From 0c71de56bb1d09757091f195de6ba46258e6a404 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 14:07:07 +0200 Subject: [PATCH 01/23] chore: run snakefmt --- pyproject.toml | 2 +- workflow/Snakefile | 4 - workflow/rules/data.smk | 2 +- workflow/rules/inference.smk | 251 +++++++++++++++----------------- workflow/rules/plot.smk | 6 +- workflow/rules/report.smk | 8 +- workflow/rules/summary.smk | 9 +- workflow/rules/verification.smk | 38 ++--- 8 files changed, 151 insertions(+), 169 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 3bbf08e9..53f4207c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -47,7 +47,7 @@ build-backend = "hatchling.build" [dependency-groups] dev = [ "pre-commit>=4.2.0", - "snakefmt>=0.11.0", + "snakefmt>=2.0", ] [tool.pytest.ini_options] diff --git a/workflow/Snakefile b/workflow/Snakefile index becffcb6..c29c3e7a 100644 --- a/workflow/Snakefile +++ b/workflow/Snakefile @@ -72,9 +72,7 @@ def _fmt_seconds(s: float) -> str: onstart: global _T0 _T0 = time.time() - when_iso = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - print() _hr() print(_c("🚀 EvalML workflow started", "1")) @@ -94,7 +92,6 @@ onstart: onsuccess: dt = _fmt_seconds(time.time() - (_T0 or time.time())) - print() _hr() print(_c("✅ Workflow finished successfully", "1")) @@ -106,7 +103,6 @@ onsuccess: onerror: dt = _fmt_seconds(time.time() - (_T0 or time.time())) - print() _hr() print(_c("❌ Workflow failed", "1")) diff --git a/workflow/rules/data.smk b/workflow/rules/data.smk index 217b6a68..652ea64d 100644 --- a/workflow/rules/data.smk +++ b/workflow/rules/data.smk @@ -11,9 +11,9 @@ else: rule data_download_obs_from_peakweather: - localrule: True output: root=directory(output_peakweather_root), + localrule: True run: from peakweather.dataset import PeakWeatherDataset diff --git a/workflow/rules/inference.smk b/workflow/rules/inference.smk index f59d6102..0296611b 100644 --- a/workflow/rules/inference.smk +++ b/workflow/rules/inference.smk @@ -8,79 +8,76 @@ from datetime import datetime rule inference_get_checkpoint: - localrule: True output: checkpoint=OUT_ROOT / "data/runs/{env_id}/inference-last.ckpt", metadata=OUT_ROOT / "data/runs/{env_id}/anemoi.json", + log: + OUT_ROOT / "logs/inference_prepare_checkpoint/{env_id}.log", + localrule: True params: checkpoint=lambda wc: ENV_CONFIGS[wc.env_id]["checkpoint"], checkpoint_type=lambda wc: _checkpoint_uri_type( ENV_CONFIGS[wc.env_id]["checkpoint"] ), - log: - OUT_ROOT / "logs/inference_prepare_checkpoint/{env_id}.log", shell: - r"""( - mkdir -p $(dirname {output.checkpoint}) - if [ "{params.checkpoint_type}" = "mlflow" ]; then - ln -s $(python workflow/scripts/inference_get_checkpoint_mlflow.py {params.checkpoint}) {output.checkpoint} - echo "Located checkpoint from MLFlow log." - echo "Created symlink: {output.checkpoint} -> $(readlink {output.checkpoint})" - elif [ "{params.checkpoint_type}" = "huggingface" ]; then - repo_id=$(python -c "import re; print(re.search(r'huggingface\.co/([^/]+/[^/]+)', '{params.checkpoint}').group(1))") - file_path=$(python -c "import re; print(re.search(r'huggingface\.co/[^/]+/[^/]+/blob/[^/]+/(.*)', '{params.checkpoint}').group(1))") - cp $(uvx hf download $repo_id $file_path) {output.checkpoint} - echo "Copied checkpoint from HuggingFace: {output.checkpoint}" - elif [ "{params.checkpoint_type}" = "local" ]; then - ln -s {params.checkpoint} {output.checkpoint} - echo "Created symlink: {output.checkpoint} -> $(readlink {output.checkpoint})" - else - echo "Unknown checkpoint type: {params.checkpoint_type}" - fi - anemoi-utils metadata --dump --json {output.checkpoint} > {output.metadata} - echo "Extracted metadata from checkpoint: {output.metadata}" - ) > {log} 2>&1 + r""" + ( + mkdir -p $(dirname {output.checkpoint}) + if [ "{params.checkpoint_type}" = "mlflow" ]; then + ln -s $(python workflow/scripts/inference_get_checkpoint_mlflow.py {params.checkpoint}) {output.checkpoint} + echo "Located checkpoint from MLFlow log." + echo "Created symlink: {output.checkpoint} -> $(readlink {output.checkpoint})" + elif [ "{params.checkpoint_type}" = "huggingface" ]; then + repo_id=$(python -c "import re; print(re.search(r'huggingface\.co/([^/]+/[^/]+)', '{params.checkpoint}').group(1))") + file_path=$(python -c "import re; print(re.search(r'huggingface\.co/[^/]+/[^/]+/blob/[^/]+/(.*)', '{params.checkpoint}').group(1))") + cp $(uvx hf download $repo_id $file_path) {output.checkpoint} + echo "Copied checkpoint from HuggingFace: {output.checkpoint}" + elif [ "{params.checkpoint_type}" = "local" ]; then + ln -s {params.checkpoint} {output.checkpoint} + echo "Created symlink: {output.checkpoint} -> $(readlink {output.checkpoint})" + else + echo "Unknown checkpoint type: {params.checkpoint_type}" + fi + anemoi-utils metadata --dump --json {output.checkpoint} >{output.metadata} + echo "Extracted metadata from checkpoint: {output.metadata}" + ) >{log} 2>&1 """ +# Generate a pyproject.toml that contains the information needed +# to set up a virtual environment for inference of a specific checkpoint. +# The list of dependencies is taken from the checkpoint's MLFlow run metadata, +# and additional dependencies can be specified under a run entry in the main +# config file. rule inference_extract_requirements: - """ - Generate a pyproject.toml that contains the information needed - to set up a virtual environment for inference of a specific checkpoint. - The list of dependencies is taken from the checkpoint's MLFlow run metadata, - and additional dependencies can be specified under a run entry in the main - config file. - """ - localrule: True input: metadata=OUT_ROOT / "data/runs/{env_id}/anemoi.json", script="workflow/scripts/inference_extract_requirements.py", output: requirements=OUT_ROOT / "data/runs/{env_id}/requirements.txt", + log: + OUT_ROOT / "logs/inference_extract_checkpoint_requirements/{env_id}.log", + localrule: True params: extra_requirements=lambda wc: ",".join( ENV_CONFIGS[wc.env_id].get("extra_requirements", []) ), - log: - OUT_ROOT / "logs/inference_extract_checkpoint_requirements/{env_id}.log", shell: - """( - echo "[$(date)] Starting requirement extraction..." - python {input.script} {input.metadata} \ - --overrides "{params.extra_requirements}" > {output.requirements} - echo "[$(date)] Extracted requirements from metadata: {output.requirements}" - echo $(cat {output.requirements}) - ) > {log} 2>&1 + """ + ( + echo "[$(date)] Starting requirement extraction..." + python {input.script} {input.metadata} \ + --overrides "{params.extra_requirements}" >{output.requirements} + echo "[$(date)] Extracted requirements from metadata: {output.requirements}" + echo $(cat {output.requirements}) + ) >{log} 2>&1 """ +# Create a virtual environment for inference, using the pyproject.toml created above. +# The virtual environment is managed with uv. The created virtual environment is relocatable, +# so it can be squashed later. Pre-compilation to bytecode is done to speed up imports. rule inference_create_venv: - """ - Create a virtual environment for inference, using the pyproject.toml created above. - The virtual environment is managed with uv. The created virtual environment is relocatable, - so it can be squashed later. Pre-compilation to bytecode is done to speed up imports. - """ - localrule: True input: metadata=OUT_ROOT / "data/runs/{env_id}/anemoi.json", requirements=OUT_ROOT / "data/runs/{env_id}/requirements.txt", @@ -88,63 +85,54 @@ rule inference_create_venv: venv=temp(directory(OUT_ROOT / "data/runs/{env_id}/.venv")), log: OUT_ROOT / "logs/inference_create_venv/{env_id}.log", + localrule: True shell: - """( - - PYTHON_VERSION=$(cat {input.metadata} | jq -r ".provenance_training.python") - echo "[$(date)] Creating virtual environment with Python $PYTHON_VERSION..." - uv venv --managed-python --python $PYTHON_VERSION --relocatable --link-mode=copy {output.venv} - source {output.venv}/bin/activate - - echo "[$(date)] Installing requirements from {input.requirements}..." - uv pip install -r {input.requirements} - - echo "[$(date)] Compiling Python bytecode..." - python -m compileall -j 8 -o 0 -o 1 -o 2 .venv/lib/python*/site-packages - echo "[$(date)] Testing that eccodes is working..." - if ! python -c "import eccodes" &>/dev/null; then - echo "[$(date)] ERROR: eccodes is not installed correctly in the virtual environment." - echo "[$(date)] Please check the installation and try again." - exit 1 - fi - echo "[$(date)] Inference virtual environment successfully created at {output.venv}" - ) > {log} 2>&1 + """ + ( + + PYTHON_VERSION=$(cat {input.metadata} | jq -r ".provenance_training.python") + echo "[$(date)] Creating virtual environment with Python $PYTHON_VERSION..." + uv venv --managed-python --python $PYTHON_VERSION --relocatable --link-mode=copy {output.venv} + source {output.venv}/bin/activate + + echo "[$(date)] Installing requirements from {input.requirements}..." + uv pip install -r {input.requirements} + + echo "[$(date)] Compiling Python bytecode..." + python -m compileall -j 8 -o 0 -o 1 -o 2 .venv/lib/python*/site-packages + echo "[$(date)] Testing that eccodes is working..." + if ! python -c "import eccodes" &>/dev/null; then + echo "[$(date)] ERROR: eccodes is not installed correctly in the virtual environment." + echo "[$(date)] Please check the installation and try again." + exit 1 + fi + echo "[$(date)] Inference virtual environment successfully created at {output.venv}" + ) >{log} 2>&1 """ +# Create a squashfs image for the inference virtual environment of +# a specific checkpoint. Find more about this at +# https://docs.cscs.ch/guides/storage/#python-virtual-environments-with-uenv. rule inference_make_squashfs_image: - """ - Create a squashfs image for the inference virtual environment of - a specific checkpoint. Find more about this at - https://docs.cscs.ch/guides/storage/#python-virtual-environments-with-uenv. - """ - localrule: True input: venv=rules.inference_create_venv.output.venv, output: image=OUT_ROOT / "data/runs/{env_id}/venv.squashfs", log: OUT_ROOT / "logs/inference_make_squashfs_image/{env_id}.log", + localrule: True shell: - # we can safely ignore the many warnings "Unrecognised xattr prefix..." "mksquashfs $(realpath {input.venv}) {output.image}" " -no-recovery -noappend -Xcompression-level 3" " > {log} 2>/dev/null" +# Create a zipped directory that, when extracted, can be used as a sandbox +# for running inference jobs for a specific checkpoint. Its main purpose is +# to serve as a development environment for anemoi-inference and to facilitate +# sharing with external collaborators. rule inference_create_sandbox: - """ - Create a zipped directory that, when extracted, can be used as a sandbox - for running inference jobs for a specific checkpoint. Its main purpose is - to serve as a development environment for anemoi-inference and to facilitate - sharing with external collaborators. - - TO use this sandbox, unzip it to a target directory. - - ```bash - unzip sandbox.zip -d /path/to/target/directory - ``` - """ input: script="workflow/scripts/inference_create_sandbox.py", checkpoint=lambda wc: OUT_ROOT @@ -165,7 +153,7 @@ rule inference_create_sandbox: --requirements {input.requirements} \ --readme-template {input.readme_template} \ --output {output.sandbox} \ - > {log} 2>&1 + >{log} 2>&1 """ @@ -187,7 +175,6 @@ def get_leadtime(wc): rule inference_prepare_forecaster: - localrule: True input: checkpoint=lambda wc: OUT_ROOT / f"data/runs/{RUN_CONFIGS[wc.run_id]['env_id']}/inference-last.ckpt", @@ -199,6 +186,9 @@ rule inference_prepare_forecaster: okfile=touch( OUT_ROOT / "logs/inference_prepare_forecaster/{run_id}-{init_time}.ok" ), + log: + OUT_ROOT / "logs/inference_prepare_forecaster/{run_id}-{init_time}.log", + localrule: True params: lead_time=lambda wc: get_leadtime(wc), output_root=(OUT_ROOT / "data").resolve(), @@ -206,8 +196,6 @@ rule inference_prepare_forecaster: reftime_to_iso=lambda wc: datetime.strptime( wc.init_time, "%Y%m%d%H%M" ).strftime("%Y-%m-%dT%H:%M"), - log: - OUT_ROOT / "logs/inference_prepare_forecaster/{run_id}-{init_time}.log", script: "../scripts/inference_prepare.py" @@ -217,9 +205,8 @@ def _get_forecaster_run_id(run_id): return RUN_CONFIGS[run_id]["forecaster"]["run_id"] +# Prepare interpolator for a specific run ID rule inference_prepare_interpolator: - """Run the interpolator for a specific run ID.""" - localrule: True input: checkpoint=lambda wc: OUT_ROOT / f"data/runs/{RUN_CONFIGS[wc.run_id]['env_id']}/inference-last.ckpt", @@ -240,6 +227,9 @@ rule inference_prepare_interpolator: okfile=touch( OUT_ROOT / "logs/inference_prepare_interpolator/{run_id}-{init_time}.ok" ), + log: + OUT_ROOT / "logs/inference_prepare_interpolator/{run_id}-{init_time}.log", + localrule: True params: lead_time=lambda wc: get_leadtime(wc), output_root=(OUT_ROOT / "data").resolve(), @@ -252,8 +242,6 @@ rule inference_prepare_interpolator: