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  • xarray · 3 ✖
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
331668890 MDU6SXNzdWUzMzE2Njg4OTA= 2227 Slow performance of isel JohnMrziglod 4180033 open 0     28 2018-06-12T16:46:14Z 2023-03-14T18:54:16Z   NONE      

Hi,

I get a very slow performance of Dataset.isel or DataArray.isel in comparison with the native numpy approach. Do you know where this comes from?

python ds = xr.Dataset( { "a": ("time", np.arange(55_000_000)) }, coords={ "time": np.arange(55_000_000) } ) time_filter = ds.time > 50_000

Select some values with DataArray.isel: python %timeit ds.a.isel(time=time_filter) 2.22 s ± 375 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

Use the native numpy approach: python %timeit ds.a.values[time_filter] 163 ms ± 12.1 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

INSTALLED VERSIONS ------------------ commit: None python: 3.6.5.final.0 python-bits: 64 OS: Linux OS-release: 3.16.0-4-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_US.utf8 LOCALE: en_US.UTF-8 xarray: 0.10.4 pandas: 0.23.0 numpy: 1.14.2 scipy: 1.1.0 netCDF4: 1.4.0 h5netcdf: 0.5.1 h5py: 2.8.0 Nio: None zarr: None bottleneck: 1.2.1 cyordereddict: None dask: 0.17.5 distributed: 1.21.8 matplotlib: 2.2.2 cartopy: 0.16.0 seaborn: 0.8.1 setuptools: 39.1.0 pip: 9.0.3 conda: None pytest: 3.5.1 IPython: 6.4.0 sphinx: 1.7.4 
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     xarray 13221727 issue
313010564 MDU6SXNzdWUzMTMwMTA1NjQ= 2049 Keeping attributes when using DataArray.astype JohnMrziglod 4180033 closed 0     5 2018-04-10T17:02:18Z 2020-08-19T20:34:35Z 2020-08-19T20:34:35Z NONE      

Hi all,

I was wondering whether there is an easier way to keep the attributes when using the DataArray.astype method?

```python import xarray as xr

DataArray with attributes

da = xr.DataArray( [[0, 1, 2], [0, 1, 2]], attrs={"attr1": "value1"} )

the attributes are not passed over to new_da

new_da = da.astype(float)

I have to set the attributes by myself

new_da.attrs = da.attrs.copy() ```

This is just one extra-line, but I have to keep track of the old DataArray and it may become unhandy if I do many astype calls.

Any hints?

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.4.final.0 python-bits: 64 OS: Linux OS-release: 3.16.0-4-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_US.utf8 LOCALE: en_US.UTF-8 xarray: 0.10.2 pandas: 0.22.0 numpy: 1.14.2 scipy: 1.0.0 netCDF4: 1.3.1 h5netcdf: 0.5.0 h5py: 2.7.1 Nio: None zarr: None bottleneck: 1.2.1 cyordereddict: None dask: 0.17.2 distributed: 1.21.4 matplotlib: 2.2.2 cartopy: 0.16.0 seaborn: 0.8.1 setuptools: 39.0.1 pip: 9.0.1 conda: None pytest: 3.4.2 IPython: 6.2.1 sphinx: 1.7.1 
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   completed xarray 13221727 issue
316726712 MDU6SXNzdWUzMTY3MjY3MTI= 2076 Get sub level names from multiindex JohnMrziglod 4180033 closed 0     2 2018-04-23T09:14:30Z 2018-05-18T05:13:38Z 2018-05-18T05:13:38Z NONE      

Hi, is there any method / attribute to get the sub level names from a MultiIndex?

python ds = xr.Dataset({ "lat": np.arange(100), "lon": np.arange(100), }) ds.stack(main=("lat", "lon"))

<xarray.Dataset> Dimensions: (main: 10000) Coordinates: * main (main) MultiIndex - lat (main) int64 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... - lon (main) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ... Data variables: *empty*

I would like to have the names lat and lon as a list (let's assume I did not know that they were stacked together). They should be stored internally, right? I even went through the formatting module to search for the correct attribute but I could not find it.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.5.final.0 python-bits: 64 OS: Linux OS-release: 3.16.0-4-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: en_US.utf8 LOCALE: en_US.UTF-8 xarray: 0.10.3 pandas: 0.22.0 numpy: 1.14.2 scipy: 1.0.1 netCDF4: 1.3.1 h5netcdf: 0.5.0 h5py: 2.7.1 Nio: None zarr: None bottleneck: 1.2.1 cyordereddict: None dask: 0.17.2 distributed: 1.21.6 matplotlib: 2.2.2 cartopy: 0.16.0 seaborn: 0.8.1 setuptools: 39.0.1 pip: 9.0.3 conda: None pytest: 3.5.0 IPython: 6.3.1 sphinx: 1.7.2 
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   completed xarray 13221727 issue

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