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f94d06f12427fade9370247c1dfa42de0ea9d752
oopt-gnpy/gnpy/core/network.py
Jonas Mårtensson f94d06f124 Fix warnings for raman amp type varieties 
Currently, a warning about fiber lineic loss being above threshold is
printed even when the warning is triggered by that the previous node is
not a fiber, which is confusing. Additionally, when a warning about
raman is triggered, the code in the following else clause is not
executed, which means that a potential warning about gain level is
disabled. These two warnings are independent and the second one should
not be disabled by the first one.

Signed-off-by: Jonas Mårtensson <jonas.martensson@ri.se>
Change-Id: I8ad58b4ebf6e7df1a949a77d67ed948ef385c47e
2021-09-28 13:08:57 +02:00

555 lines
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
'''
gnpy.core.network
=================
Working with networks which consist of network elements
'''
from operator import attrgetter
from gnpy.core import ansi_escapes, elements
from gnpy.core.exceptions import ConfigurationError, NetworkTopologyError
from gnpy.core.utils import round2float, convert_length
from collections import namedtuple
def edfa_nf(gain_target, variety_type, equipment):
amp_params = equipment['Edfa'][variety_type]
amp = elements.Edfa(
uid='calc_NF',
params=amp_params.__dict__,
operational={
'gain_target': gain_target,
'tilt_target': 0
}
)
amp.pin_db = 0
amp.nch = 88
return amp._calc_nf(True)
def select_edfa(raman_allowed, gain_target, power_target, equipment, uid, restrictions=None):
"""amplifer selection algorithm
@Orange Jean-Luc Augé
"""
Edfa_list = namedtuple('Edfa_list', 'variety power gain_min nf')
TARGET_EXTENDED_GAIN = equipment['Span']['default'].target_extended_gain
# for roadm restriction only: create a dict including not allowed for design amps
# because main use case is to have specific radm amp which are not allowed for ILA
# with the auto design
edfa_dict = {name: amp for (name, amp) in equipment['Edfa'].items()
if restrictions is None or name in restrictions}
pin = power_target - gain_target
# create 2 list of available amplifiers with relevant attributes for their selection
# edfa list with:
# extended gain min allowance of 3dB: could be parametrized, but a bit complex
# extended gain max allowance TARGET_EXTENDED_GAIN is coming from eqpt_config.json
# power attribut include power AND gain limitations
edfa_list = [Edfa_list(
variety=edfa_variety,
power=min(
pin
+ edfa.gain_flatmax
+ TARGET_EXTENDED_GAIN,
edfa.p_max
)
- power_target,
gain_min=gain_target + 3
- edfa.gain_min,
nf=edfa_nf(gain_target, edfa_variety, equipment))
for edfa_variety, edfa in edfa_dict.items()
if ((edfa.allowed_for_design or restrictions is not None) and not edfa.raman)]
# consider a Raman list because of different gain_min requirement:
# do not allow extended gain min for Raman
raman_list = [Edfa_list(
variety=edfa_variety,
power=min(
pin
+ edfa.gain_flatmax
+ TARGET_EXTENDED_GAIN,
edfa.p_max
)
- power_target,
gain_min=gain_target
- edfa.gain_min,
nf=edfa_nf(gain_target, edfa_variety, equipment))
for edfa_variety, edfa in edfa_dict.items()
if (edfa.allowed_for_design and edfa.raman)] \
if raman_allowed else []
# merge raman and edfa lists
amp_list = edfa_list + raman_list
# filter on min gain limitation:
acceptable_gain_min_list = [x for x in amp_list if x.gain_min > 0]
if len(acceptable_gain_min_list) < 1:
