v0.3.0

Implemented generator-based approaches in several functions to reduce memory usage.

v0.2.9

This release simplifies the dependencies and optimizes matrix multiplication operations.

v0.2.8

This release simplifies the dependencies and optimizes matrix multiplication operations.

v0.2.7

New Features:

• Introduced an optional GPU mode to enhance processing speed and efficiency.

v0.2.5

New Features:

• DataFrame Output: The function has been updated to return a Pandas DataFrame, enhancing the structure and accessibility of the output data. The DataFrame contains two columns: gene_names and p_values, providing a clear and comprehensive overview of the gene expression analysis.

v0.2.4

New Features:

• Enhanced Flexibility in Distance Calculation: With this release, scBSP users gain the ability to select between two powerful algorithms for distance calculation:
  • Ball Tree is now the default distance calculation method, optimized for efficiency and accuracy in processing biological data.
  • HNSW (Hierarchical Navigable Small World graphs) has been introduced as an optional method, providing an alternative that balances speed and precision for large datasets.

v0.2.3

This release primarily focuses on enhancing the documentation of our Python functions through the addition of more comprehensive docstrings. Additionally, we have relaxed the version requirements for dependent packages, aiming to improve compatibility and flexibility for our users.

v0.2.1

This is the release of scBSP version 0.2.1. This package is a breakthrough tool in the realm of biological data analysis, particularly tailored for gene expression and cell coordinate analysis.

v0.2.0

This is the release of scBSP version 0.2.0. This package is a breakthrough tool in the realm of biological data analysis, particularly tailored for gene expression and cell coordinate analysis.

v0.1.0

The initial release for scBSP, a specialized package designed for processing biological data.