![]() ![]() The following code shows how to calculate the Hamming distance between two arrays that each contain several character values: from scipy. Example 3: Hamming Distance Between String Arrays The Hamming distance between the two arrays is 3. The following code shows how to calculate the Hamming distance between two arrays that each contain several numerical values: from scipy. Example 2: Hamming Distance Between Numerical Arrays The Hamming distance between the two arrays is 2. #calculate Hamming distance between the two arrays The following code shows how to calculate the Hamming distance between two arrays that each contain only two possible values: from scipy. Example 1: Hamming Distance Between Binary Arrays ![]() This tutorial provides several examples of how to use this function in practice. Thus, to obtain the Hamming distance we can simply multiply by the length of one of the arrays: scipy. Note that this function returns the percentage of corresponding elements that differ between the two arrays. To calculate the Hamming distance between two arrays in Python we can use the hamming() function from the library, which uses the following syntax: scipy. ![]() The Hamming distance between the two vectors would be 2, since this is the total number of corresponding elements that have different values. The Hamming distance between two vectors is simply the sum of corresponding elements that differ between the vectors.įor example, suppose we have the following two vectors: x = ![]()
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