Comments (1)
gcpy.open_mfdataset is a wrapper around xarray function open_mfdataset which reads in netcdf variables as dask arrays. See http://xarray.pydata.org/en/stable/dask.html for more information on using dask arrays in xarray.
For example, I used open_mfdataset to read in several files and my resulting data looks like this:
<xarray.Dataset>
Dimensions: (lat: 288, lev: 72, lon: 48)
Coordinates:
- lon (lon) float64 1.0 2.0 3.0 4.0 5.0 ... 45.0 46.0 47.0 48.0
- lat (lat) float64 1.0 2.0 3.0 4.0 5.0 ... 285.0 286.0 287.0 288.0
- lev (lev) float64 1.0 2.0 3.0 4.0 5.0 ... 69.0 70.0 71.0 72.0
Data variables:
Jval_O3O3P (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
Jval_O3O1D (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
Jval_O2 (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
Jval_INPN (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
Jval_MRP (lev, lat, lon) float32 dask.array<shape=(72, 288, 48), chunksize=(72, 288, 48)>
This will cause problems when regridding since xesmf expects numpy array or xarray DataArray. When you ran your code for compare_single_level you likely did not regrid and so did not run into this problem. However, when you pass the same cubed-sphere data to compare_zonal_mean it will automatically be regridded to calculate zonal mean.
To avoid this problem you can convert your dask arrays to numpy arrays or xarray DataArrays prior to passing the data to the plotting functions. For example, np.array(ds_ref['varname'].data). You can also create an issue for xesmf to expand the handling to include dask arrays.
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Related Issues (20)
- Update benchmarking scripts to look for species_database.yml in the Config rundir archive folder HOT 2
- [BUG/ISSUE] - Regridding GCHP C48 to standard lat x lon HOT 3
- TypeError encountered when running file_regrid.py HOT 1
- GCPy 1.4.1 usages of seaborn-talk is deprecated in older matplotlib versions HOT 2
- Problems creating virtual environment compatible with GCPy 1.4.1 HOT 1
- Plot parallelization off failing in GCPy 1.4.1 HOT 4
- [FEATURE REQUEST] Transport tracer benchmark improvements HOT 2
- Make GCPy a conventional Python package HOT 7
- file_regrid.py creates GCHP restart files with variable name `DELPDRY` instead of `DELP_DRY` HOT 1
- pip install geoschem-gcpy==1.4.2 fails with error due to awscli version HOT 2
- [FEATURE REQUEST] Clean up start/end time usages in benchmark scripts HOT 1
- [FEATURE REQUEST] Transport Tracers benchmark for less than one year HOT 2
- Feature request: Add benchmark results paths and other related info to the the `config` object
- Combine Ref and Dev in the same file for TransportTracers budgets and mass conservation tables
- Bugs about automatic regridding for cube-sphere when plotting HOT 4
- Feature request: Add a script to scrape timing info from benchmark simulation log files HOT 3
- Can't generate zonal differences for global vs nested model output
- GCPy not properly recognizing 0.125x0.15625 lat-lon grid HOT 4
- Replace whitespace with underscores in benchmark plot/table version labels and file names HOT 1
- RnPbBe budget table benchmark code assumes initial restart is run resolution HOT 1
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