Miscellaneous data generators for unittests and demos
Functions
| autocorrelated_noise(ds, sr, cutoff[, lfnl, ...]) | Generate a dataset with samples being temporally autocorrelated noise. |
| chirp_linear(n_instances[, n_features, ...]) | Generates simple dataset for linear regressions |
| dumb_feature_binary_dataset() | Very simple binary (2 labels) dataset |
| dumb_feature_dataset() | Create a very simple dataset with 2 features and 3 labels |
| get_mv_pattern(s2n) | Simple multivariate dataset |
| linear1d_gaussian_noise([size, slope, ...]) | A straight line with some Gaussian noise. |
| linear_awgn([size, intercept, slope, ...]) | Generate a dataset from a linear function with AWGN |
| load_datadb_demo_blockfmri([path, roi]) | Loads the block-design demo dataset from PyMVPA dataset DB. |
| load_datadb_tutorial_data([path, roi]) | Loads the block-design demo dataset from PyMVPA dataset DB. |
| load_example_fmri_dataset() | Load minimal fMRI dataset that is shipped with PyMVPA. |
| multiple_chunks(func, n_chunks, *args, **kwargs) | Replicate datasets multiple times raising different chunks |
| noisy_2d_fx(size_per_fx, dfx, sfx, center[, ...]) | Yet another generator of random dataset |
| normal_feature_dataset([perlabel, nlabels, ...]) | Generate a univariate dataset with normal noise and specified means. |
| pure_multivariate_signal(patterns[, ...]) | Create a 2d dataset with a clear multivariate signal, but no univariate information. |
| sin_modulated(n_instances, n_features[, ...]) | Generate a (quite) complex multidimensional non-linear dataset |
| wr1996([size]) | Generate ‘6d robot arm’ dataset (Williams and Rasmussen 1996) |
Classes
| Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |