diff --git a/.github/ci-hpc-config.yml b/.github/ci-hpc-config.yml new file mode 100644 index 0000000..2e20c20 --- /dev/null +++ b/.github/ci-hpc-config.yml @@ -0,0 +1,3 @@ +build: + python: 3.10 + parallel: 1 diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 4ef239e..7783738 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -1,192 +1,42 @@ name: ci on: + # Trigger the workflow on push to master or develop, except tag creation push: branches: - - main - - develop - tags: - - "*" + - 'main' + - 'develop' + tags-ignore: + - '**' + + # Trigger the workflow on pull request pull_request: - branches: - - main - - develop - pull_request_target: - types: [labeled] - workflow_dispatch: -concurrency: - group: ${{ github.workflow }}-${{ github.ref }} - cancel-in-progress: true + # Trigger the workflow manually + workflow_dispatch: -defaults: - run: - shell: bash -l {0} + # Trigger after public PR approved for CI + pull_request_target: + types: [labeled] jobs: - pre-commit: - if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v3 - with: - ref: ${{ github.event.pull_request.head.sha || github.ref }} - - uses: actions/setup-python@v4 - with: - python-version: 3.x - - uses: pre-commit/action@v3.0.0 - - unit-tests: - name: unit-tests (3.10) - if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v3 - with: - ref: ${{ github.event.pull_request.head.sha || github.ref }} - - name: Install Conda environment with Micromamba - uses: mamba-org/provision-with-micromamba@v14 - with: - environment-file: tests/environment-unit-tests.yml - environment-name: DEVELOP - channels: conda-forge - cache-env: true - extra-specs: | - python=3.10 - - name: Install package - run: | - python -m pip install --no-deps -e . - - name: Run tests - run: | - make unit-tests - - type-check: - needs: [unit-tests] - if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} - runs-on: ubuntu-latest - defaults: - run: - shell: bash -l {0} - - steps: - - uses: actions/checkout@v3 - with: - ref: ${{ github.event.pull_request.head.sha || github.ref }} - - name: Install Conda environment with Micromamba - uses: mamba-org/provision-with-micromamba@v12 - with: - environment-file: environment.yml - environment-name: DEVELOP - channels: conda-forge - cache-env: true - cache-env-key: ubuntu-latest-3.10 - extra-specs: | - python=3.10 - - name: Install package - run: | - python -m pip install --no-deps -e . - - name: Run code quality checks - run: | - echo type-check not used - - documentation: - needs: [unit-tests] + # Run CI including downstream packages on self-hosted runners + downstream-ci: + name: downstream-ci if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} - runs-on: ubuntu-latest - defaults: - run: - shell: bash -l {0} + uses: ecmwf-actions/downstream-ci/.github/workflows/downstream-ci.yml@main + with: + earthkit-meteo: ecmwf/earthkit-meteo@${{ github.event.pull_request.head.sha || github.sha }} + codecov_upload: true + python_qa: true + secrets: inherit - steps: - - uses: actions/checkout@v3 - with: - ref: ${{ github.event.pull_request.head.sha || github.ref }} - - name: Install Conda environment with Micromamba - uses: mamba-org/provision-with-micromamba@v12 - with: - environment-file: environment.yml - environment-name: DEVELOP - channels: conda-forge - cache-env: true - cache-env-key: ubuntu-latest-3.10 - extra-specs: | - python=3.10 - - name: Install package - run: | - python -m pip install --no-deps -e . - - name: Build documentation - run: | - make docs-build - integration-tests: - needs: [unit-tests] + # Build downstream packages on HPC + downstream-ci-hpc: + name: downstream-ci-hpc if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} - runs-on: ubuntu-latest - defaults: - run: - shell: bash -l {0} - - strategy: - matrix: - include: - - python-version: "3.10" - # extra: -minver # This will need to be uncommented and environment-minver.yml updated if we want to publish on conda - - steps: - - uses: actions/checkout@v3 - with: - ref: ${{ github.event.pull_request.head.sha || github.ref }} - - name: Install Conda environment with Micromamba - uses: mamba-org/provision-with-micromamba@v12 - with: - environment-file: tests/environment-unit-tests${{ matrix.extra }}.yml - environment-name: DEVELOP${{ matrix.extra }} - channels: conda-forge - cache-env: true - cache-env-key: ubuntu-latest-${{ matrix.python-version }}${{ matrix.extra }}. - extra-specs: | - python=${{matrix.python-version }} - - name: Install package - run: | - python -m pip install --no-deps -e . - - name: Run tests - run: | - make unit-tests - - distribution: - needs: [integration-tests, type-check, documentation] - if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v3 - with: - ref: ${{ github.event.pull_request.head.sha || github.ref }} - - name: Build distributions - run: | - $CONDA/bin/python -m pip install build - $CONDA/bin/python -m build - - name: Publish a Python distribution to PyPI - if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags') - uses: pypa/gh-action-pypi-publish@release/v1 - with: - user: __token__ - password: ${{ secrets.PYPI_API_TOKEN }} - - notify: - if: always() && ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} - needs: - - pre-commit - - unit-tests - - type-check - - documentation - - integration-tests - - distribution - runs-on: ubuntu-latest - steps: - - name: Trigger Teams notification - uses: ecmwf-actions/notify-teams@v1 - with: - incoming_webhook: ${{ secrets.MS_TEAMS_INCOMING_WEBHOOK }} - needs_context: ${{ toJSON(needs) }} + uses: ecmwf-actions/downstream-ci/.github/workflows/downstream-ci-hpc.yml@main + with: + earthkit-meteo: ecmwf/earthkit-meteo@${{ github.event.pull_request.head.sha || github.sha }} + secrets: inherit diff --git a/.github/workflows/legacy-ci.yml b/.github/workflows/legacy-ci.yml new file mode 100644 index 0000000..921fb15 --- /dev/null +++ b/.github/workflows/legacy-ci.yml @@ -0,0 +1,192 @@ +name: legacy-ci + +on: + push: + branches: + - main + - develop + tags: + - "*" + pull_request: + branches: + - main + - develop + pull_request_target: + types: [labeled] + workflow_dispatch: + +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + +defaults: + run: + shell: bash -l {0} + +jobs: + pre-commit: + if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + - uses: actions/setup-python@v4 + with: + python-version: 3.x + - uses: pre-commit/action@v3.0.0 + + unit-tests: + name: unit-tests (3.10) + if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v3 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + - name: Install Conda environment with Micromamba + uses: mamba-org/provision-with-micromamba@v14 + with: + environment-file: tests/environment-unit-tests.yml + environment-name: DEVELOP + channels: conda-forge + cache-env: true + extra-specs: | + python=3.10 + - name: Install package + run: | + python -m pip install --no-deps -e . + - name: Run tests + run: | + make unit-tests + + type-check: + needs: [unit-tests] + if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} + runs-on: ubuntu-latest + defaults: + run: + shell: bash -l {0} + + steps: + - uses: actions/checkout@v3 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + - name: Install Conda environment with Micromamba + uses: mamba-org/provision-with-micromamba@v12 + with: + environment-file: environment.yml + environment-name: DEVELOP + channels: conda-forge + cache-env: true + cache-env-key: ubuntu-latest-3.10 + extra-specs: | + python=3.10 + - name: Install package + run: | + python -m pip install --no-deps -e . + - name: Run code quality checks + run: | + echo type-check not used + + documentation: + needs: [unit-tests] + if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} + runs-on: ubuntu-latest + defaults: + run: + shell: bash -l {0} + + steps: + - uses: actions/checkout@v3 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + - name: Install Conda environment with Micromamba + uses: mamba-org/provision-with-micromamba@v12 + with: + environment-file: environment.yml + environment-name: DEVELOP + channels: conda-forge + cache-env: true + cache-env-key: ubuntu-latest-3.10 + extra-specs: | + python=3.10 + - name: Install package + run: | + python -m pip install --no-deps -e . + - name: Build documentation + run: | + make docs-build + + integration-tests: + needs: [unit-tests] + if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} + runs-on: ubuntu-latest + defaults: + run: + shell: bash -l {0} + + strategy: + matrix: + include: + - python-version: "3.10" + # extra: -minver # This will need to be uncommented and environment-minver.yml updated if we want to publish on conda + + steps: + - uses: actions/checkout@v3 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + - name: Install Conda environment with Micromamba + uses: mamba-org/provision-with-micromamba@v12 + with: + environment-file: tests/environment-unit-tests${{ matrix.extra }}.yml + environment-name: DEVELOP${{ matrix.extra }} + channels: conda-forge + cache-env: true + cache-env-key: ubuntu-latest-${{ matrix.python-version }}${{ matrix.extra }}. + extra-specs: | + python=${{matrix.python-version }} + - name: Install package + run: | + python -m pip install --no-deps -e . + - name: Run tests + run: | + make unit-tests + + distribution: + needs: [integration-tests, type-check, documentation] + if: ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v3 + with: + ref: ${{ github.event.pull_request.head.sha || github.ref }} + - name: Build distributions + run: | + $CONDA/bin/python -m pip install build + $CONDA/bin/python -m build + - name: Publish a Python distribution to PyPI + if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags') + uses: pypa/gh-action-pypi-publish@release/v1 + with: + user: __token__ + password: ${{ secrets.PYPI_API_TOKEN }} + + notify: + if: always() && ${{ !github.event.pull_request.head.repo.fork && github.event.action != 'labeled' || github.event.label.name == 'approved-for-ci' }} + needs: + - pre-commit + - unit-tests + - type-check + - documentation + - integration-tests + - distribution + runs-on: ubuntu-latest + steps: + - name: Trigger Teams notification + uses: ecmwf-actions/notify-teams@v1 + with: + incoming_webhook: ${{ secrets.MS_TEAMS_INCOMING_WEBHOOK }} + needs_context: ${{ toJSON(needs) }} diff --git a/.gitignore b/.gitignore index 206a455..913eabb 100644 --- a/.gitignore +++ b/.gitignore @@ -357,7 +357,10 @@ notebooks/data/*/ # local code _dev +_util ? ?.* tempCodeRunnerFile* dev/ +_util +docs/experimental diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 9a8a723..5ffa512 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -15,7 +15,7 @@ repos: hooks: - id: isort - repo: https://github.com/psf/black - rev: 23.3.0 + rev: 23.9.1 hooks: - id: black - repo: https://github.com/keewis/blackdoc @@ -24,7 +24,7 @@ repos: - id: blackdoc additional_dependencies: [black==23.3.0] - repo: https://github.com/PyCQA/flake8 - rev: 4.0.1 + rev: 6.1.0 hooks: - id: flake8 - repo: https://github.com/executablebooks/mdformat @@ -33,13 +33,12 @@ repos: - id: mdformat exclude: cruft-update-template.md - repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks - rev: v2.4.0 + rev: v2.11.0 hooks: - id: pretty-format-yaml args: [--autofix, --preserve-quotes] - id: pretty-format-toml args: [--autofix] - additional_dependencies: [toml-sort<0.22.0] - repo: https://github.com/PyCQA/pydocstyle.git rev: 6.1.1 hooks: diff --git a/.readthedocs.yml b/.readthedocs.yml index dd982fd..326f882 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -1,12 +1,9 @@ version: 2 formats: [] - build: os: "ubuntu-22.04" tools: - python: "3.8" - + python: "3.9" python: install: - requirements: docs/requirements.txt - system_packages: true diff --git a/README.md b/README.md index cc14706..40d415f 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,25 @@ # earthkit-meteo -Meteorological computations. + **DISCLAIMER** This project is **BETA** and will be **Experimental** for the foreseeable future. Interfaces and functionality are likely to change, and the project itself may be scrapped. **DO NOT** use this software in any project/software that is operational. +**earthkit-meteo** is a Python package providing meteorological computations using **numpy** input and output. + +```python +from earthkit.meteo import thermo +import numpy as np + +t = np.array([264.12, 261.45]) # Kelvins +p = np.array([850, 850]) * 100. # Pascals + +theta = thermo.potential_temperature(t, p) +``` + ## Documentation The documentation can be found at https://earthkit-meteo.readthedocs.io/. diff --git a/docs/_static/wind_direction.png b/docs/_static/wind_direction.png new file mode 100644 index 0000000..d19befb Binary files /dev/null and b/docs/_static/wind_direction.png differ diff --git a/docs/_static/wind_sector.png b/docs/_static/wind_sector.png new file mode 100644 index 0000000..6d36431 Binary files /dev/null and b/docs/_static/wind_sector.png differ diff --git a/docs/conf.py b/docs/conf.py index 05c02a9..cae2e00 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -55,6 +55,7 @@ autoapi_root = "_api" autoapi_member_order = "alphabetical" autoapi_add_toctree_entry = False +autoapi_own_page_level = "function" # napoleon configuration napoleon_google_docstring = False @@ -86,3 +87,9 @@ html_css_files = ["style.css"] html_logo = "_static/earthkit-meteo.png" + + +def setup(app): + from skip_api_rules import _skip_api_items + + app.connect("autoapi-skip-member", _skip_api_items) diff --git a/docs/index.rst b/docs/index.rst index a89df34..ad767bb 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -5,23 +5,33 @@ Welcome to earthkit-meteo's documentation This project is **BETA** and will be **Experimental** for the foreseeable future. Interfaces and functionality are likely to change, and the project itself may be scrapped. **DO NOT** use this software in any project/software that is operational. -.. warning:: - This documentation is still work in progress and can only be regarded as a **DRAFT**. +**earthkit-meteo** is a Python package providing meteorological computations using **numpy** input and output. +.. code-block:: python -.. toctree:: - :maxdepth: 1 - :caption: Examples - :titlesonly: + from earthkit.meteo import thermo + import numpy as np + + t = np.array([264.12, 261.45]) # Kelvins + p = np.array([850, 850]) * 100.0 # Pascals + + theta = thermo.potential_temperature(t, p) + + +.. .. toctree:: +.. :maxdepth: 1 +.. :caption: Examples +.. :titlesonly: - examples +.. examples .. toctree:: :maxdepth: 1 :caption: Documentation _api/meteo/index + references.rst .. toctree:: :maxdepth: 1 diff --git a/docs/references.rst b/docs/references.rst index b290bcf..d92ef2f 100644 --- a/docs/references.rst +++ b/docs/references.rst @@ -1,11 +1,51 @@ References ================ +.. [Bechtold2015] + +Bechtold, P., (2015). Atmospheric thermodynamics. Technical report, ECMWF Leture Notes, URL: https://www.ecmwf.int/sites/default/files/elibrary/2015/16954-atmospheric-thermodynamics.pdf + + .. [Biricombe2022] Brimicombe et al. (2022). doi: https://doi.org/10.21957/o7pcu1x2b +.. [Bolton1980] + +Bolton, D., (1980). The computation of equivalent potential temperature. Mon. Wea. Rev., 108, 1046-1053, doi: `10.1175/1520-0493(1980)108%3C1046:TCOEPT%3E2.0.CO;2 `_ + + +.. [DaviesJones1983] + +Davies-Jones, R. P., (1983). An accurate theoretical approximation for adiabatic condensation temperature. Mon. Wea. Rev., 111 , 1119–1121. + + +.. [DaviesJones2008] + +Davies-Jones, R., (2008). An Efficient and Accurate Method for Computing the Wet-Bulb Temperature +along Pseudoadiabats. Mon. Wea. Rev., 136, 2764-2785, doi: `10.1175/2007MWR2224.1 `_ + + +.. [Hersbach2000] + +Hersbach, H., (2000). Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems. Weather and Forecasting 15: 559-570. + + .. [Hogan_and_Hirahara2015] Hogan and Hirahara (2015). doi: https://doi.org/10.1002/2015GL066868 + + +.. [IFS-CY47R3-PhysicalProcesses] + +IFS Documentation CY47R3 - Part IV Physical processes, (2021). URL: https://www.ecmwf.int/en/elibrary/20198-ifs-documentation-cy47r3-part-iv-physical-processes + +.. [Stipanuk1973] + +Stipanuk, G. S., (1973). Algorithms for Generating a Skew-T, Log P Diagram and Computing Selected Meteorological Quantities. Atmospheric Sciences Laboratory, U.S. Army Electronics Command. White Sands Missile Range, New Mexico 88002. + + +.. [Wallace2006] + +Wallace, J. M and P. V. Hobbs, P. V., (2006). Atmospheric Science: An Introductory Survey. 2nd ed. Academic Press, 504 pp. diff --git a/docs/skip_api_rules.py b/docs/skip_api_rules.py new file mode 100644 index 0000000..e5a9159 --- /dev/null +++ b/docs/skip_api_rules.py @@ -0,0 +1,28 @@ +# (C) Copyright 2021 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. +# + + +# define skip rules for autoapi +def _skip_api_items(app, what, name, obj, skip, options): + # print(f"{what=} {name=}") + + if ( + what == "module" + and ".array" not in name + and name not in ["earthkit.meteo.solar", "earthkit.meteo.solar.array"] + ): + skip = True + elif what == "package" and ".array" not in name and len(name.split(".")) > 2: + skip = True + elif what == "function" and ".array" not in name: + skip = True + + # if not skip: + # print(f"{what} {name}") + return skip diff --git a/earthkit/meteo/__init__.py b/earthkit/meteo/__init__.py index c521135..d64217c 100644 --- a/earthkit/meteo/__init__.py +++ b/earthkit/meteo/__init__.py @@ -1,11 +1,11 @@ -# (C) Copyright 2023 ECMWF. +# (C) Copyright 2021 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. - +# try: # NOTE: the `version.py` file must not be present in the git repository diff --git a/tests/test_solar.py b/earthkit/meteo/constants/__init__.py similarity index 79% rename from tests/test_solar.py rename to earthkit/meteo/constants/__init__.py index 5643a00..afcccbb 100644 --- a/tests/test_solar.py +++ b/earthkit/meteo/constants/__init__.py @@ -1,13 +1,10 @@ -# (C) Copyright 2023 ECMWF. +# (C) Copyright 2021 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. +# -# import earthkit.meteo - - -def test_solar() -> None: - pass +from .constants import * # noqa diff --git a/earthkit/meteo/constants/constants.py b/earthkit/meteo/constants/constants.py new file mode 100644 index 0000000..adc1ba1 --- /dev/null +++ b/earthkit/meteo/constants/constants.py @@ -0,0 +1,80 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + +""" +Collection of meteorological constants in SI units. +""" + +# Thermodynamics. Values were taken form the IFS CY47r3 documentation. + +R = 8.31451 +r"""Universal gas constant [:math:`J K^{-1} mol^{-1}`]. +See [IFS-CY47R3-PhysicalProcesses]_ (Chapter 12).""" + +Rd = 287.0597 +r"""Gas constant for dry air [:math:`J kg^{-1} K^{-1}`]. +See [IFS-CY47R3-PhysicalProcesses]_ (Chapter 12).""" + +Rv = 461.51 +r"""Gas constant for water vapour [:math:`J kg^{-1} K^{-1}`]. + See [IFS-CY47R3-PhysicalProcesses]_ (Chapter 12).""" + +c_pd = 1004.79 +r"""Specific heat of dry air on constant pressure [:math:`J kg^{-1} K^{-1}`]. +See [IFS-CY47R3-PhysicalProcesses]_ (Chapter 12).""" + +c_pv = 1846.1 +r"""Specific heat of water vapour on constant pressure [:math:`J kg^{-1} K^{-1}`]. +See [IFS-CY47R3-PhysicalProcesses]_ (Chapter 12).""" + +Lv = 2.5008e6 +r"""Latent heat of vapourisation [:math:`J kg^{-1}`].""" + +kappa = 0.285691 +r"""Kappa coefficient used in adiabatic equations :math:`\kappa = \frac{R_{d}}{C_{pd}}`.""" + +p0 = 1e5 +r"""Reference pressure used in potential temperature calculations [Pa].""" + +epsilon = 0.621981 +r"""Epsilon coefficient used in humidity formulas :math:`\epsilon = \frac{R_{d}}{R_{v}}`.""" + +T0 = 273.16 +r"""Triple point of water [K].""" + +g = 9.80665 +r"""Gravitational acceleration on the surface of the Earth [:math:`m s^{-2}`]. +See [IFS-CY47R3-PhysicalProcesses]_ (Chapter 12).""" + +R_earth = 6371229 +r"""Average radius of the Earth [:math:`m`]. See [IFS-CY47R3-PhysicalProcesses]_ + (Chapter 12).""" + +solar_day = 86400 +r"""Length of the solar day [:math:`s`].""" + +sideral_year = 365.25 * solar_day * 2 * np.pi / 6.283076 +r"""Length of the sideral year [:math:`s`]. +Defined as :math:`\frac{2\pi\times 365.25\times solar\_day}{6.283076}`.""" + +sideral_day = solar_day / (1.0 + solar_day / sideral_year) +r"""Length of the sideral day [:math:`s`]. +Defined as :math:`\frac{solar\_day}{1 + \frac{solar\_day}{sideral\_year}}`.""" + +omega = 2.0 * np.pi / sideral_day +r"""Rotation rate of the Earth [:math:`s^{-1}`]. +Defined as :math:`\frac{2\pi}{sideral\_day}`.""" + +degree = 180.0 / np.pi +r"""Factor for converting radians to degrees.""" + +radian = 1.0 / degree +r"""Factor for converting degrees to radians.""" diff --git a/earthkit/meteo/extreme/__init__.py b/earthkit/meteo/extreme/__init__.py new file mode 100644 index 0000000..d3ee0b6 --- /dev/null +++ b/earthkit/meteo/extreme/__init__.py @@ -0,0 +1,20 @@ +# (C) Copyright 2021 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. +# + +""" +Extreme index functions. + +The API is split into two levels. The low level functions are in the ``array`` submodule and they +can be used to operate on numpy arrays. The high level functions are still to be developed and +planned to work with objects like *earthkit.data FieldLists* or *xarray DataSets*. +""" + +from .cpf import * # noqa +from .efi import * # noqa +from .sot import * # noqa diff --git a/earthkit/meteo/extreme/array/__init__.py b/earthkit/meteo/extreme/array/__init__.py new file mode 100644 index 0000000..dcf2242 --- /dev/null +++ b/earthkit/meteo/extreme/array/__init__.py @@ -0,0 +1,16 @@ +# (C) Copyright 2021 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. +# + +""" +Extreme index functions operating on numpy arrays. +""" + +from .cpf import * # noqa +from .efi import * # noqa +from .sot import * # noqa diff --git a/earthkit/meteo/extreme/array/cpf.py b/earthkit/meteo/extreme/array/cpf.py