Changelog#

Changelog#

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

0.6.5 - 2026-02-03#

Added#

  • Comprehensive ReadTheDocs documentation structure with roadmap.rst and tests.rst

  • Tutorial.rst for complete dimensional analysis workflow

Changed#

  • Enhanced README and pyproject.toml descriptions

  • Improved code structure and readability

  • Updated notebook outputs for better readability

Fixed#

  • Property validation in MonteCarlo simulation class

    • Fixed summary property to access _count directly without validation

    • Fixed data property getter to handle pre-allocated data with NaN arrays

  • Calculate coefficients method in AnalysisEngine to filter setpoints per coefficient using var_dims.keys()

Removed#

  • Obsolete testing.rst and empty documentation files

  • Dictionary comprehensions replaced with explicit loops for clarity

0.6.4 - 2026-01-26#

Fixed#

  • Codecov action configuration

  • Notebook test outputs

Changed#

  • Refactored test structure for improved maintainability

0.6.3 - 2026-01-26#

Fixed#

  • Enhanced MonteCarlo variable handling and serialization

  • Updated Codecov action to v5 with improved coverage report upload

Removed#

  • Removed unused Jupyter notebook PyDASA-Yoly.ipynb from examples directory

Changed#

  • Re-enabled notebook testing in CI workflow

0.6.2 - 2026-01-26#

Fixed#

  • Improved MonteCarlo initialization and handling of non-init fields

Changed#

  • Temporarily commented out notebook testing step in CI workflow

0.6.1 - 2026-01-26#

Added#

  • Quickstart guide and Reynolds number analysis example documentation

Fixed#

  • Enhanced testing workflow with coverage reporting

  • Updated README badges

0.6.0 - 2026-01-25#

Changed#

  • Refactored MonteCarloSimulation to inherit from WorkflowBase (same pattern as AnalysisEngine)

  • Updated utility methods: reset() preserves coefficients, clear() resets everything, to_dict()/from_dict() use parent serialization

Removed#

  • ~100 lines of duplicate code: attributes (_variables, _coefficients, _results), properties, and _validate_dict() method

Improved#

  • Consistent inheritance pattern across all workflow classes (14/14 tests passing)

0.5.3 - 2026-01-19#

Added#

  • allow_nan parameter to validate_type decorator for np.nan validation

  • data property (getter/setter) for MonteCarlo input data matrix with automatic list-to-array conversion

  • median property to BoundsSpecs and StandardizedSpecs classes

  • calculate_setpoint() method to Coefficient class with comprehensive validation

Changed#

  • MonteCarlo now inherits from both Foundation and BoundsSpecs (multiple inheritance)

  • BoundsSpecs setters accept np.nan values via allow_nan=True parameter

  • MonteCarlo type annotations changed to Optional[float] to match BoundsSpecs

  • statistics and summary properties return Dict[str, Union[float, int, None]]

  • _reset_statistics() and clear() call BoundsSpecs.clear(self) for inherited attributes

  • AnalysisEngine symbol formatting and serialization improved in to_dict() and from_dict()

Removed#

  • _variance attribute from MonteCarlo (standard deviation is sufficient)

  • Redundant property getters: mean, median, dev, min_value, max_value (now inherited from BoundsSpecs)

  • ~120 lines of duplicate code through inheritance refactoring

Fixed#

  • Type checker errors for property overrides in MonteCarlo

  • Test assertion in test_buckingham.py to match error message: “std_setpoint is not defined”

  • Type mismatch between BoundsSpecs (float | None) and MonteCarlo declarations

  • np.isnan() type errors with proper Optional[float] annotations

Improved#

  • Validation decorator system with np.nan support for statistical computations

  • Architecture: None for user config, np.nan for computed results

  • Test coverage: 26 MonteCarlo tests, 53 Buckingham tests, 330+ numerical spec tests passing

0.5.2 - 2026-01-15#

Fixed#

  • Fixed type annotations in Sensitivity class for better type safety

    • Changed _sym_func from Callable to sp.Expr to properly represent SymPy expressions

    • Updated _exe_func to Union[Callable, Dict[str, Callable]] to handle both analysis modes

    • Fixed _symbols type from Dict[str, Symbol] to Dict[sp.Symbol, sp.Symbol]

    • Split _variables into Dict[str, Variable] for objects and _var_names: List[str] for names

    • Fixed property return types to match attribute types

  • Resolved type checking errors: “subs is not a known attribute”, “Dict is not callable”

  • Fixed “var is possibly unbound” error in exception handlers with proper initialization

