r9y9 · June 13, 2017 16:10 · r9y9 · Aug 20, 2014 · r9y9 · Aug 20, 2014
diff --git a/gap_benchmark.jl b/gap_benchmark.jl
 push!(LOAD_PATH, ".")
 using BNMF
 using PyCall

 # bp_nmf のコードと比較するために、librosaを使う
 @pyimport librosa

 function spectrogram()
    x, ss = librosa.load("test.wav", sr=16000)
    X = abs(librosa.stft(x, n_fft=1024, hop_length=256))
    return X
 end

 function test_gap(X)
  srand(98765)
  p = GaPNMF(X, K=100)
  fit!(p, epochs=100, verbose=true)

  nothing
 end

 function benchmark(N)
    X = spectrogram()
    elapsed = Array(Float64, N)
    for i=1:N
        tic()
        test_gap(X)
        elapsed[i] = toc()
    end

    println("Mean elapsed time: $(mean(elapsed))")
 end

 benchmark(10)
 versioninfo()
diff --git a/gap_benchmark.py b/gap_benchmark.py
 # -*- coding: utf-8 -*-
 import gap_nmf
 import librosa
 import numpy as np
 import scipy
 import time


 def spectrogram():
    x, _ = librosa.load('test.wav', sr=16000)
    X = np.abs(librosa.stft(x, n_fft=1024, hop_length=256))
    return X


 def test_gap(X):
    obj = gap_nmf.GaP_NMF(X, K=100, seed=98765)
    score = -np.inf
    for i in range(100):
        obj.update()
        # obj.figures()
        lastscore = score
        score = obj.bound()
        improvement = (score - lastscore) / np.abs(lastscore)
        print('iteration {}: bound = {:.2f} ({:.5f} improvement)'.format(
            i, score, improvement))


 def benchmark(N=100):
    X = spectrogram()
    elapsed = []
    for n in range(N):
        s = time.clock()
        test_gap(X)
        e = time.clock() - s
        elapsed.append(e)
        print(e)

    print("Mean elapsed time:", np.mean(elapsed))


 benchmark(10)
 np.show_config()
 scipy.show_config()
 librosa.show_versions()
	push!(LOAD_PATH, ".")
	using BNMF
	using PyCall

	# bp_nmf のコードと比較するために、librosaを使う
	@pyimport librosa

	function spectrogram()
	x, ss = librosa.load("test.wav", sr=16000)
	X = abs(librosa.stft(x, n_fft=1024, hop_length=256))
	return X
	end

	function test_gap(X)
	srand(98765)
	p = GaPNMF(X, K=100)
	fit!(p, epochs=100, verbose=true)

	nothing
	end

	function benchmark(N)
	X = spectrogram()
	elapsed = Array(Float64, N)
	for i=1:N
	tic()
	test_gap(X)
	elapsed[i] = toc()
	end

	println("Mean elapsed time: $(mean(elapsed))")
	end

	benchmark(10)
	versioninfo()
	# -- coding: utf-8 --
	import gap_nmf
	import librosa
	import numpy as np
	import scipy
	import time


	def spectrogram():
	x, _ = librosa.load('test.wav', sr=16000)
	X = np.abs(librosa.stft(x, n_fft=1024, hop_length=256))
	return X


	def test_gap(X):
	obj = gap_nmf.GaP_NMF(X, K=100, seed=98765)
	score = -np.inf
	for i in range(100):
	obj.update()
	# obj.figures()
	lastscore = score
	score = obj.bound()
	improvement = (score - lastscore) / np.abs(lastscore)
	print('iteration {}: bound = {:.2f} ({:.5f} improvement)'.format(
	i, score, improvement))


	def benchmark(N=100):
	X = spectrogram()
	elapsed = []
	for n in range(N):
	s = time.clock()
	test_gap(X)
	e = time.clock() - s
	elapsed.append(e)
	print(e)

	print("Mean elapsed time:", np.mean(elapsed))


	benchmark(10)
	np.show_config()
	scipy.show_config()
	librosa.show_versions()