FariborzDaneshvar-NOAA
commented
1 month ago First Error (KeyError):
KeyError Traceback (most recent call last)
Cell In[44], line 13
10 training_set_adjusted = training_set.copy(deep=True)
11 else:
12 # make an adjusted training set for dry areas..
---> 13 training_set_adjusted = extrapolate_water_elevation_to_dry_areas(
14 da=training_set,
15 k_neighbors=k_neighbors,
16 idw_order=idw_order,
17 compute_headloss=True,
18 mann_coef=mann_coef,
19 u_ref=0.4,
20 d_ref=1,
21 )
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/ensembleperturbation/parsing/adcirc.py:890, in extrapolate_water_elevation_to_dry_areas(da, k_neighbors, idw_order, compute_headloss, mann_coef, u_ref, d_ref, min_depth)
888 tree = KDTree(projected_coordinates[~null])
889 dd, nn = tree.query(projected_coordinates[null], k=k_neighbors)
--> 890 max_allowable_values = da['depth'][null].values + min_depth - numpy.finfo(float).eps
891 if k_neighbors == 1:
892 headloss = dd * friction_factor # hydraulic friction loss
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/xarray/core/dataarray.py:823, in DataArray.__getitem__(self, key)
820 return self._getitem_coord(key)
821 else:
822 # xarray-style array indexing
--> 823 return self.isel(indexers=self._item_key_to_dict(key))
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/xarray/core/dataarray.py:1413, in DataArray.isel(self, indexers, drop, missing_dims, **indexers_kwargs)
1410 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, "isel")
1412 if any(is_fancy_indexer(idx) for idx in indexers.values()):
-> 1413 ds = self._to_temp_dataset()._isel_fancy(
1414 indexers, drop=drop, missing_dims=missing_dims
1415 )
1416 return self._from_temp_dataset(ds)
1418 # Much faster algorithm for when all indexers are ints, slices, one-dimensional
1419 # lists, or zero or one-dimensional np.ndarray's
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/xarray/core/dataset.py:2704, in Dataset._isel_fancy(self, indexers, drop, missing_dims)
2700 var_indexers = {
2701 k: v for k, v in valid_indexers.items() if k in var.dims
2702 }
2703 if var_indexers:
-> 2704 new_var = var.isel(indexers=var_indexers)
2705 # drop scalar coordinates
2706 # https://github.com/pydata/xarray/issues/6554
2707 if name in self.coords and drop and new_var.ndim == 0:
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/xarray/core/variable.py:1378, in Variable.isel(self, indexers, missing_dims, **indexers_kwargs)
1375 indexers = drop_dims_from_indexers(indexers, self.dims, missing_dims)
1377 key = tuple(indexers.get(dim, slice(None)) for dim in self.dims)
-> 1378 return self[key]
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/xarray/core/variable.py:899, in Variable.__getitem__(self, key)
886 def __getitem__(self: T_Variable, key) -> T_Variable:
887 """Return a new Variable object whose contents are consistent with
888 getting the provided key from the underlying data.
889
(...)
897 array `x.values` directly.
898 """
--> 899 dims, indexer, new_order = self._broadcast_indexes(key)
900 data = as_indexable(self._data)[indexer]
901 if new_order:
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/xarray/core/variable.py:732, in Variable._broadcast_indexes(self, key)
729 if all(isinstance(k, BASIC_INDEXING_TYPES) for k in key):
730 return self._broadcast_indexes_basic(key)
--> 732 self._validate_indexers(key)
733 # Detect it can be mapped as an outer indexer
734 # If all key is unlabeled, or
735 # key can be mapped as an OuterIndexer.
736 if all(not isinstance(k, Variable) for k in key):
File /nhc/Fariborz.Daneshvar/miniconda3/envs/nhc_colab/lib/python3.10/site-packages/xarray/core/variable.py:784, in Variable._validate_indexers(self, key)
779 raise IndexError(
780 "{}-dimensional boolean indexing is "
781 "not supported. ".format(k.ndim)
782 )
783 if is_duck_dask_array(k.data):
--> 784 raise KeyError(
785 "Indexing with a boolean dask array is not allowed. "
786 "This will result in a dask array of unknown shape. "
787 "Such arrays are unsupported by Xarray."
788 "Please compute the indexer first using .compute()"
789 )
790 if getattr(k, "dims", (dim,)) != (dim,):
791 raise IndexError(
792 "Boolean indexer should be unlabeled or on the "
793 "same dimension to the indexed array. Indexer is "
(...)
796 )
797 )
KeyError: 'Indexing with a boolean dask array is not allowed. This will result in a dask array of unknown shape. Such arrays are unsupported by Xarray.Please compute the indexer first using .compute()'
If I use
chunks='auto'for reading the subset file:Then extrapolate_water_elevation_to_dry_areas() function that uses training set from the subset (
training_set = subset.sel(run=training_perturbations['run'])) as an input (da=training_set) will fail with the following KeyError:If I add
.compute()to line 887 (as explained in this PR), then I will get this new NotImplementedError:Full error messages in the following comments.