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src/posts/flox-smart/index.md

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@@ -110,7 +110,7 @@ The steps are as follows:
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1. Use `"cohorts"` when every chunk only has a single group, but that group might extend across multiple chunks
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1. [and more](https://github.com/xarray-contrib/flox/blob/e6159a657c55fa4aeb31bcbcecb341a4849da9fe/flox/core.py#L408-L426)
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Here is an example:
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![bitmask-patterns](/../diagrams/bitmask-patterns-perfect.png)
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<!-- ![bitmask-patterns](/../diagrams/bitmask-patterns-perfect.png) -->
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- On the left, is a monthly grouping for a monthly time series with chunk size 4. There are 3 non-overlapping cohorts so
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`method="cohorts"` is perfect.
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labels = np.tile(np.arange(1, 13), 30)
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```
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![cohorts-schematic](/../diagrams/containment.png)
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<!-- ![cohorts-schematic](/../diagrams/containment.png) -->
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1. To choose between `"map-reduce"` and `"cohorts"`, we need a summary measure of the degree to which the labels overlap with
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each other. We can use _sparsity_ --- the number of non-zero elements in `C` divided by the number of elements in `C`, `C.nnz/C.size`.

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