# do not take this empty list into account for the rest of the code
# but issue a warning to the user and do not consider Raman
# Raman below min gain should not be allowed because i is meant to be a design requirement
# and raman padding at the amplifier input is impossible!
if len(edfa_list) < 1:
raise ConfigurationError(f'auto_design could not find any amplifier \
to satisfy min gain requirement in node {uid} \
please increase span fiber padding')
else:
# TODO: convert to logging
print(
f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain in node {uid} is below all available amplifiers min gain: \
amplifier input padding will be assumed, consider increase span fiber padding instead'
)
acceptable_gain_min_list = edfa_list
# filter on gain+power limitation:
# this list checks both the gain and the power requirement
# because of the way .power is calculated in the list
acceptable_power_list = [x for x in acceptable_gain_min_list if x.power > 0]
if len(acceptable_power_list) < 1:
# no amplifier satisfies the required power, so pick the highest power(s):
power_max = max(acceptable_gain_min_list, key=attrgetter('power')).power
# check and pick if other amplifiers may have a similar gain/power
# allow a 0.3dB power range
# this allows to chose an amplifier with a better NF subsequentely
acceptable_power_list = [x for x in acceptable_gain_min_list
if x.power - power_max > -0.3]
# gain and power requirements are resolved,
# =>chose the amp with the best NF among the acceptable ones:
selected_edfa = min(acceptable_power_list, key=attrgetter('nf')) # filter on NF
# check what are the gain and power limitations of this amp
power_reduction = round(min(selected_edfa.power, 0), 2)
if power_reduction < -0.5:
print(
f'{ansi_escapes.red}WARNING:{ansi_escapes.reset} target gain and power in node {uid}\n \
is beyond all available amplifiers capabilities and/or extended_gain_range:\n\
a power reduction of {power_reduction} is applied\n'
)
return selected_edfa.variety, power_reduction
def target_power(network, node, equipment): # get_fiber_dp
if isinstance(node, elements.Roadm):
return 0
SPAN_LOSS_REF = 20
POWER_SLOPE = 0.3
dp_range = list(equipment['Span']['default'].delta_power_range_db)
node_loss = span_loss(network, node)
try:
dp = round2float((node_loss - SPAN_LOSS_REF) * POWER_SLOPE, dp_range[2])
dp = max(dp_range[0], dp)
dp = min(dp_range[1], dp)
except IndexError:
raise ConfigurationError(f'invalid delta_power_range_db definition in eqpt_config[Span]'
f'delta_power_range_db: [lower_bound, upper_bound, step]')
return dp
_fiber_fused_types = (elements.Fused, elements.Fiber)
def prev_node_generator(network, node):
"""fused spans interest:
iterate over all predecessors while they are either Fused or Fibers succeeded by Fused"""
try:
prev_node = next(network.predecessors(node))
except StopIteration:
if isinstance(node, elements.Transceiver):
return
raise NetworkTopologyError(f'Node {node.uid} is not properly connected, please check network topology')
if ((isinstance(prev_node, elements.Fused) and isinstance(node, _fiber_fused_types)) or
(isinstance(prev_node, _fiber_fused_types) and isinstance(node, elements.Fused))):
yield prev_node
yield from prev_node_generator(network, prev_node)
def next_node_generator(network, node):
"""fused spans interest:
iterate over all predecessors while they are either Fused or Fibers preceded by Fused"""
try:
next_node = next(network.successors(node))
except StopIteration:
if isinstance(node, elements.Transceiver):
return
raise NetworkTopologyError(f'Node {node.uid} is not properly connected, please check network topology')
if ((isinstance(next_node, elements.Fused) and isinstance(node, _fiber_fused_types)) or
(isinstance(next_node, _fiber_fused_types) and isinstance(node, elements.Fused))):
yield next_node
yield from next_node_generator(network, next_node)
def span_loss(network, node):
"""Total loss of a span (Fiber and Fused nodes) which contains the given node"""
loss = node.loss if node.passive else 0
loss += sum(n.loss for n in prev_node_generator(network, node))
loss += sum(n.loss for n in next_node_generator(network, node))
return loss
def find_first_node(network, node):
"""Fused node interest:
returns the 1st node at the origin of a succession of fused nodes
(aka no amp in between)"""
this_node = node
for this_node in prev_node_generator(network, node):
pass
return this_node
def find_last_node(network, node):
"""Fused node interest:
returns the last node in a succession of fused nodes
(aka no amp in between)"""
this_node = node
for this_node in next_node_generator(network, node):
pass
return this_node
def set_amplifier_voa(amp, power_target, power_mode):
VOA_MARGIN = 1 # do not maximize the VOA optimization
