4f3da275037d4fe3108039fdbfc03b2f81fbee8c,dipy/reconst/dti.py,,ols_fit_tensor,#Any#Any#,1251

Before Change

    
    tol = 1e-6

    data = np.asarray(data)
    data_flat = data.reshape((-1, data.shape[-1]))
    evals = np.empty((len(data_flat), 3))
    evecs = np.empty((len(data_flat), 3, 3))
    dti_params = np.empty((len(data_flat), 4, 3))

    //obtain OLS fitting matrix
    //U,S,V = np.linalg.svd(design_matrix, False)
    //math: beta_ols = inv(X.T*X)*X.T*y
    //math: ols_fit = X*beta_ols*inv(y)
    //ols_fit =  np.dot(U, U.T)

    min_diffusivity = tol / -design_matrix.min()
    inv_design = np.linalg.pinv(design_matrix)

    for param, sig in zip(dti_params, data_flat):
        param[0], param[1:] = _ols_iter(inv_design, sig, min_diffusivity)

    dti_params.shape = data.shape[:-1] + (12,)
    dti_params = dti_params
    return dti_params

After Change

        from_lower_triangular(
            np.einsum("...ij,...j",
                      np.linalg.pinv(design_matrix),
                      np.log(np.asarray(data)))
        ),
        min_diffusivity=tol / -design_matrix.min()
    )

Instances