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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_examples_scalable_scalable_tm.py>`
        to download the full example code

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

.. _sphx_glr_examples_scalable_scalable_tm.py:


Scalable problem of Tedford and Martins, 2010
=============================================

.. GENERATED FROM PYTHON SOURCE LINES 26-43

.. code-block:: default

    from __future__ import annotations

    from gemseo.api import configure_logger
    from gemseo.api import generate_n2_plot
    from gemseo.problems.scalable.parametric.core.design_space import TMDesignSpace
    from gemseo.problems.scalable.parametric.disciplines import TMMainDiscipline
    from gemseo.problems.scalable.parametric.disciplines import TMSubDiscipline
    from gemseo.problems.scalable.parametric.problem import TMScalableProblem
    from gemseo.problems.scalable.parametric.study import TMParamSS
    from gemseo.problems.scalable.parametric.study import TMParamSSPost
    from gemseo.problems.scalable.parametric.study import TMScalableStudy
    from numpy import array
    from numpy.random import rand

    configure_logger()






.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    <RootLogger root (INFO)>



.. GENERATED FROM PYTHON SOURCE LINES 44-54

Disciplines
-----------
We define two strongly coupled disciplines and a weakly coupled discipline,
with:

- 2 shared design parameters,
- 2 local design parameters for the first discipline,
- 3 local design parameters for the second discipline,
- 3 coupling variables for the first discipline,
- 2 coupling variables for the second discipline.

.. GENERATED FROM PYTHON SOURCE LINES 54-57

.. code-block:: default

    sizes = {"x_shared": 2, "x_local_0": 2, "x_local_1": 3, "y_0": 3, "y_1": 2}









.. GENERATED FROM PYTHON SOURCE LINES 58-64

We use any values for the coefficients and the default values of the design
parameters and coupling variables.

Strongly coupled disciplines
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Here is the first strongly coupled discipline.

.. GENERATED FROM PYTHON SOURCE LINES 64-79

.. code-block:: default

    default_inputs = {
        "x_shared": rand(sizes["x_shared"]),
        "x_local_0": rand(sizes["x_local_0"]),
        "y_1": rand(sizes["y_1"]),
    }
    index = 0
    c_shared = rand(sizes["y_0"], sizes["x_shared"])
    c_local = rand(sizes["y_0"], sizes["x_local_0"])
    c_coupling = {"y_1": rand(sizes["y_0"], sizes["y_1"])}
    disc0 = TMSubDiscipline(index, c_shared, c_local, c_coupling, default_inputs)

    print(disc0.name)
    print(disc0.get_input_data_names())
    print(disc0.get_output_data_names())





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    SubModel_0
    ['x_local_0', 'x_shared', 'y_1']
    ['y_0']




.. GENERATED FROM PYTHON SOURCE LINES 80-85

.. code-block:: console

   TM_Discipline_0
   dict_keys(['x_shared', 'x_local_0', 'y_1'])
   dict_keys(['y_0'])

.. GENERATED FROM PYTHON SOURCE LINES 88-89

Here is the second one, strongly coupled with the first one.

.. GENERATED FROM PYTHON SOURCE LINES 89-104

.. code-block:: default

    default_inputs = {
        "x_shared": rand(sizes["x_shared"]),
        "x_local_1": rand(sizes["x_local_1"]),
        "y_0": rand(sizes["y_0"]),
    }
    index = 1
    c_shared = rand(sizes["y_1"], sizes["x_shared"])
    c_local = rand(sizes["y_1"], sizes["x_local_1"])
    c_coupling = {"y_0": rand(sizes["y_1"], sizes["y_0"])}
    disc1 = TMSubDiscipline(index, c_shared, c_local, c_coupling, default_inputs)

    print(disc1.name)
    print(disc1.get_input_data_names())
    print(disc1.get_output_data_names())





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    SubModel_1
    ['x_local_1', 'x_shared', 'y_0']
    ['y_1']




.. GENERATED FROM PYTHON SOURCE LINES 105-110

.. code-block:: console

   TM_Discipline_1
   dict_keys(['x_shared', 'x_local_1', 'y_0'])
   dict_keys(['y_1'])

.. GENERATED FROM PYTHON SOURCE LINES 112-115

Weakly coupled discipline
^^^^^^^^^^^^^^^^^^^^^^^^^
Here is the discipline weakly coupled to the previous ones.

.. GENERATED FROM PYTHON SOURCE LINES 115-127

.. code-block:: default

    c_constraint = [array([1.0, 2.0]), array([3.0, 4.0, 5.0])]
    default_inputs = {
        "x_shared": array([0.5]),
        "y_0": array([2.0, 3.0]),
        "y_1": array([4.0, 5.0, 6.0]),
    }
    system = TMMainDiscipline(c_constraint, default_inputs)

    print(system.name)
    print(system.get_input_data_names())
    print(system.get_output_data_names())





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    MainModel
    ['x_shared', 'y_0', 'y_1']
    ['cstr_0', 'cstr_1', 'obj']




.. GENERATED FROM PYTHON SOURCE LINES 128-133

.. code-block:: console

   TM_System
   dict_keys(['x_shared', 'y_0', 'y_1'])
   dict_keys(['obj', 'cstr_0', 'cstr_1'])

.. GENERATED FROM PYTHON SOURCE LINES 135-138

Coupling chart
^^^^^^^^^^^^^^
We can represent these three disciplines by means of an N2 chart.

.. GENERATED FROM PYTHON SOURCE LINES 138-140

.. code-block:: default

    generate_n2_plot([disc0, disc1, system], save=False, show=True)




.. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_001.png
   :alt: scalable tm
   :srcset: /examples/scalable/images/sphx_glr_scalable_tm_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 141-142

.. image:: /_images/scalable_tm/N2chart.png

.. GENERATED FROM PYTHON SOURCE LINES 144-148

Design space
------------
We define the design space from the sizes of the shared design parameters,
local parameters and coupling variables.

.. GENERATED FROM PYTHON SOURCE LINES 148-155

.. code-block:: default

    n_shared = sizes["x_shared"]
    n_local = [sizes["x_local_0"], sizes["x_local_1"]]
    n_coupling = [sizes["y_0"], sizes["y_1"]]
    design_space = TMDesignSpace(n_shared, n_local, n_coupling)

    print(design_space)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    <gemseo.problems.scalable.parametric.core.design_space.TMDesignSpace object at 0x7fbc386f57c0>




.. GENERATED FROM PYTHON SOURCE LINES 156-175

.. code-block:: console

   Design Space:
   +-----------+-------------+-------+-------------+-------+
   | name      | lower_bound | value | upper_bound | type  |
   +-----------+-------------+-------+-------------+-------+
   | x_local_0 |      0      |  0.5  |      1      | float |
   | x_local_0 |      0      |  0.5  |      1      | float |
   | x_local_1 |      0      |  0.5  |      1      | float |
   | x_local_1 |      0      |  0.5  |      1      | float |
   | x_local_1 |      0      |  0.5  |      1      | float |
   | x_shared  |      0      |  0.5  |      1      | float |
   | x_shared  |      0      |  0.5  |      1      | float |
   | y_0       |      0      |  0.5  |      1      | float |
   | y_0       |      0      |  0.5  |      1      | float |
   | y_0       |      0      |  0.5  |      1      | float |
   | y_1       |      0      |  0.5  |      1      | float |
   | y_1       |      0      |  0.5  |      1      | float |
   +-----------+-------------+-------+-------------+-------+

.. GENERATED FROM PYTHON SOURCE LINES 177-187

Scalable problem
----------------
We define a scalable problem based on two strongly coupled disciplines
and a weakly one, with the following properties:

- 3 shared design parameters,
- 2 local design parameters for the first strongly coupled discipline,
- 2 coupling variables for the first strongly coupled discipline,
- 4 local design parameters for the second strongly coupled discipline,
- 3 coupling variables for the second strongly coupled discipline.

