////// Load data ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
from load_poldrack import load_gain_poldrack
mem = Memory(cachedir="cache", verbose=3)
X, y, _, mask, affine = mem.cache(load_gain_poldrack)(smooth=0)
img_data = np.zeros(list(mask.shape) + [len(X)])
img_data[mask, :] = X.T
// prepare input data for learner
After Change
////// Load data ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
from nilearn.datasets import fetch_mixed_gambles
mem = Memory(cachedir="cache", verbose=3)
data = mem.cache(fetch_mixed_gambles)("data/Jimura_Poldrack_2012_zmaps",
n_subjects=16, make_Xy=True)
X, y, mask_img = data.X, data.y, data.mask_img
// prepare input data for learner
n_samples = len(X)
