diff --git a/.github/workflows/cd-ppcore.yml b/.github/workflows/cd-ppcore.yml new file mode 100644 index 00000000..ecd55f1a --- /dev/null +++ b/.github/workflows/cd-ppcore.yml @@ -0,0 +1,76 @@ +name: Publish pproc-core to PyPI or TestPyPI + +on: + workflow_dispatch: + inputs: + tag: + description: 'Release tag ppcore-X.Y.Z' + required: true + type: string + environment: + description: 'Publish to' + required: true + type: choice + options: + - testpypi + - pypi + default: testpypi + +jobs: + test: + runs-on: ubuntu-latest + strategy: + fail-fast: true + matrix: + python_version: ["3.11", "3.12", "3.13"] + steps: + - uses: actions/checkout@v4 + with: + ref: ${{ inputs.tag }} + + - uses: astral-sh/setup-uv@v7 + - name: Run checks and tests + run: | + cd pproc-core + uv sync --python "${{ matrix.python_version }}" --all-packages + uv run prek --directory . --config ../.pre-commit-config.yaml + if [ -d "tests" ]; then + uv run -m pytest tests/ -v + fi + + publish: + needs: test + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2 + with: + ref: ${{ inputs.tag }} + + - name: Set up Python + uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0 + with: + python-version: "3.x" + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install setuptools wheel twine build + + - run: | + cd pproc-core + python -m pip install --upgrade build twine + python -m build + twine check dist/* + if [ "${{ inputs.environment }}" = "testpypi" ] ; then + TARGET="--repository testpypi" + export TWINE_PASSWORD="$TWINE_PASSWORD_TEST" + else + TARGET="" + export TWINE_PASSWORD="$TWINE_PASSWORD_PROD" + fi + twine upload $TARGET --verbose dist/* + env: + TWINE_USERNAME: __token__ + TWINE_PASSWORD_PROD: ${{ secrets.PYPI_API_TOKEN }} + TWINE_PASSWORD_TEST: ${{ secrets.PYPI_TEST_API_TOKEN }} diff --git a/.github/workflows/cd.yml b/.github/workflows/cd-pproc.yml similarity index 86% rename from .github/workflows/cd.yml rename to .github/workflows/cd-pproc.yml index cf58fe88..3b316bab 100644 --- a/.github/workflows/cd.yml +++ b/.github/workflows/cd-pproc.yml @@ -9,4 +9,6 @@ jobs: pypi: uses: ecmwf/reusable-workflows/.github/workflows/cd-pypi.yml@v2 + with: + working-directory: pproc secrets: inherit diff --git a/.github/workflows/cd-ppruntime.yml b/.github/workflows/cd-ppruntime.yml new file mode 100644 index 00000000..2b08ad26 --- /dev/null +++ b/.github/workflows/cd-ppruntime.yml @@ -0,0 +1,76 @@ +name: Publish pproc-runtime to PyPI or TestPyPI + +on: + workflow_dispatch: + inputs: + tag: + description: 'Release tag ppruntime-X.Y.Z' + required: true + type: string + environment: + description: 'Publish to' + required: true + type: choice + options: + - testpypi + - pypi + default: testpypi + +jobs: + test: + runs-on: ubuntu-latest + strategy: + fail-fast: true + matrix: + python_version: ["3.10", "3.11", "3.12", "3.13"] + steps: + - uses: actions/checkout@v4 + with: + ref: ${{ inputs.tag }} + - uses: astral-sh/setup-uv@v7 + - name: Run checks and tests + run: | + cd pproc-runtime + uv sync --python "${{ matrix.python_version }}" --all-packages + uv run prek --directory . --config ../.pre-commit-config.yaml + uv run ty check + if [ -d "tests" ]; then + uv run -m pytest tests/ -v + fi + + publish: + needs: test + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + with: + ref: ${{ inputs.tag }} + + - name: Set up Python + uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0 + with: + python-version: "3.x" + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install setuptools wheel twine build + + - run: | + cd pproc-runtime + python -m pip install --upgrade build twine + python -m build + twine check dist/* + if [ "${{ inputs.environment }}" = "testpypi" ] ; then + TARGET="--repository testpypi" + export TWINE_PASSWORD="$TWINE_PASSWORD_TEST" + else + TARGET="" + export TWINE_PASSWORD="$TWINE_PASSWORD_PROD" + fi + twine upload $TARGET --verbose dist/* + env: + TWINE_USERNAME: __token__ + TWINE_PASSWORD_PROD: ${{ secrets.PYPI_API_TOKEN }} + TWINE_PASSWORD_TEST: ${{ secrets.PYPI_TEST_API_TOKEN }} diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 00000000..9bdc218a --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,71 @@ +name: ci + +on: + # Trigger the workflow manually + workflow_dispatch: ~ + + push: + branches: + - 'main' + - 'develop' + + pull_request: ~ + +jobs: + ppruntime_test: + runs-on: ubuntu-latest + strategy: + fail-fast: true + matrix: + python-version: ['3.10', '3.11', '3.12', '3.13'] + steps: + - uses: actions/checkout@v4 + - uses: astral-sh/setup-uv@v7 + - name: Run checks and tests + run: | + cd pproc-runtime + export UV_FROZEN=1 + uv sync --python "${{ matrix.python_version }}" --all-packages + uv run prek --directory . --config ../.pre-commit-config.yaml + uv run ty check + if [ -d "tests" ]; then + uv run -m pytest tests/ -v + fi + + ppcore_test: + runs-on: ubuntu-latest + strategy: + fail-fast: true + matrix: + python-version: ['3.11', '3.12', '3.13'] + steps: + - uses: actions/checkout@v4 + - uses: astral-sh/setup-uv@v7 + - name: Run checks and tests + run: | + cd pproc-core + export UV_FROZEN=1 + uv sync --python "${{ matrix.python_version }}" --all-packages + uv run prek --directory . --config ../.pre-commit-config.yaml + if [ -d "tests" ]; then + uv run -m pytest tests/ -v + fi + + pproc_test: + runs-on: ubuntu-latest + strategy: + fail-fast: true + matrix: + python-version: ['3.11', '3.12', '3.13'] + steps: + - uses: actions/checkout@v4 + - uses: astral-sh/setup-uv@v7 + - name: Run pproc tests + run: | + cd pproc + export UV_FROZEN=1 + uv sync --python "${{ matrix.python_version }}" --all-packages + # uv run prek --directory . --config ../.pre-commit-config.yaml + if [ -d "tests" ]; then + uv run -m pytest tests/ -v + fi diff --git a/.github/workflows/sync.yml b/.github/workflows/sync.yml index fc06d5d9..3597c7bc 100644 --- a/.github/workflows/sync.yml +++ b/.github/workflows/sync.yml @@ -1,20 +1,20 @@ name: sync - + # Controls when the workflow will run on: - + # Trigger the workflow on all pushes push: branches: - '**' tags: - '**' - + # Trigger the workflow when a branch or tag is deleted delete: ~ - + jobs: - + # Calls a reusable CI workflow to sync the current with a remote repository. # It will correctly handle addition of any new and removal of existing Git objects. sync: diff --git a/.github/workflows/test-pypi.yml b/.github/workflows/test-pypi.yml deleted file mode 100644 index 4a4e8a22..00000000 --- a/.github/workflows/test-pypi.yml +++ /dev/null @@ -1,11 +0,0 @@ -name: test cd - -on: - workflow_dispatch: ~ - -jobs: - deploy: - uses: ecmwf/reusable-workflows/.github/workflows/cd-pypi.yml@v2 - secrets: inherit - with: - testpypi: true diff --git a/.gitignore b/.gitignore index 36a2e8dd..d5e4f15f 100644 --- a/.gitignore +++ b/.gitignore @@ -1,40 +1 @@ -*.sw[op] -.DS_Store -.idea/ - -# Byte-compiled / optimized / DLL files -__pycache__/ -*.py[cod] -*$py.class - -# Distribution / packaging -.Python -build/ -develop-eggs/ -dist/ -downloads/ -eggs/ -.eggs/ -lib/ -lib64/ -parts/ -sdist/ -var/ -wheels/ -share/python-wheels/ -*.egg-info/ -.installed.cfg -*.egg -MANIFEST - -# Jupyter Notebook -.ipynb_checkpoints - -# IPython -profile_default/ -ipython_config.py - -tests/data - - -src/pproc/_version.py +**/__pycache__ \ No newline at end of file diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 00000000..7d556f8e --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,46 @@ +default_language_version: + python: python3 +default_stages: + - commit + - push +repos: +# Empty notebookds +- repo: local + hooks: + - id: clear-notebooks-output + name: clear-notebooks-output + files: tools/.*\.ipynb$ + stages: [pre-commit] + language: python + entry: jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace + additional_dependencies: [jupyter] +- repo: https://github.com/charliermarsh/ruff-pre-commit + rev: v0.5.6 + hooks: + - id: ruff + args: [--fix] + - id: ruff-format +- repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.4.0 + hooks: + - id: detect-private-key + - id: check-ast + - id: end-of-file-fixer + - id: mixed-line-ending + args: [--fix=lf] + - id: trailing-whitespace + - id: check-case-conflict +- repo: local + hooks: + - id: forbid-to-commit + name: Don't commit rej files + entry: | + Cannot commit .rej files. These indicate merge conflicts that + arise during automated template updates. + Fix the merge conflicts manually and remove the .rej files. + language: fail + files: '.*\.rej$' +- repo: https://github.com/tox-dev/pyproject-fmt + rev: "v2.5.0" + hooks: + - id: pyproject-fmt \ No newline at end of file diff --git a/LICENSE b/LICENSE index e7338b3b..af25a625 100644 --- a/LICENSE +++ b/LICENSE @@ -1,190 +1,79 @@ - Apache License - Version 2.0, January 2004 - http://www.apache.org/licenses/ - - TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION - - 1. Definitions. - - "License" shall mean the terms and conditions for use, reproduction, - and distribution as defined by Sections 1 through 9 of this document. - - "Licensor" shall mean the copyright owner or entity authorized by - the copyright owner that is granting the License. - - "Legal Entity" shall mean the union of the acting entity and all - other entities that control, are controlled by, or are under common - control with that entity. For the purposes of this definition, - "control" means (i) the power, direct or indirect, to cause the - direction or management of such entity, whether by contract or - otherwise, or (ii) ownership of fifty percent (50%) or more of the - outstanding shares, or (iii) beneficial ownership of such entity. - - "You" (or "Your") shall mean an individual or Legal Entity - exercising permissions granted by this License. - - "Source" form shall mean the preferred form for making modifications, - including but not limited to software source code, documentation - source, and configuration files. - - "Object" form shall mean any form resulting from mechanical - transformation or translation of a Source form, including but - not limited to compiled object code, generated documentation, - and conversions to other media types. - - "Work" shall mean the work of authorship, whether in Source or - Object form, made available under the License, as indicated by a - copyright notice that is included in or attached to the work - (an example is provided in the Appendix below). - - "Derivative Works" shall mean any work, whether in Source or Object - form, that is based on (or derived from) the Work and for which the - editorial revisions, annotations, elaborations, or other modifications - represent, as a whole, an original work of authorship. For the purposes - of this License, Derivative Works shall not include works that remain - separable from, or merely link (or bind by name) to the interfaces of, - the Work and Derivative Works thereof. - - "Contribution" shall mean any work of authorship, including - the original version of the Work and any modifications or additions - to that Work or Derivative Works thereof, that is intentionally - submitted to Licensor for inclusion in the Work by the copyright owner - or by an individual or Legal Entity authorized to submit on behalf of - the copyright owner. For the purposes of this definition, "submitted" - means any form of electronic, verbal, or written communication sent - to the Licensor or its representatives, including but not limited to - communication on electronic mailing lists, source code control systems, - and issue tracking systems that are managed by, or on behalf of, the - Licensor for the purpose of discussing and improving the Work, but - excluding communication that is conspicuously marked or otherwise - designated in writing by the copyright owner as "Not a Contribution." - - "Contributor" shall mean Licensor and any individual or Legal Entity - on behalf of whom a Contribution has been received by Licensor and - subsequently incorporated within the Work. - - 2. Grant of Copyright License. Subject to the terms and conditions of - this License, each Contributor hereby grants to You a perpetual, - worldwide, non-exclusive, no-charge, royalty-free, irrevocable - copyright license to reproduce, prepare Derivative Works of, - publicly display, publicly perform, sublicense, and distribute the - Work and such Derivative Works in Source or Object form. - - 3. Grant of Patent License. Subject to the terms and conditions of - this License, each Contributor hereby grants to You a perpetual, - worldwide, non-exclusive, no-charge, royalty-free, irrevocable - (except as stated in this section) patent license to make, have made, - use, offer to sell, sell, import, and otherwise transfer the Work, - where such license applies only to those patent claims licensable - by such Contributor that are necessarily infringed by their - Contribution(s) alone or by combination of their Contribution(s) - with the Work to which such Contribution(s) was submitted. If You - institute patent litigation against any entity (including a - cross-claim or counterclaim in a lawsuit) alleging that the Work - or a Contribution incorporated within the Work constitutes direct - or contributory patent infringement, then any patent licenses - granted to You under this License for that Work shall terminate - as of the date such litigation is filed. - - 4. Redistribution. You may reproduce and distribute copies of the - Work or Derivative Works thereof in any medium, with or without - modifications, and in Source or Object form, provided that You - meet the following conditions: - - (a) You must give any other recipients of the Work or - Derivative Works a copy of this License; and - - (b) You must cause any modified files to carry prominent notices - stating that You changed the files; and - - (c) You must retain, in the Source form of any Derivative Works - that You distribute, all copyright, patent, trademark, and - attribution notices from the Source form of the Work, - excluding those notices that do not pertain to any part of - the Derivative Works; and - - (d) If the Work includes a "NOTICE" text file as part of its - distribution, then any Derivative Works that You distribute must - include a readable copy of the attribution notices contained - within such NOTICE file, excluding those notices that do not - pertain to any part of the Derivative Works, in at least one - of the following places: within a NOTICE text file distributed - as part of the Derivative Works; within the Source form or - documentation, if provided along with the Derivative Works; or, - within a display generated by the Derivative Works, if and - wherever such third-party notices normally appear. The contents - of the NOTICE file are for informational purposes only and - do not modify the License. You may add Your own attribution - notices within Derivative Works that You distribute, alongside - or as an addendum to the NOTICE text from the Work, provided - that such additional attribution notices cannot be construed - as modifying the License. - - You may add Your own copyright statement to Your modifications and - may provide additional or different license terms and conditions - for use, reproduction, or distribution of Your modifications, or - for any such Derivative Works as a whole, provided Your use, - reproduction, and distribution of the Work otherwise complies with - the conditions stated in this License. - - 5. Submission of Contributions. Unless You explicitly state otherwise, - any Contribution intentionally submitted for inclusion in the Work - by You to the Licensor shall be under the terms and conditions of - this License, without any additional terms or conditions. - Notwithstanding the above, nothing herein shall supersede or modify - the terms of any separate license agreement you may have executed - with Licensor regarding such Contributions. - - 6. Trademarks. This License does not grant permission to use the trade - names, trademarks, service marks, or product names of the Licensor, - except as required for reasonable and customary use in describing the - origin of the Work and reproducing the content of the NOTICE file. - - 7. Disclaimer of Warranty. Unless required by applicable law or - agreed to in writing, Licensor provides the Work (and each - Contributor provides its Contributions) on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or - implied, including, without limitation, any warranties or conditions - of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A - PARTICULAR PURPOSE. You are solely responsible for determining the - appropriateness of using or redistributing the Work and assume any - risks associated with Your exercise of permissions under this License. - - 8. Limitation of Liability. In no event and under no legal theory, - whether in tort (including negligence), contract, or otherwise, - unless required by applicable law (such as deliberate and grossly - negligent acts) or agreed to in writing, shall any Contributor be - liable to You for damages, including any direct, indirect, special, - incidental, or consequential damages of any character arising as a - result of this License or out of the use or inability to use the - Work (including but not limited to damages for loss of goodwill, - work stoppage, computer failure or malfunction, or any and all - other commercial damages or losses), even if such Contributor - has been advised of the possibility of such damages. - - 9. Accepting Warranty or Additional Liability. While redistributing - the Work or Derivative Works thereof, You may choose to offer, - and charge a fee for, acceptance of support, warranty, indemnity, - or other liability obligations and/or rights consistent with this - License. However, in accepting such obligations, You may act only - on Your own behalf and on Your sole responsibility, not on behalf - of any other Contributor, and only if You agree to indemnify, - defend, and hold each Contributor harmless for any liability - incurred by, or claims asserted against, such Contributor by reason - of your accepting any such warranty or additional liability. - - END OF TERMS AND CONDITIONS - - Copyright 2021- ECMWF - - Licensed under the Apache License, Version 2.0 (the "License"); - you may not use this file except in compliance with the License. - You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - - Unless required by applicable law or agreed to in writing, software - distributed under the License is distributed on an "AS IS" BASIS, - WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - See the License for the specific language governing permissions and - limitations under the License. +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. Definitions. + +"License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. + +"Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. + +"Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. + +"You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. + +"Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. + +"Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. + +"Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). + +"Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. + +"Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. + +3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. + +4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: + + (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. + + You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. + +5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. + +6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. + +7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. + +8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. + +9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. + +END OF TERMS AND CONDITIONS + +APPENDIX: How to apply the Apache License to your work. + +To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. + +Copyright [yyyy] [name of copyright owner] + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. + +------------------------------------------------------------------------------- + +In applying this licence, ECMWF does not waive the privileges and immunities +granted to it by virtue of its status as an intergovernmental organisation +nor does it submit to any jurisdiction. diff --git a/LICENSES/Apache-2.0.txt b/LICENSES/Apache-2.0.txt new file mode 100644 index 00000000..137069b8 --- /dev/null +++ b/LICENSES/Apache-2.0.txt @@ -0,0 +1,73 @@ +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. Definitions. + +"License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. + +"Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. + +"Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. + +"You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. + +"Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. + +"Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. + +"Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). + +"Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. + +"Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Definitions. + +"License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. + +"Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. + +"Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. 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You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: + + (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and + + (b) You must cause any modified files to carry prominent notices stating that You changed the files; and + + (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and + + (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. 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Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. + +6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. + +7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. + +8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. + +9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. + +END OF TERMS AND CONDITIONS + +APPENDIX: How to apply the Apache License to your work. + +To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. + +Copyright [yyyy] [name of copyright owner] + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. + +------------------------------------------------------------------------------- + +In applying this licence, ECMWF does not waive the privileges and immunities +granted to it by virtue of its status as an intergovernmental organisation +nor does it submit to any jurisdiction. diff --git a/pproc-core/README.md b/pproc-core/README.md new file mode 100644 index 00000000..6d7f22f1 --- /dev/null +++ b/pproc-core/README.md @@ -0,0 +1,24 @@ +# pproc-core + +

+ + Static Badge + + + + Code Coverage + + + + License: Apache 2.0 + + + + Latest Release + +

+ +> \[!IMPORTANT\] +> This software is **Sandbox** and subject to ECMWF's guidelines on [Software Maturity](https://github.com/ecmwf/codex/raw/refs/heads/main/Project%20Maturity). + +ppcore-core is a Python library for constructing task graphs associated to forecast post-processing products provided. These task graphs are an extension of the [earthkit-workflows](https://github.com/ecmwf/earthkit-workflows) framework, in which the graphs can be executed. diff --git a/pproc-core/docs/examples/ensms.ipynb b/pproc-core/docs/examples/ensms.ipynb new file mode 100644 index 00000000..ba56ec7c --- /dev/null +++ b/pproc-core/docs/examples/ensms.ipynb @@ -0,0 +1,85 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Graph Construction" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "from earthkit.workflows.plugins.pproc.fluent import from_source\n", + "from earthkit.workflows.graph import deduplicate_nodes\n", + "\n", + "interpolation = {\n", + " \"grid\": \"O320\"\n", + "}\n", + "\n", + "actions = (\n", + " from_source([{\n", + " \"class\": \"od\", \n", + " \"expver\": \"0001\", \n", + " \"stream\": \"enfo\", \n", + " \"date\": \"20240425\", \n", + " \"time\": \"00\", \n", + " \"param\": 167, \n", + " \"levtype\": \"sfc\", \n", + " \"type\": \"pf\", \n", + " \"number\": range(1, 6), \n", + " \"step\": range(0, 25, 6),\n", + " \"source\": \"mars\", \n", + " \"interpolate\": interpolation,\n", + " }])\n", + " .accum_operation(\n", + " \"mean\", \n", + " [[0, 6, 12, 18, 24], [12, 18, 24]],\n", + " dim=\"step\", batch_size=2) \n", + " .ensemble_operation(\"ensms\", dim=\"number\")\n", + ")\n", + "\n", + "graph = deduplicate_nodes(actions.graph())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "from earthkit.workflows.visualise import visualise\n", + "\n", + "visualise(graph, \"mean.html\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "ppcascade", + "language": "python", + "name": "ppcascade" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pproc-core/docs/examples/multi-prods.ipynb b/pproc-core/docs/examples/multi-prods.ipynb new file mode 100644 index 00000000..c12b12cb --- /dev/null +++ b/pproc-core/docs/examples/multi-prods.ipynb @@ -0,0 +1,154 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Graph Construction" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "from earthkit.workflows.plugins.pproc.fluent import from_source\n", + "from earthkit.workflows.plugins.pproc.utils.request import Request\n", + "from earthkit.workflows.graph import deduplicate_nodes\n", + "\n", + "GRID = \"O320\" # For higher memory usage increase to O640 or O1280\n", + "NUM_ENSEMBLES = 2 # Can increase up to 50\n", + "SOURCE = \"mars\" # Change to fdb if using local fdb. Note FDB_HOME will need to be specified \n", + " # and to change the grid from that archived in the FDB you will need to add \n", + " # the commented out interpolation line in the request and remove the \"grid\" \n", + " # key\n", + "END_STEP = 60 # Can increase to a number divisible by 6 up to 240\n", + "DATE = \"20241015\"\n", + "CLIM_DATE = \"20241014\"\n", + "\n", + "inputs = from_source([{\n", + " \"class\": \"od\", \n", + " \"expver\": \"0001\", \n", + " \"stream\": \"enfo\", \n", + " \"date\": DATE, \n", + " \"time\": \"00\", \n", + " \"param\": 167, \n", + " \"levtype\": \"sfc\", \n", + " \"type\": \"pf\", \n", + " \"number\": range(1, NUM_ENSEMBLES + 1), \n", + " \"step\": range(0, END_STEP + 1, 3),\n", + " \"source\": SOURCE, \n", + " \"grid\": GRID,\n", + " # \"interpolate\": {\"grid\": GRID},\n", + " }])\n", + "\n", + "# Graph for computing ensemble mean and standard deviation for each time step\n", + "ensms_graph = (\n", + " inputs \n", + " .ensemble_operation(\"ensms\", dim=\"number\", batch_size=2)\n", + " .graph()\n", + ")\n", + "\n", + "# Graph for computing probability of exceeding a certain threshold across a step window\n", + "prob_windows = [[x] for x in range(0, END_STEP + 1, 24)] + [\n", + " list(range(x, x + 121, 6)) for x in range(0, END_STEP - 119, 120)\n", + "]\n", + "prob_graph = (\n", + " inputs\n", + " .accum_operation(\n", + " \"min\", \n", + " prob_windows,\n", + " dim=\"step\", batch_size=2)\n", + " .ensemble_operation(\n", + " \"threshold_prob\", \n", + " comparison=\"<=\", \n", + " local_scale_factor=2, \n", + " value= 273.15,\n", + " )\n", + " .graph()\n", + ")\n", + "\n", + "# Graph for computing extreme forecast indices - this has the highest memory consumption \n", + "efi_windows = [list(range(x, x+25, 6)) for x in range(0, END_STEP - 23, 24)]\n", + "climatology = from_source(\n", + " [Request({\n", + " \"class\": \"od\", \n", + " \"expver\": \"0001\", \n", + " \"stream\": \"efhs\", \n", + " \"date\": CLIM_DATE, \n", + " \"time\": \"00\", \n", + " \"param\": 228004, \n", + " \"levtype\": \"sfc\", \n", + " \"type\": \"cd\", \n", + " \"quantile\": [f\"{x}:100\" for x in range(101)],\n", + " \"step\": [f\"{x}-{x+24}\" for x in range(0, END_STEP - 23, 24)],\n", + " \"source\": SOURCE, \n", + " \"grid\": GRID,\n", + " # \"interpolate\": {\"grid\": GRID},\n", + " }, no_expand=(\"quantile\",))]\n", + ")\n", + "efi_graph = (\n", + " inputs\n", + " .accum_operation(\n", + " \"mean\", \n", + " efi_windows,\n", + " dim=\"step\", batch_size=2)\n", + " .ensemble_extreme(\n", + " \"extreme\",\n", + " climatology,\n", + " [f\"{x[0]}-{x[-1]}\" for x in efi_windows],\n", + " sot=[10, 90],\n", + " eps=1e-4,\n", + " metadata={\n", + " \"edition\": 1,\n", + " \"gribTablesVersionNo\": 132,\n", + " \"indicatorOfParameter\": 167,\n", + " \"localDefinitionNumber\": 19,\n", + " \"timeRangeIndicator\": 3\n", + " }\n", + " )\n", + " .graph()\n", + ")\n", + "\n", + "total_graph = deduplicate_nodes(ensms_graph + prob_graph + efi_graph)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "from earthkit.workflows.visualise import visualise\n", + "\n", + "visualise(total_graph, \"pproc_2t.html\")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "ppcascade", + "language": "python", + "name": "ppcascade" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pproc-core/pyproject.toml b/pproc-core/pyproject.toml new file mode 100644 index 00000000..da3bdcaf --- /dev/null +++ b/pproc-core/pyproject.toml @@ -0,0 +1,85 @@ +# (C) Copyright 2024 ECMWF. +# +# This software is licensed under the terms of the Apache Licence Version 2.0 +# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0. +# In applying this licence, ECMWF does not waive the privileges and immunities +# granted to it by virtue of its status as an intergovernmental organisation +# nor does it submit to any jurisdiction. + +[build-system] +build-backend = "setuptools.build_meta" + +requires = [ "setuptools>=65", "setuptools-scm[toml]>=6.2" ] + +[project] +name = "pproc-core" +description = "An earthkit-workflows interface to PProc" +readme = "README.md" +license = "Apache-2.0" +license-files = [ "LICENSE" ] +authors = [ + { name = "European Centre for Medium-Range Weather Forecasts (ECMWF)", email = "software.support@ecmwf.int" }, +] +requires-python = ">=3.11" +classifiers = [ + "Programming Language :: Python :: 3 :: Only", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", +] +dynamic = [ "version" ] + +dependencies = [ + "code-meters", + "conflator>=0.1.8", + "earthkit-time", + "earthkit-workflows>=0.15.5", + "numpy", + "pandas", + "pydantic", + "qubed>=0.3,<0.4.4", +] + +optional-dependencies.vizualize = [ + "earthkit-workflows[vizualize]>=0.15.4", +] + +scripts.ppcore-config = "ppcore.config:main" +scripts.pproc-product = "ppcore.product:main" + +[dependency-groups] +dev = [ + "prek>=0.4.4", + "pytest>=9.0.3", + "ty>=0.0.43", +] + +[tool.setuptools] +include-package-data = true +zip-safe = false + +[tool.setuptools.packages.find] +where = [ "src" ] + +[tool.setuptools_scm] +write_to = "src/earthkit/workflows/plugins/pproc/_version.py" +write_to_template = '''# Do not change! Do not track in version control! +__version__ = "{version}" +''' +root = ".." +local_scheme = "no-local-version" +fallback_version = "0.0.0" + +[tool.setuptools_scm.tag] +prefix = "ppcore-" +strict = true + +[tool.ruff] +lint.ignore = [ "E722", "E731", "E741" ] + +[tool.pytest.ini_options] +log_cli = true +testpaths = [ "tests/" ] + +[tool.uv] +package = true diff --git a/src/pproc/ecpt/__init__.py b/pproc-core/src/earthkit/workflows/plugins/pproc/__init__.py similarity index 100% rename from src/pproc/ecpt/__init__.py rename to pproc-core/src/earthkit/workflows/plugins/pproc/__init__.py diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/config/accumulation.py b/pproc-core/src/earthkit/workflows/plugins/pproc/config/accumulation.py new file mode 100644 index 00000000..b5239c2d --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/config/accumulation.py @@ -0,0 +1,58 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Literal, Optional, Union, Annotated +import datetime + +from earthkit.time.calendar import MonthInYear +from earthkit.time.sequence import MonthlySequence + +from pydantic import Field, ConfigDict + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel + +NumericCoord = int +NumericCoords = Union[list[int], range] + +Coord = Union[str, NumericCoord] +Coords = Union[list[str], NumericCoords] + + +class Default(PProcBaseModel): + model_config = ConfigDict(validate_by_name=True) + + type_: Literal["default"] = Field("default", alias="type") + length: Optional[int] = None + + def name(self, coords: Coords) -> str: + if len(coords) == 0: + return "" + end = coords[-1] + if len(coords) == 1 and (self.length is None or isinstance(coords[0], str)): + return f"{end}" + start = coords[0] if self.length is None else int(end) - self.length + return f"{start}-{end}" + + +class Monthly(PProcBaseModel): + model_config = ConfigDict(validate_by_name=True) + + type_: Literal["monthly"] = Field("monthly", alias="type") + date: str + + def name(self, coords: Coords) -> str: + if len(coords) == 0: + return "" + end = coords[-1] + fcdate = datetime.datetime.strptime(self.date, "%Y%m%d") + end = int(end) + seq = MonthlySequence(1) + seq.next(fcdate, False) + this_month = fcdate + datetime.timedelta(hours=end - 1) + month_length = MonthInYear(this_month.year, this_month.month).length() * 24 + start = end - month_length + return f"{start}-{end}" + + +AccumName = Annotated[Union[Default, Monthly], Field(discriminator="type")] diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/config/mask.py b/pproc-core/src/earthkit/workflows/plugins/pproc/config/mask.py new file mode 100644 index 00000000..83d6605e --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/config/mask.py @@ -0,0 +1,25 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Any, Literal + +from pydantic import model_validator + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel + + +class MaskExpression(PProcBaseModel): + select: dict + comparison: Literal["<", ">", ">=", "<=", "==", "!="] + value: float + + @model_validator(mode="before") + @classmethod + def validate_model(cls, data: Any) -> Any: + if isinstance(data, list): + assert ( + len(data) == 3 + ), "Mask expression should be a [select, comparison, value] list" + return {"select": data[0], "comparison": data[1], "value": data[2]} + return data diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/config/threshold.py b/pproc-core/src/earthkit/workflows/plugins/pproc/config/threshold.py new file mode 100644 index 00000000..def584d5 --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/config/threshold.py @@ -0,0 +1,47 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from pydantic import model_validator +from typing import Any, Optional, Literal + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel + +Comparisons = Literal["<", ">", "<=", ">="] + + +class Threshold(PProcBaseModel): + select: Optional[dict] = None + lower_scale_factor: int = 0 + lower_comparison: Comparisons + lower_value: float + upper_scale_factor: int = 0 + upper_comparison: Optional[Comparisons] = None + upper_value: Optional[float] = None + + @model_validator(mode="before") + def validate_threshold(cls, data: Any) -> Any: + if isinstance(data, dict): + if "comparison" in data: + data["lower_comparison"] = data.pop("comparison") + data["lower_value"] = data.pop("value") + data["lower_scale_factor"] = data.pop("scale_factor", 0) + if any(k in data for k in ["upper_comparison", "upper_value"]) and not all( + k in data for k in ["upper_comparison", "upper_value"] + ): + raise ValueError( + "Both upper_comparison and upper_value must be provided together" + ) + # Derive scale factors for custom thresholds + for value in ["lower_value", "upper_value"]: + upper_or_lower = value.split("_")[0] + if ( + isinstance(data.get(value), float) + and f"{upper_or_lower}_scale_factor" not in data + ): + scale_factor = 0 + while abs(data[value] * 10**scale_factor) < 1: + scale_factor += 1 + data[f"{upper_or_lower}_scale_factor"] = scale_factor + data[value] = round(data[value] * 10**scale_factor) + return data diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/fluent.py b/pproc-core/src/earthkit/workflows/plugins/pproc/fluent.py new file mode 100644 index 00000000..1c33e8bb --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/fluent.py @@ -0,0 +1,827 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 +from __future__ import annotations + +import inspect +from typing import Optional, Union, Any +from pydantic import TypeAdapter +import logging + +import numpy as np +from earthkit.workflows.backends.earthkit import FieldListBackend +from earthkit.workflows.nodetree import nodetree_size + +from earthkit.workflows import fluent +from earthkit.workflows.nodetree import ( + nodetree_array, + nodetree_arrays, + nodetree_dimensions, + nodetree_from_dict, +) +from earthkit.workflows.plugins.pproc.utils.request import MultiSourceRequest +from earthkit.workflows.plugins.pproc.utils.request import Request +from earthkit.workflows.plugins.pproc.utils.metadata import fill_template_values +from earthkit.workflows.plugins.pproc.config.mask import MaskExpression +from earthkit.workflows.plugins.pproc.config.threshold import Threshold +from earthkit.workflows.plugins.pproc.config.accumulation import ( + Coords, + Default, + AccumName, +) +from earthkit.workflows.plugins.pproc.metadata.accumulation import accumulation_metadata +from earthkit.workflows.plugins.pproc.metadata.threshold import threshold_metadata + + +ENVIRONMENT = { + "ppruntime": [ + "pproc-runtime", + ], +} + + +logger = logging.getLogger(__name__) + + +class Action(fluent.Action): + def _reduction_with_metadata( + self, + operation: str, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + batched = batch_size > 1 and self.nodes.sizes[dim] > batch_size + + if not batched or metadata is None: + if isinstance(operation, str): + if hasattr(super(), operation): + return getattr(super(), operation)( + dim=dim, + batch_size=batch_size, + keep_dim=keep_dim, + backend_kwargs={"metadata": metadata}, + ) + else: + operation = ( + fluent.Payload(operation, kwargs={"metadata": metadata}), + ) + else: + operation.kwargs.setdefault("metadata", {}).update(metadata or {}) + return super().reduce( + operation, + dim=dim, + batch_size=batch_size, + keep_dim=keep_dim, + ) + + if isinstance(operation, str): + if hasattr(super(), operation): + batched_action = getattr(super(), operation)( + dim=dim, batch_size=batch_size, keep_dim=keep_dim + ) + else: + batched_action = super().reduce( + fluent.Payload(operation), + dim=dim, + batch_size=batch_size, + keep_dim=keep_dim, + ) + else: + batched_action = super().reduce( + operation, dim=dim, batch_size=batch_size, keep_dim=keep_dim + ) + # If batched, add additional node for setting window operation metadata. Doing this in a separate tasks + # allows batched operations for overlapping windows to be identified and only computed once + return batched_action.map( + fluent.Payload( + FieldListBackend.set_metadata, [fluent.Node.input_name(0), metadata] + ) + ) + + def sum( + self, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + return self._reduction_with_metadata( + "sum", dim=dim, batch_size=batch_size, keep_dim=keep_dim, metadata=metadata + ) + + def mean( + self, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + return self._reduction_with_metadata( + "mean", dim=dim, batch_size=batch_size, keep_dim=keep_dim, metadata=metadata + ) + + def std( + self, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + return self._reduction_with_metadata( + "std", dim=dim, batch_size=batch_size, keep_dim=keep_dim, metadata=metadata + ) + + def max( + self, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + return self._reduction_with_metadata( + "max", dim=dim, batch_size=batch_size, keep_dim=keep_dim, metadata=metadata + ) + + maximum = max + + def min( + self, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + return self._reduction_with_metadata( + "min", dim=dim, batch_size=batch_size, keep_dim=keep_dim, metadata=metadata + ) + + minimum = min + + def prod( + self, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + return self._reduction_with_metadata( + "prod", dim=dim, batch_size=batch_size, keep_dim=keep_dim, metadata=metadata + ) + + def norm( + self, + dim: str = "", + batch_size: int = 0, + keep_dim: bool = False, + metadata: dict | None = None, + ) -> Action: + return self._reduction_with_metadata( + fluent.Payload(FieldListBackend.norm), + dim=dim, + batch_size=batch_size, + keep_dim=keep_dim, + metadata=metadata, + ) + + def subtract( + self, other: Union[Action, float], metadata: dict | None = None + ) -> Action: + return super().subtract(other, backend_kwargs={"metadata": metadata}) + + def divide( + self, other: Union[Action, float], metadata: dict | None = None + ) -> Action: + return super().divide(other, backend_kwargs={"metadata": metadata}) + + def add(self, other: Union[Action, float], metadata: dict | None = None) -> Action: + return super().add(other, backend_kwargs={"metadata": metadata}) + + def multiply( + self, other: Union[Action, float], metadata: dict | None = None + ) -> Action: + return super().multiply(other, backend_kwargs={"metadata": metadata}) + + def scale(self, value: float, metadata: dict | None = None) -> Action: + return super().multiply(value, backend_kwargs={"metadata": metadata}) + + def power( + self, other: Union[Action, float], metadata: dict | None = None + ) -> Action: + return super().power(other, backend_kwargs={"metadata": metadata}) + + def extreme( + self, + operation: str, + climatology: fluent.Action, + step_ranges: list[str], + ensemble_dim: str = "number", + step_dim: str = "step", + **kwargs, + ) -> Action: + return self.concatenate(ensemble_dim).