OpenTURNS
ConstantBasisFactory¶
- class ConstantBasisFactory(*args)¶
Constant basis factory.
- Parameters:
- dimensionint
Input dimension of the basis.
Methods
build()Build the basis.
Accessor to the object's name.
getName()Accessor to the object's name.
hasName()Test if the object is named.
setName(name)Accessor to the object's name.
See also
Notes
A factory for constant basis of input dimension dimension.
Examples
>>> import openturns as ot >>> basis = ot.ConstantBasisFactory(2).build() >>> f = ot.AggregatedFunction(basis) >>> x = [2, 3] >>> print(f(x)) [1]
- __init__(*args)¶
- getClassName()¶
Accessor to the object’s name.
- Returns:
- class_namestr
The object class name (object.__class__.__name__).
- getName()¶
Accessor to the object’s name.
- Returns:
- namestr
The name of the object.
- hasName()¶
Test if the object is named.
- Returns:
- hasNamebool
True if the name is not empty.
- setName(name)¶
Accessor to the object’s name.
- Parameters:
- namestr
The name of the object.
Examples using the class¶
Gaussian Process Regression: multiple input dimensions
Gaussian Process-based active learning for reliability
Gaussian Process Regression: choose a polynomial trend on the beam model
Gaussian Process Regression : cantilever beam model
Gaussian Process Regression: surrogate model with continuous and categorical variables
Gaussian Process Regression: choose a polynomial trend
Gaussian process fitter: configure the optimization solver
Gaussian Process Regression: use an isotropic covariance kernel
Gaussian Process Regression : generate trajectories from the metamodel
Gaussian Process Regression: metamodel of the Branin-Hoo function
Sequentially adding new points to a Gaussian Process metamodel
Gaussian Process Regression: propagate uncertainties
