ddl.datasets.make_toy_data

ddl.datasets.make_toy_data(data_name, n_samples=1000, random_state=None, **maker_kwargs)[source]

Make simple toy datasets.

Useful for illustrating density destructors.

Parameters:
data_name : str

Should be one of the following strings: {'concentric_circles', 'grid', 'gaussian_grid', 'uniform_grid', 'rotated_uniform', 'autoregressive', 'sin_wave', 'rbig_sin_wave', 'quadratic'}.

n_samples : int, default=1000

Number of samples to make.

random_state : int, RandomState instance or None, optional (default=None)

If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by numpy.random.

maker_kwargs : dict, optional

Other keyword arguments to pass to the associated maker.
Returns:
data : object

Data object with the following attributes:

X : array-like with shape (n_samples, n_features)
y : array-like with shape (n_samples,) or None
is_canonical_domain : bool, whether domain is [0, 1]