__getattribute__(operation)( + climatology, step_ranges, dim=step_dim, **kwargs + ) + + def efi( + self, + climatology: fluent.Action, + step_ranges: list[str], + eps: float, + dim: str = "step", + metadata: dict | None = None, + ) -> Action: + """ + Create nodes computing the EFI for each window. Expects ensemble member dimension + to already be concatenated into a single array. + + Parameters + ---------- + climatology: Action, nodes containing climatology data + step_ranges: list of str, list of step ranges + eps: float + dim: str, window dimension + + Return + ------ + Action + """ + eps = float(eps) + if nodetree_size(self.nodes) == 1: + if len(step_ranges) != 1: + raise ValueError("Single node, but multiple step ranges") + payload = fluent.Payload( + "ppruntime.stats.efi", + (fluent.Node.input_name(1), fluent.Node.input_name(0), eps), + kwargs={"metadata": metadata}, + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ) + return self.join(climatology, "**datatype**").reduce(payload) # type: ignore + + join = self.join(climatology, "**datatype**", match_coord_values=True) + return join.transform( + _efi_window_transform, + [({dim: srange}, eps, metadata) for srange in step_ranges], + dim, + ) # type: ignore + + def sot( + self, + climatology: fluent.Action, + step_ranges: list[str], + eps: float, + sot: list[int], + dim: str = "step", + new_dim: str = "sot", + metadata: dict | None = None, + ) -> Action: + """ + Create nodes computing the SOT for each window. Expects ensemble member dimension + to already be concatenated into a single array. + + Parameters + ---------- + climatology: Action, nodes containing climatology data + step_ranges: list of str, list of step ranges + eps: float + sot: list of ints, Shift-Of-Tail values + dim: str, window dimension + new_dim: str, name of new dimension corresponding to SOT nodes. + + Return + ------ + Action + """ + eps = float(eps) + if not isinstance(sot, list): + sot = [sot] + + if nodetree_size(self.nodes) == 1: + if len(step_ranges) != 1: + raise ValueError("Single node, but multiple step ranges") + ret = self.join( + climatology, "**datatype**", match_coord_values=True + ).transform( + _sot_transform, + [(int(num), eps, new_dim, metadata) for num in sot], + new_dim, + ) + else: + params = [ + ({dim: srange}, sot, eps, new_dim, metadata) for srange in step_ranges + ] + ret = self.join( + climatology, "**datatype**", match_coord_values=True + ).transform(_sot_window_transform, params, dim) + return ret # type: ignore + + def threshold_probability( + self, + thresholds: list[Union[Threshold, dict]], + dim: str = "number", + batch_size: int = 0, + metadata: Optional[dict] = None, + clim_metadata: Optional[dict] = None, + ) -> Action: + combined: Action = None + for threshold in thresholds: + if isinstance(threshold, dict): + threshold = Threshold(**threshold) + selected = self.sel(threshold.select) if threshold.select else self + selected = selected.map( + fluent.Payload( + "ppruntime.stats.mask", + (fluent.Node.input_name(0),), + threshold.model_dump( + exclude={"select", "lower_scale_factor", "upper_scale_factor"} + ), + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ) + ) + if combined is None: + combined = selected + else: + combined = combined.join(selected, dim="param").reduce( # type: ignore + fluent.Payload( + "ppruntime.stats.logical_and", + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ), + dim="param", + ) + + base_threshold = ( + thresholds[0] + if isinstance(thresholds[0], Threshold) + else Threshold(**thresholds[0]) + ) + thr_metadata = threshold_metadata( + threshold=base_threshold, metadata=metadata, clim_metadata=clim_metadata + ) + return combined.multiply(100).mean( + dim=dim, batch_size=batch_size, metadata=thr_metadata + ) + + def anomaly( + self, + clim_mean: fluent.Action, + clim_std: fluent.Action, + std_anomaly: bool = False, + metadata: dict | None = None, + ) -> Action: + anom = self.subtract(clim_mean, metadata=metadata) # type: ignore + if not std_anomaly: + return anom + return anom.divide(clim_std) # type: ignore + + def quantiles( + self, + quantiles: int | list[float] | str, + dim: str = "number", + new_dim: str = "quantile", + metadata: dict | None = None, + ) -> Action: + """ + Compute quantiles over the specified dimension. If quantiles is an integer, it will compute that many evenly spaced quantiles. + If quantiles is a string, it should be in the format "q_number:total_number". + If quantiles is a list of floats, it will compute the quantiles at the specified values. + + Parameters + ---------- + quantiles: int | list[float] | str, quantiles to compute + dim: str, dimension to compute quantiles over + new_dim: str, name of the new dimension for quantiles + metadata: dict, optional metadata to set on the output + """ + if isinstance(quantiles, int): + total_number = quantiles + q_numbers = range(0, quantiles + 1) + elif isinstance(quantiles, str): + q_number, total_number = map(int, quantiles.split(":")) + q_numbers = [q_number] + else: + even_spacing = np.all(np.diff(quantiles) == quantiles[1] - quantiles[0]) + total_number = len(quantiles) - 1 if even_spacing else 100 + q_numbers = ( + range(0, len(quantiles)) if even_spacing else map(int, quantiles * 100) + ) + + params = [(x, total_number, new_dim, metadata) for x in q_numbers] + ret = self.concatenate(dim).transform(_quantiles_transform, params, new_dim) + return ret # type: ignore + + def _wrapped_reduction( + self, + operation: str | fluent.Payload | None, + dim: str, + **kwargs, + ) -> Action: + if operation is None: + return self + + if isinstance(operation, str): + # operation is fluent method + if hasattr(self, operation): + op = getattr(self, operation) + sig = inspect.signature(op) + args = [ + p.name + for p in sig.parameters.values() + if p.kind == p.POSITIONAL_OR_KEYWORD + ] + if "dim" in args: + kwargs["dim"] = dim + return op(**kwargs) + # operation is payload + op_function = getattr(FieldListBackend, operation, None) or operation + operation = fluent.Payload( + op_function, + ) + # Fallback on applying reduction operation during payload + return self.reduce(operation, dim=dim, **kwargs) # type: ignore + + def preprocessing( + self, + operation: str | fluent.Payload | None, + dim: str = "param", + **kwargs, + ) -> Action: + """ + Pre-processing operation across different parameters + + Params + ------ + operation: str or Payload, operation to perform on ensemble members + dim: str, dimension to perform operation along + + Return + ------ + Action + """ + return self._wrapped_reduction(operation, dim, **kwargs) + + def thermal_index( + self, + function: str, + params: list[str], + deaccumulate: Optional[list[str]] = None, + dim: str = "param", + join: bool = True, + metadata: dict | None = None, + ) -> Action: + """ + Thermal index computation + + Params + ------ + function: str, pproc-runtime function to call for thermal index computation + params: list[str], list of input parameters + deaccumulate: list[str], list of parameters that require deaccumulating + dim: str, parameter dimension + join: bool, whether to join the resulting action with input action + metadata: dict, metadata to set on the output + """ + logger.debug( + f"Thermal index: function {function}, params {params}, deaccumulate {deaccumulate}" + ) + if deaccumulate is not None: + deaccum = self.sel(param=deaccumulate) + array = nodetree_array(deaccum.nodes) + steps = array.coords["step"].data.tolist() + deaccum = deaccum.accumulation( + operation=None, + coords=[[steps[x], steps[x + 1]] for x in range(len(steps) - 1)], + deaccumulate=True, + metadata={"stepType": "diff"}, + ) + deaccum = type(self)( + nodetree_from_dict( + { + path: array.assign_coords( + {"step": steps[1] if len(steps) <= 2 else steps[1:]} + ) + for path, array in nodetree_arrays(deaccum.nodes) + } + ) + ) + param_action = fluent.merge( + self.select( + param=[x for x in params if x not in deaccumulate], + step=steps[1:], + expand=True, + ), + deaccum, + ) + param_action._squeeze_dimension("step") + param_action = param_action.combine_branches(dim=dim) + else: + param_action = self.select(param=params, expand=True) + param_action._squeeze_dimension("step") + param_action = param_action.combine_branches(dim=dim) + + if method := getattr(param_action, function, None): + ret = method(dim=dim, metadata=metadata) + else: + ret = param_action._wrapped_reduction( + fluent.Payload( + func=function, + kwargs={"metadata": metadata or {}}, + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ), + dim=dim, + ) + ret._add_dimension(dim, str(metadata.get("paramId"))) + if not join: + return ret + ret = ret.set_path(f"/{metadata.get('paramId')}") + return fluent.merge(self, ret) + + def mask( + self, + select: dict, + mask: Union[MaskExpression, dict], + replacement: float = 0.0, + dim: str = "param", + metadata: dict | None = None, + ) -> Action: + if isinstance(mask, dict): + mask = MaskExpression(**mask) + mask_action = self.sel(mask.select, drop=True) if select else self + mask_action = mask_action.map( + fluent.Payload( + "ppruntime.stats.mask", + (fluent.Node.input_name(0),), + {"lower_comparison": mask.comparison, "lower_value": mask.value}, + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ) + ) + return ( + self.sel(select, drop=True) + .join(mask_action, dim=dim) + ._wrapped_reduction( + fluent.Payload( + FieldListBackend.filter, kwargs={"replacement": replacement} + ), + dim=dim, + metadata=metadata, + ) + ) + + def ensemble_statistics( + self, + operation: str | fluent.Payload | None, + dim: str = "number", + metadata: dict | None = None, + **kwargs, + ) -> Action: + """ + Reduction operation across ensemble members. If batch_size > 1 and less than the size + of the named dimension, the reduction will be computed first in + batches and then aggregated, otherwise no batching will be performed. + + Params + ------ + operation: str or Payload, operation to perform on ensemble members + dim: str, dimension to perform operation along + computation is not batched + + Return + ------ + Action + + Raises + ------ + ValueError if payload function is not batchable and batch_size is not 0 + """ + metadata = metadata or {} + + for _, narray in nodetree_arrays(self.nodes): + if dim not in narray.coords: + raise ValueError( + f"Dimension {dim} not found in nodes for ensemble_statistics" + ) + stat_metadata = fill_template_values( + metadata, {"num_fields": narray.coords[dim].size} + ) + break + + kwargs.setdefault("metadata", {}).update(stat_metadata) + return self._wrapped_reduction(operation, dim, **kwargs) + + def accumulation( + self, + operation: Optional[str | fluent.Payload], + coords: list[Coords], + dim: str = "step", + metadata: dict | None = None, + deaccumulate: bool = False, + name: Union[AccumName, dict] = Default(), + **kwargs, + ) -> Action: + """ + Reduction operation across a dimension. If batch_size > 1 and less than the size + of the named dimension, the reduction will be computed first in + batches and then aggregated, otherwise no batching will be performed. + + Params + ------ + operation: str or Payload, operation to perform on steps + coords: list of values to accumulate over + dim: str, dimension to perform operation along + metadata: optional dict, metadata to set on the output + deaccumulate: bool, whether to deaccumulate consecutive values before accumulation + + Return + ------ + Action + + Raises + ------ + ValueError if payload function is not batchable and batch_size is not 0 + """ + params = [ + ( + dim, + coord, + operation, + metadata, + deaccumulate, + name, + kwargs, + ) + for coord in coords + ] + return self.transform(_accum_transform, params, dim) # type: ignore + + def write(self, targets: list[dict], metadata: Optional[dict] = None) -> Action: + if len(targets) == 0: + raise ValueError("No targets provided for write") + return self.transform( + _write_transform, + [(target, metadata) for target in targets], + dim="target", + ) # type: ignore + + +def _write_transform( + action: fluent.Action, target: dict, metadata: Optional[dict] = None +) -> fluent.Action: + kwargs = target.copy() + if metadata is not None: + kwargs["metadata"] = metadata + return action.map( + fluent.Payload( + "ppruntime.io.write", + (fluent.Node.input_name(0),), + kwargs, + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ) + ) + + +def _sot_transform( + action: fluent.Action, number: int, eps: float, new_dim: str, metadata: dict | None +) -> fluent.Action: + new_sot = action.reduce( + fluent.Payload( + "ppruntime.stats.sot", + (fluent.Node.input_name(1), fluent.Node.input_name(0), number, eps), + kwargs={"metadata": metadata}, + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ) + ) + new_sot._add_dimension(new_dim, number) + return new_sot + + +def _sot_window_transform( + action: fluent.Action, + selection: dict, + sot: list[int], + eps: float, + new_dim: str, + metadata: dict, +) -> fluent.Action: + return action.select(selection).transform( + _sot_transform, [(int(num), eps, new_dim, metadata) for num in sot], new_dim + ) + + +def _efi_window_transform( + action: fluent.Action, selection: dict, eps: float, metadata: dict | None +) -> fluent.Action: + ret = action.select(selection).reduce( + fluent.Payload( + "ppruntime.stats.efi", + (fluent.Node.input_name(1), fluent.Node.input_name(0), eps), + kwargs={"metadata": metadata}, + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ), + dim="**datatype**", + ) + return ret + + +def _quantiles_transform( + action, q_number: int, total_number: int, new_dim: str, metadata: dict | None +): + payload = fluent.Payload( + "ppruntime.stats.quantiles", + (fluent.Node.input_name(0), q_number, total_number), + kwargs={"metadata": metadata}, + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ) + new_quantile = action.map(payload) + new_quantile._add_dimension(new_dim, q_number / total_number) + return new_quantile + + +def _accum_transform( + action: fluent.Action, + dim: str, + coords: Coords, + operation: str | fluent.Payload, + metadata: Optional[dict] = None, + deaccumulate: bool = False, + name: Union[AccumName, dict] = Default(), + kwargs: dict = {}, +) -> fluent.Action: + if deaccumulate: + accum_action = action.select({dim: coords[:-1]}) + accum_action = accum_action.subtract(action.select({dim: coords[1:]})) + else: + if len(coords) == 1 and dim not in nodetree_dimensions(action.nodes): + accum_action = action + else: + accum_action = action.select({dim: coords}) + + if isinstance(name, dict): + name = TypeAdapter(AccumName, name).validate_python() + accum_name = name.name(coords) + accum_metadata = accumulation_metadata(dim, coords, accum_name, metadata) + + if operation is None: + accum_action._squeeze_dimension(dim) + if len(accum_metadata) > 0: + accum_action = accum_action.map( + fluent.Payload( + FieldListBackend.set_metadata, + [fluent.Node.input_name(0), accum_metadata], + ) + ) + else: + if isinstance(operation, fluent.Payload): + operation.kwargs.setdefault("metadata", {}).update(accum_metadata) + else: + kwargs["metadata"] = accum_metadata + accum_action = accum_action._wrapped_reduction( + operation, + dim=dim, + **kwargs, + ) + + accum_action._add_dimension(dim, accum_name) + + return accum_action + + +def from_source( + sources: list[Union[str, dict]], + requests: Union[list[dict[str, Any]], list[Request], list[MultiSourceRequest]], + dtype: Optional[str] = None, + join_key: str = "", +): + all_actions = None + for request in requests: + if isinstance(request, dict): + request = Request(request) + payloads = np.empty(tuple(request.dims().values()), dtype=object) + for indices, new_request in request.expand(): + payloads[indices] = fluent.Payload( + "ppruntime.io.retrieve", + [sources, [new_request], dtype], + metadata={"environment": ENVIRONMENT["ppruntime"]}, + ) + new_action = fluent.from_source( + payloads, + dims=request.dims().keys(), + coords={ + key: request[key] for key in request.dims(exclude_scalar=False).keys() + }, + action=Action, + ) + + if len(join_key) != 0 and join_key not in new_action.nodes.coords: + new_action._add_dimension(join_key, request[join_key]) + + if all_actions is None: + all_actions = new_action + else: + if len(join_key) == 0: + raise ValueError("Join key must be specified for multiple requests") + all_actions = all_actions.join(new_action, join_key) + return all_actions + + +def path_from_request(request: dict, keys: list[str] = ["levtype", "param"]) -> str: + return "/".join([str(request[x]) for x in keys if x in request]) diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/metadata/accumulation.py b/pproc-core/src/earthkit/workflows/plugins/pproc/metadata/accumulation.py new file mode 100644 index 00000000..d38eb9e0 --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/metadata/accumulation.py @@ -0,0 +1,56 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional +from earthkit.workflows.plugins.pproc.config.accumulation import Coords +from earthkit.workflows.plugins.pproc.utils.metadata import fill_template_values + + +def accumulation_metadata( + dim: str, coords: Coords, name: str, metadata: Optional[dict] = None +) -> dict: + metadata = (metadata or {}).copy() + if dim == "step": + steps = name.split("-") + if len(steps) > 1: + start = int(steps[0].split("_")[-1]) + end = int(steps[-1].split("_")[0]) + else: + start = coords[0] + end = start + + if end != start: + assert isinstance(start, int) and isinstance(end, int) + assert end > start, "Start step can not be greater than end step" + steprange = f"{start}-{end}" + if end >= 256 and metadata.get("edition", 1) == 1: + # The range is encoded as two 8-bit integers + metadata.setdefault("unitOfTimeRange", 11) + if coords[0] != steprange: + metadata.setdefault( + "stepType", "max" + ) # Don't override if set in config + metadata["stepRange"] = steprange + else: + assert end == start + if "timeRangeIndicator" not in metadata: + assert isinstance(end, int) + if end >= 256: + metadata["timeRangeIndicator"] = 10 + elif end == 0: + metadata["timeRangeIndicator"] = 1 + else: + metadata["timeRangeIndicator"] = 0 + metadata.setdefault("step", str(start)) + else: + start = coords[0] + end = coords[-1] + return fill_template_values( + metadata, + { + "num_coords": len(coords), + "start_coord": start, + "end_coord": end, + }, + ) diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/metadata/threshold.py b/pproc-core/src/earthkit/workflows/plugins/pproc/metadata/threshold.py new file mode 100644 index 00000000..f30aa252 --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/metadata/threshold.py @@ -0,0 +1,99 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional + +from earthkit.workflows.plugins.pproc.config.threshold import Threshold + + +def threshold_metadata( + threshold: Threshold, + metadata: Optional[dict] = None, + clim_metadata: Optional[dict] = None, +) -> dict: + metadata = metadata or {} + edition = metadata.get("edition", 1) + thr_metadata = {} + if "paramId" in metadata: + thr_metadata["paramId"] = metadata["paramId"] + + if threshold.upper_comparison is None: + threshold_value = round( + threshold.lower_value * 10**threshold.lower_scale_factor + ) + comparison = threshold.lower_comparison.strip("=") + if edition == 1 and comparison == "<": + thr_metadata.update( + { + "localDefinitionNumber": 5, + "localDecimalScaleFactor": threshold.lower_scale_factor, + "thresholdIndicator": 2, + "upperThreshold": threshold_value, + } + ) + elif edition == 1 and comparison == ">": + thr_metadata.update( + { + "localDefinitionNumber": 5, + "localDecimalScaleFactor": threshold.lower_scale_factor, + "thresholdIndicator": 1, + "lowerThreshold": threshold_value, + } + ) + elif edition == 2: + # GRIB 2 has probability types above/below upper/lower limits (see Code Table 4.9) + # where the threshold value can correspond to either limit. + # Default is to use limit_type=lower probability types + prob_types = { + "<": {"upper": 4, "lower": 0}, + ">": {"upper": 1, "lower": 3}, + } + if not metadata.get("probabilityType", None): + limit_type = "lower" + probability_type = prob_types[comparison][limit_type] + else: + probability_type = metadata["probabilityType"] + if probability_type in [0, 3]: + limit_type = "lower" + elif probability_type in [1, 4]: + limit_type = "upper" + else: + raise ValueError( + f"Unsupported probability type {probability_type} for threshold comparison {comparison}" + ) + missing = "Upper" if limit_type == "lower" else "Lower" + thr_metadata.update( + { + f"scaleFactorOf{limit_type.capitalize()}Limit": threshold.lower_scale_factor, + f"scaledValueOf{limit_type.capitalize()}Limit": threshold_value, + "probabilityType": probability_type, + f"scaleFactorOf{missing}Limit": "MISSING", + f"scaledValueOf{missing}Limit": "MISSING", + } + ) + thr_metadata.update(clim_metadata or {}) + else: + raise ValueError( + f"Unsupported threshold comparison {comparison} for grib edition {edition}" + ) + thr_metadata.update(metadata) + return thr_metadata + if edition != 2: + raise ValueError("Threshold ranges are only supported for GRIB edition 2") + thr_metadata.update( + { + "scaleFactorOfLowerLimit": threshold.lower_scale_factor, + "scaledValueOfLowerLimit": round( + threshold.lower_value * 10**threshold.lower_scale_factor, 0 + ), + "probabilityType": 2, + "scaleFactorOfUpperLimit": threshold.upper_scale_factor, + "scaledValueOfUpperLimit": round( + threshold.upper_value * 10**threshold.upper_scale_factor, 0 + ), + } + ) + thr_metadata.update(clim_metadata or {}) + thr_metadata.update(metadata) + return thr_metadata diff --git a/src/pproc/quantile/__init__.py b/pproc-core/src/earthkit/workflows/plugins/pproc/utils/__init__.py similarity index 100% rename from src/pproc/quantile/__init__.py rename to pproc-core/src/earthkit/workflows/plugins/pproc/utils/__init__.py diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/utils/metadata.py b/pproc-core/src/earthkit/workflows/plugins/pproc/utils/metadata.py new file mode 100644 index 00000000..ea951e1b --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/utils/metadata.py @@ -0,0 +1,31 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import re + +_TEMPLATE_RE = re.compile("^{([a-z_]*)}:?([a-z]*)$", re.I) +_TYPES = { + "int": int, + "str": str, + "float": float, +} + + +def fill_template_value(val: str, template_map: dict): + m = _TEMPLATE_RE.fullmatch(val) + if m is None: + return val + value, tp = m.groups() + if value not in template_map: + return val + + return template_map[value] if len(tp) == 0 else _TYPES[tp](template_map[value]) + + +def fill_template_values(metadata: dict, template_map: dict) -> dict: + metadata = metadata.copy() + for key, val in metadata.items(): + if isinstance(val, str): + metadata[key] = fill_template_value(val, template_map) + return metadata diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/utils/pydantic_utils.py b/pproc-core/src/earthkit/workflows/plugins/pproc/utils/pydantic_utils.py new file mode 100644 index 00000000..97a37292 --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/utils/pydantic_utils.py @@ -0,0 +1,9 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from pydantic import BaseModel, ConfigDict + + +class PProcBaseModel(BaseModel): + model_config = ConfigDict(extra="forbid") diff --git a/pproc-core/src/earthkit/workflows/plugins/pproc/utils/request.py b/pproc-core/src/earthkit/workflows/plugins/pproc/utils/request.py new file mode 100644 index 00000000..21b1a3f9 --- /dev/null +++ b/pproc-core/src/earthkit/workflows/plugins/pproc/utils/request.py @@ -0,0 +1,117 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import copy +import itertools +from typing import Optional +from collections import OrderedDict + +import numpy as np + + +class Request: + def __init__(self, request: dict, no_expand: Optional[tuple[str]] = None): + self.request = request.copy() + self.fake_dims = [] + self.no_expand = no_expand or tuple() + self.ignore = ["interpolate"] + + def dims(self, exclude_scalar: bool = True) -> OrderedDict: + dimensions = OrderedDict() + for key, values in self.request.items(): + if key in self.ignore or key in self.no_expand: + continue + if exclude_scalar and np.ndim(values) == 0: + continue + dimensions[key] = np.size(values) + return dimensions + + def __setitem__(self, key, value): + self.request[key] = value + + def __getitem__(self, key): + return self.request[key] + + def __contains__(self, key) -> bool: + return key in self.request + + def update(self, **kwargs): + self.request.update(**kwargs) + + def pop(self, key, default=None): + if default is None: + return self.request.pop(key) + return self.request.pop(key, default) + + def make_dim(self, key, value=None): + if key in self: + assert isinstance(self[key], (str, int, float)) + self[key] = [self[key]] + else: + self[key] = [value] + self.fake_dims.append(key) + + def expand(self): + reqs = [self.request[x] for x in self.dims().keys()] + for indices, params in zip( + itertools.product(*(range(len(x)) for x in reqs)), itertools.product(*reqs) + ): + new_request = self.request.copy() + for index, expand_param in enumerate(self.dims().keys()): + new_request[expand_param] = params[index] + + # Remove fake dims from request + for dim in self.fake_dims: + new_request.pop(dim) + yield indices, new_request + + +class MultiSourceRequest(Request): + def __init__(self, requests: list[dict], no_expand: Optional[tuple[str]] = None): + super().__init__(requests[0], no_expand) + self.requests = requests + + def __setitem__(self, key, value): + super().__setattr__(key, value) + [x.__setitem__(key, value) for x in self.requests] + + def __getitem__(self, key): + values = [x.__getitem__(key) for x in self.requests] + if np.all([values[0] == values[x] for x in range(1, len(values))]): + return values[0] + raise Exception(f"Requests {self.requests} differ on value for key {key}") + + def __contains__(self, key) -> bool: + contains = [x.__contains__(key) for x in self.requests] + if all([contains[0] == contains[x] for x in range(1, len(contains))]): + return contains[0] + raise Exception(f"Not all requests {self.requests} contain key {key}") + + def update(self, **kwargs): + super().update(**kwargs) + [x.update(**kwargs) for x in self.requests] + + def pop(self, key, default=None): + contains = key in self + if default is None or contains: + value = self[key] + super().pop(key) + [x.pop(key) for x in self.requests] + return value + super().pop(key) + [x.pop(key) for x in self.requests] + return default + + def expand(self): + for params in itertools.product(*[self.request[x] for x in self.dims().keys()]): + indices = [] + new_requests = copy.deepcopy(self.requests) + for index, expand_param in enumerate(self.dims().keys()): + [x.__setitem__(expand_param, params[index]) for x in new_requests] + indices.append(list(self.request[expand_param]).index(params[index])) + + # Remove fake dims from request + for dim in self.fake_dims: + [x.pop(dim) for x in new_requests] + yield tuple(indices), new_requests diff --git a/pproc-core/src/ppcore/__init__.py b/pproc-core/src/ppcore/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pproc-core/src/ppcore/config.py b/pproc-core/src/ppcore/config.py new file mode 100644 index 00000000..122055ec --- /dev/null +++ b/pproc-core/src/ppcore/config.py @@ -0,0 +1,295 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import argparse +import sys +import os +from typing import List +import logging + +import yaml +import json +from pydantic import TypeAdapter + +from ppcore.configs import from_outputs as config_from_outputs +from ppcore.configs import from_inputs as config_from_inputs +from ppcore.configs.entrypoint.base import EntrypointConfig +from ppcore.products import product_from_config, graph_from_configs +from ppcore.utils import mars +from ppcore.utils.requests import datacubes, expand +from ppcore.schema.forecast import DatasetDefinition + +logging.basicConfig( + format="%(asctime)s; %(name)s; %(levelname)s - %(message)s", + level=os.environ.get("PPROC_LOG", "INFO").upper(), +) + + +def from_outputs(args): + overrides = {} + if args.overrides: + with open(args.overrides, "r") as f: + overrides = yaml.safe_load(f) + + with open(args.outputs, "r") as f: + output_requests = yaml.safe_load(f) + + forecast = args.forecast + if os.path.exists(forecast): + with open(forecast, "r") as f: + forecast = TypeAdapter(DatasetDefinition).validate_python( + **yaml.safe_load(f) + ) + + climatology = args.climatology + if climatology and os.path.exists(climatology): + with open(climatology, "r") as f: + climatology = TypeAdapter(DatasetDefinition).validate_python( + **yaml.safe_load(f) + ) + + entrypoint_config = EntrypointConfig( + products=list( + config_from_outputs( + output_requests, args.schema, forecast=forecast, climatology=climatology + ) + ), + **overrides, + ) + with open(args.config, "w") as f: + yaml.dump( + entrypoint_config.model_dump(exclude_none=True, by_alias=True), + f, + sort_keys=False, + ) + + +def from_inputs(args): + overrides = {} + if args.overrides: + with open(args.overrides, "r") as f: + overrides = yaml.safe_load(f) + + forecast = args.forecast + if os.path.exists(forecast): + with open(forecast, "r") as f: + forecast = TypeAdapter(DatasetDefinition).validate_python( + **yaml.safe_load(f) + ) + + climatology = args.climatology + if climatology and os.path.exists(climatology): + with open(climatology, "r") as f: + climatology = TypeAdapter(DatasetDefinition).validate_python( + **yaml.safe_load(f) + ) + + entrypoint_config = EntrypointConfig( + products=list( + config_from_inputs( + args.restriction, + args.schema, + forecast, + climatology=climatology, + **overrides, + ) + ), + **overrides, + ) + with open(args.config, "w") as f: + yaml.dump( + entrypoint_config.model_dump(exclude_none=True, by_alias=True), + f, + sort_keys=False, + ) + + +def _to_mars(requests: list[dict]) -> str: + ret = b"" + for req in requests: + source = req.pop("source", None) + target = req.pop("target", None) + # Reverse source/target keys so request can be used to + # create/extract from the input/output files + if source and source not in ["fdb", "mars"]: + req["target"] = f"'{source}'" + elif target and target != "fdb": + req["source"] = f"'{target}'" + ret += mars.to_mars(b"retrieve", req) + ret += b"\n" + return ret.decode("utf-8") + + +def requests(args): + with open(args.config, "r") as f: + config = yaml.safe_load(f) + entrypoint_config = EntrypointConfig(**config) + + inputs = [] + outputs = [] + for prod_config in entrypoint_config.products: + product = product_from_config(prod_config) + + inputs.extend(product.in_mars(args.source)) + outputs.extend(product.out_mars(args.target)) + + inputs = list(expand(datacubes(inputs), dim="type")) + outputs = list(expand(datacubes(outputs), dim="type")) + + # TODO: Add method to simplify requests + if args.inputs: + _, extension = os.path.splitext(args.inputs) + with open(args.inputs, "w") as f: + if args.mars: + f.write(_to_mars(inputs)) + elif extension == ".json": + json.dump(inputs, f, sort_keys=False, indent=2) + else: + yaml.dump(inputs, f, sort_keys=False) + + if args.outputs: + _, extension = os.path.splitext(args.outputs) + with open(args.outputs, "w") as f: + if args.mars: + f.write(_to_mars(outputs)) + elif extension == ".json": + json.dump(outputs, f, sort_keys=False, indent=2) + else: + yaml.dump(outputs, f, sort_keys=False) + + +def plot(args): + with open(args.config, "r") as f: + config = yaml.safe_load(f) + entrypoint_config = EntrypointConfig(**config) + + graph = graph_from_configs( + entrypoint_config.products, + entrypoint_config.input_overrides, + entrypoint_config.output_overrides, + ) + from earthkit.workflows.visualise import visualise + + visualise(graph, args.file) + + +def main(args: List[str] = sys.argv[1:]): + parser = argparse.ArgumentParser("Generate configuration file for PProc") + parser.add_argument( + "--config", + type=str, + required=True, + help="Path to configuration file", + ) + + subparsers = parser.add_subparsers(required=True) + output_parser = subparsers.add_parser( + "from_outputs", help="Generate configuration from output requests" + ) + output_parser.add_argument( + "--outputs", type=str, required=True, help="Path to output request file" + ) + output_parser.add_argument( + "--schema", type=str, required=True, help="Path to products schema" + ) + output_parser.add_argument( + "--forecast", + type=str, + required=True, + help="Path to forecast definition, or name of preset definition in schema", + ) + output_parser.add_argument( + "--climatology", + type=str, + required=False, + default=None, + help="Path to climatology definition, or name of preset definition in schema", + ) + output_parser.add_argument( + "--overrides", + type=str, + required=False, + help="Path to configuration template for overriding default configuration", + ) + output_parser.set_defaults(func=from_outputs) + + input_parser = subparsers.add_parser( + "from_inputs", help="Generate configuration from input requests" + ) + input_parser.add_argument( + "--inputs", type=str, required=True, help="Path to input request file" + ) + input_parser.add_argument( + "--schema", type=str, required=True, help="Path to products schema" + ) + input_parser.add_argument( + "--forecast", + type=str, + required=True, + help="Path to forecast definition, or name of preset definition in schema", + ) + input_parser.add_argument( + "--climatology", + type=str, + required=False, + default=None, + help="Path to climatology definition, or name of preset definition in schema", + ) + input_parser.add_argument( + "--restriction", + type=str, + required=False, + help="Restriction to place on output requests e.g. type=em", + ) + input_parser.add_argument( + "--overrides", + type=str, + required=False, + help="Path to configuration template for overriding default configuration", + ) + input_parser.set_defaults(func=from_inputs) + + request_parser = subparsers.add_parser( + "requests", help="Generate input/output requests from PProc config file" + ) + request_parser.add_argument( + "--outputs", type=str, required=False, help="Path to output request file" + ) + request_parser.add_argument( + "--target", + action="append", + default=None, + help="Target type to select output requests for", + ) + request_parser.add_argument( + "--inputs", type=str, required=False, help="Path to input request file" + ) + request_parser.add_argument( + "--source", + action="append", + default=None, + help="Source type to select input requests for", + ) + request_parser.add_argument( + "--mars", + action="store_true", + default=False, + help="Output in MARS request format", + ) + request_parser.set_defaults(func=requests) + + plot_parser = subparsers.add_parser( + "plot", help="Generate plot of earthkit-workflows graph from PProc config file" + ) + plot_parser.add_argument( + "--file", type=str, required=False, help="Path to graph html file" + ) + plot_parser.set_defaults(func=plot) + + parsed = parser.parse_args(args) + parsed.func(parsed) + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/pproc-core/src/ppcore/configs/__init__.py b/pproc-core/src/ppcore/configs/__init__.py new file mode 100644 index 00000000..e0720813 --- /dev/null +++ b/pproc-core/src/ppcore/configs/__init__.py @@ -0,0 +1,80 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +from typing import Iterator, Optional, Union + +from ppcore.schema.schema import Schema +from ppcore.schema.forecast import ( + ForecastDefinition, + ReforecastDefinition, + ClimatologyDefinition, +) +from ppcore.configs.product import from_schema, ProductConfig +from ppcore.utils.requests import expand + + +def config_from_output( + request: dict, + pproc_schema: Union[str, os.PathLike, Schema], + forecast: Union[ForecastDefinition, ReforecastDefinition], + climatology: Optional[ClimatologyDefinition] = None, + metadata: Optional[dict] = None, + **overrides, +) -> ProductConfig: + if isinstance(pproc_schema, Schema): + schema = pproc_schema + else: + schema = Schema.from_file(pproc_schema) + schema_config = schema.config_from_output(request, forecast, climatology) + return from_schema(schema_config, request, metadata, **overrides) + + +def from_outputs( + requests: list[dict], + pproc_schema: Union[str, os.PathLike, Schema], + forecast: Union[str, ForecastDefinition, ReforecastDefinition], + climatology: Optional[Union[str, ClimatologyDefinition]] = None, + metadata: Optional[dict] = None, + **overrides, +) -> Iterator[ProductConfig]: + """ + Returns product configuration from output request and PProc schema + """ + if isinstance(pproc_schema, Schema): + schema = pproc_schema + else: + schema = Schema.from_file(pproc_schema) + if isinstance(forecast, str): + forecast = schema.datasets.definition(forecast) + if isinstance(climatology, str): + climatology = schema.datasets.definition(climatology) + for request in expand(requests): + schema_config = schema.config_from_output(request, forecast, climatology) + yield from_schema(schema_config, request, metadata, **overrides) + + +def from_inputs( + template: dict, + pproc_schema: Union[str, os.PathLike, Schema], + forecast: Union[str, ForecastDefinition, ReforecastDefinition], + climatology: Optional[Union[str, ClimatologyDefinition]] = None, + metadata: Optional[dict] = None, + **overrides, +) -> Iterator[ProductConfig]: + """ + Returns product configuration from input forecast, template for the output request and PProc schema + """ + if isinstance(pproc_schema, Schema): + schema = pproc_schema + else: + schema = Schema.from_file(pproc_schema) + if isinstance(forecast, str): + forecast = schema.datasets.definition(forecast) + if isinstance(climatology, str): + climatology = schema.datasets.definition(climatology) + for schema_config in schema.config_from_input( + forecast, climatology, output_template=template + ): + yield from_schema(schema_config, template, metadata, **overrides) diff --git a/pproc-core/src/ppcore/configs/common/__init__.py b/pproc-core/src/ppcore/configs/common/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pproc-core/src/ppcore/configs/common/accumulation.py b/pproc-core/src/ppcore/configs/common/accumulation.py new file mode 100644 index 00000000..3549086d --- /dev/null +++ b/pproc-core/src/ppcore/configs/common/accumulation.py @@ -0,0 +1,145 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional, Union, Literal, Annotated, Any + +from pydantic import Discriminator, Field, Tag, field_validator, model_validator + +from earthkit.workflows.fluent import Payload +from earthkit.workflows.plugins.pproc.config.accumulation import ( + Default, + Monthly, +) +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel + +Coords = Union[list[str], list[int]] + + +class BaseAccumulation(PProcBaseModel): + coords: list[Coords] + payload: Optional[str] = None + metadata: Optional[dict] = None + deaccumulate: bool = False + name: Annotated[ + Union[Default, Monthly], + Field(discriminator="type_", default_factory=Default), + ] + + @model_validator(mode="before") + def validate_config(cls, data: Any) -> Any: + if isinstance(data, dict): + # TODO Update schema to remove these keys + data.pop("type", None) + return data + + @field_validator("coords", mode="before") + @classmethod + def validate_coords(cls, values: Any) -> list[Union[list[int], list[str]]]: + if isinstance(values, (str, int)): + return [[values]] + if isinstance(values, list) and all(isinstance(v, (str, int)) for v in values): + return [values] + return values + + def create_action(self) -> dict: + return { + "operation": self.payload, + "coords": self.coords, + "metadata": self.metadata, + "deaccumulate": self.deaccumulate, + "name": self.name, + } + + +class NullAccumulation(BaseAccumulation): + operation: Literal["aggregation"] = "aggregation" + payload: None = None + + +class MinAccumulation(BaseAccumulation): + operation: Literal["minimum"] = "minimum" + payload: Literal["min"] = "min" + + +class MaxAccumulation(BaseAccumulation): + operation: Literal["maximum"] = "maximum" + payload: Literal["max"] = "max" + + +class MeanAccumulation(BaseAccumulation): + operation: Literal["mean"] = "mean" + payload: Literal["mean"] = "mean" + + +class StdAccumulation(BaseAccumulation): + operation: Literal["standard_deviation"] = "standard_deviation" + payload: Literal["std"] = "std" + + +class SumAccumulation(BaseAccumulation): + operation: Literal["sum"] = "sum" + payload: Literal["sum"] = "sum" + + +class DifferenceAccumulation(BaseAccumulation): + operation: Literal["difference"] = "difference" + payload: None = None + deaccumulate: bool = Field(True, frozen=True) + + @field_validator("coords", mode="after") + @classmethod + def validate_num_coords(cls, coords: list[Coords]) -> list[Coords]: + if any([len(coord) > 2 for coord in coords]): + raise ValueError("difference accumulation accepts only 1 or 2 coordinates") + return coords + + +class DifferenceRateAccumulation(BaseAccumulation): + operation: Literal["difference_rate"] = "difference_rate" + payload: Literal["ppruntime.accumulation.difference_rate"] = ( + "ppruntime.accumulation.difference_rate" + ) + factor: float = 1.0 + + @field_validator("coords", mode="after") + @classmethod + def validate_num_coords(cls, coords: list[Coords]) -> list[Coords]: + if any([len(coord) > 2 for coord in coords]): + raise ValueError( + "difference_rate accumulation accepts only 1 or 2 coordinates" + ) + return coords + + def create_action(self) -> dict: + return { + "operation": Payload( + self.payload, + kwargs={"factor": self.factor, "metadata": self.metadata}, + metadata={"environment": ["ppruntime"]}, + ), + "coords": self.coords, + "deaccumulate": self.deaccumulate, + "name": self.name, + } + + +def accum_discriminator(data: Any) -> str: + if isinstance(data, dict): + return data.get("operation", "aggregation") + return data.operation + + +Accumulation = Annotated[ + Union[ + Annotated[NullAccumulation, Tag("aggregation")], + Annotated[MinAccumulation, Tag("minimum")], + Annotated[MaxAccumulation, Tag("maximum")], + Annotated[MeanAccumulation, Tag("mean")], + Annotated[StdAccumulation, Tag("standard_deviation")], + Annotated[SumAccumulation, Tag("sum")], + Annotated[DifferenceAccumulation, Tag("difference")], + Annotated[DifferenceRateAccumulation, Tag("difference_rate")], + ], + Discriminator(accum_discriminator), +] diff --git a/pproc-core/src/ppcore/configs/common/input.py b/pproc-core/src/ppcore/configs/common/input.py new file mode 100644 index 00000000..33c6da85 --- /dev/null +++ b/pproc-core/src/ppcore/configs/common/input.py @@ -0,0 +1,71 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Any, ClassVar + +from pydantic import ( + create_model, + field_validator, +) +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from ppcore.configs.common.source import Source +from ppcore.utils.io import split_location + + +class Input(PProcBaseModel): + sources: list[Source] = [] + requests: list[dict] + expand_exclude: list[str] = [] + dtype: str = "float32" + + @field_validator("sources", mode="before") + @classmethod + def validate_sources(cls, data: Any) -> Any: + if isinstance(data, list): + for index, source in enumerate(data): + if isinstance(source, str): + name, loc = split_location(source, default="file") + config = {"name": name} + if loc: + if name == "fdb": + config["config"] = loc + elif name == "file": + config["file"] = loc + elif name == "file-pattern": + config["pattern"] = loc + else: + raise ValueError( + f"Source type {name} does not support location specification" + ) + data[index] = config + return data + + def base_request(self) -> dict: + keys = set(self.requests[0].keys()) + for ireq in range(1, len(self.requests)): + keys.intersection_update(self.requests[ireq].keys()) + return { + k: self.requests[0][k] + for k in keys + if all(self.requests[0][k] == x[k] for x in self.requests) + } + + +class InputsCollection(PProcBaseModel): + names: ClassVar[list[str]] + + +def create_input_model( + name: str, inputs: list[str], optional: list[str] = [], **kwargs +) -> type[InputsCollection]: + field_definitions = {input: (Input, ...) for input in inputs} + for input in optional: + field_definitions[input] = (Input, Input(requests=[])) + return create_model( + f"{name}InputModel", + names=(ClassVar[list[str]], inputs + optional), + **field_definitions, + __base__=InputsCollection, + **kwargs, + ) # type: ignore diff --git a/pproc-core/src/ppcore/configs/common/output.py b/pproc-core/src/ppcore/configs/common/output.py new file mode 100644 index 00000000..ef753672 --- /dev/null +++ b/pproc-core/src/ppcore/configs/common/output.py @@ -0,0 +1,58 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Any, ClassVar, Union + +from pydantic import ( + create_model, + field_validator, +) +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from ppcore.utils.io import split_location +from ppcore.configs.common.target import Target + + +class Output(PProcBaseModel): + targets: list[Target] = [] + request: dict + metadata: dict = {} + + @field_validator("targets", mode="before") + @classmethod + def validate_targets(cls, data: Any) -> Any: + for index, target in enumerate(data): + if isinstance(target, str): + name, loc = split_location(target, default="file") + config: dict[str, Any] = {"name": name} + if loc: + if name == "fdb": + config["config"] = loc + elif name in ["file", "file-pattern"]: + config["file"] = loc + elif name == "zarr": + config["xarray_to_zarr_kwargs"] = {"store": loc, "mode": "w"} + else: + raise ValueError( + f"Target type {name} does not support location specification" + ) + data[index] = config + return data + + +class OutputsCollection(PProcBaseModel): + names: ClassVar[list[str]] + + +def create_output_model( + name: str, outputs: Union[list[str], dict[str, dict]], **kwargs +) -> type[OutputsCollection]: + field_definitions = {output: (Output, ...) for output in outputs} + names = outputs if isinstance(outputs, list) else list(outputs.keys()) + return create_model( + f"{name}OutputModel", + names=(ClassVar[list[str]], names), + **field_definitions, + __base__=OutputsCollection, + **kwargs, + ) # type: ignore diff --git a/pproc-core/src/ppcore/configs/common/preprocessing.py b/pproc-core/src/ppcore/configs/common/preprocessing.py new file mode 100644 index 00000000..85d49c8c --- /dev/null +++ b/pproc-core/src/ppcore/configs/common/preprocessing.py @@ -0,0 +1,100 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Annotated +from typing import Any +from typing import List +from typing import Literal +from typing import Optional +from typing import Union + +from pydantic import Field +from pydantic import model_validator + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from earthkit.workflows.plugins.pproc.config.mask import MaskExpression + + +class Scale(PProcBaseModel): + # - operation: scale + # value: 3600 + operation: Literal["scale"] = "scale" + value: Union[float, int] + metadata: Optional[dict] = None + + +class Divide(PProcBaseModel): + # - operation: divide + # value: 3600 + operation: Literal["divide"] = "divide" + value: Union[float, int] + metadata: Optional[dict] = None + + +class Combination(PProcBaseModel): + # - operation: norm + operation: Literal["direction", "norm", "sum"] + metadata: Optional[dict] = None + + +class Expand(PProcBaseModel): + operation: Literal["expand"] = "expand" + internal_dim: list[Union[str, list[str], list[int]]] + backend_kwargs: Optional[dict] = None + + +class Select(PProcBaseModel): + operation: Literal["select"] = "select" + dim: str + values: Union[int, str, list[int], list[str]] + + +class ThermalIndex(PProcBaseModel): + operation: Literal["thermal_index"] = "thermal_index" + function: str + params: list[str] + deaccumulate: Optional[list[str]] = None + metadata: Optional[dict] = None + join: bool = True + + +# class Expression(Preprocessing): +# operation: Literal["expression"] = "expression" +# expr: str +# expr_data: dict +# dtype: Optional[str] = None + + +class Masking(PProcBaseModel): + # - operation: mask + # select: {param: 228036} + # mask: [{param: 228035, level: 250}, ">=", 10] + operation: Literal["mask"] = "mask" + mask: MaskExpression + select: dict + replacement: float = 0.0 + metadata: Optional[dict] = None + + +class PreprocessingConfig(PProcBaseModel): + # preprocessing: + # - operation: norm + # - operation: mask + # select: {param: 228036} + # mask: [{param: 228035, level: 250}, ">=", 10] + # - operation: scale + # value: 3600 + actions: List[ + Annotated[ + Union[Scale, Divide, Combination, Masking, Expand, Select, ThermalIndex], + Field(discriminator="operation"), + ] + ] = Field(default_factory=list) + + @model_validator(mode="before") + @classmethod + def validate_model(cls, data: Any) -> Any: + if isinstance(data, list): + return {"actions": data} + return data diff --git a/pproc-core/src/ppcore/configs/common/source.py b/pproc-core/src/ppcore/configs/common/source.py new file mode 100644 index 00000000..fc5b89a9 --- /dev/null +++ b/pproc-core/src/ppcore/configs/common/source.py @@ -0,0 +1,35 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional, Literal, Annotated, Union +from pydantic import Field + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel + + +class FDBSource(PProcBaseModel): + name: Literal["fdb"] = "fdb" + config: Optional[str] = None + stream: bool = True + + +class MARSSource(PProcBaseModel): + name: Literal["mars"] = "mars" + + +class FileSource(PProcBaseModel): + name: Literal["file"] = "file" + path: str + + +class FilePatternSource(PProcBaseModel): + name: Literal["file-pattern"] = "file-pattern" + pattern: str + hive_partitioning: bool = True + + +Source = Annotated[ + Union[FileSource, FilePatternSource, FDBSource, MARSSource], + Field(discriminator="name"), +] diff --git a/pproc-core/src/ppcore/configs/common/stats.py b/pproc-core/src/ppcore/configs/common/stats.py new file mode 100644 index 00000000..b7e5c334 --- /dev/null +++ b/pproc-core/src/ppcore/configs/common/stats.py @@ -0,0 +1,48 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Literal, Any +from pydantic import Field, model_validator + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from earthkit.workflows.plugins.pproc.config.threshold import Threshold + + +class Statistics(PProcBaseModel): + metadata: dict = Field(default_factory=dict) + + +class Quantiles(Statistics): + operation: Literal["quantiles"] = "quantiles" + quantiles: int | list[float] | str = 100 + + +class EFI(Statistics): + operation: Literal["efi"] = "efi" + eps: float = -1.0 + + +class SOT(Statistics): + operation: Literal["sot"] = "sot" + eps: float = -1.0 + sot: list[int] + + +class Mean(Statistics): + operation: Literal["mean"] = "mean" + + +class StandardDeviation(Statistics): + operation: Literal["std"] = "std" + + +class ThresholdProbability(Statistics): + operation: Literal["threshold_probability"] = "threshold_probability" + thresholds: list[Threshold] = Field(default_factory=list) + + @model_validator(mode="before") + def validate_thresholds(cls, data: Any) -> Any: + if isinstance(data, dict) and "threshold" in data: + data.setdefault("thresholds", []).append(data.pop("threshold")) + return data diff --git a/pproc-core/src/ppcore/configs/common/target.py b/pproc-core/src/ppcore/configs/common/target.py new file mode 100644 index 00000000..4ab4d63b --- /dev/null +++ b/pproc-core/src/ppcore/configs/common/target.py @@ -0,0 +1,42 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + + +from typing import Literal, Optional, Annotated, Union +from pydantic import Field + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel + + +class NullTarget(PProcBaseModel): + name: Literal["null"] = "null" + + +class FileTarget(PProcBaseModel): + name: Literal["file"] = "file" + file: str + append: bool = False + + +class FilePatternTarget(PProcBaseModel): + name: Literal["file-pattern"] = "file-pattern" + file: str + append: bool = False + + +class FDBTarget(PProcBaseModel): + name: Literal["fdb"] = "fdb" + config: Optional[str] = None + + +class ZarrTarget(PProcBaseModel): + name: Literal["zarr"] = "zarr" + earthkit_to_xarray_kwargs: Optional[dict[str, str]] = None + xarray_to_zarr_kwargs: Optional[dict[str, str]] = None + + +Target = Annotated[ + Union[FileTarget, FilePatternTarget, FDBTarget, NullTarget, ZarrTarget], + Field(discriminator="name"), +] diff --git a/pproc-core/src/ppcore/configs/entrypoint/base.py b/pproc-core/src/ppcore/configs/entrypoint/base.py new file mode 100644 index 00000000..506d68d3 --- /dev/null +++ b/pproc-core/src/ppcore/configs/entrypoint/base.py @@ -0,0 +1,46 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import yaml +from annotated_types import Annotated +from pydantic import Field, BeforeValidator +from conflator import ConfigModel, CLIArg + +from ppcore.configs.entrypoint.log import LoggingConfig +from ppcore.configs.entrypoint.execution import ExecutionConfig +from ppcore.configs.product import ProductConfig +from ppcore.utils.entrypoint import validate_overrides + + +class EntrypointConfig(ConfigModel): + log: LoggingConfig = LoggingConfig() + execution: ExecutionConfig = ExecutionConfig() + products: