Grasshopper2.Types.Functionsnamespace

Interface for functions which self-identify as a type of polynomial.

Enumerates the function shapes which can be fitted through a set of samples.

Enumerates the error metrics which fitting can seek to minimise.

Enumerates the mechanisms for discarding poorly fitted samples between fitting rounds.

Base level class for mathematical functions in the form y = f(x), representing a mapping from individual 64-bit double precision values onto individual 64-bit double precision values.

Do not inherit from this class if you wish to create a new function unless you need an absolutely minimal implementation to start with. Consider instead deriving from FunctionWithCaching.

Implementation of FunctionWithCaching which exposes one scalar argument.

Implementation of FunctionWithCaching which exposes two scalar arguments.

Implementation of FunctionWithCaching which exposes three scalar arguments.

Implementation of FunctionWithCaching which exposes four scalar arguments.

Implementation of FunctionWithCaching which exposes five scalar arguments.

Abstract base function for unary operations. That is, a function which requires 1 other function as input.

Abstract base function for binary operations. That is, functions which require two other functions as operands.

Abstract base function for ternary operations. That is, function which require 3 other functions as inputs.

Abstract base function for quarternary operations. That is, function which require 4 other functions as inputs.

Provides fitting of standard function shapes through arbitrary (x,y) samples.

A utility class for creating a visual sampling of a function.

Useful abstract class for creating your own functions. This class extends the Function abstract class by providing caching for derivative and indefinite integral functions. Note that it does *not* cache results for evaluations. If you want that level of caching, you must build it yourself.

A function which acts as a stand-in for identity mapping.

A trapezoidal approximation of a function as a stand-in for an unknown indefinite integral. This approximation is only defined on positive values of x, if you wish to approximate a negative domain you must use an inverted evaluation function, and the absolute values of evaluation parameters.

Represents a function pole, where the y-value goes off to infinity or becomes undefined in some other way.