def run_FFT_analyzer():
args = parse_args()
window_ratio = convert_window_ratio(args.window_ratio)
ear = Stream_Analyzer(
device=args.
device, # Pyaudio (portaudio) device index, defaults to first mic input
rate=None, # Audio samplerate, None uses the default source settings
FFT_window_size_ms=60, # Window size used for the FFT transform
updates_per_second=
1000, # How often to read the audio stream for new data
smoothing_length_ms=
50, # Apply some temporal smoothing to reduce noisy features
n_frequency_bins=args.
frequency_bins, # The FFT features are grouped in bins
visualize=1, # Visualize the FFT features with PyGame
verbose=args.verbose, # Print running statistics (latency, fps, ...)
height=args.height, # Height, in pixels, of the visualizer window,
window_ratio=
window_ratio # Float ratio of the visualizer window. e.g. 24/9
)
fps = 60 #How often to update the FFT features + display
last_update = time.time()
while True:
if (time.time() - last_update) > (1. / fps):
last_update = time.time()
raw_fftx, raw_fft, binned_fftx, binned_fft = ear.get_audio_features(
)
import time
from src.stream_analyzer import Stream_Analyzer
ear = Stream_Analyzer(
device = None, # Manually play with this (int) if you don't see anything
rate = None, # Audio samplerate, None uses the default source settings
FFT_window_size_ms = 60, # Window size used for the FFT transform
updates_per_second = 2000, # How often to read the audio stream for new data
smoothing_length_ms = 50, # Apply some temporal smoothing to reduce noisy features
n_frequency_bins = 300, # The FFT features are grouped in bins
visualize = 1, # Visualize the FFT features with PyGame
verbose = 0 # Print running statistics (latency, fps, ...)
)
fps = 60 #How often to update the FFT features + display
last_update = time.time()
while True:
if (time.time() - last_update) > (1./fps):
last_update = time.time()
raw_fftx, raw_fft, binned_fftx, binned_fft = ear.get_audio_features()