  • Removed trailing whitespace in docstrings

Added#

  • New var_names property getter in Sensitivity class

  • Added _validate_sympy_expr() validation method for SymPy expression validation

  • Added _validate_analysis_ready() method to check if analysis can be performed

  • Comprehensive test suite for Sensitivity class (56 tests total, up from 43)

    • Tests for exe_func property setter with callable and dict types

    • Tests for schema property setter and validation

    • Tests for variables property setter and validation

    • Tests for _validate_sympy_expr() method

    • Tests for _validate_analysis_ready() method with various failure scenarios

    • Tests for var_names property getter

Changed#

  • Improved error messages in Sensitivity class for better debugging

  • Updated analyze_symbolically() with better type guards and current variable tracking

  • Updated analyze_numerically() with proper type guards using local variables

  • Enhanced _parse_expression() method with proper type narrowing

  • Refactored property decorators for consistency with validation patterns

  • Replaced lambda expressions with proper function definitions for PEP 8 compliance

Internal#

  • Added type guards to prevent runtime errors with Union types

  • Improved exception handling with proper context preservation (raise ... from e)

  • Enhanced type safety for SymPy integration throughout the module

  • Used local variables to satisfy type checker in complex assignment scenarios

0.5.1 - 2026-01-14#

Changed#

  • Updated terminology from ‘framework’ to ‘schema’ in Matrix and AnalysisEngine classes for consistency

  • Refined dimensional analysis workflow capabilities

Fixed#

  • Fixed error message for invalid schema assignment in TestAnalysisEngine

0.5.0 - 2026-01-13#

Added#

  • Enhanced dimensional expression parsing and validation in parser.py

  • Functions to extract coefficients, powered coefficients, and numeric constants from expressions

  • New method derive_coefficient in AnalysisEngine for deriving coefficients from existing ones

  • Comprehensive validation for AnalysisEngine schema input types

Changed#

  • Improved dimensional operation computations and validations

  • Updated regex patterns in patterns.py for better matching of numeric constants and operations

  • Refactored AnalysisEngine in phenomena.py to support custom schemas

  • Restructured analysis workflows for better modularity

  • Enhanced unit tests for the Matrix class and AnalysisEngine

  • Updated error messages for clarity and consistency across validation checks

Fixed#

  • Fixed test assertions to match updated property names

  • Corrected framework validation logic in multiple classes

0.4.10 - 2026-01-12#

Added#

  • New validation decorators validate_list_types and validate_dict_types in pydasa.validations.decorators module

  • Comprehensive test suite for new validation decorators (8 new test cases)

  • Tests for Coefficient.get_data() method in test_buckingham.py

Changed#

  • Refactored Coefficient class to use new @validate_list_types and @validate_dict_types decorators

  • Simplified Coefficient.clear() method to use super().clear() from parent classes (Foundation, BoundsSpecs)

  • Updated test assertions to match new decorator error messages

Fixed#

  • Updated variable test data keys from metric to setpoint

  • Adjusted decorator validation range syntax

Improved#

  • Reduced code duplication by replacing custom validation methods with reusable decorators

  • Enhanced type validation for parameterized generics (Dict[str, Variable], List[int])

  • Cleaner and more maintainable validation architecture

0.4.9 - 2026-01-10#

Changed#

  • Updated author information and email in setup.py

  • Refactored Dimension class to use Frameworks enum

Fixed#

  • Cleaned up redundant code in Variable class

  • Revised comments in memory.py and functions.py

  • Removed deprecated workflows/init.py file

0.4.8 - 2026-01-08#

Added#

  • metric and std_metric properties to NumericalSpecs class

  • Comprehensive tests for new metric properties

Fixed#

  • Enhanced numerical specifications with metric property support

  • Updated test data structure to support metric properties

0.4.7 - 2026-01-07#

Changed#

  • Update CHANGELOG for versions 0.4.4, 0.4.5, and 0.4.6 releases

0.4.6 - 2026-01-07#

Fixed#

  • Downgrade sphinx-autodoc-typehints to 2.5.0 for Sphinx 8 compatibility

0.4.5 - 2026-01-07#

Fixed#

  • Downgrade isort to 6.1.0 for pylint compatibility

0.4.4 - 2026-01-07#

Fixed#

  • Downgrade isort to 6.1.2 for pylint compatibility

Changed#

  • Update CHANGELOG for version 0.4.3 release

0.4.3 - 2026-01-07#

Fixed#

  • Downgrade astroid and pylint for sphinx-autoapi compatibility

0.4.2 - 2026-01-07#

Changed#

  • Minor release updates

0.4.1 - 2026-01-07#

Fixed#

  • Update PyPI token secret name in release workflow

0.4.0 - 2026-01-07#

Added#

  • Read the Docs configuration file (.readthedocs.yaml)

