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
1768118776,I_kwDOAMm_X85pY1n4,7935,Interpolation loses edge points,31730876,open,0,,,0,2023-06-21T17:51:13Z,2023-06-21T17:51:13Z,,NONE,,,,"### What happened?
I'm not sure if this is a bug, normal behaviour or a feature request but if it's expected behaviour, it should be better documented.
I want to interpolate a 2D dataset to a finer spatial grid. I've put together a reproducible example based on the tutorial here: https://docs.xarray.dev/en/stable/user-guide/interpolation.html
The result is this:
![]()
When I do this, the edge points are lost (as you can see on the west/north boundaries here).
### What did you expect to happen?
I'd expect the interpolation to protect the boundary points and not lose them.
### Minimal Complete Verifiable Example
```Python
ds = xr.tutorial.load_dataset(""air_temperature"")
subplot_kw = dict(projection=ccrs.PlateCarree())
new_lon = np.linspace(ds.lon[0], ds.lon[-1], ds.dims[""lon""] * 4)
new_lat = np.linspace(ds.lat[0], ds.lat[-1], ds.dims[""lat""] * 4)
dsi = ds.interp(lat=new_lat, lon=new_lon, method='nearest', kwargs={'fill_value':None})
fig, axes = plt.subplots(1, 2, figsize=(18, 12), subplot_kw=subplot_kw)
axes = np.ravel(axes)
ax = axes[1]
ds.air.isel(time=0).plot(x='lon', y='lat', ax=ax, add_colorbar=False)
ax.set_extent([ds.lon.min()-5., ds.lon.min()+20., ds.lat.max()-20, ds.lat.max()+5])
ax.coastlines()
ax = axes[0]
dsi.air.isel(time=0).plot(x='lon', y='lat', ax=ax, add_colorbar=False)
ax.set_extent([ds.lon.min()-5., ds.lon.min()+20., ds.lat.max()-20, ds.lat.max()+5])
ax.coastlines()
plt.show()
```
### MVCE confirmation
- [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- [X] Complete example — the example is self-contained, including all data and the text of any traceback.
- [X] Verifiable example — the example copy & pastes into an IPython prompt or [Binder notebook](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), returning the result.
- [X] New issue — a search of GitHub Issues suggests this is not a duplicate.
### Relevant log output
_No response_
### Anything else we need to know?
_No response_
### Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.8 | packaged by conda-forge | (default, Jul 31 2020, 02:25:08)
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-1160.90.1.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4
xarray: 0.16.1
pandas: 1.1.3
numpy: 1.19.2
scipy: 1.5.2
netCDF4: 1.5.4
pydap: None
h5netcdf: None
h5py: 2.10.0
Nio: None
zarr: None
cftime: 1.2.1
nc_time_axis: 1.2.0
PseudoNetCDF: None
rasterio: 1.1.8
cfgrib: None
iris: 2.4.0
bottleneck: None
dask: 2.30.0
distributed: 2.30.0
matplotlib: 3.3.2
cartopy: 0.18.0
seaborn: 0.11.0
numbagg: None
pint: None
setuptools: 49.6.0.post20201009
pip: 20.2.3
conda: None
pytest: None
IPython: 5.8.0
sphinx: None
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7935/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
618141254,MDU6SXNzdWU2MTgxNDEyNTQ=,4061,Colormap Normalisation Giving Unexpected/Incorrect Output,31730876,open,0,,,11,2020-05-14T11:10:53Z,2023-03-10T16:10:44Z,,NONE,,,,"The behaviour when specifying ""norm"" for a colormap normalisation does not work as anticipated.
Below I use the example code from matplotlib and apply the same normalisation to the DataArray version of the data but get very different results.
#### MCVE Code Sample
```python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import xarray
#example from https://matplotlib.org/3.1.1/tutorials/colors/colormapnorms.html
#for colormap normalisation
N = 100
X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)]
Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
Z = (Z1 - Z2) * 2
fig, ax = plt.subplots(2, 1, figsize=(8, 8))
ax = ax.flatten()
bounds = np.linspace(-1, 1, 10)
norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
ax[0].pcolormesh(X, Y, Z,
norm=norm,
cmap='RdBu_r')
#now add data into dataset and plot it using same normalisation
data = xarray.DataArray(Z, dims=('x', 'y'), coords={'x': X[:,0], 'y': Y[0,:]})
data.plot(ax=ax[1], x='x', y='y', norm=norm, add_colorbar=False)
plt.show()
```
#### Expected Output
Top is expected, bottom is actual
![]()
#### Problem Description
Colormap normalisation appears to be broken in xarray
#### Versions
Output of xr.show_versions()
xarray.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 21:52:21)
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-957.21.3.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8
libhdf5: 1.10.4
libnetcdf: 4.6.2
xarray: 0.15.1
pandas: 0.25.1
numpy: 1.17.2
scipy: 1.3.1
netCDF4: 1.5.1.2
pydap: None
h5netcdf: None
h5py: 2.9.0
Nio: None
zarr: None
cftime: 1.0.3.4
nc_time_axis: None
PseudoNetCDF: None
rasterio: 1.0.28
cfgrib: None
iris: 2.2.0
bottleneck: None
dask: 2.5.2
distributed: 2.5.2
matplotlib: 3.1.1
cartopy: 0.17.0
seaborn: 0.9.0
numbagg: None
setuptools: 41.4.0
pip: 19.2.3
conda: None
pytest: None
IPython: 7.8.0
sphinx: None