Documentation for the abstract class IBaseFunctionMultiDim. Interface (abstract class) for generic functions objects of multi-dimension Provides a method to evaluate the function given a vector of coordinate values, by implementing operator() (const double *). In addition it defines the interface for copying functions via the pure virtual method Clone() and the interface for getting the function dimension via the NDim() method. Derived classes must implement the pure private virtual method DoEval(const double *) for the function evaluation in addition to NDim() and Clone(). @ingroup GenFunc

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virtual | ~IGradientOneDim() |

double | Derivative(double x) const |

double | Derivative(const double* x) const |

virtual void | FdF(double x, double& f, double& df) const |

void | FdF(const double* x, double& f, double* df) const |

void | Gradient(const double* x, double* g) const |

ROOT::Math::IGradientOneDim& | operator=(const ROOT::Math::IGradientOneDim&) |

virtual double | DoDerivative(double x) const |

void Gradient(const double* x, double* g) const

Evaluate all the vector of function derivatives (gradient) at a point x. Derived classes must re-implement if it is more efficient than evaluting one at a time

double Derivative(const double * x, unsigned int icoord = 0)

Return the partial derivative with respect to the passed coordinate

return DoDerivative(x, icoord)

void FdF(const double* x, double& f, double* df) const

Optimized method to evaluate at the same time the function value and derivative at a point x. Often both value and derivatives are needed and it is often more efficient to compute them at the same time. Derived class should implement this method if performances play an important role and if it is faster to evaluate value and derivative at the same time

double Derivative(double x) const

Return the derivative of the function at a point x Use the private method DoDerivative

void FdF(double x, double& f, double& df) const

Optimized method to evaluate at the same time the function value and derivative at a point x. Often both value and derivatives are needed and it is often more efficient to compute them at the same time. Derived class should implement this method if performances play an important role and if it is faster to evaluate value and derivative at the same time