list[ProductConfig] + input_overrides: Annotated[ + dict, + BeforeValidator(validate_overrides), + CLIArg( + "--override-input", + action="append", + default=[], + metavar="KEY=VALUE,...", + ), + Field( + default_factory=dict, description="Override input requests with these keys" + ), + ] + output_overrides: Annotated[ + dict, + BeforeValidator(validate_overrides), + CLIArg( + "--override-output", + action="append", + default=[], + metavar="KEY=VALUE,...", + ), + Field(default_factory=dict, description="Override outputs with these keys"), + ] + + def dump(self) -> str: + return yaml.dump(self.model_dump(by_alias=True), sort_keys=False) diff --git a/pproc-core/src/ppcore/configs/entrypoint/execution.py b/pproc-core/src/ppcore/configs/entrypoint/execution.py new file mode 100644 index 00000000..1ad33bd2 --- /dev/null +++ b/pproc-core/src/ppcore/configs/entrypoint/execution.py @@ -0,0 +1,11 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + + +from conflator import ConfigModel + + +class ExecutionConfig(ConfigModel): + hosts: int = 1 + workers: int = 1 diff --git a/pproc-core/src/ppcore/configs/entrypoint/log.py b/pproc-core/src/ppcore/configs/entrypoint/log.py new file mode 100644 index 00000000..19119d4b --- /dev/null +++ b/pproc-core/src/ppcore/configs/entrypoint/log.py @@ -0,0 +1,26 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import logging +from typing import Literal + +from annotated_types import Annotated +from conflator import CLIArg, ConfigModel, EnvVar +from pydantic import Field + + +class LoggingConfig(ConfigModel): + level: Annotated[ + Literal["CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG"], + CLIArg("--log"), + EnvVar("LOG"), + Field( + description="Logging level [CRITICAL, ERROR, WARNING, INFO, DEBUG] (default: INFO)" + ), + ] = "INFO" + format: str = "%(asctime)s; %(name)s; %(levelname)s - %(message)s" + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + logging.basicConfig(format=self.format, level=self.level, force=True) diff --git a/pproc-core/src/ppcore/configs/product/__init__.py b/pproc-core/src/ppcore/configs/product/__init__.py new file mode 100644 index 00000000..a90327d5 --- /dev/null +++ b/pproc-core/src/ppcore/configs/product/__init__.py @@ -0,0 +1,59 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import logging +from typing import Optional, Union +from annotated_types import Annotated +import copy +from pydantic import Field + +from ppcore.configs.product.ensemble import Ensemble + +logger = logging.getLogger(__name__) + + +ProductConfig = Annotated[ + Union[Ensemble], + Field(discriminator="name"), +] + + +def from_schema( + schema: dict, request: dict, metadata: Optional[dict] = None, **overrides +) -> ProductConfig: + name = schema.pop("config", "ensemble") + schema.pop("name") + schema.pop("entrypoint", None) + interp_keys = schema.pop("interp_keys", {}) + inputs = copy.deepcopy(schema.pop("inputs")) + accums = schema.pop("accumulations", None) + + for req in inputs: + if grid := req.pop("target_grid", None): + req["interpolate"] = { + "grid": grid, + **interp_keys, + } + + config = { + "name": name, + "requests": { + "original": request, + "inputs": inputs, + }, + "sources": request.pop("sources", []), + "targets": request.pop("targets", []), + "metadata": metadata, + **schema, + } + + if accums is not None: + # Populate coords in accumulations with values from inputs + for dim, accum in accums.items(): + accum["coords"] = inputs[0][dim] + config["accumulations"] = accums + + logger.info(f"Schema config: {config}") + base = ProductConfig(**config) # type: ignore + return ProductConfig(**{**base.model_dump(), **overrides}) # type: ignore diff --git a/pproc-core/src/ppcore/configs/product/ensemble.py b/pproc-core/src/ppcore/configs/product/ensemble.py new file mode 100644 index 00000000..c79b8ab2 --- /dev/null +++ b/pproc-core/src/ppcore/configs/product/ensemble.py @@ -0,0 +1,71 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Any, Union, Literal, Annotated, Optional +from pydantic import Field, model_validator + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from ppcore.configs.common.preprocessing import PreprocessingConfig +from ppcore.configs.common.input import create_input_model, InputsCollection +from ppcore.configs.common.output import Output +from ppcore.configs.common.accumulation import Accumulation +from ppcore.configs.common.stats import ( + Mean, + StandardDeviation, + Quantiles, + ThresholdProbability, +) +from ppcore.utils.mars import extract_mars + + +EnsembleInputModel: type[InputsCollection] = create_input_model( + "EnsembleInputsModel", inputs=["fc"] +) + + +class Ensemble(PProcBaseModel): + name: Literal["ensemble"] = Field("ensemble") + preprocessing: PreprocessingConfig = Field(default_factory=PreprocessingConfig) + accumulations: dict[str, Accumulation] = Field(default_factory=dict) + statistics: Optional[ + Annotated[ + Union[Mean, StandardDeviation, Quantiles, ThresholdProbability], + Field(discriminator="operation"), + ] + ] = None + inputs: EnsembleInputModel # type: ignore + output: Output + + @model_validator(mode="before") + def validate_config(cls, data: Any) -> Any: + if isinstance(data, dict) and "requests" in data: + requests = data.pop("requests") + input_config = data.pop("input", {}) + original = requests.pop("original") + sources = data.pop("sources", []) + if isinstance(sources, dict): + sources = sources["fc"] + if isinstance(sources, str): + sources = [sources] + data["inputs"] = { + "fc": { + "requests": requests.pop("inputs"), + "sources": sources, + **input_config, + } + } + targets = data.pop("targets", []) + data["output"] = { + "targets": targets if isinstance(targets, list) else [targets], + "request": extract_mars(original), + } + if metadata := data.pop("metadata", None): + stat_metadata = data.get("statistics", {}).setdefault("metadata", {}) + stat_metadata.update(metadata) + if data.pop("quantiles", None) is not None: + data["statistics"]["quantiles"] = original["quantile"] + return data + + +Config = Ensemble diff --git a/pproc-core/src/ppcore/product.py b/pproc-core/src/ppcore/product.py new file mode 100644 index 00000000..64e68716 --- /dev/null +++ b/pproc-core/src/ppcore/product.py @@ -0,0 +1,34 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import sys +import logging + +from conflator import Conflator + +from earthkit.workflows.compilers import graph2job +from cascade.low.core import JobInstanceRich +from cascade.main import run_locally +from ppcore.configs.entrypoint.base import EntrypointConfig +from ppcore.products import graph_from_configs + +logger = logging.getLogger(__name__) + + +def main(): + sys.stdout.reconfigure(line_buffering=True) # type: ignore + cfg: EntrypointConfig = Conflator( + app_name="pproc-product", model=EntrypointConfig + ).load() # type: ignore + logger.info(cfg.dump()) + graph = graph_from_configs(cfg.products, cfg.input_overrides, cfg.output_overrides) + run_locally( + JobInstanceRich(jobInstance=graph2job(graph), checkpointSpec=None), + hosts=cfg.execution.hosts, + workers=cfg.execution.workers, + ) + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/pproc-core/src/ppcore/products/__init__.py b/pproc-core/src/ppcore/products/__init__.py new file mode 100644 index 00000000..fe269580 --- /dev/null +++ b/pproc-core/src/ppcore/products/__init__.py @@ -0,0 +1,158 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +from typing import Optional, Union + +from earthkit.workflows.graph import Graph, deduplicate_nodes +from earthkit.workflows.fluent import Action, merge +from earthkit.workflows.nodetree import datacubes +from qubed import Qube + +from earthkit.workflows.plugins.pproc.fluent import path_from_request +from ppcore.utils.requests import expand +from ppcore.configs import from_outputs as config_from_outputs +from ppcore.configs.product import ProductConfig +from ppcore.schema.schema import Schema +from ppcore.schema.forecast import ( + ForecastDefinition, + ReforecastDefinition, + ClimatologyDefinition, +) +from ppcore.products.base import Product +from ppcore.products.ensemble import Ensemble + + +_PRODUCTS = {"ensemble": Ensemble} + + +def product_from_config( + config: ProductConfig, input_overrides: dict = {}, output_overrides: dict = {} +) -> Product: + if config.name not in _PRODUCTS: + raise ValueError(f"Product {config.name} not supported") + return _PRODUCTS[config.name]( + config=config, + input_overrides=input_overrides, + output_overrides=output_overrides, + ) + + +def product_from_output( + request: dict, + pproc_schema: Union[str, os.PathLike, Schema], + forecast: Union[str, ForecastDefinition, ReforecastDefinition], + climatology: Optional[Union[str, ClimatologyDefinition]] = None, + metadata: Optional[dict] = None, +) -> Product: + """ + Returns fluent.Action for computing the product specified by the output request + and PProc schema + """ + requests = list(expand(request)) + if len(requests) != 1: + raise ValueError( + f"Expected a single request after expansion, got {len(requests)}" + ) + config = list( + config_from_outputs( + requests, pproc_schema, forecast, climatology, metadata=metadata + ) + )[0] + return product_from_config(config) + + +def action_from_outputs( + requests: list[dict], + pproc_schema: Union[str, os.PathLike, Schema], + forecast: Union[str, Action, ForecastDefinition, ReforecastDefinition], + climatology: Optional[Union[str, Action, ClimatologyDefinition]] = None, + metadata: Optional[dict] = None, +) -> Action: + action_kwargs = {} + if isinstance(forecast, Action): + action_kwargs["forecast"] = forecast + dataset = ForecastDefinition(datacubes=datacubes(forecast.nodes)) + else: + action_kwargs["forecast"] = None + dataset = forecast + if isinstance(climatology, Action): + action_kwargs["climatology"] = climatology + clim_dataset = ClimatologyDefinition(datacubes=datacubes(climatology.nodes)) + else: + clim_dataset = climatology + + expanded_requests = list(expand(requests)) + + # Determine coords that might be joined over and promote to dimension + # TODO: enable generating outputs with a mix of instantaneous steps and step ranges + # Should be done with changing more generally all values for "step" in requests to be + # strings + qube = Qube.empty() + for request in expanded_requests: + qube = qube | qube.from_datacube(request) + promote = {dim for dim, values in qube.axes().items() if len(values) > 1} + + actions = [] + for request in expanded_requests: + request_path = "" + for datacube in qube.datacubes(): + if all([request[x] in datacube.get(x, []) for x in request.keys()]): + request_path = path_from_request(datacube) + break + assert len(request_path) != 0 + actions.append( + product_from_output( + request, + pproc_schema=pproc_schema, + forecast=dataset, + climatology=clim_dataset, + metadata=metadata, + ) + .action(**action_kwargs, final_dims=promote) + .set_path(request_path) + ) + return merge(*actions) + + +def graph_from_outputs( + requests: list[dict], + pproc_schema: Union[str, os.PathLike, Schema], + forecast: Union[str, ForecastDefinition, ReforecastDefinition], + climatology: Optional[Union[str, ClimatologyDefinition]] = None, + metadata: Optional[dict] = None, +) -> Graph: + """ + Returns fluent.Action for computing the product specified by the output request + and PProc schema + """ + graph = Graph([]) + for request in expand(requests): + graph += ( + product_from_output( + request, + pproc_schema=pproc_schema, + forecast=forecast, + climatology=climatology, + metadata=metadata, + ) + .action() + .graph() + ) + return deduplicate_nodes(graph) + + +def graph_from_configs( + configs: list[ProductConfig], + input_overrides: dict = {}, + output_overrides: dict = {}, +) -> Graph: + graph = Graph([]) + for config in configs: + graph += ( + product_from_config(config, input_overrides, output_overrides) + .action() + .graph() + ) + return deduplicate_nodes(graph) diff --git a/pproc-core/src/ppcore/products/base.py b/pproc-core/src/ppcore/products/base.py new file mode 100644 index 00000000..416aaf42 --- /dev/null +++ b/pproc-core/src/ppcore/products/base.py @@ -0,0 +1,22 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from abc import ABC +from dataclasses import dataclass +from typing import Iterator, Optional + + +@dataclass +class Product(ABC): + input_overrides: dict + output_overrides: dict + + def action(self, *args, **kwargs): + raise NotImplementedError + + def in_mars(self, sources: Optional[list[str]] = None) -> Iterator[dict]: + raise NotImplementedError + + def out_mars(self, targets: Optional[list[str]] = None) -> Iterator[dict]: + raise NotImplementedError diff --git a/pproc-core/src/ppcore/products/ensemble.py b/pproc-core/src/ppcore/products/ensemble.py new file mode 100644 index 00000000..b46b4e85 --- /dev/null +++ b/pproc-core/src/ppcore/products/ensemble.py @@ -0,0 +1,191 @@ +# Copyright 2024 ECMWF. +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional, Iterator +from dataclasses import dataclass +import numpy as np +import logging + +from earthkit.workflows.fluent import merge +from earthkit.workflows.nodetree import nodetree_dimensions +from earthkit.workflows.plugins.pproc.fluent import ( + Action, + from_source, + path_from_request, +) +from earthkit.workflows.plugins.pproc.utils.request import Request + +from ppcore.utils.mars import extract_mars +from ppcore.configs.product.ensemble import Config +from ppcore.products.base import Product + + +logger = logging.Logger(__name__) + + +@dataclass +class Ensemble(Product): + config: Config + preprocessing_dim: str = "param" + ensemble_dim: str = "number" + + def source(self, ensemble_dim: Optional[str] = None) -> Action: + input_config = self.config.inputs.fc + ensemble_dim = ensemble_dim or self.ensemble_dim + expand_dims = { + ensemble_dim, + self.preprocessing_dim, + "step", + *self.config.accumulations.keys(), + } + + if len(input_config.sources) == 0: + raise ValueError("No sources provided for ensemble config") + actions = [] + for req_dict in [ + dict(x, **self.input_overrides) for x in input_config.requests + ]: + req = Request( + { + k: [val] if np.ndim(val) == 0 and k in expand_dims else val + for k, val in req_dict.items() + }, + no_expand=("number", *input_config.expand_exclude), + ) + new_action = from_source( + input_config.sources, + [req], + input_config.dtype, + ) + new_action = new_action.set_path(path_from_request(req_dict)) + if "number" in req_dict: + new_action = new_action.expand( + "number", + ("number", req["number"]), + backend_kwargs={"method": "sel"}, + ) + else: + new_action._add_dimension("number", 0) + actions.append(new_action) + action = merge(*actions) + return action + + def action( + self, + forecast: Optional[Action] = None, + preprocessing_dim: Optional[str] = None, + ensemble_dim: Optional[str] = None, + final_dims: Optional[set[str]] = None, + ) -> Action: + ens_dim = ensemble_dim or self.ensemble_dim + preprocess_dim = preprocessing_dim or self.preprocessing_dim + if forecast: + logger.debug(f"Forecast {forecast.nodes}") + actions = [] + is_ensemble = ens_dim in nodetree_dimensions(forecast.nodes) + for req in self.config.inputs.fc.requests: + if is_ensemble: + req.setdefault(ens_dim, [0]) + selected = forecast.sel(req) + selected = selected.set_path(path_from_request(req)) + for dim in [ + ens_dim, + preprocess_dim, + "step", + *self.config.accumulations.keys(), + ]: + if dim in req and np.size(req[dim]) == 1: + selected.set_scalar_coords( + {dim: np.atleast_1d(req[dim])[0]}, + override=True, + make_dim=True, + ) + actions.append(selected) + ret = merge(*actions) + else: + ret = self.source(ensemble_dim=ensemble_dim) + for preprocessing in self.config.preprocessing.actions: + ret = ret.preprocessing( + dim=preprocess_dim, + **preprocessing.model_dump(), + ) + for dim, accumulation in self.config.accumulations.items(): + ret = ret.accumulation( + dim=dim, + **accumulation.create_action(), + ) + if self.config.statistics is not None: + ret = ret.ensemble_statistics( + dim=ens_dim, + **self.config.statistics.model_dump(), + ) + + if len(self.config.output.targets) > 0: + output_config = self.config.output.model_dump() + out_metadata = output_config["metadata"].copy() + out_metadata.update(self.output_overrides) + ret = ret.write(output_config["targets"], metadata=out_metadata) + + final_dims = final_dims or [] + if preprocess_dim in final_dims: + # Stream is uniquely determined by parameter + final_dims.discard("stream") + if ens_dim in final_dims: + # Stream/type of member is determined by ensemble number + final_dims.discard("type") + final_dims.discard("stream") + ret.set_scalar_coords( + {k: v for k, v in self.config.output.request.items() if k in final_dims}, + override=True, + make_dim=True, + ) + ret.set_scalar_coords( + { + k: v + for k, v in self.config.output.request.items() + if k not in final_dims + }, + override=True, + ) + return ret.set_path(path_from_request(self.config.output.request)) + + def in_mars(self, sources: Optional[list[str]] = None) -> Iterator[dict]: + if self.config.inputs is None: + return + inputs = self.config.inputs.fc + if not sources or set.intersection( + set(sources), set(x.name for x in inputs.sources) + ): + source = inputs.sources[0] + for input in inputs.requests: + overridden = input.copy() + overridden = extract_mars(overridden) + if source.name == "file": + overridden["source"] = source.path + elif source.name == "file-pattern": + overridden["source"] = source.pattern + else: + overridden["source"] = source.name + overridden.update(self.input_overrides) + yield overridden + + def out_mars(self, targets: Optional[list[str]] = None) -> Iterator[dict]: + output = self.config.output + if output is None: + return + if not targets or set.intersection( + set(targets), set(x.name for x in output.targets) + ): + target = output.targets[0] + overridden = output.request.copy() + overridden = extract_mars(overridden) + if target.name == "file": + overridden["target"] = target.file + elif target.name == "file-pattern": + overridden["target"] = target.file + else: + overridden["target"] = target.name + overridden.update(self.output_overrides) + yield overridden diff --git a/pproc-core/src/ppcore/schema/__init__.py b/pproc-core/src/ppcore/schema/__init__.py new file mode 100644 index 00000000..96793c76 --- /dev/null +++ b/pproc-core/src/ppcore/schema/__init__.py @@ -0,0 +1,3 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 diff --git a/pproc-core/src/ppcore/schema/base.py b/pproc-core/src/ppcore/schema/base.py new file mode 100644 index 00000000..c339b3d2 --- /dev/null +++ b/pproc-core/src/ppcore/schema/base.py @@ -0,0 +1,328 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import copy +import logging +from collections import OrderedDict +from typing import Any +from typing import Callable +from typing import Iterator +from typing import Optional +from typing import Literal + +import yaml +import json +from typing_extensions import Self + +from ppcore.utils.dicts import deep_update +from ppcore.schema.exceptions import PProcSchemaError + +logger = logging.getLogger(__name__) + +UpdateFunc = Callable[[dict, dict], dict] +FilterFunc = Callable[[dict, str], Any] +MatchFunc = Callable[[dict, Any, Any], bool] + + +def dict_update(base: dict, update: dict) -> dict: + base.update(update) + return base + + +DEFAULT_UPDATE: UpdateFunc = deep_update +DEFAULT_FILTER: FilterFunc = dict.__getitem__ +DEFAULT_MATCH: MatchFunc = lambda _, value, expected: value == expected + + +class BaseSchema: + exception = PProcSchemaError + custom_update: dict[str, UpdateFunc] = {} + custom_filter: dict[str, FilterFunc] = {} + custom_match: dict[str, MatchFunc] = {} + + def __init__( + self, + schema: dict, + *, + matching_cache_size: int = 0, + ): + self.all_filters, self.schema = self.expand(schema) + self.filters = self.all_filters.difference(set(self.custom_filter.keys())) + self.matching_cache_size = max(0, matching_cache_size) + self._matching_cache: OrderedDict[tuple, tuple[dict, ...]] = OrderedDict() + + def _matching_cache_key(self, output_template: dict, matching: dict) -> tuple: + return ( + id(self.schema), + json.dumps(output_template, sort_keys=True), + json.dumps(matching, sort_keys=True), + ) + + def clear_matching_cache(self) -> None: + self._matching_cache.clear() + + def _get_cached_matching(self, key: tuple) -> Optional[list[dict]]: + if self.matching_cache_size == 0: + return None + + cached = self._matching_cache.get(key, None) + if cached is None: + return None + + self._matching_cache.move_to_end(key) + return [copy.deepcopy(cfg) for cfg in cached] + + def _set_cached_matching(self, key: tuple, configs: list[dict]) -> None: + if self.matching_cache_size == 0: + return + + self._matching_cache[key] = tuple(copy.deepcopy(cfg) for cfg in configs) + self._matching_cache.move_to_end(key) + while len(self._matching_cache) > self.matching_cache_size: + self._matching_cache.popitem(last=False) + + @classmethod + def from_file(cls, schema_path: str) -> Self: + with open(schema_path, "r") as f: + schema = yaml.safe_load(f) + return cls(schema) + + @classmethod + def expand(cls, schema: dict) -> tuple[set, dict]: + expanded = {} + filters = set() + for key, value in schema.items(): + if cls.is_subschema(key): + filters.add(key.split(":")[1]) + expanded.setdefault(key, {}) + for sub_keys, sub_values in value.items(): + new_filters, sub_expanded = cls.expand(sub_values) + filters.update(new_filters) + for sub_key in sub_keys.split("/"): + expanded[key][sub_key] = sub_expanded + else: + expanded[key] = value + return filters, expanded + + @classmethod + def is_subschema(cls, key: str) -> bool: + return "filter" in key + + @classmethod + def subschema( + cls, key: str, schema: dict, request: dict, traversed: list[str] + ) -> dict: + _, mars_key = key.split(":") + filter_value = cls.custom_filter.get(mars_key, DEFAULT_FILTER)( + request, mars_key + ) + if filter_value in schema: + ret = schema[filter_value] + traversed.append(f"{mars_key}={filter_value}") + else: + ret = schema.get("*", None) + if ret is None: + raise cls.exception( + f"No match for {mars_key}={filter_value} along path {','.join(traversed)}, and no default provided" + ) + traversed.append(f"{mars_key}=*") + + if not isinstance(ret, dict): + raise cls.exception("Subschema must be a dictionary.") + return ret + + @classmethod + def _traverse( + cls, sub_schema: dict, request: dict, config: dict, traversed: list[str] + ) -> dict: + for key, value in sub_schema.items(): + if cls.is_subschema(key): + path = traversed.copy() + cls._traverse( + cls.subschema(key, value, request, path), request, config, path + ) + else: + # TODO: Remove copies? + cls.custom_update.get(key, DEFAULT_UPDATE)( + config, {key: copy.deepcopy(value)} + ) + return config + + def traverse(self, request: dict, config: Optional[dict] = None) -> dict: + if len(set.intersection(set(request.keys()), self.filters)) < len(self.filters): + raise self.exception( + f"Request {request} does not contain all required filters {self.filters}" + ) + traversed = [] + return self._traverse(self.schema, request, config or {}, traversed) + + @classmethod + def _find_matching( + cls, + schema: dict, + configs: list[dict], + **matching, + ) -> Iterator[dict]: + missing = object() + matching_funcs = [ + (key, value, cls.custom_match.get(key, DEFAULT_MATCH)) + for key, value in matching.items() + ] + for key, value in schema.items(): + if cls.is_subschema(key): + filter_key = key.split(":")[1] + wildcard_schema = value.get("*", None) + new_configs = [] + value_matched = False + for filter_value, sub_schema in value.items(): + if filter_value == "*": + continue + for fout in configs: + current_value = fout["recon_req"].get(filter_key, missing) + if current_value == filter_value: + value_matched = True + elif current_value is not missing: + continue + + new_fout = copy.deepcopy(fout) + if current_value is missing: + new_fout["recon_req"][filter_key] = copy.deepcopy( + filter_value + ) + + new_configs.extend( + cls._find_matching( + sub_schema, + [new_fout], + **matching, + ) + ) + if wildcard_schema is not None and not value_matched: + new_configs.extend( + cls._find_matching(wildcard_schema, configs, **matching) + ) + configs = new_configs + else: + update = cls.custom_update.get(key, DEFAULT_UPDATE) + for cfg in configs: + update(cfg, {key: copy.deepcopy(value)}) + + for cfg in configs: + is_match = True + for key, value, match_func in matching_funcs: + if not match_func( + cfg["recon_req"], + cfg.get(key, value), + value, + ): + is_match = False + break + if is_match: + logger.debug("Matched config: %s", cfg) + yield cfg + + @classmethod + def _find_matching_dfs( + cls, + schema: dict, + configs: list[dict], + **matching, + ) -> Iterator[dict]: + missing = object() + matching_funcs = [ + (key, value, cls.custom_match.get(key, DEFAULT_MATCH)) + for key, value in matching.items() + ] + + def _walk_schema(current_schema: dict, current_cfg: dict) -> Iterator[dict]: + items = list(current_schema.items()) + + def _walk_items(index: int, cfg: dict) -> Iterator[dict]: + if index >= len(items): + yield cfg + return + + key, value = items[index] + if cls.is_subschema(key): + filter_key = key.split(":")[1] + wildcard_schema = value.get("*", None) + current_value = cfg["recon_req"].get(filter_key, missing) + value_matched = False + + for filter_value, sub_schema in value.items(): + if filter_value == "*": + continue + + if current_value == filter_value: + value_matched = True + elif current_value is not missing: + continue + + branch_cfg = copy.deepcopy(cfg) + if current_value is missing: + branch_cfg["recon_req"][filter_key] = copy.deepcopy( + filter_value + ) + + for resolved_cfg in _walk_schema(sub_schema, branch_cfg): + yield from _walk_items(index + 1, resolved_cfg) + + if wildcard_schema is not None and not value_matched: + wildcard_cfg = copy.deepcopy(cfg) + for resolved_cfg in _walk_schema(wildcard_schema, wildcard_cfg): + yield from _walk_items(index + 1, resolved_cfg) + else: + update = cls.custom_update.get(key, DEFAULT_UPDATE) + update(cfg, {key: copy.deepcopy(value)}) + yield from _walk_items(index + 1, cfg) + + yield from _walk_items(0, current_cfg) + + for initial_cfg in configs: + for cfg in _walk_schema(schema, copy.deepcopy(initial_cfg)): + is_match = True + for key, value, match_func in matching_funcs: + if not match_func( + cfg["recon_req"], + cfg.get(key, value), + value, + ): + is_match = False + break + if is_match: + logger.debug("Matched config: %s", cfg) + yield cfg + + def reconstruct( + self, + output_template: Optional[dict] = None, + initial_config: Optional[dict] = None, + method: Literal["dfs", "bfs"] = "bfs", + enable_cache: bool = True, + **matching, + ) -> Iterator[tuple[dict, dict]]: + output_template = output_template or {} + initial_config = initial_config or {} + cache_key = self._matching_cache_key(output_template, matching) + configs = self._get_cached_matching(cache_key) + + if method not in ["dfs", "bfs"]: + raise self.exception(f"Invalid method '{method}'. Must be 'dfs' or 'bfs'.") + method_func = ( + self._find_matching_dfs if method == "dfs" else self._find_matching + ) + + if configs is None: + configs = method_func( + self.schema, + [{"recon_req": output_template, **initial_config}], + **matching, + ) + if self.matching_cache_size > 0 and enable_cache: + self._set_cached_matching(cache_key, list(configs)) + configs = self._get_cached_matching(cache_key) + + assert configs is not None, "Configs should not be None after reconstruction" + for cfg in configs: + yield cfg.pop("recon_req"), cfg diff --git a/pproc-core/src/ppcore/schema/config.py b/pproc-core/src/ppcore/schema/config.py new file mode 100644 index 00000000..69c3fc54 --- /dev/null +++ b/pproc-core/src/ppcore/schema/config.py @@ -0,0 +1,62 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import numpy as np + +from earthkit.workflows.plugins.pproc.utils.metadata import fill_template_value +from ppcore.schema.base import BaseSchema, dict_update +from ppcore.schema.filters import _selection, _steplength, _steptype +from ppcore.schema.exceptions import PProcConfigSchemaError +from ppcore.utils.dicts import dict_apply +from ppcore.utils.helpers import to_list +from ppcore.utils.requests import validate_request + + +class ConfigSchema(BaseSchema): + exception = PProcConfigSchemaError + custom_filter = { + "steplength": _steplength, + "selection": _selection, + "steptype": _steptype, + } + custom_update = {"interp_keys": dict_update} + + def config(self, output_request: dict) -> dict: + output_request = validate_request(output_request) + config = self.traverse(output_request) + if "quantile" in output_request: + out_quantiles = to_list(output_request["quantile"]) + numbers = np.zeros(len(out_quantiles)) + totals = np.zeros(len(out_quantiles)) + for index, quantile in enumerate(out_quantiles): + number, total = map(int, quantile.split(":")) + numbers[index] = number + totals[index] = total + if ( + np.all(totals == totals[0]) + and np.all(np.diff(numbers) == 1) + and len(numbers) == total + 1 + ): + quantiles = int(totals[0]) + else: + quantiles = list(numbers / totals) + config["quantiles"] = quantiles + if output_request["type"] == "sot": + config["sot"] = to_list(output_request["number"]) + + out_vals = output_request.copy() + date = str(output_request["date"]) + out_vals.update( + { + "year": date[0:4], + "month": date[4:6], + "day": date[6:8], + "steplength": _steplength(output_request, "step"), + } + ) + config = dict_apply( + lambda v: fill_template_value(v, out_vals) if isinstance(v, str) else v, + config, + ) + return config diff --git a/pproc-core/src/ppcore/schema/deriver.py b/pproc-core/src/ppcore/schema/deriver.py new file mode 100644 index 00000000..3cf6c455 --- /dev/null +++ b/pproc-core/src/ppcore/schema/deriver.py @@ -0,0 +1,296 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import bisect +import datetime +from typing import Annotated +from typing import Any +from typing import Literal +from typing import Optional +from typing import Union + +import numpy as np +from earthkit.time import Sequence +from earthkit.time.climatology import RelativeYear +from earthkit.time.climatology import date_range +from pydantic import BaseModel +from pydantic import ConfigDict +from pydantic import Field + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from ppcore.utils.stepseq import fcmonth_to_steprange +from ppcore.schema.forecast import Dataset, Climatology + + +class BaseDeriver(BaseModel): + model_config = ConfigDict(validate_by_name=True) + + +class DefaultStepDeriver(BaseDeriver): + name: Literal["step_default"] = Field("step_default") + by: Optional[int] = None + include_start: bool = False + allow_missing_zero: bool = False + + def _inst_step(self, step: int, fc_steps: list[int]) -> list[int]: + if step not in fc_steps: + raise ValueError(f"Required step {step} not in forecast steps") + return [step] + + def _range(self, start: int, end: int, fc_steps: list[int]) -> list[int]: + if self.by: + fc_steps = [ + x + for x in fc_steps + if x + in range((fc_steps[0] // self.by) * self.by, fc_steps[-1] + 1, self.by) + ] + if self.include_start: + if start not in fc_steps: + if start == 0 and self.allow_missing_zero: + start_index = 0 + else: + raise ValueError(f"Required step {start} not in forecast steps") + else: + start_index = fc_steps.index(start) + else: + start_index = bisect.bisect_right(fc_steps, start) + if end not in fc_steps: + raise ValueError(f"Required step {end} not in forecast steps") + return fc_steps[start_index : fc_steps.index(end) + 1] + + def derive(self, request: dict, forecast: Dataset) -> list[int]: + steps = list(map(int, str(request["step"]).split("-"))) + fc_steps = list(map(int, forecast.steps(request))) + if len(steps) == 1: + return self._inst_step(int(steps[0]), fc_steps) + return self._range(*steps, fc_steps=fc_steps) + + +class DeaccumulateStepDeriver(BaseDeriver): + name: Literal["step_deaccumulate"] = Field("step_deaccumulate") + by: int = 0 + allow_missing_zero: bool = False + + def _inst_step(self, step: int, fc_steps: list[int]) -> list[int]: + if step == 0: + raise ValueError("Cannot perform de-accumulation for step 0") + if step == fc_steps[0]: + return [step] + start = fc_steps[fc_steps.index(step) - 1] + return self._range(start, step, fc_steps) + + def _range(self, start: int, end: int, fc_steps: list[int]) -> list[int]: + end = max(end, self.by) + start = min(end - self.by, start) + if end not in fc_steps: + raise ValueError(f"Required step {end} not in forecast steps") + if start not in fc_steps: + if start == 0 and self.allow_missing_zero: + return [end] + raise ValueError(f"Required step {start} not in forecast steps") + return [start, end] + + def derive(self, request: dict, forecast: Dataset) -> list[int]: + steps = list(map(int, str(request["step"]).split("-"))) + fc_steps = list(map(int, forecast.steps(request))) + if len(steps) == 1: + return self._inst_step(int(steps[0]), fc_steps) + return self._range(*steps, fc_steps=fc_steps) + + +class PrecomputedStepDeriver(BaseDeriver): + name: Literal["step_precomputed"] = Field("step_precomputed") + + def derive(self, request: dict, forecast: Dataset) -> list[int]: + if not isinstance(request["step"], str): + raise ValueError( + f"Step {request['step']} must be step range for pre-computed steps" + ) + return [request["step"]] + + +class FcmonthStepDeriver(DefaultStepDeriver): + name: Literal["step_monthly"] = Field("step_monthly") + + def derive(self, request: dict, forecast: Dataset) -> list[int]: + fcmonth = int(request["fcmonth"]) + fc_steps = list(map(int, forecast.steps(request))) + start, end = map( + int, + fcmonth_to_steprange( + datetime.datetime.strptime(str(request["date"]), "%Y%m%d"), + fcmonth, + ).split("-"), + ) + return self._range(start, end, fc_steps) + + +class SelectionStepDeriver(DefaultStepDeriver): + name: Literal["step_select"] = Field("step_select") + index: int + + def derive(self, request: dict, forecast: Dataset) -> list[int]: + steps = list(map(int, str(request["step"]).split("-"))) + if len(steps) == 1: + raise ValueError("SelectionStepDeriver can not be used for single steps") + fc_steps = list(map(int, forecast.steps(request))) + selection_range = self._range(*steps, fc_steps=fc_steps) + return [selection_range[self.index]] + + +class StaticStepDeriver(BaseDeriver): + name: Literal["step_static"] = Field("step_static") + values: Union[int, list[int]] + + def derive(self, request: dict, forecast: Dataset) -> list[int]: + steps = [self.values] if isinstance(self.values, int) else self.values + fc_steps = forecast.steps(request) + if not all([x in fc_steps for x in steps]): + raise ValueError(f"Values {steps}, must be contained in forecast steps") + return steps + + +class ClimStepRangeDeriver(BaseDeriver): + name: Literal["clim_step_range"] = Field("clim_step_range") + + def derive(self, request: dict, climatology: Climatology) -> str: + time = int(request["time"]) // 100 + req_steps = request["step"] + if isinstance(req_steps, (int, str)): + req_steps = [req_steps] + clim_steps = list(map(str, climatology.steps(request))) + + if len(req_steps) == 1 and isinstance(req_steps[0], str): + req_steps = list(map(int, req_steps[0].split("-"))) + start, end = req_steps[0], req_steps[-1] + widths = [np.diff(list(map(int, x.split("-"))))[0] for x in clim_steps] + width = end - start + if width not in widths: + if len(req_steps) == 1: + # Only possible if start should be step 0 and it is missing + start = 0 + else: + step_intervals = np.diff(req_steps) + if np.any(step_intervals != step_intervals[0]): + raise ValueError( + "Can not derive width not irregular step intervals" + ) + start = start - step_intervals[0] + width = end - start + if width not in widths: + raise ValueError("Can not derive step range from input steps") + filtered_clim_steps = [ + x for index, x in enumerate(clim_steps) if widths[index] == width + ] + + # Find nearest clim window range to real forecast time + relative_time = start + int(time) + if time == 12: + relative_time = start - int(time) + + if end < 240: + clim_start_steps = [int(x.split("-")[0]) for x in filtered_clim_steps] + nearest = bisect.bisect_right(clim_start_steps, relative_time) + clim_start = clim_start_steps[nearest - 1] + if (nearest <= (len(clim_start_steps) - 1)) and ( + (clim_start_steps[nearest] - relative_time) + < (relative_time - clim_start) + ): + clim_start = clim_start_steps[nearest] + return f"{clim_start}-{clim_start + width}" + return f"{start}-{end}" + + +class ClimStepInstantaneousDeriver(BaseDeriver): + name: Literal["clim_step_inst"] = Field("clim_step_inst") + + def derive(self, request: dict, climatology: Climatology) -> list[int]: + time = int(request["time"]) // 100 + steps = request["step"] + if isinstance(steps, (int, str)): + steps = [steps] + clim_steps = climatology.steps(request) + # Match on valid time. Reforecast assumed to run at 00UTC only + matched_steps = [] + for step in steps: + valid_time = step + time + if valid_time > clim_steps[-1] and time == 12: + # This rule only applies to 12UTC runs + valid_time = step - time + if valid_time not in clim_steps: + raise ValueError(f"Required step {valid_time} not in climatology steps") + matched_steps.append(valid_time) + return matched_steps + + +class ClimDateDeriver(PProcBaseModel): + model_config = ConfigDict(extra="allow") + name: Literal["clim_date"] = Field("clim_date") + option: str + sequence: Optional[dict] = None + + def derive(self, request: dict, climatology: Climatology) -> str | list[str]: + date = datetime.datetime.strptime(str(request["date"]), "%Y%m%d") + if self.sequence is not None: + seq = Sequence.from_dict(self.sequence) + else: + seq = Sequence.from_resource(climatology.scheme) + kwargs = self.model_dump(exclude={"option", "sequence", "name"}) + clim_date = getattr(seq, self.option)(date.date(), **kwargs) + if isinstance(clim_date, datetime.date): + return datetime.datetime.strftime(clim_date, "%Y%m%d") + return [datetime.datetime.strftime(x, "%Y%m%d") for x in clim_date] + + +class HindcastDatesDeriver(PProcBaseModel): + name: Literal["hindcast_dates"] = Field("hindcast_dates") + rstart: int + rend: int + recurrence: str = "yearly" + include_endpoint: bool = False + + def derive(self, request: dict, forecast: Dataset) -> list[str]: + date = datetime.datetime.strptime(str(request["date"]), "%Y%m%d").date() + start = RelativeYear(self.rstart).relative_to(date) + end = RelativeYear(self.rend).relative_to(date) + return [ + datetime.datetime.strftime(x, "%Y%m%d") + for x in date_range( + date, start, end, self.recurrence, self.include_endpoint + ) + ] + + +class OutputDeriver(PProcBaseModel): + name: Literal["from_output"] = Field("from_output") + key: str + + def derive(self, request: dict, forecast: Dataset) -> Any: + return request[self.key] + + +ForecastDeriver = Annotated[ + Union[ + DefaultStepDeriver, + DeaccumulateStepDeriver, + PrecomputedStepDeriver, + FcmonthStepDeriver, + SelectionStepDeriver, + StaticStepDeriver, + HindcastDatesDeriver, + OutputDeriver, + ], + Field(discriminator="name"), +] + +ClimatologyDeriver = Annotated[ + Union[ + ClimStepRangeDeriver, + ClimStepInstantaneousDeriver, + ClimDateDeriver, + OutputDeriver, + ], + Field(discriminator="name"), +] diff --git a/pproc-core/src/ppcore/schema/exceptions.py b/pproc-core/src/ppcore/schema/exceptions.py new file mode 100644 index 00000000..d189b9fc --- /dev/null +++ b/pproc-core/src/ppcore/schema/exceptions.py @@ -0,0 +1,18 @@ +class PProcSchemaError(Exception): + pass + + +class PProcConfigSchemaError(PProcSchemaError): + pass + + +class PProcInputSchemaError(PProcSchemaError): + pass + + +class PProcStepSchemaError(PProcSchemaError): + pass + + +class PProcDatasetError(Exception): + pass diff --git a/pproc-core/src/ppcore/schema/filters.py b/pproc-core/src/ppcore/schema/filters.py new file mode 100644 index 00000000..0aa819fc --- /dev/null +++ b/pproc-core/src/ppcore/schema/filters.py @@ -0,0 +1,37 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from ppcore.utils.stepseq import fcmonth_to_steprange + + +def _steptype(request: dict, key: str) -> str: + step = request.get("step", "") + steprange = str(step).split("-") + return "range" if len(steprange) == 2 else "instantaneous" + + +def _steplength(request: dict, key: str) -> str: + if "fcmonth" in request: + step = fcmonth_to_steprange(str(request["date"]), int(request["fcmonth"])) + else: + step = request.get("step", "") + steprange = list(map(int, str(step).split("-"))) + length = str(0) if len(steprange) == 1 else str(steprange[1] - steprange[0]) + return length + + +def _selection(request: dict, key: str) -> str: + return request.get("selection", "default") + + +def _members(request: dict, key: str) -> str: + number = request["number"] + if isinstance(number, (int, str)): + number = [number] + number = list(map(int, number)) + if 0 not in number: + return "no_zero" + if len(number) == 1: + return "only_zero" + return "contains_zero" diff --git a/pproc-core/src/ppcore/schema/forecast.py b/pproc-core/src/ppcore/schema/forecast.py new file mode 100644 index 00000000..b4f4489f --- /dev/null +++ b/pproc-core/src/ppcore/schema/forecast.py @@ -0,0 +1,288 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional, Annotated, Union, Literal, Self +from dataclasses import dataclass +from functools import cached_property +from qubed import Qube +from pydantic import Field, model_validator, field_validator +import bisect +import logging +import numpy as np + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from ppcore.utils.requests import validate_request +from ppcore.schema.exceptions import PProcDatasetError + +logger = logging.getLogger(__name__) + + +class BaseDefinition(PProcBaseModel): + datacubes: list[dict] + wave: Optional[list[dict]] = None + + +class ForecastDefinition(BaseDefinition): + dataset_type: Literal["forecast"] = "forecast" + unperturbed: Optional[dict] = None + + @field_validator("datacubes", mode="before") + def populate_request(cls, data: list[dict]) -> list[dict]: + data = data.copy() + for index, cube in enumerate(data): + if members := cube.pop("members", None): + cube["number"] = list(range(members["start"], members["end"] + 1)) + steps = [] + cube_step = cube.pop("step", []) + if isinstance(cube_step, (int, str)): + cube_step = [cube_step] + for step in cube_step: + if isinstance(step, dict): + steps.extend(range(step["from"], step["to"] + 1, step.get("by", 1))) + else: + steps.append(step) + cube["step"] = steps + if quantile := cube.pop("quantile", None): + cube["quantile"] = [f"{x}:{quantile}" for x in range(0, quantile + 1)] + data[index] = validate_request(cube) + return data + + @model_validator(mode="after") + def validate_qube(self) -> Self: + if self.wave is None and any(["param" not in cube for cube in self.datacubes]): + raise PProcDatasetError( + "Forecast must contain a list of parameters or a wave configuration" + ) + return self + + +class ReforecastDefinition(ForecastDefinition): + dataset_type: Literal["reforecast"] = "reforecast" + scheme: str + + +class ClimatologyDefinition(BaseDefinition): + dataset_type: Literal["climatology"] = "climatology" + scheme: str + + +DatasetDefinition = Annotated[ + Union[ForecastDefinition, ReforecastDefinition, ClimatologyDefinition], + Field(discriminator="dataset_type"), +] + + +@dataclass(kw_only=True) +class Dataset: + datacubes: list[dict] + wave: Optional[list[dict]] = None + + @cached_property + def qube(self) -> Qube: + dataqube = Qube.empty() + for cube in self.datacubes: + dataqube = dataqube | Qube.from_datacube(cube) + return dataqube + + @cached_property + def wave_qube(self) -> Qube: + if self.wave is None: + raise PProcDatasetError("No wave configuration defined for this forecast") + wave_qube = Qube.empty() + for condition in self.wave: + wave_qube = wave_qube | self.qube.select(condition) + return wave_qube + + @cached_property + def atmos_qube(self) -> Qube: + if self.wave is None: + raise PProcDatasetError("No wave configuration defined for this forecast") + return self.qube - self.wave_qube + + def stream(self, request: dict) -> str: + if self.wave is None: + raise PProcDatasetError("No wave configuration defined for this forecast") + for condition in self.wave: + if all([request[key] == value for key, value in condition.items()]): + return "wave" + return "atmos" + + def stream_qube(self, stream: Optional[str]) -> Qube: + if stream is None: + return self.qube + if stream == "wave": + return self.wave_qube + if stream == "atmos": + return self.atmos_qube + return self.qube.select({"stream": stream}) + + def type_qube(self, tp: Optional[str], number: Optional[str]) -> Qube: + qube = self.qube if tp is None else self.qube.select({"type": tp}) + if number is None or number == "{number}" or "number" not in qube.axes(): + return qube + + if isinstance(number, int): + number = [number] + number_axes = sorted(qube.axes()["number"]) + start = bisect.bisect_left(number, number_axes[0]) + end = bisect.bisect_right(number, number_axes[-1]) + return qube.select({"number": number[start:end]}) + + def select( + self, selection: dict, select_to_override: bool = False + ) -> tuple[Qube, dict]: + stream = selection.pop("stream", None) + tp = selection.pop("type", None) + number = selection.pop("number", None) + stream_qube = self.stream_qube(stream) + type_qube = self.type_qube(tp, number) + qube = stream_qube & type_qube + overrides = {} + for key, vals in selection.items(): + logger.debug(f"Selecting {key}:{vals} from {qube}") + if key in qube.axes(): + qube = qube.select({key: vals}) + if len(qube.axes().get(key, [])) != len(np.atleast_1d(vals)): + logger.debug( + f"Not all required inputs retrieved, got {qube.axes().get(key, [])}" + ) + return Qube.empty(), {} + elif select_to_override: + overrides[key] = vals + else: + return Qube.empty(), {} + return qube, overrides + + def steps(self, request: dict) -> list[int] | list[str]: + time = request.get("time", None) + qube = self.qube + if time is not None and len(qube.axes().get("time", [])) > 1: + qube = self.qube.select({"time": time}) + if qube.n_leaves == 0: + raise PProcDatasetError(f"No datacubes available for time {time}") + steps = list(qube.axes()["step"]) + return sorted( + steps, key=lambda x: int(x.split("-")[0]) if isinstance(x, str) else x + ) + + def sample_datacube(self, qube: Optional[Qube] = None) -> dict: + qube = qube or self.qube + if qube.n_leaves == 0: + raise PProcDatasetError("No datacubes available for this forecast") + return validate_request(list(qube.datacubes())[0]) + + +@dataclass(kw_only=True) +class Forecast(Dataset): + fc_type: Literal["forecast"] = "forecast" + unperturbed: Optional[dict] = None + + @cached_property + def unperturbed_qube(self) -> Qube: + if self.unperturbed is None: + return Qube.empty() + return self.qube.select(self.unperturbed) + + @cached_property + def perturbed_qube(self) -> Qube: + return self.qube - self.unperturbed_qube + + @cached_property + def is_ensemble(self) -> bool: + n_perturbed = len(self.qube.axes().get("number", [])) + n_unperturbed = 0 + if self.unperturbed is not None: + n_unperturbed = 1 if self.type_qube("unperturbed").n_leaves > 0 else 0 + return (n_perturbed + n_unperturbed) > 1 + + def type_qube(self, tp: Optional[str], number: Optional[str] = None) -> Qube: + if tp is None: + qube = self.qube + elif tp == "unperturbed": + if self.unperturbed is None: + raise ValueError( + "No unperturbed configuration defined for this forecast" + ) + qube = self.unperturbed_qube + elif tp == "perturbed": + if self.unperturbed is None: + raise ValueError( + "No unperturbed configuration defined for this forecast" + ) + qube = self.perturbed_qube + else: + qube = self.qube.select({"type": tp}) + + if number is None or number == "{number}" or "number" not in qube.axes(): + return qube + + if isinstance(number, int): + number = [number] + number_axes = sorted(qube.axes()["number"]) + start = bisect.bisect_left(number, number_axes[0]) + end = bisect.bisect_right(number, number_axes[-1]) + return qube.select({"number": number[start:end]}) + + def select( + self, selection: dict, select_to_override: bool = False + ) -> tuple[Qube, dict]: + ensemble = selection.pop("ensemble", None) + if ensemble is not None and ensemble != self.is_ensemble: + return Qube.empty(), {} + return super().select(selection, select_to_override=select_to_override) + + def sample_datacube(self, qube: Optional[Qube] = None, pop: list[str] = []) -> dict: + qube = qube or self.qube + if qube.n_leaves == 0: + raise ValueError("No datacubes available for this forecast") + if self.is_ensemble and "number" in qube.axes(): + number_axes = sorted(map(int, qube.axes()["number"])) + qube = qube.select({"number": [str(number_axes[0])]}) + out = validate_request(list(qube.datacubes())[0]) + for key in pop: + out.pop(key, None) + return out + + +@dataclass(kw_only=True) +class Reforecast(Forecast): + scheme: str + + +@dataclass(kw_only=True) +class Climatology(Dataset): + scheme: str + + +class DatasetDefinitions(PProcBaseModel): + definitions: dict[str, DatasetDefinition] + + def definition(self, name: str) -> DatasetDefinition: + if name not in self.definitions: + raise ValueError(f"Dataset {name} not defined") + return self.definitions[name] + + +def definition_to_dataset(definition: DatasetDefinition) -> Dataset: + if isinstance(definition, ForecastDefinition): + return Forecast( + datacubes=definition.datacubes, + wave=definition.wave, + unperturbed=definition.unperturbed, + ) + elif isinstance(definition, ReforecastDefinition): + return Reforecast( + datacubes=definition.datacubes, + wave=definition.wave, + unperturbed=definition.unperturbed, + scheme=definition.scheme, + ) + elif isinstance(definition, ClimatologyDefinition): + return Climatology( + datacubes=definition.datacubes, + wave=definition.wave, + scheme=definition.scheme, + ) + else: + raise ValueError(f"Unknown dataset definition type: {type(definition)}") diff --git a/pproc-core/src/ppcore/schema/input.py b/pproc-core/src/ppcore/schema/input.py new file mode 100644 index 00000000..bc789cfa --- /dev/null +++ b/pproc-core/src/ppcore/schema/input.py @@ -0,0 +1,426 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import logging +import itertools +from typing import Any +from typing import Iterator +from typing import Optional +from typing import Union +from typing import Literal + +from pydantic import field_validator + +from qubed import Qube +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from earthkit.workflows.plugins.pproc.utils.metadata import fill_template_values +from ppcore.schema.base import BaseSchema +from ppcore.schema.step import StepSchema +from ppcore.utils.helpers import to_list +from ppcore.schema.forecast import ( + Dataset, + Forecast, + Reforecast, + Climatology, + ForecastDefinition, + ReforecastDefinition, + ClimatologyDefinition, + definition_to_dataset, +) +from ppcore.schema.deriver import ForecastDeriver, ClimatologyDeriver +from ppcore.schema.filters import ( + _members, + _selection, + _steplength, + _steptype, +) +from ppcore.schema.exceptions import PProcInputSchemaError, PProcDatasetError +from ppcore.utils.requests import ( + validate_request, + update_request, + expand, +) +from ppcore.utils.mars import extract_mars +from ppcore.utils.qube import union + +logger = logging.getLogger(__name__) + + +INHERIT_FROM_OUTPUT = [ + "class", + "expver", + "date", + "time", + "levtype", + "levelist", + "param", + "step", + "model", + "method", + "origin", + "system", +] + + +class ForecastInput(PProcBaseModel): + select: dict = {} + derive: dict[str, list[ForecastDeriver]] = {} + override: dict = {} + select_to_override: bool = False + + @field_validator("derive", mode="before") + @classmethod + def format_derivers(cls, data: Any) -> Any: + if isinstance(data, dict): + for key, derivers in data.items(): + if isinstance(derivers, dict): + data[key] = [derivers] + return data + + def _from_output(self, request: dict, pop: list[str] = []) -> dict: + out = {} + inherit = set(INHERIT_FROM_OUTPUT) + for key in self.derive.keys(): + if key in inherit: + inherit.remove(key) + for key in inherit: + if key in request: + out[key] = request[key] + return out + + def derived_selection(self, base_request: dict, forecast: Dataset) -> dict: + derived_selection = {} + request = base_request.copy() + for key, derivers in self.derive.items(): + for deriver in derivers: + request[key] = deriver.derive(request, forecast) + derived_selection[key] = request[key] + return derived_selection + + def requests( + self, + base_request: dict, + forecast: Dataset, + **extra, + ) -> Iterator[dict]: + select_criteria = self.create_selection(base_request, forecast) + selection, select_overrides = forecast.select( + select_criteria, select_to_override=self.select_to_override + ) + logger.debug( + "Selected cubes: %s, select overrides: %s", selection, select_overrides + ) + override = self.override.copy() + override.update(select_overrides) + if "target_grid" in base_request: + override["target_grid"] = base_request["target_grid"] + pop = [] + for key, value in override.items(): + if value is None: + override.pop(key) + pop.append(key) + + # Order outputs by unperturbed first, if present + datacubes = [] + if ( + getattr(forecast, "unperturbed", None) is not None + and selection.select(forecast.unperturbed).n_leaves > 0 + ): + datacubes.extend(selection.select(forecast.unperturbed).datacubes()) + datacubes.extend( + cube for cube in selection.datacubes() if cube not in datacubes + ) + else: + datacubes = list(selection.datacubes()) + for cube in datacubes: + cube.update(override) + for key in pop: + cube.pop(key, None) + if cube["type"] in ["fcmean", "fcmax", "fcstdev", "fcmin"]: + cube.setdefault("number", 0) + cube.update(extra) + # Sort request keys for consistent ordering in output configs + yield validate_request({k: v for k, v in sorted(cube.items())}) + + def create_selection( + self, base_request: dict, forecast: Dataset, include_derived: bool = True + ) -> dict: + selection = self.select.copy() + if include_derived: + selection.update(self.derived_selection(base_request, forecast)) + selection = fill_template_values(selection, base_request) + if forecast.wave is not None and "stream" not in selection: + selection["stream"] = forecast.stream(base_request) + return validate_request({**self._from_output(base_request), **selection}) + + def match( + self, request: dict, forecast: Union[Forecast, Reforecast] + ) -> Iterator[Qube]: + if "param" not in self.select: + groupby = ["param", "levtype"] + else: + groupby = ["levtype"] + + selection = self.create_selection(request, forecast, include_derived=False) + request_qube, _ = forecast.select(selection) + logger.debug( + "Selected %s from forecast using selection %s", request_qube, selection + ) + seen = set() + for cube in request_qube.datacubes(): + for selection in zip(*[cube[axis] for axis in groupby if axis in cube]): + selection_key = str(selection) + if selection_key in seen: + continue + seen.add(selection_key) + selected = request_qube.select(dict(zip(groupby, selection))) + if selected.n_leaves == 0: + raise KeyError( + f"No datacubes available for selection {selection} from request {request_qube}" + ) + yield selected + + +class ClimatologyInput(ForecastInput): + derive: dict[str, list[ClimatologyDeriver]] = {} + + @field_validator("select", mode="after") + @classmethod + def populate_request(cls, select: dict) -> dict: + if select.get("type", None) == "cd": + select["quantile"] = [f"{x}:100" for x in range(0, 101)] + return select + + @field_validator("derive", mode="after") + @classmethod + def validate_derivers( + cls, derive: dict[str, list[ClimatologyDeriver]] + ) -> dict[str, list[ClimatologyDeriver]]: + if "step" not in derive: + raise PProcInputSchemaError("Step driver required for climatology input") + if "date" not in derive: + raise PProcInputSchemaError("Date driver required for climatology input") + return derive + + def create_selection( + self, base_request: dict, forecast: Dataset, include_derived: bool = True + ) -> dict: + selection = self.select.copy() + if include_derived: + selection.update(self.derived_selection(base_request, forecast)) + selection = fill_template_values(selection, base_request) + if forecast.wave is not None and "stream" not in selection: + selection["stream"] = forecast.stream(base_request) + return validate_request( + {**self._from_output(base_request, pop=["number", "date"]), **selection} + ) + + +class InputConfig(PProcBaseModel): + fc_inputs: list[ForecastInput] + clim_inputs: Optional[list[ClimatologyInput]] = None + from_inputs: bool = True + + @field_validator("fc_inputs", mode="before") + @classmethod + def format_fc_inputs(cls, data: Any) -> Any: + if isinstance(data, dict): + data = [data] + return data + + @field_validator("clim_inputs", mode="before") + @classmethod + def format_clim_inputs(cls, data: Any) -> Any: + if isinstance(data, dict): + data = [data] + return data + + def inputs( + self, + output_request: dict, + forecast: Union[Forecast], + climatology: Optional[Climatology] = None, + ) -> Iterator[dict]: + sample_input = None + for inp in self.fc_inputs: + inputs = list(inp.requests(output_request, forecast)) + if len(inputs) == 0: + raise PProcDatasetError( + f"No forecast inputs matched for {output_request}, requiring {inp}" + ) + if sample_input is None: + sample_input = inputs[0] + yield from inputs + + if self.clim_inputs: + assert ( + climatology is not None + ), "Climatology input defined but no climatology provided" + for inp in self.clim_inputs: + yield from inp.requests( + validate_request(sample_input), climatology, climatology=True + ) + + def matched_outputs( + self, + request: dict, + forecast: Union[Forecast, Reforecast], + climatology: Optional[Climatology] = None, + step_schema: Optional[StepSchema] = None, + ) -> Iterator[dict]: + fc_inputs = [ + union(paired_inputs) + for paired_inputs in zip( + *[list(inp.match(request, forecast)) for inp in self.fc_inputs] + ) + ] + if len(fc_inputs) == 0: + logger.debug("No inputs for request %s", request) + return iter([]) + + if self.clim_inputs and len(fc_inputs) > 1: + raise PProcDatasetError("Climatology should be uniquely tied to forecast") + # Determine output steps that can be generated + step_schema = step_schema or StepSchema({}) + fc_steps = list(fc_inputs[0].axes()["step"]) + if len(fc_steps) > 1: + if any("-" in str(x) for x in fc_steps): + raise NotImplementedError( + "Combining different step ranges is not supported" + ) + fc_steps = sorted(list(map(int, fc_steps))) + + sample = forecast.sample_datacube(fc_inputs[0], pop=["step", "number"]) + step_dim, out_steps = step_schema.out_steps({**sample, **request}, fc_steps) + logger.debug( + "Obtained values %s from forecast steps %s for dim %s", + out_steps, + fc_steps, + step_dim, + ) + + for fc_input, step in itertools.product(fc_inputs, out_steps): + sample_datacube = forecast.sample_datacube(fc_input, pop=["step", "number"]) + out = {**sample_datacube, **request, step_dim: step} + # Determine climatology is present + if self.clim_inputs: + if climatology is None: + raise PProcDatasetError( + "Climatology input required but no climatology provided" + ) + clim_input = [ + union(paired_inputs) + for paired_inputs in zip( + *[ + list(inp.match(request, climatology)) + for inp in self.clim_inputs + ] + ) + ] + if len(clim_input) == 0: + continue + if len(clim_input) > 1: + raise PProcDatasetError( + "Climatology should be uniquely tied to forecast" + ) + yield out + + +def _update_inputs(config, update) -> dict: + for key, val in update.items(): + config[key] = update_request(config.get(key, {}), val) + return config + + +class InputSchema(BaseSchema): + exception = PProcInputSchemaError + custom_update = { + "fc_inputs": _update_inputs, + "clim_inputs": _update_inputs, + } + custom_filter = { + "steptype": _steptype, + "steplength": _steplength, + "selection": _selection, + "members": _members, + } + + def inputs( + self, + output_request: dict, + forecast: Union[ForecastDefinition, ReforecastDefinition], + climatology: Optional[Climatology] = None, + ) -> Iterator[dict]: + output_request = validate_request(output_request) + config = InputConfig(**self.traverse(output_request)) + forecast = definition_to_dataset(forecast) + if climatology is not None: + climatology = definition_to_dataset(climatology) + + for inp in config.inputs(output_request, forecast, climatology): + yield inp + + def _set_defaults(cls, output_request: dict, input_requests: list[dict]) -> dict: + output_request = validate_request(output_request) + tp = output_request["type"] + if tp in ["fcmean", "fcmax", "fcstdev", "fcmin"]: + output_request["number"] = sum( + [to_list(req.get("number", [0])) for req in input_requests], [] + ) + elif tp in ["pf", "gwt"]: + for req in input_requests: + if req["type"] in ["pf", "gwt"] and "number" in req: + output_request["number"] = req["number"] + break + elif tp in ["pb", "cd"]: + output_request.setdefault("quantile", [f"{x}:100" for x in range(0, 101)]) + elif tp == "sot": + output_request.setdefault("number", [10, 90]) + return output_request + + def outputs( + self, + forecast: Union[ForecastDefinition, ReforecastDefinition], + climatology: Optional[ClimatologyDefinition] = None, + step_schema: Optional[StepSchema] = None, + output_template: Optional[dict[str, Any]] = None, + method: Literal["dfs", "bfs"] = "bfs", + enable_cache: bool = True, + ) -> Iterator[tuple[dict, list[dict]]]: + """ + Assumes inputs are from the same forecast for a single date and time + """ + output_template = output_template or {} + forecast = definition_to_dataset(forecast) + if climatology is not None: + climatology = definition_to_dataset(climatology) + # Check that the output template contains the required keys to derive outputs from inputs + # To avoid generating outputs across different streams + # TODO: consider splitting schema by dataset definers to avoid this requirement + dataset_definers = {"class", "stream", "model"} + required = set.intersection(dataset_definers, self.all_filters) + if any(key not in output_template for key in required): + raise ValueError( + f"Output template must contain {required} to derive outputs from inputs" + ) + for template in expand(output_template, dim=self.all_filters): + template = validate_request(template) + # Derive output requests and corresponding input configs that match the template + for base_output, config in self.reconstruct( + output_template=template, + from_inputs=True, + method=method, + enable_cache=enable_cache, + ): + logger.debug("Reconstructed output %s", base_output) + config = InputConfig(**config) + # Perform intersection with the forecast and climatology qubes to determine + # the actual output requests that can be generated from the inputs + for mout in config.matched_outputs( + base_output, forecast, climatology, step_schema + ): + inputs = list(config.inputs(mout, forecast, climatology)) + mout = extract_mars(self._set_defaults(mout, inputs)) + logger.info("Output %s, requiring inputs %s", mout, inputs) + yield mout, inputs diff --git a/pproc-core/src/ppcore/schema/schema.py b/pproc-core/src/ppcore/schema/schema.py new file mode 100644 index 00000000..5e3a8900 --- /dev/null +++ b/pproc-core/src/ppcore/schema/schema.py @@ -0,0 +1,109 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +from typing import Iterator, Optional, Union, Literal, Any + +import numpy as np +import yaml +from typing_extensions import Self + +from ppcore.schema.config import ConfigSchema +from ppcore.schema.input import InputSchema +from ppcore.schema.step import StepSchema +from ppcore.schema.forecast import ( + DatasetDefinitions, + DatasetDefinition, + ForecastDefinition, + ReforecastDefinition, + ClimatologyDefinition, +) +from ppcore.utils.mars import METADATA_KEYS +from ppcore.utils.requests import VALUE_TYPES, expand + + +class Schema: + def __init__( + self, + config: dict, + inputs: dict, + windows: dict, + datasets: dict, + matching_cache_size: int = 0, + ): + self.config_schema = ConfigSchema( + config, matching_cache_size=matching_cache_size + ) + self.param_schema = InputSchema(inputs, matching_cache_size=matching_cache_size) + self.step_schema = StepSchema(windows, matching_cache_size=matching_cache_size) + self.datasets = DatasetDefinitions(definitions=datasets) + + @classmethod + def from_file( + cls, schema_path: Union[str, os.PathLike], matching_cache_size: int = 0 + ) -> Self: + with open(schema_path, "r") as f: + schema = yaml.safe_load(f) + return cls(**schema, matching_cache_size=matching_cache_size) + + def config_from_output( + self, + output_request: dict[str, Any], + forecast: Union[ForecastDefinition, ReforecastDefinition], + climatology: Optional[ClimatologyDefinition] = None, + ) -> dict: + config = self.config_schema.config(output_request) + inputs = list(self.param_schema.inputs(output_request, forecast, climatology)) + + # Set metadata + base_request = inputs[0] + metadata = config.setdefault("metadata", {}) + if np.size(base_request["param"]) > 1: + config["name"] = f"{output_request['param']}_{output_request['levtype']}" + config.setdefault( + "name", f"{base_request['param']}_{output_request['levtype']}" + ) + for key in config.pop("metadata_from_output", []): + if base_request.get(key, None) != VALUE_TYPES.get(key, str)( + output_request[key] + ): + metadata_key = METADATA_KEYS.get(key, key) + metadata[metadata_key] = VALUE_TYPES.get(metadata_key, str)( + output_request[key] + ) + return {**config, "inputs": inputs} + + def config_from_input( + self, + forecast: Union[ForecastDefinition, ReforecastDefinition], + climatology: Optional[ClimatologyDefinition] = None, + output_template: Optional[dict] = None, + ) -> Iterator[dict]: + for output_template in expand(output_template) if output_template else [None]: + for output, inputs in self.outputs_from_inputs( + forecast, climatology, output_template=output_template + ): + out_config = self.config_from_output(output, forecast, climatology) + out_config["inputs"] = inputs + yield out_config + + def outputs_from_inputs( + self, + forecast: Union[ForecastDefinition, ReforecastDefinition], + climatology: Optional[ClimatologyDefinition] = None, + output_template: Optional[dict[str, Any]] = None, + method: Literal["dfs", "bfs"] = "bfs", + enable_cache: bool = True, + ) -> Iterator[tuple[dict, list[dict]]]: + yield from self.param_schema.outputs( + forecast, + climatology, + self.step_schema, + output_template, + method=method, + enable_cache=enable_cache, + ) + + def definition(self, name: str) -> DatasetDefinition: + return self.datasets.definition(name) diff --git a/pproc-core/src/ppcore/schema/step.py b/pproc-core/src/ppcore/schema/step.py new file mode 100644 index 00000000..a6e1450a --- /dev/null +++ b/pproc-core/src/ppcore/schema/step.py @@ -0,0 +1,135 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import bisect +from typing import Annotated +from typing import Literal +from typing import Optional +from typing import Union + +import numpy as np +from pydantic import Field +from pydantic import RootModel + +from earthkit.workflows.plugins.pproc.utils.pydantic_utils import PProcBaseModel +from ppcore.schema.base import BaseSchema +from ppcore.schema.exceptions import PProcStepSchemaError +from ppcore.utils.stepseq import steprange_to_fcmonth, stepseq_monthly + + +class Instantaneous(PProcBaseModel): + type_: Literal["instantaneous"] = Field("instantaneous", alias="type") + deaccumulate: bool = False + start: Optional[int] = None + end: Optional[int] = None + interval: Optional[int] = None + dim: Literal["step"] = "step" + + def generate_steps(self, steps: list[int]) -> list[int]: + start = self.start or steps[0] + end = self.end or steps[-1] + if self.interval: + interval_steps = list(range(start, end + 1, self.interval)) + selected_steps = [x for x in interval_steps if x in steps] + else: + start_index = bisect.bisect_left(steps, start) + end_index = bisect.bisect_right(steps, end) + selected_steps = steps[start_index:end_index] + return selected_steps[1:] if self.deaccumulate else selected_steps + + +class Range(PProcBaseModel): + type_: Literal["range"] = Field("range", alias="type") + start: Optional[int] = None + end: Optional[int] = None + interval: int + width: int + dim: Literal["step"] = "step" + + def generate_steps(self, steps: Union[list[int], list[str]]) -> list[str]: + if all(isinstance(x, str) for x in steps): + return steps # type: ignore + assert all( + isinstance(x, int) for x in steps + ), "Steps can not be a mix of strings and integers" + start: int = self.start or steps[0] # type: ignore + end: int = min((self.end or steps[-1]), steps[-1]) - self.width # type: ignore + rstarts = set(range(start, end + 1, self.interval)) + rstarts.intersection_update(steps) + return [f"{rstart}-{rstart + self.width}" for rstart in sorted(rstarts)] + + +class Monthly(PProcBaseModel): + type_: Literal["monthly"] = Field("monthly", alias="type") + date: str + dim: Literal["fcmonth"] = "fcmonth" + + def generate_steps(self, steps: list[int]) -> list[int]: + by = np.diff(steps) + if len(by) == 0: + return [] + if len(set(by)) != 1: + raise ValueError("Monthly steps must be evenly spaced") + return [ + steprange_to_fcmonth(self.date, f"{x[0]}-{x[-1]}") + for x in stepseq_monthly(self.date, steps[0], steps[-1], by[0]) + ] + + +StepType = RootModel[ + Annotated[ + Union[Instantaneous, Range, Monthly], + Field(discriminator="type_"), + ] +] + + +class StepSchema(BaseSchema): + exception = PProcStepSchemaError + + @classmethod + def _create_steps(cls, step_config: list[dict]) -> list[int]: + steps = set( + sum( + [ + list(range(x["from"], x["to"] + 1, x.get("by", 1))) + for x in step_config + ], + [], + ) + ) + return sorted(steps) + + def out_steps( + self, request: dict, in_steps: list[int] + ) -> tuple[str, list[Union[int, str]]]: + for dim in ["step", "fcmonth"]: + if dim in request: + return dim, [request[dim]] + + config = self.traverse(request, {}) + step_configs = config.get("out_steps", None) + if step_configs is None: + raise self.exception(f"No output steps defined {request}") + + if isinstance(step_configs, dict): + step_configs = [step_configs] + + out = [] + dim: str = "" + for step_config in step_configs: + if isinstance(step_config, str): + if all(x in in_steps for x in map(int, step_config.split("-"))): + out.append(step_config) + continue + step_config = { + k: v.format_map(request) if isinstance(v, str) else v + for k, v in step_config.items() + } + step_type = StepType(**step_config).root + if not dim: + dim = step_type.dim + assert dim == step_type.dim, "All steps must be of the same dimension" + out.extend([x for x in step_type.generate_steps(in_steps) if x not in out]) + return dim, out diff --git a/pproc-core/src/ppcore/utils/dicts.py b/pproc-core/src/ppcore/utils/dicts.py new file mode 100644 index 00000000..bafd902f --- /dev/null +++ b/pproc-core/src/ppcore/utils/dicts.py @@ -0,0 +1,44 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import collections +import itertools +from typing import Callable +from typing import Dict +from typing import Iterable +from typing import Iterator +from typing import TypeAlias +from typing import TypeVar + +K = TypeVar("K") +T = TypeVar("T") +U = TypeVar("U") +V = TypeVar("V") +NestedDict: TypeAlias = Dict[K, V | "NestedDict"] + + +def dict_product(dic: collections.abc.Mapping[K, Iterable[V]]) -> Iterator[Dict[K, V]]: + keys = list(dic.keys()) + its = tuple(dic.values()) + for vals in itertools.product(*its): + yield dict(zip(keys, vals)) + + +def dict_apply(func: Callable[[V], V], dic: NestedDict) -> NestedDict: + modified_dic = dic.copy() + for k, v in modified_dic.items(): + if isinstance(v, dict): + modified_dic[k] = dict_apply(func, v) + else: + modified_dic[k] = func(v) + return modified_dic + + +def deep_update(original: NestedDict, update: NestedDict) -> NestedDict: + for key, value in update.items(): + if isinstance(value, dict) and isinstance(original.get(key, None), dict): + original[key] = deep_update(original[key], value) + else: + original[key] = value + return original diff --git a/pproc-core/src/ppcore/utils/entrypoint.py b/pproc-core/src/ppcore/utils/entrypoint.py new file mode 100644 index 00000000..1ba648b7 --- /dev/null +++ b/pproc-core/src/ppcore/utils/entrypoint.py @@ -0,0 +1,25 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Any + + +def parse_vars(items: list[str]) -> dict: + """ + Parse a series of key-value pairs and return a dictionary + """ + return dict(map(lambda s: s.split("="), items)) + + +def parse_var_strs(items: list[str]) -> dict: + """ + Parse a list of comma-separated lists of key-value pairs and return a dictionary + """ + return parse_vars(sum((s.split(",") for s in items if s), start=[])) + + +def validate_overrides(data: Any) -> Any: + if isinstance(data, list): + return parse_var_strs(data) + return data diff --git a/pproc-core/src/ppcore/utils/helpers.py b/pproc-core/src/ppcore/utils/helpers.py new file mode 100644 index 00000000..f846adbb --- /dev/null +++ b/pproc-core/src/ppcore/utils/helpers.py @@ -0,0 +1,13 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Any + +import numpy as np + + +def to_list(value: Any) -> list[Any]: + if np.ndim(value) == 0: + return [value] + return list(value) diff --git a/pproc-core/src/ppcore/utils/io.py b/pproc-core/src/ppcore/utils/io.py new file mode 100644 index 00000000..c3798487 --- /dev/null +++ b/pproc-core/src/ppcore/utils/io.py @@ -0,0 +1,17 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional, Tuple +import re + +_LOCATION_RE = re.compile("^([a-z](?:[a-z0-9+-.])*):(.*)$", re.I) + + +def split_location( + loc: str, default: Optional[str] = None +) -> Tuple[Optional[str], str]: + m = _LOCATION_RE.fullmatch(loc) + if m is None: + return (default, loc) + return m.groups() # type: ignore diff --git a/pproc-core/src/ppcore/utils/mars.py b/pproc-core/src/ppcore/utils/mars.py new file mode 100644 index 00000000..cd6473a3 --- /dev/null +++ b/pproc-core/src/ppcore/utils/mars.py @@ -0,0 +1,77 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional +from datetime import datetime, date +from math import ceil + +METADATA_KEYS = {"param": "paramId", "date": "dataDate"} + + +def _val_to_mars(val): + if isinstance(val, bytes): + return val + elif isinstance(val, (list, tuple)): + return b"/".join(_val_to_mars(v) for v in val) + elif isinstance(val, str): + pass + elif isinstance(val, int): + val = str(val) + elif isinstance(val, (datetime, date)): + val = val.strftime("%Y%m%d") + elif isinstance(val, range): + first = val.start + last = val.start + (ceil((val.stop - val.start) / val.step) - 1) * val.step + step = val.step + val = f"{first}/to/{last}" + if step != 1: + val += f"/by/{step}" + elif isinstance(val, float) and val.is_integer(): + val = str(int(val)) + else: + raise TypeError(f"Cannot convert {type(val)} to MARS request") + return val.encode("utf-8") + + +def to_mars(verb: bytes, req: dict) -> bytes: + def _gen_req(): + yield verb + for key, val in req.items(): + key = key.encode("utf-8") + val = _val_to_mars(val) + yield key + b"=" + val + + return b",".join(_gen_req()) + + +def extract_mars(keys: dict, additional: Optional[list[str]] = None) -> dict: + additional = additional or [] + for key, metadata_key in METADATA_KEYS.items(): + if metadata_key in keys: + keys[key] = keys.pop(metadata_key) + mars_namespace = [ + "class", + "type", + "stream", + "expver", + "model", + "levtype", + "levelist", + "param", + "date", + "year", + "month", + "hdate", + "fcmonth", + "fcperiod", + "time", + "step", + "number", + "domain", + "quantile", + "method", + "origin", + "system", + ] + return {k: v for k, v in keys.items() if (k in mars_namespace) or (k in additional)} diff --git a/pproc-core/src/ppcore/utils/qube.py b/pproc-core/src/ppcore/utils/qube.py new file mode 100644 index 00000000..9cdbbfec --- /dev/null +++ b/pproc-core/src/ppcore/utils/qube.py @@ -0,0 +1,27 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Iterable + +from qubed import Qube + + +def union(qubes: Iterable[Qube]) -> Qube: + """ + Return the union of a list of Qubes + """ + out = Qube.empty() + for qube in qubes: + out = out | qube + return out + + +def qube_from_datacubes(datacubes: Iterable[dict]) -> Qube: + """ + Return a Qube from a list of datacubes + """ + out = Qube.empty() + for cube in datacubes: + out = out | Qube.from_datacube(cube) + return out diff --git a/pproc-core/src/ppcore/utils/requests.py b/pproc-core/src/ppcore/utils/requests.py new file mode 100644 index 00000000..d623b934 --- /dev/null +++ b/pproc-core/src/ppcore/utils/requests.py @@ -0,0 +1,148 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import copy +import itertools +from typing import Iterator, Optional, Iterable, Any + +import numpy as np +import pandas as pd +from qubed import Qube + +from ppcore.utils.dicts import deep_update +from ppcore.utils.dicts import dict_product +from ppcore.utils.helpers import to_list + + +VALUE_TYPES = { + "param": str, + "paramId": int, + "levelist": int, + "step": int, + "fcmonth": int, + "number": int, + "dataDate": int, + "date": str, +} + + +def validate_request(request: dict) -> dict: + """ + Format request into desired format for schema and config generation + """ + out = copy.deepcopy(request) + # Map types + for key, value in request.items(): + if isinstance(value, list) and len(value) == 1: + value = value[0] + if key in VALUE_TYPES: + value_type = VALUE_TYPES[key] + try: + value = ( + value_type(value) + if np.ndim(value) == 0 + else list(map(value_type, value)) + ) + except ValueError: + pass + out[key] = value + # Format time + if times := out.get("time", None): + if isinstance(times, (int, str)): + times = [times] + out_times = [] + for ti in times: + out_times.append(f"{int(ti):02d}".ljust(4, "0")) + out["time"] = out_times if len(out_times) > 1 else out_times[0] + return out + + +def expand( + requests: dict[str, Any] | Iterable[dict[str, Any]], + dim: Optional[str | list[str]] = None, + exclude: list[str] = [], +) -> Iterator[dict]: + requests: Iterable[dict[str, Any]] = ( + [requests] if isinstance(requests, dict) else requests + ) # type: ignore + + for request in requests: + request = copy.deepcopy(request) + # Expand all if no dimension is specified + if dim is None: + dims = [x for x in request.keys() if x not in exclude] + elif isinstance(dim, str): + dims = [dim] + else: + dims = dim + + expansion = {} + for d in dims: + coords = request.pop(d, None) + if coords is None: + continue + expansion[d] = to_list(coords) + + for vals in dict_product(expansion): + yield {**request, **vals} + + +def squeeze(reqs: list[dict], dims: list[str]) -> Iterator[dict]: + df = pd.DataFrame(reqs) + drop_dims = df.drop(dims, axis=1, errors="ignore").drop_duplicates() + for _, row in drop_dims.iterrows(): + req = row.dropna().to_dict() + condition = np.logical_and.reduce([df[k] == v for k, v in req.items()]) + cond_reqs = df.loc[condition].to_dict("records") + for dim in dims: + val = cond_reqs[0].get(dim, np.nan) + if val is None: + continue + if isinstance(val, str) or not np.isnan(val): + req[dim] = sorted(list({x[dim] for x in cond_reqs})) + yield req + + +def datacubes(reqs: list[dict]) -> Iterator[dict]: + qube = Qube.empty() + for req in reqs: + qube = qube | Qube.from_datacube(req) + for dataqube in qube.datacubes(): + yield {key: val if len(val) > 1 else val[0] for key, val in dataqube.items()} + + +def update_request( + base: dict | list[dict], update: dict | list[dict], method: str = "map", **kwargs +): + if isinstance(base, dict): + base = [base] + if isinstance(update, dict): + update = [update] + + if len(update) == 0: + return copy.deepcopy(base) + if len(base) == 0: + return copy.deepcopy(update) + if method == "map": + if len(base) == len(update): + combinations = zip(base, update) + else: + assert len(base) == 1 or len(update) == 1 + combinations = itertools.product(base, update) + elif method == "product": + combinations = itertools.product(base, update) + else: + raise ValueError( + f"Unknown method for combining requests: {method}. Supported methods are 'map' and 'product'" + ) + new_requests = [ + deep_update(copy.deepcopy(breq), {**ureq, **kwargs}) + for breq, ureq in combinations + ] + # Remove duplicates + deduplicated = [] + for inp in new_requests: + if inp not in deduplicated: + deduplicated.append(inp) + return deduplicated diff --git a/pproc-core/src/ppcore/utils/stepseq.py b/pproc-core/src/ppcore/utils/stepseq.py new file mode 100644 index 00000000..a41b4149 --- /dev/null +++ b/pproc-core/src/ppcore/utils/stepseq.py @@ -0,0 +1,70 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import datetime +from typing import Iterator + +from earthkit.time.calendar import MonthInYear +from earthkit.time.sequence import MonthlySequence + + +def steprange_to_fcmonth(fcdate: datetime.datetime | str, steprange: str) -> int: + if isinstance(fcdate, str): + fcdate = datetime.datetime.strptime(str(fcdate), "%Y%m%d") + start, end = map(int, steprange.split("-")) + seq = MonthlySequence(1) + first_month = seq.next(fcdate, False) + this_month = fcdate + datetime.timedelta(hours=int(start)) + + month_length = MonthInYear(this_month.year, this_month.month).length() * 24 + assert ( + month_length == (end - start) + ), f"Expected month length {end - start} for {fcdate} and step range {steprange}. Got {month_length}." + + return ( + (this_month.year - first_month.year) * 12 + + this_month.month + - first_month.month + + 1 + ) + + +def fcmonth_to_steprange(fcdate: datetime.datetime | str, fcmonth: int) -> str: + if isinstance(fcdate, str): + fcdate = datetime.datetime.strptime(str(fcdate), "%Y%m%d") + seq = MonthlySequence(1) + month = seq.next(fcdate, False) + for _ in range(1, fcmonth): + month = seq.next(month, True) + date = datetime.datetime(month.year, month.month, month.day) + start = (date - fcdate).total_seconds() // 3600 + end = start + MonthInYear(date.year, date.month).length() * 24 + return f"{int(start)}-{int(end)}" + + +def stepseq_monthly(date: str, start: int, end: int, interval: int) -> Iterator: + fcdate = datetime.datetime.strptime(str(date), "%Y%m%d") + start_date = fcdate + datetime.timedelta(hours=start) + seq = MonthlySequence(1) + start_month = seq.next(start_date.date(), strict=False) + # Steps are in hours, from forecast date + step_start = (start_month - fcdate.date()).days * 24 + miny = MonthInYear(start_month.year, start_month.month) + while step_start < end: + delta = miny.length() * 24 + step_end = step_start + delta + + if step_end > end: + break + + yield range(step_start, step_end + 1, interval) + miny = miny.next() + step_start = step_end + + +def stepseq_ranges( + start: int, end: int, width: int, interval: int, by: int +) -> Iterator: + for start in range(start, end - width + 1, interval): + yield range(start, start + width + 1, by) diff --git a/pproc-core/tests/conftest.py b/pproc-core/tests/conftest.py new file mode 100644 index 00000000..98d46628 --- /dev/null +++ b/pproc-core/tests/conftest.py @@ -0,0 +1,17 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +from typing import Optional + +import yaml + +TEST_DIR = os.path.dirname(os.path.realpath(__file__)) +SCHEMA = os.path.join(TEST_DIR, "schema.yaml") + + +def schema(section: Optional[str] = None) -> dict: + with open(SCHEMA, "r") as f: + schema = yaml.safe_load(f) + return schema if section is None else schema[section] diff --git a/pproc-core/tests/ppcore/configs/entrypoint/test_log.py b/pproc-core/tests/ppcore/configs/entrypoint/test_log.py new file mode 100644 index 00000000..73dd7809 --- /dev/null +++ b/pproc-core/tests/ppcore/configs/entrypoint/test_log.py @@ -0,0 +1,77 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import logging +from unittest.mock import patch + +import pytest +from conflator import Conflator +from pydantic import ValidationError + +from ppcore.configs.entrypoint.log import LoggingConfig + + +def test_logging_model_default(): + """Test that the logging configuration is applied after validation.""" + model = LoggingConfig() + assert model.level == "INFO" + + # Check logging level + assert logging.getLogger().getEffectiveLevel() == logging.INFO + + +def test_logging_app_default(): + """Test that the default values are correctly set.""" + + with patch("sys.argv", ["test_script.py"]): + conflator = Conflator("pproc", LoggingConfig, nested={}) + config: LoggingConfig = conflator.load() # type: ignore + + assert config.level == "INFO" + assert config.format == "%(asctime)s; %(name)s; %(levelname)s - %(message)s" + + # Check logging level + assert logging.getLogger().getEffectiveLevel() == logging.INFO + + +def test_logging_model_set(): + """Test that the logging configuration is applied after validation.""" + model = LoggingConfig(level="DEBUG") + assert model.level == "DEBUG" + + # Check logging level + assert logging.getLogger().getEffectiveLevel() == logging.DEBUG + + +def test_logging_model_env_var(monkeypatch): + """Test that environment variable overrides are applied.""" + + monkeypatch.setenv("PPROC_LOG", "WARNING") + with patch("sys.argv", ["test_script.py"]): + conflator = Conflator("pproc", LoggingConfig, nested={}) + config: LoggingConfig = conflator.load() # type: ignore + + assert config.level == "WARNING" + + # Check logging level + assert logging.getLogger().getEffectiveLevel() == logging.WARNING + + +def test_logging_model_cli_arg(): + """Test that CLI arguments override defaults.""" + + with patch("sys.argv", ["test_script.py"] + ["--log", "ERROR"]): + conflator = Conflator("pproc", LoggingConfig, nested={}) + config: LoggingConfig = conflator.load() # type: ignore + + assert config.level == "ERROR" + + # Check logging level + assert logging.getLogger().getEffectiveLevel() == logging.ERROR + + +def test_invalid_logging_level(): + """Test that invalid logging levels raise an error.""" + with pytest.raises(ValidationError): + LoggingConfig(level="INVALID") diff --git a/pproc-core/tests/ppcore/products/templates/ensms.yaml b/pproc-core/tests/ppcore/products/templates/ensms.yaml new file mode 100644 index 00000000..8f530dbe --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/ensms.yaml @@ -0,0 +1,46 @@ +- class: od + stream: enfo + type: em + levtype: pl + levelist: [250, 500, 850] + domain: g + param: "130" + date: "20230914" + time: 12 + expver: "0001" + step: [0, 3, 6] + sources: "fdb:" +- class: od + stream: enfo + type: es + levtype: pl + levelist: [250, 500, 850] + domain: g + param: "130" + date: "20230914" + time: 12 + expver: "0001" + step: [0, 3, 6] + sources: "fdb:" +- class: od + stream: enfo + type: em + levtype: sfc + domain: g + param: "200228" + date: "20230914" + time: 12 + expver: "0001" + step: [0-6, 6-12] + sources: "fdb:" +- class: od + stream: enfo + type: es + levtype: sfc + domain: g + param: "200228" + date: "20230914" + time: 12 + expver: "0001" + step: [0-6, 6-12] + sources: "fdb:" diff --git a/pproc-core/tests/ppcore/products/templates/extreme.yaml b/pproc-core/tests/ppcore/products/templates/extreme.yaml new file mode 100644 index 00000000..198038f0 --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/extreme.yaml @@ -0,0 +1,124 @@ +- class: od + stream: enfo + type: efi + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 12-36 +- class: od + stream: enfo + type: efi + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 36-60 +- class: od + stream: enfo + type: efi + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 12-84 +- class: od + stream: enfo + type: efic + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 12-36 +- class: od + stream: enfo + type: efic + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 36-60 +- class: od + stream: enfo + type: efic + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 12-84 +- class: od + stream: enfo + type: sot + number: [90] + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 12-36 +- class: od + stream: enfo + type: sot + number: [90] + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 36-60 +- class: od + stream: enfo + type: sot + number: [90] + levtype: sfc + domain: g + param: "132228" + date: "20230914" + time: 12 + expver: "0001" + step: 12-84 +- class: od + stream: enfo + type: efi + levtype: sfc + domain: g + param: "132044" + date: "20230914" + time: 12 + expver: "0001" + step: 12-36 +- class: od + stream: enfo + type: efic + levtype: sfc + domain: g + param: "132044" + date: "20230914" + time: 12 + expver: "0001" + step: 12-36 +- class: od + stream: enfo + type: sot + number: [90] + levtype: sfc + domain: g + param: "132044" + date: "20230914" + time: 12 + expver: "0001" + step: 12-36 diff --git a/pproc-core/tests/ppcore/products/templates/prob.yaml b/pproc-core/tests/ppcore/products/templates/prob.yaml new file mode 100644 index 00000000..21863d26 --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/prob.yaml @@ -0,0 +1,88 @@ +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131060" + date: "20230914" + time: 12 + expver: "0001" + step: [0-24, 12-36] + sources: "fdb:" +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131061" + date: "20230914" + time: 12 + expver: "0001" + step: 0-24 + sources: "fdb:" +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131061" + date: "20230914" + time: 12 + expver: "0001" + step: 12-36 + sources: "fdb:" +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131098" + date: "20230914" + time: 12 + expver: "0001" + step: [0-24, 12-36] + sources: "fdb:" +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131068" + date: 20230914 + time: 12 + expver: "0001" + step: [12, 24] + sources: "fdb:" +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131069" + date: 20230914 + time: 12 + expver: "0001" + step: 12 + sources: "fdb:" +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131069" + date: 20230914 + time: 12 + expver: "0001" + step: 24 + sources: "fdb:" +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131073" + date: 20230914 + time: 12 + expver: "0001" + step: [120-168, 120-240, 168-240, 126] + sources: "fdb:" diff --git a/pproc-core/tests/ppcore/products/templates/quantiles.yaml b/pproc-core/tests/ppcore/products/templates/quantiles.yaml new file mode 100644 index 00000000..e54a1db2 --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/quantiles.yaml @@ -0,0 +1,36 @@ +- class: od + stream: enfo + type: pb + levtype: sfc + domain: g + param: "167" + date: "20230914" + time: 12 + expver: "0001" + step: [0, 3, 6] + quantile: ['0:100', '25:100', '50:100', '75:100', '100:100'] + sources: "fdb:" +- class: od + stream: enfo + type: pb + levtype: sfc + domain: g + param: "200228" + date: "20230914" + time: 12 + expver: "0001" + step: 0-6 + quantile: ['0:100', '25:100', '50:100', '75:100', '100:100'] + sources: "fdb:" +- class: od + stream: enfo + type: pb + levtype: sfc + domain: g + param: "200228" + date: "20230914" + time: 12 + expver: "0001" + step: 3-9 + quantile: ['0:100', '25:100', '50:100', '75:100', '100:100'] + sources: "fdb:" diff --git a/pproc-core/tests/ppcore/products/templates/t850.yaml b/pproc-core/tests/ppcore/products/templates/t850.yaml new file mode 100644 index 00000000..263433e2 --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/t850.yaml @@ -0,0 +1,120 @@ +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131022" + date: "20230914" + time: 12 + expver: "0001" + step: 120 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131022" + date: "20230914" + time: 12 + expver: "0001" + step: 168 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131023" + date: "20230914" + time: 12 + expver: "0001" + step: 120 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131023" + date: "20230914" + time: 12 + expver: "0001" + step: 168 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131020" + date: "20230914" + time: 12 + expver: "0001" + step: 120-168 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "131021" + date: "20230914" + time: 12 + expver: "0001" + step: 120-168 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "133093" + date: "20230914" + time: 12 + expver: "0001" + step: 120 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "133093" + date: "20230914" + time: 12 + expver: "0001" + step: 132 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "133093" + date: "20230914" + time: 12 + expver: "0001" + step: 168 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "133094" + date: "20230914" + time: 12 + expver: "0001" + step: 120 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "133094" + date: "20230914" + time: 12 + expver: "0001" + step: 132 +- class: od + stream: enfo + type: ep + levtype: sfc + domain: g + param: "133094" + date: "20230914" + time: 12 + expver: "0001" + step: 168 diff --git a/pproc-core/tests/ppcore/products/templates/thermo_ens.yaml b/pproc-core/tests/ppcore/products/templates/thermo_ens.yaml new file mode 100644 index 00000000..c16399cc --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/thermo_ens.yaml @@ -0,0 +1,23 @@ +- class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: [261002, 261001, 260004, 260005, 260255, 260242, 261016, 261018, 261015, 261014, 261023] + date: "20230914" + time: 12 + expver: "0001" + step: [3, 6] + sources: "fdb:" +- class: od + stream: enfo + type: pf + levtype: sfc + domain: g + param: [261002, 261001, 260004, 260005, 260255, 260242, 261016, 261018, 261015, 261014, 261023] + date: "20230914" + time: 12 + expver: "0001" + step: [3, 6] + sources: "fdb:" + number: [1, 2] diff --git a/pproc-core/tests/ppcore/products/templates/thermo_fc.yaml b/pproc-core/tests/ppcore/products/templates/thermo_fc.yaml new file mode 100644 index 00000000..28e6872a --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/thermo_fc.yaml @@ -0,0 +1,22 @@ +- class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: [261002, 261001, 260004, 260005, 260255, 260242, 261016, 261018, 261015, 261014, 261023] + date: "20230914" + time: 12 + expver: "0001" + step: [1, 2] + sources: "fdb:" +- class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: [260242, 261023, 261018, 260255, 260004, 260005, 261016] + date: "20230914" + time: 12 + expver: "0001" + step: 0 + sources: "fdb:" diff --git a/pproc-core/tests/ppcore/products/templates/wind.yaml b/pproc-core/tests/ppcore/products/templates/wind.yaml new file mode 100644 index 00000000..1ef6c3f8 --- /dev/null +++ b/pproc-core/tests/ppcore/products/templates/wind.yaml @@ -0,0 +1,34 @@ +- class: od + stream: enfo + type: [em, es] + levtype: sfc + domain: g + param: "10" + date: "20230914" + time: 12 + expver: "0001" + step: [0, 3, 6] + sources: "fdb:" +- class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: "10" + date: "20230914" + time: 12 + expver: "0001" + step: [0, 3, 6] + sources: "fdb:" +- class: od + stream: enfo + type: pf + number: [1, 2, 3, 4] + levtype: sfc + domain: g + param: "10" + date: "20230914" + time: 12 + expver: "0001" + step: [0, 3, 6] + sources: "fdb:" diff --git a/pproc-core/tests/ppcore/products/test_products.py b/pproc-core/tests/ppcore/products/test_products.py new file mode 100644 index 00000000..0f01f930 --- /dev/null +++ b/pproc-core/tests/ppcore/products/test_products.py @@ -0,0 +1,188 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os + +import pytest +import yaml + +from earthkit.workflows.graph import Graph +from earthkit.workflows.fluent import merge + +from earthkit.workflows.plugins.pproc.fluent import from_source +from earthkit.workflows.plugins.pproc.utils.request import Request +from ppcore.schema.forecast import definition_to_dataset, ForecastDefinition +from ppcore.products import product_from_output, graph_from_outputs, action_from_outputs +from ppcore.utils.requests import expand +from conftest import SCHEMA + + +ROOT_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__))) + + +INPUTS = { + "ensemble": [ + { + "stream": "oper", + "type": "fc", + "step": list(range(0, 24, 3)), + "param": [ + "228", + "47", + "165", + "166", + "167", + "168", + "169", + "175", + "176", + "177", + "228021", + "138", + "155", + ], + "levtype": "sfc", + }, + { + "stream": "enfo", + "type": "pf", + "step": list(range(0, 24, 3)), + "param": [ + "228", + "47", + "165", + "166", + "167", + "168", + "169", + "175", + "176", + "177", + "228021", + "138", + "155", + ], + "number": list(range(1, 5)), + "levtype": "sfc", + }, + { + "stream": "oper", + "type": "fc", + "step": list(range(0, 24, 3)), + "param": ["130"], + "levtype": "pl", + "levelist": [250, 500, 850], + }, + { + "stream": "enfo", + "type": "pf", + "step": list(range(0, 24, 3)), + "param": ["130"], + "levtype": "pl", + "levelist": [250, 500, 850], + "number": list(range(1, 5)), + }, + ], + "deterministic": [ + { + "stream": "oper", + "type": "fc", + "step": [0, 1, 2], + "param": [ + "47", + "165", + "166", + "167", + "168", + "169", + "175", + "176", + "177", + "228021", + ], + "levtype": "sfc", + }, + { + "stream": "oper", + "type": "fc", + "step": list(range(0, 24, 3)), + "param": ["130"], + "levtype": "pl", + "levelist": [250, 500, 850], + }, + ], +} + + +@pytest.mark.parametrize( + "filename", + ["ensms", "prob", "quantiles", "thermo_fc", "thermo_ens", "wind"], +) +def test_graph_construction(filename): + path = os.path.join(ROOT_DIR, "templates", f"{filename}.yaml") + with open(path, "r") as f: + output_requests = yaml.safe_load(f) + graph_from_outputs(output_requests, SCHEMA, forecast="enfo") + + +@pytest.mark.parametrize("filename", ["ensms", "quantiles", "thermo_ens", "wind"]) +def test_action_construction(filename): + # TODO: Enable prob when we can handle mixed step types in output requests + path = os.path.join(ROOT_DIR, "templates", f"{filename}.yaml") + with open(path, "r") as f: + output_requests = yaml.safe_load(f) + action_from_outputs(output_requests, SCHEMA, forecast="enfo") + + +@pytest.mark.parametrize( + "input_name, filename", + [ + ["ensemble", "ensms"], + ["ensemble", "quantiles"], + ["ensemble", "wind"], + ["deterministic", "thermo_fc"], + ["ensemble", "thermo_ens"], + ], + ids=["ensms", "quantiles", "wind", "thermo_fc", "thermo_ens"], +) +def test_custom_source(input_name, filename): + path = os.path.join(ROOT_DIR, "templates", f"{filename}.yaml") + with open(path, "r") as f: + output_requests = yaml.safe_load(f) + + graph = Graph([]) + defaults = {"class": "od", "date": "20230914", "time": "1200", "expver": "0001"} + for req in expand(output_requests): + inputs = [{**defaults, **inp} for inp in INPUTS[input_name]] + forecast = ForecastDefinition( + datacubes=inputs, unperturbed={"stream": "oper", "type": "fc"} + ) + product = product_from_output( + req, + SCHEMA, + forecast=forecast, + metadata={"edition": 2}, + ) + source_actions = [] + is_ensemble = definition_to_dataset(forecast).is_ensemble + for levtype in ["sfc", "pl"]: + for request in inputs: + if request["levtype"] != levtype: + continue + req = Request(request) + if is_ensemble and "number" not in req: + req.make_dim("number", 0) + new_action = from_source( + ["fdb"], + [req], + join_key="number" if is_ensemble else "", + ) + new_action = new_action.set_path(f"/levtype={levtype}/{req['param']}") + source_actions.append(new_action) + sources = merge(*source_actions) + new_action = product.action( + ensemble_dim="number", + forecast=sources, + ).write([{"name": "null"}]) + graph += new_action.graph() diff --git a/pproc-core/tests/ppcore/schema/test_config_schema.py b/pproc-core/tests/ppcore/schema/test_config_schema.py new file mode 100644 index 00000000..daece7a4 --- /dev/null +++ b/pproc-core/tests/ppcore/schema/test_config_schema.py @@ -0,0 +1,119 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import pytest +from conftest import schema + +from ppcore.schema.config import ConfigSchema + + +def test_reconstruct(): + config_schema = ConfigSchema(schema("config")) + cfgs = list(config_schema.reconstruct(entrypoint="pproc-ensms")) + assert len(cfgs) != 0 + for out, cfg in cfgs: + assert cfg["entrypoint"] == "pproc-ensms" + assert out["type"] in ["em", "es", "taem", "taes"] + assert len([x for x, _ in cfgs if x["type"] == "em"]) == len( + [x for x, _ in cfgs if x["type"] == "es"] + ) + + +def test_reconstruct_cache(): + config_schema = ConfigSchema( + schema("config"), + matching_cache_size=2, + ) + cfgs_a = list(config_schema.reconstruct(entrypoint="pproc-ensms")) + + cfgs_b = list(config_schema.reconstruct(entrypoint="pproc-ensms")) + assert cfgs_a == cfgs_b + assert len(config_schema._matching_cache) == 1 + + config_schema.clear_matching_cache() + assert len(config_schema._matching_cache) == 0 + + +def test_reconstruct_dfs(): + config_schema = ConfigSchema(schema("config")) + dfs_cfgs = list( + config_schema.reconstruct( + entrypoint="pproc-ensms", method="dfs", enable_cache=False + ) + ) + bfs_cfgs = list( + config_schema.reconstruct( + entrypoint="pproc-ensms", method="bfs", enable_cache=False + ) + ) + assert dfs_cfgs[0] == bfs_cfgs[0] + assert len(dfs_cfgs) == len(bfs_cfgs) + + +@pytest.mark.parametrize( + "out_request, expected_config", + [ + [ + { + "class": "od", + "stream": "enfo", + "date": "20250101", + "time": "00", + "type": "sot", + "number": 90, + "param": "132167", + "step": "0-24", + "levtype": "sfc", + }, + {"sot": [90]}, + ], + [ + { + "class": "od", + "stream": "enfo", + "date": "20250101", + "time": "00", + "type": "sot", + "number": [10, 90], + "param": "132167", + "step": "0-24", + "levtype": "sfc", + }, + {"sot": [10, 90]}, + ], + [ + { + "class": "od", + "stream": "enfo", + "date": "20250101", + "time": "00", + "type": "pb", + "quantile": "1:100", + "param": "167", + "step": "0-24", + "levtype": "sfc", + }, + {"quantiles": [0.01]}, + ], + [ + { + "class": "od", + "stream": "enfo", + "date": "20250101", + "time": "00", + "type": "pb", + "quantile": ["1:100", "2:100"], + "param": "167", + "step": "0-24", + "levtype": "sfc", + }, + {"quantiles": [0.01, 0.02]}, + ], + ], +) +def test_config_from_output(out_request, expected_config): + config_schema = ConfigSchema(schema("config")) + config = config_schema.config(out_request) + for key, value in expected_config.items(): + assert config[key] == value diff --git a/pproc-core/tests/ppcore/schema/test_deriver.py b/pproc-core/tests/ppcore/schema/test_deriver.py new file mode 100644 index 00000000..14fc1eb1 --- /dev/null +++ b/pproc-core/tests/ppcore/schema/test_deriver.py @@ -0,0 +1,301 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import pytest +from pydantic import TypeAdapter + +from ppcore.schema.forecast import Dataset, Climatology +from ppcore.schema.deriver import ClimDateDeriver, ClimatologyDeriver, ForecastDeriver + +FcDeriver = TypeAdapter(ForecastDeriver) +ClimDeriver = TypeAdapter(ClimatologyDeriver) + + +@pytest.mark.parametrize( + "config, output_request, fc_steps, expected", + [ + pytest.param({"name": "step_default"}, {"step": 6}, [0, 6, 12], [6], id="inst"), + pytest.param( + {"name": "step_default"}, {"step": "0-6"}, [0, 3, 6, 12], [3, 6], id="range" + ), + pytest.param( + {"name": "step_default", "include_start": True}, + {"step": "0-6"}, + [0, 3, 6, 12], + [0, 3, 6], + id="range-with-start", + ), + pytest.param( + {"name": "step_default", "include_start": True, "allow_missing_zero": True}, + {"step": "0-6"}, + [0, 3, 6, 12], + [0, 3, 6], + id="range-allow-missing", + ), + pytest.param( + {"name": "step_default", "include_start": True, "allow_missing_zero": True}, + {"step": "0-6"}, + [3, 6, 12], + [3, 6], + id="range-missing-zero", + ), + pytest.param( + {"name": "step_default", "by": 6}, + {"step": "0-6"}, + [0, 3, 6, 12], + [6], + id="range-with-by", + ), + pytest.param( + {"name": "step_deaccumulate"}, + {"step": "0-6"}, + [0, 6, 9, 12], + [0, 6], + id="deacc-range", + ), + pytest.param( + {"name": "step_deaccumulate", "allow_missing_zero": True}, + {"step": "0-6"}, + [6, 9, 12], + [6], + id="deacc-missing-zero", + ), + pytest.param( + {"name": "step_deaccumulate"}, + {"step": 6}, + [0, 6, 9, 12], + [0, 6], + id="deacc-inst", + ), + pytest.param( + {"name": "step_deaccumulate", "allow_missing_zero": True}, + {"step": 6}, + [6, 9, 12], + [6], + id="deacc-inst-missing-zero", + ), + pytest.param( + {"name": "step_deaccumulate", "by": 12}, + {"step": 12}, + [0, 6, 9, 12], + [0, 12], + id="deacc-inst-by", + ), + pytest.param( + {"name": "step_deaccumulate", "by": 24, "allow_missing_zero": True}, + {"step": "0-12"}, + [12, 18, 24], + [24], + id="deacc-range-by", + ), + pytest.param( + {"name": "step_precomputed"}, + {"step": "0-12"}, + [6, 9, 12], + ["0-12"], + id="precomputed", + ), + pytest.param( + {"name": "step_monthly"}, + {"fcmonth": 1, "date": "20250601"}, + list(range(0, 745, 6)), + list(range(6, 721, 6)), + id="monthly", + ), + pytest.param( + {"name": "step_monthly", "include_start": True}, + {"fcmonth": 1, "date": "20250601"}, + list(range(0, 745, 6)), + list(range(0, 721, 6)), + id="monthly-with-start", + ), + pytest.param( + { + "name": "step_monthly", + "include_start": True, + "allow_missing_zero": True, + "by": 24, + }, + {"fcmonth": 1, "date": "20250601"}, + list(range(6, 745, 6)), + list(range(24, 721, 24)), + id="monthly-missing-zero", + ), + pytest.param( + {"name": "step_select", "index": 1}, + {"step": "0-24"}, + [0, 12, 24], + [24], + id="select", + ), + pytest.param( + {"name": "step_select", "index": 0, "include_start": True}, + {"step": "0-24"}, + [0, 12, 24], + [0], + id="select-with-start", + ), + pytest.param( + { + "name": "step_select", + "index": 0, + "include_start": True, + "allow_missing_zero": True, + }, + {"step": "0-24"}, + [12, 24], + [12], + id="select-missing-zero", + ), + pytest.param( + {"name": "step_static", "values": [0, 12]}, + {"step": "0-24"}, + [0, 12, 24], + [0, 12], + id="static", + ), + ], +) +def test_forecast_step_deriver(config, output_request, fc_steps, expected): + deriver = FcDeriver.validate_python(config) + assert expected == deriver.derive( + output_request, Dataset(datacubes=[{"step": fc_steps}]) + ) + + +@pytest.mark.parametrize( + "step_type, times, step, clim_steps, expected", + [ + [ + "clim_step_inst", + ["0000"], + [0, 6, 12, 18, 24, 354, 360], + list(range(0, 361, 6)), + [0, 6, 12, 18, 24, 354, 360], + ], + [ + "clim_step_inst", + ["0600"], + [0, 6, 12, 18, 24, 138], + list(range(0, 361, 6)), + [6, 12, 18, 24, 30, 144], + ], + [ + "clim_step_inst", + ["1200"], + [0, 6, 12, 18, 24, 354, 360], + list(range(0, 361, 6)), + [12, 18, 24, 30, 36, 342, 348], + ], + [ + "clim_step_inst", + ["1800"], + [0, 6, 12, 18, 24, 138], + list(range(0, 361, 6)), + [18, 24, 30, 36, 42, 156], + ], + [ + "clim_step_range", + ["0000", "0600"], + list(range(0, 25, 12)), + ["0-24", "12-36", "24-28", "0-240"], + "0-24", + ], + [ + "clim_step_range", + ["0000", "0600"], + list(range(0, 241, 12)), + ["0-24", "12-36", "24-28", "0-240"], + "0-240", + ], + [ + "clim_step_range", + ["0000", "0600"], + list(range(12, 25, 12)), + ["0-24", "12-36", "24-28", "0-240"], + "0-24", + ], + [ + "clim_step_range", + ["0000", "0600"], + [24], + ["0-24", "12-36", "24-28", "0-240"], + "0-24", + ], + [ + "clim_step_range", + ["1200", "1800"], + list(range(0, 25, 12)), + ["0-24", "12-36", "24-28", "0-240"], + "12-36", + ], + [ + "clim_step_range", + ["1200", "1800"], + list(range(0, 241, 12)), + ["0-24", "12-36", "24-28", "0-240"], + "0-240", + ], + [ + "clim_step_range", + ["1200", "1800"], + list(range(12, 25, 12)), + ["0-24", "12-36", "24-28", "0-240"], + "12-36", + ], + [ + "clim_step_range", + ["1200", "1800"], + [240], + ["0-24", "12-36", "24-28", "0-240"], + "0-240", + ], + [ + "clim_step_range", + ["0000"], + ["0-168"], + ["0-168", "24-192", "48-216"], + "0-168", + ], + [ + "clim_step_range", + ["0000"], + ["24-192"], + ["0-168", "24-192", "48-216"], + "24-192", + ], + ], +) +def test_clim_step_deriver(step_type, times, step, clim_steps, expected): + deriver = ClimDeriver.validate_python({"name": step_type}) # type: ignore + for time in times: + assert ( + deriver.derive( + {"time": time, "step": step}, + Climatology(datacubes=[{"step": clim_steps}], scheme="ecmwf-4days"), + ) + == expected + ) + + +@pytest.mark.parametrize( + "config, date, expected", + [ + [{"option": "next", "sequence": {"type": "daily"}}, "20250930", "20251001"], + [{"option": "previous", "strict": False}, "20250930", "20250929"], + [{"option": "previous"}, "20250929", "20250927"], + [{"option": "nearest"}, "20250930", "20250929"], + [ + {"option": "bracket", "num": 1, "strict": False}, + "20250930", + ["20250929", "20251001"], + ], + ], +) +def test_clim_date_deriver(config, date, expected): + deriver = ClimDateDeriver(**config) + assert ( + deriver.derive({"date": date}, Climatology(datacubes=[], scheme="ecmwf-2days")) + == expected + ) diff --git a/pproc-core/tests/ppcore/schema/test_input_schema.py b/pproc-core/tests/ppcore/schema/test_input_schema.py new file mode 100644 index 00000000..53dc14a3 --- /dev/null +++ b/pproc-core/tests/ppcore/schema/test_input_schema.py @@ -0,0 +1,662 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import pytest +from conftest import schema + +from ppcore.schema.input import InputSchema +from ppcore.schema.step import StepSchema +from ppcore.schema.forecast import ( + ForecastDefinition, + ClimatologyDefinition, + DatasetDefinitions, + definition_to_dataset, +) +from ppcore.schema.schema import Schema +from ppcore.utils.requests import update_request +from ppcore.utils.mars import extract_mars +from ppcore.utils.qube import qube_from_datacubes + +INPUTS = { + "ensms": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "levtype": "sfc", + "param": "167", + "step": 3, + "type": "fc", + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "levtype": "sfc", + "param": "167", + "step": 3, + "type": "pf", + "number": list(range(1, 51)), + "time": "0000", + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + None, + ], + "thermofeel": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "levtype": "sfc", + "param": ["169", "175", "176", "177", "228021", "47"], + "step": [2, 3], + "type": "fc", + "time": "0000", + }, + { + "class": "od", + "stream": "oper", + "levtype": "sfc", + "param": ["165", "166", "167", "168"], + "step": 3, + "type": "fc", + "time": "0000", + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + None, + ], + "thermo_pf": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "enfo", + "levtype": "sfc", + "param": ["169", "175", "176", "177", "228021", "47"], + "step": [2, 3], + "type": "pf", + "time": "0000", + "number": [1, 2, 3], + }, + { + "class": "od", + "stream": "enfo", + "levtype": "sfc", + "param": ["165", "166", "167", "168"], + "step": 3, + "type": "pf", + "time": "0000", + "number": [1, 2, 3], + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + None, + ], + "t850": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "param": "130", + "step": list(range(120, 169, 6)), + "type": "fc", + "date": "20250314", + "time": "1200", + "levtype": "pl", + "levelist": 250, + }, + { + "class": "od", + "stream": "enfo", + "param": "130", + "step": list(range(120, 169, 6)), + "type": "pf", + "number": list(range(1, 51)), + "date": "20250314", + "time": "1200", + "levtype": "pl", + "levelist": 250, + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + ClimatologyDefinition( + datacubes=[ + { + "class": "od", + "stream": "efhs", + "param": "130", + "step": list(range(132, 181, 6)), + "type": "em", + "date": "20250313", + "time": "0000", + "levtype": "pl", + "levelist": 250, + }, + { + "class": "od", + "stream": "efhs", + "param": "130", + "step": list(range(132, 181, 6)), + "type": "es", + "date": "20250313", + "time": "0000", + "levtype": "pl", + "levelist": 250, + }, + ], + scheme="ecmwf-4days", + ), + ], + "efi": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "eefo", + "levtype": "sfc", + "param": "167", + "step": "0-168", + "type": "fcmean", + "date": "20250315", + "number": list(range(0, 101)), + "time": "0000", + }, + ], + unperturbed={"stream": "eefo", "type": "cf"}, + ), + ClimatologyDefinition( + datacubes=[ + { + "class": "od", + "stream": "eehs", + "levtype": "sfc", + "param": "228004", + "step": "0-168", + "type": "cd", + "date": "20250315", + "time": "0000", + "quantile": [f"{x}:100" for x in range(0, 101)], + }, + ], + scheme="ecmwf-2days", + ), + ], + "monthly": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "mmsf", + "levtype": "sfc", + "param": ["165", "166"], + "step": list(range(6, 745, 6)), + "type": "fc", + "number": list(range(0, 51)), + "date": "20241001", + "time": "0000", + }, + ], + ), + None, + ], + "prob": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "levtype": "sfc", + "param": "228", + "step": [0, 24], + "type": "fc", + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "levtype": "sfc", + "param": "228", + "step": [0, 24], + "type": "pf", + "number": list(range(1, 51)), + "time": "0000", + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + None, + ], + "sfc-pl": [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "levtype": "pl", + "levelist": [250, 850], + "param": "130", + "step": 6, + "type": "fc", + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "levtype": "pl", + "levelist": [250, 850], + "param": "130", + "step": 6, + "type": "pf", + "number": list(range(1, 51)), + "time": "0000", + }, + { + "class": "od", + "stream": "oper", + "levtype": "sfc", + "param": "167", + "step": 6, + "type": "fc", + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "levtype": "sfc", + "param": "167", + "step": 6, + "type": "pf", + "number": list(range(1, 51)), + "time": "0000", + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + None, + ], +} + + +@pytest.mark.parametrize( + "output", + [ + { + "class": "od", + "stream": "enfo", + "type": "em", + "time": "0000", + "param": "167", + "step": 3, + "levtype": "sfc", + }, + { + "class": "od", + "stream": "oper", + "type": "fc", + "param": "261001", + "step": 3, + "levtype": "sfc", + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "type": "pf", + "param": "261001", + "step": 3, + "levtype": "sfc", + "time": "0000", + "number": [1, 2, 3], + }, + { + "class": "od", + "stream": "enfo", + "type": "ep", + "param": "131020", + "step": "120-168", + "date": "20250314", + "time": "1200", + "levtype": "pl", + "levelist": 250, + "selection": "default", + }, + { + "class": "od", + "stream": "eefo", + "levtype": "sfc", + "type": "efi", + "param": "132167", + "step": "0-168", + "date": "20250315", + "time": "0000", + }, + { + "class": "od", + "stream": "msmm", + "levtype": "sfc", + "type": "fcmean", + "param": "207", + "fcmonth": 1, + "date": "20241001", + "number": list(range(0, 51)), + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "levtype": "sfc", + "type": "ep", + "param": "131060", + "step": "0-24", + "time": "0000", + "selection": "default", + }, + ], + ids=["ensms", "thermofeel", "thermo_pf", "t850", "efi", "monthly", "prob"], +) +def test_inputs(request, output): + forecast, climatology = INPUTS[request.node.callspec.id] + input_schema = InputSchema(schema("inputs")) + step_schema = StepSchema(schema("windows")) + all_inputs = list(input_schema.inputs(output, forecast, climatology)) + for dataset, clim in [(forecast, False), (climatology, True)]: + if dataset is None: + continue + generated_inputs = list( + qube_from_datacubes( + [ + extract_mars(x) + for x in all_inputs + if x.get("climatology", False) == clim + ] + ).datacubes() + ) + expected_inputs = list(definition_to_dataset(dataset).qube.datacubes()) + assert expected_inputs == generated_inputs + + generated = list( + input_schema.outputs( + forecast, climatology, step_schema=step_schema, output_template=output + ) + ) + assert len(generated) == 1 + assert generated[0][0] == extract_mars(output) + for dataset, clim in [(forecast, False), (climatology, True)]: + if dataset is None: + continue + generated_inputs = list( + qube_from_datacubes( + [ + extract_mars(x) + for x in generated[0][1] + if x.get("climatology", False) == clim + ] + ).datacubes() + ) + expected_inputs = list(definition_to_dataset(dataset).qube.datacubes()) + assert expected_inputs == generated_inputs + + +@pytest.mark.parametrize( + "template, num_outputs", + [ + [{"stream": "enfo", "type": ["em", "es"]}, 2], + [ + { + "stream": "oper", + "type": "fc", + "param": [ + 261002, + 261001, + 260004, + 260005, + 260255, + 260242, + 261016, + 261018, + 261015, + 261014, + 261023, + 207, + ], + }, + 12, + ], + [{"stream": "enfo", "type": "ep", "selection": "default"}, 52], + [{"stream": "eefo", "type": "efi"}, 1], + [{"stream": "msmm", "type": ["fcmean", "fcmax"]}, 3], + [{"stream": "enfo", "type": "ep", "selection": "default"}, 7], + ], + ids=["ensms", "thermofeel", "t850", "efi", "monthly", "prob"], +) +def test_outputs(request, template, num_outputs): + test_schema = Schema(**schema()) + forecast, climatology = INPUTS[request.node.callspec.id] + generated = list( + test_schema.outputs_from_inputs(forecast, climatology, output_template=template) + ) + assert len(generated) == num_outputs + + +def test_input_format(): + input_schema = InputSchema(schema("inputs")) + step_schema = StepSchema(schema("windows")) + dataset, _ = INPUTS["sfc-pl"] + generated = list( + input_schema.outputs( + dataset, + step_schema=step_schema, + output_template={"stream": "enfo", "type": "em"}, + enable_cache=False, + ) + ) + expected_outputs = [ + { + "class": "od", + "stream": "enfo", + "levtype": "pl", + "levelist": [250, 850], + "param": "130", + "step": 6, + "type": "em", + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "levtype": "sfc", + "param": "167", + "step": 6, + "type": "em", + "time": "0000", + }, + ] + for out, inputs in generated: + assert out in expected_outputs + for inp in inputs: + selection, _ = definition_to_dataset(dataset).select(inp) + assert selection.n_leaves > 0 + + +@pytest.mark.parametrize( + "inputs, template, num_outputs", + [ + [INPUTS["t850"][0], {"stream": "enfo", "type": "em", "step": 120}, 1], + [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "param": [ + "165", + "166", + "167", + "168", + "169", + "175", + "176", + "177", + "228021", + "47", + "228", + ], + "step": [2, 3], + "type": "fc", + "levtype": "sfc", + "time": "0000", + } + ], + ), + {"stream": "oper", "type": "fc"}, + 20, + ], + [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "levtype": "sfc", + "param": [ + "165", + "166", + "167", + "168", + "169", + "175", + "176", + "177", + ], + "step": [0, 1], + "type": "fc", + "time": "0000", + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + {"stream": "oper", "type": "fc", "step": 1}, + 8, + ], + [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "param": ["228246", "228247"], + "type": "fc", + "levtype": "sfc", + "time": "0000", + "step": 3, + } + ], + ), + {"stream": "oper", "type": "fc"}, + 0, + ], + [ + ForecastDefinition( + datacubes=[ + { + "class": "od", + "stream": "oper", + "param": "129", + "type": "fc", + "levtype": "sfc", + "step": 3, + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "param": "129", + "type": "pf", + "levtype": "sfc", + "number": list(range(1, 51)), + "step": 3, + "time": "0000", + }, + { + "class": "od", + "stream": "oper", + "param": "129", + "type": "fc", + "levtype": "pl", + "levelist": [50, 100], + "step": 3, + "time": "0000", + }, + { + "class": "od", + "stream": "enfo", + "param": "129", + "type": "pf", + "levtype": "pl", + "number": list(range(1, 51)), + "levelist": [50, 100], + "step": 3, + "time": "0000", + }, + ], + unperturbed={"stream": "oper", "type": "fc"}, + ), + {"stream": "enfo", "levtype": "pl", "levelist": 50, "type": "em"}, + 1, + ], + ], + ids=[ + "redundant-steps", + "redundant-params", + "insufficient-params", + "not-from-inputs", + "levels", + ], +) +def test_non_exact_inputs(inputs, template, num_outputs): + input_schema = InputSchema(schema("inputs")) + step_schema = StepSchema(schema("windows")) + generated = list( + input_schema.outputs(inputs, step_schema=step_schema, output_template=template) + ) + assert len(generated) == num_outputs + + +@pytest.mark.parametrize( + "number, updates", + [ + [0, {"type": "cf"}], + [[0, 1], [{"type": "cf"}, {"type": "pf", "number": 1}]], + [[1, 2], {"type": "pf", "number": [1, 2]}], + ], + ids=["cf", "cf-and-pf", "pf"], +) +def test_fcstat_inputs(number, updates): + input_schema = InputSchema(schema("inputs")) + datasets = DatasetDefinitions(definitions=schema("datasets")) + output = { + "class": "od", + "stream": "eefo", + "type": "fcmean", + "number": number, + "param": "167", + "step": "0-168", + "time": "0000", + "levtype": "sfc", + "domain": "g", + } + inputs = input_schema.inputs(output, datasets.definition("eefo")) # type: ignore + base_input = output.copy() + base_input.pop("number") + expected = update_request({**base_input, "step": list(range(6, 169, 6))}, updates) + assert list(inputs) == expected diff --git a/pproc-core/tests/ppcore/schema/test_schema.py b/pproc-core/tests/ppcore/schema/test_schema.py new file mode 100644 index 00000000..4e4c9df1 --- /dev/null +++ b/pproc-core/tests/ppcore/schema/test_schema.py @@ -0,0 +1,487 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + + +import pytest +from conftest import schema + +from ppcore.schema.forecast import ForecastDefinition +from ppcore.schema.schema import Schema + + +@pytest.mark.parametrize( + "req, dataset, config, num_generated", + [ + [ + { + "class": "od", + "stream": "msmm", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": 167, + "date": "20241001", + "time": "0", + "fcmonth": 1, + "type": "fcmean", + "number": 0, + }, + "seasonal", + { + "entrypoint": "pproc-monthly-stats", + "name": "167_sfc", + "interp_keys": { + "intgrid": "none", + "legendre-loader": "shmem", + "matrix-loader": "file-io", + }, + "dtype": "float64", + "inputs": [ + { + "class": "od", + "stream": "mmsf", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": "167", + "date": "20241001", + "time": "0000", + "type": "fc", + "step": list(range(6, 745, 6)), + "number": 0, + }, + ], + "accumulations": { + "step": { + "type": "legacywindow", + "operation": "mean", + "metadata": {"type": "fcmean", "bitsPerValue": 16}, + "name": { + "type": "monthly", + "date": "20241001", + }, + } + }, + }, + 1, + ], + [ + { + "class": "od", + "stream": "eefo", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": 172228, + "date": "20241001", + "time": "00", + "step": "0-168", + "type": "fcmean", + "number": [0, 1, 2, 3], + }, + "eefo", + { + "entrypoint": "pproc-accumulate", + "name": "228_sfc", + "interp_keys": { + "intgrid": "none", + "legendre-loader": "shmem", + "matrix-loader": "file-io", + }, + "dtype": "float64", + "accumulations": { + "step": { + "type": "legacywindow", + "operation": "mean", + "deaccumulate": True, + "metadata": { + "type": "fcmean", + "bitsPerValue": 16, + "legBaseDate": 0, + "legNumber": 0, + "numberIncludedInAverage": "{num_coords}:int", + "stepType": "avg", + "timeRangeIndicator": 3, + }, + "name": { + "type": "default", + "length": 168, + }, + } + }, + "vmin": 0.0, + "preprocessing": [ + { + "operation": "scale", + "value": 0.00001157407, + } + ], + "inputs": [ + { + "class": "od", + "stream": "eefo", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": "228", + "date": "20241001", + "time": "0000", + "type": "cf", + "step": list(range(0, 169, 24)), + }, + { + "class": "od", + "stream": "eefo", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": "228", + "date": "20241001", + "time": "0000", + "type": "pf", + "step": list(range(0, 169, 24)), + "number": list(range(1, 4)), + }, + ], + }, + 2, + ], + [ + { + "class": "od", + "stream": "enfo", + "expver": "0001", + "levtype": "pl", + "levelist": [250, 850], + "domain": "g", + "param": "130", + "date": "20241001", + "time": "00", + "step": 12, + "type": "em", + "target_grid": "O640", + }, + "enfo", + { + "entrypoint": "pproc-ensms", + "name": "130_pl", + "interp_keys": { + "intgrid": "none", + "legendre-loader": "shmem", + "matrix-loader": "file-io", + }, + "input": { + "dtype": "float64", + }, + "statistics": { + "metadata": { + "bitsPerValue": 16, + "legBaseDate": 20241001, + "legBaseTime": 0, + "legNumber": 1, + "localDefinitionNumber": 30, + "numberOfForecastsInEnsemble": "{num_fields}:int", + "oceanAtmosphereCoupling": 2, + "perturbationNumber": 0, + }, + "operation": "mean", + }, + "inputs": [ + { + "class": "od", + "stream": "oper", + "expver": "0001", + "levtype": "pl", + "domain": "g", + "param": "130", + "date": "20241001", + "time": "0000", + "type": "fc", + "levelist": [250, 850], + "step": 12, + "target_grid": "O640", + }, + { + "class": "od", + "stream": "enfo", + "expver": "0001", + "levtype": "pl", + "domain": "g", + "param": "130", + "date": "20241001", + "time": "0000", + "type": "pf", + "levelist": [250, 850], + "step": 12, + "number": list(range(1, 51)), + "target_grid": "O640", + }, + ], + }, + 1, + ], + ], + ids=["2t", "tp", "T"], +) +def test_schema_from_output(req, dataset, config, num_generated): + test_schema = Schema(**schema()) + test_config = test_schema.config_from_output(req, test_schema.definition(dataset)) # type: ignore + test_config.pop("metadata", None) + assert config == test_config + + generated = test_schema.config_from_input( + ForecastDefinition( + datacubes=config["inputs"], + unperturbed={x: config["inputs"][0][x] for x in ["stream", "type"]}, + ), + output_template={x: req[x] for x in ["stream", "type"]}, # type: ignore + ) + assert len(list(generated)) == num_generated + + +@pytest.mark.parametrize( + "inputs, out_template, num_expected, expected", + [ + [ + [ + { + "class": "od", + "stream": "oper", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": "167", + "date": "20241001", + "time": "0", + "step": list(range(0, 169, 6)), + "type": "fc", + }, + { + "class": "od", + "stream": "enfo", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": "167", + "date": "20241001", + "time": "0", + "step": list(range(0, 169, 6)), + "type": "pf", + "number": list(range(1, 11)), + }, + ], + {"stream": "enfo", "type": "fcmean"}, + 2, + { + "entrypoint": "pproc-accumulate", + "name": "167_sfc", + "inputs": [ + { + "class": "od", + "stream": "oper", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": "167", + "date": "20241001", + "time": "0000", + "type": "fc", + "step": list(range(6, 169, 6)), + } + ], + "accumulations": { + "step": { + "type": "legacywindow", + "operation": "mean", + "metadata": { + "type": "fcmean", + "bitsPerValue": 16, + "legBaseDate": 0, + "legNumber": 0, + "numberIncludedInAverage": "{num_coords}:int", + "stepType": "avg", + "timeRangeIndicator": 3, + }, + "name": { + "type": "default", + "length": 168, + }, + } + }, + "interp_keys": { + "intgrid": "none", + "legendre-loader": "shmem", + "matrix-loader": "file-io", + }, + "dtype": "float64", + }, + ], + [ + [ + { + "class": "od", + "stream": "mmsf", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": 228, + "date": "20241001", + "time": "00", + "step": list(range(0, 5161, 6)), + "number": list(range(1, 21)), + "type": "fc", + } + ], + {"stream": "msmm", "type": "fcmean"}, + 7, + { + "entrypoint": "pproc-monthly-stats", + "name": "228_sfc", + "accumulations": { + "step": { + "type": "legacywindow", + "operation": "mean", + "deaccumulate": True, + "metadata": { + "type": "fcmean", + "bitsPerValue": 16, + }, + "name": { + "type": "monthly", + "date": "20241001", + }, + } + }, + "vmin": 0.0, + "dtype": "float64", + "preprocessing": [ + { + "operation": "scale", + "value": 0.00001157407, + } + ], + "inputs": [ + { + "class": "od", + "stream": "mmsf", + "expver": "0001", + "levtype": "sfc", + "domain": "g", + "param": "228", + "date": "20241001", + "time": "0000", + "type": "fc", + "step": list(range(0, 745, 24)), + "number": list(range(1, 21)), + } + ], + "interp_keys": { + "intgrid": "none", + "legendre-loader": "shmem", + "matrix-loader": "file-io", + }, + }, + ], + [ + [ + { + "class": "od", + "stream": "oper", + "expver": "0001", + "levtype": "pl", + "levelist": [250, 850], + "domain": "g", + "param": "130", + "date": "20241001", + "time": "0", + "step": [0, 6, 12, 18, 24], + "type": "fc", + }, + { + "class": "od", + "stream": "enfo", + "expver": "0001", + "levtype": "pl", + "levelist": [250, 850], + "domain": "g", + "param": "130", + "date": "20241001", + "time": "0", + "step": [0, 6, 12, 18, 24], + "type": "pf", + "number": list(range(1, 51)), + }, + ], + {"stream": "enfo", "type": ["em", "es"]}, + 10, + { + "entrypoint": "pproc-ensms", + "name": "130_pl", + "inputs": [ + { + "class": "od", + "stream": "oper", + "expver": "0001", + "levtype": "pl", + "levelist": [250, 850], + "domain": "g", + "param": "130", + "date": "20241001", + "time": "0000", + "type": "fc", + "step": 0, + }, + { + "class": "od", + "stream": "enfo", + "expver": "0001", + "levtype": "pl", + "levelist": [250, 850], + "domain": "g", + "param": "130", + "date": "20241001", + "time": "0000", + "type": "pf", + "step": 0, + "number": list(range(1, 51)), + }, + ], + "interp_keys": { + "intgrid": "none", + "legendre-loader": "shmem", + "matrix-loader": "file-io", + }, + "input": { + "dtype": "float64", + }, + "statistics": { + "metadata": { + "bitsPerValue": 16, + "legBaseDate": 20241001, + "legBaseTime": 0, + "legNumber": 1, + "localDefinitionNumber": 30, + "numberOfForecastsInEnsemble": "{num_fields}:int", + "oceanAtmosphereCoupling": 2, + "perturbationNumber": 0, + }, + "operation": "mean", + }, + }, + ], + ], + ids=["2t", "tp", "T"], +) +def test_schema_from_input(inputs, out_template, num_expected, expected): + test_schema = Schema(**schema()) + forecast = ForecastDefinition( + datacubes=inputs, unperturbed={x: inputs[0][x] for x in ["stream", "type"]} + ) + configs = list( + test_schema.config_from_input(forecast, output_template=out_template) + ) + assert len(configs) == num_expected + test_config = configs[0] + test_config.pop("metadata", None) + assert test_config == expected diff --git a/pproc-core/tests/ppcore/schema/test_step_schema.py b/pproc-core/tests/ppcore/schema/test_step_schema.py new file mode 100644 index 00000000..5752d564 --- /dev/null +++ b/pproc-core/tests/ppcore/schema/test_step_schema.py @@ -0,0 +1,128 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import pytest +from conftest import schema + +from ppcore.schema.exceptions import PProcStepSchemaError +from ppcore.schema.step import StepSchema +from ppcore.schema.step import StepType +from ppcore.schema.forecast import DatasetDefinitions, definition_to_dataset + + +@pytest.mark.parametrize( + "config, steps, expected", + [ + [{"type": "instantaneous"}, [0, 1, 2], [0, 1, 2]], + [{"type": "instantaneous", "deaccumulate": True}, [0, 1, 2], [1, 2]], + [{"type": "instantaneous", "start": 1, "end": 2}, [0, 1, 2, 3], [1, 2]], + [{"type": "instantaneous", "interval": 2}, [0, 1, 2, 3, 4], [0, 2, 4]], + [{"type": "instantaneous", "start": 3, "end": 6}, [0, 1, 2], []], + [ + {"type": "range", "interval": 3, "width": 6}, + list(range(0, 10)), + ["0-6", "3-9"], + ], + [ + {"type": "range", "interval": 1, "width": 1}, + list(range(0, 5)), + ["0-1", "1-2", "2-3", "3-4"], + ], + [ + {"type": "range", "start": 2, "end": 8, "interval": 2, "width": 2}, + list(range(0, 7)), + ["2-4", "4-6"], + ], + [ + {"type": "range", "start": 12, "end": 24, "interval": 2, "width": 4}, + list(range(0, 10)), + [], + ], + [{"type": "monthly", "date": "20240601"}, list(range(0, 800)), [1]], + [{"type": "monthly", "date": "20240601"}, list(range(0, 500)), []], + [{"type": "monthly", "date": "20240601"}, [0], []], + ], +) +def test_step_type(config, steps, expected): + step_type = StepType(**config).root + assert step_type.generate_steps(steps) == expected + + +@pytest.mark.parametrize( + "out, dataset, expected, in_steps", + [ + [ + {"stream": "enfo", "type": "em", "param": "167", "time": "0000"}, + "enfo", + list(range(0, 145, 3)) + list(range(150, 361, 6)), + None, + ], + [ + {"stream": "enfo", "type": "em", "param": "167", "time": "0000"}, + "enfo", + list(range(0, 361, 12)), + list(range(0, 361, 12)), + ], + [ + {"stream": "enfo", "type": "cf", "param": "261001", "time": "0000"}, + "enfo", + list(range(1, 91)) + list(range(93, 145, 3)) + list(range(150, 361, 6)), + None, + ], + [ + {"stream": "eefo", "type": "fcmean", "param": "167", "time": "0000"}, + "eefo", + [f"{x}-{x+168}" for x in list(range(0, 1104 - 168 + 1, 24))], + None, + ], + [ + { + "stream": "msmm", + "type": "fcmean", + "param": "167", + "date": "20241001", + "time": "0000", + }, + "seasonal", + list(range(1, 8)), + None, + ], + [ + {"stream": "enfo", "type": "ep", "param": "131064", "time": "0000"}, + "enfo", + ["120-240", "240-360", "120-168", "168-240"], + None, + ], + [ + {"stream": "oper", "type": "fc", "param": "207", "time": "0000"}, + "enfo", + list(range(1, 91)), + list(range(1, 91)), + ], + ], + ids=[ + "ensms_default", + "ensms_insteps", + "deaccumulate", + "weekly", + "monthly", + "prob", + "fc", + ], +) +def test_out_steps(out, dataset, expected, in_steps): + datasets = DatasetDefinitions(definitions=schema("datasets")) + test_schema = StepSchema(schema("windows")) + if in_steps is None: + in_steps = definition_to_dataset(datasets.definition(dataset)).steps(out) + _, out_steps = test_schema.out_steps(out, in_steps) + assert out_steps == expected + + +def test_exception(): + step_schema = StepSchema(schema("windows")) + with pytest.raises(PProcStepSchemaError, match="type=ep,stream=enfo"): + step_schema.traverse( + {"type": "ep", "stream": "enfo", "param": "unknown", "time": "0000"} + ) diff --git a/pproc-core/tests/ppcore/utils/test_dicts.py b/pproc-core/tests/ppcore/utils/test_dicts.py new file mode 100644 index 00000000..81328a49 --- /dev/null +++ b/pproc-core/tests/ppcore/utils/test_dicts.py @@ -0,0 +1,29 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from ppcore.utils.dicts import dict_product + + +def test_dictprod(): + assert list(dict_product({})) == [{}] + + assert list(dict_product({"x": range(3), "empty": []})) == [] + + assert list(dict_product({"foo": [1, 2, 3]})) == [{"foo": n} for n in [1, 2, 3]] + + dic = {"a": [5, 12], "b": range(3), "c": ("a", "b")} + assert list(dict_product(dic)) == [ + {"a": 5, "b": 0, "c": "a"}, + {"a": 5, "b": 0, "c": "b"}, + {"a": 5, "b": 1, "c": "a"}, + {"a": 5, "b": 1, "c": "b"}, + {"a": 5, "b": 2, "c": "a"}, + {"a": 5, "b": 2, "c": "b"}, + {"a": 12, "b": 0, "c": "a"}, + {"a": 12, "b": 0, "c": "b"}, + {"a": 12, "b": 1, "c": "a"}, + {"a": 12, "b": 1, "c": "b"}, + {"a": 12, "b": 2, "c": "a"}, + {"a": 12, "b": 2, "c": "b"}, + ] diff --git a/pproc-core/tests/ppcore/utils/test_mars.py b/pproc-core/tests/ppcore/utils/test_mars.py new file mode 100644 index 00000000..25a5ba9f --- /dev/null +++ b/pproc-core/tests/ppcore/utils/test_mars.py @@ -0,0 +1,46 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from datetime import date, datetime + +import pytest + +from ppcore.utils import mars + + +@pytest.mark.parametrize( + "val, expected", + [ + pytest.param("abc", b"abc", id="str"), + pytest.param(b"def", b"def", id="bytes"), + pytest.param(123, b"123", id="int"), + pytest.param(date(2021, 12, 13), b"20211213", id="date"), + pytest.param(datetime(2022, 5, 8, 14, 36, 25), b"20220508", id="datetime"), + pytest.param(range(5), b"0/to/4", id="range1"), + pytest.param(range(2, 8), b"2/to/7", id="range2"), + pytest.param(range(1, 9, 3), b"1/to/7/by/3", id="range3"), + pytest.param(("u", "v", "z"), b"u/v/z", id="tuple"), + pytest.param([1, 3, 4, 9], b"1/3/4/9", id="list"), + ], +) +def test_val_to_mars(val, expected): + assert mars._val_to_mars(val) == expected + + +def test_to_mars(): + req = { + "class": "od", + "expver": "0001", + "stream": "enfo", + "date": datetime(2020, 10, 11), + "time": "0000", + "type": "pf", + "number": range(1, 51), + "step": [24, 36, 72], + "levtype": "pl", + "levelist": 500, + "param": (129, 130), + } + expected = b"retrieve,class=od,expver=0001,stream=enfo,date=20201011,time=0000,type=pf,number=1/to/50,step=24/36/72,levtype=pl,levelist=500,param=129/130" + assert mars.to_mars(b"retrieve", req) == expected diff --git a/pproc-core/tests/ppcore/utils/test_stepseq.py b/pproc-core/tests/ppcore/utils/test_stepseq.py new file mode 100644 index 00000000..9f88e006 --- /dev/null +++ b/pproc-core/tests/ppcore/utils/test_stepseq.py @@ -0,0 +1,66 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import pytest +from datetime import datetime + +from ppcore.utils import stepseq + + +@pytest.mark.parametrize( + "date, start, end, interval, num_months, remaining", + [ + ["20241001", 12, 5160, 12, 7, 6], + ["20241001", 6, 5160, 6, 7, 12], + ["20241001", 0, 5160, 6, 7, 12], + ["20241002", 6, 5160, 6, 6, 16], + ["20241002", 6, 800, 6, 0, 0], + ], +) +def test_monthly(date, start, end, interval, num_months, remaining): + steps = list(range(start, end + 1, interval)) + step_ranges = [x for x in stepseq.stepseq_monthly(date, start, end, interval)] + assert len(step_ranges) == num_months + if num_months > 0: + assert len(steps[steps.index(step_ranges[-1][-1]) + 1 :]) == remaining + + +@pytest.mark.parametrize( + "start, end, width, interval, by, expected", + [ + [0, 0, 0, 1, 1, [range(0, 1)]], + [0, 120, 0, 24, 1, [range(x, x + 1) for x in range(0, 121, 24)]], + [ + 0, + 360, + 120, + 120, + 6, + [range(0, 121, 6), range(120, 241, 6), range(240, 361, 6)], + ], + ], +) +def test_ranges(start, end, width, interval, by, expected): + assert [ + x for x in stepseq.stepseq_ranges(start, end, width, interval, by) + ] == expected + + +@pytest.mark.parametrize( + "date, fcmonth, expected", + [ + ["20241001", 1, f"0-{31*24}"], + ["20241001", 7, f"{182*24}-{(182+30)*24}"], + ["20241002", 1, f"{30*24}-{(30+30)*24}"], + ], +) +def test_conversions(date, fcmonth, expected): + assert ( + stepseq.fcmonth_to_steprange(datetime.strptime(date, "%Y%m%d"), fcmonth) + == expected + ) + assert ( + stepseq.steprange_to_fcmonth(datetime.strptime(date, "%Y%m%d"), expected) + == fcmonth + ) diff --git a/pproc-core/tests/schema.yaml b/pproc-core/tests/schema.yaml new file mode 100644 index 00000000..d210f809 --- /dev/null +++ b/pproc-core/tests/schema.yaml @@ -0,0 +1,3138 @@ +config: + interp_keys: + intgrid: "none" + legendre-loader: "shmem" + matrix-loader: "file-io" + metadata_from_output: ["param", "stream", "date"] + + filter:param: + "*": {} + "10": + preprocessing: + - operation: expand + internal_dim: ["param", ["u", "v"]] + backend_kwargs: {"method": "sel"} + - operation: norm + interp_keys: + intgrid: "none" + legendre-loader: "shmem" + matrix-loader: "file-io" + vod2uv: true + input: + expand_exclude: ["param"] + "131/132": + filter:type: + taem/taes: {} + cf/pf/fc/fcmean/fcstdev/fcmax/fcmin: + filter:levtype: + pl: + metadata_from_output: ["stream", "date"] + vod2uv: true + "121/122/123/228026/228027": + filter:type: + em/es/pb: + statistics: + metadata: + timeRangeIndicator: 2 + accumulations: + step: + name: + type: default + length: "{steplength}:int" + "*": {} + "207": + filter:stream: + msmm: + preprocessing: + - operation: norm + "*": {} + "140249": + filter:type: + fc/cf/pf/em/es/pb/fcmean/fcstdev/fcmin/fcmax: + preprocessing: + - operation: "direction" + cd: {} + "172008/172009/172142/172143/172144/172146/172147/172169/172175/172176/172177/172178/172179/172180/172181/172182/172189/172205/172212/172228": + filter:type: + fcmean/fcstdev/fcmin/fcmax: + filter:param: + 172142/172143/172144/172228: + vmin: 0. + "172189": + vmin: 0. + vmax: 1. + "*": {} + preprocessing: + - operation: scale + value: 0.00001157407 + filter:stream: + enfh/enwh/eefh/weeh: + accumulations: + hdate: {} + "*": {} + accumulations: + step: + deaccumulate: true + taem/taes: {} + "260033/260053": + preprocessing: + - operation: sum + metadata: + shortName: tprate + edition: 2 + "200189/200142/200143/200144/228216/200228": + accumulations: + step: + type: legacywindow + operation: difference + name: + type: default + length: "{steplength}:int" + metadata: + timeRangeIndicator: 5 + stepType: diff + "234167": + metadata: + bitsPerValue: 24 + "234228": + preprocessing: + - operation: scale + value: 604800000 + filter:type: + pf/cf/fc: + filter:levtype: + fl: + entrypoint: pproc-flight-levels + target_flight_levels: "{levelist}" + metadata: + edition: 2 + bitsPerValue: 16 + filter:type: + fc: + metadata: + productDefinitionTemplateNumber: 1 + typeOfGeneratingProcess: 4 + typeOfProcessedData: 3 + typeOfEnsembleForecast: 5 + perturbationNumber: 0 + numberOfForecastsInEnsemble: 51 # TODO: Remove in 50r2 when oper/fc encodes this correctly + localTablesVersion: 1 + deletePV: 1 + pf: + metadata: + grib2LocalSectionNumber: 1 + typeOfEnsembleForecast: 6 + localTablesVersion: 1 + deletePV: 1 + accumulations: + step: {} + number: {} + "*": + filter:param: + "*": + entrypoint: pproc-accumulate + "200189/200142/200143/200144/228216/200228": + entrypoint: pproc-accumulate + accumulations: + step: + type: legacywindow + operation: difference + name: + type: default + length: "{steplength}:int" + metadata: + timeRangeIndicator: 5 + stepType: diff + "261016": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_hmdx" + params: ["167", "168"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261016 + join: false + "261023": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_rhp" + params: ["167", "168"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 260242 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_wbt" + params: ["167", "260242"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261023 + join: false + "260242": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_rhp" + params: ["167", "168"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 260242 + join: false + "260004": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_heatx" + params: ["167", "168"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 260004 + join: false + "260005": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: norm + params: ["165", "166"] + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_wcf" + params: ["167", "207"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 260005 + join: false + "214001": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_cossza" + params: ["167", "228021"] + deaccumulate: ["228021"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 214001 + join: false + "47": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_cossza" + params: ["167", "228021"] + deaccumulate: ["228021"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_dsrp" + params: ["228021", "214001"] + deaccumulate: ["228021"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 47 + join: false + "261002": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_cossza" + params: ["167", "228021"] + deaccumulate: ["228021"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_mrt" + params: ["167", "214001", "47", "169", "228021", "175", "177", "176"] + deaccumulate: ["47", "169", "228021", "175", "177", "176"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261002 + join: false + "261001": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: norm + params: ["165", "166"] + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_cossza" + params: ["167", "228021"] + deaccumulate: ["228021"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_mrt" + params: ["167", "214001", "47", "169", "228021", "175", "177", "176"] + deaccumulate: ["47", "169", "228021", "175", "177", "176"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261002 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_utci" + params: ["167", "168", "207", "261002"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261001 + join: false + "261014": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: norm + params: ["165", "166"] + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_cossza" + params: ["167", "228021"] + deaccumulate: ["228021"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_mrt" + params: ["167", "214001", "47", "169", "228021", "175", "177", "176"] + deaccumulate: ["47", "169", "228021", "175", "177", "176"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261002 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_wbgt" + params: ["167", "168", "207", "261002"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261014 + join: false + "261015": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: norm + params: ["165", "166"] + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_cossza" + params: ["167", "228021"] + deaccumulate: ["228021"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_mrt" + params: ["167", "214001", "47", "169", "228021", "175", "177", "176"] + deaccumulate: ["47", "169", "228021", "175", "177", "176"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261002 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_gt" + params: ["167", "207", "261002"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261015 + join: false + "261018": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: norm + params: ["165", "166"] + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_rhp" + params: ["167", "168"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 260242 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_nefft" + params: ["167", "207", "260242"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 261018 + join: false + "260255": + entrypoint: pproc-thermal-indices + preprocessing: + - operation: thermal_index + function: norm + params: ["165", "166"] + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_rhp" + params: ["167", "168"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 260242 + join: true + - operation: thermal_index + function: "ppruntime.thermal_indices.calc_aptmp" + params: ["167", "260242", "207"] + metadata: + edition: 2 + bitsPerValue: 16 + packingType: "grid_ccsds" + typeOfGeneratingProcess: 2 + paramId: 260255 + join: false + em/es: + entrypoint: "pproc-ensms" + metadata_from_output: ["param", "stream", "date", "type"] + filter:type: + em: + statistics: + operation: mean + es: + statistics: + operation: std + filter:stream: + enfo/waef/eefo/weef: + input: + dtype: float64 + statistics: + metadata: + localDefinitionNumber: 30 + oceanAtmosphereCoupling: 2 + legBaseDate: "{date}:int" + legBaseTime: "{time}:int" + legNumber: 1 + perturbationNumber: 0 + bitsPerValue: 16 + numberOfForecastsInEnsemble: "{num_fields}:int" + filter:param: + "10": + statistics: + metadata: + bitsPerValue: 24 + "*": {} + efhs/wehs/eehs: + filter:steptype: + range: + statistics: + metadata: + localDefinitionNumber: 19 + bitsPerValue: 12 + sampleSizeOfModelClimate: "{num_fields}:int" + versionOfModelClimate: 0 + efiOrder: 0 + numberOfReforecastYearsInModelClimate: 20 + accumulations: + date: + operation: "aggregation" + filter:steplength: + "*": + statistics: + metadata: + numberOfDaysInClimateSamplingWindow: 31 + "168": + statistics: + metadata: + numberOfDaysInClimateSamplingWindow: 7 + instantaneous: + input: + dtype: float64 + statistics: + metadata: + perturbationNumber: 0 + numberOfForecastsInEnsemble: "{num_fields}:int" + bitsPerValue: 16 + dataDate: "{date}:int" + accumulations: + step: {} + filter:param: + "129": + statistics: + metadata: + bitsPerValue: 24 + "*": {} + efi/sot/efic: + entrypoint: pproc-extreme + dtype: float64 + accumulations: + step: + type: legacywindow + name: + type: default + length: "{steplength}:int" + filter:param: + "132044": + eps: 1e-4 + preprocessing: + - operation: mask + select: {param: "228036"} + mask: [{param: "228035"}, "<=", 10] + accumulations: + step: + operation: maximum + metadata: + typeOfStatisticalProcessing: 1 + edition: 1 + bitsPerValue: 12 + indicatorOfTypeOfLevel: 1 + localDefinitionNumber: 19 + "132059": + eps: 1e-4 + preprocessing: + - operation: mask + select: {param: "228035"} + mask: [{param: "228035"}, "<=", 10] + accumulations: + step: + operation: maximum + metadata: + typeOfStatisticalProcessing: 1 + edition: 1 + bitsPerValue: 12 + indicatorOfTypeOfLevel: 1 + localDefinitionNumber: 19 + "132045": + eps: -1e-4 + preprocessing: + - operation: norm + accumulations: + step: + operation: mean + metadata: + edition: 1 + localDefinitionNumber: 19 + bitsPerValue: 12 + timeRangeIndicator: 3 + stepType: avg + 132165/132167: + eps: -1e-4 + accumulations: + step: + operation: mean + metadata: + edition: 1 + localDefinitionNumber: 19 + bitsPerValue: 12 + timeRangeIndicator: 3 + stepType: avg + 132049/132201: + eps: -1e-4 + accumulations: + step: + operation: maximum + metadata: + edition: 1 + localDefinitionNumber: 19 + bitsPerValue: 12 + "132216": + eps: 1e-4 + preprocessing: + - operation: mask + select: {param: "140229"} + mask: [{param: "140229"}, "<=", 0.1] + accumulations: + step: + operation: maximum + metadata: + edition: 1 + localDefinitionNumber: 19 + bitsPerValue: 12 + "132144": + eps: 1e-4 + accumulations: + step: + operation: difference + metadata: + edition: 1 + localDefinitionNumber: 19 + bitsPerValue: 12 + timeRangeIndicator: 5 + stepType: diff + "132202": + eps: -1e-4 + accumulations: + step: + operation: minimum + metadata: + edition: 1 + localDefinitionNumber: 19 + bitsPerValue: 12 + "132228": + eps: 1e-4 + accumulations: + step: + operation: difference + metadata: + edition: 1 + localDefinitionNumber: 19 + bitsPerValue: 12 + timeRangeIndicator: 5 + stepType: diff + filter:stream: + "*": {} + "eefo": + preprocessing: + - operation: scale + value: 604800000 + ep: + entrypoint: pproc-probabilities + metadata_from_output: ["param", "stream", "date", "type"] + statistics: + operation: threshold_probability + input: + dtype: float64 + filter:steptype: + instantaneous: + accumulations: + step: + range: + accumulations: + step: + name: + type: default + length: "{steplength}:int" + filter:param: + "131060/131061/131062/131063/131064": + accumulations: + step: + operation: difference + metadata: + timeRangeIndicator: 5 + stepType: diff + "131098/131099/131085": + accumulations: + step: + operation: difference + metadata: + stepType: "accum" + stepRange: "0-0" + "131065/131066/131067": + accumulations: + step: + operation: difference_rate + factor: 0.041666666666666664 + metadata: + timeRangeIndicator: 5 + stepType: diff + "131068/131069": + preprocessing: + - operation: norm + accumulations: + step: + operation: maximum + "131070/131071/131072/131074/131075/131076/131077/131078/131079/131080/131081": + accumulations: + step: + operation: maximum + "131073": + accumulations: + step: + operation: minimum + "131100": + accumulations: + step: + operation: maximum + 131020/131021/131022/131023/131024/131025/133093/133094/133095/133096/133097/133098: + config: anomaly + filter:param: + "131020/131021": + accumulations: + step: + operation: "mean" + "131022/131023": + accumulations: + step: + operation: minimum + "131024/131025": + accumulations: + step: + operation: maximum + "133093/133094/133095": + accumulations: + step: + operation: maximum + std_anomaly: true + "133096/133097/133098": + accumulations: + step: + operation: minimum + std_anomaly: true + "260290": {} + filter:selection: + "default": + filter:param: + "131020": + statistics: + threshold: + comparison: "<" + value: -2 + metadata: + bitsPerValue: 24 + "131021": + statistics: + threshold: + comparison: ">=" + value: 2 + metadata: + bitsPerValue: 24 + "131022": + statistics: + threshold: + comparison: "<" + value: -8 + metadata: + bitsPerValue: 24 + "131023": + statistics: + threshold: + comparison: "<" + value: -4 + metadata: + bitsPerValue: 24 + "131024": + statistics: + threshold: + comparison: ">" + value: 4 + metadata: + bitsPerValue: 24 + "131025": + statistics: + threshold: + comparison: ">" + value: 8 + metadata: + bitsPerValue: 24 + "131060": + statistics: + threshold: + comparison: ">=" + value: 0.001 + scale_factor: 3 + metadata: + bitsPerValue: 8 + "131061": + statistics: + threshold: + comparison: ">=" + value: 0.005 + scale_factor: 3 + metadata: + bitsPerValue: 8 + "131062": + statistics: + threshold: + comparison: ">=" + value: 0.01 + scale_factor: 3 + metadata: + bitsPerValue: 8 + "131063": + statistics: + threshold: + comparison: ">=" + value: 0.02 + scale_factor: 3 + metadata: + bitsPerValue: 8 + "131064": + statistics: + threshold: + comparison: '<' + value: 0.0001 + scale_factor: 4 + metadata: + bitsPerValue: 8 + "131065": + statistics: + threshold: + comparison: '<' + value: 0.001 + scale_factor: 4 + metadata: + bitsPerValue: 8 + "131066": + statistics: + threshold: + comparison: '>=' + value: 0.003 + scale_factor: 4 + metadata: + bitsPerValue: 8 + "131067": + statistics: + threshold: + comparison: '>=' + value: 0.005 + scale_factor: 4 + metadata: + bitsPerValue: 8 + "131068": + statistics: + threshold: + comparison: ">=" + value: 10 + metadata: + bitsPerValue: 8 + "131069": + statistics: + threshold: + comparison: ">=" + value: 15 + metadata: + bitsPerValue: 8 + "131070": + statistics: + threshold: + comparison: ">=" + value: 15 + metadata: + bitsPerValue: 8 + "131071": + statistics: + threshold: + comparison: ">=" + value: 20 + metadata: + bitsPerValue: 8 + "131072": + statistics: + threshold: + comparison: ">=" + value: 25 + metadata: + bitsPerValue: 8 + "131073": + statistics: + threshold: + comparison: "<=" + value: 273.15 + scale_factor: 2 + metadata: + bitsPerValue: 8 + "131074": + statistics: + threshold: + comparison: ">=" + value: 2 + metadata: + bitsPerValue: 8 + "131075": + statistics: + threshold: + comparison: ">=" + value: 4 + metadata: + bitsPerValue: 8 + "131076": + statistics: + threshold: + comparison: ">=" + value: 6 + metadata: + bitsPerValue: 8 + "131077": + statistics: + threshold: + comparison: ">=" + value: 8 + metadata: + bitsPerValue: 8 + "131078": + statistics: + threshold: + comparison: ">=" + value: 8 + metadata: + bitsPerValue: 8 + "131079": + statistics: + threshold: + comparison: ">=" + value: 10 + metadata: + bitsPerValue: 8 + "131080": + statistics: + threshold: + comparison: ">=" + value: 12 + metadata: + bitsPerValue: 8 + "131081": + statistics: + threshold: + comparison: ">=" + value: 15 + metadata: + bitsPerValue: 8 + "131085": + statistics: + threshold: + comparison: ">=" + value: 0.1 + scale_factor: 3 + metadata: + localDefinitionNumber: 5 + edition: 2 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + timeIncrement: 12 + packingType: "grid_ccsds" + bitsPerValue: 8 + scaleFactorOfLowerLimit: 0 + "131098": + statistics: + threshold: + comparison: ">=" + value: 0.025 + scale_factor: 3 + metadata: + localDefinitionNumber: 5 + edition: 2 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + timeIncrement: 12 + packingType: "grid_ccsds" + bitsPerValue: 8 + scaleFactorOfLowerLimit: 0 + "131099": + statistics: + threshold: + comparison: ">=" + value: 0.05 + scale_factor: 3 + metadata: + localDefinitionNumber: 5 + edition: 2 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + timeIncrement: 12 + packingType: "grid_ccsds" + bitsPerValue: 8 + scaleFactorOfLowerLimit: 0 + "131100": + statistics: + threshold: + comparison: ">=" + value: 10 + metadata: + localDefinitionNumber: 5 + edition: 2 + productDefinitionTemplateNumber: 9 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + timeIncrement: 12 + typeOfTimeIncrement: 2 + packingType: "grid_ccsds" + bitsPerValue: 8 + "133093": + statistics: + threshold: + comparison: '>' + value: 1 + metadata: + localDefinitionNumber: 30 + edition: 2 + productDefinitionTemplateNumber: 9 + oceanAtmosphereCoupling: 2 + legBaseDate: "{date}:int" + legBaseTime: "{time}:int" + legNumber: 1 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + paramId: 0 + timeIncrement: 12 + typeOfStatisticalProcessing: 10 + packingType: "grid_ccsds" + bitsPerValue: 24 + "133094": + statistics: + threshold: + comparison: '>' + value: 1.5 + scale_factor: 1 + metadata: + localDefinitionNumber: 30 + edition: 2 + productDefinitionTemplateNumber: 9 + oceanAtmosphereCoupling: 2 + legBaseDate: "{date}:int" + legBaseTime: "{time}:int" + legNumber: 1 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + paramId: 0 + timeIncrement: 12 + typeOfStatisticalProcessing: 10 + packingType: "grid_ccsds" + bitsPerValue: 24 + scaleFactorOfLowerLimit: 1 + "133095": + statistics: + threshold: + comparison: '>' + value: 2 + metadata: + localDefinitionNumber: 30 + edition: 2 + productDefinitionTemplateNumber: 9 + oceanAtmosphereCoupling: 2 + legBaseDate: "{date}:int" + legBaseTime: "{time}:int" + legNumber: 1 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + paramId: 0 + timeIncrement: 12 + typeOfStatisticalProcessing: 10 + packingType: "grid_ccsds" + bitsPerValue: 24 + "133096": + statistics: + threshold: + comparison: '<' + value: -1 + limit_type: lower + metadata: + localDefinitionNumber: 30 + edition: 2 + productDefinitionTemplateNumber: 9 + oceanAtmosphereCoupling: 2 + legBaseDate: "{date}:int" + legBaseTime: "{time}:int" + legNumber: 1 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + paramId: 0 + timeIncrement: 12 + typeOfStatisticalProcessing: 10 + packingType: "grid_ccsds" + bitsPerValue: 24 + "133097": + statistics: + threshold: + comparison: '<' + value: -1.5 + scale_factor: 1 + limit_type: lower + metadata: + localDefinitionNumber: 30 + edition: 2 + productDefinitionTemplateNumber: 9 + oceanAtmosphereCoupling: 2 + legBaseDate: "{date}:int" + legBaseTime: "{time}:int" + legNumber: 1 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + paramId: 0 + timeIncrement: 12 + typeOfStatisticalProcessing: 10 + packingType: "grid_ccsds" + bitsPerValue: 24 + scaleFactorOfLowerLimit: 1 + "133098": + statistics: + threshold: + comparison: '<' + value: -2 + limit_type: lower + metadata: + localDefinitionNumber: 30 + edition: 2 + productDefinitionTemplateNumber: 9 + oceanAtmosphereCoupling: 2 + legBaseDate: "{date}:int" + legBaseTime: "{time}:int" + legNumber: 1 + typeOfGeneratingProcess: 5 + indicatorOfUnitForTimeIncrement: 1 + paramId: 0 + timeIncrement: 12 + typeOfStatisticalProcessing: 10 + packingType: "grid_ccsds" + bitsPerValue: 24 + "eccharts": + filter:param: + statistics: + "131060": + threshold: + comparison: ">=" + value: "{threshold}:float" + scale_factor: 3 + metadata: + bitsPerValue: 8 + "260290": + statistics: + threshold: "{threshold}" + metadata: + edition: 2 + productDefinitionTemplateNumber: 5 + typeOfGeneratingProcess: 5 + pb: + entrypoint: pproc-quantiles + metadata_from_output: ["param", "stream", "date", "type"] + statistics: + operation: quantiles + filter:stream: + enfo/waef: + statistics: + metadata: + localDefinitionNumber: 30 + "*": {} + fcmean: + filter:param: + 171001/171002/171006/171007/171078/171079/171033/171034/171121/171122/171129/171130/171131/171132/171133/171136/171137/171139/171141/171151/171164/171165/171166/171167/171168/171201/171202/173142/173143/173144/173189/173228: + filter:stream: + eefo: + entrypoint: pproc-anomaly + dtype: float64 + metadata: + bitsPerValue: 24 + accumulations: + step: + type: legacywindow + name: + type: default + length: "{steplength}:int" + metadata: + timeRangeIndicator: 3 + stepType: avg + clim: + accumulations: + step: {} + levelist: {} + date: + operation: mean + "*": + dtype: float64 + filter:stream: + enfo/waef/eefo/weef: + entrypoint: pproc-accumulate + accumulations: + step: + type: legacywindow + name: + type: default + length: "{steplength}:int" + operation: mean + metadata: + bitsPerValue: 16 + legBaseDate: 0 + legNumber: 0 + stepType: avg + type: fcmean + filter:param: + "*": + accumulations: + step: + metadata: + timeRangeIndicator: 3 + numberIncludedInAverage: "{num_coords}:int" + "201": + metadata_from_output: ["stream", "date"] + accumulations: + step: + metadata: + paramId: 201 + timeRangeIndicator: 3 + numberIncludedInAverage: "{num_coords}:int" + "202": + metadata_from_output: ["stream", "date"] + accumulations: + step: + metadata: + paramId: 202 + timeRangeIndicator: 3 + numberIncludedInAverage: "{num_coords}:int" + "235117": + metadata_from_output: ["stream", "date"] + accumulations: + step: + metadata: + edition: 2 + paramId: 235117 + discipline: 0 + parameterCategory: 7 + parameterNumber: 6 + typeOfFirstFixedSurface: 17 + typeOfStatisticalProcessing: 0 + indicatorOfUnitForTimeIncrement: 1 + timeIncrement: 6 + "enfh/enwh/eefh/weeh": + entrypoint: pproc-accumulate + filter:selection: + mclimate: + dtype: float32 + accumulations: + step: + type: legacywindow + name: + type: default + length: "{steplength}:int" + levelist: {} + hdate: {} + filter:param: + "140229": + preprocessing: + - operation: mask + select: {param: "140229"} + mask: [{param: "140229"}, "<=", 0.1] + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 2 + stepType: max + "123": + vmin: 0. + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 2 + stepType: max + "140249": + vmin: 0. + vmax: 360. + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + "162071": + preprocessing: + - operation: norm + accumulations: + step: + metadata: + edition: 1 + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 3 + stepType: avg + "164": + vmin: 0. + vmax: 1. + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 3 + stepType: avg + "167": + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 3 + stepType: avg + "228/144": + vmin: 0. + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 5 + stepType: diff + "121": + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 2 + stepType: max + "122": + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 2 + "207": + vmin: 0. + preprocessing: + - operation: norm + accumulations: + step: + metadata: + bitsPerValue: 12 + type: fcmean + timeRangeIndicator: 3 + stepType: avg + "228044": + vmin: 0 + preprocessing: + - operation: mask + select: {param: "228036"} + mask: [{param: "228035"}, "<=", 10] + accumulations: + step: + metadata: + typeOfStatisticalProcessing: 1 + edition: 1 + bitsPerValue: 12 + indicatorOfTypeOfLevel: 1 + type: fcmean + timeRangeIndicator: 2 + stepType: max + "59": + vmin: 0 + preprocessing: + - operation: mask + select: {param: "228035"} + mask: [{param: "228035"}, "<=", 10] + accumulations: + step: + metadata: + typeOfStatisticalProcessing: 1 + edition: 1 + bitsPerValue: 12 + indicatorOfTypeOfLevel: 1 + type: fcmean + timeRangeIndicator: 2 + stepType: max + filter:steplength: + "*": + filter:param: + "228/144": + accumulations: + step: + operation: difference + metadata: + numberIncludedInAverage: "{num_coords}:int" + "123/140229/121/228044/59": + accumulations: + step: + operation: maximum + metadata: + numberIncludedInAverage: "{num_coords}:int" + "122": + accumulations: + step: + operation: minimum + metadata: + numberIncludedInAverage: "{num_coords}:int" + "164/167/162071/207": + accumulations: + step: + operation: mean + metadata: + numberIncludedInAverage: "{num_coords}:int" + "140249": + accumulations: + step: + operation: aggregation + metadata: + numberIncludedInAverage: "{num_coords}:int" + "168": + accumulations: + step: + operation: aggregation + filter:param: + "228": + preprocessing: + - operation: scale + value: 604800000 + "167": {} + "*": + accumulations: + hdate: {} + levelist: {} + step: + type: legacywindow + operation: mean + name: + type: default + length: "{steplength}:int" + metadata: + bitsPerValue: 16 + legBaseDate: 0 + legNumber: 0 + stepType: avg + type: fcmean + filter:param: + "*": + accumulations: + step: + metadata: + timeRangeIndicator: 3 + numberIncludedInAverage: "{num_coords}:int" + "201": + metadata_from_output: ["stream", "date"] + accumulations: + step: + metadata: + paramId: 201 + timeRangeIndicator: 3 + numberIncludedInAverage: "{num_coords}:int" + "202": + metadata_from_output: ["stream", "date"] + accumulations: + step: + metadata: + paramId: 202 + timeRangeIndicator: 3 + numberIncludedInAverage: "{num_coords}:int" + "235117": + metadata_from_output: ["stream", "date"] + accumulations: + step: + metadata: + edition: 2 + paramId: 235117 + stepType: avg + discipline: 0 + parameterCategory: 7 + parameterNumber: 6 + typeOfFirstFixedSurface: 17 + typeOfStatisticalProcessing: 0 + indicatorOfUnitForTimeIncrement: 1 + timeIncrement: 6 + msmm/swmm: + entrypoint: pproc-monthly-stats + accumulations: + step: + type: legacywindow + operation: mean + name: + type: monthly + date: "{date}:str" + metadata: + type: fcmean + bitsPerValue: 16 +windows: + filter:type: + em/es/pb: + filter:stream: + enfo/waef: + filter:param: + "*": + out_steps: + - type: instantaneous + end: 90 + interval: 3 + - type: instantaneous + start: 90 + 121/122: + out_steps: + type: instantaneous + interval: 6 + 228026/228027: + out_steps: + type: instantaneous + interval: 3 + eefo/weef: + type: instantaneous + efhs/wehs/eehs: + out_steps: &efhs_em_steps + type: instantaneous + interval: 6 + fc/cf/pf: + filter:stream: + "*": + filter:param: + "*": + out_steps: + type: instantaneous + 261001/261014/261015/261002: + out_steps: + type: instantaneous + deaccumulate: true + fcmean/fcstdev/fcmax/fcmin: + filter:stream: + "enfo/eefo/oper/eefh/weef": + out_steps: + type: range + interval: 24 + width: 168 + "enfh/enwh": + out_steps: + filter:param: + "*": + out_steps: + - type: range + width: 24 + interval: 24 + - type: range + width: 72 + end: 240 + interval: 24 + - type: range + width: 120 + end: 240 + interval: 24 + - "0-240" + - "0-360" + - "240-360" + 121/122/123/140229/59/228044/140249/164: + out_steps: + type: range + end: 168 + width: 24 + interval: 24 + "eefh/weeh": + filter:param: + "*": + out_steps: + type: range + interval: 24 + width: 168 + "msmm": + out_steps: + type: monthly + date: "{date}" + taem/taes: + filter:stream: + "enfo/eefo/oper/efhs/eehs": + out_steps: + type: range + interval: 24 + width: 168 + ep: + filter:stream: + enfo: + filter:param: + 131060/131061/131062/131063/131098/131099/131085/131070/131071/131072/131100: + out_steps: + type: range + width: 24 + interval: 12 + 131064/131065/131066/131067/131070/131071/131072/131100/131020/131021/131073: + out_steps: + - type: range + width: 120 + start: 120 + interval: 120 + - "120-168" + - "168-240" + 131068/131069/131073/131022/131023/131024/131025/133093/133094/133095/133096/133097/133098: + out_steps: + type: instantaneous + start: 12 + interval: 12 + "260290": + out_steps: + - type: instantaneous + start: 0 + end: 90 + interval: 1 + - type: instantaneous + start: 91 + end: 144 + interval: 3 + - type: instantaneous + start: 150 + end: 360 + interval: 6 + waef: + filter:param: + 131074/131075/131076/131077/131078/131079/131080/131081: + out_steps: + - type: instantaneous + start: 12 + interval: 12 + - type: range + width: 120 + start: 120 + interval: 120 + - "120-168" + - "168-240" + efi/efic/sot: + filter:stream: + "eefo/weef": + out_steps: + type: range + interval: 24 + width: 168 + "enfo/waef": + filter:param: + "*": + filter:time: + "1200": + out_steps: + - type: range + start: 12 + end: 240 + width: 24 + interval: 24 + - type: range + start: 12 + end: 240 + width: 72 + interval: 24 + - type: range + start: 12 + end: 240 + width: 120 + interval: 24 + - type: range + start: 240 + width: 24 + interval: 24 + - "0-240" + - "0-360" + - "240-360" + "0000": + out_steps: + - type: range + width: 24 + interval: 24 + - type: range + width: 72 + end: 240 + interval: 24 + - type: range + width: 120 + end: 240 + interval: 24 + - "0-240" + - "0-360" + - "240-360" + "0600/1800": + out_steps: + - type: range + width: 24 + end: 144 + interval: 12 + 132201/132202/132049/132144/132216/132059/132044: + filter:time: + "1200": + out_steps: + type: range + start: 12 + end: 180 + width: 24 + interval: 24 + "0000": + out_steps: + type: range + end: 168 + width: 24 + interval: 24 + "0600/1800": + out_steps: + - type: range + width: 24 + end: 144 + interval: 12 + cd: + filter:stream: + efhs/wehs: + filter:param: + "*": + out_steps: &efhs_cd_steps + - type: range + width: 24 + interval: 12 + - type: range + width: 72 + end: 240 + interval: 12 + - type: range + width: 120 + end: 240 + interval: 12 + - "0-240" + - "0-360" + - "240-360" + "202/201/49/140200/59/228044/140249/228006": + out_steps: + type: range + width: 24 + interval: 12 + eehs: &eehs_cd_steps + out_steps: + type: range + width: 168 + interval: 24 + gwt/pfc: + filter:param: + "228/201/202": + out_steps: + type: range + width: 12 + interval: 6 + cm/cr: + filter:stream: + enfo: + out_steps: + - "72-96" + - "120-168" + - "192-240" + - "240-360" +datasets: + enfo: + dataset_type: forecast + unperturbed: + type: fc + datacubes: + - class: od + stream: oper + type: fc + time: ["0000", "1200"] + step: &mr_steps + - from: 0 + to: 90 + by: 1 + - from: 93 + to: 144 + by: 3 + - from: 150 + to: 360 + by: 6 + domain: g + - class: od + stream: wave + type: fc + time: ["0000", "1200"] + step: *mr_steps + domain: g + - class: od + stream: enfo + type: pf + members: + start: 1 + end: 50 + time: ["0000", "1200"] + step: *mr_steps + domain: g + - class: od + stream: waef + type: pf + members: + start: 1 + end: 50 + time: ["0000", "1200"] + step: *mr_steps + domain: g + - class: od + stream: oper + type: fc + time: ["0600", "1800"] + step: &bc_steps + - from: 0 + to: 90 + by: 1 + - from: 93 + to: 144 + by: 3 + domain: g + - class: od + stream: wave + type: fc + time: ["0600", "1800"] + step: *bc_steps + domain: g + - class: od + stream: enfo + type: pf + members: + start: 1 + end: 50 + time: ["0600", "1800"] + step: *bc_steps + domain: g + - class: od + stream: waef + type: pf + members: + start: 1 + end: 50 + time: ["0600", "1800"] + step: *bc_steps + domain: g + wave: + - stream: wave + - stream: waef + eefo: + dataset_type: forecast + unperturbed: + type: cf + datacubes: + - class: od + stream: eefo + type: cf + time: "0000" + levtype: sfc + step: &subs_steps + - from: 0 + to: 1104 + by: 6 + domain: g + - class: od + stream: weef + type: cf + time: "0000" + levtype: sfc + step: *subs_steps + domain: g + - class: od + stream: eefo + type: pf + time: "0000" + levtype: sfc + members: + start: 1 + end: 100 + step: *subs_steps + domain: g + - class: od + stream: weef + type: pf + time: "0000" + levtype: sfc + members: + start: 1 + end: 100 + step: *subs_steps + domain: g + wave: + - stream: weef + seasonal: + dataset_type: forecast + datacubes: + - class: od + stream: mmsf + type: fc + members: + start: 0 + end: 50 + step: &seas_steps + - from: 0 + to: 5160 + by: 6 + domain: g + - class: od + stream: wasf + type: fc + members: + start: 0 + end: 50 + step: *seas_steps + domain: g + wave: + - stream: wasf + enfh: + dataset_type: reforecast + unperturbed: + type: cf + datacubes: + - stream: enfh + type: cf + step: &mr_hind_steps + - from: 0 + to: 360 + by: 6 + - stream: enwh + type: cf + step: *mr_hind_steps + - stream: enfh + type: pf + members: + start: 1 + end: 10 + step: *mr_hind_steps + - stream: enwh + type: pf + members: + start: 1 + end: 10 + step: *mr_hind_steps + wave: + - stream: enwh + scheme: ecmwf-4days + eefh: + dataset_type: reforecast + unperturbed: + type: cf + datacubes: + - stream: eefh + type: cf + step: &subs_hind_steps + - from: 0 + to: 1104 + by: 6 + - stream: weeh + type: cf + step: *subs_hind_steps + - stream: eefh + type: pf + members: + start: 1 + end: 10 + step: *subs_hind_steps + - stream: weeh + type: pf + members: + start: 1 + end: 10 + step: *subs_hind_steps + wave: + - stream: weeh + scheme: ecmwf-2days + efhs-cd: + dataset_type: climatology + datacubes: + - stream: efhs + type: cd + quantile: 100 + step: *efhs_cd_steps + - stream: wehs + type: cd + quantile: 100 + step: *efhs_cd_steps + wave: + - stream: wehs + scheme: ecmwf-4days + eehs-cd: + dataset_type: climatology + datacubes: + - stream: efhs + type: cd + quantile: 100 + step: *eehs_cd_steps + scheme: ecmwf-4days + efhs-em: + dataset_type: climatology + datacubes: + - stream: efhs + type: em + step: *efhs_em_steps + - stream: efhs + type: es + step: *efhs_em_steps + scheme: ecmwf-4days +inputs: + fc_inputs: + select_to_override: true + filter:type: + fc/cf/pf: + filter:type: + pf: + fc_inputs: + select: + type: pf + number: "{number}" + "*": + fc_inputs: + select: + type: "{type}" + filter:param: + "*": + fc_inputs: + select: + param: "{param}" + type: "{type}" + "10/131/132": + fc_inputs: + select: + param: ["138", "155"] + "207": + fc_inputs: + select: + param: ["165", "166"] + "260290": + filter:levtype: + "fl": + fc_inputs: + - select: + levtype: ml + levelist: [58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137] + param: 260290 + - select: + levtype: ml + levelist: 1 + param: 152 + "*": + fc_inputs: + select: + param: "{param}" + levtype: "{levtype}" + type: "{type}" + "261001": + fc_inputs: + - select: + param: ["169", "175", "176", "177", "228021", "47"] + derive: + step: + name: step_deaccumulate + - select: + param: ["165", "166", "167", "168"] + "261014": + fc_inputs: + - select: + param: ["169", "175", "176", "177", "228021", "47"] + derive: + step: + name: step_deaccumulate + - select: + param: ["165", "166", "167", "168"] + "261015": + fc_inputs: + - select: + param: ["169", "175", "176", "177", "228021", "47"] + derive: + step: + name: step_deaccumulate + - select: + param: ["165", "166", "167", "168"] + "260004": + fc_inputs: + select: + param: ["167", "168"] + "260242": + fc_inputs: + select: + param: ["167", "168"] + "261016": + fc_inputs: + select: + param: ["167", "168"] + "260005": + fc_inputs: + select: + param: ["165", "166", "167"] + "260255": + fc_inputs: + select: + param: ["165", "166", "167", "168"] + "261018": + fc_inputs: + select: + param: ["165", "166", "167", "168"] + "261002": + fc_inputs: + - select: + param: ["47", "228021", "169", "175", "176", "177"] + derive: + step: + name: step_deaccumulate + - select: + param: "167" # Required for metadata of cossza + "261023": + fc_inputs: + select: + param: ["167", "168"] + fcmean: + filter:stream: + enfo/waef/eefo/weef: + filter:members: + only_zero: + fc_inputs: + select: + type: unperturbed + no_zero: + fc_inputs: + select: + type: perturbed + number: "{number}" + contains_zero: + from_inputs: false + fc_inputs: + - select: + type: unperturbed + - select: + type: perturbed + number: "{number}" + filter:param: + "31/33/34/39/49/78/79/121/122/136/137/139/141/151/151130/151131/151132/151145/151148/151163/151164/151175/159/164/165/166/167/168/201/202/207/228246/228247/235117/237117/238117/239117": + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_default + 40/41/42/170/140229/140231/140232/140233/140245: + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_default + by: 24 + "172228": + fc_inputs: + select: + param: "228" + derive: + step: + name: step_default + include_start: true + by: 24 + 1/2/3/54/60/129/130/131/132/133/138/155/203: + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_default + by: 12 + msmm/swmm: + fc_inputs: + select: + number: "{number}" + filter:param: + "34/139/151/164/165/166/167/168/168/229/230": + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_monthly + 31/33/39/40/41/42/49/51/52/78/79/137/141/170/183/186/206/236/243/140220/140221/140229/140231/140232/140233/140244/140245/228008/228014: + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_monthly + by: 24 + "207": + fc_inputs: + select: + param: ["165", "166"] + derive: + step: + name: step_monthly + "172228": + fc_inputs: + select: + param: "228" + derive: + step: + name: step_monthly + include_start: true + allow_missing_zero: true + by: 24 + 129/130/133/138/155/203: + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_monthly + by: 12 + efi/efic/sot: + filter:type: + efic: + fc_inputs: + select: + type: unperturbed + efi/sot: {} + filter:param: + "132044": + fc_inputs: + select: + param: ["228036", "228035"] + clim_inputs: + select: + param: "228044" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132045": + fc_inputs: + select: + param: ["162071", "162072"] + clim_inputs: + select: + param: "162045" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132049": + fc_inputs: + select: + param: "123" + clim_inputs: + select: + param: "49" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132059": + fc_inputs: + select: + param: "228035" + clim_inputs: + select: + param: "59" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132144": + fc_inputs: + select: + param: "144" + clim_inputs: + select: + param: "144" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_deaccumulate + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132165": + fc_inputs: + select: + param: "207" + clim_inputs: + select: + param: "228005" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132167": + fc_inputs: + select: + param: "167" + clim_inputs: + select: + param: "228004" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132201": + fc_inputs: + select: + param: "121" + clim_inputs: + select: + param: "201" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132202": + fc_inputs: + select: + param: "122" + clim_inputs: + select: + param: "202" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132216": + fc_inputs: + select: + param: "140229" + clim_inputs: + select: + param: "140200" + type: cd + time: "0000" + filter:stream: + eefo: + clim_inputs: + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + derive: + step: + name: step_default + by: 6 + clim_inputs: + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + "132228": + filter:stream: + eefo: + fc_inputs: + select: + param: "172228" + clim_inputs: + select: + param: "228" + type: cd + time: "0000" + derive: + date: + name: clim_date + option: nearest + step: + name: clim_step_range + enfo: + fc_inputs: + select: + param: "228" + derive: + step: + name: step_deaccumulate + clim_inputs: + select: + param: "228" + derive: + date: + - name: clim_date + option: next + sequence: + type: daily + - name: clim_date + option: previous + strict: false + step: + name: clim_step_range + taem/taes: + fc_inputs: + select: + ensemble: True + filter:stream: + eefo: + filter:param: + "*": {} + 171001/171002/171006/171007/171078/171079/171033/171034/171121/171122/171129/171130/171131/171132/171133/171136/171137/171139/171141/171151/171164/171165/171166/171167/171168/171201/171202/173142/173143/173144/173189/173228: + fc_inputs: + derive: + step: + name: step_precomputed + clim_inputs: + select: + type: taem + derive: + date: + - name: clim_date + option: nearest + - name: clim_date + option: bracket + num: 2 + strict: False + step: + name: clim_step_range + 234167/234139/234151/234228: + fc_inputs: + derive: + step: + name: step_precomputed + clim_inputs: + - select: + type: fcmean + ensemble: True + derive: + date: + - name: clim_date + option: nearest + - name: clim_date + option: bracket + num: 1 + strict: False + step: + name: clim_step_range + - select: + type: taem + derive: + date: + - name: clim_date + option: nearest + - name: clim_date + option: bracket + num: 1 + strict: False + step: + name: clim_step_range + efhs/wehs/eehs: + fc_inputs: + select: + type: "fcmean" + derive: + step: + name: step_precomputed + hdate: + name: hindcast_dates + rstart: -20 + rend: 0 + recurrence: "yearly" + include_endpoint: false + cd: + filter:stream: + efhs/eehs: + from_inputs: false + fc_inputs: + - select: + type: "fcmean" + derive: + step: + name: step_precomputed + filter:steplength: + "*": + filter:stream: + efhs: + fc_inputs: + derive: + date: + name: clim_date + option: bracket + num: 4 + strict: False + "168": + fc_inputs: + derive: + date: + name: clim_date + option: bracket + num: 2 + strict: False + filter:param: + "228004": + fc_inputs: + select: + param: "167.128" + "49": + fc_inputs: + select: + param: "123.128" + "228005": + fc_inputs: + select: + param: "207.128" + "201": + fc_inputs: + select: + param: "121.128" + "202": + fc_inputs: + select: + param: "122.128" + "162045": + fc_inputs: + select: + param: "71.162" + "228006": + fc_inputs: + select: + param: "164.128" + "228": + fc_inputs: + select: + param: "228.128" + "144": + fc_inputs: + select: + param: "144.128" + "59": + fc_inputs: + select: + param: "59.128" + "228044": + fc_inputs: + select: + param: "44.228" + "140249": + fc_inputs: + select: + param: "249.140" + override: + members: null + "wehs": + from_inputs: false + fc_inputs: + - select: + type: "fcmean" + derive: + step: + type: step_precomputed + filter:steplength: + "*": + fc_inputs: + derive: + date: + - name: clim_date + option: bracket + num: 4 + strict: False + "168": + fc_inputs: + derive: + date: + - name: clim_date + option: bracket + num: 2 + strict: False + filter:param: + "140200": + fc_inputs: + select: + param: "229.140" + em/es: + fc_inputs: + select: + ensemble: true + filter:stream: + enfo/waef: + filter:param: + "10": + fc_inputs: + select: + param: ["138", "155"] + "121/122/123": + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_default + by: 6 + "228026/228027": + fc_inputs: + select: + param: "{param}" + derive: + step: + name: step_default + by: 3 + "200228": + fc_inputs: + select: + param: ["228"] + derive: + step: + name: step_deaccumulate + "*": {} + eefo/weef: + filter:steplength: + "168": + fc_inputs: + select: + type: fcmean + derive: + step: + name: step_precomputed + "*": {} + efhs/eehs: + filter:steptype: + range: + from_inputs: false + fc_inputs: + select: + type: fcmean + derive: + step: + name: step_precomputed + filter:steplength: + "*": + filter:stream: + efhs: + fc_inputs: + derive: + date: + name: clim_date + option: bracket + num: 4 + strict: False + "168": + fc_inputs: + derive: + date: + name: clim_date + option: bracket + num: 4 + strict: False + filter:param: + "228004": + fc_inputs: + select: + param: "167.128" + "49": + fc_inputs: + select: + param: "123.128" + "228005": + fc_inputs: + select: + param: "207.128" + "201": + fc_inputs: + select: + param: "121.128" + "202": + fc_inputs: + select: + param: "122.128" + "162045": + fc_inputs: + select: + param: "71.162" + "228006": + fc_inputs: + select: + param: "164.128" + "228": + fc_inputs: + select: + param: "228.128" + "144": + fc_inputs: + select: + param: "144.128" + "59": + fc_inputs: + select: + param: "59.128" + "228044": + fc_inputs: + select: + param: "44.228" + instantaneous: + fc_inputs: + derive: + hdate: + name: hindcast_dates + rstart: -20 + rend: 0 + recurrence: "yearly" + include_endpoint: false + "wehs": + filter:steptype: + range: + from_inputs: false + filter:param: + "140200": + fc_inputs: + select: + param: "229.140" + type: "fcmean" + derive: + step: + type: step_precomputed + date: + - name: clim_date + option: bracket + num: 4 + strict: False + instantaneous: + fc_inputs: + derive: + hdate: + name: hindcast_dates + rstart: -20 + rend: 0 + recurrence: "yearly" + include_endpoint: false + gwt: + filter:param: + "228": + filter:steplength: + "6": + fc_inputs: + - select: + param: "228" + derive: + step: + name: step_deaccumulate + - select: + param: ["138", "155"] + levtype: pl + levelist: 700 + derive: + step: + type: step_default + include_start: true + by: 3 + - select: + param: "143" + derive: + step: + name: step_deaccumulate + - select: + param: "228022" + derive: + step: + name: step_deaccumulate + by: 24 + - select: + param: "228035" + derive: + step: + name: step_default + by: 6 + - select: + param: [167, 168] + derive: + step: + name: step_default + by: 3 + include_start: true + pfc: + fc_inputs: + select: + ensemble: true + derive: + step: + name: step_precomputed + ep: + fc_inputs: + select: + ensemble: True + filter:selection: + custom: {} + default: + filter:param: + 131020/131021/131022/131023/131024/131025/133093/133094/133095/133096/133097/133098: + fc_inputs: + select: + param: "130" + derive: + step: + name: step_default + include_start: true + by: 6 + clim_inputs: + - select: + param: "130" + type: "em" + time: "0000" + derive: + step: + name: clim_step_inst + date: + name: clim_date + option: previous + strict: False + - select: + param: "130" + type: "es" + time: "0000" + derive: + step: + name: clim_step_inst + date: + name: clim_date + option: previous + strict: False + 131022/131023/131024/131025/133093/133094/133095/133096/133097/133098: + fc_inputs: + select: + param: "130" + derive: + step: + name: step_default + by: 6 + clim_inputs: + - select: + param: "130" + type: "em" + time: "0000" + derive: + step: + name: clim_step_inst + date: + name: clim_date + option: previous + strict: False + - select: + param: "130" + type: "es" + time: "0000" + derive: + step: + name: clim_step_inst + date: + name: clim_date + option: previous + strict: False + 131060/131061/131062/131063/131064/131065/131066/131067/131098/131099/131085: + fc_inputs: + select: + param: "228" + derive: + step: + name: step_deaccumulate + "131068/131069": + fc_inputs: + select: + param: ["165", "166"] + 131070/131071/131072/131100: + fc_inputs: + select: + param: "123" + derive: + step: + name: step_default + by: 6 + "131073": + filter:steptype: + instantaneous: + fc_inputs: + select: + param: "167" + range: + fc_inputs: + select: + param: "122" + derive: + step: + name: step_default + by: 6 + 131074/131075/131076/131077: + fc_inputs: + select: + param: "140229" + 131078/131079/131080/131081: + fc_inputs: + select: + param: "140232" + pb: + fc_inputs: + select: + ensemble: True + filter:param: + "121/122/123": + fc_inputs: + derive: + step: + name: step_default + by: 6 + "228026/228027": + fc_inputs: + derive: + step: + name: step_default + by: 3 + "200228": + fc_inputs: + select: + param: ["228"] + derive: + step: + name: 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index 00000000..af25a625 --- /dev/null +++ b/pproc-runtime/LICENSE @@ -0,0 +1,79 @@ +Apache License +Version 2.0, January 2004 +http://www.apache.org/licenses/ + +TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + +1. 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We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. + +Copyright [yyyy] [name of copyright owner] + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + +http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. + +------------------------------------------------------------------------------- + +In applying this licence, ECMWF does not waive the privileges and immunities +granted to it by virtue of its status as an intergovernmental organisation +nor does it submit to any jurisdiction. diff --git a/pproc-runtime/README.md b/pproc-runtime/README.md new file mode 100644 index 00000000..8f873bfe --- /dev/null +++ b/pproc-runtime/README.md @@ -0,0 +1,24 @@ +# pproc-runtime + +

+ + Static Badge + + + + Code Coverage + + + + License: Apache 2.0 + + + + Latest Release + +

