html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/6003#issuecomment-981408883,https://api.github.com/repos/pydata/xarray/issues/6003,981408883,IC_kwDOAMm_X846fxxz,34062862,2021-11-29T08:49:02Z,2021-11-29T08:49:02Z,NONE,"""does that work on your end?""
yes it does. Will remove the xfail and then we can merge once https://github.com/pydata/bottleneck/pull/382 is merged.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057355557
https://github.com/pydata/xarray/pull/6003#issuecomment-979285475,https://api.github.com/repos/pydata/xarray/issues/6003,979285475,IC_kwDOAMm_X846XrXj,34062862,2021-11-25T15:03:17Z,2021-11-25T15:03:17Z,NONE,"I've added xfail , thanks for the link.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057355557
https://github.com/pydata/xarray/pull/6003#issuecomment-979146287,https://api.github.com/repos/pydata/xarray/issues/6003,979146287,IC_kwDOAMm_X846XJYv,34062862,2021-11-25T12:01:38Z,2021-11-25T12:01:38Z,NONE,"Hi @max-sixty , what is a `xfail` ?
Also, the issue turned out to be bottleneck-bug , ref: https://github.com/pydata/bottleneck/issues/393#issuecomment-978017397 (fix available)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057355557
https://github.com/pydata/xarray/issues/6002#issuecomment-974066877,https://api.github.com/repos/pydata/xarray/issues/6002,974066877,IC_kwDOAMm_X846DxS9,34062862,2021-11-19T13:20:28Z,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!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057335460
https://github.com/pydata/xarray/issues/6002#issuecomment-973937765,https://api.github.com/repos/pydata/xarray/issues/6002,973937765,IC_kwDOAMm_X846DRxl,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.
- If I call nanmax on the internal data of xarray then nanmax fails with a segfault:
```python
np_data = xdata['Spec name'].data
bn.nanmax(np_data) # Segfault
```
- But if I create a **copy** of that data and then call nanmax then it works fine.
```python
np_data = xdata['Spec name'].data
new_data = np_data.copy()
bn.nanmax(new_data) # works
```
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 dataset
dirs = 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')
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057335460
https://github.com/pydata/xarray/issues/6002#issuecomment-973159855,https://api.github.com/repos/pydata/xarray/issues/6002,973159855,IC_kwDOAMm_X846AT2v,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","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057335460
https://github.com/pydata/xarray/issues/6001#issuecomment-972680945,https://api.github.com/repos/pydata/xarray/issues/6001,972680945,IC_kwDOAMm_X845-e7x,34062862,2021-11-18T09:21:18Z,2021-11-18T09:21:18Z,NONE,Gets too messy - will clean up and re-open,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057082683
https://github.com/pydata/xarray/issues/6001#issuecomment-972678034,https://api.github.com/repos/pydata/xarray/issues/6001,972678034,IC_kwDOAMm_X845-eOS,34062862,2021-11-18T09:17:49Z,2021-11-18T09:17:49Z,NONE,"Minimum conda environment to reproduce:
```yml
name: ws
dependencies:
- xarray
- numba
channels:
- defaults
- conda-forge
```
resulting in:
```
# Name Version Build Channel
blas 1.0 mkl
bottleneck 1.3.2 py38h2a96729_1
ca-certificates 2021.10.26 haa95532_2
importlib-metadata 4.8.2 py38haa244fe_0 conda-forge
importlib_metadata 4.8.2 hd8ed1ab_0 conda-forge
intel-openmp 2021.4.0 haa95532_3556
libblas 3.9.0 12_win64_mkl conda-forge
libcblas 3.9.0 12_win64_mkl conda-forge
liblapack 3.9.0 12_win64_mkl conda-forge
llvmlite 0.35.0 py38h34b8924_4
mkl 2021.4.0 h0e2418a_729 conda-forge
mkl-service 2.4.0 py38h2bbff1b_0
numba 0.52.0 py38hf11a4ad_0
numexpr 2.7.3 py38hb80d3ca_1
numpy 1.21.4 py38h089cfbf_0 conda-forge
openssl 1.1.1l h2bbff1b_0
pandas 1.3.4 py38h6214cd6_0
pip 21.3.1 pyhd8ed1ab_0 conda-forge
python 3.8.12 h6244533_0
python-dateutil 2.8.2 pyhd3eb1b0_0
python_abi 3.8 2_cp38 conda-forge
pytz 2021.3 pyhd3eb1b0_0
setuptools 59.1.1 py38haa244fe_0 conda-forge
six 1.16.0 pyhd3eb1b0_0
sqlite 3.36.0 h2bbff1b_0
tbb 2021.4.0 h59b6b97_0
typing_extensions 4.0.0 pyha770c72_0 conda-forge
ucrt 10.0.20348.0 h57928b3_0 conda-forge
vc 14.2 h21ff451_1
vs2015_runtime 14.29.30037 h902a5da_5 conda-forge
wheel 0.37.0 pyhd3eb1b0_1
xarray 0.20.1 pyhd8ed1ab_0 conda-forge
zipp 3.6.0 pyhd3eb1b0_0
zlib 1.2.11 h62dcd97_4
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057082683
https://github.com/pydata/xarray/issues/6001#issuecomment-972665006,https://api.github.com/repos/pydata/xarray/issues/6001,972665006,IC_kwDOAMm_X845-bCu,34062862,2021-11-18T09:02:05Z,2021-11-18T09:02:05Z,NONE,So not sure if I should post the issue here on with numba,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1057082683
https://github.com/pydata/xarray/issues/3622#issuecomment-575520252,https://api.github.com/repos/pydata/xarray/issues/3622,575520252,MDEyOklzc3VlQ29tbWVudDU3NTUyMDI1Mg==,34062862,2020-01-17T08:06:04Z,2020-01-17T08:06:04Z,NONE,Thanks for the link to the tutorial! ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,537936090