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This repository has been archived by the owner on Aug 29, 2023. It is now read-only.
The Zarr Data Store contains data from the ODP that has been converted into the zarr format. There is one BIOMASS dataset in the Zarr data store. For the purposes of this issue, we say that a dataset is supported when
it can be opened in cate
it can be opened in cate with a spatial subset
its content can be written to disk
its data can be displayed in cate
The BIOMASS dataset cannot be opened with a spatial subset. The traceback is:
Traceback (most recent call last):
File "test_cci_data_support.py", line 327, in test_open_ds
dataset, _ = open_dataset(dataset_id=data_id,
File "/home/users/tfincke/Projects/cate/cate/core/ds.py", line 432, in open_dataset
dataset = select_subset(dataset, **subset_args)
File "/home/users/tfincke/Projects/xcube/xcube/core/select.py", line 37, in select_subset
dataset = select_spatial_subset(dataset, xy_bbox=bbox)
File "/home/users/tfincke/Projects/xcube/xcube/core/select.py", line 85, in select_spatial_subset
geo_coding = geo_coding if geo_coding is not None else GeoCoding.from_dataset(dataset, xy_names=xy_names)
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 132, in from_dataset
return cls.from_xy((x, y), xy_names=(x_name, y_name))
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 169, in from_xy
x, is_lon_normalized = _maybe_normalise_2d_lon(x)
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 462, in _maybe_normalise_2d_lon
if _is_crossing_antimeridian(lon_var):
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 457, in _is_crossing_antimeridian
return abs(lon_var.diff(dim=dim_x)).max() > 180.0 or
File "/home/users/tfincke/miniconda3/envs/xcube/lib/python3.8/site-packages/xarray/core/dataarray.py", line 3107, in diff
ds = self._to_temp_dataset().diff(n=n, dim=dim, label=label)
File "/home/users/tfincke/miniconda3/envs/xcube/lib/python3.8/site-packages/xarray/core/dataset.py", line 5489, in diff
variables[name] = var.isel(**kwargs_end) - var.isel(**kwargs_start)
File "/home/users/tfincke/miniconda3/envs/xcube/lib/python3.8/site-packages/xarray/core/variable.py", line 2301, in func
f(self_data, other_data)
numpy.core._exceptions._ArrayMemoryError: Unable to allocate 475. GiB for an array with shape (157500, 404999) and data type float64
The text was updated successfully, but these errors were encountered:
Viewing the dataset will resilt in a DeveloperError: Width must be less than or equal to the maximum texture size (16384). Check maximumTextureSize. This error probably happens due to the massive size of the dataset (157500 * 405000)
The Zarr Data Store contains data from the ODP that has been converted into the zarr format. There is one BIOMASS dataset in the Zarr data store. For the purposes of this issue, we say that a dataset is supported when
The BIOMASS dataset cannot be opened with a spatial subset. The traceback is:
[2021-04-29 08:49:29] Request:
open_dataset(datasetid=ESACCI-BIOMASS-L4-AGB-MERGED-100m-2010-2018-fv2.0.zarr, time_range=('2017-01-01', '2017-01-01'), var_names=['agb', 'agb_se'], region=[123.5265, 60.20374, 123.52827, 60.20552])
Traceback (most recent call last):
File "test_cci_data_support.py", line 327, in test_open_ds
dataset, _ = open_dataset(dataset_id=data_id,
File "/home/users/tfincke/Projects/cate/cate/core/ds.py", line 432, in open_dataset
dataset = select_subset(dataset, **subset_args)
File "/home/users/tfincke/Projects/xcube/xcube/core/select.py", line 37, in select_subset
dataset = select_spatial_subset(dataset, xy_bbox=bbox)
File "/home/users/tfincke/Projects/xcube/xcube/core/select.py", line 85, in select_spatial_subset
geo_coding = geo_coding if geo_coding is not None else GeoCoding.from_dataset(dataset, xy_names=xy_names)
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 132, in from_dataset
return cls.from_xy((x, y), xy_names=(x_name, y_name))
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 169, in from_xy
x, is_lon_normalized = _maybe_normalise_2d_lon(x)
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 462, in _maybe_normalise_2d_lon
if _is_crossing_antimeridian(lon_var):
File "/home/users/tfincke/Projects/xcube/xcube/core/geocoding.py", line 457, in _is_crossing_antimeridian
return abs(lon_var.diff(dim=dim_x)).max() > 180.0 or
File "/home/users/tfincke/miniconda3/envs/xcube/lib/python3.8/site-packages/xarray/core/dataarray.py", line 3107, in diff
ds = self._to_temp_dataset().diff(n=n, dim=dim, label=label)
File "/home/users/tfincke/miniconda3/envs/xcube/lib/python3.8/site-packages/xarray/core/dataset.py", line 5489, in diff
variables[name] = var.isel(**kwargs_end) - var.isel(**kwargs_start)
File "/home/users/tfincke/miniconda3/envs/xcube/lib/python3.8/site-packages/xarray/core/variable.py", line 2301, in func
f(self_data, other_data)
numpy.core._exceptions._ArrayMemoryError: Unable to allocate 475. GiB for an array with shape (157500, 404999) and data type float64
The text was updated successfully, but these errors were encountered: