def getXLeastSimilarIndex(term, terms_to_match, terms_to_ignore, amt):
least_similar_term_indexes = []
for a in range(amt):
lowest_term = 99999999
term_index = 0
for t in range(len(terms_to_match)):
if dt.checkIfInArray(terms_to_ignore, t) is False:
s = getSimilarity(term, terms_to_match[t])
if s < lowest_term and dt.checkIfInArray(least_similar_term_indexes, t) is False:
lowest_term = s
term_index = t
least_similar_term_indexes.append(term_index)
return least_similar_term_indexes
def getXMostSimilarIndex(term, terms_to_match, terms_to_ignore, amt):
most_similar_term_indexes = []
for a in range(amt):
highest_term = 0
term_index = 0
for t in range(len(terms_to_match)):
if dt.checkIfInArray(terms_to_ignore, t) is False:
s = getSimilarity(term, terms_to_match[t])
if s > highest_term and dt.checkIfInArray(most_similar_term_indexes, t) is False:
highest_term = s
term_index = t
most_similar_term_indexes.append(term_index)
return most_similar_term_indexes
def getXMostSimilarIndex(term, terms_to_match, terms_to_ignore, amt):
most_similar_term_indexes = []
for a in range(amt):
highest_term = 0
term_index = 0
for t in range(len(terms_to_match)):
if dt.checkIfInArray(terms_to_ignore, t) is False:
s = getSimilarity(term, terms_to_match[t])
if s > highest_term and dt.checkIfInArray(
most_similar_term_indexes, t) is False:
highest_term = s
term_index = t
most_similar_term_indexes.append(term_index)
return most_similar_term_indexes
def getXLeastSimilarIndex(term, terms_to_match, terms_to_ignore, amt):
least_similar_term_indexes = []
for a in range(amt):
lowest_term = 99999999
term_index = 0
for t in range(len(terms_to_match)):
if dt.checkIfInArray(terms_to_ignore, t) is False:
s = getSimilarity(term, terms_to_match[t])
if s < lowest_term and dt.checkIfInArray(
least_similar_term_indexes, t) is False:
lowest_term = s
term_index = t
least_similar_term_indexes.append(term_index)
return least_similar_term_indexes
def getNextClusterTerm(cluster_terms, terms_to_match, terms_to_ignore, amt):
min_value = 999999999999999
min_index = 0
for t in range(len(terms_to_match)):
max_value = 0
if dt.checkIfInArray(terms_to_ignore, t) is False:
for c in range(len(cluster_terms)):
s = getSimilarity(cluster_terms[c], terms_to_match[t])
if s > max_value:
max_value = s
if max_value < min_value:
min_value = max_value
min_index = t
return min_index
def getNextClusterTerm(cluster_terms, terms_to_match, terms_to_ignore, amt):
min_value = 999999999999999
min_index = 0
for t in range(len(terms_to_match)):
max_value = 0
if dt.checkIfInArray(terms_to_ignore, t) is False:
for c in range(len(cluster_terms)):
s = getSimilarity(cluster_terms[c], terms_to_match[t])
if s > max_value:
max_value = s
if max_value < min_value:
min_value = max_value
min_index = t
return min_index
