def _init_w_transforms(data, features):
    """Initialize the mappings (Wi) for the SRM with random orthogonal matrices.

    Parameters
    ----------

    data : list of 2D arrays, element i has shape=[voxels_i, samples]
        Each element in the list contains the fMRI data of one subject.

    features : int
        The number of features in the model.


    Returns
    -------

    w : list of array, element i has shape=[voxels_i, features]
        The initialized orthogonal transforms (mappings) :math:`W_i` for each
        subject.

    voxels : list of int
        A list with the number of voxels per subject.


    Note
    ----

        This function assumes that the numpy random number generator was
        initialized.

        Not thread safe.
    """
    w = []
    subjects = len(data)
    voxels = np.empty(subjects, dtype=int)

    # Set Wi to a random orthogonal voxels by features matrix
    for subject in range(subjects):
        voxels[subject] = data[subject].shape[0]
        rnd_matrix = np.random.random((voxels[subject], features))
        q, r = np.linalg.qr(rnd_matrix)
        w.append(q)

    return w, voxels
Initialize the mappings (Wi) for the SRM with random orthogonal matrices.

    Parameters
    ----------

    data : list of 2D arrays, element i has shape=[voxels_i, samples]
        Each element in the list contains the fMRI data of one subject.

    features : int
        The number of features in the model.


    Returns
    -------

    w : list of array, element i has shape=[voxels_i, features]
        The initialized orthogonal transforms (mappings) :math:`W_i` for each
        subject.

    voxels : list of int
        A list with the number of voxels per subject.


    Note
    ----

        This function assumes that the numpy random number generator was
        initialized.

        Not thread safe.