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Merge pull request #224 from Orange-OpenSource/auto_design3

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Auto design3
This commit is contained in:
James
2019-04-18 11:42:09 -04:00
committed by GitHub
parent 6e94834033 0fee63fa81
commit 9c440764c7
2 changed files with 94 additions and 53 deletions
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143
gnpy/core/network.py
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@@ -97,13 +97,18 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid):
"""amplifer selection algorithm """amplifer selection algorithm
@Orange Jean-Luc Augé @Orange Jean-Luc Augé
""" """
Edfa_list = namedtuple('Edfa_list', 'raman variety power gain_min nf') Edfa_list = namedtuple('Edfa_list', 'variety power gain_min nf')
TARGET_EXTENDED_GAIN = equipment['Span']['default'].target_extended_gain TARGET_EXTENDED_GAIN = equipment['Span']['default'].target_extended_gain
edfa_dict = equipment['Edfa'] edfa_dict = equipment['Edfa']
pin = power_target - gain_target pin = power_target - gain_target
#create 2 list of available amplifiers with relevant attributs 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( edfa_list = [Edfa_list(
raman=edfa.raman,
variety=edfa_variety, variety=edfa_variety,
power=min( power=min(
pin pin
@@ -117,49 +122,75 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid):
-edfa.gain_min, -edfa.gain_min,
nf=edfa_nf(gain_target, edfa_variety, equipment)) \ nf=edfa_nf(gain_target, edfa_variety, equipment)) \
for edfa_variety, edfa in edfa_dict.items() for edfa_variety, edfa in edfa_dict.items()
if edfa.allowed_for_design] if (edfa.allowed_for_design and not edfa.raman)]
#filter on raman restriction #consider a Raman list because of different gain_min requirement:
raman_filter = lambda edfa: (edfa.raman and raman_allowed) or not edfa.raman #do not allow extended gain min for Raman
edfa_list = list(filter(raman_filter, edfa_list)) raman_list = [Edfa_list(
#print(f'\n{uid}, gain {gain_target}, {power_target}') variety=edfa_variety,
#print('edfa',edfa_list) 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: #filter on min gain limitation:
#consider gain_target+3 to allow some operation below min gain acceptable_gain_min_list = [x for x in amp_list if x.gain_min>0]
#(~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: if len(acceptable_gain_min_list) < 1:
#do not take this empty list into account for the rest of the code #do not take this empty list into account for the rest of the code
#but issue a warning to the user #but issue a warning to the user and do not consider Raman
print( #Raman below min gain should not be allowed because i is meant to be a design requirement
f'\x1b[1;31;40m'\ #and raman padding at the amplifier input is impossible!
+ 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: if len(edfa_list) < 1:
acceptable_power_list = \ print(
list(filter(lambda x : x.power>=0, edfa_list)) f'\x1b[1;31;40m'\
+ f'CRITICAL _ ABORT: auto_design could not find any amplifier \
to satisfy min gain requirement in node {uid} \
please increase span fiber padding'\
+ '\x1b[0m'
)
exit()
else:
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 span fiber padding instead'\
+ '\x1b[0m'
)
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: if len(acceptable_power_list) < 1:
#no amplifier satisfies the required power, so pick the highest power: #no amplifier satisfies the required power, so pick the highest power(s):
power_max = max(edfa_list, key=attrgetter('power')).power power_max = max(acceptable_gain_min_list, key=attrgetter('power')).power
#pick up all amplifiers that share this max gain: #check and pick if other amplifiers may have a similar gain/power
acceptable_power_list = \ #allow a 0.3dB power range
list(filter(lambda x : x.power-power_max>-0.3, edfa_list)) #this allows to chose an amplifier with a better NF subsequentely
#print('power', acceptable_power_list) acceptable_power_list = [x for x in acceptable_gain_min_list
if x.power-power_max>-0.3]
# debug:
# print(gain_target, power_target, '=>\n',acceptable_power_list)
# gain and power requirements are resolved, # gain and power requirements are resolved,
# =>chose the amp with the best NF among the acceptable ones: # =>chose the amp with the best NF among the acceptable ones:
selected_edfa = min(acceptable_power_list, key=attrgetter('nf')) #filter on NF 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) power_reduction = round(min(selected_edfa.power, 0),2)
if power_reduction < -0.5: if power_reduction < -0.5:
print( print(
@@ -168,7 +199,8 @@ def select_edfa(raman_allowed, gain_target, power_target, equipment, uid):
is beyond all available amplifiers capabilities and/or extended_gain_range:\n\ is beyond all available amplifiers capabilities and/or extended_gain_range:\n\
a power reduction of {power_reduction} is applied\n'\ a power reduction of {power_reduction} is applied\n'\
+ '\x1b[0m' + '\x1b[0m'
) )
return selected_edfa.variety, power_reduction return selected_edfa.variety, power_reduction
@@ -295,8 +327,7 @@ def set_egress_amplifier(network, roadm, equipment, pref_total_db):
#go through all nodes in the OMS (loop until next Roadm instance) #go through all nodes in the OMS (loop until next Roadm instance)
if isinstance(node, Edfa): if isinstance(node, Edfa):
node_loss = span_loss(network, prev_node) node_loss = span_loss(network, prev_node)
if node.out_voa: voa = node.out_voa if node.out_voa else 0
voa = node.out_voa
if node.delta_p is None: if node.delta_p is None:
dp = target_power(network, next_node, equipment) dp = target_power(network, next_node, equipment)
else: else:
@@ -308,20 +339,28 @@ def set_egress_amplifier(network, roadm, equipment, pref_total_db):
gain_target = node.effective_gain gain_target = node.effective_gain
dp = prev_dp - node_loss + gain_target dp = prev_dp - node_loss + gain_target
#print(node.delta_p, dp, gain_target) #print(node.delta_p, dp, gain_target)
power_target = pref_total_db + dp power_target = pref_total_db + dp
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
if node.params.type_variety == '' : 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, edfa_variety, power_reduction = select_edfa(raman_allowed,
gain_target, power_target, equipment, node.uid) gain_target, power_target, equipment, node.uid)
extra_params = equipment['Edfa'][edfa_variety] extra_params = equipment['Edfa'][edfa_variety]
node.params.update_params(extra_params.__dict__) node.params.update_params(extra_params.__dict__)
dp += power_reduction dp += power_reduction
gain_target += power_reduction gain_target += power_reduction
elif node.params.raman and not raman_allowed:
print(
f'\x1b[1;31;40m'\
+ f'WARNING: raman is used in node {node.uid}\n \
but fiber lineic loss is above threshold\n'\
+ '\x1b[0m'
)
node.delta_p = dp if power_mode else None node.delta_p = dp if power_mode else None
node.effective_gain = gain_target node.effective_gain = gain_target
@@ -436,13 +475,13 @@ def split_fiber(network, fiber, bounds, target_length, equipment):
edgeweight = 0.01 edgeweight = 0.01
network.add_edge(prev_node, next_node, weight = edgeweight) network.add_edge(prev_node, next_node, weight = edgeweight)
def add_connector_loss(fibers, con_in, con_out, EOL): def add_connector_loss(network, fibers, default_con_in, default_con_out, EOL):
for fiber in fibers: for fiber in fibers:
if fiber.con_in is None: fiber.con_in = con_in if fiber.con_in is None: fiber.con_in = default_con_in
if fiber.con_out is None: if fiber.con_out is None: fiber.con_out = default_con_out
fiber.con_out = con_out #con_out includes EOL next_node = next(n for n in network.successors(fiber))
else: if not isinstance(next_node, Fused):
fiber.con_out = fiber.con_out+EOL fiber.con_out += EOL
def add_fiber_padding(network, fibers, padding): def add_fiber_padding(network, fibers, padding):
"""last_fibers = (fiber for n in network.nodes() """last_fibers = (fiber for n in network.nodes()
@@ -473,13 +512,13 @@ def build_network(network, equipment, pref_ch_db, pref_total_db):
min_length = max(int(default_span_data.padding/0.2*1e3),50_000) min_length = max(int(default_span_data.padding/0.2*1e3),50_000)
bounds = range(min_length, max_length) bounds = range(min_length, max_length)
target_length = max(min_length, 90_000) target_length = max(min_length, 90_000)
con_in = default_span_data.con_in default_con_in = default_span_data.con_in
con_out = default_span_data.con_out + default_span_data.EOL default_con_out = default_span_data.con_out
padding = default_span_data.padding padding = default_span_data.padding
#set raodm loss for gain_mode before to build network #set roadm loss for gain_mode before to build network
fibers = [f for f in network.nodes() if isinstance(f, Fiber)] fibers = [f for f in network.nodes() if isinstance(f, Fiber)]
add_connector_loss(fibers, con_in, con_out, default_span_data.EOL) add_connector_loss(network, fibers, default_con_in, default_con_out, default_span_data.EOL)
add_fiber_padding(network, fibers, padding) add_fiber_padding(network, fibers, padding)
# don't group split fiber and add amp in the same loop # don't group split fiber and add amp in the same loop
# =>for code clarity (at the expense of speed): # =>for code clarity (at the expense of speed):

