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I wonder if anyone can shed some light on to what I am doing wrong here in terms of rolling the data 180. Is there some option I have to pass to rioarray? This should be trivial....

I wonder if anyone can shed some light on to what I am doing wrong here in terms of rolling the data 180. Is there some option I have to pass to rioarray? This should be trivial....

    projection=ccrs.PlateCarree(central_longitude=-180)
    ax = plt.subplot(1, 1, 1, projection=projection)
    ax.coastlines()

    extent = [-248, -100, 20, 85]
    ax.set_extent(extent)
    ax.add_feature(cfeature.LAND)
    ax.add_feature(cfeature.COASTLINE)

    records = pices.get_LME_records()
    
    for key in config_pices_obj.dset_dict:
        ds=config_pices_obj.dset_dict[key]
    

        ds = ds.assign_coords(lon=(((ds.lon + 180) % 360) - 180)).sortby('lon')
        ds = pices.preprocessing_wrapper(ds)
 
        # Set the CRS of the CMIP6 data
        ds = ds.rio.write_crs(4326)
        print("Geometric projection of dataset : {}".format(ds.rio.crs))
 
        counter=0
        all_lmes=[]
        for LME_GEO, record in zip(records.geometries(), records.records()):
           LME_NAME = record.attributes['LME_NAME']
           LME_NUMBER = int(record.attributes['LME_NUMBER'])
        
           if (LME_NAME in config_pices_obj.LMES):
               print("=> LME_NAME {} ({})".format(LME_NAME,LME_NUMBER))
               ax.add_geometries([LME_GEO], projection,
                   facecolor="None", edgecolor='k')
           
               geometries = [get_geometry_for_LME(LME_NAME)]
        
               # Clip the data inside the LME: 
               clipped = ds.rio.clip(geometries=geometries, crs=ds.rio.crs)
               all_lmes.append(clipped)
         
          #  ds.tos.isel(time=0).plot(ax=ax, cmap='coolwarm',transform=ccrs.PlateCarree())
            
          #  plt.show()
    
       ds_lme=xr.merge(all_lmes)
       ds_lme.tos.isel(time=0).plot(ax=ax, transform=ccrs.PlateCarree(), cmap='coolwarm')

       plt.show()
 

projection=ccrs.PlateCarree(central_longitude=-180)
ax = plt.subplot(1, 1, 1, projection=projection)
ax.coastlines()

extent = [-248, -100, 20, 85]
ax.set_extent(extent)
ax.add_feature(cfeature.LAND)
ax.add_feature(cfeature.COASTLINE)

records = pices.get_LME_records()

for key in config_pices_obj.dset_dict:
    ds=config_pices_obj.dset_dict[key]


    ds = ds.assign_coords(lon=(((ds.lon + 180) % 360) - 180)).sortby('lon')
    ds = pices.preprocessing_wrapper(ds)
 
    # Set the CRS of the CMIP6 data
    ds = ds.rio.write_crs(4326)
    print("Geometric projection of dataset : {}".format(ds.rio.crs))
 
    counter=0
    all_lmes=[]
    for LME_GEO, record in zip(records.geometries(), records.records()):
       LME_NAME = record.attributes['LME_NAME']
       LME_NUMBER = int(record.attributes['LME_NUMBER'])
    
       if (LME_NAME in config_pices_obj.LMES):
           print("=> LME_NAME {} ({})".format(LME_NAME,LME_NUMBER))
           ax.add_geometries([LME_GEO], projection,
               facecolor="None", edgecolor='k')
       
           geometries = [get_geometry_for_LME(LME_NAME)]
    
           # Clip the data inside the LME: 
           clipped = ds.rio.clip(geometries=geometries, crs=ds.rio.crs)
           all_lmes.append(clipped)
     
      #  ds.tos.isel(time=0).plot(ax=ax, cmap='coolwarm',transform=ccrs.PlateCarree())
        
      #  plt.show()

   ds_lme=xr.merge(all_lmes)
   ds_lme.tos.isel(time=0).plot(ax=ax, transform=ccrs.PlateCarree(), cmap='coolwarm')

   plt.show()