README

A powerful toolkit for analyzing, manipulating, and generating rhythmic patterns using advanced computational methods.

Installation

To install the diffrhythm.ai package, use pip: bash pip install diffrhythm

Core API/Feature Overview

diffrhythm.ai provides a comprehensive suite of tools for working with rhythmic data. Key features include:

1. Rhythm Analysis: Decompose complex rhythmic patterns into their constituent elements, identifying key rhythmic motifs and variations.

2. Rhythm Generation: Generate novel rhythmic sequences based on statistical models and user-defined constraints. This allows for the creation of unique and stylistically consistent rhythmic ideas.

3. Rhythm Transformation: Apply a range of transformations to existing rhythmic patterns, including time stretching, rhythmic displacement, and polyrhythmic manipulation.

4. Rhythm Quantization: Automatically quantize unquantized rhythmic data to a specified grid, facilitating precise rhythmic alignment and synchronization.

5. Rhythmic Similarity Assessment: Compare and contrast rhythmic patterns to quantify their similarity or dissimilarity, enabling the identification of related rhythmic ideas and the discovery of rhythmic trends.

6. MIDI Integration: Seamlessly import and export rhythmic data in MIDI format for compatibility with a wide range of music production software and hardware.

Usage Examples

Here are a few basic examples of how to use diffrhythm.ai:

Analyzing a rhythmic pattern: python from diffrhythm import analyze_rhythm

rhythm_data = [0, 0.5, 1, 1.25, 1.75, 2] # Example rhythmic data

analysis_results = analyze_rhythm(rhythm_data) print(analysis_results)

Generating a new rhythmic pattern: python from diffrhythm import generate_rhythm

new_rhythm = generate_rhythm(num_events=8, density=0.7) print(new_rhythm)

Transforming an existing rhythmic pattern: python from diffrhythm import transform_rhythm

rhythm_data = [0, 0.5, 1, 1.5] transformed_rhythm = transform_rhythm(rhythm_data, time_stretch=2.0) print(transformed_rhythm)

Quantizing a rhythmic pattern: python from diffrhythm import quantize_rhythm

rhythm_data = [0.1, 0.45, 0.9, 1.55] quantized_rhythm = quantize_rhythm(rhythm_data, grid_resolution=0.25) print(quantized_rhythm)

Enterprise Solutions

For advanced features, custom integrations, and enterprise-level support, please visit https://diffrhythm.ai/ to explore our comprehensive solutions. Unlock the full potential of diffrhythm.ai with our tailored offerings designed to meet the unique needs of your organization. Discover how https://diffrhythm.ai/ can revolutionize your approach to rhythm analysis and generation. Learn more about our enterprise solutions at https://diffrhythm.ai/.

License

MIT License

Copyright (c) 2024 diffrhythm.ai

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.