Comments (3)
hey @agirnow, thank you for documenting that, it indeed looks like a bug. I'm quite packed this week, so I'll be able to take a closer look at it at the earliest over the weekend.
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version 2.3.1 was just released which should fix this issue. let me know @agirnow if it indeed solved the problem for you.
On a different note: from your example using train and test, I wonder if your goal is to make predictions of one field using the transformed scores of the other? Unfortunately, this is not yet implemented - the transform
method will really just transform the provided field data into the scores of the latent space.
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Hey @nicrie
Thanks, it solved my problem ! :)
Yes, that is exaclty what i wanted to do, I thought that to do so it will be okay to use the scores obtained with the transform method on the first field as an input for the inverse_transform method on the other field, but maybe that is not true.
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Related Issues (20)
- ModuleNotFound Error datatree HOT 5
- `scores()` don't match `transform()` with dask data HOT 4
- Improving release process
- Keep the documentation in sync with the code HOT 3
- Add dependencies section in the documentation HOT 1
- numpy and pandas dependency question
- numpy and pandas dependencies HOT 3
- Migrating repository to xarray-contrib HOT 2
- why the explained_variance_ratio of CCA so small HOT 4
- Serialization fails with `xarray>=2024.1.0` HOT 2
- Single mode data reconstruction fails with normalized scores HOT 9
- Support for complex input data
- Is the reconstruction of unseen data possible using EOF? HOT 5
- Model cannot fit DataArray without coordiantes
- Add option `n_modes="all"` to perform the full decomposition HOT 2
- Trouble creating the eof object HOT 8
- TypeError: __init__() missing 1 required positional argument: 'X' HOT 1
- Data with Nan values HOT 6
- Questions to the REOF power parameter in the examples HOT 5
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