Move to xarray-regrid for all regridding.

demo/cams_co2_dataset_demo.ipynb

@@ -142,7 +142,6 @@
     "    spatial_bounds=bbox_demo,\n",
     "    variable_names=[\"co2_concentration\"],\n",
     "    resolution=1.0,\n",
-    "    regrid_method=\"flox\",\n",
     ")"
    ]
   },

demo/era5-land_dataset_demo.ipynb

@@ -149,7 +149,6 @@
     "    spatial_bounds=bbox_demo,\n",
     "    variable_names=[\"air_temperature\", \"dewpoint_temperature\"],\n",
     "    resolution=1.0,\n",
-    "    regrid_method=\"flox\",\n",
     ")"
    ]
   },

demo/era5_dataset_demo.ipynb

@@ -143,7 +143,6 @@
     "    spatial_bounds=bbox_demo,\n",
     "    variable_names=[\"eastward_component_of_wind\"],\n",
     "    resolution=1.0,\n",
-    "    regrid_method=\"flox\",\n",
     ")"
    ]
   },

demo/eth_dataset_demo.ipynb

@@ -126,7 +126,6 @@
     "    spatial_bounds=bbox_demo,\n",
     "    variable_names=[\"height_of_vegetation\"],\n",
     "    resolution=0.05,\n",
-    "    regrid_method=\"flox\",\n",
     ")"
    ]
   },

demo/land_cover_dataset_demo.ipynb

@@ -145,7 +145,6 @@
     "    spatial_bounds=bbox_demo,\n",
     "    variable_names=[\"land_cover\"],\n",
     "    resolution=1.0,\n",
-    "    regrid_method=\"most_common\",\n",
     ")"
    ]
   },
@@ -1115,7 +1114,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.0"
+   "version": "3.10.12"
   },
   "orig_nbformat": 4
  },

demo/prism_dem_demo.ipynb

@@ -139,7 +139,6 @@
     "    spatial_bounds=bbox_demo,\n",
     "    variable_names=[\"elevation\"],\n",
     "    resolution=0.01,\n",
-    "    regrid_method=\"flox\",\n",
     ")"
    ]
   },

example_recipe.yml

@@ -15,7 +15,6 @@ convert:
   standard: ALMA-PLUMBER2
   frequency: 1H  # outputs at 1 hour frequency. Pandas-like freq-keyword.
   resolution: 0.01  # output resolution in degrees.
-  conversion-method: "flox"  # Either flox or xesmf. xesmf requires conda + linux.
 
   additional_variables:  # Possible future addition
     saturation_vapor_pressure:

pyproject.toml

@@ -62,9 +62,8 @@ dependencies = [
   "pint",
   "cf_xarray",  # required to auto-pint CF compliant datasets.
   "pint-xarray",
-  "flox",  # For better groupby methods.
   "cdsapi",
-  "xarray-regrid", # for land cover data regridding
+  "xarray-regrid", # for regridding
 ]
 dynamic = ["version"]
 
@@ -120,16 +119,6 @@ features = ["docs"]
 build = ["mkdocs build"]
 serve = ["mkdocs serve"]
 
-# [tool.hatch.envs.conda]
-# type = "conda"
-# python = "3.10"
-# command = "micromamba"
-# environment-file = "environment.yml"
-# extra-dependencies = ["pytest", "pytest-cov"]
-
-# [tool.hatch.envs.conda.scripts]
-# test = ["pytest ./tests/",]
-
 [tool.pytest.ini_options]
 testpaths = ["tests"]
 

src/zampy/__init__.py

@@ -1,11 +1,10 @@
 """zampy."""
 from zampy import datasets
-from zampy import utils
 
 
 __author__ = "Bart Schilperoort"
 __email__ = "[email protected]"
 __version__ = "0.1.0"
 
 
-__all__ = ["datasets", "utils"]
+__all__ = ["datasets"]

src/zampy/datasets/dataset_protocol.py

@@ -130,7 +130,6 @@ def load(
         time_bounds: TimeBounds,
         spatial_bounds: SpatialBounds,
         resolution: float,
-        regrid_method: str,
         variable_names: list[str],
     ) -> xr.Dataset:
         """Get the dataset as an xarray Dataset.
@@ -142,9 +141,6 @@ def load(
                 loaded.
             resolution: The desired resolution of the loaded data. The ingested data
                 will be regridded to match this resolution.
-            regrid_method: Which routines to use to resample. Either "flox" (default) or
-                "esmf". Of these two, esmf is the more robust and accurate regridding
-                method, however it can be difficult to install.
 
