def stats():
lines = [
'## Concept Lists',
'',
' name | mapped | mergers ',
' ---- | ------ | ------- ',
]
for cl in sorted(
PKG_PATH.joinpath('conceptlists').glob('*.tsv'), key=lambda _cl: _cl.name):
concepts = list(reader(cl, namedtuples=True, delimiter='\t'))
mapped = len([c for c in concepts if c.CONCEPTICON_ID])
mapped_ratio = int((mapped / len(concepts)) * 100)
concepticon_ids = Counter(
[c.CONCEPTICON_ID for c in concepts if c.CONCEPTICON_ID])
mergers = len([k for k, v in concepticon_ids.items() if v > 1])
line = [
'[%s](%s) ' % (cl.stem, cl.name),
badge('mapped', '%s%%' % mapped_ratio, Colors.red if mapped_ratio < 99 else Colors.brightgreen),
badge('mergers', '%s' % mergers, Colors.red if mergers else Colors.brightgreen),
]
lines.append(' | '.join(line))
with PKG_PATH.joinpath('conceptlists', 'README.md').open('w', encoding='utf8') as fp:
fp.write('\n'.join(lines))
def stats():
lines = [
'## Concept Lists',
'',
' name | mapped | mergers ',
' ---- | ------ | ------- ',
]
for cl in sorted(PKG_PATH.joinpath('conceptlists').glob('*.tsv'),
key=lambda _cl: _cl.name):
concepts = list(reader(cl, namedtuples=True, delimiter='\t'))
mapped = len([c for c in concepts if c.CONCEPTICON_ID])
mapped_ratio = int((mapped / len(concepts)) * 100)
concepticon_ids = Counter(
[c.CONCEPTICON_ID for c in concepts if c.CONCEPTICON_ID])
mergers = len([k for k, v in concepticon_ids.items() if v > 1])
line = [
'[%s](%s) ' % (cl.stem, cl.name),
badge('mapped', '%s%%' % mapped_ratio,
Colors.red if mapped_ratio < 99 else Colors.brightgreen),
badge('mergers', '%s' % mergers,
Colors.red if mergers else Colors.brightgreen),
]
lines.append(' | '.join(line))
with PKG_PATH.joinpath('conceptlists',
'README.md').open('w', encoding='utf8') as fp:
fp.write('\n'.join(lines))
def metadata(write_stats=True):
"""Writes statistics on metadata to readme."""
txt = '# Basic Statistics on Metadata\n\n'
cnc = list(reader(data_path('concepticon.tsv'), namedtuples=True, delimiter="\t"))
for i,cl in enumerate(PKG_PATH.joinpath('concept_set_meta').glob('*.tsv')):
data = list(reader(cl, namedtuples=True, delimiter="\t"))
txt += '* {0} covers {1} concept sets ({2:.2f} %)\n'.format(cl.name[:-4], len(data), len(data) / len(cnc))
if write_stats:
with PKG_PATH.joinpath('concept_set_meta', 'README.md').open('w', encoding='utf8') as fp:
fp.write(txt)
def metadata(write_stats=True):
"""Writes statistics on metadata to readme."""
txt = '# Basic Statistics on Metadata\n\n'
cnc = list(
reader(data_path('concepticon.tsv'), namedtuples=True, delimiter="\t"))
for i, cl in enumerate(
PKG_PATH.joinpath('concept_set_meta').glob('*.tsv')):
data = list(reader(cl, namedtuples=True, delimiter="\t"))
txt += '* {0} covers {1} concept sets ({2:.2f} %)\n'.format(
cl.name[:-4], len(data),
len(data) / len(cnc))
if write_stats:
with PKG_PATH.joinpath('concept_set_meta',
'README.md').open('w', encoding='utf8') as fp:
fp.write(txt)
def list_attributes(write_stats=True):
"""Calculate the addditional attributes in the lists."""
