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Description:

pghipy 0.1.1

pghipy: Phase Gradient Heap Integration in Python
A Python implementation of STFT/ISTFT transforms and phase recovery using Phase Gradient Heap Integration. Based on code from phase-reconstruction and tifgan/phase_recovery. The package does not require installation of ltfatpy and works in Windows/MacOS/Linux.
Installation
pip install pghipy

Usage
import librosa
import numpy as np
from pghipy import get_default_window, calculate_synthesis_window
from pghipy import stft, pghi, istft

NFFT = 1024
HOP = NFFT//8 # Increasing overlap improves phase recovery

# Create Gaussian windows
winpghi, gamma = get_default_window(NFFT)
winsynth = calculate_synthesis_window(NFFT, HOP, winpghi)

# Magnitude spectrogram
y, sr = librosa.load(librosa.example('trumpet'))
S = np.abs(stft(y,win_length=NFFT,hop_length=HOP,window=winpghi))

# Estimate phase
phase = pghi(S,win_length=NFFT,hop_length=HOP,gamma=gamma)

# Invert
S = S*np.exp(1.0j*phase)
y_inv = istft(S,win_length=NFFT,hop_length=HOP,synthesis_window=winsynth)

Note: Uses numba JIT compiler to obtain a significant speed-up in phase recovery. Compilation is deferred until the first execution of the function pghi (i.e., lazy compilation).
Dependencies

numpy
scipy
numba

Thanks
Richard Lyman rrlyman
Andrés Marafioti andimarafioti
License
The MIT License (MIT)