maths-toolkit 2.0.0

A toolkit for intermediate-level Maths A and Maths B calculations.

Maths Toolkit

Author : N V R K SAI KAMESH SHARMA

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Maths Toolkit is a Python library designed to simplify intermediate-level mathematics calculations for both Maths A (Algebra) and Maths B (Trigonometry, Calculus, and more). It provides easy-to-use functions for common operations, making it ideal for students, educators, and developers.

Features

Algebra (Maths A)

• Solve quadratic equations.
• Matrix operations (addition, multiplication, transpose).

Trigonometry (Maths B)

• Sine, cosine, and other trigonometric functions (in degrees).

Calculus (Maths B)

• Differentiate polynomials.
• Integrate polynomials.

Statistics

• Calculate mean, variance, and standard deviation.

Installation

Install Maths Toolkit using pip:

pip install maths-toolkit

Usage

Here's how to use Maths Toolkit:

Example: Solving Quadratic Equations

from maths_toolkit import MathsToolkit

# Solve x^2 - 5x + 6 = 0
roots = MathsToolkit.solve_quadratic(1, -5, 6)
print("Roots:", roots)

Example: Trigonometry

# Calculate sin(30 degrees)
sine = MathsToolkit.sin_deg(30)
print("Sin 30°:", sine)

Example: Calculus

# Differentiate 3x^2 + 2x + 1
derivative = MathsToolkit.differentiate([3, 2, 1])
print("Derivative:", derivative)

# Integrate 3x^2 + 2x + 1
integral = MathsToolkit.integrate([3, 2, 1])
print("Integral:", integral)

Example: Statistics

# Data set
data = [1, 2, 3, 4, 5]

# Calculate mean, variance, and standard deviation
mean = MathsToolkit.mean(data)
variance = MathsToolkit.variance(data)
std_dev = MathsToolkit.standard_deviation(data)

print("Mean:", mean)
print("Variance:", variance)
print("Standard Deviation:", std_dev)

Example: Matrix Operations

# Matrices
a = [[1, 2], [3, 4]]
b = [[5, 6], [7, 8]]

# Matrix addition
addition = MathsToolkit.matrix_add(a, b)
print("Matrix Addition:", addition)

# Matrix multiplication
multiplication = MathsToolkit.matrix_multiply(a, b)
print("Matrix Multiplication:", multiplication)

# Matrix transpose
transpose = MathsToolkit.matrix_transpose(a)
print("Matrix Transpose:", transpose)

Future Plans

• Expand support for advanced calculus.
• Include graphical visualizations.

Contributing

Contributions are welcome! If you'd like to contribute, please fork the repository and submit a pull request with your changes.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

N V R K Sai Kamesh Sharma

For questions or feedback, feel free to reach out at [[e-mail]].