qbiocode.data_generation.make_spirals module#

Generate synthetic n-dimensional spiral datasets for multi-class classification.

This module creates multiple configurations of high-dimensional spiral datasets with varying sample sizes, noise levels, and dimensionality, useful for testing machine learning algorithms on complex non-linearly separable patterns.

Summary#

Functions:

generate_spirals_datasets

Generate multiple n-dimensional spiral datasets with varying parameters.

make_spirals

Generate an n-dimensional dataset of intertwined spirals.

Reference#

make_spirals(n_samples=5000, n_classes=2, noise=0.3, dim=3)[source]#

Generate an n-dimensional dataset of intertwined spirals.

Creates spiral patterns in n-dimensional space where each class forms a distinct spiral arm. Supports dimensions 3, 6, 9, and 12.

Parameters:

  • n_samples (int, default=5000) – Total number of samples to generate.

  • n_classes (int, default=2) – Number of spiral arms (classes).

  • noise (float, default=0.3) – Standard deviation of Gaussian noise added to each dimension.

  • dim (int, default=3) – Dimensionality of the output space (must be 3, 6, 9, or 12).

Returns:

  • X (ndarray of shape (n_samples, dim)) – Generated spiral data points.

  • y (ndarray of shape (n_samples,)) – Class labels for each sample.

generate_spirals_datasets(n_s=[100, 150, 200, 250], n_c=[2], n_n=[0.3, 0.6, 0.9], n_d=[3, 6, 9, 12], save_path=None, random_state=42)[source]#

Generate multiple n-dimensional spiral datasets with varying parameters.

Creates a series of high-dimensional datasets where samples form intertwined spiral patterns, providing challenging non-linearly separable multi-class classification problems. Each configuration varies the number of samples, classes, noise level, and dimensionality.

Parameters:

  • n_s (list of int, default=range(100, 300, 50)) – List of sample sizes to generate for each configuration.

  • n_c (list of int, default=[2]) – List of class counts (number of spiral arms).

  • n_n (list of float, default=[0.3, 0.6, 0.9]) – List of noise standard deviations to apply to the data.

  • n_d (list of int, default=[3, 6, 9, 12]) – List of dimensionalities (must be 3, 6, 9, or 12).

  • save_path (str, optional) – Directory path where datasets and configuration files will be saved.

  • random_state (int, default=42) – Random seed for reproducibility.

Returns:

Saves CSV files for each dataset configuration and a JSON file with all configuration parameters.

Return type:

None

Notes

  • Each dataset is saved as ‘spirals_data-{i}.csv’ where i is the configuration number

  • Configuration parameters are saved in ‘dataset_config.json’

  • The last column ‘class’ contains class labels

  • Spiral patterns become increasingly complex in higher dimensions

Examples

>>> from qbiocode.data_generation import generate_spirals_datasets
>>> generate_spirals_datasets(n_s=[200], n_c=[2], n_n=[0.3], n_d=[3], save_path='data')
Generating spirals dataset...