Files
oopt-gnpy/gnpy/core/network.py
EstherLerouzic 137fab1d92 Adding weights on edges to have shortest path in length instead of hops
add weight = length of fiber nodes on connections wher from_node is a fiber
add weight = 0.01 km on other edges

Signed-off-by: EstherLerouzic <esther.lerouzic@orange.com>
2019-04-18 11:16:07 +01:00

504 lines
20 KiB
Python

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
'''
gnpy.core.network
=================
This module contains functions for constructing networks of network elements.
'''
from gnpy.core.convert import convert_file
from networkx import DiGraph
from numpy import arange
from scipy.interpolate import interp1d
from logging import getLogger
from os import path
from operator import itemgetter, attrgetter
from gnpy.core import elements
from gnpy.core.elements import Fiber, Edfa, Transceiver, Roadm, Fused
from gnpy.core.equipment import edfa_nf
from gnpy.core.units import UNITS
from gnpy.core.utils import load_json, save_json, round2float, db2lin, lin2db
from sys import exit
from collections import namedtuple
logger = getLogger(__name__)
def load_network(filename, equipment, name_matching = False):
json_filename = ''
if filename.suffix.lower() == '.xls':
logger.info('Automatically generating topology JSON file')
json_filename = convert_file(filename, name_matching)
elif filename.suffix.lower() == '.json':
json_filename = filename
else:
raise ValueError(f'unsuported topology filename extension {filename.suffix.lower()}')
json_data = load_json(json_filename)
return network_from_json(json_data, equipment)
def save_network(filename, network):
filename_output = path.splitext(filename)[0] + '_auto_design.json'
json_data = network_to_json(network)
save_json(json_data, filename_output)
def network_from_json(json_data, equipment):
# NOTE|dutc: we could use the following, but it would tie our data format
# too closely to the graph library
# from networkx import node_link_graph
g = DiGraph()
for el_config in json_data['elements']:
typ = el_config.pop('type')
variety = el_config.pop('type_variety', 'default')
if typ in equipment and variety in equipment[typ]:
extra_params = equipment[typ][variety]
el_config.setdefault('params', {}).update(extra_params.__dict__)
elif typ in ['Edfa', 'Fiber']: #catch it now because the code will crash later!
print( f'The {typ} of variety type {variety} was not recognized:'
'\nplease check it is properly defined in the eqpt_config json file')
exit()
cls = getattr(elements, typ)
el = cls(**el_config)
g.add_node(el)
nodes = {k.uid: k for k in g.nodes()}
for cx in json_data['connections']:
from_node, to_node = cx['from_node'], cx['to_node']
try:
if isinstance(nodes[from_node], Fiber):
edge_length = nodes[from_node].params.length
print(from_node)
print(edge_length)
else:
edge_length = 0.01
g.add_edge(nodes[from_node], nodes[to_node], weight = edge_length)
except KeyError:
msg = f'In {__name__} network_from_json function:\n\tcan not find {from_node} or {to_node} defined in {cx}'
print(msg)
exit(1)
return g
def network_to_json(network):
data = {
'elements': [n.to_json for n in network]
}
connections = {
'connections': [{"from_node": n.uid,
"to_node": next_n.uid}
for n in network
for next_n in network.successors(n) if next_n is not None]
}
data.update(connections)
return data
def select_edfa(raman_allowed, gain_target, power_target, equipment, uid):
"""amplifer selection algorithm
@Orange Jean-Luc Augé
"""
Edfa_list = namedtuple('Edfa_list', 'raman variety power gain_min nf')
TARGET_EXTENDED_GAIN = equipment['Span']['default'].target_extended_gain
edfa_dict = equipment['Edfa']
pin = power_target - gain_target
edfa_list = [Edfa_list(
raman=edfa.raman,
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]
#filter on raman restriction
raman_filter = lambda edfa: (edfa.raman and raman_allowed) or not edfa.raman
edfa_list = list(filter(raman_filter, edfa_list))
#print(f'\n{uid}, gain {gain_target}, {power_target}')
#print('edfa',edfa_list)
#filter on min gain limitation:
#consider gain_target+3 to allow some operation below min gain
#(~counterpart to the extended gain range)
acceptable_gain_min_list = \
list(filter(lambda x : x.gain_min>0, edfa_list))
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
print(
f'\x1b[1;31;40m'\
+ f'WARNING: target gain in node {uid} is below all available amplifiers min gain: \
amplifier input padding will be assumed, consider increase fiber padding instead'\
+ '\x1b[0m'
)
else:
edfa_list = acceptable_gain_min_list
#print('gain_min', acceptable_gain_min_list)
#filter on max power limitation:
acceptable_power_list = \
list(filter(lambda x : x.power>=0, edfa_list))
if len(acceptable_power_list) < 1:
#no amplifier satisfies the required power, so pick the highest power:
power_max = max(edfa_list, key=attrgetter('power')).power