.. GENERATED FROM PYTHON SOURCE LINES 187-195

.. code-block:: default

    problem = TMScalableProblem(3, [2, 4], [2, 3])

    print(problem)

    print(problem.get_design_space())

    print(problem.get_default_inputs())





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Scalable problem
    .... MainModel
    ........ Inputs:
    ............ x_shared (3)
    ............ y_0 (2)
    ............ y_1 (3)
    ........ Outputs:
    ............ cstr_0 (2)
    ............ cstr_1 (3)
    ............ obj (1)
    .... SubModel_0
    ........ Inputs:
    ............ x_local_0 (2)
    ............ x_shared (3)
    ............ y_1 (3)
    ........ Outputs:
    ............ y_0 (2)
    .... SubModel_1
    ........ Inputs:
    ............ x_local_1 (4)
    ............ x_shared (3)
    ............ y_0 (2)
    ........ Outputs:
    ............ y_1 (3)
    +------------------------------------------------------------------------------+
    |                               Parameter space                                |
    +-----------+-------------+-------+-------------+-------+----------------------+
    | name      | lower_bound | value | upper_bound | type  | Initial distribution |
    +-----------+-------------+-------+-------------+-------+----------------------+
    | x_local_0 |      0      |  0.5  |      1      | float |                      |
    | x_local_0 |      0      |  0.5  |      1      | float |                      |
    | x_local_1 |      0      |  0.5  |      1      | float |                      |
    | x_local_1 |      0      |  0.5  |      1      | float |                      |
    | x_local_1 |      0      |  0.5  |      1      | float |                      |
    | x_local_1 |      0      |  0.5  |      1      | float |                      |
    | x_shared  |      0      |  0.5  |      1      | float |                      |
    | x_shared  |      0      |  0.5  |      1      | float |                      |
    | x_shared  |      0      |  0.5  |      1      | float |                      |
    | y_0       |      0      |  0.5  |      1      | float |                      |
    | y_0       |      0      |  0.5  |      1      | float |                      |
    | y_1       |      0      |  0.5  |      1      | float |                      |
    | y_1       |      0      |  0.5  |      1      | float |                      |
    | y_1       |      0      |  0.5  |      1      | float |                      |
    +-----------+-------------+-------+-------------+-------+----------------------+
    {'x_shared': array([0.5, 0.5, 0.5]), 'x_local_0': array([0.5, 0.5]), 'y_0': array([0.5, 0.5]), 'cstr_0': array([0.5, 0.5]), 'u_local_0': array([0., 0.]), 'x_local_1': array([0.5, 0.5, 0.5, 0.5]), 'y_1': array([0.5, 0.5, 0.5]), 'cstr_1': array([0.5, 0.5, 0.5]), 'u_local_1': array([0., 0., 0.])}




.. GENERATED FROM PYTHON SOURCE LINES 196-246

.. code-block:: console

    Scalable problem
    > TM_System
       >> Inputs:
          | x_shared (3)
          | y_0 (2)
          | y_1 (3)
       >> Outputs:
          | cstr_0 (2)
          | cstr_1 (3)
          | obj (1)
    > TM_Discipline_0
       >> Inputs:
          | x_local_0 (2)
          | x_shared (3)
          | y_1 (3)
       >> Outputs:
          | y_0 (2)
    > TM_Discipline_1
       >> Inputs:
          | x_local_1 (4)
          | x_shared (3)
          | y_0 (2)
       >> Outputs:
          | y_1 (3)

    Design Space:
    +-----------+-------------+-------+-------------+-------+
    | name      | lower_bound | value | upper_bound | type  |
    +-----------+-------------+-------+-------------+-------+
    | x_local_0 |      0      |  0.5  |      1      | float |
    | x_local_0 |      0      |  0.5  |      1      | float |
    | x_local_1 |      0      |  0.5  |      1      | float |
    | x_local_1 |      0      |  0.5  |      1      | float |
    | x_local_1 |      0      |  0.5  |      1      | float |
    | x_local_1 |      0      |  0.5  |      1      | float |
    | x_shared  |      0      |  0.5  |      1      | float |
    | x_shared  |      0      |  0.5  |      1      | float |
    | x_shared  |      0      |  0.5  |      1      | float |
    | y_0       |      0      |  0.5  |      1      | float |
    | y_0       |      0      |  0.5  |      1      | float |
    | y_1       |      0      |  0.5  |      1      | float |
    | y_1       |      0      |  0.5  |      1      | float |
    | y_1       |      0      |  0.5  |      1      | float |
    +-----------+-------------+-------+-------------+-------+
    {'x_shared': array([0.5, 0.5, 0.5]), 'x_local_0': array([0.5, 0.5]),
    'y_0': array([0.5, 0.5]), 'cstr_0': array([0.5]), 'x_local_1':
    array([0.5, 0.5, 0.5, 0.5]), 'y_1': array([0.5, 0.5, 0.5]), 'cstr_1':
    array([0.5])}

.. GENERATED FROM PYTHON SOURCE LINES 248-256

Scalable study
--------------
We define a scalable study based on two strongly coupled disciplines
and a weakly one, with the following properties:

- 3 shared design parameters,
- 2 local design parameters for each strongly coupled discipline,
- 3 coupling variables for each strongly coupled discipline.

.. GENERATED FROM PYTHON SOURCE LINES 256-259

.. code-block:: default

    study = TMScalableStudy(n_disciplines=2, n_shared=3, n_local=2, n_coupling=3)
    print(study)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Scalable study
    .... 2 disciplines
    .... 3 shared design parameters
    .... 2 local design parameters per discipline
    .... 3 coupling variables per discipline




.. GENERATED FROM PYTHON SOURCE LINES 260-267

.. code-block:: console

   Scalable study
   > 2 disciplines
   > 3 shared design parameters
   > 2 local design parameters per discipline
   > 3 coupling variables per discipline

.. GENERATED FROM PYTHON SOURCE LINES 269-270

Then, we run MDF and IDF formulations:

.. GENERATED FROM PYTHON SOURCE LINES 270-273

.. code-block:: default

    study.run_formulation("MDF")
    study.run_formulation("IDF")




.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_002.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_003.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_003.png
         :class: sphx-glr-multi-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

