C++ API Reference
Complete API reference for libsonare C++ interface.
Overview
libsonare provides comprehensive audio analysis for C++ applications:
| Component | Purpose | Key Classes/Functions |
|---|---|---|
| Core | Audio I/O and signal processing | Audio, Spectrogram |
| Quick API | Simple one-line analysis | detect_bpm(), detect_key(), analyze() |
| MusicAnalyzer | Full analysis with callbacks | MusicAnalyzer, AnalysisResult |
| Features | Low-level feature extraction | MelSpectrogram, Chroma, spectral functions |
| Effects | Audio processing | hpss(), time_stretch(), pitch_shift() |
Terminology
New to audio analysis? See the Glossary for explanations of terms like BPM, STFT, Chroma, HPSS, and more.
Namespaces
All libsonare functionality is contained within the sonare namespace.
#include <sonare/sonare.h>
using namespace sonare;Core Classes
Audio
Audio buffer with shared ownership and zero-copy slicing.
Factory Methods
// From raw sample buffer (copied)
static Audio Audio::from_buffer(const float* samples, size_t size, int sample_rate);
// From vector (moved)
static Audio Audio::from_vector(std::vector<float> samples, int sample_rate);
// From file (WAV, MP3)
static Audio Audio::from_file(const std::string& path);
static Audio Audio::from_file(const std::string& path, const AudioLoadOptions& options);
// From memory buffer
static Audio Audio::from_memory(const uint8_t* data, size_t size);
static Audio Audio::from_memory(const uint8_t* data, size_t size, const AudioLoadOptions& options);Properties
const float* data() const; // Pointer to samples
size_t size() const; // Number of samples
int sample_rate() const; // Sample rate in Hz
float duration() const; // Duration in seconds
int channels() const; // Always 1 (mono)
bool empty() const; // True if no samplesOperations
// Zero-copy slice by time
Audio slice(float start_time, float end_time = -1.0f) const;
// Zero-copy slice by sample index
Audio slice_samples(size_t start_sample, size_t end_sample = -1) const;
// Access sample
float operator[](size_t index) const;
// Iterator support
const float* begin() const;
const float* end() const;AudioLoadOptions
Configuration for loading audio files with resource limits.
struct AudioLoadOptions {
size_t max_file_size = 500 * 1024 * 1024; // 500 MB default
int target_sample_rate = 0; // 0 = keep original
bool normalize = false; // Peak normalize on load
};Large File Handling
For very large files, set max_file_size appropriately or process in segments using slice().
Example
auto audio = sonare::Audio::from_file("song.mp3");
std::cout << "Duration: " << audio.duration() << "s\n";
// Zero-copy slicing
auto intro = audio.slice(0.0f, 30.0f);
auto chorus = audio.slice(60.0f, 90.0f);Spectrogram
Short-Time Fourier Transform (STFT) of audio signal.
struct StftConfig {
int n_fft = 2048;
int hop_length = 512;
int win_length = 0; // 0 = n_fft
WindowType window = WindowType::Hann;
bool center = true;
};
// Compute STFT
auto spec = Spectrogram::compute(audio, config);
// Properties
spec.n_bins(); // Frequency bins (n_fft/2 + 1)
spec.n_frames(); // Time frames
spec.n_fft();
spec.hop_length();
spec.sample_rate();
// Data access
spec.complex_view(); // [n_bins x n_frames]
spec.magnitude(); // Cached
spec.power(); // Cached
spec.to_db(); // Convert to dB
// Reconstruction
auto reconstructed = spec.to_audio();Thread Safety
Spectrogram objects are not thread-safe. The cached magnitude() and power() results use lazy initialization. If you need to access the same Spectrogram from multiple threads, create separate copies or synchronize access externally.
Quick API
Simple functions for common analysis tasks.
namespace sonare::quick {
// BPM detection (±2 BPM accuracy)
float detect_bpm(const float* samples, size_t length, int sample_rate);
// Key detection
Key detect_key(const float* samples, size_t length, int sample_rate);
// Beat times in seconds
std::vector<float> detect_beats(const float* samples, size_t length, int sample_rate);
// Onset times in seconds
std::vector<float> detect_onsets(const float* samples, size_t length, int sample_rate);
// Full analysis
AnalysisResult analyze(const float* samples, size_t length, int sample_rate);
}MusicAnalyzer Heavy
Facade class for comprehensive music analysis with lazy initialization.
Performance
Full analysis is computationally intensive. For long audio files (>3 minutes), consider using progress callbacks to show progress, or analyze only relevant segments.
