connorferster/handcalcs
Handcalcs
handcalcs is a mathematical documentation generator and Python LaTeX calculation renderer. It serves as an automated calculation sheet tool that converts Python code and numeric calculations into formatted LaTeX mathematical documentation, functioning as both a symbolic math formatter and a Jupyter notebook math extension.
The project transforms Python variable names into Greek symbols, subscripts, and standard mathematical notation. It converts code into formatted mathematical expressions that display the original formula, the numeric substitution, and the final result, allowing for the creation of parameterized calculation sheets and human-readable reports.
The tool covers a wide range of rendering capabilities, including automatic variable subscripts, inline comment integration, and multi-column parameter layouts. It supports the generation of raw LaTeX code, PDF document rendering, and integration with symbolic math libraries to handle algebraic expressions.
The system integrates directly into Jupyter notebook environments using cell magics to display formatted equations in real-time.
Features
- Automated Engineering Reports - Converts Python calculations into rendered LaTeX equations to create human-readable engineering reports.
- Mathematical Expression Generators - Generates human-readable mathematical reports and LaTeX expressions from Python source code and numeric substitutions.
- Code-to-LaTeX Converters - Transforms Python source code and calculations into formatted LaTeX mathematical expressions for documentation.
- Jupyter Notebook Integrations - Displays formatted mathematical expressions directly within Jupyter Notebooks using cell magics.
- Cell Magic Integrations - Integrates with Jupyter via cell magics to display formatted LaTeX outputs in real-time.
- Mathematical Rendering - Provides a specialized integration for rendering mathematical expressions directly within Jupyter Notebook environments.
- Notebook Math Rendering - Renders Python code as professional LaTeX equations directly within Jupyter notebook environments.
- Python AST Parsing - Analyzes Python source code using abstract syntax trees to convert logic into mathematical notation.
- Automated Calculation Sheets - Provides a framework for generating parameterized mathematical documents and PDFs from dynamic Python calculations.
- Greek Symbol Translation - Translates variable names containing Greek letter strings into their corresponding mathematical symbols.
- Variable-to-Symbol Mappings - Transforms Python variable names into Greek symbols and standard mathematical notation for better readability.
- LaTeX Math Rendering - Provides global preferences for decimal precision and scientific notation for LaTeX math rendering.
- Variable-to-Symbol Mappings - Translates Python variable names into Greek letters and subscripts using predefined replacement rules.
- Parametric Calculation Sheets - Creates automated reports that generate formatted mathematical calculations based on varying input parameters.
- Notation Converters - Transforms variable names into Greek symbols, subscripts, and prime notation while converting functions into operators.
- Function Decorators - Wraps functions with decorators to capture internal calculations for formatting.
- State Capture Decorators - Uses Python decorators to intercept local variable assignments and evaluations for rendering.
- Mathematical Operator Formatting - Converts Python function calls and custom operators into standard notation, such as using radical signs for square roots.
- Scientific Report Formatting - Generates formatted scientific reports showing both the mathematical formula and the numeric substitution.
- Equation Layout Customization - Adjusts the visual presentation of equations, including decimal precision and view toggles via tags.
- Calculation Annotation Integration - Displays source code comments as formatted annotations alongside rendered mathematical calculations.
- Automatic Mathematical Subscripts - Automatically creates LaTeX subscripts and nested subscripts based on the use of underscores in Python variable names.
- Calculation Step Recording - Captures and recalls calculation steps for specific iterations when processing data in tables.
- Mathematical Rendering Configurations - Sets session-wide formatting rules for decimal precision, LaTeX block delimiters, and scientific notation.
- Equation Renderers - Displays mathematical formulas without numeric substitutions to create purely symbolic equations.
- Calculation Context Documentation - Renders code comments as inline notes and uses conditional statements to provide context for mathematical results.
- Interactive Calculation Rendering - Generates formatted mathematics from code that updates in real-time based on interactive user input widgets.
- Symbolic Derivation Documentation - Combines symbolic algebra libraries with LaTeX to document complex mathematical derivations.
- Symbolic Engine Interoperability - Integrates with symbolic math engines to render algebraic expressions without forcing numeric evaluation.
- Rendering Integrations - Integrates with symbolic libraries like Sympy to handle algebraic expression substitution for rendering.
- Iteration Trace Recording - Stores calculation steps of repeated function calls to display specific iterations in a report.
- Jupyter Ecosystem - Rendering mathematical equations in notebook cells.
Star history
How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
