def test_add_noise(self):
'''Test that noise is added predictably.'''
# test uniform noise, seed for reproducibility
inp_data = \
array([-1.875, -1.5 , -1.125, -0.75 , -0.375, 0., 0.375, 0.75 ,
1.125, 1.5 , 1.875, 2.25 , 2.625, -3. , -2.625, -2.25 ,
-1.875, -1.5 , -1.125, -0.75 , -0.375, 0. , 0.375, 0.75 ,
1.125])
nfap = [uniform, -.1, .2]
seed(0)
exp = uniform.rvs(-.1, .2, size=25)+inp_data
seed(0)
obs = add_noise(nfap, inp_data)
assert_array_almost_equal(exp, obs)
def test_add_noise(self):
'''Test that noise is added predictably.'''
# test uniform noise, seed for reproducibility
inp_data = \
array([-1.875, -1.5 , -1.125, -0.75 , -0.375, 0., 0.375, 0.75 ,
1.125, 1.5 , 1.875, 2.25 , 2.625, -3. , -2.625, -2.25 ,
-1.875, -1.5 , -1.125, -0.75 , -0.375, 0. , 0.375, 0.75 ,
1.125])
nfap = [uniform, -.1, .2]
seed(0)
exp = uniform.rvs(-.1, .2, size=25) + inp_data
seed(0)
obs = add_noise(nfap, inp_data)
assert_array_almost_equal(exp, obs)
def test_generate_otu_from_pt_in_R5(self):
'''Test that an OTU is correctly generated.'''
seed(0)
pt = (2, 10, 0, .5, [subsample_otu_evenly, .5])
nfap = [uniform, -5, 10]
y_shift = 100
wave_f = sawtooth
base_otu = 100 + signal(pt[1], pt[0], pt[2], wave_f)
noisy_otu = add_noise(nfap, base_otu)
sampling_f = subsample_otu_evenly
exp_otu = sampling_f(noisy_otu, .5)
seed(0)
obs_otu = generate_otu_from_pt_in_R5(pt, wave_f, y_shift)
assert_array_almost_equal(obs_otu, exp_otu)
def test_generate_otu_from_pt_in_R5(self):
'''Test that an OTU is correctly generated.'''
seed(0)
pt = (2, 10, 0, .5, [subsample_otu_evenly, .5])
nfap = [uniform, -5, 10]
y_shift = 100
wave_f = sawtooth
base_otu = 100 + signal(pt[1], pt[0], pt[2], wave_f)
noisy_otu = add_noise(nfap, base_otu)
sampling_f = subsample_otu_evenly
exp_otu = sampling_f(noisy_otu, .5)
seed(0)
obs_otu = generate_otu_from_pt_in_R5(pt, wave_f, y_shift)
assert_array_almost_equal(obs_otu, exp_otu)
