def test_add_signal1D_5(self):
"""Add a signal to an 2D AnalogSignalArray
Note: should pass on row-wise signals"""
asa = nel.AnalogSignalArray([[1, 2, 4], [7, 8, 9]])
asa.add_signal([3, 4, 5])
assert np.array(
asa.data == np.array([[1, 2, 4], [7, 8, 9], [3, 4, 5]])).all()
def get_base_data(data_path, spike_path, session):
"""
Load and format data for replay analysis
"""
# get data session path from mat file
path = functions.get_session_path(
os.path.join(data_path, session) + '.mat')
# load position data from .mat file
df = functions.load_position(os.path.join(data_path, session) + '.mat')
# get the size of each maze
maze_size_cm = functions.get_maze_size_cm(
os.path.join(data_path, session) + '.mat')
# get session epochs
session_epochs = nel.EpochArray(
functions.get_epochs(os.path.join(data_path, session) + '.mat'))
# rescale epoch coordinates into cm
df = rescale_coords(df, session_epochs, maze_size_cm)
# put position into object
pos = nel.AnalogSignalArray(timestamps=df.ts,
data=[df.x],
fs=1 / statistics.mode(np.diff(df.ts)),
support=(session_epochs))
# load spikes & add to object
spikes = np.load(os.path.join(spike_path, session) + '.npy',
allow_pickle=True)
spikes_ = list(itertools.chain(*spikes))
session_bounds = nel.EpochArray([min(spikes_), max(spikes_)])
st = nel.SpikeTrainArray(timestamps=spikes,
support=session_bounds,
fs=32000)
return maze_size_cm, pos, st
def test_complex_asa_3(self):
N = 6
theta = np.array(2 * pi / N * np.arange(N))
exp_theta = np.exp(np.array(theta) * 1j)
casa = nel.AnalogSignalArray(exp_theta)
expected = np.array(
[[0., 1.04719755, 2.0943951, 3.14159265, -2.0943951, -1.04719755]])
assert np.all(np.isclose(casa.angle.data, expected))
def test_asa_mean3(self):
asa = nel.AnalogSignalArray([[1, 2, 4, 5], [7, 8, 9, 10]])
asa.add_signal([3, 4, 5, 6])
asa = asa[nel.EpochArray([[0, 1.1], [1.9, 3.1]])]
means = [seg.mean() for seg in asa]
assert np.array(means == np.array(
[np.array([1.5, 7.5, 3.5]),
np.array([4.5, 9.5, 5.5])])).all()
def test_complex_asa_2(self):
N = 6
theta = np.array(2 * pi / N * np.arange(N))
exp_theta = np.exp(np.array(theta) * 1j)
casa = nel.AnalogSignalArray(exp_theta)
expected = np.array([[
1.0 + 0.00000000e+00j, 0.5 + 8.66025404e-01j,
-0.5 + 8.66025404e-01j, -1.0 + 1.22464680e-16j,
-0.5 - 8.66025404e-01j, 0.5 - 8.66025404e-01j
]])
assert np.all(np.isclose(casa.data, expected))
def test_asa_data_format2(self):
asa = nel.AnalogSignalArray([[1, 2, 4], [7, 8, 9]])
asa.add_signal([3, 4, 5])
assert np.array(asa._data_colsig == np.array([[1, 7, 3], [2, 8, 4],
[4, 9, 5]])).all()
def test_asa_data_format1(self):
asa = nel.AnalogSignalArray([[1, 2, 4], [7, 8, 9]])
asa.add_signal([3, 4, 5])
assert np.array(asa._data_rowsig == np.array([[1, 2, 4], [7, 8, 9],
[3, 4, 5]])).all()
def test_complex_asa_1(self):
N = 128
theta = np.array(2 * pi / N * np.arange(N))
exp_theta = np.exp(np.array(theta) * 1j)
casa = nel.AnalogSignalArray(exp_theta)
assert np.all(np.isclose(casa.abs.data, 1))
def test_asa_asarray2(self):
asa = nel.AnalogSignalArray(np.arange(10), fs=1)
assert asa(0.5) == np.array([0.5])
assert asa.asarray(at=0.5).yvals == np.array([0.5])
def test_asa_halfopen_4(self):
asa = nel.AnalogSignalArray([0, 0, 0, 1, 1, 1, 2, 2, 2])
epochs = nel.utils.get_inactive_epochs(asa, v1=1, v2=1)
assert np.allclose(epochs.data, np.array([0, 6]))
def test_asa_halfopen_2(self):
asa = nel.AnalogSignalArray([0, 0, 0, 1, 1, 1, 2, 2, 2])
epochs = nel.utils.get_run_epochs(asa, v1=2, v2=2)
assert np.allclose(epochs.data, np.array([6, 9]))
def test_asa_halfopen_1(self):
asa = nel.AnalogSignalArray([0, 1, 2, 3, 4, 5, 6])
assert asa.n_samples == 7
assert asa.support.duration == 7
def test_asa_mean2(self):
asa = nel.AnalogSignalArray([[1, 2, 4, 5], [7, 8, 9, 10]])
asa.add_signal([3, 4, 5, 6])
asa = asa[nel.EpochArray([[0, 1.1], [1.9, 3.1]])]
assert np.array(asa.mean() == np.array([3., 8.5, 4.5])).all()
def test_asa_mean1(self):
asa = nel.AnalogSignalArray([[1, 2, 4, 5], [7, 8, 9, 10]])
asa.add_signal([3, 4, 5, 6])
assert np.array(asa.mean() == np.array([3., 8.5, 4.5])).all()
def test_asa_n_samples(self):
asa = nel.AnalogSignalArray([[1, 2, 4, 5], [7, 8, 9, 10]])
asa.add_signal([3, 4, 5, 6])
assert asa.n_samples == 4
def test_add_signal1D_1(self):
"""Add a signal to an 1D AnalogSignalArray"""
asa = nel.AnalogSignalArray([1, 2, 4])
asa.add_signal([3, 4, 5])
assert asa.n_signals == 2
def test_asa_asarray(self):
asa = nel.AnalogSignalArray([[1, 2, 4], [7, 8, 9]])
asa.add_signal([3, 4, 5])
assert np.array(asa.asarray().yvals == np.array([[1, 2, 4], [7, 8, 9],
[3, 4, 5]])).all()