Comments (2)
Hi @bonfils2 - There is no normalization in the library, you have to do it yourself. One approach is to standardize each anomaly field (divide by its standard deviation) before computing the EOFs. You should refer to the scientific literature for methodological guidance.
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Hi @ajdawson, That sounds good, thank you very much for the information!
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Related Issues (20)
- Opposite signal in EOF correlation map HOT 3
- Multivariate EOF Variance Discrepancies HOT 1
- SVD error when using eof solver on dask array HOT 1
- projectField not working on data with non-dimension coordinates in latest xarray version HOT 5
- eofs.xarray.Eof behaves unexpectedly when provided a DataArray with a coordinate called 'mode'
- Error while using solver.eofs with eofs.xarray HOT 5
- Question about projectField HOT 1
- reconstructedField raises an AttributeError in latest Python / Xarray version HOT 1
- Python collection issue with reconstructedField() HOT 2
- Input Data Missing Error from Standard Solver HOT 1
- update the release version
- about the difference between .pcs() and .projectField()
- eof not normalized and not conserving cell measures HOT 1
- reconstructedField broken because of reliance on now non-existent collections.Iterable HOT 2
- Building failed in Python 3.12 HOT 2
- Temporal interpolation?
- Missing value location error from projectField HOT 2
- Python 3.12 Support Release HOT 2
- conda release update needed HOT 2
- Extended eof HOT 1
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