Metadata-Version: 2.2
Name: rr_echelon_f_48
Version: 0.0.1
Summary: A small package for solving linear equations system and converting into reduced row echelon form
Author-email: Abdullah Bajwa <abdullahbajwa2019@gmail.com>
Project-URL: Homepage, https://github.com/AbdullahBajwa48/reduced_row_echelon_form
Project-URL: Issues, https://github.com/pypa/sampleproject/issues
Keywords: reduced_row_echelon_form,Gauss_jordan_elimination
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.4
Description-Content-Type: text/markdown

# RREF_Package

The **RREF_Package** provides an efficient implementation for computing the **Reduced Row Echelon Form (RREF)** of a given matrix. It simplifies matrices to a canonical form, making it useful for solving linear systems, rank determination, and inverse calculations.

Developed by [Your Name] (c) 2024

## Installation

You can install the package using pip:
```sh
pip install rref_package
```

## Features
- Compute the **Reduced Row Echelon Form (RREF)** of any matrix.
- Supports integer, floating-point matrices.
- Handles both square and rectangular matrices.
- Provides step-by-step transformation details (optional).

## Example Usage

```python
from rref_package import RREF

# Define a matrix
matrix = [
    [1, 2, -1, 3],
    [2, 3, 4, 1],
    [1, -1, 1, 2]
]

# Compute RREF
rref_matrix = rref.full_solve(list of equations)

# Print result
for row in rref_matrix:
    print(row)
```

## Additional Features

```python
# Optional: Show step-by-step row operations
rref_matrix, steps = RREF.compute_with_steps(matrix)

# Display transformation steps
for step in steps:
    print(step)
```

## API Reference

### `RREF.compute(matrix: list) -> list`
Computes the reduced row echelon form of the given matrix.

### `RREF.compute_with_steps(matrix: list) -> tuple`
Returns the RREF along with a list of row operations performed.

## License
This project is licensed under the MIT License.

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Feel free to contribute or report issues on GitHub!