        INFO - 16:56:41: Make the starting point feasible.
        INFO - 16:56:41:  
        INFO - 16:56:41: *** Start MDOScenario execution ***
        INFO - 16:56:41: MDOScenario
        INFO - 16:56:41:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:56:41:    MDO formulation: MDF
        INFO - 16:56:41: Optimization problem:
        INFO - 16:56:41:    minimize obj(x_local_0, x_local_1, x_shared)
        INFO - 16:56:41:    with respect to x_local_0, x_local_1, x_shared
        INFO - 16:56:41:    subject to constraints:
        INFO - 16:56:41:       cstr_0(x_local_0, x_local_1, x_shared) <= [ 0.65250671 -2.8453087  -4.16343355]
        INFO - 16:56:41:       cstr_1(x_local_0, x_local_1, x_shared) <= [0.85268891 0.52747299 0.62341835]
        INFO - 16:56:41:    over the design space:
        INFO - 16:56:41:    |                               Parameter space                                |
        INFO - 16:56:41:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:41:    | name      | lower_bound | value | upper_bound | type  | Initial distribution |
        INFO - 16:56:41:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:41:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:41:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:41:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:41:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:41:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:41:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:41:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:41:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:41: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:56:41: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:56:41: ...   1%|          | 1/100 [00:00<00:01, 66.19 it/sec, obj=0.5]
        INFO - 16:56:41: ...   2%|▏         | 2/100 [00:00<00:09, 10.44 it/sec, obj=0.389]
        INFO - 16:56:42: ...   3%|▎         | 3/100 [00:00<00:08, 11.78 it/sec, obj=0.314]
        INFO - 16:56:42: ...   4%|▍         | 4/100 [00:00<00:07, 12.60 it/sec, obj=0.3]
        INFO - 16:56:42: ...   5%|▌         | 5/100 [00:00<00:07, 13.18 it/sec, obj=0.29]
        INFO - 16:56:42: ...   6%|▌         | 6/100 [00:00<00:06, 13.58 it/sec, obj=0.289]
        INFO - 16:56:42: ...   7%|▋         | 7/100 [00:00<00:06, 13.89 it/sec, obj=0.289]
        INFO - 16:56:42: ...   8%|▊         | 8/100 [00:00<00:05, 15.85 it/sec, obj=Not evaluated]
        INFO - 16:56:42: Optimization result:
        INFO - 16:56:42:    Optimizer info:
        INFO - 16:56:42:       Status: None
        INFO - 16:56:42:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:56:42:       Number of calls to the objective function by the optimizer: 8
        INFO - 16:56:42:    Solution:
        INFO - 16:56:42:       The solution is feasible.
        INFO - 16:56:42:       Objective: 0.28903317159094793
        INFO - 16:56:42:       Standardized constraints:
        INFO - 16:56:42:          cstr_0 + offset = [-1.59418542e+00 -1.77635684e-15 -2.20075451e+01]
        INFO - 16:56:42:          cstr_1 + offset = [-0.62818923 -1.7413806  -1.62123925]
        INFO - 16:56:42:       +--------------------------------------------------------------------------------------------+
        INFO - 16:56:42:       |                                      Parameter space                                       |
        INFO - 16:56:42:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:42:       | name      | lower_bound |        value        | upper_bound | type  | Initial distribution |
        INFO - 16:56:42:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:42:       | x_local_0 |      0      |  0.801127355733839  |      1      | float |                      |
        INFO - 16:56:42:       | x_local_0 |      0      |  0.6239177332508217 |      1      | float |                      |
        INFO - 16:56:42:       | x_local_1 |      0      |          1          |      1      | float |                      |
        INFO - 16:56:42:       | x_local_1 |      0      |          1          |      1      | float |                      |
        INFO - 16:56:42:       | x_shared  |      0      | 0.07024612283000739 |      1      | float |                      |
        INFO - 16:56:42:       | x_shared  |      0      |  0.1762493157624942 |      1      | float |                      |
        INFO - 16:56:42:       | x_shared  |      0      |  0.1499619831353362 |      1      | float |                      |
        INFO - 16:56:42:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:42: *** End MDOScenario execution (time: 0:00:00.520738) ***
        INFO - 16:56:43: Generating HTML XDSM file in : results/coupling/MDF_xdsm.html
        INFO - 16:56:45: Make the starting point feasible.
        INFO - 16:56:45:  
        INFO - 16:56:45: *** Start MDOScenario execution ***
        INFO - 16:56:45: MDOScenario
        INFO - 16:56:45:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:56:45:    MDO formulation: IDF
        INFO - 16:56:45: Optimization problem:
        INFO - 16:56:45:    minimize obj(x_shared, y_0, y_1)
        INFO - 16:56:45:    with respect to x_local_0, x_local_1, x_shared, y_0, y_1
        INFO - 16:56:45:    subject to constraints:
        INFO - 16:56:45:       cstr_0(x_shared, y_0, y_1) <= [ 0.65250671  0.23093826 -4.16343355]
        INFO - 16:56:45:       cstr_1(x_shared, y_0, y_1) <= [ 0.85268891 -1.36263503  0.62341835]
        INFO - 16:56:45:       y_0: y_0(x_local_0, x_shared, y_1): y_0(x_local_0, x_shared, y_1) - y_0 == 0.0
        INFO - 16:56:45:       y_1: y_1(x_local_1, x_shared, y_0): y_1(x_local_1, x_shared, y_0) - y_1 == 0.0
        INFO - 16:56:45:    over the design space:
        INFO - 16:56:45:    |                               Parameter space                                |
        INFO - 16:56:45:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:45:    | name      | lower_bound | value | upper_bound | type  | Initial distribution |
        INFO - 16:56:45:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:45:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | y_0       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | y_0       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | y_0       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | y_1       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | y_1       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    | y_1       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:45:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:45: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:56:45: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:56:45: ...   1%|          | 1/100 [00:00<00:00, 1026.51 it/sec, obj=0.5]
        INFO - 16:56:45: ...   2%|▏         | 2/100 [00:00<00:00, 145.18 it/sec, obj=0.385]
        INFO - 16:56:45: ...   3%|▎         | 3/100 [00:00<00:00, 148.61 it/sec, obj=0.27]
        INFO - 16:56:45: ...   4%|▍         | 4/100 [00:00<00:00, 151.87 it/sec, obj=0.262]
        INFO - 16:56:45: ...   5%|▌         | 5/100 [00:00<00:00, 152.94 it/sec, obj=0.257]
        INFO - 16:56:45: ...   6%|▌         | 6/100 [00:00<00:00, 154.82 it/sec, obj=0.252]
        INFO - 16:56:45: ...   7%|▋         | 7/100 [00:00<00:00, 155.25 it/sec, obj=0.251]
        INFO - 16:56:45: ...   8%|▊         | 8/100 [00:00<00:00, 156.38 it/sec, obj=0.251]
        INFO - 16:56:45: ...   9%|▉         | 9/100 [00:00<00:00, 156.58 it/sec, obj=0.251]
        INFO - 16:56:45: ...  10%|█         | 10/100 [00:00<00:00, 171.46 it/sec, obj=Not evaluated]
        INFO - 16:56:45: Optimization result:
        INFO - 16:56:45:    Optimizer info:
        INFO - 16:56:45:       Status: None
        INFO - 16:56:45:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:56:45:       Number of calls to the objective function by the optimizer: 10
        INFO - 16:56:45:    Solution:
        INFO - 16:56:45:       The solution is feasible.
        INFO - 16:56:45:       Objective: 0.2505909523154283
        INFO - 16:56:45:       Standardized constraints:
        INFO - 16:56:45:          cstr_0 + offset = [ -1.27965363  -2.31226949 -19.05735903]
        INFO - 16:56:45:          cstr_1 + offset = [-0.59186125  0.         -1.52367146]
        INFO - 16:56:45:          y_0 = [ 5.55111512e-17  0.00000000e+00 -5.55111512e-17]
        INFO - 16:56:45:          y_1 = [ 1.11022302e-16 -5.55111512e-17 -1.11022302e-16]
        INFO - 16:56:45:       +--------------------------------------------------------------------------------------------+
        INFO - 16:56:45:       |                                      Parameter space                                       |
        INFO - 16:56:45:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:45:       | name      | lower_bound |        value        | upper_bound | type  | Initial distribution |
        INFO - 16:56:45:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:45:       | x_local_0 |      0      |  0.9999999999999999 |      1      | float |                      |
        INFO - 16:56:45:       | x_local_0 |      0      |          1          |      1      | float |                      |
        INFO - 16:56:45:       | x_local_1 |      0      |  0.9999999999999999 |      1      | float |                      |
        INFO - 16:56:45:       | x_local_1 |      0      |  0.7594082578802717 |      1      | float |                      |
        INFO - 16:56:45:       | x_shared  |      0      |  0.1558252960698979 |      1      | float |                      |
        INFO - 16:56:45:       | x_shared  |      0      |  0.2044810243675251 |      1      | float |                      |
        INFO - 16:56:45:       | x_shared  |      0      | 0.08695435101337673 |      1      | float |                      |
        INFO - 16:56:45:       | y_0       |      0      |  0.4682527561624886 |      1      | float |                      |
        INFO - 16:56:45:       | y_0       |      0      |   0.40066110028851  |      1      | float |                      |
        INFO - 16:56:45:       | y_0       |      0      |  0.4690830695053916 |      1      | float |                      |
        INFO - 16:56:45:       | y_1       |      0      |  0.5017764477639917 |      1      | float |                      |
        INFO - 16:56:45:       | y_1       |      0      |         0.5         |      1      | float |                      |
        INFO - 16:56:45:       | y_1       |      0      |  0.5046058665567719 |      1      | float |                      |
        INFO - 16:56:45:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:45: *** End MDOScenario execution (time: 0:00:00.078866) ***
        INFO - 16:56:47: Generating HTML XDSM file in : results/coupling/IDF_xdsm.html

    {'x_opt': array([1.        , 1.        , 1.        , 0.75940826, 0.1558253 ,
           0.20448102, 0.08695435, 0.46825276, 0.4006611 , 0.46908307,
           0.50177645, 0.5       , 0.50460587]), 'f_opt': 0.2505909523154283, 'status': None, 'n_iter': 62, 'is_feas': True, 'exec_time': 0.0789481120000346}



.. GENERATED FROM PYTHON SOURCE LINES 274-275

We can look at the result in the console:

.. GENERATED FROM PYTHON SOURCE LINES 275-277

.. code-block:: default

    print(study)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Scalable study
    .... 2 disciplines
    .... 3 shared design parameters
    .... 2 local design parameters per discipline
    .... 3 coupling variables per discipline
    MDO formulations
    .... MDF
    ........ MainModel = 10 calls / 8 linearizations / 0.0019797660006588558 seconds
    ........ SubModel_0 = 147 calls / 8 linearizations / 0.01275821499984886 seconds
    ........ SubModel_1 = 139 calls / 8 linearizations / 0.011692841007061361 seconds
    ........ mda = 8 calls / 8 linearizations / 0.47214829299991834 seconds
    ........ mdo_chain = 8 calls / 0 linearizations / 0.10213971200028027 seconds
    ........ sub_mda = 8 calls / 0 linearizations / 0.09416592600246076 seconds
    ........ scenario = 1 calls / 0 linearizations / 0.5208088700001099 seconds
    .... IDF
    ........ MainModel = 12 calls / 10 linearizations / 0.0022795539998696768 seconds
    ........ SubModel_0 = 11 calls / 9 linearizations / 0.0018025740000666701 seconds
    ........ SubModel_1 = 11 calls / 9 linearizations / 0.0017692370010990999 seconds
    ........ mda = 0 calls / 0 linearizations / 0.0 seconds
    ........ mdo_chain = 0 calls / 0 linearizations / 0.0 seconds
    ........ sub_mda = 0 calls / 0 linearizations / 0.0 seconds
    ........ scenario = 1 calls / 0 linearizations / 0.0789481120000346 seconds




.. GENERATED FROM PYTHON SOURCE LINES 278-303

.. code-block:: console

   Scalable study
   > 2 disciplines
   > 3 shared design parameters
   > 2 local design parameters per discipline
   > 3 coupling variables per discipline

   MDO formulations
   > MDF
      >> TM_System = 9 calls / 7 linearizations / 3.29e-03 seconds
      >> TM_Discipline_0 = 132 calls / 7 linearizations / 2.19e-02 seconds
      >> TM_Discipline_1 = 124 calls / 7 linearizations / 2.04e-02 seconds
      >> mda = 7 calls / 7 linearizations / 2.68e-01 seconds
      >> mdo_chain = 7 calls / 0 linearizations / 1.20e-01 seconds
      >> sub_mda = 7 calls / 0 linearizations / 1.16e-01 seconds
      >> scenario = 1 calls / 0 linearizations / 3.35e-01 seconds
   > IDF
      >> TM_System = 12 calls / 9 linearizations / 2.98e-03 seconds
      >> TM_Discipline_0 = 12 calls / 9 linearizations / 2.19e-03 seconds
      >> TM_Discipline_1 = 11 calls / 9 linearizations / 2.01e-03 seconds
      >> mda = 0 calls / 0 linearizations / 0.00e+00 seconds
      >> mdo_chain = 0 calls / 0 linearizations / 0.00e+00 seconds
      >> sub_mda = 0 calls / 0 linearizations / 0.00e+00 seconds
      >> scenario = 1 calls / 0 linearizations / 7.60e-02 seconds

.. GENERATED FROM PYTHON SOURCE LINES 305-306

or plot the execution time:

.. GENERATED FROM PYTHON SOURCE LINES 306-308

.. code-block:: default

    study.plot_exec_time()




.. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_004.png
   :alt: scalable tm
   :srcset: /examples/scalable/images/sphx_glr_scalable_tm_004.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 309-310

.. image:: /_images/scalable_tm/exec_time.png

.. GENERATED FROM PYTHON SOURCE LINES 312-321

Parametric scalability study
----------------------------
We define a parametric scalability study
based on two strongly coupled disciplines
and a weakly one, with the following properties:

- 3 shared design parameters,
- 2 coupling variables for each strongly coupled discipline,
- 1, 5 or 25 local design parameters for each strongly coupled discipline,

.. GENERATED FROM PYTHON SOURCE LINES 321-324

.. code-block:: default

    study = TMParamSS(n_disciplines=2, n_shared=3, n_local=[1, 5, 25], n_coupling=2)
    print(study)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Parametric scalable study
    > 2 disciplines
    > 3 shared design parameters
    > 1, 5 or 25 local design parameters per discipline
    > 2 coupling variables per discipline





.. GENERATED FROM PYTHON SOURCE LINES 325-332

.. code-block:: console

   Parametric scalable study
   > 2 disciplines
   > 3 shared design parameters
   > 1, 5 or 25 local design parameters per discipline
   > 2 coupling variables per discipline

.. GENERATED FROM PYTHON SOURCE LINES 334-335

Then, we run MDF and IDF formulations:

.. GENERATED FROM PYTHON SOURCE LINES 335-338

.. code-block:: default

    study.run_formulation("MDF")
    study.run_formulation("IDF")




.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_005.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_005.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_006.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_006.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_007.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_007.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_008.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_008.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_009.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_009.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_010.png
         :alt: scalable tm
         :srcset: /examples/scalable/images/sphx_glr_scalable_tm_010.png
         :class: sphx-glr-multi-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

