparison is based on the binary representation. +
    +

    bool IsLargerRelative(this double a, double b, int decimalPlaces)

    +
    Compares two doubles and determines if the first value is larger than the second value to within the specified number of decimal places or not.
    +

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by +two so that we have half the range on each side of the numbers, e.g. if decimalPlaces == 2, then 0.01 will equal between +0.005 and 0.015, but not 0.02 and not 0.00

    +
    Parameters
    -
    float a
    +
    double a

    The first value.

    -
    float b
    +
    double b

    The second value.

    -
    long maxNumbersBetween
    -

    The maximum number of floating point values for which the two values are considered equal. Must be 1 or larger.

    +
    int decimalPlaces
    +

    The number of decimal places.

    @@ -1685,7 +1732,7 @@ two so that we have half the range on each side of the numbers, e.g. if de
    -

    bool IsLargerRelative(this double a, double b, int decimalPlaces)

    +

    bool IsLargerRelative(this float a, float b, int decimalPlaces)

    Compares two doubles and determines if the first value is larger than the second value to within the specified number of decimal places or not.

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by two so that we have half the range on each side of the numbers, e.g. if decimalPlaces == 2, then 0.01 will equal between @@ -1696,9 +1743,9 @@ two so that we have half the range on each side of the numbers, e.g. if de

    Parameters
    -
    double a
    +
    float a

    The first value.

    -
    double b
    +
    float b

    The second value.

    int decimalPlaces

    The number of decimal places.

    @@ -1760,11 +1807,11 @@ two so that we have half the range on each side of the numbers, e.g. if de
    -
    -

    bool IsLargerRelative(this float a, float b, int decimalPlaces)

    -
    Compares two doubles and determines if the first value is larger than the second value to within the specified number of decimal places or not.
    +
    +

    bool IsSmaller(this float a, float b, int decimalPlaces)

    +
    Compares two doubles and determines if the first value is smaller than the second value to within the specified number of decimal places or not.

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by -two so that we have half the range on each side of the numbers, e.g. if decimalPlaces == 2, then 0.01 will equal between +two so that we have half the range on each side of th decimalPlaces g. if decimalPlaces == 2, then 0.01 will equal between 0.005 and 0.015, but not 0.02 and not 0.00

    @@ -1783,14 +1830,18 @@ two so that we have half the range on each side of the numbers, e.g. if de
    Return
    bool
    -

    true if the first value is larger than the second value; otherwise false.

    +

    true if the first value is smaller than the second value; otherwise false.

    -

    bool IsSmaller(this double a, double b, double maximumAbsoluteError)

    -
    Compares two doubles and determines if the first value is smaller than the second value to within the specified number of decimal places or not. +

    bool IsSmaller(this double a, double b, int decimalPlaces)

    +
    Compares two doubles and determines if the first value is smaller than the second value to within the specified number of decimal places or not.
    +

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by +two so that we have half the range on each side of th decimalPlaces g. if decimalPlaces == 2, then 0.01 will equal between +0.005 and 0.015, but not 0.02 and not 0.00

    +
    @@ -1800,8 +1851,8 @@ two so that we have half the range on each side of the numbers, e.g. if de

    The first value.

    double b

    The second value.

    -
    double maximumAbsoluteError
    -

    The absolute accuracy required for being almost equal.

    +
    int decimalPlaces
    +

    The number of decimal places.

    @@ -1837,12 +1888,8 @@ two so that we have half the range on each side of the numbers, e.g. if de
    -

    bool IsSmaller(this double a, double b, int decimalPlaces)

    -
    Compares two doubles and determines if the first value is smaller than the second value to within the specified number of decimal places or not.
    -

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by -two so that we have half the range on each side of th decimalPlaces g. if decimalPlaces == 2, then 0.01 will equal between -0.005 and 0.015, but not 0.02 and not 0.00

    -
    +

    bool IsSmaller(this double a, double b, double maximumAbsoluteError)

    +
    Compares two doubles and determines if the first value is smaller than the second value to within the specified number of decimal places or not.
    @@ -1852,36 +1899,8 @@ two so that we have half the range on each side of th decimalPlaces g

    The first value.

    double b

    The second value.

