mirror of
https://github.com/Telecominfraproject/oopt-gnpy.git
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0fee63fa81
code exit if no edfa are available and raman do not fill min gain requirement Signed-off-by: Jean-Luc Auge <jeanluc.auge@orange.com>
543 lines
22 KiB
Python
543 lines
22 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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'''
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gnpy.core.network
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=================
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This module contains functions for constructing networks of network elements.
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'''
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from gnpy.core.convert import convert_file
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from networkx import DiGraph
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from numpy import arange
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from scipy.interpolate import interp1d
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from logging import getLogger
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from os import path
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from operator import itemgetter, attrgetter
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from gnpy.core import elements
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from gnpy.core.elements import Fiber, Edfa, Transceiver, Roadm, Fused
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from gnpy.core.equipment import edfa_nf
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from gnpy.core.units import UNITS
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from gnpy.core.utils import load_json, save_json, round2float, db2lin, lin2db
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from sys import exit
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from collections import namedtuple
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logger = getLogger(__name__)
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def load_network(filename, equipment, name_matching = False):
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json_filename = ''
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if filename.suffix.lower() == '.xls':
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logger.info('Automatically generating topology JSON file')
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json_filename = convert_file(filename, name_matching)
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elif filename.suffix.lower() == '.json':
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json_filename = filename
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else:
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raise ValueError(f'unsuported topology filename extension {filename.suffix.lower()}')
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json_data = load_json(json_filename)
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return network_from_json(json_data, equipment)
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def save_network(filename, network):
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filename_output = path.splitext(filename)[0] + '_auto_design.json'
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json_data = network_to_json(network)
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save_json(json_data, filename_output)
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def network_from_json(json_data, equipment):
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# NOTE|dutc: we could use the following, but it would tie our data format
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# too closely to the graph library
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# from networkx import node_link_graph
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g = DiGraph()
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for el_config in json_data['elements']:
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typ = el_config.pop('type')
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variety = el_config.pop('type_variety', 'default')
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if typ in equipment and variety in equipment[typ]:
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extra_params = equipment[typ][variety]
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el_config.setdefault('params', {}).update(extra_params.__dict__)
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elif typ in ['Edfa', 'Fiber']: #catch it now because the code will crash later!
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print( f'The {typ} of variety type {variety} was not recognized:'
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'\nplease check it is properly defined in the eqpt_config json file')
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exit()
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cls = getattr(elements, typ)
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el = cls(**el_config)
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g.add_node(el)
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nodes = {k.uid: k for k in g.nodes()}
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for cx in json_data['connections']:
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from_node, to_node = cx['from_node'], cx['to_node']
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try:
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if isinstance(nodes[from_node], Fiber):
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edge_length = nodes[from_node].params.length
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# print(from_node)
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# print(edge_length)
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else:
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edge_length = 0.01
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g.add_edge(nodes[from_node], nodes[to_node], weight = edge_length)
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except KeyError:
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msg = f'In {__name__} network_from_json function:\n\tcan not find {from_node} or {to_node} defined in {cx}'
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print(msg)
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exit(1)
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return g
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def network_to_json(network):
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data = {
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'elements': [n.to_json for n in network]
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}
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connections = {
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'connections': [{"from_node": n.uid,
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"to_node": next_n.uid}
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for n in network
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for next_n in network.successors(n) if next_n is not None]
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}
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data.update(connections)
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return data
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def select_edfa(raman_allowed, gain_target, power_target, equipment, uid):
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"""amplifer selection algorithm
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@Orange Jean-Luc Augé
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"""
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Edfa_list = namedtuple('Edfa_list', 'variety power gain_min nf')
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TARGET_EXTENDED_GAIN = equipment['Span']['default'].target_extended_gain
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edfa_dict = equipment['Edfa']
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pin = power_target - gain_target
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#create 2 list of available amplifiers with relevant attributs for their selection
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#edfa list with :
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#extended gain min allowance of 3dB: could be parametrized, but a bit complex
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#extended gain max allowance TARGET_EXTENDED_GAIN is coming from eqpt_config.json
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#power attribut include power AND gain limitations
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edfa_list = [Edfa_list(
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variety=edfa_variety,
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power=min(
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pin
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+edfa.gain_flatmax
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+TARGET_EXTENDED_GAIN,
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edfa.p_max
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)
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-power_target,
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gain_min=
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gain_target+3
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-edfa.gain_min,
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nf=edfa_nf(gain_target, edfa_variety, equipment)) \
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for edfa_variety, edfa in edfa_dict.items()
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if (edfa.allowed_for_design and not edfa.raman)]
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#consider a Raman list because of different gain_min requirement:
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#do not allow extended gain min for Raman
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raman_list = [Edfa_list(
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variety=edfa_variety,
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power=min(
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pin
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+edfa.gain_flatmax
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+TARGET_EXTENDED_GAIN,
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edfa.p_max
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)
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-power_target,
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gain_min=
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gain_target
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-edfa.gain_min,
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nf=edfa_nf(gain_target, edfa_variety, equipment))
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for edfa_variety, edfa in edfa_dict.items()
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if (edfa.allowed_for_design and edfa.raman)] \
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if raman_allowed else []
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#merge raman and edfa lists
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amp_list = edfa_list + raman_list
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#filter on min gain limitation:
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acceptable_gain_min_list = [x for x in amp_list if x.gain_min>0]
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if len(acceptable_gain_min_list) < 1:
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#do not take this empty list into account for the rest of the code
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#but issue a warning to the user and do not consider Raman
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#Raman below min gain should not be allowed because i is meant to be a design requirement
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#and raman padding at the amplifier input is impossible!
