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new fixed gain amp in nf_model

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new type_def attribute for nf_model amplifiers
variable gain: requires nf_min & nf_max input
fixed_gain: requires nf0 input
	=> NF=nf0 in the [gain_min, gain_flatmax] range
	=> NF=nf0+pad if gain < gain_min: automatic input padding

Signed-off-by: Jean-Luc Auge <jeanluc.auge@orange.com>
This commit is contained in:
Jean-Luc Auge
2018-07-30 12:58:30 +02:00
parent e3acf02bde
commit 5c16d9539f
3 changed files with 55 additions and 17 deletions
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6
gnpy/core/elements.py
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@@ -307,7 +307,7 @@ class Fiber(Node):
# TODO|dutc: eliminate duplication with .equipment.EdfaBase
EdfaParams = namedtuple('EdfaParams',
'type_variety, gain_flatmax gain_min p_max nf_min nf_max'
'type_variety, type_def, gain_flatmax gain_min p_max'
' nf_model nf_fit_coeff nf_ripple dgt gain_ripple')
class EdfaOperational:
def __init__(self, gain_target, tilt_target):
@@ -412,9 +412,11 @@ class Edfa(Node):
pad = max(self.params.gain_min - self.effective_gain, 0)
gain_target = self.effective_gain + pad
dg = max(self.params.gain_flatmax - gain_target, 0)
if self.params.nf_model:
if self.params.type_def == 'variable_gain':
g1a = gain_target - self.params.nf_model.delta_p - dg
nf_avg = lin2db(db2lin(self.params.nf_model.nf1) + db2lin(self.params.nf_model.nf2)/db2lin(g1a))
elif self.params.type_def == 'fixed_gain':
nf_avg = self.params.nf_model.nf0
else:
nf_avg = polyval(self.params.nf_fit_coeff, -dg)
return self.interpol_nf_ripple + nf_avg + pad # input VOA = 1 for 1 NF degradation