CDS input

docs/configs/inputs.rst

@@ -95,3 +95,39 @@ You can change that to use ERA5 reanalysis data (``class=ea``).
 
 The ``mars`` input also accepts the ``namer`` parameter of the GRIB
 input.
+
+*****
+ cds
+*****
+
+You can also specify the input as ``cds`` to read the data from the
+`Climate Data Store <https://cds.climate.copernicus.eu/>`_. This
+requires the `cdsapi` package to be installed, and the user to have a
+CDS account.
+
+.. literalinclude:: inputs_8.yaml
+   :language: yaml
+
+As the CDS contains a plethora of `datasets
+<https://cds.climate.copernicus.eu/datasets>`_, you can specify the
+dataset you want to use with the key `dataset`.
+
+This can be a str in which case the dataset is used for all requests, or
+a dict of any number of levels which will be descended based on the
+key/values for each request.
+
+You can use `*` to represent any not given value for a key, i.e. set a
+dataset for `param: 2t`. and `param: *` to represent any other param.
+
+.. literalinclude:: inputs_9.yaml
+   :language: yaml
+
+In the above example, the dataset `reanalysis-era5-pressure-levels` is
+used for all with `levtype: pl` and `reanalysis-era5-single-levels` used
+for all with `levtype: sfc`.
+
+Additionally, any kwarg can be passed to be added to all requests, i.e.
+for ERA5 data, `product_type: 'reanalysis'` is needed.
+
+.. literalinclude:: inputs_10.yaml
+   :language: yaml

docs/configs/inputs_10.yaml

@@ -0,0 +1,7 @@
+input:
+  cds:
+    dataset:
+      levtype:
+        pl: reanalysis-era5-pressure-levels
+        sfc: reanalysis-era5-single-levels
+    product_type: 'reanalysis'

docs/configs/inputs_8.yaml

@@ -0,0 +1,3 @@
+input:
+  cds:
+    dataset: ???

docs/configs/inputs_9.yaml

@@ -0,0 +1,24 @@
+input:
+  cds:
+    # Dataset examples
+    ## As a string
+    dataset:
+      'reanalysis-era5-pressure-levels'
+
+    ## As a simple dictionary
+    dataset:
+      levtype:
+        pl: reanalysis-era5-pressure-levels
+        sfc: reanalysis-era5-single-levels
+
+    ## As a complex dictionary
+    dataset:
+      stream:
+        oper:
+          levtype:
+            pl: reanalysis-era5-pressure-levels
+            sfc: reanalysis-era5-single-levels
+        an:
+          # ... Other datasets
+        '*': # Any other stream
+          # ... Other datasets

src/anemoi/inference/inputs/cds.py

@@ -0,0 +1,118 @@
+# (C) Copyright 2024 Anemoi contributors.
+#
+# This software is licensed under the terms of the Apache Licence Version 2.0
+# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# In applying this licence, ECMWF does not waive the privileges and immunities
+# granted to it by virtue of its status as an intergovernmental organisation
+# nor does it submit to any jurisdiction.
+
+
+import logging
+
+from earthkit.data.utils.dates import to_datetime
+
+from . import input_registry
+from .grib import GribInput
+from .mars import postproc
+
+LOG = logging.getLogger(__name__)
+
+
+def retrieve(requests, grid, area, dataset, **kwargs):
+    import earthkit.data as ekd
+
+    def _(r):
+        mars = r.copy()
+        for k, v in r.items():
+            if isinstance(v, (list, tuple)):
+                mars[k] = "/".join(str(x) for x in v)
+            else:
+                mars[k] = str(v)
+
+        return ",".join(f"{k}={v}" for k, v in mars.items())
+
+    pproc = postproc(grid, area)
+
+    result = ekd.from_source("empty")
+    for r in requests:
+        if isinstance(dataset, str):
+            d = dataset
+        elif isinstance(dataset, dict):
+            # Get dataset from intersection of keys between request and dataset dict
+            search_dataset = dataset.copy()
+            while isinstance(search_dataset, dict):
+                keys = set(r.keys()).intersection(set(search_dataset.keys()))
+                if len(keys) == 0:
+                    raise KeyError(
+                        f"While searching for dataset, could not find any valid key in dictionary: {r.keys()}, {search_dataset}"
+                    )
+                key = list(keys)[0]
+                if r[key] not in search_dataset[key]:
+                    if "*" in search_dataset[key]:
+                        search_dataset = search_dataset[key]["*"]
+                        continue
+
+                    raise KeyError(
+                        f"Dataset dictionary does not contain key {r[key]!r} in {key!r}: {dict(search_dataset[key])}."
+                    )
+                search_dataset = search_dataset[key][r[key]]
+
+            d = search_dataset
+
+        r.update(pproc)
+        r.update(kwargs)
+
+        LOG.debug("%s", _(r))
+        result += ekd.from_source("cds", d, r)
+
+    return result
+
+
+@input_registry.register("cds")
+class CDSInput(GribInput):
+    """Get input fields from CDS"""
+
+    def __init__(self, context, *, dataset, namer=None, **kwargs):
+        super().__init__(context, namer=namer)
+
+        self.variables = self.checkpoint.variables_from_input(include_forcings=False)
+        self.dataset = dataset
+        self.kwargs = kwargs
+
+    def create_input_state(self, *, date):
+        if date is None:
+            date = to_datetime(-1)
+            LOG.warning("CDSInput: `date` parameter not provided, using yesterday's date: %s", date)
+
+        date = to_datetime(date)
+
+        return self._create_input_state(
+            self.retrieve(
+                self.variables,
+                [date + h for h in self.checkpoint.lagged],
+            ),
+            variables=self.variables,
+            date=date,
+        )
+
+    def retrieve(self, variables, dates):
+
+        requests = self.checkpoint.mars_requests(
+            variables=variables,
+            dates=dates,
+            use_grib_paramid=self.context.use_grib_paramid,
+        )
+
+        if not requests:
+            raise ValueError("No requests for %s (%s)" % (variables, dates))
+
+        return retrieve(
+            requests, self.checkpoint.grid, self.checkpoint.area, dataset=self.dataset, expver="0001", **self.kwargs
+        )
+
+    def template(self, variable, date, **kwargs):
+        return self.retrieve([variable], [date])[0]
+
+    def load_forcings(self, variables, dates):
+        return self._load_forcings(self.retrieve(variables, dates), variables, dates)