InterfaceObject¶
- class InterfaceObject(*args, **kwargs)¶
Methods
Accessor to the object's name.
getId
()Accessor to the object's id.
getName
()Accessor to the object's name.
setName
(name)Accessor to the object's name.
- __init__(*args, **kwargs)¶
- getClassName()¶
Accessor to the object’s name.
- Returns:
- class_namestr
The object class name (object.__class__.__name__).
- getId()¶
Accessor to the object’s id.
- Returns:
- idint
Internal unique identifier.
- getName()¶
Accessor to the object’s name.
- Returns:
- namestr
The name of the object.
- setName(name)¶
Accessor to the object’s name.
- Parameters:
- namestr
The name of the object.
Examples using the class¶
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A quick start guide to the Point and Sample classes
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Kolmogorov-Smirnov : get the statistics distribution
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Estimate tail dependence coefficients on the wave-surge data
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Estimate tail dependence coefficients on the wind data
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Create your own distribution given its quantile function
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Create a process from random vectors and processes
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Sample trajectories from a Gaussian Process with correlated outputs
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Apply a transform or inverse transform on your polynomial chaos
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Create a full or sparse polynomial chaos expansion
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Create a polynomial chaos metamodel from a data set
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Create a polynomial chaos for the Ishigami function: a quick start guide to polynomial chaos
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Example of multi output Kriging on the fire satellite model
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Kriging: metamodel with continuous and categorical variables
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Evaluate the mean of a random vector by simulations
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Use the Adaptive Directional Stratification Algorithm
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Use the post-analytical importance sampling algorithm
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Estimate a probability with Monte-Carlo on axial stressed beam: a quick start guide to reliability
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Use the FORM algorithm in case of several design points
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Non parametric Adaptive Importance Sampling (NAIS)
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Test the design point with the Strong Maximum Test
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Axial stressed beam : comparing different methods to estimate a probability
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An illustrated example of a FORM probability estimate
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Using the FORM - SORM algorithms on a nonlinear function
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Estimate Sobol indices on a field to point function
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Estimate Sobol’ indices for a function with multivariate output
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Example of sensitivity analyses on the wing weight model
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Create mixed deterministic and probabilistic designs of experiments
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Create a design of experiments with discrete and continuous variables
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Defining Python and symbolic functions: a quick start introduction to functions
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Create a multivariate basis of functions from scalar multivariable functions
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Calibrate a parametric model: a quick-start guide to calibration
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Generate observations of the Chaboche mechanical model
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Linear Regression with interval-censored observations
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Compute leave-one-out error of a polynomial chaos expansion
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Compute confidence intervals of a regression model from data
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Compute confidence intervals of a univariate noisy function
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Plot the log-likelihood contours of a distribution