:orphan: .. _sphx_glr_auto_meta_modeling: .. _Meta modeling: Meta modeling ============= .. raw:: html
.. _sphx_glr_auto_meta_modeling_general_purpose_metamodels: .. _General purpose metamodels: General purpose metamodels -------------------------- .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_create_linear_least_squares_model_thumb.png :alt: Create a linear least squares model :ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_create_linear_least_squares_model.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/general_purpose_metamodels/plot_create_linear_least_squares_model .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_general_linear_model_thumb.png :alt: Create a general linear model metamodel :ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_general_linear_model.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/general_purpose_metamodels/plot_general_linear_model .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_taylor_approximation_thumb.png :alt: Taylor approximations :ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_taylor_approximation.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/general_purpose_metamodels/plot_taylor_approximation .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_linear_model_thumb.png :alt: Create a linear model :ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_linear_model.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/general_purpose_metamodels/plot_linear_model .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_expert_mixture_thumb.png :alt: Mixture of experts :ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_expert_mixture.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/general_purpose_metamodels/plot_expert_mixture .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_stepwise_thumb.png :alt: Perfom stepwise regression :ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_stepwise.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/general_purpose_metamodels/plot_stepwise .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/general_purpose_metamodels/images/thumb/sphx_glr_plot_overfitting_model_selection_thumb.png :alt: Over-fitting and model selection :ref:`sphx_glr_auto_meta_modeling_general_purpose_metamodels_plot_overfitting_model_selection.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/general_purpose_metamodels/plot_overfitting_model_selection .. raw:: html
.. _sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel: .. _Polynomial chaos metamodel: Polynomial chaos metamodel -------------------------- .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_distribution_transformation_thumb.png :alt: Apply a transform or inverse transform on your polynomial chaos :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_distribution_transformation.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_distribution_transformation .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_build_distribution_thumb.png :alt: Fit a distribution from an input sample :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_build_distribution.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_build_distribution .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_exploitation_thumb.png :alt: Polynomial chaos exploitation :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_exploitation.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_exploitation .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_database_thumb.png :alt: Polynomial chaos over database :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_database.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_database .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_ishigami_grouped_indices_thumb.png :alt: Compute grouped indices for the Ishigami function :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_ishigami_grouped_indices.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_ishigami_grouped_indices .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_draw_validation_thumb.png :alt: Validate a polynomial chaos :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_draw_validation.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_draw_validation .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_graphs_thumb.png :alt: Polynomial chaos graphs :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_graphs.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_graphs .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_cantilever_beam_integration_thumb.png :alt: Create a polynomial chaos metamodel by integration on the cantilever beam :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_cantilever_beam_integration.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_cantilever_beam_integration .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_advanced_ctors_thumb.png :alt: Advanced polynomial chaos construction :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos_advanced_ctors.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos_advanced_ctors .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_functional_chaos_thumb.png :alt: Create a polynomial chaos metamodel :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_functional_chaos.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_functional_chaos .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_ishigami_thumb.png :alt: Create a polynomial chaos for the Ishigami function: a quick start guide to polynomial chaos :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_ishigami.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_ishigami .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/polynomial_chaos_metamodel/images/thumb/sphx_glr_plot_chaos_beam_sensitivity_degree_thumb.png :alt: Polynomial chaos is sensitive to the degree :ref:`sphx_glr_auto_meta_modeling_polynomial_chaos_metamodel_plot_chaos_beam_sensitivity_degree.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/polynomial_chaos_metamodel/plot_chaos_beam_sensitivity_degree .. raw:: html
