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id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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1957984278 | PR_kwDOAMm_X85dkvM8 | 8363 | docs: add searchable word "asterisk" | templiert 34257249 | closed | 0 | 1 | 2023-10-23T20:37:59Z | 2023-10-23T21:44:13Z | 2023-10-23T21:44:07Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/8363 | { "url": "https://api.github.com/repos/pydata/xarray/issues/8363/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
xarray 13221727 | pull | ||||||
1656130602 | I_kwDOAMm_X85itowq | 7726 | open_zarr: PermissionError with multiple processes despite use of ProcessSynchronizer | templiert 34257249 | open | 0 | 0 | 2023-04-05T18:55:12Z | 2023-04-06T01:37:32Z | CONTRIBUTOR | What happened?Several processes read and write to a xarray stored in .zarr format, on a network. The write operations write to existing regions. These regions are not aligned to chunks, therefore I use a ProcessSynchronizer. The ProcessSynchronizer points to a local folder on SSD, separate from the actual stored array. After several hundreds of read/write I get permission errors like below. So far I have failed to reproduce the error with a MCVE. The file What did you expect to happen?No permission error. Minimal Complete Verifiable Example```Python I have failed so far to reproduce the error with an MVCE. Here my attempt. from pathlib import Path import dask.array as da import pandas as pd import xarray as xr from dask.distributed import Client from zarr.sync import ProcessSynchronizer if name == "main": path_store = Path(aaa) path_synchronizer = Path(bbb) # must exist, and not same location as store
``` MVCE confirmation
Relevant log output
Anything else we need to know?No response Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.10.9 | packaged by Anaconda, Inc. | (main, Mar 1 2023, 18:18:15) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('English_United States', '1252')
libhdf5: 1.10.6
libnetcdf: None
xarray: 2022.11.0
pandas: 1.5.3
numpy: 1.23.5
scipy: 1.10.0
netCDF4: None
pydap: None
h5netcdf: None
h5py: 3.7.0
Nio: None
zarr: 2.14.2
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.5
dask: 2022.7.0
distributed: None
matplotlib: 3.7.0
cartopy: None
seaborn: 0.12.2
numbagg: None
fsspec: 2022.11.0
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.6.3
pip: 23.0.1
conda: 23.1.0
pytest: 7.1.2
IPython: 8.10.0
sphinx: 5.0.2
|
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xarray 13221727 | issue | ||||||||
1584580877 | I_kwDOAMm_X85ecskN | 7527 | DataArray.idxmax converts coordinates into float64 by default | templiert 34257249 | open | 0 | 0 | 2023-02-14T17:45:07Z | 2023-02-14T17:51:33Z | CONTRIBUTOR | What happened?Same example as in DataArray.idxmax but instead we look at the "y" dimension.
The starting "y" coordinates are of type int: The return values of argmax are of type int64: good. The return values of idxmax are of type float64: bad. What did you expect to happen?If no fillna operation must occur, then the return values of idxmax should be the same type as from the input. Else, the return type might change to a new type depending on the type of the filled value. Minimal Complete Verifiable Example
MVCE confirmation
Relevant log output```Python In [41]: print(array.argmax(dim="y").dtype) int64 In [42]: print(array.idxmax(dim="y").dtype) float64 ``` Anything else we need to know?Suggestions:
- change these two lines:
Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.13 (main, Aug 25 2022, 23:51:50) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('English_United States', '1252')
libhdf5: 1.10.6
libnetcdf: None
xarray: 0.20.1
pandas: 1.4.4
numpy: 1.24.2
scipy: 1.9.1
netCDF4: None
pydap: None
h5netcdf: None
h5py: 3.7.0
Nio: None
zarr: 2.13.3
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.5
dask: 2022.7.0
distributed: 2022.7.0
matplotlib: 3.5.2
cartopy: None
seaborn: 0.11.2
numbagg: None
fsspec: 2022.7.1
cupy: None
pint: None
sparse: None
setuptools: 63.4.1
pip: 23.0
conda: 22.9.0
pytest: 7.1.2
IPython: 7.31.1
sphinx: 5.0.2
|
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xarray 13221727 | issue | ||||||||
1449765224 | PR_kwDOAMm_X85C7az5 | 7291 | typo in xarray/doc/user-guide/reshaping.rst | templiert 34257249 | closed | 0 | 1 | 2022-11-15T13:12:41Z | 2023-02-14T17:13:46Z | 2022-11-15T15:20:42Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/7291 | Closes #7289 |
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xarray 13221727 | pull | |||||
1452123685 | I_kwDOAMm_X85WjaYl | 7294 | DataArray.transpose with transpose_coords=True does not change coords order | templiert 34257249 | open | 0 | 6 | 2022-11-16T19:02:27Z | 2022-11-24T20:40:32Z | CONTRIBUTOR | What happened?I used DataArray.transpose with The order of dims was correctly transposed but the order of coords remained unchanged. What did you expect to happen?I expected the transposed coords to be in the new order:
Minimal Complete Verifiable Example```Python import numpy as np import pandas as pd import xarray as xr np.random.seed(0) temperature = np.random.randn(4, 4, 3) dim_0_values = [1, 2, 3, 4] dim_1_values = [5, 6, 7, 8] dim_2_values = pd.date_range("2014-09-06", periods=3) starting_dims = "dim_0", "dim_1", "dim_2" da = xr.DataArray( data=temperature, dims=starting_dims, coords=dict( dim_0=dim_0_values, dim_1=dim_1_values, dim_2=dim_2_values, ), attrs=dict( description="Ambient temperature.", units="degC", ), ) print(f"{da.dims=}") print(f"{da.coords.keys()=}") reordered_dims = "dim_2", "dim_1", "dim_0" print(f"{da.transpose(reordered_dims).dims=}") print(f"{da.transpose(reordered_dims).coords.keys()=}") print(f"{da.transpose(*reordered_dims, transpose_coords=True).coords.keys()=}") ``` MVCE confirmation
Relevant log output
Anything else we need to know?No response Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.12 (main, Apr 4 2022, 05:22:27) [MSC v.1916 64 bit (AMD64)]
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('English_United States', '1252')
libhdf5: 1.10.6
libnetcdf: None
xarray: 2022.6.0
pandas: 1.4.2
numpy: 1.21.5
scipy: 1.9.3
netCDF4: None
pydap: None
h5netcdf: None
h5py: 3.6.0
Nio: None
zarr: 2.13.2
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.4
dask: 2022.02.1
distributed: 2022.2.1
matplotlib: 3.5.1
cartopy: None
seaborn: 0.11.2
numbagg: None
fsspec: 2022.02.0
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 61.2.0
pip: 22.3.1
conda: 4.12.0
pytest: 7.1.1
IPython: 8.2.0
sphinx: 4.4.0
|
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xarray 13221727 | issue | ||||||||
1449069429 | I_kwDOAMm_X85WXwt1 | 7289 | typo in xarray/doc/user-guide/reshaping.rst | templiert 34257249 | closed | 0 | 2 | 2022-11-15T02:47:56Z | 2022-11-15T15:20:44Z | 2022-11-15T15:20:44Z | CONTRIBUTOR | What is your issue?line 23 An ellipsis (...) can be use -> An ellipsis (...) can be used |
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completed | xarray 13221727 | issue |
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