+ +> \[!IMPORTANT\] +> This software is **Sandbox** and subject to ECMWF's guidelines on [Software Maturity](https://github.com/ecmwf/codex/raw/refs/heads/main/Project%20Maturity). + +pproc-runtime contains the functions required at runtime for the execution of graphs constructed using pproc-core. diff --git a/pproc-runtime/pyproject.toml b/pproc-runtime/pyproject.toml new file mode 100644 index 00000000..7812787b --- /dev/null +++ b/pproc-runtime/pyproject.toml @@ -0,0 +1,72 @@ +[build-system] +build-backend = "setuptools.build_meta" + +requires = [ "setuptools>=65", "setuptools-scm[toml]>=6.2" ] + +[project] +name = "pproc-runtime" +description = "Runtime dependencies of PProc" +readme = "README.md" +license = "Apache-2.0" +license-files = [ "LICENSE" ] +authors = [ + { name = "European Centre for Medium-Range Weather Forecasts (ECMWF)", email = "software.support@ecmwf.int" }, +] +requires-python = ">=3.10" +classifiers = [ + "Programming Language :: Python :: 3 :: Only", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", +] +dynamic = [ "version" ] + +dependencies = [ + "array-api-compat", + "code-meters", + "earthkit-data[mars,fdb]<1", + "earthkit-meteo", + "eccodes", + "fdb5lib", + "mir-python", + "numpy", + "thermofeel", +] + +[dependency-groups] +dev = [ + "prek>=0.4.4", + "pytest>=9.0.3", + "ty>=0.0.44", +] + +[tool.setuptools] +include-package-data = true +zip-safe = false + +[tool.setuptools.packages.find] +where = [ "src" ] + +[tool.setuptools_scm] +write_to = "src/ppruntime/_version.py" +write_to_template = '''# Do not change! Do not track in version control! +__version__ = "{version}" +''' +root = ".." +local_scheme = "no-local-version" +fallback_version = "0.0.0" + +[tool.setuptools_scm.tag] +prefix = "ppruntime-" +strict = true + +[tool.ruff] +lint.ignore = [ "E722", "E731", "E741" ] + +[tool.isort] +profile = "black" + +[tool.pytest.ini_options] +log_cli = true +testpaths = [ "tests/" ] diff --git a/pproc-runtime/src/ppruntime/__init__.py b/pproc-runtime/src/ppruntime/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/pproc-runtime/src/ppruntime/accumulation.py b/pproc-runtime/src/ppruntime/accumulation.py new file mode 100644 index 00000000..7dee1372 --- /dev/null +++ b/pproc-runtime/src/ppruntime/accumulation.py @@ -0,0 +1,20 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import array_api_compat +from earthkit.data import FieldList + +from ppruntime.utils import new_fieldlist + + +def difference_rate(*fields, factor: float = 1.0, metadata: dict = {}) -> FieldList: + if len(fields) not in [1, 2]: + raise ValueError("difference_rate expects 1 or 2 FieldList arguments") + xp = array_api_compat.array_namespace(fields[-1].values) + values = fields[-1].values + length = xp.asarray(fields[-1].metadata("step")) + if len(fields) != 1: + values = values - fields[0].values + length = length - xp.asarray(fields[0].metadata("step")) + return new_fieldlist(values / (factor * length), fields[-1].metadata(), metadata) diff --git a/pproc-runtime/src/ppruntime/io.py b/pproc-runtime/src/ppruntime/io.py new file mode 100644 index 00000000..1a58b6eb --- /dev/null +++ b/pproc-runtime/src/ppruntime/io.py @@ -0,0 +1,178 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import shutil +from io import BytesIO +from typing import Optional +import logging + +import mir +from earthkit.data import FieldList, settings +from earthkit.data.readers.grib.metadata import StandAloneGribMetadata +from earthkit.data.sources import from_source +from earthkit.data.sources.file import FileSource +from earthkit.data.sources.stream import StreamSource +from meters import ResourceMeter + +# Set cache policy to "temporary" to avoid "database is locked" errors when +# for wind when executing across multiple workers +settings.set("cache-policy", "temporary") + +logger = logging.getLogger(__name__) + + +def mir_job( + input: mir.MultiDimensionalGribFileInput, # type: ignore[ty:unresolved-attribute] + mir_options: dict, + cache: Optional[str] = None, +) -> FieldList: + # Convert vod2uv bool to string int + if "vod2uv" in mir_options: + mir_options["vod2uv"] = "1" if mir_options["vod2uv"] else "0" + job = mir.Job(**mir_options) # type: ignore[ty:unresolved-attribute] + stream = BytesIO() + job.execute(input, stream) + stream.seek(0) + if cache is None: + return StreamSource(stream, read_all=True).mutate().to_fieldlist() + + with open(cache, "wb") as o, stream as i: + shutil.copyfileobj(i, o) + return FileSource(cache).mutate() + + +def fdb_retrieve(request: dict, stream: bool = False, **kwargs) -> FieldList: + mir_options = request.pop("interpolate", None) + if mir_options is None: + return from_source("fdb", request, stream=stream, read_all=True, **kwargs) # type: ignore[ty:invalid-return-type] + + if mir_options.get("vod2uv", False): + stream = False + + reader: FieldList = from_source( + "fdb", request, stream=stream, read_all=False, **kwargs + ) # type: ignore[ty:invalid-assignment] + if stream: + return mir_job(reader._source._stream, mir_options) # type: ignore[ty:unresolved-attribute] + + if mir_options.get("vod2uv", False): + if len(request["param"]) != 2: + raise ValueError("Wind vod2uv requires two parameters") + inp = mir.MultiDimensionalGribFileInput(reader.path, 2) # type: ignore[ty:unresolved-attribute] + else: + inp = mir.GribFileInput(reader.path) # type: ignore[ty:unresolved-attribute] + return mir_job(inp, mir_options) + + +def mars_retrieve(request: dict, **kwargs) -> FieldList: + mir_options = request.pop("interpolate", None) + cache = request.pop("cache", None) + cache_path = None if cache is None else cache.format_map(request) + ds: FieldList = from_source("mars", request, **kwargs) # type: ignore[ty:invalid-assignment] + if mir_options is None: + return ds + + if mir_options.get("vod2uv", False): + if len(request["param"]) != 2: + raise ValueError("Wind vod2uv requires two parameters") + inp = mir.MultiDimensionalGribFileInput(ds.path, 2) # type: ignore[ty:unresolved-attribute] + else: + inp = mir.GribFileInput(ds.path) # type: ignore[ty:unresolved-attribute] + return mir_job(inp, mir_options, cache_path) + + +def _transform_steps(steps, step_type: type = str): + if isinstance(steps, (int, str)): + steps = [steps] + return list(map(step_type, steps)) + + +def _transform_request(request: dict, step_type: type = str): + try: + paramId = int(request["param"]) + del request["param"] + request["paramId"] = paramId + except ValueError: + pass + if request.get("date", None) is not None: + request["date"] = int(request["date"]) + if request.get("time", None) is not None: + time = int(request["time"]) + request["time"] = time if time % 100 == 0 else time * 100 + if request.get("step", None) is not None: + request["step"] = _transform_steps(request["step"], step_type) + return request + + +def file_retrieve(name: str, request: dict, **kwargs) -> FieldList: + mir_options = request.pop("interpolate", None) + if mir_options is not None: + raise NotImplementedError() + file_ds: FieldList = from_source(name, **kwargs) # type: ignore[ty:invalid-assignment] + if len(request) > 0: + treq = _transform_request(request) + ds = file_ds.sel(treq) + if len(ds) == 0: + try: + treq = _transform_request(request, int) + ds = file_ds.sel(treq) + except ValueError: + pass + return ds + return file_ds + + +def retrieve( + sources: list[dict], + requests: list[dict], + dtype: Optional[str] = None, +) -> FieldList: + ds: FieldList = from_source("empty") # type: ignore + for request in requests: + with ResourceMeter(f"Retrieve {request}"): + for source in sources: + if isinstance(source, str): + source = {"name": source} + name = source.pop("name") + try: + logger.debug(f"Trying source {name}") + if name == "fdb": + source_ds = fdb_retrieve(request=request, **source) + elif name == "mars": + source_ds = mars_retrieve(request=request, **source) + elif name in ["file", "file-pattern"]: + source_ds = file_retrieve( + name, request=request, **source + ).order_by("paramId") + else: + raise NotImplementedError(f"Source {source} not supported.") + assert ( + len(source_ds) > 0 + ), f"No data retrieved from {source} for request {request}" + break + except AssertionError: + logger.info( + f"No data retrieved from source {source} for request {request}" + ) + continue + if len(source_ds) == 0: + raise ValueError( + f"No data retrieved from sources {sources} for request {request}" + ) + ds += FieldList.from_array( + source_ds.to_array(flatten=True, dtype=dtype), + [ + StandAloneGribMetadata(metadata._handle) + for metadata in source_ds.metadata() + ], + ) + return ds + + +def write(data: FieldList, name: str, **kwargs): + if name == "null": + return + + with ResourceMeter(f"Write {data.ls(namespace='mars')} to {name}"): + data.to_target(target=name, **kwargs) diff --git a/pproc-runtime/src/ppruntime/metadata.py b/pproc-runtime/src/ppruntime/metadata.py new file mode 100644 index 00000000..2b80c264 --- /dev/null +++ b/pproc-runtime/src/ppruntime/metadata.py @@ -0,0 +1,146 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from typing import Optional + + +from earthkit.data import FieldList + + +def resolve_metadata(metadata: Optional[dict]) -> dict: + return metadata if metadata is not None else {} + + +def extreme(clim: FieldList, ens: FieldList, metadata: dict) -> dict: + edition = metadata.get("edition", ens[0].metadata().get("edition", 1)) + clim_edition = clim[0].metadata().get("edition", 1) + ret = {} + if edition == 1 and clim_edition == 1: + # set clim keys + clim_keys = [ + "versionNumberOfExperimentalSuite", + "implementationDateOfModelCycle", + "numberOfReforecastYearsInModelClimate", + "numberOfDaysInClimateSamplingWindow", + "sampleSizeOfModelClimate", + "versionOfModelClimate", + ] + for key in clim_keys: + ret[key] = clim[0].metadata()[key] + + # set fc keys + fc_keys = [ + "date", + "subCentre", + "totalNumber", + ] + for key in fc_keys: + ret[key] = ens[0].metadata()[key] + elif edition == 2 and clim_edition == 2: + clim_keys = [ + "typeOfReferenceDataset", + "yearOfStartOfReferencePeriod", + "dayOfStartOfReferencePeriod", + "monthOfStartOfReferencePeriod", + "hourOfStartOfReferencePeriod", + "minuteOfStartOfReferencePeriod", + "secondOfStartOfReferencePeriod", + "sampleSizeOfReferencePeriod", + "numberOfReferencePeriodTimeRanges", + "typeOfStatisticalProcessingForTimeRangeForReferencePeriod", + "indicatorOfUnitForTimeRangeForReferencePeriod", + "lengthOfTimeRangeForReferencePeriod", + ] + ret.update( + { + "productDefinitionTemplateNumber": 105, + **{key: clim[0].metadata()[key] for key in clim_keys}, + } + ) + else: + raise Exception( + f"Unsupported GRIB edition {edition} and clim edition {clim_edition}" + ) + return ret + + +def efi(ens: FieldList, clim: FieldList, metadata: dict) -> dict: + ret = extreme(ens, clim, metadata) + edition = metadata.get("edition", ens[0].metadata().get("edition", 1)) + if edition not in [1, 2]: + raise Exception(f"Unsupported GRIB edition {edition}") + + if len(ens) == 1 and ens.metadata()[0].get("type") in ["cf", "fc"]: + ret["marsType"] = 28 + if edition == 1: + ret["efiOrder"] = 0 + ret["totalNumber"] = 1 + ret["number"] = 0 + else: + ret.update( + {"typeOfRelationToReferenceDataset": 20, "typeOfProcessedData": 3} + ) + else: + ret["marsType"] = 27 + if edition == 1: + ret["efiOrder"] = 0 + ret["number"] = 0 + else: + ret.update( + {"typeOfRelationToReferenceDataset": 20, "typeOfProcessedData": 5} + ) + return ret + + +def sot(ens: FieldList, clim: FieldList, metadata: dict, number: int) -> dict: + ret = extreme(ens, clim, metadata) + ret["marsType"] = 38 + + if number == 90: + efi_order = 99 + elif number == 10: + efi_order = 1 + else: + raise Exception( + f"SOT value '{number}' not supported in template! Only accepting 10 and 90" + ) + edition = metadata.get("edition", ens[0].metadata().get("edition", 1)) + if edition == 1: + ret["number"] = sot + ret["efiOrder"] = efi_order + elif edition == 2: + ret.update( + { + "typeOfRelationToReferenceDataset": 21, + "typeOfProcessedData": 5, + "numberOfAdditionalParametersForReferencePeriod": 2, + "scaleFactorOfAdditionalParameterForReferencePeriod": [0, 0], + "scaledValueOfAdditionalParameterForReferencePeriod": [sot, efi_order], + } + ) + else: + raise Exception(f"Unsupported GRIB edition {edition}") + return ret + + +def extract(fields: FieldList, keys: list[str]) -> dict: + return {key: fields.metadata()[0].get(key) for key in keys} + + +def quantiles( + ens: FieldList, metadata: dict, pert_number: int, total_number: int +) -> dict: + edition = metadata.get("edition", ens[0].metadata().get("edition", 1)) + if edition == 1: + return { + "totalNumber": total_number, + "perturbationNumber": pert_number, + } + return { + "productDefinitionTemplateNumber": metadata.get( + "productDefinitionTemplateNumber", 86 + ), + "totalNumberOfQuantiles": total_number, + "quantileValue": pert_number, + } diff --git a/pproc-runtime/src/ppruntime/stats.py b/pproc-runtime/src/ppruntime/stats.py new file mode 100644 index 00000000..1a4c0861 --- /dev/null +++ b/pproc-runtime/src/ppruntime/stats.py @@ -0,0 +1,120 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import logging +from typing import Optional, Literal +import array_api_compat +from earthkit.data import FieldList +from earthkit.meteo.extreme import array as extreme +from earthkit.meteo.stats import array as stats +from meters import metered + +from ppruntime.metadata import resolve_metadata +from ppruntime import metadata as ppmetadata +from ppruntime.utils import new_fieldlist + + +logger = logging.getLogger(__name__) + + +Comparisons = Literal["<", ">", "<=", ">=", "==", "!="] + + +def comp_str2func(array_module, comparison: str): + if comparison == "<=": + return array_module.less_equal + if comparison == "<": + return array_module.less + if comparison == ">=": + return array_module.greater_equal + return array_module.greater + + +@metered("mask", out=logger.debug) +def mask( + arr: FieldList, + lower_comparison: Comparisons, + lower_value: float, + upper_comparison: Optional[Comparisons] = None, + upper_value: Optional[float] = None, + *, + metadata: Optional[dict] = None, +) -> FieldList: + xp = array_api_compat.array_namespace(arr.values) + # Find all locations where nan appears as an ensemble value + is_nan = xp.isnan(arr.values) + thresh = comp_str2func(xp, lower_comparison)(arr.values, lower_value) + if upper_comparison is not None: + thresh = thresh & comp_str2func(xp, upper_comparison)(arr.values, upper_value) + res = xp.where(is_nan, xp.nan, thresh) + return new_fieldlist(res, arr.metadata(), resolve_metadata(metadata)) + + +def logical_and( + arr1: FieldList, + arr2: FieldList, +) -> FieldList: + xp = array_api_compat.array_namespace(arr1.values, arr2.values) + is_nan = xp.isnan(arr1.values) | xp.isnan(arr2.values) + res = xp.where(is_nan, xp.nan, arr1.values & arr2.values) + return new_fieldlist(res, arr1.metadata()) + + +@metered("efi", out=logger.debug) +def efi( + clim: FieldList, + ens: FieldList, + eps: float, + *, + metadata: Optional[dict] = None, +) -> FieldList: + res = extreme.efi(clim.values, ens.values, eps) + resolved_metadata = resolve_metadata(metadata) + return new_fieldlist( + res, + [ens[0].metadata()], + {**resolved_metadata, **ppmetadata.efi(clim, ens, resolved_metadata)}, + ) + + +@metered("sot", out=logger.debug) +def sot( + clim: FieldList, + ens: FieldList, + number: int, + eps: float, + *, + metadata: Optional[dict] = None, +) -> FieldList: + res = extreme.sot(clim.values, ens.values, number, eps) + resolved_metadata = resolve_metadata(metadata) + return new_fieldlist( + res, + [ens[0].metadata()], + { + **resolved_metadata, + **ppmetadata.sot(clim, ens, resolved_metadata, number), + }, + ) + + +@metered("quantiles", out=logger.debug) +def quantiles( + ens: FieldList, + q_number: int, + total_number: int, + *, + metadata: Optional[dict] = None, +) -> FieldList: + quantile = q_number / total_number + res = list(stats.iter_quantiles(ens.values, [quantile], method="numpy"))[0] + resolved_metadata = resolve_metadata(metadata) + return new_fieldlist( + res, + [ens[0].metadata()], + { + **resolved_metadata, + **ppmetadata.quantiles(ens, resolved_metadata, q_number, total_number), + }, + ) diff --git a/pproc-runtime/src/ppruntime/thermal_indices.py b/pproc-runtime/src/ppruntime/thermal_indices.py new file mode 100644 index 00000000..eed44498 --- /dev/null +++ b/pproc-runtime/src/ppruntime/thermal_indices.py @@ -0,0 +1,276 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from earthkit.data import FieldList +from earthkit.data.core.metadata import Metadata as ekMetadata +import earthkit.meteo.solar +import thermofeel +from meters import metered +import numpy as np +import logging +from datetime import timedelta +from typing import Optional + +from ppruntime.thermo.helpers import ( + compute_ehPa, + find_utci_missing_values, + get_datetime, + latlon, + step_interval, + validate_utci, + create_output, +) +from ppruntime.metadata import resolve_metadata + +logger = logging.getLogger(__name__) + + +def metadata_intensity(fields: FieldList) -> list[ekMetadata]: + return fields.sel(paramId=167).metadata() + + +def metadata_accumulation(fields: FieldList) -> list[ekMetadata]: + return fields.sel(paramId=228021).metadata() + + +def field_values(fields: FieldList, params: list[int]): + shape = None + out_values = [] + for param in params: + selected = fields.sel(paramId=param) + if len(selected) == 0: + raise ValueError( + f"Field {param} not found in fields: \n {fields.ls(namespace='mars')}" + ) + if shape is None: + shape = selected.values.shape + assert ( + shape == selected.values.shape + ), f"Shape mismatch for {param} {shape} != {selected.values.shape}" + out_values.append(selected.to_array()) + return out_values + + +@metered("cossza", out=logger.debug) +def calc_cossza(*fields: FieldList, metadata: Optional[dict] = None) -> FieldList: + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_cossza: {summed_fields.ls(namespace='mars')}") + lats, lons = latlon(summed_fields) + + basetime, validtime = get_datetime(summed_fields) + + delta = step_interval(summed_fields) + + dtbegin = validtime - timedelta(hours=delta) + dtend = validtime + + cossza = earthkit.meteo.solar.cos_solar_zenith_angle_integrated( + latitudes=lats, + longitudes=lons, + begin_date=dtbegin, + end_date=dtend, + integration_order=2, + ) + + return create_output( + cossza, + metadata_intensity(summed_fields)[:1], + {**resolve_metadata(metadata)}, + ) + + +@metered("hmdx", out=logger.debug) +def calc_hmdx(*fields: FieldList, metadata: Optional[dict] = None) -> FieldList: + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_hmdx: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 168]) + hmdx = thermofeel.calculate_humidex(*inputs) + return create_output( + hmdx, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("rhp", out=logger.debug) +def calc_rhp(*fields: FieldList, metadata: Optional[dict] = None) -> FieldList: + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_rhp: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 168]) + rhp = thermofeel.calculate_relative_humidity_percent(*inputs) + return create_output( + rhp, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("heatx", out=logger.debug) +def calc_heatx(*fields: FieldList, metadata: Optional[dict] = None) -> FieldList: + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_heatx: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 168]) + heatx = thermofeel.calculate_heat_index_adjusted(*inputs) + return create_output( + heatx, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("dsrp", out=logger.debug) +def calc_dsrp(*fields: FieldList, metadata: Optional[dict] = None): + """ + In the absence of dsrp, approximate it with fdir and cossza. + Note this introduces some amount of error as cossza approaches zero + """ + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_dsrp: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [228021, 214001]) + dsrp = thermofeel.approximate_dsrp(*inputs) + return create_output( + dsrp, + metadata_accumulation(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("utci", out=logger.debug) +def calc_utci(*fields: FieldList, metadata: Optional[dict] = None, validate=True): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_utci: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 168, 207, 261002]) + + ehPa = compute_ehPa(inputs[0], inputs[1]) + utci = thermofeel.calculate_utci( + t2_k=inputs[0], va=inputs[2], mrt=inputs[3], ehPa=ehPa + ) # Kelvin + + for index in range(len(utci)): + missing = find_utci_missing_values( + inputs[0][index], + inputs[2][index], + inputs[3][index], + ehPa[index], + utci[index], + ) + + if validate: + lats, lons = latlon(summed_fields) + validate_utci(utci[index], missing, lats, lons) + utci[index][missing] = np.nan + + return create_output( + utci, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("wbgt", out=logger.debug) +def calc_wbgt(*fields: FieldList, metadata: Optional[dict] = None): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_wbgt: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 261002, 207, 168]) + wbgt = thermofeel.calculate_wbgt(*inputs) + return create_output( + wbgt, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("gt", out=logger.debug) +def calc_gt(*fields: FieldList, metadata: Optional[dict] = None): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_gt: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 261002, 207]) + + gt = thermofeel.calculate_bgt(*inputs) + + return create_output( + gt, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("wbt", out=logger.debug) +def calc_wbt(*fields: FieldList, metadata: Optional[dict] = None): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_wbt: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 260242]) + wbt = thermofeel.calculate_wbt(*inputs) + return create_output( + wbt, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("nefft", out=logger.debug) +def calc_nefft(*fields: FieldList, metadata: Optional[dict] = None): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_nefft: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 207, 260242]) + nefft = thermofeel.calculate_normal_effective_temperature(*inputs) + return create_output( + nefft, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("wcf", out=logger.debug) +def calc_wcf(*fields: FieldList, metadata: Optional[dict] = None): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_wcf: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 207]) + wcf = thermofeel.calculate_wind_chill(*inputs) + return create_output( + wcf, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("aptmp", out=logger.debug) +def calc_aptmp(*fields: FieldList, metadata: Optional[dict] = None): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_aptmp: {summed_fields.ls(namespace='mars')}") + inputs = field_values(summed_fields, [167, 207, 260242]) + aptmp = thermofeel.calculate_apparent_temperature(*inputs) + return create_output( + aptmp, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) + + +@metered("mrt", out=logger.debug) +def calc_mrt(*fields: FieldList, metadata: Optional[dict] = None): + summed_fields: FieldList = sum(fields[1:], fields[0]) + logger.debug(f"calc_mrt: {summed_fields.ls(namespace='mars')}") + ssrd, ssr, dsrp, strd, fdir, strr, cossza = field_values( + summed_fields, [169, 176, 47, 175, 228021, 177, 214001] + ) + + delta = step_interval(summed_fields) + seconds_in_time_step = delta * 3600 # steps are in hours + + f = 1.0 / float(seconds_in_time_step) + + # remove negative values from deaccumulated solar fields + for v in ssrd, fdir, strd, ssr: + v[v < 0] = 0 + + mrt = thermofeel.calculate_mean_radiant_temperature( + ssrd * f, ssr * f, dsrp * f, strd * f, fdir * f, strr * f, cossza + ) # Kelvin + + return create_output( + mrt, + metadata_intensity(summed_fields), + {**resolve_metadata(metadata)}, + ) diff --git a/pproc-runtime/src/ppruntime/thermo/__init__.py b/pproc-runtime/src/ppruntime/thermo/__init__.py new file mode 100644 index 00000000..96793c76 --- /dev/null +++ b/pproc-runtime/src/ppruntime/thermo/__init__.py @@ -0,0 +1,3 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 diff --git a/pproc-runtime/src/ppruntime/thermo/helpers.py b/pproc-runtime/src/ppruntime/thermo/helpers.py new file mode 100644 index 00000000..08ff8421 --- /dev/null +++ b/pproc-runtime/src/ppruntime/thermo/helpers.py @@ -0,0 +1,175 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import earthkit.data +from earthkit.data.core.metadata import Metadata +import logging +import numpy as np +import thermofeel +from meters import metered + +logger = logging.getLogger(__name__) + +# Constants +UTCI_MIN_VALUE = thermofeel.celsius_to_kelvin(-80) +UTCI_MAX_VALUE = thermofeel.celsius_to_kelvin(90) + +MRT_DIFF_HIGH = 150 +MRT_DIFF_LOW = -30 + +# parameter to units +units = { + "cossza": "", + "2t": "K", + "2d": "K", + "wcf": "K", + "aptmp": "K", + "hmdx": "K", + "nefft": "K", + "wbgt": "K", + "wbt": "K", + "gt": "K", + "2r": "%", + "10si": "m/s", + "mrt": "K", + "utci": "K", + "heatx": "K", + "dsrp": "W/m2", + "ssrd": "W/m2", + "ssr": "W/m2", + "fdir": "W/m2", + "strd": "W/m2", + "str": "W/m2", +} + + +def compute_ehPa_(rh_pc, svp): + return svp * rh_pc * 0.01 # / 100.0 + + +@metered("ehPa", out=logger.debug) +def compute_ehPa(t2m, t2d): + rh_pc = thermofeel.calculate_relative_humidity_percent(t2m, t2d) + svp = thermofeel.calculate_saturation_vapour_pressure(t2m) + ehPa = compute_ehPa_(rh_pc, svp) + return ehPa + + +def find_utci_missing_values(t2m, va, mrt, ehPa, utci, print_misses=True): + e_mrt = np.subtract(mrt, t2m) + + misses = np.where(t2m >= thermofeel.celsius_to_kelvin(70)) + nt2high = len(misses[0]) + t = np.where(t2m <= thermofeel.celsius_to_kelvin(-70)) + nt2low = len(t[0]) + misses = np.union1d(t, misses) + + t = np.where(va >= 25.0) # 90kph + nhighwind = len(t[0]) + misses = np.union1d(t, misses) + + t = np.where(ehPa > 50.0) + nehpa = len(t[0]) + misses = np.union1d(t, misses) + + t = np.where(e_mrt >= MRT_DIFF_HIGH) + ndiffmrt = len(t[0]) + misses = np.union1d(t, misses) + + t = np.where(e_mrt <= MRT_DIFF_LOW) + ndiffmrtneg = len(t[0]) + misses = np.union1d(t, misses) + + t = np.where(np.isnan(utci)) + nnan = len(t[0]) + misses = np.union1d(t, misses) + + nmisses = len(misses) + + if print_misses: + print( + f"UTCI nmisses {nmisses} NANs {nnan} T2>70C {nt2high} T2<-70 {nt2low} highwind {nhighwind}" + + f"nehpa {nehpa} MRT-T2>{MRT_DIFF_HIGH} {ndiffmrt} MRT-T2<{MRT_DIFF_LOW} {ndiffmrtneg}" + ) + + return misses + + +def validate_utci(utci, misses, lats, lons): + out_of_bounds = 0 + nans = 0 + for i in range(len(utci)): + v = utci[i] + if v < UTCI_MIN_VALUE or v > UTCI_MAX_VALUE: + out_of_bounds += 1 + logger.info("UTCI [", i, "] = ", utci[i], " : lat/lon ", lats[i], lons[i]) + if np.isnan(v): + nans += 1 + logger.info("UTCI [", i, "] = ", utci[i], " : lat/lon ", lats[i], lons[i]) + + nmisses = len(misses) + if nmisses > 0 or out_of_bounds > 0 or nans > 0: + logger.info( + f"UTCI => nmisses {nmisses} out_of_bounds {out_of_bounds} NANs {nans}" + ) + + +def get_datetime(fields: earthkit.data.FieldList): + dt = fields[0].datetime() + base_time = dt["base_time"] + valid_time = dt["valid_time"] + assert all( + x == valid_time for x in fields.datetime()["valid_time"] + ), ( + f"Obtained different valid times {[x for x in fields.datetime()['valid_time']]}" + ) # verify valid time all same + return base_time, valid_time + + +def latlon(fields: earthkit.data.FieldList): + latlon = fields[0].to_latlon(flatten=True) + lat = latlon["lat"] + lon = latlon["lon"] + assert lat.size == lon.size + assert fields[0].values.size == lat.size + return lat, lon + + +def field_values(fields: earthkit.data.FieldList, param: str) -> np.ndarray: + sel = fields.sel(param=param) + if len(sel) == 0: + raise ValueError( + f"Field {param} not found in fields {fields.ls(namespace='mars')}" + ) + return sel.to_array() + + +def check_field_sizes(fields: earthkit.data.FieldList): + all(f.values.shape == fields[0].values.shape for f in fields) + + +def step_interval(fields) -> int: + # Derive step interval from de-accumulated fields + accum_field = fields.sel(stepType="diff") + if len(accum_field) == 0: + raise ValueError( + f"No accumulation fields found in {fields.ls(namespace='mars')}, can not derive step interval" + ) + delta = ( + accum_field[0].metadata()["endStep"] - accum_field[0].metadata()["startStep"] + ) + check = [ + delta == (f.metadata()["endStep"] - f.metadata()["startStep"]) + for f in accum_field + ] + if not all(check): + raise ValueError( + f"Step intervals are not consistent for accumulated fields {accum_field.ls()}" + ) + return delta + + +def create_output(values: np.ndarray, template: list[Metadata], metadata: dict): + template = [x.override(**metadata) for x in template] + return earthkit.data.FieldList.from_array(values, template) diff --git a/pproc-runtime/src/ppruntime/utils.py b/pproc-runtime/src/ppruntime/utils.py new file mode 100644 index 00000000..5d3571b3 --- /dev/null +++ b/pproc-runtime/src/ppruntime/utils.py @@ -0,0 +1,35 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +from earthkit.data import FieldList +from earthkit.data.core.metadata import Metadata as ekdMetadata + + +def standardise_output(data): + # Also, nest the data to avoid problems with not finding geography attribute + if len(data.shape) == 1: + data = data.reshape((1, *data.shape)) + assert len(data.shape) == 2 + return data + + +def new_fieldlist(data, metadata: list[ekdMetadata], overrides: dict = {}): + if len(overrides) > 0: + try: + new_metadata = [ + metadata[x].override(overrides) for x in range(len(metadata)) + ] + return FieldList.from_array( + standardise_output(data), + new_metadata, + ) + except Exception as e: + print( + "Error setting metadata", + overrides, + "On data with:", + list(map(lambda x: x.dump(), metadata)), + ) + print(e) + return FieldList.from_array(standardise_output(data), metadata) diff --git a/pproc-runtime/tests/conftest.py b/pproc-runtime/tests/conftest.py new file mode 100644 index 00000000..585176c3 --- /dev/null +++ b/pproc-runtime/tests/conftest.py @@ -0,0 +1,93 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +import requests +from typing import List, Iterator +import pytest +import shutil +import tempfile + +import eccodes +import pyfdb + +TEST_DIR = os.path.dirname(os.path.realpath(__file__)) +DATA_DIR = os.path.join(os.path.dirname(os.path.realpath(__file__)), "data") +NEXUS = "https://sites.ecmwf.int/repository/pproc/test-data" +SCHEMA = os.path.join(TEST_DIR, "schema.yaml") + + +def download_test_data( + test_files: List[str], dir_url: str = NEXUS, local_dir: str = DATA_DIR +) -> List[str]: + local_files = [] + for file in test_files: + if not os.path.exists(local_dir): + os.makedirs(local_dir) + nexus_url = f"{dir_url}/{file}" + local_file_path = os.path.join(local_dir, file) + + if not os.path.exists(local_file_path): + session = requests.Session() + response = session.get(nexus_url) + if response.status_code != 200: + raise Exception( + f"Error {response.status_code} downloading data file {file}" + ) + with open(local_file_path, "wb") as f: + f.write(response.content) + local_files.append(local_file_path) + return local_files + + +@pytest.fixture(scope="session") +def download_all_test_data(): + download_test_data( + [ + "test_2t_12.grib", + ], + os.path.join(NEXUS, "pproc-runtime"), + ) + download_test_data( + [ + "wind.grib", + ], + os.path.join(NEXUS, "test-data"), + ) + + +@pytest.fixture(scope="session") +def fdb(download_all_test_data) -> Iterator[pyfdb.FDB]: + tmpdir = tempfile.mkdtemp() + print("Using temporary directory", tmpdir) + os.makedirs(f"{tmpdir}/etc/fdb") + os.mkdir(f"{tmpdir}/fdb") + shutil.copyfile(f"{TEST_DIR}/templates/fdb/schema", f"{tmpdir}/etc/fdb/schema") + with open(f"{tmpdir}/etc/fdb/config.yaml", "w") as f: + f.write( + f""" +--- +type: local +engine: toc +schema: "{tmpdir}/etc/fdb/schema" +spaces: +- roots: + - path: {tmpdir}/fdb +""" + ) + os.environ["FDB_HOME"] = str(tmpdir) + os.environ["FDB_HANDLE_LUSTRE_STRIPE"] = "0" + temp_fdb = pyfdb.FDB() + for filename in [ + "test_2t_12.grib", + "wind.grib", + ]: + filepath = os.path.join(DATA_DIR, filename) + if os.path.isfile(filepath): + reader = eccodes.FileReader(filepath) + for msg in reader: + temp_fdb.archive(msg.get_buffer()) + temp_fdb.flush() + yield temp_fdb + shutil.rmtree(tmpdir) diff --git a/pproc-runtime/tests/templates/fdb/schema b/pproc-runtime/tests/templates/fdb/schema new file mode 100644 index 00000000..0eb23544 --- /dev/null +++ b/pproc-runtime/tests/templates/fdb/schema @@ -0,0 +1,588 @@ + +# * Format of the rules is: + +# [a1, a2, a3 ...[b1, b2, b3... [c1, c2, c3...]]] + +# - The first level (a) defines which attributes are used to name the top level directory +# - The second level (b) defines which attributes are used to name the data files +# - The third level (c) defines which attributes are used as index keys + +# * Rules can be grouped + +# [a1, a2, a3 ... +# [b1, b2, b3... [c1, c2, c3...]] +# [B1, B2, B3... [C1, C2, C3...]] +# ] + +# * A list of values can be given for an attribute +# [ ..., stream=enfo/efov, ... ] +# This will be used when matching rules. + +# * Attributes can be typed +# Globally, at the begining of this file: + +# refdate: Date; + +# or in the context of a rule: +# [type=cl, ... [date:ClimateMonth, ...]] + +# Typing attributes is done when the user's requests or the GRIB values need to be modified before directories, files and indexes are created. For example, ClimateMonth will transform 2010-04-01 to 'may' internally. + +# * Attributes can be optional +# [ step, levelist?, param ] +# They will be replaced internally by an empty value. It is also posiible to provide a default subtitution value: e.g. [domain?g] will consider the domain to be 'g' if missing. + +# * Attributes can be removed: +# [grid-] +# This is useful to remove attributes present in the GRIB that should not be ignored + +# * Rules are matched: + +# - If the attributes are present in the GRIB/Request, or marked optional or ignored +# - If a list of possible value is provided, one of them must match, for example +# [ class, expver, stream=enfo/efov, date, time, domain ] +# will match either stream=enfo or stream=efov, all other attributes will be matched if they exist in the GRIB or user's request + +# * On archive: +# - Attributes are extracted from the GRIB (namespace 'mars'), possibly modified by the attribute type +# - Only the first rule is used, so order is important +# - All GRIB attributes must be used by the rules, otherwise an error is raised + +# * On retrieve: +# - Attributes are extracted from the user's request, possibly modified by the attribute type (e.g. for handling of U/V) +# - All the matching rules are considered +# - Only attributes listed in the rules are used to extract values from the user's request + + +# Default types + +param: Param; +step: Step; +date: Date; +hdate: Date; +refdate: Date; +latitude: Double; +longitude: Double; +levelist: Double; +grid: Grid; +expver: Expver; + +time: Time; +fcmonth: Integer; + +number: Integer; +frequency: Integer; +direction: Integer; +channel: Integer; + +instrument: Integer; +ident: Integer; + +diagnostic: Integer; +iteration: Integer; +system: Integer; +method: Integer; + +# ??????? + +# reference: Integer; +# fcperiod: Integer; + +# opttime: Integer; +# leadtime: Integer; + +# quantile: ?????? +# range: ?????? + +# band: Integer; + + +######################################################## +# These rules must be first, otherwise fields of These +# classes will be index with the default rule for oper +[ class=ti/s2, expver, stream, date, time, model + [ origin, type, levtype, hdate? + [ step, number?, levelist?, param ]] +] + +[ class=ms, expver, stream, date, time, country=de + [ domain, type, levtype, dbase, rki, rty, ty + [ step, levelist?, param ]] +] + +[ class=ms, expver, stream, date, time, country=it + [ domain, type, levtype, model, bcmodel, icmodel:First3 + [ step, levelist?, param ] + ] +] + +[ class=el, expver, stream, date, time, domain + [ origin, type, levtype + [ step, levelist?, param ]] +] + +######################################################## +# The are the rules matching most of the fields +# oper/dcda +[ class, expver, stream=oper/dcda/scda, date, time, domain? + + [ type=im/sim + [ step?, ident, instrument, channel ]] + + [ type=ssd + [ step, param, ident, instrument, channel ]] + + [ type=4i, levtype + [ step, iteration, levelist, param ]] + + [ type=me, levtype + [ step, number, levelist?, param ]] + + [ type=ef, levtype + [ step, levelist?, param, channel? ]] + + [ type=ofb/mfb + [ obsgroup, reportype ]] + + [ type, levtype + [ step, levelist?, param ]] + +] + +# dcwv/scwv/wave +[ class, expver, stream=dcwv/scwv/wave, date, time, domain + [ type, levtype + [ step, param, frequency?, direction? ]]] + +# enfo +[ class, expver, stream=enfo/efov, date, time, domain + + [ type, levtype=dp, product?, section? + [ step, number?, levelist?, latitude?, longitude?, range?, param ]] + + [ type=tu, levtype, reference + [ step, number, levelist?, param ]] + + [ type, levtype + [ step, quantile?, number?, levelist?, param ]] + +] + +# waef/weov +[ class, expver, stream=waef/weov, date, time, domain + [ type, levtype + [ step, number?, param, frequency?, direction? ]] +] + +######################################################## +# enda +[ class, expver, stream=enda, date, time, domain + + [ type=ef/em/es/ses, levtype + [ step, number?, levelist?, param, channel? ]] + + [ type=ssd + [ step, number, param, ident, instrument, channel ]] + + + [ type, levtype + [ step, number?, levelist?, param ]] +] + +# ewda +[ class, expver, stream=ewda, date, time, domain + [ type, levtype + [ step, number?, param, frequency?, direction? ]] +] + + +######################################################## +# elda +[ class, expver, stream=elda, date, time, domain? + + [ type=ofb/mfb + [ obsgroup, reportype ]] + + [ type, levtype, anoffset + [ step, number?, levelist?, iteration?, param, channel? ]] +] + +# ewda +[ class, expver, stream=ewla, date, time, domain + [ type, levtype, anoffset + [ step, number?, param, frequency?, direction? ]] +] + +######################################################## +# elda +[ class, expver, stream=lwda, date, time, domain? + + [ type=ssd, anoffset + [ step, param, ident, instrument, channel ]] + + [type=me, levtype, anoffset + [ number, step, levelist?, param]] + + [ type=4i, levtype, anoffset + [ step, iteration, levelist, param ]] + + [ type=ofb/mfb + [ obsgroup, reportype ]] + + [ type, levtype, anoffset + [ step, levelist?, param]] +] + +# ewda +[ class, expver, stream=lwwv, date, time, domain + [ type, levtype, anoffset + [ step, param, frequency?, direction? ]] +] +######################################################## +# amap +[ class, expver, stream=amap, date, time, domain + [ type, levtype, origin + [ step, levelist?, param ]]] + +# maed +[ class, expver, stream=maed, date, time, domain + [ type, levtype, origin + [ step, levelist?, param ]]] + +# mawv +[ class, expver, stream=mawv, date, time, domain + [ type, levtype, origin + [ step, param, frequency?, direction? ]]] + +# cher +[ class, expver, stream=cher, date, time, domain + [ type, levtype + [ step, levelist, param ]]] + + +# efhc +[ class, expver, stream=efhc, refdate, time, domain + [ type, levtype, date + [ step, number?, levelist?, param ]]] + +# efho +[ class, expver, stream=efho, date, time, domain + [ type, levtype, hdate + [ step, number?, levelist?, param ]]] + + +# efhs +[ class, expver, stream=efhs, date, time, domain + [ type, levtype + [ step, quantile?, number?, levelist?, param ]]] + +# wehs +[ class, expver, stream=wehs, date, time, domain + [ type, levtype + [ step, quantile?, number?, levelist?, param ]]] + +# kwbc +[ class, expver, stream=kwbc, date, time, domain + [ type, levtype + [ step, number?, levelist?, param ]]] + +# ehmm +[ class, expver, stream=ehmm, date, time, domain + [ type, levtype, hdate + [ fcmonth, levelist?, param ]]] + + +# ammc/cwao/edzw/egrr/lfpw/rjtd/toga +[ class, expver, stream=ammc/cwao/edzw/egrr/lfpw/rjtd/toga/fgge, date, time, domain + [ type, levtype + [ step, levelist?, param ]]] + +######################################################################## + +# enfh +[ class, expver, stream=enfh, date, time, domain + + [ type, levtype=dp, hdate, product?, section? + [ step, number?, levelist?, latitude?, longitude?, range?, param ]] + + [ type, levtype, hdate + [ step, number?, levelist?, param ]] +] + +# enwh +[ class, expver, stream=enwh, date, time, domain + [ type, levtype, hdate + [ step, number?, param, frequency?, direction? ]] +] + +######################################################################## +# sens +[ class, expver, stream=sens, date, time, domain + [ type, levtype + [ step, diagnostic, iteration, levelist?, param ]]] + +######################################################################## +# esmm +[ class, expver, stream=esmm, date, time, domain + [ type, levtype + [ fcmonth, levelist?, param ]]] +# ewhc +[ class, expver, stream=ewhc, refdate, time, domain + [ type, levtype, date + [ step, number?, param, frequency?, direction? ]]] + +######################################################################## +# ewho +[ class, expver, stream=ewho, date, time, domain + [ type, levtype, hdate + [ step, number?, param, frequency?, direction? ]]] + +# mfam +[ class, expver, stream=mfam, date, time, domain + + [ type=pb/pd, levtype, origin, system?, method + [ fcperiod, quantile, levelist?, param ]] + + [ type, levtype, origin, system?, method + [ fcperiod, number?, levelist?, param ]] + +] + +# mfhm +[ class, expver, stream=mfhm, refdate, time, domain + [ type, levtype, origin, system?, method, date? + [ fcperiod, number?, levelist?, param ]]] +# mfhw +[ class, expver, stream=mfhw, refdate, time, domain + [ type, levtype, origin, system?, method, date + [ step, number?, param ]]] +# mfwm +[ class, expver, stream=mfwm, date, time, domain + [ type, levtype, origin, system?, method + [ fcperiod, number, param ]]] +# mhwm +[ class, expver, stream=mhwm, refdate, time, domain + [ type, levtype, origin, system?, method, date + [ fcperiod, number, param ]]] + +# mmsf +[ class, expver, stream=mmsf, date, time, domain + + [ type, levtype=dp, origin, product, section, system?, method + [ step, number, levelist?, latitude?, longitude?, range?, param ]] + + [ type, levtype, origin, system?, method + [ step, number, levelist?, param ]] +] + +# mnfc +[ class, expver, stream=mnfc, date, time, domain + + [ type, levtype=dp, origin, product, section, system?, method + [ step, number?, levelist?, latitude?, longitude?, range?, param ]] + + [ type, levtype, origin, system?, method + [ step, number?, levelist?, param ]] +] + +# mnfh +[ class, expver, stream=mnfh, refdate, time, domain + [ type, levtype=dp, origin, product, section, system?, method, date + [ step, number?, levelist?, latitude?, longitude?, range?, param ]] + [ type, levtype, origin, system?, method, date? + [ step, number?, levelist?, param ]] +] + +# mnfm +[ class, expver, stream=mnfm, date, time, domain + [ type, levtype, origin, system?, method + [ fcperiod, number?, levelist?, param ]]] + +# mnfw +[ class, expver, stream=mnfw, date, time, domain + [ type, levtype, origin, system?, method + [ step, number?, param ]]] + +# ea/mnth +[ class=ea, expver, stream=mnth, date, domain + [ type, levtype + [ time, step?, levelist?, param ]]] + +# mnth +[ class, expver, stream=mnth, domain + [ type=cl, levtype + [ date: ClimateMonthly, time, levelist?, param ]] + [ type, levtype + [ date , time, step?, levelist?, param ]]] + +# mofc +[ class, expver, stream=mofc, date, time, domain + [ type, levtype=dp, product, section, system?, method + [ step, number?, levelist?, latitude?, longitude?, range?, param ]] + [ type, levtype, system?, method + [ step, number?, levelist?, param ]] +] + +# mofm +[ class, expver, stream=mofm, date, time, domain + [ type, levtype, system?, method + [ fcperiod, number, levelist?, param ]]] + +# mmsa/msmm +[ class, expver, stream=mmsa, date, time, domain + [ type, levtype, origin, system?, method + [ fcmonth, number?, levelist?, param ]]] + +[ class, expver, stream=msmm, date, time, domain + [ type, levtype, origin, system?, method + [ fcmonth, number?, levelist?, param ]]] + +# ocea +[ class, expver, stream=ocea, date, time, domain + [ type, levtype, product, section, system?, method + [ step, number, levelist?, latitude?, longitude?, range?, param ]] +] + +#=# seas +[ class, expver, stream=seas, date, time, domain + + [ type, levtype=dp, product, section, system?, method + [ step, number, levelist?, latitude?, longitude?, range?, param ]] + + [ type, levtype, system?, method + [ step, number, levelist?, param ]] +] + +# sfmm/smma +[ class, expver, stream=sfmm/smma, date, time, domain + [ type, levtype, system?, method + [ fcmonth, number?, levelist?, param ]]] + +# supd +[ class=od, expver, stream=supd, date, time, domain + [ type, levtype, origin?, grid + [ step, levelist?, param ]]] + +# For era +[ class, expver, stream=supd, date, time, domain + [ type, levtype, grid- # The minus sign is here to consume 'grid', but don't index it + [ step, levelist?, param ]]] + +# swmm +[ class, expver, stream=swmm, date, time, domain + [ type, levtype, system?, method + [ fcmonth, number, param ]]] + +# wamf +[ class, expver, stream=wamf, date, time, domain + [ type, levtype, system?, method + [ step, number?, param ]]] + +# ea/wamo +[ class=ea, expver, stream=wamo, date, domain + [ type, levtype + [ time, step?, param ]]] + +# wamo +[ class, expver, stream=wamo, domain + [ type=cl, levtype + [ date: ClimateMonthly, time, param ]] + [ type, levtype + [ date, time, step?, param ]]] + +# wamd +[ class, expver, stream=wamd, date, domain + [ type, levtype + [ param ]]] + +# wasf +[ class, expver, stream=wasf, date, time, domain + [ type, levtype, system?, method + [ step, number, param ]]] +# wmfm +[ class, expver, stream=wmfm, date, time, domain + [ type, levtype, system?, method + [ fcperiod, number, param ]]] + +# moda +[ class, expver, stream=moda, date, domain + [ type, levtype + [ levelist?, param ]]] + +# msdc/mdfa/msda +[ class, expver, stream=msdc/mdfa/msda, domain + [ type, levtype + [ date, time?, step?, levelist?, param ]]] + + + +# seap +[ class, expver, stream=seap, date, time, domain + [ type=sv/svar, levtype, origin, method? + [ step, leadtime, opttime, number, levelist?, param ]] + + [ type=ef, levtype, origin + [ step, levelist?, param, channel? ]] + + [ type, levtype, origin + [ step, levelist?, param ]] + + ] + +[ class, expver, stream=mmaf, date, time, domain + [ type, levtype, origin, system?, method + [ step, number, levelist?, param ]] +] + +[ class, expver, stream=mmam, date, time, domain + [ type, levtype, origin, system?, method + [ fcmonth, number, levelist?, param ]] +] + + +[ class, expver, stream=dacl, domain + [ type=pb, levtype + [ date: ClimateDaily, time, step, quantile, levelist?, param ]] + [ type, levtype + [ date: ClimateDaily, time, step, levelist?, param ]] + +] + +[ class, expver, stream=dacw, domain + [ type=pb, levtype + [ date: ClimateDaily, time, step, quantile, param ]] + [ type, levtype + [ date: ClimateDaily, time, step, param ]] + +] + +[ class, expver, stream=edmm/ewmm, date, time, domain + [ type=ssd + [ step, number, param, ident, instrument, channel ]] + [ type, levtype + [ step, number, levelist?, param ]] +] + +[ class, expver, stream=edmo/ewmo, date, domain + [ type, levtype + [ number, levelist?, param ]] +] + +# stream gfas +[ class=mc/rd, expver, stream=gfas, date, time, domain + [ type=ga, levtype + [ step, param ]] + + [ type=gsd + [ param, ident, instrument ]] + +] + +# class is e2 +[ class, expver, stream=espd, date, time, domain + [ type, levtype, origin, grid + [ step, number, levelist?, param ]]] + +[ class=cs, expver, stream, date:Default, time, domain + [ type, levtype + [ step, levelist?, param ]]] diff --git a/pproc-runtime/tests/test_accumulation.py b/pproc-runtime/tests/test_accumulation.py new file mode 100644 index 00000000..44097f28 --- /dev/null +++ b/pproc-runtime/tests/test_accumulation.py @@ -0,0 +1,28 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +import numpy as np + +import earthkit.data +from ppruntime.accumulation import difference_rate + +TEST_DIR = os.path.dirname(os.path.realpath(__file__)) +DATA_DIR = os.path.join(TEST_DIR, "data") + + +def test_difference_rate(download_all_test_data): + fl: earthkit.data.FieldList = earthkit.data.from_source( + "file", os.path.join(DATA_DIR, "test_2t_12.grib") + ) # type: ignore + fl2 = earthkit.data.FieldList.from_array( + fl.values * 2, [x.override({"step": 24}) for x in fl.metadata()] + ) + single = difference_rate(fl, factor=0.5) + assert np.all(single.values == fl.values / 6) + double = difference_rate( + fl, fl2, factor=0.5, metadata={"stepType": "diff", "stepRange": "12-24"} + ) + assert np.all(double.values == fl.values / 6) + assert double.metadata("stepRange") == ["12-24"] diff --git a/pproc-runtime/tests/test_io.py b/pproc-runtime/tests/test_io.py new file mode 100644 index 00000000..013fb97d --- /dev/null +++ b/pproc-runtime/tests/test_io.py @@ -0,0 +1,132 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +from datetime import datetime, timedelta + +import pytest +from earthkit.data.testing import NO_MARS + +from ppruntime.io import retrieve + +TEST_DIR = os.path.dirname(os.path.realpath(__file__)) +DATA_DIR = os.path.join(TEST_DIR, "data") + +request = { + "class": "od", + "expver": "0001", + "stream": "oper", + "type": "fc", + "date": (datetime.today() - timedelta(days=1)).strftime("%Y%m%d"), + "time": "12", + "domain": "g", + "levtype": "sfc", + "step": "12", + "param": 228, +} + + +@pytest.mark.skipif(NO_MARS, reason="No access to MARS") +@pytest.mark.parametrize( + "overrides", + [ + {}, + {"interpolate": {"grid": "O640"}}, + { + "param": [138, 155], + "levtype": "pl", + "levelist": [250, 850], + "interpolate": {"grid": "O640", "vod2uv": True}, + }, + ], + ids=["default", "interpolate", "wind"], +) +def