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https://github.com/Telecominfraproject/oopt-gnpy.git
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d94dc51d88
This feature is intended to support designs such as OpenROADM where the line degree integrates a specific preamp/booster pair. In that case, it does not make sense for our autodesign to "pick an amplifier". The restrictions can be activated by: - Listing them in `eqpt_config.json`, so that they are effective for all ROADM instances. - On a per-ROADM basis within the Excel sheet or the JSON definitions. Restrictions apply to an entire ROADM as a whole, not to the individual degrees. If a per-degree exception is needed, the amplifier of this degree can be defined in the equipment sheet or in the network definition. If no booster amplifier should be placed on a degree, use the `Fused` node in place of an amplifier. Signed-off-by: Esther Le Rouzic <esther.lerouzic@orange.com> Co-authored-by: Jan Kundrát <jan.kundrat@telecominfraproject.com>
628 lines
25 KiB
Python
Executable File
628 lines
25 KiB
Python
Executable File
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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gnpy.core.convert
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=================
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This module contains utilities for converting between XLS and JSON.
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The input XLS file must contain sheets named "Nodes" and "Links".
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It may optionally contain a sheet named "Eqpt".
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In the "Nodes" sheet, only the "City" column is mandatory. The column "Type"
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can be determined automatically given the topology (e.g., if degree 2, ILA;
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otherwise, ROADM.) Incorrectly specified types (e.g., ILA for node of
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degree ≠ 2) will be automatically corrected.
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In the "Links" sheet, only the first three columns ("Node A", "Node Z" and
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"east Distance (km)") are mandatory. Missing "west" information is copied from
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the "east" information so that it is possible to input undirected data.
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"""
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from sys import exit
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try:
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from xlrd import open_workbook
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except ModuleNotFoundError:
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exit('Required: `pip install xlrd`')
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from argparse import ArgumentParser
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from collections import namedtuple, Counter, defaultdict
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from itertools import chain
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from json import dumps
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from pathlib import Path
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from difflib import get_close_matches
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from gnpy.core.utils import silent_remove
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import time
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all_rows = lambda sh, start=0: (sh.row(x) for x in range(start, sh.nrows))
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class Node(object):
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def __init__(self, **kwargs):
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super(Node, self).__init__()
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self.update_attr(kwargs)
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def update_attr(self, kwargs):
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clean_kwargs = {k:v for k,v in kwargs.items() if v !=''}
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for k,v in self.default_values.items():
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v = clean_kwargs.get(k,v)
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setattr(self, k, v)
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default_values = \
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{
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'city': '',
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'state': '',
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'country': '',
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'region': '',
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'latitude': 0,
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'longitude': 0,
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'node_type': 'ILA',
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'booster_restriction' : '',
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'preamp_restriction' : ''
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}
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class Link(object):
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"""attribtes from west parse_ept_headers dict
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+node_a, node_z, west_fiber_con_in, east_fiber_con_in
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"""
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def __init__(self, **kwargs):
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super(Link, self).__init__()
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self.update_attr(kwargs)
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self.distance_units = 'km'
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def update_attr(self, kwargs):
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clean_kwargs = {k:v for k,v in kwargs.items() if v !=''}
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for k,v in self.default_values.items():
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v = clean_kwargs.get(k,v)
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setattr(self, k, v)
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k = 'west' + k.split('east')[-1]
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v = clean_kwargs.get(k,v)
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setattr(self, k, v)
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def __eq__(self, link):
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return (self.from_city == link.from_city and self.to_city == link.to_city) \
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or (self.from_city == link.to_city and self.to_city == link.from_city)
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default_values = \
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{
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'from_city': '',
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'to_city': '',
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'east_distance': 80,
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'east_fiber': 'SSMF',
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'east_lineic': 0.2,
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'east_con_in': None,
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'east_con_out': None,
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'east_pmd': 0.1,
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'east_cable': ''
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}
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class Eqpt(object):
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def __init__(self, **kwargs):
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super(Eqpt, self).__init__()
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self.update_attr(kwargs)
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def update_attr(self, kwargs):
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clean_kwargs = {k:v for k,v in kwargs.items() if v !=''}
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for k,v in self.default_values.items():
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v_east = clean_kwargs.get(k,v)
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setattr(self, k, v_east)
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k = 'west' + k.split('east')[-1]
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v_west = clean_kwargs.get(k,v)
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setattr(self, k, v_west)
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default_values = \
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{
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'from_city': '',
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'to_city': '',
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'east_amp_type': '',
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'east_att_in': 0,
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'east_amp_gain': None,
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'east_amp_dp': None,
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'east_tilt': 0,
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'east_att_out': None
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}
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def read_header(my_sheet, line, slice_):
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""" return the list of headers !:= ''
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header_i = [(header, header_column_index), ...]
