Use design delta_p and gains instead of p_spani

Remove the visualisation of the effective_pch in amp because actual
and target are the relevant ones. effective_pch was artificially
related to a mix of reference channel and noisy channel (mixed between
on the fly redesign but using actual ROADM equalisation which includes noise
in its actual loss).

the change does no more rely on the target power (which is rounded)
but on the designed gain, which is not rounded.

Propagations are slightly changed for openroadm simulations because of that.
(I verified)

The gain of amp was estimated on the fly with p_spni also in case of
RamanFiber preceding elements. removing p_spani requies that an estimation
of Raman gain be done during design.

This commit also adds this estimation.

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
Change-Id: I960b85e99f85a7d168ac5349e325c4928fa5673b

tests/test_parser.py

@@ -110,6 +110,7 @@ def test_auto_design_generation_fromjson(tmpdir, json_input, power_mode):
     p_db = equipment['SI']['default'].power_dbm
     p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,
                                              equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
+    add_missing_elements_in_network(network, equipment)
     build_network(network, equipment, p_db, p_total_db)
     actual_json_output = tmpdir / json_input.with_name(json_input.stem + '_auto_design').with_suffix('.json').name
     save_network(network, actual_json_output)