Description
Code Sample, a copy-pastable example if possible
A "Minimal, Complete and Verifiable Example" will make it much easier for maintainers to help you:
http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
import numpy as np
import xarray as xr
data2 = np.random.randn(3,100, 4)
da = xr.DataArray(
data2,
name='value',
dims=['replicate', 'rsample', 'exp'],
coords=dict(replicate=[0,1,2],
exp=['a', 'b', 'c', 'd'], rsample=list(range(100))))
da2 = da.stack(sample=('replicate', 'rsample'))
da2.sample.max()Problem description
Calling max() on a stacked dimension raises the exception
ValueError: dimensions () must have the same length as the number of data dimensions, ndim=1
Expected Output
Maximum value of selected dimension. i.e an index I can use with loc
e.g. da2.loc['a', da2.sample.max()] that is da2.loc['a', (2,99)]
So I guess I'm expecting something like:
<xarray.DataArray 'sample' ()>
array((2, 99), dtype=object)
This works: da2.loc['a', xr.DataArray((2,99), dims=(), name='sample')]
Output of xr.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.7.3 (default, Mar 27 2019, 22:11:17)
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 4.15.0-47-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_AU.UTF-8
LOCALE: en_AU.UTF-8
libhdf5: 1.10.4
libnetcdf: 4.6.1
xarray: 0.12.1
pandas: 0.24.2
numpy: 1.15.4
scipy: 1.2.1
netCDF4: 1.4.2
pydap: None
h5netcdf: None
h5py: 2.9.0
Nio: None
zarr: None
cftime: 1.0.3.4
nc_time_axis: None
PseudonetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.2.1
dask: 1.2.0
distributed: 1.27.0
matplotlib: 3.0.3
cartopy: None
seaborn: 0.9.0
setuptools: 40.6.3
pip: 18.1
conda: 4.6.14
pytest: None
IPython: 7.4.0
sphinx: 2.0.1