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- Abnormal process termination when using bottleneck function on xarray data after transposing and having a dimension with length 1 · 3 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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974066877 | https://github.com/pydata/xarray/issues/6002#issuecomment-974066877 | https://api.github.com/repos/pydata/xarray/issues/6002 | IC_kwDOAMm_X846DxS9 | RubendeBruin 34062862 | 2021-11-19T13:20:28Z | 2021-11-19T13:20:28Z | NONE | Ok, then it is clearly a bottleneck/numpy issue. I will raise it there and close it here. Thanks! |
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Abnormal process termination when using bottleneck function on xarray data after transposing and having a dimension with length 1 1057335460 | |
973937765 | https://github.com/pydata/xarray/issues/6002#issuecomment-973937765 | https://api.github.com/repos/pydata/xarray/issues/6002 | IC_kwDOAMm_X846DRxl | RubendeBruin 34062862 | 2021-11-19T10:17:00Z | 2021-11-19T10:17:00Z | NONE | I can reproduce it with calling bn.nanmax directly, but I can not reproduce it without the xarray.transpose() function.
I suspect that the xarray.transpose function does something with the data-structure (lazy reshuffling of dimensions?) that triggers the fault in bottleneck. Full code: ```python from collections import OrderedDict import numpy as np import xarray as xr xr.show_versions() n_time = 1 # 1 : Fails, 2 : everything is fine from xarray.core.options import OPTIONS OPTIONS["use_bottleneck"] = True # Set to False for work-around Build some datasetdirs = np.linspace(0,360, num=121) freqs = np.linspace(0,4,num=192) spec_data = np.random.random(size=(n_time,192,121)) dims = ('time', 'freq', 'dir') coords = OrderedDict() coords['time'] = range(n_time) coords['freq'] = freqs coords['dir'] = dirs xdata = xr.DataArray( data=spec_data, coords=coords, dims=dims, name='Spec name', ).to_dataset() xdata = xdata.transpose(..., "freq") import bottleneck as bn np_data = xdata['Spec name'].data new_data = np_data.copy() bn.nanmax(new_data) # works bn.nanmax(np_data) # Segfault print('direct bn call done') ``` |
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Abnormal process termination when using bottleneck function on xarray data after transposing and having a dimension with length 1 1057335460 | |
973159855 | https://github.com/pydata/xarray/issues/6002#issuecomment-973159855 | https://api.github.com/repos/pydata/xarray/issues/6002 | IC_kwDOAMm_X846AT2v | RubendeBruin 34062862 | 2021-11-18T18:51:50Z | 2021-11-18T18:51:50Z | NONE | tests on another machine (also win64) with the same result. Running under WSL/Ubuntu results in a Segmentation Fault |
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Abnormal process termination when using bottleneck function on xarray data after transposing and having a dimension with length 1 1057335460 |
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