ad567a1b6694efecf5b52c013b7f507ca57d3df3,dipy/reconst/dti.py,,tensor_prediction,#Any#Any#Any#,655

Before Change

    sphere = Sphere(xyz=gtab.bvecs[~gtab.b0s_mask])
    adc = apparent_diffusion_coef(qform, sphere)

    if isinstance(S0, np.ndarray):
        // If it"s an array, we need to give it one more dimension:
        S0 = S0[..., None]

    // First do the calculation for the diffusion weighted measurements:
    pre_pred_sig = S0 * np.exp(-gtab.bvals[~gtab.b0s_mask] * adc)

    // Then we need to sort out what goes where:
    pred_sig = np.zeros(pre_pred_sig.shape[:-1] + (gtab.bvals.shape[0],))

    // These are the diffusion-weighted values
    pred_sig[..., ~gtab.b0s_mask] = pre_pred_sig

After Change

    del qform

    D = design_matrix(gtab)
    return np.exp(np.dot(lower_tri, D.T))


class TensorModel(ReconstModel):
     Diffusion Tensor

Instances