mirror of
https://github.com/Telecominfraproject/oopt-gnpy.git
synced 2025-11-03 19:47:46 +00:00
8eb5980ca9
I would like to create a package for distribution to PIP, and this seems like the path of least resistance. This is, apparently, the way for shippign arbitrary data with Python [1]. I've at least tried to make it user-firendly via adding a simple utility which just prints out whatever that data path is. [1] https://python-packaging.readthedocs.io/en/latest/non-code-files.html Change-Id: I220ecad84b1d57d01e3f98f15befc700bd97c0b8
90 lines
2.8 KiB
Python
90 lines
2.8 KiB
Python
#!/usr/bin/env python3
|
|
# -*- coding: utf-8 -*-
|
|
"""
|
|
Created on Tue Jan 30 12:32:00 2018
|
|
|
|
@author: jeanluc-auge
|
|
|
|
update an existing json file with all the 96ch txt files for a given amplifier type
|
|
amplifier type 'OA_type1' is hard coded but can be modified and other types added
|
|
returns an updated amplifier json file: output_json_file_name = 'edfa_config.json'
|
|
"""
|
|
import re
|
|
import sys
|
|
import json
|
|
import numpy as np
|
|
|
|
"""amplifier file names
|
|
convert a set of amplifier files + input json definiton file into a valid edfa_json_file:
|
|
nf_fit_coeff: NF 3rd order polynomial coefficients txt file
|
|
nf = f(dg)
|
|
with dg = gain_operational - gain_max
|
|
nf_ripple: NF ripple excursion txt file
|
|
gain_ripple: gain ripple txt file
|
|
dgt: dynamic gain txt file
|
|
input json file in argument (defult = 'OA.json')
|
|
|
|
the json input file should have the following fields:
|
|
{
|
|
"nf_fit_coeff": "nf_filename.txt",
|
|
"nf_ripple": "nf_ripple_filename.txt",
|
|
"gain_ripple": "DFG_filename.txt",
|
|
"dgt": "DGT_filename.txt",
|
|
}
|
|
|
|
"""
|
|
|
|
input_json_file_name = "OA.json" # default path
|
|
output_json_file_name = "default_edfa_config.json"
|
|
gain_ripple_field = "gain_ripple"
|
|
nf_ripple_field = "nf_ripple"
|
|
nf_fit_coeff = "nf_fit_coeff"
|
|
|
|
|
|
def read_file(field, file_name):
|
|
"""read and format the 96 channels txt files describing the amplifier NF and ripple
|
|
convert dfg into gain ripple by removing the mean component
|
|
"""
|
|
|
|
# with open(path + file_name,'r') as this_file:
|
|
# data = this_file.read()
|
|
# data.strip()
|
|
#data = re.sub(r"([0-9])([ ]{1,3})([0-9-+])",r"\1,\3",data)
|
|
#data = list(data.split(","))
|
|
#data = [float(x) for x in data]
|
|
data = np.loadtxt(file_name)
|
|
print(len(data), file_name)
|
|
if field == gain_ripple_field or field == nf_ripple_field:
|
|
# consider ripple excursion only to avoid redundant information
|
|
# because the max flat_gain is already given by the 'gain_flat' field in json
|
|
# remove the mean component
|
|
print(file_name, ', mean value =', data.mean(), ' is substracted')
|
|
data = data - data.mean()
|
|
data = data.tolist()
|
|
return data
|
|
|
|
|
|
def input_json(path):
|
|
"""read the json input file and add all the 96 channels txt files
|
|
create the output json file with output_json_file_name"""
|
|
with open(path, 'r') as edfa_json_file:
|
|
amp_text = edfa_json_file.read()
|
|
amp_dict = json.loads(amp_text)
|
|
|
|
for k, v in amp_dict.items():
|
|
if re.search(r'.txt$', str(v)):
|
|
amp_dict[k] = read_file(k, v)
|
|
|
|
amp_text = json.dumps(amp_dict, indent=4)
|
|
# print(amp_text)
|
|
with open(output_json_file_name, 'w') as edfa_json_file:
|
|
edfa_json_file.write(amp_text)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
if len(sys.argv) == 2:
|
|
path = sys.argv[1]
|
|
else:
|
|
path = input_json_file_name
|
|
input_json(path)
|