test_mars_retrieve(overrides): + test_request = request.copy() + test_request.update(overrides) + retrieve([{"name": "mars"}], [test_request]) + + +@pytest.mark.parametrize( + "stream", + [True, False], +) +@pytest.mark.parametrize( + "overrides", + [ + {}, + {"interpolate": {"grid": "O640"}}, + { + "date": "20240507", + "stream": "enfo", + "type": "cf", + "step": 3, + "param": [138, 155], + "levtype": "pl", + "levelist": [250, 850], + "interpolate": {"grid": "O640", "vod2uv": True}, + }, + ], + ids=["default", "interpolate", "wind"], +) +def test_fdb_retrieve(fdb, stream, overrides): + test_request = { + "class": "od", + "expver": "0001", + "stream": "enfo", + "type": "cf", + "date": "20240507", + "time": "12", + "domain": "g", + "levtype": "sfc", + "step": "12", + "param": 167, + } + test_request.update(overrides) + retrieve([{"name": "fdb", "stream": stream}], [test_request]) + + +@pytest.mark.parametrize( + "source", + [ + {"name": "file", "path": os.path.join(DATA_DIR, "test_2t_12.grib")}, + { + "name": "file-pattern", + "pattern": os.path.join(DATA_DIR, "test_{param}_{step}.grib"), + "hive_partitioning": True, + }, + ], + ids=["file", "file-pattern"], +) +def test_file_retrieve(download_all_test_data, source): + request = { + "stream": "enfo", + "type": "cf", + "date": "20240507", + "time": "12", + "param": "2t", + "expver": "0001", + "levtype": "sfc", + } + retrieve([source], [request]) + + +def test_multi_source_retrieve(fdb): + request = { + "stream": "enfo", + "type": "cf", + "date": "20240507", + "time": "12", + "param": "2t", + "expver": "0001", + "levtype": "sfc", + } + sources = [ + {"name": "fdb", "stream": True}, + { + "name": "file", + "path": os.path.join(DATA_DIR, "test_2t_12.grib"), + }, + ] + retrieve(sources, [request]) diff --git a/pproc-runtime/tests/test_thermal_indices.py b/pproc-runtime/tests/test_thermal_indices.py new file mode 100644 index 00000000..dd1dc4db --- /dev/null +++ b/pproc-runtime/tests/test_thermal_indices.py @@ -0,0 +1,63 @@ +# SPDX-FileCopyrightText: 2026 European Centre for Medium-Range Weather Forecasts (ECMWF) +# +# SPDX-License-Identifier: Apache-2.0 + +import os +import pytest +from typing import Optional +import numpy as np + +import earthkit.data + +from ppruntime import thermal_indices + +TEST_DIR = os.path.dirname(os.path.realpath(__file__)) +DATA_DIR = os.path.join(TEST_DIR, "data") + + +@pytest.mark.parametrize( + "function, paramid", + [ + [thermal_indices.calc_mrt, 261002], + [thermal_indices.calc_aptmp, 260255], + [thermal_indices.calc_wcf, 260005], + [thermal_indices.calc_nefft, 261018], + [thermal_indices.calc_wbt, 261023], + [thermal_indices.calc_gt, 261015], + [thermal_indices.calc_wbgt, 261014], + [thermal_indices.calc_utci, 261001], + [thermal_indices.calc_dsrp, 47], + [thermal_indices.calc_heatx, 260004], + [thermal_indices.calc_rhp, 260242], + [thermal_indices.calc_hmdx, 261016], + [thermal_indices.calc_cossza, 214001], + ], +) +def test_thermal_indices(monkeypatch, download_all_test_data, function, paramid): + inputs: earthkit.data.FieldList = earthkit.data.from_source( + "file", os.path.join(DATA_DIR, "test_2t_12.grib") + ) # type: ignore + + def patched_sel(paramId: Optional[int] = None, stepType: Optional[str] = None): + if paramId is not None: + selected = inputs.sel(param="2t") + if paramId == 214001: + # To avoid invalid value warnings for arcsin + return earthkit.data.FieldList.from_array( + np.random.rand(*selected.values.shape), + selected[0].metadata().override(stepType="diff", stepRange="0-12"), + ) + return selected + if stepType is not None: + param = inputs.sel(param="2t") + return earthkit.data.FieldList.from_array( + param.values, + param[0].metadata().override(stepType="diff", stepRange="0-12"), + ) + + ds = earthkit.data.FieldList.from_array(inputs.values, inputs.metadata()) + monkeypatch.setattr(ds, "sel", patched_sel) + out = function(ds, metadata={"edition": 2, "paramId": paramid}) + metadata = out[0].metadata() + assert metadata.get("paramId") == paramid + assert metadata.get("typeOfFirstFixedSurface") == "sfc" diff --git a/pproc-runtime/uv.lock b/pproc-runtime/uv.lock new file mode 100644 index 00000000..a09ab81c --- /dev/null +++ b/pproc-runtime/uv.lock @@ 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Do not track in version control! __version__ = "{version}" ''' +root = ".." local_scheme = "no-local-version" scm.git.describe_command = ['git', 'describe', '--dirty', '--tags', '--long', '--abbrev=40', '--match', '[0-9]*'] + +[tool.uv] +package = true + +[tool.uv.sources] +pproc-core = { workspace = true } + +[tool.uv.workspace] +members = [ + "../pproc-core", +] diff --git a/requirements.txt b/pproc/requirements.txt similarity index 100% rename from requirements.txt rename to pproc/requirements.txt diff --git a/setup.py b/pproc/setup.py similarity index 100% rename from setup.py rename to pproc/setup.py diff --git a/src/pproc/Config.py b/pproc/src/pproc/Config.py similarity index 100% rename from src/pproc/Config.py rename to pproc/src/pproc/Config.py diff --git a/src/pproc/__init__.py b/pproc/src/pproc/__init__.py similarity index 100% rename from src/pproc/__init__.py rename to pproc/src/pproc/__init__.py diff --git a/src/pproc/accum/__init__.py b/pproc/src/pproc/accum/__init__.py similarity index 100% rename from src/pproc/accum/__init__.py rename to pproc/src/pproc/accum/__init__.py diff --git a/src/pproc/accum/main.py b/pproc/src/pproc/accum/main.py similarity index 100% rename from src/pproc/accum/main.py rename to pproc/src/pproc/accum/main.py diff --git a/src/pproc/accum/postprocess.py b/pproc/src/pproc/accum/postprocess.py similarity index 100% rename from src/pproc/accum/postprocess.py rename to pproc/src/pproc/accum/postprocess.py diff --git a/src/pproc/accumulate.py b/pproc/src/pproc/accumulate.py similarity index 100% rename from src/pproc/accumulate.py rename to pproc/src/pproc/accumulate.py diff --git a/src/pproc/anomaly.py b/pproc/src/pproc/anomaly.py similarity index 100% rename from src/pproc/anomaly.py rename to pproc/src/pproc/anomaly.py diff --git a/src/pproc/clustereps/__init__.py b/pproc/src/pproc/clustereps/__init__.py similarity index 100% rename from src/pproc/clustereps/__init__.py rename to pproc/src/pproc/clustereps/__init__.py diff --git a/src/pproc/clustereps/__main__.py b/pproc/src/pproc/clustereps/__main__.py similarity index 100% rename from src/pproc/clustereps/__main__.py rename to pproc/src/pproc/clustereps/__main__.py diff --git a/src/pproc/clustereps/attribution.py b/pproc/src/pproc/clustereps/attribution.py similarity index 100% rename from src/pproc/clustereps/attribution.py rename to pproc/src/pproc/clustereps/attribution.py diff --git a/src/pproc/clustereps/cluster.py b/pproc/src/pproc/clustereps/cluster.py similarity index 100% rename from src/pproc/clustereps/cluster.py rename to pproc/src/pproc/clustereps/cluster.py diff --git a/src/pproc/clustereps/io.py b/pproc/src/pproc/clustereps/io.py similarity index 100% rename from src/pproc/clustereps/io.py rename to pproc/src/pproc/clustereps/io.py diff --git a/src/pproc/clustereps/pca.py b/pproc/src/pproc/clustereps/pca.py similarity index 100% rename from src/pproc/clustereps/pca.py rename to pproc/src/pproc/clustereps/pca.py diff --git 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to pproc/src/pproc/schema/input.py diff --git a/src/pproc/schema/schema.py b/pproc/src/pproc/schema/schema.py similarity index 100% rename from src/pproc/schema/schema.py rename to pproc/src/pproc/schema/schema.py diff --git a/src/pproc/schema/step.py b/pproc/src/pproc/schema/step.py similarity index 100% rename from src/pproc/schema/step.py rename to pproc/src/pproc/schema/step.py diff --git a/src/pproc/schema/utils.py b/pproc/src/pproc/schema/utils.py similarity index 100% rename from src/pproc/schema/utils.py rename to pproc/src/pproc/schema/utils.py diff --git a/src/pproc/signi/__init__.py b/pproc/src/pproc/signi/__init__.py similarity index 100% rename from src/pproc/signi/__init__.py rename to pproc/src/pproc/signi/__init__.py diff --git a/src/pproc/signi/clim.py b/pproc/src/pproc/signi/clim.py similarity index 100% rename from src/pproc/signi/clim.py rename to pproc/src/pproc/signi/clim.py diff --git a/src/pproc/significance.py b/pproc/src/pproc/significance.py similarity index 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a/src/pproc/tcycl/tcycl_run.py b/pproc/src/pproc/tcycl/tcycl_run.py similarity index 100% rename from src/pproc/tcycl/tcycl_run.py rename to pproc/src/pproc/tcycl/tcycl_run.py diff --git a/src/pproc/tcycl/tcycl_summarise_ibtks.py b/pproc/src/pproc/tcycl/tcycl_summarise_ibtks.py similarity index 100% rename from src/pproc/tcycl/tcycl_summarise_ibtks.py rename to pproc/src/pproc/tcycl/tcycl_summarise_ibtks.py diff --git a/src/pproc/tcycl/tcycl_summarise_tcycl.py b/pproc/src/pproc/tcycl/tcycl_summarise_tcycl.py similarity index 100% rename from src/pproc/tcycl/tcycl_summarise_tcycl.py rename to pproc/src/pproc/tcycl/tcycl_summarise_tcycl.py diff --git a/src/pproc/tcycl/tcycl_summarise_trckr.py b/pproc/src/pproc/tcycl/tcycl_summarise_trckr.py similarity index 100% rename from src/pproc/tcycl/tcycl_summarise_trckr.py rename to pproc/src/pproc/tcycl/tcycl_summarise_trckr.py diff --git a/src/pproc/tcycl/tcycl_tools.py b/pproc/src/pproc/tcycl/tcycl_tools.py similarity index 100% rename from src/pproc/tcycl/tcycl_tools.py rename to pproc/src/pproc/tcycl/tcycl_tools.py diff --git a/src/pproc/thermal_indices.py b/pproc/src/pproc/thermal_indices.py similarity index 100% rename from src/pproc/thermal_indices.py rename to pproc/src/pproc/thermal_indices.py diff --git a/src/pproc/thermo/__init__.py b/pproc/src/pproc/thermo/__init__.py similarity index 100% rename from src/pproc/thermo/__init__.py rename to pproc/src/pproc/thermo/__init__.py diff --git a/src/pproc/thermo/helpers.py b/pproc/src/pproc/thermo/helpers.py similarity index 100% rename from src/pproc/thermo/helpers.py rename to pproc/src/pproc/thermo/helpers.py diff --git a/src/pproc/thermo/indices.py b/pproc/src/pproc/thermo/indices.py similarity index 100% rename from src/pproc/thermo/indices.py rename to pproc/src/pproc/thermo/indices.py diff --git a/src/pproc/wind.py b/pproc/src/pproc/wind.py similarity index 100% rename from src/pproc/wind.py rename to pproc/src/pproc/wind.py diff --git a/src/pproc/wind850.py b/pproc/src/pproc/wind850.py similarity index 100% rename from src/pproc/wind850.py rename to pproc/src/pproc/wind850.py diff --git a/src/pproc/wind850.yaml b/pproc/src/pproc/wind850.yaml similarity index 100% rename from src/pproc/wind850.yaml rename to pproc/src/pproc/wind850.yaml diff --git a/tests/clusteps/test_season.py b/pproc/tests/clusteps/test_season.py similarity index 100% rename from tests/clusteps/test_season.py rename to pproc/tests/clusteps/test_season.py diff --git a/tests/common/test_accumulation.py b/pproc/tests/common/test_accumulation.py similarity index 100% rename from tests/common/test_accumulation.py rename to pproc/tests/common/test_accumulation.py diff --git a/tests/common/test_accumulation_manager.py b/pproc/tests/common/test_accumulation_manager.py similarity index 100% rename from tests/common/test_accumulation_manager.py rename to pproc/tests/common/test_accumulation_manager.py diff --git a/tests/common/test_config.py b/pproc/tests/common/test_config.py similarity index 100% rename from tests/common/test_config.py rename to pproc/tests/common/test_config.py diff --git a/tests/common/test_io.py b/pproc/tests/common/test_io.py similarity index 95% rename from tests/common/test_io.py rename to pproc/tests/common/test_io.py index bca69093..9a5f7f97 100644 --- a/tests/common/test_io.py +++ b/pproc/tests/common/test_io.py @@ -30,8 +30,6 @@ "param": [138, 155], "step": range(0, 7, 3), } - - def test_fdb_read(fdb): data = io.fdb_read(fdb, request) assert len(data.coords["param"]) == 2 @@ -73,7 +71,7 @@ def test_fdb_missing_values(fdb): assert not np.any(data == 9999) -def test_fdb_target(): +def test_fdb_target(download_all_test_data): target = io.target_from_location("fdb:") for msg in eccodes.FileReader(f"{DATA_DIR}/wind.grib"): msg.set("type", "em") @@ -85,7 +83,7 @@ def test_fdb_target(): assert len(data) == 6 -def test_file_target(tmpdir): +def test_file_target(tmpdir, download_all_test_data): target = io.target_from_location(f"file:{tmpdir}/test.grib") messages = [ msg @@ -99,7 +97,7 @@ def test_file_target(tmpdir): assert len(data) == 5 -def test_fileset_target(tmpdir): +def test_fileset_target(tmpdir, download_all_test_data): target = io.target_from_location(f"fileset:{tmpdir}" + "/test_{step}.grib") for msg in eccodes.FileReader(f"{DATA_DIR}/2t_ens.grib"): target.write(msg) @@ -128,6 +126,7 @@ def _write(target, message): [{"step": x} for x in range(12, 37, 6)], ], ], + ids=["file", "fileset"] ) def test_target_parallel(tmpdir, fdb, loc, out_loc, reqs): loc = loc.replace("TMPDIR", str(tmpdir)) diff --git a/tests/common/test_mars.py b/pproc/tests/common/test_mars.py similarity index 100% rename from tests/common/test_mars.py rename to pproc/tests/common/test_mars.py diff --git a/tests/common/test_steps.py b/pproc/tests/common/test_steps.py similarity index 100% rename from tests/common/test_steps.py rename to pproc/tests/common/test_steps.py diff --git a/tests/common/test_stepseq.py b/pproc/tests/common/test_stepseq.py similarity index 100% rename from tests/common/test_stepseq.py rename to pproc/tests/common/test_stepseq.py diff --git a/tests/common/test_utils.py b/pproc/tests/common/test_utils.py similarity index 100% rename from tests/common/test_utils.py rename to pproc/tests/common/test_utils.py diff --git a/tests/config/test_accum.py b/pproc/tests/config/test_accum.py similarity index 100% rename from tests/config/test_accum.py rename to pproc/tests/config/test_accum.py diff --git a/tests/config/test_base.py b/pproc/tests/config/test_base.py similarity index 100% rename from tests/config/test_base.py rename to pproc/tests/config/test_base.py diff --git a/tests/config/test_factory.py b/pproc/tests/config/test_factory.py similarity index 100% rename from tests/config/test_factory.py rename to pproc/tests/config/test_factory.py diff --git a/tests/config/test_io_models.py b/pproc/tests/config/test_io_models.py similarity index 100% rename from tests/config/test_io_models.py rename to pproc/tests/config/test_io_models.py diff --git a/tests/config/test_log.py b/pproc/tests/config/test_log.py similarity index 100% rename from tests/config/test_log.py rename to pproc/tests/config/test_log.py diff --git a/tests/config/test_param.py b/pproc/tests/config/test_param.py similarity index 100% rename from tests/config/test_param.py rename to pproc/tests/config/test_param.py diff --git a/tests/config/test_preprocessing.py b/pproc/tests/config/test_preprocessing.py similarity index 100% rename from tests/config/test_preprocessing.py rename to pproc/tests/config/test_preprocessing.py diff --git a/tests/config/test_recovery.py b/pproc/tests/config/test_recovery.py similarity index 100% rename from tests/config/test_recovery.py rename to pproc/tests/config/test_recovery.py diff --git a/tests/config/types/test_ecpoint.py b/pproc/tests/config/types/test_ecpoint.py similarity index 100% rename from tests/config/types/test_ecpoint.py rename to pproc/tests/config/types/test_ecpoint.py diff --git a/tests/config/types/test_extreme.py b/pproc/tests/config/types/test_extreme.py similarity index 100% rename from tests/config/types/test_extreme.py rename to pproc/tests/config/types/test_extreme.py diff --git a/tests/config/types/test_flightlevels.py b/pproc/tests/config/types/test_flightlevels.py similarity index 100% rename from tests/config/types/test_flightlevels.py rename to pproc/tests/config/types/test_flightlevels.py diff --git a/tests/conftest.py b/pproc/tests/conftest.py similarity index 86% rename from tests/conftest.py rename to pproc/tests/conftest.py index 43c1046c..8b401adb 100644 --- a/tests/conftest.py +++ b/pproc/tests/conftest.py @@ -48,43 +48,8 @@ def download_test_data( return local_files -def populate_fdb( - fdb, - test_files: List[str], - dir_url: str = NEXUS, - local_dir: str = DATA_DIR, -): - data_files = download_test_data(test_files, dir_url, local_dir) - for filepath in data_files: - if os.path.isfile(filepath): - reader = eccodes.FileReader(filepath) - for msg in reader: - fdb.archive(msg.get_buffer()) - fdb.flush() - - @pytest.fixture(scope="session") -def fdb() -> pyfdb.FDB: - tmpdir = tempfile.mkdtemp() - print("Using temporary directory", tmpdir) - os.makedirs(f"{tmpdir}/etc/fdb") - os.mkdir(f"{tmpdir}/fdb") - shutil.copyfile(f"{TEST_DIR}/templates/fdb/schema", f"{tmpdir}/etc/fdb/schema") - with open(f"{tmpdir}/etc/fdb/config.yaml", "w") as f: - f.write( - f""" ---- -type: local -engine: toc -schema: "{tmpdir}/etc/fdb/schema" -spaces: -- roots: - - path: {tmpdir}/fdb -""" - ) - os.environ["FDB_HOME"] = str(tmpdir) - os.environ["FDB_HANDLE_LUSTRE_STRIPE"] = "0" - temp_fdb = pyfdb.FDB() +def download_all_test_data(): download_test_data( [ "era_clcen_eof_mjjas.gts", @@ -97,8 +62,7 @@ def fdb() -> pyfdb.FDB: f"{NEXUS}/clustclim", f"{DATA_DIR}/clustclim", ) - populate_fdb( - temp_fdb, + download_test_data( [ "2t_ens.grib", "2t_clim.grib", @@ -108,8 +72,48 @@ def fdb() -> pyfdb.FDB: "has_missing.grib", "thermo.grib", ], + NEXUS, + DATA_DIR, ) + +@pytest.fixture(scope="session") +def fdb(download_all_test_data) -> pyfdb.FDB: + tmpdir = tempfile.mkdtemp() + print("Using temporary directory", tmpdir) + os.makedirs(f"{tmpdir}/etc/fdb") + os.mkdir(f"{tmpdir}/fdb") + shutil.copyfile(f"{TEST_DIR}/templates/fdb/schema", f"{tmpdir}/etc/fdb/schema") + with open(f"{tmpdir}/etc/fdb/config.yaml", "w") as f: + f.write( + f""" +--- +type: local +engine: toc +schema: "{tmpdir}/etc/fdb/schema" +spaces: +- roots: + - path: {tmpdir}/fdb +""" + ) + os.environ["FDB_HOME"] = str(tmpdir) + os.environ["FDB_HANDLE_LUSTRE_STRIPE"] = "0" + temp_fdb = pyfdb.FDB() + for filename in [ + "2t_ens.grib", + "2t_clim.grib", + "wind.grib", + "t850.grib", + "cluster.grib", + "has_missing.grib", + "thermo.grib", + ]: + filepath = os.path.join(DATA_DIR, filename) + if os.path.isfile(filepath): + reader = eccodes.FileReader(filepath) + for msg in reader: + temp_fdb.archive(msg.get_buffer()) + temp_fdb.flush() yield temp_fdb shutil.rmtree(tmpdir) diff --git a/tests/ecpt/test_predictors.py b/pproc/tests/ecpt/test_predictors.py similarity index 100% rename from tests/ecpt/test_predictors.py rename to pproc/tests/ecpt/test_predictors.py diff --git a/tests/prob/test_prob_accumulation_manager.py b/pproc/tests/prob/test_prob_accumulation_manager.py similarity index 100% rename from tests/prob/test_prob_accumulation_manager.py rename to pproc/tests/prob/test_prob_accumulation_manager.py diff --git a/tests/prob/test_prob_parallel.py b/pproc/tests/prob/test_prob_parallel.py similarity index 100% rename from tests/prob/test_prob_parallel.py rename to pproc/tests/prob/test_prob_parallel.py diff --git a/tests/schema/schema.yaml b/pproc/tests/schema/schema.yaml similarity index 100% rename from tests/schema/schema.yaml rename to pproc/tests/schema/schema.yaml diff --git a/tests/schema/test_config_schema.py b/pproc/tests/schema/test_config_schema.py similarity index 100% rename from tests/schema/test_config_schema.py rename to pproc/tests/schema/test_config_schema.py diff --git a/tests/schema/test_deriver.py b/pproc/tests/schema/test_deriver.py similarity index 100% rename from tests/schema/test_deriver.py rename to pproc/tests/schema/test_deriver.py diff --git a/tests/schema/test_input_schema.py b/pproc/tests/schema/test_input_schema.py similarity index 100% rename from tests/schema/test_input_schema.py rename to pproc/tests/schema/test_input_schema.py diff --git a/tests/schema/test_schema.py b/pproc/tests/schema/test_schema.py similarity index 100% rename from tests/schema/test_schema.py rename to pproc/tests/schema/test_schema.py diff --git a/tests/schema/test_step_schema.py b/pproc/tests/schema/test_step_schema.py similarity index 100% rename from tests/schema/test_step_schema.py rename to pproc/tests/schema/test_step_schema.py diff --git a/tests/templates/fdb/schema b/pproc/tests/templates/fdb/schema similarity index 100% rename from tests/templates/fdb/schema rename to pproc/tests/templates/fdb/schema diff --git a/tests/templates/clustereps.yaml b/pproc/tests/templates/v2/clustereps.yaml similarity index 99% rename from tests/templates/clustereps.yaml rename to pproc/tests/templates/v2/clustereps.yaml index 35c9a579..f87f7dd6 100644 --- a/tests/templates/clustereps.yaml +++ b/pproc/tests/templates/v2/clustereps.yaml @@ -185,4 +185,4 @@ indexes: null deterministic_is_control: true date: 2024-05-07 00:00:00 compute_spread: true -pca_output: null \ No newline at end of file +pca_output: null diff --git a/tests/templates/ensms.yaml b/pproc/tests/templates/v2/ensms.yaml similarity index 92% rename from tests/templates/ensms.yaml rename to pproc/tests/templates/v2/ensms.yaml index bf5aeba0..16bb81a3 100644 --- a/tests/templates/ensms.yaml +++ b/pproc/tests/templates/v2/ensms.yaml @@ -4,7 +4,7 @@ parallelisation: queue_size: 2 parameters: 2t: - inputs: + inputs: fc: request: param: '167.128' @@ -34,12 +34,12 @@ inputs: type: pf number: [1, 2, 3, 4, 5] source: - type: "fdb" + type: "fdb" outputs: default: metadata: mars.expver: '0001' numberOfForecastsInEnsemble: 6 perturbationNumber: 0 - target: - type: "fdb" \ No newline at end of file + target: + type: "fdb" diff --git a/tests/templates/extreme.yaml b/pproc/tests/templates/v2/extreme.yaml similarity index 94% rename from tests/templates/extreme.yaml rename to pproc/tests/templates/v2/extreme.yaml index e38d6382..22d319bf 100644 --- a/tests/templates/extreme.yaml +++ b/pproc/tests/templates/v2/extreme.yaml @@ -16,7 +16,7 @@ parameters: request: param: 228004 step: - 12-36: 0-24 + 12-36: 0-24 accumulations: step: type: legacywindow @@ -52,10 +52,10 @@ inputs: stream: enfo date: 20240507 time: 12 - type: pf + type: pf number: [1, 2, 3, 4, 5] source: - type: fdb + type: fdb clim: request: class: od @@ -71,4 +71,4 @@ inputs: outputs: default: target: - type: fdb \ No newline at end of file + type: fdb diff --git a/tests/templates/prob.yaml b/pproc/tests/templates/v2/prob.yaml similarity index 97% rename from tests/templates/prob.yaml rename to pproc/tests/templates/v2/prob.yaml index 3a30a28c..0dfbc3ca 100644 --- a/tests/templates/prob.yaml +++ b/pproc/tests/templates/v2/prob.yaml @@ -20,7 +20,7 @@ parameters: metadata: paramId: 131073 value: 273.15 -inputs: +inputs: fc: request: class: od @@ -41,5 +41,5 @@ outputs: localDefinitionNumber: 5 mars.expver: '0001' type: ep - target: + target: type: "fdb" diff --git a/tests/templates/quantiles.yaml b/pproc/tests/templates/v2/quantiles.yaml similarity index 92% rename from tests/templates/quantiles.yaml rename to pproc/tests/templates/v2/quantiles.yaml index faf1594f..94a3f8fd 100644 --- a/tests/templates/quantiles.yaml +++ b/pproc/tests/templates/v2/quantiles.yaml @@ -5,7 +5,7 @@ parallelisation: quantiles: 3 parameters: 2t: - inputs: + inputs: fc: request: param: '167.128' @@ -39,10 +39,10 @@ inputs: type: pf number: [1, 2, 3, 4, 5] source: - type: "fdb" + type: "fdb" outputs: default: metadata: mars.expver: '0001' - target: - type: "fdb" \ No newline at end of file + target: + type: "fdb" diff --git a/tests/templates/t850.yaml b/pproc/tests/templates/v2/t850.yaml similarity index 70% rename from tests/templates/t850.yaml rename to pproc/tests/templates/v2/t850.yaml index 9053bc68..75525f5f 100644 --- a/tests/templates/t850.yaml +++ b/pproc/tests/templates/v2/t850.yaml @@ -53,38 +53,6 @@ parameters: value: 2 metadata: bitsPerValue: 24 - - coords: [[0], [12]] - operation: maximum - std_anomaly: true - thresholds: - - metadata: {"paramId": 133093} - comparison: '>' - value: 1 - metadata: - localDefinitionNumber: 30 - bitsPerValue: 24 - edition: 2 - typeOfGeneratingProcess: 5 - paramId: 0 - timeIncrement: 12 - typeOfStatisticalProcessing: 10 - packingType: grid_ccsds - - coords: [[0], [12]] - operation: minimum - std_anomaly: true - thresholds: - - metadata: {"paramId": 133096} - comparison: < - value: -1 - metadata: - localDefinitionNumber: 30 - bitsPerValue: 24 - edition: 2 - typeOfGeneratingProcess: 5 - paramId: 0 - timeIncrement: 12 - typeOfStatisticalProcessing: 10 - packingType: grid_ccsds inputs: fc: request: @@ -140,4 +108,4 @@ outputs: localDefinitionNumber: 5 bitsPerValue: 8 target: - type: fdb \ No newline at end of file + type: fdb diff --git a/tests/templates/thermo.yaml b/pproc/tests/templates/v2/thermo.yaml similarity index 87% rename from tests/templates/thermo.yaml rename to pproc/tests/templates/v2/thermo.yaml index d2c7e4ff..8b69a6c7 100644 --- a/tests/templates/thermo.yaml +++ b/pproc/tests/templates/v2/thermo.yaml @@ -1,7 +1,7 @@ parallelisation: n_par_compute: 2 -defs: - base_request: &base_request +defs: + base_request: &base_request class: od domain: g expver: '0001' @@ -29,9 +29,9 @@ parameters: step: coords: [[0]] indices: - inputs: - accum: - request: + inputs: + accum: + request: <<: *base_request date: 20240605 param: *accum_params @@ -53,7 +53,7 @@ parameters: - wbt - wbgt - 2r -inputs: +inputs: inst: request: <<: *base_request @@ -76,4 +76,4 @@ outputs: path: "intermediate.grib" indices: target: - type: fdb \ No newline at end of file + type: fdb diff --git a/tests/templates/wind.yaml b/pproc/tests/templates/v2/wind.yaml similarity index 92% rename from tests/templates/wind.yaml rename to pproc/tests/templates/v2/wind.yaml index 01753ab8..9f25ac09 100644 --- a/tests/templates/wind.yaml +++ b/pproc/tests/templates/v2/wind.yaml @@ -1,4 +1,7 @@ -parallelisation: 1 +parallelisation: + n_par_compute: 2 + n_par_read: 2 + queue_size: 2 inputs: fc: request: @@ -49,4 +52,4 @@ outputs: indicatorOfParameter: 10 mars.expver: '0001' target: - type: fdb \ No newline at end of file + type: fdb diff --git a/pproc/tests/templates/v3/ensms.yaml b/pproc/tests/templates/v3/ensms.yaml new file mode 100644 index 00000000..3d8893ba --- /dev/null +++ b/pproc/tests/templates/v3/ensms.yaml @@ -0,0 +1,223 @@ +log: + level: INFO + format: '%(asctime)s; %(name)s; %(levelname)s - %(message)s' +execution: + hosts: 1 + workers: 1 +products: +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + oceanAtmosphereCoupling: 2 + legBaseDate: 20240507 + legBaseTime: 1200 + legNumber: 1 + perturbationNumber: 0 + bitsPerValue: 16 + numberOfForecastsInEnsemble: '{num_fields}:int' + stream: enfo + type: em + operation: mean + output: + targets: + - name: fdb + request: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: cf + param: 167 + step: 12 + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pf + param: 167 + step: 12 + number: + - 1 + - 2 + - 3 + - 4 + - 5 + dtype: float64 +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + oceanAtmosphereCoupling: 2 + legBaseDate: 20240507 + legBaseTime: 1200 + legNumber: 1 + perturbationNumber: 0 + bitsPerValue: 16 + numberOfForecastsInEnsemble: '{num_fields}:int' + stream: enfo + type: es + operation: std + output: + targets: + - name: fdb + request: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: cf + param: 167 + step: 12 + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pf + param: 167 + step: 12 + number: + - 1 + - 2 + - 3 + - 4 + - 5 + dtype: float64 +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + oceanAtmosphereCoupling: 2 + legBaseDate: 20240507 + legBaseTime: 1200 + legNumber: 1 + perturbationNumber: 0 + bitsPerValue: 16 + numberOfForecastsInEnsemble: '{num_fields}:int' + stream: enfo + type: em + operation: mean + output: + targets: + - name: fdb + request: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: cf + param: 167 + step: 36 + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pf + param: 167 + step: 36 + number: + - 1 + - 2 + - 3 + - 4 + - 5 + dtype: float64 +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + oceanAtmosphereCoupling: 2 + legBaseDate: 20240507 + legBaseTime: 1200 + legNumber: 1 + perturbationNumber: 0 + bitsPerValue: 16 + numberOfForecastsInEnsemble: '{num_fields}:int' + stream: enfo + type: es + operation: std + output: + targets: + - name: fdb + request: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: cf + param: 167 + step: 36 + - class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pf + param: 167 + step: 36 + number: + - 1 + - 2 + - 3 + - 4 + - 5 + dtype: float64 diff --git a/pproc/tests/templates/v3/prob.yaml b/pproc/tests/templates/v3/prob.yaml new file mode 100644 index 00000000..77ffd86b --- /dev/null +++ b/pproc/tests/templates/v3/prob.yaml @@ -0,0 +1,157 @@ +log: + level: INFO + format: '%(asctime)s; %(name)s; %(levelname)s - %(message)s' +execution: + hosts: 1 + workers: 1 +products: +- name: ensemble + preprocessing: + actions: [] + accumulations: + step: + operation: minimum + coords: + - - 12 + deaccumulate: false + statistics: + metadata: + localDefinitionNumber: 5 + bitsPerValue: 8 + paramId: 131073 + stream: enfo + type: ep + operation: threshold_probability + thresholds: + - lower_scale_factor: 2 + lower_comparison: <= + lower_value: 273.15 + upper_scale_factor: 0 + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + domain: g + expver: '0001' + levtype: sfc + stream: enfo + type: cf + date: '20240507' + time: '1200' + param: '167' + step: 12 + - class: od + domain: g + expver: '0001' + levtype: sfc + stream: enfo + type: pf + date: '20240507' + time: '1200' + param: '167' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 12 + dtype: float64 + output: + targets: + - name: fdb + request: + class: od + domain: g + expver: '0001' + levtype: sfc + stream: enfo + type: ep + date: 20240507 + time: 12 + param: 131073 + step: 12 + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: + step: + operation: minimum + coords: + - 24 + - 36 + deaccumulate: false + name: + type: default + length: 24 + statistics: + metadata: + localDefinitionNumber: 5 + bitsPerValue: 8 + paramId: 131073 + stream: enfo + type: ep + operation: threshold_probability + thresholds: + - lower_scale_factor: 2 + lower_comparison: <= + lower_value: 273.15 + upper_scale_factor: 0 + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + domain: g + expver: '0001' + levtype: sfc + stream: enfo + type: cf + date: '20240507' + time: '1200' + param: '167' + step: + - 24 + - 36 + - class: od + domain: g + expver: '0001' + levtype: sfc + stream: enfo + type: pf + date: '20240507' + time: '1200' + param: '167' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: + - 24 + - 36 + dtype: float64 + output: + targets: + - name: fdb + request: + class: od + domain: g + expver: '0001' + levtype: sfc + stream: enfo + type: ep + date: 20240507 + time: 12 + param: 131073 + step: 12-36 + metadata: {} +input_overrides: {} +output_overrides: {} diff --git a/pproc/tests/templates/v3/quantiles.yaml b/pproc/tests/templates/v3/quantiles.yaml new file mode 100644 index 00000000..6a337172 --- /dev/null +++ b/pproc/tests/templates/v3/quantiles.yaml @@ -0,0 +1,1209 @@ +log: + level: INFO + format: '%(asctime)s; %(name)s; %(levelname)s - %(message)s' +execution: + hosts: 1 + workers: 1 +products: +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: 0:3 + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 12 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 12 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 12 + quantile: 0:3 + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '1:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 12 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 12 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 12 + quantile: '1:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '2:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 12 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 12 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 12 + quantile: '2:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '3:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 12 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 12 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 12 + quantile: '3:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: 0:3 + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 18 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 18 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 18 + quantile: 0:3 + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '1:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 18 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 18 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 18 + quantile: '1:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '2:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 18 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 18 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 18 + quantile: '2:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '3:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 18 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 18 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 18 + quantile: '3:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: 0:3 + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 24 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 24 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 24 + quantile: 0:3 + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '1:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 24 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 24 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 24 + quantile: '1:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '2:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 24 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 24 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 24 + quantile: '2:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '3:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 24 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 24 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 24 + quantile: '3:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: 0:3 + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 30 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 30 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 30 + quantile: 0:3 + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '1:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 30 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 30 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 30 + quantile: '1:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '2:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 30 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 30 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 30 + quantile: '2:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '3:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 30 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 30 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 30 + quantile: '3:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: 0:3 + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 36 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 36 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 36 + quantile: 0:3 + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '1:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 36 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 36 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 36 + quantile: '1:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '2:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 36 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 36 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 36 + quantile: '2:3' + metadata: {} +- name: ensemble + preprocessing: + actions: [] + accumulations: {} + statistics: + metadata: + localDefinitionNumber: 30 + stream: enfo + type: pb + operation: quantiles + quantiles: '3:3' + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: cf + param: '167.128' + step: 36 + - class: od + date: '20240507' + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: '1200' + type: pf + param: '167.128' + number: + - 1 + - 2 + - 3 + - 4 + - 5 + step: 36 + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + date: 20240507 + domain: g + levtype: sfc + expver: '0001' + stream: enfo + time: 12 + type: pb + param: '167.128' + step: 36 + quantile: '3:3' + metadata: {} +input_overrides: {} +output_overrides: {} diff --git a/pproc/tests/templates/v3/thermo.yaml b/pproc/tests/templates/v3/thermo.yaml new file mode 100644 index 00000000..0200d582 --- /dev/null +++ b/pproc/tests/templates/v3/thermo.yaml @@ -0,0 +1,886 @@ +log: + level: INFO + format: '%(asctime)s; %(name)s; %(levelname)s - %(message)s' +execution: + hosts: 1 + workers: 1 +products: +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: ppruntime.thermal_indices.calc_cossza + params: + - '167' + - '228021' + deaccumulate: + - '228021' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_mrt + params: + - '167' + - '214001' + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + deaccumulate: + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261002 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: + - 0 + - 1 + expver: '0001' + levtype: sfc + param: + - '47' + - '228021' + - '169' + - '175' + - '176' + - '177' + date: '20240605' + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: '167' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 261002 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: norm + params: + - '165' + - '166' + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_cossza + params: + - '167' + - '228021' + deaccumulate: + - '228021' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_mrt + params: + - '167' + - '214001' + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + deaccumulate: + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261002 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_utci + params: + - '167' + - '168' + - '207' + - '261002' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261001 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: + - 0 + - 1 + expver: '0001' + levtype: sfc + param: + - '169' + - '175' + - '176' + - '177' + - '228021' + - '47' + date: '20240605' + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '165' + - '166' + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 261001 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: ppruntime.thermal_indices.calc_heatx + params: + - '167' + - '168' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 260004 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 260004 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: norm + params: + - '165' + - '166' + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_wcf + params: + - '167' + - '207' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 260005 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '165' + - '166' + - '167' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 260005 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: norm + params: + - '165' + - '166' + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_rhp + params: + - '167' + - '168' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 260242 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_aptmp + params: + - '167' + - '260242' + - '207' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 260255 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '165' + - '166' + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 260255 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: ppruntime.thermal_indices.calc_rhp + params: + - '167' + - '168' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 260242 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 260242 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: ppruntime.thermal_indices.calc_hmdx + params: + - '167' + - '168' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261016 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 261016 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: norm + params: + - '165' + - '166' + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_rhp + params: + - '167' + - '168' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 260242 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_nefft + params: + - '167' + - '207' + - '260242' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261018 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '165' + - '166' + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 261018 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: norm + params: + - '165' + - '166' + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_cossza + params: + - '167' + - '228021' + deaccumulate: + - '228021' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_mrt + params: + - '167' + - '214001' + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + deaccumulate: + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261002 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_gt + params: + - '167' + - '207' + - '261002' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261015 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: + - 0 + - 1 + expver: '0001' + levtype: sfc + param: + - '169' + - '175' + - '176' + - '177' + - '228021' + - '47' + date: '20240605' + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '165' + - '166' + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 261015 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: norm + params: + - '165' + - '166' + metadata: + paramId: 207 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_cossza + params: + - '167' + - '228021' + deaccumulate: + - '228021' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 214001 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_mrt + params: + - '167' + - '214001' + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + deaccumulate: + - '47' + - '169' + - '228021' + - '175' + - '177' + - '176' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261002 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_wbgt + params: + - '167' + - '168' + - '207' + - '261002' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261014 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: + - 0 + - 1 + expver: '0001' + levtype: sfc + param: + - '169' + - '175' + - '176' + - '177' + - '228021' + - '47' + date: '20240605' + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '165' + - '166' + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 261014 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +- name: ensemble + preprocessing: + actions: + - operation: thermal_index + function: ppruntime.thermal_indices.calc_rhp + params: + - '167' + - '168' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 260242 + join: true + - operation: thermal_index + function: ppruntime.thermal_indices.calc_wbt + params: + - '167' + - '260242' + metadata: + edition: 2 + bitsPerValue: 16 + packingType: grid_ccsds + typeOfGeneratingProcess: 2 + paramId: 261023 + join: false + accumulations: {} + inputs: + fc: + sources: + - name: fdb + stream: true + requests: + - class: od + stream: oper + type: fc + time: '0000' + domain: g + step: 1 + expver: '0001' + levtype: sfc + param: + - '167' + - '168' + date: '20240605' + expand_exclude: [] + dtype: float32 + output: + targets: + - name: fdb + request: + class: od + stream: oper + type: fc + levtype: sfc + domain: g + param: 261023 + date: '20240605' + time: 12 + expver: '0001' + step: 1 + metadata: {} +input_overrides: {} +output_overrides: {} diff --git a/tests/test_ensms.py b/pproc/tests/test_ensms.py similarity index 100% rename from tests/test_ensms.py rename to pproc/tests/test_ensms.py diff --git a/tests/test_ensms.yaml b/pproc/tests/test_ensms.yaml similarity index 100% rename from tests/test_ensms.yaml rename to pproc/tests/test_ensms.yaml diff --git a/tests/test_products.py b/pproc/tests/test_products.py similarity index 71% rename from tests/test_products.py rename to pproc/tests/test_products.py index ffd54979..d6a1bd79 100644 --- a/tests/test_products.py +++ b/pproc/tests/test_products.py @@ -17,9 +17,9 @@ from pproc.ensms import main as ensms_main from pproc.extreme import main as extreme_main from pproc.quantiles import main as quantiles_main -from pproc.wind import main as wind_main from pproc.thermal_indices import main as thermo_main from pproc.clustereps.__main__ import main as clustereps_main +from ppcore.product import main as ppcore_main from conftest import DATA_DIR TEST_DIR = os.path.dirname(os.path.realpath(__file__)) @@ -46,7 +46,7 @@ "param": [131022, 133093], "step": [0, 12], }, - 4, + 2, ], [ "ensms", @@ -80,7 +80,7 @@ ], [ "wind", - wind_main, + ensms_main, [], { "type": "es", @@ -155,9 +155,9 @@ "clustereps", ], ) -def test_products(tmpdir, monkeypatch, fdb, product, main, custom_args, req, length): +def test_products_v2(tmpdir, monkeypatch, fdb, product, main, custom_args, req, length): monkeypatch.chdir(tmpdir) # To avoid polluting cwd with grib templates - args = [product, "--config", f"{TEST_DIR}/templates/{product}.yaml"] + [ + args = [product, "--config", f"{TEST_DIR}/templates/v2/{product}.yaml"] + [ x.format_map( { "test_dir": str(tmpdir), @@ -182,3 +182,61 @@ def test_products(tmpdir, monkeypatch, fdb, product, main, custom_args, req, len request.update(req) messages = list(eccodes.StreamReader(test_fdb.retrieve(request))) assert len(messages) == length + + +@pytest.mark.parametrize( + "product, req, length", + [ + [ + "ensms", + {"type": "em", "param": 167, "step": [12, 36]}, + 2, + ], + [ + "prob", + {"type": "ep", "param": 131073, "step": ["12", "12-36"]}, + 2, + ], + [ + "quantiles", + { + "type": "pb", + "param": 167, + "step": [12, 18, 24, 30, 36], + "quantile": ["{}:3".format(x) for x in range(4)], + }, + 20, + ], + [ + "thermo", + { + "stream": "oper", + "type": "fc", + "param": [261002, 261001, 260004, 260005, 260255, 260242, 261016, 261018, 261015, 261014, 261023], + "step": [1], + "date": 20240605, + "time": 00, + }, + 11, + ], + ], + ids=["ensms", "prob", "quantiles", "thermo"], +) +def test_products_v3(tmpdir, monkeypatch, fdb, product, req, length): + monkeypatch.chdir(tmpdir) # To avoid polluting cwd with grib templates + args = [product, "--config", f"{TEST_DIR}/templates/v3/{product}.yaml"] + monkeypatch.setattr("sys.argv", args) + ppcore_main() + test_fdb = pyfdb.FDB() + request = { + "class": "od", + "expver": "0001", + "stream": "enfo", + "date": 20240507, + "time": 12, + "levtype": "sfc", + "domain": "g", + } + request.update(req) + messages = list(eccodes.StreamReader(test_fdb.retrieve(request))) + assert len(messages) == length diff --git a/tests/test_spectral_order.py b/pproc/tests/test_spectral_order.py similarity index 100% rename from tests/test_spectral_order.py rename to pproc/tests/test_spectral_order.py diff --git a/pproc/uv.lock b/pproc/uv.lock new file mode 100644 index 00000000..aa1f9c4d --- /dev/null +++ b/pproc/uv.lock @@ -0,0 +1,2890 @@ +version = 1 +revision = 3 +requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.14' and platform_machine == 'ARM64' and sys_platform == 'win32'", + 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