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in a {line, slice1_x, slice_y} range
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"""
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Param_header = namedtuple('Param_header', 'header colindex')
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try:
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header = [x.value.strip() for x in my_sheet.row_slice(line, slice_[0], slice_[1])]
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header_i = [Param_header(header,i+slice_[0]) for i, header in enumerate(header) if header != '']
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except Exception:
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header_i = []
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if header_i != [] and header_i[-1].colindex != slice_[1]:
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header_i.append(Param_header('',slice_[1]))
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return header_i
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def read_slice(my_sheet, line, slice_, header):
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"""return the slice range of a given header
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in a defined range {line, slice_x, slice_y}"""
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header_i = read_header(my_sheet, line, slice_)
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slice_range = (-1,-1)
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if header_i != []:
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try:
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slice_range = next((h.colindex,header_i[i+1].colindex) \
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for i,h in enumerate(header_i) if header in h.header)
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except Exception:
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pass
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return slice_range
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def parse_headers(my_sheet, input_headers_dict, headers, start_line, slice_in):
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"""return a dict of header_slice
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key = column index
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value = header name"""
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for h0 in input_headers_dict:
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slice_out = read_slice(my_sheet, start_line, slice_in, h0)
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iteration = 1
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while slice_out == (-1,-1) and iteration < 10:
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#try next lines
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#print(h0, iteration)
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slice_out = read_slice(my_sheet, start_line+iteration, slice_in, h0)
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iteration += 1
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if slice_out == (-1, -1):
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if h0 in ('east', 'Node A', 'Node Z', 'City') :
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print(f'\x1b[1;31;40m'+f'CRITICAL: missing _{h0}_ header: EXECUTION ENDS'+ '\x1b[0m')
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exit()
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else:
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print(f'missing header {h0}')
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elif not isinstance(input_headers_dict[h0], dict):
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headers[slice_out[0]] = input_headers_dict[h0]
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else:
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headers = parse_headers(my_sheet, input_headers_dict[h0], headers, start_line+1, slice_out)
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if headers == {}:
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print(f'\x1b[1;31;40m'+f'CRITICAL ERROR: could not find any header to read _ ABORT'+ '\x1b[0m')
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exit()
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return headers
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def parse_row(row, headers):
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#print([label for label in ept.values()])
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#print([i for i in ept.keys()])
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#print(row[i for i in ept.keys()])
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return {f: r.value for f, r in \
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zip([label for label in headers.values()], [row[i] for i in headers])}
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#if r.ctype != XL_CELL_EMPTY}
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def parse_sheet(my_sheet, input_headers_dict, header_line, start_line, column):
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headers = parse_headers(my_sheet, input_headers_dict, {}, header_line, (0,column))
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for row in all_rows(my_sheet, start=start_line):
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yield parse_row(row[0: column], headers)
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def sanity_check(nodes, links, nodes_by_city, links_by_city, eqpts_by_city):
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duplicate_links = []
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for l1 in links:
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for l2 in links:
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if l1 is not l2 and l1 == l2 and l2 not in duplicate_links:
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print(f'\nWARNING\n \
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link {l1.from_city}-{l1.to_city} is duplicate \
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\nthe 1st duplicate link will be removed but you should check Links sheet input')
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duplicate_links.append(l1)
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#if duplicate_links != []:
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#time.sleep(3)
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for l in duplicate_links:
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links.remove(l)
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try :
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test_nodes = [n for n in nodes_by_city if not n in links_by_city]
