# Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com
#
# This work is licensed under a BSD 0-Clause License.
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# Contributors:
#    INITIAL AUTHORS - initial API and implementation and/or initial
#                           documentation
#        :author: Matthias De Lozzo
#    OTHER AUTHORS   - MACROSCOPIC CHANGES
"""
Parametric scalable MDO problem - MDF
=====================================
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.

We would like to solve this MDO problem by means of an MDF formulation.
"""
from gemseo.api import configure_logger
from gemseo.api import create_scenario
from gemseo.api import generate_n2_plot
from gemseo.problems.scalable.parametric.problem import TMScalableProblem
from matplotlib import pyplot as plt

configure_logger()

#######################################################################################
# Instantiation of the scalable problem
# -------------------------------------
n_shared = 3
n_local = [2, 4]
n_coupling = [2, 3]
problem = TMScalableProblem(n_shared, n_local, n_coupling)

#######################################################################################
# Display the coupling structure
# ------------------------------
generate_n2_plot(problem.disciplines, save=False, show=True)

#######################################################################################
# Solve the MDO using an MDF formulation
# --------------------------------------
scenario = create_scenario(problem.disciplines, "MDF", "obj", problem.design_space)
scenario.add_constraint("cstr_0", "ineq")
scenario.add_constraint("cstr_1", "ineq")
scenario.execute({"algo": "NLOPT_SLSQP", "max_iter": 100})

#######################################################################################
# Post-process the results
# ------------------------
scenario.post_process("OptHistoryView", save=False, show=False)
# Workaround for HTML rendering, instead of ``show=True``
plt.show()