if amp.out_voa is None:
if power_mode and amp.params.out_voa_auto:
voa = min(amp.params.p_max - power_target,
amp.params.gain_flatmax - amp.effective_gain)
voa = max(round2float(voa, 0.5) - VOA_MARGIN, 0)
amp.delta_p = amp.delta_p + voa
amp.effective_gain = amp.effective_gain + voa
else:
voa = 0 # no output voa optimization in gain mode
amp.out_voa = voa
def set_egress_amplifier(network, this_node, equipment, pref_ch_db, pref_total_db):
""" this node can be a transceiver or a ROADM (same function called in both cases)
"""
power_mode = equipment['Span']['default'].power_mode
next_oms = (n for n in network.successors(this_node) if not isinstance(n, elements.Transceiver))
this_node_degree = {k: v for k, v in this_node.per_degree_pch_out_db.items()} if hasattr(this_node, 'per_degree_pch_out_db') else {}
for oms in next_oms:
# go through all the OMS departing from the ROADM
prev_node = this_node
node = oms
# if isinstance(next_node, elements.Fused): #support ROADM wo egress amp for metro applications
# node = find_last_node(next_node)
# next_node = next(n for n in network.successors(node))
# next_node = find_last_node(next_node)
if node.uid not in this_node_degree:
# if no target power is defined on this degree or no per degree target power is given use the global one
# if target_pch_out_db is not an attribute, then the element must be a transceiver
this_node_degree[node.uid] = getattr(this_node.params, 'target_pch_out_db', 0)
# use the target power on this degree
prev_dp = this_node_degree[node.uid] - pref_ch_db
dp = prev_dp
prev_voa = 0
voa = 0
visited_nodes = []
while not (isinstance(node, elements.Roadm) or isinstance(node, elements.Transceiver)):
# go through all nodes in the OMS (loop until next Roadm instance)
try:
next_node = next(network.successors(node))
except StopIteration:
raise NetworkTopologyError(f'{type(node).__name__} {node.uid} is not properly connected, please check network topology')
visited_nodes.append(node)
if next_node in visited_nodes:
raise NetworkTopologyError(f'Loop detected for {type(node).__name__} {node.uid}, please check network topology')
if isinstance(node, elements.Edfa):
node_loss = span_loss(network, prev_node)
voa = node.out_voa if node.out_voa else 0
if node.delta_p is None:
dp = target_power(network, next_node, equipment) + voa
else:
dp = node.delta_p
if node.effective_gain is None or power_mode:
gain_target = node_loss + dp - prev_dp + prev_voa
else: # gain mode with effective_gain
gain_target = node.effective_gain
dp = prev_dp - node_loss - prev_voa + gain_target
power_target = pref_total_db + dp
if isinstance(prev_node, elements.Fiber):
max_fiber_lineic_loss_for_raman = \
equipment['Span']['default'].max_fiber_lineic_loss_for_raman
raman_allowed = prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman
else:
raman_allowed = False
if node.params.type_variety == '':
if node.variety_list and isinstance(node.variety_list, list):
restrictions = node.variety_list
elif isinstance(prev_node, elements.Roadm) and prev_node.restrictions['booster_variety_list']:
# implementation of restrictions on roadm boosters
restrictions = prev_node.restrictions['booster_variety_list']
elif isinstance(next_node, elements.Roadm) and next_node.restrictions['preamp_variety_list']:
# implementation of restrictions on roadm preamp
restrictions = next_node.restrictions['preamp_variety_list']
else:
restrictions = None
edfa_variety, power_reduction = select_edfa(raman_allowed, gain_target, power_target, equipment, node.uid, restrictions)
extra_params = equipment['Edfa'][edfa_variety]
node.params.update_params(extra_params.__dict__)
dp += power_reduction
gain_target += power_reduction
else:
if node.params.raman and not raman_allowed:
if isinstance(prev_node, elements.Fiber):
print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: raman is used in node {node.uid}\n '
'but fiber lineic loss is above threshold\n')
else:
print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: raman is used in node {node.uid}\n '
'but previous node is not a fiber\n')
# if variety is imposed by user, and if the gain_target (computed or imposed) is also above
# variety max gain + extended range, then warn that gain > max_gain + extended range
if gain_target - equipment['Edfa'][node.params.type_variety].gain_flatmax - \
equipment['Span']['default'].target_extended_gain > 1e-2:
# 1e-2 to allow a small margin according to round2float min step
print(f'{ansi_escapes.red}WARNING{ansi_escapes.reset}: '
f'WARNING: effective gain in Node {node.uid} is above user '
f'specified amplifier {node.params.type_variety}\n'
f'max flat gain: {equipment["Edfa"][node.params.type_variety].gain_flatmax}dB ; '
f'required gain: {gain_target}dB. Please check amplifier type.')
