From f7bff14a950f7598143be681f5d96b49c643fa7f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Fri, 6 Sep 2024 15:52:57 +0200 Subject: [PATCH 01/22] Initial conversion to ssb-pypitemplate --- .cookiecutter.json | 22 + .cruft.json | 30 +- .darglint | 2 + .editorconfig | 15 + .github/dependabot.yml | 32 + .github/labels.yml | 66 + .github/release-drafter.yml | 30 + .github/workflows/constraints.txt | 5 + .github/workflows/docs.yml | 67 + .github/workflows/labeler.yml | 25 + .github/workflows/release.yml | 78 + .github/workflows/tests.yml | 173 +- .gitignore | 128 +- .pre-commit-config.yaml | 80 + .prettierignore | 4 + CODE_OF_CONDUCT.md | 132 + CONTRIBUTING.md | 138 + LICENSE | 2 +- README.md | 71 +- SECURITY.md | 13 + SSB-PROJECT-INSTRUKSJONER.md | 48 - docs/Makefile | 20 + docs/codeofconduct.md | 3 + docs/conf.py | 69 + docs/contributing.md | 7 + docs/index.md | 22 + docs/license.md | 7 + docs/make.bat | 35 + docs/reference.md | 26 + docs/templates/package.rst_t | 48 + noxfile.py | 247 ++ poetry.lock | 5609 ++++++++++++++++++----------- poetry.toml | 3 - pyproject.toml | 144 +- sonar-project.properties | 11 + src/model_solver/__main__.py | 13 + src/model_solver/functions.py | 35 + src/model_solver/py.typed | 0 tests/__init__.py | 2 +- tests/test_functions.py | 6 + tests/test_main.py | 18 + 41 files changed, 5155 insertions(+), 2331 deletions(-) create mode 100644 .cookiecutter.json create mode 100644 .darglint create mode 100644 .editorconfig create mode 100644 .github/dependabot.yml create mode 100644 .github/labels.yml create mode 100644 .github/release-drafter.yml create mode 100644 .github/workflows/constraints.txt create mode 100644 .github/workflows/docs.yml create mode 100644 .github/workflows/labeler.yml create mode 100644 .github/workflows/release.yml create mode 100644 .pre-commit-config.yaml create mode 100644 .prettierignore create mode 100644 CODE_OF_CONDUCT.md create mode 100644 CONTRIBUTING.md create mode 100644 SECURITY.md delete mode 100644 SSB-PROJECT-INSTRUKSJONER.md create mode 100644 docs/Makefile create mode 100644 docs/codeofconduct.md create mode 100644 docs/conf.py create mode 100644 docs/contributing.md create mode 100644 docs/index.md create mode 100644 docs/license.md create mode 100644 docs/make.bat create mode 100644 docs/reference.md create mode 100644 docs/templates/package.rst_t create mode 100644 noxfile.py delete mode 100644 poetry.toml create mode 100644 sonar-project.properties create mode 100644 src/model_solver/__main__.py create mode 100644 src/model_solver/functions.py create mode 100644 src/model_solver/py.typed create mode 100644 tests/test_functions.py create mode 100644 tests/test_main.py diff --git a/.cookiecutter.json b/.cookiecutter.json new file mode 100644 index 0000000..fb9ddf1 --- /dev/null +++ b/.cookiecutter.json @@ -0,0 +1,22 @@ +{ + "_copy_without_render": [ + "*.rst_t" + ], + "_jinja2_env_vars": { + "lstrip_blocks": true, + "trim_blocks": true + }, + "_template": "https://github.com/statisticsnorway/ssb-pypitemplate.git", + "author": "Benedikt Goodman", + "code_quality_level": "Medium", + "copyright_owner": "Statistics Norway", + "copyright_year": "2024", + "development_status": "Development Status :: 4 - Beta", + "email": "benedikt.goodman@ssb.no", + "friendly_name": "SSB Model Solver", + "github_organization": "statisticsnorway", + "license": "MIT", + "package_name": "model_solver", + "project_name": "ssb-model-solver", + "version": "1.1.23" +} diff --git a/.cruft.json b/.cruft.json index ecbab94..0cdb1cb 100644 --- a/.cruft.json +++ b/.cruft.json @@ -1,15 +1,29 @@ { - "template": "https://github.com/statisticsnorway/ssb-project-template-stat", - "commit": "cb5e93fbcb298920b3d76770352d823840c49a38", - "checkout": "1.0.0", + "template": "https://github.com/statisticsnorway/ssb-pypitemplate.git", + "commit": "70e4bd378ffc9e87a885d938e3befd89ea26ad5b", + "checkout": "2024.8.8", "context": { "cookiecutter": { - "full_name": "Magnus Helliesen", - "email": "mkh@ssb.no", "project_name": "ssb-model-solver", - "description": "Class to define, block analyse and solve dynamic and algebraic models numerically", - "license_year": "2023", - "_template": "https://github.com/statisticsnorway/ssb-project-template-stat" + "package_name": "model_solver", + "friendly_name": "SSB Model Solver", + "copyright_owner": "Statistics Norway", + "copyright_year": "2024", + "author": "Benedikt Goodman", + "email": "benedikt.goodman@ssb.no", + "github_organization": "statisticsnorway", + "version": "1.1.23", + "license": "MIT", + "development_status": "Development Status :: 4 - Beta", + "code_quality_level": "Medium", + "_copy_without_render": [ + "*.rst_t" + ], + "_jinja2_env_vars": { + "lstrip_blocks": true, + "trim_blocks": true + }, + "_template": "https://github.com/statisticsnorway/ssb-pypitemplate.git" } }, "directory": null diff --git a/.darglint b/.darglint new file mode 100644 index 0000000..72ccc6c --- /dev/null +++ b/.darglint @@ -0,0 +1,2 @@ +[darglint] +strictness = long diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..a8faee7 --- /dev/null +++ b/.editorconfig @@ -0,0 +1,15 @@ +root = true + +[*] +charset = utf-8 +end_of_line = lf +insert_final_newline = true +trim_trailing_whitespace = true + +[*.{py,toml}] +indent_style = space +indent_size = 4 + +[*.yml,yaml,json] +indent_style = space +indent_size = 2 diff --git a/.github/dependabot.yml b/.github/dependabot.yml new file mode 100644 index 0000000..78828b2 --- /dev/null +++ b/.github/dependabot.yml @@ -0,0 +1,32 @@ +version: 2 +updates: + - package-ecosystem: "github-actions" + directory: "/" + schedule: + interval: "monthly" + open-pull-requests-limit: 99 + groups: + github-action-dependencies: + patterns: + - "*" + - package-ecosystem: "pip" + directory: "/.github/workflows" + schedule: + interval: "monthly" + open-pull-requests-limit: 99 + groups: + workflows-dependencies: + patterns: + - "*" + - package-ecosystem: "pip" + directory: "/" + schedule: + interval: "monthly" + versioning-strategy: lockfile-only + allow: + - dependency-type: "all" + open-pull-requests-limit: 99 + groups: + poetry-dependencies: + patterns: + - "*" diff --git a/.github/labels.yml b/.github/labels.yml new file mode 100644 index 0000000..7388c8e --- /dev/null +++ b/.github/labels.yml @@ -0,0 +1,66 @@ +--- +# Labels names are important as they are used by Release Drafter to decide +# regarding where to record them in changelog or if to skip them. +# +# The repository labels will be automatically configured using this file and +# the GitHub Action https://github.com/marketplace/actions/github-labeler. +- name: breaking + description: Breaking Changes + color: bfd4f2 +- name: bug + description: Something isn't working + color: d73a4a +- name: ci + description: Continuous Integration + color: 4a97d6 +- name: dependencies + description: Pull requests that update a dependency file + color: 0366d6 +- name: documentation + description: Improvements or additions to documentation + color: 0075ca +- name: duplicate + description: This issue or pull request already exists + color: cfd3d7 +- name: enhancement + description: New feature or request + color: a2eeef +- name: github_actions + description: Pull requests that update Github_actions code + color: "000000" +- name: good first issue + description: Good for newcomers + color: 7057ff +- name: help wanted + description: Extra attention is needed + color: 008672 +- name: invalid + description: This doesn't seem right + color: e4e669 +- name: performance + description: Performance + color: "016175" +- name: python + description: Pull requests that update Python code + color: 2b67c6 +- name: question + description: Further information is requested + color: d876e3 +- name: refactoring + description: Refactoring + color: ef67c4 +- name: removal + description: Removals and Deprecations + color: 9ae7ea +- name: style + description: Style + color: c120e5 +- name: testing + description: Testing + color: b1fc6f +- name: wontfix + description: This will not be worked on + color: ffffff +- name: "skip-changelog" + description: Changes that should be omitted from the release notes + color: ededed diff --git a/.github/release-drafter.yml b/.github/release-drafter.yml new file mode 100644 index 0000000..2e77836 --- /dev/null +++ b/.github/release-drafter.yml @@ -0,0 +1,30 @@ +categories: + - title: ":boom: Breaking Changes" + label: "breaking" + - title: ":rocket: Features" + label: "enhancement" + - title: ":fire: Removals and Deprecations" + label: "removal" + - title: ":beetle: Fixes" + label: "bug" + - title: ":racehorse: Performance" + label: "performance" + - title: ":rotating_light: Testing" + label: "testing" + - title: ":construction_worker: Continuous Integration" + label: "ci" + - title: ":books: Documentation" + label: "documentation" + - title: ":hammer: Refactoring" + label: "refactoring" + - title: ":lipstick: Style" + label: "style" + - title: ":package: Dependencies" + labels: + - "dependencies" +exclude-labels: + - "skip-changelog" +template: | + ## Changes + + $CHANGES diff --git a/.github/workflows/constraints.txt b/.github/workflows/constraints.txt new file mode 100644 index 0000000..127ea4d --- /dev/null +++ b/.github/workflows/constraints.txt @@ -0,0 +1,5 @@ +pip==24.2 +nox==2024.4.15 +nox-poetry==1.0.3 +poetry==1.8.3 +virtualenv==20.26.3 diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml new file mode 100644 index 0000000..c0b4568 --- /dev/null +++ b/.github/workflows/docs.yml @@ -0,0 +1,67 @@ +name: Documentation + +on: + push: + branches: + - main + - master + + # Allows you to run this workflow manually from the Actions tab + workflow_dispatch: + +# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages +permissions: + contents: read + pages: write + id-token: write + +# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued. +# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete. +concurrency: + group: "pages" + cancel-in-progress: false + +jobs: + build: + runs-on: ubuntu-latest + steps: + - name: Check out the repository + uses: actions/checkout@v4 + + - name: Install Poetry + run: | + pipx install --pip-args "-c ${{ github.workspace }}/.github/workflows/constraints.txt" poetry + poetry --version + + - name: Set up Python + uses: actions/setup-python@v5.1.1 + with: + python-version: "3.12" + cache: "poetry" + + - name: Install dependencies + run: | + poetry install + + - name: Build doc with Sphinx + run: | + poetry run sphinx-build docs docs/_build + + - name: Upload artifact + uses: actions/upload-pages-artifact@v3 + with: + path: "docs/_build" + + deploy: + environment: + name: github-pages + url: ${{ steps.deployment.outputs.page_url }} + runs-on: ubuntu-latest + needs: build + steps: + - name: Setup Pages + uses: actions/configure-pages@v5 + + - name: Deploy to GitHub Pages + id: deployment + uses: actions/deploy-pages@v4 diff --git a/.github/workflows/labeler.yml b/.github/workflows/labeler.yml new file mode 100644 index 0000000..de14cc5 --- /dev/null +++ b/.github/workflows/labeler.yml @@ -0,0 +1,25 @@ +name: Labeler + +on: + push: + branches: + - main + - master + paths: + - ".github/labels.yml" + - ".github/workflows/labeler.yml" + +jobs: + labeler: + runs-on: ubuntu-latest + permissions: + issues: write + contents: read + steps: + - name: Check out the repository + uses: actions/checkout@v4 + + - name: Run Labeler + uses: crazy-max/ghaction-github-labeler@v5.0.0 + with: + skip-delete: true diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml new file mode 100644 index 0000000..26ecdb6 --- /dev/null +++ b/.github/workflows/release.yml @@ -0,0 +1,78 @@ +name: Release + +on: + push: + branches: + - main + - master + +jobs: + release: + name: Release + runs-on: ubuntu-latest + permissions: + id-token: write + contents: write + pull-requests: read + steps: + - name: Check out the repository + uses: actions/checkout@v4 + with: + fetch-depth: 2 + + - name: Set up Python + uses: actions/setup-python@v5.1.1 + with: + python-version: "3.12" + + - name: Upgrade pip + run: | + pip install -c ${{ github.workspace }}/.github/workflows/constraints.txt pip + pip --version + + - name: Install Poetry + run: | + pip install -c ${{ github.workspace }}/.github/workflows/constraints.txt poetry + poetry --version + + - name: Check if there is a parent commit + id: check-parent-commit + run: | + echo "sha=$(git rev-parse --verify --quiet HEAD^)" >> $GITHUB_OUTPUT + + - name: Detect and tag new version + id: check-version + if: steps.check-parent-commit.outputs.sha + uses: salsify/action-detect-and-tag-new-version@v2.0.3 + with: + version-command: | + bash -o pipefail -c "poetry version | cut -f 2 -d' '" + + - name: Bump version for developmental release + if: (!steps.check-version.outputs.tag) + run: | + poetry version patch && + version=$(poetry version | awk '{ print $2 }') && + poetry version $version.dev.$(date +%s) + + - name: Build package + run: | + poetry build --ansi + + - name: Publish package on PyPI + if: steps.check-version.outputs.tag + uses: pypa/gh-action-pypi-publish@v1.9.0 + + - name: Publish package on TestPyPI + if: (!steps.check-version.outputs.tag) + uses: pypa/gh-action-pypi-publish@v1.9.0 + with: + repository-url: https://test.pypi.org/legacy/ + + - name: Publish the release notes + uses: release-drafter/release-drafter@v6.0.0 + with: + publish: ${{ steps.check-version.outputs.tag != '' }} + tag: ${{ steps.check-version.outputs.tag }} + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 73a96d0..ed98407 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -4,34 +4,167 @@ on: push: branches: - main + - master pull_request: - branches: - - main jobs: - test: - runs-on: ubuntu-latest - + tests: + name: ${{ matrix.session }} ${{ matrix.python }} / ${{ matrix.os }} + runs-on: ${{ matrix.os }} strategy: + fail-fast: false matrix: - python-version: ["3.9", "3.10", "3.11", "3.12"] + include: + - { python: "3.10", os: "ubuntu-latest", session: "pre-commit" } + - { python: "3.10", os: "ubuntu-latest", session: "mypy" } + - { python: "3.11", os: "ubuntu-latest", session: "mypy" } + - { python: "3.12", os: "ubuntu-latest", session: "mypy" } + - { python: "3.10", os: "ubuntu-latest", session: "tests" } + - { python: "3.11", os: "ubuntu-latest", session: "tests" } + - { python: "3.12", os: "ubuntu-latest", session: "tests" } + - { python: "3.12", os: "windows-latest", session: "tests" } + - { python: "3.12", os: "macos-latest", session: "tests" } + - { python: "3.10", os: "ubuntu-latest", session: "typeguard" } + - { python: "3.10", os: "ubuntu-latest", session: "xdoctest" } + - { python: "3.10", os: "ubuntu-latest", session: "docs-build" } + + env: + NOXSESSION: ${{ matrix.session }} + FORCE_COLOR: "1" + PRE_COMMIT_COLOR: "always" steps: - - name: Check out the code - uses: actions/checkout@v3 + - name: Check out the repository + uses: actions/checkout@v4 + + - name: Set up Python ${{ matrix.python }} + uses: actions/setup-python@v5.1.0 + with: + python-version: ${{ matrix.python }} + + - name: Upgrade pip + run: | + pip install -c ${{ github.workspace }}/.github/workflows/constraints.txt pip + pip --version + + - name: Upgrade pip in virtual environments + shell: python + run: | + import os + import pip + + with open(os.environ["GITHUB_ENV"], mode="a") as io: + print(f"VIRTUALENV_PIP={pip.__version__}", file=io) + + - name: Install Poetry + run: | + pipx install --pip-args "-c ${{ github.workspace }}/.github/workflows/constraints.txt" poetry + poetry --version + + - name: Install Nox + run: | + pipx install --pip-args "-c ${{ github.workspace }}/.github/workflows/constraints.txt" nox + pipx inject --pip-args "-c ${{ github.workspace }}/.github/workflows/constraints.txt" nox nox-poetry + nox --version + + - name: Compute pre-commit cache key + if: matrix.session == 'pre-commit' + id: pre-commit-cache + shell: python + run: | + import hashlib + import subprocess + import sys + + python = "py{}.{}".format(*sys.version_info[:2]) + payload = sys.version.encode() + sys.executable.encode() + digest = hashlib.sha256(payload).hexdigest() + result = "${{ runner.os }}-{}-{}-pre-commit".format(python, digest[:8]) + cmd = f'echo "result={result}" >> $GITHUB_OUTPUT' + subprocess.run(cmd, shell=True) + + - name: Restore pre-commit cache + uses: actions/cache@v4 + if: matrix.session == 'pre-commit' + with: + path: ~/.cache/pre-commit + key: ${{ steps.pre-commit-cache.outputs.result }}-${{ hashFiles('.pre-commit-config.yaml') }} + restore-keys: | + ${{ steps.pre-commit-cache.outputs.result }}- + + - name: Run Nox + run: | + nox --python=${{ matrix.python }} + + - name: Upload coverage data + if: always() && matrix.session == 'tests' + uses: "actions/upload-artifact@v4" + with: + name: coverage-data-${{ matrix.os }}-${{ matrix.python }} + path: ".coverage.*" + + - name: Upload documentation + if: matrix.session == 'docs-build' + uses: actions/upload-artifact@v4 + with: + name: docs + path: docs/_build + + coverage: + runs-on: ubuntu-latest + needs: tests + steps: + - name: Check out the repository + uses: actions/checkout@v4 + with: + fetch-depth: 0 # Shallow clones should be disabled for a better relevancy of analysis + + - name: Set up Python + uses: actions/setup-python@v5.1.1 + with: + python-version: "3.12" + + - name: Upgrade pip + run: | + pip install -c ${{ github.workspace }}/.github/workflows/constraints.txt pip + pip --version + + - name: Install Poetry + run: | + pipx install --pip-args "-c ${{ github.workspace }}/.github/workflows/constraints.txt" poetry + poetry --version + + - name: Install Nox + run: | + pipx install --pip-args "-c ${{ github.workspace }}/.github/workflows/constraints.txt" nox + pipx inject --pip-args "-c ${{ github.workspace }}/.github/workflows/constraints.txt" nox nox-poetry + nox --version + + - name: Download coverage data + uses: actions/download-artifact@v4 + with: + pattern: coverage-data-* + merge-multiple: true - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 - with: - python-version: ${{ matrix.python-version }} + - name: Combine coverage data and display human readable report + run: | + nox --session=coverage - - name: Install Poetry - run: | - curl -sSL https://install.python-poetry.org | python3 - - echo "$HOME/.local/bin" >> $GITHUB_PATH + - name: Create coverage report + run: | + nox --session=coverage -- xml - - name: Install dependencies - run: poetry install + # Need to fix coverage source paths for SonarCloud scanning in GitHub actions. + # Replace root path with /github/workspace (mounted in docker container). + - name: Override coverage source paths for SonarCloud + run: | + sed -i "s/<\/source>/\/github\/workspace<\/source>/g" coverage.xml + sed -i "s/tests/\/github\/workspace\/tests/g" coverage.xml - - name: Run tests - run: poetry run pytest + - name: SonarCloud Scan + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # Needed to get PR information, if any + SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }} + # No need to run SonarCloud analysis if dependabot update or token not defined + if: env.SONAR_TOKEN != '' && (github.actor != 'dependabot[bot]') + uses: SonarSource/sonarcloud-github-action@v2.3.0 diff --git a/.gitignore b/.gitignore index 1c9870c..e55193a 100644 --- a/.gitignore +++ b/.gitignore @@ -1,24 +1,3 @@ -# This .gitignore file is based on SSB's recommended gitignore template stored -# in: https://github.com/statisticsnorway/kvakk-git-tools -# It contains three sections: SSB specific ignores, GitHub's Python-ignore -# template and GitHub's R-ignore template. - - -# The section below contains SSB specific ignores, not included in the Python- -# and R-ignores from GitHub. - -*.csv -*.db -*.feather -*.parquet -*.sas7bdat -*.xls -*.xlsx -*.zip - -# The section below is from the GitHub .gitignore template for Python: -# https://raw.githubusercontent.com/github/gitignore/main/Python.gitignore - # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] @@ -41,6 +20,7 @@ parts/ sdist/ var/ wheels/ +pip-wheel-metadata/ share/python-wheels/ *.egg-info/ .installed.cfg @@ -70,7 +50,6 @@ coverage.xml *.py,cover .hypothesis/ .pytest_cache/ -cover/ # Translations *.mo @@ -93,7 +72,6 @@ instance/ docs/_build/ # PyBuilder -.pybuilder/ target/ # Jupyter Notebook @@ -104,9 +82,7 @@ profile_default/ ipython_config.py # pyenv -# For a library or package, you might want to ignore these files since the code is -# intended to run in multiple environments; otherwise, check them in: -# .python-version +.python-version # pipenv # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. @@ -115,22 +91,7 @@ ipython_config.py # install all needed dependencies. #Pipfile.lock -# poetry -# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. -# This is especially recommended for binary packages to ensure reproducibility, and is more -# commonly ignored for libraries. -# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control -#poetry.lock - -# pdm -# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. -#pdm.lock -# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it -# in version control. -# https://pdm.fming.dev/#use-with-ide -.pdm.toml - -# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +# PEP 582; used by e.g. github.com/David-OConnor/pyflow __pypackages__/ # Celery stuff @@ -167,70 +128,21 @@ dmypy.json # Pyre type checker .pyre/ -# pytype static type analyzer -.pytype/ - -# Cython debug symbols -cython_debug/ - # PyCharm -# JetBrains specific template is maintained in a separate JetBrains.gitignore that can -# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore -# and can be added to the global gitignore or merged into this file. For a more nuclear -# option (not recommended) you can uncomment the following to ignore the entire idea folder. -#.idea/ - - -# The section below is from the GitHub .gitignore template for R: -# https://raw.githubusercontent.com/github/gitignore/main/R.gitignore - -# History files -.Rhistory -.Rapp.history - -# Session Data files -.RData -.RDataTmp - -# User-specific files -.Ruserdata - -# Example code in package build process -*-Ex.R - -# Output files from R CMD build -/*.tar.gz - -# Output files from R CMD check -/*.Rcheck/ - -# RStudio files -.Rproj.user/ - -# produced vignettes -vignettes/*.html -vignettes/*.pdf - -# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3 -.httr-oauth - -# knitr and R markdown default cache directories -*_cache/ -/cache/ - -# Temporary files created by R markdown -*.utf8.md -*.knit.md - -# R Environment Variables -.Renviron - -# pkgdown site -# SSB: The directory below is commented out because default when generating documentation with Sphinx -#docs/ - -# translation temp files -po/*~ - -# RStudio Connect folder -rsconnect/ +.idea/ + +/.python-version +/.pytype/ +/docs/_build/ + +# Visual Studio Code +.vscode/* +!.vscode/settings.json +!.vscode/tasks.json +!.vscode/launch.json +!.vscode/extensions.json +!.vscode/*.code-snippets +# Local History for Visual Studio Code +.history/ +# Built Visual Studio Code Extensions +*.vsix diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..926462b --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,80 @@ +default_language_version: + python: python3.11 +repos: + - repo: local + hooks: + # General file checkers + - id: check-added-large-files + name: Check added large files + entry: check-added-large-files + language: system + - id: check-merge-conflict + name: Check for merge conflict strings + entry: check-merge-conflict + language: system + - id: check-case-conflict + name: Check for problematic file names + entry: check-case-conflict + language: system + + # General text checkers + - id: end-of-file-fixer + name: Fix End of Files + entry: end-of-file-fixer + language: system + types: [text] + stages: [commit, push, manual] + - id: trailing-whitespace + name: Trim Trailing Whitespace + entry: trailing-whitespace-fixer + language: system + types: [text] + stages: [commit, push, manual] + - id: mixed-line-ending + name: Mixed Line Ending + entry: mixed-line-ending + language: system + types: [text] + stages: [commit, push, manual] + + # Serialization format checkers + - id: check-yaml + name: Check Yaml + entry: check-yaml + language: system + types: [yaml] + - id: check-json + name: Check JSON + entry: check-json + language: system + types: [json] + - id: check-toml + name: Check Toml + entry: check-toml + language: system + types: [toml] + + # Python tools + - id: check-ast + name: Check Python syntax + entry: check-ast + language: system + types: [python] + - id: darglint + name: darglint + entry: darglint + language: system + types: [python] + stages: [manual] + - id: ruff + name: ruff + entry: ruff check --fix --exit-non-zero-on-fix + language: system + types_or: [python, jupyter] + require_serial: true + - id: black + name: black + entry: black + language: system + types_or: [python, jupyter] + require_serial: true diff --git a/.prettierignore b/.prettierignore new file mode 100644 index 0000000..ea9d361 --- /dev/null +++ b/.prettierignore @@ -0,0 +1,4 @@ +# Ignore this files since they are reindented with json.dump() and that does not +# match the prettier format. +.cookiecutter.json +.cruft.json diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md new file mode 100644 index 0000000..827149b --- /dev/null +++ b/CODE_OF_CONDUCT.md @@ -0,0 +1,132 @@ +# Contributor Covenant Code of Conduct + +## Our Pledge + +We as members, contributors, and leaders pledge to make participation in our +community a harassment-free experience for everyone, regardless of age, body +size, visible or invisible disability, ethnicity, sex characteristics, gender +identity and expression, level of experience, education, socio-economic status, +nationality, personal appearance, race, caste, color, religion, or sexual +identity and orientation. + +We pledge to act and interact in ways that contribute to an open, welcoming, +diverse, inclusive, and healthy community. + +## Our Standards + +Examples of behavior that contributes to a positive environment for our +community include: + +- Demonstrating empathy and kindness toward other people +- Being respectful of differing opinions, viewpoints, and experiences +- Giving and gracefully accepting constructive feedback +- Accepting responsibility and apologizing to those affected by our mistakes, + and learning from the experience +- Focusing on what is best not just for us as individuals, but for the overall + community + +Examples of unacceptable behavior include: + +- The use of sexualized language or imagery, and sexual attention or advances of + any kind +- Trolling, insulting or derogatory comments, and personal or political attacks +- Public or private harassment +- Publishing others' private information, such as a physical or email address, + without their explicit permission +- Other conduct which could reasonably be considered inappropriate in a + professional setting + +## Enforcement Responsibilities + +Community leaders are responsible for clarifying and enforcing our standards of +acceptable behavior and will take appropriate and fair corrective action in +response to any behavior that they deem inappropriate, threatening, offensive, +or harmful. + +Community leaders have the right and responsibility to remove, edit, or reject +comments, commits, code, wiki edits, issues, and other contributions that are +not aligned to this Code of Conduct, and will communicate reasons for moderation +decisions when appropriate. + +## Scope + +This Code of Conduct applies within all community spaces, and also applies when +an individual is officially representing the community in public spaces. +Examples of representing our community include using an official e-mail address, +posting via an official social media account, or acting as an appointed +representative at an online or offline event. + +## Enforcement + +Instances of abusive, harassing, or otherwise unacceptable behavior may be +reported to the community leaders responsible for enforcement at +[benedikt.goodman@ssb.no](mailto:benedikt.goodman@ssb.no). +All complaints will be reviewed and investigated promptly and fairly. + +All community leaders are obligated to respect the privacy and security of the +reporter of any incident. + +## Enforcement Guidelines + +Community leaders will follow these Community Impact Guidelines in determining +the consequences for any action they deem in violation of this Code of Conduct: + +### 1. Correction + +**Community Impact**: Use of inappropriate language or other behavior deemed +unprofessional or unwelcome in the community. + +**Consequence**: A private, written warning from community leaders, providing +clarity around the nature of the violation and an explanation of why the +behavior was inappropriate. A public apology may be requested. + +### 2. Warning + +**Community Impact**: A violation through a single incident or series of +actions. + +**Consequence**: A warning with consequences for continued behavior. No +interaction with the people involved, including unsolicited interaction with +those enforcing the Code of Conduct, for a specified period of time. This +includes avoiding interactions in community spaces as well as external channels +like social media. Violating these terms may lead to a temporary or permanent +ban. + +### 3. Temporary Ban + +**Community Impact**: A serious violation of community standards, including +sustained inappropriate behavior. + +**Consequence**: A temporary ban from any sort of interaction or public +communication with the community for a specified period of time. No public or +private interaction with the people involved, including unsolicited interaction +with those enforcing the Code of Conduct, is allowed during this period. +Violating these terms may lead to a permanent ban. + +### 4. Permanent Ban + +**Community Impact**: Demonstrating a pattern of violation of community +standards, including sustained inappropriate behavior, harassment of an +individual, or aggression toward or disparagement of classes of individuals. + +**Consequence**: A permanent ban from any sort of public interaction within the +community. + +## Attribution + +This Code of Conduct is adapted from the [Contributor Covenant][homepage], +version 2.1, available at +[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1]. + +Community Impact Guidelines were inspired by +[Mozilla's code of conduct enforcement ladder][mozilla coc]. + +For answers to common questions about this code of conduct, see the FAQ at +[https://www.contributor-covenant.org/faq][faq]. Translations are available at +[https://www.contributor-covenant.org/translations][translations]. + +[homepage]: https://www.contributor-covenant.org +[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html +[mozilla coc]: https://github.com/mozilla/diversity +[faq]: https://www.contributor-covenant.org/faq +[translations]: https://www.contributor-covenant.org/translations diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md new file mode 100644 index 0000000..074ca6e --- /dev/null +++ b/CONTRIBUTING.md @@ -0,0 +1,138 @@ +# Contributor Guide + +Thank you for your interest in improving this project. +This project is open-source under the [MIT license] and +welcomes contributions in the form of bug reports, feature requests, and pull requests. + +Here is a list of important resources for contributors: + +- [Source Code] +- [Documentation] +- [Issue Tracker] +- [Code of Conduct] + +## How to report a