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In data science we have "Manhattan Distance" as a slang term for Level 1 Distance and "Euclidean Distance" as a slang term for Level 2 Distance. Is there an accepted term for linear distance in memory of cells in different rows in a matrix? That is, given an 8x8 matrix, the "linear distance" from [3,2] to [4,5] is: (4-3) * 8 + (5-2)

This is the distance in memory addressing. "Level 0 Distance" doesn't really work as a technical term, because computer memory layout is not a native concept in mathematics. Is there a standard term for this? It reminds me of the old flyback transformers in cathode ray tubes, so "flyback distance" makes sense as a slang term.

Jack Parsons
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Actually this is the Manhattan / $L_1$ / Norm 1 distance, if you just multiply the row by $8$ (or $N$).

The $L_1$ distance between $[24, 2]$ and $[32, 5]$ is what you are looking for.

Pieter21
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