node.delta_p = dp if power_mode else None
node.effective_gain = gain_target
set_amplifier_voa(node, power_target, power_mode)
prev_dp = dp
prev_voa = voa
prev_node = node
node = next_node
# print(f'{node.uid}')
if isinstance(this_node, elements.Roadm):
this_node.per_degree_pch_out_db = {k: v for k, v in this_node_degree.items()}
def add_roadm_booster(network, roadm):
next_nodes = [n for n in network.successors(roadm)
if not (isinstance(n, elements.Transceiver) or isinstance(n, elements.Fused) or isinstance(n, elements.Edfa))]
# no amplification for fused spans or TRX
for next_node in next_nodes:
network.remove_edge(roadm, next_node)
amp = elements.Edfa(
uid=f'Edfa_booster_{roadm.uid}_to_{next_node.uid}',
params={},
metadata={
'location': {
'latitude': roadm.lat,
'longitude': roadm.lng,
'city': roadm.loc.city,
'region': roadm.loc.region,
}
},
operational={
'gain_target': None,
'tilt_target': 0,
})
network.add_node(amp)
network.add_edge(roadm, amp, weight=0.01)
network.add_edge(amp, next_node, weight=0.01)
def add_roadm_preamp(network, roadm):
prev_nodes = [n for n in network.predecessors(roadm)
if not (isinstance(n, elements.Transceiver) or isinstance(n, elements.Fused) or isinstance(n, elements.Edfa))]
# no amplification for fused spans or TRX
for prev_node in prev_nodes:
network.remove_edge(prev_node, roadm)
amp = elements.Edfa(
uid=f'Edfa_preamp_{roadm.uid}_from_{prev_node.uid}',
params={},
metadata={
'location': {
'latitude': roadm.lat,
'longitude': roadm.lng,
'city': roadm.loc.city,
'region': roadm.loc.region,
}
},
operational={
'gain_target': None,
'tilt_target': 0,
})
network.add_node(amp)
if isinstance(prev_node, elements.Fiber):
edgeweight = prev_node.params.length
else:
edgeweight = 0.01
network.add_edge(prev_node, amp, weight=edgeweight)
network.add_edge(amp, roadm, weight=0.01)
def add_inline_amplifier(network, fiber):
next_node = next(network.successors(fiber))
if isinstance(next_node, elements.Fiber) or isinstance(next_node, elements.RamanFiber):
# no amplification for fused spans or TRX
network.remove_edge(fiber, next_node)
amp = elements.Edfa(
uid=f'Edfa_{fiber.uid}',
params={},
metadata={
'location': {
'latitude': (fiber.lat + next_node.lat) / 2,
'longitude': (fiber.lng + next_node.lng) / 2,
'city': fiber.loc.city,
'region': fiber.loc.region,
}
},
operational={
'gain_target': None,
'tilt_target': 0,
})
network.add_node(amp)
network.add_edge(fiber, amp, weight=fiber.params.length)
network.add_edge(amp, next_node, weight=0.01)
def calculate_new_length(fiber_length, bounds, target_length):
if fiber_length < bounds.stop:
return fiber_length, 1
n_spans2 = int(fiber_length // target_length)
n_spans1 = n_spans2 + 1
length1 = fiber_length / n_spans1
length2 = fiber_length / n_spans2
if (bounds.start <= length1 <= bounds.stop) and not(bounds.start <= length2 <= bounds.stop):
return (length1, n_spans1)
elif (bounds.start <= length2 <= bounds.stop) and not(bounds.start <= length1 <= bounds.stop):
return (length2, n_spans2)
elif target_length - length1 < length2 - target_length:
return (length1, n_spans1)
else:
return (length2, n_spans2)
def split_fiber(network, fiber, bounds, target_length, equipment):
new_length, n_spans = calculate_new_length(fiber.params.length, bounds, target_length)
if n_spans == 1:
return
try:
next_node = next(network.successors(fiber))
prev_node = next(network.predecessors(fiber))
except StopIteration:
raise NetworkTopologyError(f'Fiber {fiber.uid} is not properly connected, please check network topology')
network.remove_node(fiber)
fiber.params.length = new_length
xpos = [prev_node.lng + (next_node.lng - prev_node.lng) * (n + 0.5) / n_spans for n in range(n_spans)]
ypos = [prev_node.lat + (next_node.lat - prev_node.lat) * (n + 0.5) / n_spans for n in range(n_spans)]
