.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery_examples/drainage_bassin/make_optimization_drainage.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_drainage_bassin_make_optimization_drainage.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_examples_drainage_bassin_make_optimization_drainage.py:


Drainage bassin
###############

In the same category than https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.1811

.. GENERATED FROM PYTHON SOURCE LINES 7-56

.. code-block:: Python


    import sys
    import os
    path = os.getcwd() + '/../../'
    sys.path.append(path)

    import numpy as np
    import h5py

    import nlopt
                                  
    from HydrOpTop.Functions import Mean_Liquid_Piezometric_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


    if __name__ == "__main__":
      #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-10], power=3)
  
      #define cost function as sum of the head in the pit
      cf = Mean_Liquid_Piezometric_Head(ids_to_sum="everywhere", penalizing_power=1)
  
      #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], [max_vol], [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(),dtype='f8') + 0.15
      p_opt = crafted_problem.optimize(optimizer="nlopt-mma", action="minimize", max_it=75, ftol=0.0001, initial_guess=p)
    


.. _sphx_glr_download_gallery_examples_drainage_bassin_make_optimization_drainage.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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