equipment: remember NF_min, NF_max when using the operator model
...so that these original values are accessible to the YANG conversion
later on, if needed.
@@ -27,7 +27,7 @@ import time
_logger = getLogger(__name__)
-Model_vg = namedtuple('Model_vg', 'nf1 nf2 delta_p')
+Model_vg = namedtuple('Model_vg', 'nf1 nf2 delta_p orig_nf_min orig_nf_max')
Model_fg = namedtuple('Model_fg', 'nf0')
Model_openroadm_ila = namedtuple('Model_openroadm_ila', 'nf_coef')
Model_hybrid = namedtuple('Model_hybrid', 'nf_ram gain_ram edfa_variety')
@@ -196,7 +196,7 @@ class Amp(_JsonThing):
except KeyError:
pass # nf0 is not needed for variable gain amp
nf1, nf2, delta_p = estimate_nf_model(type_variety, gain_min, gain_max, nf_min, nf_max)
- nf_def = Model_vg(nf1, nf2, delta_p)
+ nf_def = Model_vg(nf1, nf2, delta_p, nf_min, nf_max)
elif type_def == 'openroadm':
try:
nf_coef = kwargs.pop('nf_coef')
