60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
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# Herein I'm practicing two-dimensional matrix traversals in all directions of
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# which I can conceive:
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# 0. T -> B; L -> R
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# 1. T -> B; R -> L
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# 2. B -> T; L -> R
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# 3. B -> T; R -> L
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#
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# Commentary:
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# When I think of matrices, I'm reminded of cartesian planes. I think of the
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# cells as (X,Y) coordinates. This has been a pitfall for me because matrices
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# are usually encoded in the opposite way. That is, to access a cell at the
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# coordinates (X,Y) given a matrix M, you index M like this: M[Y][X]. To attempt
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# to avoid this confusion, instead of saying X and Y, I will prefer saying
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# "column" and "row".
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#
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# When traversing a matrix, you typically traverse vertically and then
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# horizontally; in other words, the rows come first followed by the columns. As
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# such, I'd like to refer to traversal orders as "top-to-bottom, left-to-right"
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# rather than "left-to-right, top-to-bottom".
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#
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# These practices are all in an attempt to rewire my thinking.
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# This is a list of matrices where the index of a matrix corresponds to the
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# order in which it should be traversed to produce the sequence:
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# [1,2,3,4,5,6,7,8,9].
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boards = [[[1, 2, 3], [4, 5, 6], [7, 8, 9]], [[3, 2, 1], [6, 5, 4], [9, 8, 7]],
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[[7, 8, 9], [4, 5, 6], [1, 2, 3]], [[9, 8, 7], [6, 5, 4], [3, 2, 1]]]
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# T -> B; L -> R
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board = boards[0]
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result = []
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for row in board:
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for col in row:
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result.append(col)
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print(result)
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# T -> B; R -> L
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board = boards[1]
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result = []
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for row in board:
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for col in reversed(row):
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result.append(col)
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print(result)
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# B -> T; L -> R
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board = boards[2]
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result = []
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for row in reversed(board):
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for col in row:
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result.append(col)
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print(result)
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# B -> T; R -> L
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board = boards[3]
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result = []
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for row in reversed(board):
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for col in reversed(row):
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result.append(col)
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print(result)
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