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

.. only:: html

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

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

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

.. _sphx_glr_examples_scenario_plot_gantt_chart.py:


Execution statistics as a Gantt chart
=====================================

When
the global attribute :attr:`.ExecutionStatistics.is_time_stamps_enabled` is ``True``
(default: ``False``),
the global attribute :attr:`.ExecutionStatistics.time_stamps` is
a dictionary of the form ``{name: (initial_time, final_time, is_linearization)}``
to store
the initial and final times of each execution and linearization of each discipline.

The :func:`.create_gantt_chart` function can display this dictionary
in the form of a `Gantt chart <https://en.wikipedia.org/wiki/Gantt_chart>`__.

In this example,
we illustrate the use of this function
on the Sobieski's SSBJ problem.

.. GENERATED FROM PYTHON SOURCE LINES 40-53

.. code-block:: Python


    from __future__ import annotations

    from gemseo import configure_logger
    from gemseo import create_discipline
    from gemseo import create_scenario
    from gemseo.core.execution_statistics import ExecutionStatistics
    from gemseo.post.core.gantt_chart import create_gantt_chart
    from gemseo.problems.mdo.sobieski.core.design_space import SobieskiDesignSpace

    configure_logger()






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

 .. code-block:: none


    <RootLogger root (INFO)>



.. GENERATED FROM PYTHON SOURCE LINES 54-60

Create the scenario
------------------
First, we define the Sobieski's SSBJ problem as a scenario.

For this,
we instantiate the disciplines:

.. GENERATED FROM PYTHON SOURCE LINES 60-67

.. code-block:: Python

    disciplines = create_discipline([
        "SobieskiPropulsion",
        "SobieskiAerodynamics",
        "SobieskiStructure",
        "SobieskiMission",
    ])








.. GENERATED FROM PYTHON SOURCE LINES 68-69

as well as the design space:

.. GENERATED FROM PYTHON SOURCE LINES 69-71

.. code-block:: Python

    design_space = SobieskiDesignSpace()








.. GENERATED FROM PYTHON SOURCE LINES 72-76

Then,
given these disciplines and design space,
we build an MDO scenario using the MDF formulation
in order to maximize the range ``"y_4"`` with respect to the design variables:

.. GENERATED FROM PYTHON SOURCE LINES 76-84

.. code-block:: Python

    scenario = create_scenario(
        disciplines,
        "y_4",
        design_space,
        formulation_name="MDF",
        maximize_objective=True,
    )





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

 .. code-block:: none

     WARNING - 11:42:52: Unsupported feature 'minItems' in JSONGrammar 'SobieskiMission_discipline_output' for property 'y_4' in conversion to SimpleGrammar.
     WARNING - 11:42:52: Unsupported feature 'maxItems' in JSONGrammar 'SobieskiMission_discipline_output' for property 'y_4' in conversion to SimpleGrammar.




.. GENERATED FROM PYTHON SOURCE LINES 85-87

and satisfy the inequality constraints
associated with the outputs ``"g_1"``, ``"g_2"`` and ``"g_3"``:

.. GENERATED FROM PYTHON SOURCE LINES 87-90

.. code-block:: Python

    for constraint in ["g_1", "g_2", "g_3"]:
        scenario.add_constraint(constraint, constraint_type="ineq")








.. GENERATED FROM PYTHON SOURCE LINES 91-96

Execute the scenario
--------------------
By default,
a scenario does *not* produce execution statistics.
We need to enable this *global* mechanism before executing the scenario:

.. GENERATED FROM PYTHON SOURCE LINES 96-97

.. code-block:: Python

    ExecutionStatistics.is_time_stamps_enabled = True







.. GENERATED FROM PYTHON SOURCE LINES 98-105

.. warning::
   This mechanism is *global*
   and shall be modified from the :class:`.ExecutionStatistics` class
   (not from an :class:`.ExecutionStatistics` instance).

