Fix call to as_mars()

pyproject.toml

@@ -41,7 +41,7 @@ classifiers = [
 
 dependencies = [
     "cdsapi",
-    "earthkit-data>=0.10.1",
+    "earthkit-data>=0.10.3",
     "earthkit-meteo",
     "earthkit-regrid",
     "eccodes>=2.37",
@@ -72,6 +72,7 @@ file = "ai_models.inputs.file:FileInput"
 mars = "ai_models.inputs.mars:MarsInput"
 cds = "ai_models.inputs.cds:CdsInput"
 ecmwf-open-data = "ai_models.inputs.opendata:OpenDataInput"
+opendata = "ai_models.inputs.opendata:OpenDataInput"
 
 [project.entry-points."ai_models.output"]
 file = "ai_models.outputs:FileOutput"

src/ai_models/inputs/interpolate.py

@@ -8,6 +8,7 @@
 import logging
 
 import earthkit.regrid as ekr
+import tqdm
 from earthkit.data.indexing.fieldlist import FieldArray
 
 from .transform import NewDataField
@@ -22,7 +23,9 @@ def __init__(self, grid, source):
 
     def __call__(self, ds):
         result = []
-        for f in ds:
+        for f in tqdm.tqdm(ds, delay=0.5, desc="Interpolating", leave=False):
             data = ekr.interpolate(f.to_numpy(), dict(grid=self.source), dict(grid=self.grid))
             result.append(NewDataField(f, data))
+
+        LOG.info("Interpolated %d fields. Input shape %s, output shape %s.", len(result), ds[0].shape, result[0].shape)
         return FieldArray(result)

src/ai_models/inputs/opendata.py

@@ -35,10 +35,10 @@ class OpenDataInput(RequestBasedInput):
     WHERE = "OPENDATA"
 
     RESOLS = {
-        (0.25, 0.25): ("0p25", (0.25, 0.25), False),
-        "N320": ("0p25", (0.25, 0.25), True),
-        "O96": ("0p25", (0.25, 0.25), True),
-        # (0.1, 0.1): ("0p25", (0.25, 0.25), False),
+        (0.25, 0.25): ("0p25", (0.25, 0.25), False, False),
+        "N320": ("0p25", (0.25, 0.25), True, False),
+        "O96": ("0p25", (0.25, 0.25), True, False),
+        (0.1, 0.1): ("0p25", (0.25, 0.25), True, True),
     }
 
     def __init__(self, owner, **kwargs):
@@ -56,12 +56,15 @@ def _adjust(self, kwargs):
         if isinstance(grid, list):
             grid = tuple(grid)
 
-        kwargs["resol"], source, interp = self.RESOLS[grid]
+        kwargs["resol"], source, interp, oversampling = self.RESOLS[grid]
         r = dict(**kwargs)
         r.update(self.owner.retrieve)
 
         if interp:
-            logging.debug("Interpolating from %s to %s", source, grid)
+
+            logging.info("Interpolating input data from %s to %s.", source, grid)
+            if oversampling:
+                logging.warning("This will oversample the input data.")
             return Interpolate(grid, source)
         else:
             return lambda x: x

src/ai_models/inputs/transform.py

@@ -25,6 +25,7 @@ class NewDataField(WrappedField):
     def __init__(self, field, data):
         super().__init__(field)
         self._data = data
+        self.shape = data.shape
 
     def to_numpy(self, flatten=False, dtype=None, index=None):
         data = self._data

src/ai_models/model.py

@@ -127,7 +127,7 @@ def collect_archive_requests(self, written):
                 # does not return always return recently set keys
                 handle = handle.clone()
 
-            self.archiving[path].add(handle.as_mars())
+            self.archiving[path].add(handle.as_namespace("mars"))
 
     def finalise(self):
         self.output.flush()
@@ -536,6 +536,8 @@ def write_input_fields(
         accumulations_shape=None,
         ignore=None,
     ):
+        LOG.info("Starting date is %s", self.start_datetime)
+        LOG.info("Writing input fields")
         if ignore is None:
             ignore = []
 
@@ -553,7 +555,7 @@ def write_input_fields(
 
             if accumulations is not None:
                 if accumulations_template is None:
-                    accumulations_template = fields.sel(param="2t")[0]
+                    accumulations_template = fields.sel(param="msl")[0]
 
                 if accumulations_shape is None:
                     accumulations_shape = accumulations_template.shape

src/ai_models/outputs/__init__.py

@@ -67,6 +67,18 @@ def write(self, data, *args, check=False, **kwargs):
                     raise ValueError(f"NaN values found in field. args={args} kwargs={kwargs}")
                 if np.isinf(data).any():
                     raise ValueError(f"Infinite values found in field. args={args} kwargs={kwargs}")
+
+            options = {}
+            options.update(self.grib_keys)
+            options.update(kwargs)
+            LOG.error("Failed to write data to %s %s", args, options)
+            cmd = []
+            for k, v in options.items():
+                if isinstance(v, (int, str, float)):
+                    cmd.append("%s=%s" % (k, v))
+
+            LOG.error("grib_set -s%s", ",".join(cmd))
+
             raise
 
         if check: