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Releases: weadtech/ahpd_cli_public

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Stable 0.1.1

Stable 0.1.1 Latest
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@adrianowead adrianowead released this 24 Oct 21:32
0.1.1
a18813a

Changelog

0.1.1 - 2025-10-24

Changed

  • Criteria Display: The normalization logic for breakdown data (alternatives_contribution.by_criteria) has been improved. It now applies a two-step normalization that ensures that:
  1. The lowest negative value is correctly mapped to min (e.g., 0).
  2. The sum of normalized values for each alternative is always equal to the total sum (e.g., 100).

This ensures a better and more consistent display of criteria performance, especially those derived from original data that include negative values.

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Stable 0.1.0

Stable 0.1.0

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@adrianowead adrianowead released this 19 Oct 20:00
0.1.0
a6c6070

CHANGELOG

1.0.0 - 2025-10-19

This is the initial production release of the AHPd CLI (Command Line Interface), providing a high-performance, data-driven, and objective multi-criteria decision system built on an optimized core.

This version enables seamless integration of the AHPd decision engine into automated pipelines, scripting environments, and real-time systems.

✨ Features

  • Initial Core Release: Introduction of the AHPd CLI application for Linux (ahpd) and Windows (ahpd.exe).
  • Data-Driven Decision Engine: Full implementation of the AHPd algorithm, providing $100%$ objective criteria weighting based on statistical data dispersion.
  • Multiple Input Methods: Support for loading JSON input data via three methods:
    • Reading from a File (ahpd json -f <file>).
    • Receiving via Standard Input (Pipe) (cat file | ahpd json).
    • Providing data Inline (ahpd inline -i '<json>').
  • Structured JSON Input: Enforces a mandatory input structure (data, criteria, options) and validates criteria preferences (min or max).
  • Comprehensive Output Control: Users can define the level of output detail using the --level flag:
    • r: Final Rank (normalized priority vector).
    • g: Global Contribution (automatic criteria weights).
    • d: Detailed Contribution (audit trail/explainability).
  • Flexible Output Destination: Support for printing results to Standard Output (--output inline) or saving to a File (--output <filename>).
  • Auditability: Output data is consistently represented in f64 (double-precision floating-point) for high precision and full decision auditability.

🛠️ Improvements

  • High Performance: Core compiled for maximum processing speed, suitable for high-volume analysis.
  • Debugging Tools: Added a Verbose Mode (-v) for progress messages and a Validation Mode (--check) to quickly verify JSON structure without running the calculation.
  • Readability: Added the --pretty flag to format JSON output with indentation.
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