def test_instantialtion(self):
# locations
locations1 = [(1.0, 2.), (3., 4.), (5, 6)]
locations2 = ((1.0, 2.), (3., 4.), (5, 6))
locations3 = np.array([[1.0, 2.], [3., 4.], [5, 6]])
# print(locations3)
# signs
signs1 = [1., -1., 0.]
signs2 = (-0.5, 0.6, 1)
signs3 = np.array([1, 1, -1])
# traces
traces1 = [np.random.rand(3, 4), np.ones((5, 4)), np.zeros((6, 4))]
traces2 = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16)
]
traces3 = np.random.randn(3, 5, 4)
# time axis
time = np.arange(-1, 3).astype(np.float32)
# trigger_ts
trigger_ts1 = [[0., 5., 6.],
np.array([3.3, 2.5, 7., 7.5, 9.]),
[8.1, 3.2, 4.0, 7.4, 20.9, 6.4]]
trigger_ts2 = None
trigger_ts3 = np.random.rand(3, 5)
strf1 = STRF.from_components(locations=locations1,
signs=signs1,
traces=traces1,
trigger_ts=trigger_ts1,
time=time)
strf2 = STRF.from_components(locations=locations2,
signs=signs2,
traces=traces2,
trigger_ts=trigger_ts2,
time=time)
strf3 = STRF.from_components(locations=locations3,
signs=signs3,
traces=traces3,
trigger_ts=trigger_ts3,
time=time)
print(strf1.get_conditions())
print(strf2.get_conditions())
print(strf3.get_conditions())
def test_to_from_h5_group(self):
locations = [(1.0, 2.), (3., 4.), (5, 6)]
signs = [1., -1., 0.]
traces = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16)
]
trigger_ts = [[0., 5., 6.], (7., 7.5, 9., 9.8, 10.4),
[8.1, 3.2, 4.0, 2, 4, 5]]
time = np.arange(-1, 3).astype(np.float32)
strf = STRF.from_components(locations=locations,
signs=signs,
traces=traces,
trigger_ts=trigger_ts,
time=time)
import h5py
if 'test.hdf5' in os.listdir(curr_folder) and os.path.isfile(
'test.hdf5'):
os.remove('test.hdf5')
test_f = h5py.File('test.hdf5')
strf_grp = test_f.create_group('strf')
strf.to_h5_group(strf_grp)
test_f.close()
load_f = h5py.File('test.hdf5', 'r')
strf2 = STRF.from_h5_group(load_f['strf'])
assert (np.array_equal(strf.data.loc[0, 'trigger_ts'],
strf2.data.loc[0, 'trigger_ts']))
assert (np.array_equal(strf.data.loc[1, 'trigger_ts'],
strf2.data.loc[1, 'trigger_ts']))
assert (np.array_equal(strf.data.loc[2, 'trigger_ts'],
strf2.data.loc[2, 'trigger_ts']))
assert (np.array_equal(strf.data.loc[0, 'traces'],
strf2.data.loc[0, 'traces']))
assert (np.array_equal(strf.data.loc[1, 'traces'],
strf2.data.loc[1, 'traces']))
assert (np.array_equal(strf.data.loc[2, 'traces'],
strf2.data.loc[2, 'traces']))
'''
something can be added here to test the strf2 object
'''
load_f.close()
os.remove('test.hdf5')
def test_get_delta_amplitude_map(self):
np.random.seed(0)
locations = [(1.0, 10.), (2., 11.), (3., 12)]
signs = [1., -1., 0.]
traces = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16)
]
trigger_ts = [[0., 5., 6.], (7., 7.5, 9., 9.8, 10.4),
[8.1, 3.2, 4.0, 2, 4, 5]]
time = np.arange(-1, 3).astype(np.float32)
strf = STRF.from_components(locations=locations,
signs=signs,
traces=traces,
trigger_ts=trigger_ts,
time=time)
ampON, ampOFF, allAltPos, allAziPos = strf.get_delta_amplitude_map(
timeWindow=[0.5, 2.5])
# print(ampON)
# print(ampOFF)
# print(allAltPos)
# print(allAziPos)
assert (ampON[2, 0] + 0.01243919 < 1E-7)
assert (ampOFF[1, 1] - 0. < 1E-10)
assert (np.isnan(ampON[0, 0]))
assert (np.isnan(ampOFF[0, 0]))
def test_plot_traces(self):
locations = [(1.0, 10.), (2., 11.), (3., 12)]
signs = [1., -1., 0.]
traces = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16)
]
trigger_ts = [[0., 5., 6.], (7., 7.5, 9., 9.8, 10.4),
[8.1, 3.2, 4.0, 2, 4, 5]]
time = np.arange(-1, 3).astype(np.float32)
strf = STRF.from_components(locations=locations,
signs=signs,
traces=traces,
trigger_ts=trigger_ts,
time=time)
strf.plot_traces(f=None,
figSize=(10, 10),
yRange=[-0.1, 1.1],
altRange=None,
aziRange=None)
import matplotlib.pyplot as plt
# plt.show()
plt.close('all')
def test_merge_duplicates(self):
locations = [(1.0, 2.), (3., 4.), (5, 6), (3., 4.), (5., 6.)]