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if len(edfa_list) < 1:
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print(
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f'\x1b[1;31;40m'\
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+ f'CRITICAL _ ABORT: auto_design could not find any amplifier \
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to satisfy min gain requirement in node {uid} \
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please increase span fiber padding'\
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+ '\x1b[0m'
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)
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exit()
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else:
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print(
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f'\x1b[1;31;40m'\
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+ f'WARNING: target gain in node {uid} is below all available amplifiers min gain: \
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amplifier input padding will be assumed, consider increase span fiber padding instead'\
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+ '\x1b[0m'
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)
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acceptable_gain_min_list = edfa_list
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#filter on gain+power limitation:
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#this list checks both the gain and the power requirement
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#because of the way .power is calculated in the list
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acceptable_power_list = [x for x in acceptable_gain_min_list if x.power>0]
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if len(acceptable_power_list) < 1:
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#no amplifier satisfies the required power, so pick the highest power(s):
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power_max = max(acceptable_gain_min_list, key=attrgetter('power')).power
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#check and pick if other amplifiers may have a similar gain/power
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#allow a 0.3dB power range
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#this allows to chose an amplifier with a better NF subsequentely
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acceptable_power_list = [x for x in acceptable_gain_min_list
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if x.power-power_max>-0.3]
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# gain and power requirements are resolved,
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# =>chose the amp with the best NF among the acceptable ones:
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selected_edfa = min(acceptable_power_list, key=attrgetter('nf')) #filter on NF
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#check what are the gain and power limitations of this amp
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power_reduction = round(min(selected_edfa.power, 0),2)
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if power_reduction < -0.5:
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print(
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f'\x1b[1;31;40m'\
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+ f'WARNING: target gain and power in node {uid}\n \
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is beyond all available amplifiers capabilities and/or extended_gain_range:\n\
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a power reduction of {power_reduction} is applied\n'\
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+ '\x1b[0m'
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)
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return selected_edfa.variety, power_reduction
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def target_power(network, node, equipment): #get_fiber_dp
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SPAN_LOSS_REF = 20
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POWER_SLOPE = 0.3
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power_mode = equipment['Span']['default'].power_mode
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dp_range = list(equipment['Span']['default'].delta_power_range_db)
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node_loss = span_loss(network, node)
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try:
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dp = round2float((node_loss - SPAN_LOSS_REF) * POWER_SLOPE, dp_range[2])
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dp = max(dp_range[0], dp)
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dp = min(dp_range[1], dp)
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except KeyError:
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print(f'invalid delta_power_range_db definition in eqpt_config[Span]'
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f'delta_power_range_db: [lower_bound, upper_bound, step]')
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exit()
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if isinstance(node, Roadm):
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dp = 0
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return dp
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def prev_node_generator(network, node):
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"""fused spans interest:
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iterate over all predecessors while they are Fused or Fiber type"""
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try:
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prev_node = next(n for n in network.predecessors(node))
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except StopIteration:
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msg = f'In {__name__} prev_node_generator function:\n\t{node.uid} is not properly connected, please check network topology'
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print(msg)
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logger.critical(msg)
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exit(1)
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# yield and re-iterate
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if isinstance(prev_node, Fused) or isinstance(node, Fused):
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yield prev_node
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yield from prev_node_generator(network, prev_node)
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else:
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StopIteration
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def next_node_generator(network, node):
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"""fused spans interest:
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iterate over all successors while they are Fused or Fiber type"""
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try:
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next_node = next(n for n in network.successors(node))
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except StopIteration:
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print(f'In {__name__} next_node_generator function:\n\t{node.uid} is not properly connected, please check network topology')
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exit(1)
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# yield and re-iterate
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if isinstance(next_node, Fused) or isinstance(node, Fused):
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yield next_node
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yield from next_node_generator(network, next_node)
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else:
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StopIteration
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def span_loss(network, node):
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"""Fused span interest:
