def test_csv_response_generation(json_input, csv_output):
""" tests if generated csv is consistant with expected generation
same columns (order not important)
"""
with open(json_input) as jsonfile:
json_data = load(jsonfile)
equipment = load_equipment(eqpt_filename)
csv_filename = str(csv_output)+'.csv'
with open(csv_filename, 'w', encoding='utf-8') as fcsv:
jsontocsv(json_data, equipment, fcsv)
expected_csv_filename = str(csv_output)+'_expected.csv'
# expected header
# csv_header = \
# [
# 'response-id',
# 'source',
# 'destination',
# 'path_bandwidth',
# 'Pass?',
# 'nb of tsp pairs',
# 'total cost',
# 'transponder-type',
# 'transponder-mode',
# 'OSNR-0.1nm',
# 'SNR-0.1nm',
# 'SNR-bandwidth',
# 'baud rate (Gbaud)',
# 'input power (dBm)',
# 'path'
# ]
resp = read_csv(csv_filename)
unlink(csv_filename)
expected_resp = read_csv(expected_csv_filename)
resp_header = list(resp.head(0))
expected_resp_header = list(expected_resp.head(0))
# check that headers are the same
resp_header.sort()
expected_resp_header.sort()
print('headers are differents')
print(resp_header)
print(expected_resp_header)
assert resp_header == expected_resp_header
# for each header checks that the output are as expected
resp.sort_values(by=['response-id'])
expected_resp.sort_values(by=['response-id'])
for column in expected_resp:
assert list(resp[column].fillna('')) == list(expected_resp[column].fillna(''))
print('results are different')
print(list(resp[column]))
print(list(expected_resp[column]))
print(type(list(resp[column])[-1]))
def launch_cli(network, data, equipment):
""" Compute requests using network, data and equipment with client line interface
"""
propagatedpths, reversed_propagatedpths, rqs = compute_requests(
network, data, equipment)
#Generate the output
if ARGS.output:
result = []
# assumes that list of rqs and list of propgatedpths have same order
for i, pth in enumerate(propagatedpths):
result.append(
Result_element(rqs[i], pth, reversed_propagatedpths[i]))
temp = path_result_json(result)
fnamecsv = f'{str(ARGS.output)[0:len(str(ARGS.output))-len(str(ARGS.output.suffix))]}.csv'
fnamejson = f'{str(ARGS.output)[0:len(str(ARGS.output))-len(str(ARGS.output.suffix))]}.json'
with open(fnamejson, 'w', encoding='utf-8') as fjson:
fjson.write(
dumps(path_result_json(result), indent=2, ensure_ascii=False))
with open(fnamecsv, "w", encoding='utf-8') as fcsv:
jsontocsv(temp, equipment, fcsv)
print('\x1b[1;34;40m' +
f'saving in {ARGS.output} and {fnamecsv}' + '\x1b[0m')
Reads JSON path result file in accordance with the Yang model for requesting
path computation and writes results to a CSV file.
See: draft-ietf-teas-yang-path-computation-01.txt
"""
from argparse import ArgumentParser
from pathlib import Path
from json import loads
from gnpy.core.equipment import load_equipment
from gnpy.core.request import jsontocsv
parser = ArgumentParser(description = 'A function that writes json path results in an excel sheet.')
