Comments (8)
Hello, I am not sure but this might help conda/conda#9367
from xeofs.
I think this is more related to conda and your environments than xeofs
. It's generally good practice to create and use different conda environments depending on your task. Try creating a new conda environment only with the packages you need, e.g.
conda create -n xeofs python=3.9
conda activate xeofs
conda install -c conda-forge xeofs
This should work :) Also, there shouldn't be any dependency issues with neither eofs
nor xmca
. It's probably because there are other packages in your base environment.
from xeofs.
I think this is more related to conda and your environments than
xeofs
. It's generally good practice to create and use different conda environments depending on your task. Try creating a new conda environment only with the packages you need, e.g.conda create -n xeofs python=3.9 conda activate xeofs conda install -c conda-forge xeofsThis should work :) Also, there shouldn't be any dependency issues with neither
eofs
norxmca
. It's probably because there are other packages in your base environment.
Thanks a lot @nicrie Niclas, you're of timely help, as always.
And, it did work (As you said).
from xeofs.
Great, glad it worked :)
from xeofs.
from xeofs.
Hi Girija,
Actually cartopy
is not a dependency of xeofs
- so you definitely want to install it in addition if you want to use cartopy
.
Personally, I do not use windows but Linux, so I do not have experience with installing cartopy
on your operating system. For me, installing cartopy
together with xeofs
from the conda-forge
channel works without problems:
conda create -n xeofs python=3.9
conda activate xeofs
conda install -c conda-forge xeofs cartopy
Unfortunately, I cannot see the attached image. If you can please copy & paste the warning as text here.
from xeofs.
Well, this worked.
Plots are great as I don't have to plot SVDs and hom_patterns separately like that of xMCA.
Thanks a lot.
Can you please share some references for understanding homogenous and nd heterogeneous patterns?
Mine looks this way :
from xeofs.
Perfect! For understanding a bit better the theory, check out Chapter 14.3 in Wilks' Statistical Methods in the Atmospheric Sciences or the paper by Bretherton et al. 1992.
But in brief: Homogeneous patterns are just the correlation maps between the PCs and the corresponding input field (e.g. hom. pattern 1 = "left" field correlated with "left" PC1). Heterogeneous patterns represent the correlation maps between the PCs and the opposite input field (e.g. het. pattern 1 = "left" field correlated with "right" PC1).
from xeofs.
Related Issues (20)
- Centering the input data is not equivalent to removing the linear trend beforehand HOT 5
- `dask`-based computation not entirely lazy HOT 3
- 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
- MCA incorrect coords alignment in transform method HOT 3
- 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
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