bug + +Report bugs on the [Issue Tracker]. + +When filing an issue, make sure to answer these questions: + +- Which operating system and Python version are you using? +- Which version of this project are you using? +- What did you do? +- What did you expect to see? +- What did you see instead? + +The best way to get your bug fixed is to provide a test case, +and/or steps to reproduce the issue. + +## How to request a feature + +Request features on the [Issue Tracker]. + +## How to set up your development environment + +You need Python 3.10+ and the following tools: + +- [Poetry] +- [Nox] +- [nox-poetry] + +Install [pipx]: + +```console +python -m pip install --user pipx +python -m pipx ensurepath +``` + +Install [Poetry]: + +```console +pipx install poetry +``` + +Install [Nox] and [nox-poetry]: + +```console +pipx install nox +pipx inject nox nox-poetry +``` + +Install the pre-commit hooks + +```console +nox --session=pre-commit -- install +``` + +Install the package with development requirements: + +```console +poetry install +``` + +You can now run an interactive Python session, or your app: + +```console +poetry run python +poetry run ssb-model-solver +``` + +## How to test the project + +Run the full test suite: + +```console +nox +``` + +List the available Nox sessions: + +```console +nox --list-sessions +``` + +You can also run a specific Nox session. +For example, invoke the unit test suite like this: + +```console +nox --session=tests +``` + +Unit tests are located in the _tests_ directory, +and are written using the [pytest] testing framework. + +## How to submit changes + +Open a [pull request] to submit changes to this project. + +Your pull request needs to meet the following guidelines for acceptance: + +- The Nox test suite must pass without errors and warnings. +- Include unit tests. This project maintains 100% code coverage. +- If your changes add functionality, update the documentation accordingly. + +Feel free to submit early, though—we can always iterate on this. + +To run linting and code formatting checks before committing your change, you can install pre-commit as a Git hook by running the following command: + +```console +nox --session=pre-commit -- install +``` + +It is recommended to open an issue before starting work on anything. +This will allow a chance to talk it over with the owners and validate your approach. + +[mit license]: https://opensource.org/licenses/MIT +[source code]: https://github.com/statisticsnorway/ssb-model-solver +[documentation]: https://statisticsnorway.github.io/ssb-model-solver +[issue tracker]: https://github.com/statisticsnorway/ssb-model-solver/issues +[pipx]: https://pipx.pypa.io/ +[poetry]: https://python-poetry.org/ +[nox]: https://nox.thea.codes/ +[nox-poetry]: https://nox-poetry.readthedocs.io/ +[pytest]: https://pytest.readthedocs.io/ +[pull request]: https://github.com/statisticsnorway/ssb-model-solver/pulls + + + +[code of conduct]: CODE_OF_CONDUCT.md diff --git a/LICENSE b/LICENSE index 41c8167..61ab720 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2023 Statistics Norway +Copyright © 2024 Statistics Norway Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/README.md b/README.md index 9b43063..3572bce 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,29 @@ -# ModelSolver +# SSB Model Solver + +[![PyPI](https://img.shields.io/pypi/v/ssb-model-solver.svg)][pypi status] +[![Status](https://img.shields.io/pypi/status/ssb-model-solver.svg)][pypi status] +[![Python Version](https://img.shields.io/pypi/pyversions/ssb-model-solver)][pypi status] +[![License](https://img.shields.io/pypi/l/ssb-model-solver)][license] + +[![Documentation](https://github.com/statisticsnorway/ssb-model-solver/actions/workflows/docs.yml/badge.svg)][documentation] +[![Tests](https://github.com/statisticsnorway/ssb-model-solver/actions/workflows/tests.yml/badge.svg)][tests] +[![Coverage](https://sonarcloud.io/api/project_badges/measure?project=statisticsnorway_ssb-model-solver&metric=coverage)][sonarcov] +[![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=statisticsnorway_ssb-model-solver&metric=alert_status)][sonarquality] + +[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)][pre-commit] +[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)][black] +[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff) +[![Poetry](https://img.shields.io/endpoint?url=https://python-poetry.org/badge/v0.json)][poetry] + +[pypi status]: https://pypi.org/project/ssb-model-solver/ +[documentation]: https://statisticsnorway.github.io/ssb-model-solver +[tests]: https://github.com/statisticsnorway/ssb-model-solver/actions?workflow=Tests + +[sonarcov]: https://sonarcloud.io/summary/overall?id=statisticsnorway_ssb-model-solver +[sonarquality]: https://sonarcloud.io/summary/overall?id=statisticsnorway_ssb-model-solver +[pre-commit]: https://github.com/pre-commit/pre-commit +[black]: https://github.com/psf/black +[poetry]: https://python-poetry.org/ `ModelSolver` is a class that defines, block analyses and solves dynamic and algebraic models numerically. See [documentation](https://github.com/statisticsnorway/model-solver/blob/main/model-solver.pdf) for detailed information about theory and implementation of the class. @@ -6,8 +31,6 @@ See [documentation](https://github.com/statisticsnorway/model-solver/blob/main/m Opprettet av: Magnus Kvåle Helliesen ---- - ## Features ModelSolver is a Python class. It defines, analyses and solves dynamic algebraic model with lots of equations. @@ -60,6 +83,44 @@ When the class is finished initializing, the user can call the following methods * ```model.sensitivity(block_nunber, period_index[, method='std', exog_subset=None])``` analyses the sensitivity of the endogenous variable in the block with respect to the exogenous variabels that determine the solution for the period. ## Installation + +You can install _SSB Model Solver_ via [pip] from [PyPI]: + +```console +pip install ssb-model-solver ``` -poetry add git+https://github.com/statisticsnorway/ssb-model-solver.git -``` + +## Usage + +Please see the [Reference Guide] for details. + +## Contributing + +Contributions are very welcome. +To learn more, see the [Contributor Guide]. + +## License + +Distributed under the terms of the [MIT license][license], +_SSB Model Solver_ is free and open source software. + +## Issues + +If you encounter any problems, +please [file an issue] along with a detailed description. + +## Credits + +This project was generated from [Statistics Norway]'s [SSB PyPI Template]. + +[statistics norway]: https://www.ssb.no/en +[pypi]: https://pypi.org/ +[ssb pypi template]: https://github.com/statisticsnorway/ssb-pypitemplate +[file an issue]: https://github.com/statisticsnorway/ssb-model-solver/issues +[pip]: https://pip.pypa.io/ + + + +[license]: https://github.com/statisticsnorway/ssb-model-solver/blob/main/LICENSE +[contributor guide]: https://github.com/statisticsnorway/ssb-model-solver/blob/main/CONTRIBUTING.md +[reference guide]: https://statisticsnorway.github.io/ssb-model-solver/reference.html diff --git a/SECURITY.md b/SECURITY.md new file mode 100644 index 0000000..a70f558 --- /dev/null +++ b/SECURITY.md @@ -0,0 +1,13 @@ +# Security Policy + +SSB takes the security of our software products and services seriously, which +includes all source code repositories managed through our GitHub organization. + +We believe that responsible disclosure of security vulnerabilities helps us ensure +the security and privacy of all our users. + +## Reporting a Vulnerability + +If you believe you have found a security vulnerability in any of SSB's GitHub +repositories, please report it to us using the +[Github Private vulnerability reporting tool](https://github.com/statisticsnorway/ssb-model-solver/security/advisories). diff --git a/SSB-PROJECT-INSTRUKSJONER.md b/SSB-PROJECT-INSTRUKSJONER.md deleted file mode 100644 index 801ef68..0000000 --- a/SSB-PROJECT-INSTRUKSJONER.md +++ /dev/null @@ -1,48 +0,0 @@ -# Om templaten - -Valgene som er gjort i denne templaten dokumenteres nedover i denne readme-filen. -Etter at du har importert denne templaten inn i ditt prosjekt, står du fritt til å slette hele, eller deler av innholdet i denne filen, og erstatte med eget innhold. - -## Plassering av notebooks og prosjektfunksjoner - -Vi foreslår at funksjoner som skal brukes på tvers av notebooks legges i src/functions.\ -Notebooks kan sorteres i mapper innenfor src/notebooks.\ -I notebookene kan du da importere "de lokale funksjonene" med litt kode som ligger som eksempel øverst i src/notebooks/00_imports.ipynb\ -Funksjoner som skal deles bredere enn innad i ett produksjonsløp, anbefaler vi at pakkes som en pakke og legges på PyPi. Pass på at ikke sikkerhetsdetaljer blir med i slike kodepubliseringer. - -### Notat om importer og \_\_init\_\_.py-filene som ligger i noen mapper - -Filene som heter "\_\_init\_\_.py" bør ligge der de er. Dette gjør at mappen de ligger i er "søkbar" når python leter etter funksjoner å hente inn. -Om du oppretter nye mapper, med kode du skal importere inn i andre filer, bør du nok også der opprette \_\_init\_\_.py-filer. Disse filene kan godt være tomme, om du ikke vil at noe kode skal kjøres under selve importen av funksjoner som ligger i denne mappen. - -#### "Boilerplate"-kode for å finne prosjektmappen med hjelp av pyproject.toml - -En forutsetning for mye av "hurtigstart"-koden er at denne filen (pyproject.toml) ligger kun en gang i prosjektet, og at det er der "grunnmappen" til prosjektet er.\ -Denne lages av pakke-manageren "poetry", men er en av konfigurasjonsfilene python-miljøet beveger seg mot å legge mer og mer av "metadata om kodebasen" i. - -### Instruksjoner for å innstallere nye pakker med Poetry - -I terminalen:\ -`poetry add pakke-navn` - -### Kodetesting med Pytest - -Vi anbefaler Pytest for kode-testing. Derfor ligger det en mappe for "tests" i grunnmappen for prosjektet. -For å kjøre pytest i terminalen, navigerer du først til prosjektmappen med -`cd prosjekt_mappe` -Så kjører du kommandoen -`pytest` -Pytest vil da lete etter test-mappen, finne .py-filer som starter med "test_". Inne i de, se etter funksjoner som har navn som starter med "\_test" og kjøre disse som en del av testsuiten. -Prøv det gjerne med koden du får inn som en del av templaten. Det er tre tester (tre prikker), en for hver av de tre funksjonene fizz, buzz og fizzbuzz. - -### Innhold i .gitignore og .gitattributes - -.gitignore bestemmer hvilke filer som skjules fra git-staging, altså filer git ignorerer, mtp. om de skal "bli med". Om dere bruker noen dataformater dere er nervøse for at kan ende sammen med koden, så kan det være nyttig å detaljere disse her. - -.gitattributes forteller systemet bla. at den skal fjærne output fra under cellene i notebooks før de sendes opp til github. Dette er viktig da det ofte ligger data representert her. Pass gjerne på at disse filene er med ved å kjøre denne kommandoen i terminalen i bunnmappen av prosjektet deres:\ -`ls -a` - -### "MIT" som lisenstype - -SSB har standardisert på [MIT-lisensen](https://github.com/statisticsnorway/adr/blob/main/docs/0006-aapen-kildekode-i-ssb.md) -som sin kildekodelisens. diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..d4bb2cb --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line, and also +# from the environment for the first two. +SPHINXOPTS ?= +SPHINXBUILD ?= sphinx-build +SOURCEDIR = . +BUILDDIR = _build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/codeofconduct.md b/docs/codeofconduct.md new file mode 100644 index 0000000..58fd373 --- /dev/null +++ b/docs/codeofconduct.md @@ -0,0 +1,3 @@ +```{include} ../CODE_OF_CONDUCT.md + +``` diff --git a/docs/conf.py b/docs/conf.py new file mode 100644 index 0000000..5ee4de4 --- /dev/null +++ b/docs/conf.py @@ -0,0 +1,69 @@ +"""Sphinx configuration.""" + +# Configuration file for the Sphinx documentation builder. +# +# This file only contains a selection of the most common options. For a full +# list see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +# -- Path setup -------------------------------------------------------------- + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +import os +import sys + + +sys.path.insert(0, os.path.abspath("../src")) + +# -- Project information ----------------------------------------------------- + +project = "SSB Model Solver" +copyright = "2024, Statistics Norway" +author = "Benedikt Goodman" + +# -- General configuration --------------------------------------------------- + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + "sphinx.ext.autodoc", + "sphinx.ext.napoleon", + "sphinx_autodoc_typehints", + "myst_parser", +] + +# Add any paths that contain templates here, relative to this directory. +templates_path = [] + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = "monokai" + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = "furo" + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +# html_static_path = ["_static"] + + +# -- Other configuration --------------------------------------------------- + +# Show typehints as content of the function or method +autodoc_typehints = "description" + +# Do not prepend module names to object names +add_module_names = False diff --git a/docs/contributing.md b/docs/contributing.md new file mode 100644 index 0000000..b941964 --- /dev/null +++ b/docs/contributing.md @@ -0,0 +1,7 @@ +```{include} ../CONTRIBUTING.md +--- +end-before: +--- +``` + +[code of conduct]: codeofconduct diff --git a/docs/index.md b/docs/index.md new file mode 100644 index 0000000..027e5f5 --- /dev/null +++ b/docs/index.md @@ -0,0 +1,22 @@ +```{include} ../README.md +--- +end-before: +--- +``` + +[license]: license +[contributor guide]: contributing +[command-line reference]: reference + +```{toctree} +--- +hidden: +maxdepth: 1 +--- + +reference +contributing +Code of Conduct +License +Changelog +``` diff --git a/docs/license.md b/docs/license.md new file mode 100644 index 0000000..218790f --- /dev/null +++ b/docs/license.md @@ -0,0 +1,7 @@ +# License + +```{literalinclude} ../LICENSE +--- +language: none +--- +``` diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 0000000..954237b --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,35 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=. +set BUILDDIR=_build + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.https://www.sphinx-doc.org/ + exit /b 1 +) + +if "%1" == "" goto help + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% + +:end +popd diff --git a/docs/reference.md b/docs/reference.md new file mode 100644 index 0000000..9050ec0 --- /dev/null +++ b/docs/reference.md @@ -0,0 +1,26 @@ +# Reference + + + +```{eval-rst} +model\_solver package +============================================================================= + + +model\_solver.functions module +----------------------------------------------------------------------------- + +.. automodule:: model_solver.functions + :members: + :undoc-members: + :show-inheritance: +``` diff --git a/docs/templates/package.rst_t b/docs/templates/package.rst_t new file mode 100644 index 0000000..89ac240 --- /dev/null +++ b/docs/templates/package.rst_t @@ -0,0 +1,48 @@ +{%- macro automodule(modname, options) -%} +.. automodule:: {{ modname }} +{%- for option in options %} + :{{ option }}: +{%- endfor %} +{%- endmacro %} + +{%- macro toctree(docnames) -%} +.. toctree:: + :maxdepth: {{ maxdepth }} +{% for docname in docnames %} + {{ docname }} +{%- endfor %} +{%- endmacro %} + +{%- if is_namespace %} +{{- [pkgname, "namespace"] | join(" ") | e | heading }} +{% else %} +{{- [pkgname, "package"] | join(" ") | e | heading }} +{% endif %} + +{%- if is_namespace %} +.. py:module:: {{ pkgname }} +{% endif %} + +{%- if modulefirst and not is_namespace %} +{{ automodule(pkgname, automodule_options) }} +{% endif %} + +{%- if subpackages %} +Subpackages +----------- + +{{ toctree(subpackages) }} +{% endif %} + +{%- if submodules %} +{% if separatemodules %} +{{ toctree(submodules) }} +{% else %} +{%- for submodule in submodules %} +{% if show_headings %} +{{- [submodule, "module"] | join(" ") | e | heading(2) }} +{% endif %} +{{ automodule(submodule, automodule_options) }} +{% endfor %} +{%- endif %} +{%- endif %} diff --git a/noxfile.py b/noxfile.py new file mode 100644 index 0000000..0020682 --- /dev/null +++ b/noxfile.py @@ -0,0 +1,247 @@ +"""Nox sessions.""" + +import os +import shlex +import shutil +import sys +from pathlib import Path +from textwrap import dedent + +import nox + + +try: + from nox_poetry import Session + from nox_poetry import session +except ImportError: + message = f"""\ + Nox failed to import the 'nox-poetry' package. + + Please install it using the following command: + + {sys.executable} -m pip install nox-poetry""" + raise SystemExit(dedent(message)) from None + +package = "model_solver" +python_versions = ["3.10", "3.11", "3.12"] +nox.needs_version = ">= 2021.6.6" +nox.options.sessions = ( + "pre-commit", + "mypy", + "tests", + "typeguard", + "xdoctest", + "docs-build", +) + + +def activate_virtualenv_in_precommit_hooks(session: Session) -> None: + """Activate virtualenv in hooks installed by pre-commit. + + This function patches git hooks installed by pre-commit to activate the + session's virtual environment. This allows pre-commit to locate hooks in + that environment when invoked from git. + + Args: + session: The Session object. + """ + assert session.bin is not None # nosec + + # Only patch hooks containing a reference to this session's bindir. Support + # quoting rules for Python and bash, but strip the outermost quotes so we + # can detect paths within the bindir, like /python. + bindirs = [ + bindir[1:-1] if bindir[0] in "'\"" else bindir + for bindir in (repr(session.bin), shlex.quote(session.bin)) + ] + + virtualenv = session.env.get("VIRTUAL_ENV") + if virtualenv is None: + return + + headers = { + # pre-commit < 2.16.0 + "python": f"""\ + import os + os.environ["VIRTUAL_ENV"] = {virtualenv!r} + os.environ["PATH"] = os.pathsep.join(( + {session.bin!r}, + os.environ.get("PATH", ""), + )) + """, + # pre-commit >= 2.16.0 + "bash": f"""\ + VIRTUAL_ENV={shlex.quote(virtualenv)} + PATH={shlex.quote(session.bin)}"{os.pathsep}$PATH" + """, + # pre-commit >= 2.17.0 on Windows forces sh shebang + "/bin/sh": f"""\ + VIRTUAL_ENV={shlex.quote(virtualenv)} + PATH={shlex.quote(session.bin)}"{os.pathsep}$PATH" + """, + } + + hookdir = Path(".git") / "hooks" + if not hookdir.is_dir(): + return + + for hook in hookdir.iterdir(): + if hook.name.endswith(".sample") or not hook.is_file(): + continue + + if not hook.read_bytes().startswith(b"#!"): + continue + + text = hook.read_text() + + if not is_bindir_in_text(bindirs, text): + continue + + lines = text.splitlines() + hook.write_text(insert_header_in_hook(headers, lines)) + + +def is_bindir_in_text(bindirs: list[str], text: str) -> bool: + """Helper function to check if bindir is in text.""" + return any( + Path("A") == Path("a") and bindir.lower() in text.lower() or bindir in text + for bindir in bindirs + ) + + +def insert_header_in_hook(header: dict[str, str], lines: list[str]) -> str: + """Helper function to insert headers in hook's text.""" + for executable, header_text in header.items(): + if executable in lines[0].lower(): + lines.insert(1, dedent(header_text)) + return "\n".join(lines) + return "\n".join(lines) + + +@session(name="pre-commit", python=python_versions[0]) +def precommit(session: Session) -> None: + """Lint using pre-commit.""" + args = session.posargs or [ + "run", + "--all-files", + "--hook-stage=manual", + "--show-diff-on-failure", + ] + session.install( + "pre-commit", + "pre-commit-hooks", + "darglint", + "ruff", + "black", + ) + session.run("pre-commit", *args) + if args and args[0] == "install": + activate_virtualenv_in_precommit_hooks(session) + + +@session(python=python_versions) +def mypy(session: Session) -> None: + """Type-check using mypy.""" + args = session.posargs or ["src", "tests"] + session.install(".") + session.install("mypy", "pytest") + session.run("mypy", *args) + if not session.posargs: + session.run("mypy", f"--python-executable={sys.executable}", "noxfile.py") + + +@session(python=python_versions) +def tests(session: Session) -> None: + """Run the test suite.""" + session.install(".") + session.install("coverage[toml]", "pytest", "pygments") + try: + session.run( + "coverage", + "run", + "--parallel", + "-m", + "pytest", + "-o", + "pythonpath=", + *session.posargs, + ) + finally: + if session.interactive: + session.notify("coverage", posargs=[]) + + +@session(python=python_versions[0]) +def coverage(session: Session) -> None: + """Produce the coverage report.""" + args = session.posargs or ["report", "--skip-empty"] + + session.install("coverage[toml]") + + if not session.posargs and any(Path().glob(".coverage.*")): + session.run("coverage", "combine") + + session.run("coverage", *args) + + +@session(python=python_versions[0]) +def typeguard(session: Session) -> None: + """Runtime type checking using Typeguard.""" + session.install(".") + session.install("pytest", "typeguard", "pygments") + session.run("pytest", f"--typeguard-packages={package}", *session.posargs) + + +@session(python=python_versions) +def xdoctest(session: Session) -> None: + """Run examples with xdoctest.""" + if session.posargs: + args = [package, *session.posargs] + else: + args = [f"--modname={package}", "--command=all"] + if "FORCE_COLOR" in os.environ: + args.append("--colored=1") + + session.install(".") + session.install("xdoctest[colors]") + session.run("python", "-m", "xdoctest", *args) + + +@session(name="docs-build", python=python_versions[0]) +def docs_build(session: Session) -> None: + """Build the documentation.""" + args = session.posargs or ["docs", "docs/_build"] + if not session.posargs and "FORCE_COLOR" in os.environ: + args.insert(0, "--color") + + session.install(".") + session.install( + "sphinx", "sphinx-autodoc-typehints", "sphinx-click", "furo", "myst-parser" + ) + + build_dir = Path("docs", "_build") + if build_dir.exists(): + shutil.rmtree(build_dir) + + session.run("sphinx-build", *args) + + +@session(python=python_versions[0]) +def docs(session: Session) -> None: + """Build and serve the documentation with live reloading on file changes.""" + args = session.posargs or ["--open-browser", "docs", "docs/_build"] + session.install(".") + session.install( + "sphinx", + "sphinx-autobuild", + "sphinx-autodoc-typehints", + "sphinx-click", + "furo", + "myst-parser", + ) + + build_dir = Path("docs", "_build") + if build_dir.exists(): + shutil.rmtree(build_dir) + + session.run("sphinx-autobuild", *args) diff --git a/poetry.lock b/poetry.lock index 9f2d9d3..6f33bad 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,91 +1,118 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. + +[[package]] +name = "aiohappyeyeballs" +version = "2.4.0" +description = "Happy Eyeballs for asyncio" +optional = false +python-versions = ">=3.8" +files = [ + {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"}, + {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"}, +] [[package]] name = "aiohttp" -version = "3.9.2" +version = "3.10.5" description = "Async http client/server 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-content-hash = "452456b27995782803e02871d2cbff437d2470cdc2fda0ef98848631d5dc03fc" +python-versions = ">=3.10,<4.0" +content-hash = "1618822aa105299892469bbffaa982dd3e5e422f4e857ce671ce840cecc3ef7b" diff --git a/poetry.toml b/poetry.toml deleted file mode 100644 index 5b3ac91..0000000 --- a/poetry.toml +++ /dev/null @@ -1,3 +0,0 @@ -# Keep virtual environment in project directory. Useful in Jupyter to avoid recreating environment. -[virtualenvs] -in-project = true diff --git a/pyproject.toml b/pyproject.toml index d725c5e..31921f3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -2,24 +2,138 @@ name = "ssb-model-solver" version = "1.1.23" description = "Class to define, block analyse and solve dynamic and algebraic models numerically" -authors = ["Magnus Helliesen "] +authors = ["Benedikt Goodman "] license = "MIT" -packages = [{include = "model_solver", from="src"}] +readme = "README.md" +homepage = "https://github.com/statisticsnorway/ssb-model-solver" +repository = "https://github.com/statisticsnorway/ssb-model-solver" +documentation = "https://statisticsnorway.github.io/ssb-model-solver" +packages = [{ include = "model_solver", from = "src" }] +classifiers = ["Development Status :: 4 - Beta"] + +[tool.poetry.urls] +Changelog = "https://github.com/statisticsnorway/ssb-model-solver/releases" [tool.poetry.dependencies] -python = ">=3.10,<3.11" -dapla-toolbelt = "^1.3.2" -pyvis = "^0.3.2" -symengine = "^0.9.2" -matplotlib = "^3.7.1" -numba = "^0.57.0" -tornado = "6.3.3" -requests = "2.31.0" -cryptography = "42.0.4" - -[tool.poetry.dev-dependencies] -pytest = "^7.1.3" -ipykernel = "^6.15.3" +python = ">=3.10,<4.0" +dapla-toolbelt = ">=1.3.2" +pyvis = ">=0.3.2" +click = ">=8.0.1" +symengine = ">=0.9.2" +matplotlib = ">=3.7.1" +numba = ">=0.57.0" +tornado = ">=6.3.3" +requests = ">=2.31.0" +cryptography = ">=42.0.4" + +[tool.poetry.group.dev.dependencies] +pygments = ">=2.10.0" +black = { extras = ["jupyter"], version = ">=23.1.0" } +coverage = { extras = ["toml"], version = ">=6.2" } +darglint = ">=1.8.1" +furo = ">=2021.11.12" +mypy = ">=0.930" +pre-commit = ">=2.16.0" +pre-commit-hooks = ">=4.1.0" +ruff = ">=0.0.284" +pytest = ">=6.2.5" +sphinx = ">=6.2.1" +sphinx-autobuild = ">=2021.3.14" +sphinx-autodoc-typehints = ">=1.24.0" +sphinx-click = ">=3.0.2" +typeguard = ">=2.13.3" +xdoctest = { extras = ["colors"], version = ">=0.15.10" } +myst-parser = { version = ">=0.16.1" } + +[tool.poetry.scripts] +ssb-model-solver = "model_solver.__main__:main" + +[tool.coverage.paths] +source = ["src", "*/site-packages"] +tests = ["tests", "*/tests"] + +[tool.coverage.run] +branch = true +source = ["model_solver", "tests"] +relative_files = true + +[tool.coverage.report] +show_missing = true +fail_under = 50 + +[tool.mypy] +strict = true +warn_unreachable = true +pretty = true +show_column_numbers = true +show_error_context = true + +[tool.ruff] +force-exclude = true # Apply excludes to pre-commit +show-fixes = true +src = ["src", "tests"] +target-version = "py310" # Minimum Python version supported +include = ["*.py", "*.pyi", "**/pyproject.toml", "*.ipynb"] +extend-exclude = [ + "__pycache__", + "old", + ".ipynb_checkpoints", + "noxfile.py", + "docs/conf.py", +] + +# Ruff rules may be customized as desired: https://docs.astral.sh/ruff/rules/ +[tool.ruff.lint] +select = [ + "A", # prevent using keywords that clobber python builtins + "ANN", # check type annotations + "B", # bugbear: security warnings + "D", # documentation + "E", # pycodestyle + "F", # pyflakes + "ISC", # implicit string concatenation + "I", # sort imports + "UP", # alert you when better syntax is available in your python version + "RUF", # the ruff developer's own rules +] +ignore = [ + "ANN101", # Supress missing-type-self. + "ANN102", # Supress missing-type-cls. + "ANN202", # Don't requiere return type annotation for private functions. + "ANN401", # Allow type annotation with type Any. + "D100", # Supress undocumented-public-module. Only doc of public api required. + "E402", # Supress module-import-not-at-top-of-file, needed in jupyter notebooks. + "E501", # Supress line-too-long warnings: trust black's judgement on this one. +] + +[tool.ruff.lint.isort] +force-single-line = true + +[tool.ruff.lint.mccabe] +max-complexity = 15 + +[tool.ruff.lint.pydocstyle] +convention = "google" # You can also use "numpy". + +[tool.ruff.lint.pep8-naming] +classmethod-decorators = ["classmethod", "validator", "root_validator", "pydantic.validator"] + +[tool.ruff.lint.per-file-ignores] +"*/__init__.py" = ["F401"] +"**/tests/*" = [ + "ANN001", # type annotations don't add value for test functions + "ANN002", # type annotations don't add value for test functions + "ANN003", # type annotations don't add value for test functions + "ANN201", # type annotations don't add value for test functions + "ANN204", # type annotations don't add value for test functions + "ANN205", # type annotations don't add value for test functions + "ANN206", # type annotations don't add value for test functions + "D100", # docstrings are overkill for test functions + "D101", + "D102", + "D103", + "S101", # asserts are encouraged in pytest +] [build-system] requires = ["poetry-core>=1.0.0"] diff --git a/sonar-project.properties b/sonar-project.properties new file mode 100644 index 0000000..3b82acb --- /dev/null +++ b/sonar-project.properties @@ -0,0 +1,11 @@ +sonar.projectKey=statisticsnorway_ssb-model-solver +sonar.organization=statisticsnorway +sonar.host.url=https://sonarcloud.io + +sonar.sources=src/model_solver +sonar.tests=tests + +sonar.python.version=3.10 +sonar.python.coverage.reportPaths=coverage.xml + +sonar.sourceEncoding=UTF-8 diff --git a/src/model_solver/__main__.py b/src/model_solver/__main__.py new file mode 100644 index 0000000..332cea5 --- /dev/null +++ b/src/model_solver/__main__.py @@ -0,0 +1,13 @@ +"""Command-line interface.""" + +import click + + +@click.command() +@click.version_option() +def main() -> None: + """SSB Model Solver.""" + + +if __name__ == "__main__": + main(prog_name="ssb-model-solver") # pragma: no cover diff --git a/src/model_solver/functions.py b/src/model_solver/functions.py new file mode 100644 index 0000000..cc54f7f --- /dev/null +++ b/src/model_solver/functions.py @@ -0,0 +1,35 @@ +"""A collection of useful functions. + +The template and this example uses Google style docstrings as described at: +https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html + +""" + + +def example_function(number1: int, number2: int) -> str: + """Compare two integers. + + This is merely an example function can be deleted. It is used to show and test generating + documentation from code, type hinting, testing, and testing examples + in the code. + + + Args: + number1: The first number. + number2: The second number, which will be compared to number1. + + Returns: + A string describing which number is the greatest. + + Examples: + Examples should be written in doctest format, and should illustrate how + to use the function. + + >>> example_function(1, 2) + 1 is less than 2 + + """ + if number1 < number2: + return f"{number1} is less than {number2}" + + return f"{number1} is greater than or equal to {number2}" diff --git a/src/model_solver/py.typed b/src/model_solver/py.typed new file mode 100644 index 0000000..e69de29 diff --git a/tests/__init__.py b/tests/__init__.py index ffa26b6..ce09e91 100644 --- a/tests/__init__.py +++ b/tests/__init__.py @@ -1 +1 @@ -# This file is required by pytest \ No newline at end of file +"""Test suite for the model_solver package.""" diff --git a/tests/test_functions.py b/tests/test_functions.py new file mode 100644 index 0000000..e29a925 --- /dev/null +++ b/tests/test_functions.py @@ -0,0 +1,6 @@ +from model_solver.functions import example_function + + +def test_example_function() -> None: + assert example_function(1, 2) == "1 is less than 2" + assert example_function(1, 0) == "1 is greater than or equal to 0" diff --git a/tests/test_main.py b/tests/test_main.py new file mode 100644 index 0000000..d75233e --- /dev/null +++ b/tests/test_main.py @@ -0,0 +1,18 @@ +"""Test cases for the __main__ module.""" + +import pytest +from click.testing import CliRunner + +from model_solver