    -
    int decimalPlaces
    -

    The number of decimal places.

    -
    - -
    -
    Return
    -
    bool
    -

    true if the first value is smaller than the second value; otherwise false.

    -
    - -
    -
    -
    -

    bool IsSmaller(this float a, float b, int decimalPlaces)

    -
    Compares two doubles and determines if the first value is smaller than the second value to within the specified number of decimal places or not.
    -

    The values are equal if the difference between the two numbers is smaller than 10^(-numberOfDecimalPlaces). We divide by -two so that we have half the range on each side of th decimalPlaces g. if decimalPlaces == 2, then 0.01 will equal between -0.005 and 0.015, but not 0.02 and not 0.00

    -
    - - -
    -
    Parameters
    - -
    float a
    -

    The first value.

    -
    float b
    -

    The second value.

    -
    int decimalPlaces
    -

    The number of decimal places.

    +
    double maximumAbsoluteError
    +

    The absolute accuracy required for being almost equal.

    @@ -1893,16 +1912,16 @@ two so that we have half the range on each side of th decimalPlaces g
    -

    bool IsSmallerNumbersBetween(this float a, float b, long maxNumbersBetween)

    +

    bool IsSmallerNumbersBetween(this double a, double b, long maxNumbersBetween)

    Compares two doubles and determines if the first value is smaller than the second value to within the tolerance or not. Equality comparison is based on the binary representation.
    Parameters
    -
    float a
    +
    double a

    The first value.

    -
    float b
    +
    double b

    The second value.

    long maxNumbersBetween

    The maximum number of floating point values for which the two values are considered equal. Must be 1 or larger.

    @@ -1917,16 +1936,16 @@ two so that we have half the range on each side of th decimalPlaces g
    -

    bool IsSmallerNumbersBetween(this double a, double b, long maxNumbersBetween)

    +

    bool IsSmallerNumbersBetween(this float a, float b, long maxNumbersBetween)

    Compares two doubles and determines if the first value is smaller than the second value to within the tolerance or not. Equality comparison is based on the binary representation.
    Parameters
    -
    double a
    +
    float a

    The first value.

    -
    double b
    +
    float b

    The second value.

    long maxNumbersBetween

    The maximum number of floating point values for which the two values are considered equal. Must be 1 or larger.

    @@ -2037,7 +2056,7 @@ two so that we have half the range on each side of th decimalPlaces g
    -

    bool ListAlmostEqual(this IList<double> a, IList<double> b, double maximumAbsoluteError)

    +

    bool ListAlmostEqual(this IList<double> a, IList<double> b, int decimalPlaces)

    Compares two lists of doubles and determines if they are equal within the specified maximum error. @@ -2049,15 +2068,15 @@ specified maximum error.

    The first value list.

    IList<double> b

    The second value list.

    -
    double maximumAbsoluteError
    -

    The accuracy required for being almost equal.

    +
    int decimalPlaces
    +

    The number of decimal places.

    -

    bool ListAlmostEqual(this IList<double> a, IList<double> b, int decimalPlaces)

    +

    bool ListAlmostEqual(this IList<double> a, IList<double> b, double maximumAbsoluteError)

    Compares two lists of doubles and determines if they are equal within the specified maximum error. @@ -2069,8 +2088,8 @@ specified maximum error.

    The first value list.

    IList<double> b

    The second value list.

    -
    int decimalPlaces
    -

    The number of decimal places.

    +
    double maximumAbsoluteError
    +

    The accuracy required for being almost equal.