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return the total span loss of all the fibers spliced by a Fused node"""
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loss = node.loss if node.passive else 0
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try:
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prev_node = next(n for n in network.predecessors(node))
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if isinstance(prev_node, Fused):
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loss += sum(n.loss for n in prev_node_generator(network, node))
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except StopIteration:
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pass
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try:
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next_node = next(n for n in network.successors(node))
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if isinstance(next_node, Fused):
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loss += sum(n.loss for n in next_node_generator(network, node))
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except StopIteration:
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pass
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return loss
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def find_first_node(network, node):
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"""Fused node interest:
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returns the 1st node at the origin of a succession of fused nodes
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(aka no amp in between)"""
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this_node = node
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for this_node in prev_node_generator(network, node):
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pass
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return this_node
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def find_last_node(network, node):
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"""Fused node interest:
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returns the last node in a succession of fused nodes
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(aka no amp in between)"""
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this_node = node
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for this_node in next_node_generator(network, node):
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pass
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return this_node
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def set_amplifier_voa(amp, power_target, power_mode):
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VOA_MARGIN = 1 #do not maximize the VOA optimization
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if amp.out_voa is None:
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if power_mode:
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gain_target = amp.effective_gain
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voa = min(amp.params.p_max-power_target,
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amp.params.gain_flatmax-amp.effective_gain)
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voa = max(round2float(max(voa, 0), 0.5) - VOA_MARGIN, 0) if amp.params.out_voa_auto else 0
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amp.delta_p = amp.delta_p + voa
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amp.effective_gain = amp.effective_gain + voa
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else:
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voa = 0 # no output voa optimization in gain mode
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amp.out_voa = voa
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def set_egress_amplifier(network, roadm, equipment, pref_total_db):
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power_mode = equipment['Span']['default'].power_mode
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next_oms = (n for n in network.successors(roadm) if not isinstance(n, Transceiver))
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for oms in next_oms:
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#go through all the OMS departing from the Roadm
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node = roadm
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prev_node = roadm
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next_node = oms
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# if isinstance(next_node, Fused): #support ROADM wo egress amp for metro applications
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# node = find_last_node(next_node)
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# next_node = next(n for n in network.successors(node))
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# next_node = find_last_node(next_node)
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prev_dp = getattr(node.params, 'target_pch_out_db', 0)
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dp = prev_dp
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prev_voa = 0
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voa = 0
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while True:
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#go through all nodes in the OMS (loop until next Roadm instance)
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if isinstance(node, Edfa):
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node_loss = span_loss(network, prev_node)
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voa = node.out_voa if node.out_voa else 0
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if node.delta_p is None:
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dp = target_power(network, next_node, equipment)
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else:
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dp = node.delta_p
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gain_from_dp = node_loss + dp - prev_dp + prev_voa
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if node.effective_gain is None or power_mode:
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gain_target = gain_from_dp
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else: #gain mode with effective_gain
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gain_target = node.effective_gain
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dp = prev_dp - node_loss + gain_target
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#print(node.delta_p, dp, gain_target)
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power_target = pref_total_db + dp
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raman_allowed = False
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if isinstance(prev_node, Fiber):
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max_fiber_lineic_loss_for_raman = \
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equipment['Span']['default'].max_fiber_lineic_loss_for_raman
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raman_allowed = prev_node.params.loss_coef < max_fiber_lineic_loss_for_raman
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if node.params.type_variety == '' :
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edfa_variety, power_reduction = select_edfa(raman_allowed,
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gain_target, power_target, equipment, node.uid)
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extra_params = equipment['Edfa'][edfa_variety]
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node.params.update_params(extra_params.__dict__)
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dp += power_reduction
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gain_target += power_reduction
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elif node.params.raman and not raman_allowed:
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print(
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f'\x1b[1;31;40m'\
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+ f'WARNING: raman is used in node {node.uid}\n \
