本文整理汇总了Python中neo.core.SpikeTrain.segment方法的典型用法代码示例。如果您正苦于以下问题：Python SpikeTrain.segment方法的具体用法？Python SpikeTrain.segment怎么用？Python SpikeTrain.segment使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类neo.core.SpikeTrain的用法示例。
在下文中一共展示了SpikeTrain.segment方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _read_spiketrain
# 需要导入模块: from neo.core import SpikeTrain [as 别名]
# 或者: from neo.core.SpikeTrain import segment [as 别名]
def _read_spiketrain(self, node, parent):
attributes = self._get_standard_attributes(node)
t_start = self._get_quantity(node["t_start"])
t_stop = self._get_quantity(node["t_stop"])
# todo: handle sampling_rate, waveforms, left_sweep
spiketrain = SpikeTrain(self._get_quantity(node["times"]),
t_start=t_start, t_stop=t_stop,
**attributes)
spiketrain.segment = parent
self.object_refs[node.attrs["object_ref"]] = spiketrain
return spiketrain示例2: _handle_processing_group
# 需要导入模块: from neo.core import SpikeTrain [as 别名]
# 或者: from neo.core.SpikeTrain import segment [as 别名]
def _handle_processing_group(self, block):
# todo: handle other modules than Units
units_group = self._file.get('processing/Units/UnitTimes')
segment_map = dict((segment.name, segment) for segment in block.segments)
for name, group in units_group.items():
if name == 'unit_list':
pass # todo
else:
segment_name = group['source'].value
#desc = group['unit_description'].value # use this to store Neo Unit id?
segment = segment_map[segment_name]
if self._lazy:
times = np.array(())
lazy_shape = group['times'].shape
else:
times = group['times'].value
spiketrain = SpikeTrain(times, units=pq.second,
t_stop=group['t_stop'].value*pq.second) # todo: this is a custom Neo value, general NWB files will not have this - use segment.t_stop instead in that case?
if self._lazy:
spiketrain.lazy_shape = lazy_shape
spiketrain.segment = segment
segment.spiketrains.append(spiketrain)示例3: test__issue_285
# 需要导入模块: from neo.core import SpikeTrain [as 别名]
# 或者: from neo.core.SpikeTrain import segment [as 别名]
def test__issue_285(self):
##Spiketrain
train = SpikeTrain([3, 4, 5] * pq.s, t_stop=10.0)
unit = Unit()
train.unit = unit
unit.spiketrains.append(train)
epoch = Epoch([0, 10, 20], [2, 2, 2], ["a", "b", "c"], units="ms")
blk = Block()
seg = Segment()
seg.spiketrains.append(train)
seg.epochs.append(epoch)
epoch.segment = seg
blk.segments.append(seg)
reader = PickleIO(filename="blk.pkl")
reader.write(blk)
reader = PickleIO(filename="blk.pkl")
r_blk = reader.read_block()
r_seg = r_blk.segments[0]
self.assertIsInstance(r_seg.spiketrains[0].unit, Unit)
self.assertIsInstance(r_seg.epochs[0], Epoch)
os.remove('blk.pkl')
##Epoch
train = Epoch(times=np.arange(0, 30, 10)*pq.s,durations=[10, 5, 7]*pq.ms,labels=np.array(['btn0', 'btn1', 'btn2'], dtype='S'))
train.segment = Segment()
unit = Unit()
unit.spiketrains.append(train)
blk = Block()
seg = Segment()
seg.spiketrains.append(train)
blk.segments.append(seg)
reader = PickleIO(filename="blk.pkl")
reader.write(blk)
reader = PickleIO(filename="blk.pkl")
r_blk = reader.read_block()
r_seg = r_blk.segments[0]
self.assertIsInstance(r_seg.spiketrains[0].segment, Segment)
os.remove('blk.pkl')
##Event
train = Event(np.arange(0, 30, 10)*pq.s,labels=np.array(['trig0', 'trig1', 'trig2'],dtype='S'))
train.segment = Segment()
unit = Unit()
unit.spiketrains.append(train)
blk = Block()
seg = Segment()
seg.spiketrains.append(train)
blk.segments.append(seg)
reader = PickleIO(filename="blk.pkl")
reader.write(blk)
reader = PickleIO(filename="blk.pkl")
r_blk = reader.read_block()
r_seg = r_blk.segments[0]
self.assertIsInstance(r_seg.spiketrains[0].segment, Segment)
os.remove('blk.pkl')
##IrregularlySampledSignal
train = IrregularlySampledSignal([0.0, 1.23, 6.78], [1, 2, 3],units='mV', time_units='ms')
train.segment = Segment()
unit = Unit()
train.channel_index = ChannelIndex(1)
unit.spiketrains.append(train)
blk = Block()
seg = Segment()
seg.spiketrains.append(train)
blk.segments.append(seg)
blk.segments[0].block = blk
reader = PickleIO(filename="blk.pkl")
reader.write(blk)
reader = PickleIO(filename="blk.pkl")
r_blk = reader.read_block()
r_seg = r_blk.segments[0]
self.assertIsInstance(r_seg.spiketrains[0].segment, Segment)
self.assertIsInstance(r_seg.spiketrains[0].channel_index, ChannelIndex)
os.remove('blk.pkl')