    @@ -2267,7 +2286,7 @@ always smaller than the value)
    -

    float PositiveEpsilonOf(this float value)

    +

    double PositiveEpsilonOf(this double value)

    Evaluates the minimum distance to the next distinguishable number near the argument value.
    Evaluates the epsilon. See also EpsilonOf
    @@ -2276,20 +2295,20 @@ always smaller than the value)
    Parameters
    -
    float value
    +
    double value

    The value used to determine the minimum distance.

    Return
    -
    float
    -

    Relative Epsilon (positive float or NaN)

    +
    double
    +

    Relative Epsilon (positive double or NaN)

    -

    double PositiveEpsilonOf(this double value)

    +

    float PositiveEpsilonOf(this float value)

    Evaluates the minimum distance to the next distinguishable number near the argument value.
    Evaluates the epsilon. See also EpsilonOf
    @@ -2298,14 +2317,14 @@ always smaller than the value)
    Parameters
    -
    double value
    +
    float value

    The value used to determine the minimum distance.

    Return
    -
    double
    -

    Relative Epsilon (positive double or NaN)

    +
    float
    +

    Relative Epsilon (positive float or NaN)

    @@ -2484,7 +2503,7 @@ On a standard machine this is equivalent to `PositiveDoublePrecision`.
    diff --git a/api/MathNet.Numerics/SingularUMatrixException.htm b/api/MathNet.Numerics/SingularUMatrixException.htm index ba5b205a..d835554e 100644 --- a/api/MathNet.Numerics/SingularUMatrixException.htm +++ b/api/MathNet.Numerics/SingularUMatrixException.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -407,7 +410,7 @@
    • diff --git a/api/MathNet.Numerics/Sorting.htm b/api/MathNet.Numerics/Sorting.htm index ad8ec70b..b8900302 100644 --- a/api/MathNet.Numerics/Sorting.htm +++ b/api/MathNet.Numerics/Sorting.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -404,7 +407,7 @@ diff --git a/api/MathNet.Numerics/SpecialFunctions.htm b/api/MathNet.Numerics/SpecialFunctions.htm index f40cb124..951bf09c 100644 --- a/api/MathNet.Numerics/SpecialFunctions.htm +++ b/api/MathNet.Numerics/SpecialFunctions.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -1913,13 +1916,15 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    • -

    double KelvinBei(double x)

    -
    Returns the Kelvin function bei.

    KelvinBei(x) is given by the imaginary part of BesselJ(0, j * sqrt(j) * x) where j = sqrt(-1).

    KelvinBei(x) is equivalent to KelvinBei(0, x).

    +

    double KelvinBei(double nu, double x)

    +
    Returns the Kelvin function bei.

    KelvinBei(nu, x) is given by the imaginary part of BesselJ(nu, j * sqrt(j) * x) where j = sqrt(-1).

    Parameters
    +
    double nu
    +

    the order of the the Kelvin function.

    double x

    The value to compute the Kelvin function of.

    @@ -1933,15 +1938,13 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    -

    double KelvinBei(double nu, double x)

    -
    Returns the Kelvin function bei.

    KelvinBei(nu, x) is given by the imaginary part of BesselJ(nu, j * sqrt(j) * x) where j = sqrt(-1).

    +

    double KelvinBei(double x)

    +
    Returns the Kelvin function bei.

    KelvinBei(x) is given by the imaginary part of BesselJ(0, j * sqrt(j) * x) where j = sqrt(-1).

    KelvinBei(x) is equivalent to KelvinBei(0, x).

    Parameters
    -
    double nu
    -

    the order of the the Kelvin function.

    double x

    The value to compute the Kelvin function of.

    @@ -1955,13 +1958,15 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    -

    double KelvinBeiPrime(double x)

    +

    double KelvinBeiPrime(double nu, double x)

    Returns the derivative of the Kelvin function bei.
    Parameters
    +
    double nu
    +

    The order of the Kelvin function.

    double x

    The value to compute the derivative of the Kelvin function of.

    @@ -1969,21 +1974,19 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    Return
    double
    -

    The derivative of the Kelvin function bei.