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test_links = [n for n in links_by_city if not n in nodes_by_city]
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test_eqpts = [n for n in eqpts_by_city if not n in nodes_by_city]
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assert (test_nodes == [] or test_nodes == [''])\
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and (test_links == [] or test_links ==[''])\
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and (test_eqpts == [] or test_eqpts ==[''])
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except AssertionError:
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print(f'CRITICAL error: \nNames in Nodes and Links sheets do no match, check:\
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\n{test_nodes} in Nodes sheet\
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\n{test_links} in Links sheet\
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\n{test_eqpts} in Eqpt sheet')
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exit(1)
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for city,link in links_by_city.items():
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if nodes_by_city[city].node_type.lower()=='ila' and len(link) != 2:
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#wrong input: ILA sites can only be Degree 2
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# => correct to make it a ROADM and remove entry in links_by_city
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#TODO : put in log rather than print
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print(f'invalid node type ({nodes_by_city[city].node_type})\
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specified in {city}, replaced by ROADM')
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nodes_by_city[city].node_type = 'ROADM'
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for n in nodes:
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if n.city==city:
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n.node_type='ROADM'
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return nodes, links
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def convert_file(input_filename, names_matching=False, filter_region=[]):
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nodes, links, eqpts = parse_excel(input_filename)
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if filter_region:
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nodes = [n for n in nodes if n.region.lower() in filter_region]
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cities = {n.city for n in nodes}
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links = [lnk for lnk in links if lnk.from_city in cities and
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lnk.to_city in cities]
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cities = {lnk.from_city for lnk in links} | {lnk.to_city for lnk in links}
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nodes = [n for n in nodes if n.city in cities]
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global nodes_by_city
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nodes_by_city = {n.city: n for n in nodes}
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#create matching dictionary for node name mismatch analysis
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cities = {''.join(c.strip() for c in n.city.split('C+L')).lower(): n.city for n in nodes}
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cities_to_match = [k for k in cities]
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city_match_dic = defaultdict(list)
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for city in cities:
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if city in cities_to_match:
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cities_to_match.remove(city)
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matches = get_close_matches(city, cities_to_match, 4, 0.85)
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for m in matches:
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city_match_dic[cities[city]].append(cities[m])
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#check lower case/upper case
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for city in nodes_by_city:
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for match_city in nodes_by_city:
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if match_city.lower() == city.lower() and match_city != city:
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city_match_dic[city].append(match_city)
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if names_matching:
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print('\ncity match dictionary:',city_match_dic)
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with open('name_match_dictionary.json', 'w', encoding='utf-8') as city_match_dic_file:
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city_match_dic_file.write(dumps(city_match_dic, indent=2, ensure_ascii=False))
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global links_by_city
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links_by_city = defaultdict(list)
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for link in links:
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links_by_city[link.from_city].append(link)
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links_by_city[link.to_city].append(link)
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global eqpts_by_city
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eqpts_by_city = defaultdict(list)
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for eqpt in eqpts:
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eqpts_by_city[eqpt.from_city].append(eqpt)
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nodes, links = sanity_check(nodes, links, nodes_by_city, links_by_city, eqpts_by_city)
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data = {
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'elements':
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[{'uid': f'trx {x.city}',
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'metadata': {'location': {'city': x.city,
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'region': x.region,
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'latitude': x.latitude,
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'longitude': x.longitude}},
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'type': 'Transceiver'}
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for x in nodes_by_city.values() if x.node_type.lower() == 'roadm'] +
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[{'uid': f'roadm {x.city}',