             variable_names: Which variables should be loaded.
 

src/zampy/datasets/ecmwf_dataset.py

@@ -2,6 +2,7 @@
 
 from pathlib import Path
 import xarray as xr
+import xarray_regrid  # noqa: F401
 from zampy.datasets import cds_utils
 from zampy.datasets import converter
 from zampy.datasets import validation
@@ -10,7 +11,7 @@
 from zampy.datasets.dataset_protocol import Variable
 from zampy.datasets.dataset_protocol import copy_properties_file
 from zampy.datasets.dataset_protocol import write_properties_file
-from zampy.utils import regrid
+from zampy.datasets.utils import make_grid
 
 
 ## Ignore missing class/method docstrings: they are implemented in the Dataset class.
@@ -111,7 +112,6 @@ def load(
         time_bounds: TimeBounds,
         spatial_bounds: SpatialBounds,
         resolution: float,
-        regrid_method: str,
         variable_names: list[str],
     ) -> xr.Dataset:
         files: list[Path] = []
@@ -121,7 +121,11 @@ def load(
 
         ds = xr.open_mfdataset(files, chunks={"latitude": 200, "longitude": 200})
         ds = ds.sel(time=slice(time_bounds.start, time_bounds.end))
-        ds = regrid.regrid_data(ds, spatial_bounds, resolution, regrid_method)
+
+        grid = xarray_regrid.create_regridding_dataset(
+            make_grid(spatial_bounds, resolution)
+        )
+        ds = ds.regrid.linear(grid)
 
         return ds
 

src/zampy/datasets/eth_canopy_height.py

@@ -3,6 +3,7 @@
 from pathlib import Path
 import numpy as np
 import xarray as xr
+import xarray_regrid
 from zampy.datasets import converter
 from zampy.datasets import utils
 from zampy.datasets import validation
@@ -13,7 +14,6 @@
 from zampy.datasets.dataset_protocol import write_properties_file
 from zampy.reference.variables import VARIABLE_REFERENCE_LOOKUP
 from zampy.reference.variables import unit_registry
-from zampy.utils import regrid
 
 
 VALID_NAME_FILE = (
@@ -126,7 +126,6 @@ def load(
         time_bounds: TimeBounds,
         spatial_bounds: SpatialBounds,
         resolution: float,
-        regrid_method: str,
         variable_names: list[str],
     ) -> xr.Dataset:
         files: list[Path] = []
@@ -137,7 +136,11 @@ def load(
 
         ds = xr.open_mfdataset(files, chunks={"latitude": 2000, "longitude": 2000})
         ds = ds.sel(time=slice(time_bounds.start, time_bounds.end))
-        ds = regrid.regrid_data(ds, spatial_bounds, resolution, regrid_method)
+
+        grid = xarray_regrid.create_regridding_dataset(
+            utils.make_grid(spatial_bounds, resolution)
+        )
+        ds = ds.regrid.linear(grid)
         return ds
 
     def convert(

src/zampy/datasets/fapar_lai.py

@@ -13,6 +13,7 @@
 from tqdm import tqdm
 from zampy.datasets import cds_utils
 from zampy.datasets import converter
+from zampy.datasets import utils
 from zampy.datasets import validation
 from zampy.datasets.dataset_protocol import SpatialBounds
 from zampy.datasets.dataset_protocol import TimeBounds
@@ -141,16 +142,17 @@ def load(
         time_bounds: TimeBounds,
         spatial_bounds: SpatialBounds,
         resolution: float,
-        regrid_method: str,  # should be deprecated.
         variable_names: list[str],
     ) -> xr.Dataset:
         files = list((ingest_dir / self.name).glob("*.nc"))
 
         ds = xr.open_mfdataset(files, parallel=True)
         ds = ds.sel(time=slice(time_bounds.start, time_bounds.end))
 
-        target_dataset = create_regridding_ds(spatial_bounds, resolution)
-        ds = ds.regrid.linear(target_dataset)
+        grid = xarray_regrid.create_regridding_dataset(
+            utils.make_grid(spatial_bounds, resolution)
+        )
+        ds = ds.regrid.linear(grid)
 
         return ds
 
@@ -175,29 +177,6 @@ def convert(  # Will be removed, see issue #43.
         return True
 
