peach.pp.generate_synthetic

peach.pp.generate_synthetic#

peach.pp.generate_synthetic(n_points=1000, n_dimensions=50, n_archetypes=4, noise=0.1, *, seed=1205, archetype_type='random', scale=20.0, return_torch=True)[source]#

Generate synthetic convex data for testing.

Parameters:

  • n_points (int, default: 1000) – Number of data points to generate (matches _core parameter)

  • n_dimensions (int, default: 50) – Number of dimensions/features (matches _core parameter)

  • n_archetypes (int, default: 4) – Number of archetypes

  • noise (float, default: 0.1) – Noise level (matches _core parameter)

  • seed (int, default: 1205) – Random seed for reproducibility

  • archetype_type (str, default: "random") – Type of archetype generation (‘random’, ‘corners’, ‘sphere’)

  • scale (float, default: 20.0) – Scale factor for data generation

  • return_torch (bool, default: True) – Whether to return PyTorch tensors

Returns:

Synthetic data with ground truth archetypes in .uns

Return type:

AnnData