The scenario can now be executed
using the SLSQP optimization algorithm and a maximum of 10 iterations:

.. GENERATED FROM PYTHON SOURCE LINES 105-107

.. code-block:: Python

    scenario.execute(algo_name="SLSQP", max_iter=10)





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

 .. code-block:: none

        INFO - 11:42:52: *** Start MDOScenario execution ***
        INFO - 11:42:52: MDOScenario
        INFO - 11:42:52:    Disciplines: SobieskiAerodynamics SobieskiMission SobieskiPropulsion SobieskiStructure
        INFO - 11:42:52:    MDO formulation: MDF
        INFO - 11:42:52: Optimization problem:
        INFO - 11:42:52:    minimize -y_4(x_shared, x_1, x_2, x_3)
        INFO - 11:42:52:    with respect to x_1, x_2, x_3, x_shared
        INFO - 11:42:52:    subject to constraints:
        INFO - 11:42:52:       g_1(x_shared, x_1, x_2, x_3) <= 0
        INFO - 11:42:52:       g_2(x_shared, x_1, x_2, x_3) <= 0
        INFO - 11:42:52:       g_3(x_shared, x_1, x_2, x_3) <= 0
        INFO - 11:42:52:    over the design space:
        INFO - 11:42:52:       +-------------+-------------+-------+-------------+-------+
        INFO - 11:42:52:       | Name        | Lower bound | Value | Upper bound | Type  |
        INFO - 11:42:52:       +-------------+-------------+-------+-------------+-------+
        INFO - 11:42:52:       | x_shared[0] |     0.01    |  0.05 |     0.09    | float |
        INFO - 11:42:52:       | x_shared[1] |    30000    | 45000 |    60000    | float |
        INFO - 11:42:52:       | x_shared[2] |     1.4     |  1.6  |     1.8     | float |
        INFO - 11:42:52:       | x_shared[3] |     2.5     |  5.5  |     8.5     | float |
        INFO - 11:42:52:       | x_shared[4] |      40     |   55  |      70     | float |
        INFO - 11:42:52:       | x_shared[5] |     500     |  1000 |     1500    | float |
        INFO - 11:42:52:       | x_1[0]      |     0.1     |  0.25 |     0.4     | float |
        INFO - 11:42:52:       | x_1[1]      |     0.75    |   1   |     1.25    | float |
        INFO - 11:42:52:       | x_2         |     0.75    |   1   |     1.25    | float |
        INFO - 11:42:52:       | x_3         |     0.1     |  0.5  |      1      | float |
        INFO - 11:42:52:       +-------------+-------------+-------+-------------+-------+
        INFO - 11:42:52: Solving optimization problem with algorithm SLSQP:
        INFO - 11:42:52:     10%|█         | 1/10 [00:00<00:01,  8.05 it/sec, obj=-536]
        INFO - 11:42:52:     20%|██        | 2/10 [00:00<00:01,  6.36 it/sec, obj=-2.12e+3]
     WARNING - 11:42:52: MDAJacobi has reached its maximum number of iterations, but the normalized residual norm 5.741449586530469e-06 is still above the tolerance 1e-06.
        INFO - 11:42:52:     30%|███       | 3/10 [00:00<00:01,  5.12 it/sec, obj=-3.46e+3]
        INFO - 11:42:53:     40%|████      | 4/10 [00:00<00:01,  4.89 it/sec, obj=-3.96e+3]
        INFO - 11:42:53:     50%|█████     | 5/10 [00:00<00:00,  5.04 it/sec, obj=-4.61e+3]
        INFO - 11:42:53:     60%|██████    | 6/10 [00:01<00:00,  5.25 it/sec, obj=-4.5e+3]
        INFO - 11:42:53:     70%|███████   | 7/10 [00:01<00:00,  5.31 it/sec, obj=-4.26e+3]
        INFO - 11:42:53:     80%|████████  | 8/10 [00:01<00:00,  5.36 it/sec, obj=-4.11e+3]
        INFO - 11:42:53:     90%|█████████ | 9/10 [00:01<00:00,  5.40 it/sec, obj=-4.02e+3]
        INFO - 11:42:54:    100%|██████████| 10/10 [00:01<00:00,  5.42 it/sec, obj=-3.99e+3]
        INFO - 11:42:54: Optimization result:
        INFO - 11:42:54:    Optimizer info:
        INFO - 11:42:54:       Status: None
        INFO - 11:42:54:       Message: Maximum number of iterations reached. GEMSEO stopped the driver.
        INFO - 11:42:54:       Number of calls to the objective function by the optimizer: 12
        INFO - 11:42:54:    Solution:
        INFO - 11:42:54:       The solution is feasible.
        INFO - 11:42:54:       Objective: -3463.120411437138
        INFO - 11:42:54:       Standardized constraints:
        INFO - 11:42:54:          g_1 = [-0.01112145 -0.02847064 -0.04049911 -0.04878943 -0.05476349 -0.14014207
        INFO - 11:42:54:  -0.09985793]
        INFO - 11:42:54:          g_2 = -0.0020925663903177405
        INFO - 11:42:54:          g_3 = [-0.71359843 -0.28640157 -0.05926796 -0.183255  ]
        INFO - 11:42:54:       Design space:
        INFO - 11:42:54:          +-------------+-------------+---------------------+-------------+-------+
        INFO - 11:42:54:          | Name        | Lower bound |        Value        | Upper bound | Type  |
        INFO - 11:42:54:          +-------------+-------------+---------------------+-------------+-------+
        INFO - 11:42:54:          | x_shared[0] |     0.01    | 0.05947685840242058 |     0.09    | float |
        INFO - 11:42:54:          | x_shared[1] |    30000    |   59246.692998739   |    60000    | float |
        INFO - 11:42:54:          | x_shared[2] |     1.4     |         1.4         |     1.8     | float |
        INFO - 11:42:54:          | x_shared[3] |     2.5     |   2.64097355362077  |     8.5     | float |
        INFO - 11:42:54:          | x_shared[4] |      40     |  69.32144380869019  |      70     | float |
        INFO - 11:42:54:          | x_shared[5] |     500     |  1478.031626737187  |     1500    | float |
        INFO - 11:42:54:          | x_1[0]      |     0.1     |         0.4         |     0.4     | float |
        INFO - 11:42:54:          | x_1[1]      |     0.75    |  0.7608797907508461 |     1.25    | float |
        INFO - 11:42:54:          | x_2         |     0.75    |  0.7607584987262048 |     1.25    | float |
        INFO - 11:42:54:          | x_3         |     0.1     |  0.1514057659459843 |      1      | float |
        INFO - 11:42:54:          +-------------+-------------+---------------------+-------------+-------+
        INFO - 11:42:54: *** End MDOScenario execution (time: 0:00:01.851873) ***




