Calculate cosine similarity between given two 1d list. Two list must have the same length. Example: cosine_similarity([1, 1, 1], [1, 2, -1]) # output : 0.47140452079103173 """ import math def _l2_distance(vec): """ Calculate l2 distance from two given vectors. """ norm = 0. for element in vec: norm += element * element norm = math.sqrt(norm) return norm def cosine_similarity(vec1, vec2): """ Calculate cosine similarity between given two vectors :type vec1: list :type vec2: list """ if len(vec1) != len(vec2): raise ValueError("The two vectors must be the same length. Got shape " + str(len(vec1)) + " and " + str(len(vec2))) norm_a = _l2_distance(vec1) norm_b = _l2_distance(vec2) similarity = 0. # Calculate the dot product of two vectors for vec1_element, vec2_element in zip(vec1, vec2): similarity += vec1_element * vec2_element similarity /= (norm_a * norm_b).
Calculate cosine similarity between given two 1d list.
Two list must have the same length.
Example:
cosine_similarity([1, 1, 1], [1, 2, -1]) # output : 0.47140452079103173
"""
import math
def _l2_distance(vec):
"""
Calculate l2 distance from two given vectors.
"""
norm = 0.
for element in vec:
norm += element * element
norm = math.sqrt(norm)
return norm
def cosine_similarity(vec1, vec2):
"""
Calculate cosine similarity between given two vectors
:type vec1: list
:type vec2: list
"""
if len(vec1) != len(vec2):
raise ValueError("The two vectors must be the same length. Got shape " + str(len(vec1))
+ " and " + str(len(vec2)))
norm_a = _l2_distance(vec1)
norm_b = _l2_distance(vec2)
similarity = 0.
# Calculate the dot product of two vectors
for vec1_element, vec2_element in zip(vec1, vec2):
similarity += vec1_element * vec2_element
similarity /= (norm_a * norm_b).
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