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'metadata': {'location': {'city': x.city,
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'region': x.region,
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'latitude': x.latitude,
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'longitude': x.longitude}},
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'type': 'Roadm'}
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for x in nodes_by_city.values() if x.node_type.lower() == 'roadm' \
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and x.booster_restriction == '' and x.preamp_restriction == ''] +
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[{'uid': f'roadm {x.city}',
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'params' : {
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'restrictions': {
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'preamp_variety_list': silent_remove(x.preamp_restriction.split(' | '),''),
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'booster_variety_list': silent_remove(x.booster_restriction.split(' | '),'')
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}
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},
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'metadata': {'location': {'city': x.city,
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'region': x.region,
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'latitude': x.latitude,
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'longitude': x.longitude}},
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'type': 'Roadm'}
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for x in nodes_by_city.values() if x.node_type.lower() == 'roadm' and \
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(x.booster_restriction != '' or x.preamp_restriction != '')] +
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[{'uid': f'west fused spans in {x.city}',
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'metadata': {'location': {'city': x.city,
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'region': x.region,
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'latitude': x.latitude,
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'longitude': x.longitude}},
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'type': 'Fused'}
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for x in nodes_by_city.values() if x.node_type.lower() == 'fused'] +
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[{'uid': f'east fused spans in {x.city}',
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'metadata': {'location': {'city': x.city,
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'region': x.region,
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'latitude': x.latitude,
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'longitude': x.longitude}},
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'type': 'Fused'}
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for x in nodes_by_city.values() if x.node_type.lower() == 'fused'] +
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[{'uid': f'fiber ({x.from_city} \u2192 {x.to_city})-{x.east_cable}',
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'metadata': {'location': midpoint(nodes_by_city[x.from_city],
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nodes_by_city[x.to_city])},
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'type': 'Fiber',
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'type_variety': x.east_fiber,
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'params': {'length': round(x.east_distance, 3),
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'length_units': x.distance_units,
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'loss_coef': x.east_lineic,
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'con_in':x.east_con_in,
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'con_out':x.east_con_out}
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}
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for x in links] +
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[{'uid': f'fiber ({x.to_city} \u2192 {x.from_city})-{x.west_cable}',
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'metadata': {'location': midpoint(nodes_by_city[x.from_city],
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nodes_by_city[x.to_city])},
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'type': 'Fiber',
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'type_variety': x.west_fiber,
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'params': {'length': round(x.west_distance, 3),
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'length_units': x.distance_units,
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'loss_coef': x.west_lineic,
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'con_in':x.west_con_in,
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'con_out':x.west_con_out}
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} # missing ILA construction
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for x in links] +
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[{'uid': f'east edfa in {e.from_city} to {e.to_city}',
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'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
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'region': nodes_by_city[e.from_city].region,
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'latitude': nodes_by_city[e.from_city].latitude,
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'longitude': nodes_by_city[e.from_city].longitude}},
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'type': 'Edfa',
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'type_variety': e.east_amp_type,
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'operational': {'gain_target': e.east_amp_gain,
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'delta_p': e.east_amp_dp,
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'tilt_target': e.east_tilt,
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'out_voa' : e.east_att_out}
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}
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for e in eqpts if (e.east_amp_type.lower() != '' and \
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e.east_amp_type.lower() != 'fused')] +
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[{'uid': f'west edfa in {e.from_city} to {e.to_city}',
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'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
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'region': nodes_by_city[e.from_city].region,
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'latitude': nodes_by_city[e.from_city].latitude,
