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0d3a86f1d8
* JSON file based on Orange operator typical input Signed-off-by: Jean-Luc Auge <jeanluc.auge@orange.com> * update of the standalone edfa model creation of a new amlifier2.py = v2 creation of a json parser build_oa_json.py the parser takes OA.json as input and newOA.json as output creation of a pytest verification module amplifier_pytest.py Signed-off-by: Jean-Luc Auge <jeanluc.auge@orange.com> * put the code together and transmission example script -basic dijkstra propagation -ase noise propagation based on amplifier model -fake nli noise propagation -integration of the amplifier model -interpolation function in the edfa class -code cleaning and units harmonization Signed-off-by: Jean-Luc Auge <jeanluc.auge@orange.com> * mv transmission_main_example and rm _main__ Signed-off-by: Jean-Luc Auge <jeanluc.auge@orange.com> * 2nd edfa model and build_oa_json file add a dual coil stages edfa model in case the nf polynomial fit is not known add a build_oa_json file that convert the input files in edfa_config.json file and pre-calculate the nf_model nf1, nf2 and delta_p parameters adding power violation check and input padding (below minimum gain) in the edfa model class Signed-off-by: Jean-Luc Auge <jeanluc.auge@orange.com>
164 lines
6.4 KiB
Python
164 lines
6.4 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Created on Tue Jan 30 12:32:00 2018
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@author: jeanluc-auge
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@comments about amplifier input files from Brian Taylor & Dave Boertjes
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update an existing json file with all the 96ch txt files for a given amplifier type
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amplifier type 'OA_type1' is hard coded but can be modified and other types added
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returns an updated amplifier json file: output_json_file_name = 'edfa_config.json'
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"""
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import re
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import sys
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import json
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import numpy as np
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from gnpy.core.utils import lin2db, db2lin
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"""amplifier file names
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convert a set of amplifier files + input json definiton file into a valid edfa_json_file:
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nf_fit_coeff: NF polynomial coefficients txt file (optional)
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nf_ripple: NF ripple excursion txt file
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dfg: gain txt file
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dgt: dynamic gain txt file
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input json file in argument (defult = 'OA.json')
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the json input file should have the following fields:
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{
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"gain_flatmax": 25,
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"gain_min": 15,
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"p_max": 21,
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"nf_fit_coeff": "pNFfit3.txt",
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"nf_ripple": "NFR_96.txt",
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"dfg": "DFG_96.txt",
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"dgt": "DGT_96.txt",
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"nf_model":
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{
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"enabled": true,
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"nf_min": 5.8,
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"nf_max": 10
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}
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}
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gain_flat = max flat gain (dB)
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gain_min = min gain (dB) : will consider an input VOA if below (TBD vs throwing an exception)
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p_max = max power (dBm)
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nf_fit = boolean (True, False) :
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if False nf_fit_coeff are ignored and nf_model fields are used
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"""
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input_json_file_name = "OA.json" #default path
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output_json_file_name = "edfa_config.json"
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param_field ="params"
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gain_min_field = "gain_min"
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gain_max_field = "gain_flatmax"
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gain_ripple_field = "dfg"
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nf_ripple_field = "nf_ripple"
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nf_fit_coeff = "nf_fit_coeff"
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nf_model_field = "nf_model"
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nf_model_enabled_field = "enabled"
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nf_min_field ="nf_min"
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nf_max_field = "nf_max"
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def read_file(field, file_name):
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"""read and format the 96 channels txt files describing the amplifier NF and ripple
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convert dfg into gain ripple by removing the mean component
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"""
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#with open(path + file_name,'r') as this_file:
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# data = this_file.read()
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#data.strip()
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#data = re.sub(r"([0-9])([ ]{1,3})([0-9-+])",r"\1,\3",data)
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#data = list(data.split(","))
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#data = [float(x) for x in data]
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data = np.loadtxt(file_name)
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if field == gain_ripple_field or field == nf_ripple_field:
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#consider ripple excursion only to avoid redundant information
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#because the max flat_gain is already given by the 'gain_flat' field in json
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#remove the mean component
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data = data - data.mean()
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data = data.tolist()
