@@ -137,16 +137,16 @@ For more detail [see the docs](https://flox.readthedocs.io/en/latest/implementat
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Suggestions and improvements are very welcome!
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Here is containment ` C[i, j] ` for a range of chunk sizes from 1 to 12 for computing ` groupby("time.month") ` of a monthly mean dataset.
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- The images only show 12 time steps.
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- These are colored so that light yellow is C=0, and dark purple is C=1.
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+ These panels are colored so that light yellow is ` C=0 ` , and dark purple is ` C=1 ` .
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` C[i,j] = 1 ` when the chunks occupied by group ` i ` perfectly overlaps with those occupied by group ` j ` (so the diagonal elements
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are always 1).
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+ Since there are 12 groups, ` C ` is a 12x12 matrix.
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The title on each image is ` (chunk size, sparsity) ` .
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- When the chunksize _ is_ a divisor of the period 12, $C$ is a [ block diagonal] ( https://en.wikipedia.org/wiki/Block_matrix ) matrix.
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- When the chunksize _ is not_ a divisor of the period 12, $C$ is much less sparse in comparison.
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+ When the chunksize _ is_ a divisor of the period 12, ` C ` is a [ block diagonal] ( https://en.wikipedia.org/wiki/Block_matrix ) matrix.
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+ When the chunksize _ is not_ a divisor of the period 12, ` C ` is much less sparse in comparison.
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![ flox sparsity image] ( https://flox.readthedocs.io/en/latest/_images/containment.png )
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- Given the above ` C ` , flox will choose ` "cohorts" ` for chunk sizes (1, 2, 3, 4, 6, 12 ), and ` "map-reduce" ` for the rest.
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+ Given the above ` C ` , flox will choose ` "cohorts" ` for chunk sizes (1, 2, 3, 4, 6), and ` "map-reduce" ` for the rest.
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Cool, isn't it?!
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