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but fiber lineic loss is above threshold\n'\
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+ '\x1b[0m'
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)
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node.delta_p = dp if power_mode else None
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node.effective_gain = gain_target
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set_amplifier_voa(node, power_target, power_mode)
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if isinstance(next_node, Roadm) or isinstance(next_node, Transceiver):
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break
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prev_dp = dp
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prev_voa = voa
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prev_node = node
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node = next_node
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# print(f'{node.uid}')
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next_node = next(n for n in network.successors(node))
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def add_egress_amplifier(network, node):
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next_nodes = [n for n in network.successors(node)
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if not (isinstance(n, Transceiver) or isinstance(n, Fused) or isinstance(n, Edfa))]
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#no amplification for fused spans or TRX
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for i, next_node in enumerate(next_nodes):
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network.remove_edge(node, next_node)
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amp = Edfa(
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uid = f'Edfa{i}_{node.uid}',
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params = {},
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metadata = {
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'location': {
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'latitude': (node.lat * 2 + next_node.lat * 2) / 4,
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'longitude': (node.lng * 2 + next_node.lng * 2) / 4,
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'city': node.loc.city,
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'region': node.loc.region,
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}
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},
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operational = {
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'gain_target': None,
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'tilt_target': 0,
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})
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network.add_node(amp)
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if isinstance(node,Fiber):
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edgeweight = node.params.length
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else:
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edgeweight = 0.01
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network.add_edge(node, amp, weight = edgeweight)
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network.add_edge(amp, next_node, weight = 0.01)
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def calculate_new_length(fiber_length, bounds, target_length):
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if fiber_length < bounds.stop:
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return fiber_length, 1
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n_spans = int(fiber_length // target_length)
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length1 = fiber_length / (n_spans+1)
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delta1 = target_length-length1
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result1 = (length1, n_spans+1)
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length2 = fiber_length / n_spans
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delta2 = length2-target_length
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result2 = (length2, n_spans)
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if (bounds.start<=length1<=bounds.stop) and not(bounds.start<=length2<=bounds.stop):
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result = result1
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elif (bounds.start<=length2<=bounds.stop) and not(bounds.start<=length1<=bounds.stop):
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result = result2
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else:
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result = result1 if delta1 < delta2 else result2
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return result
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def split_fiber(network, fiber, bounds, target_length, equipment):
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new_length, n_spans = calculate_new_length(fiber.length, bounds, target_length)
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if n_spans == 1:
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return
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try:
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next_node = next(network.successors(fiber))
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prev_node = next(network.predecessors(fiber))
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except StopIteration:
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print(f'In {__name__} split_fiber function:\n\t{fiber.uid} is not properly connected, please check network topology')
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exit()
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network.remove_node(fiber)
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fiber_params = fiber.params._asdict()
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fiber_params['length'] = new_length / UNITS[fiber.params.length_units]
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fiber_params['con_in'] = fiber.con_in
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fiber_params['con_out'] = fiber.con_out
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f = interp1d([prev_node.lng, next_node.lng], [prev_node.lat, next_node.lat])
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xpos = [prev_node.lng + (next_node.lng - prev_node.lng) * (n+1)/(n_spans+1) for n in range(n_spans)]
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ypos = f(xpos)
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for span, lng, lat in zip(range(n_spans), xpos, ypos):
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new_span = Fiber(uid = f'{fiber.uid}_({span+1}/{n_spans})',
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metadata = {
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'location': {
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'latitude': lat,
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'longitude': lng,
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'city': fiber.loc.city,
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'region': fiber.loc.region,
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}
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},
|
|
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(network, fibers, default_con_in, default_con_out, EOL):
|
|
for fiber in fibers:
|
|
if fiber.con_in is None: fiber.con_in = default_con_in
|
|
if fiber.con_out is None: fiber.con_out = default_con_out
|
|
next_node = next(n for n in network.successors(fiber))
|
|
if not isinstance(next_node, Fused):
|
|
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)
|
|
default_con_in = default_span_data.con_in
|
|
default_con_out = default_span_data.con_out
|
|
padding = default_span_data.padding
|
|
|
|
#set roadm loss for gain_mode before to build network
|
|
fibers = [f for f in network.nodes() if isinstance(f, Fiber)]
|
|
add_connector_loss(network, fibers, default_con_in, default_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)
|
|
|