def get_cosine_test_vector():
'''Get a max amplitude cosine test vector to try saturate the pipeline
with.'''
t = np.linspace(0, 1, 16000)
f = 20 # Hz
A = 2**15 - 1 # max 16b signed amplitude
x = A * np.cos(2 * np.pi * f * t)
x = aco.pdm_model(x, 'fast')
sigs = aco.aco(x)
return x, sigs
def get_multi_cosine_test_vector():
'''Get a max amplitude cosine test vector to try saturate the pipeline
with.'''
t = np.linspace(0, 1, 16000)
n_freqs = 100
freqs = np.logspace(0, np.log10(16000), 10)
A = (2**15 - 1) / n_freqs # max 16b signed amplitude
x = np.zeros(16000)
for f in freqs:
x += A * np.cos(2 * np.pi * f * t)
x = aco.pdm_model(x, 'fast')
sigs = aco.aco(x)
return x, sigs
def get_random_sample_test_vector(test_num):
top_dir = '../../../py/'
categories = ['yes/', 'noise/', 'no/', 'unknown/']
category = categories[test_num % 4]
sample_dir = top_dir + category
fnames = os.listdir(sample_dir)
idx = np.random.randint(len(fnames))
fname = sample_dir + fnames[idx]
print('Running test with', fname)
x = pdm.read_sample_file(fname)
x = aco.pdm_model(x, 'fast')
sigs = aco.aco(x)
return x, sigs
def get_random_test_vector():
x = np.random.randint(-2**15, 2**15 - 1, size=16000)
x = aco.pdm_model(x, 'fast')
sigs = aco.aco(x)
return x, sigs
def get_sample_test_vector():
'''Get a real audio sample for input and calculate the expected outputs.'''
x = pdm.read_sample_file(pdm.SAMPLE_FNAME)
x_distorted = aco.pdm_model(x, 'fast')
sigs = aco.aco(x_distorted)
return x_distorted, sigs