#!/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)