if RUN_CONFIGS[wc.run_id].get("forecaster") is None else _get_forecaster_run_id(wc.run_id) ), - log: - OUT_ROOT / "logs/inference_prepare_interpolator/{run_id}-{init_time}.log", script: "../scripts/inference_prepare.py" @@ -275,7 +263,6 @@ def _inference_routing_fn(wc): rule inference_execute: - localrule: True input: okfile=_inference_routing_fn, image=lambda wc: OUT_ROOT @@ -284,14 +271,7 @@ rule inference_execute: okfile=touch(OUT_ROOT / "logs/inference_execute/{run_id}-{init_time}.ok"), log: OUT_ROOT / "logs/inference_execute/{run_id}-{init_time}.log", - params: - image_path=lambda wc, input: f"{Path(input.image).resolve()}", - workdir=lambda wc: ( - OUT_ROOT / f"data/runs/{wc.run_id}/{wc.init_time}" - ).resolve(), - disable_local_definitions=lambda wc: RUN_CONFIGS[wc.run_id].get( - "disable_local_eccodes_definitions", False - ), + localrule: True resources: slurm_partition=lambda wc: get_resource(wc, "slurm_partition", "short-shared"), cpus_per_task=lambda wc: get_resource(wc, "cpus_per_task", 24), @@ -300,36 +280,45 @@ rule inference_execute: gres=lambda wc: f"gpu:{get_resource(wc, 'gpu',1)}", ntasks=lambda wc: get_resource(wc, "tasks", 1), gpus=lambda wc: get_resource(wc, "gpu", 1), + params: + image_path=lambda wc, input: f"{Path(input.image).resolve()}", + workdir=lambda wc: ( + OUT_ROOT / f"data/runs/{wc.run_id}/{wc.init_time}" + ).resolve(), + disable_local_definitions=lambda wc: RUN_CONFIGS[wc.run_id].get( + "disable_local_eccodes_definitions", False + ), + # fmt: off shell: """ ( - set -euo pipefail - - cd {params.workdir} - - squashfs-mount {params.image_path}:/user-environment -- bash -c ' - source /user-environment/bin/activate - - if [ "{params.disable_local_definitions}" = "False" ]; then - export ECCODES_DEFINITION_PATH=/user-environment/share/eccodes-cosmo-resources/definitions - fi - - CMD_ARGS=() - - # is GPU > 1, add parallel flag to CMD_ARGS and override automatic cluster detection - if [ {resources.gpus} -gt 1 ]; then - CMD_ARGS+=(runner.parallel.cluster=slurm) - fi - - srun \ - --unbuffered \ - --partition={resources.slurm_partition} \ - --cpus-per-task={resources.cpus_per_task} \ - --mem-per-cpu={resources.mem_mb_per_cpu} \ - --time={resources.runtime} \ - --gres={resources.gres} \ - --ntasks={resources.ntasks} \ - anemoi-inference run config.yaml "${{CMD_ARGS[@]}}" - ' - ) > {log} 2>&1 + set -euo pipefail + + cd {params.workdir} + + squashfs-mount {params.image_path}:/user-environment -- bash -c ' + source /user-environment/bin/activate + + if [ "{params.disable_local_definitions}" = "False" ]; then + export ECCODES_DEFINITION_PATH=/user-environment/share/eccodes-cosmo-resources/definitions + fi + + CMD_ARGS=() + + # is GPU > 1, add parallel flag to CMD_ARGS and override automatic cluster detection + if [ {resources.gpus} -gt 1 ]; then + CMD_ARGS+=(runner.parallel.cluster=slurm) + fi + + srun \ + --unbuffered \ + --partition={resources.slurm_partition} \ + --cpus-per-task={resources.cpus_per_task} \ + --mem-per-cpu={resources.mem_mb_per_cpu} \ + --time={resources.runtime} \ + --gres={resources.gres} \ + --ntasks={resources.ntasks} \ + anemoi-inference run config.yaml "${{CMD_ARGS[@]}}" + ' + ) >{log} 2>&1 """ diff --git a/workflow/rules/plot.smk b/workflow/rules/plot.smk index 7eb90a59..d0310d08 100644 --- a/workflow/rules/plot.smk +++ b/workflow/rules/plot.smk @@ -105,9 +105,9 @@ rule plot_forecast_frame: """ export ECCODES_DEFINITION_PATH=$(realpath .venv/share/eccodes-cosmo-resources/definitions) python {input.script} \ - --input {params.grib_out_dir} --date {wildcards.init_time} --outfn {output[0]} \ + --input {params.grib_out_dir} --date {wildcards.init_time} --outfn {output[0]} \ --param {wildcards.param} --leadtime {wildcards.leadtime} --region {wildcards.region} \ - --accu {params.accu} \ + --accu {params.accu} # interactive editing (needs to set localrule: True and use only one core) # marimo edit {input.script} -- \ # --input {params.grib_out_dir} --date {wildcards.init_time} --outfn {output[0]}\ @@ -126,7 +126,6 @@ def get_leadtimes(wc): rule make_forecast_animation: - localrule: True input: expand( rules.plot_forecast_frame.output, @@ -136,6 +135,7 @@ rule make_forecast_animation: output: OUT_ROOT / "results/{showcase}/{run_id}/{init_time}/{init_time}_{param}_{region}.gif", + localrule: True params: delay=lambda wc: 10 * int(RUN_CONFIGS[wc.run_id]["steps"].split("/")[2]), shell: diff --git a/workflow/rules/report.smk b/workflow/rules/report.smk index f8ee9a9f..1d106862 100644 --- a/workflow/rules/report.smk +++ b/workflow/rules/report.smk @@ -20,7 +20,6 @@ def make_header_text(): rule report_experiment_dashboard: - localrule: True input: "src/verification/__init__.py", script="workflow/scripts/report_experiment_dashboard.py", @@ -33,12 +32,13 @@ rule report_experiment_dashboard: directory(OUT_ROOT / "results/{experiment}/dashboard"), htmlindex="dashboard.html", ), + log: + OUT_ROOT / "logs/report_experiment_dashboard/{experiment}.log", + localrule: True params: sources=",".join(list(EXPERIMENT_PARTICIPANTS.keys())), header_text=make_header_text(), stratification=" ".join(config["dashboard"]["stratification"]), - log: - OUT_ROOT / "logs/report_experiment_dashboard/{experiment}.log", shell: """ python {input.script} \ @@ -48,5 +48,5 @@ rule report_experiment_dashboard: --header_text "{params.header_text}" \ --configfile "{input.configfile}" \ --stratification {params.stratification} \ - --output {output} > {log} 2>&1 + --output {output} >{log} 2>&1 """ diff --git a/workflow/rules/summary.smk b/workflow/rules/summary.smk index 38d8c2fe..bd4c0721 100644 --- a/workflow/rules/summary.smk +++ b/workflow/rules/summary.smk @@ -10,27 +10,22 @@ from pprint import pprint rule write_summary: - """ - Produce a human-readable summary of the configuration. - """ + output: + OUT_ROOT / "data/runs/{run_id}/summary.md", localrule: True params: configfile=lambda wc: workflow.configfiles[0], - output: - OUT_ROOT / "data/runs/{run_id}/summary.md", run: import yaml from datetime import datetime cfg_path = params.configfile cfg = yaml.safe_load(open(cfg_path)) - with open(output[0], "w") as out: out.write(f"# Run Summary\n\n") out.write(f"- 🆔 **Run ID:** {wildcards.run_id}\n") out.write(f"- 📄 **Configuration file:** `{cfg_path}`\n") out.write(f"- 🕒 **Generated on:** {datetime.now().isoformat()}\n\n") - # config block out.write("## ⚙️ Configuration\n") out.write("```yaml\n") diff --git a/workflow/rules/verification.smk b/workflow/rules/verification.smk index 683c65f1..cdb691b2 100644 --- a/workflow/rules/verification.smk +++ b/workflow/rules/verification.smk @@ -24,12 +24,6 @@ rule verification_metrics_baseline: script="workflow/scripts/verification_metrics.py", forecast=_get_baseline_forecast_path, truth=config["truth"]["root"], - params: - baseline_label=lambda wc: BASELINE_CONFIGS[wc.baseline_id].get("label"), - baseline_steps=lambda wc: BASELINE_CONFIGS[wc.baseline_id]["steps"], - truth_label=config["truth"]["label"], - regions=REGIONS, - threshold_dict=config["thresholds"], output: OUT_ROOT / "data/baselines/{baseline_id}/{init_time}/verif.nc", log: @@ -38,8 +32,15 @@ rule verification_metrics_baseline: cpus_per_task=24, mem_mb=50_000, runtime="60m", + params: + baseline_label=lambda wc: BASELINE_CONFIGS[wc.baseline_id].get("label"), + baseline_steps=lambda wc: BASELINE_CONFIGS[wc.baseline_id]["steps"], + truth_label=config["truth"]["label"], + regions=REGIONS, + threshold_dict=config["thresholds"], shell: """ + export ECCODES_DEFINITION_PATH=$(realpath .venv/share/eccodes-cosmo-resources/definitions) uv run {input.script} \ --forecast {input.forecast} \ --truth {input.truth} \ @@ -49,7 +50,7 @@ rule verification_metrics_baseline: --truth_label "{params.truth_label}" \ --regions "{params.regions}" \ --threshold_dict "{params.threshold_dict}" \ - --output {output} > {log} 2>&1 + --output {output} >{log} 2>&1 """ @@ -69,6 +70,12 @@ rule verification_metrics: truth=config["truth"]["root"], output: OUT_ROOT / "data/runs/{run_id}/{init_time}/verif.nc", + log: + OUT_ROOT / "logs/verification_metrics/{run_id}-{init_time}.log", + resources: + cpus_per_task=24, + mem_mb=50_000, + runtime="60m", # wildcard_constraints: # run_id="^" # to avoid ambiguitiy with run_baseline_verif # TODO: implement logic to use experiment name instead of run_id as wildcard @@ -81,14 +88,9 @@ rule verification_metrics: Path(OUT_ROOT) / f"data/runs/{wc.run_id}/{wc.init_time}/grib" ).resolve(), threshold_dict=config["thresholds"], - log: - OUT_ROOT / "logs/verification_metrics/{run_id}-{init_time}.log", - resources: - cpus_per_task=24, - mem_mb=50_000, - runtime="60m", shell: """ + export ECCODES_DEFINITION_PATH=$(realpath .venv/share/eccodes-cosmo-resources/definitions) uv run {input.script} \ --forecast {params.grib_out_dir} \ --truth {input.truth} \ @@ -98,7 +100,7 @@ rule verification_metrics: --truth_label "{params.truth_label}" \ --regions "{params.regions}" \ --threshold_dict "{params.threshold_dict}" \ - --output {output} > {log} 2>&1 + --output {output} >{log} 2>&1 """ @@ -127,7 +129,7 @@ rule verification_metrics_aggregation: runtime="2h", shell: """ - uv run {input.script} {input.verif_nc} --output {output} > {log} 2>&1 + uv run {input.script} {input.verif_nc} --output {output} >{log} 2>&1 """ @@ -155,15 +157,15 @@ rule verification_metrics_plot: directory(OUT_ROOT / "results/{experiment}/plots"), patterns=["{name}.png"], ), - params: - labels=",".join(list(EXPERIMENT_PARTICIPANTS.keys())), log: OUT_ROOT / "logs/verification_metrics_plot/{experiment}.log", resources: cpus_per_task=16, mem_mb=50_000, runtime="20m", + params: + labels=",".join(list(EXPERIMENT_PARTICIPANTS.keys())), shell: """ - uv run {input.script} {input.verif} --output_dir {output} > {log} 2>&1 + uv run {input.script} {input.verif} --output_dir {output} >{log} 2>&1 """ From 4475d1fd54c5c6d1ef48c7620f570cca2a21874d Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 14:07:30 +0200 Subject: [PATCH 02/23] update main project dependencies --- pyproject.toml | 18 +- uv.lock | 4725 ++++++++++++++++++++++++++++-------------------- 2 files changed, 2806 insertions(+), 1937 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 53f4207c..d3279e91 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -12,7 +12,6 @@ dependencies = [ "snakemake<9.10", # https://github.com/snakemake/snakemake/issues/3289 "snakemake-executor-plugin-slurm", "click", - "meteodata-lab>=0.4.0", "anemoi-datasets>=0.5.31", "mlflow>=3.1.1", "pydantic>=2.11.7", @@ -21,20 +20,18 @@ dependencies = [ "shapely>=2.1.2", "cartopy>=0.25.0", "pyproj>=3.7.2", - "earthkit-plots", "marimo>=0.23.3", "geopandas>=0.14.0", "peakweather", "pyzmq>=27.1.0", "scores>=2.0.0", -] - -[project.optional-dependencies] -kerchunk = [ - "kerchunk", - 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hash = "sha256:25ad4e16390cd314347dd8f1de67a2ac538ae658ed4ab9db16029c07c188e97f", size = 10238, upload-time = "2026-05-18T20:08:57.045Z" }, ] From b440427024ec5d47c385ee303001c3a9232a75c1 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 14:07:58 +0200 Subject: [PATCH 03/23] update dependencies for inference environment --- workflow/scripts/inference_extract_requirements.