User manual for the Python interface¶
Model creation¶
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Create a variable base class. |
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Create an input variable. |
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Create an output variable. |
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Create a mesh model base class. |
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Create a model to build regular meshes. |
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Create a model with imported meshes |
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Physical model base class. |
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Create a physical model defined by analytical formulas. |
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Create a physical model defined by analytical formulas and a mesh. |
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Create a physical model defined by Python code. |
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Create a physical model defined by Python code and a mesh. |
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Create a data model from an imported dataset. |
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DataModel sample manipulation. |
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Metamodel. |
Coupling model¶
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Input file metadata for coupling. |
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Resource file metadata for coupling. |
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Output file metadata for coupling. |
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Coupling step. |
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File-exchange based coupling model. |
Model evaluation¶
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Generate a simple evaluation of a model. |
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Generate the evaluation of a model with mesh. |
Optimization¶
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Perform the optimization analysis of a model. |
Screening¶
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Perform a Morris analysis. |
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Get the result of a Morris analysis. |
Calibration¶
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Create observations for variables of a model. |
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Run a calibration analysis. |
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Get the results of a calibration analysis. |
Probabilistic studies¶
Central tendency¶
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Perform a Monte Carlo central tendency analysis. |
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Run a Monte Carlo analysis for models with mesh. |
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Get the results of a Monte Carlo analysis with mesh. |
Get the Taylor expansions for moments estimation. |
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Get the results of Taylor expansions for moments estimation. |
Sensitivity analysis¶
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Run a Sobol sensitivity analysis. |
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Get the results of a Sobol sensitivity analysis. |
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Run a SRC sensitivity analysis. |
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Get the results of a SRC sensitivity analysis. |
Reliability model¶
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Create a limit state. |
Reliability analysis¶
Run a reliability analysis using the Monte Carlo method. |
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Run a FORM analysis followed by an importance sampling for reliability analysis. |
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Run importance sampling for reliability analysis. |
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Process a reliability analysis using the FORM method. |
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Run a reliability analysis using the SORM method. |
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Get simulation results from a reliability analysis using Monte Carlo or Importance Sampling method. |
Design of experiments¶
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Design of experiments base class. |
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Create a fixed design of experiments. |
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Create a grid design of experiments. |
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Create a design of experiments, using an imported design. |
Create a probabilistic design of experiments. |
Data analysis¶
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Create a data analysis of a design of experiments. |
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Get the results of a data analysis. |
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Perform a Kolmogorov goodness-of-fit test for 1-D continuous distributions. |
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Get the results of an inference analysis. |
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Get the results of a fitting test. |
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Perform a dependence inference analysis. |
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Get the results of a dependence inference analysis. |
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Dependence inference result for a set of variables. |
Metamodel¶
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Create a base class for the creation of meta models. |
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Create a Functional chaos analysis. |
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Create a Kriging analysis. |
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Create the base class for a metamodel analysis result. |
Get the results for a Functional chaos analysis. |
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Get the results of a Kriging analysis. |
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Create the base class for the results of a metamodel validation. |
Function caching¶
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Function proxy with a CSV file cache. |