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Python SpikeTrain.sampling_rate方法代码示例

本文整理汇总了Python中neo.core.SpikeTrain.sampling_rate方法的典型用法代码示例。如果您正苦于以下问题:Python SpikeTrain.sampling_rate方法的具体用法?Python SpikeTrain.sampling_rate怎么用?Python SpikeTrain.sampling_rate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neo.core.SpikeTrain的用法示例。


在下文中一共展示了SpikeTrain.sampling_rate方法的1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 sampling_rate [as 别名]
    def read_spiketrain(self ,
                                            # the 2 first key arguments are imposed by neo.io API
                                            lazy = False,
                                            cascade = True,

                                                segment_duration = 15.,
                                                t_start = -1,
                                                channel_index = 0,
                                                ):
        """
        With this IO SpikeTrain can e acces directly with its channel number
        """
        # There are 2 possibles behaviour for a SpikeTrain
        # holding many Spike instance or directly holding spike times
        # we choose here the first :
        if not HAVE_SCIPY:
            raise SCIPY_ERR

        num_spike_by_spiketrain = 40
        sr = 10000.

        if lazy:
            times = [ ]
        else:
            times = (np.random.rand(num_spike_by_spiketrain)*segment_duration +
                     t_start)

        # create a spiketrain
        spiketr = SpikeTrain(times, t_start = t_start*pq.s, t_stop = (t_start+segment_duration)*pq.s ,
                                            units = pq.s,
                                            name = 'it is a spiketrain from exampleio',
                                            )

        if lazy:
            # we add the attribute lazy_shape with the size if loaded
            spiketr.lazy_shape = (num_spike_by_spiketrain,)

        # ours spiketrains also hold the waveforms:

        # 1 generate a fake spike shape (2d array if trodness >1)
        w1 = -stats.nct.pdf(np.arange(11,60,4), 5,20)[::-1]/3.
        w2 = stats.nct.pdf(np.arange(11,60,2), 5,20)
        w = np.r_[ w1 , w2 ]
        w = -w/max(w)

        if not lazy:
            # in the neo API the waveforms attr is 3 D in case tetrode
            # in our case it is mono electrode so dim 1 is size 1
            waveforms  = np.tile( w[np.newaxis,np.newaxis,:], ( num_spike_by_spiketrain ,1, 1) )
            waveforms *=  np.random.randn(*waveforms.shape)/6+1
            spiketr.waveforms = waveforms*pq.mV
            spiketr.sampling_rate = sr * pq.Hz
            spiketr.left_sweep = 1.5* pq.s

        # for attributes out of neo you can annotate
        spiketr.annotate(channel_index = channel_index)

        return spiketr
开发者ID:CINPLA,项目名称:python-neo,代码行数:60,代码来源:exampleio.py


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