css-make 1.1.0

A package designed as a patching solution for issues in `ldpc` and `bp_osd`, addressing matrix handling in `mod2.row_echelon` and fixing bugs in the `css_code` class.

css_make

Overview

css_make is a package designed as a patching solution to address specific issues in existing tools, particularly the mod2.row_echelon function in the ldpc package and the css_code class in the bp_osd package.

In the ldpc package, the mod2.row_echelon function struggled to correctly process certain matrix formats, leading to errors when handling sparse matrices.

Meanwhile, the css_code class in bp_osd exhibited unexpected behavior due to implementation bugs, hindering its intended functionality.

This package provides targeted fixes for these problems while maintaining compatibility with the original workflows.

PS: If you've encountered errors like ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all(). while using these functionalities in the original packages, don’t hesitate——this project is likely the solution you need!

Features

• Enhanced Compatibility: Supports dense matrices (ndarray), CSR-format sparse matrices, and CSC-format sparse matrices.
• Error Handling: Automatically attempts to convert unsupported formats to ndarray. If conversion fails, an error message is printed and None is returned.
• Improved CssCode Functionality: The CssCode class resolves issues found in the original bposd.css.css_code.

Installation

Install the package using pip:

pip install css_make

How to Use

Example 1: Using cm_mod2.row_echelon

import css_make as cm  # Import the css_make module
import numpy as np
import scipy


# Create a dense matrix (Dense Matrix)
H = np.array([[1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
              [0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0],
              [0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0],
              [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1],
              [0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0],
              [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0],
              [1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1],
              [0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0],
              [0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1],
              [0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0],
              [0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0],
              [1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]])

# Example 1: Using cm_mod2.row_echelon
# cm.cm_mod2.row_echelon produces results equivalent to ldpc.mod2.row_echelon.
# In addition, this function **correctly** supports dense matrices (ndarray), CSR-format sparse matrices, and CSC-format sparse matrices.
# For other formats, the function attempts to convert them to ndarray format.
# Note: If the conversion fails, the function will print an error message and return None.

# 1.1 Processing a dense matrix
result = cm.cm_mod2.row_echelon(H)
assert result is not None  # If the return value is None, it might be due to the input matrix not being converted to ndarray format. Check the error message for details.
print("Dense Matrix (ndarray) Row Echelon:")
print(result[3])

# 1.2 Processing a CSR-format sparse matrix
H_sparse = scipy.sparse.csr_matrix(H)
result = cm.cm_mod2.row_echelon(H_sparse)
assert result is not None
print("CSR Sparse Matrix Row Echelon:")
print(result[3])

# 1.3 Processing a CSC-format sparse matrix
H_csc = scipy.sparse.csc_matrix(H)
result = cm.cm_mod2.row_echelon(H_csc)
assert result is not None
print("CSC Sparse Matrix Row Echelon:")
print(result[3])

Example 2: Using the CssCode class

# Example 2: Using the CssCode class
# The CssCode class provides functionality similar to bposd.css.css_code
# but resolves issues in the original implementation.
import css_make as cm
from ldpc.codes import hamming_code

H = hamming_code(3).toarray()  # Generate a Hamming code matrix
qcode = cm.CssCode(hx=H, hz=H)  # Create a CssCode instance

# Inspect the logical operations of CssCode
print("CssCode Logical X:")
print(qcode.lx.toarray())  # Print the logical X operation result
print("CssCode Logical Z:")
print(qcode.lz.toarray())  # Print the logical Z operation result

Example 3: Using the stab.StabCode class

# Example 3: Using the stab.StabCode class
# The StabCode class is equivalent to the stab_code in /src/bposd/stab.py,
# and serves as a dependency for other modules in this context.
print("StabCode is available as a dependency.")

Contributing

Feel free to open issues or submit pull requests if you encounter bugs or have feature requests.

Acknowledgments

This project is modified from the following two projects, and includes selected files or components under the MIT License:

1. bp_osd (GitHub Repository)
2. ldpc (GitHub Repository)

The included files have been modified to fit the specific needs of this project. For details about the modifications, see the respective directories under third_party/. The original LICENSE files from these projects are preserved.