LaTeX Math Evaluator #

A Flutter/Dart library for parsing and evaluating mathematical expressions written in LaTeX format with support for symbolic differentiation, matrix operations, and advanced mathematical notation.

Note

This library is under active development; see the changelog for release notes.

Kindly check our Roadmap 🚚 for planned features and progress.

✨ Highlights #

🎯 Native LaTeX Support - Parse expressions directly from academic papers and textbooks
🧮 Symbolic Differentiation - Compute exact derivatives using calculus rules (not approximations)
🔢 Advanced Notation - Summation, products, limits, integration, matrices, and vectors
⚡ High Performance - Parse once, evaluate thousands of times with built-in LRU caching
🎨 Type-Safe Results - Handle numeric, matrix, complex, and vector results safely
🔧 Extensible - Add your own custom functions and commands easily

📑 Table of Contents #

LaTeX Math Evaluator

Installation #

Add this to your pubspec.yaml:

dependencies:
  latex_math_evaluator: ^0.1.2

Or use the latest development version:

dependencies:
  latex_math_evaluator:
    git:
      url: https://github.com/xirf/latex_math_evaluator.git

Then run:

dart pub get

Quick Start #

import 'package:latex_math_evaluator/latex_math_evaluator.dart';

final evaluator = LatexMathEvaluator();

// Basic arithmetic
print(evaluator.evaluateNumeric(r'2 + 3 \times 4'));  // 14.0

// With variables
print(evaluator.evaluateNumeric(r'x^{2} + 1', {'x': 3}));  // 10.0

// Trigonometric functions
print(evaluator.evaluateNumeric(r'\sin{\pi}'));  // 0.0

// Fractions and roots
print(evaluator.evaluateNumeric(r'\frac{\sqrt{16}}{2}'));  // 2.0

// Summation
print(evaluator.evaluateNumeric(r'\sum_{i=1}^{5} i'));  // 15.0

Core Features #

1. Variable Binding and Reusability #

Parse once, evaluate many times with different variable values:

final evaluator = LatexMathEvaluator();

// Parse the expression once
final equation = evaluator.parse(r'x^{2} + 2x + 1');

// Evaluate with different values (faster than reparsing)
print(evaluator.evaluateParsed(equation, {'x': 1}));  // 4.0
print(evaluator.evaluateParsed(equation, {'x': 2}));  // 9.0
print(evaluator.evaluateParsed(equation, {'x': 3}));  // 16.0

// Multi-variable expressions
final multiVar = evaluator.parse(r'2x + 3y - z');
print(evaluator.evaluateParsed(multiVar, {
  'x': 1, 'y': 2, 'z': 3
}));  // 5.0

2. Expression Validation #

Catch errors before evaluation with detailed feedback:

final evaluator = LatexMathEvaluator();

// Quick validation
if (evaluator.isValid(r'\sin{x}')) {
  print('Valid syntax!');
}

// Detailed error information
final result = evaluator.validate(r'\frac{1{2}');
if (!result.isValid) {
  print('Error: ${result.errorMessage}');
  print('Position: ${result.position}');
  print('Suggestion: ${result.suggestion}');
}

Error messages show exactly where problems occur:

ParserException at position 10: Expected '}' after numerator

\frac{1{2}
          ^
Suggestion: Add a closing brace } or check for matching braces

Learn more about validation ->

3. Type-Safe Results #

Handle different result types safely:

final result = evaluator.evaluate(r'2 + 3');

// Pattern matching (Dart 3.0+)
switch (result) {
  case NumericResult(:final value):
    print('Number: $value');
  case MatrixResult(:final matrix):
    print('Matrix: $matrix');
}

// Type checking
if (result.isNumeric) {
  print(result.asNumeric());
}

4. Matrix Operations #

Full support for matrix notation and operations:

// Create matrices
final matrixA = evaluator.evaluateMatrix(
  r'\begin{matrix} 1 & 2 \\ 3 & 4 \end{matrix}'
);

// Matrix operations
evaluator.evaluateMatrix(r'A + B', {
  'A': [[1, 2], [3, 4]],
  'B': [[5, 6], [7, 8]]
});  // [[6, 8], [10, 12]]

// Determinant
evaluator.evaluateNumeric(r'\det{A}', {
  'A': [[1, 2], [3, 4]]
});  // -2.0

// Transpose
evaluator.evaluateMatrix(r'A^{T}', {
  'A': [[1, 2], [3, 4]]
});  // [[1, 3], [2, 4]]

Supported Operations #

Functions by Category #

Category	Functions / Examples
Trigonometric	`\sin`, `\cos`, `\tan`, `\asin`, `\acos`, `\atan`
Hyperbolic	`\sinh`, `\cosh`, `\tanh`, `\asinh`, `\acosh`, `\atanh`
Logarithmic	`\ln`, `\log`, `\log_{b}{x}` (e.g. `\log_{2}{8}`)
Rounding	`\ceil`, `\floor`, `\round`
Power & Roots	`\sqrt`, `\sqrt[3]{27}`, `\exp`
Matrix Operations	`\det`, `\trace`, `\tr`
Combinatorics	`\binom{n}{k}`
Number Theory	`\gcd(a, b)`, `\lcm(a, b)`
Other	`\abs`, `\|x\|`, `\sgn`, `\factorial`, `\min_{a}{b}`, `\max_{a}{b}`

