def test_temporaldataset_convert_to_dataset(self):
measurements = np.zeros((10, 5, 15))
des = {'session': 0, 'subj': 0}
obs_des = {'conds': np.array([0, 0, 1, 1, 2, 2, 2, 3, 4, 5])}
chn_des = {'rois': np.array(['V1', 'V1', 'IT', 'IT', 'V4'])}
tim_des = {
'time': np.linspace(0, 1000, 15),
'time_formatted':
['%0.0f ms' % (x) for x in np.linspace(0, 1000, 15)]
}
data_temporal = rsd.TemporalDataset(measurements=measurements,
descriptors=des,
obs_descriptors=obs_des,
channel_descriptors=chn_des,
time_descriptors=tim_des)
data = data_temporal.convert_to_dataset('time')
self.assertEqual(data.n_obs, 150)
self.assertEqual(data.n_channel, 5)
self.assertEqual(len(data.obs_descriptors['time']), 150)
self.assertEqual(data.obs_descriptors['time'][0], tim_des['time'][0])
self.assertEqual(data.obs_descriptors['time'][10], tim_des['time'][1])
self.assertEqual(data.obs_descriptors['time_formatted'][10],
tim_des['time_formatted'][1])
self.assertEqual(data.obs_descriptors['conds'][0], obs_des['conds'][0])
self.assertEqual(data.obs_descriptors['conds'][1], obs_des['conds'][1])
def test_temporaldataset_subset_time(self):
measurements = np.zeros((10, 5, 15))
des = {'session': 0, 'subj': 0}
obs_des = {'conds': np.array([0, 0, 1, 1, 2, 2, 2, 3, 4, 5])}
chn_des = {'rois': np.array(['V1', 'V1', 'IT', 'IT', 'V4'])}
tim_des = {'time': np.linspace(0, 1000, 15)}
data = rsd.TemporalDataset(measurements=measurements,
descriptors=des,
obs_descriptors=obs_des,
channel_descriptors=chn_des,
time_descriptors=tim_des)
subset = data.subset_time(by='time',
t_from=tim_des['time'][3],
t_to=tim_des['time'][3])
self.assertEqual(subset.n_obs, 10)
self.assertEqual(subset.n_channel, 5)
self.assertEqual(subset.n_time, 1)
self.assertEqual(subset.time_descriptors['time'][0],
tim_des['time'][3])
subset = data.subset_time(by='time',
t_from=tim_des['time'][3],
t_to=tim_des['time'][5])
self.assertEqual(subset.n_obs, 10)
self.assertEqual(subset.n_channel, 5)
self.assertEqual(subset.n_time, 3)
self.assertEqual(subset.time_descriptors['time'][0],
tim_des['time'][3])
self.assertEqual(subset.time_descriptors['time'][-1],
tim_des['time'][5])
def test_temporaldataset_simple_init(self):
measurements = np.zeros((10, 5, 15))
data = rsd.TemporalDataset(measurements)
self.assertEqual(data.n_obs, 10)
self.assertEqual(data.n_channel, 5)
self.assertEqual(data.n_time, 15)
self.assertEqual(len(data.time_descriptors['time']), 15)
self.assertEqual(data.time_descriptors['time'][0], 0)
def test_temporaldataset_bin_time(self):
measurements = np.random.randn(10, 5, 15)
des = {'session': 0, 'subj': 0}
obs_des = {'conds': np.array([0, 0, 1, 1, 2, 2, 2, 3, 4, 5])}
chn_des = {'rois': np.array(['V1', 'V1', 'IT', 'IT', 'V4'])}
tim_des = {'time': np.linspace(0, 1000, 15)}
data = rsd.TemporalDataset(measurements=measurements,
descriptors=des,
obs_descriptors=obs_des,
channel_descriptors=chn_des,
time_descriptors=tim_des)
bins = np.reshape(tim_des['time'], [5, 3])
binned_data = data.bin_time('time', bins)
self.assertEqual(binned_data.n_obs, 10)
self.assertEqual(binned_data.n_channel, 5)
self.assertEqual(binned_data.n_time, 5)
self.assertEqual(binned_data.time_descriptors['time'][0],
np.mean(bins[0]))
self.assertEqual(binned_data.measurements[0, 0, 0],
np.mean(measurements[0, 0, :3]))
def test_temporaldataset_split_obs(self):
measurements = np.zeros((10, 5, 15))
des = {'session': 0, 'subj': 0}
obs_des = {'conds': np.array([0, 0, 1, 1, 2, 2, 2, 3, 4, 5])}
chn_des = {'rois': np.array(['V1', 'V1', 'IT', 'IT', 'V4'])}
tim_des = {'time': np.linspace(0, 1000, 15)}
data = rsd.TemporalDataset(measurements=measurements,
descriptors=des,
obs_descriptors=obs_des,
channel_descriptors=chn_des,
time_descriptors=tim_des)
splited_list = data.split_obs('conds')
self.assertEqual(len(splited_list), 6)
self.assertEqual(splited_list[0].n_obs, 2)
self.assertEqual(splited_list[2].n_obs, 3)
self.assertEqual(splited_list[0].n_channel, 5)
self.assertEqual(splited_list[2].n_channel, 5)
self.assertEqual(splited_list[0].n_time, 15)
self.assertEqual(splited_list[2].n_time, 15)
self.assertEqual(splited_list[2].obs_descriptors['conds'][0], 2)
def test_temporaldataset_full_init(self):
measurements = np.zeros((10, 5, 15))
des = {'session': 0, 'subj': 0}
obs_des = {
'conds': np.array(['cond_' + str(x) for x in np.arange(10)])
}
chn_des = {'rois': np.array(['roi_' + str(x) for x in np.arange(5)])}
tim_des = {'time': np.linspace(0, 1000, 15)}
data = rsd.TemporalDataset(measurements=measurements,
descriptors=des,
obs_descriptors=obs_des,
channel_descriptors=chn_des,
time_descriptors=tim_des)
self.assertEqual(data.n_obs, 10)
self.assertEqual(data.n_channel, 5)
self.assertEqual(data.n_time, 15)
self.assertEqual(data.descriptors, des)
self.assertEqual(data.obs_descriptors, obs_des)
self.assertEqual(data.channel_descriptors, chn_des)
self.assertEqual(data.time_descriptors, tim_des)