    +

    the derivative of the Kelvin function bei.

    -

    double KelvinBeiPrime(double nu, double x)

    +

    double KelvinBeiPrime(double x)

    Returns the derivative of the Kelvin function bei.
    Parameters
    -
    double nu
    -

    The order of the Kelvin function.

    double x

    The value to compute the derivative of the Kelvin function of.

    @@ -1991,19 +1994,21 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    Return
    double
    -

    the derivative of the Kelvin function bei.

    +

    The derivative of the Kelvin function bei.

    -

    double KelvinBer(double x)

    -
    Returns the Kelvin function ber.

    KelvinBer(x) is given by the real part of BesselJ(0, j * sqrt(j) * x) where j = sqrt(-1).

    KelvinBer(x) is equivalent to KelvinBer(0, x).

    +

    double KelvinBer(double nu, double x)

    +
    Returns the Kelvin function ber.

    KelvinBer(nu, x) is given by the real part of BesselJ(nu, j * sqrt(j) * x) where j = sqrt(-1).

    Parameters
    +
    double nu
    +

    the order of the the Kelvin function.

    double x

    The value to compute the Kelvin function of.

    @@ -2017,15 +2022,13 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    -

    double KelvinBer(double nu, double x)

    -
    Returns the Kelvin function ber.

    KelvinBer(nu, x) is given by the real part of BesselJ(nu, j * sqrt(j) * x) where j = sqrt(-1).

    +

    double KelvinBer(double x)

    +
    Returns the Kelvin function ber.

    KelvinBer(x) is given by the real part of BesselJ(0, j * sqrt(j) * x) where j = sqrt(-1).

    KelvinBer(x) is equivalent to KelvinBer(0, x).

    Parameters
    -
    double nu
    -

    the order of the the Kelvin function.

    double x

    The value to compute the Kelvin function of.

    @@ -2039,13 +2042,15 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    -

    double KelvinBerPrime(double x)

    +

    double KelvinBerPrime(double nu, double x)

    Returns the derivative of the Kelvin function ber.
    Parameters
    +
    double nu
    +

    The order of the Kelvin function.

    double x

    The value to compute the derivative of the Kelvin function of.

    @@ -2053,21 +2058,19 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    Return
    double
    -

    The derivative of the Kelvin function ber.

    +

    the derivative of the Kelvin function ber

    -

    double KelvinBerPrime(double nu, double x)

    +

    double KelvinBerPrime(double x)

    Returns the derivative of the Kelvin function ber.
    Parameters
    -
    double nu
    -

    The order of the Kelvin function.

    double x

    The value to compute the derivative of the Kelvin function of.

    @@ -2075,7 +2078,7 @@ Q(a,x) = 1/Gamma(a) * int(exp(-t)t^(a-1),t=0..x) for real a > 0, x > 0.
    Return
    double
    -

    the derivative of the Kelvin function ber

    +

    The derivative of the Kelvin function ber.

    @@ -2449,7 +2452,7 @@ between 0 and 1.

    diff --git a/api/MathNet.Numerics/TestFunctions.htm b/api/MathNet.Numerics/TestFunctions.htm index 8312919a..b50ce9a0 100644 --- a/api/MathNet.Numerics/TestFunctions.htm +++ b/api/MathNet.Numerics/TestFunctions.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -377,7 +380,7 @@ Common range: x in [-3,3], y in [-2,2].
    diff --git a/api/MathNet.Numerics/Trig.htm b/api/MathNet.Numerics/Trig.htm index 46acaefc..9120f9a0 100644 --- a/api/MathNet.Numerics/Trig.htm +++ b/api/MathNet.Numerics/Trig.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -1312,81 +1315,81 @@
    • -

    double Tan(double radian)

    -
    Trigonometric Tangent of an angle in radian, or opposite / adjacent. +

    Complex Tan(this Complex value)

    +
    Trigonometric Tangent of a Complex number.
    Parameters
    -
    double radian
    -

    The angle in radian.