  • Automated documentation building and hosting on Read the Docs

Changed#

  • Update CHANGELOG for version 0.3.4 release

0.3.4 - 2026-01-07#

Fixed#

  • Downgrade Sphinx to 8.1.3 for myst-parser compatibility

Changed#

  • Update Python version to 3.11 in Read the Docs configuration

  • Configure Read the Docs for automated documentation builds

  • Add PyPI publishing workflow with GitHub Actions

0.3.3 - 2026-01-07#

Added#

  • First public release published to PyPI

  • Configure automated PyPI publishing via GitHub Actions

  • Add Read the Docs integration with .readthedocs.yaml

  • Include CHANGELOG.md in documentation via myst-parser

Changed#

  • Update documentation structure with public folder integration

  • Configure linkify-it-py for markdown link rendering in docs

0.3.2 - 2026-01-06#

Fixed#

  • Package now includes core/cfg/*.json configuration files in distribution

  • __version__ attribute is now properly exposed in the main pydasa module

  • Resolved FileNotFoundError when importing pydasa after installation

Added#

  • Added [tool.setuptools.package-data] configuration to include non-Python files

  • Comprehensive test suite in tests/test_package.py to verify package initialization

  • Tests for version accessibility, configuration file inclusion, and main exports

Changed#

  • Configured semantic release with major_on_zero = false to keep versions in 0.x range

