.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_functional_modeling/vectorial_functions/plot_aggregated_function.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_functional_modeling_vectorial_functions_plot_aggregated_function.py: Create an aggregated function ============================= .. GENERATED FROM PYTHON SOURCE LINES 6-11 In this example we are going to build a function that stacks all the outputs from several functions .. math:: f = (f_1, \dots, f_n) .. GENERATED FROM PYTHON SOURCE LINES 13-17 .. code-block:: Python import openturns as ot ot.Log.Show(ot.Log.NONE) .. GENERATED FROM PYTHON SOURCE LINES 18-19 assume a list of functions to aggregate .. GENERATED FROM PYTHON SOURCE LINES 19-25 .. code-block:: Python functions = list() functions.append(ot.SymbolicFunction(["x1", "x2", "x3"], ["x1^2 + x2", "x1 + x2 + x3"])) functions.append( ot.SymbolicFunction(["x1", "x2", "x3"], ["x1 + 2 * x2 + x3", "x1 + x2 - x3"]) ) .. GENERATED FROM PYTHON SOURCE LINES 26-27 create the aggregated function .. GENERATED FROM PYTHON SOURCE LINES 27-29 .. code-block:: Python function = ot.AggregatedFunction(functions) .. GENERATED FROM PYTHON SOURCE LINES 30-31 evaluate the function .. GENERATED FROM PYTHON SOURCE LINES 31-34 .. code-block:: Python x = [1.0, 2.0, 3.0] y = function(x) print("x=", x, "y=", y) .. rst-class:: sphx-glr-script-out .. code-block:: none x= [1.0, 2.0, 3.0] y= [3,6,8,0] .. _sphx_glr_download_auto_functional_modeling_vectorial_functions_plot_aggregated_function.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_aggregated_function.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_aggregated_function.py `