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/workflow/scripts/inference_extract_requirements.py b/workflow/scripts/inference_extract_requirements.py index 12e3e29a..dc3441ae 100644 --- a/workflow/scripts/inference_extract_requirements.py +++ b/workflow/scripts/inference_extract_requirements.py @@ -19,8 +19,8 @@ BASE_DEPENDENCIES = [ "anemoi-inference", - "eccodes==2.39.1", - "eccodes-cosmo-resources-python", + "eccodes>=2.44.0,<2.48.0", + "eccodes-cosmo-resources-python==2.44.0.1", ] # Packages emitted in the output even when only found in provenance (not overrides). From d2c4f2ad946c56085e7d35e9bbb906697dc33b51 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 14:08:44 +0200 Subject: [PATCH 04/23] renaming dimensions --- workflow/scripts/report_experiment_dashboard.py | 4 ++-- workflow/scripts/verification_aggregation.py | 10 +++++----- workflow/scripts/verification_metrics.py | 4 ++-- workflow/scripts/verification_plot_metrics.py | 14 +++++++------- 4 files changed, 16 insertions(+), 16 deletions(-) diff --git a/workflow/scripts/report_experiment_dashboard.py b/workflow/scripts/report_experiment_dashboard.py index 414eb146..75635f40 100644 --- a/workflow/scripts/report_experiment_dashboard.py +++ b/workflow/scripts/report_experiment_dashboard.py @@ -46,7 +46,7 @@ def main(args): df[["param", "metric"]] = df["stack"].str.split(".", n=1, expand=True) df["metric"] = df.metric.apply(decode_metric) df.drop(columns=["stack"], inplace=True) - df["lead_time"] = df["lead_time"].dt.total_seconds() / 3600 + df["step"] = df["step"].dt.total_seconds() / 3600 # convert numeric column init_hour to string in format HH:00 UTC and replace -999 with "all" df["init_hour"] = df["init_hour"].astype(str).str.zfill(2) + ":00 UTC" df["init_hour"] = df["init_hour"].where(df["init_hour"] != "-999:00 UTC", "all") @@ -87,7 +87,7 @@ def _round_sig(x, sig=6): "source", "param", "metric", - "lead_time", + "step", "value", "region", "season", diff --git a/workflow/scripts/verification_aggregation.py b/workflow/scripts/verification_aggregation.py index 94623c2d..861e5530 100644 --- a/workflow/scripts/verification_aggregation.py +++ b/workflow/scripts/verification_aggregation.py @@ -41,8 +41,8 @@ def aggregate_results(ds: xr.Dataset) -> xr.Dataset: # for simplicity we group by season based on ref_time (as this is a dimension of the dataset) ds = ds.assign_coords( - season=lambda ds: ds.ref_time.dt.season, - init_hour=lambda ds: ds.ref_time.dt.hour, + season=lambda ds: ds["forecast_reference_time"].dt.season, + init_hour=lambda ds: ds["forecast_reference_time"].dt.hour, ).drop_vars(["time"], errors="ignore") # compute mean with grouping by all permutations of season and init_hour @@ -52,7 +52,7 @@ def aggregate_results(ds: xr.Dataset) -> xr.Dataset: ds_grouped = ds else: ds_grouped = ds.groupby(group) - ds_grouped = ds_grouped.mean(dim="ref_time").compute( + ds_grouped = ds_grouped.mean(dim="forecast_reference_time").compute( num_workers=4, scheduler="threads" ) if "init_hour" not in group: @@ -66,7 +66,7 @@ def aggregate_results(ds: xr.Dataset) -> xr.Dataset: for var in out.data_vars: if "contingency_table" in var: # convert contingency table elements to counts - out[var] = out[var] * len(ds["ref_time"]) + out[var] = out[var] * len(ds["forecast_reference_time"]) contingency_manager = scores.categorical.BasicContingencyManager( { "tp_count": out[var].sel(contingency="tp_count"), @@ -133,7 +133,7 @@ def main(args: Namespace) -> None: ds = xr.open_mfdataset( sorted(args.verif_files), combine="nested", - concat_dim="ref_time", + concat_dim="forecast_reference_time", data_vars="minimal", coords="minimal", compat="override", diff --git a/workflow/scripts/verification_metrics.py b/workflow/scripts/verification_metrics.py index 20f0e1fc..1cbb4c5c 100644 --- a/workflow/scripts/verification_metrics.py +++ b/workflow/scripts/verification_metrics.py @@ -70,7 +70,7 @@ def main(args: ScriptConfig): # align forecast and truth data spatially and temporally fcst = map_forecast_to_truth(fcst, truth) - truth = truth.sel(time=fcst.time) + truth = truth.sel(time=fcst["valid_time"]) # compute metrics and statistics results = verify( @@ -84,7 +84,7 @@ def main(args: ScriptConfig): # save results to NetCDF args.output.parent.mkdir(parents=True, exist_ok=True) - results.to_netcdf(args.output) + results.earthkit.to_netcdf(args.output) LOG.info("Saved verification results to %s", args.output) LOG.info("Program completed successfully.") diff --git a/workflow/scripts/verification_plot_metrics.py b/workflow/scripts/verification_plot_metrics.py index 92149d82..2f4b685a 100644 --- a/workflow/scripts/verification_plot_metrics.py +++ b/workflow/scripts/verification_plot_metrics.py @@ -18,12 +18,12 @@ def _ensure_unique_lead_time(ds: xr.Dataset) -> xr.Dataset: """Drop duplicate lead_time entries within a Dataset (keep first occurrence).""" try: - idx = ds.get_index("lead_time") + idx = ds.get_index("step") except Exception: - idx = pd.Index(ds["lead_time"].values) + idx = pd.Index(ds["step"].values) if getattr(idx, "has_duplicates", False): keep = ~idx.duplicated(keep="first") - ds = ds.isel(lead_time=keep) + ds = ds.isel(step=keep) return ds @@ -44,9 +44,9 @@ def _select_best_sources(dfs: list[xr.Dataset]) -> list[xr.Dataset]: if s in d.source.values: di = d.sel(source=s) try: - n = pd.Index(di["lead_time"].values).unique().size + n = pd.Index(di["step"].values).unique().size except Exception: - n = len(pd.unique(di["lead_time"].values)) + n = len(pd.unique(di["step"].values)) candidates.append((i, n)) if candidates: best_idx, _ = max(candidates, key=lambda t: t[1]) @@ -91,7 +91,7 @@ def main(args: Namespace) -> None: ) all_df[["param", "metric"]] = all_df["stack"].str.split(".", n=1, expand=True) all_df.drop(columns=["stack"], inplace=True) - all_df["lead_time"] = all_df["lead_time"].dt.total_seconds() / 3600 + all_df["step"] = all_df["step"].dt.total_seconds() / 3600 metrics = all_df["metric"].unique() params = all_df["param"].unique() @@ -128,7 +128,7 @@ def _subset_df(df): title += f"- {season} - {init_hour}" if args.stratify else "" for source, df in sub_df.groupby("source"): df.plot( - x="lead_time", + x="step", y="value", kind="line", marker="o", From 6107544f1368044e2373c3be41301c77e9441539 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 14:15:55 +0200 Subject: [PATCH 05/23] refactor source files for new earthkit --- src/data_input/__init__.py | 175 ++++++++++++++++++++--------------- src/verification/__init__.py | 10 +- src/verification/spatial.py | 18 ++-- 3 files changed, 116 insertions(+), 87 deletions(-) diff --git a/src/data_input/__init__.py b/src/data_input/__init__.py index 2c49151e..036a3325 100644 --- a/src/data_input/__init__.py +++ b/src/data_input/__init__.py @@ -1,19 +1,20 @@ import logging -import os -import sys from datetime import datetime, timedelta from pathlib import Path +from typing import Literal, Any -eccodes_definition_path = Path(sys.prefix) / "share/eccodes-cosmo-resources/definitions" -os.environ["ECCODES_DEFINITION_PATH"] = str(eccodes_definition_path) - -from meteodatalab import data_source, grib_decoder # noqa: E402 - -import numpy as np # noqa: E402 -import xarray as xr # noqa: E402 +import earthkit.data as ekd +import numpy as np +import xarray as xr LOG = logging.getLogger(__name__) +XARRAY_ENGINE_PROFILE = { + "ensure_dims": ["z", "number", "step", "forecast_reference_time"], + "add_valid_time_coord": True, + "global_attrs": [{"institution": "MeteoSwiss"}, {"Conventions": "CF-1.8"}], +} + def _select_valid_times(ds, times: np.datetime64): # (handle special case where some valid times are not in the dataset, e.g. at the end) @@ -88,8 +89,8 @@ def load_analysis_data_from_zarr( # set lat lon as coords (optional) if "latitudes" in ds and "longitudes" in ds: - ds = ds.rename({"latitudes": "lat", "longitudes": "lon"}) - ds = ds.set_coords(["lat", "lon"]) + ds = ds.rename({"latitudes": "latitude", "longitudes": "longitude"}) + ds = ds.set_coords(["latitude", "longitude"]) ds = ( ds["data"] .to_dataset("variable") @@ -107,18 +108,22 @@ def load_analysis_data_from_zarr( return _select_valid_times(ds, times) -def _collect_ml_grib_files( - root: Path, reftime: datetime, steps: list[int] | None = None -) -> list[Path]: +def _collect_ml_grib_files(root: Path, steps: list[int] | None = None) -> list[Path]: """Return GRIB files for an ML inference run (flat directory layout). When `steps` is provided, the discovered files are filtered to those whose name ends with ``_{step:03d}.grib``. """ - files = sorted(root.glob(f"{reftime:%Y%m%d%H%M}*.grib")) + # TODO: this glob pattern is a dirty fix for anemoi-inference writing outputs + # with wrong formatting. Eventually we will either have to have a fix upstream + # or write a single output file. + files = sorted(root.glob("20*.grib")) if steps is None: return files + + # again, two different patterns might be used for step formatting suffixes = {f"_{step:03d}.grib" for step in steps} + suffixes |= {f"_{step}.grib" for step in steps} return [f for f in files if any(f.name.endswith(s) for s in suffixes)] @@ -154,67 +159,86 @@ def _collect_icon_archive_files( ] +def load_from_grib_file(file: str | list[str], sel_kwargs): + fieldlist = ekd.from_source("file", file, lazily=True).to_fieldlist() + return fieldlist_to_xarray(fieldlist.sel(**sel_kwargs)) + + +def variable_name_profile( + level_type: Literal["height_above_ground_level", "mean_sea", "surface", "pressure"], +) -> dict[str, Any]: + """Resolve variable name profile based on the level type.""" + if level_type in ["height_above_ground_level", "mean_sea", "surface"]: + return {} + elif level_type == "pressure": + return { + "variable_key": "p_l", + "remapping": {"p_l": "{parameter.variable}_{vertical.level}"}, + } + else: + raise ValueError(f"Unsupported level type: {level_type}") + + +def fieldlist_to_xarray(fieldlist) -> xr.Dataset: + ds = xr.Dataset() + for level_type_group in fieldlist.group_by("vertical.level_type"): + # earthkit-data should return the group key...TODO: open issue? + level_type = level_type_group.get("vertical.level_type")[0] + profile = XARRAY_ENGINE_PROFILE | variable_name_profile(level_type) + _ds = level_type_group.to_xarray(**profile, allow_holes=True) + ds = ds.merge(_ds, compat="no_conflicts", combine_attrs="no_conflicts") + return ds + + +def _tot_prec_handling(tp: xr.DataArray) -> xr.DataArray: + _full_step_coord = tp["step"] # step coordinate before .diff() + + # anemoi-inference sometimes omits step 0 from the GRIB even with + # accumulate_from_start_of_forecast enabled. If missing, earthkit-data + # will fill it with NaNs following the `allow_holes=True` flag. + if tp[{"step": 0}].isnull().all(): + LOG.warning( + "Step 0 of TOT_PREC is missing, filling with zeroes " + "assuming accumulate_from_start_of_forecast is enabled." + ) + tp[{"step": 0}] = 0.0 + + # Disaggregate TOT_PREC from cumulative-from-start (expected when the + # accumulate_from_start_of_forecast post-processor is enabled in + # anemoi-inference) to per-step accumulations. + LOG.info( + "Disaggregating TOT_PREC from cumulative-from-start to per-step accumulations." + ) + tp = tp.diff("step") + + # Sanity-check that the incoming data is actually cumulative. If + # some values are significantly negative, it indicates that the data + # is already period-accumulated. + min_diff = float(tp.min().compute()) + if min_diff < -0.1: # NOTE: TOT_PREC canonical units are mm + raise ValueError( + "TOT_PREC in the GRIB appears to already be " + f"period-accumulated (min(.diff()) = {min_diff:.3e} m). " + "Check that the accumulate_from_start_of_forecast post-processor " + "is enabled in the anemoi-inference config for this source." + ) + + # Clip remaining small negative values to zero + tp = tp.clip(min=0.0) + + # Reindex to match the original lead_time coordinate + tp = tp.reindex(step=_full_step_coord) + + return tp + + def load_fct_data_from_grib(files: list[Path], params: list[str]) -> xr.Dataset: """Load forecast data from a list of GRIB files.""" - fds = data_source.FileDataSource(datafiles=files) - ds = grib_decoder.load(fds, {"param": params}) - for var, da in ds.items(): - if "z" in da.dims and da.sizes["z"] == 1: - ds[var] = da.squeeze("z", drop=True) - elif "z" in da.dims and da.sizes["z"] > 1: - ds[var] = da.rename({"z": da.attrs["vcoord_type"]}) - ds = xr.merge([ds[p].rename(p) for p in ds], compat="no_conflicts") - lead_times = ds.lead_time.values + ds = load_from_grib_file(files, {"parameter.variable": params}) + if "TOT_PREC" in ds.data_vars: - ## Disaggregate TOT_PREC from cumulative-from-start (expected when the - ## accumulate_from_start_of_forecast post-processor is enabled in - ## anemoi-inference) to per-step accumulations. - ## - ## anemoi-inference sometimes omits step 0 from the GRIB even with - ## accumulate_from_start_of_forecast enabled. After the outer-join - ## merge above, lead_time=0 of TOT_PREC is then NaN, which would - ## propagate through .diff() and wipe out the first period - ## accumulation. Set it explicitly to 0 (cumulative-from-start has - ## nothing accumulated at the forecast initial time by definition). - ## Restricting to lead_time=0 leaves any other NaNs (e.g. from - ## boundary-trim masks) untouched. - ds = ds.assign( - TOT_PREC=xr.where( - ds.lead_time == np.timedelta64(0, "h"), - 0.0, - ds.TOT_PREC, - ) - ) - ## Sanity-check that the incoming data is actually cumulative: if - ## .diff() produces significantly negative values, TOT_PREC is already - ## period-accumulated and a second disaggregation would produce - ## garbage. In that case raise — we always expect cumulative-from- - ## start precipitation here. - diff = ds.TOT_PREC.diff("lead_time") - min_diff = float(diff.min().compute()) - if min_diff < -0.1: # TOT_PREC canonical units are mm - raise ValueError( - f"TOT_PREC in the GRIB appears to already be " - f"period-accumulated (min(.diff()) = {min_diff:.3e} m). " - f"Check that the accumulate_from_start_of_forecast " - f"post-processor is enabled in the anemoi-inference config " - f"for this source." - ) - ## .diff() drops lead_time=0; .reindex() restores it as NaN (no - ## accumulation period exists at the forecast initial time). Clip - ## small float-noise negatives to zero (anything below -0.1 mm has - ## already been caught by the check above). - ds = ds.assign(TOT_PREC=diff.clip(min=0.0).reindex(lead_time=lead_times)) - # make sure time coordinate is available, and valid_time is not - if "valid_time" in ds.coords: - ds = ds.rename({"valid_time": "time"}) - if "time" not in ds.coords: - ds = ds.assign_coords(time=ds.ref_time + ds.lead_time) - ds = ds.squeeze("ref_time", drop=False) + ds["TOT_PREC"] = _tot_prec_handling(ds["TOT_PREC"]) - # rename 'cell' dimension to 'values' (it's earthkit-data default for flattened spatial dim) - if "cell" in ds.dims: - ds = ds.rename({"cell": "values"}) return ds @@ -263,8 +287,8 @@ def load_obs_data_from_peakweather( ds = ds.rename(param_names) ds = ds.assign_coords(time=ds.indexes["time"].tz_convert("UTC").tz_localize(None)) ds = ds.assign_coords(values=ds.indexes["values"]) - ds = ds.assign_coords(lon=("values", pw.stations_table["longitude"])) - ds = ds.assign_coords(lat=("values", pw.stations_table["latitude"])) + ds = ds.assign_coords(longitude=("values", pw.stations_table["longitude"])) + ds = ds.assign_coords(latitude=("values", pw.stations_table["latitude"])) if "T_2M" in ds: ds["T_2M"] = ds["T_2M"] + 273.15 # convert to Kelvin ds = ds.dropna("values", how="all") @@ -317,7 +341,8 @@ def load_forecast_data( if any(root.glob("*.grib")): LOG.info("Loading forecasts from GRIB files...") return load_fct_data_from_grib( - files=_collect_ml_grib_files(root, reftime, steps), + # NOTE: root is already for a specific reftime + files=_collect_ml_grib_files(root, steps), params=params, ) LOG.info("Loading baseline forecasts from ICON GRIB archive...") diff --git a/src/verification/__init__.py b/src/verification/__init__.py index 751344cf..941e3433 100644 --- a/src/verification/__init__.py +++ b/src/verification/__init__.py @@ -196,8 +196,10 @@ def _compute_statistics( def _merge_metrics(ds: xr.Dataset, num_workers: int = 4) -> xr.Dataset: out = xr.merge(ds, compat="no_conflicts") - if "ref_time" not in out.dims: - out = out.expand_dims("ref_time").set_coords("ref_time") + if "forecast_reference_time" not in out.dims: + out = out.expand_dims("forecast_reference_time").set_coords( + "forecast_reference_time" + ) out = out.compute(num_workers=num_workers, scheduler="threads") return out @@ -278,7 +280,9 @@ def verify( # return the results as a xarray Dataset fcst_aligned, obs_aligned = xr.align(fcst, obs, join="inner", copy=False) region_polygons = ShapefileSpatialAggregationMasks(shp=regions) - masks = region_polygons.get_masks(lon=obs_aligned["lon"], lat=obs_aligned["lat"]) + masks = region_polygons.get_masks( + lon=obs_aligned["longitude"], lat=obs_aligned["latitude"] + ) scores = [] statistics = [] diff --git a/src/verification/spatial.py b/src/verification/spatial.py index a5186d5f..347521a1 100644 --- a/src/verification/spatial.py +++ b/src/verification/spatial.py @@ -81,11 +81,11 @@ def nearest_grid_yx_indices( Arrays of `y` and `x` indices for each target location. """ - if "lat" not in grid or "lon" not in grid: + if "latitude" not in grid or "longitude" not in grid: raise ValueError("Input must provide 'lat' and 'lon' coordinates") - lat2d = np.asarray(grid["lat"].values) - lon2d = np.asarray(grid["lon"].values) + lat2d = np.asarray(grid["latitude"].values) + lon2d = np.asarray(grid["longitude"].values) if lat2d.ndim != 2 or lon2d.ndim != 2: raise ValueError("'lat' and 'lon' must be 2D on (y, x) for y/x indexing") @@ -131,16 +131,16 @@ def map_forecast_to_truth(fcst: xr.Dataset, truth: xr.Dataset) -> xr.Dataset: truth = truth.stack(values=("y", "x")) nearest_idx = spherical_nearest_neighbor_indices( - source_lat=fcst["lat"].values, - source_lon=fcst["lon"].values, - target_lat=truth["lat"].values, - target_lon=truth["lon"].values, + source_lat=fcst["latitude"].values, + source_lon=fcst["longitude"].values, + target_lat=truth["latitude"].values, + target_lon=truth["longitude"].values, ) fcst = fcst.isel(values=nearest_idx) fcst = fcst.drop_vars(["x", "y", "values"], errors="ignore") - fcst = fcst.assign_coords(lon=("values", truth.lon.data)) - fcst = fcst.assign_coords(lat=("values", truth.lat.data)) + fcst = fcst.assign_coords(lon=("values", truth["longitude"].data)) + fcst = fcst.assign_coords(lat=("values", truth["latitude"].data)) fcst = fcst.assign_coords(values=truth["values"]) if truth_is_grid: From f6c0fce0ae53806c16b1a376dc4514b09c88811b Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 14:24:02 +0200 Subject: [PATCH 06/23] add earthkit workaround instructions --- README.md | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/README.md b/README.md index a3849086..9eaa3150 100644 --- a/README.md +++ b/README.md @@ -236,3 +236,17 @@ All outputs are rooted at `OUT_ROOT` (from `locations.output_root` in the config | `{param}` | variable name | `T_2M`, `TOT_PREC` | | `{region}` | geographic region slug | `switzerland`, `globe` | | `{leadtime}` | zero-padded hours | `000`, `006`, `024` | + + +## earthkit v1.0rc support + +The adoption of the first upcoming stable release of earthkit has started. +Some issues may still be present. A known issue that is affecting us is that the automatic download and caching of files required +by earthkit to support the ICON-CH grids is currently broken. This requires us to perform this step manually. + +```bash +export ECKIT_GEO_CACHE=$HOME/.local/share/eckit/geo/grid/icon +mkdir -p $ECKIT_GEO_CACHE +curl https:/sites.ecmwf.int/repository/eckit/geo/grid/icon-ch/icon-ch1-c.ek > $ECKIT_GEO_CACHE/17643da2574959b644d254a3cd6e2bc0-b0699f374c63d05028c18c12f80a48f4.ek +curl https:/sites.ecmwf.int/repository/eckit/geo/grid/icon-ch/icon-ch2-c.ek > $ECKIT_GEO_CACHE/bbbd5a09855499243c7a4aa4c8762920-67adabf5c0cff041ebaafa61a3bda267.ek +``` From b7e547b10194374c3d9e7fa946dbf14b6f27b9b0 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 14:24:32 +0200 Subject: [PATCH 07/23] wip: update inference configs --- .../sgm-forecaster-global-ich1-oper.yaml | 28 +++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml b/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml index fb1cda60..bbf1e63e 100644 --- a/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml +++ b/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml @@ -39,6 +39,34 @@ output: encoding: typeOfGeneratingProcess: 2 centre: ecmf + modifiers: + - patches: + - variable: + U_10M: {"param": 165, "shortName": "10u"} + 10u: {"param": 165, "shortName": "10u"} + V_10M: {"param": 166, "shortName": "10v"} + 10v: {"param": 166, "shortName": "10v"} + TD_2M: {"param": 167, "shortName": "2d"} + 2d: {"param": 168, "shortName": "2d"} + T_2M: {"param": 167, "shortName": "2t"} + 2t: {"param": 167, "shortName": "2t"} + FR_LAND: {"param": 172, "shortName": "lsm"} + lsm: {"param": 172, "shortName": "lsm"} + PMSL: {"param": 151, "shortName": "msl"} + msl: {"param": 151, "shortName": "msl"} + PS: {"param": 134, "shortName": "sp"} + sp: {"param": 134, "shortName": "sp"} + TOT_PREC: {"param": 228, "shortName": "tp"} + tp: {"param": 228, "shortName": "tp"} + z: {"param": 129, "shortName": "z"} + "^q_(\\d+)$": {"param": 133, "shortName": "q"} + "^t_(\\d+)$": {"param": 130, "shortName": "t"} + "^u_(\\d+)$": {"param": 131, "shortName": "u"} + "^v_(\\d+)$": {"param": 132, "shortName": "v"} + "^w_(\\d+)$": {"param": 135, "shortName": "w"} + "^z_(\\d+)$": {"param": 129, "shortName": "z"} + + templates: samples: resources/templates_index_ifs.yaml post_processors: From f4a972d450e837bf6a9d275b30cb5c56a23a20d6 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 17:11:28 +0200 Subject: [PATCH 08/23] remove unused inference configs --- .../sgm-forecaster-global_trimedge.yaml | 53 ----------- .../configs/sgm-forecaster-regional.yaml | 31 ------- .../sgm-forecaster-regional_fromtraining.yaml | 30 ------- .../sgm-forecaster-regional_trimedge.yaml | 47 ---------- ...interpolator-global_trimedge_fromtest.yaml | 58 ------------ .../sgm-interpolator-regional_trimedge.yaml | 89 ------------------- 6 files changed, 308 deletions(-) delete mode 100644 resources/inference/configs/sgm-forecaster-global_trimedge.yaml delete mode 100644 resources/inference/configs/sgm-forecaster-regional.yaml delete mode 100644 resources/inference/configs/sgm-forecaster-regional_fromtraining.yaml delete mode 100644 resources/inference/configs/sgm-forecaster-regional_trimedge.yaml delete mode 100644 resources/inference/configs/sgm-interpolator-global_trimedge_fromtest.yaml delete mode 100644 resources/inference/configs/sgm-interpolator-regional_trimedge.yaml diff --git a/resources/inference/configs/sgm-forecaster-global_trimedge.yaml b/resources/inference/configs/sgm-forecaster-global_trimedge.yaml deleted file mode 100644 index 539d202c..00000000 --- a/resources/inference/configs/sgm-forecaster-global_trimedge.yaml +++ /dev/null @@ -1,53 +0,0 @@ -write_initial_state: true -allow_nans: true - -patch_metadata: - dataset: - constant_fields: [z, lsm] - -input: - test: - use_original_paths: true - -constant_forcings: - test: - use_original_paths: true - -post_processors: - - accumulate_from_start_of_forecast: # accumulate tp from start of forecast - accumulations: - - tp - - forward_transform_filter: - rescale: - scale: 1000 # convert units from m to kg m-2 - offset: 0 - param: tp - -output: - tee: - - grib: - path: grib/{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_cosmo.yaml - post_processors: - - extract_mask: # removes global points - mask: "lam_0/cutout_mask" - as_slice: true - - assign_mask: # fill boundary "trimmed" points with nan - mask: "source0/trimedge_mask" - - - grib: - path: grib/ifs-{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_ifs.yaml - post_processors: - - extract_mask: # removes lam points - mask: "lam_0/cutout_mask" - as_slice: true - inverse: true - - assign_mask: # fill local/global overlapping points with nan - mask: "global/cutout_mask" diff --git a/resources/inference/configs/sgm-forecaster-regional.yaml b/resources/inference/configs/sgm-forecaster-regional.yaml deleted file mode 100644 index dfd907f2..00000000 --- a/resources/inference/configs/sgm-forecaster-regional.yaml +++ /dev/null @@ -1,31 +0,0 @@ -input: - test: - use_original_paths: true - -allow_nans: true - - -post_processors: - - accumulate_from_start_of_forecast: # accumulate tp from start of forecast - accumulations: - - tp - - forward_transform_filter: - rescale: - scale: 1000 # convert units from m to kg m-2 - offset: 0 - param: tp - -output: - tee: - outputs: - - extract_lam: - output: - grib: - path: grib/{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_cosmo.yaml - - printer - -write_initial_state: true diff --git a/resources/inference/configs/sgm-forecaster-regional_fromtraining.yaml b/resources/inference/configs/sgm-forecaster-regional_fromtraining.yaml deleted file mode 100644 index 203d74ff..00000000 --- a/resources/inference/configs/sgm-forecaster-regional_fromtraining.yaml +++ /dev/null @@ -1,30 +0,0 @@ -input: - training: - use_original_paths: true - -allow_nans: true - - -post_processors: - - accumulate_from_start_of_forecast: # accumulate tp from start of forecast - accumulations: - - tp - - forward_transform_filter: - rescale: - scale: 1000 # convert units from m to kg m-2 - offset: 0 - param: tp - -output: - grib: - path: grib/{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_cosmo.yaml - post_processors: - - extract_mask: # removes global points - mask: "source0/cutout_mask" - as_slice: true - -write_initial_state: true diff --git a/resources/inference/configs/sgm-forecaster-regional_trimedge.yaml b/resources/inference/configs/sgm-forecaster-regional_trimedge.yaml deleted file mode 100644 index 2b50eece..00000000 --- a/resources/inference/configs/sgm-forecaster-regional_trimedge.yaml +++ /dev/null @@ -1,47 +0,0 @@ -input: - test: - use_original_paths: true - -allow_nans: true - -post_processors: - - accumulate_from_start_of_forecast: # accumulate tp from start of forecast - accumulations: - - tp - - forward_transform_filter: - rescale: - scale: 1000 # convert units from m to kg m-2 - offset: 0 - param: tp - -output: - grib: - path: grib/{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_cosmo.yaml - post_processors: - - extract_mask: # removes global points - mask: "source0/cutout_mask" - as_slice: true - - assign_mask: # fill boundary "trimmed" points with nan - mask: "source0/trimedge_mask" - - accumulate_from_start_of_forecast: # accumulate tp from start of forecast - accumulations: - - tp - - forward_transform_filter: - rescale: - scale: 1000 # convert units from m to kg m-2 - offset: 0 - param: tp - -constant_forcings: - test: - use_original_paths: true - -patch_metadata: - dataset: - constant_fields: [z, lsm] - -write_initial_state: true diff --git a/resources/inference/configs/sgm-interpolator-global_trimedge_fromtest.yaml b/resources/inference/configs/sgm-interpolator-global_trimedge_fromtest.yaml deleted file mode 100644 index 557cf87f..00000000 --- a/resources/inference/configs/sgm-interpolator-global_trimedge_fromtest.yaml +++ /dev/null @@ -1,58 +0,0 @@ -runner: time_interpolator - -input: - test: - use_original_paths: true - cutout: - - lam_0: - grib: - pre_processors: - - forward_transform_filter: - rescale: - scale: 0.001 # convert from kg m-2 