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equipment: move NF estimation into science_utils

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I envision equipment.py as something which deals exclusively with the
traditional GNPy's JSON-formatted data, so make sure we do not include
any computation in that file.

Change-Id: I8473cccd84243147181a7195ba39fc6c9db3c42f
This commit is contained in:
Jan Kundrát
2020-05-23 16:32:00 +02:00
parent f728d96d07
commit a094568d6e
2 changed files with 52 additions and 51 deletions
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53
gnpy/core/equipment.py
View File

@@ -8,14 +8,13 @@ gnpy.core.equipment
This module contains functionality for specifying equipment.
'''
from numpy import clip
from math import isclose
from pathlib import Path
from json import load
from gnpy.core.utils import automatic_nch, lin2db, db2lin, load_json
from gnpy.core.utils import automatic_nch, db2lin, load_json
from collections import namedtuple
from gnpy.core import ansi_escapes
from gnpy.core.exceptions import EquipmentConfigError
from gnpy.core.science_utils import estimate_nf_model
import time
Model_vg = namedtuple('Model_vg', 'nf1 nf2 delta_p')
@@ -183,7 +182,7 @@ class Amp(common):
del kwargs['nf0']
except KeyError:
pass # nf0 is not needed for variable gain amp
nf1, nf2, delta_p = nf_model(type_variety, gain_min, gain_max, nf_min, nf_max)
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)
elif type_def == 'openroadm':
try:
@@ -206,52 +205,6 @@ class Amp(common):
'nf_model': nf_def, 'dual_stage_model': dual_stage_def})
def nf_model(type_variety, gain_min, gain_max, nf_min, nf_max):
if nf_min < -10:
raise EquipmentConfigError(f'Invalid nf_min value {nf_min!r} for amplifier {type_variety}')
if nf_max < -10:
raise EquipmentConfigError(f'Invalid nf_max value {nf_max!r} for amplifier {type_variety}')
# NF estimation model based on nf_min and nf_max
# delta_p: max power dB difference between first and second stage coils
# dB g1a: first stage gain - internal VOA attenuation
# nf1, nf2: first and second stage coils
# calculated by solving nf_{min,max} = nf1 + nf2 / g1a{min,max}
delta_p = 5
g1a_min = gain_min - (gain_max - gain_min) - delta_p
g1a_max = gain_max - delta_p
nf2 = lin2db((db2lin(nf_min) - db2lin(nf_max)) /
(1 / db2lin(g1a_max) - 1 / db2lin(g1a_min)))
nf1 = lin2db(db2lin(nf_min) - db2lin(nf2) / db2lin(g1a_max))
if nf1 < 4:
raise EquipmentConfigError(f'First coil value too low {nf1} for amplifier {type_variety}')
# Check 1 dB < delta_p < 6 dB to ensure nf_min and nf_max values make sense.
# There shouldn't be high nf differences between the two coils:
# nf2 should be nf1 + 0.3 < nf2 < nf1 + 2
# If not, recompute and check delta_p
if not nf1 + 0.3 < nf2 < nf1 + 2:
nf2 = clip(nf2, nf1 + 0.3, nf1 + 2)
g1a_max = lin2db(db2lin(nf2) / (db2lin(nf_min) - db2lin(nf1)))
delta_p = gain_max - g1a_max
g1a_min = gain_min - (gain_max - gain_min) - delta_p
if not 1 < delta_p < 11:
raise EquipmentConfigError(f'Computed \N{greek capital letter delta}P invalid \
\n 1st coil vs 2nd coil calculated DeltaP {delta_p:.2f} for \
\n amplifier {type_variety} is not valid: revise inputs \
\n calculated 1st coil NF = {nf1:.2f}, 2nd coil NF = {nf2:.2f}')
# Check calculated values for nf1 and nf2
calc_nf_min = lin2db(db2lin(nf1) + db2lin(nf2) / db2lin(g1a_max))
if not isclose(nf_min, calc_nf_min, abs_tol=0.01):
raise EquipmentConfigError(f'nf_min does not match calc_nf_min, {nf_min} vs {calc_nf_min} for amp {type_variety}')
calc_nf_max = lin2db(db2lin(nf1) + db2lin(nf2) / db2lin(g1a_min))
if not isclose(nf_max, calc_nf_max, abs_tol=0.01):
raise EquipmentConfigError(f'nf_max does not match calc_nf_max, {nf_max} vs {calc_nf_max} for amp {type_variety}')
return nf1, nf2, delta_p
def trx_mode_params(equipment, trx_type_variety='', trx_mode='', error_message=False):
"""return the trx and SI parameters from eqpt_config for a given type_variety and mode (ie format)"""
trx_params = {}