    +
    Complex value
    +

    The complex value.

    Return
    -
    double
    -

    The tangent of the radian angle.

    +
    Complex
    +

    The tangent of the complex number.

    -

    Complex Tan(this Complex value)

    -
    Trigonometric Tangent of a Complex number. +

    double Tan(double radian)

    +
    Trigonometric Tangent of an angle in radian, or opposite / adjacent.
    Parameters
    -
    Complex value
    -

    The complex value.

    +
    double radian
    +

    The angle in radian.

    Return
    -
    Complex
    -

    The tangent of the complex number.

    +
    double
    +

    The tangent of the radian angle.

    -

    Complex Tanh(this Complex value)

    -
    Hyperbolic Tangent of a Complex number. +

    double Tanh(double angle)

    +
    Hyperbolic Tangent in radian
    Parameters
    -
    Complex value
    -

    The complex value.

    +
    double angle
    +

    The hyperbolic angle, i.e. the area of the hyperbolic sector.

    Return
    -
    Complex
    -

    The hyperbolic tangent of a complex number.

    +
    double
    +

    The hyperbolic tangent of the angle.

    -

    double Tanh(double angle)

    -
    Hyperbolic Tangent in radian +

    Complex Tanh(this Complex value)

    +
    Hyperbolic Tangent of a Complex number.
    Parameters
    -
    double angle
    -

    The hyperbolic angle, i.e. the area of the hyperbolic sector.

    +
    Complex value
    +

    The complex value.

    Return
    -
    double
    -

    The hyperbolic tangent of the angle.

    +
    Complex
    +

    The hyperbolic tangent of a complex number.

    @@ -1394,7 +1397,7 @@ diff --git a/api/MathNet.Numerics/Window.htm b/api/MathNet.Numerics/Window.htm index aef91de2..dea52b5e 100644 --- a/api/MathNet.Numerics/Window.htm +++ b/api/MathNet.Numerics/Window.htm @@ -138,6 +138,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -455,7 +458,7 @@ by half a cosine window on each side. diff --git a/api/MathNet.Numerics/index.htm b/api/MathNet.Numerics/index.htm index de19b08a..bfcfb54f 100644 --- a/api/MathNet.Numerics/index.htm +++ b/api/MathNet.Numerics/index.htm @@ -137,6 +137,9 @@
  • Constants +
    • +
  • + ContourIntegrate
  • Control @@ -235,6 +238,7 @@
  • Complex32
  • ComplexExtensions
  • Constants
    • +
  • ContourIntegrate
  • Control
  • Differentiate
  • Distance
    • @@ -270,7 +274,7 @@
    diff --git a/api/index.htm b/api/index.htm index 92894221..0e1cebd4 100644 --- a/api/index.htm +++ b/api/index.htm @@ -55,6 +55,7 @@
  • Complex32
  • ComplexExtensions
  • Constants
    • +
  • ContourIntegrate
  • Control
  • Differentiate
  • Distance
    • @@ -92,6 +93,7 @@
  • Beta
  • BetaScaled
  • Binomial
    • +
  • Burr
  • Categorical
  • Cauchy
  • Chi
    • @@ -110,6 +112,7 @@
  • IDiscreteDistribution
  • IDistribution
  • InverseGamma
    • +
  • InverseGaussian
  • InverseWishart
  • IUnivariateDistribution
  • Laplace
    • @@ -126,6 +129,7 @@
  • Stable
  • StudentT
  • Triangular
    • +
  • TruncatedPareto
  • Weibull
  • Wishart
  • Zipf
    • @@ -136,6 +140,7 @@
  • Hartley
  • HartleyOptions
  • DoubleExponentialTransformation
    • +
  • GaussKronrodRule
  • GaussLegendreRule
  • NewtonCotesTrapeziumRule
  • SimpsonRule
    • @@ -377,7 +382,7 @@

    Math.NET Numerics Documentation