def METHOD_NAME():
    """Test adding noise from M/EEG float32 (I/O) cov with projectors."""
    # See gh-5940
    evoked = read_evokeds(ave_fname, 0, baseline=(None, 0))
    evoked.info["bads"] = ["MEG 2443"]
    with evoked.info._unlock():
        evoked.info["lowpass"] = 20  # fake for decim
    picks = pick_types(evoked.info, meg=True, eeg=False)
    picks = picks[::16]
    evoked.pick_channels([evoked.ch_names[pick] for pick in picks])
    evoked.info.normalize_proj()
    cov = read_cov(cov_fname)
    cov["projs"] = []
    cov = regularize(cov, evoked.info, rank=None)
    cov = pick_channels_cov(cov, evoked.ch_names)
    evoked.data[:] = 0
    add_noise(evoked, cov, random_state=0)
    cov_new = compute_covariance(
        EpochsArray(evoked.data[np.newaxis], evoked.info), verbose="error"
    )
    assert cov["names"] == cov_new["names"]
    r = np.corrcoef(cov["data"].ravel(), cov_new["data"].ravel())[0, 1]
    assert r > 0.98