50
gnpy/core/science_utils.py
View File

@@ -6,8 +6,10 @@ from scipy.integrate import solve_bvp
from scipy.integrate import cumtrapz
from scipy.interpolate import interp1d
from scipy.optimize import OptimizeResult
from math import isclose
from gnpy.core.utils import db2lin
from gnpy.core.utils import db2lin, lin2db
from gnpy.core.exceptions import EquipmentConfigError
logger = getLogger(__name__)
@@ -682,3 +684,49 @@ def _psi(carrier, interfering_carrier, beta2, asymptotic_length):
psi -= np.arcsinh(np.pi**2 * asymptotic_length * abs(beta2) *
carrier.baud_rate * (delta_f - 0.5 * interfering_carrier.baud_rate))
return psi
def estimate_nf_model(type_variety, gain_min, gain_max, nf_min, nf_max):
if nf_min < -10:
raise EquipmentConfigError(f'Invalid nf_min value {nf_min!r} for amplifier {type_variety}')
if nf_max < -10:
raise EquipmentConfigError(f'Invalid nf_max value {nf_max!r} for amplifier {type_variety}')
# NF estimation model based on nf_min and nf_max
# delta_p: max power dB difference between first and second stage coils
# dB g1a: first stage gain - internal VOA attenuation
# nf1, nf2: first and second stage coils
# calculated by solving nf_{min,max} = nf1 + nf2 / g1a{min,max}
delta_p = 5
g1a_min = gain_min - (gain_max - gain_min) - delta_p
g1a_max = gain_max - delta_p
nf2 = lin2db((db2lin(nf_min) - db2lin(nf_max)) /
(1 / db2lin(g1a_max) - 1 / db2lin(g1a_min)))
nf1 = lin2db(db2lin(nf_min) - db2lin(nf2) / db2lin(g1a_max))
if nf1 < 4:
raise EquipmentConfigError(f'First coil value too low {nf1} for amplifier {type_variety}')
# Check 1 dB < delta_p < 6 dB to ensure nf_min and nf_max values make sense.
# There shouldn't be high nf differences between the two coils:
# nf2 should be nf1 + 0.3 < nf2 < nf1 + 2
# If not, recompute and check delta_p
if not nf1 + 0.3 < nf2 < nf1 + 2:
nf2 = np.clip(nf2, nf1 + 0.3, nf1 + 2)
g1a_max = lin2db(db2lin(nf2) / (db2lin(nf_min) - db2lin(nf1)))
delta_p = gain_max - g1a_max
g1a_min = gain_min - (gain_max - gain_min) - delta_p
if not 1 < delta_p < 11:
raise EquipmentConfigError(f'Computed \N{greek capital letter delta}P invalid \
\n 1st coil vs 2nd coil calculated DeltaP {delta_p:.2f} for \
\n amplifier {type_variety} is not valid: revise inputs \
\n calculated 1st coil NF = {nf1:.2f}, 2nd coil NF = {nf2:.2f}')
# Check calculated values for nf1 and nf2
calc_nf_min = lin2db(db2lin(nf1) + db2lin(nf2) / db2lin(g1a_max))
if not isclose(nf_min, calc_nf_min, abs_tol=0.01):
raise EquipmentConfigError(f'nf_min does not match calc_nf_min, {nf_min} vs {calc_nf_min} for amp {type_variety}')
calc_nf_max = lin2db(db2lin(nf1) + db2lin(nf2) / db2lin(g1a_min))
if not isclose(nf_max, calc_nf_max, abs_tol=0.01):
raise EquipmentConfigError(f'nf_max does not match calc_nf_max, {nf_max} vs {calc_nf_max} for amp {type_variety}')
return nf1, nf2, delta_p