Post-processing

In this example, we will discover the different functions of the API related to graphical post-processing of scenarios.

from __future__ import annotations

from gemseo import configure_logger
from gemseo import create_discipline
from gemseo import create_scenario
from gemseo import execute_post
from gemseo import get_available_post_processings
from gemseo import get_post_processing_options_schema
from gemseo.problems.mdo.sellar.sellar_design_space import SellarDesignSpace

configure_logger()
<RootLogger root (INFO)>

Get available DOE algorithms

The get_available_post_processings() function returns the list of post-processing algorithms available in GEMSEO or in external modules

get_available_post_processings()
['Animation', 'BasicHistory', 'Compromise', 'ConstraintsHistory', 'Correlations', 'DataVersusModel', 'GradientSensitivity', 'HighTradeOff', 'MultiObjectiveDiagram', 'ObjConstrHist', 'OptHistoryView', 'ParallelCoordinates', 'ParetoFront', 'Petal', 'QuadApprox', 'Radar', 'RadarChart', 'Robustness', 'SOM', 'ScatterPareto', 'ScatterPlotMatrix', 'TopologyView', 'VariableInfluence']

Get options schema

For a given post-processing algorithm, e.g. "RadarChart", we can get the options; e.g.

get_post_processing_options_schema("RadarChart")
{'$schema': 'http://json-schema.org/draft-04/schema', 'additionalProperties': False, 'type': 'object', 'properties': {'save': {'description': 'If ``True``, save the figure.', 'type': 'boolean'}, 'show': {'description': 'If ``True``, display the figure.', 'type': 'boolean'}, 'file_path': {'anyOf': [{'description': 'The path of the file to save the figures.\nIf the extension is missing, use ``file_extension``.\nIf ``None``,\ncreate a file path\nfrom ``directory_path``, ``file_name`` and ``file_extension``.', 'type': 'string'}, {'description': 'The path of the file to save the figures.\nIf the extension is missing, use ``file_extension``.\nIf ``None``,\ncreate a file path\nfrom ``directory_path``, ``file_name`` and ``file_extension``.', 'type': 'null'}]}, 'file_extension': {'anyOf': [{'description': "A file extension, e.g. 'png', 'pdf', 'svg', ...\nIf ``None``, use a default file extension.", 'type': 'string'}, {'description': "A file extension, e.g. 'png', 'pdf', 'svg', ...\nIf ``None``, use a default file extension.", 'type': 'null'}]}, 'file_name': {'anyOf': [{'description': 'The name of the file to save the figures.\nIf ``None``, use a default one generated by the post-processing.', 'type': 'string'}, {'description': 'The name of the file to save the figures.\nIf ``None``, use a default one generated by the post-processing.', 'type': 'null'}]}, 'directory_path': {'anyOf': [{'description': 'The path of the directory to save the figures.\nIf ``None``, use the current working directory.', 'type': 'string'}, {'description': 'The path of the directory to save the figures.\nIf ``None``, use the current working directory.', 'type': 'null'}]}, 'fig_size': {'anyOf': [{'description': 'The width and height of the figure in inches, e.g. ``(w, h)``.\nIf ``None``, use the :attr:`.OptPostProcessor.DEFAULT_FIG_SIZE`\nof the post-processor.', 'type': 'null'}, {'minItems': 2, 'maxItems': 2, 'description': 'The width and height of the figure in inches, e.g. ``(w, h)``.\nIf ``None``, use the :attr:`.OptPostProcessor.DEFAULT_FIG_SIZE`\nof the post-processor.', 'type': 'array', 'items': {'type': 'number'}}]}, 'iteration': {'anyOf': [{'description': 'Either an iteration in :math:`-N,\\ldots,-1,1,`ldots,N`\nor the tag :attr:`.OPTIMUM` for the iteration\nat which the optimum is located,\nwhere :math:`N` is the length of the database.', 'type': 'integer'}, {'enum': ['opt'], 'description': 'Either an iteration in :math:`-N,\\ldots,-1,1,`ldots,N`\nor the tag :attr:`.OPTIMUM` for the iteration\nat which the optimum is located,\nwhere :math:`N` is the length of the database.', 'type': 'string'}]}, 'constraint_names': {'anyOf': [{'description': 'The names of the constraints.\nIf ``None``, use all the constraints.', 'type': 'null'}, {'description': 'The names of the constraints.\nIf ``None``, use all the constraints.', 'type': 'array', 'items': {'minItems': 1, 'type': 'string'}}]}, 'show_names_radially': {'description': 'Whether to write the names of the constraints\nin the radial direction.\nOtherwise, write them horizontally.\nThe radial direction can be useful for a high number of constraints.', 'type': 'boolean'}}, 'required': []}

Post-process a scenario

The API function execute_post() can generate visualizations of the optimization or DOE results. For that, it consider the object to post-process to_post_proc, the post processing post_name with its **options. E.g.