        INFO - 16:56:50: Make the starting point feasible.
        INFO - 16:56:50:  
        INFO - 16:56:50: *** Start MDOScenario execution ***
        INFO - 16:56:50: MDOScenario
        INFO - 16:56:50:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:56:50:    MDO formulation: MDF
        INFO - 16:56:50: Optimization problem:
        INFO - 16:56:50:    minimize obj(x_local_0, x_local_1, x_shared)
        INFO - 16:56:50:    with respect to x_local_0, x_local_1, x_shared
        INFO - 16:56:50:    subject to constraints:
        INFO - 16:56:50:       cstr_0(x_local_0, x_local_1, x_shared) <= [0.88589544 0.88821903]
        INFO - 16:56:50:       cstr_1(x_local_0, x_local_1, x_shared) <= [-0.17585898 -1.56050583]
        INFO - 16:56:50:    over the design space:
        INFO - 16:56:50:    |                               Parameter space                                |
        INFO - 16:56:50:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:50:    | name      | lower_bound | value | upper_bound | type  | Initial distribution |
        INFO - 16:56:50:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:50:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:50:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:50:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:50:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:50:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:50:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:50: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:56:50: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:56:50: ...   1%|          | 1/100 [00:00<00:01, 70.90 it/sec, obj=0.5]
     WARNING - 16:56:50: MDAGaussSeidel has reached its maximum number of iterations but the normed residual 1.3486125443736518e-14 is still above the tolerance 1e-14.
        INFO - 16:56:50: ...   2%|▏         | 2/100 [00:00<00:07, 13.33 it/sec, obj=0.453]
        INFO - 16:56:50: ...   3%|▎         | 3/100 [00:00<00:06, 14.94 it/sec, obj=0.41]
     WARNING - 16:56:50: MDAGaussSeidel has reached its maximum number of iterations but the normed residual 1.0303264460093434e-14 is still above the tolerance 1e-14.
        INFO - 16:56:50: ...   4%|▍         | 4/100 [00:00<00:06, 15.86 it/sec, obj=0.396]
     WARNING - 16:56:50: MDAGaussSeidel has reached its maximum number of iterations but the normed residual 1.221308406312274e-14 is still above the tolerance 1e-14.
        INFO - 16:56:50: ...   5%|▌         | 5/100 [00:00<00:05, 16.47 it/sec, obj=0.384]
     WARNING - 16:56:50: MDAGaussSeidel has reached its maximum number of iterations but the normed residual 1.0624260076854628e-14 is still above the tolerance 1e-14.
        INFO - 16:56:50: ...   6%|▌         | 6/100 [00:00<00:05, 16.89 it/sec, obj=0.381]
     WARNING - 16:56:50: MDAGaussSeidel has reached its maximum number of iterations but the normed residual 1.1319239632249289e-14 is still above the tolerance 1e-14.
        INFO - 16:56:50: ...   7%|▋         | 7/100 [00:00<00:05, 17.21 it/sec, obj=0.381]
        INFO - 16:56:50: ...   8%|▊         | 8/100 [00:00<00:04, 19.63 it/sec, obj=Not evaluated]
        INFO - 16:56:50: Optimization result:
        INFO - 16:56:50:    Optimizer info:
        INFO - 16:56:50:       Status: None
        INFO - 16:56:50:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:56:50:       Number of calls to the objective function by the optimizer: 8
        INFO - 16:56:50:    Solution:
        INFO - 16:56:50:       The solution is feasible.
        INFO - 16:56:50:       Objective: 0.3805071026441499
        INFO - 16:56:50:       Standardized constraints:
        INFO - 16:56:50:          cstr_0 + offset = [-0.41404086 -0.37054477]
        INFO - 16:56:50:          cstr_1 + offset = [ -4.10330374 -10.67148731]
        INFO - 16:56:50:       +-------------------------------------------------------------------------------------------+
        INFO - 16:56:50:       |                                      Parameter space                                      |
        INFO - 16:56:50:       +-----------+-------------+--------------------+-------------+-------+----------------------+
        INFO - 16:56:50:       | name      | lower_bound |       value        | upper_bound | type  | Initial distribution |
        INFO - 16:56:50:       +-----------+-------------+--------------------+-------------+-------+----------------------+
        INFO - 16:56:50:       | x_local_0 |      0      |         1          |      1      | float |                      |
        INFO - 16:56:50:       | x_local_1 |      0      |         1          |      1      | float |                      |
        INFO - 16:56:50:       | x_shared  |      0      | 0.4316204495066337 |      1      | float |                      |
        INFO - 16:56:50:       | x_shared  |      0      | 0.5112660072459285 |      1      | float |                      |
        INFO - 16:56:50:       | x_shared  |      0      | 0.2050544622846011 |      1      | float |                      |
        INFO - 16:56:50:       +-----------+-------------+--------------------+-------------+-------+----------------------+
        INFO - 16:56:50: *** End MDOScenario execution (time: 0:00:00.422275) ***
        INFO - 16:56:52: Generating HTML XDSM file in : results/coupling/MDF_xdsm.html
        INFO - 16:56:54: Make the starting point feasible.
        INFO - 16:56:54:  
        INFO - 16:56:54: *** Start MDOScenario execution ***
        INFO - 16:56:54: MDOScenario
        INFO - 16:56:54:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:56:54:    MDO formulation: MDF
        INFO - 16:56:54: Optimization problem:
        INFO - 16:56:54:    minimize obj(x_local_0, x_local_1, x_shared)
        INFO - 16:56:54:    with respect to x_local_0, x_local_1, x_shared
        INFO - 16:56:54:    subject to constraints:
        INFO - 16:56:54:       cstr_0(x_local_0, x_local_1, x_shared) <= [0.89887356 0.86633976]
        INFO - 16:56:54:       cstr_1(x_local_0, x_local_1, x_shared) <= [0.64342256 0.87330214]
        INFO - 16:56:54:    over the design space:
        INFO - 16:56:54:    |                               Parameter space                                |
        INFO - 16:56:54:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:54:    | name      | lower_bound | value | upper_bound | type  | Initial distribution |
        INFO - 16:56:54:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:54:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:56:54:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:56:54: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:56:54: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:56:54: ...   1%|          | 1/100 [00:00<00:01, 73.11 it/sec, obj=0.5]
        INFO - 16:56:54: ...   2%|▏         | 2/100 [00:00<00:06, 14.46 it/sec, obj=0.368]
        INFO - 16:56:54: ...   3%|▎         | 3/100 [00:00<00:05, 16.41 it/sec, obj=0.26]
        INFO - 16:56:54: ...   4%|▍         | 4/100 [00:00<00:05, 17.47 it/sec, obj=0.196]
        INFO - 16:56:54: ...   5%|▌         | 5/100 [00:00<00:05, 18.23 it/sec, obj=0.175]
        INFO - 16:56:54: ...   6%|▌         | 6/100 [00:00<00:05, 18.74 it/sec, obj=0.159]
        INFO - 16:56:54: ...   7%|▋         | 7/100 [00:00<00:04, 19.13 it/sec, obj=0.151]
        INFO - 16:56:54: ...   8%|▊         | 8/100 [00:00<00:04, 19.45 it/sec, obj=0.145]
        INFO - 16:56:54: ...   9%|▉         | 9/100 [00:00<00:04, 19.70 it/sec, obj=0.143]
        INFO - 16:56:54: ...  10%|█         | 10/100 [00:00<00:04, 19.90 it/sec, obj=0.14]
        INFO - 16:56:55: ...  11%|█         | 11/100 [00:00<00:04, 20.06 it/sec, obj=0.139]
        INFO - 16:56:55: ...  12%|█▏        | 12/100 [00:00<00:04, 20.19 it/sec, obj=0.139]
        INFO - 16:56:55: ...  13%|█▎        | 13/100 [00:00<00:04, 20.31 it/sec, obj=0.139]
        INFO - 16:56:55: ...  14%|█▍        | 14/100 [00:00<00:03, 21.85 it/sec, obj=Not evaluated]
        INFO - 16:56:55: Optimization result:
        INFO - 16:56:55:    Optimizer info:
        INFO - 16:56:55:       Status: None
