Add aggregate operator with corresponding yaml file and changes in re…

…cipes.

src/CSET/operators/__init__.py

@@ -15,7 +15,7 @@
 """This subpackage contains all of CSET's operators."""
 
 # Import operators here so they are exported for use by recipes.
-from CSET.operators import constraints, read, write, filters, plot, misc
+from CSET.operators import constraints, read, write, filters, aggregate, plot, misc
 
 
 from pathlib import Path

src/CSET/operators/aggregate.py

@@ -0,0 +1,109 @@
+# Copyright 2022 Met Office and contributors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Operators to perform various kind of aggregation on either 1 or 2 dimensions.
+"""
+
+import iris
+import iris.cube
+import iris.analysis
+
+
+def aggregate_1dim(
+    cube: iris.cube.Cube, coordinate: str, method: str, **kwargs
+) -> iris.cube.Cube:
+    """
+    Aggregates similar (stash) fields in a cube into a cube aggregating around the specified coordinate and method.
+    This could be a (weighted) mean or an accumulation.
+
+    Arguments
+    ---------
+    cube: iris.cube.Cube
+         Cube to aggregate and iterate over one dimension
+    coordinate: str
+         Coordinate to aggregate over i.e.
+         'time', 'longitude', 'latitude','model_level_number'
+    method: str
+         Type of aggregation i.e. method: 'MEAN', 'MAX', 'MIN', 'MEDIAN', 'PERCENTILE'
+         getattr creates iris.analysis.MEAN, etc
+         For PERCENTILE YAML file requires i.e.
+         method: 'PERCENTILE'
+         additional_percent: 90
+
+    Returns
+    -------
+    cube: iris.cube.Cube
+         Single variable but several methods of aggregation
+
+
+    Raises
+    ------
+    ValueError
+    If the constraint doesn't produce a single cube containing a field.
+    """
+
+    if method != "PERCENTILE":
+        aggregated_cube = cube.collapsed(coordinate, getattr(iris.analysis, method))
+    if method == "PERCENTILE":
+        for num in kwargs.values():
+            aggregated_cube = cube.collapsed(
+                coordinate, getattr(iris.analysis, method), percent=num
+            )
+
+    return aggregated_cube
+
+
+def aggregate_cube_2dim(
+    cube: iris.cube.Cube, coordinate1: str, coordinate2: str, method: str, **kargs
+) -> iris.cube.Cube:
+    """
+    Aggregates similar (stash) fields in a cube into a 2D field in a cube based on 2 coordinates and method to aggregated. This could include time and vertical coordinate for instance.
+    This could be a (weighted) mean or an accumulation.
+
+    Arguments
+    ---------
+    cube: iris.cube.Cube
+         Cube to aggregate and iterate over one dimension
+    coordinate: str
+         Coordinate to aggregate over
+    method: Type of aggregation i.e. method: 'MEAN', 'MAX', 'MIN', 'MEDIAN', 'PERCENTILE'
+         getattr creates iris.analysis.MEAN, etc
+         For PERCENTILE YAML file requires i.e.
+         method: 'PERCENTILE'
+         additional_percent: 90
+
+
+    Returns
+    -------
+    cube: iris.cube.Cube
+         Single variable but several methods of aggregation such as mean, median, max, min, percentile
+
+
+    Raises
+    ------
+    ValueError
+    If the constraint doesn't produce a single cube containing a field.
+    """
+
+    # aggregate cube over single dimension
+    # dimensions: 2 of i.e. 'time', 'longitude', 'latitude'
+    # method: iris.analysis.MEAN, iris.analysis.MAX, iris.analysis.MIN
+    # ensure that time is passed in as 'time'
+    # aggregated_cube = cube.collapsed("time", iris.analysis.MEAN)
+    aggregated_cube = cube.collapsed(
+        [coordinate2, coordinate2], getattr(iris.analysis, method)
+    )
+
+    return aggregated_cube

tests/operators/test_aggregate.py

@@ -0,0 +1,32 @@
+# Copyright 2022 Met Office and contributors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import iris
+import iris.cube
+import iris.analysis
+from CSET.operators import read, filters, constraints
+
+
+def test_aggregate_1dim():
+    """Reduces dimension of cube."""
+    cubes = read.read_cubes("tests/test_data/air_temp.nc")
+    constraint = constraints.combine_constraints(
+        constraints.generate_stash_constraint("m01s03i236"),
+        a=constraints.generate_cell_methods_constraint([]),
+    )
+    cube = filters.filter_cubes(cubes, constraint)
+    aggregated_cube = cube.collapsed("time", iris.analysis.MEAN)
+    assert aggregated_cube.cell_methods == ()
+    expected_cube = "<iris 'Cube' of air_temperature / (K) (time: 1; grid_latitude: 17; grid_longitude: 13)>"
+    assert repr(aggregated_cube) == expected_cube

tests/test_data/plot_instant_air_temp_aggregate.yaml

@@ -0,0 +1,36 @@
+name: Extract Instant Air Temperature
+description: |
+  Extracts out the instantaneous 1.5m air temperature from a file and writes it
+  to a new one.
+
+steps:
+  - operator: read.read_cubes
+    constraint:
+      operator: constraints.generate_stash_constraint
+      stash: m01s03i236
+
+  - operator: filters.filter_cubes
+    constraint:
+      operator: constraints.combine_constraints
+      stash_constraint:
+        operator: constraints.generate_stash_constraint
+        stash: m01s03i236
+      cell_methods_constraint:
+        operator: constraints.generate_cell_methods_constraint
+        cell_methods: []
+#      time_constraint:
+#        operator: constraints.generate_time_constraint
+#        time_start: 2022-09-21T03:00:00
+#        time_end: 2022-09-21T03:30:00
+
+  - operator: aggregate.aggregate_1dim
+    coordinate: 'time'
+    method: 'MEAN'
+    additional_percent: 90
+
+  - operator: write.write_cube_to_nc
+    # This is a magic value that becomes the runtime output file path.
+    file_path: CSET_OUTPUT_PATH
+    plot_data_as_well:
+      operator: plot.spatial_contour_plot
+      file_path: CSET_OUTPUT_PATH