.. GENERATED FROM PYTHON SOURCE LINES 108-119

.. seealso::
   The formulation settings passed to :func:`.create_scenario`
   and the algorithm settings passed to :meth:`.BaseScenario.execute`
   can be provided via Pydantic models.
   For more information,
   see :ref:`algorithm_settings` and :ref:`formulation_settings`.

Plot the Gantt chart
--------------------
Lastly,
we plot the Gantt chart from the global :attr:`.ExecutionStatistics.time_stamps`:

.. GENERATED FROM PYTHON SOURCE LINES 119-120

.. code-block:: Python

    create_gantt_chart(save=False, show=True)



.. image-sg:: /examples/scenario/images/sphx_glr_plot_gantt_chart_001.png
   :alt: Execution (blue) and linearization (red) of the disciplines
   :srcset: /examples/scenario/images/sphx_glr_plot_gantt_chart_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    <Figure size 1500x1000 with 1 Axes>



.. GENERATED FROM PYTHON SOURCE LINES 121-128

This graph shows the evolution over time:

- the execution and linearizations of the different user disciplines,
  *e.g.* :class:`~gemseo.problems.mdo.sobieski.disciplines.SobieskiAerodynamics`,
- the execution and linearizations of the different process disciplines,
  *e.g.* :class:`.MDAJacobi`,
- the execution of the scenario.

.. GENERATED FROM PYTHON SOURCE LINES 130-134

Disable recording
-----------------
Finally,
we disable the recording of time stamps for other executions:

.. GENERATED FROM PYTHON SOURCE LINES 134-135

.. code-block:: Python

    ExecutionStatistics.is_time_stamps_enabled = False







.. GENERATED FROM PYTHON SOURCE LINES 136-142

.. note::
   As this reset :attr:`.ExecutionStatistics.time_stamps` to ``None``,
   the :func:`.create_gantt_chart` function can no longer be used.
   Set :attr:`.ExecutionStatistics.is_time_stamps_enabled` to ``True``
   and execute or linearize some disciplines
   so that you can use it again.


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

   **Total running time of the script:** (0 minutes 2.121 seconds)


.. _sphx_glr_download_examples_scenario_plot_gantt_chart.py:

.. only:: html

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

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

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_gantt_chart.zip <plot_gantt_chart.zip>`


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