ts_clustering

ts_clustering_similarity_eng.py

def compute_correlation(a1, a2):
    """
    Calculate the correlation between two vectors
    """
    return np.corrcoef(a1, a2)[0, 1]

def compute_dynamic_time_warping(a1, a2):
    """
    Compute the dynamic time warping between two sequences
    """
    
    DTW = {}

    for i in range(len(a1)):
        DTW[(i, -1)] = float('inf')
    for i in range(len(a2)):
        DTW[(-1, i)] = float('inf')
    DTW[(-1, -1)] = 0

    for i in range(len(a1)):
        for j in range(len(a2)):
            dist = (a1[i]-a2[j])**2
            DTW[(i, j)] = dist + min(DTW[(i-1, j)], DTW[(i, j-1)], DTW[(i-1, j-1)])

    return np.sqrt(DTW[len(a1)-1, len(a2)-1])


# create empty matrix
S = np.zeros((len(A), len(A)))

# populate S
for i in range(len(A)):
    for j in range(len(A)):
        # weigh the dynamic time warping with the correlation
        S[i, j] = compute_dynamic_time_warping(A[i], A[j]) * (1 - compute_correlation(A[i], A[j]))