new file mode 100644 index 0000000..16596de --- /dev/null +++ b/earthkit/meteo/extreme/array/cpf.py @@ -0,0 +1,99 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + + +def cpf(clim, ens, sort_clim=True, sort_ens=True): + """Compute Crossing Point Forecast (CPF) + + WARNING: this code is experimental, use at your own risk! + + Parameters + ---------- + clim: numpy array (nclim, npoints) + Per-point climatology + ens: numpy array (nens, npoints) + Ensemble forecast + sort_clim: bool + If True, sort the climatology first + sort_ens: bool + If True, sort the ensemble first + + Returns + ------- + numpy array (npoints) + CPF values + """ + nclim, npoints = clim.shape + nens, npoints_ens = ens.shape + assert npoints == npoints_ens + + cpf = np.ones(npoints, dtype=np.float32) + mask = np.zeros(npoints, dtype=np.bool_) + + if sort_clim: + clim = np.sort(clim, axis=0) + if sort_ens: + ens = np.sort(ens, axis=0) + + for icl in range(1, nclim - 1): + # quantile level of climatology + tau_c = icl / (nclim - 1.0) + for iq in range(nens): + # quantile level of forecast + tau_f = (iq + 1.0) / (nens + 1.0) + if tau_f >= tau_c: + # quantile values of forecast and climatology + qv_f = ens[iq, :] + qv_c = clim[icl, :] + + # lowest climate quantile: interpolate between 2 consecutive quantiles + if iq < 2: + # quantile value and quantile level of climatology at previous + qv_c_2 = clim[icl - 1, :] + tau_c_2 = (icl - 1) / (nclim - 1) + + # condition of crossing situtaion: + idx = (qv_f < qv_c) & (qv_c_2 < qv_c) + + # intersection between two lines + tau_i = ( + tau_c * (qv_c_2[idx] - qv_f[idx]) + + tau_c_2 * (qv_f[idx] - qv_c[idx]) + ) / (qv_c_2[idx] - qv_c[idx]) + + # populate matrix, no values below 0 + cpf[idx] = np.maximum(tau_i, 0) + mask[idx] = True + + # check crossing cases + idx = (qv_f < qv_c) & (~mask) + cpf[idx] = tau_f + mask[idx] = True + + # largest climate quantile: interpolate + if iq == nens - 1: + qv_c_2 = clim[nclim - 1, :] + tau_c_2 = 1.0 + + idx = (qv_f > qv_c) & (qv_c_2 > qv_c) & (~mask) + + tau_i = ( + tau_c * (qv_c_2[idx] - qv_f[idx]) + + tau_c_2 * (qv_f[idx] - qv_c[idx]) + ) / (qv_c_2[idx] - qv_c[idx]) + + # populate matrix, no values above 1 + cpf[idx] = np.minimum(tau_i, 1) + + # speed up process + break + + return cpf diff --git a/earthkit/meteo/extreme/array/efi.py b/earthkit/meteo/extreme/array/efi.py new file mode 100644 index 0000000..455222b --- /dev/null +++ b/earthkit/meteo/extreme/array/efi.py @@ -0,0 +1,148 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + +# import numba +# from numba import float64, float32 + + +def efi(clim, ens, eps=-0.1): + """Compute Extreme Forecast Index (EFI) + + Parameters + ---------- + clim: numpy array (nclim, npoints) + Sorted per-point climatology + ens: numpy array (nens, npoints) + Ensemble forecast + eps: (float) + Epsilon factor for zero values + + Returns + ------- + numpy array (npoints) + EFI values + """ + # locate missing values + missing_mask = np.logical_or( + np.sum(np.isnan(clim), axis=0), np.sum(np.isnan(ens), axis=0) + ) + + # Compute fraction of the forecast below climatology + nclim, npoints = clim.shape + nens, npoints_ens = ens.shape + assert npoints == npoints_ens + frac = np.zeros_like(clim) + ################################## + for icl in range(nclim): + frac[icl, :] = np.sum(ens[:, :] <= clim[icl, np.newaxis, :], axis=0) + ################################## + frac /= nens + + # Compute formula coefficients + p = np.linspace(0.0, 1.0, nclim) + dp = 1 / (nclim - 1) + dFdp = np.diff(frac, axis=0) / dp + + acosdiff = np.diff(np.arccos(np.sqrt(p))) + proddiff = np.diff(np.sqrt(p * (1.0 - p))) + + acoef = (1.0 - 2.0 * p[:-1]) * acosdiff + proddiff + + # compute EFI from coefficients + efi = np.zeros(npoints) + ################################## + if eps > 0: + efimax = np.zeros(npoints) + for icl in range(nclim - 1): + mask = clim[icl + 1, :] > eps + dEFI = np.where( + mask, + (2.0 * frac[icl, :] - 1.0) * acosdiff[icl] + + acoef[icl] * dFdp[icl, :] + - proddiff[icl], + 0.0, + ) + defimax = np.where(mask, -acosdiff[icl] - proddiff[icl], 0.0) + efi += dEFI + efimax += defimax + efimax = np.fmax(efimax, eps) + efi /= efimax + else: + for icl in range(nclim - 1): + dEFI = ( + (2.0 * frac[icl, :] - 1.0) * acosdiff[icl] + + acoef[icl] * dFdp[icl, :] + - proddiff[icl] + ) + efi += dEFI + efi *= 2.0 / np.pi + ################################## + + # apply missing values + efi[missing_mask] = np.nan + + return efi + + +# @numba.jit(float64[:](float64[:,:], float64[:,:]), fastmath=False, nopython=True, nogil=True, cache=True) +# @numba.jit(nopython=True) +# def efi_numba(clim, ens): +# """Compute EFI + +# Parameters +# ---------- +# clim: numpy array (nclim, npoints) +# Sorted per-point climatology +# ens: numpy array (nens, npoints) +# Ensemble forecast + +# Returns +# ------- +# numpy array (npoints) +# EFI values +# """ + +# # Compute fraction of the forecast below climatology +# nclim, npoints = clim.shape +# nens, npoints_ens = ens.shape +# assert npoints == npoints_ens +# frac = np.zeros_like(clim) +# ################################## +# for ifo in numba.prange(nens): +# for icl in range(nclim): +# for i in range(npoints): +# if ens[ifo, i] <= clim[icl, i]: +# frac[icl, i] += 1 +# ################################## +# frac /= nens + +# # Compute formula coefficients +# p = np.linspace(0., 1., nclim) +# dp = 1 / (nclim - 1) #np.diff(p) + +# acosdiff = np.diff(np.arccos(np.sqrt(p))) +# proddiff = np.diff(np.sqrt(p * (1. - p))) + +# acoef = (1. - 2. * p[:-1]) * acosdiff + proddiff + +# # TODO: handle epsilon +# efi = np.zeros(npoints) +# ################################## +# for icl in numba.prange(nclim-1): +# for i in range(npoints): +# dFdp = (frac[icl+1, i] - frac[icl, i]) / dp +# # XXX: why proddiff here?! +# dEFI = (2. * frac[icl, i] - 1.) * acosdiff[icl] + acoef[icl] * dFdp - proddiff[icl] +# efi[i] += dEFI +# efi *= 2. / np.pi +# ################################## + +# return efi diff --git a/earthkit/meteo/extreme/array/sot.py b/earthkit/meteo/extreme/array/sot.py new file mode 100644 index 0000000..f556afa --- /dev/null +++ b/earthkit/meteo/extreme/array/sot.py @@ -0,0 +1,173 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + + +def sot_func(qc_tail, qc, qf, eps=-1e-4, lower_bound=-10, upper_bound=10): + """Compute basic Shift of Tails (SOT) + using already computed percentiles + + Parameters + ---------- + qc_tail: numpy array (npoints) + Tail percentile value (99% or 1%) + Model climatology + qc: numpy array (npoints) + Upper or lower percentile (at 90% or 10%) + Model climatology + qf: numpy array (npoints) + Upper or lower percentile (at 90% or 10%) + Ensemble forecast + eps: (float) + Epsilon factor for zero values + missing: (float) + missing points values where denominator is zero + + Returns + ------- + numpy array (npoints) + SOT values + """ + # avoid divided by zero warning + err = np.seterr(divide="ignore", invalid="ignore") + + min_den = np.fmax(eps, 0) + sot = np.where( + np.fabs(qc_tail - qc) > min_den, (qf - qc_tail) / (qc_tail - qc), np.nan + ) + + # revert to original error state + np.seterr(**err) + + mask_missing = np.isnan(sot) + + # upper and lower bounds + mask2 = np.logical_and(np.logical_not(mask_missing), sot < lower_bound) + sot[mask2] = lower_bound + mask3 = np.logical_and(np.logical_not(mask_missing), sot > upper_bound) + sot[mask3] = upper_bound + + return sot + + +def sot(clim, ens, perc, eps=-1e4): + """Compute Shift of Tails (SOT) + from climatology percentiles (sorted) + and ensemble forecast (not sorted) + + Parameters + ---------- + clim: numpy array (nclim, npoints) + Model climatology (percentiles) + ens: numpy array (nens, npoints) + Ensemble forecast + perc: int + Percentile value (typically 10 or 90) + eps: (float) + Epsilon factor for zero values + + Returns + ------- + numpy array (npoints) + SOT values + """ + if not (isinstance(perc, int) or isinstance(perc, np.int64)) or ( + perc < 2 or perc > 98 + ): + raise Exception( + "Percentile value should be and Integer between 2 and 98, is {}".format( + perc + ) + ) + + if clim.shape[0] != 101: + raise Exception( + "Climatology array should contain 101 percentiles, it has {} values".format( + clim.shape + ) + ) + + qc = clim[perc] + # if eps>0, set to zero everything below eps + if eps > 0: + ens = np.where(ens < eps, 0.0, ens) + qc = np.where(qc < eps, 0.0, qc) + + qf = np.percentile(ens, q=perc, axis=0) + if perc > 50: + qc_tail = clim[99] + elif perc < 50: + qc_tail = clim[1] + else: + raise Exception( + "Percentile value to be computed cannot be 50 for sot, has to be in the upper or lower half" + ) + + sot = sot_func(qc_tail, qc, qf, eps=eps) + + return sot + + +def sot_unsorted(clim, ens, perc, eps=-1e4): + """Compute Shift of Tails (SOT) + from climatology percentiles (sorted) + and ensemble forecast (not sorted) + + Parameters + ---------- + clim: numpy array (nclim, npoints) + Model climatology (percentiles) + ens: numpy array (nens, npoints) + Ensemble forecast + perc: int + Percentile value (typically 10 or 90) + eps: (float) + Epsilon factor for zero values + + Returns + ------- + numpy array (npoints) + SOT values + """ + if not (isinstance(perc, int) or isinstance(perc, np.int64)) or ( + perc < 2 or perc > 98 + ): + raise Exception( + "Percentile value should be and Integer between 2 and 98, is {}".format( + perc + ) + ) + + if clim.shape[0] != 101: + raise Exception( + "Climatology array should contain 101 percentiles, it has {} values".format( + clim.shape + ) + ) + + if eps > 0: + ens = np.where(ens < eps, 0.0, ens) + clim = np.where(clim < eps, 0.0, clim) + + qf = np.percentile(ens, q=perc, axis=0) + qc = np.percentile(clim, q=perc, axis=0) + if perc > 50: + perc_tail = 99 + elif perc < 50: + perc_tail = 1 + else: + raise Exception( + "Percentile value to be computed cannot be 50 for sot, has to be in the upper or lower half" + ) + qc_tail = np.percentile(clim, q=perc_tail, axis=0) + + sot = sot_func(qc_tail, qc, qf, eps=eps) + + return sot diff --git a/earthkit/meteo/extreme/cpf.py b/earthkit/meteo/extreme/cpf.py new file mode 100644 index 0000000..5b9e88a --- /dev/null +++ b/earthkit/meteo/extreme/cpf.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +from . import array # noqa + + +def cpf(*args, **kwargs): + return array.cpf(*args, **kwargs) diff --git a/earthkit/meteo/extreme/efi.py b/earthkit/meteo/extreme/efi.py new file mode 100644 index 0000000..cb312b1 --- /dev/null +++ b/earthkit/meteo/extreme/efi.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +from . import array # noqa + + +def efi(*args, **kwargs): + return array.efi(*args, **kwargs) diff --git a/earthkit/meteo/extreme/sot.py b/earthkit/meteo/extreme/sot.py new file mode 100644 index 0000000..7546d4a --- /dev/null +++ b/earthkit/meteo/extreme/sot.py @@ -0,0 +1,18 @@ +# (C) Copyright 2021 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. +# + +from . import array # noqa + + +def sot(*args, **kwargs): + return array.sot(*args, **kwargs) + + +def sot_unsorted(*args, **kwargs): + return array.sot_unsorted(*args, **kwargs) diff --git a/earthkit/meteo/score/__init__.py b/earthkit/meteo/score/__init__.py new file mode 100644 index 0000000..f11e64d --- /dev/null +++ b/earthkit/meteo/score/__init__.py @@ -0,0 +1,18 @@ +# (C) Copyright 2021 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. +# + +""" +Verification functions. + +The API is split into two levels. The low level functions are in the ``array`` submodule and they +can be used to operate on numpy arrays. The high level functions are still to be developed and +planned to work with objects like *earthkit.data FieldLists* or *xarray DataSets*. +""" + +from .crps import * # noqa diff --git a/earthkit/meteo/score/array/__init__.py b/earthkit/meteo/score/array/__init__.py new file mode 100644 index 0000000..ba1acf9 --- /dev/null +++ b/earthkit/meteo/score/array/__init__.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +""" +Verification functions operating on numpy arrays. +""" + +from .crps import * # noqa diff --git a/earthkit/meteo/score/array/crps.py b/earthkit/meteo/score/array/crps.py new file mode 100644 index 0000000..9595094 --- /dev/null +++ b/earthkit/meteo/score/array/crps.py @@ -0,0 +1,60 @@ +# +# # (C) Copyright 2021 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. +# ## +import numpy as np + + +def crps(x, y): + """Computes Continuous Ranked Probability Score (CRPS). + + Parameters + ---------- + x: numpy array (n_ens, n_points) + Ensemble forecast + y: numpy array (n_points) + Observation/analysis + + Returns + ------- + numpy array (n_points) + CRPS values + + + The method is described in [Hersbach2000]_. + """ + # first sort ensemble + x.sort(axis=0) + + # construct alpha and beta, size nens+1 + n_ens = x.shape[0] + shape = (n_ens + 1,) + x.shape[1:] + alpha = np.zeros(shape) + beta = np.zeros(shape) + + # x[i+1]-x[i] and x[i]-y[i] arrays + diffxy = x - y.reshape(1, *(y.shape)) + diffxx = x[1:] - x[:-1] # x[i+1]-x[i], size ens-1 + + # if i == 0 + alpha[0] = 0 + beta[0] = np.fmax(diffxy[0], 0) # x(0)-y + # if i == n_ens + alpha[-1] = np.fmax(-diffxy[-1], 0) # y-x(n) + beta[-1] = 0 + # else + alpha[1:-1] = np.fmin( + diffxx, np.fmax(-diffxy[:-1], 0) + ) # x(i+1)-x(i) or y-x(i) or 0 + beta[1:-1] = np.fmin(diffxx, np.fmax(diffxy[1:], 0)) # 0 or x(i+1)-y or x(i+1)-x(i) + + # compute crps + p_exp = (np.arange(n_ens + 1) / float(n_ens)).reshape(n_ens + 1, *([1] * y.ndim)) + crps = np.sum(alpha * (p_exp**2) + beta * ((1 - p_exp) ** 2), axis=0) + + return crps diff --git a/earthkit/meteo/score/crps.py b/earthkit/meteo/score/crps.py new file mode 100644 index 0000000..4423b84 --- /dev/null +++ b/earthkit/meteo/score/crps.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +from . import array + + +def crps(*args, **kwargs): + return array.crps(*args, **kwargs) diff --git a/earthkit/meteo/solar/__init__.py b/earthkit/meteo/solar/__init__.py index 212bb87..9bad33c 100644 --- a/earthkit/meteo/solar/__init__.py +++ b/earthkit/meteo/solar/__init__.py @@ -1,240 +1,19 @@ -# (C) Copyright 2023 ECMWF. +# (C) Copyright 2021 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. +# -import datetime - -import numpy as np - -DAYS_PER_YEAR = 365.25 """ -WARNING: This code is incomplete and not tested. DO NOT USE. -""" - - -def julian_day(date): - delta = date - datetime.datetime(date.year, 1, 1) - return delta.days + delta.seconds / 86400.0 - - -def solar_declination_angle(date): - angle = julian_day(date) / DAYS_PER_YEAR * np.pi * 2 - - # declination in [degrees] - declination = ( - 0.396372 - - 22.91327 * np.cos(angle) - + 4.025430 * np.sin(angle) - - 0.387205 * np.cos(2 * angle) - + 0.051967 * np.sin(2 * angle) - - 0.154527 * np.cos(3 * angle) - + 0.084798 * np.sin(3 * angle) - ) - # time correction in [ h.degrees ] - time_correction = ( - 0.004297 - + 0.107029 * np.cos(angle) - - 1.837877 * np.sin(angle) - - 0.837378 * np.cos(2 * angle) - - 2.340475 * np.sin(2 * angle) - ) - return declination, time_correction - - -def cos_solar_zenith_angle(date, latitudes, longitudes): - """Cosine of solar zenith angle. - - Parameters - ---------- - date: datetime.datetime - Date - lat: float array - Latitude [degrees] - lon: float array - Longitude [degrees] - - Returns - ------- - float array - Cosine of the solar zenith angle (all values, including negatives) - [Hogan_and_Hirahara2015]_. See also: - http://answers.google.com/answers/threadview/id/782886.html - - """ - # declination angle + time correction for solar angle - declination, time_correction = solar_declination_angle(date) - - # solar_declination_angle returns degrees - declination = np.deg2rad(declination) - - latitudes = np.deg2rad(latitudes) - - sindec_sinlat = np.sin(declination) * np.sin(latitudes) - cosdec_coslat = np.cos(declination) * np.cos(latitudes) - - # solar hour angle [h.deg] - solar_angle = np.deg2rad((date.hour - 12) * 15 + longitudes + time_correction) - zenith_angle = sindec_sinlat + cosdec_coslat * np.cos(solar_angle) - - # Clip negative values - return np.clip(zenith_angle, 0, None) - +Solar computation functions. -def _integrate( - func, - begin_date, - end_date, - latitudes, - longitudes, - *, - intervals_per_hour=1, - integration_order=3, -): - # Gauss-Integration coefficients - if integration_order == 3: # default, good speed and accuracy (3 points) - E = np.array([-np.sqrt(3.0 / 5.0), 0.0, np.sqrt(3.0 / 5.0)]) - W = np.array([5.0 / 9.0, 8.0 / 9.0, 5.0 / 9.0]) - elif integration_order == 1: # fastest, worse accuracy (1 point) - E = np.array([0.0]) - W = np.array([2.0]) - elif integration_order == 2: # faster, less accurate (2 points) - E = np.array([-1.0 / np.sqrt(3.0), 1.0 / np.sqrt(3.0)]) - W = np.array([1.0, 1.0]) - elif integration_order == 4: # slower, more accurate (4 points) - E = np.array( - [ - -np.sqrt(3.0 / 7.0 + 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), - -np.sqrt(3.0 / 7.0 - 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), - np.sqrt(3.0 / 7.0 - 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), - np.sqrt(3.0 / 7.0 + 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), - ] - ) - W = np.array( - [ - (18 - np.sqrt(30)) / 36, - (18 + np.sqrt(30)) / 36, - (18 + np.sqrt(30)) / 36, - (18 - np.sqrt(30)) / 36, - ] - ) - else: - raise ValueError("Invalid integration order %d", integration_order) - - assert intervals_per_hour > 0 - assert end_date > begin_date - - date = begin_date - interval_size_hours = (end_date - begin_date).total_seconds() / 3600.0 - - nsplits = int(interval_size_hours * intervals_per_hour + 0.5) - - assert nsplits > 0 - - time_steps = np.linspace(0, interval_size_hours, num=nsplits + 1) - - integral = np.zeros_like(latitudes) - for s in range(len(time_steps) - 1): - ti = time_steps[s] - tf = time_steps[s + 1] - - deltat = tf - ti - jacob = deltat / 2.0 - - w = jacob * W - w /= interval_size_hours # average of integral - t = jacob * E - t += (tf + ti) / 2.0 - - for n in range(len(w)): - integral += w[n] * func( - date + datetime.timedelta(hours=t[n]), - latitudes, - longitudes, - ) - - return integral - - -def cos_solar_zenith_angle_integrated( - begin_date, - end_date, - latitudes, - longitudes, - *, - intervals_per_hour=1, - integration_order=3, -): - """Average of solar zenith angle based on numerical integration. - - Parameters - ---------- - begin_date: datetime.datetime - end_date: datetime.datetime - lat: int darray - Latitude [degrees]. - lon: int darray - Longitude [degrees]. - tbegin: int - Offset in hours from forecast time to begin of time interval for integration. - tend: int - Offset in hours from forecast time to end of time interval for integration. - intervals_per_hour: int - Number of time integrations per hour. - integration order: int - Order of gauss integration, valid = (1, 2, 3, 4) - - Returns - ------- - float array - Average of cosine of the solar zenith angle during interval [degrees]. Based on - numerical integration using the 3 point - `Gauss integration `_ rule. - [Hogan_and_Hirahara2015]_, [Biricombe2022]_ - - """ - return _integrate( - cos_solar_zenith_angle, - begin_date, - end_date, - latitudes, - longitudes, - intervals_per_hour=intervals_per_hour, - integration_order=integration_order, - ) - - -def incoming_solar_radiation(date): - # To be replaced with improved formula - (a, b) = (165120.0, 4892416.0) - angle = julian_day(date) / DAYS_PER_YEAR * np.pi * 2 - return np.cos(angle) * a + b - - -def toa_incident_solar_radiation( - begin_date, - end_date, - latitudes, - longitudes, - *, - intervals_per_hour=1, - integration_order=3, -): - def func(date, latitudes, longitudes): - isr = incoming_solar_radiation(date) - csza = cos_solar_zenith_angle(date, latitudes, longitudes) - return isr * csza +The API is split into two levels. The low level functions are in the ``array`` submodule and they +can be used to operate on numpy arrays. The high level functions are still to be developed and +planned to work with objects like *earthkit.data FieldLists* or *xarray DataSets* +""" - return _integrate( - func, - begin_date, - end_date, - latitudes, - longitudes, - intervals_per_hour=intervals_per_hour, - integration_order=integration_order, - ) +from .solar import * # noqa diff --git a/earthkit/meteo/solar/array/__init__.py b/earthkit/meteo/solar/array/__init__.py new file mode 100644 index 0000000..da2e210 --- /dev/null +++ b/earthkit/meteo/solar/array/__init__.