to m - offset: 0 - param: tp - - -post_processors: - - accumulate_from_start_of_forecast: # accumulate tp from start of forecast - accumulations: - - tp - - forward_transform_filter: - rescale: - scale: 1000 # convert units from m to kg m-2 - offset: 0 - param: tp - -output: - tee: - - grib: - path: grib/{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_cosmo.yaml - post_processors: - - extract_mask: # removes global points - mask: "lam_0/cutout_mask" - as_slice: true - - assign_mask: # fill boundary "trimmed" points with nan - mask: "source0/trimedge_mask" - - - grib: - path: grib/ifs-{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_ifs.yaml - post_processors: - - extract_mask: # removes lam points - mask: "lam_0/cutout_mask" - as_slice: true - inverse: true - - assign_mask: # fill local/global overlapping points with nan - mask: "global/cutout_mask" - -verbosity: 1 -allow_nans: true -output_frequency: "1h" diff --git a/resources/inference/configs/sgm-interpolator-regional_trimedge.yaml b/resources/inference/configs/sgm-interpolator-regional_trimedge.yaml deleted file mode 100644 index 74b48bb5..00000000 --- a/resources/inference/configs/sgm-interpolator-regional_trimedge.yaml +++ /dev/null @@ -1,89 +0,0 @@ -runner: time_interpolator -allow_nans: true - -output_frequency: "1h" - -patch_metadata: - dataset: - constant_fields: [z, lsm] - -input: - cutout: - - lam_0: - grib: - pre_processors: - - extract_mask: "source0/trimedge_mask" - - forward_transform_filter: - rescale: - scale: 0.001 # convert from kg m-2 to m - offset: 0 - param: tp - - path: forecaster/20* - namer: &namer - rules: - - - shortName: T - - t_{level} - - - shortName: U - - u_{level} - - - shortName: V - - v_{level} - - - shortName: W - - w_{level} - - - shortName: QV - - q_{level} - - - shortName: FI - - z_{level} - - - shortName: PMSL - - msl - - - shortName: FIS - - z - - - shortName: PS - - sp - - - shortName: T_2M - - 2t - - - shortName: TD_2M - - 2d - - - shortName: T_G - - skt - - - shortName: U_10M - - 10u - - - shortName: V_10M - - 10v - - - shortName: FR_LAND - - lsm - - - shortName: TOT_PREC - - tp - - global: - grib: - path: forecaster/ifs* - namer: *namer - -constant_forcings: - test: - use_original_paths: true - - -post_processors: - - accumulate_from_start_of_forecast: # accumulate tp from start of forecast - accumulations: - - tp - - forward_transform_filter: - rescale: - scale: 1000 # convert units from m to kg m-2 - offset: 0 - param: tp - -output: - grib: - path: grib/{dateTime}_{step:03}.grib - encoding: - typeOfGeneratingProcess: 2 - templates: - samples: resources/templates_index_cosmo.yaml - post_processors: - - extract_mask: # removes global points - mask: "lam_0/cutout_mask" - as_slice: true - - assign_mask: # fill boundary "trimmed" points with nan - mask: "source0/trimedge_mask" From 563d695cf60c6a358b73872ba5a269d9057d2a7a Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 17:23:34 +0200 Subject: [PATCH 09/23] update configs with patches --- .../sgm-forecaster-global-disentangled.yaml | 30 +++++++++++++++++++ .../sgm-forecaster-global-ich1-oper.yaml | 4 +++ .../configs/sgm-forecaster-global-ich1.yaml | 30 +++++++++++++++++++ .../configs/sgm-forecaster-global.yaml | 30 +++++++++++++++++++ .../sgm-interpolator-global_trimedge.yaml | 30 +++++++++++++++++++ ...gm-interpolator-global_trimedge_multi.yaml | 30 +++++++++++++++++++ ...tidataset-forecaster-global-ich1-oper.yaml | 30 +++++++++++++++++++ 7 files changed, 184 insertions(+) diff --git a/resources/inference/configs/sgm-forecaster-global-disentangled.yaml b/resources/inference/configs/sgm-forecaster-global-disentangled.yaml index 72956088..c2bc62ca 100644 --- a/resources/inference/configs/sgm-forecaster-global-disentangled.yaml +++ b/resources/inference/configs/sgm-forecaster-global-disentangled.yaml @@ -41,5 +41,35 @@ output: inverse: true - assign_mask: # fill local/global overlapping points with nan mask: "global/cutout_mask" + modifiers: + - patches: + - variable: + U_10M: {"param": 165, "shortName": "10u"} + 10u: {"param": 165, "shortName": "10u"} + V_10M: {"param": 166, "shortName": "10v"} + 10v: {"param": 166, "shortName": "10v"} + TD_2M: {"param": 167, "shortName": "2d"} + 2d: {"param": 168, "shortName": "2d"} + T_2M: {"param": 167, "shortName": "2t"} + 2t: {"param": 167, "shortName": "2t"} + FR_LAND: {"param": 172, "shortName": "lsm"} + lsm: {"param": 172, "shortName": "lsm"} + PMSL: {"param": 151, "shortName": "msl"} + msl: {"param": 151, "shortName": "msl"} + PS: {"param": 134, "shortName": "sp"} + sp: {"param": 134, "shortName": "sp"} + SSO_SIGMA: {"param": 163, "shortName": "slor"} + slor: {"param": 163, "shortName": "slor"} + SSO_STDH: {"param": 160, "shortName": "sdor"} + sdor: {"param": 160, "shortName": "sdor"} + TOT_PREC: {"param": 228, "shortName": "tp"} + tp: {"param": 228, "shortName": "tp"} + z: {"param": 129, "shortName": "z"} + "^q_(\\d+)$": {"param": 133, "shortName": "q"} + "^t_(\\d+)$": {"param": 130, "shortName": "t"} + "^u_(\\d+)$": {"param": 131, "shortName": "u"} + "^v_(\\d+)$": {"param": 132, "shortName": "v"} + "^w_(\\d+)$": {"param": 135, "shortName": "w"} + "^z_(\\d+)$": {"param": 129, "shortName": "z"} write_initial_state: true diff --git a/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml b/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml index bbf1e63e..ba3a3478 100644 --- a/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml +++ b/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml @@ -56,6 +56,10 @@ output: msl: {"param": 151, "shortName": "msl"} PS: {"param": 134, "shortName": "sp"} sp: {"param": 134, "shortName": "sp"} + SSO_SIGMA: {"param": 163, "shortName": "slor"} + slor: {"param": 163, "shortName": "slor"} + SSO_STDH: {"param": 160, "shortName": "sdor"} + sdor: {"param": 160, "shortName": "sdor"} TOT_PREC: {"param": 228, "shortName": "tp"} tp: {"param": 228, "shortName": "tp"} z: {"param": 129, "shortName": "z"} diff --git a/resources/inference/configs/sgm-forecaster-global-ich1.yaml b/resources/inference/configs/sgm-forecaster-global-ich1.yaml index 73fde873..890e8833 100644 --- a/resources/inference/configs/sgm-forecaster-global-ich1.yaml +++ b/resources/inference/configs/sgm-forecaster-global-ich1.yaml @@ -46,5 +46,35 @@ output: inverse: true - assign_mask: # fill local/global overlapping points with nan mask: "global/cutout_mask" + modifiers: + - patches: + - variable: + U_10M: {"param": 165, "shortName": "10u"} + 10u: {"param": 165, "shortName": "10u"} + V_10M: {"param": 166, "shortName": "10v"} + 10v: {"param": 166, "shortName": "10v"} + TD_2M: {"param": 167, "shortName": "2d"} + 2d: {"param": 168, "shortName": "2d"} + T_2M: {"param": 167, "shortName": "2t"} + 2t: {"param": 167, "shortName": "2t"} + FR_LAND: {"param": 172, "shortName": "lsm"} + lsm: {"param": 172, "shortName": "lsm"} + PMSL: {"param": 151, "shortName": "msl"} + msl: {"param": 151, "shortName": "msl"} + PS: {"param": 134, "shortName": "sp"} + sp: {"param": 134, "shortName": "sp"} + SSO_SIGMA: {"param": 163, "shortName": "slor"} + slor: {"param": 163, "shortName": "slor"} + SSO_STDH: {"param": 160, "shortName": "sdor"} + sdor: {"param": 160, "shortName": "sdor"} + TOT_PREC: {"param": 228, "shortName": "tp"} + tp: {"param": 228, "shortName": "tp"} + z: {"param": 129, "shortName": "z"} + "^q_(\\d+)$": {"param": 133, "shortName": "q"} + "^t_(\\d+)$": {"param": 130, "shortName": "t"} + "^u_(\\d+)$": {"param": 131, "shortName": "u"} + "^v_(\\d+)$": {"param": 132, "shortName": "v"} + "^w_(\\d+)$": {"param": 135, "shortName": "w"} + "^z_(\\d+)$": {"param": 129, "shortName": "z"} patch_metadata: resources/sgm-ich1-patch_metadata.yaml diff --git a/resources/inference/configs/sgm-forecaster-global.yaml b/resources/inference/configs/sgm-forecaster-global.yaml index fdc280b0..ca4f4693 100644 --- a/resources/inference/configs/sgm-forecaster-global.yaml +++ b/resources/inference/configs/sgm-forecaster-global.yaml @@ -39,5 +39,35 @@ output: inverse: true - assign_mask: # fill local/global overlapping points with nan mask: "global/cutout_mask" + modifiers: + - patches: + - variable: + U_10M: {"param": 165, "shortName": "10u"} + 10u: {"param": 165, "shortName": "10u"} + V_10M: {"param": 166, "shortName": "10v"} + 10v: {"param": 166, "shortName": "10v"} + TD_2M: {"param": 167, "shortName": "2d"} + 2d: {"param": 168, "shortName": "2d"} + T_2M: {"param": 167, "shortName": "2t"} + 2t: {"param": 167, "shortName": "2t"} + FR_LAND: {"param": 172, "shortName": "lsm"} + lsm: {"param": 172, "shortName": "lsm"} + PMSL: {"param": 151, "shortName": "msl"} + msl: {"param": 151, "shortName": "msl"} + PS: {"param": 134, "shortName": "sp"} + sp: {"param": 134, "shortName": "sp"} + SSO_SIGMA: {"param": 163, "shortName": "slor"} + slor: {"param": 163, "shortName": "slor"} + SSO_STDH: {"param": 160, "shortName": "sdor"} + sdor: {"param": 160, "shortName": "sdor"} + TOT_PREC: {"param": 228, "shortName": "tp"} + tp: {"param": 228, "shortName": "tp"} + z: {"param": 129, "shortName": "z"} + "^q_(\\d+)$": {"param": 133, "shortName": "q"} + "^t_(\\d+)$": {"param": 130, "shortName": "t"} + "^u_(\\d+)$": {"param": 131, "shortName": "u"} + "^v_(\\d+)$": {"param": 132, "shortName": "v"} + "^w_(\\d+)$": {"param": 135, "shortName": "w"} + "^z_(\\d+)$": {"param": 129, "shortName": "z"} write_initial_state: true diff --git a/resources/inference/configs/sgm-interpolator-global_trimedge.yaml b/resources/inference/configs/sgm-interpolator-global_trimedge.yaml index 589af1cb..771a6ae9 100644 --- a/resources/inference/configs/sgm-interpolator-global_trimedge.yaml +++ b/resources/inference/configs/sgm-interpolator-global_trimedge.yaml @@ -97,6 +97,36 @@ output: inverse: true - assign_mask: # fill local/global overlapping points with nan mask: "global/cutout_mask" + modifiers: + - patches: + - variable: + U_10M: {"param": 165, "shortName": "10u"} + 10u: {"param": 165, "shortName": "10u"} + V_10M: {"param": 166, "shortName": "10v"} + 10v: {"param": 166, "shortName": "10v"} + TD_2M: {"param": 167, "shortName": "2d"} + 2d: {"param": 168, "shortName": "2d"} + T_2M: {"param": 167, "shortName": "2t"} + 2t: {"param": 167, "shortName": "2t"} + FR_LAND: {"param": 172, "shortName": "lsm"} + lsm: {"param": 172, "shortName": "lsm"} + PMSL: {"param": 151, "shortName": "msl"} + msl: {"param": 151, "shortName": "msl"} + PS: {"param": 134, "shortName": "sp"} + sp: {"param": 134, "shortName": "sp"} + SSO_SIGMA: {"param": 163, "shortName": "slor"} + slor: {"param": 163, "shortName": "slor"} + SSO_STDH: {"param": 160, "shortName": "sdor"} + sdor: {"param": 160, "shortName": "sdor"} + TOT_PREC: {"param": 228, "shortName": "tp"} + tp: {"param": 228, "shortName": "tp"} + z: {"param": 129, "shortName": "z"} + "^q_(\\d+)$": {"param": 133, "shortName": "q"} + "^t_(\\d+)$": {"param": 130, "shortName": "t"} + "^u_(\\d+)$": {"param": 131, "shortName": "u"} + "^v_(\\d+)$": {"param": 132, "shortName": "v"} + "^w_(\\d+)$": {"param": 135, "shortName": "w"} + "^z_(\\d+)$": {"param": 129, "shortName": "z"} verbosity: 1 allow_nans: true diff --git a/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml b/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml index 9274e691..17f524d6 100644 --- a/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml +++ b/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml @@ -94,6 +94,36 @@ output: inverse: true - assign_mask: # fill local/global overlapping points with nan mask: "global/cutout_mask" + modifiers: + - patches: + - variable: + U_10M: {"param": 165, "shortName": "10u"} + 10u: {"param": 165, "shortName": "10u"} + V_10M: {"param": 166, "shortName": "10v"} + 10v: {"param": 166, "shortName": "10v"} + TD_2M: {"param": 167, "shortName": "2d"} + 2d: {"param": 168, "shortName": "2d"} + T_2M: {"param": 167, "shortName": "2t"} + 2t: {"param": 167, "shortName": "2t"} + FR_LAND: {"param": 172, "shortName": "lsm"} + lsm: {"param": 172, "shortName": "lsm"} + PMSL: {"param": 151, "shortName": "msl"} + msl: {"param": 151, "shortName": "msl"} + PS: {"param": 134, "shortName": "sp"} + sp: {"param": 134, "shortName": "sp"} + SSO_SIGMA: {"param": 163, "shortName": "slor"} + slor: {"param": 163, "shortName": "slor"} + SSO_STDH: {"param": 160, "shortName": "sdor"} + sdor: {"param": 160, "shortName": "sdor"} + TOT_PREC: {"param": 228, "shortName": "tp"} + tp: {"param": 228, "shortName": "tp"} + z: {"param": 129, "shortName": "z"} + "^q_(\\d+)$": {"param": 133, "shortName": "q"} + "^t_(\\d+)$": {"param": 130, "shortName": "t"} + "^u_(\\d+)$": {"param": 131, "shortName": "u"} + "^v_(\\d+)$": {"param": 132, "shortName": "v"} + "^w_(\\d+)$": {"param": 135, "shortName": "w"} + "^z_(\\d+)$": {"param": 129, "shortName": "z"} # silenced due to bug in anemoi-inference for multi-step interpolators, can be removed when fixed verbosity: 0 diff --git a/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml