make dimension.py xarray compatible #397
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Fantastic work @mats-knmi ! Code is really looking much better (and this PR has a negative impact on the number of lines, brilliant!) and I know that the code you had to adapt is not easy to navigate... so well done!
I only had few minor comments, mostly concerning documentation - how are we going to make sure that the structure of the dataset is clearly documented? perhaps it could also be a good idea to add some basic input validator with a decorator, what do you think?
pysteps/utils/dimension.py
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| R: array-like | ||
| Array of shape (t,m,n) or (l,t,m,n) containing | ||
| dataset: Dataset |
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I would still mention here that this is an xarray dataset, even if it's already obvious from the type hints
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also, the methods expect certain attributes, not just any kind of dataset. These should be mentioned somehow. See for example the description of "metadata" where we referenced the documention in pysteps.io.importers.
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Yes indeed a documentation similar to the "metadata" description (but for the dataset structure), which we can link to from these docstrings, would be very a very useful addition. I will take a look at this.
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| dataset: Dataset | |
| dataset: xarray.Dataset |
Is this what you mean?
pysteps/utils/dimension.py
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| ---------- | ||
| R: array-like | ||
| Array of shape (m,n), (t,m,n) or (l,t,m,n) containing a single field or | ||
| dataset: Dataset |
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need to update the name in the rest of the docstrings (see the text for space_window)
| metadata: dict | ||
| The metadata with updated attributes. | ||
| dataset: Dataset | ||
| The new dataset. |
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Is it self-explanatory how the fields are aggregate with a given spatial window?
pysteps/utils/dimension.py
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| def aggregate_fields_time(R, metadata, time_window_min, ignore_nan=False): | ||
| def aggregate_fields_time(dataset: xr.Dataset, time_window_min, ignore_nan=False): |
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need to specify the type of the output, as it's not detailed in the docstrings
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@dnerini I have added a ticket to the project backlog, for a basic input validator with a decorator. |
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@dnerini I believe I have also taken care of the remaining comments you had, let me know what you think |
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* make dimension.py xarray compatible * convert final method in the dimension module * nanmin in stead of zerovalue in square domain method * make test steps skill run * undo accidental change * remove commented out code * The dataset can contain more than one dataarray * Address pull request comments * Add links to dataset documentation everywhere
* make dimension.py xarray compatible * convert final method in the dimension module * nanmin in stead of zerovalue in square domain method * make test steps skill run * undo accidental change * remove commented out code * The dataset can contain more than one dataarray * Address pull request comments * Add links to dataset documentation everywhere
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Converted the methods in
dimension.pyto work with the new xarray datamodel. Since these methods can largely be replaced by xarray functionality, I updated these methods to make use of this.