def sentences(lines):
#@typecheck([str], [(str, [object])], n=int)
def parseloop(lines, n=0):
return [(clean(lines[0]),
parseloop(lines[1:], n=n+1) if lines[1:] else [])
for lines in splitby(lambda line:n==indent(line), lines, True)]
return dct.collapse(filter(None, splitby(elem('<sent>'), lines, first=True)),
pipe(car, speaker_code),
pipe(cdr, cur(filter, useful), parseloop, car))
def group_words(csv):
"[[str]]-> {str:{str:{str:[float]}}} ie {Word:{Segment:{Feature:[Value]}}}"
segment_name = lambda s: s[:re.search('[0-9]', s).end()]
segment = fnc.pipe(car, dropwhile(str.islower), segment_name)
feature = lambda s: s[re.search('[0-9]', s).end():]
fillsegments = curried(dct.map_items)(makesegment)
features = carcdr(lambda title, data:(feature(title), map(float, data)))
phones = lambda l: dct.map(dict, dct.collapse(l, segment, features))
words = dct.collapse(cdr(csv),
fnc.pipe(car, takewhile(str.islower)),
fnc.ident)
return dct.map(fnc.pipe(phones, fillsegments), words)
def run_compare_to_base(fs):
"[str] -> [{utf-8-char:set<lev.Rule>}]"
return map(pipe(cur(compare, fs[0]), classify), fs)
def corpusSize(path, regions):
"path*{region:[filename]}"
numbers = dct.map(lambda files:lap(pipe(read(path), len), files), regions)
return sorted(dct.map(sum, numbers).items(), key=snd)
def groupedRegions(path, regions):
"path*{region:[site]} -> {region:[filename]}"
return dct.map(pipe(cur(groupedSites)(path), dict.values, concat),
regions)
swewords = [w for r in regions for w in r.splitlines()]
swevocab = set(swewords)
swecount = dct.count(swewords)
unsharedTokensTal = sum(talcount[w] for w in sharedVocab)
unsharedTokensSwe = sum(swecount[w] for w in sharedVocab)
print(len(talvocab))
print(len(swevocab))
print(len(swevocab & talvocab))
print(len(swevocab - talvocab))
print(len(talvocab - swevocab)
+ len(swevocab - talvocab)
+ len(swevocab & talvocab))
print(unsharedTokensTal)
print(unsharedTokensSwe)
print(len(talwords) + len(swewords) - unsharedTokensTal - unsharedTokensSwe)
lap = pipe(map, list) # Python 3 sucks
lilter = pipe(filter, list)
# (iterators as imperative laziness are at fault here)
def corpusSize(path, regions):
"path*{region:[filename]}"
numbers = dct.map(lambda files:lap(pipe(read(path), len), files), regions)
return sorted(dct.map(sum, numbers).items(), key=snd)
def printCorpusSize(path, regions):
for region, total in corpusSize(path, regions):
print(region, ":\t", total, '\t', numbers[region])
def swediaProvinceSize():
"Example use of corpusSize"
corpusSize(consts.swpath,
groupedRegions(consts.swpath, consts.swediaProvinces))
def swediaSiteSize():
"Another example use"
