otmorris.MorrisFunction

class otmorris.MorrisFunction(alpha=class=Point name=Unnamed dimension=10 values=[0,0,0,0,0,0,0,0,0,0], beta=class=Point name=Unnamed dimension=84 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], gamma=class=Point name=Unnamed dimension=280 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], b0=0.0)

The non-monotonic function of Morris f: R^20 -> R

Reference:

M. D. Morris, 1991, Factorial sampling plans for preliminary computational experiments,Technometrics, 33, 161–174.

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(123)
>>> b0 = ot.DistFunc.rNormal()
>>> alpha = ot.DistFunc.rNormal(10)
>>> beta =  ot.DistFunc.rNormal(6*14)
>>> gamma =  ot.DistFunc.rNormal(20*14)
>>> f = ot.Function(MorrisFunction(alpha, beta, gamma, b0))
>>> input_sample = ot.ComposedDistribution([ot.Uniform(0,1)] * 20).getSample(20)
>>> output_sample = f(input_sample)

Methods

__call__(X)	Call self as a function.
getInputDescription()	Input description accessor.
getInputDimension()	Input dimension accessor.
getOutputDescription()	Output description accessor.
getOutputDimension()	Output dimension accessor.
setInputDescription(descIn)	Input description accessor.
setOutputDescription(descOut)	Output description accessor.

__init__(alpha=class=Point name=Unnamed dimension=10 values=[0,0,0,0,0,0,0,0,0,0], beta=class=Point name=Unnamed dimension=84 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], gamma=class=Point name=Unnamed dimension=280 values=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], b0=0.0)

Methods

__init__([alpha, beta, gamma, b0])
getInputDescription()	Input description accessor.
getInputDimension()	Input dimension accessor.
getOutputDescription()	Output description accessor.
getOutputDimension()	Output dimension accessor.
setInputDescription(descIn)	Input description accessor.
setOutputDescription(descOut)	Output description accessor.

getInputDescription()

Input description accessor.

getInputDimension()

Input dimension accessor.

getOutputDescription()

Output description accessor.

getOutputDimension()

Output dimension accessor.

setInputDescription(descIn)

Input description accessor.

setOutputDescription(descOut)

Output description accessor.