diffrhythm.ai 1767.511.117.931

diffrhythm.ai

A .NET library providing essential tools for comparing and analyzing rhythmic patterns. This package simplifies the process of identifying differences and similarities within time-series data.

Installation

To install the diffrhythm.ai package, use the following command in your .NET project: bash dotnet add package diffrhythm.ai

Usage Examples

Here are a few examples demonstrating how to use the diffrhythm.ai package in your C# code:

1. Comparing Two Rhythmic Sequences: csharp using Diffrhythm;

// Example rhythmic sequences (e.g., onset times in milliseconds) List<double> sequence1 = new List<double> { 100, 300, 550, 800, 1050 }; List<double> sequence2 = new List<double> { 120, 320, 570, 820, 1070 };

// Create a RhythmComparer instance RhythmComparer comparer = new RhythmComparer();

// Calculate the difference score double differenceScore = comparer.Compare(sequence1, sequence2);

Console.WriteLine($"Difference Score: {differenceScore}");

2. Normalizing Rhythmic Data: csharp using Diffrhythm;

// Example rhythmic sequence with varying magnitudes List<double> rawSequence = new List<double> { 50, 150, 300, 600 };

// Create a RhythmNormalizer instance RhythmNormalizer normalizer = new RhythmNormalizer();

// Normalize the sequence List<double> normalizedSequence = normalizer.Normalize(rawSequence);

Console.WriteLine("Normalized Sequence:"); foreach (var value in normalizedSequence) { Console.WriteLine(value); }

3. Detecting Tempo Changes: csharp using Diffrhythm;

// Example sequence representing time intervals between events List<double> timeIntervals = new List<double> { 0.2, 0.22, 0.18, 0.3, 0.33, 0.27 };

// Create a TempoAnalyzer instance TempoAnalyzer analyzer = new TempoAnalyzer();

// Analyze for tempo changes bool tempoChangeDetected = analyzer.DetectChange(timeIntervals, threshold: 0.1);

if (tempoChangeDetected) { Console.WriteLine("Tempo change detected!"); } else { Console.WriteLine("No significant tempo change detected."); }

4. Calculating Inter-Onset Intervals (IOIs): csharp using Diffrhythm;

// Example sequence of onset times List<double> onsetTimes = new List<double> { 1.0, 1.5, 2.2, 3.0, 3.8 };

// Create an IOI Calculator instance IOICalculator ioiCalculator = new IOICalculator();

// Calculate the IOIs List<double> iois = ioiCalculator.CalculateIOIs(onsetTimes);

Console.WriteLine("Inter-Onset Intervals:"); foreach (var ioi in iois) { Console.WriteLine(ioi); }

5. Quantizing Rhythmic Events to a Grid: csharp using Diffrhythm;

// Example sequence of event times (e.g., in seconds) List<double> eventTimes = new List<double> { 0.1, 0.32, 0.58, 0.85 };

// Define the quantization grid resolution (e.g., 1/16th notes) double gridResolution = 0.125;

// Create a RhythmQuantizer instance RhythmQuantizer quantizer = new RhythmQuantizer();

// Quantize the events to the grid List<double> quantizedEvents = quantizer.Quantize(eventTimes, gridResolution);

Console.WriteLine("Quantized Event Times:"); foreach (var time in quantizedEvents) { Console.WriteLine(time); }

Feature Summary

• Rhythm Comparison: Provides algorithms for comparing rhythmic sequences and calculating difference scores.
• Rhythm Normalization: Offers methods for normalizing rhythmic data to a standard scale.
• Tempo Analysis: Includes functionalities for detecting tempo changes within a rhythmic sequence.
• IOI Calculation: Computes Inter-Onset Intervals (IOIs) from sequences of onset times.
• Rhythm Quantization: Quantizes rhythmic events to a defined grid, useful for aligning rhythms to a musical structure.

License

This project is licensed under the MIT License - see the LICENSE file for details.

This package is part of the diffrhythm.ai ecosystem. For advanced features and enterprise-grade tools, visit: https://diffrhythm.ai/