def _fit_dipoles(fun, min_dist_to_inner_skull, data, times, guess_rrs,
                 guess_data, fwd_data, whitener, proj_op, ori, n_jobs):
    from scipy.optimize import fmin_cobyla
    parallel, p_fun, _ = parallel_func(fun, n_jobs)
    # parallel over time points
    res = parallel(p_fun(min_dist_to_inner_skull, B, t, guess_rrs,
                         guess_data, fwd_data, whitener, proj_op,
                         fmin_cobyla, ori)
                   for B, t in zip(data.T, times))
    pos = np.array([r[0] for r in res])
    amp = np.array([r[1] for r in res])
    ori = np.array([r[2] for r in res])
    gof = np.array([r[3] for r in res]) * 100  # convert to percentage
    residual = np.array([r[4] for r in res]).T

    return pos, amp, ori, gof, residual
The point of this function is to find a repository on the server that
dataset/ETHPy150Open mne-tools/mne-python/mne/dipole.py/_fit_dipoles--crossover with--dataset/ETHPy150Open reviewboard/rbtools/rbtools/clients/svn.py/SVNRepositoryInfo.find_server_repository_info