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 650547452,MDU6SXNzdWU2NTA1NDc0NTI=,4196,Convolution operation,31700619,closed,0,,,10,2020-07-03T11:51:15Z,2024-02-02T18:29:40Z,2022-04-17T18:09:14Z,CONTRIBUTOR,,,,"I would like to perform 2d convolution operation with dask-data stored in xarray, defining the kernel. Related issue are: https://github.com/pydata/xarray/issues/1142 https://github.com/pydata/xarray/issues/2010 https://github.com/pydata/xarray/issues/1323 Referring to Dask, they have a specific image-oriented API which allows for convolutions: http://image.dask.org/en/latest/dask_image.ndfilters.html And this guy already implemented convolution operation based on xarray and dask: https://github.com/serazing https://github.com/serazing/xscale https://xscale.readthedocs.io/en/latest/api.html Are there plans to implement this feature? In the meanwhile I'll try dask-image and xscale.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4196/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 599583548,MDU6SXNzdWU1OTk1ODM1NDg=,3969,[BUG] xr.merge converts automatically variables into float64,31700619,closed,0,,,2,2020-04-14T13:42:48Z,2020-12-07T16:42:13Z,2020-12-07T16:42:13Z,CONTRIBUTOR,,,," Merging two datasets using xr.merge converts all the variables to float64 type. #### MCVE Code Sample ``` import numpy as np import xarray as xr x = np.arange(0,10) y = np.arange(0,10) time = [0,1] data = np.zeros((10,10), dtype=bool) dataArray1 = xr.DataArray([data], coords={'time': [time[0]], 'y': y, 'x': x}, dims=['time', 'y', 'x']) dataArray2 = xr.DataArray([data], coords={'time': [time[1]], 'y': y, 'x': x}, dims=['time', 'y', 'x']) dataArray1 = dataArray1.to_dataset(name='data') dataArray2 = dataArray2.to_dataset(name='data') xr.merge([dataArray1,dataArray2]) ``` #### Current Output ``` Dimensions: (time: 2, x: 10, y: 10) Coordinates: * time (time) int64 0 1 * y (y) int64 0 1 2 3 4 5 6 7 8 9 * x (x) int64 0 1 2 3 4 5 6 7 8 9 Data variables: data (time, y, x) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 ``` #### Expected Output ``` Dimensions: (time: 2, x: 10, y: 10) Coordinates: * time (time) int64 0 1 * y (y) int64 0 1 2 3 4 5 6 7 8 9 * x (x) int64 0 1 2 3 4 5 6 7 8 9 Data variables: data (time, y, x) bool False False False False False ... False False False False False ``` #### Problem Description The merge function should not convert data types into float64. In this case is increasing the memory usage compared to what is expected. #### Versions
INSTALLED VERSIONS ------------------ commit: None python: 3.6.8 (default, May 7 2019, 14:58:50) [GCC 8.3.0] python-bits: 64 OS: Linux OS-release: 4.15.0-88-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: C.UTF-8 LOCALE: en_US.UTF-8 libhdf5: None libnetcdf: None xarray: 0.15.1 pandas: 1.0.3 numpy: 1.18.2 scipy: None netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: 3.2.0 cartopy: None seaborn: None numbagg: None setuptools: 46.1.3 pip: 9.0.1 conda: None pytest: None IPython: 7.13.0 sphinx: 2.4.3
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3969/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 620009114,MDU6SXNzdWU2MjAwMDkxMTQ=,4072,[BUG] xr.concat inverts coordinates order,31700619,closed,0,,,5,2020-05-18T08:25:09Z,2020-09-19T09:41:01Z,2020-09-19T09:41:00Z,CONTRIBUTOR,,,," Following the issue #3969 Merging two datasets using xr.concat inverts the coordinates order. #### MCVE Code Sample ``` import numpy as np import xarray as xr x = np.arange(0,10) y = np.arange(0,10) time = [0,1] data = np.zeros((10,10), dtype=bool) dataArray1 = xr.DataArray([data], coords={'time': [time[0]], 'y': y, 'x': x}, dims=['time', 'y', 'x']) dataArray2 = xr.DataArray([data], coords={'time': [time[1]], 'y': y, 'x': x}, dims=['time', 'y', 'x']) dataArray1 = dataArray1.to_dataset(name='data') dataArray2 = dataArray2.to_dataset(name='data') print(dataArray1) print(xr.concat([dataArray1,dataArray2], dim='time')) ``` #### Current Output ``` Dimensions: (time: 1, x: 10, y: 10) Coordinates: * time (time) int64 0 * y (y) int64 0 1 2 3 4 5 6 7 8 9 * x (x) int64 0 1 2 3 4 5 6 7 8 9 Data variables: data (time, y, x) bool False False False False ... False False False Dimensions: (time: 2, x: 10, y: 10) Coordinates: * x (x) int64 0 1 2 3 4 5 6 7 8 9 ##Inverted x and y * y (y) int64 0 1 2 3 4 5 6 7 8 9 * time (time) int64 0 1 Data variables: data (time, y, x) bool False False False False ... False False False ``` #### Expected Output ``` Dimensions: (time: 1, x: 10, y: 10) Coordinates: * time (time) int64 0 * y (y) int64 0 1 2 3 4 5 6 7 8 9 * x (x) int64 0 1 2 3 4 5 6 7 8 9 Data variables: data (time, y, x) bool False False False False ... False False False Dimensions: (time: 2, x: 10, y: 10) Coordinates: * y (y) int64 0 1 2 3 4 5 6 7 8 9 * x (x) int64 0 1 2 3 4 5 6 7 8 9 * time (time) int64 0 1 Data variables: data (time, y, x) bool False False False False ... False False False ``` #### Problem Description The concat function should not invert the coordinates but maintain the original order. #### Versions
INSTALLED VERSIONS ------------------ commit: None python: 3.6.8 (default, May 7 2019, 14:58:50) [GCC 8.3.0] python-bits: 64 OS: Linux OS-release: 4.15.0-88-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: C.UTF-8 LOCALE: en_US.UTF-8 libhdf5: None libnetcdf: None xarray: 0.15.1 pandas: 1.0.3 numpy: 1.18.2 scipy: None netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: 3.2.0 cartopy: None seaborn: None numbagg: None setuptools: 46.1.3 pip: 9.0.1 conda: None pytest: None IPython: 7.13.0 sphinx: 2.4.3
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4072/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 618248655,MDExOlB1bGxSZXF1ZXN0NDE4MDExMDk2,4063,Io docs typo fix,31700619,closed,0,,,1,2020-05-14T13:50:45Z,2020-05-14T14:28:58Z,2020-05-14T14:28:55Z,CONTRIBUTOR,,0,pydata/xarray/pulls/4063," - [x] Closes #4059 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4063/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 617990073,MDU6SXNzdWU2MTc5OTAwNzM=,4059,Typo in Reading and writing files docs,31700619,closed,0,,,3,2020-05-14T07:24:39Z,2020-05-14T14:28:55Z,2020-05-14T14:28:55Z,CONTRIBUTOR,,,," There is a typo in http://xarray.pydata.org/en/stable/io.html#rasterio `In [35]: rds4326 = rio.rio.reproject(""epsg:4326"")` Should instead be `In [35]: rds4326 = rds.rio.reproject(""epsg:4326"")` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4059/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue