bhargava-swara 0.0.13

A library for analysis and synthesis of Indian classical music

Bhargava Swara

A Python library for analyzing and visualizing Indian classical music, including spectrogram generation (Mel-frequency, Chroma, CQT, and Cent filterbank), raga, tala, tempo, tradition, ornaments, and full analysis.

Prerequisites

• Gemini API Key:
  This library uses Google's Gemini API for music analysis. To obtain a key:

  1. Sign up for a Google Cloud account
  2. Enable the Generative AI API in the Google Cloud Console
  3. Create an API key in the "Credentials" section
     Refer to Google's Generative AI Docs for details

• Audio Files:
  Supported formats include WAV and MP3 for analysis and spectrogram generation

Installation

Install the library using pip:

pip install bhargava_swara

Dependencies

• google-generativeai>=0.1.0
• librosa>=0.10.0
• matplotlib>=3.7.0
• numpy>=1.24.0

Spectrogram Generation

Generate various types of spectrograms to visualize different aspects of audio frequency content over time.

Mel-Frequency Spectrogram

from bhargava_swara import generate_mel_spectrogram

audio = "path/to/audio.wav"
output = "path/to/output_mel_spectrogram.png"
generate_mel_spectrogram(audio, output, n_mels=128, fmax=8000)
print("Mel spectrogram generated successfully!")

CQT Spectrogram

from bhargava_swara import generate_cqt_spectrogram

audio = "path/to/audio.wav"
output = "path/to/output_cqt_spectrogram.png"
generate_cqt_spectrogram(audio, output, hop_length=512, n_bins=84)
print("CQT spectrogram generated successfully!")

Cent Filterbank Spectrogram

from bhargava_swara import generate_cent_spectrogram

audio = "path/to/audio.wav"
output = "path/to/output_cent_spectrogram.png"
generate_cent_spectrogram(audio, output, n_filters=128, fmax=8000)
print("Cent filterbank spectrogram generated successfully!")

Spectrogram Parameters:

• audio: Path to the input audio file (e.g., WAV or MP3)
• output: Path to save the PNG file
• Mel-specific: n_mels (default: 128), fmax (default: 8000)
• Chroma-specific: n_chroma (default: 12), hop_length (default: 512)
• CQT-specific: hop_length (default: 512), n_bins (default: 84)
• Cent-specific: n_filters (default: 128), fmax (default: 8000)

Music Analysis

Analyze various aspects of Indian classical music using the Gemini API.

Raga Analysis

from bhargava_swara import analyze_raga

api_key = "YOUR_API_KEY"
audio = "path/to/audio.wav"
result = analyze_raga(audio, api_key)
print(f"Raga: {result}")

Tala Analysis

from bhargava_swara import analyze_tala

api_key = "YOUR_API_KEY"
audio = "path/to/audio.wav"
result = analyze_tala(audio, api_key)
print(f"Tala: {result}")

Tempo Analysis

from bhargava_swara import analyze_tempo

api_key = "YOUR_API_KEY"
audio = "path/to/audio.wav"
result = analyze_tempo(audio, api_key)
print(f"Tempo: {result}")

Tradition Analysis

from bhargava_swara import analyze_tradition

api_key = "YOUR_API_KEY"
audio = "path/to/audio.wav"
result = analyze_tradition(audio, api_key)
print(f"Tradition: {result}")

Ornament Analysis

from bhargava_swara import analyze_ornaments

api_key = "YOUR_API_KEY"
audio = "path/to/audio.wav"
result = analyze_ornaments(audio, api_key)
print(f"Ornaments: {result}")

Full Music Analysis

from bhargava_swara import analyze_music_full

api_key = "YOUR_API_KEY"
audio = "path/to/audio.wav"
result = analyze_music_full(audio, api_key)
print(f"Full Analysis:\n{result}")

Music Synthesis

Create Indian classical music elements with ease.

Tanpura Drone

Generate a tanpura drone for practice or ambiance.

from bhargava_swara import generate_tanpura_drone

# Play in real-time
generate_tanpura_drone(pitch=261.63, duration=10)

# Save to WAV
generate_tanpura_drone(pitch=261.63, duration=10, output_path="tanpura_drone.wav")

Parameters:

• pitch: Fundamental frequency of Sa (e.g., 261.63 Hz for C4).
• duration: Length of the drone in seconds.
• output_path: Path to save WAV file (optional; if None, plays in real-time).

License

This library is licensed under the MIT License. See the LICENSE file for details.

Change Log
==========

0.0.1 (26/03/2025)
-------------------
- First Release

===========

0.0.2 (27/03/2025)
-------------------
- Fixed missing module files in package

0.0.3 (27/03/2025)
-------------------
- Fixed ornaments detection file

0.0.4 (27/03/2025)
-------------------
- Fixed real time full analysis file

0.0.5 (27/03/2025)
-------------------
- Added mel-frequency spectogram generation

0.0.6 (27/03/2025)
-------------------
- seaborn included. README.txt updated

0.0.7 (27/03/2025)
-------------------
- mel-frequency spectogram issue resolved. README.md is created

0.0.8 (06/04/2025)
-------------------
- 3 more spectogram generations added. README.md file updated

0.0.9 (06/04/2025)
-------------------
- fixed bugs

0.0.10 to 0.0.12 (18/04/2025)
-------------------
- added tanpura droid generation

0.0.13 (18/04/2025)
-------------------
- removed spectograms