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +""" +Solar computation functions operating on numpy arrays. +""" + +from .solar import * # noqa diff --git a/earthkit/meteo/solar/array/solar.py b/earthkit/meteo/solar/array/solar.py new file mode 100644 index 0000000..21848b4 --- /dev/null +++ b/earthkit/meteo/solar/array/solar.py @@ -0,0 +1,241 @@ +# (C) Copyright 2021 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. +# + +import datetime + +import numpy as np + +DAYS_PER_YEAR = 365.25 + +""" +WARNING: This code is incomplete and not tested. DO NOT USE. +""" + + +def julian_day(date): + delta = date - datetime.datetime(date.year, 1, 1) + return delta.days + delta.seconds / 86400.0 + + +def solar_declination_angle(date): + angle = julian_day(date) / DAYS_PER_YEAR * np.pi * 2 + + # declination in [degrees] + declination = ( + 0.396372 + - 22.91327 * np.cos(angle) + + 4.025430 * np.sin(angle) + - 0.387205 * np.cos(2 * angle) + + 0.051967 * np.sin(2 * angle) + - 0.154527 * np.cos(3 * angle) + + 0.084798 * np.sin(3 * angle) + ) + # time correction in [ h.degrees ] + time_correction = ( + 0.004297 + + 0.107029 * np.cos(angle) + - 1.837877 * np.sin(angle) + - 0.837378 * np.cos(2 * angle) + - 2.340475 * np.sin(2 * angle) + ) + return declination, time_correction + + +def cos_solar_zenith_angle(date, latitudes, longitudes): + """Cosine of solar zenith angle. + + Parameters + ---------- + date: datetime.datetime + Date + lat: float array + Latitude [degrees] + lon: float array + Longitude [degrees] + + Returns + ------- + float array + Cosine of the solar zenith angle (all values, including negatives) + [Hogan_and_Hirahara2015]_. See also: + http://answers.google.com/answers/threadview/id/782886.html + + """ + # declination angle + time correction for solar angle + declination, time_correction = solar_declination_angle(date) + + # solar_declination_angle returns degrees + declination = np.deg2rad(declination) + + latitudes = np.deg2rad(latitudes) + + sindec_sinlat = np.sin(declination) * np.sin(latitudes) + cosdec_coslat = np.cos(declination) * np.cos(latitudes) + + # solar hour angle [h.deg] + solar_angle = np.deg2rad((date.hour - 12) * 15 + longitudes + time_correction) + zenith_angle = sindec_sinlat + cosdec_coslat * np.cos(solar_angle) + + # Clip negative values + return np.clip(zenith_angle, 0, None) + + +def _integrate( + func, + begin_date, + end_date, + latitudes, + longitudes, + *, + intervals_per_hour=1, + integration_order=3, +): + # Gauss-Integration coefficients + if integration_order == 3: # default, good speed and accuracy (3 points) + E = np.array([-np.sqrt(3.0 / 5.0), 0.0, np.sqrt(3.0 / 5.0)]) + W = np.array([5.0 / 9.0, 8.0 / 9.0, 5.0 / 9.0]) + elif integration_order == 1: # fastest, worse accuracy (1 point) + E = np.array([0.0]) + W = np.array([2.0]) + elif integration_order == 2: # faster, less accurate (2 points) + E = np.array([-1.0 / np.sqrt(3.0), 1.0 / np.sqrt(3.0)]) + W = np.array([1.0, 1.0]) + elif integration_order == 4: # slower, more accurate (4 points) + E = np.array( + [ + -np.sqrt(3.0 / 7.0 + 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), + -np.sqrt(3.0 / 7.0 - 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), + np.sqrt(3.0 / 7.0 - 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), + np.sqrt(3.0 / 7.0 + 2.0 / 7.0 * np.sqrt(6.0 / 5.0)), + ] + ) + W = np.array( + [ + (18 - np.sqrt(30)) / 36, + (18 + np.sqrt(30)) / 36, + (18 + np.sqrt(30)) / 36, + (18 - np.sqrt(30)) / 36, + ] + ) + else: + raise ValueError("Invalid integration order %d", integration_order) + + assert intervals_per_hour > 0 + assert end_date > begin_date + + date = begin_date + interval_size_hours = (end_date - begin_date).total_seconds() / 3600.0 + + nsplits = int(interval_size_hours * intervals_per_hour + 0.5) + + assert nsplits > 0 + + time_steps = np.linspace(0, interval_size_hours, num=nsplits + 1) + + integral = np.zeros_like(latitudes) + for s in range(len(time_steps) - 1): + ti = time_steps[s] + tf = time_steps[s + 1] + + deltat = tf - ti + jacob = deltat / 2.0 + + w = jacob * W + w /= interval_size_hours # average of integral + t = jacob * E + t += (tf + ti) / 2.0 + + for n in range(len(w)): + integral += w[n] * func( + date + datetime.timedelta(hours=t[n]), + latitudes, + longitudes, + ) + + return integral + + +def cos_solar_zenith_angle_integrated( + begin_date, + end_date, + latitudes, + longitudes, + *, + intervals_per_hour=1, + integration_order=3, +): + """Average of solar zenith angle based on numerical integration. + + Parameters + ---------- + begin_date: datetime.datetime + end_date: datetime.datetime + lat: int darray + Latitude [degrees]. + lon: int darray + Longitude [degrees]. + tbegin: int + Offset in hours from forecast time to begin of time interval for integration. + tend: int + Offset in hours from forecast time to end of time interval for integration. + intervals_per_hour: int + Number of time integrations per hour. + integration order: int + Order of gauss integration, valid = (1, 2, 3, 4) + + Returns + ------- + float array + Average of cosine of the solar zenith angle during interval [degrees]. Based on + numerical integration using the 3 point + `Gauss integration `_ rule. + [Hogan_and_Hirahara2015]_, [Biricombe2022]_ + + """ + return _integrate( + cos_solar_zenith_angle, + begin_date, + end_date, + latitudes, + longitudes, + intervals_per_hour=intervals_per_hour, + integration_order=integration_order, + ) + + +def incoming_solar_radiation(date): + # To be replaced with improved formula + (a, b) = (165120.0, 4892416.0) + angle = julian_day(date) / DAYS_PER_YEAR * np.pi * 2 + return np.cos(angle) * a + b + + +def toa_incident_solar_radiation( + begin_date, + end_date, + latitudes, + longitudes, + *, + intervals_per_hour=1, + integration_order=3, +): + def func(date, latitudes, longitudes): + isr = incoming_solar_radiation(date) + csza = cos_solar_zenith_angle(date, latitudes, longitudes) + return isr * csza + + return _integrate( + func, + begin_date, + end_date, + latitudes, + longitudes, + intervals_per_hour=intervals_per_hour, + integration_order=integration_order, + ) diff --git a/earthkit/meteo/solar/solar.py b/earthkit/meteo/solar/solar.py new file mode 100644 index 0000000..77c754b --- /dev/null +++ b/earthkit/meteo/solar/solar.py @@ -0,0 +1,34 @@ +# (C) Copyright 2021 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. +# + +from . import array + + +def julian_day(*args, **kwargs): + return array.julian_day(*args, **kwargs) + + +def solar_declination_angle(*args, **kwargs): + return array.solar_declination_angle(*args, **kwargs) + + +def cos_solar_zenith_angle(*args, **kwargs): + return array.cos_solar_zenith_angle(*args, **kwargs) + + +def cos_solar_zenith_angle_integrated(*args, **kwargs): + return array.cos_solar_zenith_angle_integrated(*args, **kwargs) + + +def incoming_solar_radiation(*args, **kwargs): + return array.incoming_solar_radiation(*args, **kwargs) + + +def toa_incident_solar_radiation(*args, **kwargs): + return array.toa_incident_solar_radiation(*args, **kwargs) diff --git a/earthkit/meteo/stats/__init__.py b/earthkit/meteo/stats/__init__.py new file mode 100644 index 0000000..af8730a --- /dev/null +++ b/earthkit/meteo/stats/__init__.py @@ -0,0 +1,19 @@ +# (C) Copyright 2021 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. +# + +""" +Statistical functions. + +The API is split into two levels. The low level functions are in the ``array`` submodule and they +can be used to operate on numpy arrays. The high level functions are still to be developed and +planned to work with objects like *earthkit.data FieldLists* or *xarray DataSets*. +""" + +from .numpy_extended import * # noqa +from .quantiles import * # noqa diff --git a/earthkit/meteo/stats/array/__init__.py b/earthkit/meteo/stats/array/__init__.py new file mode 100644 index 0000000..e43761a --- /dev/null +++ b/earthkit/meteo/stats/array/__init__.py @@ -0,0 +1,15 @@ +# (C) Copyright 2021 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. +# + +""" +Statistical functions operating on numpy arrays. +""" + +from .numpy_extended import * # noqa +from .quantiles import * # noqa diff --git a/earthkit/meteo/stats/array/numpy_extended.py b/earthkit/meteo/stats/array/numpy_extended.py new file mode 100644 index 0000000..7f78884 --- /dev/null +++ b/earthkit/meteo/stats/array/numpy_extended.py @@ -0,0 +1,55 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + + +def nanaverage(data, weights=None, **kwargs): + """A merge of the functionality of np.nanmean and np.average. + + Parameters + ---------- + data : numpy array + weights: Weights to apply to the data for averaging. + Weights will be normalised and must correspond to the + shape of the numpy data array and axis/axes that is/are + averaged over. + axis: axis/axes to compute the nanaverage over. + kwargs: any other np.nansum kwargs + + Returns + ------- + numpy array + mean of data (along axis) where nan-values are ignored + and weights applied if provided. + """ + if weights is not None: + # set weights to nan where data is nan: + this_weights = np.ones(data.shape) * weights + this_weights[np.isnan(data)] = np.nan + # Weights must be scaled to the sum of valid + # weights for each relevant axis: + this_denom = np.nansum(this_weights, **kwargs) + # If averaging over an axis then we must add dummy + # dimension[s] to the denominator to make compatible + # with the weights. + if kwargs.get("axis", None) is not None: + reshape = list(this_weights.shape) + reshape[kwargs.get("axis")] = 1 + this_denom = this_denom.reshape(reshape) + + # Scale weights to mean of valid weights: + this_weights = this_weights / this_denom + # Apply weights to data: + nanaverage = np.nansum(data * this_weights, **kwargs) + else: + # If no weights, then nanmean will suffice + nanaverage = np.nanmean(data, **kwargs) + + return nanaverage diff --git a/earthkit/meteo/stats/array/quantiles.py b/earthkit/meteo/stats/array/quantiles.py new file mode 100644 index 0000000..33e1cd6 --- /dev/null +++ b/earthkit/meteo/stats/array/quantiles.py @@ -0,0 +1,77 @@ +# (C) Copyright 2021 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. +# + +from typing import Iterable, List, Union + +import numpy as np + + +def iter_quantiles( + arr: np.ndarray, + which: Union[int, List[float]] = 100, + axis: int = 0, + method: str = "sort", +) -> Iterable[np.ndarray]: + """Iterate over the quantiles of a large array + + Parameters + ---------- + arr: numpy array + Data array + which: int or list of floats + List of quantiles to compute, e.g. `[0., 0.25, 0.5, 0.75, 1.]`, or + number of evenly-spaced intervals (e.g. 100 for percentiles). + axis: int + Axis along which to compute the quantiles + method: 'sort', 'numpy_bulk', 'numpy' + Method of computing the quantiles: + * sort: sort `arr` in place, then interpolates the quantiles one by one + * numpy_bulk: compute all the quantiles at once using `numpy.quantile` + * numpy: compute the quantiles one by one using `numpy.quantile` + + Returns + ------- + Iterable[numpy array] + Quantiles, in increasing order if `which` is an `int`, otherwise in the order specified + """ + if method not in ("sort", "numpy_bulk", "numpy"): + raise ValueError( + f"Invalid method {method!r}, expected 'sort', 'numpy_bulk', or 'numpy'" + ) + + if isinstance(which, int): + n = which + qs = np.linspace(0.0, 1.0, n + 1) + else: + qs = np.asarray(which) + + if method == "numpy_bulk": + quantiles = np.quantile(arr, qs, axis=axis) + yield from quantiles + return + + if method == "sort": + arr = np.asarray(arr) + arr.sort(axis=axis) + + for q in qs: + if method == "numpy": + yield np.quantile(arr, q, axis=axis) + + elif method == "sort": + m = arr.shape[axis] + f = (m - 1) * q + j = int(f) + x = f - j + quantile = arr.take(j, axis=axis) + quantile *= 1 - x + tmp = arr.take(min(j + 1, m - 1), axis=axis) + tmp *= x + quantile += tmp + yield quantile diff --git a/earthkit/meteo/stats/numpy_extended.py b/earthkit/meteo/stats/numpy_extended.py new file mode 100644 index 0000000..3a8fdec --- /dev/null +++ b/earthkit/meteo/stats/numpy_extended.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +from . import array + + +def nanaverage(*args, **kwargs): + return array.nanaverage(*args, **kwargs) diff --git a/earthkit/meteo/stats/quantiles.py b/earthkit/meteo/stats/quantiles.py new file mode 100644 index 0000000..4f607d0 --- /dev/null +++ b/earthkit/meteo/stats/quantiles.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +from . import array + + +def iter_quantiles(*args, **kwargs): + return array.iter_quantiles(*args, **kwargs) diff --git a/earthkit/meteo/thermo/__init__.py b/earthkit/meteo/thermo/__init__.py new file mode 100644 index 0000000..270a840 --- /dev/null +++ b/earthkit/meteo/thermo/__init__.py @@ -0,0 +1,19 @@ +# (C) Copyright 2021 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. +# + +""" +Thermodynamic functions. + +The API is split into two levels. The low level functions are in the ``array`` submodule and they +can be used to operate on numpy arrays. The high level functions are still to be developed and +planned to work with objects like *earthkit.data FieldLists* or *xarray DataSets*. +""" + + +from .thermo import * # noqa diff --git a/earthkit/meteo/thermo/array/__init__.py b/earthkit/meteo/thermo/array/__init__.py new file mode 100644 index 0000000..5507b1b --- /dev/null +++ b/earthkit/meteo/thermo/array/__init__.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +""" +Thermodynamic functions operating on numpy arrays. +""" + +from .thermo import * # noqa diff --git a/earthkit/meteo/thermo/array/thermo.py b/earthkit/meteo/thermo/array/thermo.py new file mode 100644 index 0000000..f0c2b7a --- /dev/null +++ b/earthkit/meteo/thermo/array/thermo.py @@ -0,0 +1,1791 @@ +# (C) Copyright 2021 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. +# + + +import numpy as np + +from earthkit.meteo import constants + + +def celsius_to_kelvin(t): + """Converts temperature values from Celsius to Kelvin. + + Parameters + ---------- + t : number or ndarray + Temperature in Celsius units + + Returns + ------- + number or ndarray + Temperature in Kelvin units + + """ + return t + constants.T0 + + +def kelvin_to_celsius(t): + """Converts temperature values from Kelvin to Celsius. + + Parameters + ---------- + t : number or ndarray + Temperature in Kelvin units + + Returns + ------- + number or ndarray + Temperature in Celsius units + + """ + return t - constants.T0 + + +def specific_humidity_from_mixing_ratio(w): + r"""Computes the specific humidity from mixing ratio. + + Parameters + ---------- + w : number or ndarray + Mixing ratio (kg/kg) + + Returns + ------- + number or ndarray + Specific humidity (kg/kg) + + + The result is the specific humidity in kg/kg units. The computation is based on + the following definition [Wallace2006]_: + + .. math:: + + q = \frac {w}{1+w} + + """ + return w / (1 + w) + + +def mixing_ratio_from_specific_humidity(q): + r"""Computes the mixing ratio from specific humidity. + + Parameters + ---------- + q : number or ndarray + Specific humidity (kg/kg) + + Returns + ------- + number or ndarray + Mixing ratio (kg/kg) + + + The result is the mixing ratio in kg/kg units. The computation is based on + the following definition [Wallace2006]_: + + .. math:: + + w = \frac {q}{1-q} + + """ + return q / (1 - q) + + +def vapour_pressure_from_specific_humidity(q, p): + r"""Computes the vapour pressure from specific humidity. + + Parameters + ---------- + q: number or ndarray + Specific humidity (kg/kg) + p: number or ndarray + Pressure (Pa) + + Returns + ------- + number or ndarray + Vapour pressure (Pa) + + + The computation is based on the following formula [Wallace2006]_: + + .. math:: + + e = \frac{p\;q}{\epsilon\; (1 + q(\frac{1}{\epsilon} -1 ))} + + with :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + + """ + c = constants.epsilon * (1 / constants.epsilon - 1) + return (p * q) / (constants.epsilon + c * q) + + +def vapour_pressure_from_mixing_ratio(w, p): + r"""Computes the vapour pressure from mixing ratio. + + Parameters + ---------- + w: number or ndarray + Mixing ratio (kg/kg) + p: number or ndarray + Pressure (Pa) + + Returns + ------- + number or ndarray + Vapour pressure (Pa) + + + The computation is based on the following formula: + + .. math:: + + e = \frac{p\;w}{\epsilon + w} + + with :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + + """ + return (p * w) / (constants.epsilon + w) + + +def specific_humidity_from_vapour_pressure(e, p, eps=1e-4): + r"""Computes the specific humidity from vapour pressure. + + Parameters + ---------- + e: number or ndarray + Vapour pressure (Pa) + p: number or ndarray + Pressure (Pa) + eps: number + Where p - e < ``eps`` np.nan is returned. + + Returns + ------- + number or ndarray + Specific humidity (kg/kg) + + + The computation is based on the following formula: + + .. math:: + + q = \frac{\epsilon e}{p + e(\epsilon-1)} + + with :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + + """ + if eps <= 0: + raise ValueError( + f"specific_humidity_from_vapour_pressure(): eps={eps} must be > 0" + ) + + v = np.asarray(p + (constants.epsilon - 1) * e) + v[np.asarray(p - e) < eps] = np.nan + return constants.epsilon * e / v + + +def mixing_ratio_from_vapour_pressure(e, p, eps=1e-4): + r"""Computes the mixing ratio from vapour pressure. + + Parameters + ---------- + e: number or ndarray + Vapour pressure (Pa) + p: number or ndarray + Pressure (Pa) + eps: number + Where p - e < ``eps`` np.nan is returned. + + Returns + ------- + number or ndarray + Mixing ratio (kg/kg). + + + The computation is based on the following formula: + + .. math:: + + w = \frac{\epsilon e}{p - e} + + with :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + + """ + if eps <= 0: + raise ValueError(f"mixing_ratio_from_vapour_pressure(): eps={eps} must be > 0") + + v = np.asarray(p - e) + v[v < eps] = np.nan + return constants.epsilon * e / v + + +class _EsComp: + c1 = 611.21 + c3w = 17.502 + c4w = 32.19 + c3i = 22.587 + c4i = -0.7 + t0 = 273.16 + ti = t0 - 23 + PHASES = ["mixed", "water", "ice"] + + def _check_phase(self, phase): + if phase not in _EsComp.PHASES: + raise ValueError( + f"saturation_vapour_pressure(): invalid phase={phase}! Allowed values = {_EsComp.PHASES}" + ) + return True + + def compute_es(self, t, phase): + self._check_phase(phase) + if phase == "mixed": + return self._es_mixed(t) + elif phase == "water": + return self._es_water(t) + elif phase == "ice": + return self._es_ice(t) + + def compute_slope(self, t, phase): + self._check_phase(phase) + if phase == "mixed": + return self._es_mixed_slope(t) + elif phase == "water": + return self._es_water_slope(t) + elif phase == "ice": + return self._es_ice_slope(t) + + def t_from_es(self, es): + v = np.log(es / self.c1) + return (v * self.c4w - self.c3w * self.t0) / (v - self.c3w) + + def _es_water(self, t): + return self.c1 * np.exp(self.c3w * (t - self.t0) / (t - self.c4w)) + + def _es_ice(self, t): + return self.c1 * np.exp(self.c3i * (t - self.t0) / (t - self.c4i)) + + def _es_mixed(self, t): + # Fraction of liquid water (=alpha): + # t <= ti => alpha=0 + # t > ti and t < t0 => alpha=(t-ti)/(t0-ti))^2 + # t >= t0 => alpha=1 + # + # svp is interpolated between the ice and water phases: + # svp = alpha * es_water + (1.0 - alpha) * es_ice + + t = np.asarray(t) + svp = np.zeros(t.shape) + + # ice range + i_mask = t <= self.ti + svp[i_mask] = self._es_ice(t[i_mask]) + + # water range + w_mask = t >= self.t0 + svp[w_mask] = self._es_water(t[w_mask]) + + # mixed range + m_mask = ~(i_mask | w_mask) + alpha = np.square(t[m_mask] - self.ti) / np.square(self.t0 - self.ti) + svp[m_mask] = alpha * self._es_water(t[m_mask]) + (1.0 - alpha) * self._es_ice( + t[m_mask] + ) + return svp + + def _es_water_slope(self, t): + return ( + self._es_water(t) + * (self.c3w * (self.t0 - self.c4w)) + / np.square(t - self.c4w) + ) + + def _es_ice_slope(self, t): + return ( + self._es_ice(t) + * (self.c3i * (self.t0 - self.c4i)) + / np.square(t - self.c4i) + ) + + def _es_mixed_slope(self, t): + t = np.asarray(t) + d_svp = np.zeros(t.shape) + + # ice range + i_mask = t <= self.ti + d_svp[i_mask] = self._es_ice_slope(t[i_mask]) + + # water range + w_mask = t >= self.t0 + d_svp[w_mask] = self._es_water_slope(t[w_mask]) + + # mixed range + m_mask = ~(i_mask | w_mask) + alpha = np.square(t[m_mask] - self.ti) / np.square(self.t0 - self.ti) + d_alpha = (2.0 / np.square(self.t0 - self.ti)) * (t[m_mask] - self.ti) + t_m = t[m_mask] + d_svp[m_mask] = ( + d_alpha * self._es_water(t_m) + + alpha * self._es_water_slope(t_m) + - d_alpha * self._es_ice(t_m) + + (1.0 - alpha) * self._es_ice_slope(t_m) + ) + return d_svp + + +def saturation_vapour_pressure(t, phase="mixed"): + r"""Computes the saturation vapour pressure from temperature with respect to a phase. + + Parameters + ---------- + t: ndarray + Temperature (K) + phase: str, optional + Defines the phase with respect to the saturation vapour pressure is computed. + It is either “water”, “ice” or “mixed”. + + Returns + ------- + ndarray + Saturation vapour pressure (Pa) + + + The algorithm was taken from the IFS model [IFS-CY47R3-PhysicalProcesses]_ (see Chapter 12). + It uses the following formula when ``phase`` is "water" or "ice": + + .. math:: + + e_{sat} = a_{1}\;exp \left(a_{3}\frac{t-273.16}{t-a_{4}}\right) + + where the parameters are set as follows: + + * ``phase`` = "water": :math:`a_{1}` =611.21 Pa, :math:`a_{3}` =17.502 and :math:`a_{4}` =32.19 K + * ``phase`` = "ice": :math:`a_{1}` =611.21 Pa, :math:`a_{3}` =22.587 and :math:`a_{4}` =-0.7 K + + When ``phase`` is "mixed" the formula is based on the value of ``t``: + + * if :math:`t <= t_{i}`: the formula for ``phase`` = "ice" is used (:math:`t_{i} = 250.16 K`) + * if :math:`t >= t_{0}`: the formula for ``phase`` = "water" is used (:math:`t_{0} = 273.16 K`) + * for the range :math:`t_{i} < t < t_{0}` an interpolation is used between the "ice" and "water" phases: + + .. math:: + + \alpha(t) e_{wsat}(t) + (1 - \alpha(t)) e_{isat}(t) + + with :math:`\alpha(t) = (\frac{t-t_{i}}{t_{0}-t_{i}})^2`. + + """ + return _EsComp().compute_es(t, phase) + + +def saturation_mixing_ratio(t, p, phase="mixed"): + r"""Computes the saturation mixing ratio from temperature with respect to a phase. + + Parameters + ---------- + t: ndarray + Temperature (K) + p: ndarray + Pressure (Pa) + phase: str + Defines the phase with respect to the :func:`saturation_vapour_pressure` is computed. + It is either “water”, “ice” or “mixed”. + + Returns + ------- + ndarray + Saturation mixing ratio (kg/kg) + + + Equivalent to the following code: + + .. code-block:: python + + e = saturation_vapour_pressure(t, phase=phase) + return mixing_ratio_from_vapour_pressure(e, p) + + """ + e = saturation_vapour_pressure(t, phase=phase) + return mixing_ratio_from_vapour_pressure(e, p) + + +def saturation_specific_humidity(t, p, phase="mixed"): + r"""Computes the saturation specific humidity from temperature with respect to a phase. + + Parameters + ---------- + t: ndarray + Temperature (K) + p: ndarray + Pressure (Pa) + phase: str, optional + Defines the phase with respect