        INFO - 16:56:55:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:56:55:       Number of calls to the objective function by the optimizer: 14
        INFO - 16:56:55:    Solution:
        INFO - 16:56:55:       The solution is feasible.
        INFO - 16:56:55:       Objective: 0.1385357381285276
        INFO - 16:56:55:       Standardized constraints:
        INFO - 16:56:55:          cstr_0 + offset = [-0.23668859 -0.10569247]
        INFO - 16:56:55:          cstr_1 + offset = [-1.21308758 -0.34258749]
        INFO - 16:56:55:       +--------------------------------------------------------------------------------------------+
        INFO - 16:56:55:       |                                      Parameter space                                       |
        INFO - 16:56:55:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:55:       | name      | lower_bound |        value        | upper_bound | type  | Initial distribution |
        INFO - 16:56:55:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:55:       | x_local_0 |      0      |  0.9999999999999999 |      1      | float |                      |
        INFO - 16:56:55:       | x_local_0 |      0      |          1          |      1      | float |                      |
        INFO - 16:56:55:       | x_local_0 |      0      |          1          |      1      | float |                      |
        INFO - 16:56:55:       | x_local_0 |      0      |  0.9999999999999999 |      1      | float |                      |
        INFO - 16:56:55:       | x_local_0 |      0      |  0.9999999999999999 |      1      | float |                      |
        INFO - 16:56:55:       | x_local_1 |      0      |  0.9999999999999998 |      1      | float |                      |
        INFO - 16:56:55:       | x_local_1 |      0      |          1          |      1      | float |                      |
        INFO - 16:56:55:       | x_local_1 |      0      |          1          |      1      | float |                      |
        INFO - 16:56:55:       | x_local_1 |      0      |  0.9999999999999998 |      1      | float |                      |
        INFO - 16:56:55:       | x_local_1 |      0      |  0.9999999999999998 |      1      | float |                      |
        INFO - 16:56:55:       | x_shared  |      0      |  0.1458505152901145 |      1      | float |                      |
        INFO - 16:56:55:       | x_shared  |      0      |  0.1819162891601797 |      1      | float |                      |
        INFO - 16:56:55:       | x_shared  |      0      | 0.07257747464173495 |      1      | float |                      |
        INFO - 16:56:55:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:56:55: *** End MDOScenario execution (time: 0:00:00.660415) ***
        INFO - 16:56:56: Generating HTML XDSM file in : results/coupling/MDF_xdsm.html
        INFO - 16:56:58: Make the starting point feasible.
        INFO - 16:56:58:  
        INFO - 16:56:58: *** Start MDOScenario execution ***
        INFO - 16:56:58: MDOScenario
        INFO - 16:56:58:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:56:58:    MDO formulation: MDF
        INFO - 16:56:58: Optimization problem:
        INFO - 16:56:58:    minimize obj(x_local_0, x_local_1, x_shared)
        INFO - 16:56:58:    with respect to x_local_0, x_local_1, x_shared
        INFO - 16:56:58:    subject to constraints:
        INFO - 16:56:58:       cstr_0(x_local_0, x_local_1, x_shared) <= [ -4.03014722 -18.07597002]
        INFO - 16:56:58:       cstr_1(x_local_0, x_local_1, x_shared) <= [-2.53275899  0.59384442]
        INFO - 16:56:58: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:56:58: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:56:58: ...   1%|          | 1/100 [00:00<00:01, 70.15 it/sec, obj=0.5]
        INFO - 16:56:59: ...   2%|▏         | 2/100 [00:00<00:06, 14.48 it/sec, obj=0.29]
        INFO - 16:56:59: ...   3%|▎         | 3/100 [00:00<00:05, 16.37 it/sec, obj=0.248]
        INFO - 16:56:59: ...   4%|▍         | 4/100 [00:00<00:05, 17.52 it/sec, obj=0.236]
        INFO - 16:56:59: ...   5%|▌         | 5/100 [00:00<00:05, 18.19 it/sec, obj=0.186]
        INFO - 16:56:59: ...   6%|▌         | 6/100 [00:00<00:05, 18.74 it/sec, obj=0.12]
        INFO - 16:56:59: ...   7%|▋         | 7/100 [00:00<00:04, 19.13 it/sec, obj=0.114]
        INFO - 16:56:59: ...   8%|▊         | 8/100 [00:00<00:04, 19.31 it/sec, obj=0.107]
        INFO - 16:56:59: ...   9%|▉         | 9/100 [00:00<00:04, 19.50 it/sec, obj=0.104]
        INFO - 16:56:59: ...  10%|█         | 10/100 [00:00<00:04, 19.70 it/sec, obj=0.101]
        INFO - 16:56:59: ...  11%|█         | 11/100 [00:00<00:04, 19.86 it/sec, obj=0.0963]
        INFO - 16:56:59: ...  12%|█▏        | 12/100 [00:00<00:04, 19.97 it/sec, obj=0.0942]
        INFO - 16:56:59: ...  13%|█▎        | 13/100 [00:00<00:04, 20.10 it/sec, obj=0.0922]
        INFO - 16:56:59: ...  14%|█▍        | 14/100 [00:00<00:04, 20.20 it/sec, obj=0.0908]
        INFO - 16:56:59: ...  15%|█▌        | 15/100 [00:00<00:04, 20.29 it/sec, obj=0.0901]
        INFO - 16:56:59: ...  16%|█▌        | 16/100 [00:00<00:04, 20.36 it/sec, obj=0.0894]
        INFO - 16:56:59: ...  17%|█▋        | 17/100 [00:00<00:04, 20.41 it/sec, obj=0.0878]
        INFO - 16:56:59: ...  18%|█▊        | 18/100 [00:00<00:04, 20.46 it/sec, obj=0.0867]
        INFO - 16:56:59: ...  19%|█▉        | 19/100 [00:00<00:03, 20.51 it/sec, obj=0.0865]
        INFO - 16:56:59: ...  20%|██        | 20/100 [00:00<00:03, 21.57 it/sec, obj=Not evaluated]
        INFO - 16:56:59: Optimization result:
        INFO - 16:56:59:    Optimizer info:
        INFO - 16:56:59:       Status: None
        INFO - 16:56:59:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:56:59:       Number of calls to the objective function by the optimizer: 20
        INFO - 16:56:59:    Solution:
        INFO - 16:56:59:       The solution is feasible.
        INFO - 16:56:59:       Objective: 0.08650593635886976
        INFO - 16:56:59:       Standardized constraints:
        INFO - 16:56:59:          cstr_0 + offset = [-8.43715914  0.        ]
        INFO - 16:56:59:          cstr_1 + offset = [-6.67439741e-01  4.44089210e-16]
        INFO - 16:56:59: *** End MDOScenario execution (time: 0:00:00.939134) ***
        INFO - 16:57:01: Generating HTML XDSM file in : results/coupling/MDF_xdsm.html
        INFO - 16:57:04: Make the starting point feasible.
        INFO - 16:57:04:  
        INFO - 16:57:04: *** Start MDOScenario execution ***
        INFO - 16:57:04: MDOScenario
        INFO - 16:57:04:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:57:04:    MDO formulation: IDF
        INFO - 16:57:04: Optimization problem:
        INFO - 16:57:04:    minimize obj(x_shared, y_0, y_1)
        INFO - 16:57:04:    with respect to x_local_0, x_local_1, x_shared, y_0, y_1
        INFO - 16:57:04:    subject to constraints:
        INFO - 16:57:04:       cstr_0(x_shared, y_0, y_1) <= [0.88589544 0.88821903]
        INFO - 16:57:04:       cstr_1(x_shared, y_0, y_1) <= [-0.17585898 -1.56050583]
        INFO - 16:57:04:       y_0: y_0(x_local_0, x_shared, y_1): y_0(x_local_0, x_shared, y_1) - y_0 == 0.0
        INFO - 16:57:04:       y_1: y_1(x_local_1, x_shared, y_0): y_1(x_local_1, x_shared, y_0) - y_1 == 0.0
        INFO - 16:57:04:    over the design space:
        INFO - 16:57:04:    |                               Parameter space                                |
        INFO - 16:57:04:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:57:04:    | name      | lower_bound | value | upper_bound | type  | Initial distribution |
        INFO - 16:57:04:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:57:04:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | y_0       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | y_0       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | y_1       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    | y_1       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:04:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:57:04: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:57:04: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:57:04: ...   1%|          | 1/100 [00:00<00:00, 967.99 it/sec, obj=0.5]