signs = [1., -1., 0., -1., 0]
traces = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16),
np.random.randn(10, 4), [np.array([5, 6, 7, 8])]
]
trigger_ts = [[0., 5., 6.], (7., 7.5, 9., 9.8, 10.4),
[8.1, 3.2, 4.0, 2, 4, 5],
np.arange(15, 25), [20.5]]
time = np.arange(-1, 3).astype(np.float32)
strf = STRF.from_components(locations=locations,
signs=signs,
traces=traces,
trigger_ts=trigger_ts,
time=time)
strf.merge_duplicates()
assert (len(strf.data) == 3)
assert (len(strf.data.loc[1, 'trigger_ts']) == 15)
assert (len(strf.data.loc[2, 'trigger_ts']) == 7)
strf.check_integrity()
def test_add_traces(self):
locations = [(1.0, 2.), (3., 4.), (5, 6)]
signs = [1., -1., 0.]
traces = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16)
]
trigger_ts = [[0., 5., 6.], (7., 7.5, 9., 9.8, 10.4),
[8.1, 3.2, 4.0, 2, 4, 5]]
time = np.arange(-1, 3).astype(np.float32)
strf = STRF.from_components(locations=locations,
signs=signs,
traces=traces,
trigger_ts=trigger_ts,
time=time)
locations2 = [(3., 4.), (5., 6.)]
signs2 = [-1., 0]
traces2 = [np.random.randn(3, 4), [np.array([5, 6, 7, 8])]]
trigger_ts2 = [np.arange(15, 18), [20.5]]
strf.add_traces(locations=locations2,
signs=signs2,
traces=traces2,
trigger_ts=trigger_ts2,
verbose=False)
assert (len(strf.data) == 3)
assert (np.array_equal(strf.data.iloc[0]['trigger_ts'],
np.array([0.0, 5.0, 6.0], dtype=np.float64)))
assert (np.array_equal(
strf.data.iloc[1]['trigger_ts'],
np.array([7.0, 7.5, 9.0, 9.8, 10.4, 15., 16., 17.],
dtype=np.float64)))
assert (np.array_equal(
strf.data.iloc[2]['trigger_ts'],
np.array([8.1, 3.2, 4.0, 2.0, 4.0, 5.0, 20.5], dtype=np.float64)))
strf.add_traces(locations=locations2,
signs=signs2,
traces=traces2,
trigger_ts=None,
verbose=False)
assert (len(strf.data) == 3)
assert (np.array_equal(strf.data.iloc[0]['trigger_ts'],
np.array([0.0, 5.0, 6.0], dtype=np.float64)))
assert (len(strf.data.iloc[1]['trigger_ts']) == 11)
assert (len(strf.data.iloc[2]['trigger_ts']) == 8)
def test_get_local_dff_strf(self):
np.random.seed(0)
locations = [(1.0, 10.), (2., 11.), (3., 12)]
signs = [1., -1., 0.]
traces = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16)
]
trigger_ts = [[0., 5., 6.], (7., 7.5, 9., 9.8, 10.4),
[8.1, 3.2, 4.0, 2, 4, 5]]
time = np.arange(-1, 3).astype(np.float32)
strf = STRF.from_components(locations=locations,
signs=signs,
traces=traces,
trigger_ts=trigger_ts,
time=time)
strf_dff = strf.get_local_dff_strf(is_collaps_before_normalize=True,
add_to_trace=3.)
# print(strf_dff.data)
# print(strf_dff.data.iloc[0]['traces'])
# print(strf_dff.data.iloc[1]['traces'])
# print(strf_dff.data.iloc[2]['traces'])
assert (strf_dff.data.iloc[0]['traces'].shape ==
strf_dff.data.iloc[1]['traces'].shape ==
strf_dff.data.iloc[2]['traces'].shape == (1, 4))
assert (np.isnan(strf_dff.data.iloc[0]['trigger_ts']))
assert (np.isnan(strf_dff.data.iloc[1]['trigger_ts']))
assert (np.isnan(strf_dff.data.iloc[2]['trigger_ts']))
assert (np.array_equal(strf_dff.data.iloc[1]['traces'],
np.zeros((1, 4), dtype=np.float32)))
assert (np.array_equal(strf_dff.data.iloc[2]['traces'],
np.zeros((1, 4), dtype=np.float32)))
strf_dff = strf.get_local_dff_strf(is_collaps_before_normalize=False,
add_to_trace=3.)
# print(strf_dff.data)
# print(strf_dff.data.iloc[0]['traces'])
# print(strf_dff.data.iloc[1]['traces'])
# print(strf_dff.data.iloc[2]['traces'])
assert (np.array_equal(strf_dff.data.iloc[1]['traces'],
np.zeros((5, 4), dtype=np.float32)))
assert (np.array_equal(strf_dff.data.iloc[2]['traces'],
np.zeros((6, 4), dtype=np.float32)))
def test_shink(self):
np.random.seed(0)
locations = [(1.0, 10.), (2., 11.), (3., 12)]
signs = [1., -1., 0.]
traces = [
np.random.rand(3, 4),
np.ones((5, 4), dtype=np.uint8),
np.zeros((6, 4), dtype=np.int16)
]
trigger_ts = [[0., 5., 6.], (7., 7.5, 9., 9.8, 10.4),
[8.1, 3.2, 4.0, 2, 4, 5]]
time = np.arange(-1, 3).astype(np.float32)
strf = STRF.from_components(locations=locations,
signs=signs,
traces=traces,
trigger_ts=trigger_ts,
time=time)
strf.shrink(altRange=[1.5, 3.5], aziRange=[10.5, 12.5])
assert (len(strf.data) == 2)