def test_raiseinputerrors():
"""
Confirm that ValueErrors from dumb user input are raised
"""
# Load data
data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
data2 = copy.copy(data)
data2[-1] = np.nan
with pytest.raises(ValueError) as excinfo:
plv(data, data[:-1], (13, 30), (80, 200))
assert 'same length' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data2, (13, 30), (80, 200))
assert 'NaNs' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (13, 30, 31), (80, 200))
assert 'two elements' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (13, 30), (80, 200, 201))
assert 'two elements' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (-13, 30), (80, 200))
assert 'must be > 0' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (13, 30), (-80, 200))
assert 'must be > 0' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
mi_tort(data, data, (13, 30), (80, 200), Nbins=1)
assert 'integer >1' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
mi_tort(data, data, (13, 30), (80, 200), Nbins=8.8)
assert 'integer >1' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
otc(data, (80, 200), -1)
assert 'positive number' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
otc(data, (80, 200), 4, t_modsig=(.5, -.5))
assert 'Invalid time range' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
_peaktimes(data, prc=101)
assert '0 and 100' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
_chunk_time(data, samp_buffer=-1)
assert 'positive number' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
_chunk_time(data, samp_buffer=2.5)
assert 'integer' in str(excinfo.value)
def test_raiseinputerrors():
"""
Confirm that ValueErrors from dumb user input are raised
"""
# Load data
data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
data2 = copy.copy(data)
data2[-1] = np.nan
with pytest.raises(ValueError) as excinfo:
plv(data, data[:-1], (13, 30), (80, 200))
assert 'same length' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data2, (13, 30), (80, 200))
assert 'NaNs' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (13, 30, 31), (80, 200))
assert 'two elements' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (13, 30), (80, 200, 201))
assert 'two elements' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (-13, 30), (80, 200))
assert 'must be > 0' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
plv(data, data, (13, 30), (-80, 200))
assert 'must be > 0' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
mi_tort(data, data, (13, 30), (80, 200), Nbins=1)
assert 'integer >1' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
mi_tort(data, data, (13, 30), (80, 200), Nbins=8.8)
assert 'integer >1' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
otc(data, (80, 200), -1)
assert 'positive number' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
otc(data, (80, 200), 4, t_modsig=(.5, -.5))
assert 'Invalid time range' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
_peaktimes(data, prc=101)
assert '0 and 100' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
_chunk_time(data, samp_buffer=-1)
assert 'positive number' in str(excinfo.value)
with pytest.raises(ValueError) as excinfo:
_chunk_time(data, samp_buffer=2.5)
assert 'integer' in str(excinfo.value)
def test_otc():
"""
Test PAC function: OTC
"""
# Load data
data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
# Confirm consistency in result
t_modsig = (-.5, .5)
fs = 1000.
f_hi = (80, 200)
f_step = 4
pac, tf, a_events, mod_sig = otc(data,
f_hi,
f_step,
fs=fs,
t_modsig=t_modsig)
assert np.allclose(pac, 235.02888, atol=10**-5)
# Confirm correct shapes in outputs
assert np.shape(tf) == ((f_hi[1] - f_hi[0]) / f_step, len(data))
for i in range(len(a_events)):
assert np.max(a_events[i]) <= len(data)
assert np.shape(mod_sig) == ((f_hi[1] - f_hi[0]) / f_step,
len(
np.arange(t_modsig[0], t_modsig[1],
1 / fs)))
def test_otc():
"""
Test PAC function: OTC
"""
# Load data
data = np.load(os.path.dirname(pacpy.__file__) + '/tests/exampledata.npy')
# Confirm consistency in result
t_modsig = (-.5, .5)
fs = 1000.
f_hi = (80, 200)
f_step = 4
pac, tf, a_events, mod_sig = otc(
data, f_hi, f_step, fs=fs, t_modsig=t_modsig)
assert np.allclose(pac, 235.02888, atol=10 ** -5)
# Confirm correct shapes in outputs
assert np.shape(tf) == ((f_hi[1] - f_hi[0]) / f_step, len(data))
for i in range(len(a_events)):
assert np.max(a_events[i]) <= len(data)
assert np.shape(mod_sig) == (
(f_hi[1] - f_hi[0]) / f_step, len(np.arange(t_modsig[0], t_modsig[1], 1 / fs)))
