def interp_corr(locs,
corrs,
width=10,
vox_size=10,
outfile=None,
save_nii=None):
nii = se.load('std', vox_size=vox_size)
full_locs = nii.get_locs().values
W = np.exp(_log_rbf(full_locs, locs, width=width))
interp_corrs = np.dot(corrs, W.T)
bo_nii = se.Brain(data=interp_corrs, locs=full_locs)
nii_bo = _brain_to_nifti(bo_nii, nii)
ni_plt.plot_glass_brain(nii_bo,
colorbar=True,
threshold=None,
vmax=1,
vmin=0)
#ni_plt.plot_glass_brain(nii_bo, colorbar=True, threshold=None, vmax=1, vmin=0, display_mode='lyrz')
if save_nii:
nii_bo.save(save_nii)
if not outfile is None:
plt.savefig(outfile)
else:
plt.show()
def test_log_rbf():
weights = _log_rbf(locs, locs[:10])
assert isinstance(weights, np.ndarray)
assert np.allclose(np.diag(weights), 0)