skdim.datasets.BenchmarkManifolds.generate

BenchmarkManifolds.generate(name: str = 'all', n: int = 2500, dim: int = None, d: int = None, noise: float = 0.0)

Generates all datasets. A ground truth dict of intrinsic dimension and embedding dimension is in BenchmarkManifolds.dict_truth.keys()

Parameters:

n : int

The number of sample points

dim : int

If generating a single dataset, choose the embedding dimension. Note that some datasets have restrictions on the chosen embedding dimension

d : int

If generating a single dataset, choose the intrinsic dimension. Note that some datasets have restrictions on the chosen intrinsic dimension

noise : float, optional(default=0.0)

The value of noise in data

Returns:

data (a dict of np.arrays or a single np.array with shape (n, dim)) – Generated data