ref: 31a3fd4363da1a4b13ef6550ba07fbba2ec1f3b2
dir: /python/demos/demo_reading_speed.py/
#! /usr/bin/env python
# -*- coding: utf-8 -*-
"""
Compare the speed of several methods for reading and loading a sound file.
Optionally, this file can make use of the following packages:
- audioread https://github.com/beetbox/audioread
- scipy https://scipy.org
- librosa https://github.com/bmcfee/librosa
- pydub https://github.com/jiaaro/pydub
Uncomment the function names below and send us your speed results!
"""
test_functions = [
"read_file_aubio",
"load_file_aubio",
#"load_file_scipy",
#"load_file_scipy_mmap",
#"read_file_audioread",
#"load_file_librosa",
#"read_file_pydub",
#"load_file_pydub",
]
import numpy as np
def read_file_audioread(filename):
import audioread
# taken from librosa.util.utils
def convert_buffer_to_float(buf, n_bytes = 2, dtype = np.float32):
# Invert the scale of the data
scale = 1./float(1 << ((8 * n_bytes) - 1))
# Construct the format string
fmt = '<i{:d}'.format(n_bytes)
# Rescale and format the data buffer
out = scale * np.frombuffer(buf, fmt).astype(dtype)
return out
with audioread.audio_open(filename) as f:
total_frames = 0
for buf in f:
samples = convert_buffer_to_float(buf)
samples = samples.reshape(f.channels, -1)
total_frames += samples.shape[1]
return total_frames, f.samplerate
def load_file_librosa(filename):
import librosa
y, sr = librosa.load(filename, sr = None)
#print y.mean(), y.shape
return len(y), sr
def load_file_scipy(filename):
import scipy.io.wavfile
sr, y = scipy.io.wavfile.read(filename)
y = y.astype('float32') / 32767
#print y.mean(), y.shape
return len(y), sr
def load_file_scipy_mmap(filename):
import scipy.io.wavfile
sr, y = scipy.io.wavfile.read(filename, mmap = True)
#print y.mean(), y.shape
return len(y), sr
def read_file_pydub(filename):
from pydub import AudioSegment
song = AudioSegment.from_file(filename)
song.get_array_of_samples()
return song.frame_count(), song.frame_rate
def load_file_pydub(filename):
from pydub import AudioSegment
song = AudioSegment.from_file(filename)
y = np.asarray(song.get_array_of_samples(), dtype = 'float32')
y = y.reshape(song.channels, -1) / 32767.
return song.frame_count(), song.frame_rate
def read_file_aubio(filename):
import aubio
f = aubio.source(filename, hop_size = 1024)
total_frames = 0
while True:
_, read = f()
total_frames += read
if read < f.hop_size: break
return total_frames, f.samplerate
def load_file_aubio(filename):
import aubio
f = aubio.source(filename, hop_size = 1024)
y = np.zeros(f.duration, dtype = aubio.float_type)
total_frames = 0
while True:
samples, read = f()
y[total_frames:total_frames + read] = samples[:read]
total_frames += read
if read < f.hop_size: break
assert len(y) == total_frames
#print y.mean(), y.shape
return total_frames, f.samplerate
def test_speed(function, filename):
times = []
for _ in range(10):
start = time.time()
try:
total_frames, samplerate = function(filename)
except ImportError as e:
print ("error: failed importing {:s}".format(e))
return
elapsed = time.time() - start
#print ("{:5f} ".format(elapsed)),
times.append(elapsed)
#print
times = np.array(times)
duration_min = int(total_frames/float(samplerate) // 60)
str_format = '{:25s} took {:5f} seconds avg (±{:5f}) to run on a ~ {:d} minutes long file'
print (str_format.format(function.__name__, times.mean(), times.std(), duration_min ))
if __name__ == '__main__':
import sys, time
if len(sys.argv) < 2:
print ("not enough arguments")
sys.exit(1)
filename = sys.argv[1]
for f in test_functions:
# get actual function from globals
test_function = globals()[f]
test_speed(test_function, filename)