MusicAnalyzerConfig config;
config.bpm_min = 80.0f;
config.bpm_max = 180.0f;
MusicAnalyzer analyzer(audio, config);
// Set progress callback
analyzer.set_progress_callback([](float progress, const char* stage) {
std::cout << stage << ": " << (progress * 100) << "%\n";
});
// Individual results
float bpm = analyzer.bpm();
Key key = analyzer.key();
auto beats = analyzer.beat_times();
auto chords = analyzer.chords();
// Full analysis
auto result = analyzer.analyze();StreamAnalyzer Real-time
Real-time streaming audio analyzer for visualizations and live monitoring.
Batch vs Streaming
Use MusicAnalyzer for full analysis of pre-recorded files. Use StreamAnalyzer for real-time processing with low latency.
Configuration
struct StreamConfig {
int sample_rate = 44100;
int n_fft = 2048;
int hop_length = 512;
WindowType window = WindowType::Hann;
// Feature flags
bool compute_magnitude = true;
bool compute_mel = true;
bool compute_chroma = true;
bool compute_onset = true;
bool compute_spectral = true;
// Mel configuration
int n_mels = 128;
float fmin = 0.0f;
float fmax = 0.0f; // 0 = sr/2
// Output throttling
int emit_every_n_frames = 1; // 4 = ~60fps at 44100Hz
// Progressive estimation intervals
float key_update_interval_sec = 5.0f;
float bpm_update_interval_sec = 10.0f;
};Basic Usage
#include <sonare/streaming/stream_analyzer.h>
StreamConfig config;
config.sample_rate = 44100;
config.n_mels = 64;
config.emit_every_n_frames = 4;
StreamAnalyzer analyzer(config);
// Process audio chunks (e.g., from audio callback)
void audio_callback(const float* samples, size_t n_samples) {
analyzer.process(samples, n_samples);
// Read available frames
size_t available = analyzer.available_frames();
if (available > 0) {
auto frames = analyzer.read_frames(available);
for (const auto& frame : frames) {
// frame.timestamp - time in seconds
// frame.mel - [n_mels] mel spectrogram
// frame.chroma - [12] chromagram
// frame.onset_strength - onset value
// frame.rms_energy - RMS energy
visualize(frame);
}
}
}StreamFrame
struct StreamFrame {
float timestamp; // Stream time in seconds
int frame_index; // Cumulative frame count
// Frequency features (sizes depend on config)
std::vector<float> magnitude; // [n_bins] or downsampled
std::vector<float> mel; // [n_mels]
std::vector<float> chroma; // [12]
// Scalar features
float spectral_centroid;
float spectral_flatness;
float rms_energy;
// Onset detection (1-frame lag)
float onset_strength;
bool onset_valid; // false for first frame
};SOA Format (Efficient Transfer)
For efficient inter-thread transfer, use Structure-of-Arrays format:
FrameBuffer buffer;
analyzer.read_frames_soa(max_frames, buffer);
// buffer.n_frames
// buffer.timestamps - [n_frames]
// buffer.mel - [n_frames * n_mels]
// buffer.chroma - [n_frames * 12]
// buffer.onset_strength - [n_frames]
// buffer.rms_energy - [n_frames]Quantized Formats (Bandwidth Reduction)
// 8-bit quantized (4x bandwidth reduction)
QuantizedFrameBufferU8 u8_buffer;
QuantizeConfig qconfig;
qconfig.mel_db_min = -80.0f;
qconfig.mel_db_max = 0.0f;
analyzer.read_frames_quantized_u8(max_frames, u8_buffer, qconfig);
// 16-bit quantized (2x bandwidth reduction)
QuantizedFrameBufferI16 i16_buffer;
analyzer.read_frames_quantized_i16(max_frames, i16_buffer, qconfig);Progressive Estimation
Get BPM and key estimates that improve over time:
AnalyzerStats stats = analyzer.stats();
// BPM (available after ~10 seconds)
if (stats.estimate.bpm > 0) {
std::cout << "BPM: " << stats.estimate.bpm
<< " (confidence: " << stats.estimate.bpm_confidence << ")\n";
}
// Key (available after ~5 seconds)
if (stats.estimate.key >= 0) {
const char* keys[] = {"C", "C#", "D", "D#", "E", "F", "F#", "G", "G#", "A", "A#", "B"};
std::cout << "Key: " << keys[stats.estimate.key]
<< (stats.estimate.key_minor ? " minor" : " major") << "\n";
}External Synchronization
For precise timing with external timeline:
// Track cumulative sample offset externally
size_t sample_offset = 0;
