def mostCommonNGramsFromPosts(posts, N=12):
# Basic Algorithm:
for p in posts:
n = e.normalizeString(p["raw_message"])
p["unigrams"] = e.nGramsFromString(n,1)
p["bigrams"] = e.nGramsFromString(n,2)
p["trigrams"] = e.nGramsFromString(n,3)
p["normalized_string"] = n
# count unigrams and bigrams
common = lambda s: nCommonNgrams(countNgrams(posts, s),N)
return [common("unigrams"), common("bigrams"), common("trigrams")]
def mostCommonNGramsFromString(string, N=8):
n = e.normalizeString(string)
nGrams = [1,2,3]
nGrams = map(lambda a: e.nGramsFromString(n,a),nGrams)
count = [{},{},{}]
for i in [0,1,2]:
for gram in nGrams[i]:
count[i][gram] = count[i].get(gram,0) + 1
count[i] = flipDictionary(count[i])
print(nCommonNgrams(count[i],N))
return nGrams