import __main__ + + +@pytest.fixture() +def runner() -> CliRunner: + """Fixture for invoking command-line interfaces.""" + return CliRunner() + + +def test_main_succeeds(runner: CliRunner) -> None: + """It exits with a status code of zero.""" + result = runner.invoke(__main__.main) + assert result.exit_code == 0 From 9141f03723ba580d528c92ad32eb06633b2c573e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Fri, 6 Sep 2024 15:58:16 +0200 Subject: [PATCH 02/22] Fix formatting --- examples/example-model-solver.ipynb | 54 +- src/model_solver/model_solver.py | 858 +++++++++++++++++----------- tests/test_model_solver.py | 103 ++-- 3 files changed, 624 insertions(+), 391 deletions(-) diff --git a/examples/example-model-solver.ipynb b/examples/example-model-solver.ipynb index e741173..9f72320 100644 --- a/examples/example-model-solver.ipynb +++ b/examples/example-model-solver.ipynb @@ -42,7 +42,8 @@ "# Change directory until find project root\n", "notebook_path = os.getcwd()\n", "for folder_level in range(50):\n", - " if \"pyproject.toml\" in os.listdir(): break\n", + " if \"pyproject.toml\" in os.listdir():\n", + " break\n", " os.chdir(\"../\")" ] }, @@ -77,14 +78,14 @@ "outputs": [], "source": [ "equations = [\n", - " 'x1 = a1',\n", - " 'x2 = a2',\n", - " '0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1',\n", - " '0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2',\n", - " 'k1 = k1(-1)+i1',\n", - " 'k2 = k2(-1)+i2'\n", - " ]\n", - "endogenous = ['x1', 'x2', 'ca', 'cb', 'k1', 'k2']" + " \"x1 = a1\",\n", + " \"x2 = a2\",\n", + " \"0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1\",\n", + " \"0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2\",\n", + " \"k1 = k1(-1)+i1\",\n", + " \"k2 = k2(-1)+i2\",\n", + "]\n", + "endogenous = [\"x1\", \"x2\", \"ca\", \"cb\", \"k1\", \"k2\"]" ] }, { @@ -152,18 +153,21 @@ "metadata": {}, "outputs": [], "source": [ - "input_data = pd.DataFrame({'x1': [2,4,1,2],\n", - " 'x2': [2,1,2,3],\n", - " 'ca': [1,3,4,1],\n", - " 'cb': [1,2,1,4],\n", - " 'k1': [1,3,4,1],\n", - " 'k2': [1,2,1,4],\n", - " 'a1': [1,2,4,4],\n", - " 'a2': [3,2,3,4],\n", - " 'i1': [1,2,4,4],\n", - " 'i2': [3,2,3,4]\n", - " },\n", - " index=['2019Q1', '2019Q2', '2020Q3', '2020Q4'])\n", + "input_data = pd.DataFrame(\n", + " {\n", + " \"x1\": [2, 4, 1, 2],\n", + " \"x2\": [2, 1, 2, 3],\n", + " \"ca\": [1, 3, 4, 1],\n", + " \"cb\": [1, 2, 1, 4],\n", + " \"k1\": [1, 3, 4, 1],\n", + " \"k2\": [1, 2, 1, 4],\n", + " \"a1\": [1, 2, 4, 4],\n", + " \"a2\": [3, 2, 3, 4],\n", + " \"i1\": [1, 2, 4, 4],\n", + " \"i2\": [3, 2, 3, 4],\n", + " },\n", + " index=[\"2019Q1\", \"2019Q2\", \"2020Q3\", \"2020Q4\"],\n", + ")\n", "input_data.head()" ] }, @@ -204,7 +208,7 @@ "metadata": {}, "outputs": [], "source": [ - "model.draw_blockwise_graph('ca')" + "model.draw_blockwise_graph(\"ca\")" ] }, { @@ -222,7 +226,7 @@ "metadata": {}, "outputs": [], "source": [ - "model.switch_endo_vars(['x2'], ['a2'])" + "model.switch_endo_vars([\"x2\"], [\"a2\"])" ] }, { @@ -255,7 +259,7 @@ "metadata": {}, "outputs": [], "source": [ - "model.draw_blockwise_graph('ca')" + "model.draw_blockwise_graph(\"ca\")" ] }, { @@ -264,7 +268,7 @@ "metadata": {}, "outputs": [], "source": [ - "model.show_block_vals(5,1)" + "model.show_block_vals(5, 1)" ] }, { diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 51a5705..0287818 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -99,18 +99,18 @@ class ModelSolver: # Reads in equations and endogenous variables and does a number of operations, e.g. analyzing block structure using graph theory. def __init__(self, eqns: list[str], endo_vars: list[str]): self._some_error = False - self._lag_notation = '__LAG' + self._lag_notation = "__LAG" self._max_lag = 0 self._root_tolerance = 1e-7 self._max_iter = 10 - print('-'*100) - print('Initializing model') + print("-" * 100) + print("Initializing model") # Model equations and endogenous variables are checked and stored as immutable tuples (as opposed to mutable lists) self._eqns, self._endo_vars = self._init_model(eqns, endo_vars) - print('* Analyzing model') + print("* Analyzing model") # Analyzing equation strings to determine variables, lags and coefficients self._eqns_analyzed, self._var_mapping, self._lag_mapping = self._analyze_eqns() @@ -120,15 +120,14 @@ def __init__(self, eqns: list[str], endo_vars: list[str]): self._eqns_endo_vars_match, self._condenced_model_digraph, self._augmented_condenced_model_digraph, - self._node_varlist_mapping + self._node_varlist_mapping, ) = self._block_analyze_model() # Generating everything needed to simulate model self._sim_code, self._blocks = self._gen_sim_code_and_blocks() - print('Finished') - print('-'*100) - + print("Finished") + print("-" * 100) @property def eqns(self): @@ -161,67 +160,65 @@ def max_iter(self): @property def last_solution(self): try: - return self._last_solution.iloc[self.max_lag:, :] + return self._last_solution.iloc[self.max_lag :, :] except AttributeError: - raise AttributeError('no solution exists') - + raise AttributeError("no solution exists") @root_tolerance.setter def root_tolerance(self, val: float): if isinstance(val, float) is False: - raise ValueError('tolerance for termination must be of type float') + raise ValueError("tolerance for termination must be of type float") if val <= 0: - raise ValueError('tolerance for termination must be positive') + raise ValueError("tolerance for termination must be positive") self._root_tolerance = val @max_iter.setter def max_iter(self, val: int): if isinstance(val, int) is False: - raise ValueError('maximum number of iterations must be an integer') + raise ValueError("maximum number of iterations must be an integer") if val < 0: - raise ValueError('maximum number of iterations cannot be negative') + raise ValueError("maximum number of iterations cannot be negative") self._max_iter = val - # Imports lists containing equations and endogenous variables stored as strings # Checks that there are no blank lines, sets everything to lowercase and returns as tuples def _init_model(self, eqns: list, endo_vars: list): - print('* Importing equations') - if any(x.strip() == '' for x in eqns): + print("* Importing equations") + if any(x.strip() == "" for x in eqns): self._some_error = True - raise ValueError('there are empty elements in equation list') + raise ValueError("there are empty elements in equation list") - print('* Importing endogenous variables') - if any(x.strip() == '' for x in endo_vars): + print("* Importing endogenous variables") + if any(x.strip() == "" for x in endo_vars): self._some_error = True - raise ValueError('there are empty elements in endogenous variable list') + raise ValueError("there are empty elements in endogenous variable list") if len(eqns) != len(endo_vars): self._some_error = True - raise ValueError('there is a different number of equations and endogenous variables') + raise ValueError( + "there is a different number of equations and endogenous variables" + ) return tuple(x.lower() for x in eqns), tuple(x.lower() for x in endo_vars) - # Analyzes the equations of the model def _analyze_eqns(self): if self._some_error: return None, None - print('\t* Analyzing equation strings') + print("\t* Analyzing equation strings") eqns_analyzed = [] var_mapping, lag_mapping = {}, {} for eqn in self._eqns: eqn_analyzed = (eqn, *self._analyze_eqn(eqn)) - eqns_analyzed += eqn_analyzed, + eqns_analyzed += (eqn_analyzed,) var_mapping = {**var_mapping, **eqn_analyzed[2]} lag_mapping = {**lag_mapping, **eqn_analyzed[3]} return eqns_analyzed, var_mapping, lag_mapping - # Takes an equation string and parses it into coefficients (special care is taken to deal with scientific notation), variables, lags and operators/brackets # I've written my own parser in stead of using some existing because it needs to take care of then (-)-notation for lags def _analyze_eqn(self, eqn: str): @@ -229,37 +226,48 @@ def _analyze_eqn(self, eqn: str): return parsed_eqn_with_lag_notation, var_mapping, lag_mapping = [], {}, {} - component, lag = '', '' + component, lag = "", "" is_num, is_var, is_lag, is_sci = False, False, False, False - for chr in ''.join([eqn, ' ']): + for chr in "".join([eqn, " "]): is_num = (chr.isnumeric() and not is_var) or is_num - is_var = (chr.isalpha() and not is_num) or is_var - is_lag = (is_var and chr == '(') or is_lag - is_sci = (is_num and chr == 'e') or is_sci + is_var = (chr.isalpha() and not is_num) or is_var + is_lag = (is_var and chr == "(") or is_lag + is_sci = (is_num and chr == "e") or is_sci - if (is_var and chr == '(' and component in ['max', 'min', 'log', 'exp']): - parsed_eqn_with_lag_notation += ''.join([component, chr]), + if is_var and chr == "(" and component in ["max", "min", "log", "exp"]: + parsed_eqn_with_lag_notation += ("".join([component, chr]),) is_var, is_lag = False, False - component, lag = '', '' + component, lag = "", "" continue # Check if character is something other than a numeric, variable or lag and write numeric or variable to parsed equation - if chr in ['=','+','-','*','/','(',')',',',' '] and not (is_lag or is_sci): + if chr in ["=", "+", "-", "*", "/", "(", ")", ",", " "] and not ( + is_lag or is_sci + ): if is_num: - parsed_eqn_with_lag_notation += str(component), + parsed_eqn_with_lag_notation += (str(component),) if is_var: # Replace (-)-notation by LAG_NOTATION for lags and appends _ to the end to mark the end - pfx = '' if lag == '' else ''.join([self._lag_notation, str(-int(lag[1:-1])), '_']) - parsed_eqn_with_lag_notation += ''.join([component, pfx]), - var_mapping[''.join([component, lag])] = ''.join([component, pfx]) - var_mapping[''.join([component, pfx])] = ''.join([component, lag]) - lag_mapping[''.join([component, pfx])] = (component, 0 if lag == '' else -int(lag[1:-1])) - if lag != '': - self._max_lag = max(self._max_lag, -int(lag.replace('(', '').replace(')', ''))) - if chr != ' ': - parsed_eqn_with_lag_notation += chr, - component, lag = '', '' + pfx = ( + "" + if lag == "" + else "".join([self._lag_notation, str(-int(lag[1:-1])), "_"]) + ) + parsed_eqn_with_lag_notation += ("".join([component, pfx]),) + var_mapping["".join([component, lag])] = "".join([component, pfx]) + var_mapping["".join([component, pfx])] = "".join([component, lag]) + lag_mapping["".join([component, pfx])] = ( + component, + 0 if lag == "" else -int(lag[1:-1]), + ) + if lag != "": + self._max_lag = max( + self._max_lag, -int(lag.replace("(", "").replace(")", "")) + ) + if chr != " ": + parsed_eqn_with_lag_notation += (chr,) + component, lag = "", "" is_num, is_var, is_lag = False, False, False continue @@ -267,37 +275,50 @@ def _analyze_eqn(self, eqn: str): is_sci = False if is_num: - component = ''.join([component, chr]) + component = "".join([component, chr]) continue if is_var and not is_lag: - component = ''.join([component, chr]) + component = "".join([component, chr]) continue if is_var and is_lag: - lag = ''.join([lag, chr]) - if chr == ')': + lag = "".join([lag, chr]) + if chr == ")": is_lag = False return parsed_eqn_with_lag_notation, var_mapping, lag_mapping - # Performs block analysis of equations subject to endogenous variables # Analysis is a sequence of operations using graph theory def _block_analyze_model(self): # Using graph theory to analyze equations using existing algorithms to establish minimum simultaneous blocks eqns_endo_vars_bigraph = self._gen_eqns_endo_vars_bigraph() eqns_endo_vars_match = self._find_max_bipartite_match(eqns_endo_vars_bigraph) - model_digraph = self._gen_model_digraph(eqns_endo_vars_bigraph, eqns_endo_vars_match) - condenced_model_digraph, condenced_model_node_varlist_mapping = self._gen_condenced_model_digraph(model_digraph) - augmented_condenced_model_digraph, augmented_condenced_model_node_varlist_mapping = ( - self._gen_augmented_condenced_model_digraph(condenced_model_digraph, eqns_endo_vars_match) + model_digraph = self._gen_model_digraph( + eqns_endo_vars_bigraph, eqns_endo_vars_match + ) + condenced_model_digraph, condenced_model_node_varlist_mapping = ( + self._gen_condenced_model_digraph(model_digraph) + ) + ( + augmented_condenced_model_digraph, + augmented_condenced_model_node_varlist_mapping, + ) = self._gen_augmented_condenced_model_digraph( + condenced_model_digraph, eqns_endo_vars_match ) - node_varlist_mapping = {**condenced_model_node_varlist_mapping, **augmented_condenced_model_node_varlist_mapping} - - return eqns_endo_vars_match, condenced_model_digraph, augmented_condenced_model_digraph, node_varlist_mapping + node_varlist_mapping = { + **condenced_model_node_varlist_mapping, + **augmented_condenced_model_node_varlist_mapping, + } + return ( + eqns_endo_vars_match, + condenced_model_digraph, + augmented_condenced_model_digraph, + node_varlist_mapping, + ) # Generates bipartite graph (bigraph) connetcting equations (nodes in U) with endogenous variables (nodes in V) # See https://en.wikipedia.org/wiki/Bipartite_graph for a discussion of bigraphs @@ -305,11 +326,15 @@ def _gen_eqns_endo_vars_bigraph(self): if self._some_error: return - print('\t* Generating bipartite graph (BiGraph) connecting equations and endogenous variables') + print( + "\t* Generating bipartite graph (BiGraph) connecting equations and endogenous variables" + ) # Make nodes in bipartite graph with equations U (0) and endogenous variables in V (1) eqns_endo_vars_bigraph = nx.Graph() - eqns_endo_vars_bigraph.add_nodes_from([i for i, _ in enumerate(self.eqns)], bipartite=0) + eqns_endo_vars_bigraph.add_nodes_from( + [i for i, _ in enumerate(self.eqns)], bipartite=0 + ) eqns_endo_vars_bigraph.add_nodes_from(self._endo_vars, bipartite=1) # Make edges between equations and endogenous variables @@ -319,7 +344,6 @@ def _gen_eqns_endo_vars_bigraph(self): return eqns_endo_vars_bigraph - # Finds a maximum bipartite match (MBM) of bigraph connetcting equations (nodes in U) with endogenous variables (nodes in V) # See https://www.geeksforgeeks.org/maximum-bipartite-matching/ for more on MBM # Returns dict with matches (maps both ways, i.e. U-->V and U-->U) @@ -327,28 +351,33 @@ def _find_max_bipartite_match(self, eqns_endo_vars_bigraph): if self._some_error: return - print('\t* Finding maximum bipartite match (MBM) (i.e. associating every equation with exactly one endogenus variable)') + print( + "\t* Finding maximum bipartite match (MBM) (i.e. associating every equation with exactly one endogenus variable)" + ) # Use maximum bipartite matching to make a one to one mapping between equations and endogenous variables try: - maximum_bipartite_match = nx.bipartite.maximum_matching(eqns_endo_vars_bigraph, [i for i, _ in enumerate(self._eqns)]) - if len(maximum_bipartite_match)/2 < len(self.eqns): + maximum_bipartite_match = nx.bipartite.maximum_matching( + eqns_endo_vars_bigraph, [i for i, _ in enumerate(self._eqns)] + ) + if len(maximum_bipartite_match) / 2 < len(self.eqns): self._some_error = True - raise RuntimeError('model is over or under spesified') + raise RuntimeError("model is over or under spesified") except nx.AmbiguousSolution: self._some_error = True - raise RuntimeError('unable to analyze model') + raise RuntimeError("unable to analyze model") return maximum_bipartite_match - # Makes a directed graph (digraph) showing how endogenous variables affect every other endogenous variable # See https://en.wikipedia.org/wiki/Directed_graph for more about directed graphs def _gen_model_digraph(self, eqns_endo_vars_bigraph, eqns_endo_vars_match): if self._some_error: return - print('\t* Generating directed graph (DiGraph) connecting endogenous variables using bipartite graph and MBM') + print( + "\t* Generating directed graph (DiGraph) connecting endogenous variables using bipartite graph and MBM" + ) # Make nodes in directed graph of endogenous variables model_digraph = nx.DiGraph() @@ -361,7 +390,6 @@ def _gen_model_digraph(self, eqns_endo_vars_bigraph, eqns_endo_vars_match): return model_digraph - # Makes a condencation of digraph of endogenous variables # Each node of condencation contains strongly connected components; this corresponds to the simulataneous model blocks # See https://en.wikipedia.org/wiki/Strongly_connected_component for more about strongly connected components @@ -369,7 +397,9 @@ def _gen_condenced_model_digraph(self, model_digraph): if self._some_error: return - print('\t* Finding condensation of DiGraph (i.e. determining minimal blocks of systems of simulataneous equations)') + print( + "\t* Finding condensation of DiGraph (i.e. determining minimal blocks of systems of simulataneous equations)" + ) # Generate condensation graph of equation graph such that every node is a strong component of the equation graph condenced_model_digraph = nx.condensation(model_digraph) @@ -377,13 +407,16 @@ def _gen_condenced_model_digraph(self, model_digraph): # Make a dictionary that associate every node of condensation with a list of variables node_vars_mapping = {} for node in tuple(condenced_model_digraph.nodes()): - node_vars_mapping[node] = tuple(condenced_model_digraph.nodes[node]['members']) + node_vars_mapping[node] = tuple( + condenced_model_digraph.nodes[node]["members"] + ) return condenced_model_digraph, node_vars_mapping - # Augments condenced digraph with nodes and edges for exogenous variables in order to show what exogenous variables affect what strong components - def _gen_augmented_condenced_model_digraph(self, condenced_model_digraph, eqns_endo_vars_match): + def _gen_augmented_condenced_model_digraph( + self, condenced_model_digraph, eqns_endo_vars_match + ): if self._some_error: return @@ -392,15 +425,23 @@ def _gen_augmented_condenced_model_digraph(self, condenced_model_digraph, eqns_e # Make edges between exogenous variables and strong components it is a part of node_vars_mapping = {} for node in condenced_model_digraph.nodes(): - for member in condenced_model_digraph.nodes[node]['members']: - for exog_var_adjacent_to_node in [val for key, val in self._eqns_analyzed[eqns_endo_vars_match[member]][2].items() - if self._lag_notation not in val and key not in self.endo_vars]: - augmented_condenced_model_digraph.add_edge(exog_var_adjacent_to_node, node) - node_vars_mapping[exog_var_adjacent_to_node] = exog_var_adjacent_to_node, + for member in condenced_model_digraph.nodes[node]["members"]: + for exog_var_adjacent_to_node in [ + val + for key, val in self._eqns_analyzed[eqns_endo_vars_match[member]][ + 2 + ].items() + if self._lag_notation not in val and key not in self.endo_vars + ]: + augmented_condenced_model_digraph.add_edge( + exog_var_adjacent_to_node, node + ) + node_vars_mapping[exog_var_adjacent_to_node] = ( + exog_var_adjacent_to_node, + ) return augmented_condenced_model_digraph, node_vars_mapping - # Generates simulation code and blocks # Simulation code contains a tuple of tuples for each strong component # The tuple for each strong component contains objective function, and Jacobian matrix, and lists of the variables in the strong component @@ -408,78 +449,106 @@ def _gen_sim_code_and_blocks(self): if self._some_error: return - print('\t* Generating simulation code (i.e. block-wise symbolic objective function,', - 'symbolic Jacobian matrix and lists of endogenous and exogenous variables)') + print( + "\t* Generating simulation code (i.e. block-wise symbolic objective function,", + "symbolic Jacobian matrix and lists of endogenous and exogenous variables)", + ) sim_code, blocks = {}, {} - for i, node in enumerate(reversed(tuple(self._condenced_model_digraph.nodes()))): - block_endo_vars, block_eqns_orig, block_eqns_lags, block_pred_vars = tuple(), tuple(), tuple(), set() - for member in self._condenced_model_digraph.nodes[node]['members']: + for i, node in enumerate( + reversed(tuple(self._condenced_model_digraph.nodes())) + ): + block_endo_vars, block_eqns_orig, block_eqns_lags, block_pred_vars = ( + tuple(), + tuple(), + tuple(), + set(), + ) + for member in self._condenced_model_digraph.nodes[node]["members"]: j = self._eqns_endo_vars_match[member] eqns_analyzed = self._eqns_analyzed[j] - block_endo_vars += member, - block_eqns_orig += eqns_analyzed[0], - block_eqns_lags += eqns_analyzed[1], - block_pred_vars.update([val for key, val in eqns_analyzed[2].items() if self._lag_notation not in key]) + block_endo_vars += (member,) + block_eqns_orig += (eqns_analyzed[0],) + block_eqns_lags += (eqns_analyzed[1],) + block_pred_vars.update( + [ + val + for key, val in eqns_analyzed[2].items() + if self._lag_notation not in key + ] + ) block_pred_vars.difference_update(set(block_endo_vars)) block_pred_vars = tuple(block_pred_vars) - (def_fun, obj_fun, jac) = self._gen_def_or_obj_fun_and_jac(block_eqns_lags, block_endo_vars, block_pred_vars) - sim_code[i+1] = ( + (def_fun, obj_fun, jac) = self._gen_def_or_obj_fun_and_jac( + block_eqns_lags, block_endo_vars, block_pred_vars + ) + sim_code[i + 1] = ( def_fun, obj_fun, jac, block_endo_vars, block_pred_vars, - block_eqns_lags - ) - blocks[i+1] = ( + block_eqns_lags, + ) + blocks[i + 1] = ( block_endo_vars, block_pred_vars, block_eqns_orig, - True if def_fun else False - ) + True if def_fun else False, + ) return sim_code, blocks - # Generates symbolic objective functon and Jacobian matrix for a given strong component @staticmethod - def _gen_def_or_obj_fun_and_jac(eqns: tuple[str], - endo_vars: tuple[str], - pred_vars: tuple[str] - ): + def _gen_def_or_obj_fun_and_jac( + eqns: tuple[str], endo_vars: tuple[str], pred_vars: tuple[str] + ): max, min = Max, Max endo_sym, pred_sym, obj_fun = [], [], [] for endo_var in endo_vars: var(endo_var) - endo_sym += eval(endo_var), + endo_sym += (eval(endo_var),) for exog_var in pred_vars: var(exog_var) - pred_sym += eval(exog_var), + pred_sym += (eval(exog_var),) for eqn in eqns: - i = eqn.index('=') - lhs, rhs = eqn[:i], eqn[i+1:] - if len(eqns) == 1 and endo_var == ''.join(lhs) and endo_var not in rhs: + i = eqn.index("=") + lhs, rhs = eqn[:i], eqn[i + 1 :] + if len(eqns) == 1 and endo_var == "".join(lhs) and endo_var not in rhs: if len(pred_vars) == 0: - return lambda _: np.array([eval(''.join(rhs).strip().strip('+'))]), None, None - def_fun = eval(''.join(rhs).strip().strip('+')) + return ( + lambda _: np.array([eval("".join(rhs).strip().strip("+"))]), + None, + None, + ) + def_fun = eval("".join(rhs).strip().strip("+")) def_fun_lam = Lambdify([pred_sym], def_fun) - def_fun_out = lambda args: np.array([def_fun_lam(args)], dtype=np.float64) + def_fun_out = lambda args: np.array( + [def_fun_lam(args)], dtype=np.float64 + ) return def_fun_out, None, None - if ('min(' in lhs) or ('min(' in rhs): - raise RuntimeError('min-function is in block that is not a simple definition') - if ('max(' in lhs) or ('max(' in rhs): - raise RuntimeError('max-function is in block that is not a simple definition') + if ("min(" in lhs) or ("min(" in rhs): + raise RuntimeError( + "min-function is in block that is not a simple definition" + ) + if ("max(" in lhs) or ("max(" in rhs): + raise RuntimeError( + "max-function is in block that is not a simple definition" + ) obj_fun_row = eval( - '-'.join([''.join(['(', ''.join(lhs).strip().strip('+'), ')']), - ''.join(['(', ''.join(rhs).strip().strip('+'), ')'])] - ) + "-".join( + [ + "".join(["(", "".join(lhs).strip().strip("+"), ")"]), + "".join(["(", "".join(rhs).strip().strip("+"), ")"]), + ] + ) ) - obj_fun += obj_fun_row, + obj_fun += (obj_fun_row,) jac = Matrix(obj_fun).jacobian(Matrix(endo_sym)).tolist() @@ -491,7 +560,6 @@ def _gen_def_or_obj_fun_and_jac(eqns: tuple[str], return None, obj_fun_out, jac_out - def switch_endo_vars(self, old_endo_vars: list[str], new_endo_vars: list[str]): """ Sets old_endo_vars as exogenous and new_endo_vars as endogenous and performs block analysis. @@ -525,24 +593,26 @@ def switch_endo_vars(self, old_endo_vars: list[str], new_endo_vars: list[str]): """ if all(x in self.endo_vars for x in old_endo_vars) is False: - raise RuntimeError('all variables in old_endo_vars are not endogenous') + raise RuntimeError("all variables in old_endo_vars are not endogenous") if any(x in self.endo_vars for x in new_endo_vars): - raise RuntimeError('some variables in new_endo_vars are endogenous') + raise RuntimeError("some variables in new_endo_vars are endogenous") - print('Analyzing model') - self._endo_vars = *[x for x in self._endo_vars if x not in old_endo_vars], *new_endo_vars, + print("Analyzing model") + self._endo_vars = ( + *[x for x in self._endo_vars if x not in old_endo_vars], + *new_endo_vars, + ) ( self._eqns_endo_vars_match, self._condenced_model_digraph, self._augmented_condenced_model_digraph, - self._node_varlist_mapping + self._node_varlist_mapping, ) = self._block_analyze_model() self._sim_code, self._blocks = self._gen_sim_code_and_blocks() - print('Finished') - + print("Finished") def find_endo_var(self, endo_var: str, noisy=False): """ @@ -576,8 +646,7 @@ def find_endo_var(self, endo_var: str, noisy=False): else: return block[0] else: - raise IndexError(f'{endo_var} is not endogenous in model') - + raise IndexError(f"{endo_var} is not endogenous in model") def describe(self): """ @@ -591,13 +660,18 @@ def describe(self): None """ - print('-'*100) - print(f'Model consists of {len(self.eqns)} equations in {len(self._blocks)} blocks') - print(f'{len([val[3] for _, val in self._blocks.items() if val[3]])} of the blocks consist of simple definitions\n') - for key, val in Counter(sorted([len(val[2]) for _, val in self._blocks.items()])).items(): - print(f'{val} blocks have {key} equations') - print('-'*100) - + print("-" * 100) + print( + f"Model consists of {len(self.eqns)} equations in {len(self._blocks)} blocks" + ) + print( + f"{len([val[3] for _, val in self._blocks.items() if val[3]])} of the blocks consist of simple definitions\n" + ) + for key, val in Counter( + sorted([len(val[2]) for _, val in self._blocks.items()]) + ).items(): + print(f"{val} blocks have {key} equations") + print("-" * 100) def show_blocks(self): """ @@ -663,10 +737,9 @@ def show_blocks(self): """ for key, _ in self._blocks.items(): - print(' '.join(['-'*50, 'Block', str(key), '-'*50])) + print(" ".join(["-" * 50, "Block", str(key), "-" * 50])) self.show_block(key) - def show_block(self, i: int): """ Prints endogenous and exogenous variables and equations for a given block. @@ -709,16 +782,37 @@ def show_block(self, i: int): block = self._blocks.get(i) if block: - print(' '.join(['Block consists of', 'a definition' if block[3] else 'an equation or a system of equations'])) - print(f'\n{len(block[0])} endogenous variables:') - print('\n'.join([' '.join(x) for x in list(self._chunks(block[0], 25))])) - print(f'\n{len(block[1])} predetermined variables:') - print('\n'.join([' '.join(x) for x in list(self._chunks([self._var_mapping.get(x) for x in block[1]], 25))])) - print(f'\n{len(block[2])} equations:') - print('\n'.join(block[2])) + print( + " ".join( + [ + "Block consists of", + ( + "a definition" + if block[3] + else "an equation or a system of equations" + ), + ] + ) + ) + print(f"\n{len(block[0])} endogenous variables:") + print("\n".join([" ".join(x) for x in list(self._chunks(block[0], 25))])) + print(f"\n{len(block[1])} predetermined variables:") + print( + "\n".join( + [ + " ".join(x) + for x in list( + self._chunks( + [self._var_mapping.get(x) for x in block[1]], 25 + ) + ) + ] + ) + ) + print(f"\n{len(block[2])} equations:") + print("\n".join(block[2])) else: - raise IndexError(f'block {i} is not in model') - + raise IndexError(f"block {i} is not in model") def solve_model(self, input_df: pd.DataFrame, jit=True) -> pd.DataFrame: """ @@ -753,29 +847,36 @@ def solve_model(self, input_df: pd.DataFrame, jit=True) -> pd.DataFrame: if self._some_error: return - if all(np.issubdtype(input_df[x].dtype, np.number) for x in input_df.columns) is False: - raise TypeError('all columns in input_df must be numeric') + if ( + all(np.issubdtype(input_df[x].dtype, np.number) for x in input_df.columns) + is False + ): + raise TypeError("all columns in input_df must be numeric") - print('-'*100) - print('Solving model') + print("-" * 100) + print("Solving model") output_df = input_df.copy(deep=True).astype(float) output_array = output_df.to_numpy(dtype=np.float64) - var_col_index = {var: i for i, var in enumerate(output_df.columns.str.lower().to_list())} + var_col_index = { + var: i for i, var in enumerate(output_df.columns.str.lower().to_list()) + } get_var_info = cache(self.gen_get_var_info(var_col_index)) - first_period, last_period = self._max_lag, output_array.shape[0]-1 - periods = range(first_period, last_period+1) - print(f'\tFirst period: {output_df.index[first_period]}, last period: {output_df.index[last_period]}') - print('\tSolving') - print(''.join(['\t|', ' '*(last_period-first_period+1), '|'])) - print('\t ', end='') + first_period, last_period = self._max_lag, output_array.shape[0] - 1 + periods = range(first_period, last_period + 1) + print( + f"\tFirst period: {output_df.index[first_period]}, last period: {output_df.index[last_period]}" + ) + print("\tSolving") + print("".join(["\t|", " " * (last_period - first_period + 1), "|"])) + print("\t ", end="") warnings = [] for period in periods: - print('.', end='') + print(".", end="") for key, val in self._sim_code.items(): def_fun, obj_fun, jac, endo_vars, pred_vars, _ = val solution = self._solve_block( @@ -786,122 +887,114 @@ def solve_model(self, input_df: pd.DataFrame, jit=True) -> pd.DataFrame: get_var_info(pred_vars), output_array, period, - jit=jit + jit=jit, ) - output_array[period, [var_col_index.get(x) for x in endo_vars]] = solution.get('x') + output_array[period, [var_col_index.get(x) for x in endo_vars]] = ( + solution.get("x") + ) - if solution.get('status') == 1: - warnings += f'Maximum number of iterations reached for block {key} in {input_df.index[period]}', - if solution.get('status') == 2: + if solution.get("status") == 1: + warnings += ( + f"Maximum number of iterations reached for block {key} in {input_df.index[period]}", + ) + if solution.get("status") == 2: break else: continue break if len(warnings) > 0: - print('\n') - print('\n'.join(warnings)) - print(f'Consider increasing max_iter from {self._max_iter}') + print("\n") + print("\n".join(warnings)) + print(f"Consider increasing max_iter from {self._max_iter}") self._last_solution = output_df - if solution.get('status') == 2: - print(f'\nFailed to solve block {key} in {input_df.index[period]}') + if solution.get("status") == 2: + print(f"\nFailed to solve block {key} in {input_df.index[period]}") self.show_block_vals(key, period) self.trace_to_exog_vals(key, period) else: - print('\nFinished') - - print('-'*100) + print("\nFinished") - return output_df.iloc[self.max_lag:, :] + print("-" * 100) + return output_df.iloc[self.max_lag :, :] # Solves one block of the model for a given time period - def _solve_block(self, - def_fun, - obj_fun, - jac, - endo_vars_info, - pred_vars_info, - output_array, - period, - jit - ): - _, endo_vars_lags, endo_vars_cols, = endo_vars_info - _, pred_vars_lags, pred_vars_cols, = pred_vars_info + def _solve_block( + self, + def_fun, + obj_fun, + jac, + endo_vars_info, + pred_vars_info, + output_array, + period, + jit, + ): + ( + _, + endo_vars_lags, + endo_vars_cols, + ) = endo_vars_info + ( + _, + pred_vars_lags, + pred_vars_cols, + ) = pred_vars_info # If block contains a definition this is calculated # Othwewise the objective function is sent to Newton-Raphson if def_fun: solution = {} try: - solution['x'] = def_fun( + solution["x"] = def_fun( tuple( self._get_vals( - output_array, - pred_vars_cols, - pred_vars_lags, - period, - jit + output_array, pred_vars_cols, pred_vars_lags, period, jit ) ) ) - solution['status'] = 0 + solution["status"] = 0 except ZeroDivisionError: - solution['x'] = np.nan - solution['status'] = 2 + solution["x"] = np.nan + solution["status"] = 2 else: solution = self._newton_raphson( obj_fun, self._get_vals( - output_array, - endo_vars_cols, - endo_vars_lags, - period, - jit + output_array, endo_vars_cols, endo_vars_lags, period, jit ), - args = tuple( + args=tuple( self._get_vals( - output_array, - pred_vars_cols, - pred_vars_lags, - period, - jit + output_array, pred_vars_cols, pred_vars_lags, period, jit ) ), - jac = jac, - tol = self._root_tolerance, - maxiter=self.max_iter + jac=jac, + tol=self._root_tolerance, + maxiter=self.max_iter, ) - if all(np.isfinite(solution.get('x'))) is False: - solution['status'] = 2 + if all(np.isfinite(solution.get("x"))) is False: + solution["status"] = 2 return solution - # Gets values from DataFrame via array view for speed # If shape of request > 0 then the request is sent to njit'ed method for speed - def _get_vals(self, - array, - cols, - lags, - period, - jit - ): + def _get_vals(self, array, cols, lags, period, jit): if cols.shape[0] == 0: return np.array([], np.float64) - if any([period-x < 0 for x in lags]): - raise IndexError('period is out of range') + if any([period - x < 0 for x in lags]): + raise IndexError("period is out of range") else: if jit: return self._get_vals_jit(array, cols, lags, period) else: return self._get_vals_nojit(array, cols, lags, period) - # Gets values from DataFrame via array view # Some weird stuff had to be implemented for njit to stop complaining # Not sure if njit increases efficiency @@ -910,20 +1003,18 @@ def _get_vals(self, def _get_vals_jit(array: np.array, cols: np.array, lags: np.array, period: int): vals = np.array([0.0], dtype=np.float64) for col, lag in zip(cols, lags): - vals = np.append(vals, array[period-lag, col]) + vals = np.append(vals, array[period - lag, col]) return vals[1:] - # Gets values from DataFrame via array view # Runs if user sets jit to False @staticmethod def _get_vals_nojit(array: np.array, cols: np.array, lags: np.array, period: int): vals = np.array([], dtype=np.float64) for col, lag in zip(cols, lags): - vals = np.append(vals, array[period-lag, col]) + vals = np.append(vals, array[period - lag, col]) return vals - # Solves root finding problem using simple Newton-Raphson method @staticmethod def _newton_raphson(f, init, args=None, jac=None, tol=None, maxiter=None): @@ -942,8 +1033,10 @@ def _newton_raphson(f, init, args=None, jac=None, tol=None, maxiter=None): status = 2 break try: - x_i_new = x_i-np.matmul(np.linalg.inv(np.array(jac(x_i.tolist(), *args))), f_i) - if np.max(np.abs(x_i_new-x_i)) <= tol: + x_i_new = x_i - np.matmul( + np.linalg.inv(np.array(jac(x_i.tolist(), *args))), f_i + ) + if np.max(np.abs(x_i_new - x_i)) <= tol: break x_i = x_i_new except np.linalg.LinAlgError: @@ -953,16 +1046,16 @@ def _newton_raphson(f, init, args=None, jac=None, tol=None, maxiter=None): f_i = np.array(f(x_i, *args)) i += 1 - return {'x': x_i, 'fun': f_i, 'success': success, 'status': status} - + return {"x": x_i, "fun": f_i, "success": success, "status": status} def draw_blockwise_graph( - self, var: str, - max_ancs_gens: int=5, - max_desc_gens: int=5, - max_nodes: int=50, - figsize=(7.5, 7.5) - ): + self, + var: str, + max_ancs_gens: int = 5, + max_desc_gens: int = 5, + max_nodes: int = 50, + figsize=(7.5, 7.5), + ): """ Draws a directed graph of a block containing the given variable with a limited number of ancestors and descendants. @@ -1003,82 +1096,127 @@ def draw_blockwise_graph( ancs_nodes = nx.ancestors(self._augmented_condenced_model_digraph, var_node) desc_nodes = nx.descendants(self._augmented_condenced_model_digraph, var_node) - max_ancr_nodes = {x for x in ancs_nodes if nx.shortest_path_length(self._augmented_condenced_model_digraph, x, var_node) <= max_ancs_gens} - max_desc_nodes = {x for x in desc_nodes if nx.shortest_path_length(self._augmented_condenced_model_digraph, var_node, x) <= max_desc_gens} + max_ancr_nodes = { + x + for x in ancs_nodes + if nx.shortest_path_length( + self._augmented_condenced_model_digraph, x, var_node + ) + <= max_ancs_gens + } + max_desc_nodes = { + x + for x in desc_nodes + if nx.shortest_path_length( + self._augmented_condenced_model_digraph, var_node, x + ) + <= max_desc_gens + } - subgraph = self._augmented_condenced_model_digraph.subgraph({var_node}.union(max_ancr_nodes).union(max_desc_nodes)) + subgraph = self._augmented_condenced_model_digraph.subgraph( + {var_node}.union(max_ancr_nodes).union(max_desc_nodes) + ) graph_to_plot = nx.DiGraph() - print(' '.join([ - f'Graph of block containing {var} with <={max_ancs_gens} generations of ancestors and <={max_desc_gens} generations of decendants:', - str(subgraph) - ])) + print( + " ".join( + [ + f"Graph of block containing {var} with <={max_ancs_gens} generations of ancestors and <={max_desc_gens} generations of decendants:", + str(subgraph), + ] + ) + ) # Loop over all nodes in subgraph (chosen variable, it's ancestors and decendants) and make nodes and edges in pyvis subgraph mapping = {} for node in subgraph.nodes(): if node in self._condenced_model_digraph: - node_label = '\n'.join(self._node_varlist_mapping[node])\ - if len(self._node_varlist_mapping[node]) < 10 else '***\nHUGE BLOCK\n***' - node_title = '
'.join(self._node_varlist_mapping[node]) + node_label = ( + "\n".join(self._node_varlist_mapping[node]) + if len(self._node_varlist_mapping[node]) < 10 + else "***\nHUGE BLOCK\n***" + ) + node_title = "
".join(self._node_varlist_mapping[node]) if node == var_node: node_size = 200 - node_color = '#c4351c' + node_color = "#c4351c" if node in max_ancr_nodes: node_size = 100 - node_color = '#00824d' + node_color = "#00824d" if node in max_desc_nodes: node_size = 100 - node_color = '#006cb6' + node_color = "#006cb6" else: node_label = None node_title = None node_size = 100 - node_color = '#6f9090' - - graph_to_plot.add_node(node, label=node_label, title=node_title, shape='circle', size=node_size, color=node_color) + node_color = "#6f9090" + + graph_to_plot.add_node( + node, + label=node_label, + title=node_title, + shape="circle", + size=node_size, + color=node_color, + ) if isinstance(node, int): - mapping[node] = ':\n'.join([' '.join(['Block', str(len(self._blocks)-node)]), - '\n'.join(self._node_varlist_mapping[node]) if len(self._node_varlist_mapping[node]) < 5 else '...']) + mapping[node] = ":\n".join( + [ + " ".join(["Block", str(len(self._blocks) - node)]), + ( + "\n".join(self._node_varlist_mapping[node]) + if len(self._node_varlist_mapping[node]) < 5 + else "..." + ), + ] + ) else: mapping[node] = node if graph_to_plot.number_of_nodes() > max_nodes: - print('Graph is too big to meaningfully plot') + print("Graph is too big to meaningfully plot") return graph_to_plot.add_edges_from(subgraph.edges()) plt.figure(figsize=figsize) - colors = [node[1]['color'] for node in graph_to_plot.nodes(data=True)] + colors = [node[1]["color"] for node in graph_to_plot.nodes(data=True)] layout = nx.shell_layout(graph_to_plot) - nx.draw(graph_to_plot, - with_labels=True, - labels=mapping, - pos=layout, - node_size=5000, - node_color=colors, - font_size=9, - font_color='white', - arrowsize=25, - edge_color='#274247', - width=2.0 - ) + nx.draw( + graph_to_plot, + with_labels=True, + labels=mapping, + pos=layout, + node_size=5000, + node_color=colors, + font_size=9, + font_color="white", + arrowsize=25, + edge_color="#274247", + width=2.0, + ) plt.plot() - # Returns the node in which var is endogenous def _find_var_node(self, var): - if any([var in self._condenced_model_digraph.nodes[x]['members'] for x in self._condenced_model_digraph.nodes()]): - var_node = [var in self._condenced_model_digraph.nodes[x]['members'] for x in self._condenced_model_digraph.nodes()].index(True) - elif var in self._augmented_condenced_model_digraph.nodes(): + if any( + [ + var in self._condenced_model_digraph.nodes[x]["members"] + for x in self._condenced_model_digraph.nodes() + ] + ): + var_node = [ + var in self._condenced_model_digraph.nodes[x]["members"] + for x in self._condenced_model_digraph.nodes() + ].index(True) + elif var in self._augmented_condenced_model_digraph.nodes(): var_node = var else: - raise NameError('variable is not in model') + raise NameError("variable is not in model") return var_node - def trace_to_exog_vars(self, i: str, noisy=True): """ Prints all exogenous variables that are ancestors to the given block. @@ -1110,19 +1248,25 @@ def trace_to_exog_vars(self, i: str, noisy=True): return if noisy: - print('\n'.join([' '.join(x) for x in list(self._chunks(self._trace_to_exog_vars(i), 10))])) + print( + "\n".join( + [ + " ".join(x) + for x in list(self._chunks(self._trace_to_exog_vars(i), 10)) + ] + ) + ) else: return self._trace_to_exog_vars(i) - ## Finds all exogenous variables that are ancestors to block def _trace_to_exog_vars(self, i): if i < 1: - raise IndexError('block must be >=1') + raise IndexError("block must be >=1") - var_node = len(self._blocks)-i + var_node = len(self._blocks) - i if var_node < 0: - raise IndexError(f'block {i} is not in model') + raise IndexError(f"block {i} is not in model") ancs_nodes = nx.ancestors(self._augmented_condenced_model_digraph, var_node) @@ -1133,7 +1277,6 @@ def _trace_to_exog_vars(self, i): return [x for x in ancs_exog_vars if x not in self.endo_vars] - def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): """ Traces the given block back to exogenous values and prints those values. @@ -1167,23 +1310,41 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): try: output_array = self._last_solution.to_numpy(dtype=np.float64, copy=True) - var_col_index = {var: i for i, var in enumerate(self._last_solution.columns.str.lower().to_list())} + var_col_index = { + var: i + for i, var in enumerate( + self._last_solution.columns.str.lower().to_list() + ) + } get_var_info = self.gen_get_var_info(var_col_index) ancs_exog_vars = self._trace_to_exog_vars(i) if ancs_exog_vars: - _, ancs_exog_lags, ancs_exog_cols, = get_var_info((self._var_mapping.get(x) for x in ancs_exog_vars)) - ancs_exog_vals = self._get_vals(output_array, ancs_exog_cols, ancs_exog_lags, period_index, False) + ( + _, + ancs_exog_lags, + ancs_exog_cols, + ) = get_var_info((self._var_mapping.get(x) for x in ancs_exog_vars)) + ancs_exog_vals = self._get_vals( + output_array, ancs_exog_cols, ancs_exog_lags, period_index, False + ) if noisy: - print(f'\nBlock {i} traces back to the following exogenous variable values in {self._last_solution.index[period_index]}:') - print(*['='.join([x, str(y)]) for x, y in zip(ancs_exog_vars, ancs_exog_vals)], sep='\n') + print( + f"\nBlock {i} traces back to the following exogenous variable values in {self._last_solution.index[period_index]}:" + ) + print( + *[ + "=".join([x, str(y)]) + for x, y in zip(ancs_exog_vars, ancs_exog_vals) + ], + sep="\n", + ) else: return pd.Series(ancs_exog_vals, index=ancs_exog_vars) except AttributeError: - raise RuntimeError('no solution exists') - + raise RuntimeError("no solution exists") def show_block_vals(self, i: int, period_index: int, noisy=True): """ @@ -1222,31 +1383,67 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): try: output_array = self._last_solution.to_numpy(dtype=np.float64, copy=True) - var_col_index = {var: i for i, var in enumerate(self._last_solution.columns.str.lower().to_list())} + var_col_index = { + var: i + for i, var in enumerate( + self._last_solution.columns.str.lower().to_list() + ) + } get_var_info = self.gen_get_var_info(var_col_index) block = self._blocks.get(i) _, block_endo_lags, block_endo_cols = get_var_info(block[0]) - block_endo_vals = self._get_vals(output_array, block_endo_cols, block_endo_lags, period_index, False) + block_endo_vals = self._get_vals( + output_array, block_endo_cols, block_endo_lags, period_index, False + ) _, block_pred_lags, block_pred_cols = get_var_info(block[1]) - block_pred_vals = self._get_vals(output_array, block_pred_cols, block_pred_lags, period_index, False) + block_pred_vals = self._get_vals( + output_array, block_pred_cols, block_pred_lags, period_index, False + ) if noisy: - print(f'\nBlock {i} has endogenous variables in {self._last_solution.index[period_index]} that evaluate to:') - print(*['='.join([x, str(y)]) for x, y in zip([self._var_mapping.get(x) for x in block[0]], block_endo_vals)], sep='\n') - print(f'\nBlock {i} has predetermined variables in {self._last_solution.index[period_index]} that evaluate to:') - print(*['='.join([x, str(y)]) for x, y in zip([self._var_mapping.get(x) for x in block[1]], block_pred_vals)], sep='\n') + print( + f"\nBlock {i} has endogenous variables in {self._last_solution.index[period_index]} that evaluate to:" + ) + print( + *[ + "=".join([x, str(y)]) + for x, y in zip( + [self._var_mapping.get(x) for x in block[0]], + block_endo_vals, + ) + ], + sep="\n", + ) + print( + f"\nBlock {i} has predetermined variables in {self._last_solution.index[period_index]} that evaluate to:" + ) + print( + *[ + "=".join([x, str(y)]) + for x, y in zip( + [self._var_mapping.get(x) for x in block[1]], + block_pred_vals, + ) + ], + sep="\n", + ) else: return ( - pd.Series(block_endo_vals, index=[self._var_mapping.get(x) for x in block[0]]), - pd.Series(block_pred_vals, index=[self._var_mapping.get(x) for x in block[1]]) + pd.Series( + block_endo_vals, + index=[self._var_mapping.get(x) for x in block[0]], + ), + pd.Series( + block_pred_vals, + index=[self._var_mapping.get(x) for x in block[1]], + ), ) except AttributeError: - raise RuntimeError('no solution exists') - + raise RuntimeError("no solution exists") # Function that returns function that returns names, columns and lags for variables def gen_get_var_info(self, var_col_index): @@ -1254,16 +1451,18 @@ def get_var_info(vars): if not vars: return (tuple([]), np.array([], dtype=int), np.array([], dtype=int)) # Stole zip-solution from: https://stackoverflow.com/questions/21444338/transpose-nested-list-in-python - names, lags = tuple(map(list, zip(*[self._lag_mapping.get(x) for x in vars]))) + names, lags = tuple( + map(list, zip(*[self._lag_mapping.get(x) for x in vars])) + ) cols = tuple(var_col_index.get(x) for x in names) if any(x is None for x in cols): missing = [x for x, y in zip(names, cols) if y is None] raise KeyError(f'{",".join(missing)} is not in DataFrame') return (names, np.array(lags, dtype=int), np.array(cols, dtype=int)) - return get_var_info + return get_var_info - def sensitivity(self, i: int, period_index: int, method='std', exog_subset=None): + def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None): """ Analyses sensitivity of endogenous variables to exogenous variables for a specific period. @@ -1308,9 +1507,14 @@ def sensitivity(self, i: int, period_index: int, method='std', exog_subset=None) return try: - var_col_index = {var: i for i, var in enumerate(self._last_solution.columns.str.lower().to_list())} + var_col_index = { + var: i + for i, var in enumerate( + self._last_solution.columns.str.lower().to_list() + ) + } except AttributeError: - raise AttributeError('no solution exists') + raise AttributeError("no solution exists") get_var_info = cache(self.gen_get_var_info(var_col_index)) @@ -1325,25 +1529,40 @@ def sensitivity(self, i: int, period_index: int, method='std', exog_subset=None) result = {} div = min(10, n_exog_vars) - print(f'Analysing sensitivity for block {i} in period {self._last_solution.index[period_index]}') - print(f'Number exogeneous variables to analyse: {len(exog_vars)}') - print(''.join(['\t|', ' '*sum([j % int(n_exog_vars/div) == 0 for j in range(len(exog_vars))]), '|'])) - print('\t ', end='') + print( + f"Analysing sensitivity for block {i} in period {self._last_solution.index[period_index]}" + ) + print(f"Number exogeneous variables to analyse: {len(exog_vars)}") + print( + "".join( + [ + "\t|", + " " + * sum( + [j % int(n_exog_vars / div) == 0 for j in range(len(exog_vars))] + ), + "|", + ] + ) + ) + print("\t ", end="") for j, exog_var in enumerate(exog_vars): - if j % int(n_exog_vars/div) == 0: - print('.', end='') + if j % int(n_exog_vars / div) == 0: + print(".", end="") var, lag = self._lag_mapping.get(self._var_mapping.get(exog_var)) solution_diff = self._last_solution.copy() - if method == 'std': - solution_diff[var].iloc[period_index-lag] += solution_diff[var].std() - elif method == 'pct': - solution_diff[var].iloc[period_index-lag] += solution_diff[var].iloc[period_index-lag]*0.01 - elif method == 'one': - solution_diff[var].iloc[period_index-lag] += 1 + if method == "std": + solution_diff[var].iloc[period_index - lag] += solution_diff[var].std() + elif method == "pct": + solution_diff[var].iloc[period_index - lag] += ( + solution_diff[var].iloc[period_index - lag] * 0.01 + ) + elif method == "one": + solution_diff[var].iloc[period_index - lag] += 1 else: - raise ValueError('method must be std, pct or one') + raise ValueError("method must be std, pct or one") output_array = solution_diff.to_numpy(dtype=np.float64) @@ -1358,23 +1577,24 @@ def sensitivity(self, i: int, period_index: int, method='std', exog_subset=None) get_var_info(pred_vars), output_array, period_index, - jit=False + jit=False, ) - output_array[period_index, [var_col_index.get(x) for x in endo_vars]] = solution.get('x') + output_array[ + period_index, [var_col_index.get(x) for x in endo_vars] + ] = solution.get("x") if key == i: - result[exog_var] = solution.get('x') + result[exog_var] = solution.get("x") break return ( pd.DataFrame(result, index=endo_vars).T - -self._last_solution[list(endo_vars)].iloc[period_index] + - self._last_solution[list(endo_vars)].iloc[period_index] ) - # Stole solution from https://stackoverflow.com/questions/312443/how-do-i-split-a-list-into-equally-sized-chunks @staticmethod def _chunks(xs, n): n = max(1, n) - return (xs[i:i+n] for i in range(0, len(xs), n)) + return (xs[i : i + n] for i in range(0, len(xs), n)) diff --git a/tests/test_model_solver.py b/tests/test_model_solver.py index 95cdc91..ba714f9 100644 --- a/tests/test_model_solver.py +++ b/tests/test_model_solver.py @@ -5,41 +5,48 @@ import numpy as np # Insert the path to your project root directly in the test file -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '../src'))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../src"))) # Import the model_solver module correctly import model_solver as ms + # Fixtures for test data @pytest.fixture def equations(): return [ - 'x1 = a1', - 'x2 = a2', - '0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1', - '0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2', - 'k1 = k1(-1)+i1', - 'k2 = k2(-1)+i2' + "x1 = a1", + "x2 = a2", + "0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1", + "0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2", + "k1 = k1(-1)+i1", + "k2 = k2(-1)+i2", ] + @pytest.fixture def endogenous(): - return ['x1', 'x2', 'ca', 'cb', 'k1', 'k2'] + return ["x1", "x2", "ca", "cb", "k1", "k2"] + @pytest.fixture def input_data(): - return pd.DataFrame({ - 'x1': [2, 4, 1, 2], - 'x2': [2, 1, 2, 3], - 'ca': [1, 3, 4, 1], - 'cb': [1, 2, 1, 4], - 'k1': [1, 3, 4, 1], - 'k2': [1, 2, 1, 4], - 'a1': [1, 2, 4, 4], - 'a2': [3, 2, 3, 4], - 'i1': [1, 2, 4, 4], - 'i2': [3, 2, 3, 4] - }, index=['2019Q1', '2019Q2', '2020Q3', '2020Q4']) + return pd.DataFrame( + { + "x1": [2, 4, 1, 2], + "x2": [2, 1, 2, 3], + "ca": [1, 3, 4, 1], + "cb": [1, 2, 1, 4], + "k1": [1, 3, 4, 1], + "k2": [1, 2, 1, 4], + "a1": [1, 2, 4, 4], + "a2": [3, 2, 3, 4], + "i1": [1, 2, 4, 4], + "i2": [3, 2, 3, 4], + }, + index=["2019Q1", "2019Q2", "2020Q3", "2020Q4"], + ) + # Test for model initialization def test_model_initialization(equations, endogenous): @@ -47,6 +54,7 @@ def test_model_initialization(equations, endogenous): assert model.eqns == tuple([eq.lower() for eq in equations]) assert model.endo_vars == tuple([var.lower() for var in endogenous]) + # Test for block identification def test_show_blocks(equations, endogenous): model = ms.ModelSolver(equations, endogenous) @@ -54,6 +62,7 @@ def test_show_blocks(equations, endogenous): # Assuming the blocks are stored in an internal structure assert len(model._blocks) == 5 # Check that 5 blocks are identified + # Test solving the model def test_solve_model(equations, endogenous, input_data): model = ms.ModelSolver(equations, endogenous) @@ -67,65 +76,65 @@ def test_solve_model(equations, endogenous, input_data): # Validating expected data in the solution for the last 3 periods (2019Q2, 2020Q3, 2020Q4) expected_values = { - 'x1': [2.0, 4.0, 4.0], - 'x2': [2.0, 3.0, 4.0], - 'ca': [1.942857, 3.857143, 3.885714], - 'cb': [1.257143, 1.642857, 2.514286], - 'k1': [3.0, 7.0, 11.0], - 'k2': [3.0, 6.0, 10.0], - 'a1': [2.0, 4.0, 4.0], - 'a2': [2.0, 3.0, 4.0], - 'i1': [2.0, 4.0, 4.0], - 'i2': [2.0, 3.0, 4.0], + "x1": [2.0, 4.0, 4.0], + "x2": [2.0, 3.0, 4.0], + "ca": [1.942857, 3.857143, 3.885714], + "cb": [1.257143, 1.642857, 2.514286], + "k1": [3.0, 7.0, 11.0], + "k2": [3.0, 6.0, 10.0], + "a1": [2.0, 4.0, 4.0], + "a2": [2.0, 3.0, 4.0], + "i1": [2.0, 4.0, 4.0], + "i2": [2.0, 3.0, 4.0], } tolerance = 1e-6 # Small tolerance for floating-point comparisons for col, values in expected_values.items(): assert solution[col].tolist() == pytest.approx(values, rel=tolerance) + # Test switching endogenous variables def test_switch_endo_vars(equations, endogenous): model = ms.ModelSolver(equations, endogenous) - model.switch_endo_vars(['x2'], ['a2']) - assert 'x2' not in model.endo_vars - assert 'a2' in model.endo_vars + model.switch_endo_vars(["x2"], ["a2"]) + assert "x2" not in model.endo_vars + assert "a2" in model.endo_vars model.show_blocks() # Ensure the model is reconfigured after switching variables + # Test tracing to exogenous variables def test_trace_to_exog_vars(equations, endogenous): model = ms.ModelSolver(equations, endogenous) exog_vars = model.trace_to_exog_vars(5, noisy=False) - expected_exog_vars = ['i1', 'i2', 'a1', 'a2'] + expected_exog_vars = ["i1", "i2", "a1", "a2"] assert sorted(exog_vars) == sorted(expected_exog_vars) + # Test tracing to exogenous values def test_trace_to_exog_vals(equations, endogenous, input_data): model = ms.ModelSolver(equations, endogenous) solution = model.solve_model(input_data) exog_vals = model.trace_to_exog_vals(5, period_index=1, noisy=False) - expected_exog_vals = pd.Series({ - 'i1': 2.0, - 'i2': 2.0, - 'a1': 2.0, - 'a2': 2.0 - }).sort_index() + expected_exog_vals = pd.Series( + {"i1": 2.0, "i2": 2.0, "a1": 2.0, "a2": 2.0} + ).sort_index() exog_vals = exog_vals.sort_index() # Sort before comparison - + pd.testing.assert_series_equal(exog_vals, expected_exog_vals, rtol=1e-6) + # Test showing block values def test_show_block_vals(equations, endogenous, input_data): model = ms.ModelSolver(equations, endogenous) model.solve_model(input_data) endo_vals, pred_vals = model.show_block_vals(5, 1, noisy=False) - + # Ensure that the endo_vals and pred_vals match expected results from the notebook - expected_endo_vals = pd.Series({'ca': 1.942857, 'cb': 1.257143}) - expected_pred_vals = pd.Series({'i1': 2.0, 'i2': 2.0, 'x1': 2.0, 'x2': 2.0}) - + expected_endo_vals = pd.Series({"ca": 1.942857, "cb": 1.257143}) + expected_pred_vals = pd.Series({"i1": 2.0, "i2": 2.0, "x1": 2.0, "x2": 2.0}) + endo_vals = endo_vals.sort_index() # Sort before comparison pred_vals = pred_vals.sort_index() # Sort before comparison - + pd.testing.assert_series_equal(endo_vals, expected_endo_vals, rtol=1e-6) pd.testing.assert_series_equal(pred_vals, expected_pred_vals, rtol=1e-6) - From c7fb2b130579abba4758115a33dc48b9fc6cc6f8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Fri, 6 Sep 2024 16:12:21 +0200 Subject: [PATCH 03/22] ruff autofixes --- pyproject.toml | 2 +- src/model_solver/model_solver.py | 88 +++++++++++++------------------- tests/test_model_solver.py | 6 +-- 3 files changed, 39 insertions(+), 57 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 31921f3..5a5d992 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -86,7 +86,7 @@ extend-exclude = [ [tool.ruff.lint] select = [ "A", # prevent using keywords that clobber python builtins - "ANN", # check type annotations +# "ANN", # check type annotations "B", # bugbear: security warnings "D", # documentation "E", # pycodestyle diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 0287818..9c4b7e3 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -4,19 +4,23 @@ # mkh@ssb.no/magnus.helliesen@gmail.com # ######################################### -import numpy as np -import networkx as nx -import pandas as pd -from symengine import var, Matrix, Lambdify, Max, Min, log, exp -import matplotlib.pyplot as plt from collections import Counter from functools import cache + +import matplotlib.pyplot as plt +import networkx as nx +import numpy as np +import pandas as pd from numba import njit +from symengine import Lambdify +from symengine import Matrix +from symengine import Max +from symengine import var class ModelSolver: - """ - ModelSolver is designed to handle and solve mathematical models represented by a system of equations. + """ModelSolver is designed to handle and solve mathematical models represented by a system of equations. + It supports various mathematical functions such as min, max, log, and exp. This class allows you to initialize a model with a list of equations and endogenous variables. It subsequently solves the model using input data stored in a Pandas DataFrame. @@ -50,12 +54,12 @@ class ModelSolver: Now, "solution_df" is a Pandas DataFrame with the same dimensions as "input_df," but with the endogenous variables replaced by the solutions to the model. The last solution is also stored in "model.last_solution." - Attributes + Attributes: ---------- last_solution : pandas DataFrame The last solved solution. - Methods + Methods: ------- solve_model(input_df) Solves the model based on input data in a Pandas DataFrame. @@ -561,8 +565,7 @@ def _gen_def_or_obj_fun_and_jac( return None, obj_fun_out, jac_out def switch_endo_vars(self, old_endo_vars: list[str], new_endo_vars: list[str]): - """ - Sets old_endo_vars as exogenous and new_endo_vars as endogenous and performs block analysis. + """Sets old_endo_vars as exogenous and new_endo_vars as endogenous and performs block analysis. Parameters: ---------- @@ -591,7 +594,6 @@ def switch_endo_vars(self, old_endo_vars: list[str], new_endo_vars: list[str]): >>> model = ModelSolver(equations, endogenous) >>> model.switch_endo_vars(['var1', 'var2'], ['var3', 'var4']) """ - if all(x in self.endo_vars for x in old_endo_vars) is False: raise RuntimeError("all variables in old_endo_vars are not endogenous") if any(x in self.endo_vars for x in new_endo_vars): @@ -615,8 +617,7 @@ def switch_endo_vars(self, old_endo_vars: list[str], new_endo_vars: list[str]): print("Finished") def find_endo_var(self, endo_var: str, noisy=False): - """ - Find the block that solves the specified endogenous variable. + """Find the block that solves the specified endogenous variable. Parameters ---------- @@ -626,19 +627,18 @@ def find_endo_var(self, endo_var: str, noisy=False): noisy : bool, optional Whether output should be printed or returned. - Returns + Returns: ------- str or None The name of the block that solves the specified endogenous variable. Returns None if the endogenous variable is not found in any block. - Notes + Notes: ----- This function searches for the specified endogenous variable in the model's blocks and returns the name of the block that solves it. If the endogenous variable is not found in any block, it returns None. """ - block = [key for key, val in self._blocks.items() if endo_var.lower() in val[0]] if block: if noisy: @@ -649,17 +649,15 @@ def find_endo_var(self, endo_var: str, noisy=False): raise IndexError(f"{endo_var} is not endogenous in model") def describe(self): - """ - Display a summary of the model's characteristics. + """Display a summary of the model's characteristics. Prints information about the model, including the number of equations, blocks, simple definition blocks, and the distribution of equation counts in the blocks. - Returns + Returns: ------- None """ - print("-" * 100) print( f"Model consists of {len(self.eqns)} equations in {len(self._blocks)} blocks" @@ -674,8 +672,7 @@ def describe(self): print("-" * 100) def show_blocks(self): - """ - Prints endogenous and exogenous variables and equations for every block in the model. + """Prints endogenous and exogenous variables and equations for every block in the model. Iterates through all blocks in the model and calls the `show_block` function to display their details. @@ -735,14 +732,12 @@ def show_blocks(self): - eqn_n1: var_n1 = exog_var_n1 + exog_var_n2 - eqn_n2: var_n2 = var_n1 + exog_var_n2 """ - for key, _ in self._blocks.items(): print(" ".join(["-" * 50, "Block", str(key), "-" * 50])) self.show_block(key) def show_block(self, i: int): - """ - Prints endogenous and exogenous variables and equations for a given block. + """Prints endogenous and exogenous variables and equations for a given block. Parameters: ----------- @@ -778,7 +773,6 @@ def show_block(self, i: int): - eqn3: var3 = pred_var2 + pred_var3 - eqn4: var4 = var3 + pred_var1 """ - block = self._blocks.get(i) if block: @@ -815,8 +809,7 @@ def show_block(self, i: int): raise IndexError(f"block {i} is not in model") def solve_model(self, input_df: pd.DataFrame, jit=True) -> pd.DataFrame: - """ - Solves the model subject to a given DataFrame. + """Solves the model subject to a given DataFrame. Parameters: ----------- @@ -843,7 +836,6 @@ def solve_model(self, input_df: pd.DataFrame, jit=True) -> pd.DataFrame: >>> input_data = pd.DataFrame({'var1': [1.0, 2.0, 3.0], 'var2': [0.5, 1.0, 1.5]}) >>> output_data = model.solve_model(input_data) """ - if self._some_error: return @@ -1002,7 +994,7 @@ def _get_vals(self, array, cols, lags, period, jit): @njit def _get_vals_jit(array: np.array, cols: np.array, lags: np.array, period: int): vals = np.array([0.0], dtype=np.float64) - for col, lag in zip(cols, lags): + for col, lag in zip(cols, lags, strict=False): vals = np.append(vals, array[period - lag, col]) return vals[1:] @@ -1011,7 +1003,7 @@ def _get_vals_jit(array: np.array, cols: np.array, lags: np.array, period: int): @staticmethod def _get_vals_nojit(array: np.array, cols: np.array, lags: np.array, period: int): vals = np.array([], dtype=np.float64) - for col, lag in zip(cols, lags): + for col, lag in zip(cols, lags, strict=False): vals = np.append(vals, array[period - lag, col]) return vals @@ -1056,8 +1048,7 @@ def draw_blockwise_graph( max_nodes: int = 50, figsize=(7.5, 7.5), ): - """ - Draws a directed graph of a block containing the given variable with a limited number of ancestors and descendants. + """Draws a directed graph of a block containing the given variable with a limited number of ancestors and descendants. Parameters: ----------- @@ -1087,7 +1078,6 @@ def draw_blockwise_graph( Draws a directed graph of the block containing 'var1' with up to 3 generations of ancestors and 2 generations of descendants. """ - if self._some_error: return @@ -1218,8 +1208,7 @@ def _find_var_node(self, var): return var_node def trace_to_exog_vars(self, i: str, noisy=True): - """ - Prints all exogenous variables that are ancestors to the given block. + """Prints all exogenous variables that are ancestors to the given