parser.add_argument('filename', nargs='?', type = Path)
parser.add_argument('output_filename', nargs='?', type = Path)
parser.add_argument('eqpt_filename', nargs='?', type = Path, default=Path(__file__).parent / 'eqpt_config.json')
if __name__ == '__main__':
args = parser.parse_args()
with open(args.output_filename, 'w', encoding='utf-8') as file:
with open(args.filename, encoding='utf-8') as f:
print(f'Reading {args.filename}')
json_data = loads(f.read())
equipment = load_equipment(args.eqpt_filename)
print(f'Writing in {args.output_filename}')
jsontocsv(json_data,equipment,file)
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', f'{round(mean(p[-1].snr),2)}',\
f'{round(mean(p[-1].snr+lin2db(rqs[i].baud_rate/(12.5e9))),2)}',\
f'{rqs[i].OSNR}', f'{rqs[i].tsp_mode}' , f'{round(rqs[i].path_bandwidth * 1e-9,2)}' , f'{ceil(rqs[i].path_bandwidth / rqs[i].bit_rate) }']
else:
line = [f'{rqs[i].request_id}',f' {rqs[i].source} to {rqs[i].destination} : not feasible ']
data.append(line)
col_width = max(len(word) for row in data for word in row[2:]) # padding
firstcol_width = max(len(row[0]) for row in data ) # padding
secondcol_width = max(len(row[1]) for row in data ) # padding
for row in data:
firstcol = ''.join(row[0].ljust(firstcol_width))
secondcol = ''.join(row[1].ljust(secondcol_width))
remainingcols = ''.join(word.center(col_width,' ') for word in row[2:])
print(f'{firstcol} {secondcol} {remainingcols}')
if args.output :
result = []
# assumes that list of rqs and list of propgatedpths have same order
for i,p in enumerate(propagatedpths):
result.append(Result_element(rqs[i],p))
temp = path_result_json(result)
fnamecsv = f'{str(args.output)[0:len(str(args.output))-len(str(args.output.suffix))]}.csv'
fnamejson = f'{str(args.output)[0:len(str(args.output))-len(str(args.output.suffix))]}.json'
with open(fnamejson, 'w', encoding='utf-8') as f:
f.write(dumps(path_result_json(result), indent=2, ensure_ascii=False))
with open(fnamecsv,"w", encoding='utf-8') as fcsv :
jsontocsv(temp,equipment,fcsv)
print('\x1b[1;34;40m'+f'saving in {args.output} and {fnamecsv}'+ '\x1b[0m')
def main(args):
""" main function that calls all functions
"""
LOGGER.info(
f'Computing path requests {args.service_filename} into JSON format')
print('\x1b[1;34;40m' +\
f'Computing path requests {args.service_filename} into JSON format'+ '\x1b[0m')
# for debug
# print( args.eqpt_filename)
try:
data = load_requests(args.service_filename, args.eqpt_filename,
args.bidir)
equipment = load_equipment(args.eqpt_filename)
network = load_network(args.network_filename, equipment)
except EquipmentConfigError as this_e:
print(
f'{ansi_escapes.red}Configuration error in the equipment library:{ansi_escapes.reset} {this_e}'
)
exit(1)
except NetworkTopologyError as this_e:
print(
f'{ansi_escapes.red}Invalid network definition:{ansi_escapes.reset} {this_e}'
)
exit(1)
except ConfigurationError as this_e:
print(
f'{ansi_escapes.red}Configuration error:{ansi_escapes.reset} {this_e}'
)
exit(1)
except ServiceError as this_e:
print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {this_e}')
exit(1)
# Build the network once using the default power defined in SI in eqpt config
# TODO power density: db2linp(ower_dbm": 0)/power_dbm": 0 * nb channels as defined by
# spacing, f_min and f_max
p_db = equipment['SI']['default'].power_dbm
p_total_db = p_db + lin2db(automatic_nch(equipment['SI']['default'].f_min,\
equipment['SI']['default'].f_max, equipment['SI']['default'].spacing))
build_network(network, equipment, p_db, p_total_db)
save_network(args.network_filename, network)
oms_list = build_oms_list(network, equipment)
try:
rqs = requests_from_json(data, equipment)
except ServiceError as this_e:
print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {this_e}')
exit(1)
# check that request ids are unique. Non unique ids, may
# mess the computation: better to stop the computation
all_ids = [r.request_id for r in rqs]
if len(all_ids) != len(set(all_ids)):
for item in list(set(all_ids)):
all_ids.remove(item)
msg = f'Requests id {all_ids} are not unique'
LOGGER.critical(msg)
exit()
try:
rqs = correct_route_list(network, rqs)
except ServiceError as this_e:
print(f'{ansi_escapes.red}Service error:{ansi_escapes.reset} {this_e}')
exit(1)
# pths = compute_path(network, equipment, rqs)
dsjn = disjunctions_from_json(data)
print('\x1b[1;34;40m' + f'List of disjunctions' + '\x1b[0m')
print(dsjn)
# need to warn or correct in case of wrong disjunction form
# disjunction must not be repeated with same or different ids
dsjn = correct_disjn(dsjn)
# Aggregate demands with same exact constraints
print('\x1b[1;34;40m' + f'Aggregating similar requests' + '\x1b[0m')
rqs, dsjn = requests_aggregation(rqs, dsjn)
# TODO export novel set of aggregated demands in a json file
print('\x1b[1;34;40m' + 'The following services have been requested:' +
'\x1b[0m')
print(rqs)
print('\x1b[1;34;40m' + f'Computing all paths with constraints' +
'\x1b[0m')
try:
pths = compute_path_dsjctn(network, equipment, rqs, dsjn)
except DisjunctionError as this_e:
print(
f'{ansi_escapes.red}Disjunction error:{ansi_escapes.reset} {this_e}'
)
exit(1)
print('\x1b[1;34;40m' + f'Propagating on selected path' + '\x1b[0m')
propagatedpths, reversed_pths, reversed_propagatedpths = \
compute_path_with_disjunction(network, equipment, rqs, pths)