.. _sphx_glr_auto_meta_modeling_kriging_metamodel: .. _Kriging metamodel: Kriging metamodel ----------------- .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_propagate_kriging_ishigami_thumb.png :alt: Kriging : propagate uncertainties :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_propagate_kriging_ishigami.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_propagate_kriging_ishigami .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_thumb.png :alt: Kriging : multiple input dimensions :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_likelihood_thumb.png :alt: Kriging : draw the likelihood :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_likelihood.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_likelihood .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_cantilever_beam_thumb.png :alt: Kriging : cantilever beam model :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_cantilever_beam.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_cantilever_beam .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_beam_arbitrary_trend_thumb.png :alt: Configuring an arbitrary trend in Kriging :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_beam_arbitrary_trend.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_beam_arbitrary_trend .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_cantilever_beam_hmat_thumb.png :alt: Kriging the cantilever beam model using HMAT :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_cantilever_beam_hmat.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_cantilever_beam_hmat .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_beam_trend_thumb.png :alt: Choose the trend basis of a kriging metamodel :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_beam_trend.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_beam_trend .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_isotropic_thumb.png :alt: Kriging with an isotropic covariance function :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_isotropic.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_isotropic .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_simulate_thumb.png :alt: Kriging : generate trajectories from a metamodel :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_simulate.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_simulate .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_hyperparameters_optimization_thumb.png :alt: Kriging :configure the optimization solver :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_hyperparameters_optimization.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_hyperparameters_optimization .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_branin_function_thumb.png :alt: Kriging: metamodel of the Branin-Hoo function :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_branin_function.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_branin_function .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_1d_thumb.png :alt: Kriging : quick-start :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_1d.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_1d .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_sequential_thumb.png :alt: Sequentially adding new points to a kriging :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_sequential.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_sequential .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_advanced_thumb.png :alt: Advanced kriging :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_advanced.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_advanced .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_kriging_chose_trend_thumb.png :alt: Kriging : choose a trend vector space :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_kriging_chose_trend.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_kriging_chose_trend .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/kriging_metamodel/images/thumb/sphx_glr_plot_draw_covariance_models_thumb.png :alt: Kriging : draw covariance models :ref:`sphx_glr_auto_meta_modeling_kriging_metamodel_plot_draw_covariance_models.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/kriging_metamodel/plot_draw_covariance_models .. raw:: html
.. _sphx_glr_auto_meta_modeling_low_rank_tensors_metamodel: .. _Low rank tensors metamodel: Low rank tensors metamodel -------------------------- .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/low_rank_tensors_metamodel/images/thumb/sphx_glr_plot_tensor_cantilever_beam_thumb.png :alt: Tensor approximation of the cantilever beam model :ref:`sphx_glr_auto_meta_modeling_low_rank_tensors_metamodel_plot_tensor_cantilever_beam.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/low_rank_tensors_metamodel/plot_tensor_cantilever_beam .. raw:: html
.. _sphx_glr_auto_meta_modeling_fields_metamodels: .. _Fields metamodels: Fields metamodels ----------------- .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/fields_metamodels/images/thumb/sphx_glr_plot_karhunenloeve_validation_thumb.png :alt: Validation of a Karhunen-Loeve decomposition :ref:`sphx_glr_auto_meta_modeling_fields_metamodels_plot_karhunenloeve_validation.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/fields_metamodels/plot_karhunenloeve_validation .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/fields_metamodels/images/thumb/sphx_glr_plot_viscous_fall_metamodel_thumb.png :alt: Viscous free fall: metamodel of a field function :ref:`sphx_glr_auto_meta_modeling_fields_metamodels_plot_viscous_fall_metamodel.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/fields_metamodels/plot_viscous_fall_metamodel .. raw:: html
.. only:: html .. figure:: /auto_meta_modeling/fields_metamodels/images/thumb/sphx_glr_plot_fieldfunction_metamodel_thumb.png :alt: Metamodel of a field function :ref:`sphx_glr_auto_meta_modeling_fields_metamodels_plot_fieldfunction_metamodel.py` .. raw:: html
.. toctree:: :hidden: /auto_meta_modeling/fields_metamodels/plot_fieldfunction_metamodel .. raw:: html
.. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-gallery .. container:: sphx-glr-download sphx-glr-download-python :download:`Download all examples in Python source code: auto_meta_modeling_python.zip ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download all examples in Jupyter notebooks: auto_meta_modeling_jupyter.zip `