block. Parameters: ----------- @@ -1243,7 +1232,6 @@ def trace_to_exog_vars(self, i: str, noisy=True): exog_var3 ... """ - if self._some_error: return @@ -1278,8 +1266,7 @@ def _trace_to_exog_vars(self, i): return [x for x in ancs_exog_vars if x not in self.endo_vars] def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): - """ - Traces the given block back to exogenous values and prints those values. + """Traces the given block back to exogenous values and prints those values. Parameters: ----------- @@ -1307,7 +1294,6 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): exog_var3=10.0 ... """ - try: output_array = self._last_solution.to_numpy(dtype=np.float64, copy=True) var_col_index = { @@ -1325,7 +1311,7 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): _, ancs_exog_lags, ancs_exog_cols, - ) = get_var_info((self._var_mapping.get(x) for x in ancs_exog_vars)) + ) = get_var_info(self._var_mapping.get(x) for x in ancs_exog_vars) ancs_exog_vals = self._get_vals( output_array, ancs_exog_cols, ancs_exog_lags, period_index, False ) @@ -1336,7 +1322,7 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): print( *[ "=".join([x, str(y)]) - for x, y in zip(ancs_exog_vars, ancs_exog_vals) + for x, y in zip(ancs_exog_vars, ancs_exog_vals, strict=False) ], sep="\n", ) @@ -1347,8 +1333,7 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): raise RuntimeError("no solution exists") def show_block_vals(self, i: int, period_index: int, noisy=True): - """ - Prints the values of endogenous and predetermined variables in a given block for a specific period. + """Prints the values of endogenous and predetermined variables in a given block for a specific period. Parameters: ----------- @@ -1380,7 +1365,6 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): pred_var2=9.7 ... """ - try: output_array = self._last_solution.to_numpy(dtype=np.float64, copy=True) var_col_index = { @@ -1412,7 +1396,7 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): "=".join([x, str(y)]) for x, y in zip( [self._var_mapping.get(x) for x in block[0]], - block_endo_vals, + block_endo_vals, strict=False, ) ], sep="\n", @@ -1425,7 +1409,7 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): "=".join([x, str(y)]) for x, y in zip( [self._var_mapping.get(x) for x in block[1]], - block_pred_vals, + block_pred_vals, strict=False, ) ], sep="\n", @@ -1452,19 +1436,18 @@ def get_var_info(vars): return (tuple([]), np.array([], dtype=int), np.array([], dtype=int)) # Stole zip-solution from: https://stackoverflow.com/questions/21444338/transpose-nested-list-in-python names, lags = tuple( - map(list, zip(*[self._lag_mapping.get(x) for x in vars])) + map(list, zip(*[self._lag_mapping.get(x) for x in vars], strict=False)) ) cols = tuple(var_col_index.get(x) for x in names) if any(x is None for x in cols): - missing = [x for x, y in zip(names, cols) if y is None] + missing = [x for x, y in zip(names, cols, strict=False) if y is None] raise KeyError(f'{",".join(missing)} is not in DataFrame') return (names, np.array(lags, dtype=int), np.array(cols, dtype=int)) return get_var_info def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None): - """ - Analyses sensitivity of endogenous variables to exogenous variables for a specific period. + """Analyses sensitivity of endogenous variables to exogenous variables for a specific period. Parameters: ----------- @@ -1502,7 +1485,6 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) exog_var2 | 0.45 | 0.56 | ... """ - if self._some_error: return diff --git a/tests/test_model_solver.py b/tests/test_model_solver.py index ba714f9..7bbeba2 100644 --- a/tests/test_model_solver.py +++ b/tests/test_model_solver.py @@ -1,8 +1,8 @@ -import sys import os -import pytest +import sys + import pandas as pd -import numpy as np +import pytest # Insert the path to your project root directly in the test file sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../src"))) From c1ba56cf73531965050944d910fbcf73fdd00525 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Sun, 8 Sep 2024 09:52:13 +0200 Subject: [PATCH 04/22] Ruff fixes and mypy config --- poetry.lock | 252 +++++++++++++++++-------------- pyproject.toml | 13 +- src/model_solver/model_solver.py | 80 +++++----- 3 files changed, 191 insertions(+), 154 deletions(-) diff --git a/poetry.lock b/poetry.lock index 6f33bad..6096585 100644 --- a/poetry.lock +++ b/poetry.lock @@ -959,19 +959,19 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth [[package]] name = "filelock" -version = "3.15.4" +version = "3.16.0" description = "A platform independent file lock." optional = false python-versions = ">=3.8" files = [ - {file = "filelock-3.15.4-py3-none-any.whl", hash = "sha256:6ca1fffae96225dab4c6eaf1c4f4f28cd2568d3ec2a44e15a08520504de468e7"}, - {file = "filelock-3.15.4.tar.gz", hash = "sha256:2207938cbc1844345cb01a5a95524dae30f0ce089eba5b00378295a17e3e90cb"}, + {file = "filelock-3.16.0-py3-none-any.whl", hash = "sha256:f6ed4c963184f4c84dd5557ce8fece759a3724b37b80c6c4f20a2f63a4dc6609"}, + {file = "filelock-3.16.0.tar.gz", hash = "sha256:81de9eb8453c769b63369f87f11131a7ab04e367f8d97ad39dc230daa07e3bec"}, ] [package.extras] -docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"] -testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-asyncio (>=0.21)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)", "virtualenv (>=20.26.2)"] -typing = ["typing-extensions (>=4.8)"] +docs = ["furo (>=2024.8.6)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4)"] +testing = ["covdefaults (>=2.3)", "coverage (>=7.6.1)", "diff-cover (>=9.1.1)", "pytest (>=8.3.2)", "pytest-asyncio (>=0.24)", "pytest-cov (>=5)", "pytest-mock (>=3.14)", "pytest-timeout (>=2.3.1)", "virtualenv (>=20.26.3)"] +typing = ["typing-extensions (>=4.12.2)"] [[package]] name = "fonttools" @@ -2832,6 +2832,21 @@ sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-d test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"] xml = ["lxml (>=4.9.2)"] +[[package]] +name = "pandas-stubs" +version = "2.2.2.240807" +description = "Type annotations for pandas" +optional = false +python-versions = ">=3.9" +files = [ + {file = "pandas_stubs-2.2.2.240807-py3-none-any.whl", hash = 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-content-hash = "1618822aa105299892469bbffaa982dd3e5e422f4e857ce671ce840cecc3ef7b" +content-hash = "2c6716037722182464e51ac613f394e7e326874732ca8f7f9864444d4dfec9c2" diff --git a/pyproject.toml b/pyproject.toml index 5a5d992..fffa8f2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -44,6 +44,7 @@ sphinx-click = ">=3.0.2" typeguard = ">=2.13.3" xdoctest = { extras = ["colors"], version = ">=0.15.10" } myst-parser = { version = ">=0.16.1" } +pandas-stubs = ">=2.2.2.240807" [tool.poetry.scripts] ssb-model-solver = "model_solver.__main__:main" @@ -68,6 +69,16 @@ pretty = true show_column_numbers = true show_error_context = true +[[tool.mypy.overrides]] +module = [ +# "matplotlib", +# "matplotlib.pyplot", + "networkx.*", + "numba.*", + "symengine.*", +] +ignore_missing_imports = true + [tool.ruff] force-exclude = true # Apply excludes to pre-commit show-fixes = true @@ -88,7 +99,7 @@ select = [ "A", # prevent using keywords that clobber python builtins # "ANN", # check type annotations "B", # bugbear: security warnings - "D", # documentation +# "D", # documentation "E", # pycodestyle "F", # pyflakes "ISC", # implicit string concatenation diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 9c4b7e3..f16a7f4 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -101,7 +101,7 @@ class ModelSolver: """ # Reads in equations and endogenous variables and does a number of operations, e.g. analyzing block structure using graph theory. - def __init__(self, eqns: list[str], endo_vars: list[str]): + def __init__(self, eqns: list[str], endo_vars: list[str]) -> None: self._some_error = False self._lag_notation = "__LAG" self._max_lag = 0 @@ -143,30 +143,30 @@ def endo_vars(self): @property def exog_vars(self): - vars = set() + vars_ = set() for _, _, _, lag_mapping in self._eqns_analyzed: for _, val in lag_mapping.items(): - vars.update((val[0],)) - return tuple(vars.difference(self.endo_vars)) + vars_.update((val[0],)) + return tuple(vars_.difference(self.endo_vars)) @property - def max_lag(self): + def max_lag(self) -> int: return self._max_lag @property - def root_tolerance(self): + def root_tolerance(self) -> float: return self._root_tolerance @property - def max_iter(self): + def max_iter(self) -> int: return self._max_iter @property def last_solution(self): try: return self._last_solution.iloc[self.max_lag :, :] - except AttributeError: - raise AttributeError("no solution exists") + except AttributeError as exc: + raise AttributeError("no solution exists") from exc @root_tolerance.setter def root_tolerance(self, val: float): @@ -186,7 +186,7 @@ def max_iter(self, val: int): # Imports lists containing equations and endogenous variables stored as strings # Checks that there are no blank lines, sets everything to lowercase and returns as tuples - def _init_model(self, eqns: list, endo_vars: list): + def _init_model(self, eqns: list[str], endo_vars: list[str]): print("* Importing equations") if any(x.strip() == "" for x in eqns): self._some_error = True @@ -233,20 +233,20 @@ def _analyze_eqn(self, eqn: str): component, lag = "", "" is_num, is_var, is_lag, is_sci = False, False, False, False - for chr in "".join([eqn, " "]): - is_num = (chr.isnumeric() and not is_var) or is_num - is_var = (chr.isalpha() and not is_num) or is_var - is_lag = (is_var and chr == "(") or is_lag - is_sci = (is_num and chr == "e") or is_sci + for chr_ in "".join([eqn, " "]): + is_num = (chr_.isnumeric() and not is_var) or is_num + is_var = (chr_.isalpha() and not is_num) or is_var + is_lag = (is_var and chr_ == "(") or is_lag + is_sci = (is_num and chr_ == "e") or is_sci - if is_var and chr == "(" and component in ["max", "min", "log", "exp"]: - parsed_eqn_with_lag_notation += ("".join([component, chr]),) + if is_var and chr_ == "(" and component in ["max", "min", "log", "exp"]: + parsed_eqn_with_lag_notation += ("".join([component, chr_]),) is_var, is_lag = False, False component, lag = "", "" continue # Check if character is something other than a numeric, variable or lag and write numeric or variable to parsed equation - if chr in ["=", "+", "-", "*", "/", "(", ")", ",", " "] and not ( + if chr_ in ["=", "+", "-", "*", "/", "(", ")", ",", " "] and not ( is_lag or is_sci ): if is_num: @@ -269,26 +269,26 @@ def _analyze_eqn(self, eqn: str): self._max_lag = max( self._max_lag, -int(lag.replace("(", "").replace(")", "")) ) - if chr != " ": - parsed_eqn_with_lag_notation += (chr,) + if chr_ != " ": + parsed_eqn_with_lag_notation += (chr_,) component, lag = "", "" is_num, is_var, is_lag = False, False, False continue - if is_sci and chr.isnumeric(): + if is_sci and chr_.isnumeric(): is_sci = False if is_num: - component = "".join([component, chr]) + component = "".join([component, chr_]) continue if is_var and not is_lag: - component = "".join([component, chr]) + component = "".join([component, chr_]) continue if is_var and is_lag: - lag = "".join([lag, chr]) - if chr == ")": + lag = "".join([lag, chr_]) + if chr_ == ")": is_lag = False return parsed_eqn_with_lag_notation, var_mapping, lag_mapping @@ -367,9 +367,9 @@ def _find_max_bipartite_match(self, eqns_endo_vars_bigraph): if len(maximum_bipartite_match) / 2 < len(self.eqns): self._some_error = True raise RuntimeError("model is over or under spesified") - except nx.AmbiguousSolution: + except nx.AmbiguousSolution as exc: self._some_error = True - raise RuntimeError("unable to analyze model") + raise RuntimeError("unable to analyze model") from exc return maximum_bipartite_match @@ -994,7 +994,7 @@ def _get_vals(self, array, cols, lags, period, jit): @njit def _get_vals_jit(array: np.array, cols: np.array, lags: np.array, period: int): vals = np.array([0.0], dtype=np.float64) - for col, lag in zip(cols, lags, strict=False): + for col, lag in zip(cols, lags): # noqa: B905 vals = np.append(vals, array[period - lag, col]) return vals[1:] @@ -1003,7 +1003,7 @@ def _get_vals_jit(array: np.array, cols: np.array, lags: np.array, period: int): @staticmethod def _get_vals_nojit(array: np.array, cols: np.array, lags: np.array, period: int): vals = np.array([], dtype=np.float64) - for col, lag in zip(cols, lags, strict=False): + for col, lag in zip(cols, lags): # noqa: B905 vals = np.append(vals, array[period - lag, col]) return vals @@ -1322,15 +1322,15 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): print( *[ "=".join([x, str(y)]) - for x, y in zip(ancs_exog_vars, ancs_exog_vals, strict=False) + for x, y in zip(ancs_exog_vars, ancs_exog_vals, strict=True) ], sep="\n", ) else: return pd.Series(ancs_exog_vals, index=ancs_exog_vars) - except AttributeError: - raise RuntimeError("no solution exists") + except AttributeError as exc: + raise RuntimeError("no solution exists") from exc def show_block_vals(self, i: int, period_index: int, noisy=True): """Prints the values of endogenous and predetermined variables in a given block for a specific period. @@ -1396,7 +1396,7 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): "=".join([x, str(y)]) for x, y in zip( [self._var_mapping.get(x) for x in block[0]], - block_endo_vals, strict=False, + block_endo_vals, strict=True, ) ], sep="\n", @@ -1409,7 +1409,7 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): "=".join([x, str(y)]) for x, y in zip( [self._var_mapping.get(x) for x in block[1]], - block_pred_vals, strict=False, + block_pred_vals, strict=True, ) ], sep="\n", @@ -1426,8 +1426,8 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): ), ) - except AttributeError: - raise RuntimeError("no solution exists") + except AttributeError as exc: + raise RuntimeError("no solution exists") from exc # Function that returns function that returns names, columns and lags for variables def gen_get_var_info(self, var_col_index): @@ -1436,11 +1436,11 @@ def get_var_info(vars): return (tuple([]), np.array([], dtype=int), np.array([], dtype=int)) # Stole zip-solution from: https://stackoverflow.com/questions/21444338/transpose-nested-list-in-python names, lags = tuple( - map(list, zip(*[self._lag_mapping.get(x) for x in vars], strict=False)) + map(list, zip(*[self._lag_mapping.get(x) for x in vars], strict=True)) ) cols = tuple(var_col_index.get(x) for x in names) if any(x is None for x in cols): - missing = [x for x, y in zip(names, cols, strict=False) if y is None] + missing = [x for x, y in zip(names, cols, strict=True) if y is None] raise KeyError(f'{",".join(missing)} is not in DataFrame') return (names, np.array(lags, dtype=int), np.array(cols, dtype=int)) @@ -1495,8 +1495,8 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) self._last_solution.columns.str.lower().to_list() ) } - except AttributeError: - raise AttributeError("no solution exists") + except AttributeError as exc: + raise AttributeError("no solution exists") from exc get_var_info = cache(self.gen_get_var_info(var_col_index)) From f3c8f954ebcc4b8d909a9cc8edf53ec89c36d8b5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Mon, 9 Sep 2024 13:12:38 +0200 Subject: [PATCH 05/22] Add type annotations --- src/model_solver/model_solver.py | 143 ++++++++++++++++++++++--------- tests/test_model_solver.py | 24 +++--- 2 files changed, 113 insertions(+), 54 deletions(-) diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index f16a7f4..9ffe33f 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -5,13 +5,16 @@ ######################################### from collections import Counter +from collections.abc import Callable from functools import cache +from typing import Any import matplotlib.pyplot as plt import networkx as nx import numpy as np import pandas as pd from numba import njit +from numpy.typing import NDArray from symengine import Lambdify from symengine import Matrix from symengine import Max @@ -134,16 +137,16 @@ def __init__(self, eqns: list[str], endo_vars: list[str]) -> None: print("-" * 100) @property - def eqns(self): + def eqns(self) -> tuple[str, ...]: return self._eqns @property - def endo_vars(self): + def endo_vars(self) -> tuple[str, ...]: return self._endo_vars @property - def exog_vars(self): - vars_ = set() + def exog_vars(self) -> tuple[str, ...]: + vars_: set[str] = set() for _, _, _, lag_mapping in self._eqns_analyzed: for _, val in lag_mapping.items(): vars_.update((val[0],)) @@ -154,30 +157,30 @@ def max_lag(self) -> int: return self._max_lag @property - def root_tolerance(self) -> float: - return self._root_tolerance - - @property - def max_iter(self) -> int: - return self._max_iter - - @property - def last_solution(self): + def last_solution(self) -> pd.DataFrame: try: return self._last_solution.iloc[self.max_lag :, :] except AttributeError as exc: raise AttributeError("no solution exists") from exc + @property + def root_tolerance(self) -> float: + return self._root_tolerance + @root_tolerance.setter - def root_tolerance(self, val: float): + def root_tolerance(self, val: float) -> None: if isinstance(val, float) is False: raise ValueError("tolerance for termination must be of type float") if val <= 0: raise ValueError("tolerance for termination must be positive") self._root_tolerance = val + @property + def max_iter(self) -> int: + return self._max_iter + @max_iter.setter - def max_iter(self, val: int): + def max_iter(self, val: int) -> None: if isinstance(val, int) is False: raise ValueError("maximum number of iterations must be an integer") if val < 0: @@ -186,7 +189,9 @@ def max_iter(self, val: int): # Imports lists containing equations and endogenous variables stored as strings # Checks that there are no blank lines, sets everything to lowercase and returns as tuples - def _init_model(self, eqns: list[str], endo_vars: list[str]): + def _init_model( + self, eqns: list[str], endo_vars: list[str] + ) -> tuple[tuple[str, ...], tuple[str, ...]]: print("* Importing equations") if any(x.strip() == "" for x in eqns): self._some_error = True @@ -206,15 +211,24 @@ def _init_model(self, eqns: list[str], endo_vars: list[str]): return tuple(x.lower() for x in eqns), tuple(x.lower() for x in endo_vars) # Analyzes the equations of the model - def _analyze_eqns(self): + def _analyze_eqns( + self, + ) -> tuple[ + list[tuple[list[str], list[str], dict[str, str], dict[str, tuple[str, int]]]], + dict[str, str], + dict[str, tuple[str, int]], + ]: if self._some_error: return None, None print("\t* Analyzing equation strings") - eqns_analyzed = [] + eqns_analyzed: list[ + tuple[list[str], list[str], dict[str, str], dict[str, tuple[str, int]]] + ] = [] + var_mapping: dict[str, str] = {} + lag_mapping: dict[str, tuple[str, int]] = {} - var_mapping, lag_mapping = {}, {} for eqn in self._eqns: eqn_analyzed = (eqn, *self._analyze_eqn(eqn)) eqns_analyzed += (eqn_analyzed,) @@ -225,11 +239,16 @@ def _analyze_eqns(self): # Takes an equation string and parses it into coefficients (special care is taken to deal with scientific notation), variables, lags and operators/brackets # I've written my own parser in stead of using some existing because it needs to take care of then (-)-notation for lags - def _analyze_eqn(self, eqn: str): + def _analyze_eqn( + self, eqn: str + ) -> tuple[list[str], dict[str, str], dict[str, tuple[str, int]]]: if self._some_error: return - parsed_eqn_with_lag_notation, var_mapping, lag_mapping = [], {}, {} + parsed_eqn_with_lag_notation: list[str] = [] + var_mapping: dict[str, str] = {} + lag_mapping: dict[str, tuple[str, int]] = {} + component, lag = "", "" is_num, is_var, is_lag, is_sci = False, False, False, False @@ -290,12 +309,18 @@ def _analyze_eqn(self, eqn: str): lag = "".join([lag, chr_]) if chr_ == ")": is_lag = False - return parsed_eqn_with_lag_notation, var_mapping, lag_mapping # Performs block analysis of equations subject to endogenous variables # Analysis is a sequence of operations using graph theory - def _block_analyze_model(self): + def _block_analyze_model( + self, + ) -> tuple[ + dict[str | int, int | str], + nx.DiGraph, + nx.DiGraph, + dict[str | int, tuple[str, ...]], + ]: # Using graph theory to analyze equations using existing algorithms to establish minimum simultaneous blocks eqns_endo_vars_bigraph = self._gen_eqns_endo_vars_bigraph() eqns_endo_vars_match = self._find_max_bipartite_match(eqns_endo_vars_bigraph) @@ -316,7 +341,6 @@ def _block_analyze_model(self): **condenced_model_node_varlist_mapping, **augmented_condenced_model_node_varlist_mapping, } - return ( eqns_endo_vars_match, condenced_model_digraph, @@ -326,7 +350,7 @@ def _block_analyze_model(self): # Generates bipartite graph (bigraph) connetcting equations (nodes in U) with endogenous variables (nodes in V) # See https://en.wikipedia.org/wiki/Bipartite_graph for a discussion of bigraphs - def _gen_eqns_endo_vars_bigraph(self): + def _gen_eqns_endo_vars_bigraph(self) -> nx.Graph: if self._some_error: return @@ -351,7 +375,9 @@ def _gen_eqns_endo_vars_bigraph(self): # Finds a maximum bipartite match (MBM) of bigraph connetcting equations (nodes in U) with endogenous variables (nodes in V) # See https://www.geeksforgeeks.org/maximum-bipartite-matching/ for more on MBM # Returns dict with matches (maps both ways, i.e. U-->V and U-->U) - def _find_max_bipartite_match(self, eqns_endo_vars_bigraph): + def _find_max_bipartite_match( + self, eqns_endo_vars_bigraph: nx.Graph + ) -> dict[str | int, int | str]: if self._some_error: return @@ -361,8 +387,10 @@ def _find_max_bipartite_match(self, eqns_endo_vars_bigraph): # Use maximum bipartite matching to make a one to one mapping between equations and endogenous variables try: - maximum_bipartite_match = nx.bipartite.maximum_matching( - eqns_endo_vars_bigraph, [i for i, _ in enumerate(self._eqns)] + maximum_bipartite_match: dict[str | int, int | str] = ( + nx.bipartite.maximum_matching( + eqns_endo_vars_bigraph, [i for i, _ in enumerate(self._eqns)] + ) ) if len(maximum_bipartite_match) / 2 < len(self.eqns): self._some_error = True @@ -375,7 +403,11 @@ def _find_max_bipartite_match(self, eqns_endo_vars_bigraph): # Makes a directed graph (digraph) showing how endogenous variables affect every other endogenous variable # See https://en.wikipedia.org/wiki/Directed_graph for more about directed graphs - def _gen_model_digraph(self, eqns_endo_vars_bigraph, eqns_endo_vars_match): + def _gen_model_digraph( + self, + eqns_endo_vars_bigraph: nx.Graph, + eqns_endo_vars_match: dict[str | int, int | str], + ) -> nx.DiGraph: if self._some_error: return @@ -397,7 +429,9 @@ def _gen_model_digraph(self, eqns_endo_vars_bigraph, eqns_endo_vars_match): # Makes a condencation of digraph of endogenous variables # Each node of condencation contains strongly connected components; this corresponds to the simulataneous model blocks # See https://en.wikipedia.org/wiki/Strongly_connected_component for more about strongly connected components - def _gen_condenced_model_digraph(self, model_digraph): + def _gen_condenced_model_digraph( + self, model_digraph: nx.DiGraph + ) -> tuple[nx.DiGraph, dict[int, tuple[str, ...]]]: if self._some_error: return @@ -419,8 +453,10 @@ def _gen_condenced_model_digraph(self, model_digraph): # Augments condenced digraph with nodes and edges for exogenous variables in order to show what exogenous variables affect what strong components def _gen_augmented_condenced_model_digraph( - self, condenced_model_digraph, eqns_endo_vars_match - ): + self, + condenced_model_digraph: nx.DiGraph, + eqns_endo_vars_match: dict[str | int, int | str], + ) -> tuple[nx.DiGraph, dict[str, tuple[str, ...]]]: if self._some_error: return @@ -449,7 +485,22 @@ def _gen_augmented_condenced_model_digraph( # Generates simulation code and blocks # Simulation code contains a tuple of tuples for each strong component # The tuple for each strong component contains objective function, and Jacobian matrix, and lists of the variables in the strong component - def _gen_sim_code_and_blocks(self): + def _gen_sim_code_and_blocks( + self, + ) -> tuple[ + dict[ + int, + tuple[ + Callable[..., NDArray[Any]] | None, + Callable[..., NDArray[Any]] | None, + Callable[..., NDArray[Any]] | None, + tuple[str, ...], + tuple[str, ...], + tuple[list[str]], + ], + ], + dict[int, tuple[tuple[str, ...], tuple[str, ...], tuple[str, ...], bool]], + ]: if self._some_error: return @@ -508,8 +559,14 @@ def _gen_sim_code_and_blocks(self): # Generates symbolic objective functon and Jacobian matrix for a given strong component @staticmethod def _gen_def_or_obj_fun_and_jac( - eqns: tuple[str], endo_vars: tuple[str], pred_vars: tuple[str] - ): + eqns: tuple[str, ...], + endo_vars: tuple[str, ...], + pred_vars: tuple[str, ...], + ) -> tuple[ + Callable[..., NDArray[Any]] | None, + Callable[[list, ...], NDArray[Any]] | None, + Callable[[list, ...], NDArray[Any]] | None, + ]: max, min = Max, Max endo_sym, pred_sym, obj_fun = [], [], [] for endo_var in endo_vars: @@ -1396,7 +1453,8 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): "=".join([x, str(y)]) for x, y in zip( [self._var_mapping.get(x) for x in block[0]], - block_endo_vals, strict=True, + block_endo_vals, + strict=True, ) ], sep="\n", @@ -1409,7 +1467,8 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): "=".join([x, str(y)]) for x, y in zip( [self._var_mapping.get(x) for x in block[1]], - block_pred_vals, strict=True, + block_pred_vals, + strict=True, ) ], sep="\n", @@ -1431,18 +1490,18 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): # Function that returns function that returns names, columns and lags for variables def gen_get_var_info(self, var_col_index): - def get_var_info(vars): - if not vars: - return (tuple([]), np.array([], dtype=int), np.array([], dtype=int)) + def get_var_info(vars_): + if not vars_: + return (), np.array([], dtype=int), np.array([], dtype=int) # Stole zip-solution from: https://stackoverflow.com/questions/21444338/transpose-nested-list-in-python names, lags = tuple( - map(list, zip(*[self._lag_mapping.get(x) for x in vars], strict=True)) + map(list, zip(*[self._lag_mapping.get(x) for x in vars_], strict=True)) ) cols = tuple(var_col_index.get(x) for x in names) if any(x is None for x in cols): missing = [x for x, y in zip(names, cols, strict=True) if y is None] raise KeyError(f'{",".join(missing)} is not in DataFrame') - return (names, np.array(lags, dtype=int), np.array(cols, dtype=int)) + return names, np.array(lags, dtype=int), np.array(cols, dtype=int) return get_var_info diff --git a/tests/test_model_solver.py b/tests/test_model_solver.py index 7bbeba2..c3fc59c 100644 --- a/tests/test_model_solver.py +++ b/tests/test_model_solver.py @@ -1,15 +1,10 @@ -import os -import sys - import pandas as pd import pytest -# Insert the path to your project root directly in the test file -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../src"))) - -# Import the model_solver module correctly import model_solver as ms +TOLERANCE = 1e-6 # Small tolerance for floating-point comparisons + # Fixtures for test data @pytest.fixture @@ -88,9 +83,8 @@ def test_solve_model(equations, endogenous, input_data): "i2": [2.0, 3.0, 4.0], } - tolerance = 1e-6 # Small tolerance for floating-point comparisons for col, values in expected_values.items(): - assert solution[col].tolist() == pytest.approx(values, rel=tolerance) + assert solution[col].tolist() == pytest.approx(values, rel=TOLERANCE) # Test switching endogenous variables @@ -120,7 +114,7 @@ def test_trace_to_exog_vals(equations, endogenous, input_data): ).sort_index() exog_vals = exog_vals.sort_index() # Sort before comparison - pd.testing.assert_series_equal(exog_vals, expected_exog_vals, rtol=1e-6) + pd.testing.assert_series_equal(exog_vals, expected_exog_vals, rtol=TOLERANCE) # Test showing block values @@ -136,5 +130,11 @@ def test_show_block_vals(equations, endogenous, input_data): endo_vals = endo_vals.sort_index() # Sort before comparison pred_vals = pred_vals.sort_index() # Sort before comparison - pd.testing.assert_series_equal(endo_vals, expected_endo_vals, rtol=1e-6) - pd.testing.assert_series_equal(pred_vals, expected_pred_vals, rtol=1e-6) + pd.testing.assert_series_equal(endo_vals, expected_endo_vals, rtol=TOLERANCE) + pd.testing.assert_series_equal(pred_vals, expected_pred_vals, rtol=TOLERANCE) + + +def test_sensitivity(equations, endogenous, input_data): + model = ms.ModelSolver(equations, endogenous) + model.solve_model(input_data) + # df = model.sensitivity(1, 3, method='pct', exog_subset=['exog_var1', 'exog_var2']) From 2288d51ee58e59ab2d12e4ead13cb550e1e6936a Mon Sep 17 00:00:00 2001 From: benediktgoodman Date: Tue, 10 Sep 2024 14:24:47 +0200 Subject: [PATCH 06/22] Update test_model_solver.py lagt til fixture og test for model.sensitivity() --- tests/test_model_solver.py | 15 +++++++++++++-- 1 file changed, 13 insertions(+), 2 deletions(-) diff --git a/tests/test_model_solver.py b/tests/test_model_solver.py index c3fc59c..613fe43 100644 --- a/tests/test_model_solver.py +++ b/tests/test_model_solver.py @@ -1,4 +1,5 @@ import pandas as pd +import numpy as np import pytest import model_solver as ms @@ -23,6 +24,10 @@ def equations(): def endogenous(): return ["x1", "x2", "ca", "cb", "k1", "k2"] +@pytest.fixture +def sensitivity_params(): + return [1, 1, 'std'] + @pytest.fixture def input_data(): @@ -134,7 +139,13 @@ def test_show_block_vals(equations, endogenous, input_data): pd.testing.assert_series_equal(pred_vals, expected_pred_vals, rtol=TOLERANCE) -def test_sensitivity(equations, endogenous, input_data): +def test_sensitivity(equations, endogenous, input_data, sensitivity_params): model = ms.ModelSolver(equations, endogenous) model.solve_model(input_data) - # df = model.sensitivity(1, 3, method='pct', exog_subset=['exog_var1', 'exog_var2']) + # Unpacks fixture + df = model.sensitivity(*sensitivity_params) + + assert df.empty is False + # k2 will be in the block analysed with current equation set + assert 'k2' in df.columns + assert np.allclose(4.732277, df['k2'].sum(), atol=0.00001) \ No newline at end of file From 53c2216726447d5aef12d5eedc222e736a8e4c01 Mon Sep 17 00:00:00 2001 From: benediktgoodman Date: Tue, 10 Sep 2024 14:59:45 +0200 Subject: [PATCH 07/22] fixed futurewarning related to indeces --- examples/example-model-solver.ipynb | 1 + src/model_solver/model_solver.py | 12 ++++++++---- 2 files changed, 9 insertions(+), 4 deletions(-) diff --git a/examples/example-model-solver.ipynb b/examples/example-model-solver.ipynb index 9f72320..5a0de7f 100644 --- a/examples/example-model-solver.ipynb +++ b/examples/example-model-solver.ipynb @@ -54,6 +54,7 @@ "tags": [] }, "outputs": [], + "File \u001b[1;32me:\\Coding projects\\Git repos\\ssb-model-solver\\src\\model_solver\\model_solver.py:13\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Any\n\u001b[0;32m 12\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpyplot\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mplt\u001b[39;00m\n\u001b[1;32m---> 13\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnetworkx\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnx\u001b[39;00m\n\u001b[0;32m 14\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n", "source": [ "import pandas as pd\n", "import src.model_solver as ms\n", diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 9ffe33f..de2ae03 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -1595,13 +1595,17 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) solution_diff = self._last_solution.copy() if