Description
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
<xarray.Dataset>
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
<xarray.Dataset>
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
<xarray.Dataset>
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
<xarray.Dataset>
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: Nonexarray: 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
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