Mathematical Constants #

Constants are available with or without backslash notation:

Constant	LaTeX	Symbol	Value	Usage
Pi	`\pi`	π	3.14159...	`\pi` or `pi`
Euler	`\e`	e	2.71828...	`\e` or `e`
Tau	`\tau`	τ	6.28318...	`\tau` or `tau`
Phi	`\phi`	φ	1.61803...	`\phi` or `phi`
Gamma	`\gamma`	γ	0.57721...	`\gamma` or `gamma`

Note: User-provided variables always override built-in constants.

Advanced Notation #

Feature	Equation	LaTeX
Fractions	$\frac{a+b}{c}$	`\frac{a + b}{c}`
Summation	$\sum_{i=1}^{10} i^{2}$	`\sum_{i=1}^{10} i^{2}`
Products	$\prod_{i=1}^{5} i$	`\prod_{i=1}^{5} i` (Factorial: 120)
Limits (numeric approximation)	$\lim_{x \to 0} \frac{\sin{x}}{x}$	`\lim_{x \to 0} \frac{\sin{x}}{x}`
Numerical Integration (Simpson's Rule)	$\int_{0}^{\pi} \sin{x}, dx$	`\int_{0}^{\pi} \sin{x}\, dx`
Symbolic Differentiation	$\frac{d}{dx}(x^{2})$	`\frac{d}{dx}(x^{2})`
Higher Order Derivatives	$\frac{d^{2}}{dx^{2}}(x^{3})$	`\frac{d^{2}}{dx^{2}}(x^{3})`
Absolute Value	$\|x\|$, $\|-5\|$, $\|x^2 - 4\|$	`\|x\|`, `\|-5\|`, `\|x^2 - 4\|`
Domain Constraints	$f(x) = 2x - 3, 3 < x < 5$	`f(x) = 2x - 3, 3 < x < 5`

Symbolic Differentiation #

Compute derivatives symbolically with full support for all standard calculus rules:

final evaluator = LatexMathEvaluator();

// Basic derivative: d/dx(x^2) = 2x
print(evaluator.evaluateNumeric(r'\frac{d}{dx}(x^{2})', {'x': 3}));  // 6.0

// Product rule: d/dx(x * sin(x))
print(evaluator.evaluateNumeric(r'\frac{d}{dx}(x \cdot \sin{x})', {'x': 0}));  // 1.0

// Chain rule: d/dx(sin(x^2))
print(evaluator.evaluateNumeric(r'\frac{d}{dx}(\sin{x^{2}})', {'x': 0}));  // 0.0

// Higher order derivatives: d²/dx²(x^3) = 6x
print(evaluator.evaluateNumeric(r'\frac{d^{2}}{dx^{2}}(x^{3})', {'x': 2}));  // 12.0

// Get symbolic derivative for reuse
final expr = evaluator.parse(r'x^{2} + 3x + 1');
final derivative = evaluator.differentiate(expr, 'x');
print(evaluator.evaluateParsed(derivative, {'x': 2}).asNumeric());  // 7.0

Supported rules:

Power, sum, difference, product, quotient, chain rules
Trigonometric: sin, cos, tan, cot, sec, csc
Inverse trig: arcsin, arccos, arctan
Exponential & logarithmic: e^x, a^x, ln(x), log(x)
Hyperbolic: sinh, cosh, tanh
Special cases: √x, |x|, x^x

See full differentiation documentation →

Configuration Options #

Implicit Multiplication #

Control how adjacent variables are interpreted:

// Enabled (default): xy means x * y
final evaluator1 = LatexMathEvaluator();
print(evaluator1.evaluate('xy', {'x': 2, 'y': 3}));  // 6.0

// Disabled: xy is treated as a single variable
final evaluator2 = LatexMathEvaluator(
  allowImplicitMultiplication: false
);
print(evaluator2.evaluate('xy', {'xy': 10}));  // 10.0

Extending the Library #

Add custom functions and commands:

import 'dart:math' as math;

final registry = ExtensionRegistry();

// Register a custom command
registry.registerCommand('cbrt', (cmd, pos) =>
  Token(type: TokenType.function, value: 'cbrt', position: pos)
);

// Register the evaluator
registry.registerEvaluator((expr, vars, evaluate) {
  if (expr is FunctionCall && expr.name == 'cbrt') {
    final arg = evaluate(expr.argument);
    return math.pow(arg, 1/3).toDouble();
  }
  return null;
});

// Use your custom function
final evaluator = LatexMathEvaluator(extensions: registry);
print(evaluator.evaluate(r'\cbrt{27}'));  // 3.0

Learn more about extensions ->

Performance Tips #

Parse once, evaluate many times when using the same expression with different variables
Validate expressions during development to catch errors early
Disable implicit multiplication if you need to support multi-character variable names
Cache parsed expressions for repeated evaluations

How to enable and use caching:

// Configure LRU cache size for parsed expressions.
final evaluator = LatexMathEvaluator(parsedExpressionCacheSize: 512);

// Reuse parsed expression manually to avoid re-parsing.
final parsed = evaluator.parse(r'x^{2} + 2x + 1');
print(evaluator.evaluateParsed(parsed, {'x': 1}));

// Clear cache when extensions or runtime tokens change.
evaluator.clearParsedExpressionCache();

New functions: \fibonacci{n} is available with memoized implementations. Quick benchmark: Run dart run benchmark/expression_cache_benchmark.dart to measure parsed-expression caching benefits and fibonacci memoization.

Why This Library Exists #

Comparison with Existing Solutions #

If you're familiar with Dart's ecosystem, you might know about the math_expressions package. Here's what LaTeX Math Evaluator offers that sets it apart:

1. Native LaTeX Support

math_expressions: Uses custom syntax (sin(x), x^2, sqrt(x))
latex_math_evaluator: Native LaTeX notation (\sin{x}, x^{2}, \sqrt{x})

We hope to make it easier for users to work with mathematical expressions in their familiar LaTeX format, reducing the need for translation between different syntaxes.

2. Symbolic Differentiation

math_expressions: Numerical differentiation only (approximations)
latex_math_evaluator: Full symbolic differentiation with calculus rules

// Get exact derivatives, not approximations
final expr = evaluator.parse(r'x^{2} + 3x + 1');
final derivative = evaluator.differentiate(expr, 'x');  // Returns: 2x + 3
print(evaluator.evaluateParsed(derivative, {'x': 2}).asNumeric());  // 7.0

Supports power rule, product rule, quotient rule, chain rule, and derivatives of all trig/log/exp functions.

3. Advanced Mathematical Notation

Built-in support for:

Feature	Equation	LaTeX
Summation	`\sum_{i=1}^{n} i^{2}`	$ \sum_{i=1}^{n} i^{2} $
Products	`\prod_{i=1}^{n} i`	$ \prod_{i=1}^{n} i $
Limits	`\lim_{x \to 0} \frac{\sin{x}}{x}`	$ \lim_{x \to 0} \frac{\sin{x}}{x} $
Integration	`\int_{0}^{\pi} \sin{x}\, dx`	$ \int_{0}^{\pi} \sin{x}, dx $
Matrices	`\begin{matrix} 1 & 2 \\ 3 & 4 \end{matrix}`	$ \begin{matrix} 1 & 2 \ 3 & 4 \end{matrix} $
Higher-order derivatives	`\frac{d^{2}}{dx^{2}}(x^{3})`	$ \frac{d^{2}}{dx^{2}}(x^{3}) $

4. Matrix and Vector Operations

Full matrix algebra built-in:

// Determinant, inverse, transpose, multiplication - all native
evaluator.evaluateNumeric(r'\det{\begin{matrix} 1 & 2 \\ 3 & 4 \end{matrix}}');  // -2.0

5. Complex Number Support

// Complex arithmetic with i notation
evaluator.evaluate('(1 + 2*i) * (3 + 4*i)');  // Complex(-5, 10)
evaluator.evaluate(r'\Re(2 + 3i)');  // 2.0
evaluator.evaluate(r'\Im(2 + 3i)');  // 3.0

6. Validation with Detailed Error Messages

final result = evaluator.validate(r'\frac{1{2}');
// Shows exactly where the error is with suggestions
// ParserException at position 10: Expected '}' after numerator
// \frac{1{2}
//           ^

When to Use Each Library #

Use Case	Recommended Library
LaTeX expressions from papers/textbooks	✅ latex_math_evaluator
Symbolic calculus (derivatives, simplification)	✅ latex_math_evaluator
Matrix/vector operations	✅ latex_math_evaluator
Complex numbers	✅ latex_math_evaluator
Educational platforms & scientific software	✅ latex_math_evaluator
Simple calculator with custom syntax	math_expressions
Lightweight numeric evaluation only	math_expressions (smaller package)

Bottom Line #

LaTeX Math Evaluator is purpose-built for applications that need:

📚 Academic/scientific accuracy with LaTeX notation
🧮 Symbolic mathematics (calculus, algebra)
🎓 Educational platforms, homework checkers, graphing calculators
🔬 Advanced mathematical constructs
🔗 Integration with LaTeX-heavy ecosystems

Documentation #

The guides available in the doc/ folder:

Getting Started - Installation and basic usage
Functions - Complete function reference
Notation - Supported LaTeX notation
Constants - Built-in mathematical constants
Validation - Error handling and validation
Extensions - Creating custom functions
Caching - Parsed expression cache and memoization

Contributing #

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License #

This project is licensed under the MIT License. You are free to use, modify, and distribute this software in accordance with the terms of the license. See the LICENSE file for more details.

Support #

Issues: GitHub Issues
Discussions: GitHub Discussions
Documentation: Full Documentation