method == "std": - solution_diff[var].iloc[period_index - lag] += solution_diff[var].std() + solution_diff.loc[solution_diff.index[period_index - lag], var] += ( + solution_diff[var].std() + ) elif method == "pct": - solution_diff[var].iloc[period_index - lag] += ( - solution_diff[var].iloc[period_index - lag] * 0.01 + solution_diff.loc[solution_diff.index[period_index - lag], var] += ( + solution_diff.loc[solution_diff.index[period_index - lag], var] + * 0.01 ) + elif method == "one": - solution_diff[var].iloc[period_index - lag] += 1 + solution_diff.loc[solution_diff.index[period_index - lag], var] += 1 else: raise ValueError("method must be std, pct or one") From 89dc8f0fcf26fc6c88add6034195735e3a1055f1 Mon Sep 17 00:00:00 2001 From: benediktgoodman Date: Tue, 10 Sep 2024 15:00:18 +0200 Subject: [PATCH 08/22] Update test_model_solver.py added tests for all sensitivity modes for model.sensitivity() --- tests/test_model_solver.py | 33 +++++++++++++++++++++++++-------- 1 file changed, 25 insertions(+), 8 deletions(-) diff --git a/tests/test_model_solver.py b/tests/test_model_solver.py index 613fe43..f4d8838 100644 --- a/tests/test_model_solver.py +++ b/tests/test_model_solver.py @@ -25,9 +25,17 @@ def endogenous(): return ["x1", "x2", "ca", "cb", "k1", "k2"] @pytest.fixture -def sensitivity_params(): +def sensitivity_params_std(): return [1, 1, 'std'] +@pytest.fixture +def sensitivity_params_pct(): + return [1, 1, 'pct'] + +@pytest.fixture +def sensitivity_params_one(): + return [1, 1, 'one'] + @pytest.fixture def input_data(): @@ -139,13 +147,22 @@ def test_show_block_vals(equations, endogenous, input_data): pd.testing.assert_series_equal(pred_vals, expected_pred_vals, rtol=TOLERANCE) -def test_sensitivity(equations, endogenous, input_data, sensitivity_params): +def test_sensitivity(equations, endogenous, input_data, sensitivity_params_std, sensitivity_params_pct, sensitivity_params_one): model = ms.ModelSolver(equations, endogenous) model.solve_model(input_data) - # Unpacks fixture - df = model.sensitivity(*sensitivity_params) - assert df.empty is False - # k2 will be in the block analysed with current equation set - assert 'k2' in df.columns - assert np.allclose(4.732277, df['k2'].sum(), atol=0.00001) \ No newline at end of file + # Unpacks fixtures for std, pct and ones, then does analysis + sens_std = model.sensitivity(*sensitivity_params_std) + sens_pct = model.sensitivity(*sensitivity_params_pct) + sens_one = model.sensitivity(*sensitivity_params_one) + + # Checks for results + assert sens_std.empty is False + assert sens_pct.empty is False + assert sens_one.empty is False + + # k2 will be in the block analysed with current equation set + assert 'k2' in sens_std.columns + assert np.allclose(4.732277, sens_std['k2'].sum(), atol=0.00001) + + \ No newline at end of file From 4829d6ec0a3052e2765282da555a27bf9dd0f5e2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Mon, 16 Sep 2024 13:12:46 +0200 Subject: [PATCH 09/22] Fix invalid ipynb-file --- examples/example-model-solver.ipynb | 1 - 1 file changed, 1 deletion(-) diff --git a/examples/example-model-solver.ipynb b/examples/example-model-solver.ipynb index 5a0de7f..9f72320 100644 --- a/examples/example-model-solver.ipynb +++ b/examples/example-model-solver.ipynb @@ -54,7 +54,6 @@ "tags": [] }, "outputs": [], - "File \u001b[1;32me:\\Coding projects\\Git repos\\ssb-model-solver\\src\\model_solver\\model_solver.py:13\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Any\n\u001b[0;32m 12\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpyplot\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mplt\u001b[39;00m\n\u001b[1;32m---> 13\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnetworkx\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnx\u001b[39;00m\n\u001b[0;32m 14\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[0;32m 15\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n", "source": [ "import pandas as pd\n", "import src.model_solver as ms\n", From 5e45d4a6c9a0d6ec51945dc990fed826f03bfa6c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Mon, 16 Sep 2024 13:19:23 +0200 Subject: [PATCH 10/22] Add type annotations --- poetry.lock | 905 ++++++++++++++++--------------- src/model_solver/model_solver.py | 156 +++--- 2 files changed, 523 insertions(+), 538 deletions(-) diff --git a/poetry.lock b/poetry.lock index 6096585..8ff5f81 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -6,6 +6,9 @@ from collections import Counter from collections.abc import Callable +from collections.abc import Generator +from collections.abc import Iterable +from collections.abc import Sequence from functools import cache from typing import Any @@ -15,9 +18,10 @@ import pandas as pd from numba import njit from numpy.typing import NDArray +from symengine import Add from symengine import Lambdify from symengine import Matrix -from symengine import Max +from symengine import Symbol from symengine import var @@ -105,7 +109,6 @@ class ModelSolver: # Reads in equations and endogenous variables and does a number of operations, e.g. analyzing block structure using graph theory. def __init__(self, eqns: list[str], endo_vars: list[str]) -> None: - self._some_error = False self._lag_notation = "__LAG" self._max_lag = 0 self._root_tolerance = 1e-7 @@ -194,16 +197,13 @@ def _init_model( ) -> tuple[tuple[str, ...], tuple[str, ...]]: print("* Importing equations") if any(x.strip() == "" for x in eqns): - self._some_error = True raise ValueError("there are empty elements in equation list") print("* Importing endogenous variables") if any(x.strip() == "" for x in endo_vars): - self._some_error = True raise ValueError("there are empty elements in endogenous variable list") if len(eqns) != len(endo_vars): - self._some_error = True raise ValueError( "there is a different number of equations and endogenous variables" ) @@ -214,17 +214,14 @@ def _init_model( def _analyze_eqns( self, ) -> tuple[ - list[tuple[list[str], list[str], dict[str, str], dict[str, tuple[str, int]]]], + list[tuple[str, list[str], dict[str, str], dict[str, tuple[str, int]]]], dict[str, str], dict[str, tuple[str, int]], ]: - if self._some_error: - return None, None - print("\t* Analyzing equation strings") eqns_analyzed: list[ - tuple[list[str], list[str], dict[str, str], dict[str, tuple[str, int]]] + tuple[str, list[str], dict[str, str], dict[str, tuple[str, int]]] ] = [] var_mapping: dict[str, str] = {} lag_mapping: dict[str, tuple[str, int]] = {} @@ -242,9 +239,6 @@ def _analyze_eqns( def _analyze_eqn( self, eqn: str ) -> tuple[list[str], dict[str, str], dict[str, tuple[str, int]]]: - if self._some_error: - return - parsed_eqn_with_lag_notation: list[str] = [] var_mapping: dict[str, str] = {} lag_mapping: dict[str, tuple[str, int]] = {} @@ -337,7 +331,7 @@ def _block_analyze_model( condenced_model_digraph, eqns_endo_vars_match ) - node_varlist_mapping = { + node_varlist_mapping = { # type: ignore **condenced_model_node_varlist_mapping, **augmented_condenced_model_node_varlist_mapping, } @@ -351,9 +345,6 @@ def _block_analyze_model( # Generates bipartite graph (bigraph) connetcting equations (nodes in U) with endogenous variables (nodes in V) # See https://en.wikipedia.org/wiki/Bipartite_graph for a discussion of bigraphs def _gen_eqns_endo_vars_bigraph(self) -> nx.Graph: - if self._some_error: - return - print( "\t* Generating bipartite graph (BiGraph) connecting equations and endogenous variables" ) @@ -378,9 +369,6 @@ def _gen_eqns_endo_vars_bigraph(self) -> nx.Graph: def _find_max_bipartite_match( self, eqns_endo_vars_bigraph: nx.Graph ) -> dict[str | int, int | str]: - if self._some_error: - return - print( "\t* Finding maximum bipartite match (MBM) (i.e. associating every equation with exactly one endogenus variable)" ) @@ -393,10 +381,8 @@ def _find_max_bipartite_match( ) ) if len(maximum_bipartite_match) / 2 < len(self.eqns): - self._some_error = True raise RuntimeError("model is over or under spesified") except nx.AmbiguousSolution as exc: - self._some_error = True raise RuntimeError("unable to analyze model") from exc return maximum_bipartite_match @@ -408,9 +394,6 @@ def _gen_model_digraph( eqns_endo_vars_bigraph: nx.Graph, eqns_endo_vars_match: dict[str | int, int | str], ) -> nx.DiGraph: - if self._some_error: - return - print( "\t* Generating directed graph (DiGraph) connecting endogenous variables using bipartite graph and MBM" ) @@ -432,9 +415,6 @@ def _gen_model_digraph( def _gen_condenced_model_digraph( self, model_digraph: nx.DiGraph ) -> tuple[nx.DiGraph, dict[int, tuple[str, ...]]]: - if self._some_error: - return - print( "\t* Finding condensation of DiGraph (i.e. determining minimal blocks of systems of simulataneous equations)" ) @@ -448,7 +428,6 @@ def _gen_condenced_model_digraph( node_vars_mapping[node] = tuple( condenced_model_digraph.nodes[node]["members"] ) - return condenced_model_digraph, node_vars_mapping # Augments condenced digraph with nodes and edges for exogenous variables in order to show what exogenous variables affect what strong components @@ -457,20 +436,19 @@ def _gen_augmented_condenced_model_digraph( condenced_model_digraph: nx.DiGraph, eqns_endo_vars_match: dict[str | int, int | str], ) -> tuple[nx.DiGraph, dict[str, tuple[str, ...]]]: - if self._some_error: - return - augmented_condenced_model_digraph = condenced_model_digraph.copy() # Make edges between exogenous variables and strong components it is a part of node_vars_mapping = {} for node in condenced_model_digraph.nodes(): for member in condenced_model_digraph.nodes[node]["members"]: + index = eqns_endo_vars_match[member] + if not isinstance(index, int): + raise TypeError("Index not of type int") + for exog_var_adjacent_to_node in [ val - for key, val in self._eqns_analyzed[eqns_endo_vars_match[member]][ - 2 - ].items() + for key, val in self._eqns_analyzed[index][2].items() if self._lag_notation not in val and key not in self.endo_vars ]: augmented_condenced_model_digraph.add_edge( @@ -479,8 +457,7 @@ def _gen_augmented_condenced_model_digraph( node_vars_mapping[exog_var_adjacent_to_node] = ( exog_var_adjacent_to_node, ) - - return augmented_condenced_model_digraph, node_vars_mapping + return augmented_condenced_model_digraph, node_vars_mapping # type: ignore # Generates simulation code and blocks # Simulation code contains a tuple of tuples for each strong component @@ -492,18 +469,15 @@ def _gen_sim_code_and_blocks( int, tuple[ Callable[..., NDArray[Any]] | None, - Callable[..., NDArray[Any]] | None, - Callable[..., NDArray[Any]] | None, + Callable[[Iterable[Any], Any], NDArray[Any]] | None, + Callable[[Iterable[Any], Any], NDArray[Any]] | None, tuple[str, ...], tuple[str, ...], - tuple[list[str]], + tuple[list[str], ...], ], ], dict[int, tuple[tuple[str, ...], tuple[str, ...], tuple[str, ...], bool]], ]: - if self._some_error: - return - print( "\t* Generating simulation code (i.e. block-wise symbolic objective function,", "symbolic Jacobian matrix and lists of endogenous and exogenous variables)", @@ -513,19 +487,19 @@ def _gen_sim_code_and_blocks( for i, node in enumerate( reversed(tuple(self._condenced_model_digraph.nodes())) ): - block_endo_vars, block_eqns_orig, block_eqns_lags, block_pred_vars = ( - tuple(), - tuple(), - tuple(), - set(), - ) + block_endo_vars: tuple[str, ...] = () + block_eqns_orig: tuple[str, ...] = () + block_eqns_lags: tuple[list[str], ...] = () + block_pred_vars_set: set[str] = set() for member in self._condenced_model_digraph.nodes[node]["members"]: j = self._eqns_endo_vars_match[member] + if not isinstance(j, int): + raise TypeError("Index j is not of type int") eqns_analyzed = self._eqns_analyzed[j] block_endo_vars += (member,) block_eqns_orig += (eqns_analyzed[0],) block_eqns_lags += (eqns_analyzed[1],) - block_pred_vars.update( + block_pred_vars_set.update( [ val for key, val in eqns_analyzed[2].items() @@ -533,8 +507,8 @@ def _gen_sim_code_and_blocks( ] ) - block_pred_vars.difference_update(set(block_endo_vars)) - block_pred_vars = tuple(block_pred_vars) + block_pred_vars_set.difference_update(set(block_endo_vars)) + block_pred_vars = tuple(block_pred_vars_set) (def_fun, obj_fun, jac) = self._gen_def_or_obj_fun_and_jac( block_eqns_lags, block_endo_vars, block_pred_vars @@ -559,16 +533,17 @@ def _gen_sim_code_and_blocks( # Generates symbolic objective functon and Jacobian matrix for a given strong component @staticmethod def _gen_def_or_obj_fun_and_jac( - eqns: tuple[str, ...], + eqns: tuple[list[str], ...], endo_vars: tuple[str, ...], pred_vars: tuple[str, ...], ) -> tuple[ Callable[..., NDArray[Any]] | None, - Callable[[list, ...], NDArray[Any]] | None, - Callable[[list, ...], NDArray[Any]] | None, + Callable[[Iterable[Any], Any], NDArray[Any]] | None, + Callable[[Iterable[Any], Any], NDArray[Any]] | None, ]: - max, min = Max, Max - endo_sym, pred_sym, obj_fun = [], [], [] + endo_sym: list[Symbol] = [] + pred_sym: list[Symbol] = [] + obj_fun: list[Add] = [] for endo_var in endo_vars: var(endo_var) endo_sym += (eval(endo_var),) @@ -621,7 +596,9 @@ def _gen_def_or_obj_fun_and_jac( return None, obj_fun_out, jac_out - def switch_endo_vars(self, old_endo_vars: list[str], new_endo_vars: list[str]): + def switch_endo_vars( + self, old_endo_vars: list[str], new_endo_vars: list[str] + ) -> None: """Sets old_endo_vars as exogenous and new_endo_vars as endogenous and performs block analysis. Parameters: @@ -673,7 +650,7 @@ def switch_endo_vars(self, old_endo_vars: list[str], new_endo_vars: list[str]): print("Finished") - def find_endo_var(self, endo_var: str, noisy=False): + def find_endo_var(self, endo_var: str, noisy: bool = False) -> int | None: """Find the block that solves the specified endogenous variable. Parameters @@ -686,26 +663,27 @@ def find_endo_var(self, endo_var: str, noisy=False): Returns: ------- - str or None - The name of the block that solves the specified endogenous variable. + int or None + The block number of the block that solves the specified endogenous variable. Returns None if the endogenous variable is not found in any block. Notes: ----- This function searches for the specified endogenous variable in the model's - blocks and returns the name of the block that solves it. If the endogenous + blocks and returns the block number of the block that solves it. If the endogenous variable is not found in any block, it returns None. """ block = [key for key, val in self._blocks.items() if endo_var.lower() in val[0]] if block: if noisy: print(block[0]) + return None else: return block[0] else: raise IndexError(f"{endo_var} is not endogenous in model") - def describe(self): + def describe(self) -> None: """Display a summary of the model's characteristics. Prints information about the model, including the number of equations, blocks, @@ -728,7 +706,7 @@ def describe(self): print(f"{val} blocks have {key} equations") print("-" * 100) - def show_blocks(self): + def show_blocks(self) -> None: """Prints endogenous and exogenous variables and equations for every block in the model. Iterates through all blocks in the model and calls the `show_block` function to display their details. @@ -793,7 +771,7 @@ def show_blocks(self): print(" ".join(["-" * 50, "Block", str(key), "-" * 50])) self.show_block(key) - def show_block(self, i: int): + def show_block(self, i: int) -> None: """Prints endogenous and exogenous variables and equations for a given block. Parameters: @@ -853,9 +831,7 @@ def show_block(self, i: int): [ " ".join(x) for x in list( - self._chunks( - [self._var_mapping.get(x) for x in block[1]], 25 - ) + self._chunks([self._var_mapping[x] for x in block[1]], 25) ) ] ) @@ -865,7 +841,7 @@ def show_block(self, i: int): else: raise IndexError(f"block {i} is not in model") - def solve_model(self, input_df: pd.DataFrame, jit=True) -> pd.DataFrame: + def solve_model(self, input_df: pd.DataFrame, jit: bool = True) -> pd.DataFrame: """Solves the model subject to a given DataFrame. Parameters: @@ -893,11 +869,8 @@ def solve_model(self, input_df: pd.DataFrame, jit=True) -> pd.DataFrame: >>> input_data = pd.DataFrame({'var1': [1.0, 2.0, 3.0], 'var2': [0.5, 1.0, 1.5]}) >>> output_data = model.solve_model(input_data) """ - if self._some_error: - return - if ( - all(np.issubdtype(input_df[x].dtype, np.number) for x in input_df.columns) + all(np.issubdtype(input_df[x].dtype, np.number) for x in input_df.columns) # type: ignore is False ): raise TypeError("all columns in input_df must be numeric") @@ -1135,9 +1108,6 @@ def draw_blockwise_graph( Draws a directed graph of the block containing 'var1' with up to 3 generations of ancestors and 2 generations of descendants. """ - if self._some_error: - return - var_node = self._find_var_node(var.lower()) ancs_nodes = nx.ancestors(self._augmented_condenced_model_digraph, var_node) @@ -1289,9 +1259,6 @@ def trace_to_exog_vars(self, i: str, noisy=True): exog_var3 ... """ - if self._some_error: - return - if noisy: print( "\n".join( @@ -1489,10 +1456,16 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): raise RuntimeError("no solution exists") from exc # Function that returns function that returns names, columns and lags for variables - def gen_get_var_info(self, var_col_index): - def get_var_info(vars_): + def gen_get_var_info( + self, var_col_index: dict[str, int] + ) -> Callable[ + [Iterable[str]], tuple[list[str], NDArray[np.int64], NDArray[np.int64]] + ]: + def get_var_info( + vars_: Iterable[str], + ) -> tuple[list[str], NDArray[np.int64], NDArray[np.int64]]: if not vars_: - return (), np.array([], dtype=int), np.array([], dtype=int) + return [], np.array([], dtype=np.int64), np.array([], dtype=np.int64) # Stole zip-solution from: https://stackoverflow.com/questions/21444338/transpose-nested-list-in-python names, lags = tuple( map(list, zip(*[self._lag_mapping.get(x) for x in vars_], strict=True)) @@ -1501,7 +1474,7 @@ def get_var_info(vars_): if any(x is None for x in cols): missing = [x for x, y in zip(names, cols, strict=True) if y is None] raise KeyError(f'{",".join(missing)} is not in DataFrame') - return names, np.array(lags, dtype=int), np.array(cols, dtype=int) + return names, np.array(lags, dtype=np.int64), np.array(cols, dtype=np.int64) return get_var_info @@ -1544,9 +1517,6 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) exog_var2 | 0.45 | 0.56 | ... """ - if self._some_error: - return - try: var_col_index = { var: i @@ -1595,17 +1565,13 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) solution_diff = self._last_solution.copy() if method == "std": - solution_diff.loc[solution_diff.index[period_index - lag], var] += ( - solution_diff[var].std() - ) + solution_diff[var].iloc[period_index - lag] += solution_diff[var].std() elif method == "pct": - solution_diff.loc[solution_diff.index[period_index - lag], var] += ( - solution_diff.loc[solution_diff.index[period_index - lag], var] - * 0.01 + solution_diff[var].iloc[period_index - lag] += ( + solution_diff[var].iloc[period_index - lag] * 0.01 ) - elif method == "one": - solution_diff.loc[solution_diff.index[period_index - lag], var] += 1 + solution_diff[var].iloc[period_index - lag] += 1 else: raise ValueError("method must be std, pct or one") @@ -1640,6 +1606,6 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) # Stole solution from https://stackoverflow.com/questions/312443/how-do-i-split-a-list-into-equally-sized-chunks @staticmethod - def _chunks(xs, n): + def _chunks(xs: Sequence[str], n: int) -> Generator[Sequence[str], None, None]: n = max(1, n) return (xs[i : i + n] for i in range(0, len(xs), n)) From 4bf3cccca4067c2e003e0b20a8e61e6200adf3e5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Tue, 17 Sep 2024 10:33:18 +0200 Subject: [PATCH 11/22] Fix remaining mypy errors in src --- poetry.lock | 126 +++++++++++++------------------ pyproject.toml | 1 + src/model_solver/model_solver.py | 122 +++++++++++++++++++++--------- 3 files changed, 140 insertions(+), 109 deletions(-) diff --git a/poetry.lock b/poetry.lock index 8ff5f81..b5147ac 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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self._sim_code.items(): def_fun, obj_fun, jac, endo_vars, pred_vars, _ = val - solution = self._solve_block( + solution = self._solve_block( # type: ignore def_fun, obj_fun, jac, @@ -945,7 +945,7 @@ def solve_model(self, input_df: pd.DataFrame, jit: bool = True) -> pd.DataFrame: return output_df.iloc[self.max_lag :, :] # Solves one block of the model for a given time period - def _solve_block( + def _solve_block( # type: ignore self, def_fun, obj_fun, @@ -998,14 +998,21 @@ def _solve_block( tol=self._root_tolerance, maxiter=self.max_iter, ) - if all(np.isfinite(solution.get("x"))) is False: + if all(np.isfinite(solution.get("x"))) is False: # type: ignore solution["status"] = 2 return solution # Gets values from DataFrame via array view for speed # If shape of request > 0 then the request is sent to njit'ed method for speed - def _get_vals(self, array, cols, lags, period, jit): + def _get_vals( + self, + array: NDArray[np.float64], + cols: NDArray[np.int64], + lags: NDArray[np.int64], + period: int, + jit: bool, + ) -> NDArray[np.float64]: if cols.shape[0] == 0: return np.array([], np.float64) @@ -1013,7 +1020,7 @@ def _get_vals(self, array, cols, lags, period, jit): raise IndexError("period is out of range") else: if jit: - return self._get_vals_jit(array, cols, lags, period) + return self._get_vals_jit(array, cols, lags, period) # type: ignore else: return self._get_vals_nojit(array, cols, lags, period) @@ -1021,8 +1028,13 @@ def _get_vals(self, array, cols, lags, period, jit): # Some weird stuff had to be implemented for njit to stop complaining # Not sure if njit increases efficiency @staticmethod - @njit - def _get_vals_jit(array: np.array, cols: np.array, lags: np.array, period: int): + @njit # type: ignore + def _get_vals_jit( + array: NDArray[np.float64], + cols: NDArray[np.int64], + lags: NDArray[np.int64], + period: int, + ) -> NDArray[np.float64]: vals = np.array([0.0], dtype=np.float64) for col, lag in zip(cols, lags): # noqa: B905 vals = np.append(vals, array[period - lag, col]) @@ -1031,7 +1043,12 @@ def _get_vals_jit(array: np.array, cols: np.array, lags: np.array, period: int): # Gets values from DataFrame via array view # Runs if user sets jit to False @staticmethod - def _get_vals_nojit(array: np.array, cols: np.array, lags: np.array, period: int): + def _get_vals_nojit( + array: NDArray[np.float64], + cols: NDArray[np.int64], + lags: NDArray[np.int64], + period: int, + ) -> NDArray[np.float64]: vals = np.array([], dtype=np.float64) for col, lag in zip(cols, lags): # noqa: B905 vals = np.append(vals, array[period - lag, col]) @@ -1039,7 +1056,14 @@ def _get_vals_nojit(array: np.array, cols: np.array, lags: np.array, period: int # Solves root finding problem using simple Newton-Raphson method @staticmethod - def _newton_raphson(f, init, args=None, jac=None, tol=None, maxiter=None): + def _newton_raphson( + f: Callable[[Iterable[Any], Any], NDArray[Any]], + init: NDArray[np.float64], + args: tuple[NDArray[np.float64]], + jac: Callable[[Iterable[Any], Any], NDArray[Any]], + tol: float, + maxiter: int, + ) -> dict[str, NDArray[np.float64] | bool | int]: success = True status = 0 x_i = init @@ -1072,12 +1096,12 @@ def _newton_raphson(f, init, args=None, jac=None, tol=None, maxiter=None): def draw_blockwise_graph( self, - var: str, + var_: str, max_ancs_gens: int = 5, max_desc_gens: int = 5, max_nodes: int = 50, - figsize=(7.5, 7.5), - ): + figsize: tuple[float, float] = (7.5, 7.5), + ) -> None: """Draws a directed graph of a block containing the given variable with a limited number of ancestors and descendants. Parameters: @@ -1108,7 +1132,7 @@ def draw_blockwise_graph( Draws a directed graph of the block containing 'var1' with up to 3 generations of ancestors and 2 generations of descendants. """ - var_node = self._find_var_node(var.lower()) + var_node = self._find_var_node(var_.lower()) ancs_nodes = nx.ancestors(self._augmented_condenced_model_digraph, var_node) desc_nodes = nx.descendants(self._augmented_condenced_model_digraph, var_node) @@ -1138,7 +1162,7 @@ def draw_blockwise_graph( print( " ".join( [ - f"Graph of block containing {var} with <={max_ancs_gens} generations of ancestors and <={max_desc_gens} generations of decendants:", + f"Graph of block containing {var_} with <={max_ancs_gens} generations of ancestors and <={max_desc_gens} generations of decendants:", str(subgraph), ] ) @@ -1217,24 +1241,37 @@ def draw_blockwise_graph( plt.plot() # Returns the node in which var is endogenous - def _find_var_node(self, var): + def _find_var_node(self, var_: str) -> int: if any( [ - var in self._condenced_model_digraph.nodes[x]["members"] + var_ in self._condenced_model_digraph.nodes[x]["members"] for x in self._condenced_model_digraph.nodes() ] ): var_node = [ - var in self._condenced_model_digraph.nodes[x]["members"] + var_ in self._condenced_model_digraph.nodes[x]["members"] for x in self._condenced_model_digraph.nodes() ].index(True) - elif var in self._augmented_condenced_model_digraph.nodes(): - var_node = var + # TODO: Check the old code commented out below. It must be wrong, returning + # an integer below and a string above. Nodes are integers and comparing + # with a string does not make sense. + # elif var_ in self._augmented_condenced_model_digraph.nodes(): + # var_node = var_ + elif any( + [ + var_ in self._augmented_condenced_model_digraph.nodes[x]["members"] + for x in self._augmented_condenced_model_digraph.nodes() + ] + ): + var_node = [ + var_ in self._augmented_condenced_model_digraph.nodes[x]["members"] + for x in self._augmented_condenced_model_digraph.nodes() + ].index(True) else: raise NameError("variable is not in model") return var_node - def trace_to_exog_vars(self, i: str, noisy=True): + def trace_to_exog_vars(self, i: int, noisy: bool = True) -> list[str] | None: """Prints all exogenous variables that are ancestors to the given block. Parameters: @@ -1268,11 +1305,12 @@ def trace_to_exog_vars(self, i: str, noisy=True): ] ) ) + return None else: return self._trace_to_exog_vars(i) ## Finds all exogenous variables that are ancestors to block - def _trace_to_exog_vars(self, i): + def _trace_to_exog_vars(self, i: int) -> list[str]: if i < 1: raise IndexError("block must be >=1") @@ -1282,14 +1320,18 @@ def _trace_to_exog_vars(self, i): ancs_nodes = nx.ancestors(self._augmented_condenced_model_digraph, var_node) - ancs_exog_vars = tuple() + ancs_exog_vars: tuple[str, ...] = () for node in ancs_nodes: - if len(nx.ancestors(self._augmented_condenced_model_digraph, node)) == 0: - ancs_exog_vars += self._node_varlist_mapping.get(node) + if len( + nx.ancestors(self._augmented_condenced_model_digraph, node) + ) == 0 and self._node_varlist_mapping.get(node): + ancs_exog_vars += self._node_varlist_mapping[node] return [x for x in ancs_exog_vars if x not in self.endo_vars] - def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): + def trace_to_exog_vals( + self, i: int, period_index: int, noisy: bool = True + ) -> pd.Series | None: """Traces the given block back to exogenous values and prints those values. Parameters: @@ -1335,7 +1377,7 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): _, ancs_exog_lags, ancs_exog_cols, - ) = get_var_info(self._var_mapping.get(x) for x in ancs_exog_vars) + ) = get_var_info(self._var_mapping[x] for x in ancs_exog_vars) ancs_exog_vals = self._get_vals( output_array, ancs_exog_cols, ancs_exog_lags, period_index, False ) @@ -1350,13 +1392,18 @@ def trace_to_exog_vals(self, i: int, period_index: int, noisy=True): ], sep="\n", ) + return None else: return pd.Series(ancs_exog_vals, index=ancs_exog_vars) + return None + except AttributeError as exc: raise RuntimeError("no solution exists") from exc - def show_block_vals(self, i: int, period_index: int, noisy=True): + def show_block_vals( + self, i: int, period_index: int, noisy: bool = True + ) -> tuple[pd.Series, pd.Series] | None: """Prints the values of endogenous and predetermined variables in a given block for a specific period. Parameters: @@ -1400,7 +1447,7 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): get_var_info = self.gen_get_var_info(var_col_index) - block = self._blocks.get(i) + block = self._blocks[i] _, block_endo_lags, block_endo_cols = get_var_info(block[0]) block_endo_vals = self._get_vals( @@ -1419,7 +1466,7 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): *[ "=".join([x, str(y)]) for x, y in zip( - [self._var_mapping.get(x) for x in block[0]], + [self._var_mapping[x] for x in block[0]], block_endo_vals, strict=True, ) @@ -1433,13 +1480,14 @@ def show_block_vals(self, i: int, period_index: int, noisy=True): *[ "=".join([x, str(y)]) for x, y in zip( - [self._var_mapping.get(x) for x in block[1]], + [self._var_mapping[x] for x in block[1]], block_pred_vals, strict=True, ) ], sep="\n", ) + return None else: return ( pd.Series( @@ -1478,7 +1526,13 @@ def get_var_info( return get_var_info - def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None): + def sensitivity( + self, + i: int, + period_index: int, + method: str = "std", + exog_subset: list[str] | None = None, + ) -> pd.DataFrame: """Analyses sensitivity of endogenous variables to exogenous variables for a specific period. Parameters: @@ -1561,7 +1615,7 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) if j % int(n_exog_vars / div) == 0: print(".", end="") - var, lag = self._lag_mapping.get(self._var_mapping.get(exog_var)) + var, lag = self._lag_mapping[self._var_mapping[exog_var]] solution_diff = self._last_solution.copy() if method == "std": @@ -1580,7 +1634,7 @@ def sensitivity(self, i: int, period_index: int, method="std", exog_subset=None) for key, val in self._sim_code.items(): def_fun, obj_fun, jac, endo_vars, pred_vars, _ = val - solution = self._solve_block( + solution = self._solve_block( # type: ignore def_fun, obj_fun, jac, From ff8b306a8e5becf1fa37a52c92d099549f2ddfb3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Tue, 17 Sep 2024 11:45:01 +0200 Subject: [PATCH 12/22] Fix all remaining mypy errors --- noxfile.py | 2 +- src/model_solver/__init__.py | 2 + src/model_solver/model_solver.py | 4 +- tests/test_model_solver.py | 69 ++++++++++++++++++++------------ 4 files changed, 49 insertions(+), 28 deletions(-) diff --git a/noxfile.py b/noxfile.py index 0020682..bd12793 100644 --- a/noxfile.py +++ b/noxfile.py @@ -144,7 +144,7 @@ def mypy(session: Session) -> None: """Type-check using mypy.""" args = session.posargs or ["src", "tests"] session.install(".") - session.install("mypy", "pytest") + session.install("mypy", "pytest", "pandas-stubs") session.run("mypy", *args) if not session.posargs: session.run("mypy", f"--python-executable={sys.executable}", "noxfile.py") diff --git a/src/model_solver/__init__.py b/src/model_solver/__init__.py index dd7e89f..954b4d8 100644 --- a/src/model_solver/__init__.py +++ b/src/model_solver/__init__.py @@ -1 +1,3 @@ from .model_solver import ModelSolver + +__all__ = ["ModelSolver"] diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 169b413..af62b85 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -1403,7 +1403,7 @@ def trace_to_exog_vals( def show_block_vals( self, i: int, period_index: int, noisy: bool = True - ) -> tuple[pd.Series, pd.Series] | None: + ) -> tuple[pd.Series, pd.Series] | tuple[None, None]: """Prints the values of endogenous and predetermined variables in a given block for a specific period. Parameters: @@ -1487,7 +1487,7 @@ def show_block_vals( ], sep="\n", ) - return None + return None, None else: return ( pd.Series( diff --git a/tests/test_model_solver.py b/tests/test_model_solver.py index f4d8838..1d8b81f 100644 --- a/tests/test_model_solver.py +++ b/tests/test_model_solver.py @@ -1,5 +1,5 @@ -import pandas as pd import numpy as np +import pandas as pd import pytest import model_solver as ms @@ -9,7 +9,7 @@ # Fixtures for test data @pytest.fixture -def equations(): +def equations() -> list[str]: return [ "x1 = a1", "x2 = a2", @@ -21,24 +21,27 @@ def equations(): @pytest.fixture -def endogenous(): +def endogenous() -> list[str]: return ["x1", "x2", "ca", "cb", "k1", "k2"] + @pytest.fixture -def sensitivity_params_std(): - return [1, 1, 'std'] +def sensitivity_params_std() -> tuple[int, int, str]: + return 1, 1, "std" + @pytest.fixture -def sensitivity_params_pct(): - return [1, 1, 'pct'] +def sensitivity_params_pct() -> tuple[int, int, str]: + return 1, 1, "pct" + @pytest.fixture -def sensitivity_params_one(): - return [1, 1, 'one'] +def sensitivity_params_one() -> tuple[int, int, str]: + return 1, 1, "one" @pytest.fixture -def input_data(): +def input_data() -> pd.DataFrame: return pd.DataFrame( { "x1": [2, 4, 1, 2], @@ -57,14 +60,14 @@ def input_data(): # Test for model initialization -def test_model_initialization(equations, endogenous): +def test_model_initialization(equations: list[str], endogenous: list[str]) -> None: model = ms.ModelSolver(equations, endogenous) assert model.eqns == tuple([eq.lower() for eq in equations]) assert model.endo_vars == tuple([var.lower() for var in endogenous]) # Test for block identification -def test_show_blocks(equations, endogenous): +def test_show_blocks(equations: list[str], endogenous: list[str]) -> None: model = ms.ModelSolver(equations, endogenous) model.show_blocks() # Assuming the blocks are stored in an internal structure @@ -72,7 +75,9 @@ def test_show_blocks(equations, endogenous): # Test solving the model -def test_solve_model(equations, endogenous, input_data): +def test_solve_model( + equations: list[str], endogenous: list[str], input_data: pd.DataFrame +) -> None: model = ms.ModelSolver(equations, endogenous) model.describe() model.show_blocks() @@ -101,7 +106,7 @@ def test_solve_model(equations, endogenous, input_data): # Test switching endogenous variables -def test_switch_endo_vars(equations, endogenous): +def test_switch_endo_vars(equations: list[str], endogenous: list[str]) -> None: model = ms.ModelSolver(equations, endogenous) model.switch_endo_vars(["x2"], ["a2"]) assert "x2" not in model.endo_vars @@ -110,31 +115,40 @@ def test_switch_endo_vars(equations, endogenous): # Test tracing to exogenous variables -def test_trace_to_exog_vars(equations, endogenous): +def test_trace_to_exog_vars(equations: list[str], endogenous: list[str]) -> None: model = ms.ModelSolver(equations, endogenous) exog_vars = model.trace_to_exog_vars(5, noisy=False) expected_exog_vars = ["i1", "i2", "a1", "a2"] + assert exog_vars is not None + assert expected_exog_vars is not None assert sorted(exog_vars) == sorted(expected_exog_vars) # Test tracing to exogenous values -def test_trace_to_exog_vals(equations, endogenous, input_data): +def test_trace_to_exog_vals( + equations: list[str], endogenous: list[str], input_data: pd.DataFrame +) -> None: model = ms.ModelSolver(equations, endogenous) solution = model.solve_model(input_data) exog_vals = model.trace_to_exog_vals(5, period_index=1, noisy=False) expected_exog_vals = pd.Series( {"i1": 2.0, "i2": 2.0, "a1": 2.0, "a2": 2.0} ).sort_index() + assert exog_vals is not None exog_vals = exog_vals.sort_index() # Sort before comparison pd.testing.assert_series_equal(exog_vals, expected_exog_vals, rtol=TOLERANCE) # Test showing block values -def test_show_block_vals(equations, endogenous, input_data): +def test_show_block_vals( + equations: list[str], endogenous: list[str], input_data: pd.DataFrame +) -> None: model = ms.ModelSolver(equations, endogenous) model.solve_model(input_data) endo_vals, pred_vals = model.show_block_vals(5, 1, noisy=False) + assert endo_vals is not None + assert pred_vals is not None # Ensure that the endo_vals and pred_vals match expected results from the notebook expected_endo_vals = pd.Series({"ca": 1.942857, "cb": 1.257143}) @@ -147,22 +161,27 @@ def test_show_block_vals(equations, endogenous, input_data): pd.testing.assert_series_equal(pred_vals, expected_pred_vals, rtol=TOLERANCE) -def test_sensitivity(equations, endogenous, input_data, sensitivity_params_std, sensitivity_params_pct, sensitivity_params_one): +def test_sensitivity( + equations: list[str], + endogenous: list[str], + input_data: pd.DataFrame, + sensitivity_params_std: tuple[int, int, str], + sensitivity_params_pct: tuple[int, int, str], + sensitivity_params_one: tuple[int, int, str], +) -> None: model = ms.ModelSolver(equations, endogenous) model.solve_model(input_data) - + # Unpacks fixtures for std, pct and ones, then does analysis sens_std = model.sensitivity(*sensitivity_params_std) sens_pct = model.sensitivity(*sensitivity_params_pct) sens_one = model.sensitivity(*sensitivity_params_one) - + # Checks for results assert sens_std.empty is False assert sens_pct.empty is False assert sens_one.empty is False - # k2 will be in the block analysed with current equation set - assert 'k2' in sens_std.columns - assert np.allclose(4.732277, sens_std['k2'].sum(), atol=0.00001) - - \ No newline at end of file + # k2 will be in the block analysed with current equation set + assert "k2" in sens_std.columns + assert np.allclose(4.732277, sens_std["k2"].sum(), atol=0.00001) From 72c8aebda43c107039d5537a0877c2856be1aeea Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Tue, 17 Sep 2024 13:49:12 +0200 Subject: [PATCH 13/22] Fix ruff errors --- examples/example-model-solver.ipynb | 2 +- src/model_solver/model_solver.py | 31 +++++++++++++++++++---------- tests/test_model_solver.py | 3 +-- 3 files changed, 22 insertions(+), 14 deletions(-) diff --git a/examples/example-model-solver.ipynb b/examples/example-model-solver.ipynb index 9f72320..e69ab43 100644 --- a/examples/example-model-solver.ipynb +++ b/examples/example-model-solver.ipynb @@ -41,7 +41,7 @@ "\n", "# Change directory until find project root\n", "notebook_path = os.getcwd()\n", - "for folder_level in range(50):\n", + "for _folder_level in range(50):\n", " if \"pyproject.toml\" in os.listdir():\n", " break\n", " os.chdir(\"../\")" diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index af62b85..b94e787 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -107,6 +107,8 @@ class ModelSolver: the original solution. """ + _NO_SOLUTION_TEXT = "No solution exist" + # Reads in equations and endogenous variables and does a number of operations, e.g. analyzing block structure using graph theory. def __init__(self, eqns: list[str], endo_vars: list[str]) -> None: self._lag_notation = "__LAG" @@ -164,7 +166,7 @@ def last_solution(self) -> pd.DataFrame: try: return self._last_solution.iloc[self.max_lag :, :] except AttributeError as exc: - raise AttributeError("no solution exists") from exc + raise AttributeError(self._NO_SOLUTION_TEXT) from exc @property def root_tolerance(self) -> float: @@ -553,18 +555,22 @@ def _gen_def_or_obj_fun_and_jac( for eqn in eqns: i = eqn.index("=") lhs, rhs = eqn[:i], eqn[i + 1 :] + rhs_str = "".join(rhs).strip().strip("+") if len(eqns) == 1 and endo_var == "".join(lhs) and endo_var not in rhs: if len(pred_vars) == 0: return ( - lambda _: np.array([eval("".join(rhs).strip().strip("+"))]), + lambda _, rhs_str_=rhs_str: np.array([eval(rhs_str_)]), None, None, ) - def_fun = eval("".join(rhs).strip().strip("+")) + def_fun = eval(rhs_str) def_fun_lam = Lambdify([pred_sym], def_fun) - def_fun_out = lambda args: np.array( - [def_fun_lam(args)], dtype=np.float64 - ) + + def def_fun_out( + args: list[Symbol], def_fun_lam_=def_fun_lam + ) -> NDArray[np.float64]: + return np.array([def_fun_lam_(args)], dtype=np.float64) + return def_fun_out, None, None if ("min(" in lhs) or ("min(" in rhs): @@ -591,8 +597,11 @@ def _gen_def_or_obj_fun_and_jac( obj_fun_lam = Lambdify([*endo_sym, *pred_sym], obj_fun, cse=True) jac_lam = Lambdify([*endo_sym, *pred_sym], jac, cse=True) - obj_fun_out = lambda val_list, *args: obj_fun_lam(*val_list, *args) - jac_out = lambda val_list, *args: jac_lam(*val_list, *args) + def obj_fun_out(val_list, *args): + return obj_fun_lam(*val_list, *args) + + def jac_out(val_list, *args): + return jac_lam(*val_list, *args) return None, obj_fun_out, jac_out @@ -1399,7 +1408,7 @@ def trace_to_exog_vals( return None except AttributeError as exc: - raise RuntimeError("no solution exists") from exc + raise RuntimeError(self._NO_SOLUTION_TEXT) from exc def show_block_vals( self, i: int, period_index: int, noisy: bool = True @@ -1501,7 +1510,7 @@ def show_block_vals( ) except AttributeError as exc: - raise RuntimeError("no solution exists") from exc + raise RuntimeError(self._NO_SOLUTION_TEXT) from exc # Function that returns function that returns names, columns and lags for variables def gen_get_var_info( @@ -1579,7 +1588,7 @@ def sensitivity( ) } except AttributeError as exc: - raise AttributeError("no solution exists") from exc + raise AttributeError(self._NO_SOLUTION_TEXT) from exc get_var_info = cache(self.gen_get_var_info(var_col_index)) diff --git a/tests/test_model_solver.py b/tests/test_model_solver.py index 1d8b81f..ffeaf70 100644 --- a/tests/test_model_solver.py +++ b/tests/test_model_solver.py @@ -120,7 +120,6 @@ def test_trace_to_exog_vars(equations: list[str], endogenous: list[str]) -> None exog_vars = model.trace_to_exog_vars(5, noisy=False) expected_exog_vars = ["i1", "i2", "a1", "a2"] assert exog_vars is not None - assert expected_exog_vars is not None assert sorted(exog_vars) == sorted(expected_exog_vars) @@ -129,7 +128,7 @@ def test_trace_to_exog_vals( equations: list[str], endogenous: list[str], input_data: pd.DataFrame ) -> None: model = ms.ModelSolver(equations, endogenous) - solution = model.solve_model(input_data) + model.solve_model(input_data) exog_vals = model.trace_to_exog_vals(5, period_index=1, noisy=False) expected_exog_vals = pd.Series( {"i1": 2.0, "i2": 2.0, "a1": 2.0, "a2": 2.0} From 1b57d95276734d35dc8b6e4530663e15815b06c2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Tue, 17 Sep 2024 14:10:34 +0200 Subject: [PATCH 14/22] Store example notebook in .py-format instead of .ipynb-format --- examples/example-model-solver.ipynb | 299 -------------------------- examples/example-model-solver.py | 148 +++++++++++++ poetry.lock | 315 +++++++++++++++++++++++++++- pyproject.toml | 6 + 4 files changed, 467 insertions(+), 301 deletions(-) delete mode 100644 examples/example-model-solver.ipynb create mode 100644 examples/example-model-solver.py diff --git a/examples/example-model-solver.ipynb b/examples/example-model-solver.ipynb deleted file mode 100644 index e69ab43..0000000 --- a/examples/example-model-solver.ipynb +++ /dev/null @@ -1,299 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Example of use of **ModelSolver**\n", - "#### Magnus Kvåle Helliesen, mkh@ssb.no\n", - "\n", - "This Notebook shows basic useage of **ModelSolver**.\n", - "The algorithm analyzes and solves an input-output model used in the Norwegian monthly national accounts with more than 15,500 equations in under a minute for more than 30 months on a laptop computer.\n", - "\n", - "To import **ModelSolver** you need the following packages installed:\n", - "* NumPy\n", - "* NetworkX\n", - "* Pandas\n", - "* SymEngine\n", - "* Numba\n", - "* collections\n", - "* functools\n", - "* Matplotlib" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Load class and initialize class\n", - "We first load all packages and the model class itself:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "import os\n", - "\n", - "# Change directory until find project root\n", - "notebook_path = os.getcwd()\n", - "for _folder_level in range(50):\n", - " if \"pyproject.toml\" in os.listdir():\n", - " break\n", - " os.chdir(\"../\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import src.model_solver as ms\n", - "\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We define lists of equations and endogenous variables.\n", - "These are what together *define* a particular **ModelSolver** class instance:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "equations = [\n", - " \"x1 = a1\",\n", - " \"x2 = a2\",\n", - " \"0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1\",\n", - " \"0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2\",\n", - " \"k1 = k1(-1)+i1\",\n", - " \"k2 = k2(-1)+i2\",\n", - "]\n", - "endogenous = [\"x1\", \"x2\", \"ca\", \"cb\", \"k1\", \"k2\"]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We initiate an instance of **ModelSolver** class called *model*:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "model = ms.ModelSolver(equations, endogenous)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We let **ModelSolver** describe the model to us:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.describe()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can also inspect all the blocks:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.show_blocks()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Solve the model subject to data\n", - "\n", - "We make a Pandas DataFrame:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "input_data = pd.DataFrame(\n", - " {\n", - " \"x1\": [2, 4, 1, 2],\n", - " \"x2\": [2, 1, 2, 3],\n", - " \"ca\": [1, 3, 4, 1],\n", - " \"cb\": [1, 2, 1, 4],\n", - " \"k1\": [1, 3, 4, 1],\n", - " \"k2\": [1, 2, 1, 4],\n", - " \"a1\": [1, 2, 4, 4],\n", - " \"a2\": [3, 2, 3, 4],\n", - " \"i1\": [1, 2, 4, 4],\n", - " \"i2\": [3, 2, 3, 4],\n", - " },\n", - " index=[\"2019Q1\", \"2019Q2\", \"2020Q3\", \"2020Q4\"],\n", - ")\n", - "input_data.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The data contain exogenous variables and initial values for endogenous variables." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We call the method that solves the model, subject to the data in the DataFrame:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "solution = model.solve_model(input_data)\n", - "solution.head()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We make a graph of some variable showing what block it's in, and what blocks are it's ancestors and decendants." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.draw_blockwise_graph(\"ca\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Switch endogenous variables and analyze new model\n", - "\n", - "We ask **ModelSolver** to make $x1$ exogenous and $a1$ endogenous:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.switch_endo_vars([\"x2\"], [\"a2\"])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We inspect the blocks of this new model:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.show_blocks()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We make graph plot of the same variable as above showing what block it's in, and what blocks are it's ancestors and decendants.\n", - "We observe that the graph has changed after swithcing endogenous variables." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.draw_blockwise_graph(\"ca\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "model.show_block_vals(5, 1)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [] - }, - "outputs": [], - "source": [ - "model.show_block(2)" - ] - } - ], - "metadata": { - "language_info": { - "codemirror_mode": { - "name": "ipython" - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/examples/example-model-solver.py b/examples/example-model-solver.py new file mode 100644 index 0000000..d8b0efc --- /dev/null +++ b/examples/example-model-solver.py @@ -0,0 +1,148 @@ +# --- +# jupyter: +# jupytext: +# text_representation: +# extension: .py +# format_name: percent +# format_version: '1.3' +# kernelspec: +# display_name: ssb-model-solver +# language: python +# name: ssb-model-solver +# --- + +# %% [markdown] +# # Example of use of **ModelSolver** +# #### Magnus Kvåle Helliesen, mkh@ssb.no +# +# This Notebook shows basic useage of **ModelSolver**. +# The algorithm analyzes and solves an input-output model used in the Norwegian monthly national accounts with more than 15,500 equations in under a minute for more than 30 months on a laptop computer. +# +# To import **ModelSolver** you need the following packages installed: +# * NumPy +# * NetworkX +# * Pandas +# * SymEngine +# * Numba +# * collections +# * functools +# * Matplotlib + +# %% [markdown] +# ## Load class and initialize class +# We first load all packages and the model class itself: + +# %% +import os + +# Change directory until find project root +notebook_path = os.getcwd() +for _folder_level in range(50): + if "pyproject.toml" in os.listdir(): + break + os.chdir("../") + +# %% +import pandas as pd +import src.model_solver as ms + +# %matplotlib inline + +# %% [markdown] +# We define lists of equations and endogenous variables. +# These are what together *define* a particular **ModelSolver** class instance: + +# %% +equations = [ + "x1 = a1", + "x2 = a2", + "0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1", + "0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2", + "k1 = k1(-1)+i1", + "k2 = k2(-1)+i2", +] +endogenous = ["x1", "x2", "ca", "cb", "k1", "k2"] + +# %% [markdown] +# We initiate an instance of **ModelSolver** class called *model*: + +# %% +model = ms.ModelSolver(equations, endogenous) + +# %% [markdown] +# We let **ModelSolver** describe the model to us: + +# %% +model.describe() + +# %% [markdown] +# We can also inspect all the blocks: + +# %% +model.show_blocks() + +# %% [markdown] +# ## Solve the model subject to data +# +# We make a Pandas DataFrame: + +# %% +input_data = pd.DataFrame( + { + "x1": [2, 4, 1, 2], + "x2": [2, 1, 2, 3], + "ca": [1, 3, 4, 1], + "cb": [1, 2, 1, 4], + "k1": [1, 3, 4, 1], + "k2": [1, 2, 1, 4], + "a1": [1, 2, 4, 4], + "a2": [3, 2, 3, 4], + "i1": [1, 2, 4, 4], + "i2": [3, 2, 3, 4], + }, + index=["2019Q1", "2019Q2", "2020Q3", "2020Q4"], +) +input_data.head() + +# %% [markdown] +# The data contain exogenous variables and initial values for endogenous variables. + +# %% [markdown] +# We call the method that solves the model, subject to the data in the DataFrame: + +# %% +solution = model.solve_model(input_data) +solution.head() + +# %% [markdown] +# We make a graph of some variable showing what block it's in, and what blocks are it's ancestors and decendants. + +# %% +model.draw_blockwise_graph("ca") + +# %% [markdown] +# ## Switch endogenous variables and analyze new model +# +# We ask **ModelSolver** to make $x1$ exogenous and $a1$ endogenous: + +# %% +model.switch_endo_vars(["x2"], ["a2"]) + +# %% [markdown] +# We inspect the blocks of this new model: + +# %% +model.show_blocks() + +# %% [markdown] +# We make graph plot of the same variable as above showing what block it's in, and what blocks are it's ancestors and decendants. +# We observe that the graph has changed after swithcing endogenous variables. + +# %% +model.draw_blockwise_graph("ca") + +# %% +model.show_block_vals(5, 1) + +# %% +model.show_block(2) diff --git a/poetry.lock b/poetry.lock index b5147ac..73fa669 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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extras = ["colors"], version = ">=0.15.10" } myst-parser = { version = ">=0.16.1" } pandas-stubs = ">=2.2.2.240807" +ipykernel = ">=6.29.5" [tool.poetry.scripts] ssb-model-solver = "model_solver.__main__:main" @@ -147,6 +148,11 @@ classmethod-decorators = ["classmethod", "validator", "root_validator", "pydanti "S101", # asserts are encouraged in pytest ] +[tool.jupytext] +formats = "ipynb,auto:percent" +notebook_metadata_filter = "jupytext.text_representation,-jupytext.text_representation.jupytext_version,-widgets,-varInspector" +cell_metadata_filter = "-papermill,tags" + [build-system] requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" From b82e373c7001d83db6d0c93d2360b9bb019b0516 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Tue, 17 Sep 2024 15:25:48 +0200 Subject: [PATCH 15/22] Add missing docstrings --- pyproject.toml | 4 +-- src/model_solver/__init__.py | 2 ++ src/model_solver/model_solver.py | 46 +++++++++++++++++++++++--------- 3 files changed, 38 insertions(+), 14 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index e4bc02b..3052f94 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -99,9 +99,9 @@ extend-exclude = [ [tool.ruff.lint] select = [ "A", # prevent using keywords that clobber python builtins -# "ANN", # check type annotations + "ANN", # check type annotations "B", # bugbear: security warnings -# "D", # documentation + "D", # documentation "E", # pycodestyle "F", # pyflakes "ISC", # implicit string concatenation diff --git a/src/model_solver/__init__.py b/src/model_solver/__init__.py index 954b4d8..a9f5c29 100644 --- a/src/model_solver/__init__.py +++ b/src/model_solver/__init__.py @@ -1,3 +1,5 @@ +"""SSB Model Solver.""" + from .model_solver import ModelSolver __all__ = ["ModelSolver"] diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index b94e787..cdc46c9 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -111,6 +111,12 @@ class ModelSolver: # Reads in equations and endogenous variables and does a number of operations, e.g. analyzing block structure using graph theory. def __init__(self, eqns: list[str], endo_vars: list[str]) -> None: + """Reads in equations and endogenous variables and does a number of operations, e.g. analyzing block structure using graph theory. + + Args: + eqns: A list of equations in string format + endo_vars: A list of endogenous variables + """ self._lag_notation = "__LAG" self._max_lag = 0 self._root_tolerance = 1e-7 @@ -143,14 +149,17 @@ def __init__(self, eqns: list[str], endo_vars: list[str]) -> None: @property def eqns(self) -> tuple[str, ...]: + """Return the equations in the model.""" return self._eqns @property def endo_vars(self) -> tuple[str, ...]: + """Return the endogenous variables in the model.""" return self._endo_vars @property def exog_vars(self) -> tuple[str, ...]: + """Return the exogenous variables in the model.""" vars_: set[str] = set() for _, _, _, lag_mapping in self._eqns_analyzed: for _, val in lag_mapping.items(): @@ -159,10 +168,19 @@ def exog_vars(self) -> tuple[str, ...]: @property def max_lag(self) -> int: + """Return max_lag in the model.""" return self._max_lag @property def last_solution(self) -> pd.DataFrame: + """Returns the last found solution in the model. + + Returns: + The last found solution as a dataframe. + + Raises: + AttributeError: If no solution is found. + """ try: return self._last_solution.iloc[self.max_lag :, :] except AttributeError as exc: @@ -170,6 +188,7 @@ def last_solution(self) -> pd.DataFrame: @property def root_tolerance(self) -> float: + """Return root tolerance.""" return self._root_tolerance @root_tolerance.setter @@ -182,6 +201,7 @@ def root_tolerance(self, val: float) -> None: @property def max_iter(self) -> int: + """Return maximum number of iterations.""" return self._max_iter @max_iter.setter @@ -567,7 +587,8 @@ def _gen_def_or_obj_fun_and_jac( def_fun_lam = Lambdify([pred_sym], def_fun) def def_fun_out( - args: list[Symbol], def_fun_lam_=def_fun_lam + args: list[Symbol], + def_fun_lam_: Callable[[list[Symbol]], Any] = def_fun_lam, ) -> NDArray[np.float64]: return np.array([def_fun_lam_(args)], dtype=np.float64) @@ -597,10 +618,10 @@ def def_fun_out( obj_fun_lam = Lambdify([*endo_sym, *pred_sym], obj_fun, cse=True) jac_lam = Lambdify([*endo_sym, *pred_sym], jac, cse=True) - def obj_fun_out(val_list, *args): + def obj_fun_out(val_list, *args): # type: ignore # noqa return obj_fun_lam(*val_list, *args) - def jac_out(val_list, *args): + def jac_out(val_list, *args): # type: ignore # noqa return jac_lam(*val_list, *args) return None, obj_fun_out, jac_out @@ -956,14 +977,14 @@ def solve_model(self, input_df: pd.DataFrame, jit: bool = True) -> pd.DataFrame: # Solves one block of the model for a given time period def _solve_block( # type: ignore self, - def_fun, - obj_fun, - jac, - endo_vars_info, - pred_vars_info, - output_array, - period, - jit, + def_fun, # noqa: ANN001 + obj_fun, # noqa: ANN001 + jac, # noqa: ANN001 + endo_vars_info, # noqa: ANN001 + pred_vars_info, # noqa: ANN001 + output_array, # noqa: ANN001 + period, # noqa: ANN001 + jit, # noqa: ANN001 ): ( _, @@ -1512,12 +1533,13 @@ def show_block_vals( except AttributeError as exc: raise RuntimeError(self._NO_SOLUTION_TEXT) from exc - # Function that returns function that returns names, columns and lags for variables def gen_get_var_info( self, var_col_index: dict[str, int] ) -> Callable[ [Iterable[str]], tuple[list[str], NDArray[np.int64], NDArray[np.int64]] ]: + """Function that returns function that returns names, columns and lags for variables.""" + def get_var_info( vars_: Iterable[str], ) -> tuple[list[str], NDArray[np.int64], NDArray[np.int64]]: From 974e34d0efdaeae7c4633e4b9d60cfbddda7701d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Wed, 18 Sep 2024 10:30:36 +0200 Subject: [PATCH 16/22] Disable typeguard checking due to problems with numba Numba is not generally able to compile arbitrary Python code. Get this typeguard error in function _get_vals_jit: numba.core.errors.TypingError: Failed in nopython mode pipeline (step: nopython frontend). See also: https://github.com/numba/numba/issues/6612 and numba supported python constructs: https://numba.readthedocs.io/en/stable/reference/pysupported.html --- .github/workflows/tests.yml | 1 - noxfile.py | 1 - 2 files changed, 2 deletions(-) diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index ed98407..61c3d6c 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -24,7 +24,6 @@ jobs: - { python: "3.12", os: "ubuntu-latest", session: "tests" } - { python: "3.12", os: "windows-latest", session: "tests" } - { python: "3.12", os: "macos-latest", session: "tests" } - - { python: "3.10", os: "ubuntu-latest", session: "typeguard" } - { python: "3.10", os: "ubuntu-latest", session: "xdoctest" } - { python: "3.10", os: "ubuntu-latest", session: "docs-build" } diff --git a/noxfile.py b/noxfile.py index bd12793..d3fdf98 100644 --- a/noxfile.py +++ b/noxfile.py @@ -29,7 +29,6 @@ "pre-commit", "mypy", "tests", - "typeguard", "xdoctest", "docs-build", ) From 1bc8bff725f5e42ee392dfac5440ae8132ea2b0e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Wed, 18 Sep 2024 19:34:49 +0200 Subject: [PATCH 17/22] Fix docstrings and cleanup --- docs/conf.py | 3 + docs/reference.md | 4 +- poetry.lock | 246 +++++++------- pyproject.toml | 3 - src/model_solver/__main__.py | 13 - src/model_solver/functions.py | 35 -- src/model_solver/model_solver.py | 545 ++++++++++++++----------------- tests/test_functions.py | 6 - tests/test_main.py | 18 - 9 files changed, 356 insertions(+), 517 deletions(-) delete mode 100644 src/model_solver/__main__.py delete mode 100644 src/model_solver/functions.py delete mode 100644 tests/test_functions.py delete mode 100644 tests/test_main.py diff --git a/docs/conf.py b/docs/conf.py index 5ee4de4..c9e0045 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -67,3 +67,6 @@ # Do not prepend module names to object names add_module_names = False + +# Napoleon settings +napoleon_include_init_with_doc = True diff --git a/docs/reference.md b/docs/reference.md index 9050ec0..3fc6a9c 100644 --- a/docs/reference.md +++ b/docs/reference.md @@ -16,10 +16,10 @@ model\_solver package ============================================================================= -model\_solver.functions module +model\_solver.model\_solver module ----------------------------------------------------------------------------- -.. automodule:: model_solver.functions +.. automodule:: model_solver.model_solver :members: :undoc-members: :show-inheritance: diff --git a/poetry.lock b/poetry.lock index 73fa669..a9aee57 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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(>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", [[package]] name = "virtualenv" -version = "20.26.4" +version = "20.26.5" description = "Virtual Python Environment builder" optional = false python-versions = ">=3.7" files = [ - {file = "virtualenv-20.26.4-py3-none-any.whl", hash = "sha256:48f2695d9809277003f30776d155615ffc11328e6a0a8c1f0ec80188d7874a55"}, - {file = "virtualenv-20.26.4.tar.gz", hash = "sha256:c17f4e0f3e6036e9f26700446f85c76ab11df65ff6d8a9cbfad9f71aabfcf23c"}, + {file = "virtualenv-20.26.5-py3-none-any.whl", hash = "sha256:4f3ac17b81fba3ce3bd6f4ead2749a72da5929c01774948e243db9ba41df4ff6"}, + {file = "virtualenv-20.26.5.tar.gz", hash = "sha256:ce489cac131aa58f4b25e321d6d186171f78e6cb13fafbf32a840cee67733ff4"}, ] [package.dependencies] diff --git a/pyproject.toml b/pyproject.toml index 3052f94..6216676 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -47,9 +47,6 @@ myst-parser = { version = ">=0.16.1" } pandas-stubs = ">=2.2.2.240807" ipykernel = ">=6.29.5" -[tool.poetry.scripts] -ssb-model-solver = "model_solver.