gemseo / problems / dataset

Hide inherited members

rosenbrock module

Rosenbrock dataset.

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

\[f(x,y)=(1-x)^2+100(y-x^2)^2\]

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

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

More information about the Rosenbrock function

gemseo.problems.dataset.rosenbrock.create_rosenbrock_dataset(n_samples=100, opt_naming=True, categorize=True)[source]

Rosenbrock dataset parametrization.

Parameters:
  • n_samples (int) –

    The number of samples.

    By default it is set to 100.

  • opt_naming (bool) –

    Whether to use an optimization naming.

    By default it is set to True.

  • categorize (bool) –

    Whether to distinguish between the different groups of variables.

    By default it is set to True.

Returns:

The Rosenbrock dataset.

Return type:

Dataset

Examples using create_rosenbrock_dataset

Calibration of a polynomial regression

Calibration of a polynomial regression