D = {}
for i,cl in enumerate(PKG_PATH.joinpath('conceptlists').glob('*.tsv')):
header = list(reader(cl, delimiter="\t"))[0]
header = [h for h in header if h not in ['ID', 'CONCEPTICON_ID',
'CONCEPTICON_GLOSS', 'ENGLISH', 'GLOSS', 'NUMBER']]
for h in header:
try:
D[h] += [cl.name]
except KeyError:
D[h] = [cl.name]
txt = '# Common Additional Columns of Concept Lists\n'
for k,v in sorted(D.items(), key=lambda x: len(x[1]), reverse=True):
txt += '* {2} occurences: {0}, {1}\n'.format(k, ', '.join(v), len(v))
print(txt)
def list_attributes(write_stats=True):
"""Calculate the addditional attributes in the lists."""
D = {}
for i, cl in enumerate(PKG_PATH.joinpath('conceptlists').glob('*.tsv')):
header = list(reader(cl, delimiter="\t"))[0]
header = [
h for h in header if h not in [
'ID', 'CONCEPTICON_ID', 'CONCEPTICON_GLOSS', 'ENGLISH',
'GLOSS', 'NUMBER'
]
]
for h in header:
try:
D[h] += [cl.name]
except KeyError:
D[h] = [cl.name]
txt = '# Common Additional Columns of Concept Lists\n'
for k, v in sorted(D.items(), key=lambda x: len(x[1]), reverse=True):
txt += '* {2} occurences: {0}, {1}\n'.format(k, ', '.join(v), len(v))
print(txt)
def test():
conceptlists = {
cl.name: read_tsv(cl, unique=None)
for cl in PKG_PATH.joinpath('conceptlists').glob('*.tsv')
if not cl.stem.startswith('.')
}
read_tsv(data_path('concepticon.tsv'))
concepticon = read_tsv(data_path('concepticon.tsv'), unique='GLOSS')
for i, cs in concepticon:
for attr in ['SEMANTICFIELD', 'ONTOLOGICAL_CATEGORY']:
valid = getattr(data, attr)
value = cs[attr]
if value and value not in valid:
error('invalid %s: %s' % (attr, value),
data_path('concepticon.tsv'), i)
for source in read_metadata(data_path('concept_set_meta')):
specs = json.loads(
open(data_path('concept_set_meta',
source + '.tsv-metadata.json')).read())
tsv = read_tsv(data_path('concept_set_meta', source + '.tsv'),
unique='CONCEPTICON_ID')
cnames = [var['name'] for var in specs['tableSchema']['columns']]
if not [n for n in cnames if n in list(tsv[0][1])]:
error('column names in {0} do not json-specs'.format(source),
'name')
for i, line in tsv:
if len(line) != len(cnames):
error(
'meta data {0} contains irregular number of columns in line {1}'
.format(source, i), 'name')
refs = set()
with io.open(data_path('references', 'references.bib'),
encoding='utf8') as fp:
for line in fp:
match = BIB_ID_PATTERN.match(line.strip())
if match:
refs.add(match.group('id'))
#
# Make sure only records in the BibTeX file references.bib are referenced by
# concept lists.
clmd = data_path('conceptlists.tsv')
clids = {}
visited = []
tags = getattr(data, 'CL_TYPES')
for i, cl in read_tsv(clmd):
clids[cl['ID']] = cl
for ref in split_ids(cl['REFS']):
if ref not in refs and ref not in visited:
error('unknown bibtex record "%s" referenced' % ref, clmd, i)
visited += [ref]
for tag in split_ids(cl['TAGS']):
if tag not in tags:
error('invalid cl type: %s' % tag, clmd, i)
#
# make also sure that all sources are accompanied as pdf, but only write a
# warning if this is not the case
#
pdfs = read_sources(data_path('sources'))
no_pdf_for_source = []
for i, cl in read_tsv(clmd):
for ref in split_ids(cl['PDF']):
if ref not in pdfs:
no_pdf_for_source += [ref]
if no_pdf_for_source:
warning('\n'.join(no_pdf_for_source),
'no pdf found for {0} sources'.format(len(no_pdf_for_source)))
ref_cols = {
'CONCEPTICON_ID': set(cs[1]['ID'] for cs in concepticon),
'CONCEPTICON_GLOSS': set(cs[1]['GLOSS'] for cs in concepticon),
}
for name, concepts in conceptlists.items():
try:
cl = clids[name.replace('.tsv', '')]
except KeyError:
error('unkown record {0} referenced'.format(name), '', '')
cl = {}
missing = []
for i, (line, concept) in enumerate(concepts):
if i == 0:
cols = list(concept.keys())
try:
namedtuple('nt', [normalize_name(n) for n in cols])
except ValueError as e:
error('%s' % e, name, line)
for lg in split(cl.get('SOURCE_LANGUAGE', [])):
if lg.upper() not in cols:
error('missing source language col %s' % lg.upper(),
name, '')
if not NUMBER_PATTERN.match(concept['NUMBER']):
error('invalid concept NUMBER %(NUMBER)s' % concept, name,
line)
for col, values in ref_cols.items():
if col not in concept:
if col not in missing:
error('missing column %s' % col, name)
missing.append(col)
elif concept[col] and concept[col] not in values:
error('invalid value for %s: %s' % (col, concept[col]),
name, line)
if not SUCCESS:
raise ValueError('integrity checks failed!')
