Python bindings to the miniDSP C library
Project description
pyminidsp
Python bindings to the miniDSP C library.
A comprehensive DSP toolkit providing signal generation, spectral analysis, filtering, effects, and more. All functions accept and return NumPy arrays.
Prerequisites
- Python >= 3.9
- FFTW3 development headers
- Ubuntu/Debian:
sudo apt install libfftw3-dev - macOS:
brew install fftw
- Ubuntu/Debian:
- A C compiler (gcc or clang)
Installation
# Clone the miniDSP C library (if not already present)
git clone https://github.com/wooters/miniDSP.git
# Create virtual environment (uses .python-version for Python version)
uv venv
# Install pyminidsp (set MINIDSP_SRC to point to the C library)
MINIDSP_SRC=./miniDSP uv sync
Or for development:
MINIDSP_SRC=./miniDSP uv sync --extra dev
Quick Start
import pyminidsp as md
# Generate a 440 Hz sine wave (1 second at 44.1 kHz)
signal = md.sine_wave(44100, amplitude=1.0, freq=440.0, sample_rate=44100.0)
# Compute the magnitude spectrum
mag = md.magnitude_spectrum(signal)
# Compute MFCCs from a frame
coeffs = md.mfcc(signal[:512], sample_rate=44100.0, num_mels=26, num_coeffs=13)
# Apply a low-pass biquad filter
lpf = md.BiquadFilter(md.LPF, freq=1000.0, sample_rate=44100.0)
filtered = lpf.process_array(signal)
# Clean up FFT caches when done
md.shutdown()
API Overview
Signal Generators
| Function | Description |
|---|---|
sine_wave(n, amplitude, freq, sample_rate) |
Pure sine tone |
white_noise(n, amplitude, seed) |
Gaussian white noise |
impulse(n, amplitude, position) |
Kronecker delta |
chirp_linear(n, amplitude, f_start, f_end, sample_rate) |
Linear frequency sweep |
chirp_log(n, amplitude, f_start, f_end, sample_rate) |
Logarithmic frequency sweep |
square_wave(n, amplitude, freq, sample_rate) |
Square wave |
sawtooth_wave(n, amplitude, freq, sample_rate) |
Sawtooth wave |
shepard_tone(n, amplitude, base_freq, sample_rate, rate, num_octaves) |
Shepard tone illusion |
Spectral Analysis
| Function | Description |
|---|---|
magnitude_spectrum(signal) |
One-sided magnitude spectrum via FFT |
power_spectral_density(signal) |
Periodogram PSD estimate |
phase_spectrum(signal) |
Phase spectrum in radians |
stft(signal, n, hop) |
Short-Time Fourier Transform |
mel_filterbank(n, sample_rate, num_mels) |
Mel-spaced triangular filterbank |
mel_energies(signal, sample_rate, num_mels) |
Mel-band energies |
mfcc(signal, sample_rate, num_mels, num_coeffs) |
Mel-frequency cepstral coefficients |
Signal Analysis
| Function | Description |
|---|---|
rms(signal) |
Root mean square |
energy(signal) |
Signal energy |
power(signal) / power_db(signal) |
Signal power (linear / dB) |
zero_crossing_rate(signal) |
Zero-crossing rate |
autocorrelation(signal, max_lag) |
Normalised autocorrelation |
peak_detect(signal, threshold, min_distance) |
Local maxima detection |
f0_autocorrelation(signal, sample_rate, min_freq, max_freq) |
F0 via autocorrelation |
f0_fft(signal, sample_rate, min_freq, max_freq) |
F0 via FFT peak picking |
Effects & Filters
| Function | Description |
|---|---|
delay_echo(signal, delay_samples, feedback, dry, wet) |
Echo effect |
tremolo(signal, rate_hz, depth, sample_rate) |
Amplitude modulation |
comb_reverb(signal, delay_samples, feedback, dry, wet) |
Comb-filter reverb |
convolution_time(signal, kernel) |
Time-domain convolution |
convolution_fft_ola(signal, kernel) |
FFT overlap-add convolution |
moving_average(signal, window_len) |
Moving average filter |
fir_filter(signal, coeffs) |
FIR filter |
BiquadFilter(type, freq, sample_rate) |
IIR biquad filter (LPF/HPF/BPF/etc.) |
DTMF
| Function | Description |
|---|---|
dtmf_generate(digits, sample_rate, tone_ms, pause_ms) |
Generate DTMF tones |
dtmf_detect(signal, sample_rate) |
Detect DTMF digits |
Delay Estimation (GCC-PHAT)
| Function | Description |
|---|---|
get_delay(sig_a, sig_b, margin, weighting) |
Delay between two signals |
gcc(sig_a, sig_b, weighting) |
Full cross-correlation |
Audio Steganography
| Function | Description |
|---|---|
steg_encode(host, message, sample_rate, method) |
Hide text in audio |
steg_decode(stego, sample_rate, method) |
Recover hidden text |
steg_encode_bytes(host, data, sample_rate, method) |
Hide binary data |
steg_decode_bytes(stego, sample_rate, method) |
Recover binary data |
steg_detect(signal, sample_rate) |
Detect steganography method |
Spectrogram Art
| Function | Description |
|---|---|
spectrogram_text(text, freq_lo, freq_hi, duration, sample_rate) |
Text visible in spectrogram |
Running Tests
MINIDSP_SRC=./miniDSP uv run pytest tests/ -v
License
MIT
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