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'longitude': nodes_by_city[e.from_city].longitude}},
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'type': 'Edfa',
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'type_variety': e.west_amp_type,
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'operational': {'gain_target': e.west_amp_gain,
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'delta_p': e.west_amp_dp,
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'tilt_target': e.west_tilt,
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'out_voa' : e.west_att_out}
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}
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for e in eqpts if (e.west_amp_type.lower() != '' and \
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e.west_amp_type.lower() != 'fused')] +
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# fused edfa variety is a hack to indicate that there should not be
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# booster amplifier out the roadm.
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# If user specifies ILA in Nodes sheet and fused in Eqpt sheet, then assumes that
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# this is a fused nodes.
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[{'uid': f'east edfa in {e.from_city} to {e.to_city}',
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'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
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'region': nodes_by_city[e.from_city].region,
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'latitude': nodes_by_city[e.from_city].latitude,
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'longitude': nodes_by_city[e.from_city].longitude}},
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'type': 'Fused',
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'params': {'loss': 0}
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}
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for e in eqpts if e.east_amp_type.lower() == 'fused'] +
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[{'uid': f'west edfa in {e.from_city} to {e.to_city}',
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'metadata': {'location': {'city': nodes_by_city[e.from_city].city,
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'region': nodes_by_city[e.from_city].region,
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'latitude': nodes_by_city[e.from_city].latitude,
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'longitude': nodes_by_city[e.from_city].longitude}},
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'type': 'Fused',
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'params': {'loss': 0}
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}
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for e in eqpts if e.west_amp_type.lower() == 'fused'],
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'connections':
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list(chain.from_iterable([eqpt_connection_by_city(n.city)
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for n in nodes]))
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+
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list(chain.from_iterable(zip(
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[{'from_node': f'trx {x.city}',
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'to_node': f'roadm {x.city}'}
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for x in nodes_by_city.values() if x.node_type.lower()=='roadm'],
|
|
[{'from_node': f'roadm {x.city}',
|
|
'to_node': f'trx {x.city}'}
|
|
for x in nodes_by_city.values() if x.node_type.lower()=='roadm'])))
|
|
}
|
|
|
|
suffix_filename = str(input_filename.suffixes[0])
|
|
full_input_filename = str(input_filename)
|
|
split_filename = [full_input_filename[0:len(full_input_filename)-len(suffix_filename)] , suffix_filename[1:]]
|
|
output_json_file_name = split_filename[0]+'.json'
|
|
with open(output_json_file_name, 'w', encoding='utf-8') as edfa_json_file:
|
|
edfa_json_file.write(dumps(data, indent=2, ensure_ascii=False))
|
|
return output_json_file_name
|
|
|
|
def parse_excel(input_filename):
|
|
link_headers = \
|
|
{ 'Node A': 'from_city',
|
|
'Node Z': 'to_city',
|
|
'east':{
|
|
'Distance (km)': 'east_distance',
|
|
'Fiber type': 'east_fiber',
|
|
'lineic att': 'east_lineic',
|
|
'Con_in': 'east_con_in',
|
|
'Con_out': 'east_con_out',
|
|
'PMD': 'east_pmd',
|
|
'Cable id': 'east_cable'
|
|
},
|
|
'west':{
|
|
'Distance (km)': 'west_distance',
|
|
'Fiber type': 'west_fiber',
|
|
'lineic att': 'west_lineic',
|
|
'Con_in': 'west_con_in',
|
|
'Con_out': 'west_con_out',
|
|
'PMD': 'west_pmd',
|
|
'Cable id': 'west_cable'
|
|
}
|
|
}
|
|
node_headers = \
|
|
{ 'City': 'city',
|
|
'State': 'state',
|
|
'Country': 'country',
|
|
'Region': 'region',
|
|
'Latitude': 'latitude',
|
|
'Longitude': 'longitude',
|
|
'Type': 'node_type',
|
|
'Booster_restriction': 'booster_restriction',
|
|
'Preamp_restriction': 'preamp_restriction'
|
|
}
|
|
eqpt_headers = \
|
|
{ 'Node A': 'from_city',
|
|
'Node Z': 'to_city',
|
|
'east':{
|
|
'amp type': 'east_amp_type',
|
|
'att_in': 'east_att_in',
|
|
'amp gain': 'east_amp_gain',
|
|
'delta p': 'east_amp_dp',
|
|
'tilt': 'east_tilt',
|
|
'att_out': 'east_att_out'
|
|
},
|
|
'west':{
|
|
'amp type': 'west_amp_type',
|
|
'att_in': 'west_att_in',
|
|
'amp gain': 'west_amp_gain',
|
|
'delta p': 'west_amp_dp',
|
|
'tilt': 'west_tilt',
|
|
'att_out': 'west_att_out'
|
|
}
|
|
}
|
|
|
|
with open_workbook(input_filename) as wb:
|
|
nodes_sheet = wb.sheet_by_name('Nodes')
|
|
links_sheet = wb.sheet_by_name('Links')
|
|
try:
|
|
eqpt_sheet = wb.sheet_by_name('Eqpt')
|
|
except Exception:
|
|
#eqpt_sheet is optional
|
|
eqpt_sheet = None
|
|
|
|
nodes = []
|
|
for node in parse_sheet(nodes_sheet, node_headers, NODES_LINE, NODES_LINE+1, NODES_COLUMN):
|
|
nodes.append(Node(**node))
|
|
expected_node_types = {'ROADM', 'ILA', 'FUSED'}
|
|
for n in nodes:
|
|
if n.node_type not in expected_node_types:
|
|
n.node_type = 'ILA'
|
|
|
|
links = []
|
|
for link in parse_sheet(links_sheet, link_headers, LINKS_LINE, LINKS_LINE+2, LINKS_COLUMN):
|
|
links.append(Link(**link))
|
|
#print('\n', [l.__dict__ for l in links])
|
|
|
|
eqpts = []
|
|
if eqpt_sheet != None:
|
|
for eqpt in parse_sheet(eqpt_sheet, eqpt_headers, EQPTS_LINE, EQPTS_LINE+2, EQPTS_COLUMN):
|
|
eqpts.append(Eqpt(**eqpt))
|
|
|
|
# sanity check
|
|
all_cities = Counter(n.city for n in nodes)
|
|
if len(all_cities) != len(nodes):
|
|
raise ValueError(f'Duplicate city: {all_cities}')
|
|
if any(ln.from_city not in all_cities or
|
|
ln.to_city not in all_cities for ln in links):
|
|
raise ValueError(f'Bad link.')
