ashaxiom 1.2.0

Intelligent Analytical Framework for Higher Mathematics

AshAxiom Library 🚀

The Intelligent Analytical Ecosystem for Higher Mathematics in Jupyter.

AshAxiom is a high-level Python framework designed for scientific research, symbolic mathematics, and data visualization. It features a dynamic AI engine that transforms classical textbooks into an interactive calculation environment.

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🌟 Key Features

• Axiom Brain (AI): An intelligent dispatcher that navigates through sections/authors and maps user intent to the correct mathematical model.
• Dynamic Scopes: Filter knowledge by Author or Section to accelerate discovery and minimize conflicts.
• Fluent Chaining (Piping): Build complex analytical pipelines using intuitive dot-notation.
• Task Parallelization: Multithreaded execution for heavy computational groups.
• Output Explorer: Interactive, scrollable HTML output with precision control (up to 15 decimal places).
• 2D/3D Visualization: High-level wrappers for complex surfaces and mathematical plotting.

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📚 Integrated Knowledge Base

AshAxiom is systematically trained on world-class mathematical literature:

• M.L. Krasnov et al. (Volumes 1-7): Full implementation of vector algebra, ODEs, TFCP, probability, and optimization.
• G.M. Fikhtengolts (Volumes 1-3): Deep integration of differential and integral calculus.

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📦 Dependencies

Ensure the following are installed in your environment: numpy, sympy, matplotlib, pandas, openpyxl, scipy.

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🚀 Usage Examples

1. Intelligent Solving (Brain Mode)

import ashaxiom
# Solve a 2D geometry problem by author
res = (ashaxiom.Axiom.think()
       .author("Krasnov")
       .solve("plane", p1=(1,0,0), p2=(0,1,0), p3=(0,0,1)))
display(res)


# Browse what the brain knows
brain = ashaxiom.Axiom.think("library")
print(brain.sections().show())
print(brain.section("hMath").show()) # Lists authors