#pick up all amplifiers that share this max gain:
acceptable_power_list = \
list(filter(lambda x : x.power-power_max>-0.3, edfa_list))
#print('power', acceptable_power_list)
# debug:
# print(gain_target, power_target, '=>\n',acceptable_power_list)
# 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
power_reduction = round(min(selected_edfa.power, 0),2)
if power_reduction < -0.5:
print(
f'\x1b[1;31;40m'\
+ f'WARNING: 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'\
+ '\x1b[0m'
)
return selected_edfa.variety, power_reduction
def target_power(network, node, equipment): #get_fiber_dp
SPAN_LOSS_REF = 20
POWER_SLOPE = 0.3
power_mode = equipment['Span']['default'].power_mode
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 KeyError:
print(f'invalid delta_power_range_db definition in eqpt_config[Span]'
f'delta_power_range_db: [lower_bound, upper_bound, step]')
exit()
if isinstance(node, Roadm):
dp = 0
return dp
def prev_node_generator(network, node):
"""fused spans interest:
iterate over all predecessors while they are Fused or Fiber type"""
try:
prev_node = next(n for n in network.predecessors(node))
except StopIteration:
msg = f'In {__name__} prev_node_generator function:\n\t{node.uid} is not properly connected, please check network topology'
print(msg)
logger.critical(msg)
exit(1)
# yield and re-iterate
if isinstance(prev_node, Fused) or isinstance(node, Fused):
yield prev_node
yield from prev_node_generator(network, prev_node)
else:
StopIteration
def next_node_generator(network, node):
"""fused spans interest:
iterate over all successors while they are Fused or Fiber type"""
try:
next_node = next(n for n in network.successors(node))
except StopIteration:
print(f'In {__name__} next_node_generator function:\n\t{node.uid} is not properly connected, please check network topology')
exit(1)
# yield and re-iterate
if isinstance(next_node, Fused) or isinstance(node, Fused):
yield next_node
yield from next_node_generator(network, next_node)
else:
StopIteration
def span_loss(network, node):
"""Fused span interest:
return the total span loss of all the fibers spliced by a Fused node"""
loss = node.loss if node.passive else 0
try:
prev_node = next(n for n in network.predecessors(node))
if isinstance(prev_node, Fused):
loss += sum(n.loss for n in prev_node_generator(network, node))
except StopIteration:
pass
try:
next_node = next(n for n in network.successors(node))
if isinstance(next_node, Fused):
loss += sum(n.loss for n in next_node_generator(network, node))
except StopIteration:
pass
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:
gain_target = amp.effective_gain
voa = min(amp.params.p_max-power_target,
amp.params.gain_flatmax-amp.effective_gain)
voa = max(round2float(max(voa, 0), 0.5) - VOA_MARGIN, 0) if amp.params.out_voa_auto else 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, roadm, equipment, pref_total_db):
power_mode = equipment['Span']['default'].power_mode
next_oms = (n for n in network.successors(roadm) if not isinstance(n, Transceiver))
for oms in next_oms:
#go through all the OMS departing from the Roadm
node = roadm
prev_node = roadm
next_node = oms
# if isinstance(next_node, 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)
prev_dp = getattr(node.params, 'target_pch_out_db', 0)
dp = prev_dp
prev_voa = 0
voa = 0
while True:
#go through all nodes in the OMS (loop until next Roadm instance)
if isinstance(node, Edfa):
node_loss = span_loss(network, prev_node)
if node.out_voa:
voa = node.out_voa
if node.delta_p is None:
dp = target_power(network, next_node, equipment)
else:
dp = node.delta_p
gain_from_dp = node_loss + dp - prev_dp + prev_voa
if node.effective_gain is None or power_mode:
gain_target = gain_from_dp
else: #gain mode with effective_gain
gain_target = node.effective_gain
dp = prev_dp - node_loss + gain_target
#print(node.delta_p, dp, gain_target)
power_target = pref_total_db + dp
if node.params.type_variety == '' :
raman_allowed = False
if isinstance(prev_node, 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
edfa_variety, power_reduction = select_edfa(raman_allowed,
gain_target, power_target, equipment, node.uid)
extra_params = equipment['Edfa'][edfa_variety]
node.params.update_params(extra_params.__dict__)
dp += power_reduction
gain_target += power_reduction
node.delta_p = dp if power_mode else None
node.effective_gain = gain_target
set_amplifier_voa(node, power_target, power_mode)
if isinstance(next_node, Roadm) or isinstance(next_node, Transceiver):
break
prev_dp = dp
prev_voa = voa
prev_node = node
node = next_node
# print(f'{node.uid}')
next_node = next(n for n in network.successors(node))
def add_egress_amplifier(network, node):
next_nodes = [n for n in network.successors(node)