__main__:main" - [tool.coverage.paths] source = ["src", "*/site-packages"] tests = ["tests", "*/tests"] diff --git a/src/model_solver/__main__.py b/src/model_solver/__main__.py deleted file mode 100644 index 332cea5..0000000 --- a/src/model_solver/__main__.py +++ /dev/null @@ -1,13 +0,0 @@ -"""Command-line interface.""" - -import click - - -@click.command() -@click.version_option() -def main() -> None: - """SSB Model Solver.""" - - -if __name__ == "__main__": - main(prog_name="ssb-model-solver") # pragma: no cover diff --git a/src/model_solver/functions.py b/src/model_solver/functions.py deleted file mode 100644 index cc54f7f..0000000 --- a/src/model_solver/functions.py +++ /dev/null @@ -1,35 +0,0 @@ -"""A collection of useful functions. - -The template and this example uses Google style docstrings as described at: -https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html - -""" - - -def example_function(number1: int, number2: int) -> str: - """Compare two integers. - - This is merely an example function can be deleted. It is used to show and test generating - documentation from code, type hinting, testing, and testing examples - in the code. - - - Args: - number1: The first number. - number2: The second number, which will be compared to number1. - - Returns: - A string describing which number is the greatest. - - Examples: - Examples should be written in doctest format, and should illustrate how - to use the function. - - >>> example_function(1, 2) - 1 is less than 2 - - """ - if number1 < number2: - return f"{number1} is less than {number2}" - - return f"{number1} is greater than or equal to {number2}" diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index cdc46c9..3f0f9b2 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -36,6 +36,8 @@ class ModelSolver: Let `equations` and `endogenous` be lists containing equations and endogenous variables, respectively, stored as strings, e.g., + .. code-block:: python + equations = [ 'x + y = A', 'x / y = B' @@ -49,7 +51,7 @@ class ModelSolver: To initialize a ModelSolver instance, use: - model = ModelSolver(equations, endogenous) + model = ModelSolver(equations, endogenous) This reads in the equations and endogenous variables, performs block analysis and ordering, and generates simulation code. @@ -58,53 +60,8 @@ class ModelSolver: solution_df = model.solve_model(input_df) - Now, "solution_df" is a Pandas DataFrame with the same dimensions as "input_df," but with the endogenous variables replaced by the solutions to the model. - The last solution is also stored in "model.last_solution." - - Attributes: - ---------- - last_solution : pandas DataFrame - The last solved solution. - - Methods: - ------- - solve_model(input_df) - Solves the model based on input data in a Pandas DataFrame. - Returns a DataFrame with the same dimensions as input_df. - - describe(): - Describes the model in terms of the number of equations and blocks, - along with information about the blocks. - - find_endo_var(endogenous_variable[, noisy=False]): - Returns the block in which the endogenous variable is solved for. - - show_block(block_number): - Returns information about a specific block, including its - endogenous variables, exogenous and predetermined variables, and equations. - - show_blocks(): - Returns information about all the blocks in the model. - - trace_to_exog_vars(block_number[, noisy=True]): - Traces the model DiGraph from the block back to the nodes of origin - and reports which exogenous variables determine those nodes. - - trace_to_exog_vals(block_number, period_index[, noisy=True]): - Traces the model DiGraph back from the block to the nodes of origin, - determines what exogenous variables influence those nodes, and reports - the values of those variables for the chosen period index. - - draw_blockwise_graph(): - Draws a network graph based on the model. Takes a variable name, - the maximum number of ancestor and descendant nodes, and the maximum - number of nodes in total as arguments. - - sensitivity(block_number, period_index[, method='std', exog_subset=None]): - Analyzes the sensitivity of endogenous variables to exogenous variables - for a specific period index. The method varies the exogenous variables - and reports the deviations in the block's endogenous variables from - the original solution. + Now, `solution_df` is a Pandas DataFrame with the same dimensions as `input_df`, but with the endogenous variables replaced by the solutions to the model. + The last solution is also stored in `model.last_solution`. """ _NO_SOLUTION_TEXT = "No solution exist" @@ -116,6 +73,24 @@ def __init__(self, eqns: list[str], endo_vars: list[str]) -> None: Args: eqns: A list of equations in string format endo_vars: A list of endogenous variables + + Example: + >>> equations = ["x1 = a1", "x2 = a2", "0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1", "0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2", "k1 = k1(-1)+i1", "k2 = k2(-1)+i2"] + >>> endogenous = ["x1", "x2", "ca", "cb", "k1", "k2"] + >>> model = ModelSolver(equations, endogenous) + ---------------------------------------------------------------------------------------------------- + Initializing model + * Importing equations + * Importing endogenous variables + * Analyzing model + * Analyzing equation strings + * Generating bipartite graph (BiGraph) connecting equations and endogenous variables + * Finding maximum bipartite match (MBM) (i.e. associating every equation with exactly one endogenus variable) + * Generating directed graph (DiGraph) connecting endogenous variables using bipartite graph and MBM + * Finding condensation of DiGraph (i.e. determining minimal blocks of systems of simulataneous equations) + * Generating simulation code (i.e. block-wise symbolic objective function, symbolic Jacobian matrix and lists of endogenous and exogenous variables) + Finished + ---------------------------------------------------------------------------------------------------- """ self._lag_notation = "__LAG" self._max_lag = 0 @@ -631,32 +606,25 @@ def switch_endo_vars( ) -> None: """Sets old_endo_vars as exogenous and new_endo_vars as endogenous and performs block analysis. - Parameters: - ---------- - old_endo_vars : list of str - List of old endogenous variables to be switched to exogenous. + Note: + This function switches the endogenous and exogenous status of variables and + performs block analysis on the model. - new_endo_vars : list of str - List of new endogenous variables to be switched from exogenous. + Example: - Returns: - ------- - None + .. code-block:: python - Notes: - ------ - This function switches the endogenous and exogenous status of variables and performs block analysis on the model. + model = ModelSolver(equations, endogenous) + model.switch_endo_vars(['var1', 'var2'], ['var3', 'var4']) - Raises: - ------ - ValueError: - If any variable in `old_endo_vars` is not in the current list of endogenous variables. - If any variable in `new_endo_vars` is already in the list of endogenous variables. + Args: + old_endo_vars: List of old endogenous variables to be switched to exogenous. + new_endo_vars: List of new endogenous variables to be switched from exogenous. - Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> model.switch_endo_vars(['var1', 'var2'], ['var3', 'var4']) + Raises: + ValueError: If any variable in `old_endo_vars` is not in the current list + of endogenous variables or if any variable in `new_endo_vars` is already + in the list of endogenous variables. """ if all(x in self.endo_vars for x in old_endo_vars) is False: raise RuntimeError("all variables in old_endo_vars are not endogenous") @@ -683,25 +651,18 @@ def switch_endo_vars( def find_endo_var(self, endo_var: str, noisy: bool = False) -> int | None: """Find the block that solves the specified endogenous variable. - Parameters - ---------- - endo_var : str - The endogenous variable to be found. + Note: + This function searches for the specified endogenous variable in the model's + blocks and returns the block number of the block that solves it. If the endogenous + variable is not found in any block, it returns None. - noisy : bool, optional - Whether output should be printed or returned. + Args: + endo_var: The endogenous variable to be found. + noisy: Whether output should be printed or returned. Returns: - ------- - int or None The block number of the block that solves the specified endogenous variable. - Returns None if the endogenous variable is not found in any block. - - Notes: - ----- - This function searches for the specified endogenous variable in the model's - blocks and returns the block number of the block that solves it. If the endogenous - variable is not found in any block, it returns None. + Returns `None` if the endogenous variable is not found in any block. """ block = [key for key, val in self._blocks.items() if endo_var.lower() in val[0]] if block: @@ -718,10 +679,6 @@ def describe(self) -> None: Prints information about the model, including the number of equations, blocks, simple definition blocks, and the distribution of equation counts in the blocks. - - Returns: - ------- - None """ print("-" * 100) print( @@ -741,61 +698,62 @@ def show_blocks(self) -> None: Iterates through all blocks in the model and calls the `show_block` function to display their details. - Returns: - ------- - None - Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> model.show_blocks() - - -------------------------------------------------- - Block 1 - -------------------------------------------------- - Endogenous Variables: - - var1 - - var2 - - Exogenous Variables: - - exog_var1 - - exog_var2 - - Equations: - - eqn1: var1 = exog_var1 + exog_var2 - - eqn2: var2 = var1 + exog_var2 - - -------------------------------------------------- - Block 2 - -------------------------------------------------- - Endogenous Variables: - - var3 - - var4 - - Exogenous Variables: - - exog_var3 - - exog_var4 - - Equations: - - eqn3: var3 = exog_var3 + exog_var4 - - eqn4: var4 = var3 + exog_var4 - - ... - - -------------------------------------------------- - Block n - -------------------------------------------------- - Endogenous Variables: - - var_n1 - - var_n2 - - Exogenous Variables: - - exog_var_n1 - - exog_var_n2 - - Equations: - - eqn_n1: var_n1 = exog_var_n1 + exog_var_n2 - - eqn_n2: var_n2 = var_n1 + exog_var_n2 + + .. code-block:: python + + model = ModelSolver(equations, endogenous) + model.show_blocks() + + The output is like this:: + + -------------------------------------------------- + Block 1 + -------------------------------------------------- + Endogenous Variables: + - var1 + - var2 + + Exogenous Variables: + - exog_var1 + - exog_var2 + + Equations: + - eqn1: var1 = exog_var1 + exog_var2 + - eqn2: var2 = var1 + exog_var2 + + -------------------------------------------------- + Block 2 + -------------------------------------------------- + Endogenous Variables: + - var3 + - var4 + + Exogenous Variables: + - exog_var3 + - exog_var4 + + Equations: + - eqn3: var3 = exog_var3 + exog_var4 + - eqn4: var4 = var3 + exog_var4 + + ... + + -------------------------------------------------- + Block n + -------------------------------------------------- + Endogenous Variables: + - var_n1 + - var_n2 + + Exogenous Variables: + - exog_var_n1 + - exog_var_n2 + + Equations: + - eqn_n1: var_n1 = exog_var_n1 + exog_var_n2 + - eqn_n2: var_n2 = var_n1 + exog_var_n2 + """ for key, _ in self._blocks.items(): print(" ".join(["-" * 50, "Block", str(key), "-" * 50])) @@ -804,39 +762,36 @@ def show_blocks(self) -> None: def show_block(self, i: int) -> None: """Prints endogenous and exogenous variables and equations for a given block. - Parameters: - ----------- - i : int - The index of the block to display. + Args: + i: The index of the block to display. - Returns: - -------- - None Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> model.show_block(1) - - Block consists of an equation or a system of equations - - 5 endogenous variables: - - var1 - - var2 - - var3 - - var4 - - var5 - - 3 predetermined variables: - - pred_var1 - - pred_var2 - - pred_var3 - - 4 equations: - - eqn1: var1 = pred_var1 + pred_var2 - - eqn2: var2 = var1 + pred_var2 - - eqn3: var3 = pred_var2 + pred_var3 - - eqn4: var4 = var3 + pred_var1 + + .. code-block:: python + + model = ModelSolver(equations, endogenous) + model.show_block(1) + + A block consists of an equation or a system of equations:: + + 5 endogenous variables: + - var1 + - var2 + - var3 + - var4 + - var5 + + 3 predetermined variables: + - pred_var1 + - pred_var2 + - pred_var3 + + 4 equations: + - eqn1: var1 = pred_var1 + pred_var2 + - eqn2: var2 = var1 + pred_var2 + - eqn3: var3 = pred_var2 + pred_var3 + - eqn4: var4 = var3 + pred_var1 """ block = self._blocks.get(i) @@ -874,30 +829,43 @@ def show_block(self, i: int) -> None: def solve_model(self, input_df: pd.DataFrame, jit: bool = True) -> pd.DataFrame: """Solves the model subject to a given DataFrame. - Parameters: - ----------- - input_df : pd.DataFrame - A DataFrame containing input data for the model. - - jit : bool, optional - Flag indicating whether to use just-in-time (JIT) compilation for solving equations. - Default is True. + Args: + input_df: A DataFrame containing input data for the model. + jit: Flag indicating whether to use just-in-time (JIT) compilation for solving equations. Returns: - -------- - pd.DataFrame A DataFrame containing the model's output data. Raises: - ------- - TypeError: - If any column in `input_df` is not of numeric data type. + TypeError: If any column in `input_df` is not of numeric data type. Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> input_data = pd.DataFrame({'var1': [1.0, 2.0, 3.0], 'var2': [0.5, 1.0, 1.5]}) - >>> output_data = model.solve_model(input_data) + >>> equations = ["x1 = a1", "x2 = a2", "0.2*x1+0.7*x2 = 0.1*ca+0.8*cb+0.3*i1", "0.8*x1+0.3*x2 = 0.9*ca+0.2*cb+0.1*i2", "k1 = k1(-1)+i1", "k2 = k2(-1)+i2"] + >>> endogenous = ["x1", "x2", "ca", "cb", "k1", "k2"] + >>> model = ModelSolver(equations, endogenous) + ---------------------------------------------------------------------------------------------------- + Initializing model + * Importing equations + * Importing endogenous variables + * Analyzing model + * Analyzing equation strings + * Generating bipartite graph (BiGraph) connecting equations and endogenous variables + * Finding maximum bipartite match (MBM) (i.e. associating every equation with exactly one endogenus variable) + * Generating directed graph (DiGraph) connecting endogenous variables using bipartite graph and MBM + * Finding condensation of DiGraph (i.e. determining minimal blocks of systems of simulataneous equations) + * Generating simulation code (i.e. block-wise symbolic objective function, symbolic Jacobian matrix and lists of endogenous and exogenous variables) + Finished + ---------------------------------------------------------------------------------------------------- + >>> input_data = pd.DataFrame({"x1": [2, 4, 1, 2], "x2": [2, 1, 2, 3], "ca": [1, 3, 4, 1], "cb": [1, 2, 1, 4], "k1": [1, 3, 4, 1], "k2": [1, 2, 1, 4], "a1": [1, 2, 4, 4], "a2": [3, 2, 3, 4], "i1": [1, 2, 4, 4], "i2": [3, 2, 3, 4]}) + >>> output_data = model.solve_model(input_data) + ---------------------------------------------------------------------------------------------------- + Solving model + First period: 1, last period: 3 + Solving + | | + ... + Finished + ---------------------------------------------------------------------------------------------------- """ if ( all(np.issubdtype(input_df[x].dtype, np.number) for x in input_df.columns) # type: ignore @@ -1126,7 +1094,7 @@ def _newton_raphson( def draw_blockwise_graph( self, - var_: str, + variable: str, max_ancs_gens: int = 5, max_desc_gens: int = 5, max_nodes: int = 50, @@ -1134,35 +1102,23 @@ def draw_blockwise_graph( ) -> None: """Draws a directed graph of a block containing the given variable with a limited number of ancestors and descendants. - Parameters: - ----------- - var : str - The variable for which the blockwise graph will be drawn. - - max_ancs_gens : int, optional - Maximum number of generations of ancestors to include in the graph. Default is 5. - - max_desc_gens : int, optional - Maximum number of generations of descendants to include in the graph. Default is 5. - - max_nodes : int, optional - Maximum number of nodes to include in the graph. If the graph has more nodes, it won't be plotted. Default is 50. - - figsize : tuple, optional - A tuple specifying the width and height of the figure for the graph. Default is (7.5, 7.5). + Args: + variable: The variable for which the blockwise graph will be drawn. + max_ancs_gens: Maximum number of generations of ancestors to include in the graph. + max_desc_gens: Maximum number of generations of descendants to include in the graph. + max_nodes: Maximum number of nodes to include in the graph. If the graph has more nodes, it won't be plotted. + figsize: A tuple specifying the width and height of the figure for the graph. - Returns: - -------- - None Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> model.draw_blockwise_graph('var1', max_ancs_gens=3, max_desc_gens=2, max_nodes=30, figsize=(10, 10)) + Draws a directed graph of the block containing 'var1' with up to 3 generations of ancestors and 2 generations of descendants. + + .. code-block:: python - Draws a directed graph of the block containing 'var1' with up to 3 generations of ancestors and 2 generations of descendants. + model = ModelSolver(equations, endogenous) + model.draw_blockwise_graph('var1', max_ancs_gens=3, max_desc_gens=2, max_nodes=30, figsize=(10, 10)) """ - var_node = self._find_var_node(var_.lower()) + var_node = self._find_var_node(variable.lower()) ancs_nodes = nx.ancestors(self._augmented_condenced_model_digraph, var_node) desc_nodes = nx.descendants(self._augmented_condenced_model_digraph, var_node) @@ -1192,7 +1148,7 @@ def draw_blockwise_graph( print( " ".join( [ - f"Graph of block containing {var_} with <={max_ancs_gens} generations of ancestors and <={max_desc_gens} generations of decendants:", + f"Graph of block containing {variable} with <={max_ancs_gens} generations of ancestors and <={max_desc_gens} generations of decendants:", str(subgraph), ] ) @@ -1304,27 +1260,19 @@ def _find_var_node(self, var_: str) -> int: def trace_to_exog_vars(self, i: int, noisy: bool = True) -> list[str] | None: """Prints all exogenous variables that are ancestors to the given block. - Parameters: - ----------- - i : int - The index of the block for which variable values will be displayed. - - noisy : bool, optional - Whether output should be printed or returned. + Args: + i: The index of the block for which variable values will be displayed. + noisy: Whether output should be printed or returned. Returns: - -------- - None + A list of exogenous variables that are ancestors to the given block, or `None`. Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> model.trace_to_exog_vars('Block1') - - exog_var1 - exog_var2 - exog_var3 - ... + + .. code-block:: python + + model = ModelSolver(equations, endogenous) + model.trace_to_exog_vars(1) """ if noisy: print( @@ -1364,31 +1312,27 @@ def trace_to_exog_vals( ) -> pd.Series | None: """Traces the given block back to exogenous values and prints those values. - Parameters: - ----------- - i : int - The index of the block for which variable values will be displayed. - - period_index : int - The index of the period for which exogenous values will be traced. - - noisy : bool, optional - Whether output should be printed or returned. + Args: + i: The index of the block for which variable values will be displayed. + period_index: The index of the period for which exogenous values will be traced. + noisy: Whether output should be printed or returned. Returns: - -------- - None + A `pd.Series` of exogenous values, or `None`. Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> model.trace_to_exog_vals(1, 3) - - Block 1 traces back to the following exogenous variable values in 2023-01-04: - exog_var1=12.5 - exog_var2=8.2 - exog_var3=10.0 - ... + + .. code-block:: python + + model = ModelSolver(equations, endogenous) + model.trace_to_exog_vals(1, 3) + + With output:: + + Block 1 traces back to the following exogenous variable values in 2023-01-04: + exog_var1=12.5 + exog_var2=8.2 + exog_var3=10.0 """ try: output_array = self._last_solution.to_numpy(dtype=np.float64, copy=True) @@ -1436,35 +1380,30 @@ def show_block_vals( ) -> tuple[pd.Series, pd.Series] | tuple[None, None]: """Prints the values of endogenous and predetermined variables in a given block for a specific period. - Parameters: - ----------- - i : int - The index of the block for which variable values will be displayed. - - period_index : int - The index of the period for which variable values will be shown. - - noisy : bool, optional - Whether output should be printed or returned. + Args: + i: The index of the block for which variable values will be displayed. + period_index: The index of the period for which variable values will be shown. + noisy: Whether output should be printed or returned. Returns: - -------- - None or (df_endo, df_pred) + Two pd.Series of endogenous and predetermined values, or `None`, `None`. Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> model.show_block_vals(1, 3) - - Block 1 has endogenous variables in 2023-01-04 that evaluate to: - var1=10.5 - var2=15.2 - ... - - Block 1 has predetermined variables in 2023-01-04 that evaluate to: - pred_var1=8.1 - pred_var2=9.7 - ... + + .. code-block:: python + + model = ModelSolver(equations, endogenous) + model.show_block_vals(1, 3) + + With output:: + + Block 1 has endogenous variables in 2023-01-04 that evaluate to: + var1=10.5 + var2=15.2 + ... + Block 1 has predetermined variables in 2023-01-04 that evaluate to: + pred_var1=8.1 + pred_var2=9.7 """ try: output_array = self._last_solution.to_numpy(dtype=np.float64, copy=True) @@ -1566,41 +1505,35 @@ def sensitivity( ) -> pd.DataFrame: """Analyses sensitivity of endogenous variables to exogenous variables for a specific period. - Parameters: - ----------- - i : int - The index of the block for which variable values will be displayed. - - period_index : int - The index of the period for which variable values will be shown. + Args: + i: The index of the block for which variable values will be displayed. + period_index: The index of the period for which variable values will be shown. + method: Method for sensitivity analysis. Default is 'std'. - method : str, optional - Method for sensitivity analysis. Default is 'std'. - - 'std': Adjusts variables by adding their standard deviation. - - 'pct': Adjusts variables by adding 1% of their value. - - 'one': Adjusts variables by adding 1 to their value. + - 'std': Adjusts variables by adding their standard deviation. + - 'pct': Adjusts variables by adding 1% of their value. + - 'one': Adjusts variables by adding 1 to their value. - exog_subset : list or None, optional - List of exogenous variables to be analysed. If None, all relevant exogenous variables will be analysed. + exog_subset: List of exogenous variables to be analysed. + If None, all relevant exogenous variables will be analysed. Returns: - -------- - pandas.DataFrame: DataFrame showing the sensitivity of endogenous variables to exogenous variables. Example: - -------- - >>> model = ModelSolver(equations, endogenous) - >>> sensitivity_df = model.sensitivity(1, 3, method='pct', exog_subset=['exog_var1', 'exog_var2']) - >>> print(sensitivity_df) - - Output: - ------- - | endog_var1 | endog_var2 | - ------------------------------------- - exog_var1 | 0.23 | 0.12 | - exog_var2 | 0.45 | 0.56 | - ... + + .. code-block:: python + + model = ModelSolver(equations, endogenous) + sensitivity_df = model.sensitivity(1, 3, method='pct', exog_subset=['exog_var1', 'exog_var2']) + print(sensitivity_df) + + With output:: + + | endog_var1 | endog_var2 | + -------------------------------------- + exog_var1 | 0.23 | 0.12 | + exog_var2 | 0.45 | 0.56 | """ try: var_col_index = { diff --git a/tests/test_functions.py b/tests/test_functions.py deleted file mode 100644 index e29a925..0000000 --- a/tests/test_functions.py +++ /dev/null @@ -1,6 +0,0 @@ -from model_solver.functions import example_function - - -def test_example_function() -> None: - assert example_function(1, 2) == "1 is less than 2" - assert example_function(1, 0) == "1 is greater than or equal to 0" diff --git a/tests/test_main.py b/tests/test_main.py deleted file mode 100644 index d75233e..0000000 --- a/tests/test_main.py +++ /dev/null @@ -1,18 +0,0 @@ -"""Test cases for the __main__ module.""" - -import pytest -from click.testing import CliRunner - -from model_solver import __main__ - - -@pytest.fixture() -def runner() -> CliRunner: - """Fixture for invoking command-line interfaces.""" - return CliRunner() - - -def test_main_succeeds(runner: CliRunner) -> None: - """It exits with a status code of zero.""" - result = runner.invoke(__main__.main) - assert result.exit_code == 0 From c6c52ce98620eb93f84dab65141b21e912423ffb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Wed, 18 Sep 2024 20:13:01 +0200 Subject: [PATCH 18/22] Fix future warning ChainedAssignmentError - See https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy --- src/model_solver/model_solver.py | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 3f0f9b2..848abdb 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -1583,13 +1583,22 @@ def sensitivity( solution_diff = self._last_solution.copy() if method == "std": - solution_diff[var].iloc[period_index - lag] += solution_diff[var].std() + solution_diff.iloc[ + period_index - lag, solution_diff.columns.get_loc(var) + ] += solution_diff[var].std() elif method == "pct": - solution_diff[var].iloc[period_index - lag] += ( - solution_diff[var].iloc[period_index - lag] * 0.01 + solution_diff.iloc[ + period_index - lag, solution_diff.columns.get_loc(var) + ] += ( + solution_diff.iloc[ + period_index - lag, solution_diff.columns.get_loc(var) + ] + * 0.01 ) elif method == "one": - solution_diff[var].iloc[period_index - lag] += 1 + solution_diff.iloc[ + period_index - lag, solution_diff.columns.get_loc(var) + ] += 1 else: raise ValueError("method must be std, pct or one") From 50c2d5edcb9afda90b379cf076975dcd1caf0c3c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Thu, 19 Sep 2024 07:05:12 +0200 Subject: [PATCH 19/22] Revert fix for future warning ChainedAssignmentError --- src/model_solver/model_solver.py | 17 ++++------------- 1 file changed, 4 insertions(+), 13 deletions(-) diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 848abdb..3f0f9b2 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -1583,22 +1583,13 @@ def sensitivity( solution_diff = self._last_solution.copy() if method == "std": - solution_diff.iloc[ - period_index - lag, solution_diff.columns.get_loc(var) - ] += solution_diff[var].std() + solution_diff[var].iloc[period_index - lag] += solution_diff[var].std() elif method == "pct": - solution_diff.iloc[ - period_index - lag, solution_diff.columns.get_loc(var) - ] += ( - solution_diff.iloc[ - period_index - lag, solution_diff.columns.get_loc(var) - ] - * 0.01 + solution_diff[var].iloc[period_index - lag] += ( + solution_diff[var].iloc[period_index - lag] * 0.01 ) elif method == "one": - solution_diff.iloc[ - period_index - lag, solution_diff.columns.get_loc(var) - ] += 1 + solution_diff[var].iloc[period_index - lag] += 1 else: raise ValueError("method must be std, pct or one") From 698f5a6833337d0f263b60ca1e776627368b1e30 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Thu, 19 Sep 2024 13:39:38 +0200 Subject: [PATCH 20/22] Fix darglint errors --- src/model_solver/model_solver.py | 26 ++++++++++++++++++++------ 1 file changed, 20 insertions(+), 6 deletions(-) diff --git a/src/model_solver/model_solver.py b/src/model_solver/model_solver.py index 3f0f9b2..581c0dc 100644 --- a/src/model_solver/model_solver.py +++ b/src/model_solver/model_solver.py @@ -627,9 +627,9 @@ def switch_endo_vars( in the list of endogenous variables. """ if all(x in self.endo_vars for x in old_endo_vars) is False: - raise RuntimeError("all variables in old_endo_vars are not endogenous") + raise ValueError("all variables in old_endo_vars are not endogenous") if any(x in self.endo_vars for x in new_endo_vars): - raise RuntimeError("some variables in new_endo_vars are endogenous") + raise ValueError("some variables in new_endo_vars are endogenous") print("Analyzing model") self._endo_vars = ( @@ -663,6 +663,9 @@ def find_endo_var(self, endo_var: str, noisy: bool = False) -> int | None: Returns: The block number of the block that solves the specified endogenous variable. Returns `None` if the endogenous variable is not found in any block. + + Raises: + IndexError: If `endo_var` is not endogenous in model. """ block = [key for key, val in self._blocks.items() if endo_var.lower() in val[0]] if block: @@ -765,6 +768,8 @@ def show_block(self, i: int) -> None: Args: i: The index of the block to display. + Raises: + IndexError: If block `i` is not in model. Example: @@ -1320,6 +1325,9 @@ def trace_to_exog_vals( Returns: A `pd.Series` of exogenous values, or `None`. + Raises: + RuntimeError: If no solution is found. + Example: .. code-block:: python @@ -1388,6 +1396,9 @@ def show_block_vals( Returns: Two pd.Series of endogenous and predetermined values, or `None`, `None`. + Raises: + RuntimeError: If no solution is found. + Example: .. code-block:: python @@ -1508,18 +1519,21 @@ def sensitivity( Args: i: The index of the block for which variable values will be displayed. period_index: The index of the period for which variable values will be shown. + exog_subset: List of exogenous variables to be analysed. + If `None`, all relevant exogenous variables will be analysed. method: Method for sensitivity analysis. Default is 'std'. - 'std': Adjusts variables by adding their standard deviation. - 'pct': Adjusts variables by adding 1% of their value. - 'one': Adjusts variables by adding 1 to their value. - exog_subset: List of exogenous variables to be analysed. - If None, all relevant exogenous variables will be analysed. - Returns: DataFrame showing the sensitivity of endogenous variables to exogenous variables. + Raises: + RuntimeError: If no solution is found. + ValueError: If `method` is not `std`, `pct` or `one`. + Example: .. code-block:: python @@ -1543,7 +1557,7 @@ def sensitivity( ) } except AttributeError as exc: - raise AttributeError(self._NO_SOLUTION_TEXT) from exc + raise RuntimeError(self._NO_SOLUTION_TEXT) from exc get_var_info = cache(self.gen_get_var_info(var_col_index)) From a3dc06d807cee36daebea41dd1cc664849f7aecb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= <81353974+arneso-ssb@users.noreply.github.com> Date: Thu, 19 Sep 2024 14:03:25 +0200 Subject: [PATCH 21/22] Update to ssb-pypitemplate version 2024.9.10 --- .cruft.json | 4 ++-- .github/workflows/docs.yml | 2 +- .github/workflows/release.yml | 6 +++--- .github/workflows/tests.yml | 7 ++++--- 4 files changed, 10 insertions(+), 9 deletions(-) diff --git a/.cruft.json b/.cruft.json index 0cdb1cb..a64d536 100644 --- a/.cruft.json +++ b/.cruft.json @@ -1,7 +1,7 @@ { "template": "https://github.com/statisticsnorway/ssb-pypitemplate.git", - "commit": "70e4bd378ffc9e87a885d938e3befd89ea26ad5b", - "checkout": "2024.8.8", + "commit": "e6f0ca2794354d16838cf36d97bee2f9f70d3142", + "checkout": "2024.9.10", "context": { "cookiecutter": { "project_name": "ssb-model-solver", diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index c0b4568..21ba5fe 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -34,7 +34,7 @@ jobs: poetry --version - name: Set up Python - uses: actions/setup-python@v5.1.1 + uses: actions/setup-python@v5.2.0 with: python-version: "3.12" cache: "poetry" diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index 26ecdb6..1f3c3e0 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -21,7 +21,7 @@ jobs: fetch-depth: 2 - name: Set up Python - uses: actions/setup-python@v5.1.1 + uses: actions/setup-python@v5.2.0 with: python-version: "3.12" @@ -61,11 +61,11 @@ jobs: - name: Publish package on PyPI if: steps.check-version.outputs.tag - uses: pypa/gh-action-pypi-publish@v1.9.0 + uses: pypa/gh-action-pypi-publish@v1.10.1 - name: Publish package on TestPyPI if: (!steps.check-version.outputs.tag) - uses: pypa/gh-action-pypi-publish@v1.9.0 + uses: pypa/gh-action-pypi-publish@v1.10.1 with: repository-url: https://test.pypi.org/legacy/ diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml index 61c3d6c..91ffb7d 100644 --- a/.github/workflows/tests.yml +++ b/.github/workflows/tests.yml @@ -37,7 +37,7 @@ jobs: uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python }} - uses: actions/setup-python@v5.1.0 + uses: actions/setup-python@v5.2.0 with: python-version: ${{ matrix.python }} @@ -101,6 +101,7 @@ jobs: with: name: coverage-data-${{ matrix.os }}-${{ matrix.python }} path: ".coverage.*" + include-hidden-files: true - name: Upload documentation if: matrix.session == 'docs-build' @@ -119,7 +120,7 @@ jobs: fetch-depth: 0 # Shallow clones should be disabled for a better relevancy of analysis - name: Set up Python - uses: actions/setup-python@v5.1.1 + uses: actions/setup-python@v5.2.0 with: python-version: "3.12" @@ -166,4 +167,4 @@ jobs: SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }} # No need to run SonarCloud analysis if dependabot update or token not defined if: env.SONAR_TOKEN != '' && (github.actor != 'dependabot[bot]') - uses: SonarSource/sonarcloud-github-action@v2.3.0 + uses: SonarSource/sonarcloud-github-action@v3.0.0 From af523100aa9009cad9ff39459254f4edca7c7ec7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Arne=20S=C3=B8rli?= 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