diff --git a/packages/ref-core/pyproject.toml b/packages/ref-core/pyproject.toml index d9b2592..464cf1e 100644 --- a/packages/ref-core/pyproject.toml +++ b/packages/ref-core/pyproject.toml @@ -21,7 +21,7 @@ classifiers = [ "Topic :: Scientific/Engineering", ] dependencies = [ - "pydantic>=2.0" + "attrs" ] [tool.uv] diff --git a/packages/ref-core/src/ref_core/metrics.py b/packages/ref-core/src/ref_core/metrics.py index 8270d3d..0c6c51d 100644 --- a/packages/ref-core/src/ref_core/metrics.py +++ b/packages/ref-core/src/ref_core/metrics.py @@ -1,10 +1,12 @@ +import json import pathlib from typing import Protocol, runtime_checkable -from pydantic import BaseModel +from attrs import frozen -class Configuration(BaseModel): +@frozen +class Configuration: """ Configuration that describes the input data sources """ @@ -17,7 +19,8 @@ class Configuration(BaseModel): # TODO: Add more configuration options here -class MetricResult(BaseModel): +@frozen +class MetricResult: """ The result of running a metric. @@ -27,7 +30,7 @@ class MetricResult(BaseModel): # Do we want to load a serialised version of the output bundle here or just a file path? - output_bundle: pathlib.Path + output_bundle: pathlib.Path | None """ Path to the output bundle file. @@ -40,8 +43,36 @@ class MetricResult(BaseModel): """ # Log info is in the output bundle file already, but is definitely useful + @staticmethod + def build(configuration: Configuration, cmec_output_bundle: dict) -> "MetricResult": + """ + Build a MetricResult from a CMEC output bundle. + + Parameters + ---------- + configuration + The configuration used to run the metric. + cmec_output_bundle + An output bundle in the CMEC format. + + TODO: This needs a better type hint + + Returns + ------- + : + A prepared MetricResult object. + The output bundle will be written to the output directory. + """ + with open(configuration.output_directory / "output.json", "w") as file_handle: + json.dump(cmec_output_bundle, file_handle) + return MetricResult( + output_bundle=configuration.output_directory / "output.json", + successful=True, + ) + -class TriggerInfo(BaseModel): +@frozen +class TriggerInfo: """ The reason why the metric was run. """ diff --git a/packages/ref-metrics-example/pyproject.toml b/packages/ref-metrics-example/pyproject.toml index d6310a4..a76af08 100644 --- a/packages/ref-metrics-example/pyproject.toml +++ b/packages/ref-metrics-example/pyproject.toml @@ -21,7 +21,10 @@ classifiers = [ "Topic :: Scientific/Engineering", ] dependencies = [ - "ref-core" + "ref-core", + "xarray >= 2022", + "netcdf4", + "dask>=2024.10.0", ] [tool.uv] diff --git a/packages/ref-metrics-example/src/ref_metrics_example/example.py b/packages/ref-metrics-example/src/ref_metrics_example/example.py index 6f10f44..904e699 100644 --- a/packages/ref-metrics-example/src/ref_metrics_example/example.py +++ b/packages/ref-metrics-example/src/ref_metrics_example/example.py @@ -1,8 +1,77 @@ -import json +from pathlib import Path +import xarray as xr from ref_core.metrics import Configuration, MetricResult, TriggerInfo +def calculate_annual_mean_timeseries(dataset: Path) -> xr.Dataset: + """ + Calculate the annual mean timeseries for a dataset. + + While this function is implemented here, + in most cases the metric calculation will be in the underlying benchmarking package. + How the metric is calculated is up to the provider. + + Parameters + ---------- + dataset + A path to a CMIP6 dataset. + + This dataset may consist of multiple data files. + + Returns + ------- + : + The annual mean timeseries of the dataset + """ + input_files = dataset.glob("*.nc") + + dataset = xr.open_mfdataset(list(input_files), combine="by_coords", chunks=None) + + annual_mean = dataset.resample(time="YS").mean() + return annual_mean.mean(dim=["lat", "lon"], keep_attrs=True) + + +def format_cmec_output_bundle(dataset: xr.Dataset) -> dict: + """ + Create a simple CMEC output bundle for the dataset. + + Parameters + ---------- + dataset + Processed dataset + + Returns + ------- + A CMEC output bundle ready to be written to disk + """ + cmec_output = { + "DIMENSIONS": { + "dimensions": { + "source_id": {dataset.attrs["source_id"]: {}}, + "region": {"global": {}}, + "variable": {"tas": {}}, + }, + "json_structure": [ + "model", + "region", + "statistic", + ], + }, + # Is the schema tracked? + "SCHEMA": { + "name": "CMEC-REF", + "package": "example", + "version": "v1", + }, + "RESULTS": { + dataset.attrs["source_id"]: {"global": {"tas": ""}}, + }, + } + + return cmec_output + + class ExampleMetric: """ Example metric that does nothing but count the number of times it has been run. @@ -10,28 +79,32 @@ class ExampleMetric: name = "example" - def __init__(self) -> None: - self._count = 0 - def run(self, configuration: Configuration, trigger: TriggerInfo | None) -> MetricResult: """ Run a metric Parameters ---------- + trigger + Trigger for what caused the metric to be executed. + configuration + Configuration object Returns ------- : The result of running the metric. """ - self._count += 1 + if trigger is None: + # TODO: This should probably raise an exception + return MetricResult( + output_bundle=configuration.output_directory / "output.json", + successful=False, + ) - with open(configuration.output_directory / "output.json", "w") as fh: - json.dump(({"count": self._count}), fh) + annual_mean_global_mean_timeseries = calculate_annual_mean_timeseries(trigger.dataset) - return MetricResult( - output_bundle=configuration.output_directory / "output.json", - successful=True, + return MetricResult.build( + configuration, format_cmec_output_bundle(annual_mean_global_mean_timeseries) ) diff --git a/packages/ref-metrics-example/tests/unit/test_metrics.py b/packages/ref-metrics-example/tests/unit/test_metrics.py index 9163114..3b65543 100644 --- a/packages/ref-metrics-example/tests/unit/test_metrics.py +++ b/packages/ref-metrics-example/tests/unit/test_metrics.py @@ -1,15 +1,56 @@ -from ref_core.metrics import Configuration -from ref_metrics_example.example import ExampleMetric +from pathlib import Path +import pytest +from ref_core.metrics import Configuration, TriggerInfo +from ref_metrics_example.example import ExampleMetric, calculate_annual_mean_timeseries -def test_example_metric(tmp_path): + +@pytest.fixture +def test_dataset(esgf_data_dir) -> Path: + return ( + esgf_data_dir + / "CMIP6" + / "ScenarioMIP" + / "CSIRO" + / "ACCESS-ESM1-5" + / "ssp245" + / "r1i1p1f1" + / "Amon" + / "tas" + / "gn" + / "v20191115" + ) + + +def test_annual_mean(esgf_data_dir): + input_files = list( + ( + esgf_data_dir + / "CMIP6" + / "ScenarioMIP" + / "CSIRO" + / "ACCESS-ESM1-5" + / "ssp245" + / "r1i1p1f1" + / "Amon" + / "tas" + / "gn" + / "v20191115" + ).glob("*.nc") + ) + annual_mean = calculate_annual_mean_timeseries(input_files) + + assert annual_mean.time.size == 86 + + +def test_example_metric(tmp_path, test_dataset): metric = ExampleMetric() configuration = Configuration( output_directory=tmp_path, ) - result = metric.run(configuration, trigger=None) + result = metric.run(configuration, trigger=TriggerInfo(dataset=test_dataset)) assert result.successful assert result.output_bundle.exists() diff --git a/scripts/fetch_test_data.py b/scripts/fetch_test_data.py index 84d1d90..96e6737 100644 --- a/scripts/fetch_test_data.py +++ b/scripts/fetch_test_data.py @@ -67,7 +67,7 @@ def queue_esgf_download( # noqa: PLR0913 ] ) - res = subprocess.run( + subprocess.run( [ "esgpull", "update", @@ -78,7 +78,6 @@ def queue_esgf_download( # noqa: PLR0913 input=b"y", check=False, ) - res.check_returncode() return search_tag diff --git a/uv.lock b/uv.lock index 545195d..b9f7a23 100644 --- a/uv.lock +++ b/uv.lock @@ -1,7 +1,9 @@ version = 1 requires-python = ">=3.10" resolution-markers = [ - "python_full_version < '3.13'", + "python_full_version < '3.11'", + "python_full_version == '3.11.*'", + "python_full_version == '3.12.*'", "python_full_version >= '3.13'", ] @@ -56,15 +58,6 @@ wheels = [ { url = 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