def test():
conceptlists = {
cl.name: read_tsv(cl, unique=None)
for cl in PKG_PATH.joinpath('conceptlists').glob('*.tsv')
if not cl.stem.startswith('.')}
read_tsv(data_path('concepticon.tsv'))
concepticon = read_tsv(data_path('concepticon.tsv'), unique='GLOSS')
for i, cs in concepticon:
for attr in ['SEMANTICFIELD', 'ONTOLOGICAL_CATEGORY']:
valid = getattr(data, attr)
value = cs[attr]
if value and value not in valid:
error('invalid %s: %s' % (attr, value), data_path('concepticon.tsv'), i)
refs = set()
with io.open(data_path('references', 'references.bib'), encoding='utf8') as fp:
for line in fp:
match = BIB_ID_PATTERN.match(line.strip())
if match:
refs.add(match.group('id'))
#
# Make sure only records in the BibTeX file references.bib are referenced by
# concept lists.
clmd = data_path('conceptlists.tsv')
clids = {}
visited = []
tags = getattr(data, 'CL_TYPES')
for i, cl in read_tsv(clmd):
clids[cl['ID']] = cl
for ref in split_ids(cl['REFS']):
if ref not in refs and ref not in visited:
error('unknown bibtex record "%s" referenced' % ref, clmd, i)
visited += [ref]
for tag in split_ids(cl['TAGS']):
if tag not in tags:
error('invalid cl type: %s' % tag, clmd, i)
#
# make also sure that all sources are accompanied as pdf, but only write a
# warning if this is not the case
#
pdfs = read_sources(data_path('sources'))
no_pdf_for_source = []
for i, cl in read_tsv(clmd):
for ref in split_ids(cl['PDF']):
if ref not in pdfs:
no_pdf_for_source += [ref]
if no_pdf_for_source:
warning(
'\n'.join(no_pdf_for_source),
'no pdf found for {0} sources'.format(len(no_pdf_for_source)))
ref_cols = {
'CONCEPTICON_ID': set(cs[1]['ID'] for cs in concepticon),
'CONCEPTICON_GLOSS': set(cs[1]['GLOSS'] for cs in concepticon),
}
for name, concepts in conceptlists.items():
try:
cl = clids[name.replace('.tsv', '')]
except KeyError:
error('unkown record {0} referenced'.format(name), '', '')
cl = {}
missing = []
for i, (line, concept) in enumerate(concepts):
if i == 0:
cols = list(concept.keys())
try:
namedtuple('nt', [normalize_name(n) for n in cols])
except ValueError as e:
error('%s' % e, name, line)
for lg in split(cl.get('SOURCE_LANGUAGE', [])):
if lg.upper() not in cols:
error('missing source language col %s' % lg.upper(), name, '')
if not NUMBER_PATTERN.match(concept['NUMBER']):
error('invalid concept NUMBER %(NUMBER)s' % concept, name, line)
for col, values in ref_cols.items():
if col not in concept:
if col not in missing:
error('missing column %s' % col, name)
missing.append(col)
elif concept[col] and concept[col] not in values:
error('invalid value for %s: %s' % (col, concept[col]), name, line)
if not SUCCESS:
raise ValueError('integrity checks failed!')