  • Updated __all__ list to include __version__ for proper wildcard imports

0.3.1 - 2026-01-06#

Changed#

  • Version reset from 1.0.x to 0.3.1 to maintain pre-release versioning

  • Configured semantic release to prevent automatic major version bumps

0.3.0 - Unreleased (2026-01-06)#

Added#

  • Initial stable release with core functionality

[0.2.99] - Unreleased (2026-01-06)#

Added#

  • Distribution files: pydasa-0.2.99-py3-none-any.whl, pydasa-0.2.99.tar.gz

[0.2.75] - Unreleased (2026-01-04)#

Added#

  • Distribution files: pydasa-0.2.75-py3-none-any.whl, pydasa-0.2.75.tar.gz

[0.2.71] - Unreleased (2025-11-27)#

Added#

  • Distribution files: pydasa-0.2.71-py3-none-any.whl, pydasa-0.2.71.tar.gz

[0.2.69] - Unreleased (2025-11-24)#

Added#

  • Distribution files: pydasa-0.2.69-py3-none-any.whl, pydasa-0.2.69.tar.gz

[0.2.45] - Unreleased (2025-11-23)#

Added#

  • Distribution files: pydasa-0.2.45-py3-none-any.whl, pydasa-0.2.45.tar.gz

[0.2.43] - Unreleased (2025-11-23)#

Added#

  • Distribution files: pydasa-0.2.43-py3-none-any.whl, pydasa-0.2.43.tar.gz

[0.2.42] - Unreleased (2025-11-23)#

Added#

  • Distribution files: pydasa-0.2.42-py3-none-any.whl, pydasa-0.2.42.tar.gz

[0.2.37] - Unreleased (2025-11-23)#

Added#

  • Distribution files: pydasa-0.2.37-py3-none-any.whl, pydasa-0.2.37.tar.gz

[0.2.21] - Unreleased (2025-11-18)#

Added#

  • Distribution files: pydasa-0.2.21-py3-none-any.whl, pydasa-0.2.21.tar.gz

[0.2.17] - Unreleased (2025-11-18)#

Added#

  • Distribution files: pydasa-0.2.17-py3-none-any.whl, pydasa-0.2.17.tar.gz

[0.2.11] - Unreleased (2025-11-18)#

Added#

  • Distribution files: pydasa-0.2.11-py3-none-any.whl, pydasa-0.2.11.tar.gz

[0.2.0] - Unreleased (2025-11-17)#

Added#

  • Distribution files: pydasa-0.2.0-py3-none-any.whl, pydasa-0.2.0.tar.gz

[0.1.97] - Unreleased (2025-11-17)#

Added#

  • Distribution files: pydasa-0.1.97-py3-none-any.whl, pydasa-0.1.97.tar.gz

[0.1.95] - Unreleased (2025-11-17)#

Added#

  • Distribution files: pydasa-0.1.95-py3-none-any.whl, pydasa-0.1.95.tar.gz

[0.1.92] - Unreleased (2025-10-11)#

Added#

  • Distribution files: pydasa-0.1.92-py3-none-any.whl, pydasa-0.1.92.tar.gz

[0.1.90] - Unreleased (2025-10-11)#

Added#

  • Distribution files: pydasa-0.1.90-py3-none-any.whl, pydasa-0.1.90.tar.gz

[0.1.9] - Unreleased (2025-09-01)#

Added#

  • Distribution files: pydasa-0.1.9-py3-none-any.whl, pydasa-0.1.9.tar.gz

[0.1.8] - Unreleased (2025-08-28)#

Added#

  • Distribution files: pydasa-0.1.8-py3-none-any.whl, pydasa-0.1.8.tar.gz

[0.1.73] - Unreleased (2025-10-03)#

Added#

  • Distribution files: pydasa-0.1.73-py3-none-any.whl, pydasa-0.1.73.tar.gz

[0.1.70] - Unreleased (2025-10-03)#

Added#

  • Distribution files: pydasa-0.1.70-py3-none-any.whl, pydasa-0.1.70.tar.gz

[0.1.7] - Unreleased (2025-08-25)#

Added#

  • Distribution files: pydasa-0.1.7-py3-none-any.whl, pydasa-0.1.7.tar.gz

[0.1.65] - Unreleased (2025-10-02)#

Added#

  • Distribution files: pydasa-0.1.65-py3-none-any.whl, pydasa-0.1.65.tar.gz

[0.1.6] - Unreleased (2025-08-25)#

Added#

  • Distribution files: pydasa-0.1.6-py3-none-any.whl, pydasa-0.1.6.tar.gz

[0.1.5] - Unreleased (2025-08-24)#

Added#

  • Distribution files: pydasa-0.1.5-py3-none-any.whl, pydasa-0.1.5.tar.gz

[0.1.45] - Unreleased (2025-09-30)#

Added#

  • Distribution files: pydasa-0.1.45-py3-none-any.whl, pydasa-0.1.45.tar.gz

[0.1.35] - Unreleased (2025-09-30)#

Added#

  • Distribution files: pydasa-0.1.35-py3-none-any.whl, pydasa-0.1.35.tar.gz

[0.1.32] - Unreleased (2025-09-30)#

Added#

  • Distribution files: pydasa-0.1.32-py3-none-any.whl, pydasa-0.1.32.tar.gz

[0.1.27] - Unreleased (2025-09-29)#

Added#

  • Distribution files: pydasa-0.1.27-py3-none-any.whl, pydasa-0.1.27.tar.gz

[0.1.25] - Unreleased (2025-09-29)#

Added#

  • Distribution files: pydasa-0.1.25-py3-none-any.whl, pydasa-0.1.25.tar.gz

[0.1.2] - Unreleased (2025-08-24)#

Added#

  • Distribution files: pydasa-0.1.2-py3-none-any.whl, pydasa-0.1.2.tar.gz

[0.1.19] - Unreleased (2025-09-19)#

Added#

  • Distribution files: pydasa-0.1.19-py3-none-any.whl, pydasa-0.1.19.tar.gz

[0.1.17] - Unreleased (2025-09-19)#

Added#

  • Distribution files: pydasa-0.1.17-py3-none-any.whl, pydasa-0.1.17.tar.gz

[0.1.15] - Unreleased (2025-09-18)#

Added#

  • Distribution files: pydasa-0.1.15-py3-none-any.whl, pydasa-0.1.15.tar.gz

[0.1.12] - Unreleased (2025-09-11)#

Added#

  • Distribution files: pydasa-0.1.12-py3-none-any.whl, pydasa-0.1.12.tar.gz

[0.1.11] - Unreleased (2025-09-10)#

Added#

  • Distribution files: pydasa-0.1.11-py3-none-any.whl, pydasa-0.1.11.tar.gz

[0.1.0] - Unreleased (2025-08-20)#

Added#

  • Distribution files: pydasa-0.1.0-py3-none-any.whl, pydasa-0.1.0.tar.gz

[0.0.1] - Unreleased (2025-08-20)#

Added#

  • Distribution files: pydasa-0.0.1-py3-none-any.whl, pydasa-0.0.1.tar.gz

[0.0.0] - Initial Development (2023-08-27 to 2025-08-20)#

Added#

  • Initial commit and repository setup.

  • Fundamental dimensional unit (FDU) class implementation.

  • Proof of concept for dimensional analysis framework.

  • Core data structures for PyDASA methodology.

  • Initial documentation structure (English and Spanish).

  • Base classes for dimensional parameters and fundamental data structures.

  • Early test structure and experimental implementations.

Note#

Experimentation phase before formal semantic versioning, establishing core dimensional analysis concepts and data structures.

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