void audio_callback(const float* samples, size_t n_samples) {
analyzer.process(samples, n_samples, sample_offset);
sample_offset += n_samples;
}Reset
// Reset for new stream
analyzer.reset();
// Reset with base offset
analyzer.reset(initial_sample_offset);Feature Extraction
MelSpectrogram Medium
MelConfig config;
config.n_mels = 128;
config.stft.n_fft = 2048;
config.stft.hop_length = 512;
auto mel = MelSpectrogram::compute(audio, config);
// Power spectrum [n_mels x n_frames]
auto power = mel.power();
// Convert to dB
auto db = mel.to_db();
// MFCC
auto mfcc = mel.mfcc(13); // 13 coefficientsChroma Medium
ChromaConfig config;
config.n_chroma = 12;
auto chroma = Chroma::compute(audio, config);
// Features [12 x n_frames]
auto features = chroma.features();
// Mean energy per pitch class
auto energy = chroma.mean_energy();Spectral Features
// Per-frame spectral centroid (Hz)
std::vector<float> spectral_centroid(const Spectrogram& spec, int sr);
// Per-frame spectral bandwidth (Hz)
std::vector<float> spectral_bandwidth(const Spectrogram& spec, int sr);
// Per-frame spectral rolloff (Hz)
std::vector<float> spectral_rolloff(const Spectrogram& spec, int sr, float percent = 0.85f);
// Per-frame spectral flatness
std::vector<float> spectral_flatness(const Spectrogram& spec);
// Zero crossing rate
std::vector<float> zero_crossing_rate(const Audio& audio, int frame_length, int hop_length);
// RMS energy
std::vector<float> rms_energy(const Audio& audio, int frame_length, int hop_length);
// Spectral contrast (difference between peaks and valleys in frequency bands)
std::vector<float> spectral_contrast(const Spectrogram& spec, int sr, int n_bands = 6,
float fmin = 200.0f, float quantile = 0.02f);Pitch Tracking Medium
PitchConfig config;
config.frame_length = 2048;
config.hop_length = 512;
config.fmin = 65.0f; // C2
config.fmax = 2093.0f; // C7
config.threshold = 0.3f;
// YIN algorithm
PitchResult yin = yin_track(audio, config);
// pYIN algorithm (probabilistic YIN with HMM smoothing)
PitchResult pyin = pyin(audio, config);
// Access results
float median = pyin.median_f0();
float mean = pyin.mean_f0();
const std::vector<float>& f0 = pyin.f0;
const std::vector<bool>& voiced = pyin.voiced_flag;CQT / VQT Medium
Constant-Q Transform and Variable-Q Transform for music analysis.
CqtConfig config;
config.fmin = 32.7f; // C1
config.n_bins = 84; // 7 octaves
config.bins_per_octave = 12; // Semitone resolution
auto cqt_result = cqt(audio, config);
// Access magnitude [n_bins x n_frames]
auto mag = cqt_result.magnitude();
auto power = cqt_result.power();
// Variable-Q Transform (with variable Q factor)
VqtConfig vqt_config;
vqt_config.gamma = 0.0f; // 0 = CQT behavior
auto vqt_result = vqt(audio, vqt_config);Thread Safety
CqtResult and VqtResult objects use lazy initialization for cached results. They are not thread-safe for concurrent access. Create separate copies for multi-threaded use.
Deprecated Functions
The inverse transform functions icqt() and ivqt() are deprecated and will be removed in a future version.
// Deprecated - do not use
[[deprecated("Use Griffin-Lim reconstruction instead")]]
Audio icqt(const CqtResult& cqt);
[[deprecated("Use Griffin-Lim reconstruction instead")]]
Audio ivqt(const VqtResult& vqt);Migration: For audio reconstruction from CQT/VQT, use the Griffin-Lim algorithm with STFT instead:
// Recommended approach
auto spec = Spectrogram::compute(audio, stft_config);
// ... modify magnitude ...
auto reconstructed = griffin_lim(modified_magnitude, stft_config);Effects
HPSS Heavy
Performance
HPSS requires STFT computation and median filtering. Processing time scales with audio duration.
HpssConfig config;
config.kernel_size_harmonic = 31;
config.kernel_size_percussive = 31;
auto result = hpss(audio, config);
// result.harmonic
// result.percussive
// Convenience functions
auto harm = harmonic(audio);
auto perc = percussive(audio);Time Stretch Heavy
Performance
Uses phase vocoder algorithm. Processing time increases with audio duration.
// 0.5 = half speed, 2.0 = double speed
auto slow = time_stretch(audio, 0.5f);
auto fast = time_stretch(audio, 1.5f);Pitch Shift Heavy
Performance
Combines time stretching and resampling. Processing time increases with audio duration.
// Semitones: +12 = one octave up
auto higher = pitch_shift(audio, 2.0f);
auto lower = pitch_shift(audio, -3.0f);Normalize & Audio Utilities
// Peak normalization
auto normalized = normalize(audio, 0.0f); // Target peak level in dB
// RMS normalization
auto rms_norm = normalize_rms(audio, -20.0f); // Target RMS level in dB
// Silence trimming
auto trimmed = trim(audio, -60.0f); // Threshold in dB
// Level measurement
float peak = peak_db(audio); // Peak amplitude in dB
float rms = rms_db(audio); // RMS level in dB
// Gain application
auto louder = apply_gain(audio, 6.0f); // +6 dB
auto quieter = apply_gain(audio, -3.0f); // -3 dB
// Fades
auto with_fade_in = fade_in(audio, 0.5f); // 0.5 second fade in
auto with_fade_out = fade_out(audio, 1.0f); // 1.0 second fade out
// Find silence boundaries
auto [start, end] = detect_silence_boundaries(audio, -60.0f);Types
Key
struct Key {
PitchClass root; // C=0, Cs=1, ..., B=11
Mode mode; // Major, Minor
float confidence; // 0.0 - 1.0
std::string to_string() const; // "C major"
std::string short_name() const; // "C", "Am"
};Chord
struct Chord {
PitchClass root;
ChordQuality quality; // Major, Minor, Dim, Aug, 7th, etc.
float start; // seconds
float end; // seconds
float confidence;
std::string to_string() const; // "C", "Am", "G7"
};Section
struct Section {
SectionType type; // Intro, Verse, Chorus, etc.
float start;
float end;
float energy_level;
float confidence;
std::string to_string() const;
};AnalysisResult
struct AnalysisResult {
float bpm;
float bpm_confidence;
Key key;
TimeSignature time_signature;
std::vector<Beat> beats;
std::vector<Chord> chords;
std::vector<Section> sections;
Timbre timbre;
Dynamics dynamics;
RhythmFeatures rhythm;
std::string form; // "IABABCO"
};Enums
enum class PitchClass {
C = 0, Cs, D, Ds, E, F, Fs, G, Gs, A, As, B
};
enum class Mode { Major, Minor };
enum class ChordQuality {
Major, Minor, Diminished, Augmented,
Dominant7, Major7, Minor7, Sus2, Sus4
};
enum class SectionType {
Intro, Verse, PreChorus, Chorus, Bridge, Instrumental, Outro
};
enum class WindowType {
Hann, Hamming, Blackman, Rectangular
};Unit Conversion
// Hz <-> Mel (Slaney formula)
float hz_to_mel(float hz);
float mel_to_hz(float mel);
// Hz <-> MIDI note number
float hz_to_midi(float hz); // A4 = 440Hz = 69
float midi_to_hz(float midi);
// Hz <-> Note name
std::string hz_to_note(float hz); // "A4", "C#5"
float note_to_hz(const std::string& note);
// Time <-> Frames
float frames_to_time(int frames, int sr, int hop_length);
int time_to_frames(float time, int sr, int hop_length);C API
For FFI integration.
#include <sonare_c.h>
// Audio
SonareError sonare_audio_from_buffer(const float* data, size_t len, int sr, SonareAudio** out);
SonareError sonare_audio_from_file(const char* path, SonareAudio** out);
void sonare_audio_free(SonareAudio* audio);
// Analysis
SonareError sonare_detect_bpm(const SonareAudio* audio, float* out_bpm, float* out_confidence);
SonareError sonare_detect_key(const SonareAudio* audio, SonareKey* out_key);
SonareError sonare_detect_beats(const SonareAudio* audio, float** out_times, size_t* out_count);
SonareError sonare_analyze(const SonareAudio* audio, SonareAnalysisResult* out);
// Memory management
void sonare_free_floats(float* ptr);
void sonare_free_result(SonareAnalysisResult* result);
// Utility
const char* sonare_error_message(SonareError error);
const char* sonare_version(void);Error Handling
class SonareException : public std::exception {
public:
ErrorCode code() const;
const char* what() const noexcept override;
};
try {
auto audio = Audio::from_file("nonexistent.mp3");
} catch (const SonareException& e) {
if (e.code() == ErrorCode::FileNotFound) {
// Handle file not found
}
}