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| Next revision | Previous revision | ||
| technical:sliding_window [2019/09/25 14:25] – created chunchung | technical:sliding_window [2021/10/12 15:15] (current) – chunchung | ||
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| =====Sliding window time histogram===== | =====Sliding window time histogram===== | ||
| + | Given the spike time, plot the event rate within a sliding window. | ||
| <code python> | <code python> | ||
| def sliding_window(ts, | def sliding_window(ts, | ||
| Line 6: | Line 7: | ||
| Parameters | Parameters | ||
| ---------- | ---------- | ||
| - | ts: | + | ts: |
| - | wsz: window | + | wsz: Window |
| + | |||
| + | Returns | ||
| + | ------- | ||
| + | tss: Array of time points | ||
| + | rates: | ||
| ''' | ''' | ||
| - | tw = ts[0]-wsz | + | tw = ts[0]-wsz |
| i0 = 0 | i0 = 0 | ||
| i1 = 0 | i1 = 0 | ||
| Line 36: | Line 42: | ||
| tts.append(tw) | tts.append(tw) | ||
| rrs.append(0) | rrs.append(0) | ||
| - | return np.array(tts)+wsz/ | + | return np.array(tts)+wsz/ |
| + | </ | ||
| + | ====Example==== | ||
| + | <code python> | ||
| + | a = np.array([1, | ||
| + | tts,rrs = sliding_window(a) | ||
| + | plt.plot(tts, | ||
| + | plt.plot(a, | ||
| </ | </ | ||
| + | {{ : | ||