4
gnpy/core/request.py
View File

@@ -418,7 +418,7 @@ def propagate2(path, req, equipment, show=False):
path[-1].update_snr(req.tx_osnr, equipment['Roadm']['default'].add_drop_osnr) path[-1].update_snr(req.tx_osnr, equipment['Roadm']['default'].add_drop_osnr)
return infos return infos
def propagate_and_optimize_mode(path, req, equipment): def propagate_and_optimize_mode(path, req, equipment, show=False):
# if mode is unknown : loops on the modes starting from the highest baudrate fiting in the # if mode is unknown : loops on the modes starting from the highest baudrate fiting in the
# step 1: create an ordered list of modes based on baudrate # step 1: create an ordered list of modes based on baudrate
baudrate_to_explore = list(set([m['baud_rate'] for m in equipment['Transceiver'][req.tsp].mode baudrate_to_explore = list(set([m['baud_rate'] for m in equipment['Transceiver'][req.tsp].mode
@@ -442,6 +442,8 @@ def propagate_and_optimize_mode(path, req, equipment):
b, req.power, req.spacing) b, req.power, req.spacing)
for el in path: for el in path:
si = el(si) si = el(si)
if show:
print(el)
for m in modes_to_explore : for m in modes_to_explore :
if path[-1].snr is not None: if path[-1].snr is not None:
path[-1].update_snr(m['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr) path[-1].update_snr(m['tx_osnr'], equipment['Roadm']['default'].add_drop_osnr)