# Note that deepcopy used in compute_path_with_disjunction returns
# a list of nodes which are not belonging to network (they are copies of the node objects).
# so there can not be propagation on these nodes.
pth_assign_spectrum(pths, rqs, oms_list, reversed_pths)
print('\x1b[1;34;40m' + f'Result summary' + '\x1b[0m')
header = ['req id', ' demand', ' snr@bandwidth A-Z (Z-A)', ' [email protected] A-Z (Z-A)',\
' Receiver minOSNR', ' mode', ' Gbit/s', ' nb of tsp pairs',\
'N,M or blocking reason']
data = []
data.append(header)
for i, this_p in enumerate(propagatedpths):
rev_pth = reversed_propagatedpths[i]
if rev_pth and this_p:
psnrb = f'{round(mean(this_p[-1].snr),2)} ({round(mean(rev_pth[-1].snr),2)})'
psnr = f'{round(mean(this_p[-1].snr_01nm), 2)}' +\
f' ({round(mean(rev_pth[-1].snr_01nm),2)})'
elif this_p:
psnrb = f'{round(mean(this_p[-1].snr),2)}'
psnr = f'{round(mean(this_p[-1].snr_01nm),2)}'
try:
if rqs[i].blocking_reason in BLOCKING_NOPATH:
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} :',\
f'-', f'-', f'-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',\
f'-', f'{rqs[i].blocking_reason}']
else:
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', psnrb,\
psnr, f'-', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9, 2)}',\
f'-', f'{rqs[i].blocking_reason}']
except AttributeError:
line = [f'{rqs[i].request_id}', f' {rqs[i].source} to {rqs[i].destination} : ', psnrb,\
psnr, f'{rqs[i].OSNR}', f'{rqs[i].tsp_mode}', f'{round(rqs[i].path_bandwidth * 1e-9,2)}',\
f'{ceil(rqs[i].path_bandwidth / rqs[i].bit_rate) }', f'({rqs[i].N},{rqs[i].M})']
data.append(line)
col_width = max(len(word) for row in data for word in row[2:]) # padding
firstcol_width = max(len(row[0]) for row in data) # padding
secondcol_width = max(len(row[1]) for row in data) # padding
for row in data:
firstcol = ''.join(row[0].ljust(firstcol_width))
secondcol = ''.join(row[1].ljust(secondcol_width))
remainingcols = ''.join(
word.center(col_width, ' ') for word in row[2:])
print(f'{firstcol} {secondcol} {remainingcols}')
print('\x1b[1;33;40m'+f'Result summary shows mean SNR and OSNR (average over all channels)' +\
'\x1b[0m')
if args.output:
result = []
# assumes that list of rqs and list of propgatedpths have same order
for i, pth in enumerate(propagatedpths):
result.append(
Result_element(rqs[i], pth, reversed_propagatedpths[i]))
temp = path_result_json(result)
fnamecsv = f'{str(args.output)[0:len(str(args.output))-len(str(args.output.suffix))]}.csv'
fnamejson = f'{str(args.output)[0:len(str(args.output))-len(str(args.output.suffix))]}.json'
with open(fnamejson, 'w', encoding='utf-8') as fjson:
fjson.write(
dumps(path_result_json(result), indent=2, ensure_ascii=False))
with open(fnamecsv, "w", encoding='utf-8') as fcsv:
jsontocsv(temp, equipment, fcsv)
print('\x1b[1;34;40m' +
f'saving in {args.output} and {fnamecsv}' + '\x1b[0m')
print(pths)
test = compute_path(network, equipment, pths)
#TODO write results
header = ['demand', 'snr@bandwidth', '[email protected]', 'Receiver minOSNR']
data = []
data.append(header)
for i, p in enumerate(test):
if p:
line = [f'{pths[i].source} to {pths[i].destination} : ', f'{round(mean(p[-1].snr),2)}',\
f'{round(mean(p[-1].snr+lin2db(pths[i].baud_rate/(12.5e9))),2)}',\
f'{pths[i].OSNR}']
else:
line = [f'no path from {pths[i].source} to {pths[i].destination} ']
data.append(line)
col_width = max(len(word) for row in data for word in row) # padding
for row in data:
print(''.join(word.ljust(col_width) for word in row))
if args.output:
result = []
for p in test:
result.append(Result_element(pths[test.index(p)], p))
with open(args.output, 'w') as f:
f.write(dumps(path_result_json(result), indent=2))
fnamecsv = next(s for s in args.output.split('.')) + '.csv'
with open(fnamecsv, "w") as fcsv:
jsontocsv(path_result_json(result), equipment, fcsv)