b/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml index 12213293..dc2dd07c 100644 --- a/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml +++ b/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml @@ -47,5 +47,35 @@ output: inverse: true - assign_mask: # fill local/global overlapping points with nan mask: "global/cutout_mask" + modifiers: + - patches: + - variable: + U_10M: {"param": 165, "shortName": "10u"} + 10u: {"param": 165, "shortName": "10u"} + V_10M: {"param": 166, "shortName": "10v"} + 10v: {"param": 166, "shortName": "10v"} + TD_2M: {"param": 167, "shortName": "2d"} + 2d: {"param": 168, "shortName": "2d"} + T_2M: {"param": 167, "shortName": "2t"} + 2t: {"param": 167, "shortName": "2t"} + FR_LAND: {"param": 172, "shortName": "lsm"} + lsm: {"param": 172, "shortName": "lsm"} + PMSL: {"param": 151, "shortName": "msl"} + msl: {"param": 151, "shortName": "msl"} + PS: {"param": 134, "shortName": "sp"} + sp: {"param": 134, "shortName": "sp"} + SSO_SIGMA: {"param": 163, "shortName": "slor"} + slor: {"param": 163, "shortName": "slor"} + SSO_STDH: {"param": 160, "shortName": "sdor"} + sdor: {"param": 160, "shortName": "sdor"} + TOT_PREC: {"param": 228, "shortName": "tp"} + tp: {"param": 228, "shortName": "tp"} + z: {"param": 129, "shortName": "z"} + "^q_(\\d+)$": {"param": 133, "shortName": "q"} + "^t_(\\d+)$": {"param": 130, "shortName": "t"} + "^u_(\\d+)$": {"param": 131, "shortName": "u"} + "^v_(\\d+)$": {"param": 132, "shortName": "v"} + "^w_(\\d+)$": {"param": 135, "shortName": "w"} + "^z_(\\d+)$": {"param": 129, "shortName": "z"} patch_metadata: resources/sgm-multidataset-ich1-oper-patch.yaml From ad54000f3c5479027b40bd4f482c7412ad791703 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Tue, 26 May 2026 18:03:15 +0200 Subject: [PATCH 10/23] standardize lat/lon coordinate names to latitude/longitude --- src/data_input/__init__.py | 6 +++--- src/verification/spatial.py | 18 ++++++++++-------- tests/unit/test_spatial_mapping.py | 26 +++++++++++++------------- 3 files changed, 26 insertions(+), 24 deletions(-) diff --git a/src/data_input/__init__.py b/src/data_input/__init__.py index 12615aba..bd2b13d2 100644 --- a/src/data_input/__init__.py +++ b/src/data_input/__init__.py @@ -395,7 +395,7 @@ def load_INCA_baseline_from_netcdf( Returns: xr.Dataset with dimensions (step, y, x) and coordinates: x, y – Swiss CH1903 (EPSG:21781) easting/northing [m] - lat, lon – WGS84 latitude/longitude [°], shape (y, x), + latitude, longitude – WGS84 latitude/longitude [°], shape (y, x), derived from CH1903 via pyproj step – forecast lead time (timedelta64[ns]) valid_time – absolute timestamps (datetime64[ns]) @@ -413,12 +413,12 @@ def _chxy_to_latlon(x_1d, y_1d) -> dict: "EPSG:21781", "EPSG:4326", always_xy=True ).transform(x_2d, y_2d) return { - "lat": ( + "latitude": ( ("y", "x"), lat_2d, {"units": "degrees_north", "long_name": "latitude"}, ), - "lon": ( + "longitude": ( ("y", "x"), lon_2d, {"units": "degrees_east", "long_name": "longitude"}, diff --git a/src/verification/spatial.py b/src/verification/spatial.py index 347521a1..aacd8d93 100644 --- a/src/verification/spatial.py +++ b/src/verification/spatial.py @@ -82,12 +82,14 @@ def nearest_grid_yx_indices( """ if "latitude" not in grid or "longitude" not in grid: - raise ValueError("Input must provide 'lat' and 'lon' coordinates") + raise ValueError("Input must provide 'latitude' and 'longitude' coordinates") lat2d = np.asarray(grid["latitude"].values) lon2d = np.asarray(grid["longitude"].values) if lat2d.ndim != 2 or lon2d.ndim != 2: - raise ValueError("'lat' and 'lon' must be 2D on (y, x) for y/x indexing") + raise ValueError( + "'latitude' and 'longitude' must be 2D on (y, x) for y/x indexing" + ) flat_idx = spherical_nearest_neighbor_indices( source_lat=lat2d.ravel(), @@ -110,11 +112,11 @@ def map_forecast_to_truth(fcst: xr.Dataset, truth: xr.Dataset) -> xr.Dataset: Parameters ---------- fcst - Forecast dataset with `lat` and `lon` coordinates on either `(y, x)` or - `values`. + Forecast dataset with `latitude` and `longitude` coordinates on either + `(y, x)` or `values`. truth - Reference dataset with `lat` and `lon` coordinates on either `(y, x)` or - `values`. + Reference dataset with `latitude` and `longitude` coordinates on either + `(y, x)` or `values`. Returns ------- @@ -139,8 +141,8 @@ def map_forecast_to_truth(fcst: xr.Dataset, truth: xr.Dataset) -> xr.Dataset: fcst = fcst.isel(values=nearest_idx) fcst = fcst.drop_vars(["x", "y", "values"], errors="ignore") - fcst = fcst.assign_coords(lon=("values", truth["longitude"].data)) - fcst = fcst.assign_coords(lat=("values", truth["latitude"].data)) + fcst = fcst.assign_coords(longitude=("values", truth["longitude"].data)) + fcst = fcst.assign_coords(latitude=("values", truth["latitude"].data)) fcst = fcst.assign_coords(values=truth["values"]) if truth_is_grid: diff --git a/tests/unit/test_spatial_mapping.py b/tests/unit/test_spatial_mapping.py index 73d56954..23f8d2e4 100644 --- a/tests/unit/test_spatial_mapping.py +++ b/tests/unit/test_spatial_mapping.py @@ -27,7 +27,7 @@ def test_spherical_nearest_neighbor_indices_returns_expected_points(): def test_nearest_grid_yx_indices_returns_grid_indices(): lat = xr.DataArray([[46.0, 46.0], [47.0, 47.0]], dims=("y", "x")) lon = xr.DataArray([[7.0, 8.0], [7.0, 8.0]], dims=("y", "x")) - grid = xr.Dataset(coords={"lat": lat, "lon": lon}) + grid = xr.Dataset(coords={"latitude": lat, "longitude": lon}) y_idx, x_idx = nearest_grid_yx_indices( grid=grid, @@ -64,8 +64,8 @@ def test_map_forecast_to_truth_maps_forecast_to_truth_locations(): "time": fcst_time, "y": [0, 1], "x": [0, 1], - "lat": (("y", "x"), np.array([[46.0, 46.0], [47.0, 47.0]])), - "lon": (("y", "x"), np.array([[7.0, 8.0], [7.0, 8.0]])), + "latitude": (("y", "x"), np.array([[46.0, 46.0], [47.0, 47.0]])), + "longitude": (("y", "x"), np.array([[7.0, 8.0], [7.0, 8.0]])), }, ) truth = xr.Dataset( @@ -73,8 +73,8 @@ def test_map_forecast_to_truth_maps_forecast_to_truth_locations(): coords={ "time": truth_time, "values": ["STA1", "STA2"], - "lat": ("values", np.array([46.1, 46.9])), - "lon": ("values", np.array([7.1, 7.9])), + "latitude": ("values", np.array([46.1, 46.9])), + "longitude": ("values", np.array([7.1, 7.9])), }, ) @@ -83,8 +83,8 @@ def test_map_forecast_to_truth_maps_forecast_to_truth_locations(): assert mapped_fcst["T_2M"].dims == ("time", "values") assert np.array_equal(mapped_fcst["time"].values, fcst_time) assert np.array_equal(mapped_fcst["values"].values, np.array(["STA1", "STA2"])) - assert np.allclose(mapped_fcst["lat"].values, np.array([46.1, 46.9])) - assert np.allclose(mapped_fcst["lon"].values, np.array([7.1, 7.9])) + assert np.allclose(mapped_fcst["latitude"].values, np.array([46.1, 46.9])) + assert np.allclose(mapped_fcst["longitude"].values, np.array([7.1, 7.9])) assert np.allclose( mapped_fcst["T_2M"].values, np.array([[1.0, 4.0], [10.0, 40.0]]), @@ -105,8 +105,8 @@ def test_map_forecast_to_truth_restores_grid_when_truth_is_gridded(): "time": fcst_time, "y": [0, 1], "x": [0, 1], - "lat": (("y", "x"), np.array([[46.0, 46.0], [47.0, 47.0]])), - "lon": (("y", "x"), np.array([[7.0, 8.0], [7.0, 8.0]])), + "latitude": (("y", "x"), np.array([[46.0, 46.0], [47.0, 47.0]])), + "longitude": (("y", "x"), np.array([[7.0, 8.0], [7.0, 8.0]])), }, ) truth = xr.Dataset( @@ -115,8 +115,8 @@ def test_map_forecast_to_truth_restores_grid_when_truth_is_gridded(): "time": fcst_time, "y": [0, 1], "x": [0, 1], - "lat": (("y", "x"), np.array([[46.1, 46.1], [46.9, 46.9]])), - "lon": (("y", "x"), np.array([[7.1, 7.9], [7.1, 7.9]])), + "latitude": (("y", "x"), np.array([[46.1, 46.1], [46.9, 46.9]])), + "longitude": (("y", "x"), np.array([[7.1, 7.9], [7.1, 7.9]])), }, ) @@ -125,8 +125,8 @@ def test_map_forecast_to_truth_restores_grid_when_truth_is_gridded(): assert mapped_fcst["T_2M"].dims == ("time", "y", "x") assert np.array_equal(mapped_fcst["y"].values, np.array([0, 1])) assert np.array_equal(mapped_fcst["x"].values, np.array([0, 1])) - assert np.allclose(mapped_fcst["lat"].values, truth["lat"].values) - assert np.allclose(mapped_fcst["lon"].values, truth["lon"].values) + assert np.allclose(mapped_fcst["latitude"].values, truth["latitude"].values) + assert np.allclose(mapped_fcst["longitude"].values, truth["longitude"].values) assert np.allclose( mapped_fcst["T_2M"].values, np.array([[[1.0, 2.0], [3.0, 4.0]]]), From 966364845be23478c95abd53c840226e9cd6b0c1 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Wed, 27 May 2026 10:19:10 +0200 Subject: [PATCH 11/23] rename lead time dimension --- resources/report/dashboard/script.js | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/resources/report/dashboard/script.js b/resources/report/dashboard/script.js index 0934b4eb..238164a1 100644 --- a/resources/report/dashboard/script.js +++ b/resources/report/dashboard/script.js @@ -96,7 +96,7 @@ function makeCellSpec(cellData) { height: 160, encoding: { x: { - field: "lead_time", + field: "step", type: "quantitative", title: "Lead time (h)", }, @@ -125,7 +125,7 @@ function makeCellSpec(cellData) { tooltip: [ { field: "source", type: "nominal", title: "Source" }, { field: "region_season_init",type: "nominal", title: "Region/Season/Init" }, - { field: "lead_time", type: "quantitative", title: "Lead time (h)" }, + { field: "step", type: "quantitative", title: "Lead time (h)" }, { field: "value", type: "quantitative", title: "Value", format: ".4f" }, ], }, From f3d033e197cc93ee4824dc3b720bddc3d06b63d3 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Wed, 27 May 2026 11:39:15 +0200 Subject: [PATCH 12/23] update config --- config/forecasters-ich1-oper-fixed.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/config/forecasters-ich1-oper-fixed.yaml b/config/forecasters-ich1-oper-fixed.yaml index 30e2fe13..b6e13fc6 100644 --- a/config/forecasters-ich1-oper-fixed.yaml +++ b/config/forecasters-ich1-oper-fixed.yaml @@ -19,7 +19,7 @@ runs: steps: 0/120/6 config: resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml extra_requirements: - - git+https://github.com/ecmwf/anemoi-inference.git@b9aaee5df86614cad9d8d08b76876a4be4e980db + - git+https://github.com/ecmwf/anemoi-inference.git@main # - forecaster: # checkpoint: https://service.meteoswiss.ch/mlstore#/experiments/602/runs/233b1274e79b4bfea98378d196a8aba0 From b5014ed974aa0b582fa90850c99ed88cb6f125bd Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Thu, 28 May 2026 09:35:45 +0200 Subject: [PATCH 13/23] bugfix, use grib store --- workflow/rules/plot.smk | 20 +++++++++----------- 1 file changed, 9 insertions(+), 11 deletions(-) diff --git a/workflow/rules/plot.smk b/workflow/rules/plot.smk index 5b6a9fd8..c95deac2 100644 --- a/workflow/rules/plot.smk +++ b/workflow/rules/plot.smk @@ -10,18 +10,16 @@ import pandas as pd def _get_available_baselines(wc) -> list[dict[str, str]]: - """Get all available baseline zarr datasets for the given init time.""" + """Get all available baseline datasets for the given init time.""" baselines = [] for baseline_id in BASELINE_CONFIGS: root = BASELINE_CONFIGS[baseline_id].get("root") steps = BASELINE_CONFIGS[baseline_id].get("steps") label = BASELINE_CONFIGS[baseline_id].get("label", baseline_id) - year = wc.init_time[2:4] - baseline_zarr = f"{root}/FCST{year}.zarr" - if Path(baseline_zarr).exists(): - baselines.append({"zarr": baseline_zarr, "steps": steps, "label": label}) + if root and Path(root).exists(): + baselines.append({"root": root, "steps": steps, "label": label}) if not baselines: - raise ValueError(f"No baseline zarr found for init time {wc.init_time}") + raise ValueError(f"No baseline data found for init time {wc.init_time}") return baselines @@ -46,7 +44,7 @@ rule plot_meteogram: ).resolve(), fcst_steps=lambda wc: RUN_CONFIGS[wc.run_id]["steps"], fcst_label=lambda wc: RUN_CONFIGS[wc.run_id]["label"], - baseline_zarrs=lambda wc: [x["zarr"] for x in _get_available_baselines(wc)], + baseline_roots=lambda wc: [x["root"] for x in _get_available_baselines(wc)], baseline_steps=lambda wc: [x["steps"] for x in _get_available_baselines(wc)], baseline_labels=lambda wc: [x["label"] for x in _get_available_baselines(wc)], shell: @@ -54,7 +52,7 @@ rule plot_meteogram: set -euo pipefail export ECCODES_DEFINITION_PATH=$(realpath .venv/share/eccodes-cosmo-resources/definitions) - BASELINE_ZARRS=({params.baseline_zarrs:q}) + BASELINE_ROOTS=({params.baseline_roots:q}) BASELINE_STEPS=({params.baseline_steps:q}) BASELINE_LABELS=({params.baseline_labels:q}) @@ -71,8 +69,8 @@ rule plot_meteogram: --station {wildcards.sta:q} ) - for i in "${{!BASELINE_ZARRS[@]}}"; do - CMD_ARGS+=(--baseline "${{BASELINE_ZARRS[$i]}}") + for i in "${{!BASELINE_ROOTS[@]}}"; do + CMD_ARGS+=(--baseline "${{BASELINE_ROOTS[$i]}}") CMD_ARGS+=(--baseline_steps "${{BASELINE_STEPS[$i]}}") CMD_ARGS+=(--baseline_label "${{BASELINE_LABELS[$i]}}") done @@ -132,7 +130,7 @@ def get_leadtimes(wc): # skip lead time 0 for diagnostic