Bug: format_lon fails on latest xarray due to read-only coord values #65

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ValueError                                Traceback (most recent call last)
Cell In[5], line 1
----> 1 data_u.regrid.linear(target_dataset)

File ~\anaconda3\envs\my\Lib\site-packages\xarray_regrid\regrid.py:44, in Regridder.linear(self, ds_target_grid, time_dim)
     33 """Regrid to the coords of the target dataset with linear interpolation.
     34 
     35 Args:
   (...)     41     Data regridded to the target dataset coordinates.
     42 """
     43 ds_target_grid = validate_input(self._obj, ds_target_grid, time_dim)
---> 44 ds_formatted = format_for_regrid(self._obj, ds_target_grid)
     45 return interp.interp_regrid(ds_formatted, ds_target_grid, "linear")

File ~\anaconda3\envs\my\Lib\site-packages\xarray_regrid\utils.py:276, in format_for_regrid(obj, target, stats)
    274 result = ensure_monotonic(result, coord)
    275 target = ensure_monotonic(target, coord)
--> 276 result = coord_handlers[coord_type]["func"](result, target, formatted_coords)
    278 # Coerce back to a single chunk if that's what was passed
    279 if isinstance(obj, xr.DataArray) and len(obj.chunksizes.get(coord, ())) == 1:

File ~\anaconda3\envs\my\Lib\site-packages\xarray_regrid\utils.py:387, in format_lon(obj, target, formatted_coords)
    386 if left_pad:
--> 387     lon_vals[:left_pad] = source_lon.values[-left_pad:] - 360
    388 if right_pad:
    389     lon_vals[-right_pad:] = source_lon.values[:right_pad] + 360

ValueError: assignment destination is read-only

def format_lon(
    obj: xr.DataArray | xr.Dataset, target: xr.Dataset, formatted_coords: dict[str, str]
) -> xr.DataArray | xr.Dataset:
    """Format the longitude coordinate by shifting the source grid to line up with
    the target anywhere in the range of -360 to 360, and then add a single wraparound
    padding column if the domain is inferred to be global and the east or west edges
    of the target lie outside the source grid centers.

    For example, with a source grid ranging from 0.5 to 359.5 and a target grid ranging
    from -180 to 180, the source grid would be shifted to -179.5 to 179.5 and then
    padded on both the left and right with wraparound values at -180.5 and 180.5 to
    provide full coverage for the target edge cells at -180 and 180.
    """
    lon_coord = formatted_coords["lon"]

    # Find a wrap point outside of the left and right bounds of the target
    # This ensures we have coverage on the target and handles global > regional
    source_vals = obj.coords[lon_coord].values
    target_vals = target.coords[lon_coord].values
    wrap_point = (target_vals[-1] + target_vals[0] + 360) / 2
    source_vals = np.where(
        source_vals < wrap_point - 360, source_vals + 360, source_vals
    )
    source_vals = np.where(source_vals > wrap_point, source_vals - 360, source_vals)
    obj = update_coord(obj, lon_coord, source_vals)

    obj = ensure_monotonic(obj, lon_coord)

    # Only pad if domain is global in lon
    source_lon = obj.coords[lon_coord]
    target_lon = target.coords[lon_coord]
    dx_s = source_lon.diff(lon_coord).max().values.item()
    dx_t = target_lon.diff(lon_coord).max().values.item()
    is_global_lon = source_lon.max().values - source_lon.min().values >= 360 - dx_s

    if is_global_lon:
        left_pad = (source_lon.values[0] - target_lon.values[0] + dx_t / 2) / dx_s
        right_pad = (target_lon.values[-1] - source_lon.values[-1] + dx_t / 2) / dx_s
        left_pad = int(np.ceil(np.max([left_pad, 0])))
        right_pad = int(np.ceil(np.max([right_pad, 0])))
        obj = obj.pad({lon_coord: (left_pad, right_pad)}, mode="wrap", keep_attrs=True)
        lon_vals = obj.coords[lon_coord].values.copy()    # <- add here!!!
        if left_pad:
            lon_vals[:left_pad] = source_lon.values[-left_pad:] - 360
        if right_pad:
            lon_vals[-right_pad:] = source_lon.values[:right_pad] + 360
        obj = update_coord(obj, lon_coord, lon_vals)
        obj = ensure_monotonic(obj, lon_coord)

    return obj