to the :func:`saturation_vapour_pressure` is computed. + It is either “water”, “ice” or “mixed”. + + Returns + ------- + ndarray + Saturation specific humidity (kg/kg) + + + Equivalent to the following code: + + .. code-block:: python + + e = saturation_vapour_pressure(t, phase=phase) + return specific_humidity_from_vapour_pressure(e, p) + + """ + e = saturation_vapour_pressure(t, phase=phase) + return specific_humidity_from_vapour_pressure(e, p) + + +def saturation_vapour_pressure_slope(t, phase="mixed"): + r"""Computes the slope of saturation vapour pressure with respect to temperature. + + Parameters + ---------- + t: ndarray + Temperature (K) + phase: str, optional + Defines the phase with respect to the computation will be performed. + It is either “water”, “ice” or “mixed”. See :func:`saturation_vapour_pressure` + for details. + + Returns + ------- + ndarray + Slope of saturation vapour pressure (Pa/K) + + """ + return _EsComp().compute_slope(t, phase) + + +def saturation_mixing_ratio_slope( + t, p, es=None, es_slope=None, phase="mixed", eps=1e-4 +): + r"""Computes the slope of saturation mixing ratio with respect to temperature. + + Parameters + ---------- + t: ndarray + Temperature (K) + p: ndarray + Pressure (Pa) + es: ndarray or None, optional + :func:`saturation_vapour_pressure` pre-computed for the given ``phase`` (Pa) + es_slope: ndarray or None, optional + :func:`saturation_vapour_pressure_slope` pre-computed for the given ``phase`` (Pa/K) + phase: str, optional + Defines the phase with respect to the computation will be performed. + It is either “water”, “ice” or “mixed”. See :func:`saturation_vapour_pressure` + for details. + eps: number + Where p - es < ``eps`` np.nan is returned. + + Returns + ------- + ndarray + Slope of saturation mixing ratio (:math:`kg kg^{-1} K^{-1}`) + + + The computation is based on the following formula: + + .. math:: + + \frac{\partial w_{s}}{\partial t} = \frac{\epsilon\; p}{(p-e_{s})^{2}} \frac{d e_{s}}{d t} + + where + + * :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + * :math:`e_{s}` is the :func:`saturation_vapour_pressure` for the given ``phase`` + + """ + if eps <= 0: + raise ValueError(f"saturation_mixing_ratio_slope(): eps={eps} must be > 0") + if es is None: + es = saturation_vapour_pressure(t, phase=phase) + if es_slope is None: + es_slope = saturation_vapour_pressure_slope(t, phase=phase) + + v = np.asarray(p - es) + v[v < eps] = np.nan + return constants.epsilon * es_slope * p / np.square(v) + + +def saturation_specific_humidity_slope( + t, p, es=None, es_slope=None, phase="mixed", eps=1e-4 +): + r"""Computes the slope of saturation specific humidity with respect to temperature. + + Parameters + ---------- + t: ndarray + Temperature (K) + p: ndarray + Pressure (Pa) + es: ndarray or None, optional + :func:`saturation_vapour_pressure` pre-computed for the given ``phase`` (Pa) + es_slope: ndarray or None, optional + :func:`saturation_vapour_pressure_slope` pre-computed for the given ``phase`` (Pa/K) + phase: str, optional + Defines the phase with respect to the computation will be performed. + It is either “water”, “ice” or “mixed”. See :func:`saturation_vapour_pressure` + for details. + eps: number + Where p - es < ``eps`` np.nan is returned. + + Returns + ------- + ndarray + Slope of saturation specific humidity (:math:`kg kg^{-1} K^{-1}`) + + + The computation is based on the following formula: + + .. math:: + + \frac{\partial q_{s}}{\partial t} = + \frac{\epsilon\; p}{(p+e_{s}(\epsilon - 1))^{2}} \frac{d e_{s}}{d t} + + where + + * :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + * :math:`e_{s}` is the :func:`saturation_vapour_pressure` for the given ``phase`` + + """ + if eps <= 0: + raise ValueError(f"saturation_specific_humidity_slope(): eps={eps} must be > 0") + if es is None: + es = saturation_vapour_pressure(t, phase=phase) + if es_slope is None: + es_slope = saturation_vapour_pressure_slope(t, phase=phase) + + v = np.asarray(np.square(p + es * (constants.epsilon - 1.0))) + v[np.asarray(p - es) < eps] = np.nan + return constants.epsilon * es_slope * p / v + + +def temperature_from_saturation_vapour_pressure(es): + r"""Computes the temperature from saturation vapour pressure. + + Parameters + ---------- + es: ndarray + :func:`saturation_vapour_pressure` (Pa) + + Returns + ------- + ndarray + Temperature (K) + + + The computation is always based on the "water" phase of + the :func:`saturation_vapour_pressure` formulation irrespective of the + phase ``es`` was computed to. + + """ + return _EsComp().t_from_es(es) + + +def relative_humidity_from_dewpoint(t, td): + r"""Computes the relative humidity from dewpoint temperature. + + Parameters + ---------- + t: ndarray + Temperature (K) + td: ndarray + Dewpoint (K) + + Returns + ------- + ndarray + Relative humidity (%) + + + The computation is based on the following formula: + + .. math:: + + r = 100 \frac {e_{wsat}(td)}{e_{wsat}(t)} + + where :math:`e_{wsat}` is the :func:`saturation_vapour_pressure` over water. + + """ + e = saturation_vapour_pressure(td, phase="water") + es = saturation_vapour_pressure(t, phase="water") + return 100.0 * e / es + + +def relative_humidity_from_specific_humidity(t, q, p): + r"""Computes the relative humidity from specific humidity. + + Parameters + ---------- + t: ndarray + Temperature (K) + q: ndarray + Specific humidity (kg/kg) + p: ndarray + Pressure (Pa) + + Returns + ------- + ndarray + Relative humidity (%) + + + The computation is based on the following formula: + + .. math:: + + r = 100 \frac {e(q, p)}{e_{msat}(t)} + + where: + + * :math:`e` is the vapour pressure (see :func:`vapour_pressure_from_specific_humidity`) + * :math:`e_{msat}` is the :func:`saturation_vapour_pressure` based on the "mixed" phase + + """ + svp = saturation_vapour_pressure(t) + e = vapour_pressure_from_specific_humidity(q, p) + return 100.0 * e / svp + + +def specific_humidity_from_dewpoint(td, p): + r"""Computes the specific humidity from dewpoint. + + Parameters + ---------- + td: ndarray + Dewpoint (K) + p: ndarray + Pressure (Pa) + + Returns + ------- + ndarray + Specific humidity (kg/kg) + + + The computation starts with determining the vapour pressure: + + .. math:: + + e(q, p) = e_{wsat}(td) + + where: + + * :math:`e` is the vapour pressure (see :func:`vapour_pressure_from_specific_humidity`) + * :math:`e_{wsat}` is the :func:`saturation_vapour_pressure` over water + * :math:`q` is the specific humidity + + Then `q` is computed from :math:`e` using :func:`specific_humidity_from_vapour_pressure`. + + """ + svp = saturation_vapour_pressure(td, phase="water") + return specific_humidity_from_vapour_pressure(svp, p) + + +def mixing_ratio_from_dewpoint(td, p): + r"""Computes the mixing ratio from dewpoint. + + Parameters + ---------- + td: ndarray + Dewpoint (K) + p: ndarray + Pressure (Pa) + + Returns + ------- + ndarray + Specific humidity (kg/kg) + + + The computation starts with determining the vapour pressure: + + .. math:: + + e(w, p) = e_{wsat}(td) + + where: + + * :math:`e` is the vapour pressure (see :func:`vapour_pressure_from_mixing_ratio`) + * :math:`e_{wsat}` is the :func:`saturation_vapour_pressure` over water + * :math:`w` is the mixing ratio + + Then `w` is computed from :math:`e` using :func:`mixing_ratio_from_vapour_pressure`. + + """ + svp = saturation_vapour_pressure(td, phase="water") + return mixing_ratio_from_vapour_pressure(svp, p) + + +def specific_humidity_from_relative_humidity(t, r, p): + r"""Computes the specific humidity from relative_humidity. + + Parameters + ---------- + t: ndarray + Temperature (K) + r: ndarray + Relative humidity(%) + p: ndarray + Pressure (Pa) + + Returns + ------- + ndarray + Specific humidity (kg/kg) units + + + The computation starts with determining the the vapour pressure: + + .. math:: + + e(q, p) = r\; \frac{e_{msat}(t)}{100} + + where: + + * :math:`e` is the vapour pressure (see :func:`vapour_pressure`) + * :math:`e_{msat}` is the :func:`saturation_vapour_pressure` based on the "mixed" phase + * :math:`q` is the specific humidity + + Then :math:`q` is computed from :math:`e` using :func:`specific_humidity_from_vapour_pressure`. + + """ + e = r * saturation_vapour_pressure(t) / 100.0 + return specific_humidity_from_vapour_pressure(e, p) + + +def dewpoint_from_relative_humidity(t, r): + r"""Computes the dewpoint temperature from relative humidity. + + Parameters + ---------- + t: ndarray + Temperature (K) + r: ndarray + Relative humidity (%) + + Returns + ------- + ndarray + Dewpoint (K) + + + The computation starts with determining the the saturation vapour pressure over + water at the dewpoint temperature: + + .. math:: + + e_{wsat}(td) = \frac{r\; e_{wsat}(t)}{100} + + where: + + * :math:`e_{wsat}` is the :func:`saturation_vapour_pressure` over water + * :math:`td` is the dewpoint. + + Then :math:`td` is computed from :math:`e_{wsat}(td)` by inverting the + equations used in :func:`saturation_vapour_pressure`. + + """ + es = saturation_vapour_pressure(t, phase="water") * r / 100.0 + return temperature_from_saturation_vapour_pressure(es) + + +def dewpoint_from_specific_humidity(q, p): + r"""Computes the dewpoint temperature from specific humidity. + + Parameters + ---------- + q: ndarray + Specific humidity (kg/kg) + p: ndarray + Pressure (Pa) + + Returns + ------- + ndarray + Dewpoint (K) + + + The computation starts with determining the the saturation vapour pressure over + water at the dewpoint temperature: + + .. math:: + + e_{wsat}(td) = e(q, p) + + where: + + * :math:`e` is the vapour pressure (see :func:`vapour_pressure_from_specific_humidity`) + * :math:`e_{wsat}` is the :func:`saturation_vapour_pressure` over water + * :math:`td` is the dewpoint + + Then :math:`td` is computed from :math:`e_{wsat}(td)` by inverting the equations + used in :func:`saturation_vapour_pressure`. + + """ + return temperature_from_saturation_vapour_pressure( + vapour_pressure_from_specific_humidity(q, p) + ) + + +def virtual_temperature(t, q): + r"""Computes the virtual temperature from temperature and specific humidity. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + q: number or ndarray + Specific humidity (kg/kg) + + Returns + ------- + number or ndarray + Virtual temperature (K) + + + The computation is based on the following formula [Wallace2006]_: + + .. math:: + + t_{v} = t (1 + \frac{1 - \epsilon}{\epsilon} q) + + with :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + + """ + c1 = (1.0 - constants.epsilon) / constants.epsilon + return t * (1.0 + c1 * q) + + +def virtual_potential_temperature(t, q, p): + r"""Computes the virtual potential temperature from temperature and specific humidity. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + q: number or ndarray + Specific humidity (kg/kg) + p: number or ndarray + Pressure (Pa) + + Returns + ------- + number or ndarray + Virtual potential temperature (K) + + + The computation is based on the following formula: + + .. math:: + + \Theta_{v} = \theta (1 + \frac{1 - \epsilon}{\epsilon} q) + + where: + + * :math:`\Theta` is the :func:`potential_temperature` + * :math:`\epsilon = R_{d}/R_{v}` (see :data:`earthkit.meteo.constants.epsilon`). + + """ + c1 = (1.0 - constants.epsilon) / constants.epsilon + return potential_temperature(t, p) * (1.0 + c1 * q) + + +def potential_temperature(t, p): + r"""Computes the potential temperature. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + p: number or ndarray + Pressure (Pa) + + Returns + ------- + number or ndarray + Potential temperature (K) + + + The computation is based on the following formula [Wallace2006]_: + + .. math:: + + \theta = t (\frac{10^{5}}{p})^{\kappa} + + with :math:`\kappa = R_{d}/c_{pd}` (see :data:`earthkit.meteo.constants.kappa`). + + """ + return t * np.power(constants.p0 / p, constants.kappa) + + +def temperature_from_potential_temperature(th, p): + r"""Computes the temperature from potential temperature. + + Parameters + ---------- + th: number or ndarray + Potential temperature (K) + p: number or ndarray + Pressure (Pa) + + Returns + ------- + number or ndarray + Temperature (K) + + + The computation is based on the following formula: + + .. math:: + + t = \theta (\frac{p}{10^{5}})^{\kappa} + + with :math:`\kappa = R_{d}/c_{pd}` (see :data:`earthkit.meteo.constants.kappa`). + + """ + return th * np.power(p / constants.p0, constants.kappa) + + +def pressure_on_dry_adiabat(t, t_def, p_def): + r"""Computes the pressure on a dry adiabat. + + Parameters + ---------- + t: number or ndarray + Temperature on the dry adiabat (K) + t_def: number or ndarray + Temperature defining the dry adiabat (K) + p_def: number or ndarray + Pressure defining the dry adiabat (Pa) + + Returns + ------- + number or ndarray + Pressure on the dry adiabat (Pa) + + + The computation is based on the following formula: + + .. math:: + + p = p_{def} (\frac{t}{t_{def}})^{\frac{1}{\kappa}} + + with :math:`\kappa = R_{d}/c_{pd}` (see :data:`earthkit.meteo.constants.kappa`). + + """ + return p_def * np.power(t / t_def, 1 / constants.kappa) + + +def temperature_on_dry_adiabat(p, t_def, p_def): + r"""Computes the temperature on a dry adiabat. + + Parameters + ---------- + p: number or ndarray + Pressure on the dry adiabat (Pa) + t_def: number or ndarray + Temperature defining the dry adiabat (K) + p_def: number or ndarray + Pressure defining the dry adiabat (Pa) + + Returns + ------- + number or ndarray + Temperature on the dry adiabat (K) + + + The computation is based on the following formula: + + .. math:: + + t = t_{def} (\frac{p}{p_{def}})^{\kappa} + + with :math:`\kappa = R_{d}/c_{pd}` (see :data:`earthkit.meteo.constants.kappa`). + + """ + return t_def * np.power(p / p_def, constants.kappa) + + +def lcl_temperature(t, td, method="davies"): + r"""Computes the Lifting Condenstaion Level (LCL) temperature from dewpoint. + + Parameters + ---------- + t: number or ndarray + Temperature at the start level (K) + td: number or ndarray + Dewpoint at the start level (K) + method: str, optional + The computation method: "davies" or "bolton". + + Returns + ------- + number or ndarray + Temperature of the LCL (K) + + + The actual computation is based on the ``method``: + + * "davies": the formula by [DaviesJones1983]_ is used (it is also used by the IFS model): + + .. math:: + + t_{LCL} = + td - (0.212 + 1.571\times 10^{-3} (td - t_{0}) - 4.36\times 10^{-4} (t - t_{0})) (t - td) + + where :math:`t_{0}` is the triple point of water (see :data:`earthkit.meteo.constants.T0`). + + * "bolton": the formula by [Bolton1980]_ is used: + + .. math:: + + t_{LCL} = 56.0 + \frac{1}{\frac{1}{td - 56} + \frac{log(\frac{t}{td})}{800}} + + """ + # Davies-Jones formula + if method == "davies": + t_lcl = td - ( + 0.212 + 1.571e-3 * (td - constants.T0) - 4.36e-4 * (t - constants.T0) + ) * (t - td) + return t_lcl + # Bolton formula + elif method == "bolton": + return 56.0 + 1 / (1 / (td - 56) + np.log(t / td) / 800) + else: + raise ValueError(f"lcl_temperature: invalid method={method} specified!") + + +def lcl(t, td, p, method="davies"): + r"""Computes the temperature and pressure of the Lifting Condenstaion Level (LCL) from dewpoint. + + Parameters + ---------- + t: number or ndarray + Temperature at the start level (K) + td: number or ndarray + Dewpoint at the start level (K) + p: number or ndarray + Pressure at the start level (Pa) + method: str + method: str, optional + The computation method: "davies" or "bolton". + + Returns + ------- + number or ndarray + Temperature of the LCL (K) + number or ndarray + Pressure of the LCL (Pa) + + + The LCL temperature is determined by :func:`lcl_temperature` with the given ``method`` + and the pressure is computed with :math:`t_{LCL}` using :func:`pressure_on_dry_adiabat`. + + """ + t_lcl = lcl_temperature(t, td, method=method) + p_lcl = pressure_on_dry_adiabat(t_lcl, t, p) + return t_lcl, p_lcl + + +class _ThermoState: + def __init__(self, t=None, td=None, q=None, w=None, p=None): + self.t = t + self.td = td + self.q = q + self.w = w + self.p = p + self.e = None + self.es = None + self.ws = None + self.qs = None + + +class _EptComp: + CM = {} + c_lambda = 1.0 / constants.kappa + + @staticmethod + def make(method): + return _EptComp.CM[method]() + + def is_mixing_ratio_based(self): + return True + + def compute_ept(self, t=None, td=None, q=None, p=None): + if td is None and q is None: + raise ValueError("ept: either td or q must have a valid value!") + + # compute dewpoint since all the methods require it + if td is None: + td = dewpoint_from_specific_humidity(q, p) + + ths = _ThermoState(t=t, td=td, q=q, p=p) + return self._ept(ths) + + def compute_ept_sat(self, t, p): + ths = _ThermoState(t=t, p=p) + return self._th_sat(ths) * np.exp(self._G_sat(ths)) + + def compute_wbpt(self, ept): + t0 = 273.16 + x = ept / t0 + a = [7.101574, -20.68208, 16.11182, 2.574631, -5.205688] + b = [1.0, -3.552497, 3.781782, -0.6899655, -0.5929340] + return ept - np.exp( + np.polynomial.polynomial.polyval(x, a) + / np.polynomial.polynomial.polyval(x, b) + ) + + def compute_t_on_ma_stipanuk(self, ept, p): + if isinstance(p, np.ndarray): + t = np.full(p.shape, constants.T0 - 20) + elif isinstance(ept, np.ndarray): + t = np.full(ept.shape, constants.T0 - 20) + else: + t = constants.T0 - 20 + max_iter = 12 + dt = 120.0 + for _ in range(max_iter): + ths = _ThermoState(t=t, p=p) + dt /= 2.0 + t += ( + np.sign(ept * np.exp(self._G_sat(ths, scale=-1.0)) - self._th_sat(ths)) + * dt + ) + # ths.t = t + # return ept - self._th_sat(ths) * np.exp(self._G_sat(ths)) + return t + + def compute_t_on_ma_davies(self, ept, p): + def _k1(pp): + """Function k1 in the article.""" + a = [-53.737, 137.81, -38.5] + return np.polynomial.polynomial.polyval(pp, a) + + def _k2(pp): + """Function k2 in the article.""" + a = [-0.384, 56.831, -4.392] + return np.polynomial.polynomial.polyval(pp, a) + + def _D(p): + """Function D in the article.""" + return 1.0 / (0.1859e-5 * p + 0.6512) + + max_iter = 1 + A = 2675 + t0 = 273.16 + + if not isinstance(p, np.ndarray): + p = np.full(ept.shape, p) + + tw = ept.copy() + pp = np.power(p / constants.p0, constants.kappa) + te = ept * pp + c_te = np.power(t0 / te, _EptComp.c_lambda) + + # initial guess + mask = c_te > _D(p) + if np.any(mask): + es = saturation_vapour_pressure(te[mask]) + ws = mixing_ratio_from_vapour_pressure(es, p[mask]) + d_es = saturation_vapour_pressure_slope(te[mask]) + tw[mask] = te[mask] - t0 - (A * ws) / (1 + A * ws * d_es / es) + + mask = (1 <= c_te) & (c_te <= _D(p)) + tw[mask] = _k1(pp[mask]) - _k2(pp[mask]) * c_te[mask] + + mask = (0.4 <= c_te) & (c_te < 1) + tw[mask] = (_k1(pp[mask]) - 1.21) - (_k2(pp[mask]) - 1.21) * c_te[mask] + + mask = c_te < 0.4 + tw[mask] = ( + (_k1(pp[mask]) - 2.66) + - (_k2(pp[mask]) - 1.21) * c_te[mask] + + 0.58 / c_te[mask] + ) + # tw has to be converted to Kelvin + tw = celsius_to_kelvin(tw) + + # np.place(tw, tw > 362.16, 362.1) + # print(f"ept={ept}") + # print(f"tw={tw}") + + for i in range(max_iter): + ths = _ThermoState(t=tw, p=p) + ths.c_tw = np.power(t0 / ths.t, _EptComp.c_lambda) + ths.es = saturation_vapour_pressure(ths.t) + if self.is_mixing_ratio_based(): + ths.ws = mixing_ratio_from_vapour_pressure(ths.es, ths.p) + else: + ths.qs = specific_humidity_from_vapour_pressure(ths.es, ths.p) + f_val = self._f(ths) + # print(f"{i}") + # print(f" p={p}") + # print(f" t={ths.t}") + # print(f" f_val={f_val}") + # print(f" f_val_cte={f_val - c_te}") + # print(f" d_lnf={self._d_lnf(ths)}") + # print(tw[mask].shape) + # print(f_val.shape) + tw -= (f_val - c_te) / (f_val * self._d_lnf(ths)) + # print(f"tw={tw}") + + # when ept is derived with the Bolton methods the iteration breaks down for extremeley + # hot and humid conditions (roughly about t > 50C and r > 95%) and results in negative + # tw values! + np.place(tw, tw <= 0, np.nan) + + # ths = _ThermoState(t=tw, p=p) + # return ept - self._th_sat(ths) * np.exp(self._G_sat(ths)) + return tw + + +class _EptCompIfs(_EptComp): + def __init__(self): + self.K0 = constants.Lv / constants.c_pd + + def is_mixing_ratio_based(self): + return False + + def _ept(self, ths): + th = potential_temperature(ths.t, ths.p) + t_lcl = lcl_temperature(ths.t, ths.td, method="davies") + if ths.q is None: + ths.q = specific_humidity_from_dewpoint(ths.td, ths.p) + return th * np.exp(self.K0 * ths.q / t_lcl) + + def _th_sat(self, ths): + return potential_temperature(ths.t, ths.p) + + def _G_sat(self, ths, scale=1.0): + qs = saturation_specific_humidity(ths.t, ths.p) + return (scale * self.K0) * qs / ths.t + + def _d_G_sat(self, ths): + if ths.qs is None: + ths.qs = saturation_specific_humidity(ths.t, ths.p) + return ( + -self.K0 * ths.qs / (ths.t**2) + + self.K0 * saturation_specific_humidity_slope(ths.t, ths.p) / ths.t + ) + + def _f(self, ths): + return ths.c_tw * np.exp(self._G_sat(ths, scale=-self.c_lambda)) + + def _d_lnf(self, ths): + return -self.c_lambda * (1 / ths.t + self._d_G_sat(ths)) + + +class _EptCompBolton35(_EptComp): + def __init__(self): + self.K0 = 2675.0 + self.K3 = 0.28 + + def _ept(self, ths): + t_lcl = lcl_temperature(ths.t, ths.td, method="bolton") + if ths.q is None: + w = mixing_ratio_from_dewpoint(ths.td, ths.p) + else: + w = mixing_ratio_from_specific_humidity(ths.q) + th = ths.t * np.power(constants.p0 / ths.p, constants.kappa * (1 - self.K3 * w)) + return th * np.exp(self.K0 * w / t_lcl) + + def _th_sat(self, ths): + if ths.ws is None: + ths.ws = saturation_mixing_ratio(ths.t, ths.p) + return ths.t * np.power( + constants.p0 / ths.p, constants.kappa * (1 - self.K3 * ths.ws) + ) + + def _G_sat(self, ths, scale=1.0): + if ths.ws is None: + ths.ws = saturation_mixing_ratio(ths.t, ths.p) + return (scale * self.K0) * ths.ws / ths.t + + def _d_G_sat(self, ths): + return ( + -self.K0 * ths.ws / np.square(ths.t) + + self.K0 * saturation_mixing_ratio_slope(ths.t, ths.p) / ths.t + ) + + def _f(self, ths): + # print(f" c_tw={ths.c_tw}") + # print(f" es_frac={ths.es / ths.p}") + # print(f" exp={self._G_sat(ths, scale=-self.c_lambda)}") + return ( + ths.c_tw + * np.power(ths.p / constants.p0, self.K3 * ths.ws) + * np.exp(self._G_sat(ths, scale=-self.c_lambda)) + ) + + def _d_lnf(self, ths): + return -self.c_lambda * ( + 1 / ths.t + + self.K3 + * np.log(ths.p / constants.p0) + * saturation_vapour_pressure_slope(ths.t) + + self._d_G_sat(ths) + ) + + +class _EptCompBolton39(_EptComp): + def __init__(self): + # Comment on the Bolton formulas. The constants used by Bolton to + # derive the formulas differ from the ones used by earthkit.meteo E.g. + # Bolton earthkit.meteo + # Rd 287.04 287.0597 + # cpd 1005.7 1004.79 + # kappa 0.2854 0.285691 + # epsilon 0.6220 0.621981 + + self.K0 = 3036.0 + self.K1 = 1.78 + self.K2 = 0.448 + self.K4 = 0.28 + + def _ept(self, ths): + t_lcl = lcl_temperature(ths.t, ths.td, method="bolton") + if ths.q is None: + w = mixing_ratio_from_dewpoint(ths.td, ths.p) + else: + w = mixing_ratio_from_specific_humidity(ths.q) + + e = vapour_pressure_from_mixing_ratio(w, ths.p) + th = potential_temperature(ths.t, ths.p - e) * np.power( + ths.t / t_lcl, self.K4 * w + ) + return th * np.exp((self.K0 / t_lcl - self.K1) * w * (1.0 + self.K2 * w)) + + def _th_sat(self, ths): + if ths.es is None: + ths.es = saturation_vapour_pressure(ths.t) + ths.es[ths.p - ths.es < 1e-4] = np.nan + return potential_temperature(ths.t, ths.p - ths.es) + + def _G_sat(self, ths, scale=1.0): + if ths.es is None: + ths.es = saturation_vapour_pressure(ths.t) + ths.es[ths.p - ths.es < 1e-4] = np.nan + # print(f" es={ths.es}") + ws = mixing_ratio_from_vapour_pressure(ths.es, ths.p) + # print(f" ws={ws}") + return ( + ((scale * self.K0) / ths.t - (scale * self.K1)) * ws * (1.0 + self.K2 * ws) + ) + + def _d_G_sat(self, ths): + # print(f" d_ws={saturation_mixing_ratio_slope(ths.t, ths.p)}") + return -self.K0 * (ths.ws + self.K2 * np.square(ths.ws)) / ( + np.square(ths.t) + ) + (self.K0 / ths.t - self.K1) * ( + 1 + (2 * self.K2) * ths.ws + ) * saturation_mixing_ratio_slope( + ths.t, ths.p + ) + + def _f(self, ths): + # print(f" c_tw={ths.c_tw}") + # print(f" es_frac={ths.es / ths.p}") + # print(f" exp={self._G_sat(ths, scale=-self.c_lambda)}") + return ( + ths.c_tw + * (1 - ths.es / ths.p) + * np.exp(self._G_sat(ths, scale=-self.c_lambda)) + ) + + def _d_lnf(self, ths): + return -self.c_lambda * ( + 1 / ths.t + + constants.kappa + * saturation_vapour_pressure_slope(ths.t) + / (ths.p - ths.es) + + self._d_G_sat(ths) + ) + + +_EptComp.CM = { + "ifs": _EptCompIfs, + "bolton35": _EptCompBolton35, + "bolton39": _EptCompBolton39, +} + + +def ept_from_dewpoint(t, td, p, method="ifs"): + r"""Computes the equivalent potential temperature from dewpoint. