tick.simulation.features_normal_cov_uniform(n_samples: int = 200, n_features: int = 30, dtype='float64')[source]¶Normal features generator with uniform covariance
An example of features obtained as samples of a centered Gaussian vector with a specific covariance matrix given by 0.5 * (U + U.T), where U is uniform on [0, 1] and diagonal filled by ones.
n_samples : int, default=200
Number of samples
n_features : int, default=30
Number of features
dtype : {'float64', 'float32'}, default=’float64’
Type of the arrays used.
output : numpy.ndarray, shape=(n_samples, n_features)
n_samples realization of a Gaussian vector with the described covariance