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return data
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def nf_model(amp_dict):
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if amp_dict[nf_model_field][nf_model_enabled_field] == True:
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gain_min = amp_dict[gain_min_field]
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gain_max = amp_dict[gain_max_field]
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nf_min = amp_dict[nf_model_field][nf_min_field]
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nf_max = amp_dict[nf_model_field][nf_max_field]
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#use NF estimation model based on NFmin and NFmax in json OA file
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delta_p = 5 #max power dB difference between 1st and 2nd stage coils
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#dB g1a = (1st stage gain) - (internal voa attenuation)
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g1a_min = gain_min - (gain_max-gain_min) - delta_p
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g1a_max = gain_max - delta_p
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#nf1 and nf2 are the nf of the 1st and 2nd stage coils
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#calculate nf1 and nf2 values that solve nf_[min/max] = nf1 + nf2 / g1a[min/max]
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nf2 = lin2db((db2lin(nf_min) - db2lin(nf_max)) / (1/db2lin(g1a_max)-1/db2lin(g1a_min)))
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nf1 = lin2db(db2lin(nf_min)- db2lin(nf2)/db2lin(g1a_max)) #expression (1)
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""" now checking and recalculating the results:
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recalculate delta_p to check it is within [1-6] boundaries
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This is to check that the nf_min and nf_max values from the json file
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make sense. If not a warning is printed """
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if nf1 < 4:
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print('1st coil nf calculated value {} is too low: revise inputs'.format(nf1))
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if nf2 < nf1 + 0.3 or nf2 > nf1 + 2:
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"""nf2 should be with [nf1+0.5 - nf1 +2] boundaries
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there shouldn't be very high nf differences between 2 coils
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=> recalculate delta_p
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"""
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nf2 = max(nf2, nf1+0.3)
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nf2 = min(nf2, nf1+2)
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g1a_max = lin2db(db2lin(nf2) / (db2lin(nf_min) - db2lin(nf1))) #use expression (1)
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delta_p = gain_max - g1a_max
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g1a_min = gain_min - (gain_max-gain_min) - delta_p
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if delta_p < 1 or delta_p > 6:
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#delta_p should be > 1dB and < 6dB => consider user warning if not
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print('1st coil vs 2nd coil calculated DeltaP {} is not valid: revise inputs'
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.format(delta_p))
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#check the calculated values for nf1 & nf2:
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nf_min_calc = lin2db(db2lin(nf1) + db2lin(nf2)/db2lin(g1a_max))
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nf_max_calc = lin2db(db2lin(nf1) + db2lin(nf2)/db2lin(g1a_min))
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if (abs(nf_min_calc-nf_min) > 0.01) or (abs(nf_max_calc-nf_max) > 0.01):
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print('nf model calculation failed with nf_min {} and nf_max {} calculated'
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.format(nf_min_calc, nf_max_calc))
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print('do not use the generated edfa_config.json file')
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else :
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(nf1, nf2, delta_p) = (0, 0, 0)
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return (nf1, nf2, delta_p)
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def input_json(path):
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"""read the json input file and add all the 96 channels txt files
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create the output json file with output_json_file_name"""
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with open(path,'r') as edfa_json_file:
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amp_text = edfa_json_file.read()
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amp_dict = json.loads(amp_text)
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for k, v in amp_dict.items():
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if re.search(r'.txt$',str(v)) :
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amp_dict[k] = read_file(k, v)
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#calculate nf of 1st and 2nd coil for the nf_model if 'enabled'==true
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(nf1, nf2, delta_p) = nf_model(amp_dict)
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#rename nf_min and nf_max in nf1 and nf2 after the nf model calculation:
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del amp_dict[nf_model_field][nf_min_field]
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del amp_dict[nf_model_field][nf_max_field]
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amp_dict[nf_model_field]['nf1'] = nf1
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amp_dict[nf_model_field]['nf2'] = nf2
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amp_dict[nf_model_field]['delta_p'] = delta_p
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#rename dfg into gain_ripple after removing the average part:
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amp_dict['gain_ripple'] = amp_dict.pop(gain_ripple_field)
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new_amp_dict = {}
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new_amp_dict[param_field] = amp_dict
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amp_text = json.dumps(new_amp_dict, indent=4)
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#print(amp_text)
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with open(output_json_file_name,'w') as edfa_json_file:
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edfa_json_file.write(amp_text)
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if __name__ == '__main__':
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if len(sys.argv) == 2:
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path = sys.argv[1]
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else:
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path = input_json_file_name
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input_json(path) |