if not (isinstance(n, Transceiver) or isinstance(n, Fused) or isinstance(n, Edfa))]
#no amplification for fused spans or TRX
for i, next_node in enumerate(next_nodes):
network.remove_edge(node, next_node)
amp = Edfa(
uid = f'Edfa{i}_{node.uid}',
params = {},
metadata = {
'location': {
'latitude': (node.lat * 2 + next_node.lat * 2) / 4,
'longitude': (node.lng * 2 + next_node.lng * 2) / 4,
'city': node.loc.city,
'region': node.loc.region,
}
},
operational = {
'gain_target': None,
'tilt_target': 0,
})
network.add_node(amp)
if isinstance(node,Fiber):
edgeweight = node.params.length
else:
edgeweight = 0.01
network.add_edge(node, amp, weight = edgeweight)
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_spans = int(fiber_length // target_length)
length1 = fiber_length / (n_spans+1)
delta1 = target_length-length1
result1 = (length1, n_spans+1)
length2 = fiber_length / n_spans
delta2 = length2-target_length
result2 = (length2, n_spans)
if (bounds.start<=length1<=bounds.stop) and not(bounds.start<=length2<=bounds.stop):
result = result1
elif (bounds.start<=length2<=bounds.stop) and not(bounds.start<=length1<=bounds.stop):
result = result2
else:
result = result1 if delta1 < delta2 else result2
return result
def split_fiber(network, fiber, bounds, target_length, equipment):
new_length, n_spans = calculate_new_length(fiber.length, bounds, target_length)
if n_spans == 1:
return
try:
next_node = next(network.successors(fiber))
prev_node = next(network.predecessors(fiber))
except StopIteration:
print(f'In {__name__} split_fiber function:\n\t{fiber.uid} is not properly connected, please check network topology')
exit()
network.remove_node(fiber)
fiber_params = fiber.params._asdict()
fiber_params['length'] = new_length / UNITS[fiber.params.length_units]
fiber_params['con_in'] = fiber.con_in
fiber_params['con_out'] = fiber.con_out
f = interp1d([prev_node.lng, next_node.lng], [prev_node.lat, next_node.lat])
xpos = [prev_node.lng + (next_node.lng - prev_node.lng) * (n+1)/(n_spans+1) for n in range(n_spans)]
ypos = f(xpos)
for span, lng, lat in zip(range(n_spans), xpos, ypos):
new_span = Fiber(uid = f'{fiber.uid}_({span+1}/{n_spans})',
metadata = {
'location': {
'latitude': lat,
'longitude': lng,
'city': fiber.loc.city,
'region': fiber.loc.region,
}
},
params = fiber_params)
if isinstance(prev_node,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,Fiber):
edgeweight = prev_node.params.length
else:
edgeweight = 0.01
network.add_edge(prev_node, next_node, weight = edgeweight)
def add_connector_loss(fibers, con_in, con_out, EOL):
for fiber in fibers:
if fiber.con_in is None: fiber.con_in = con_in
if fiber.con_out is None:
fiber.con_out = con_out #con_out includes EOL
else:
fiber.con_out = fiber.con_out+EOL
def add_fiber_padding(network, fibers, padding):
"""last_fibers = (fiber for n in network.nodes()
if not (isinstance(n, Fiber) or isinstance(n, Fused))
for fiber in network.predecessors(n)
if isinstance(fiber, Fiber))"""
for fiber in fibers:
this_span_loss = span_loss(network, fiber)
try:
next_node = next(network.successors(fiber))
except StopIteration:
msg = f'In {__name__} add_fiber_padding function:\n\t{fiber.uid} is not properly connected, please check network topology'
print(msg)
logger.critical(msg)
exit(1)
if this_span_loss < padding and not (isinstance(next_node, Fused)):
#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)
if first_fiber.att_in is None:
first_fiber.att_in = padding - this_span_loss
else :
first_fiber.att_in = first_fiber.att_in + padding - this_span_loss
def build_network(network, equipment, pref_ch_db, pref_total_db):
default_span_data = equipment['Span']['default']
max_length = int(default_span_data.max_length * UNITS[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, 90_000)
con_in = default_span_data.con_in
con_out = default_span_data.con_out + default_span_data.EOL
padding = default_span_data.padding
#set raodm loss for gain_mode before to build network
fibers = [f for f in network.nodes() if isinstance(f, Fiber)]
add_connector_loss(fibers, con_in, con_out, default_span_data.EOL)
add_fiber_padding(network, fibers, padding)
# don't group split fiber and add amp in the same loop
# =>for code clarity (at the expense of speed):
for fiber in fibers:
split_fiber(network, fiber, bounds, target_length, equipment)
amplified_nodes = [n for n in network.nodes()
if isinstance(n, Fiber) or isinstance(n, Roadm)]
for node in amplified_nodes:
add_egress_amplifier(network, node)
roadms = [r for r in network.nodes() if isinstance(r, Roadm)]
for roadm in roadms:
set_egress_amplifier(network, roadm, equipment, pref_total_db)
#support older json input topology wo Roadms:
if len(roadms) == 0:
trx = [t for t in network.nodes() if isinstance(t, Transceiver)]
for t in trx:
set_egress_amplifier(network, t, equipment, pref_total_db)