mvpa2.testing.datasets

Provides convenience datasets for unittesting.

Also performs testing of storing/reloading datasets into hdf5 file if cfg.getboolean(‘tests’, ‘use hdf datasets’

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
double_gamma_hrf(t[, A1, W1, K1, A2, W2, K2])	Hemodynamic response function model.
dumb_feature_binary_dataset()	Very simple binary (2 labels) dataset
dumb_feature_dataset()	Create a very simple dataset with 2 features and 3 labels
generate_testing_datasets(\*arg, \*\*kwargs)
get_mv_pattern(s2n)	Simple multivariate dataset
get_random_rotation(ns[, nt, data])	Return some random rotation (or rotation + dim reduction) matrix
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 (Added White Gaussian Noise).
local_random_affine_transformations(ds, ...)	Distort a dataset in the local neighborhood of selected features.
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.
pathjoin(a, \*p)	Join two or more pathname components, inserting ‘/’ as needed.
pure_multivariate_signal(patterns[, ...])	Create a 2d dataset with a clear purely multivariate signal.
random_affine_transformation(ds[, ...])	Distort a dataset by random scale, shift, and rotation.
reseed_rng()	Decorator to assure the use of MVPA_SEED while running the test
saveload_warehouse()	Store all warehouse datasets into HDF5 and reload them.
simple_hrf_dataset([events, hrf_gen, ...])	events: list of Events or ndarray of onsets for simple(r) designs
sin_modulated(n_instances, n_features[, ...])	Generate a (quite) complex multidimensional non-linear dataset
single_gamma_hrf(t[, A, W, K])	Hemodynamic response function model.
vstack(datasets[, a, fa])	Stacks datasets vertically (appending samples).
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.
Event(\*\*kwargs)	Simple class to define properties of an event.
HollowSamples([shape, sid, fid, dtype])	Samples container that doesn’t store samples.
IndexQueryEngine([sorted])	Provides efficient query engine for discrete spaces.
OddEvenPartitioner([usevalues])	Create odd and even partitions based on a sample attribute.