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + td: number or ndarray + Dewpoint (K) + p: number or ndarray + Pressure (Pa) + method: str, optional + Specifies the computation method. The possible values are: "ifs", "bolton35", "bolton39". + + Returns + ------- + number or ndarray + Equivalent potential temperature (K) + + + The actual computation is based on the value of ``method``: + + * "ifs": the formula from the IFS model [IFS-CY47R3-PhysicalProcesses]_ (Chapter 6.11) is used: + + .. math:: + + \Theta_{e} = \Theta\; exp(\frac{L_{v}\; q}{c_{pd}\; t_{LCL}}) + + * "bolton35": Eq (35) from [Bolton1980]_ is used: + + + .. math:: + + \Theta_{e} = \Theta (\frac{10^{5}}{p})^{\kappa 0.28 w} exp(\frac{2675 w}{t_{LCL}}) + + * "bolton39": Eq (39) from [Bolton1980]_ is used: + + .. math:: + + \Theta_{e} = + t (\frac{10^{5}}{p-e})^{\kappa} (\frac{t}{t_{LCL}})^{0.28 w} exp[(\frac{3036}{t_{LCL}} - + 1.78)w(1+0.448\; w)] + + where: + + * :math:`\Theta` is the :func:`potential_temperature` + * :math:`t_{LCL}` is the temperature at the Lifting Condestation Level computed + with :func:`lcl_temperature` using option: + + * method="davis" when ``method`` is "ifs" + * method="bolton" when ``method`` is "bolton35" or "bolton39" + * :math:`q` is the specific humidity computed with :func:`specific_humidity_from_dewpoint` + * :math:`w`: is the mixing ratio computed with :func:`mixing_ratio_from_dewpoint` + * :math:`e` is the vapour pressure computed with :func:`vapour_pressure_from_mixing_ratio` + * :math:`L_{v}`: is the latent heat of vaporisation + (see :data:`earthkit.meteo.constants.Lv`) + * :math:`c_{pd}` is the specific heat of dry air on constant pressure + (see :data:`earthkit.meteo.constants.c_pd`) + * :math:`\kappa = R_{d}/c_{pd}` (see :data:`earthkit.meteo.constants.kappa`) + + """ + return _EptComp.make(method).compute_ept(t=t, td=td, p=p) + + +def ept_from_specific_humidity(t, q, p, method="ifs"): + r"""Computes the equivalent potential temperature from specific humidity. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + q: number or ndarray + Specific humidity (kg/kg) + p: number or ndarray + Pressure (Pa) + method: str, optional + Specifies the computation method. The possible values are: "ifs", + "bolton35", "bolton39. See :func:`ept_from_dewpoint` for details. + + Returns + ------- + number or ndarray + Equivalent potential temperature (K) + + + The computations are the same as in :func:`ept_from_dewpoint` + (the dewpoint is computed from q with :func:`dewpoint_from_specific_humidity`). + + """ + return _EptComp.make(method).compute_ept(t=t, q=q, p=p) + + +def saturation_ept(t, p, method="ifs"): + r"""Computes the saturation equivalent potential temperature. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + p: number or ndarray + Pressure (Pa) + method: str, optional + Specifies the computation method. The possible values are: "ifs", "bolton35", "bolton39". + + Returns + ------- + number or ndarray + Saturation equivalent potential temperature (K) + + + The actual computation is based on the ``method``: + + * "ifs": The formula is based on the equivalent potential temperature definition used + in the IFS model [IFS-CY47R3-PhysicalProcesses]_ (see Chapter 6.11) : + + .. math:: + + \Theta_{esat} = \Theta\; exp(\frac{L_{v}\; q_{sat}}{c_{pd}\; t}) + + * "bolton35": Eq (35) from [Bolton1980]_ is used: + + .. math:: + + \Theta_{e} = \Theta (\frac{10^{5}}{p})^{\kappa 0.28 w_{sat}}\; exp(\frac{2675\; w_{sat}}{t}) + + * "bolton39": Eq (39) from [Bolton1980]_ is used: + + .. math:: + + \Theta_{e} = + t (\frac{10^{5}}{p-e_{sat}})^{\kappa} exp[(\frac{3036}{t} - 1.78)w_{sat}(1+0.448\; w_{sat})] + + where: + + * :math:`\Theta` is the :func:`potential_temperature` + * :math:`e_{sat}` is the :func:`saturation_vapor_pressure` + * :math:`q_{sat}` is the :func:`saturation_specific_humidity` + * :math:`w_{sat}` is the :func:`saturation_mixing_ratio` + * :math:`L_{v}` is the specific latent heat of vaporization (see :data:`earthkit.meteo.constants.Lv`) + * :math:`c_{pd}` is the specific heat of dry air on constant pressure + (see :data:`earthkit.meteo.constants.c_pd`) + + """ + return _EptComp.make(method).compute_ept_sat(t, p) + + +def temperature_on_moist_adiabat(ept, p, ept_method="ifs", t_method="bisect"): + r"""Computes the temperature on a moist adiabat (pseudoadiabat) + + Parameters + ---------- + ept: number or ndarray + Equivalent potential temperature defining the moist adiabat (K) + p: number or ndarray + Pressure on the moist adiabat (Pa) + ept_method: str, optional + Specifies the computation method that was used to compute ``ept``. The possible + values are: "ifs", "bolton35", "bolton39". + (See :func:`ept_from_dewpoint` for details.) + t_method: str, optional + Specifies the iteration method along the moist adiabat to find the temperature + for the given ``p`` pressure. The possible values are as follows: + + * "bisect": a bisection method is used as defined in [Stipanuk1973]_ + * "newton": Newtons's method is used as defined by Eq (2.6) in [DaviesJones2008]_. + For extremely hot and humid conditions (``ept`` > 800 K) depending on + ``ept_method`` the computation might not be carried out + and np.nan will be returned. + + + Returns + ------- + number or ndarray + Temperature on the moist adiabat (K). For values where the computation cannot + be carried out np.nan is returned. + + """ + cm = _EptComp.make(ept_method) + if t_method == "bisect": + return cm.compute_t_on_ma_stipanuk(ept, p) + elif t_method == "newton": + return cm.compute_t_on_ma_davies(ept, p) + else: + raise ValueError( + f"temperature_on_moist_adiabat: invalid t_method={t_method} specified!" + ) + + +def wet_bulb_temperature_from_dewpoint(t, td, p, ept_method="ifs", t_method="bisect"): + r"""Computes the pseudo adiabatic wet bulb temperature from dewpoint. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + td: number or ndarray + Dewpoint (K) + p: number or ndarray + Pressure (Pa) + ept_method: str, optional + Specifies the computation method for the equivalent potential temperature. + The possible values are: "ifs", "bolton35", "bolton39". + (See :func:`ept_from_dewpoint` for details.) + t_method: str, optional + Specifies the method to find the temperature along the moist adiabat defined + by the equivalent potential temperature. The possible values are as follows: + + * "bisect": :func:`temperature_on_moist_adiabat` with ``t_method`` = "bisect" is used + * "newton": :func:`temperature_on_moist_adiabat` with ``t_method`` = "newton" is used + + Returns + ------- + number or ndarray + Wet bulb temperature (K) + + + The computation is based on Normand's rule [Wallace2006]_ (Chapter 3.5.6): + + * first the equivalent potential temperature is computed with the given + ``ept_method`` (using :func:`ept_from_dewpoint`). This defines the moist adiabat. + * then the wet bulb potential temperature is determined as the temperature at + pressure ``p`` on the moist adiabat with the given ``t_method``. + + """ + ept = ept_from_dewpoint(t, td, p, method=ept_method) + return temperature_on_moist_adiabat( + ept, p, ept_method=ept_method, t_method=t_method + ) + + +def wet_bulb_temperature_from_specific_humidity( + t, q, p, ept_method="ifs", t_method="bisect" +): + r"""Computes the pseudo adiabatic wet bulb temperature from specific humidity. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + q: number or ndarray + Specific humidity (kg/kg) + p: number or ndarray + Pressure (Pa) + ept_method: str, optional + Specifies the computation method for the equivalent potential temperature. + The possible values are: "ifs", "bolton35", "bolton39". + (See :func:`ept_from_dewpoint` for details.) + t_method: str, optional + Specifies the method to find the temperature along the moist adiabat + defined by the equivalent potential temperature. The possible values are + as follows: + + * "bisect": :func:`temperature_on_moist_adiabat` with ``t_method`` = "bisect" is used + * "newton": :func:`temperature_on_moist_adiabat` with ``t_method`` = "newton" is used + + Returns + ------- + number or ndarray + Wet bulb temperature (K) + + + The computation is based on Normand's rule [Wallace2006]_ (Chapter 3.5.6): + + * first the equivalent potential temperature is computed with the given + ``ept_method`` (using :func:`ept_from_dewpoint`). This defines the moist adiabat. + * then the wet bulb potential temperature is determined as the temperature at + pressure ``p`` on the moist adiabat with the given ``t_method``. + + """ + ept = ept_from_specific_humidity(t, q, p, method=ept_method) + return temperature_on_moist_adiabat( + ept, p, ept_method=ept_method, t_method=t_method + ) + + +def wet_bulb_potential_temperature_from_dewpoint( + t, td, p, ept_method="ifs", t_method="direct" +): + r"""Computes the pseudo adiabatic wet bulb potential temperature from dewpoint. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + td: number or ndarray + Dewpoint (K) + p: number or ndarray + Pressure (Pa) + ept_method: str, optional + Specifies the computation method for the equivalent potential temperature. + The possible values are: "ifs", "bolton35", "bolton39". + (See :func:`ept_from_dewpoint` for details.) + t_method: str, optional + Specifies the method to find the temperature along the moist adiabat defined + by the equivalent potential temperature. The possible values are as follows: + + * "direct": the rational formula defined by Eq (3.8) in [DaviesJones2008]_ is used + * "bisect": :func:`temperature_on_moist_adiabat` with ``t_method`` = "bisect" is used + * "newton": :func:`temperature_on_moist_adiabat` with ``t_method`` = "newton" is used + + Returns + ------- + number or ndarray + Wet bulb potential temperature (K) + + + The computation is based on Normand's rule [Wallace2006]_ (Chapter 3.5.6): + + * first the equivalent potential temperature is computed with the given + ``ept_method`` (using :func:`ept_from_dewpoint`). This defines the moist adiabat. + * then the wet bulb potential temperature is determined as the temperature at + pressure :math:`10^{5}` Pa on the moist adiabat with the given ``t_method``. + + """ + ept = ept_from_dewpoint(t, td, p, method=ept_method) + if t_method == "direct": + return _EptComp.make(ept_method).compute_wbpt(ept) + else: + return temperature_on_moist_adiabat( + ept, constants.p0, ept_method=ept_method, t_method=t_method + ) + + +def wet_bulb_potential_temperature_from_specific_humidity( + t, q, p, ept_method="ifs", t_method="direct" +): + r"""Computes the pseudo adiabatic wet bulb potential temperature from specific humidity. + + Parameters + ---------- + t: number or ndarray + Temperature (K) + q: number or ndarray + Specific humidity (kg/kg) + p: number or ndarray + Pressure (Pa) + ept_method: str, optional + Specifies the computation method for the equivalent potential temperature. + The possible values are: "ifs", "bolton35", "bolton39". + (See :func:`ept_from_dewpoint` for details.) + t_method: str, optional + Specifies the method to find the temperature along the moist adiabat + defined by the equivalent potential temperature. The possible values are as follows: + + * "direct": the rational formula defined by Eq (3.8) in [DaviesJones2008]_ is used + * "bisect": :func:`temperature_on_moist_adiabat` with ``t_method`` = "bisect" is used + * "newton": :func:`temperature_on_moist_adiabat` with ``t_method`` = "newton" is used + + Returns + ------- + number or ndarray + Wet bulb potential temperature (K) + + + The computations are the same as in + :func:`wet_bulb_potential_temperature_from_dewpoint` + (the dewpoint is computed from q with :func:`dewpoint_from_specific_humidity`). + + """ + ept = ept_from_specific_humidity(t, q, p, method=ept_method) + if t_method == "direct": + return _EptComp.make(ept_method).compute_wbpt(ept) + else: + return temperature_on_moist_adiabat( + ept, constants.p0, ept_method=ept_method, t_method=t_method + ) diff --git a/earthkit/meteo/thermo/thermo.py b/earthkit/meteo/thermo/thermo.py new file mode 100644 index 0000000..b6df320 --- /dev/null +++ b/earthkit/meteo/thermo/thermo.py @@ -0,0 +1,162 @@ +# (C) Copyright 2021 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. +# + +from . import array + + +def celsius_to_kelvin(*args, **kwargs): + return array.celsius_to_kelvin(*args, **kwargs) + + +def kelvin_to_celsius(*args, **kwargs): + return array.kelvin_to_celsius(*args, **kwargs) + + +def specific_humidity_from_mixing_ratio(*args, **kwargs): + return array.specific_humidity_from_mixing_ratio(*args, **kwargs) + + +def mixing_ratio_from_specific_humidity(*args, **kwargs): + return array.mixing_ratio_from_specific_humidity(*args, **kwargs) + + +def vapour_pressure_from_specific_humidity(*args, **kwargs): + return array.vapour_pressure_from_specific_humidity(*args, **kwargs) + + +def vapour_pressure_from_mixing_ratio(*args, **kwargs): + return array.vapour_pressure_from_mixing_ratio(*args, **kwargs) + + +def specific_humidity_from_vapour_pressure(*args, **kwargs): + return array.specific_humidity_from_vapour_pressure(*args, **kwargs) + + +def mixing_ratio_from_vapour_pressure(*args, **kwargs): + return array.mixing_ratio_from_vapour_pressure(*args, **kwargs) + + +def saturation_vapour_pressure(*args, **kwargs): + return array.saturation_vapour_pressure(*args, **kwargs) + + +def saturation_mixing_ratio(*args, **kwargs): + return array.saturation_mixing_ratio(*args, **kwargs) + + +def saturation_specific_humidity(*args, **kwargs): + return array.saturation_specific_humidity(*args, **kwargs) + + +def saturation_vapour_pressure_slope(*args, **kwargs): + return array.saturation_vapour_pressure_slope(*args, **kwargs) + + +def saturation_mixing_ratio_slope(*args, **kwargs): + return array.saturation_mixing_ratio_slope(*args, **kwargs) + + +def saturation_specific_humidity_slope(*args, **kwargs): + return array.saturation_specific_humidity_slope(*args, **kwargs) + + +def temperature_from_saturation_vapour_pressure(*args, **kwargs): + return array.temperature_from_saturation_vapour_pressure(*args, **kwargs) + + +def relative_humidity_from_dewpoint(*args, **kwargs): + return array.relative_humidity_from_dewpoint(*args, **kwargs) + + +def relative_humidity_from_specific_humidity(*args, **kwargs): + return array.relative_humidity_from_specific_humidity(*args, **kwargs) + + +def specific_humidity_from_dewpoint(*args, **kwargs): + return array.specific_humidity_from_dewpoint(*args, **kwargs) + + +def mixing_ratio_from_dewpoint(*args, **kwargs): + return array.mixing_ratio_from_dewpoint(*args, **kwargs) + + +def specific_humidity_from_relative_humidity(*args, **kwargs): + return array.specific_humidity_from_relative_humidity(*args, **kwargs) + + +def dewpoint_from_relative_humidity(*args, **kwargs): + return array.dewpoint_from_relative_humidity(*args, **kwargs) + + +def dewpoint_from_specific_humidity(*args, **kwargs): + return array.dewpoint_from_specific_humidity(*args, **kwargs) + + +def virtual_temperature(*args, **kwargs): + return array.virtual_temperature(*args, **kwargs) + + +def virtual_potential_temperature(*args, **kwargs): + return array.virtual_potential_temperature(*args, **kwargs) + + +def potential_temperature(*args, **kwargs): + return array.potential_temperature(*args, **kwargs) + + +def temperature_from_potential_temperature(*args, **kwargs): + return array.temperature_from_potential_temperature(*args, **kwargs) + + +def pressure_on_dry_adiabat(*args, **kwargs): + return array.pressure_on_dry_adiabat(*args, **kwargs) + + +def temperature_on_dry_adiabat(*args, **kwargs): + return array.temperature_on_dry_adiabat(*args, **kwargs) + + +def lcl_temperature(*args, **kwargs): + return array.lcl_temperature(*args, **kwargs) + + +def lcl(*args, **kwargs): + return array.lcl(*args, **kwargs) + + +def ept_from_dewpoint(*args, **kwargs): + return array.ept_from_dewpoint(*args, **kwargs) + + +def ept_from_specific_humidity(*args, **kwargs): + return array.ept_from_specific_humidity(*args, **kwargs) + + +def saturation_ept(*args, **kwargs): + return array.saturation_ept(*args, **kwargs) + + +def temperature_on_moist_adiabat(*args, **kwargs): + return array.temperature_on_moist_adiabat(*args, **kwargs) + + +def wet_bulb_temperature_from_dewpoint(*args, **kwargs): + return array.wet_bulb_temperature_from_dewpoint(*args, **kwargs) + + +def wet_bulb_temperature_from_specific_humidity(*args, **kwargs): + return array.wet_bulb_temperature_from_specific_humidity(*args, **kwargs) + + +def wet_bulb_potential_temperature_from_dewpoint(*args, **kwargs): + return array.wet_bulb_potential_temperature_from_dewpoint(*args, **kwargs) + + +def wet_bulb_potential_temperature_from_specific_humidity(*args, **kwargs): + return array.wet_bulb_potential_temperature_from_specific_humidity(*args, **kwargs) diff --git a/earthkit/meteo/wind/__init__.py b/earthkit/meteo/wind/__init__.py new file mode 100644 index 0000000..5aa9729 --- /dev/null +++ b/earthkit/meteo/wind/__init__.py @@ -0,0 +1,18 @@ +# (C) Copyright 2021 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. +# + +""" +Wind related functions. + +The API is split into two levels. The low level functions are in the ``array`` submodule and they +can be used to operate on numpy arrays. The high level functions are still to be developed and +planned to work with objects like *earthkit.data FieldLists* or *xarray DataSets*. +""" + +from .wind import * # noqa diff --git a/earthkit/meteo/wind/array/__init__.py b/earthkit/meteo/wind/array/__init__.py new file mode 100644 index 0000000..1d61d5a --- /dev/null +++ b/earthkit/meteo/wind/array/__init__.py @@ -0,0 +1,14 @@ +# (C) Copyright 2021 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. +# + +""" +Wind related functions operating on numpy arrays. +""" + +from .wind import * # noqa diff --git a/earthkit/meteo/wind/array/wind.py b/earthkit/meteo/wind/array/wind.py new file mode 100644 index 0000000..f611ca9 --- /dev/null +++ b/earthkit/meteo/wind/array/wind.py @@ -0,0 +1,295 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + +from earthkit.meteo import constants + + +def speed(u, v): + r"""Computes the wind speed/vector magnitude. + + Parameters + ---------- + u: number or ndarray + u wind/x vector component + v: number or ndarray + v wind/y vector component (same units as ``u``) + + Returns + ------- + number or ndarray + Wind speed/magnitude (same units as ``u`` and ``v``) + + """ + return np.hypot(u, v) + + +def _direction_meteo(u, v): + minus_pi2 = -np.pi / 2.0 + d = np.arctan2(v, u) + d = np.asarray(d) + m = d <= minus_pi2 + d[m] = (minus_pi2 - d[m]) * constants.degree + m = ~m + d[m] = (1.5 * np.pi - d[m]) * constants.degree + return d + + +def _direction_polar(u, v, to_positive): + d = np.arctan2(v, u) * constants.degree + if to_positive: + d = np.asarray(d) + m = d < 0 + d[m] = 360.0 + d[m] + return d + + +def direction(u, v, convention="meteo", to_positive=True): + r"""Computes the direction/angle of a vector