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Main entry point for temperament similarity and pattern detection tools. Overview of validated relationships and available explorers.

Temperament Similarity and Pattern Detection

Documentation
Documentation Procedure | Documentation Index | Further Reading | Resources

The temperament similarity and pattern detection system is a mathematical method for discovering relationships between historical temperaments. The system analyzes temperament data from multiple sources and identifies patterns, similarities, and relationships through computational analysis.

Validation Results

The system has been validated through analysis of 192 temperaments from two datasets (PianoScope and CyberTuner). Results include:

Metric Value
Cross-dataset relationships identified 308
Temperaments analyzed 192
Data completeness 100%
Validated meantone patterns 46

Key Findings

See: Validation Report | Detailed Analysis

Available Tools

Methodology

Comma Detection

The system detects comma fractions by analyzing perfect fifths (P5 = 701.955 cents). The method calculates the average fifth deviation from pure and determines the fraction using:

fraction = syntonic_comma / |avg_fifth_deviation|

Detection tolerance: ±0.5 cents. Validation requires standard deviation < 2.5 cents.

Similarity Metrics

Multiple metrics are computed on normalized temperament offsets:

Normalization

Temperaments are normalized to ensure transpositional invariance: minimum offset shifted to 0, wrapped to [0, 1200) range. This ensures temperaments in different keys are comparable.

Mathematical Constants

Comma Values (cents)

Expected Meantone Fifth Deviations

API

Endpoints:

📖 View Complete API Documentation | Technical Documentation

See Also