issue_comments

@jklymak Thanks for the explanation.

To get the old behaviour you simply need to do pcolormesh(x, y, Z[:-1, :-1], shading='flat') or make x and y one larger than Z in each dimension and specify the the corners of the quadrilaterals.

Method1: Subset value

This method works for the xarray tutorial data, but not for the TROPOMI polar-orbiting satellite data.

``` %matplotlib inline

import xarray as xr import cartopy.crs as ccrs import matplotlib.pyplot as plt

plt.figure(figsize=(14,6)) ax = plt.axes(projection=ccrs.PlateCarree())

ds = xr.open_dataset('./S5P_OFFL_L2__NO2____20190810T212136_20190810T230306_09456_01_010302_20190816T233944.nc', group='PRODUCT').isel(time=0)

m = ax.pcolormesh(ds['longitude'], ds['latitude'], ds['nitrogendioxide_tropospheric_column'][:-1, :-1], # ds['nitrogendioxide_tropospheric_column'], # shading='auto', transform=ccrs.PlateCarree(), vmin=0, vmax=1e-4, cmap='Spectral_r') ```

(The TROPOMI example data is uploaded to Google Drive)

Method2: bounds

This issue still exists with bounds data: ``` %matplotlib inline import numpy as np import xarray as xr import cartopy.crs as ccrs import matplotlib.pyplot as plt

def prepare_geo(bounds_data): """Prepare lat/lon bounds for pcolormesh. lat/lon bounds are ordered in the following way:: 3----2 | | 0----1 Extend longitudes and latitudes with one element to support "pcolormesh":: (X[i+1, j], Y[i+1, j]) (X[i+1, j+1], Y[i+1, j+1]) +--------+ | C[i,j] | +--------+ (X[i, j], Y[i, j]) (X[i, j+1], Y[i, j+1]) """ # Create the left array left = np.vstack([bounds_data[:, :, 0], bounds_data[-1:, :, 3]]) # Create the right array right = np.vstack([bounds_data[:, -1:, 1], bounds_data[-1:, -1:, 2]]) # Stack horizontally dest = np.hstack([left, right]) # Convert to DataArray dest = xr.DataArray(dest, dims=('y_bounds', 'x_bounds'), attrs=bounds_data.attrs ) return dest

ds = xr.open_dataset('./S5P_OFFL_L2__NO2_20190810T21213620190810T230306_09456_01_010302_20190816T233944.nc', group='PRODUCT').isel(time=0) ds_geo = xr.open_dataset('./S5P_OFFL_L2NO2____20190810T212136_20190810T230306_09456_01_010302_20190816T233944.nc', group='/PRODUCT/SUPPORT_DATA/GEOLOCATIONS').isel(time=0)

lon_bounds = prepare_geo(ds_geo['longitude_bounds']) lat_bounds = prepare_geo(ds_geo['latitude_bounds'])

plt.figure(figsize=(14,6)) ax = plt.axes(projection=ccrs.PlateCarree())

m = ax.pcolormesh(lon_bounds, lat_bounds, ds['nitrogendioxide_tropospheric_column'], # shading='auto', transform=ccrs.PlateCarree(), vmin=0, vmax=1e-4, cmap='Spectral_r') ```

Just to explain the issue a bit: pcolormesh(x, y, Z, shading='flat') was the default. If shape(Z) used to be (len(y), len(x)) matplotlib would drop, without warning, the last row and column of Z so that y and x were one larger than Z.

The new default is 'auto' where in the case above it uses shading='nearest' to create new x and y co-ordinates with the dumbest algorithm possible of placing them in the midpoints, and adding two new points on the outside. So rather than drop data from Z, we add to the x and y co-ordinates.

That is usually fine, except the midpoint between 0 and 360 is 180, and we get a weird wrap. Cartopy (xarray) accounted for this with the old shading by adding a NaN. I've not followed what they are doing now.

To get the old behaviour you simply need to do pcolormesh(x, y, Z[:-1, :-1], shading='flat') or make x and y one larger than Z in each dimension and specify the the corners of the quadrilaterals.

Sorry this is a pain, but the old behaviour of silently dropping data, while having a long lineage going back to Matlab, was deemed unacceptable. However, if this continues to be a nuisance to folks, I'm sure matplotlib would consider a new shading argument, something like 'flat-drop', or somesuch that would do the data dropping for you.

Thanks for the report. This is related to #4364 https://github.com/SciTools/cartopy/issues/1638 and https://github.com/matplotlib/matplotlib/issues/18317.

@QuLogic Ha, it looks well with the latest cartopy (0.20.1). Thanks a lot.

@TomNicholas So, is it better to keep this open until the doc is updated?

Have you tried with the latest Cartopy?

@TomNicholas I checked the doc and this issue begins from v0.16.1. Note that there're also small spurious lines after v0.10.9. Before v0.10.9, the figure looks fine. It's may be also related to matplotlib ... CC @jklymak and @timhoffm.

BTW, the question on StackOverflow, which was raised by @gerritholl a long time ago, looks similar. I'm not sure whether this is the cartopy issue, CC @QuLogic, and @greglucas.

Thanks for flagging this @zxdawn!

:confused: We should probably work out whether this is happening because of something we did or something cartopy/matplotlib did...

When did this start? I wonder if there is an easy way to see all the previous editions of xarray's documentation - might help us quickly narrow down which version first had this issue?