disciplines = create_discipline(["Sellar1", "Sellar2", "SellarSystem"])
design_space = SellarDesignSpace()
scenario = create_scenario(disciplines, "MDF", "obj", design_space, "SellarMDFScenario")
scenario.execute({"algo": "NLOPT_SLSQP", "max_iter": 100})
execute_post(scenario, "OptHistoryView", save=False, show=True)
  • Evolution of the optimization variables
  • Evolution of the objective value
  • Distance to the optimum
  • Hessian diagonal approximation
/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/develop/lib/python3.9/site-packages/gemseo/algos/design_space.py:467: ComplexWarning: Casting complex values to real discards the imaginary part
  self.__current_value[name] = array_value.astype(
    INFO - 08:56:28:
    INFO - 08:56:28: *** Start SellarMDFScenario execution ***
    INFO - 08:56:28: SellarMDFScenario
    INFO - 08:56:28:    Disciplines: Sellar1 Sellar2 SellarSystem
    INFO - 08:56:28:    MDO formulation: MDF
    INFO - 08:56:28: Optimization problem:
    INFO - 08:56:28:    minimize obj(x_local, x_shared)
    INFO - 08:56:28:    with respect to x_local, x_shared
    INFO - 08:56:28:    over the design space:
    INFO - 08:56:28:       +-------------+-------------+-------+-------------+-------+
    INFO - 08:56:28:       | Name        | Lower bound | Value | Upper bound | Type  |
    INFO - 08:56:28:       +-------------+-------------+-------+-------------+-------+
    INFO - 08:56:28:       | x_local     |      0      |   1   |      10     | float |
    INFO - 08:56:28:       | x_shared[0] |     -10     |   4   |      10     | float |
    INFO - 08:56:28:       | x_shared[1] |      0      |   3   |      10     | float |
    INFO - 08:56:28:       +-------------+-------------+-------+-------------+-------+
    INFO - 08:56:28: Solving optimization problem with algorithm NLOPT_SLSQP:
    INFO - 08:56:28:      1%|          | 1/100 [00:00<00:02, 47.80 it/sec, obj=21.8+0j]
    INFO - 08:56:28:      2%|▏         | 2/100 [00:00<00:02, 32.89 it/sec, obj=101+0j]
    INFO - 08:56:28:      3%|▎         | 3/100 [00:00<00:01, 49.15 it/sec, obj=4.79+0j]
 WARNING - 08:56:28: MDAJacobi has reached its maximum number of iterations but the normed residual 0.021964591272283788 is still above the tolerance 1e-06.
    INFO - 08:56:28:      4%|▍         | 4/100 [00:00<00:03, 31.06 it/sec, obj=0.779-0.0322j]
    INFO - 08:56:28:      5%|▌         | 5/100 [00:00<00:02, 35.71 it/sec, obj=1.81+0j]
    INFO - 08:56:28:      6%|▌         | 6/100 [00:00<00:02, 42.78 it/sec, obj=0.54-4.84e-12j]
    INFO - 08:56:28:      7%|▋         | 7/100 [00:00<00:02, 38.93 it/sec, obj=0.928+0j]
    INFO - 08:56:28:      8%|▊         | 8/100 [00:00<00:02, 44.42 it/sec, obj=0.537+0j]
    INFO - 08:56:28:      9%|▉         | 9/100 [00:00<00:02, 38.71 it/sec, obj=0.527+0j]
    INFO - 08:56:28:     10%|█         | 10/100 [00:00<00:02, 39.57 it/sec, obj=0.527+0j]
    INFO - 08:56:28:     11%|█         | 11/100 [00:00<00:02, 40.16 it/sec, obj=0.527+0j]
   ERROR - 08:56:28: NLopt run failed: NLopt roundoff-limited, RoundoffLimited
Traceback (most recent call last):
  File "/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/develop/lib/python3.9/site-packages/gemseo/algos/opt/lib_nlopt.py", line 498, in _run
    nlopt_problem.optimize(x_0.real)
  File "/home/docs/checkouts/readthedocs.org/user_builds/gemseo/envs/develop/lib/python3.9/site-packages/nlopt/nlopt.py", line 335, in optimize
    return _nlopt.opt_optimize(self, *args)
nlopt.RoundoffLimited: NLopt roundoff-limited
    INFO - 08:56:28:     12%|█▏        | 12/100 [00:00<00:02, 43.59 it/sec, obj=0.527+0j]
    INFO - 08:56:28: Optimization result:
    INFO - 08:56:28:    Optimizer info:
    INFO - 08:56:28:       Status: None
    INFO - 08:56:28:       Message:  GEMSEO Stopped the driver
    INFO - 08:56:28:       Number of calls to the objective function by the optimizer: 16
    INFO - 08:56:28:    Solution:
    INFO - 08:56:28:       Objective: (0.5272881441505544+0j)
    INFO - 08:56:28:       Design space:
    INFO - 08:56:28:          +-------------+-------------+-----------------------+-------------+-------+
    INFO - 08:56:28:          | Name        | Lower bound |         Value         | Upper bound | Type  |
    INFO - 08:56:28:          +-------------+-------------+-----------------------+-------------+-------+
    INFO - 08:56:28:          | x_local     |      0      | 3.264394837503948e-13 |      10     | float |
    INFO - 08:56:28:          | x_shared[0] |     -10     |   0.581639463870145   |      10     | float |
    INFO - 08:56:28:          | x_shared[1] |      0      |           0           |      10     | float |
    INFO - 08:56:28:          +-------------+-------------+-----------------------+-------------+-------+
    INFO - 08:56:28: *** End SellarMDFScenario execution (time: 0:00:00.289152) ***

<gemseo.post.opt_history_view.OptHistoryView object at 0x7f1db20b09a0>

Total running time of the script: (0 minutes 1.080 seconds)

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