|
|
|
|
return nodes, links, eqpts
|
|
|
|
|
|
def eqpt_connection_by_city(city_name):
|
|
other_cities = fiber_dest_from_source(city_name)
|
|
subdata = []
|
|
if nodes_by_city[city_name].node_type.lower() in {'ila', 'fused'}:
|
|
# Then len(other_cities) == 2
|
|
direction = ['west', 'east']
|
|
for i in range(2):
|
|
from_ = fiber_link(other_cities[i], city_name)
|
|
in_ = eqpt_in_city_to_city(city_name, other_cities[0],direction[i])
|
|
to_ = fiber_link(city_name, other_cities[1-i])
|
|
subdata += connect_eqpt(from_, in_, to_)
|
|
elif nodes_by_city[city_name].node_type.lower() == 'roadm':
|
|
for other_city in other_cities:
|
|
from_ = f'roadm {city_name}'
|
|
in_ = eqpt_in_city_to_city(city_name, other_city)
|
|
to_ = fiber_link(city_name, other_city)
|
|
subdata += connect_eqpt(from_, in_, to_)
|
|
|
|
from_ = fiber_link(other_city, city_name)
|
|
in_ = eqpt_in_city_to_city(city_name, other_city, "west")
|
|
to_ = f'roadm {city_name}'
|
|
subdata += connect_eqpt(from_, in_, to_)
|
|
return subdata
|
|
|
|
|
|
def connect_eqpt(from_, in_, to_):
|
|
connections = []
|
|
if in_ !='':
|
|
connections = [{'from_node': from_, 'to_node': in_},
|
|
{'from_node': in_, 'to_node': to_}]
|
|
else:
|
|
connections = [{'from_node': from_, 'to_node': to_}]
|
|
return connections
|
|
|
|
|
|
def eqpt_in_city_to_city(in_city, to_city, direction='east'):
|
|
rev_direction = 'west' if direction == 'east' else 'east'
|
|
amp_direction = f'{direction}_amp_type'
|
|
amp_rev_direction = f'{rev_direction}_amp_type'
|
|
return_eqpt = ''
|
|
if in_city in eqpts_by_city:
|
|
for e in eqpts_by_city[in_city]:
|
|
if nodes_by_city[in_city].node_type.lower() == 'roadm':
|
|
if e.to_city == to_city and getattr(e, amp_direction) != '':
|
|
return_eqpt = f'{direction} edfa in {e.from_city} to {e.to_city}'
|
|
elif nodes_by_city[in_city].node_type.lower() == 'ila':
|
|
if e.to_city != to_city:
|
|
direction = rev_direction
|
|
amp_direction = amp_rev_direction
|
|
if getattr(e, amp_direction) != '':
|
|
return_eqpt = f'{direction} edfa in {e.from_city} to {e.to_city}'
|
|
if nodes_by_city[in_city].node_type.lower() == 'fused':
|
|
return_eqpt = f'{direction} fused spans in {in_city}'
|
|
return return_eqpt
|
|
|
|
|
|
def fiber_dest_from_source(city_name):
|
|
destinations = []
|
|
links_from_city = links_by_city[city_name]
|
|
for l in links_from_city:
|
|
if l.from_city == city_name:
|
|
destinations.append(l.to_city)
|
|
else:
|
|
destinations.append(l.from_city)
|
|
return destinations
|
|
|
|
|
|
def fiber_link(from_city, to_city):
|
|
source_dest = (from_city, to_city)
|
|
link = links_by_city[from_city]
|
|
l = next(l for l in link if l.from_city in source_dest and l.to_city in source_dest)
|
|
if l.from_city == from_city:
|
|
fiber = f'fiber ({l.from_city} \u2192 {l.to_city})-{l.east_cable}'
|
|
else:
|
|
fiber = f'fiber ({l.to_city} \u2192 {l.from_city})-{l.west_cable}'
|
|
return fiber
|
|
|
|
|
|
def midpoint(city_a, city_b):
|
|
lats = city_a.latitude, city_b.latitude
|
|
longs = city_a.longitude, city_b.longitude
|
|
try:
|
|
result = {
|
|
'latitude': sum(lats) / 2,
|
|
'longitude': sum(longs) / 2
|
|
}
|
|
except :
|
|
result = {
|
|
'latitude': 0,
|
|
'longitude': 0
|
|
}
|
|
return result
|
|
|
|
#output_json_file_name = 'coronet_conus_example.json'
|
|
#TODO get column size automatically from tupple size
|
|
|
|
NODES_COLUMN = 10
|
|
NODES_LINE = 4
|
|
LINKS_COLUMN = 16
|
|
LINKS_LINE = 3
|
|
EQPTS_LINE = 3
|
|
EQPTS_COLUMN = 14
|
|
parser = ArgumentParser()
|
|
parser.add_argument('workbook', nargs='?', type=Path , default='meshTopologyExampleV2.xls')
|
|
parser.add_argument('-f', '--filter-region', action='append', default=[])
|
|
|
|
if __name__ == '__main__':
|
|
args = parser.parse_args()
|
|
convert_file(args.workbook, args.filter_region)
|