variables if wc.param in ["tp", "TOT_PREC"]: # TODO: make this more general start += step - return [f"{i:03}" for i in range(start, end + 1, step)] + return [f"{i}" for i in range(start, end + 1, step)] rule make_forecast_animation: From b0d0818ab446844d1248c18dd2b67bdbaf79a142 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Thu, 28 May 2026 09:36:52 +0200 Subject: [PATCH 14/23] update showcase code --- src/plotting/__init__.py | 8 +- src/plotting/colormap_loader.py | 10 +-- src/plotting/compat.py | 96 ++++++++++++---------- workflow/scripts/plot_forecast_frame.mo.py | 6 +- workflow/scripts/plot_meteogram.mo.py | 10 +-- 5 files changed, 63 insertions(+), 67 deletions(-) diff --git a/src/plotting/__init__.py b/src/plotting/__init__.py index 810468ad..a60d2dc7 100644 --- a/src/plotting/__init__.py +++ b/src/plotting/__init__.py @@ -119,15 +119,9 @@ def init_geoaxes( "bbox must be a list of four floats [lon_min, lon_max, lat_min, lat_max]" ) - domain = ( - ekp.geo.domains.Domain(bbox=bbox, crs=ccrs.PlateCarree(), name=name.title()) - if bbox is not None - else None - ) - ekp_fig = ekp.Figure( crs=projection, - domain=domain, + domain=bbox, rows=nrows, columns=ncols, size=size, diff --git a/src/plotting/colormap_loader.py b/src/plotting/colormap_loader.py index 348f472c..11bd3a22 100644 --- a/src/plotting/colormap_loader.py +++ b/src/plotting/colormap_loader.py @@ -1,6 +1,6 @@ import pathlib import numpy as np -from matplotlib.colors import ListedColormap, BoundaryNorm +from matplotlib.colors import BoundaryNorm # Base directory for colormap files BASE_DIR = ( @@ -50,10 +50,6 @@ def load_ncl_colormap(filename): if len(rgb) != n_levs + 1: raise ValueError(f"Expected {n_levs} RGB rows, got {len(rgb)}.") - # Create colormap and norm - cmap = ListedColormap(colors=rgb[1:-1], name=pathlib.Path(filename).stem) - cmap.set_under(rgb[0]) - cmap.set_over(rgb[-1]) - norm = BoundaryNorm(boundaries=bounds, ncolors=cmap.N) + norm = BoundaryNorm(boundaries=bounds, ncolors=len(rgb) - 1) - return {"cmap": cmap, "norm": norm, "bounds": bounds} + return {"cmap": rgb[1:-1], "norm": norm, "bounds": bounds} diff --git a/src/plotting/compat.py b/src/plotting/compat.py index 7c4d14d3..1d7866b7 100644 --- a/src/plotting/compat.py +++ b/src/plotting/compat.py @@ -1,22 +1,29 @@ from datetime import datetime from pathlib import Path -import earthkit.data as ekd import geopandas as gpd import numpy as np -import pandas as pd -from meteodatalab import data_source -from meteodatalab import grib_decoder from shapely.geometry import MultiPoint +from data_input import load_from_grib_file + + +PARAMS_MAP = { + "T_2M": "2t", + "TD_2M": "2d", + "U_10M": "10u", + "V_10M": "10v", + "PS": "sp", + "PMSL": "msl", + "TOT_PREC": "tp", +} + +PARAMS_MAP_INV = {v: k for k, v in PARAMS_MAP.items()} def load_state_from_grib( file: Path, paramlist: list[str] | None = None ) -> dict[str, np.ndarray | dict[str, np.ndarray] | gpd.GeoSeries]: - reftime = datetime.strptime(file.parents[1].name, "%Y%m%d%H%M") - lead_time_hours = int(file.stem.split("_")[-1]) - fds = data_source.FileDataSource(datafiles=[str(file)]) - ds = grib_decoder.load(fds, {"param": paramlist}) + ds = load_from_grib_file(file, {"parameter.variable": paramlist}) state = {} ref_param = next((p for p in (paramlist or []) if p in ds), None) if ref_param is None: @@ -25,14 +32,17 @@ def load_state_from_grib( "The GRIB file may not contain these fields at this lead time " "(e.g. accumulated fields like TOT_PREC are undefined at step 0)." ) - lats = ds[ref_param].lat.data.flatten() - lons = ds[ref_param].lon.data.flatten() - state["forecast_reference_time"] = reftime - state["valid_time"] = reftime + pd.to_timedelta(lead_time_hours, unit="h") - state["longitudes"] = lons - state["latitudes"] = lats + lons = ds["longitude"].values.flatten() + state["forecast_reference_time"] = datetime.fromtimestamp( + ds["forecast_reference_time"].values.item() / 1e9 + ) + state["valid_time"] = datetime.fromtimestamp(ds["valid_time"].values.item() / 1e9) + state["longitudes"] = ds["longitude"].values.flatten() + state["latitudes"] = ds["latitude"].values.flatten() # Add the limited-area model envelope polygon (convex hull) before global coords are added - lam_hull = MultiPoint(list(zip(lons.tolist(), lats.tolist()))).convex_hull + lam_hull = MultiPoint( + list(zip(lons.tolist(), state["latitudes"].tolist())) + ).convex_hull state["lam_envelope"] = gpd.GeoSeries([lam_hull], crs="EPSG:4326") state["fields"] = {} for param in paramlist or []: @@ -40,40 +50,36 @@ def load_state_from_grib( state["fields"][param] = ds[param].values.flatten() else: # initialize with NaNs to keep consistent length - state["fields"][param] = np.full(lats.size, np.nan, dtype=float) + state["fields"][param] = np.full( + ds["longitude"].values.size, np.nan, dtype=float + ) global_file = str(file.parent / f"ifs-{file.stem}.grib") if Path(global_file).exists(): - global_file = str(file.parent / f"ifs-{file.stem}.grib") - fds_global = ekd.from_source("file", global_file) - ds_global = { - u.metadata("param"): u.values - for u in fds_global - if u.metadata("param") in paramlist - } - # Use first key from ds_global instead of paramlist[0] - ref_key = next(iter(ds_global), None) - if ref_key is not None: - global_lats = fds_global.metadata("latitudes")[0] - global_lons = fds_global.metadata("longitudes")[0] - if max(global_lons) > 180: - global_lons = ((global_lons + 180) % 360) - 180 - mask = np.where(~np.isnan(ds_global[ref_key]))[0] - n_add = int(mask.size) - state["longitudes"] = np.concatenate( - [state["longitudes"], global_lons[mask]] - ) - state["latitudes"] = np.concatenate([state["latitudes"], global_lats[mask]]) - for param in paramlist or state["fields"].keys(): - add = ( - ds_global[param][mask] - if param in ds_global - else np.full(n_add, np.nan, dtype=float) + _paramlist_ecmwf = [PARAMS_MAP[p] for p in paramlist] + ds = load_from_grib_file(global_file, {"parameter.variable": _paramlist_ecmwf}) + mask = ~np.isnan(ds[_paramlist_ecmwf[0]].values.squeeze()) + global_lons = ds["longitude"].values.flatten() + if np.max(global_lons) > 180: + global_lons = ((global_lons + 180) % 360) - 180 + state["longitudes"] = np.concatenate([state["longitudes"], global_lons[mask]]) + state["latitudes"] = np.concatenate( + [state["latitudes"], ds["latitude"].values.flatten()[mask]] + ) + for param in _paramlist_ecmwf: + if param in ds: + state["fields"][PARAMS_MAP_INV[param]] = np.concatenate( + [ + state["fields"][PARAMS_MAP_INV[param]], + ds[param].values.flatten()[mask], + ] ) - # ensure base array exists (in case param wasn't in local ds) - base = state["fields"].get( - param, np.full(lats.size, np.nan, dtype=float) + else: + state["fields"][PARAMS_MAP_INV[param]] = np.concatenate( + [ + state["fields"][PARAMS_MAP_INV[param]], + np.full(mask.size, np.nan, dtype=float), + ] ) - state["fields"][param] = np.concatenate([base, add]) return state diff --git a/workflow/scripts/plot_forecast_frame.mo.py b/workflow/scripts/plot_forecast_frame.mo.py index 1575e330..33418949 100644 --- a/workflow/scripts/plot_forecast_frame.mo.py +++ b/workflow/scripts/plot_forecast_frame.mo.py @@ -94,9 +94,9 @@ def _(ArgumentParser, Path): @app.cell -def _(accu, grib_dir, init_time, lead_time, load_state_from_grib, param): - # load grib file - grib_file = grib_dir / f"{init_time}_{lead_time}.grib" +def _(accu, grib_dir, init_time, lead_time, load_state_from_grib, param, Path): + # TODO: fix file pattern & globbing + grib_file = Path(list(grib_dir.glob(f"2*_{lead_time}.grib"))[0]) if param == "SP_10M": paramlist = ["U_10M", "V_10M"] elif param == "SP": diff --git a/workflow/scripts/plot_meteogram.mo.py b/workflow/scripts/plot_meteogram.mo.py index c26d2c24..04e1abae 100644 --- a/workflow/scripts/plot_meteogram.mo.py +++ b/workflow/scripts/plot_meteogram.mo.py @@ -193,7 +193,7 @@ def load_data( ) forecast_ds = preprocess_ds(forecast_ds, param) - steps = forecast_ds.lead_time.dt.total_seconds().values / 3600 + steps = forecast_ds["step"].dt.total_seconds().values / 3600 analysis_ds = load_truth_data(analysis_zarr, init_time, steps, paramlist) analysis_ds = preprocess_ds(analysis_ds, param) @@ -214,8 +214,8 @@ def _(PeakWeatherDataset, peakweather_dir, station): stations = peakweather.stations_table stations.index.names = ["values"] station_ds = stations.to_xarray().sel(values=[station]) # keep singleton dim - station_ds = station_ds.rename({"latitude": "lat", "longitude": "lon"}) - station_ds = station_ds.set_coords(("lat", "lon", "station_name")) + # station_ds = station_ds.rename({"latitude": "lat", "longitude": "lon"}) + station_ds = station_ds.set_coords(("latitude", "longitude", "station_name")) station_ds = station_ds.drop_vars(list(station_ds.data_vars)) station_ds return (station_ds,) @@ -261,14 +261,14 @@ def _( zip(baseline_labels, baseline_station_ds_list), start=1 ): ax.plot( - baseline_station_ds["time"].values, + baseline_station_ds["valid_time"].values, baseline_station_ds[param].values, color=f"C{i}", label=f"{baseline_label}", ) # forecast ax.plot( - forecast_station_ds["time"].values, + forecast_station_ds["valid_time"].values, forecast_station_ds[param].values, color="C0", label=forecast_label, From d894d866a7fefccefc7711d25082a43ed74ab821 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Thu, 28 May 2026 10:03:10 +0200 Subject: [PATCH 15/23] fix colormap tests for list-of-colors loader contract --- tests/unit/test_colormaps.py | 22 +++++++++++----------- 1 file changed, 11 insertions(+), 11 deletions(-) diff --git a/tests/unit/test_colormaps.py b/tests/unit/test_colormaps.py index cb633127..b815f6ab 100644 --- a/tests/unit/test_colormaps.py +++ b/tests/unit/test_colormaps.py @@ -15,23 +15,18 @@ def test_load_valid_colormap(monkeypatch, tmp_path): monkeypatch.setattr(colormap_loader, "BASE_DIR", tmp_path) result = colormap_loader.load_ncl_colormap("test_colormap.ct") - assert isinstance(result["cmap"], ListedColormap) + # cmap is a list of RGB colors (earthkit-plots consumes it as `colors`) + assert isinstance(result["cmap"], np.ndarray) assert isinstance(result["norm"], BoundaryNorm) cmap = result["cmap"] norm = result["norm"] bounds = result["bounds"] - # cmap has n_levs-1 colors inside - assert cmap.N == 2 - # name is stem - assert cmap.name == "test_colormap" - # cmap colors - assert np.allclose(cmap(0), (40 / 255, 50 / 255, 60 / 255, 1.0)) - assert np.allclose(cmap(1), (70 / 255, 80 / 255, 90 / 255, 1.0)) - # under/over colors - assert np.allclose(cmap(-9999), (10 / 255, 20 / 255, 30 / 255, 1.0)) - assert np.allclose(cmap(9999), (100 / 255, 110 / 255, 120 / 255, 1.0)) + # cmap holds the n_levs-1 inner colors, under/over rows excluded + assert cmap.shape == (2, 3) + assert np.allclose(cmap[0], (40 / 255, 50 / 255, 60 / 255)) + assert np.allclose(cmap[1], (70 / 255, 80 / 255, 90 / 255)) # bounds assert np.allclose(norm.boundaries, [0, 1, 2]) assert np.allclose(bounds, [0, 1, 2]) @@ -75,6 +70,11 @@ def test_cmap_defaults_smoke(field, var): vmin = var.get("vmin", None) vmax = var.get("vmax", None) + # NCL colormaps are stored as a list of RGB colors (earthkit-plots + # consumes them as `colors`); wrap into a ListedColormap to plot here. + if isinstance(cmap, np.ndarray): + cmap = ListedColormap(cmap) + # make some synthetic data data = np.linspace(0, 1, 100).reshape(10, 10) From d77bead10d6c3e42c4f0d3f112e9b0ebb69f503f Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Thu, 28 May 2026 14:58:16 +0200 Subject: [PATCH 16/23] bugfixes after merge conflicts --- workflow/Snakefile | 4 +++- workflow/rules/common.smk | 2 +- workflow/scripts/plot_forecast_frame.py | 4 ++-- 3 files changed, 6 insertions(+), 4 deletions(-) diff --git a/workflow/Snakefile b/workflow/Snakefile index c629e1df..4a3ec692 100644 --- a/workflow/Snakefile +++ b/workflow/Snakefile @@ -143,7 +143,9 @@ rule experiment_all: scorecard_name=list(SCORECARD_CONFIGS), ) ] - if config.get("experiment", {}).get("scorecards", {}).get("enabled", True) + if (config.get("experiment", {}).get("scorecards") or {}).get( + "enabled", True + ) else [] ), diff --git a/workflow/rules/common.smk b/workflow/rules/common.smk index 6d05d6ab..632fa730 100644 --- a/workflow/rules/common.smk +++ b/workflow/rules/common.smk @@ -332,7 +332,7 @@ RUN_CONFIGS = collect_all_runs() ENV_CONFIGS = collect_all_envs() BASELINE_CONFIGS = collect_all_baselines() EXPERIMENT_PARTICIPANTS = collect_experiment_participants() -_scorecard = config.get("experiment", {}).get("scorecards", {}) +_scorecard = config.get("experiment", {}).get("scorecards") or {} SCORECARD_CONFIGS = ( _scorecard.get("sections", {}) if _scorecard.get("enabled", True) else {} ) diff --git a/workflow/scripts/plot_forecast_frame.py b/workflow/scripts/plot_forecast_frame.py index e7c532b8..1f327a20 100644 --- a/workflow/scripts/plot_forecast_frame.py +++ b/workflow/scripts/plot_forecast_frame.py @@ -4,7 +4,7 @@ from pathlib import Path import cartopy.crs as ccrs -import earthkit.meteo.thermo as ekm_thermo +from earthkit.meteo.utils.convert import kelvin_to_celsius import earthkit.meteo.wind as ekm_wind import earthkit.plots as ekp import numpy as np @@ -52,7 +52,7 @@ def preprocess_field(param: str, state: dict): """ fields = state["fields"] if param in ("T_2M", "TD_2M", "T", "TD"): - return ekm_thermo.kelvin_to_celsius(fields[param]), "°C" + return kelvin_to_celsius(fields[param]), "°C" if param == "SP_10M": return ekm_wind.speed(fields["U_10M"], fields["V_10M"]), "m/s" if param == "SP": From d568c40f83b5aba652e170a0e62cd06d3e49f2e0 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta <62377868+frazane@users.noreply.github.com> Date: Thu, 28 May 2026 19:25:56 +0200 Subject: [PATCH 17/23] fix wrong paramId for dewpoint temperature Co-authored-by: Jonas Bhend --- .../inference/configs/sgm-forecaster-global-disentangled.yaml | 2 +- .../inference/configs/sgm-forecaster-global-ich1-oper.yaml | 2 +- resources/inference/configs/sgm-forecaster-global-ich1.yaml | 2 +- resources/inference/configs/sgm-forecaster-global.yaml | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/resources/inference/configs/sgm-forecaster-global-disentangled.yaml b/resources/inference/configs/sgm-forecaster-global-disentangled.yaml index c2bc62ca..bc199ea8 100644 --- a/resources/inference/configs/sgm-forecaster-global-disentangled.yaml +++ b/resources/inference/configs/sgm-forecaster-global-disentangled.yaml @@ -48,7 +48,7 @@ output: 10u: {"param": 165, "shortName": "10u"} V_10M: {"param": 166, "shortName": "10v"} 10v: {"param": 166, "shortName": "10v"} - TD_2M: {"param": 167, "shortName": "2d"} + TD_2M: {"param": 168, "shortName": "2d"} 2d: {"param": 168, "shortName": "2d"} T_2M: {"param": 167, "shortName": "2t"} 2t: {"param": 167, "shortName": "2t"} diff --git a/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml b/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml index ba3a3478..b87c075e 100644 --- a/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml +++ b/resources/inference/configs/sgm-forecaster-global-ich1-oper.yaml @@ -46,7 +46,7 @@ output: 10u: {"param": 165, "shortName": "10u"} V_10M: {"param": 166, "shortName": "10v"} 10v: {"param": 166, "shortName": "10v"} - TD_2M: {"param": 167, "shortName": "2d"} + TD_2M: {"param": 168, "shortName": "2d"} 2d: {"param": 168, "shortName": "2d"} T_2M: {"param": 167, "shortName": "2t"} 2t: {"param": 167, "shortName": "2t"} diff --git a/resources/inference/configs/sgm-forecaster-global-ich1.yaml b/resources/inference/configs/sgm-forecaster-global-ich1.yaml index 890e8833..311afa07 100644 --- a/resources/inference/configs/sgm-forecaster-global-ich1.yaml +++ b/resources/inference/configs/sgm-forecaster-global-ich1.yaml @@ -53,7 +53,7 @@ output: 10u: {"param": 165, "shortName": "10u"} V_10M: {"param": 166, "shortName": "10v"} 10v: {"param": 166, "shortName": "10v"} - TD_2M: {"param": 167, "shortName": "2d"} + TD_2M: {"param": 168, "shortName": "2d"} 2d: {"param": 168, "shortName": "2d"} T_2M: {"param": 167, "shortName": "2t"} 2t: {"param": 167, "shortName": "2t"} diff --git a/resources/inference/configs/sgm-forecaster-global.yaml b/resources/inference/configs/sgm-forecaster-global.yaml index ca4f4693..5d8cbaa4 100644 --- a/resources/inference/configs/sgm-forecaster-global.yaml +++ b/resources/inference/configs/sgm-forecaster-global.yaml @@ -46,7 +46,7 @@ output: 10u: {"param": 165, "shortName": "10u"} V_10M: {"param": 166, "shortName": "10v"} 10v: {"param": 166, "shortName": "10v"} - TD_2M: {"param": 167, "shortName": "2d"} + TD_2M: {"param": 168, "shortName": "2d"} 2d: {"param": 168, "shortName": "2d"} T_2M: {"param": 167, "shortName": "2t"} 2t: {"param": 167, "shortName": "2t"} From a186804af66fc16e36a09d6b81753a85ac2c3aff Mon Sep 17 00:00:00 2001 From: Francesco Zanetta <62377868+frazane@users.noreply.github.com> Date: Thu, 28 May 2026 19:27:52 +0200 Subject: [PATCH 18/23] more fixes to wrong paramId Co-authored-by: Jonas Bhend --- .../inference/configs/sgm-interpolator-global_trimedge.yaml | 2 +- .../configs/sgm-interpolator-global_trimedge_multi.yaml | 2 +- .../configs/sgm-multidataset-forecaster-global-ich1-oper.yaml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/resources/inference/configs/sgm-interpolator-global_trimedge.yaml b/resources/inference/configs/sgm-interpolator-global_trimedge.yaml index 771a6ae9..66045aaf 100644 --- a/resources/inference/configs/sgm-interpolator-global_trimedge.yaml +++ b/resources/inference/configs/sgm-interpolator-global_trimedge.yaml @@ -104,7 +104,7 @@ output: 10u: {"param": 165, "shortName": "10u"} V_10M: {"param": 166, "shortName": "10v"} 10v: {"param": 166, "shortName": "10v"} - TD_2M: {"param": 167, "shortName": "2d"} + TD_2M: {"param": 168, "shortName": "2d"} 2d: {"param": 168, "shortName": "2d"} T_2M: {"param": 167, "shortName": "2t"} 2t: {"param": 167, "shortName": "2t"} diff --git a/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml b/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml index 17f524d6..dac23111 100644 --- a/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml +++ b/resources/inference/configs/sgm-interpolator-global_trimedge_multi.yaml @@ -101,7 +101,7 @@ output: 10u: {"param": 165, "shortName": "10u"} V_10M: {"param": 166, "shortName": "10v"} 10v: {"param": 166, "shortName": "10v"} - TD_2M: {"param": 167, "shortName": "2d"} + TD_2M: {"param": 168, "shortName": "2d"} 2d: {"param": 168, "shortName": "2d"} T_2M: {"param": 167, "shortName": "2t"} 2t: {"param": 167, "shortName": "2t"} diff --git a/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml b/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml index dc2dd07c..cd0c95a5 100644 --- a/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml +++ b/resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml @@ -54,7 +54,7 @@ output: 10u: {"param": 165, "shortName": "10u"} V_10M: {"param": 166, "shortName": "10v"} 10v: {"param": 166, "shortName": "10v"} - TD_2M: {"param": 167, "shortName": "2d"} + TD_2M: {"param": 168, "shortName": "2d"} 2d: {"param": 168, "shortName": "2d"} T_2M: {"param": 167, "shortName": "2t"} 2t: {"param": 167, "shortName": "2t"} From 19d430216123d8110e69ceac29c4ea47631c9184 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Thu, 28 May 2026 20:09:30 +0200 Subject: [PATCH 19/23] bugfix: compute uv components in obs dataset --- src/data_input/__init__.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/src/data_input/__init__.py b/src/data_input/__init__.py index bd2b13d2..9e08f411 100644 --- a/src/data_input/__init__.py +++ b/src/data_input/__init__.py @@ -271,13 +271,16 @@ def load_obs_data_from_peakweather( "wind_gust": "VMAX_10M", } param_names = {k: v for k, v in param_names.items() if v in params} - start = reftime end = start + timedelta(hours=max(steps)) if len(steps) > 1: end += timedelta(hours=steps[-1] - steps[-2]) # extend by 1 extra step years = list(set([start.year, end.year])) - pw = PeakWeatherDataset(root=root, years=years, freq=freq) + if "wind_u" in param_names or "wind_v" in param_names: + compute_uv = True + else: + compute_uv = False + pw = PeakWeatherDataset(root=root, years=years, freq=freq, compute_uv=compute_uv) ds, mask = pw.get_observations( parameters=[k for k in param_names.keys()], first_date=f"{start:%Y-%m-%d %H:%M}", From a92425d2ecd22a7e9ed9d28c36270f51465dd510 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Thu, 28 May 2026 20:11:15 +0200 Subject: [PATCH 20/23] consider both possible formats for step --- workflow/scripts/plot_forecast_frame.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/workflow/scripts/plot_forecast_frame.py b/workflow/scripts/plot_forecast_frame.py index 1f327a20..4f32ab3b 100644 --- a/workflow/scripts/plot_forecast_frame.py +++ b/workflow/scripts/plot_forecast_frame.py @@ -107,7 +107,10 @@ def main(): # Load grib once — shared across all region plots # TODO: fix file pattern & globbing - grib_file = Path(list(grib_dir.glob(f"2*_{lead_time}.grib"))[0]) + grib_file = list(grib_dir.glob(f"2*_{lead_time}.grib")) + if not grib_file: + grib_file = list(grib_dir.glob(f"2*_{lead_time:03}.grib")) + grib_file = Path(grib_file[0]) LOG.info("Loading grib file %s", grib_file) state = load_state_from_grib(grib_file, paramlist=paramlist) From 76b486c182c929b273af90893dd17e78b6b5f47f Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Fri, 29 May 2026 10:02:45 +0200 Subject: [PATCH 21/23] remove pinned versions from config --- config/interpolators-ich1.yaml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/config/interpolators-ich1.yaml b/config/interpolators-ich1.yaml index 24a1fde2..c26ea518 100644 --- a/config/interpolators-ich1.yaml +++ b/config/interpolators-ich1.yaml @@ -23,14 +23,10 @@ runs: steps: 0/120/6 extra_requirements: - git+https://github.com/ecmwf/anemoi-inference.git@e369b1a90313e9701db13f63364a467aa281cf36 - - eccodes==2.39.1 - - eccodes-cosmo-resources-python==2.38.3.1 extra_requirements: - git+https://github.com/ecmwf/anemoi-inference.git@e369b1a90313e9701db13f63364a467aa281cf36 # pinned anemoi-datasets because of ecmwf/anemoi-utils#284, can be removed when fixed - anemoi-datasets==0.5.35 - - eccodes==2.39.1 - - eccodes-cosmo-resources-python==2.38.3.1 - baseline: label: INCA root: /store_new/mch/msclim/INCA From 75301d6723a4a7a66f73fff90c56e7f072c38b53 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Fri, 29 May 2026 10:18:36 +0200 Subject: [PATCH 22/23] pin anemoi inference to current main HEAD --- config/forecasters-ich1-oper-fixed.yaml | 2 +- config/forecasters-ich1-oper.yaml | 2 +- config/forecasters-ich1.yaml | 4 ++-- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/config/forecasters-ich1-oper-fixed.yaml b/config/forecasters-ich1-oper-fixed.yaml index 3448402f..785d7cc2 100644 --- a/config/forecasters-ich1-oper-fixed.yaml +++ b/config/forecasters-ich1-oper-fixed.yaml @@ -18,7 +18,7 @@ runs: steps: 0/120/6 config: resources/inference/configs/sgm-multidataset-forecaster-global-ich1-oper.yaml extra_requirements: - - git+https://github.com/ecmwf/anemoi-inference.git@main + - git+https://github.com/ecmwf/anemoi-inference.git@de4cc0decd47dd593d2bb04cf9247e57a216d3cd # - forecaster: # checkpoint: https://service.meteoswiss.ch/mlstore#/experiments/602/runs/233b1274e79b4bfea98378d196a8aba0 diff --git a/config/forecasters-ich1-oper.yaml b/config/forecasters-ich1-oper.yaml index c5b0f76d..53c4e06b 100644 --- a/config/forecasters-ich1-oper.yaml +++ b/config/forecasters-ich1-oper.yaml @@ -20,7 +20,7 @@ runs: extra_requirements: - earthkit-utils<0.2.0 - earthkit-data<0.19.0 - - git+https://github.com/ecmwf/anemoi-inference.git@main + - git+https://github.com/ecmwf/anemoi-inference.git@de4cc0decd47dd593d2bb04cf9247e57a216d3cd - baseline: label: ICON-CH1-ctrl diff --git a/config/forecasters-ich1.yaml b/config/forecasters-ich1.yaml index c2b2ee2c..c7d05399 100644 --- a/config/forecasters-ich1.yaml +++ b/config/forecasters-ich1.yaml @@ -16,7 +16,7 @@ runs: extra_requirements: - earthkit-utils<0.2.0 - earthkit-data<0.19.0 - - git+https://github.com/ecmwf/anemoi-inference.git@main + - git+https://github.com/ecmwf/anemoi-inference.git@de4cc0decd47dd593d2bb04cf9247e57a216d3cd - forecaster: checkpoint: /scratch/mch/apennino/output/checkpoint/973b78b8b39543949abc2b154c5f98d9/inference-last.ckpt @@ -26,7 +26,7 @@ runs: extra_requirements: - earthkit-utils<0.2.0 - earthkit-data<0.19.0 - - git+https://github.com/ecmwf/anemoi-inference.git@main + - git+https://github.com/ecmwf/anemoi-inference.git@de4cc0decd47dd593d2bb04cf9247e57a216d3cd # - forecaster: # checkpoint: https://huggingface.co/met-no/bris_cloudy-skies/blob/main/2025-10/cloudy-skies-2025-10.ckpt From b201c481bf7fe612b178080076c5ea53d43e48a5 Mon Sep 17 00:00:00 2001 From: Francesco Zanetta Date: Fri, 29 May 2026 11:41:45 +0200 Subject: [PATCH 23/23] do not set short lived var --- src/plotting/compat.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/src/plotting/compat.py b/src/plotting/compat.py index 1d7866b7..ef14e473 100644 --- a/src/plotting/compat.py +++ b/src/plotting/compat.py @@ -32,7 +32,6 @@ def load_state_from_grib( "The GRIB file may not contain these fields at this lead time " "(e.g. accumulated fields like TOT_PREC are undefined at step 0)." ) - lons = ds["longitude"].values.flatten() state["forecast_reference_time"] = datetime.fromtimestamp( ds["forecast_reference_time"].values.item() / 1e9 ) @@ -41,7 +40,7 @@ def load_state_from_grib( state["latitudes"] = ds["latitude"].values.flatten() # Add the limited-area model envelope polygon (convex hull) before global coords are added lam_hull = MultiPoint( - list(zip(lons.tolist(), state["latitudes"].tolist())) + list(zip(state["longitudes"].tolist(), state["latitudes"].tolist())) ).convex_hull state["lam_envelope"] = gpd.GeoSeries([lam_hull], crs="EPSG:4326") state["fields"] = {}