.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery_examples/Permeability_calibration_small/make_calibration_permeability_2D.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_gallery_examples_Permeability_calibration_small_make_calibration_permeability_2D.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_gallery_examples_Permeability_calibration_small_make_calibration_permeability_2D.py:


2D permeability field calibration
#################################

.. GENERATED FROM PYTHON SOURCE LINES 5-47

.. code-block:: Python


    import numpy as np
                                  
    from HydrOpTop.Functions import Reference_Liquid_Head #objective
    from HydrOpTop.Functions import Volume_Percentage #constrain
    from HydrOpTop.Materials import Log_SIMP
    from HydrOpTop.Crafter import Steady_State_Crafter
    from HydrOpTop.Filters import Density_Filter
    from HydrOpTop.Solvers import PFLOTRAN

    #create PFLOTRAN simulation object
    pflotranin = "pflotran.in"
    sim = PFLOTRAN(pflotranin)

    #get cell ids in the region to optimize and parametrize permeability
    #same name than in pflotran input file
    perm = Log_SIMP(cell_ids_to_parametrize="all", property_name="PERMEABILITY", bounds=[1e-14, 1e-12], power=1)

    #define cost function as sum of the head in the pit
    cell_ids = [444, 789, 920, 1030, 1339]
    head = [230, 250, 227, 146, 210]
    cf = Reference_Liquid_Head(head, cell_ids, norm=2)

    #define maximum volume constrains
    #max_vol = Volume_Percentage("parametrized_cell")
    #max_vol.constraint_tol = 0.2

    filter_ = Density_Filter(10.)

    #craft optimization problem
    #i.e. create function to optimize, initiate IO array in classes...
    crafted_problem = Steady_State_Crafter(cf, sim, [perm], [], [filter_])
    crafted_problem.IO.output_every_iteration(1)
    crafted_problem.IO.output_gradient()
    crafted_problem.IO.output_material_properties()
    crafted_problem.IO.define_output_format("vtu")

    #initialize optimizer
    p = np.zeros(crafted_problem.get_problem_size()) + 0.5
    #p = 0.999*np.random.rand(crafted_problem.get_problem_size())+0.001 
    p_opt = crafted_problem.optimize(optimizer="nlopt-mma", action="minimize", max_it=100, ftol=0.0001, initial_guess=p)
    


.. _sphx_glr_download_gallery_examples_Permeability_calibration_small_make_calibration_permeability_2D.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: make_calibration_permeability_2D.ipynb <make_calibration_permeability_2D.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: make_calibration_permeability_2D.py <make_calibration_permeability_2D.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_