Implementation of the lensing power spectrum computation with CCL

[raphkou]

This PR implements the lensing power spectrum computation with CCL. A flag is added to choose whether to use CAMB or CCL to compute this power spectrum.

[itrharrison]

This looks good, thank you! One extra which would be good is the inclusion of a test which checks that the CCL result is comparable to the CAMB one.

e.g.

def test_lensing_ccllimber(request):

    from cobaya.install import install
    install({"likelihood": {"soliket.lensing.LensingLikelihood": None}},
            path=packages_path, skip_global=False, force=True, debug=True)

    from soliket.lensing import LensingLikelihood

    info["likelihood"] = {"LensingLikelihood": {"external": LensingLikelihood}}
    model = get_model(info)
    model.loglikes({})
    cl_ccl = model.likelihood['LensingLikelihood']._get_theory()

    info['likelihood']['LensingLikelihood']['pp_ccl'] = False
    model = get_model(info)
    model.loglikes({})
    cl_camb = model.likelihood['LensingLikelihood']._get_theory()

    assert np.any(np.not_equal(cl_ccl,cl_camb))
    assert np.allclose(cl_ccl, cl_camb)

[itrharrison]

Remove whitespace on this blank line, as requested by the codestyle test. You can check this passes locally by running tox -e codestyle.

[raphkou]

As you advised, I added a test to check that the predictions from CAMB and CCL agree (at least in the case where the mass of neutrinos is 0). I also fixed the codestyle.

[itrharrison]

This looks good now. Thank you @raphkou !