quantity. + + Parameters + ---------- + u: number or ndarray + u wind/x vector component + v: number or ndarray + v wind/y vector component (same units as ``u``) + convention: str, optional + Specifies how the direction/angle is interpreted. The possible values are as follows: + + * "meteo": the direction is the meteorological wind direction (see below for explanation) + * "polar": the direction is measured anti-clockwise from the x axis (East/right) to the vector + + positive: bool, optional + If it is True the resulting values are mapped into the [0, 360] range when + ``convention`` is "polar". Otherwise they lie in the [-180, 180] range. + + + Returns + ------- + number or ndarray + Direction/angle (degrees) + + + The meteorological wind direction is the direction from which the wind is + blowing. Wind direction increases clockwise such that a northerly wind is 0°, an easterly + wind is 90°, a southerly wind is 180°, and a westerly wind is 270°. The figure below illustrates + how it is related to the actual orientation of the wind vector: + + .. image:: /_static/wind_direction.png + :width: 400px + + """ + if convention == "meteo": + return _direction_meteo(u, v) + elif convention == "polar": + return _direction_polar(u, v, to_positive) + else: + raise ValueError(f"direction(): invalid convention={convention}!") + + +def xy_to_polar(x, y, convention="meteo"): + r"""Converts wind/vector data from xy representation to polar representation. + + Parameters + ---------- + x: number or ndarray + u wind/x vector component + y: number or ndarray + v wind/y vector component (same units as ``u``) + convention: str + Specifies how the direction/angle component of the target polar coordinate + system is interpreted. The possible values are as follows: + + * "meteo": the direction is the meteorological wind direction (see :func:`direction` for explanation) + * "polar": the direction is measured anti-clockwise from the x axis (East/right) to the vector + + + Returns + ------- + number or ndarray + Magnitude (same units as ``u``) + number or ndarray + Direction (degrees) + + + In the target xy representation the x axis points East while the y axis points North. + + """ + return speed(x, y), direction(x, y, convention=convention) + + +def _polar_to_xy_meteo(magnitude, direction): + a = (270.0 - direction) * constants.radian + return magnitude * np.cos(a), magnitude * np.sin(a) + + +def _polar_to_xy_polar(magnitude, direction): + a = direction * constants.radian + return magnitude * np.cos(a), magnitude * np.sin(a) + + +def polar_to_xy(magnitude, direction, convention="meteo"): + r"""Converts wind/vector data from polar representation to xy representation. + + Parameters + ---------- + magnitude: number or ndarray + Speed/magnitude of the vector + direction: number or ndarray + Direction of the vector (degrees) + convention: str + Specifies how ``direction`` is interpreted. The possible values are as follows: + + * "meteo": ``direction`` is the meteorological wind direction + (see :func:`direction` for explanation) + * "polar": ``direction`` is the angle measured anti-clockwise from the x axis + (East/right) to the vector + + Returns + ------- + number or ndarray + X vector component (same units as ``magnitude``) + number or ndarray + Y vector component (same units as ``magnitude``) + + + In the target xy representation the x axis points East while the y axis points North. + + """ + if convention == "meteo": + return _polar_to_xy_meteo(magnitude, direction) + elif convention == "polar": + return _polar_to_xy_polar(magnitude, direction) + else: + raise ValueError(f"polar_to_xy(): invalid convention={convention}!") + + +def w_from_omega(omega, t, p): + r"""Computes the hydrostatic vertical velocity from pressure velocity, temperature and pressure. + + Parameters + ---------- + omega : number or ndarray + Hydrostatic pressure velocity (Pa/s) + t : number or ndarray + Temperature (K) + p : number or ndarray + Pressure (Pa) + + Returns + ------- + number or ndarray + Hydrostatic vertical velocity (m/s) + + + The computation is based on the following hydrostatic formula: + + .. math:: + + w = - \frac{\omega\; t R_{d}}{p g} + + where + + * :math:`R_{d}` is the specific gas constant for dry air (see :data:`earthkit.meteo.constants.Rd`). + * :math:`g` is the gravitational acceleration (see :data:`earthkit.meteo.constants.g`) + + """ + return (-constants.Rd / constants.g) * (omega * t / p) + + +def coriolis(lat): + r"""Computes the Coriolis parameter. + + Parameters + ---------- + lat : number or ndarray + Latitude (degrees) + + Returns + ------- + number or ndarray + The Coriolis parameter (:math:`s^{-1}`) + + + The Coriolis parameter is defined by the following formula: + + .. math:: + + f = 2 \Omega sin(\phi) + + where :math:`\Omega` is the rotation rate of Earth + (see :data:`earthkit.meteo.constants.omega`) and :math:`\phi` is the latitude. + + """ + return 2 * constants.omega * np.sin(lat * constants.radian) + + +def windrose(speed, direction, sectors=16, speed_bins=[], percent=True): + """Generate windrose data. + + Parameters + ---------- + speed : number or ndarray + Speed + direction : number or ndarray + Meteorological wind direction (degrees). See :func:`direction` for details. + Values must be between 0 and 360. + sectors: number + Number of sectors the 360 degrees direction range is split into. See below for details. + speed_bin: list or ndarray + Speed bins + percent: bool + If False, returns the number of valid samples in each bin. If True, returns + the percentage of the number of samples in each bin with respect to the total + number of valid samples. + + + Returns + ------- + 2d-ndarray + The bi-dimensional histogram of ``speed`` and ``direction``. Values in + ``speed`` are histogrammed along the first dimension and values in ``direction`` + are histogrammed along the second dimension. + + ndarray + The direction bins (i.e. the sectors) (degrees) + + + The sectors do not start at 0 degrees (North) but are shifted by half a sector size. + E.g. if ``sectors`` is 4 the sectors are defined as: + + .. image:: /_static/wind_sector.png + :width: 350px + + """ + if len(speed_bins) < 2: + raise ValueError("windrose(): speed_bins must have at least 2 elements!") + + sectors = int(sectors) + if sectors < 1: + raise ValueError("windrose(): sectors must be greater than 1!") + + speed = np.atleast_1d(speed) + direction = np.atleast_1d(direction) + dir_step = 360.0 / sectors + dir_bins = np.linspace( + int(-dir_step / 2), int(360 + dir_step / 2), int(360 / dir_step) + 2 + ) + + res = np.histogram2d(speed, direction, bins=[speed_bins, dir_bins], density=False)[ + 0 + ] + + # unify the north bins + res[:, 0] = res[:, 0] + res[:, -1] + res = res[:, :-1] + dir_bins = dir_bins[:-1] + + return ((res * 100.0 / res.sum()) if percent else res), dir_bins diff --git a/earthkit/meteo/wind/wind.py b/earthkit/meteo/wind/wind.py new file mode 100644 index 0000000..3a28ae5 --- /dev/null +++ b/earthkit/meteo/wind/wind.py @@ -0,0 +1,38 @@ +# +# # (C) Copyright 2021 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. +# ## +from . import array + + +def speed(*args, **kwargs): + return array.speed(*args, **kwargs) + + +def direction(*args, **kwargs): + return array.direction(*args, **kwargs) + + +def xy_to_polar(*args, **kwargs): + return array.xy_to_polar(*args, **kwargs) + + +def polar_to_xy(*args, **kwargs): + return array.polar_to_xy(*args, **kwargs) + + +def w_from_omega(*args, **kwargs): + return array.w_from_omega(*args, **kwargs) + + +def coriolis(*args, **kwargs): + return array.coriolis(*args, **kwargs) + + +def windrose(*args, **kwargs): + return array.windrose(*args, **kwargs) diff --git a/pyproject.toml b/pyproject.toml index 040eedc..1441605 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,8 +8,8 @@ branch = true profile = "black" [tool.pydocstyle] -convention = "numpy" add_ignore = ["D1", "D200", "D205", "D400", "D401"] +convention = "numpy" [tool.setuptools_scm] write_to = "earthkit/meteo/version.py" diff --git a/setup.cfg b/setup.cfg index 4a9a83e..6e27fe8 100644 --- a/setup.cfg +++ b/setup.cfg @@ -25,6 +25,11 @@ install_requires = [options.packages.find] include = earthkit.* +[options.extras_require] +test = + pytest + pytest-cov + [flake8] max-line-length = 110 extend-ignore = E203, W503 diff --git a/tests/data/eqpt.csv b/tests/data/eqpt.csv new file mode 100644 index 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b/tests/extreme/test_extreme.py @@ -0,0 +1,825 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + +from earthkit.meteo import extreme + +ens = np.array( + [ + 273.56037903, + 273.61122131, + 273.63012695, + 273.59335327, + 273.57876587, + 273.65365601, + 273.61138916, + 273.56483459, + 273.51663208, + 273.58750916, + 273.65254211, + 273.60098267, + 273.58737183, + 273.60316467, + 273.59606934, + 273.60876465, + 273.50160217, + 273.57923889, + 273.56584167, + 273.49942017, + 273.62069702, + 273.58499146, + 273.58781433, + 273.59477234, + 273.68614197, + 273.60530090, + 273.53808594, + 273.54582214, + 273.65734863, + 273.65567017, + 273.57177734, + 273.55506897, + 273.55067444, + 273.56301880, + 273.54679871, + 273.58064270, + 273.56997681, + 273.61926270, + 273.57879639, + 273.60385132, + 273.63429260, + 273.61221313, + 273.40080261, + 273.52342224, + 273.63037109, + 273.54180908, + 273.56486511, + 273.60005188, + 273.49523926, + 273.56845093, + 273.621521, + ] +) +ens = ens[:, np.newaxis] + +ens_eps = np.array( + [ + 0.00458526611328125, + 0.0051116943359375, + 0.0065460205078125, + 0.00421142578125, + 0.0057830810546875, + 0.008014678955078125, + 0.004108428955078125, + 0.00556182861328125, + 0.004291534423828125, + 0.00505828857421875, + 0.002925872802734375, + 0.007587432861328125, + 0.00222015380859375, + 0.007373809814453125, + 0.0028076171875, + 0.005950927734375, + 0.004131317138671875, + 0.004913330078125, + 0.00797271728515625, + 0.005260467529296875, + 0.0038299560546875, + 0.007537841796875, + 0.00521087646484375, + 0.0087127685546875, + 0.007537841796875, + 0.00247955322265625, + 0.002040863037109375, + 0.0065765380859375, + 0.006870269775390625, + 0.0051422119140625, + 0.004852294921875, + 0.00359344482421875, + 0.00231170654296875, + 0.0048675537109375, + 0.0071563720703125, + 0.0062408447265625, + 0.00475311279296875, + 0.00350189208984375, + 0.00746917724609375, + 0.0047607421875, + 0.00444793701171875, + 0.00389862060546875, + 0.0027923583984375, + 0.004535675048828125, + 0.00621795654296875, + 0.00292205810546875, + 0.00658416748046875, + 0.0046234130859375, + 0.00444793701171875, + 0.0044403076171875, + 0.005218505859375, + ] +) +ens_eps = ens_eps[:, np.newaxis] + +clim = np.array( + [ + 270.31404114, + 271.04376221, + 271.88911438, + 272.17996216, + 272.29629517, + 272.45881653, + 272.55467224, + 272.67176819, + 272.76577759, + 272.89602661, + 272.93855286, + 273.01394653, + 273.08497620, + 273.13676453, + 273.19113159, + 273.22419739, + 273.25590515, + 273.26646423, + 273.30346680, + 273.31695557, + 273.31858826, + 273.33642578, + 273.37065125, + 273.39843750, + 273.40194702, + 273.44013977, + 273.44854736, + 273.47970581, + 273.49264526, + 273.50416565, + 273.52960205, + 273.54267883, + 273.56050110, + 273.55299377, + 273.56401062, + 273.58006287, + 273.58612061, + 273.62063599, + 273.60931396, + 273.60650635, + 273.61801147, + 273.62141418, + 273.65431213, + 273.63867188, + 273.65670776, + 273.67222595, + 273.65425110, + 273.68618774, + 273.68138123, + 273.67578125, + 273.69137573, + 273.68821716, + 273.69772339, + 273.69319153, + 273.70791626, + 273.73648071, + 273.71696472, + 273.72935486, + 273.74089050, + 273.73986816, + 273.76908875, + 273.75910950, + 273.78601074, + 273.78836060, + 273.80046082, + 273.79504395, + 273.81297302, + 273.80552673, + 273.81306458, + 273.83451843, + 273.83099365, + 273.84126282, + 273.84231567, + 273.85221863, + 273.88308716, + 273.87722778, + 273.89910889, + 273.90881348, + 273.88888550, + 273.90223694, + 273.92579651, + 273.93246460, + 273.93844604, + 273.95280457, + 273.96545410, + 273.98947144, + 273.98995972, + 274.02645874, + 274.05247498, + 274.06059265, + 274.05807495, + 274.10276794, + 274.12309265, + 274.15106201, + 274.16433716, + 274.19328308, + 274.20668030, + 274.27967834, + 274.33123779, + 274.42781067, + 274.55859375, + ] +) +clim = clim[:, np.newaxis] + +clim_eps = np.array( + [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 6.103515625e-05, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.0001220703125, + 0.00018310546875, + 0.000244140625, + 0.0002441406250, + 0.0002441406250, + 0.0002441406250, + 0.0002441406250, + 0.00030517578125, + 0.0003662109375, + 0.0003662109375, + 0.0003662109375, + 0.0003662109375, + 0.00042724609375, + 0.00048828125, + 0.00048828125, + 0.00048828125, + 0.00054931640625, + 0.0006103515625, + 0.0006103515625, + 0.000732421875, + 0.000732421875, + 0.00079345703125, + 0.0008544921875, + 0.0009765625, + 0.0009765625, + 0.0010986328125, + 0.001220703125, + 0.0013427734375, + 0.00146484375, + 0.00152587890625, + 0.001708984375, + 0.0018310546875, + 0.001953125, + 0.0020751953125, + 0.00225830078125, + 0.00244140625, + 0.0025634765625, + 0.0028076171875, + 0.0030517578125, + 0.0032958984375, + 0.00341796875, + 0.003662109375, + 0.0037841796875, + 0.004150390625, + 0.00433349609375, + 0.0045166015625, + 0.0047607421875, + 0.005126953125, + 0.0054931640625, + 0.005859375, + 0.0062255859375, + 0.006591796875, + 0.007080078125, + 0.00732421875, + 0.0078125, + 0.00830078125, + 0.0089111328125, + 0.009765625, + 0.01177978515625, + 0.01336669921875, + 0.015625, + 0.02294921875, + ] +) +clim_eps = clim_eps[:, np.newaxis] + +ens_eps2 = np.array( + [ + 0.41961669921875, + 0.4482269287109375, + 0.60272216796875, + 0.6380081176757812, + 0.46539306640625, + 0.461578369140625, + 0.06389617919921875, + 0.6380081176757812, + 0.3070831298828125, + 1.1043548583984375, + 0.9107589721679688, + 0.5931854248046875, + 0.48732757568359375, + 0.20503997802734375, + 0.16117095947265625, + 0.30231475830078125, + 0.5283355712890625, + 0.24127960205078125, + 0.823974609375, + 0.8258819580078125, + 0.7534027099609375, + 0.2307891845703125, + 0.09632110595703125, + 0.08106231689453125, + 0.4138946533203125, + 0.5159378051757812, + 1.7681121826171875, + 1.1615753173828125, + 0.8449554443359375, + 0.5655288696289062, + 0.05054473876953125, + 0.29754638671875, + 0.4482269287109375, + 0.186920166015625, + 0.8544921875, + 0.286102294921875, + 0.0514984130859375, + 1.2903213500976562, + 0.7524490356445312, + 0.820159912109375, + 0.13446807861328125, + 0.6704330444335938, + 0.8459091186523438, + 0.45490264892578125, + 0.4444122314453125, + 0.0896453857421875, + 0.03147125244140625, + 0.4062652587890625, + 0.16117095947265625, + 0.8554458618164062, + 1.5535354614257812, + ] +) +ens_eps2 = ens_eps2[:, np.newaxis] + +clim_eps2 = np.array( + [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.48828125, + ] +) +clim_eps2 = clim_eps2[:, np.newaxis] + + +def test_efi(): + efi = extreme.array.efi(clim, ens) + + assert np.isclose(efi[0], -0.18384250406420133) + + +def test_efi_sorted(): + # ensures the algorithm is the same if we sort the data or not + ens_perc = np.sort(ens) + + efi = extreme.array.efi(clim, ens_perc) + + assert np.isclose(efi[0], -0.18384250406420133) + + +def test_efi_eps(): + efi = extreme.array.efi(clim, ens, eps=1e-4) + + assert np.isclose(efi[0], -0.18384250406420133) + + +def test_efi_eps1(): + efi = extreme.array.efi(clim_eps, ens_eps, eps=1e-4) + + # fortran code result is 0.4604220986366272 + assert np.isclose(efi[0], 0.46039347745967046) + + +def test_efi_eps2(): + efi = extreme.array.efi(clim_eps2, ens_eps2, eps=1e-4) + + # fortran code result is + assert np.isclose(efi[0], 0.6330071575726789) + + +def test_sot(): + sot_upper = extreme.array.sot(clim, ens, 90) + sot_lower = extreme.array.sot(clim, ens, 10) + + print(sot_upper) + print(sot_lower) + + assert np.isclose(sot_upper[0], -2.14617638) + assert np.isclose(sot_lower[0], -1.3086723) + + +def test_sot_missing(): + # first value valid, second -> inf, third gives nan, third is below threshold -> nan + qc_tail = np.array([1.0, 1.0, 1.0, 1.0]) + qc = np.array([1.1, 1.0, 1.0, 1.00001]) + qf = np.array([1.5, 1.2, 1.0, 0.9]) + + sot = extreme.array.sot_func(qc_tail, qc, qf, eps=1e-4) + + print(sot) + print(np.isnan(sot)) + + assert np.isclose(sot[0], -5) + + assert np.array_equal(np.isnan(sot[1:]), [True, True, True]) + + +def test_sot_bounds(): + # first is lower bound, second is upper bound + qc_tail = np.array([1.0, 1.0]) + qc = np.array([1.1, 1.1]) + qf = np.array([15, -15.0]) + + sot = extreme.array.sot_func(qc_tail, qc, qf) + + print(sot) + assert np.allclose(sot, [-10, 10]) + + +def test_sot_eps(): + # first value valid, second -> inf, third gives nan, third is below threshold -> nan + qc_tail = np.array([0.05]) + qc = np.array([0.1]) + qf = np.array([0.2]) + + sot = extreme.array.sot_func(qc_tail, qc, qf) + print(sot) + assert np.isclose(sot[0], -3.0) + + sot = extreme.array.sot_func(qc_tail, qc, qf, eps=0.15) + print(sot) + assert np.isnan(sot[0]) + + +def test_sot_perc(): + sot = extreme.array.sot(clim_eps2, ens_eps2, 90, eps=1e4) + + assert np.isnan(sot[0]) + + +def test_efi_nan(): + clim_nan = np.empty((101, 1)) + clim_nan[:] = np.nan + ens_nan = np.empty((51, 1)) + ens_nan[:] = np.nan + print(clim_nan) + print(ens_nan) + + efi = extreme.array.efi(clim_nan, ens_nan) + + print(efi) + assert np.isnan(efi[0]) + + +def test_sot_nan(): + qc_tail = np.array([0.05]) + qc = np.array([0.1]) + qf = np.array([np.nan]) + + sot = extreme.array.sot_func(qc_tail, qc, qf) + assert np.isnan(sot[0]) + + qc_tail = np.array([0.05]) + qc = np.array([np.nan]) + qf = np.array([0.1]) + + sot = extreme.array.sot_func(qc_tail, qc, qf) + assert np.isnan(sot[0]) + + qc_tail = np.array([np.nan]) + qc = np.array([0.1]) + qf = np.array([0.2]) + + sot = extreme.array.sot_func(qc_tail, qc, qf) + assert np.isnan(sot[0]) + + +cpf_val = np.array([0.0, 1.0, 0.21153846, 0.53846157, 0.7307692], dtype=np.float32) +cpf_ens = np.array( + [ + [299.3667, 299.97998, 276.91553, 298.83936, 296.2339], + [299.99323, 299.92096, 276.72174, 298.62604, 296.4854], + [299.86163, 299.3382, 276.6468, 298.63312, 296.09015], + [299.12872, 301.24005, 277.24396, 298.7635, 296.03693], + [299.42084, 299.52435, 276.62396, 298.2802, 296.37592], + [299.12198, 299.77823, 276.53995, 298.7548, 296.5341], + [299.0536, 299.80554, 276.46375, 298.72742, 295.91296], + [299.197, 300.52902, 276.697, 298.72238, 296.01144], + [298.88193, 299.34482, 277.19247, 298.70615, 296.35068], + [299.5131, 300.50528, 276.808, 298.95255, 296.3842], + [299.88654, 299.367, 276.7713, 298.7342, 296.6053], + [299.2812, 299.88275, 276.5136, 298.89447, 296.05267], + [299.32745, 299.9505, 277.42316, 298.12042, 296.7044], + [298.97488, 299.3245, 276.65262, 298.59402, 296.4788], + [299.56702, 299.83655, 276.5006, 298.46545, 295.9342], + [300.4615, 299.86383, 277.0103, 298.80133, 296.7779], + [298.95248, 300.66537, 276.30014, 298.6888, 295.95444], + [300.07544, 300.52466, 276.85083, 298.53052, 295.72192], + [299.23877, 300.64697, 276.99072, 298.17822, 296.36377], + [299.89127, 300.12173, 276.8854, 298.80142, 296.02798], + [299.85345, 300.22455, 276.83197, 298.75775, 296.24603], + [299.69104, 300.41956, 276.75745, 298.50745, 296.03088], + [299.32013, 299.89825, 276.53497, 298.97052, 296.25372], + [299.34235, 299.8404, 276.66852, 298.65485, 296.4478], + [299.51978, 300.20142, 276.9182, 298.69556, 295.96313], + [299.12, 299.6571, 277.2411, 299.03406, 296.32312], + [299.1634, 300.07355, 276.9466, 298.73175, 295.7923], + [299.4486, 300.1361, 276.49353, 298.67908, 295.75525], + [299.0878, 299.90225, 277.06436, 298.85147, 295.54678], + [299.26794, 299.7777, 276.66052, 298.60583, 296.0453], + [300.09146, 299.7399, 276.9567, 298.81216, 296.41763], + [298.36334, 300.7813, 276.97662, 298.72662, 296.59576], + [299.5633, 299.8719, 276.65704, 298.85822, 296.02618], + [299.65924, 299.62604, 276.97955, 298.64752, 296.3858], + [299.18683, 299.6009, 276.84894, 298.8919, 296.01105], + [299.18616, 299.7213, 276.84045, 298.72522, 295.2174], + [299.2762, 299.39145, 276.59067, 299.04184, 296.18832], + [299.14, 299.89197, 276.55798, 298.95642, 296.02087], + [299.52063, 299.87805, 276.63586, 298.49133, 296.14758], + [299.1657, 300.37274, 276.78876, 298.73212, 296.1618], + [299.11887, 299.68918, 276.93137, 298.363, 296.08762], + [298.96027, 300.2884, 276.94464, 298.71417, 296.38605], + [299.3237, 299.8823, 276.62643, 298.31784, 296.33542], + [299.65875, 300.9439, 276.64313, 298.60016, 296.23883], + [299.38763, 300.9677, 276.46576, 298.706, 296.42474], + [299.6558, 300.36673, 277.55423, 298.62064, 296.1382], + [298.9718, 299.38782, 277.0265, 298.83508, 295.49915], + [299.56116, 300.26624, 276.89124, 298.8131, 296.1217], + [298.70483, 299.61694, 276.32202, 298.53687, 296.1931], + [299.25137, 300.9799, 276.9291, 298.81583, 296.1459], + [298.67615, 300.391, 277.0199, 298.65076, 296.50623], + ], + dtype=np.float32, +) +cpf_clim = np.array( + [ + [298.3246, 292.73083, 272.6996, 296.6996, 290.91833], + [298.75378, 294.94128, 273.84753, 297.41003, 292.53503], + [298.88678, 295.19928, 274.54303, 297.57428, 292.85553], + [298.95166, 295.3579, 274.7954, 297.63916, 293.0454], + [299.00775, 295.57025, 274.914, 297.7265, 293.164], + [299.07755, 295.6713, 275.07755, 297.7963, 293.32755], + [299.12042, 295.80792, 275.21417, 297.83917, 293.46417], + [299.1596, 295.94086, 275.31586, 297.87836, 293.62836], + [299.19135, 296.0351, 275.44135, 297.9101, 293.75385], + [299.21613, 296.09113, 275.52863, 297.96613, 293.87238], + [299.2633, 296.16956, 275.66956, 298.0133, 293.91956], + [299.27515, 296.2439, 275.8064, 298.02515, 293.9939], + [299.3001, 296.3001, 275.89386, 298.0501, 294.0501], + [299.32086, 