# elif convolution_type == "7_bands" or convolution_type == "mixed_7_bands":
# if p < 8:
# kern = np.ones((p,p)) - np.identity(p)
# else:
# # Diagonal where only the six subdiagonals surrounding the main diagonal is one
# k = np.array([np.ones(p-7),np.ones(p-6),np.ones(p-5),np.ones(p-4),np.ones(p-3),np.ones(p-2),np.ones(p-1),np.zeros(p),np.ones(p-1),np.ones(p-2),np.ones(p-3),np.ones(p-4),np.ones(p-5),np.ones(p-6),np.ones(p-7)], dtype=object)
Normalizing the convolutionnal cost by the number of non-zero elements in the kernel instead of the size of the kernel. As in [SJK06].
References
----------
[SJK06] Shiu, Y., Jeong, H., & Kuo, C. C. J. (2006, October). Similarity matrix processing for music structure analysis. In Proceedings of the 1st ACM workshop on Audio and music computing multimedia (pp. 69-76).
# elif convolution_type == "7_bands" or convolution_type == "mixed_7_bands":
# if p < 8:
# kern = np.ones((p,p)) - np.identity(p)
# else:
# # Diagonal where only the six subdiagonals surrounding the main diagonal is one
# k = np.array([np.ones(p-7),np.ones(p-6),np.ones(p-5),np.ones(p-4),np.ones(p-3),np.ones(p-2),np.ones(p-1),np.zeros(p),np.ones(p-1),np.ones(p-2),np.ones(p-3),np.ones(p-4),np.ones(p-5),np.ones(p-6),np.ones(p-7)], dtype=object)