Source code for gemseo.problems.dataset.rosenbrock

# -*- coding: utf-8 -*-
# Copyright 2021 IRT Saint Exupéry,
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# Contributors:
#    INITIAL AUTHORS - initial API and implementation and/or initial
#                           documentation
#        :author: Matthias De Lozzo
Rosenbrock dataset

This :class:`.Dataset` contains 100 evaluations
of the well-known Rosenbrock function:

.. math::


This function is known for its global minimum at point (1,1),
its banana valley and the difficulty to reach its minimum.

This :class:`.Dataset` is based on a full-factorial
design of experiments.

`More information about the Rosenbrock function
from __future__ import division, unicode_literals

from numpy import hstack, linspace, meshgrid

from gemseo.core.dataset import Dataset

[docs]class RosenbrockDataset(Dataset): """Rosenbrock dataset parametrization.""" def __init__( self, name="Rosenbrock", by_group=True, n_samples=100, categorize=True, opt_naming=True, ): """Constructor. :param str name: name of the dataset. :param bool by_group: if True, store the data by group. Otherwise, store them by variables. Default: True :param int n_samples: number of samples :param bool categorize: distinguish between the different groups of variables. Default: True. :parma bool opt_naming: use an optimization naming. Default: True. """ super(RosenbrockDataset, self).__init__(name, by_group) root_n_samples = int(n_samples ** 0.5) x_i = linspace(-2.0, 2.0, root_n_samples) x_i, y_i = meshgrid(x_i, x_i) x_i = x_i.reshape((-1, 1)) y_i = y_i.reshape((-1, 1)) z_i = 100 * (y_i - x_i ** 2) ** 2 + (1 - x_i) ** 2 data = hstack((x_i, y_i, z_i)) if categorize: if opt_naming: groups = {"x": Dataset.DESIGN_GROUP, "rosen": Dataset.FUNCTION_GROUP} else: groups = {"x": Dataset.INPUT_GROUP, "rosen": Dataset.OUTPUT_GROUP} else: groups = None self.set_from_array(data, ["x", "rosen"], {"x": 2, "rosen": 1}, groups=groups) self.set_metadata("root_n_samples", root_n_samples)