 
-def create_regridding_ds(
-    spatial_bounds: SpatialBounds, resolution: float
-) -> xr.Dataset:
-    """Create dataset to use with xarray-regrid regridding.
-
-    Args:
-        spatial_bounds: Spatial bounds of the new dataset.
-        resolution: Latitude and longitude resolution of the new dataset.
-
-    Returns:
-        The dataset ready to be used in regridding.
-    """
-    new_grid = xarray_regrid.Grid(
-        north=spatial_bounds.north,
-        east=spatial_bounds.east,
-        south=spatial_bounds.south,
-        west=spatial_bounds.west,
-        resolution_lat=resolution,
-        resolution_lon=resolution,
-    )
-    return xarray_regrid.create_regridding_dataset(new_grid)
-
-
 def get_year_month_pairs(time_bounds: TimeBounds) -> list[tuple[int, int]]:
     """Get the year and month pairs covering the input time bounds."""
     start = pd.to_datetime(time_bounds.start)

src/zampy/datasets/land_cover.py

@@ -8,6 +8,7 @@
 import xarray_regrid
 from zampy.datasets import cds_utils
 from zampy.datasets import converter
+from zampy.datasets import utils
 from zampy.datasets import validation
 from zampy.datasets.dataset_protocol import SpatialBounds
 from zampy.datasets.dataset_protocol import TimeBounds
@@ -121,7 +122,6 @@ def load(
         time_bounds: TimeBounds,
         spatial_bounds: SpatialBounds,
         resolution: float,
-        regrid_method: str,  # Unused in land-cover dataset
         variable_names: list[str],
     ) -> xr.Dataset:
         files: list[Path] = []
@@ -137,19 +137,13 @@ def load(
 
         ds = xr.open_mfdataset(files, chunks={"latitude": 200, "longitude": 200})
         ds = ds.sel(time=slice(time_bounds.start, time_bounds.end))
-        new_grid = xarray_regrid.Grid(
-            north=spatial_bounds.north,
-            east=spatial_bounds.east,
-            south=spatial_bounds.south,
-            west=spatial_bounds.west,
-            resolution_lat=resolution,
-            resolution_lon=resolution,
-        )
-        target_dataset = xarray_regrid.create_regridding_dataset(new_grid)
 
-        ds_regrid = ds.regrid.most_common(target_dataset, time_dim="time", max_mem=1e9)
+        grid = xarray_regrid.create_regridding_dataset(
+            utils.make_grid(spatial_bounds, resolution)
+        )
+        ds = ds.regrid.most_common(grid, time_dim="time", max_mem=1e9)
 
-        return ds_regrid
+        return ds
 
     def convert(
         self,

src/zampy/datasets/prism_dem.py

@@ -5,6 +5,7 @@
 from typing import Literal
 import numpy as np
 import xarray as xr
+import xarray_regrid
 from rasterio.io import MemoryFile
 from zampy.datasets import converter
 from zampy.datasets import utils
@@ -16,7 +17,6 @@
 from zampy.datasets.dataset_protocol import write_properties_file
 from zampy.reference.variables import VARIABLE_REFERENCE_LOOKUP
 from zampy.reference.variables import unit_registry
-from zampy.utils import regrid
 
 
 VALID_NAME_FILES = [
@@ -127,7 +127,6 @@ def load(
         time_bounds: TimeBounds,  # Unused in PrismDEM
         spatial_bounds: SpatialBounds,
         resolution: float,
-        regrid_method: str,
         variable_names: list[str],
     ) -> xr.Dataset:
         for var in variable_names:
@@ -145,7 +144,11 @@ def preproc(ds: xr.Dataset) -> xr.Dataset:
             return ds.isel(latitude=slice(None, -1), longitude=slice(None, -1))
 
         ds = xr.open_mfdataset(files, preprocess=preproc)
-        ds = regrid.regrid_data(ds, spatial_bounds, resolution, regrid_method)
+
+        grid = xarray_regrid.create_regridding_dataset(
+            utils.make_grid(spatial_bounds, resolution)
+        )
+        ds = ds.regrid.linear(grid)
 
         return ds