Merge pull request #29 from ecmwf/feature/unstructured-grid

Feature/unstructured grid

CHANGELOG.md

@@ -14,6 +14,7 @@ Keep it human-readable, your future self will thank you!
 
 - Fix: Enable inference when no constant forcings are used
 - Add anemoi-transform link to documentation
+- Add support for unstructured grids
 
 ### Changed
 

pyproject.toml

@@ -41,6 +41,7 @@ classifiers = [
 
 dynamic = [ "version" ]
 dependencies = [
+  "anemoi-transform>=0.0.4",
   "anemoi-utils>=0.3",
   "aniso8601",
   "anytree",

src/anemoi/inference/checkpoint/metadata/version_0_2_0.py

@@ -114,23 +114,23 @@ def __init__(self, metadata):
 
     @property
     def grid(self):
-        return self.request["grid"]
+        return self.request.get("grid")
 
     @property
     def area(self):
-        return self.request["area"]
+        return self.request.get("area")
 
     @property
     def param_sfc(self):
-        return self.request["param_level"].get("sfc", [])
+        return self.request.get("param_level", {}).get("sfc", [])
 
     @property
     def param_level_pl_pairs(self):
-        return self.request["param_level"].get("pl", [])
+        return self.request.get("param_level", {}).get("pl", [])
 
     @property
     def param_level_ml_pairs(self):
-        return self.request["param_level"].get("ml", [])
+        return self.request.get("param_level", {}).get("ml", [])
 
     @property
     def param_step_sfc_pairs(self):

src/anemoi/inference/runner.py

@@ -111,6 +111,7 @@ def run(
         output_callback=ignore,
         autocast=None,
         progress_callback=ignore,
+        grid_field_list=None,
     ) -> None:
         """_summary_
 
@@ -130,6 +131,8 @@ def run(
             _description_, by default None
         progress_callback : _type_, optional
             _description_, by default ignore
+        grid_field_list: _type_, optional
+            _description_, by default None
 
         Raises
         ------
@@ -334,7 +337,7 @@ def run(
 
 
         constants = forcing_and_constants(
-            source=input_fields[:1],
+            source=grid_field_list if grid_field_list is not None else input_fields[:1],
             param=self.checkpoint.computed_constants,
             date=start_datetime,
         )
@@ -406,7 +409,13 @@ def get_most_recent_datetime(input_fields):
 
         most_recent_datetime = get_most_recent_datetime(input_fields)
         reference_fields = [f for f in input_fields if f.datetime()["valid_time"] == most_recent_datetime]
-        prognostic_template = reference_fields[self.checkpoint.variable_to_index["lsm"]]
+
+        if "lsm" in self.checkpoint.variable_to_index:
+            prognostic_template = reference_fields[self.checkpoint.variable_to_index["lsm"]]
+        else:
+            first = list(self.checkpoint.variable_to_index.keys())
+            LOGGER.warning("No LSM found to use as a GRIB template, using %s", first[0])
+            prognostic_template = reference_fields[0]
 
         accumulated_output = np.zeros(
             shape=(len(diagnostic_output_mask), number_of_grid_points),