        INFO - 16:57:04: ...   2%|▏         | 2/100 [00:00<00:00, 158.68 it/sec, obj=0.453]
        INFO - 16:57:04: ...   3%|▎         | 3/100 [00:00<00:00, 163.23 it/sec, obj=0.41]
        INFO - 16:57:04: ...   4%|▍         | 4/100 [00:00<00:00, 166.66 it/sec, obj=0.396]
        INFO - 16:57:04: ...   5%|▌         | 5/100 [00:00<00:00, 167.67 it/sec, obj=0.385]
        INFO - 16:57:04: ...   6%|▌         | 6/100 [00:00<00:00, 169.58 it/sec, obj=0.381]
        INFO - 16:57:04: ...   7%|▋         | 7/100 [00:00<00:00, 169.93 it/sec, obj=0.381]
        INFO - 16:57:04: ...   8%|▊         | 8/100 [00:00<00:00, 190.28 it/sec, obj=Not evaluated]
        INFO - 16:57:04: Optimization result:
        INFO - 16:57:04:    Optimizer info:
        INFO - 16:57:04:       Status: None
        INFO - 16:57:04:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:57:04:       Number of calls to the objective function by the optimizer: 8
        INFO - 16:57:04:    Solution:
        INFO - 16:57:04:       The solution is feasible.
        INFO - 16:57:04:       Objective: 0.3805016326090851
        INFO - 16:57:04:       Standardized constraints:
        INFO - 16:57:04:          cstr_0 + offset = [-0.4105685  -0.36790752]
        INFO - 16:57:04:          cstr_1 + offset = [ -4.06820466 -10.60696021]
        INFO - 16:57:04:          y_0 = [-5.55111512e-17  5.55111512e-17]
        INFO - 16:57:04:          y_1 = [-1.66533454e-16  0.00000000e+00]
        INFO - 16:57:04:       +-------------------------------------------------------------------------------------------+
        INFO - 16:57:04:       |                                      Parameter space                                      |
        INFO - 16:57:04:       +-----------+-------------+--------------------+-------------+-------+----------------------+
        INFO - 16:57:04:       | name      | lower_bound |       value        | upper_bound | type  | Initial distribution |
        INFO - 16:57:04:       +-----------+-------------+--------------------+-------------+-------+----------------------+
        INFO - 16:57:04:       | x_local_0 |      0      |         1          |      1      | float |                      |
        INFO - 16:57:04:       | x_local_1 |      0      |         1          |      1      | float |                      |
        INFO - 16:57:04:       | x_shared  |      0      | 0.4349840014945803 |      1      | float |                      |
        INFO - 16:57:04:       | x_shared  |      0      | 0.5153341160240119 |      1      | float |                      |
        INFO - 16:57:04:       | x_shared  |      0      |  0.20620547934211  |      1      | float |                      |
        INFO - 16:57:04:       | y_0       |      0      | 0.4598177788198944 |      1      | float |                      |
        INFO - 16:57:04:       | y_0       |      0      | 0.4291325171427605 |      1      | float |                      |
        INFO - 16:57:04:       | y_1       |      0      | 0.4459772572294342 |      1      | float |                      |
        INFO - 16:57:04:       | y_1       |      0      | 0.5142525316178621 |      1      | float |                      |
        INFO - 16:57:04:       +-----------+-------------+--------------------+-------------+-------+----------------------+
        INFO - 16:57:04: *** End MDOScenario execution (time: 0:00:00.060084) ***
        INFO - 16:57:05: Generating HTML XDSM file in : results/coupling/IDF_xdsm.html
        INFO - 16:57:08: Make the starting point feasible.
        INFO - 16:57:08:  
        INFO - 16:57:08: *** Start MDOScenario execution ***
        INFO - 16:57:08: MDOScenario
        INFO - 16:57:08:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:57:08:    MDO formulation: IDF
        INFO - 16:57:08: Optimization problem:
        INFO - 16:57:08:    minimize obj(x_shared, y_0, y_1)
        INFO - 16:57:08:    with respect to x_local_0, x_local_1, x_shared, y_0, y_1
        INFO - 16:57:08:    subject to constraints:
        INFO - 16:57:08:       cstr_0(x_shared, y_0, y_1) <= [0.89887356 0.86633976]
        INFO - 16:57:08:       cstr_1(x_shared, y_0, y_1) <= [-0.78288719  0.87330214]
        INFO - 16:57:08:       y_0: y_0(x_local_0, x_shared, y_1): y_0(x_local_0, x_shared, y_1) - y_0 == 0.0
        INFO - 16:57:08:       y_1: y_1(x_local_1, x_shared, y_0): y_1(x_local_1, x_shared, y_0) - y_1 == 0.0
        INFO - 16:57:08:    over the design space:
        INFO - 16:57:08:    |                               Parameter space                                |
        INFO - 16:57:08:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:57:08:    | name      | lower_bound | value | upper_bound | type  | Initial distribution |
        INFO - 16:57:08:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:57:08:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_0 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_local_1 |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | x_shared  |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | y_0       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | y_0       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | y_1       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    | y_1       |      0      |  0.5  |      1      | float |                      |
        INFO - 16:57:08:    +-----------+-------------+-------+-------------+-------+----------------------+
        INFO - 16:57:08: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:57:08: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:57:08: ...   1%|          | 1/100 [00:00<00:00, 1126.90 it/sec, obj=0.5]
        INFO - 16:57:08: ...   2%|▏         | 2/100 [00:00<00:00, 162.68 it/sec, obj=0.369]
        INFO - 16:57:08: ...   3%|▎         | 3/100 [00:00<00:00, 165.46 it/sec, obj=0.264]
        INFO - 16:57:08: ...   4%|▍         | 4/100 [00:00<00:00, 167.71 it/sec, obj=0.206]
        INFO - 16:57:08: ...   5%|▌         | 5/100 [00:00<00:00, 168.87 it/sec, obj=0.182]
        INFO - 16:57:08: ...   6%|▌         | 6/100 [00:00<00:00, 168.90 it/sec, obj=0.172]
        INFO - 16:57:08: ...   7%|▋         | 7/100 [00:00<00:00, 169.68 it/sec, obj=0.164]
        INFO - 16:57:08: ...   8%|▊         | 8/100 [00:00<00:00, 169.56 it/sec, obj=0.158]
        INFO - 16:57:08: ...   9%|▉         | 9/100 [00:00<00:00, 170.22 it/sec, obj=0.156]
        INFO - 16:57:08: ...  10%|█         | 10/100 [00:00<00:00, 170.13 it/sec, obj=0.156]
        INFO - 16:57:08: ...  11%|█         | 11/100 [00:00<00:00, 170.61 it/sec, obj=0.154]
        INFO - 16:57:08: ...  12%|█▏        | 12/100 [00:00<00:00, 169.90 it/sec, obj=0.154]
        INFO - 16:57:08: ...  13%|█▎        | 13/100 [00:00<00:00, 181.61 it/sec, obj=Not evaluated]
        INFO - 16:57:08: Optimization result:
        INFO - 16:57:08:    Optimizer info:
        INFO - 16:57:08:       Status: None
        INFO - 16:57:08:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:57:08:       Number of calls to the objective function by the optimizer: 13
        INFO - 16:57:08:    Solution:
        INFO - 16:57:08:       The solution is feasible.
        INFO - 16:57:08:       Objective: 0.15383885100886432
        INFO - 16:57:08:       Standardized constraints:
        INFO - 16:57:08:          cstr_0 + offset = [-0.28367339 -0.13418614]
        INFO - 16:57:08:          cstr_1 + offset = [ 0.         -0.39931711]
        INFO - 16:57:08:          y_0 = [5.55111512e-17 1.66533454e-16]
        INFO - 16:57:08:          y_1 = [1.11022302e-16 1.11022302e-16]
        INFO - 16:57:08:       +--------------------------------------------------------------------------------------------+
        INFO - 16:57:08:       |                                      Parameter space                                       |
