def report(args):
"""
clpa report <FILE> [rules=FILE] [format=md|csv|cldf] [outfile=FILENAME]
Note
----
* Rules point to a tab-separated value file in which source and target are
given to convert a segment to another segment to be applied on a
data-set-specific basis which may vary from dataset to dataset and can thus
not be included as standard clpa behaviour.
* Input file needs to be in csv-format, with tabstop as separator, and it
needs to contain one column named "TOKENS".
* format now allows for md (MarkDown), csv (CSV, tab as separator), or cldf
(no pure cldf but rather current lingpy-csv-format). CLDF format means
that the original file will be given another two columns, one called
CLPA_TOKENS, one called CLPA_IDS.
* if you specify an outfile from the input, the data will be written to
file instead showing it on the screen.
"""
if len(args.args) < 1:
raise ParserError('not enough arguments')
# get keywords from arguments @xrotwang: is there any better way to do so?
settings = defaultdict(str)
settings['format'] = 'md'
fname = None
for arg in args.args:
if '=' in arg:
key, val = arg.split('=')
settings[key] = val
else:
fname = arg
if not fname:
raise ParserError('no filename passed as argument')
wordlist = Wordlist.from_file(fname)
sounds, errors = wordlist.check(rules=settings['rules'])
if settings['format'] not in ['md', 'csv']:
text = wordlist.write(settings['outfile'] or None)
if not settings['outfile']:
print(text)
return
segments = OrderedDict([('existing', []), ('missing', []),
('convertible', [])])
for k in sorted(sounds,
key=lambda x: (sounds[x]['frequency'], sounds[x]['id']),
reverse=True):
type_, symbol = None, None
if k == sounds[k]['clpa']:
type_, symbol = 'existing', k
elif sounds[k]['clpa'] == '?':
type_, symbol = 'missing', k
else:
check = sounds[k]['clpa']
if k != check != '?':
type_, symbol = 'convertible', k + ' >> ' + sounds[k]['clpa']
if type_ and symbol:
segments[type_].append(
[symbol, sounds[k]['id'], sounds[k]['frequency']])
if settings['format'] == 'csv':
with UnicodeWriter(settings['outfile'] or None,
delimiter='\t') as writer:
for key, items in segments.items():
for i, item in enumerate(items):
writer.writerow([i + 1] + item + [key])
if not settings['outfile']:
print(writer.read())
return
text = []
header_template = """
# {0} sounds
| number | sound | clpa | frequency |
| ------:| ----- | ---- | ---------:|"""
for key, items in segments.items():
text.append(header_template.format(key.capitalize()))
for i, item in enumerate(items):
text.append("| {0} | {1[0]} | {1[1]} | {1[2]} |".format(
i + 1, item))
text = '\n'.join(text)
if settings['outfile']:
with Path(settings['outfile']).open('w', encoding='utf8') as fp:
fp.write(text)
else:
print(text)
def report(args):
"""
clpa report <FILE> [rules=FILE] [format=md|csv|cldf] [outfile=FILENAME]
Note
----
* Rules point to a tab-separated value file in which source and target are
given to convert a segment to another segment to be applied on a
data-set-specific basis which may vary from dataset to dataset and can thus
not be included as standard clpa behaviour.
* Input file needs to be in csv-format, with tabstop as separator, and it
needs to contain one column named "TOKENS".
* format now allows for md (MarkDown), csv (CSV, tab as separator), or cldf
(no pure cldf but rather current lingpy-csv-format). CLDF format means
that the original file will be given another two columns, one called
CLPA_TOKENS, one called CLPA_IDS.
* if you specify an outfile from the input, the data will be written to
file instead showing it on the screen.
"""
if len(args.args) < 1:
raise ParserError('not enough arguments')
# get keywords from arguments @xrotwang: is there any better way to do so?
settings = defaultdict(str)
settings['format'] = 'md'
fname = None
for arg in args.args:
if '=' in arg:
key, val = arg.split('=')
settings[key] = val
else:
fname = arg
if not fname:
raise ParserError('no filename passed as argument')
wordlist = Wordlist.from_file(fname)
sounds, errors = wordlist.check(rules=settings['rules'])
if settings['format'] not in ['md', 'csv']:
text = wordlist.write(settings['outfile'] or None)
if not settings['outfile']:
print(text)
return
segments = OrderedDict([('existing', []), ('missing', []), ('convertible', [])])
for k in sorted(
sounds, key=lambda x: (sounds[x]['frequency'], sounds[x]['id']), reverse=True
):
type_, symbol = None, None
if k == sounds[k]['clpa']:
type_, symbol = 'existing', k
elif sounds[k]['clpa'] == '?':
type_, symbol = 'missing', k
else:
check = sounds[k]['clpa']
if k != check != '?':
type_, symbol = 'convertible', k + ' >> ' + sounds[k]['clpa']
if type_ and symbol:
segments[type_].append([symbol, sounds[k]['id'], sounds[k]['frequency']])
if settings['format'] == 'csv':
with UnicodeWriter(settings['outfile'] or None, delimiter='\t') as writer:
for key, items in segments.items():
for i, item in enumerate(items):
writer.writerow([i + 1] + item + [key])
if not settings['outfile']:
print(writer.read())
return
text = []
header_template = """
# {0} sounds
| number | sound | clpa | frequency |
| ------:| ----- | ---- | ---------:|"""
for key, items in segments.items():
text.append(header_template.format(key.capitalize()))
for i, item in enumerate(items):
text.append("| {0} | {1[0]} | {1[1]} | {1[2]} |".format(i + 1, item))
text = '\n'.join(text)
if settings['outfile']:
with Path(settings['outfile']).open('w', encoding='utf8') as fp:
fp.write(text)
else:
print(text)
def _make_one(self, path=None):
return Wordlist.from_file(path or self.data_path('KSL.tsv'))