for span, lng, lat in zip(range(n_spans), xpos, ypos):
new_span = elements.Fiber(uid=f'{fiber.uid}_({span+1}/{n_spans})',
type_variety=fiber.type_variety,
metadata={
'location': {
'latitude': lat,
'longitude': lng,
'city': fiber.loc.city,
'region': fiber.loc.region,
}
},
params=fiber.params.asdict())
if isinstance(prev_node, elements.Fiber):
edgeweight = prev_node.params.length
else:
edgeweight = 0.01
network.add_edge(prev_node, new_span, weight=edgeweight)
prev_node = new_span
if isinstance(prev_node, elements.Fiber):
edgeweight = prev_node.params.length
else:
edgeweight = 0.01
network.add_edge(prev_node, next_node, weight=edgeweight)
def add_connector_loss(network, fibers, default_con_in, default_con_out, EOL):
for fiber in fibers:
try:
next_node = next(network.successors(fiber))
except StopIteration:
raise NetworkTopologyError(f'Fiber {fiber.uid} is not properly connected, please check network topology')
if fiber.params.con_in is None:
fiber.params.con_in = default_con_in
if fiber.params.con_out is None:
fiber.params.con_out = default_con_out
if not isinstance(next_node, elements.Fused):
fiber.params.con_out += EOL
def add_fiber_padding(network, fibers, padding):
"""last_fibers = (fiber for n in network.nodes()
if not (isinstance(n, elements.Fiber) or isinstance(n, elements.Fused))
for fiber in network.predecessors(n)
if isinstance(fiber, elements.Fiber))"""
for fiber in fibers:
try:
next_node = next(network.successors(fiber))
except StopIteration:
raise NetworkTopologyError(f'Fiber {fiber.uid} is not properly connected, please check network topology')
if isinstance(next_node, elements.Fused):
continue
this_span_loss = span_loss(network, fiber)
if this_span_loss < padding:
# add a padding att_in at the input of the 1st fiber:
# address the case when several fibers are spliced together
first_fiber = find_first_node(network, fiber)
# in order to support no booster , fused might be placed
# just after a roadm: need to check that first_fiber is really a fiber
if isinstance(first_fiber, elements.Fiber):
first_fiber.params.att_in = first_fiber.params.att_in + padding - this_span_loss
def build_network(network, equipment, pref_ch_db, pref_total_db, no_insert_edfas=False):
default_span_data = equipment['Span']['default']
max_length = int(convert_length(default_span_data.max_length, default_span_data.length_units))
min_length = max(int(default_span_data.padding / 0.2 * 1e3), 50_000)
bounds = range(min_length, max_length)
target_length = max(min_length, min(max_length, 90_000))
# set roadm loss for gain_mode before to build network
fibers = [f for f in network.nodes() if isinstance(f, elements.Fiber)]
add_connector_loss(network, fibers, default_span_data.con_in, default_span_data.con_out, default_span_data.EOL)
add_fiber_padding(network, fibers, default_span_data.padding)
# don't group split fiber and add amp in the same loop
# =>for code clarity (at the expense of speed):
roadms = [r for r in network.nodes() if isinstance(r, elements.Roadm)]
if not no_insert_edfas:
for fiber in fibers:
split_fiber(network, fiber, bounds, target_length, equipment)
for roadm in roadms:
add_roadm_preamp(network, roadm)
add_roadm_booster(network, roadm)
fibers = [f for f in network.nodes() if isinstance(f, elements.Fiber)]
for fiber in fibers:
add_inline_amplifier(network, fiber)
for roadm in roadms:
set_egress_amplifier(network, roadm, equipment, pref_ch_db, pref_total_db)
trx = [t for t in network.nodes() if isinstance(t, elements.Transceiver)]
for t in trx:
next_node = next(network.successors(t), None)
if next_node and not isinstance(next_node, elements.Roadm):
set_egress_amplifier(network, t, equipment, 0, pref_total_db)
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