296.38336, 275.9771, 298.07086, 294.07086], + [299.36493, 296.42743, 276.08368, 298.11493, 294.11493], + [299.36322, 296.48822, 276.17572, 298.14447, 294.17572], + [299.39822, 296.55447, 276.24197, 298.14822, 294.24197], + [299.434, 296.6215, 276.309, 298.184, 294.27774], + [299.44525, 296.63275, 276.38275, 298.19525, 294.3515], + [299.46143, 296.68018, 276.46143, 298.21143, 294.36768], + [299.4816, 296.7316, 276.57535, 298.2316, 294.4191], + [299.49713, 296.77838, 276.62213, 298.27838, 294.49713], + [299.52496, 296.8062, 276.64996, 298.27496, 294.52496], + [299.53876, 296.82, 276.695, 298.28876, 294.60126], + [299.56372, 296.87622, 276.78247, 298.31372, 294.62622], + [299.56152, 296.93652, 276.84277, 298.31152, 294.68652], + [299.60294, 296.9467, 276.91544, 298.35294, 294.72794], + [299.61484, 296.9586, 276.98984, 298.36484, 294.7711], + [299.60883, 297.01508, 277.04633, 298.39008, 294.85883], + [299.62442, 297.03067, 277.09317, 298.37442, 294.90567], + [299.6407, 297.0782, 277.1407, 298.3907, 294.9532], + [299.67407, 297.14282, 277.20532, 298.42407, 294.98657], + [299.69638, 297.16513, 277.25888, 298.44638, 295.00888], + [299.7088, 297.2088, 277.3338, 298.4588, 295.05255], + [299.7254, 297.2254, 277.4129, 298.4754, 295.06915], + [299.75555, 297.25555, 277.4743, 298.50555, 295.0993], + [299.74548, 297.27673, 277.55798, 298.49548, 295.15173], + [299.79517, 297.32642, 277.60767, 298.51392, 295.17017], + [299.81113, 297.34238, 277.65488, 298.52988, 295.21738], + [299.80298, 297.36548, 277.70923, 298.55298, 295.24048], + [299.82, 297.3825, 277.78876, 298.57, 295.28876], + [299.83588, 297.42963, 277.86713, 298.58588, 295.30463], + [299.8523, 297.4773, 277.94604, 298.6023, 295.3523], + [299.85468, 297.47968, 277.97968, 298.60468, 295.35468], + [299.87244, 297.5287, 278.05994, 298.62244, 295.4037], + [299.9093, 297.56555, 278.0968, 298.62805, 295.44055], + [299.9245, 297.58075, 278.14325, 298.64325, 295.487], + [299.92245, 297.60995, 278.2037, 298.67245, 295.5162], + [299.95905, 297.64655, 278.3028, 298.6778, 295.5528], + [299.972, 297.6595, 278.37823, 298.69073, 295.597], + [299.96408, 297.68283, 278.46408, 298.71408, 295.62033], + [300.00043, 297.71918, 278.53168, 298.71918, 295.65668], + [300.0108, 297.7608, 278.6358, 298.72955, 295.6983], + [300.03705, 297.78705, 278.7558, 298.7558, 295.7558], + [300.0407, 297.82196, 278.82196, 298.75946, 295.7907], + [300.05652, 297.86902, 278.86902, 298.77527, 295.83777], + [300.0688, 297.8813, 278.91254, 298.78754, 295.8813], + [300.1017, 297.9142, 279.00797, 298.7892, 295.9142], + [300.09235, 297.9361, 279.09235, 298.8111, 295.96735], + [300.1114, 297.95514, 279.1739, 298.83014, 295.9864], + [300.14584, 297.9896, 279.20834, 298.83334, 296.02084], + [300.16125, 298.005, 279.28625, 298.84875, 296.0675], + [300.1659, 298.0409, 279.38464, 298.8534, 296.1034], + [300.20065, 298.07565, 279.45065, 298.8569, 296.13815], + [300.20398, 298.11023, 279.51648, 298.89148, 296.14148], + [300.21356, 298.1198, 279.58856, 298.90106, 296.1823], + [300.2539, 298.16016, 279.66016, 298.91016, 296.22266], + [300.2667, 298.2042, 279.7042, 298.92294, 296.23544], + [300.2884, 298.2259, 279.75714, 298.9134, 296.2884], + [300.28217, 298.25092, 279.84467, 298.93842, 296.31342], + [300.31854, 298.2873, 279.9123, 298.94354, 296.31854], + [300.3202, 298.3202, 279.9452, 298.9452, 296.35144], + [300.3286, 298.35986, 280.0161, 298.9536, 296.3911], + [300.37357, 298.37357, 280.09232, 298.96732, 296.43607], + [300.36435, 298.3956, 280.1456, 298.98935, 296.4581], + [300.4051, 298.43634, 280.18634, 298.99884, 296.49884], + [300.41455, 298.4458, 280.2583, 299.0083, 296.53955], + [300.4345, 298.46576, 280.3095, 299.02826, 296.59076], + [300.4567, 298.48795, 280.36295, 299.05045, 296.61295], + [300.47876, 298.54126, 280.41626, 299.0725, 296.635], + [300.48907, 298.58282, 280.52032, 299.08282, 296.67657], + [300.52576, 298.6195, 280.6195, 299.08826, 296.71326], + [300.53998, 298.63373, 280.69623, 299.10248, 296.75873], + [300.56067, 298.68567, 280.81067, 299.09192, 296.77942], + [300.57727, 298.73352, 280.88977, 299.10852, 296.82727], + [300.62796, 298.7842, 281.00296, 299.12796, 296.8467], + [300.63678, 298.82428, 281.10553, 299.16803, 296.88678], + [300.67902, 298.83527, 281.21027, 299.17902, 296.92902], + [300.71036, 298.89786, 281.3666, 299.1791, 296.9916], + [300.7229, 298.94165, 281.44165, 299.2229, 297.0354], + [300.77243, 298.99118, 281.58493, 299.24118, 297.08493], + [300.8109, 299.02966, 281.71716, 299.27966, 297.15466], + [300.84314, 299.0619, 281.8119, 299.3119, 297.21814], + [300.88876, 299.13876, 281.92, 299.32626, 297.2325], + [300.93634, 299.18634, 282.06134, 299.37384, 297.2801], + [300.98245, 299.29495, 282.16995, 299.41995, 297.35745], + [301.01904, 299.4253, 282.3003, 299.4878, 297.3628], + [301.082, 299.5195, 282.42575, 299.55075, 297.457], + [301.22263, 299.62888, 282.62888, 299.62888, 297.50388], + [301.3478, 299.7853, 282.9728, 299.75406, 297.69156], + [301.72018, 300.43893, 284.06393, 300.37643, 298.15768], + ], + dtype=np.float32, +) + + +def test_cpf(): + cpf = extreme.array.cpf(cpf_clim, cpf_ens, sort_clim=True) + np.testing.assert_allclose(cpf, cpf_val) + + +def test_highlevel_efi(): + efi = extreme.efi(clim, ens) + + assert np.isclose(efi[0], -0.18384250406420133) + + +def test_highlevel_sot(): + sot_upper = extreme.sot(clim, ens, 90) + sot_lower = extreme.sot(clim, ens, 10) + + assert np.isclose(sot_upper[0], -2.14617638) + assert np.isclose(sot_lower[0], -1.3086723) + + +def test_highlevel_cpf(): + cpf = extreme.cpf(cpf_clim, cpf_ens, sort_clim=True) + np.testing.assert_allclose(cpf, cpf_val) diff --git a/tests/score/test_score.py b/tests/score/test_score.py new file mode 100644 index 0000000..aa80c04 --- /dev/null +++ b/tests/score/test_score.py @@ -0,0 +1,854 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + +from earthkit.meteo import score + + +def crps_quaver2(x, y): + """Computes Continuous Ranked Probability Score (CRPS) from Quaver + Used for testing + + Parameters + ---------- + x: numpy array (n_ens, n_points) + Ensemble forecast + y: numpy array (n_points) + Observation/analysis + + Returns + ------- + numpy array (n_points) + CRPS values + + The method is described in [Hersbach2000]_. + """ + + n_ens = x.shape[0] + anarr = y + earr = x + # ensemble sorted by fieldset axis + esarr = np.sort(earr, axis=0) + aa = np.zeros(earr.shape) # alpha + aa = np.concatenate((aa, aa[:1, :])) + bb = aa.copy() # beta + with np.errstate(invalid="ignore"): + lcond = esarr[0, :] > anarr + aa[0, lcond] = 1.0 + bb[0, :] = np.where(lcond, esarr[0, :] - anarr, 0.0) + aa[1:-1, :] = np.where( + esarr[1:, :] <= anarr, esarr[1:, :] - esarr[:-1, :], anarr - esarr[:-1, :] + ) + aa[1:-1, :][esarr[: n_ens - 1, :] > anarr] = 0.0 # this would be hard in xarray + bb[1:-1, :] = np.where( + esarr[:-1, :] > anarr, esarr[1:, :] - esarr[:-1, :], esarr[1:, :] - anarr + ) + bb[1:-1, :][esarr[1:, :] <= anarr] = 0.0 + lcond = anarr > esarr[-1, :] + aa[-1, :] = np.where(lcond, anarr - esarr[-1, :], 0.0) + bb[-1, lcond] = 1.0 + # back to xarrays + # alpha = xarray.DataArray(aa, dims=e.dims) + # beta = xarray.DataArray(bb, dims=e.dims) + # weight = xarray.DataArray(np.arange(n_ens + 1), dims=ENS_DIM) / float(n_ens) + # w = np.arange(n_ens+1)/float(n_ens) + w = (np.arange(n_ens + 1) / float(n_ens)).reshape(n_ens + 1, *([1] * y.ndim)) + # w = np.expand_dims(np.arange(n_ens+1)/float(n_ens), axis=1) + crps = aa * w**2 + bb * (1.0 - w) ** 2 + crps_sum = np.nansum(crps, axis=0) + return crps_sum + # Fair CRPS + # fcrps = crps - self.ginis_mean_diff() / (2. * n_ens) + # return alpha, beta, crps, fcrps + + +def test_crps(): + obs = np.array( + [ + [ + 18.18332, + 16.91703, + 18.41237, + 18.52762, + 19.24018, + 18.92083, + 18.7347, + 18.74177, + 18.84006, + 18.55334, + 17.13083, + 18.84862, + 17.76169, + 18.39295, + 18.69872, + 18.83633, + 20.04871, + 18.70762, + 19.01472, + 19.28151, + 19.58305, + 18.82714, + 17.98188, + 19.38522, + 19.19444, + 20.05244, + 18.75, + ] + ] + ) + ens = np.array( + [ + [ + 18.60203, + 18.39837, + 18.15966, + 18.2023, + 18.33673, + 18.27596, + 18.16505, + 18.18332, + 18.0794, + 18.45462, + 18.511, + 18.30488, + 18.24115, + 18.96865, + 18.35899, + 18.47862, + 18.15919, + 18.33152, + 18.49652, + 18.57579, + 18.41748, + 18.54667, + 18.75921, + 18.6189, + ], + [ + 17.82097, + 18.14485, + 18.60321, + 17.84873, + 18.45063, + 18.46943, + 18.21171, + 18.01587, + 18.37726, + 18.37997, + 18.25159, + 18.74551, + 18.49753, + 18.30485, + 18.46268, + 18.38053, + 18.7921, + 18.60726, + 18.37832, + 18.63638, + 18.4735, + 18.46691, + 18.40706, + 18.46787, + ], + [ + 18.25722, + 18.31637, + 17.94259, + 18.08479, + 17.98738, + 17.84325, + 18.11392, + 17.5627, + 18.11146, + 18.66067, + 18.29907, + 18.52028, + 17.97144, + 18.00114, + 17.90269, + 18.42152, + 18.20297, + 18.23269, + 18.26792, + 18.17865, + 18.63547, + 18.18611, + 18.28587, + 18.34955, + ], + [ + 18.46637, + 18.28559, + 18.61714, + 18.54838, + 18.47381, + 18.58475, + 18.32031, + 18.39696, + 18.40214, + 18.68081, + 18.37716, + 18.30279, + 18.51266, + 18.46895, + 18.69215, + 18.0772, + 18.55367, + 18.33005, + 18.16397, + 18.32986, + 18.69788, + 18.58536, + 18.717, + 18.68816, + ], + [ + 18.33082, + 18.08299, + 18.28411, + 18.47392, + 18.1853, + 18.70116, + 18.3585, + 18.4014, + 18.50559, + 18.13646, + 18.88681, + 18.22201, + 18.3747, + 18.53531, + 18.33449, + 18.52871, + 18.5113, + 18.46233, + 18.68657, + 18.41774, + 18.35555, + 18.37039, + 18.47539, + 18.3886, + ], + [ + 18.62395, + 18.23428, + 18.782, + 18.27582, + 18.49167, + 18.27856, + 18.30689, + 18.67729, + 18.15076, + 18.35025, + 18.59495, + 18.65966, + 18.33589, + 18.82887, + 18.20526, + 18.06337, + 18.30195, + 18.94566, + 18.67036, + 18.5322, + 18.79806, + 18.54978, + 18.49529, + 18.91547, + ], + [ + 18.66162, + 18.41238, + 18.99822, + 18.88024, + 18.56961, + 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+ 18.61704, + 18.84944, + 18.48689, + 18.62681, + 18.77607, + 18.64201, + 18.8559, + 18.57702, + 18.46109, + ], + [ + 18.67784, + 18.42476, + 18.52205, + 18.41963, + 18.32471, + 18.24997, + 18.60797, + 18.54053, + 18.8739, + 18.3279, + 18.03648, + 18.65794, + 18.942, + 18.59777, + 18.63692, + 18.53363, + 19.00416, + 18.58927, + 18.47256, + 18.85754, + 18.55462, + 18.7629, + 18.49969, + 18.55102, + ], + [ + 18.6331, + 18.71255, + 18.17562, + 18.73818, + 18.96507, + 18.48447, + 18.62908, + 18.73402, + 18.99546, + 18.34555, + 18.64311, + 18.83355, + 18.61156, + 18.92137, + 18.65269, + 18.89733, + 19.15071, + 18.99898, + 18.68672, + 18.60682, + 18.90617, + 18.77038, + 18.27683, + 18.63486, + ], + [ + 18.76511, + 18.93057, + 18.95042, + 18.84819, + 18.48806, + 19.29665, + 19.13163, + 19.14136, + 18.57607, + 19.05337, + 19.0143, + 19.00267, + 18.90464, + 18.82456, + 18.74383, + 18.87646, + 19.05792, + 19.25116, + 19.20859, + 18.75791, + 18.95366, + 18.74861, + 18.97499, + 18.89206, + ], + [ 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19.08904, + 18.58958, + 18.82234, + 19.05752, + 18.79315, + ], + [ + 18.77299, + 18.68177, + 18.78737, + 18.42972, + 18.46792, + 18.89753, + 18.79876, + 18.60094, + 18.89985, + 18.98094, + 18.95772, + 18.9883, + 18.84575, + 18.76947, + 18.98135, + 19.01894, + 19.44606, + 18.89475, + 19.15412, + 19.20748, + 19.17444, + 19.32477, + 18.86843, + 19.2845, + ], + [ + 18.86211, + 18.81549, + 18.96763, + 19.0877, + 19.13518, + 18.74888, + 19.04076, + 18.85203, + 18.80738, + 19.47674, + 18.97152, + 19.30402, + 19.17206, + 18.87924, + 18.93817, + 18.84938, + 19.16146, + 18.42349, + 19.14038, + 19.11972, + 18.9862, + 19.01817, + 18.77669, + 18.95876, + ], + [ + 19.15834, + 18.85331, + 19.00297, + 19.04329, + 19.01327, + 18.69482, + 19.22047, + 18.94505, + 19.09807, + 19.51356, + 18.99829, + 19.15129, + 18.8257, + 18.99315, + 19.18298, + 19.3982, + 18.96748, + 18.94291, + 19.15574, + 19.06957, + 18.67271, + 19.23746, + 19.2181, + 19.26443, + ], + [ + 18.96979, + 18.69425, + 19.26467, + 19.31992, + 18.99275, + 18.94634, + 19.30543, + 18.72837, + 19.32144, + 19.07595, + 19.0096, + 19.27506, + 19.04715, + 19.17561, + 19.38555, + 19.40679, + 19.21241, + 19.41876, + 19.2357, + 19.27149, + 19.37533, + 19.21089, + 19.30751, + 19.35292, + ], + [ + 18.84174, + 19.03868, + 19.03287, + 18.97804, + 18.84218, + 19.42819, + 19.23164, + 19.17193, + 19.36265, + 19.07079, + 19.6104, + 19.31643, + 19.23143, + 19.36369, + 19.00115, + 18.96971, + 18.93869, + 19.19646, + 18.91059, + 18.76732, + 19.16999, + 19.43966, + 19.32732, + 19.27241, + ], + [ + 19.62295, + 19.00364, + 18.9897, + 19.04174, + 19.02866, + 19.57506, + 19.33182, + 19.07238, + 19.41094, + 19.35779, + 19.2587, + 19.17919, + 19.472, + 19.59344, + 19.32774, + 19.08439, + 19.1335, + 19.07593, + 19.82984, + 19.46689, + 19.42777, + 19.27194, + 19.10563, + 19.13054, + ], + [ + 18.96093, + 18.9821, + 19.13877, + 18.98479, + 19.21401, + 19.10517, + 19.43129, + 19.21763, + 19.51593, + 19.10233, + 19.07561, + 19.32022, + 18.76391, + 19.2432, + 19.13902, + 19.08999, + 19.28826, + 19.23503, + 18.99935, + 19.50145, + 19.09675, + 19.17403, + 19.27126, + 18.91046, + ], + ] + ) + ens_tr = ens.transpose() + + goal = [ + 0.11623786458333449, + 1.3377413194444439, + 0.14396145833333263, + 0.05145284722222212, + 0.72659345486110970, + 0.27901552083333270, + 0.067909236111111190, + 0.24382366319444510, + 0.05285151041666695, + 0.06693468750000071, + 1.3187623263888897, + 0.08775225694444466, + 1.06167119791666500, + 0.11707013888888933, + 0.06489800347222260, + 0.041414305555555560, + 1.001697135416666, + 0.12593750000000084, + 0.07581557291666664, + 0.2746188541666673, + 0.51726421875000020, + 0.08657913194444464, + 0.97686340277777720, + 0.10266149305555577, + 0.062085798611111194, + 0.6430974652777783, + 0.30735505208333325, + ] + + crps_mm = score.crps(ens_tr, obs[0]) + crps_qu = crps_quaver2(ens_tr, obs[0]) + + for j in range(ens.shape[0]): + assert np.allclose(crps_mm[j], goal[j]) + assert np.allclose(crps_qu[j], goal[j]) + + mean_goal = 0.36859501543209877 + print(crps_mm.mean()) + assert np.allclose(crps_mm.mean(), mean_goal) + assert np.allclose(crps_qu.mean(), mean_goal) diff --git a/tests/solar/test_solar.py b/tests/solar/test_solar.py new file mode 100644 index 0000000..0959128 --- /dev/null +++ b/tests/solar/test_solar.py @@ -0,0 +1,27 @@ +# (C) Copyright 2021 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. +# + +import datetime + +import numpy as np +import pytest + +from earthkit.meteo import solar + + +@pytest.mark.parametrize( + "date,expected_value", + [ + (datetime.datetime(2024, 4, 22), 112.0), + (datetime.datetime(2024, 4, 22, 12, 0, 0), 112.5), + ], +) +def test_julian_day(date, expected_value): + v = solar.julian_day(date) + assert np.isclose(v, expected_value) diff --git a/tests/stats/test_stats.py b/tests/stats/test_stats.py new file mode 100644 index 0000000..7709313 --- /dev/null +++ b/tests/stats/test_stats.py @@ -0,0 +1,67 @@ +# (C) Copyright 2021 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. +# + +import numpy as np +import pytest + +from earthkit.meteo import stats + + +def test_nanaverage(): + data = np.array([[[4, 2], [4, np.nan]], [[4, 4], [np.nan, 2]]]) + + # assert nanaverage=nanmean when no weights: + np.testing.assert_equal(np.nanmean(data, axis=-1), stats.nanaverage(data, axis=-1)) + + # Check that using weights returns target result + weights = np.array([1, 0.25]) + # calculate weighted average + target_result = np.average(data, axis=-1, weights=weights) + # replace nan values + target_result[:, 1] = np.nansum(data, axis=-1)[:, 1] + print(target_result) + np.testing.assert_equal( + stats.nanaverage(data, axis=-1, weights=weights), target_result + ) + + +@pytest.mark.parametrize("method", ["sort", "numpy_bulk", "numpy"]) +def test_quantiles(method): + data = np.array( + [ + [3, 6, 12, 0, 45, 0, 4, 0, 7], + [1, 2.5, 4, 3, 18, 3, 8, 7, 2], + [3, 4, 9, 0.5, 2, 48, 4, 9, 6], + [5, 19, 8.3, 2, 6, 1, 0, 1, 0], + ], + dtype=np.float64, + ) + + quartiles = list(stats.iter_quantiles(data.copy(), 4, axis=1, method=method)) + assert len(quartiles) == 5 + expectedq = np.array( + [ + [0, 1, 0.5, 0], + [0, 2.5, 3, 1], + [4, 3, 4, 2], + [7, 7, 9, 6], + [45, 18, 48, 19], + ], + dtype=np.float64, + ) + np.testing.assert_equal(quartiles, expectedq) + + quantiles = list(stats.iter_quantiles(data.copy(), [0.5, 1.0], method=method)) + assert len(quantiles) == 2 + expectedq = np.array( + [ + [3, 5, 6.15, 1.25, 12, 2, 4, 4, 4], + [5, 19, 12, 3, 45, 48, 8, 9, 7], + ] + ) diff --git a/tests/test_version.py b/tests/test_version.py index 631a4b4..cd35996 100644 --- a/tests/test_version.py +++ b/tests/test_version.py @@ -1,10 +1,11 @@ -# (C) Copyright 2023 ECMWF. +# (C) Copyright 2021 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. +# import earthkit.meteo diff --git a/tests/thermo/test_thermo.py b/tests/thermo/test_thermo.py new file mode 100644 index 0000000..4eda2fe --- /dev/null +++ b/tests/thermo/test_thermo.py @@ -0,0 +1,19 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + +from earthkit.meteo import thermo + + +def test_high_level_celsius_to_kelvin(): + t = np.array([-10, 23.6]) + v = thermo.celsius_to_kelvin(t) + v_ref = np.array([263.16, 296.76]) + np.testing.assert_allclose(v, v_ref) diff --git a/tests/thermo/test_thermo_array.py b/tests/thermo/test_thermo_array.py new file mode 100644 index 0000000..aa6a792 --- /dev/null +++ b/tests/thermo/test_thermo_array.py @@ -0,0 +1,743 @@ +# (C) Copyright 2021 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. +# + +import os + +import numpy as np + +from earthkit.meteo import thermo + +np.set_printoptions(formatter={"float_kind": "{:.10f}".format}) + + +def data_file(name): + return os.path.join(os.path.dirname(os.path.dirname(__file__)), "data", name) + + +def save_test_reference(file_name, data): + """Helper function to save test reference data into csv""" + np.savetxt( + data_file(file_name), + np.column_stack(tuple(data.values())), + delimiter=",", + header=",".join(list(data.keys())), + ) + + +class ThermoInputData: + """Helper class to load thermo input data.""" + + def __init__(self, file_name="t_hum_p_data.csv"): + self.file_name = file_name + + d = np.genfromtxt( + data_file(self.file_name), + delimiter=",", + names=True, + ) + self.t = d["t"] + self.td = d["td"] + self.r = d["r"] + self.q = d["q"] + self.p = d["p"] + + +def test_celsius_to_kelvin(): + t = np.array([-10, 23.6]) + v = thermo.array.celsius_to_kelvin(t) + v_ref = np.array([263.16, 296.76]) + np.testing.assert_allclose(v, v_ref) + + +def test_kelvin_to_celsius(): + t = np.array([263.16, 296.76]) + v = thermo.array.kelvin_to_celsius(t) + v_ref = np.array([-10, 23.6]) + np.testing.assert_allclose(v, v_ref) + + +def test_mixing_ratio_from_specific_humidity(): + q = np.array([0.008, 0.018]) + mr = thermo.array.mixing_ratio_from_specific_humidity(q) + v_ref = np.array([0.0080645161, 0.0183299389]) + np.testing.assert_allclose(mr, v_ref, rtol=1e-7) + + +def test_specific_humidity_from_mixing_ratio(): + mr = np.array([0.0080645161, 0.0183299389]) + q = thermo.array.specific_humidity_from_mixing_ratio(mr) + v_ref = np.array([0.008, 0.018]) + np.testing.assert_allclose(q, v_ref, rtol=1e-07) + + +def test_vapour_pressure_from_specific_humidity(): + q = np.array([0.008, 0.018]) + p = np.array([700, 1000]) * 100 + v_ref = np.array([895.992614, 2862.662152]) + vp = thermo.array.vapour_pressure_from_specific_humidity(q, p) + np.testing.assert_allclose(vp, v_ref) + + +def test_vapour_pressure_from_mixing_ratio(): + mr = np.array([0.0080645161, 0.0183299389]) + p = np.array([700, 1000]) * 100 + v_ref = np.array([895.992614, 2862.662152]) + vp = thermo.array.vapour_pressure_from_mixing_ratio(mr, p) + np.testing.assert_allclose(vp, v_ref) + + +def test_specific_humidity_from_vapour_pressure(): + vp = np.array([895.992614, 2862.662152, 10000]) + p = np.array([700, 1000, 50]) * 100 + v_ref = np.array([0.008, 0.018, np.nan]) + q = thermo.array.specific_humidity_from_vapour_pressure(vp, p) + np.testing.assert_allclose(q, v_ref) + + # single pressure value + vp = np.array([895.992614, 2862.662152, 100000]) + p = 700 * 100.0 + v_ref = np.array([0.008, 0.0258354146, np.nan]) + q = thermo.array.specific_humidity_from_vapour_pressure(vp, p) + np.testing.assert_allclose(q, v_ref) + + # numbers + vp = 895.992614 + p = 700 * 100.0 + v_ref = 0.008 + q = thermo.array.specific_humidity_from_vapour_pressure(vp, p) + np.testing.assert_allclose(q, v_ref) + + vp = 100000 + p = 700 * 100.0 + v_ref = np.nan + q = thermo.array.specific_humidity_from_vapour_pressure(vp, p) + np.testing.assert_allclose(q, v_ref) + + +def test_mixing_ratio_from_vapour_pressure(): + vp = np.array([895.992614, 2862.662152, 100000]) + p = np.array([700, 1000, 50]) * 100 + v_ref = np.array([0.0080645161, 0.0183299389, np.nan]) + mr = thermo.array.mixing_ratio_from_vapour_pressure(vp, p) + np.testing.assert_allclose(mr, v_ref, rtol=1e-07) + + # numbers + vp = 895.992614 + p = 700 * 100.0 + v_ref = 0.0080645161 + q = thermo.array.mixing_ratio_from_vapour_pressure(vp, p) + np.testing.assert_allclose(q, v_ref) + + vp = 100000.0 + p = 50 * 100.0 + v_ref = np.nan + q = thermo.array.mixing_ratio_from_vapour_pressure(vp, p) + np.testing.assert_allclose(q, v_ref) + + +def test_saturation_vapour_pressure(): + ref_file = "sat_vp.csv" + phases = ["mixed", "water", "ice"] + + # o = {"t": thermo.array.celsius_to_kelvin(np.linspace(-40.0, 56.0, 49))} + # for phase in ["mixed", "water", "ice"]: + # o[phase] = thermo.array.saturation_vapour_pressure(o["t"], phase=phase) + # save_test_reference(ref_file, o) + + d = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for phase in phases: + svp = thermo.array.saturation_vapour_pressure(d["t"], phase=phase) + np.testing.assert_allclose(svp, d[phase]) + + # scalar value + t = 267.16 + v_ref = { + "mixed": 3.807622914202970037e02, + "water": 3.909282234208898785e02, + "ice": 3.685208149695831139e02, + } + for phase, v in v_ref.items(): + svp = thermo.array.saturation_vapour_pressure(t, phase=phase) + np.testing.assert_allclose(svp, v) + + +def test_saturation_mixing_ratio(): + ref_file = "sat_mr.csv" + phases = ["mixed", "water", "ice"] + + # t = thermo.array.celsius_to_kelvin(np.linspace(-40.0, 56.0, 25)) + # p = [1000, 950, 850, 700] + # t_num = len(t) + # t = np.repeat(t, repeats=len(p)) + # p = np.array(p * t_num) * 100.0 + # o = {"t": t, "p": p} + # for phase in ["mixed", "water", "ice"]: + # o[phase] = thermo.array.saturation_mixing_ratio(t, p, phase=phase) + # save_test_reference(ref_file, o) + + d = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for phase in phases: + mr = thermo.array.saturation_mixing_ratio(d["t"], d["p"], phase=phase) + np.testing.assert_allclose(mr, d[phase]) + + +def test_saturation_specific_humidity(): + ref_file = "sat_q.csv" + phases = ["mixed", "water", "ice"] + + # t = thermo.array.celsius_to_kelvin(np.linspace(-40.0, 56.0, 25)) + # p = [1000, 950, 850, 700] + # t_num = len(t) + # t = np.repeat(t, repeats=len(p)) + # p = np.array(p * t_num) * 100.0 + # o = {"t": t, "p": p} + # for phase in ["mixed", "water", "ice"]: + # o[phase] = thermo.array.saturation_specific_humidity(t, p, phase=phase) + # save_test_reference(ref_file, o) + + d = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for phase in phases: + mr = thermo.array.saturation_specific_humidity(d["t"], d["p"], phase=phase) + np.testing.assert_allclose(mr, d[phase]) + + +def test_saturation_vapour_pressure_slope(): + ref_file = "sat_vp_slope.csv" + phases = ["mixed", "water", "ice"] + + # o = {"t": thermo.array.celsius_to_kelvin(np.linspace(-40.0, 56.0, 49))} + # for phase in ["mixed", "water", "ice"]: + # o[phase] = thermo.array.saturation_vapour_pressure_slope(o["t"], phase=phase) + # save_test_reference(ref_file, o) + + d = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for phase in phases: + svp = thermo.array.saturation_vapour_pressure_slope(d["t"], phase=phase) + np.testing.assert_allclose(svp, d[phase]) + + +def test_saturation_mixing_ratio_slope(): + ref_file = "sat_mr_slope.csv" + phases = ["mixed", "water", "ice"] + + # t = thermo.array.celsius_to_kelvin(np.linspace(-40.0, 56.0, 25)) + # p = [1000, 950, 850, 700] + # t_num = len(t) + # t = np.repeat(t, repeats=len(p)) + # p = np.array(p * t_num) * 100.0 + # o = {"t": t, "p": p} + # for phase in ["mixed", "water", "ice"]: + # o[phase] = thermo.array.saturation_mixing_ratio_slope(t, p, phase=phase) + # save_test_reference(ref_file, o) + + d = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for phase in phases: + svp = thermo.array.saturation_mixing_ratio_slope(d["t"], d["p"], phase=phase) + np.testing.assert_allclose(svp, d[phase]) + + v_ref = np.array([np.nan]) + t = thermo.array.celsius_to_kelvin(np.array([200])) + p = np.array([1000]) + svp = thermo.array.saturation_mixing_ratio_slope(t, p, phase="mixed") + np.testing.assert_allclose(svp, v_ref) + + # numbers + t = [283.0, 600.0] + p = [1e5, 1e5] + v_ref = [0.0005189819, np.nan] + for i in range(len(t)): + svp = thermo.array.saturation_mixing_ratio_slope(t[i], p[i], phase="mixed") + np.testing.assert_allclose(svp, v_ref[i]) + + +def test_saturation_specific_humidity_slope(): + ref_file = "sat_q_slope.csv" + phases = ["mixed", "water", "ice"] + + # t = thermo.array.celsius_to_kelvin(np.linspace(-40.0, 56.0, 25)) + # p = [1000, 950, 850, 700] + # t_num = len(t) + # t = np.repeat(t, repeats=len(p)) + # p = np.array(p * t_num) * 100.0 + # o = {"t": t, "p": p} + # for phase in ["mixed", "water", "ice"]: + # o[phase] = thermo.array.saturation_specific_humidity_slope(t, p, phase=phase) + # save_test_reference(ref_file, o) + + d = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for phase in phases: + svp = thermo.array.saturation_specific_humidity_slope( + d["t"], d["p"], phase=phase + ) + np.testing.assert_allclose(svp, d[phase]) + + v_ref = np.array([np.nan]) + t = thermo.array.celsius_to_kelvin(np.array([200])) + p = np.array([1000]) + svp = thermo.array.saturation_specific_humidity_slope(t, p, phase="mixed") + np.testing.assert_allclose(svp, v_ref) + + # numbers + t = [283.0, 600.0] + p = [1e5, 1e5] + v_ref = [0.0005111349, np.nan] + for i in range(len(t)): + svp = thermo.array.saturation_specific_humidity_slope(t[i], p[i], phase="mixed") + np.testing.assert_allclose(svp, v_ref[i]) + + +def test_temperature_from_saturation_vapour_pressure(): + ref_file = "sat_vp.csv" + d = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + t = thermo.array.temperature_from_saturation_vapour_pressure(d["water"]) + np.testing.assert_allclose(t, d["t"]) + + +def test_relative_humidity_from_dewpoint(): + t = thermo.array.celsius_to_kelvin(np.array([20.0, 20, 0, 35, 5, -15, 25])) + td = thermo.array.celsius_to_kelvin(np.array([20.0, 10, -10, 32, -15, -24, -3])) + # reference was tested with an online relhum calculator at: + # https://bmcnoldy.rsmas.miami.edu/Humidity.html + v_ref = np.array( + [ + 100.0000000000, + 52.5224541378, + 46.8714823296, + 84.5391163313, + 21.9244774232, + 46.1081101229, + 15.4779832381, + ] + ) + r = thermo.array.relative_humidity_from_dewpoint(t, td) + np.testing.assert_allclose(r, v_ref, rtol=1e-05) + + +def test_relative_humidity_from_specific_humidity(): + t = thermo.array.celsius_to_kelvin( + np.array([-29.2884, -14.4118, -5.9235, 9.72339, 18.4514]) + ) + p = np.array([300, 400, 500, 700, 850]) * 100.0 + q = np.array( + [ + 0.000845416891024797, + 0.00277950354211498, + 0.00464489207661245, + 0.0076785187585422, + 0.0114808182580539, + ] + ) + v_ref = np.array( + [ + 99.70488530734642, + 100.25885732613531, + 97.15956159465799, + 71.37937968160273, + 73.41420898756694, + ] + ) + r = thermo.array.relative_humidity_from_specific_humidity(t, q, p) + np.testing.assert_allclose(r, v_ref) + + +def test_specific_humidity_from_dewpoint(): + td = thermo.array.celsius_to_kelvin( + np.array([21.78907, 19.90885, 16.50236, 7.104064, -0.3548709, -16.37916]) + ) + p = np.array([967.5085, 936.3775, 872.248, 756.1647, 649.157, 422.4207]) * 100 + v_ref = np.array( + [ + 0.0169461501, + 0.0155840075, + 0.0134912382, + 0.0083409720, + 0.0057268584, + 0.0025150791, + ] + ) + q = thermo.array.specific_humidity_from_dewpoint(td, p) + np.testing.assert_allclose(q, v_ref, rtol=1e-05) + + +def test_specific_humidity_from_relative_humidity(): + t = thermo.array.celsius_to_kelvin( + np.array([-29.2884, -14.4118, -5.9235, 9.72339, 18.4514]) + ) + p = np.array([300, 400, 500, 700, 850]) * 100.0 + r = np.array( + [ + 99.70488530734642, + 100.25885732613531, + 97.15956159465799, + 71.37937968160273, + 73.41420898756694, + ] + ) + v_ref = np.array( + [ + 0.000845416891024797, + 0.00277950354211498, + 0.00464489207661245, + 0.0076785187585422, + 0.0114808182580539, + ] + ) + q = thermo.array.specific_humidity_from_relative_humidity(t, r, p) + np.testing.assert_allclose(q, v_ref) + + +def test_dewpoint_from_relative_humidity(): + t = thermo.array.celsius_to_kelvin(np.array([20.0, 20, 0, 35, 5, -15, 25])) + r = np.array( + [ + 100.0000000000, + 52.5224541378, + 46.8714823296, + 84.5391163313, + 21.9244774232, + 46.1081101229, + 15.4779832381, + ] + ) + v_ref = thermo.array.celsius_to_kelvin(np.array([20.0, 10, -10, 32, -15, -24, -3])) + # reference was tested with an online relhum calculator at: + # https://bmcnoldy.rsmas.miami.edu/Humidity.html + td = thermo.array.dewpoint_from_relative_humidity(t, r) + np.testing.assert_allclose(td, v_ref) + + +def test_dewpoint_from_specific_humidity(): + p = np.array([967.5085, 936.3775, 872.248, 756.1647, 649.157, 422.4207]) * 100 + q = np.array( + [ + 0.0169461501, + 0.0155840075, + 0.0134912382, + 0.0083409720, + 0.0057268584, + 0.0025150791, + ] + ) + v_ref = thermo.array.celsius_to_kelvin( + np.array([21.78907, 19.90885, 16.50236, 7.104064, -0.3548709, -16.37916]) + ) + td = thermo.array.dewpoint_from_specific_humidity(q, p) + np.testing.assert_allclose(td, v_ref) + + +def test_virtual_temperature(): + t = np.array([286.4, 293.4]) + # w = np.array([0.02, 0.03]) + q = np.array([0.0196078431, 0.0291262136]) + v_ref = np.array([289.8130240470, 298.5937453245]) + tv = thermo.array.virtual_temperature(t, q) + np.testing.assert_allclose(tv, v_ref) + + +def test_virtual_potential_temperature_temperature(): + t = np.array([286.4, 293.4]) + # w = np.array([0.02, 0.03]) + q = np.array([0.0196078431, 0.0291262136]) + p = np.array([100300.0, 95000.0]) + v_ref = np.array([289.5651110613, 303.0015650834]) + tv = thermo.array.virtual_potential_temperature(t, q, p) + np.testing.assert_allclose(tv, v_ref) + + +def test_potential_temperature(): + t = np.array([252.16, 298.16]) + p = np.array([72350, 100500]) + v_ref = np.array([276.588026, 297.735455]) + th = thermo.array.potential_temperature(t, p) + np.testing.assert_allclose(th, v_ref) + + +def test_temperature_from_potential_temperature(): + p = np.array([72350, 100500]) + th = np.array([276.588026, 297.735455]) + v_ref = np.array([252.16, 298.16]) + t = thermo.array.temperature_from_potential_temperature(th, p) + np.testing.assert_allclose(t, v_ref) + + +def test_temperature_on_dry_adibat(): + t_def = np.array([252.16, 298.16]) + p_def = np.array([72350, 100500]) + p = np.array([700, 500]) * 100 + v_ref = np.array([249.792414, 244.246863]) + t = thermo.array.temperature_on_dry_adiabat(p, t_def, p_def) + np.testing.assert_allclose(t, v_ref) + + # cross checking + th1 = thermo.array.potential_temperature(t_def, p_def) + th2 = thermo.array.potential_temperature(t, p) + np.testing.assert_allclose(th1, th2) + + # multiple values along a single adiabat + v_ref = np.array([249.792414, 226.898581]) + t = thermo.array.temperature_on_dry_adiabat(p, t_def[0], p_def[0]) + np.testing.assert_allclose(t, v_ref) + + +def test_pressure_on_dry_adibat(): + t_def = np.array([252.16, 298.16]) + p_def = np.array([72350, 100500]) + t = np.array([249.792414, 244.246863]) + v_ref = np.array([700, 500]) * 100 + p = thermo.array.pressure_on_dry_adiabat(t, t_def, p_def) + np.testing.assert_allclose(p, v_ref) + + # cross checking + th1 = thermo.array.potential_temperature(t_def, p_def) + th2 = thermo.array.potential_temperature(t, p) + np.testing.assert_allclose(th1, th2) + + # multiple values along a single adiabat + v_ref = np.array([70000, 64709.699161]) + p = thermo.array.pressure_on_dry_adiabat(t, t_def[0], p_def[0]) + np.testing.assert_allclose(p, v_ref) + + +def test_lcl(): + t = np.array([10, 30, 43, 20]) + 273.16 + td = np.array([-2, 26, 5, 28]) + 273.16 + p = np.array([95000, 100500, 100100, 100200]) + + # davies + t_ref = np.array([268.706024, 298.200936, 270.517934, 303.138144]) + p_ref = np.array([79081.766347, 94862.350635, 57999.83367, 112654.210439]) + t_lcl = thermo.array.lcl_temperature(t, td, method="davies") + np.testing.assert_allclose(t_lcl, t_ref) + t_lcl, p_lcl = thermo.array.lcl(t, td, p, method="davies") + np.testing.assert_allclose(t_lcl, t_ref) + np.testing.assert_allclose(p_lcl, p_ref) + + # bolton + t_ref = np.array([268.683018, 298.182282, 270.531264, 303.199544]) + p_ref = np.array([79058.068785, 94841.581142, 58009.838027, 112734.100243]) + t_lcl = thermo.array.lcl_temperature(t, td, method="bolton") + np.testing.assert_allclose(t_lcl, t_ref) + t_lcl, p_lcl = thermo.array.lcl(t, td, p, method="bolton") + np.testing.assert_allclose(t_lcl, t_ref) + np.testing.assert_allclose(p_lcl, p_ref) + + +def test_ept(): + data = ThermoInputData() + + ref_file = "eqpt.csv" + methods = ["ifs", "bolton35", "bolton39"] + + # o = {} + # for m in methods: + # o[f"{m}_td"] = thermo.array.ept_from_dewpoint(data.t, data.td, data.p, method=m) + # o[f"{m}_q"] = thermo.array.ept_from_specific_humidity( + # data.t, data.q, data.p, method=m + # ) + # save_test_reference(ref_file, o) + + ref = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for m in methods: + pt = thermo.array.ept_from_dewpoint(data.t, data.td, data.p, method=m) + np.testing.assert_allclose(pt, ref[m + "_td"], err_msg=f"method={m}") + pt = thermo.array.ept_from_specific_humidity(data.t, data.q, data.p, method=m) + np.testing.assert_allclose(pt, ref[m + "_q"], err_msg=f"method={m}") + + +def test_saturation_ept(): + data = ThermoInputData() + + ref_file = "seqpt.csv" + methods = ["ifs", "bolton35", "bolton39"] + + # o = {} + # for m in methods: + # o[m] = thermo.array.saturation_ept(data.t, data.p, method=m) + # save_test_reference(ref_file, o) + + ref = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for m in methods: + pt = thermo.array.saturation_ept(data.t, data.p, method=m) + np.testing.assert_allclose(pt, ref[m], err_msg=f"method={m}") + + +def test_temperature_on_moist_adiabat(): + ref_file = "t_on_most_adiabat.csv" + ept_methods = ["ifs", "bolton35", "bolton39"] + t_methods = ["bisect", "newton"] + + # ept = np.array([220, 250, 273.16, 300, 330, 360, 400, 500, 600, 700, 800, 900]) + # p = np.array([1010, 1000, 925, 850, 700, 500, 300]) * 100 + # o = {"ept": np.repeat(ept, repeats=len(p)), "p": np.array(p.tolist() * len(ept))} + # for m_ept in ept_methods: + # for m_t in t_methods: + # o[f"{m_ept}_{m_t}"] = thermo.array.temperature_on_moist_adiabat( + # o["ept"], o["p"], ept_method=m_ept, t_method=m_t + # ) + # save_test_reference(ref_file, o) + + ref = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for m_ept in ept_methods: + for m_t in t_methods: + pt = thermo.array.temperature_on_moist_adiabat( + ref["ept"], ref["p"], ept_method=m_ept, t_method=m_t + ) + np.testing.assert_allclose( + pt, ref[f"{m_ept}_{m_t}"], err_msg=f"method={m_ept}_{m_t}" + ) + + +def test_wet_bulb_temperature(): + data = ThermoInputData() + + ref_file = "t_wet.csv" + ept_methods = ["ifs", "bolton35", "bolton39"] + t_methods = ["bisect", "newton"] + + # o = {} + # for m_ept in ept_methods: + # for m_t in t_methods: + # o[f"{m_ept}_{m_t}_td"] = thermo.array.wet_bulb_temperature_from_dewpoint( + # data.t, data.td, data.p, ept_method=m_ept, t_method=m_t + # ) + # o[f"{m_ept}_{m_t}_q"] = thermo.array.wet_bulb_temperature_from_specific_humidity( + # data.t, data.q, data.p, ept_method=m_ept, t_method=m_t + # ) + # save_test_reference(ref_file, o) + + ref = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for m_ept in ept_methods: + for m_t in t_methods: + pt = thermo.array.wet_bulb_temperature_from_dewpoint( + data.t, data.td, data.p, ept_method=m_ept, t_method=m_t + ) + np.testing.assert_allclose( + pt, + ref[f"{m_ept}_{m_t}_td"], + rtol=1e-03, + atol=0, + err_msg=f"method={m_ept}_{m_t}_td", + ) + pt = thermo.array.wet_bulb_temperature_from_specific_humidity( + data.t, data.q, data.p, ept_method=m_ept, t_method=m_t + ) + np.testing.assert_allclose( + pt, + ref[f"{m_ept}_{m_t}_q"], + rtol=1e-03, + atol=0, + err_msg=f"method={m_ept}_{m_t}_q", + ) + + +def test_wet_bulb_potential_temperature(): + data = ThermoInputData() + + ref_file = "t_wetpt.csv" + ept_methods = ["ifs", "bolton35", "bolton39"] + t_methods = ["bisect", "newton", "direct"] + + # o = {} + # for m_ept in ept_methods: + # for m_t in t_methods: + # o[ + # f"{m_ept}_{m_t}_td" + # ] = thermo.array.wet_bulb_potential_temperature_from_dewpoint( + # data.t, data.td, data.p, ept_method=m_ept, t_method=m_t + # ) + # o[ + # f"{m_ept}_{m_t}_q" + # ] = thermo.array.wet_bulb_potential_temperature_from_specific_humidity( + # data.t, data.q, data.p, ept_method=m_ept, t_method=m_t + # ) + # save_test_reference(ref_file, o) + + ref = np.genfromtxt( + data_file(ref_file), + delimiter=",", + names=True, + ) + + for m_ept in ept_methods: + for m_t in t_methods: + pt = thermo.array.wet_bulb_potential_temperature_from_dewpoint( + data.t, data.td, data.p, ept_method=m_ept, t_method=m_t + ) + np.testing.assert_allclose( + pt, + ref[f"{m_ept}_{m_t}_td"], + rtol=1e-03, + atol=0, + err_msg=f"method={m_ept}_{m_t}_td", + ) + pt = thermo.array.wet_bulb_potential_temperature_from_specific_humidity( + data.t, data.q, data.p, ept_method=m_ept, t_method=m_t + ) + np.testing.assert_allclose( + pt, + ref[f"{m_ept}_{m_t}_q"], + rtol=1e-03, + atol=0, + err_msg=f"method={m_ept}_{m_t}_q", + ) diff --git a/tests/wind/test_wind.py b/tests/wind/test_wind.py new file mode 100644 index 0000000..09f1b1d --- /dev/null +++ b/tests/wind/test_wind.py @@ -0,0 +1,285 @@ +# (C) Copyright 2021 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. +# + +import numpy as np + +from earthkit.meteo import wind + +np.set_printoptions(formatter={"float_kind": "{:.10f}".format}) + + +def test_speed(): + u = np.array([0, 1, 1, 1, 0, -1, -1, -1, 0, np.nan, 1, np.nan]) + v = np.array([1, 1, 0, -1, -1, -1, 0, 1, 0, 1, np.nan, np.nan]) + v_ref = np.array( + [ + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 0.0, + np.nan, + np.nan, + np.nan, + ] + ) + + sp = wind.speed(u, v) + np.testing.assert_allclose(sp, v_ref) + + +def test_direction(): + # meteo + u = np.array([0, 1, 1, 1, 0, -1, -1, -1, 0, np.nan, 1, np.nan]) + v = np.array([1, 1, 0, -1, -1, -1, 0, 1, 0, 1, np.nan, np.nan]) + v_ref = np.array( + [180.0, 225, 270, 315, 0, 45, 90, 135, 270, np.nan, np.nan, np.nan] + ) + d = wind.direction(u, v, convention="meteo") + np.testing.assert_allclose(d, v_ref) + + v_ref = np.array( + [ + 90, + 45, + 0, + 315, + 270, + 225, + 180, + 135.0, + 0, + np.nan, + np.nan, + np.nan, + ] + ) + + # polar + d = wind.direction(u, v, convention="polar") + np.testing.assert_allclose(d, v_ref) + + v_ref = np.array( + [ + 90, + 45, + 0, + -45, + -90, + -135, + 180, + 135, + 0, + np.nan, + np.nan, + np.nan, + ] + ) + + d = wind.direction(u, v, convention="polar", to_positive=False) + np.testing.assert_allclose(d, v_ref) + + # numbers + u = [1.0, 1] + v = [1.0, np.nan] + v_ref = [225, np.nan] + for i in range(len(u)): + d = wind.direction(u[i], v[i], convention="meteo") + np.testing.assert_allclose(d, v_ref[i]) + + v_ref = [45, np.nan] + for i in range(len(u)): + d = wind.direction(u[i], v[i], convention="polar") + np.testing.assert_allclose(d, v_ref[i]) + + +def test_xy_to_polar(): + u = np.array([0, 1, 1, 1, 0, -1, -1, -1, 0, np.nan, 1, np.nan]) + v = np.array([1, 1, 0, -1, -1, -1, 0, 1, 0, 1, np.nan, np.nan]) + sp_ref = np.array( + [ + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 0.0, + np.nan, + np.nan, + np.nan, + ] + ) + d_ref = np.array( + [180.0, 225, 270, 315, 0, 45, 90, 135, 270, np.nan, np.nan, np.nan] + ) + sp, d = wind.xy_to_polar(u, v) + np.testing.assert_allclose(sp, sp_ref) + np.testing.assert_allclose(d, d_ref) + + +def test_polar_to_xy(): + sp = np.array( + [ + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 1.0, + 1.4142135624, + 0.0, + np.nan, + 1, + np.nan, + ] + ) + d = np.array([180.0, 225, 270, 315, 0, 45, 90, 135, 270, 1, np.nan, np.nan]) + u_ref = np.array([0, 1, 1, 1, 0, -1, -1, -1, 0, np.nan, np.nan, np.nan]) + v_ref = np.array([1, 1, 0, -1, -1, -1, 0, 1, 0, np.nan, np.nan, np.nan]) + u, v = wind.polar_to_xy(sp, d) + np.testing.assert_allclose(u, u_ref, atol=1e-7) + np.testing.assert_allclose(v, v_ref, atol=1e-7) + + +def test_w_from_omega(): + omega = np.array([1.2, 21.3]) + t = np.array([285.6, 261.1]) + p = np.array([1000, 850]) * 100 + v_ref = np.array([-0.1003208031, -1.9152219066]) + w = wind.w_from_omega(omega, t, p) + np.testing.assert_allclose(w, v_ref) + + +def test_coriolis(): + lat = np.array([-20, 0, 50]) + c = wind.coriolis(lat) + v_ref = np.array([-0.0000498810, 0.0, 0.0001117217]) + np.testing.assert_allclose(c, v_ref, rtol=1e-04) + + +def test_windrose(): + sp = np.array( + [3.5, 1, 1.1, 2.1, 0.1, 0.0, 2.4, 1.9, 1.7, 3.9, 3.1, 2.1, np.nan, np.nan] + ) + d = np.array( + [1.0, 29, 31, 93.0, 121, 171, 189, 245, 240.11, 311, 359.1, np.nan, 11, np.nan] + ) + sp_bins = [0, 1, 2, 3, 4] + + # count + v_ref = np.array( + [ + [ + 0.0000000000, + 0.0000000000, + 1.0000000000, + 1.0000000000, + 0.0000000000, + 0.0000000000, + ], + [ + 1.0000000000, + 1.0000000000, + 0.0000000000, + 0.0000000000, + 2.0000000000, + 0.0000000000, + ], + [ + 0.0000000000, + 0.0000000000, + 1.0000000000, + 1.0000000000, + 0.0000000000, + 0.0000000000, + ], + [ + 2.0000000000, + 0.0000000000, + 0.0000000000, + 0.0000000000, + 0.0000000000, + 1.0000000000, + ], + ] + ) + dir_bin_ref = np.array( + [ + -30.0000000000, + 30.0000000000, + 90.0000000000, + 150.0000000000, + 210.0000000000, + 270.0000000000, + 330.0000000000, + ] + ) + + r = wind.windrose(sp, d, sectors=6, speed_bins=sp_bins, percent=False) + np.testing.assert_allclose(r[0], v_ref, rtol=1e-04) + np.testing.assert_allclose(r[1], dir_bin_ref, rtol=1e-04) + + # percent + v_ref = v_ref * 100 / 11.0 + r = wind.windrose(sp, d, sectors=6, speed_bins=sp_bins, percent=True) + np.testing.assert_allclose(r[0], v_ref, rtol=1e-04) + np.testing.assert_allclose(r[1], dir_bin_ref, rtol=1e-04) + + # numbers + sp = 3.4 + d = 90.01 + sp_bins = [0, 5] + v_ref = np.array([[0, 0, 1, 0, 0, 0]]) + + r = wind.windrose(sp, d, sectors=6, speed_bins=sp_bins, percent=False) + np.testing.assert_allclose(r[0], v_ref, rtol=1e-04) + np.testing.assert_allclose(r[1], dir_bin_ref, rtol=1e-04) + + # single sector + sp = 3.4 + d = 90.01 + sp_bins = [0, 5] + v_ref = np.array([[1]]) + dir_bin_ref = np.array([-180.0000000000, 180.0000000000]) + + r = wind.windrose(sp, d, sectors=1, speed_bins=sp_bins, percent=False) + np.testing.assert_allclose(r[0], v_ref, rtol=1e-04) + np.testing.assert_allclose(r[1], dir_bin_ref, rtol=1e-04) + + # invalid arguments + sp = 3.4 + d = 90.01 + + sp_bins = [0, 1] + try: + r = wind.windrose(sp, d, sectors=0, speed_bins=sp_bins, percent=False) + assert False + except ValueError: + pass + + sp_bins = [0] + try: + r = wind.windrose(sp, d, sectors=6, speed_bins=sp_bins, percent=False) + assert False + except ValueError: + pass + + try: + r = wind.windrose(sp, d, sectors=6, percent=False) + assert False + except ValueError: + pass