        INFO - 16:57:08:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:57:08:       | name      | lower_bound |        value        | upper_bound | type  | Initial distribution |
        INFO - 16:57:08:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:57:08:       | x_local_0 |      0      |  0.9999999999999999 |      1      | float |                      |
        INFO - 16:57:08:       | x_local_0 |      0      |          1          |      1      | float |                      |
        INFO - 16:57:08:       | x_local_0 |      0      |          1          |      1      | float |                      |
        INFO - 16:57:08:       | x_local_0 |      0      |          1          |      1      | float |                      |
        INFO - 16:57:08:       | x_local_0 |      0      |          1          |      1      | float |                      |
        INFO - 16:57:08:       | x_local_1 |      0      |          1          |      1      | float |                      |
        INFO - 16:57:08:       | x_local_1 |      0      |  0.9999999999999999 |      1      | float |                      |
        INFO - 16:57:08:       | x_local_1 |      0      |          1          |      1      | float |                      |
        INFO - 16:57:08:       | x_local_1 |      0      |  0.9858563292487739 |      1      | float |                      |
        INFO - 16:57:08:       | x_local_1 |      0      |  0.8952030605001723 |      1      | float |                      |
        INFO - 16:57:08:       | x_shared  |      0      | 0.03908896701511936 |      1      | float |                      |
        INFO - 16:57:08:       | x_shared  |      0      | 0.05509382017067609 |      1      | float |                      |
        INFO - 16:57:08:       | x_shared  |      0      | 0.03828687665187131 |      1      | float |                      |
        INFO - 16:57:08:       | y_0       |      0      |  0.3805135756043002 |      1      | float |                      |
        INFO - 16:57:08:       | y_0       |      0      |  0.2003934597112414 |      1      | float |                      |
        INFO - 16:57:08:       | y_1       |      0      |         0.5         |      1      | float |                      |
        INFO - 16:57:08:       | y_1       |      0      |  0.4151727380322101 |      1      | float |                      |
        INFO - 16:57:08:       +-----------+-------------+---------------------+-------------+-------+----------------------+
        INFO - 16:57:08: *** End MDOScenario execution (time: 0:00:00.094564) ***
        INFO - 16:57:09: Generating HTML XDSM file in : results/coupling/IDF_xdsm.html
        INFO - 16:57:12: Make the starting point feasible.
        INFO - 16:57:12:  
        INFO - 16:57:12: *** Start MDOScenario execution ***
        INFO - 16:57:12: MDOScenario
        INFO - 16:57:12:    Disciplines: MainModel SubModel_0 SubModel_1
        INFO - 16:57:12:    MDO formulation: IDF
        INFO - 16:57:12: Optimization problem:
        INFO - 16:57:12:    minimize obj(x_shared, y_0, y_1)
        INFO - 16:57:12:    with respect to x_local_0, x_local_1, x_shared, y_0, y_1
        INFO - 16:57:12:    subject to constraints:
        INFO - 16:57:12:       cstr_0(x_shared, y_0, y_1) <= [-24.15073611  -2.815194  ]
        INFO - 16:57:12:       cstr_1(x_shared, y_0, y_1) <= [-2.53275899  0.59384442]
        INFO - 16:57:12:       y_0: y_0(x_local_0, x_shared, y_1): y_0(x_local_0, x_shared, y_1) - y_0 == 0.0
        INFO - 16:57:12:       y_1: y_1(x_local_1, x_shared, y_0): y_1(x_local_1, x_shared, y_0) - y_1 == 0.0
        INFO - 16:57:12: Solving optimization problem with algorithm NLOPT_SLSQP:
        INFO - 16:57:12: ...   0%|          | 0/100 [00:00<?, ?it]
        INFO - 16:57:12: ...   1%|          | 1/100 [00:00<00:00, 1055.44 it/sec, obj=0.5]
        INFO - 16:57:12: ...   2%|▏         | 2/100 [00:00<00:00, 127.40 it/sec, obj=0.288]
        INFO - 16:57:12: ...   3%|▎         | 3/100 [00:00<00:00, 129.38 it/sec, obj=0.237]
        INFO - 16:57:12: ...   4%|▍         | 4/100 [00:00<00:00, 130.51 it/sec, obj=0.227]
        INFO - 16:57:12: ...   5%|▌         | 5/100 [00:00<00:00, 130.29 it/sec, obj=0.181]
        INFO - 16:57:12: ...   6%|▌         | 6/100 [00:00<00:00, 129.83 it/sec, obj=0.113]
        INFO - 16:57:12: ...   7%|▋         | 7/100 [00:00<00:00, 128.87 it/sec, obj=0.107]
        INFO - 16:57:12: ...   8%|▊         | 8/100 [00:00<00:00, 127.98 it/sec, obj=0.101]
        INFO - 16:57:12: ...   9%|▉         | 9/100 [00:00<00:00, 127.05 it/sec, obj=0.0948]
        INFO - 16:57:12: ...  10%|█         | 10/100 [00:00<00:00, 126.15 it/sec, obj=0.087]
        INFO - 16:57:12: ...  11%|█         | 11/100 [00:00<00:00, 125.23 it/sec, obj=0.0853]
        INFO - 16:57:12: ...  12%|█▏        | 12/100 [00:00<00:00, 124.53 it/sec, obj=0.0842]
        INFO - 16:57:12: ...  13%|█▎        | 13/100 [00:00<00:00, 124.31 it/sec, obj=0.0825]
        INFO - 16:57:12: ...  14%|█▍        | 14/100 [00:00<00:00, 124.08 it/sec, obj=0.0817]
        INFO - 16:57:12: ...  15%|█▌        | 15/100 [00:00<00:00, 123.75 it/sec, obj=0.0805]
        INFO - 16:57:12: ...  16%|█▌        | 16/100 [00:00<00:00, 123.36 it/sec, obj=0.0802]
        INFO - 16:57:12: ...  17%|█▋        | 17/100 [00:00<00:00, 122.96 it/sec, obj=0.0796]
        INFO - 16:57:12: ...  18%|█▊        | 18/100 [00:00<00:00, 122.45 it/sec, obj=0.0791]
        INFO - 16:57:12: ...  19%|█▉        | 19/100 [00:00<00:00, 122.02 it/sec, obj=0.0786]
        INFO - 16:57:12: ...  20%|██        | 20/100 [00:00<00:00, 121.71 it/sec, obj=0.0784]
        INFO - 16:57:12: ...  21%|██        | 21/100 [00:00<00:00, 126.85 it/sec, obj=Not evaluated]
        INFO - 16:57:12: Optimization result:
        INFO - 16:57:12:    Optimizer info:
        INFO - 16:57:12:       Status: None
        INFO - 16:57:12:       Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver
        INFO - 16:57:12:       Number of calls to the objective function by the optimizer: 21
        INFO - 16:57:12:    Solution:
        INFO - 16:57:12:       The solution is feasible.
        INFO - 16:57:12:       Objective: 0.07837467586318368
        INFO - 16:57:12:       Standardized constraints:
        INFO - 16:57:12:          cstr_0 + offset = [ 0.         -3.92093323]
        INFO - 16:57:12:          cstr_1 + offset = [-3.95598136e-01 -1.11022302e-16]
        INFO - 16:57:12:          y_0 = [ 1.66533454e-16 -2.77555756e-17]
        INFO - 16:57:12:          y_1 = [ 0.00000000e+00 -4.16333634e-17]
        INFO - 16:57:12: *** End MDOScenario execution (time: 0:00:00.177320) ***
        INFO - 16:57:14: Generating HTML XDSM file in : results/coupling/IDF_xdsm.html




.. GENERATED FROM PYTHON SOURCE LINES 339-340

and save the results in a pickle file:

.. GENERATED FROM PYTHON SOURCE LINES 340-342

.. code-block:: default

    study.save("results.pkl")








.. GENERATED FROM PYTHON SOURCE LINES 343-345

We can plot these results and compare MDF and IDF formulations in terms
of execution time for different number of local design variables.

.. GENERATED FROM PYTHON SOURCE LINES 345-348

.. code-block:: default

    results = TMParamSSPost("results.pkl")
    results.plot("Comparison of MDF and IDF formulations")




.. image-sg:: /examples/scalable/images/sphx_glr_scalable_tm_011.png
   :alt: Comparison of MDF and IDF formulations
   :srcset: /examples/scalable/images/sphx_glr_scalable_tm_011.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 349-350

.. image:: /_images/scalable_tm/mdf_idf.png


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  36.285 seconds)


.. _sphx_glr_download_examples_scalable_scalable_tm.py:

.. only:: html

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


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

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

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

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


.. only:: html

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

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